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TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| #!/usr/bin/env python3
import requests
giphy_api_key = "YOUR API KEY"
# Can be fetched from https://developers.giphy.com/dashboard/
def get_gifs(query: str, api_key: str = giphy_api_key) -> list:
"""
Get a list of URLs of GIFs based on a given query..
"""
formatted_query = "+".join(query.split())
url = f"https://api.giphy.com/v1/gifs/search?q={formatted_query}&api_key={api_key}"
gifs = requests.get(url).json()["data"]
return [gif["url"] for gif in gifs]
if __name__ == "__main__":
print("\n".join(get_gifs("space ship")))
| #!/usr/bin/env python3
import requests
giphy_api_key = "YOUR API KEY"
# Can be fetched from https://developers.giphy.com/dashboard/
def get_gifs(query: str, api_key: str = giphy_api_key) -> list:
"""
Get a list of URLs of GIFs based on a given query..
"""
formatted_query = "+".join(query.split())
url = f"https://api.giphy.com/v1/gifs/search?q={formatted_query}&api_key={api_key}"
gifs = requests.get(url).json()["data"]
return [gif["url"] for gif in gifs]
if __name__ == "__main__":
print("\n".join(get_gifs("space ship")))
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Problem 119: https://projecteuler.net/problem=119
Name: Digit power sum
The number 512 is interesting because it is equal to the sum of its digits
raised to some power: 5 + 1 + 2 = 8, and 8^3 = 512. Another example of a number
with this property is 614656 = 28^4. We shall define an to be the nth term of
this sequence and insist that a number must contain at least two digits to have a sum.
You are given that a2 = 512 and a10 = 614656. Find a30
"""
import math
def digit_sum(n: int) -> int:
"""
Returns the sum of the digits of the number.
>>> digit_sum(123)
6
>>> digit_sum(456)
15
>>> digit_sum(78910)
25
"""
return sum(int(digit) for digit in str(n))
def solution(n: int = 30) -> int:
"""
Returns the value of 30th digit power sum.
>>> solution(2)
512
>>> solution(5)
5832
>>> solution(10)
614656
"""
digit_to_powers = []
for digit in range(2, 100):
for power in range(2, 100):
number = int(math.pow(digit, power))
if digit == digit_sum(number):
digit_to_powers.append(number)
digit_to_powers.sort()
return digit_to_powers[n - 1]
if __name__ == "__main__":
print(solution())
| """
Problem 119: https://projecteuler.net/problem=119
Name: Digit power sum
The number 512 is interesting because it is equal to the sum of its digits
raised to some power: 5 + 1 + 2 = 8, and 8^3 = 512. Another example of a number
with this property is 614656 = 28^4. We shall define an to be the nth term of
this sequence and insist that a number must contain at least two digits to have a sum.
You are given that a2 = 512 and a10 = 614656. Find a30
"""
import math
def digit_sum(n: int) -> int:
"""
Returns the sum of the digits of the number.
>>> digit_sum(123)
6
>>> digit_sum(456)
15
>>> digit_sum(78910)
25
"""
return sum(int(digit) for digit in str(n))
def solution(n: int = 30) -> int:
"""
Returns the value of 30th digit power sum.
>>> solution(2)
512
>>> solution(5)
5832
>>> solution(10)
614656
"""
digit_to_powers = []
for digit in range(2, 100):
for power in range(2, 100):
number = int(math.pow(digit, power))
if digit == digit_sum(number):
digit_to_powers.append(number)
digit_to_powers.sort()
return digit_to_powers[n - 1]
if __name__ == "__main__":
print(solution())
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
This is a Python implementation of the levenshtein distance.
Levenshtein distance is a string metric for measuring the
difference between two sequences.
For doctests run following command:
python -m doctest -v levenshtein-distance.py
or
python3 -m doctest -v levenshtein-distance.py
For manual testing run:
python levenshtein-distance.py
"""
def levenshtein_distance(first_word: str, second_word: str) -> int:
"""Implementation of the levenshtein distance in Python.
:param first_word: the first word to measure the difference.
:param second_word: the second word to measure the difference.
:return: the levenshtein distance between the two words.
Examples:
>>> levenshtein_distance("planet", "planetary")
3
>>> levenshtein_distance("", "test")
4
>>> levenshtein_distance("book", "back")
2
>>> levenshtein_distance("book", "book")
0
>>> levenshtein_distance("test", "")
4
>>> levenshtein_distance("", "")
0
>>> levenshtein_distance("orchestration", "container")
10
"""
# The longer word should come first
if len(first_word) < len(second_word):
return levenshtein_distance(second_word, first_word)
if len(second_word) == 0:
return len(first_word)
previous_row = list(range(len(second_word) + 1))
for i, c1 in enumerate(first_word):
current_row = [i + 1]
for j, c2 in enumerate(second_word):
# Calculate insertions, deletions and substitutions
insertions = previous_row[j + 1] + 1
deletions = current_row[j] + 1
substitutions = previous_row[j] + (c1 != c2)
# Get the minimum to append to the current row
current_row.append(min(insertions, deletions, substitutions))
# Store the previous row
previous_row = current_row
# Returns the last element (distance)
return previous_row[-1]
if __name__ == "__main__":
first_word = input("Enter the first word:\n").strip()
second_word = input("Enter the second word:\n").strip()
result = levenshtein_distance(first_word, second_word)
print(f"Levenshtein distance between {first_word} and {second_word} is {result}")
| """
This is a Python implementation of the levenshtein distance.
Levenshtein distance is a string metric for measuring the
difference between two sequences.
For doctests run following command:
python -m doctest -v levenshtein-distance.py
or
python3 -m doctest -v levenshtein-distance.py
For manual testing run:
python levenshtein-distance.py
"""
def levenshtein_distance(first_word: str, second_word: str) -> int:
"""Implementation of the levenshtein distance in Python.
:param first_word: the first word to measure the difference.
:param second_word: the second word to measure the difference.
:return: the levenshtein distance between the two words.
Examples:
>>> levenshtein_distance("planet", "planetary")
3
>>> levenshtein_distance("", "test")
4
>>> levenshtein_distance("book", "back")
2
>>> levenshtein_distance("book", "book")
0
>>> levenshtein_distance("test", "")
4
>>> levenshtein_distance("", "")
0
>>> levenshtein_distance("orchestration", "container")
10
"""
# The longer word should come first
if len(first_word) < len(second_word):
return levenshtein_distance(second_word, first_word)
if len(second_word) == 0:
return len(first_word)
previous_row = list(range(len(second_word) + 1))
for i, c1 in enumerate(first_word):
current_row = [i + 1]
for j, c2 in enumerate(second_word):
# Calculate insertions, deletions and substitutions
insertions = previous_row[j + 1] + 1
deletions = current_row[j] + 1
substitutions = previous_row[j] + (c1 != c2)
# Get the minimum to append to the current row
current_row.append(min(insertions, deletions, substitutions))
# Store the previous row
previous_row = current_row
# Returns the last element (distance)
return previous_row[-1]
if __name__ == "__main__":
first_word = input("Enter the first word:\n").strip()
second_word = input("Enter the second word:\n").strip()
result = levenshtein_distance(first_word, second_word)
print(f"Levenshtein distance between {first_word} and {second_word} is {result}")
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
pseudo-code
DIJKSTRA(graph G, start vertex s, destination vertex d):
//all nodes initially unexplored
1 - let H = min heap data structure, initialized with 0 and s [here 0 indicates
the distance from start vertex s]
2 - while H is non-empty:
3 - remove the first node and cost of H, call it U and cost
4 - if U has been previously explored:
5 - go to the while loop, line 2 //Once a node is explored there is no need
to make it again
6 - mark U as explored
7 - if U is d:
8 - return cost // total cost from start to destination vertex
9 - for each edge(U, V): c=cost of edge(U,V) // for V in graph[U]
10 - if V explored:
11 - go to next V in line 9
12 - total_cost = cost + c
13 - add (total_cost,V) to H
You can think at cost as a distance where Dijkstra finds the shortest distance
between vertices s and v in a graph G. The use of a min heap as H guarantees
that if a vertex has already been explored there will be no other path with
shortest distance, that happens because heapq.heappop will always return the
next vertex with the shortest distance, considering that the heap stores not
only the distance between previous vertex and current vertex but the entire
distance between each vertex that makes up the path from start vertex to target
vertex.
"""
import heapq
def dijkstra(graph, start, end):
"""Return the cost of the shortest path between vertices start and end.
>>> dijkstra(G, "E", "C")
6
>>> dijkstra(G2, "E", "F")
3
>>> dijkstra(G3, "E", "F")
3
"""
heap = [(0, start)] # cost from start node,end node
visited = set()
while heap:
(cost, u) = heapq.heappop(heap)
if u in visited:
continue
visited.add(u)
if u == end:
return cost
for v, c in graph[u]:
if v in visited:
continue
next_item = cost + c
heapq.heappush(heap, (next_item, v))
return -1
G = {
"A": [["B", 2], ["C", 5]],
"B": [["A", 2], ["D", 3], ["E", 1], ["F", 1]],
"C": [["A", 5], ["F", 3]],
"D": [["B", 3]],
"E": [["B", 4], ["F", 3]],
"F": [["C", 3], ["E", 3]],
}
r"""
Layout of G2:
E -- 1 --> B -- 1 --> C -- 1 --> D -- 1 --> F
\ /\
\ ||
----------------- 3 --------------------
"""
G2 = {
"B": [["C", 1]],
"C": [["D", 1]],
"D": [["F", 1]],
"E": [["B", 1], ["F", 3]],
"F": [],
}
r"""
Layout of G3:
E -- 1 --> B -- 1 --> C -- 1 --> D -- 1 --> F
\ /\
\ ||
-------- 2 ---------> G ------- 1 ------
"""
G3 = {
"B": [["C", 1]],
"C": [["D", 1]],
"D": [["F", 1]],
"E": [["B", 1], ["G", 2]],
"F": [],
"G": [["F", 1]],
}
short_distance = dijkstra(G, "E", "C")
print(short_distance) # E -- 3 --> F -- 3 --> C == 6
short_distance = dijkstra(G2, "E", "F")
print(short_distance) # E -- 3 --> F == 3
short_distance = dijkstra(G3, "E", "F")
print(short_distance) # E -- 2 --> G -- 1 --> F == 3
if __name__ == "__main__":
import doctest
doctest.testmod()
| """
pseudo-code
DIJKSTRA(graph G, start vertex s, destination vertex d):
//all nodes initially unexplored
1 - let H = min heap data structure, initialized with 0 and s [here 0 indicates
the distance from start vertex s]
2 - while H is non-empty:
3 - remove the first node and cost of H, call it U and cost
4 - if U has been previously explored:
5 - go to the while loop, line 2 //Once a node is explored there is no need
to make it again
6 - mark U as explored
7 - if U is d:
8 - return cost // total cost from start to destination vertex
9 - for each edge(U, V): c=cost of edge(U,V) // for V in graph[U]
10 - if V explored:
11 - go to next V in line 9
12 - total_cost = cost + c
13 - add (total_cost,V) to H
You can think at cost as a distance where Dijkstra finds the shortest distance
between vertices s and v in a graph G. The use of a min heap as H guarantees
that if a vertex has already been explored there will be no other path with
shortest distance, that happens because heapq.heappop will always return the
next vertex with the shortest distance, considering that the heap stores not
only the distance between previous vertex and current vertex but the entire
distance between each vertex that makes up the path from start vertex to target
vertex.
"""
import heapq
def dijkstra(graph, start, end):
"""Return the cost of the shortest path between vertices start and end.
>>> dijkstra(G, "E", "C")
6
>>> dijkstra(G2, "E", "F")
3
>>> dijkstra(G3, "E", "F")
3
"""
heap = [(0, start)] # cost from start node,end node
visited = set()
while heap:
(cost, u) = heapq.heappop(heap)
if u in visited:
continue
visited.add(u)
if u == end:
return cost
for v, c in graph[u]:
if v in visited:
continue
next_item = cost + c
heapq.heappush(heap, (next_item, v))
return -1
G = {
"A": [["B", 2], ["C", 5]],
"B": [["A", 2], ["D", 3], ["E", 1], ["F", 1]],
"C": [["A", 5], ["F", 3]],
"D": [["B", 3]],
"E": [["B", 4], ["F", 3]],
"F": [["C", 3], ["E", 3]],
}
r"""
Layout of G2:
E -- 1 --> B -- 1 --> C -- 1 --> D -- 1 --> F
\ /\
\ ||
----------------- 3 --------------------
"""
G2 = {
"B": [["C", 1]],
"C": [["D", 1]],
"D": [["F", 1]],
"E": [["B", 1], ["F", 3]],
"F": [],
}
r"""
Layout of G3:
E -- 1 --> B -- 1 --> C -- 1 --> D -- 1 --> F
\ /\
\ ||
-------- 2 ---------> G ------- 1 ------
"""
G3 = {
"B": [["C", 1]],
"C": [["D", 1]],
"D": [["F", 1]],
"E": [["B", 1], ["G", 2]],
"F": [],
"G": [["F", 1]],
}
short_distance = dijkstra(G, "E", "C")
print(short_distance) # E -- 3 --> F -- 3 --> C == 6
short_distance = dijkstra(G2, "E", "F")
print(short_distance) # E -- 3 --> F == 3
short_distance = dijkstra(G3, "E", "F")
print(short_distance) # E -- 2 --> G -- 1 --> F == 3
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| import math
from numpy import inf
from scipy.integrate import quad
def gamma(num: float) -> float:
"""
https://en.wikipedia.org/wiki/Gamma_function
In mathematics, the gamma function is one commonly
used extension of the factorial function to complex numbers.
The gamma function is defined for all complex numbers except the non-positive
integers
>>> gamma(-1)
Traceback (most recent call last):
...
ValueError: math domain error
>>> gamma(0)
Traceback (most recent call last):
...
ValueError: math domain error
>>> gamma(9)
40320.0
>>> from math import gamma as math_gamma
>>> all(.99999999 < gamma(i) / math_gamma(i) <= 1.000000001
... for i in range(1, 50))
True
>>> from math import gamma as math_gamma
>>> gamma(-1)/math_gamma(-1) <= 1.000000001
Traceback (most recent call last):
...
ValueError: math domain error
>>> from math import gamma as math_gamma
>>> gamma(3.3) - math_gamma(3.3) <= 0.00000001
True
"""
if num <= 0:
raise ValueError("math domain error")
return quad(integrand, 0, inf, args=(num))[0]
def integrand(x: float, z: float) -> float:
return math.pow(x, z - 1) * math.exp(-x)
if __name__ == "__main__":
from doctest import testmod
testmod()
| import math
from numpy import inf
from scipy.integrate import quad
def gamma(num: float) -> float:
"""
https://en.wikipedia.org/wiki/Gamma_function
In mathematics, the gamma function is one commonly
used extension of the factorial function to complex numbers.
The gamma function is defined for all complex numbers except the non-positive
integers
>>> gamma(-1)
Traceback (most recent call last):
...
ValueError: math domain error
>>> gamma(0)
Traceback (most recent call last):
...
ValueError: math domain error
>>> gamma(9)
40320.0
>>> from math import gamma as math_gamma
>>> all(.99999999 < gamma(i) / math_gamma(i) <= 1.000000001
... for i in range(1, 50))
True
>>> from math import gamma as math_gamma
>>> gamma(-1)/math_gamma(-1) <= 1.000000001
Traceback (most recent call last):
...
ValueError: math domain error
>>> from math import gamma as math_gamma
>>> gamma(3.3) - math_gamma(3.3) <= 0.00000001
True
"""
if num <= 0:
raise ValueError("math domain error")
return quad(integrand, 0, inf, args=(num))[0]
def integrand(x: float, z: float) -> float:
return math.pow(x, z - 1) * math.exp(-x)
if __name__ == "__main__":
from doctest import testmod
testmod()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """ https://en.wikipedia.org/wiki/Rail_fence_cipher """
def encrypt(input_string: str, key: int) -> str:
"""
Shuffles the character of a string by placing each of them
in a grid (the height is dependent on the key) in a zigzag
formation and reading it left to right.
>>> encrypt("Hello World", 4)
'HWe olordll'
>>> encrypt("This is a message", 0)
Traceback (most recent call last):
...
ValueError: Height of grid can't be 0 or negative
>>> encrypt(b"This is a byte string", 5)
Traceback (most recent call last):
...
TypeError: sequence item 0: expected str instance, int found
"""
temp_grid: list[list[str]] = [[] for _ in range(key)]
lowest = key - 1
if key <= 0:
raise ValueError("Height of grid can't be 0 or negative")
if key == 1 or len(input_string) <= key:
return input_string
for position, character in enumerate(input_string):
num = position % (lowest * 2) # puts it in bounds
num = min(num, lowest * 2 - num) # creates zigzag pattern
temp_grid[num].append(character)
grid = ["".join(row) for row in temp_grid]
output_string = "".join(grid)
return output_string
def decrypt(input_string: str, key: int) -> str:
"""
Generates a template based on the key and fills it in with
the characters of the input string and then reading it in
a zigzag formation.
>>> decrypt("HWe olordll", 4)
'Hello World'
>>> decrypt("This is a message", -10)
Traceback (most recent call last):
...
ValueError: Height of grid can't be 0 or negative
>>> decrypt("My key is very big", 100)
'My key is very big'
"""
grid = []
lowest = key - 1
if key <= 0:
raise ValueError("Height of grid can't be 0 or negative")
if key == 1:
return input_string
temp_grid: list[list[str]] = [[] for _ in range(key)] # generates template
for position in range(len(input_string)):
num = position % (lowest * 2) # puts it in bounds
num = min(num, lowest * 2 - num) # creates zigzag pattern
temp_grid[num].append("*")
counter = 0
for row in temp_grid: # fills in the characters
splice = input_string[counter : counter + len(row)]
grid.append(list(splice))
counter += len(row)
output_string = "" # reads as zigzag
for position in range(len(input_string)):
num = position % (lowest * 2) # puts it in bounds
num = min(num, lowest * 2 - num) # creates zigzag pattern
output_string += grid[num][0]
grid[num].pop(0)
return output_string
def bruteforce(input_string: str) -> dict[int, str]:
"""Uses decrypt function by guessing every key
>>> bruteforce("HWe olordll")[4]
'Hello World'
"""
results = {}
for key_guess in range(1, len(input_string)): # tries every key
results[key_guess] = decrypt(input_string, key_guess)
return results
if __name__ == "__main__":
import doctest
doctest.testmod()
| """ https://en.wikipedia.org/wiki/Rail_fence_cipher """
def encrypt(input_string: str, key: int) -> str:
"""
Shuffles the character of a string by placing each of them
in a grid (the height is dependent on the key) in a zigzag
formation and reading it left to right.
>>> encrypt("Hello World", 4)
'HWe olordll'
>>> encrypt("This is a message", 0)
Traceback (most recent call last):
...
ValueError: Height of grid can't be 0 or negative
>>> encrypt(b"This is a byte string", 5)
Traceback (most recent call last):
...
TypeError: sequence item 0: expected str instance, int found
"""
temp_grid: list[list[str]] = [[] for _ in range(key)]
lowest = key - 1
if key <= 0:
raise ValueError("Height of grid can't be 0 or negative")
if key == 1 or len(input_string) <= key:
return input_string
for position, character in enumerate(input_string):
num = position % (lowest * 2) # puts it in bounds
num = min(num, lowest * 2 - num) # creates zigzag pattern
temp_grid[num].append(character)
grid = ["".join(row) for row in temp_grid]
output_string = "".join(grid)
return output_string
def decrypt(input_string: str, key: int) -> str:
"""
Generates a template based on the key and fills it in with
the characters of the input string and then reading it in
a zigzag formation.
>>> decrypt("HWe olordll", 4)
'Hello World'
>>> decrypt("This is a message", -10)
Traceback (most recent call last):
...
ValueError: Height of grid can't be 0 or negative
>>> decrypt("My key is very big", 100)
'My key is very big'
"""
grid = []
lowest = key - 1
if key <= 0:
raise ValueError("Height of grid can't be 0 or negative")
if key == 1:
return input_string
temp_grid: list[list[str]] = [[] for _ in range(key)] # generates template
for position in range(len(input_string)):
num = position % (lowest * 2) # puts it in bounds
num = min(num, lowest * 2 - num) # creates zigzag pattern
temp_grid[num].append("*")
counter = 0
for row in temp_grid: # fills in the characters
splice = input_string[counter : counter + len(row)]
grid.append(list(splice))
counter += len(row)
output_string = "" # reads as zigzag
for position in range(len(input_string)):
num = position % (lowest * 2) # puts it in bounds
num = min(num, lowest * 2 - num) # creates zigzag pattern
output_string += grid[num][0]
grid[num].pop(0)
return output_string
def bruteforce(input_string: str) -> dict[int, str]:
"""Uses decrypt function by guessing every key
>>> bruteforce("HWe olordll")[4]
'Hello World'
"""
results = {}
for key_guess in range(1, len(input_string)): # tries every key
results[key_guess] = decrypt(input_string, key_guess)
return results
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| from __future__ import annotations
def stable_matching(
donor_pref: list[list[int]], recipient_pref: list[list[int]]
) -> list[int]:
"""
Finds the stable match in any bipartite graph, i.e a pairing where no 2 objects
prefer each other over their partner. The function accepts the preferences of
oegan donors and recipients (where both are assigned numbers from 0 to n-1) and
returns a list where the index position corresponds to the donor and value at the
index is the organ recipient.
To better understand the algorithm, see also:
https://github.com/akashvshroff/Gale_Shapley_Stable_Matching (README).
https://www.youtube.com/watch?v=Qcv1IqHWAzg&t=13s (Numberphile YouTube).
>>> donor_pref = [[0, 1, 3, 2], [0, 2, 3, 1], [1, 0, 2, 3], [0, 3, 1, 2]]
>>> recipient_pref = [[3, 1, 2, 0], [3, 1, 0, 2], [0, 3, 1, 2], [1, 0, 3, 2]]
>>> stable_matching(donor_pref, recipient_pref)
[1, 2, 3, 0]
"""
assert len(donor_pref) == len(recipient_pref)
n = len(donor_pref)
unmatched_donors = list(range(n))
donor_record = [-1] * n # who the donor has donated to
rec_record = [-1] * n # who the recipient has received from
num_donations = [0] * n
while unmatched_donors:
donor = unmatched_donors[0]
donor_preference = donor_pref[donor]
recipient = donor_preference[num_donations[donor]]
num_donations[donor] += 1
rec_preference = recipient_pref[recipient]
prev_donor = rec_record[recipient]
if prev_donor != -1:
if rec_preference.index(prev_donor) > rec_preference.index(donor):
rec_record[recipient] = donor
donor_record[donor] = recipient
unmatched_donors.append(prev_donor)
unmatched_donors.remove(donor)
else:
rec_record[recipient] = donor
donor_record[donor] = recipient
unmatched_donors.remove(donor)
return donor_record
| from __future__ import annotations
def stable_matching(
donor_pref: list[list[int]], recipient_pref: list[list[int]]
) -> list[int]:
"""
Finds the stable match in any bipartite graph, i.e a pairing where no 2 objects
prefer each other over their partner. The function accepts the preferences of
oegan donors and recipients (where both are assigned numbers from 0 to n-1) and
returns a list where the index position corresponds to the donor and value at the
index is the organ recipient.
To better understand the algorithm, see also:
https://github.com/akashvshroff/Gale_Shapley_Stable_Matching (README).
https://www.youtube.com/watch?v=Qcv1IqHWAzg&t=13s (Numberphile YouTube).
>>> donor_pref = [[0, 1, 3, 2], [0, 2, 3, 1], [1, 0, 2, 3], [0, 3, 1, 2]]
>>> recipient_pref = [[3, 1, 2, 0], [3, 1, 0, 2], [0, 3, 1, 2], [1, 0, 3, 2]]
>>> stable_matching(donor_pref, recipient_pref)
[1, 2, 3, 0]
"""
assert len(donor_pref) == len(recipient_pref)
n = len(donor_pref)
unmatched_donors = list(range(n))
donor_record = [-1] * n # who the donor has donated to
rec_record = [-1] * n # who the recipient has received from
num_donations = [0] * n
while unmatched_donors:
donor = unmatched_donors[0]
donor_preference = donor_pref[donor]
recipient = donor_preference[num_donations[donor]]
num_donations[donor] += 1
rec_preference = recipient_pref[recipient]
prev_donor = rec_record[recipient]
if prev_donor != -1:
if rec_preference.index(prev_donor) > rec_preference.index(donor):
rec_record[recipient] = donor
donor_record[donor] = recipient
unmatched_donors.append(prev_donor)
unmatched_donors.remove(donor)
else:
rec_record[recipient] = donor
donor_record[donor] = recipient
unmatched_donors.remove(donor)
return donor_record
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Title : Calculating the Hubble Parameter
Description : The Hubble parameter H is the Universe expansion rate
in any time. In cosmology is customary to use the redshift redshift
in place of time, becausethe redshift is directily mensure
in the light of galaxies moving away from us.
So, the general relation that we obtain is
H = hubble_constant*(radiation_density*(redshift+1)**4
+ matter_density*(redshift+1)**3
+ curvature*(redshift+1)**2 + dark_energy)**(1/2)
where radiation_density, matter_density, dark_energy are the relativity
(the percentage) energy densities that exist
in the Universe today. Here, matter_density is the
sum of the barion density and the
dark matter. Curvature is the curvature parameter and can be written in term
of the densities by the completeness
curvature = 1 - (matter_density + radiation_density + dark_energy)
Source :
https://www.sciencedirect.com/topics/mathematics/hubble-parameter
"""
def hubble_parameter(
hubble_constant: float,
radiation_density: float,
matter_density: float,
dark_energy: float,
redshift: float,
) -> float:
"""
Input Parameters
----------------
hubble_constant: Hubble constante is the expansion rate today usually
given in km/(s*Mpc)
radiation_density: relative radiation density today
matter_density: relative mass density today
dark_energy: relative dark energy density today
redshift: the light redshift
Returns
-------
result : Hubble parameter in and the unit km/s/Mpc (the unit can be
changed if you want, just need to change the unit of the Hubble constant)
>>> hubble_parameter(hubble_constant=68.3, radiation_density=1e-4,
... matter_density=-0.3, dark_energy=0.7, redshift=1)
Traceback (most recent call last):
...
ValueError: All input parameters must be positive
>>> hubble_parameter(hubble_constant=68.3, radiation_density=1e-4,
... matter_density= 1.2, dark_energy=0.7, redshift=1)
Traceback (most recent call last):
...
ValueError: Relative densities cannot be greater than one
>>> hubble_parameter(hubble_constant=68.3, radiation_density=1e-4,
... matter_density= 0.3, dark_energy=0.7, redshift=0)
68.3
"""
parameters = [redshift, radiation_density, matter_density, dark_energy]
if any(0 > p for p in parameters):
raise ValueError("All input parameters must be positive")
if any(1 < p for p in parameters[1:4]):
raise ValueError("Relative densities cannot be greater than one")
else:
curvature = 1 - (matter_density + radiation_density + dark_energy)
e_2 = (
radiation_density * (redshift + 1) ** 4
+ matter_density * (redshift + 1) ** 3
+ curvature * (redshift + 1) ** 2
+ dark_energy
)
hubble = hubble_constant * e_2 ** (1 / 2)
return hubble
if __name__ == "__main__":
import doctest
# run doctest
doctest.testmod()
# demo LCDM approximation
matter_density = 0.3
print(
hubble_parameter(
hubble_constant=68.3,
radiation_density=1e-4,
matter_density=matter_density,
dark_energy=1 - matter_density,
redshift=0,
)
)
| """
Title : Calculating the Hubble Parameter
Description : The Hubble parameter H is the Universe expansion rate
in any time. In cosmology is customary to use the redshift redshift
in place of time, becausethe redshift is directily mensure
in the light of galaxies moving away from us.
So, the general relation that we obtain is
H = hubble_constant*(radiation_density*(redshift+1)**4
+ matter_density*(redshift+1)**3
+ curvature*(redshift+1)**2 + dark_energy)**(1/2)
where radiation_density, matter_density, dark_energy are the relativity
(the percentage) energy densities that exist
in the Universe today. Here, matter_density is the
sum of the barion density and the
dark matter. Curvature is the curvature parameter and can be written in term
of the densities by the completeness
curvature = 1 - (matter_density + radiation_density + dark_energy)
Source :
https://www.sciencedirect.com/topics/mathematics/hubble-parameter
"""
def hubble_parameter(
hubble_constant: float,
radiation_density: float,
matter_density: float,
dark_energy: float,
redshift: float,
) -> float:
"""
Input Parameters
----------------
hubble_constant: Hubble constante is the expansion rate today usually
given in km/(s*Mpc)
radiation_density: relative radiation density today
matter_density: relative mass density today
dark_energy: relative dark energy density today
redshift: the light redshift
Returns
-------
result : Hubble parameter in and the unit km/s/Mpc (the unit can be
changed if you want, just need to change the unit of the Hubble constant)
>>> hubble_parameter(hubble_constant=68.3, radiation_density=1e-4,
... matter_density=-0.3, dark_energy=0.7, redshift=1)
Traceback (most recent call last):
...
ValueError: All input parameters must be positive
>>> hubble_parameter(hubble_constant=68.3, radiation_density=1e-4,
... matter_density= 1.2, dark_energy=0.7, redshift=1)
Traceback (most recent call last):
...
ValueError: Relative densities cannot be greater than one
>>> hubble_parameter(hubble_constant=68.3, radiation_density=1e-4,
... matter_density= 0.3, dark_energy=0.7, redshift=0)
68.3
"""
parameters = [redshift, radiation_density, matter_density, dark_energy]
if any(0 > p for p in parameters):
raise ValueError("All input parameters must be positive")
if any(1 < p for p in parameters[1:4]):
raise ValueError("Relative densities cannot be greater than one")
else:
curvature = 1 - (matter_density + radiation_density + dark_energy)
e_2 = (
radiation_density * (redshift + 1) ** 4
+ matter_density * (redshift + 1) ** 3
+ curvature * (redshift + 1) ** 2
+ dark_energy
)
hubble = hubble_constant * e_2 ** (1 / 2)
return hubble
if __name__ == "__main__":
import doctest
# run doctest
doctest.testmod()
# demo LCDM approximation
matter_density = 0.3
print(
hubble_parameter(
hubble_constant=68.3,
radiation_density=1e-4,
matter_density=matter_density,
dark_energy=1 - matter_density,
redshift=0,
)
)
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """Prime Check."""
import math
import unittest
def is_prime(number: int) -> bool:
"""Checks to see if a number is a prime in O(sqrt(n)).
A number is prime if it has exactly two factors: 1 and itself.
>>> is_prime(0)
False
>>> is_prime(1)
False
>>> is_prime(2)
True
>>> is_prime(3)
True
>>> is_prime(27)
False
>>> is_prime(87)
False
>>> is_prime(563)
True
>>> is_prime(2999)
True
>>> is_prime(67483)
False
"""
# precondition
assert isinstance(number, int) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
return False
# All primes number are in format of 6k +/- 1
for i in range(5, int(math.sqrt(number) + 1), 6):
if number % i == 0 or number % (i + 2) == 0:
return False
return True
class Test(unittest.TestCase):
def test_primes(self):
self.assertTrue(is_prime(2))
self.assertTrue(is_prime(3))
self.assertTrue(is_prime(5))
self.assertTrue(is_prime(7))
self.assertTrue(is_prime(11))
self.assertTrue(is_prime(13))
self.assertTrue(is_prime(17))
self.assertTrue(is_prime(19))
self.assertTrue(is_prime(23))
self.assertTrue(is_prime(29))
def test_not_primes(self):
with self.assertRaises(AssertionError):
is_prime(-19)
self.assertFalse(
is_prime(0),
"Zero doesn't have any positive factors, primes must have exactly two.",
)
self.assertFalse(
is_prime(1),
"One only has 1 positive factor, primes must have exactly two.",
)
self.assertFalse(is_prime(2 * 2))
self.assertFalse(is_prime(2 * 3))
self.assertFalse(is_prime(3 * 3))
self.assertFalse(is_prime(3 * 5))
self.assertFalse(is_prime(3 * 5 * 7))
if __name__ == "__main__":
unittest.main()
| """Prime Check."""
import math
import unittest
def is_prime(number: int) -> bool:
"""Checks to see if a number is a prime in O(sqrt(n)).
A number is prime if it has exactly two factors: 1 and itself.
>>> is_prime(0)
False
>>> is_prime(1)
False
>>> is_prime(2)
True
>>> is_prime(3)
True
>>> is_prime(27)
False
>>> is_prime(87)
False
>>> is_prime(563)
True
>>> is_prime(2999)
True
>>> is_prime(67483)
False
"""
# precondition
assert isinstance(number, int) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
return False
# All primes number are in format of 6k +/- 1
for i in range(5, int(math.sqrt(number) + 1), 6):
if number % i == 0 or number % (i + 2) == 0:
return False
return True
class Test(unittest.TestCase):
def test_primes(self):
self.assertTrue(is_prime(2))
self.assertTrue(is_prime(3))
self.assertTrue(is_prime(5))
self.assertTrue(is_prime(7))
self.assertTrue(is_prime(11))
self.assertTrue(is_prime(13))
self.assertTrue(is_prime(17))
self.assertTrue(is_prime(19))
self.assertTrue(is_prime(23))
self.assertTrue(is_prime(29))
def test_not_primes(self):
with self.assertRaises(AssertionError):
is_prime(-19)
self.assertFalse(
is_prime(0),
"Zero doesn't have any positive factors, primes must have exactly two.",
)
self.assertFalse(
is_prime(1),
"One only has 1 positive factor, primes must have exactly two.",
)
self.assertFalse(is_prime(2 * 2))
self.assertFalse(is_prime(2 * 3))
self.assertFalse(is_prime(3 * 3))
self.assertFalse(is_prime(3 * 5))
self.assertFalse(is_prime(3 * 5 * 7))
if __name__ == "__main__":
unittest.main()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
This is pure Python implementation of sentinel linear search algorithm
For doctests run following command:
python -m doctest -v sentinel_linear_search.py
or
python3 -m doctest -v sentinel_linear_search.py
For manual testing run:
python sentinel_linear_search.py
"""
def sentinel_linear_search(sequence, target):
"""Pure implementation of sentinel linear search algorithm in Python
:param sequence: some sequence with comparable items
:param target: item value to search
:return: index of found item or None if item is not found
Examples:
>>> sentinel_linear_search([0, 5, 7, 10, 15], 0)
0
>>> sentinel_linear_search([0, 5, 7, 10, 15], 15)
4
>>> sentinel_linear_search([0, 5, 7, 10, 15], 5)
1
>>> sentinel_linear_search([0, 5, 7, 10, 15], 6)
"""
sequence.append(target)
index = 0
while sequence[index] != target:
index += 1
sequence.pop()
if index == len(sequence):
return None
return index
if __name__ == "__main__":
user_input = input("Enter numbers separated by comma:\n").strip()
sequence = [int(item) for item in user_input.split(",")]
target_input = input("Enter a single number to be found in the list:\n")
target = int(target_input)
result = sentinel_linear_search(sequence, target)
if result is not None:
print(f"{target} found at positions: {result}")
else:
print("Not found")
| """
This is pure Python implementation of sentinel linear search algorithm
For doctests run following command:
python -m doctest -v sentinel_linear_search.py
or
python3 -m doctest -v sentinel_linear_search.py
For manual testing run:
python sentinel_linear_search.py
"""
def sentinel_linear_search(sequence, target):
"""Pure implementation of sentinel linear search algorithm in Python
:param sequence: some sequence with comparable items
:param target: item value to search
:return: index of found item or None if item is not found
Examples:
>>> sentinel_linear_search([0, 5, 7, 10, 15], 0)
0
>>> sentinel_linear_search([0, 5, 7, 10, 15], 15)
4
>>> sentinel_linear_search([0, 5, 7, 10, 15], 5)
1
>>> sentinel_linear_search([0, 5, 7, 10, 15], 6)
"""
sequence.append(target)
index = 0
while sequence[index] != target:
index += 1
sequence.pop()
if index == len(sequence):
return None
return index
if __name__ == "__main__":
user_input = input("Enter numbers separated by comma:\n").strip()
sequence = [int(item) for item in user_input.split(",")]
target_input = input("Enter a single number to be found in the list:\n")
target = int(target_input)
result = sentinel_linear_search(sequence, target)
if result is not None:
print(f"{target} found at positions: {result}")
else:
print("Not found")
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Jacobi Iteration Method - https://en.wikipedia.org/wiki/Jacobi_method
"""
from __future__ import annotations
import numpy as np
from numpy import float64
from numpy.typing import NDArray
# Method to find solution of system of linear equations
def jacobi_iteration_method(
coefficient_matrix: NDArray[float64],
constant_matrix: NDArray[float64],
init_val: list[int],
iterations: int,
) -> list[float]:
"""
Jacobi Iteration Method:
An iterative algorithm to determine the solutions of strictly diagonally dominant
system of linear equations
4x1 + x2 + x3 = 2
x1 + 5x2 + 2x3 = -6
x1 + 2x2 + 4x3 = -4
x_init = [0.5, -0.5 , -0.5]
Examples:
>>> coefficient = np.array([[4, 1, 1], [1, 5, 2], [1, 2, 4]])
>>> constant = np.array([[2], [-6], [-4]])
>>> init_val = [0.5, -0.5, -0.5]
>>> iterations = 3
>>> jacobi_iteration_method(coefficient, constant, init_val, iterations)
[0.909375, -1.14375, -0.7484375]
>>> coefficient = np.array([[4, 1, 1], [1, 5, 2]])
>>> constant = np.array([[2], [-6], [-4]])
>>> init_val = [0.5, -0.5, -0.5]
>>> iterations = 3
>>> jacobi_iteration_method(coefficient, constant, init_val, iterations)
Traceback (most recent call last):
...
ValueError: Coefficient matrix dimensions must be nxn but received 2x3
>>> coefficient = np.array([[4, 1, 1], [1, 5, 2], [1, 2, 4]])
>>> constant = np.array([[2], [-6]])
>>> init_val = [0.5, -0.5, -0.5]
>>> iterations = 3
>>> jacobi_iteration_method(coefficient, constant, init_val, iterations)
Traceback (most recent call last):
...
ValueError: Coefficient and constant matrices dimensions must be nxn and nx1 but
received 3x3 and 2x1
>>> coefficient = np.array([[4, 1, 1], [1, 5, 2], [1, 2, 4]])
>>> constant = np.array([[2], [-6], [-4]])
>>> init_val = [0.5, -0.5]
>>> iterations = 3
>>> jacobi_iteration_method(coefficient, constant, init_val, iterations)
Traceback (most recent call last):
...
ValueError: Number of initial values must be equal to number of rows in coefficient
matrix but received 2 and 3
>>> coefficient = np.array([[4, 1, 1], [1, 5, 2], [1, 2, 4]])
>>> constant = np.array([[2], [-6], [-4]])
>>> init_val = [0.5, -0.5, -0.5]
>>> iterations = 0
>>> jacobi_iteration_method(coefficient, constant, init_val, iterations)
Traceback (most recent call last):
...
ValueError: Iterations must be at least 1
"""
rows1, cols1 = coefficient_matrix.shape
rows2, cols2 = constant_matrix.shape
if rows1 != cols1:
raise ValueError(
f"Coefficient matrix dimensions must be nxn but received {rows1}x{cols1}"
)
if cols2 != 1:
raise ValueError(f"Constant matrix must be nx1 but received {rows2}x{cols2}")
if rows1 != rows2:
raise ValueError(
f"""Coefficient and constant matrices dimensions must be nxn and nx1 but
received {rows1}x{cols1} and {rows2}x{cols2}"""
)
if len(init_val) != rows1:
raise ValueError(
f"""Number of initial values must be equal to number of rows in coefficient
matrix but received {len(init_val)} and {rows1}"""
)
if iterations <= 0:
raise ValueError("Iterations must be at least 1")
table: NDArray[float64] = np.concatenate(
(coefficient_matrix, constant_matrix), axis=1
)
rows, cols = table.shape
strictly_diagonally_dominant(table)
# Iterates the whole matrix for given number of times
for _ in range(iterations):
new_val = []
for row in range(rows):
temp = 0
for col in range(cols):
if col == row:
denom = table[row][col]
elif col == cols - 1:
val = table[row][col]
else:
temp += (-1) * table[row][col] * init_val[col]
temp = (temp + val) / denom
new_val.append(temp)
init_val = new_val
return [float(i) for i in new_val]
# Checks if the given matrix is strictly diagonally dominant
def strictly_diagonally_dominant(table: NDArray[float64]) -> bool:
"""
>>> table = np.array([[4, 1, 1, 2], [1, 5, 2, -6], [1, 2, 4, -4]])
>>> strictly_diagonally_dominant(table)
True
>>> table = np.array([[4, 1, 1, 2], [1, 5, 2, -6], [1, 2, 3, -4]])
>>> strictly_diagonally_dominant(table)
Traceback (most recent call last):
...
ValueError: Coefficient matrix is not strictly diagonally dominant
"""
rows, cols = table.shape
is_diagonally_dominant = True
for i in range(0, rows):
total = 0
for j in range(0, cols - 1):
if i == j:
continue
else:
total += table[i][j]
if table[i][i] <= total:
raise ValueError("Coefficient matrix is not strictly diagonally dominant")
return is_diagonally_dominant
# Test Cases
if __name__ == "__main__":
import doctest
doctest.testmod()
| """
Jacobi Iteration Method - https://en.wikipedia.org/wiki/Jacobi_method
"""
from __future__ import annotations
import numpy as np
from numpy import float64
from numpy.typing import NDArray
# Method to find solution of system of linear equations
def jacobi_iteration_method(
coefficient_matrix: NDArray[float64],
constant_matrix: NDArray[float64],
init_val: list[int],
iterations: int,
) -> list[float]:
"""
Jacobi Iteration Method:
An iterative algorithm to determine the solutions of strictly diagonally dominant
system of linear equations
4x1 + x2 + x3 = 2
x1 + 5x2 + 2x3 = -6
x1 + 2x2 + 4x3 = -4
x_init = [0.5, -0.5 , -0.5]
Examples:
>>> coefficient = np.array([[4, 1, 1], [1, 5, 2], [1, 2, 4]])
>>> constant = np.array([[2], [-6], [-4]])
>>> init_val = [0.5, -0.5, -0.5]
>>> iterations = 3
>>> jacobi_iteration_method(coefficient, constant, init_val, iterations)
[0.909375, -1.14375, -0.7484375]
>>> coefficient = np.array([[4, 1, 1], [1, 5, 2]])
>>> constant = np.array([[2], [-6], [-4]])
>>> init_val = [0.5, -0.5, -0.5]
>>> iterations = 3
>>> jacobi_iteration_method(coefficient, constant, init_val, iterations)
Traceback (most recent call last):
...
ValueError: Coefficient matrix dimensions must be nxn but received 2x3
>>> coefficient = np.array([[4, 1, 1], [1, 5, 2], [1, 2, 4]])
>>> constant = np.array([[2], [-6]])
>>> init_val = [0.5, -0.5, -0.5]
>>> iterations = 3
>>> jacobi_iteration_method(coefficient, constant, init_val, iterations)
Traceback (most recent call last):
...
ValueError: Coefficient and constant matrices dimensions must be nxn and nx1 but
received 3x3 and 2x1
>>> coefficient = np.array([[4, 1, 1], [1, 5, 2], [1, 2, 4]])
>>> constant = np.array([[2], [-6], [-4]])
>>> init_val = [0.5, -0.5]
>>> iterations = 3
>>> jacobi_iteration_method(coefficient, constant, init_val, iterations)
Traceback (most recent call last):
...
ValueError: Number of initial values must be equal to number of rows in coefficient
matrix but received 2 and 3
>>> coefficient = np.array([[4, 1, 1], [1, 5, 2], [1, 2, 4]])
>>> constant = np.array([[2], [-6], [-4]])
>>> init_val = [0.5, -0.5, -0.5]
>>> iterations = 0
>>> jacobi_iteration_method(coefficient, constant, init_val, iterations)
Traceback (most recent call last):
...
ValueError: Iterations must be at least 1
"""
rows1, cols1 = coefficient_matrix.shape
rows2, cols2 = constant_matrix.shape
if rows1 != cols1:
raise ValueError(
f"Coefficient matrix dimensions must be nxn but received {rows1}x{cols1}"
)
if cols2 != 1:
raise ValueError(f"Constant matrix must be nx1 but received {rows2}x{cols2}")
if rows1 != rows2:
raise ValueError(
f"""Coefficient and constant matrices dimensions must be nxn and nx1 but
received {rows1}x{cols1} and {rows2}x{cols2}"""
)
if len(init_val) != rows1:
raise ValueError(
f"""Number of initial values must be equal to number of rows in coefficient
matrix but received {len(init_val)} and {rows1}"""
)
if iterations <= 0:
raise ValueError("Iterations must be at least 1")
table: NDArray[float64] = np.concatenate(
(coefficient_matrix, constant_matrix), axis=1
)
rows, cols = table.shape
strictly_diagonally_dominant(table)
# Iterates the whole matrix for given number of times
for _ in range(iterations):
new_val = []
for row in range(rows):
temp = 0
for col in range(cols):
if col == row:
denom = table[row][col]
elif col == cols - 1:
val = table[row][col]
else:
temp += (-1) * table[row][col] * init_val[col]
temp = (temp + val) / denom
new_val.append(temp)
init_val = new_val
return [float(i) for i in new_val]
# Checks if the given matrix is strictly diagonally dominant
def strictly_diagonally_dominant(table: NDArray[float64]) -> bool:
"""
>>> table = np.array([[4, 1, 1, 2], [1, 5, 2, -6], [1, 2, 4, -4]])
>>> strictly_diagonally_dominant(table)
True
>>> table = np.array([[4, 1, 1, 2], [1, 5, 2, -6], [1, 2, 3, -4]])
>>> strictly_diagonally_dominant(table)
Traceback (most recent call last):
...
ValueError: Coefficient matrix is not strictly diagonally dominant
"""
rows, cols = table.shape
is_diagonally_dominant = True
for i in range(0, rows):
total = 0
for j in range(0, cols - 1):
if i == j:
continue
else:
total += table[i][j]
if table[i][i] <= total:
raise ValueError("Coefficient matrix is not strictly diagonally dominant")
return is_diagonally_dominant
# Test Cases
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def norm_squared(vector: ndarray) -> float:
"""
Return the squared second norm of vector
norm_squared(v) = sum(x * x for x in v)
Args:
vector (ndarray): input vector
Returns:
float: squared second norm of vector
>>> norm_squared([1, 2])
5
>>> norm_squared(np.asarray([1, 2]))
5
>>> norm_squared([0, 0])
0
"""
return np.dot(vector, vector)
class SVC:
"""
Support Vector Classifier
Args:
kernel (str): kernel to use. Default: linear
Possible choices:
- linear
regularization: constraint for soft margin (data not linearly separable)
Default: unbound
>>> SVC(kernel="asdf")
Traceback (most recent call last):
...
ValueError: Unknown kernel: asdf
>>> SVC(kernel="rbf")
Traceback (most recent call last):
...
ValueError: rbf kernel requires gamma
>>> SVC(kernel="rbf", gamma=-1)
Traceback (most recent call last):
...
ValueError: gamma must be > 0
"""
def __init__(
self,
*,
regularization: float = np.inf,
kernel: str = "linear",
gamma: float = 0,
) -> None:
self.regularization = regularization
self.gamma = gamma
if kernel == "linear":
self.kernel = self.__linear
elif kernel == "rbf":
if self.gamma == 0:
raise ValueError("rbf kernel requires gamma")
if not (isinstance(self.gamma, float) or isinstance(self.gamma, int)):
raise ValueError("gamma must be float or int")
if not self.gamma > 0:
raise ValueError("gamma must be > 0")
self.kernel = self.__rbf
# in the future, there could be a default value like in sklearn
# sklear: def_gamma = 1/(n_features * X.var()) (wiki)
# previously it was 1/(n_features)
else:
raise ValueError(f"Unknown kernel: {kernel}")
# kernels
def __linear(self, vector1: ndarray, vector2: ndarray) -> float:
"""Linear kernel (as if no kernel used at all)"""
return np.dot(vector1, vector2)
def __rbf(self, vector1: ndarray, vector2: ndarray) -> float:
"""
RBF: Radial Basis Function Kernel
Note: for more information see:
https://en.wikipedia.org/wiki/Radial_basis_function_kernel
Args:
vector1 (ndarray): first vector
vector2 (ndarray): second vector)
Returns:
float: exp(-(gamma * norm_squared(vector1 - vector2)))
"""
return np.exp(-(self.gamma * norm_squared(vector1 - vector2)))
def fit(self, observations: list[ndarray], classes: ndarray) -> None:
"""
Fits the SVC with a set of observations.
Args:
observations (list[ndarray]): list of observations
classes (ndarray): classification of each observation (in {1, -1})
"""
self.observations = observations
self.classes = classes
# using Wolfe's Dual to calculate w.
# Primal problem: minimize 1/2*norm_squared(w)
# constraint: yn(w . xn + b) >= 1
#
# With l a vector
# Dual problem: maximize sum_n(ln) -
# 1/2 * sum_n(sum_m(ln*lm*yn*ym*xn . xm))
# constraint: self.C >= ln >= 0
# and sum_n(ln*yn) = 0
# Then we get w using w = sum_n(ln*yn*xn)
# At the end we can get b ~= mean(yn - w . xn)
#
# Since we use kernels, we only need l_star to calculate b
# and to classify observations
(n,) = np.shape(classes)
def to_minimize(candidate: ndarray) -> float:
"""
Opposite of the function to maximize
Args:
candidate (ndarray): candidate array to test
Return:
float: Wolfe's Dual result to minimize
"""
s = 0
(n,) = np.shape(candidate)
for i in range(n):
for j in range(n):
s += (
candidate[i]
* candidate[j]
* classes[i]
* classes[j]
* self.kernel(observations[i], observations[j])
)
return 1 / 2 * s - sum(candidate)
ly_contraint = LinearConstraint(classes, 0, 0)
l_bounds = Bounds(0, self.regularization)
l_star = minimize(
to_minimize, np.ones(n), bounds=l_bounds, constraints=[ly_contraint]
).x
self.optimum = l_star
# calculating mean offset of separation plane to points
s = 0
for i in range(n):
for j in range(n):
s += classes[i] - classes[i] * self.optimum[i] * self.kernel(
observations[i], observations[j]
)
self.offset = s / n
def predict(self, observation: ndarray) -> int:
"""
Get the expected class of an observation
Args:
observation (Vector): observation
Returns:
int {1, -1}: expected class
>>> xs = [
... np.asarray([0, 1]), np.asarray([0, 2]),
... np.asarray([1, 1]), np.asarray([1, 2])
... ]
>>> y = np.asarray([1, 1, -1, -1])
>>> s = SVC()
>>> s.fit(xs, y)
>>> s.predict(np.asarray([0, 1]))
1
>>> s.predict(np.asarray([1, 1]))
-1
>>> s.predict(np.asarray([2, 2]))
-1
"""
s = sum(
self.optimum[n]
* self.classes[n]
* self.kernel(self.observations[n], observation)
for n in range(len(self.classes))
)
return 1 if s + self.offset >= 0 else -1
if __name__ == "__main__":
import doctest
doctest.testmod()
| import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def norm_squared(vector: ndarray) -> float:
"""
Return the squared second norm of vector
norm_squared(v) = sum(x * x for x in v)
Args:
vector (ndarray): input vector
Returns:
float: squared second norm of vector
>>> norm_squared([1, 2])
5
>>> norm_squared(np.asarray([1, 2]))
5
>>> norm_squared([0, 0])
0
"""
return np.dot(vector, vector)
class SVC:
"""
Support Vector Classifier
Args:
kernel (str): kernel to use. Default: linear
Possible choices:
- linear
regularization: constraint for soft margin (data not linearly separable)
Default: unbound
>>> SVC(kernel="asdf")
Traceback (most recent call last):
...
ValueError: Unknown kernel: asdf
>>> SVC(kernel="rbf")
Traceback (most recent call last):
...
ValueError: rbf kernel requires gamma
>>> SVC(kernel="rbf", gamma=-1)
Traceback (most recent call last):
...
ValueError: gamma must be > 0
"""
def __init__(
self,
*,
regularization: float = np.inf,
kernel: str = "linear",
gamma: float = 0,
) -> None:
self.regularization = regularization
self.gamma = gamma
if kernel == "linear":
self.kernel = self.__linear
elif kernel == "rbf":
if self.gamma == 0:
raise ValueError("rbf kernel requires gamma")
if not (isinstance(self.gamma, float) or isinstance(self.gamma, int)):
raise ValueError("gamma must be float or int")
if not self.gamma > 0:
raise ValueError("gamma must be > 0")
self.kernel = self.__rbf
# in the future, there could be a default value like in sklearn
# sklear: def_gamma = 1/(n_features * X.var()) (wiki)
# previously it was 1/(n_features)
else:
raise ValueError(f"Unknown kernel: {kernel}")
# kernels
def __linear(self, vector1: ndarray, vector2: ndarray) -> float:
"""Linear kernel (as if no kernel used at all)"""
return np.dot(vector1, vector2)
def __rbf(self, vector1: ndarray, vector2: ndarray) -> float:
"""
RBF: Radial Basis Function Kernel
Note: for more information see:
https://en.wikipedia.org/wiki/Radial_basis_function_kernel
Args:
vector1 (ndarray): first vector
vector2 (ndarray): second vector)
Returns:
float: exp(-(gamma * norm_squared(vector1 - vector2)))
"""
return np.exp(-(self.gamma * norm_squared(vector1 - vector2)))
def fit(self, observations: list[ndarray], classes: ndarray) -> None:
"""
Fits the SVC with a set of observations.
Args:
observations (list[ndarray]): list of observations
classes (ndarray): classification of each observation (in {1, -1})
"""
self.observations = observations
self.classes = classes
# using Wolfe's Dual to calculate w.
# Primal problem: minimize 1/2*norm_squared(w)
# constraint: yn(w . xn + b) >= 1
#
# With l a vector
# Dual problem: maximize sum_n(ln) -
# 1/2 * sum_n(sum_m(ln*lm*yn*ym*xn . xm))
# constraint: self.C >= ln >= 0
# and sum_n(ln*yn) = 0
# Then we get w using w = sum_n(ln*yn*xn)
# At the end we can get b ~= mean(yn - w . xn)
#
# Since we use kernels, we only need l_star to calculate b
# and to classify observations
(n,) = np.shape(classes)
def to_minimize(candidate: ndarray) -> float:
"""
Opposite of the function to maximize
Args:
candidate (ndarray): candidate array to test
Return:
float: Wolfe's Dual result to minimize
"""
s = 0
(n,) = np.shape(candidate)
for i in range(n):
for j in range(n):
s += (
candidate[i]
* candidate[j]
* classes[i]
* classes[j]
* self.kernel(observations[i], observations[j])
)
return 1 / 2 * s - sum(candidate)
ly_contraint = LinearConstraint(classes, 0, 0)
l_bounds = Bounds(0, self.regularization)
l_star = minimize(
to_minimize, np.ones(n), bounds=l_bounds, constraints=[ly_contraint]
).x
self.optimum = l_star
# calculating mean offset of separation plane to points
s = 0
for i in range(n):
for j in range(n):
s += classes[i] - classes[i] * self.optimum[i] * self.kernel(
observations[i], observations[j]
)
self.offset = s / n
def predict(self, observation: ndarray) -> int:
"""
Get the expected class of an observation
Args:
observation (Vector): observation
Returns:
int {1, -1}: expected class
>>> xs = [
... np.asarray([0, 1]), np.asarray([0, 2]),
... np.asarray([1, 1]), np.asarray([1, 2])
... ]
>>> y = np.asarray([1, 1, -1, -1])
>>> s = SVC()
>>> s.fit(xs, y)
>>> s.predict(np.asarray([0, 1]))
1
>>> s.predict(np.asarray([1, 1]))
-1
>>> s.predict(np.asarray([2, 2]))
-1
"""
s = sum(
self.optimum[n]
* self.classes[n]
* self.kernel(self.observations[n], observation)
for n in range(len(self.classes))
)
return 1 if s + self.offset >= 0 else -1
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Changing contrast with PIL
This algorithm is used in
https://noivce.pythonanywhere.com/ Python web app.
python/black: True
flake8 : True
"""
from PIL import Image
def change_contrast(img: Image, level: int) -> Image:
"""
Function to change contrast
"""
factor = (259 * (level + 255)) / (255 * (259 - level))
def contrast(c: int) -> int:
"""
Fundamental Transformation/Operation that'll be performed on
every bit.
"""
return int(128 + factor * (c - 128))
return img.point(contrast)
if __name__ == "__main__":
# Load image
with Image.open("image_data/lena.jpg") as img:
# Change contrast to 170
cont_img = change_contrast(img, 170)
cont_img.save("image_data/lena_high_contrast.png", format="png")
| """
Changing contrast with PIL
This algorithm is used in
https://noivce.pythonanywhere.com/ Python web app.
python/black: True
flake8 : True
"""
from PIL import Image
def change_contrast(img: Image, level: int) -> Image:
"""
Function to change contrast
"""
factor = (259 * (level + 255)) / (255 * (259 - level))
def contrast(c: int) -> int:
"""
Fundamental Transformation/Operation that'll be performed on
every bit.
"""
return int(128 + factor * (c - 128))
return img.point(contrast)
if __name__ == "__main__":
# Load image
with Image.open("image_data/lena.jpg") as img:
# Change contrast to 170
cont_img = change_contrast(img, 170)
cont_img.save("image_data/lena_high_contrast.png", format="png")
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # https://en.wikipedia.org/wiki/LC_circuit
"""An LC circuit, also called a resonant circuit, tank circuit, or tuned circuit,
is an electric circuit consisting of an inductor, represented by the letter L,
and a capacitor, represented by the letter C, connected together.
The circuit can act as an electrical resonator, an electrical analogue of a
tuning fork, storing energy oscillating at the circuit's resonant frequency.
Source: https://en.wikipedia.org/wiki/LC_circuit
"""
from __future__ import annotations
from math import pi, sqrt
def resonant_frequency(inductance: float, capacitance: float) -> tuple:
"""
This function can calculate the resonant frequency of LC circuit,
for the given value of inductance and capacitnace.
Examples are given below:
>>> resonant_frequency(inductance=10, capacitance=5)
('Resonant frequency', 0.022507907903927652)
>>> resonant_frequency(inductance=0, capacitance=5)
Traceback (most recent call last):
...
ValueError: Inductance cannot be 0 or negative
>>> resonant_frequency(inductance=10, capacitance=0)
Traceback (most recent call last):
...
ValueError: Capacitance cannot be 0 or negative
"""
if inductance <= 0:
raise ValueError("Inductance cannot be 0 or negative")
elif capacitance <= 0:
raise ValueError("Capacitance cannot be 0 or negative")
else:
return (
"Resonant frequency",
float(1 / (2 * pi * (sqrt(inductance * capacitance)))),
)
if __name__ == "__main__":
import doctest
doctest.testmod()
| # https://en.wikipedia.org/wiki/LC_circuit
"""An LC circuit, also called a resonant circuit, tank circuit, or tuned circuit,
is an electric circuit consisting of an inductor, represented by the letter L,
and a capacitor, represented by the letter C, connected together.
The circuit can act as an electrical resonator, an electrical analogue of a
tuning fork, storing energy oscillating at the circuit's resonant frequency.
Source: https://en.wikipedia.org/wiki/LC_circuit
"""
from __future__ import annotations
from math import pi, sqrt
def resonant_frequency(inductance: float, capacitance: float) -> tuple:
"""
This function can calculate the resonant frequency of LC circuit,
for the given value of inductance and capacitnace.
Examples are given below:
>>> resonant_frequency(inductance=10, capacitance=5)
('Resonant frequency', 0.022507907903927652)
>>> resonant_frequency(inductance=0, capacitance=5)
Traceback (most recent call last):
...
ValueError: Inductance cannot be 0 or negative
>>> resonant_frequency(inductance=10, capacitance=0)
Traceback (most recent call last):
...
ValueError: Capacitance cannot be 0 or negative
"""
if inductance <= 0:
raise ValueError("Inductance cannot be 0 or negative")
elif capacitance <= 0:
raise ValueError("Capacitance cannot be 0 or negative")
else:
return (
"Resonant frequency",
float(1 / (2 * pi * (sqrt(inductance * capacitance)))),
)
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| #
| #
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Problem 16: https://projecteuler.net/problem=16
2^15 = 32768 and the sum of its digits is 3 + 2 + 7 + 6 + 8 = 26.
What is the sum of the digits of the number 2^1000?
"""
def solution(power: int = 1000) -> int:
"""Returns the sum of the digits of the number 2^power.
>>> solution(1000)
1366
>>> solution(50)
76
>>> solution(20)
31
>>> solution(15)
26
"""
num = 2**power
string_num = str(num)
list_num = list(string_num)
sum_of_num = 0
for i in list_num:
sum_of_num += int(i)
return sum_of_num
if __name__ == "__main__":
power = int(input("Enter the power of 2: ").strip())
print("2 ^ ", power, " = ", 2**power)
result = solution(power)
print("Sum of the digits is: ", result)
| """
Problem 16: https://projecteuler.net/problem=16
2^15 = 32768 and the sum of its digits is 3 + 2 + 7 + 6 + 8 = 26.
What is the sum of the digits of the number 2^1000?
"""
def solution(power: int = 1000) -> int:
"""Returns the sum of the digits of the number 2^power.
>>> solution(1000)
1366
>>> solution(50)
76
>>> solution(20)
31
>>> solution(15)
26
"""
num = 2**power
string_num = str(num)
list_num = list(string_num)
sum_of_num = 0
for i in list_num:
sum_of_num += int(i)
return sum_of_num
if __name__ == "__main__":
power = int(input("Enter the power of 2: ").strip())
print("2 ^ ", power, " = ", 2**power)
result = solution(power)
print("Sum of the digits is: ", result)
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
The algorithm finds the pattern in given text using following rule.
The bad-character rule considers the mismatched character in Text.
The next occurrence of that character to the left in Pattern is found,
If the mismatched character occurs to the left in Pattern,
a shift is proposed that aligns text block and pattern.
If the mismatched character does not occur to the left in Pattern,
a shift is proposed that moves the entirety of Pattern past
the point of mismatch in the text.
If there no mismatch then the pattern matches with text block.
Time Complexity : O(n/m)
n=length of main string
m=length of pattern string
"""
from __future__ import annotations
class BoyerMooreSearch:
def __init__(self, text: str, pattern: str):
self.text, self.pattern = text, pattern
self.textLen, self.patLen = len(text), len(pattern)
def match_in_pattern(self, char: str) -> int:
"""finds the index of char in pattern in reverse order
Parameters :
char (chr): character to be searched
Returns :
i (int): index of char from last in pattern
-1 (int): if char is not found in pattern
"""
for i in range(self.patLen - 1, -1, -1):
if char == self.pattern[i]:
return i
return -1
def mismatch_in_text(self, current_pos: int) -> int:
"""
find the index of mis-matched character in text when compared with pattern
from last
Parameters :
current_pos (int): current index position of text
Returns :
i (int): index of mismatched char from last in text
-1 (int): if there is no mismatch between pattern and text block
"""
for i in range(self.patLen - 1, -1, -1):
if self.pattern[i] != self.text[current_pos + i]:
return current_pos + i
return -1
def bad_character_heuristic(self) -> list[int]:
# searches pattern in text and returns index positions
positions = []
for i in range(self.textLen - self.patLen + 1):
mismatch_index = self.mismatch_in_text(i)
if mismatch_index == -1:
positions.append(i)
else:
match_index = self.match_in_pattern(self.text[mismatch_index])
i = (
mismatch_index - match_index
) # shifting index lgtm [py/multiple-definition]
return positions
text = "ABAABA"
pattern = "AB"
bms = BoyerMooreSearch(text, pattern)
positions = bms.bad_character_heuristic()
if len(positions) == 0:
print("No match found")
else:
print("Pattern found in following positions: ")
print(positions)
| """
The algorithm finds the pattern in given text using following rule.
The bad-character rule considers the mismatched character in Text.
The next occurrence of that character to the left in Pattern is found,
If the mismatched character occurs to the left in Pattern,
a shift is proposed that aligns text block and pattern.
If the mismatched character does not occur to the left in Pattern,
a shift is proposed that moves the entirety of Pattern past
the point of mismatch in the text.
If there no mismatch then the pattern matches with text block.
Time Complexity : O(n/m)
n=length of main string
m=length of pattern string
"""
from __future__ import annotations
class BoyerMooreSearch:
def __init__(self, text: str, pattern: str):
self.text, self.pattern = text, pattern
self.textLen, self.patLen = len(text), len(pattern)
def match_in_pattern(self, char: str) -> int:
"""finds the index of char in pattern in reverse order
Parameters :
char (chr): character to be searched
Returns :
i (int): index of char from last in pattern
-1 (int): if char is not found in pattern
"""
for i in range(self.patLen - 1, -1, -1):
if char == self.pattern[i]:
return i
return -1
def mismatch_in_text(self, current_pos: int) -> int:
"""
find the index of mis-matched character in text when compared with pattern
from last
Parameters :
current_pos (int): current index position of text
Returns :
i (int): index of mismatched char from last in text
-1 (int): if there is no mismatch between pattern and text block
"""
for i in range(self.patLen - 1, -1, -1):
if self.pattern[i] != self.text[current_pos + i]:
return current_pos + i
return -1
def bad_character_heuristic(self) -> list[int]:
# searches pattern in text and returns index positions
positions = []
for i in range(self.textLen - self.patLen + 1):
mismatch_index = self.mismatch_in_text(i)
if mismatch_index == -1:
positions.append(i)
else:
match_index = self.match_in_pattern(self.text[mismatch_index])
i = (
mismatch_index - match_index
) # shifting index lgtm [py/multiple-definition]
return positions
text = "ABAABA"
pattern = "AB"
bms = BoyerMooreSearch(text, pattern)
positions = bms.bad_character_heuristic()
if len(positions) == 0:
print("No match found")
else:
print("Pattern found in following positions: ")
print(positions)
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| #!/usr/bin/env python3
"""Provide the functionality to manipulate a single bit."""
def set_bit(number: int, position: int) -> int:
"""
Set the bit at position to 1.
Details: perform bitwise or for given number and X.
Where X is a number with all the bits – zeroes and bit on given
position – one.
>>> set_bit(0b1101, 1) # 0b1111
15
>>> set_bit(0b0, 5) # 0b100000
32
>>> set_bit(0b1111, 1) # 0b1111
15
"""
return number | (1 << position)
def clear_bit(number: int, position: int) -> int:
"""
Set the bit at position to 0.
Details: perform bitwise and for given number and X.
Where X is a number with all the bits – ones and bit on given
position – zero.
>>> clear_bit(0b10010, 1) # 0b10000
16
>>> clear_bit(0b0, 5) # 0b0
0
"""
return number & ~(1 << position)
def flip_bit(number: int, position: int) -> int:
"""
Flip the bit at position.
Details: perform bitwise xor for given number and X.
Where X is a number with all the bits – zeroes and bit on given
position – one.
>>> flip_bit(0b101, 1) # 0b111
7
>>> flip_bit(0b101, 0) # 0b100
4
"""
return number ^ (1 << position)
def is_bit_set(number: int, position: int) -> bool:
"""
Is the bit at position set?
Details: Shift the bit at position to be the first (smallest) bit.
Then check if the first bit is set by anding the shifted number with 1.
>>> is_bit_set(0b1010, 0)
False
>>> is_bit_set(0b1010, 1)
True
>>> is_bit_set(0b1010, 2)
False
>>> is_bit_set(0b1010, 3)
True
>>> is_bit_set(0b0, 17)
False
"""
return ((number >> position) & 1) == 1
def get_bit(number: int, position: int) -> int:
"""
Get the bit at the given position
Details: perform bitwise and for the given number and X,
Where X is a number with all the bits – zeroes and bit on given position – one.
If the result is not equal to 0, then the bit on the given position is 1, else 0.
>>> get_bit(0b1010, 0)
0
>>> get_bit(0b1010, 1)
1
>>> get_bit(0b1010, 2)
0
>>> get_bit(0b1010, 3)
1
"""
return int((number & (1 << position)) != 0)
if __name__ == "__main__":
import doctest
doctest.testmod()
| #!/usr/bin/env python3
"""Provide the functionality to manipulate a single bit."""
def set_bit(number: int, position: int) -> int:
"""
Set the bit at position to 1.
Details: perform bitwise or for given number and X.
Where X is a number with all the bits – zeroes and bit on given
position – one.
>>> set_bit(0b1101, 1) # 0b1111
15
>>> set_bit(0b0, 5) # 0b100000
32
>>> set_bit(0b1111, 1) # 0b1111
15
"""
return number | (1 << position)
def clear_bit(number: int, position: int) -> int:
"""
Set the bit at position to 0.
Details: perform bitwise and for given number and X.
Where X is a number with all the bits – ones and bit on given
position – zero.
>>> clear_bit(0b10010, 1) # 0b10000
16
>>> clear_bit(0b0, 5) # 0b0
0
"""
return number & ~(1 << position)
def flip_bit(number: int, position: int) -> int:
"""
Flip the bit at position.
Details: perform bitwise xor for given number and X.
Where X is a number with all the bits – zeroes and bit on given
position – one.
>>> flip_bit(0b101, 1) # 0b111
7
>>> flip_bit(0b101, 0) # 0b100
4
"""
return number ^ (1 << position)
def is_bit_set(number: int, position: int) -> bool:
"""
Is the bit at position set?
Details: Shift the bit at position to be the first (smallest) bit.
Then check if the first bit is set by anding the shifted number with 1.
>>> is_bit_set(0b1010, 0)
False
>>> is_bit_set(0b1010, 1)
True
>>> is_bit_set(0b1010, 2)
False
>>> is_bit_set(0b1010, 3)
True
>>> is_bit_set(0b0, 17)
False
"""
return ((number >> position) & 1) == 1
def get_bit(number: int, position: int) -> int:
"""
Get the bit at the given position
Details: perform bitwise and for the given number and X,
Where X is a number with all the bits – zeroes and bit on given position – one.
If the result is not equal to 0, then the bit on the given position is 1, else 0.
>>> get_bit(0b1010, 0)
0
>>> get_bit(0b1010, 1)
1
>>> get_bit(0b1010, 2)
0
>>> get_bit(0b1010, 3)
1
"""
return int((number & (1 << position)) != 0)
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| from sys import maxsize
def max_sub_array_sum(a: list, size: int = 0):
"""
>>> max_sub_array_sum([-13, -3, -25, -20, -3, -16, -23, -12, -5, -22, -15, -4, -7])
-3
"""
size = size or len(a)
max_so_far = -maxsize - 1
max_ending_here = 0
for i in range(0, size):
max_ending_here = max_ending_here + a[i]
if max_so_far < max_ending_here:
max_so_far = max_ending_here
if max_ending_here < 0:
max_ending_here = 0
return max_so_far
if __name__ == "__main__":
a = [-13, -3, -25, -20, 1, -16, -23, -12, -5, -22, -15, -4, -7]
print(("Maximum contiguous sum is", max_sub_array_sum(a, len(a))))
| from sys import maxsize
def max_sub_array_sum(a: list, size: int = 0):
"""
>>> max_sub_array_sum([-13, -3, -25, -20, -3, -16, -23, -12, -5, -22, -15, -4, -7])
-3
"""
size = size or len(a)
max_so_far = -maxsize - 1
max_ending_here = 0
for i in range(0, size):
max_ending_here = max_ending_here + a[i]
if max_so_far < max_ending_here:
max_so_far = max_ending_here
if max_ending_here < 0:
max_ending_here = 0
return max_so_far
if __name__ == "__main__":
a = [-13, -3, -25, -20, 1, -16, -23, -12, -5, -22, -15, -4, -7]
print(("Maximum contiguous sum is", max_sub_array_sum(a, len(a))))
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Program to calculate the amortization amount per month, given
- Principal borrowed
- Rate of interest per annum
- Years to repay the loan
Wikipedia Reference: https://en.wikipedia.org/wiki/Equated_monthly_installment
"""
def equated_monthly_installments(
principal: float, rate_per_annum: float, years_to_repay: int
) -> float:
"""
Formula for amortization amount per month:
A = p * r * (1 + r)^n / ((1 + r)^n - 1)
where p is the principal, r is the rate of interest per month
and n is the number of payments
>>> equated_monthly_installments(25000, 0.12, 3)
830.3577453212793
>>> equated_monthly_installments(25000, 0.12, 10)
358.67737100646826
>>> equated_monthly_installments(0, 0.12, 3)
Traceback (most recent call last):
...
Exception: Principal borrowed must be > 0
>>> equated_monthly_installments(25000, -1, 3)
Traceback (most recent call last):
...
Exception: Rate of interest must be >= 0
>>> equated_monthly_installments(25000, 0.12, 0)
Traceback (most recent call last):
...
Exception: Years to repay must be an integer > 0
"""
if principal <= 0:
raise Exception("Principal borrowed must be > 0")
if rate_per_annum < 0:
raise Exception("Rate of interest must be >= 0")
if years_to_repay <= 0 or not isinstance(years_to_repay, int):
raise Exception("Years to repay must be an integer > 0")
# Yearly rate is divided by 12 to get monthly rate
rate_per_month = rate_per_annum / 12
# Years to repay is multiplied by 12 to get number of payments as payment is monthly
number_of_payments = years_to_repay * 12
return (
principal
* rate_per_month
* (1 + rate_per_month) ** number_of_payments
/ ((1 + rate_per_month) ** number_of_payments - 1)
)
if __name__ == "__main__":
import doctest
doctest.testmod()
| """
Program to calculate the amortization amount per month, given
- Principal borrowed
- Rate of interest per annum
- Years to repay the loan
Wikipedia Reference: https://en.wikipedia.org/wiki/Equated_monthly_installment
"""
def equated_monthly_installments(
principal: float, rate_per_annum: float, years_to_repay: int
) -> float:
"""
Formula for amortization amount per month:
A = p * r * (1 + r)^n / ((1 + r)^n - 1)
where p is the principal, r is the rate of interest per month
and n is the number of payments
>>> equated_monthly_installments(25000, 0.12, 3)
830.3577453212793
>>> equated_monthly_installments(25000, 0.12, 10)
358.67737100646826
>>> equated_monthly_installments(0, 0.12, 3)
Traceback (most recent call last):
...
Exception: Principal borrowed must be > 0
>>> equated_monthly_installments(25000, -1, 3)
Traceback (most recent call last):
...
Exception: Rate of interest must be >= 0
>>> equated_monthly_installments(25000, 0.12, 0)
Traceback (most recent call last):
...
Exception: Years to repay must be an integer > 0
"""
if principal <= 0:
raise Exception("Principal borrowed must be > 0")
if rate_per_annum < 0:
raise Exception("Rate of interest must be >= 0")
if years_to_repay <= 0 or not isinstance(years_to_repay, int):
raise Exception("Years to repay must be an integer > 0")
# Yearly rate is divided by 12 to get monthly rate
rate_per_month = rate_per_annum / 12
# Years to repay is multiplied by 12 to get number of payments as payment is monthly
number_of_payments = years_to_repay * 12
return (
principal
* rate_per_month
* (1 + rate_per_month) ** number_of_payments
/ ((1 + rate_per_month) ** number_of_payments - 1)
)
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
This is a pure Python implementation of the greedy-merge-sort algorithm
reference: https://www.geeksforgeeks.org/optimal-file-merge-patterns/
For doctests run following command:
python3 -m doctest -v greedy_merge_sort.py
Objective
Merge a set of sorted files of different length into a single sorted file.
We need to find an optimal solution, where the resultant file
will be generated in minimum time.
Approach
If the number of sorted files are given, there are many ways
to merge them into a single sorted file.
This merge can be performed pair wise.
To merge a m-record file and a n-record file requires possibly m+n record moves
the optimal choice being,
merge the two smallest files together at each step (greedy approach).
"""
def optimal_merge_pattern(files: list) -> float:
"""Function to merge all the files with optimum cost
Args:
files [list]: A list of sizes of different files to be merged
Returns:
optimal_merge_cost [int]: Optimal cost to merge all those files
Examples:
>>> optimal_merge_pattern([2, 3, 4])
14
>>> optimal_merge_pattern([5, 10, 20, 30, 30])
205
>>> optimal_merge_pattern([8, 8, 8, 8, 8])
96
"""
optimal_merge_cost = 0
while len(files) > 1:
temp = 0
# Consider two files with minimum cost to be merged
for _ in range(2):
min_index = files.index(min(files))
temp += files[min_index]
files.pop(min_index)
files.append(temp)
optimal_merge_cost += temp
return optimal_merge_cost
if __name__ == "__main__":
import doctest
doctest.testmod()
| """
This is a pure Python implementation of the greedy-merge-sort algorithm
reference: https://www.geeksforgeeks.org/optimal-file-merge-patterns/
For doctests run following command:
python3 -m doctest -v greedy_merge_sort.py
Objective
Merge a set of sorted files of different length into a single sorted file.
We need to find an optimal solution, where the resultant file
will be generated in minimum time.
Approach
If the number of sorted files are given, there are many ways
to merge them into a single sorted file.
This merge can be performed pair wise.
To merge a m-record file and a n-record file requires possibly m+n record moves
the optimal choice being,
merge the two smallest files together at each step (greedy approach).
"""
def optimal_merge_pattern(files: list) -> float:
"""Function to merge all the files with optimum cost
Args:
files [list]: A list of sizes of different files to be merged
Returns:
optimal_merge_cost [int]: Optimal cost to merge all those files
Examples:
>>> optimal_merge_pattern([2, 3, 4])
14
>>> optimal_merge_pattern([5, 10, 20, 30, 30])
205
>>> optimal_merge_pattern([8, 8, 8, 8, 8])
96
"""
optimal_merge_cost = 0
while len(files) > 1:
temp = 0
# Consider two files with minimum cost to be merged
for _ in range(2):
min_index = files.index(min(files))
temp += files[min_index]
files.pop(min_index)
files.append(temp)
optimal_merge_cost += temp
return optimal_merge_cost
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
https://en.wikipedia.org/wiki/Lucas_number
"""
def recursive_lucas_number(n_th_number: int) -> int:
"""
Returns the nth lucas number
>>> recursive_lucas_number(1)
1
>>> recursive_lucas_number(20)
15127
>>> recursive_lucas_number(0)
2
>>> recursive_lucas_number(25)
167761
>>> recursive_lucas_number(-1.5)
Traceback (most recent call last):
...
TypeError: recursive_lucas_number accepts only integer arguments.
"""
if not isinstance(n_th_number, int):
raise TypeError("recursive_lucas_number accepts only integer arguments.")
if n_th_number == 0:
return 2
if n_th_number == 1:
return 1
return recursive_lucas_number(n_th_number - 1) + recursive_lucas_number(
n_th_number - 2
)
def dynamic_lucas_number(n_th_number: int) -> int:
"""
Returns the nth lucas number
>>> dynamic_lucas_number(1)
1
>>> dynamic_lucas_number(20)
15127
>>> dynamic_lucas_number(0)
2
>>> dynamic_lucas_number(25)
167761
>>> dynamic_lucas_number(-1.5)
Traceback (most recent call last):
...
TypeError: dynamic_lucas_number accepts only integer arguments.
"""
if not isinstance(n_th_number, int):
raise TypeError("dynamic_lucas_number accepts only integer arguments.")
a, b = 2, 1
for _ in range(n_th_number):
a, b = b, a + b
return a
if __name__ == "__main__":
from doctest import testmod
testmod()
n = int(input("Enter the number of terms in lucas series:\n").strip())
print("Using recursive function to calculate lucas series:")
print(" ".join(str(recursive_lucas_number(i)) for i in range(n)))
print("\nUsing dynamic function to calculate lucas series:")
print(" ".join(str(dynamic_lucas_number(i)) for i in range(n)))
| """
https://en.wikipedia.org/wiki/Lucas_number
"""
def recursive_lucas_number(n_th_number: int) -> int:
"""
Returns the nth lucas number
>>> recursive_lucas_number(1)
1
>>> recursive_lucas_number(20)
15127
>>> recursive_lucas_number(0)
2
>>> recursive_lucas_number(25)
167761
>>> recursive_lucas_number(-1.5)
Traceback (most recent call last):
...
TypeError: recursive_lucas_number accepts only integer arguments.
"""
if not isinstance(n_th_number, int):
raise TypeError("recursive_lucas_number accepts only integer arguments.")
if n_th_number == 0:
return 2
if n_th_number == 1:
return 1
return recursive_lucas_number(n_th_number - 1) + recursive_lucas_number(
n_th_number - 2
)
def dynamic_lucas_number(n_th_number: int) -> int:
"""
Returns the nth lucas number
>>> dynamic_lucas_number(1)
1
>>> dynamic_lucas_number(20)
15127
>>> dynamic_lucas_number(0)
2
>>> dynamic_lucas_number(25)
167761
>>> dynamic_lucas_number(-1.5)
Traceback (most recent call last):
...
TypeError: dynamic_lucas_number accepts only integer arguments.
"""
if not isinstance(n_th_number, int):
raise TypeError("dynamic_lucas_number accepts only integer arguments.")
a, b = 2, 1
for _ in range(n_th_number):
a, b = b, a + b
return a
if __name__ == "__main__":
from doctest import testmod
testmod()
n = int(input("Enter the number of terms in lucas series:\n").strip())
print("Using recursive function to calculate lucas series:")
print(" ".join(str(recursive_lucas_number(i)) for i in range(n)))
print("\nUsing dynamic function to calculate lucas series:")
print(" ".join(str(dynamic_lucas_number(i)) for i in range(n)))
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch("socket.socket")
@patch("builtins.open")
def test_send_file_running_as_expected(file, sock):
# ===== initialization =====
conn = Mock()
sock.return_value.accept.return_value = conn, Mock()
f = iter([1, None])
file.return_value.__enter__.return_value.read.side_effect = lambda _: next(f)
# ===== invoke =====
send_file(filename="mytext.txt", testing=True)
# ===== ensurance =====
sock.assert_called_once()
sock.return_value.bind.assert_called_once()
sock.return_value.listen.assert_called_once()
sock.return_value.accept.assert_called_once()
conn.recv.assert_called_once()
file.return_value.__enter__.assert_called_once()
file.return_value.__enter__.return_value.read.assert_called()
conn.send.assert_called_once()
conn.close.assert_called_once()
sock.return_value.shutdown.assert_called_once()
sock.return_value.close.assert_called_once()
| from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch("socket.socket")
@patch("builtins.open")
def test_send_file_running_as_expected(file, sock):
# ===== initialization =====
conn = Mock()
sock.return_value.accept.return_value = conn, Mock()
f = iter([1, None])
file.return_value.__enter__.return_value.read.side_effect = lambda _: next(f)
# ===== invoke =====
send_file(filename="mytext.txt", testing=True)
# ===== ensurance =====
sock.assert_called_once()
sock.return_value.bind.assert_called_once()
sock.return_value.listen.assert_called_once()
sock.return_value.accept.assert_called_once()
conn.recv.assert_called_once()
file.return_value.__enter__.assert_called_once()
file.return_value.__enter__.return_value.read.assert_called()
conn.send.assert_called_once()
conn.close.assert_called_once()
sock.return_value.shutdown.assert_called_once()
sock.return_value.close.assert_called_once()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| def multiplicative_persistence(num: int) -> int:
"""
Return the persistence of a given number.
https://en.wikipedia.org/wiki/Persistence_of_a_number
>>> multiplicative_persistence(217)
2
>>> multiplicative_persistence(-1)
Traceback (most recent call last):
...
ValueError: multiplicative_persistence() does not accept negative values
>>> multiplicative_persistence("long number")
Traceback (most recent call last):
...
ValueError: multiplicative_persistence() only accepts integral values
"""
if not isinstance(num, int):
raise ValueError("multiplicative_persistence() only accepts integral values")
if num < 0:
raise ValueError("multiplicative_persistence() does not accept negative values")
steps = 0
num_string = str(num)
while len(num_string) != 1:
numbers = [int(i) for i in num_string]
total = 1
for i in range(0, len(numbers)):
total *= numbers[i]
num_string = str(total)
steps += 1
return steps
def additive_persistence(num: int) -> int:
"""
Return the persistence of a given number.
https://en.wikipedia.org/wiki/Persistence_of_a_number
>>> additive_persistence(199)
3
>>> additive_persistence(-1)
Traceback (most recent call last):
...
ValueError: additive_persistence() does not accept negative values
>>> additive_persistence("long number")
Traceback (most recent call last):
...
ValueError: additive_persistence() only accepts integral values
"""
if not isinstance(num, int):
raise ValueError("additive_persistence() only accepts integral values")
if num < 0:
raise ValueError("additive_persistence() does not accept negative values")
steps = 0
num_string = str(num)
while len(num_string) != 1:
numbers = [int(i) for i in num_string]
total = 0
for i in range(0, len(numbers)):
total += numbers[i]
num_string = str(total)
steps += 1
return steps
if __name__ == "__main__":
import doctest
doctest.testmod()
| def multiplicative_persistence(num: int) -> int:
"""
Return the persistence of a given number.
https://en.wikipedia.org/wiki/Persistence_of_a_number
>>> multiplicative_persistence(217)
2
>>> multiplicative_persistence(-1)
Traceback (most recent call last):
...
ValueError: multiplicative_persistence() does not accept negative values
>>> multiplicative_persistence("long number")
Traceback (most recent call last):
...
ValueError: multiplicative_persistence() only accepts integral values
"""
if not isinstance(num, int):
raise ValueError("multiplicative_persistence() only accepts integral values")
if num < 0:
raise ValueError("multiplicative_persistence() does not accept negative values")
steps = 0
num_string = str(num)
while len(num_string) != 1:
numbers = [int(i) for i in num_string]
total = 1
for i in range(0, len(numbers)):
total *= numbers[i]
num_string = str(total)
steps += 1
return steps
def additive_persistence(num: int) -> int:
"""
Return the persistence of a given number.
https://en.wikipedia.org/wiki/Persistence_of_a_number
>>> additive_persistence(199)
3
>>> additive_persistence(-1)
Traceback (most recent call last):
...
ValueError: additive_persistence() does not accept negative values
>>> additive_persistence("long number")
Traceback (most recent call last):
...
ValueError: additive_persistence() only accepts integral values
"""
if not isinstance(num, int):
raise ValueError("additive_persistence() only accepts integral values")
if num < 0:
raise ValueError("additive_persistence() does not accept negative values")
steps = 0
num_string = str(num)
while len(num_string) != 1:
numbers = [int(i) for i in num_string]
total = 0
for i in range(0, len(numbers)):
total += numbers[i]
num_string = str(total)
steps += 1
return steps
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| from __future__ import annotations
from collections import deque
class Automaton:
def __init__(self, keywords: list[str]):
self.adlist: list[dict] = []
self.adlist.append(
{"value": "", "next_states": [], "fail_state": 0, "output": []}
)
for keyword in keywords:
self.add_keyword(keyword)
self.set_fail_transitions()
def find_next_state(self, current_state: int, char: str) -> int | None:
for state in self.adlist[current_state]["next_states"]:
if char == self.adlist[state]["value"]:
return state
return None
def add_keyword(self, keyword: str) -> None:
current_state = 0
for character in keyword:
next_state = self.find_next_state(current_state, character)
if next_state is None:
self.adlist.append(
{
"value": character,
"next_states": [],
"fail_state": 0,
"output": [],
}
)
self.adlist[current_state]["next_states"].append(len(self.adlist) - 1)
current_state = len(self.adlist) - 1
else:
current_state = next_state
self.adlist[current_state]["output"].append(keyword)
def set_fail_transitions(self) -> None:
q: deque = deque()
for node in self.adlist[0]["next_states"]:
q.append(node)
self.adlist[node]["fail_state"] = 0
while q:
r = q.popleft()
for child in self.adlist[r]["next_states"]:
q.append(child)
state = self.adlist[r]["fail_state"]
while (
self.find_next_state(state, self.adlist[child]["value"]) is None
and state != 0
):
state = self.adlist[state]["fail_state"]
self.adlist[child]["fail_state"] = self.find_next_state(
state, self.adlist[child]["value"]
)
if self.adlist[child]["fail_state"] is None:
self.adlist[child]["fail_state"] = 0
self.adlist[child]["output"] = (
self.adlist[child]["output"]
+ self.adlist[self.adlist[child]["fail_state"]]["output"]
)
def search_in(self, string: str) -> dict[str, list[int]]:
"""
>>> A = Automaton(["what", "hat", "ver", "er"])
>>> A.search_in("whatever, err ... , wherever")
{'what': [0], 'hat': [1], 'ver': [5, 25], 'er': [6, 10, 22, 26]}
"""
result: dict = {} # returns a dict with keywords and list of its occurrences
current_state = 0
for i in range(len(string)):
while (
self.find_next_state(current_state, string[i]) is None
and current_state != 0
):
current_state = self.adlist[current_state]["fail_state"]
next_state = self.find_next_state(current_state, string[i])
if next_state is None:
current_state = 0
else:
current_state = next_state
for key in self.adlist[current_state]["output"]:
if not (key in result):
result[key] = []
result[key].append(i - len(key) + 1)
return result
if __name__ == "__main__":
import doctest
doctest.testmod()
| from __future__ import annotations
from collections import deque
class Automaton:
def __init__(self, keywords: list[str]):
self.adlist: list[dict] = []
self.adlist.append(
{"value": "", "next_states": [], "fail_state": 0, "output": []}
)
for keyword in keywords:
self.add_keyword(keyword)
self.set_fail_transitions()
def find_next_state(self, current_state: int, char: str) -> int | None:
for state in self.adlist[current_state]["next_states"]:
if char == self.adlist[state]["value"]:
return state
return None
def add_keyword(self, keyword: str) -> None:
current_state = 0
for character in keyword:
next_state = self.find_next_state(current_state, character)
if next_state is None:
self.adlist.append(
{
"value": character,
"next_states": [],
"fail_state": 0,
"output": [],
}
)
self.adlist[current_state]["next_states"].append(len(self.adlist) - 1)
current_state = len(self.adlist) - 1
else:
current_state = next_state
self.adlist[current_state]["output"].append(keyword)
def set_fail_transitions(self) -> None:
q: deque = deque()
for node in self.adlist[0]["next_states"]:
q.append(node)
self.adlist[node]["fail_state"] = 0
while q:
r = q.popleft()
for child in self.adlist[r]["next_states"]:
q.append(child)
state = self.adlist[r]["fail_state"]
while (
self.find_next_state(state, self.adlist[child]["value"]) is None
and state != 0
):
state = self.adlist[state]["fail_state"]
self.adlist[child]["fail_state"] = self.find_next_state(
state, self.adlist[child]["value"]
)
if self.adlist[child]["fail_state"] is None:
self.adlist[child]["fail_state"] = 0
self.adlist[child]["output"] = (
self.adlist[child]["output"]
+ self.adlist[self.adlist[child]["fail_state"]]["output"]
)
def search_in(self, string: str) -> dict[str, list[int]]:
"""
>>> A = Automaton(["what", "hat", "ver", "er"])
>>> A.search_in("whatever, err ... , wherever")
{'what': [0], 'hat': [1], 'ver': [5, 25], 'er': [6, 10, 22, 26]}
"""
result: dict = {} # returns a dict with keywords and list of its occurrences
current_state = 0
for i in range(len(string)):
while (
self.find_next_state(current_state, string[i]) is None
and current_state != 0
):
current_state = self.adlist[current_state]["fail_state"]
next_state = self.find_next_state(current_state, string[i])
if next_state is None:
current_state = 0
else:
current_state = next_state
for key in self.adlist[current_state]["output"]:
if not (key in result):
result[key] = []
result[key].append(i - len(key) + 1)
return result
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # Created by sarathkaul on 12/11/19
import requests
_NEWS_API = "https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="
def fetch_bbc_news(bbc_news_api_key: str) -> None:
# fetching a list of articles in json format
bbc_news_page = requests.get(_NEWS_API + bbc_news_api_key).json()
# each article in the list is a dict
for i, article in enumerate(bbc_news_page["articles"], 1):
print(f"{i}.) {article['title']}")
if __name__ == "__main__":
fetch_bbc_news(bbc_news_api_key="<Your BBC News API key goes here>")
| # Created by sarathkaul on 12/11/19
import requests
_NEWS_API = "https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="
def fetch_bbc_news(bbc_news_api_key: str) -> None:
# fetching a list of articles in json format
bbc_news_page = requests.get(_NEWS_API + bbc_news_api_key).json()
# each article in the list is a dict
for i, article in enumerate(bbc_news_page["articles"], 1):
print(f"{i}.) {article['title']}")
if __name__ == "__main__":
fetch_bbc_news(bbc_news_api_key="<Your BBC News API key goes here>")
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| from binascii import hexlify
from hashlib import sha256
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
primes = {
# 1536-bit
5: {
"prime": int(
"FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1"
+ "29024E088A67CC74020BBEA63B139B22514A08798E3404DD"
+ "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245"
+ "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED"
+ "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D"
+ "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F"
+ "83655D23DCA3AD961C62F356208552BB9ED529077096966D"
+ "670C354E4ABC9804F1746C08CA237327FFFFFFFFFFFFFFFF",
base=16,
),
"generator": 2,
},
# 2048-bit
14: {
"prime": int(
"FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1"
+ "29024E088A67CC74020BBEA63B139B22514A08798E3404DD"
+ "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245"
+ "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED"
+ "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D"
+ "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F"
+ "83655D23DCA3AD961C62F356208552BB9ED529077096966D"
+ "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B"
+ "E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9"
+ "DE2BCBF6955817183995497CEA956AE515D2261898FA0510"
+ "15728E5A8AACAA68FFFFFFFFFFFFFFFF",
base=16,
),
"generator": 2,
},
# 3072-bit
15: {
"prime": int(
"FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1"
+ "29024E088A67CC74020BBEA63B139B22514A08798E3404DD"
+ "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245"
+ "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED"
+ "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D"
+ "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F"
+ "83655D23DCA3AD961C62F356208552BB9ED529077096966D"
+ "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B"
+ "E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9"
+ "DE2BCBF6955817183995497CEA956AE515D2261898FA0510"
+ "15728E5A8AAAC42DAD33170D04507A33A85521ABDF1CBA64"
+ "ECFB850458DBEF0A8AEA71575D060C7DB3970F85A6E1E4C7"
+ "ABF5AE8CDB0933D71E8C94E04A25619DCEE3D2261AD2EE6B"
+ "F12FFA06D98A0864D87602733EC86A64521F2B18177B200C"
+ "BBE117577A615D6C770988C0BAD946E208E24FA074E5AB31"
+ "43DB5BFCE0FD108E4B82D120A93AD2CAFFFFFFFFFFFFFFFF",
base=16,
),
"generator": 2,
},
# 4096-bit
16: {
"prime": int(
"FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1"
+ "29024E088A67CC74020BBEA63B139B22514A08798E3404DD"
+ "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245"
+ "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED"
+ "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D"
+ "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F"
+ "83655D23DCA3AD961C62F356208552BB9ED529077096966D"
+ "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B"
+ "E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9"
+ "DE2BCBF6955817183995497CEA956AE515D2261898FA0510"
+ "15728E5A8AAAC42DAD33170D04507A33A85521ABDF1CBA64"
+ "ECFB850458DBEF0A8AEA71575D060C7DB3970F85A6E1E4C7"
+ "ABF5AE8CDB0933D71E8C94E04A25619DCEE3D2261AD2EE6B"
+ "F12FFA06D98A0864D87602733EC86A64521F2B18177B200C"
+ "BBE117577A615D6C770988C0BAD946E208E24FA074E5AB31"
+ "43DB5BFCE0FD108E4B82D120A92108011A723C12A787E6D7"
+ "88719A10BDBA5B2699C327186AF4E23C1A946834B6150BDA"
+ "2583E9CA2AD44CE8DBBBC2DB04DE8EF92E8EFC141FBECAA6"
+ "287C59474E6BC05D99B2964FA090C3A2233BA186515BE7ED"
+ "1F612970CEE2D7AFB81BDD762170481CD0069127D5B05AA9"
+ "93B4EA988D8FDDC186FFB7DC90A6C08F4DF435C934063199"
+ "FFFFFFFFFFFFFFFF",
base=16,
),
"generator": 2,
},
# 6144-bit
17: {
"prime": int(
"FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD129024E08"
+ "8A67CC74020BBEA63B139B22514A08798E3404DDEF9519B3CD3A431B"
+ "302B0A6DF25F14374FE1356D6D51C245E485B576625E7EC6F44C42E9"
+ "A637ED6B0BFF5CB6F406B7EDEE386BFB5A899FA5AE9F24117C4B1FE6"
+ "49286651ECE45B3DC2007CB8A163BF0598DA48361C55D39A69163FA8"
+ "FD24CF5F83655D23DCA3AD961C62F356208552BB9ED529077096966D"
+ "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3BE39E772C"
+ "180E86039B2783A2EC07A28FB5C55DF06F4C52C9DE2BCBF695581718"
+ "3995497CEA956AE515D2261898FA051015728E5A8AAAC42DAD33170D"
+ "04507A33A85521ABDF1CBA64ECFB850458DBEF0A8AEA71575D060C7D"
+ "B3970F85A6E1E4C7ABF5AE8CDB0933D71E8C94E04A25619DCEE3D226"
+ "1AD2EE6BF12FFA06D98A0864D87602733EC86A64521F2B18177B200C"
+ "BBE117577A615D6C770988C0BAD946E208E24FA074E5AB3143DB5BFC"
+ "E0FD108E4B82D120A92108011A723C12A787E6D788719A10BDBA5B26"
+ "99C327186AF4E23C1A946834B6150BDA2583E9CA2AD44CE8DBBBC2DB"
+ "04DE8EF92E8EFC141FBECAA6287C59474E6BC05D99B2964FA090C3A2"
+ "233BA186515BE7ED1F612970CEE2D7AFB81BDD762170481CD0069127"
+ "D5B05AA993B4EA988D8FDDC186FFB7DC90A6C08F4DF435C934028492"
+ "36C3FAB4D27C7026C1D4DCB2602646DEC9751E763DBA37BDF8FF9406"
+ "AD9E530EE5DB382F413001AEB06A53ED9027D831179727B0865A8918"
+ "DA3EDBEBCF9B14ED44CE6CBACED4BB1BDB7F1447E6CC254B33205151"
+ "2BD7AF426FB8F401378CD2BF5983CA01C64B92ECF032EA15D1721D03"
+ "F482D7CE6E74FEF6D55E702F46980C82B5A84031900B1C9E59E7C97F"
+ "BEC7E8F323A97A7E36CC88BE0F1D45B7FF585AC54BD407B22B4154AA"
+ "CC8F6D7EBF48E1D814CC5ED20F8037E0A79715EEF29BE32806A1D58B"
+ "B7C5DA76F550AA3D8A1FBFF0EB19CCB1A313D55CDA56C9EC2EF29632"
+ "387FE8D76E3C0468043E8F663F4860EE12BF2D5B0B7474D6E694F91E"
+ "6DCC4024FFFFFFFFFFFFFFFF",
base=16,
),
"generator": 2,
},
# 8192-bit
18: {
"prime": int(
"FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1"
+ "29024E088A67CC74020BBEA63B139B22514A08798E3404DD"
+ "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245"
+ "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED"
+ "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D"
+ "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F"
+ "83655D23DCA3AD961C62F356208552BB9ED529077096966D"
+ "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B"
+ "E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9"
+ "DE2BCBF6955817183995497CEA956AE515D2261898FA0510"
+ "15728E5A8AAAC42DAD33170D04507A33A85521ABDF1CBA64"
+ "ECFB850458DBEF0A8AEA71575D060C7DB3970F85A6E1E4C7"
+ "ABF5AE8CDB0933D71E8C94E04A25619DCEE3D2261AD2EE6B"
+ "F12FFA06D98A0864D87602733EC86A64521F2B18177B200C"
+ "BBE117577A615D6C770988C0BAD946E208E24FA074E5AB31"
+ "43DB5BFCE0FD108E4B82D120A92108011A723C12A787E6D7"
+ "88719A10BDBA5B2699C327186AF4E23C1A946834B6150BDA"
+ "2583E9CA2AD44CE8DBBBC2DB04DE8EF92E8EFC141FBECAA6"
+ "287C59474E6BC05D99B2964FA090C3A2233BA186515BE7ED"
+ "1F612970CEE2D7AFB81BDD762170481CD0069127D5B05AA9"
+ "93B4EA988D8FDDC186FFB7DC90A6C08F4DF435C934028492"
+ "36C3FAB4D27C7026C1D4DCB2602646DEC9751E763DBA37BD"
+ "F8FF9406AD9E530EE5DB382F413001AEB06A53ED9027D831"
+ "179727B0865A8918DA3EDBEBCF9B14ED44CE6CBACED4BB1B"
+ "DB7F1447E6CC254B332051512BD7AF426FB8F401378CD2BF"
+ "5983CA01C64B92ECF032EA15D1721D03F482D7CE6E74FEF6"
+ "D55E702F46980C82B5A84031900B1C9E59E7C97FBEC7E8F3"
+ "23A97A7E36CC88BE0F1D45B7FF585AC54BD407B22B4154AA"
+ "CC8F6D7EBF48E1D814CC5ED20F8037E0A79715EEF29BE328"
+ "06A1D58BB7C5DA76F550AA3D8A1FBFF0EB19CCB1A313D55C"
+ "DA56C9EC2EF29632387FE8D76E3C0468043E8F663F4860EE"
+ "12BF2D5B0B7474D6E694F91E6DBE115974A3926F12FEE5E4"
+ "38777CB6A932DF8CD8BEC4D073B931BA3BC832B68D9DD300"
+ "741FA7BF8AFC47ED2576F6936BA424663AAB639C5AE4F568"
+ "3423B4742BF1C978238F16CBE39D652DE3FDB8BEFC848AD9"
+ "22222E04A4037C0713EB57A81A23F0C73473FC646CEA306B"
+ "4BCBC8862F8385DDFA9D4B7FA2C087E879683303ED5BDD3A"
+ "062B3CF5B3A278A66D2A13F83F44F82DDF310EE074AB6A36"
+ "4597E899A0255DC164F31CC50846851DF9AB48195DED7EA1"
+ "B1D510BD7EE74D73FAF36BC31ECFA268359046F4EB879F92"
+ "4009438B481C6CD7889A002ED5EE382BC9190DA6FC026E47"
+ "9558E4475677E9AA9E3050E2765694DFC81F56E880B96E71"
+ "60C980DD98EDD3DFFFFFFFFFFFFFFFFF",
base=16,
),
"generator": 2,
},
}
class DiffieHellman:
"""
Class to represent the Diffie-Hellman key exchange protocol
>>> alice = DiffieHellman()
>>> bob = DiffieHellman()
>>> alice_private = alice.get_private_key()
>>> alice_public = alice.generate_public_key()
>>> bob_private = bob.get_private_key()
>>> bob_public = bob.generate_public_key()
>>> # generating shared key using the DH object
>>> alice_shared = alice.generate_shared_key(bob_public)
>>> bob_shared = bob.generate_shared_key(alice_public)
>>> assert alice_shared == bob_shared
>>> # generating shared key using static methods
>>> alice_shared = DiffieHellman.generate_shared_key_static(
... alice_private, bob_public
... )
>>> bob_shared = DiffieHellman.generate_shared_key_static(
... bob_private, alice_public
... )
>>> assert alice_shared == bob_shared
"""
# Current minimum recommendation is 2048 bit (group 14)
def __init__(self, group: int = 14) -> None:
if group not in primes:
raise ValueError("Unsupported Group")
self.prime = primes[group]["prime"]
self.generator = primes[group]["generator"]
self.__private_key = int(hexlify(urandom(32)), base=16)
def get_private_key(self) -> str:
return hex(self.__private_key)[2:]
def generate_public_key(self) -> str:
public_key = pow(self.generator, self.__private_key, self.prime)
return hex(public_key)[2:]
def is_valid_public_key(self, key: int) -> bool:
# check if the other public key is valid based on NIST SP800-56
if 2 <= key and key <= self.prime - 2:
if pow(key, (self.prime - 1) // 2, self.prime) == 1:
return True
return False
def generate_shared_key(self, other_key_str: str) -> str:
other_key = int(other_key_str, base=16)
if not self.is_valid_public_key(other_key):
raise ValueError("Invalid public key")
shared_key = pow(other_key, self.__private_key, self.prime)
return sha256(str(shared_key).encode()).hexdigest()
@staticmethod
def is_valid_public_key_static(remote_public_key_str: int, prime: int) -> bool:
# check if the other public key is valid based on NIST SP800-56
if 2 <= remote_public_key_str and remote_public_key_str <= prime - 2:
if pow(remote_public_key_str, (prime - 1) // 2, prime) == 1:
return True
return False
@staticmethod
def generate_shared_key_static(
local_private_key_str: str, remote_public_key_str: str, group: int = 14
) -> str:
local_private_key = int(local_private_key_str, base=16)
remote_public_key = int(remote_public_key_str, base=16)
prime = primes[group]["prime"]
if not DiffieHellman.is_valid_public_key_static(remote_public_key, prime):
raise ValueError("Invalid public key")
shared_key = pow(remote_public_key, local_private_key, prime)
return sha256(str(shared_key).encode()).hexdigest()
if __name__ == "__main__":
import doctest
doctest.testmod()
| from binascii import hexlify
from hashlib import sha256
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
primes = {
# 1536-bit
5: {
"prime": int(
"FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1"
+ "29024E088A67CC74020BBEA63B139B22514A08798E3404DD"
+ "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245"
+ "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED"
+ "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D"
+ "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F"
+ "83655D23DCA3AD961C62F356208552BB9ED529077096966D"
+ "670C354E4ABC9804F1746C08CA237327FFFFFFFFFFFFFFFF",
base=16,
),
"generator": 2,
},
# 2048-bit
14: {
"prime": int(
"FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1"
+ "29024E088A67CC74020BBEA63B139B22514A08798E3404DD"
+ "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245"
+ "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED"
+ "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D"
+ "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F"
+ "83655D23DCA3AD961C62F356208552BB9ED529077096966D"
+ "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B"
+ "E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9"
+ "DE2BCBF6955817183995497CEA956AE515D2261898FA0510"
+ "15728E5A8AACAA68FFFFFFFFFFFFFFFF",
base=16,
),
"generator": 2,
},
# 3072-bit
15: {
"prime": int(
"FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1"
+ "29024E088A67CC74020BBEA63B139B22514A08798E3404DD"
+ "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245"
+ "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED"
+ "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D"
+ "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F"
+ "83655D23DCA3AD961C62F356208552BB9ED529077096966D"
+ "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B"
+ "E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9"
+ "DE2BCBF6955817183995497CEA956AE515D2261898FA0510"
+ "15728E5A8AAAC42DAD33170D04507A33A85521ABDF1CBA64"
+ "ECFB850458DBEF0A8AEA71575D060C7DB3970F85A6E1E4C7"
+ "ABF5AE8CDB0933D71E8C94E04A25619DCEE3D2261AD2EE6B"
+ "F12FFA06D98A0864D87602733EC86A64521F2B18177B200C"
+ "BBE117577A615D6C770988C0BAD946E208E24FA074E5AB31"
+ "43DB5BFCE0FD108E4B82D120A93AD2CAFFFFFFFFFFFFFFFF",
base=16,
),
"generator": 2,
},
# 4096-bit
16: {
"prime": int(
"FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1"
+ "29024E088A67CC74020BBEA63B139B22514A08798E3404DD"
+ "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245"
+ "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED"
+ "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D"
+ "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F"
+ "83655D23DCA3AD961C62F356208552BB9ED529077096966D"
+ "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B"
+ "E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9"
+ "DE2BCBF6955817183995497CEA956AE515D2261898FA0510"
+ "15728E5A8AAAC42DAD33170D04507A33A85521ABDF1CBA64"
+ "ECFB850458DBEF0A8AEA71575D060C7DB3970F85A6E1E4C7"
+ "ABF5AE8CDB0933D71E8C94E04A25619DCEE3D2261AD2EE6B"
+ "F12FFA06D98A0864D87602733EC86A64521F2B18177B200C"
+ "BBE117577A615D6C770988C0BAD946E208E24FA074E5AB31"
+ "43DB5BFCE0FD108E4B82D120A92108011A723C12A787E6D7"
+ "88719A10BDBA5B2699C327186AF4E23C1A946834B6150BDA"
+ "2583E9CA2AD44CE8DBBBC2DB04DE8EF92E8EFC141FBECAA6"
+ "287C59474E6BC05D99B2964FA090C3A2233BA186515BE7ED"
+ "1F612970CEE2D7AFB81BDD762170481CD0069127D5B05AA9"
+ "93B4EA988D8FDDC186FFB7DC90A6C08F4DF435C934063199"
+ "FFFFFFFFFFFFFFFF",
base=16,
),
"generator": 2,
},
# 6144-bit
17: {
"prime": int(
"FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD129024E08"
+ "8A67CC74020BBEA63B139B22514A08798E3404DDEF9519B3CD3A431B"
+ "302B0A6DF25F14374FE1356D6D51C245E485B576625E7EC6F44C42E9"
+ "A637ED6B0BFF5CB6F406B7EDEE386BFB5A899FA5AE9F24117C4B1FE6"
+ "49286651ECE45B3DC2007CB8A163BF0598DA48361C55D39A69163FA8"
+ "FD24CF5F83655D23DCA3AD961C62F356208552BB9ED529077096966D"
+ "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3BE39E772C"
+ "180E86039B2783A2EC07A28FB5C55DF06F4C52C9DE2BCBF695581718"
+ "3995497CEA956AE515D2261898FA051015728E5A8AAAC42DAD33170D"
+ "04507A33A85521ABDF1CBA64ECFB850458DBEF0A8AEA71575D060C7D"
+ "B3970F85A6E1E4C7ABF5AE8CDB0933D71E8C94E04A25619DCEE3D226"
+ "1AD2EE6BF12FFA06D98A0864D87602733EC86A64521F2B18177B200C"
+ "BBE117577A615D6C770988C0BAD946E208E24FA074E5AB3143DB5BFC"
+ "E0FD108E4B82D120A92108011A723C12A787E6D788719A10BDBA5B26"
+ "99C327186AF4E23C1A946834B6150BDA2583E9CA2AD44CE8DBBBC2DB"
+ "04DE8EF92E8EFC141FBECAA6287C59474E6BC05D99B2964FA090C3A2"
+ "233BA186515BE7ED1F612970CEE2D7AFB81BDD762170481CD0069127"
+ "D5B05AA993B4EA988D8FDDC186FFB7DC90A6C08F4DF435C934028492"
+ "36C3FAB4D27C7026C1D4DCB2602646DEC9751E763DBA37BDF8FF9406"
+ "AD9E530EE5DB382F413001AEB06A53ED9027D831179727B0865A8918"
+ "DA3EDBEBCF9B14ED44CE6CBACED4BB1BDB7F1447E6CC254B33205151"
+ "2BD7AF426FB8F401378CD2BF5983CA01C64B92ECF032EA15D1721D03"
+ "F482D7CE6E74FEF6D55E702F46980C82B5A84031900B1C9E59E7C97F"
+ "BEC7E8F323A97A7E36CC88BE0F1D45B7FF585AC54BD407B22B4154AA"
+ "CC8F6D7EBF48E1D814CC5ED20F8037E0A79715EEF29BE32806A1D58B"
+ "B7C5DA76F550AA3D8A1FBFF0EB19CCB1A313D55CDA56C9EC2EF29632"
+ "387FE8D76E3C0468043E8F663F4860EE12BF2D5B0B7474D6E694F91E"
+ "6DCC4024FFFFFFFFFFFFFFFF",
base=16,
),
"generator": 2,
},
# 8192-bit
18: {
"prime": int(
"FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1"
+ "29024E088A67CC74020BBEA63B139B22514A08798E3404DD"
+ "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245"
+ "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED"
+ "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D"
+ "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F"
+ "83655D23DCA3AD961C62F356208552BB9ED529077096966D"
+ "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B"
+ "E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9"
+ "DE2BCBF6955817183995497CEA956AE515D2261898FA0510"
+ "15728E5A8AAAC42DAD33170D04507A33A85521ABDF1CBA64"
+ "ECFB850458DBEF0A8AEA71575D060C7DB3970F85A6E1E4C7"
+ "ABF5AE8CDB0933D71E8C94E04A25619DCEE3D2261AD2EE6B"
+ "F12FFA06D98A0864D87602733EC86A64521F2B18177B200C"
+ "BBE117577A615D6C770988C0BAD946E208E24FA074E5AB31"
+ "43DB5BFCE0FD108E4B82D120A92108011A723C12A787E6D7"
+ "88719A10BDBA5B2699C327186AF4E23C1A946834B6150BDA"
+ "2583E9CA2AD44CE8DBBBC2DB04DE8EF92E8EFC141FBECAA6"
+ "287C59474E6BC05D99B2964FA090C3A2233BA186515BE7ED"
+ "1F612970CEE2D7AFB81BDD762170481CD0069127D5B05AA9"
+ "93B4EA988D8FDDC186FFB7DC90A6C08F4DF435C934028492"
+ "36C3FAB4D27C7026C1D4DCB2602646DEC9751E763DBA37BD"
+ "F8FF9406AD9E530EE5DB382F413001AEB06A53ED9027D831"
+ "179727B0865A8918DA3EDBEBCF9B14ED44CE6CBACED4BB1B"
+ "DB7F1447E6CC254B332051512BD7AF426FB8F401378CD2BF"
+ "5983CA01C64B92ECF032EA15D1721D03F482D7CE6E74FEF6"
+ "D55E702F46980C82B5A84031900B1C9E59E7C97FBEC7E8F3"
+ "23A97A7E36CC88BE0F1D45B7FF585AC54BD407B22B4154AA"
+ "CC8F6D7EBF48E1D814CC5ED20F8037E0A79715EEF29BE328"
+ "06A1D58BB7C5DA76F550AA3D8A1FBFF0EB19CCB1A313D55C"
+ "DA56C9EC2EF29632387FE8D76E3C0468043E8F663F4860EE"
+ "12BF2D5B0B7474D6E694F91E6DBE115974A3926F12FEE5E4"
+ "38777CB6A932DF8CD8BEC4D073B931BA3BC832B68D9DD300"
+ "741FA7BF8AFC47ED2576F6936BA424663AAB639C5AE4F568"
+ "3423B4742BF1C978238F16CBE39D652DE3FDB8BEFC848AD9"
+ "22222E04A4037C0713EB57A81A23F0C73473FC646CEA306B"
+ "4BCBC8862F8385DDFA9D4B7FA2C087E879683303ED5BDD3A"
+ "062B3CF5B3A278A66D2A13F83F44F82DDF310EE074AB6A36"
+ "4597E899A0255DC164F31CC50846851DF9AB48195DED7EA1"
+ "B1D510BD7EE74D73FAF36BC31ECFA268359046F4EB879F92"
+ "4009438B481C6CD7889A002ED5EE382BC9190DA6FC026E47"
+ "9558E4475677E9AA9E3050E2765694DFC81F56E880B96E71"
+ "60C980DD98EDD3DFFFFFFFFFFFFFFFFF",
base=16,
),
"generator": 2,
},
}
class DiffieHellman:
"""
Class to represent the Diffie-Hellman key exchange protocol
>>> alice = DiffieHellman()
>>> bob = DiffieHellman()
>>> alice_private = alice.get_private_key()
>>> alice_public = alice.generate_public_key()
>>> bob_private = bob.get_private_key()
>>> bob_public = bob.generate_public_key()
>>> # generating shared key using the DH object
>>> alice_shared = alice.generate_shared_key(bob_public)
>>> bob_shared = bob.generate_shared_key(alice_public)
>>> assert alice_shared == bob_shared
>>> # generating shared key using static methods
>>> alice_shared = DiffieHellman.generate_shared_key_static(
... alice_private, bob_public
... )
>>> bob_shared = DiffieHellman.generate_shared_key_static(
... bob_private, alice_public
... )
>>> assert alice_shared == bob_shared
"""
# Current minimum recommendation is 2048 bit (group 14)
def __init__(self, group: int = 14) -> None:
if group not in primes:
raise ValueError("Unsupported Group")
self.prime = primes[group]["prime"]
self.generator = primes[group]["generator"]
self.__private_key = int(hexlify(urandom(32)), base=16)
def get_private_key(self) -> str:
return hex(self.__private_key)[2:]
def generate_public_key(self) -> str:
public_key = pow(self.generator, self.__private_key, self.prime)
return hex(public_key)[2:]
def is_valid_public_key(self, key: int) -> bool:
# check if the other public key is valid based on NIST SP800-56
if 2 <= key and key <= self.prime - 2:
if pow(key, (self.prime - 1) // 2, self.prime) == 1:
return True
return False
def generate_shared_key(self, other_key_str: str) -> str:
other_key = int(other_key_str, base=16)
if not self.is_valid_public_key(other_key):
raise ValueError("Invalid public key")
shared_key = pow(other_key, self.__private_key, self.prime)
return sha256(str(shared_key).encode()).hexdigest()
@staticmethod
def is_valid_public_key_static(remote_public_key_str: int, prime: int) -> bool:
# check if the other public key is valid based on NIST SP800-56
if 2 <= remote_public_key_str and remote_public_key_str <= prime - 2:
if pow(remote_public_key_str, (prime - 1) // 2, prime) == 1:
return True
return False
@staticmethod
def generate_shared_key_static(
local_private_key_str: str, remote_public_key_str: str, group: int = 14
) -> str:
local_private_key = int(local_private_key_str, base=16)
remote_public_key = int(remote_public_key_str, base=16)
prime = primes[group]["prime"]
if not DiffieHellman.is_valid_public_key_static(remote_public_key, prime):
raise ValueError("Invalid public key")
shared_key = pow(remote_public_key, local_private_key, prime)
return sha256(str(shared_key).encode()).hexdigest()
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| from collections.abc import Sequence
def evaluate_poly(poly: Sequence[float], x: float) -> float:
"""Evaluate a polynomial f(x) at specified point x and return the value.
Arguments:
poly -- the coefficients of a polynomial as an iterable in order of
ascending degree
x -- the point at which to evaluate the polynomial
>>> evaluate_poly((0.0, 0.0, 5.0, 9.3, 7.0), 10.0)
79800.0
"""
return sum(c * (x**i) for i, c in enumerate(poly))
def horner(poly: Sequence[float], x: float) -> float:
"""Evaluate a polynomial at specified point using Horner's method.
In terms of computational complexity, Horner's method is an efficient method
of evaluating a polynomial. It avoids the use of expensive exponentiation,
and instead uses only multiplication and addition to evaluate the polynomial
in O(n), where n is the degree of the polynomial.
https://en.wikipedia.org/wiki/Horner's_method
Arguments:
poly -- the coefficients of a polynomial as an iterable in order of
ascending degree
x -- the point at which to evaluate the polynomial
>>> horner((0.0, 0.0, 5.0, 9.3, 7.0), 10.0)
79800.0
"""
result = 0.0
for coeff in reversed(poly):
result = result * x + coeff
return result
if __name__ == "__main__":
"""
Example:
>>> poly = (0.0, 0.0, 5.0, 9.3, 7.0) # f(x) = 7.0x^4 + 9.3x^3 + 5.0x^2
>>> x = -13.0
>>> # f(-13) = 7.0(-13)^4 + 9.3(-13)^3 + 5.0(-13)^2 = 180339.9
>>> evaluate_poly(poly, x)
180339.9
"""
poly = (0.0, 0.0, 5.0, 9.3, 7.0)
x = 10.0
print(evaluate_poly(poly, x))
print(horner(poly, x))
| from collections.abc import Sequence
def evaluate_poly(poly: Sequence[float], x: float) -> float:
"""Evaluate a polynomial f(x) at specified point x and return the value.
Arguments:
poly -- the coefficients of a polynomial as an iterable in order of
ascending degree
x -- the point at which to evaluate the polynomial
>>> evaluate_poly((0.0, 0.0, 5.0, 9.3, 7.0), 10.0)
79800.0
"""
return sum(c * (x**i) for i, c in enumerate(poly))
def horner(poly: Sequence[float], x: float) -> float:
"""Evaluate a polynomial at specified point using Horner's method.
In terms of computational complexity, Horner's method is an efficient method
of evaluating a polynomial. It avoids the use of expensive exponentiation,
and instead uses only multiplication and addition to evaluate the polynomial
in O(n), where n is the degree of the polynomial.
https://en.wikipedia.org/wiki/Horner's_method
Arguments:
poly -- the coefficients of a polynomial as an iterable in order of
ascending degree
x -- the point at which to evaluate the polynomial
>>> horner((0.0, 0.0, 5.0, 9.3, 7.0), 10.0)
79800.0
"""
result = 0.0
for coeff in reversed(poly):
result = result * x + coeff
return result
if __name__ == "__main__":
"""
Example:
>>> poly = (0.0, 0.0, 5.0, 9.3, 7.0) # f(x) = 7.0x^4 + 9.3x^3 + 5.0x^2
>>> x = -13.0
>>> # f(-13) = 7.0(-13)^4 + 9.3(-13)^3 + 5.0(-13)^2 = 180339.9
>>> evaluate_poly(poly, x)
180339.9
"""
poly = (0.0, 0.0, 5.0, 9.3, 7.0)
x = 10.0
print(evaluate_poly(poly, x))
print(horner(poly, x))
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # Python program to show the usage of Fermat's little theorem in a division
# According to Fermat's little theorem, (a / b) mod p always equals
# a * (b ^ (p - 2)) mod p
# Here we assume that p is a prime number, b divides a, and p doesn't divide b
# Wikipedia reference: https://en.wikipedia.org/wiki/Fermat%27s_little_theorem
def binary_exponentiation(a, n, mod):
if n == 0:
return 1
elif n % 2 == 1:
return (binary_exponentiation(a, n - 1, mod) * a) % mod
else:
b = binary_exponentiation(a, n / 2, mod)
return (b * b) % mod
# a prime number
p = 701
a = 1000000000
b = 10
# using binary exponentiation function, O(log(p)):
print((a / b) % p == (a * binary_exponentiation(b, p - 2, p)) % p)
# using Python operators:
print((a / b) % p == (a * b ** (p - 2)) % p)
| # Python program to show the usage of Fermat's little theorem in a division
# According to Fermat's little theorem, (a / b) mod p always equals
# a * (b ^ (p - 2)) mod p
# Here we assume that p is a prime number, b divides a, and p doesn't divide b
# Wikipedia reference: https://en.wikipedia.org/wiki/Fermat%27s_little_theorem
def binary_exponentiation(a, n, mod):
if n == 0:
return 1
elif n % 2 == 1:
return (binary_exponentiation(a, n - 1, mod) * a) % mod
else:
b = binary_exponentiation(a, n / 2, mod)
return (b * b) % mod
# a prime number
p = 701
a = 1000000000
b = 10
# using binary exponentiation function, O(log(p)):
print((a / b) % p == (a * binary_exponentiation(b, p - 2, p)) % p)
# using Python operators:
print((a / b) % p == (a * b ** (p - 2)) % p)
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| import matplotlib.gridspec as gridspec
import matplotlib.pyplot as plt
import numpy as np
from sklearn.utils import shuffle
import input_data
random_numer = 42
np.random.seed(random_numer)
def ReLu(x):
mask = (x > 0) * 1.0
return mask * x
def d_ReLu(x):
mask = (x > 0) * 1.0
return mask
def arctan(x):
return np.arctan(x)
def d_arctan(x):
return 1 / (1 + x ** 2)
def log(x):
return 1 / (1 + np.exp(-1 * x))
def d_log(x):
return log(x) * (1 - log(x))
def tanh(x):
return np.tanh(x)
def d_tanh(x):
return 1 - np.tanh(x) ** 2
def plot(samples):
fig = plt.figure(figsize=(4, 4))
gs = gridspec.GridSpec(4, 4)
gs.update(wspace=0.05, hspace=0.05)
for i, sample in enumerate(samples):
ax = plt.subplot(gs[i])
plt.axis("off")
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.set_aspect("equal")
plt.imshow(sample.reshape(28, 28), cmap="Greys_r")
return fig
if __name__ == "__main__":
# 1. Load Data and declare hyper
print("--------- Load Data ----------")
mnist = input_data.read_data_sets("MNIST_data", one_hot=False)
temp = mnist.test
images, labels = temp.images, temp.labels
images, labels = shuffle(np.asarray(images), np.asarray(labels))
num_epoch = 10
learing_rate = 0.00009
G_input = 100
hidden_input, hidden_input2, hidden_input3 = 128, 256, 346
hidden_input4, hidden_input5, hidden_input6 = 480, 560, 686
print("--------- Declare Hyper Parameters ----------")
# 2. Declare Weights
D_W1 = (
np.random.normal(size=(784, hidden_input), scale=(1.0 / np.sqrt(784 / 2.0)))
* 0.002
)
# D_b1 = np.random.normal(size=(128),scale=(1. / np.sqrt(128 / 2.))) *0.002
D_b1 = np.zeros(hidden_input)
D_W2 = (
np.random.normal(
size=(hidden_input, 1), scale=(1.0 / np.sqrt(hidden_input / 2.0))
)
* 0.002
)
# D_b2 = np.random.normal(size=(1),scale=(1. / np.sqrt(1 / 2.))) *0.002
D_b2 = np.zeros(1)
G_W1 = (
np.random.normal(
size=(G_input, hidden_input), scale=(1.0 / np.sqrt(G_input / 2.0))
)
* 0.002
)
# G_b1 = np.random.normal(size=(128),scale=(1. / np.sqrt(128 / 2.))) *0.002
G_b1 = np.zeros(hidden_input)
G_W2 = (
np.random.normal(
size=(hidden_input, hidden_input2),
scale=(1.0 / np.sqrt(hidden_input / 2.0)),
)
* 0.002
)
# G_b1 = np.random.normal(size=(128),scale=(1. / np.sqrt(128 / 2.))) *0.002
G_b2 = np.zeros(hidden_input2)
G_W3 = (
np.random.normal(
size=(hidden_input2, hidden_input3),
scale=(1.0 / np.sqrt(hidden_input2 / 2.0)),
)
* 0.002
)
# G_b1 = np.random.normal(size=(128),scale=(1. / np.sqrt(128 / 2.))) *0.002
G_b3 = np.zeros(hidden_input3)
G_W4 = (
np.random.normal(
size=(hidden_input3, hidden_input4),
scale=(1.0 / np.sqrt(hidden_input3 / 2.0)),
)
* 0.002
)
# G_b1 = np.random.normal(size=(128),scale=(1. / np.sqrt(128 / 2.))) *0.002
G_b4 = np.zeros(hidden_input4)
G_W5 = (
np.random.normal(
size=(hidden_input4, hidden_input5),
scale=(1.0 / np.sqrt(hidden_input4 / 2.0)),
)
* 0.002
)
# G_b1 = np.random.normal(size=(128),scale=(1. / np.sqrt(128 / 2.))) *0.002
G_b5 = np.zeros(hidden_input5)
G_W6 = (
np.random.normal(
size=(hidden_input5, hidden_input6),
scale=(1.0 / np.sqrt(hidden_input5 / 2.0)),
)
* 0.002
)
# G_b1 = np.random.normal(size=(128),scale=(1. / np.sqrt(128 / 2.))) *0.002
G_b6 = np.zeros(hidden_input6)
G_W7 = (
np.random.normal(
size=(hidden_input6, 784), scale=(1.0 / np.sqrt(hidden_input6 / 2.0))
)
* 0.002
)
# G_b2 = np.random.normal(size=(784),scale=(1. / np.sqrt(784 / 2.))) *0.002
G_b7 = np.zeros(784)
# 3. For Adam Optimzier
v1, m1 = 0, 0
v2, m2 = 0, 0
v3, m3 = 0, 0
v4, m4 = 0, 0
v5, m5 = 0, 0
v6, m6 = 0, 0
v7, m7 = 0, 0
v8, m8 = 0, 0
v9, m9 = 0, 0
v10, m10 = 0, 0
v11, m11 = 0, 0
v12, m12 = 0, 0
v13, m13 = 0, 0
v14, m14 = 0, 0
v15, m15 = 0, 0
v16, m16 = 0, 0
v17, m17 = 0, 0
v18, m18 = 0, 0
beta_1, beta_2, eps = 0.9, 0.999, 0.00000001
print("--------- Started Training ----------")
for iter in range(num_epoch):
random_int = np.random.randint(len(images) - 5)
current_image = np.expand_dims(images[random_int], axis=0)
# Func: Generate The first Fake Data
Z = np.random.uniform(-1.0, 1.0, size=[1, G_input])
Gl1 = Z.dot(G_W1) + G_b1
Gl1A = arctan(Gl1)
Gl2 = Gl1A.dot(G_W2) + G_b2
Gl2A = ReLu(Gl2)
Gl3 = Gl2A.dot(G_W3) + G_b3
Gl3A = arctan(Gl3)
Gl4 = Gl3A.dot(G_W4) + G_b4
Gl4A = ReLu(Gl4)
Gl5 = Gl4A.dot(G_W5) + G_b5
Gl5A = tanh(Gl5)
Gl6 = Gl5A.dot(G_W6) + G_b6
Gl6A = ReLu(Gl6)
Gl7 = Gl6A.dot(G_W7) + G_b7
current_fake_data = log(Gl7)
# Func: Forward Feed for Real data
Dl1_r = current_image.dot(D_W1) + D_b1
Dl1_rA = ReLu(Dl1_r)
Dl2_r = Dl1_rA.dot(D_W2) + D_b2
Dl2_rA = log(Dl2_r)
# Func: Forward Feed for Fake Data
Dl1_f = current_fake_data.dot(D_W1) + D_b1
Dl1_fA = ReLu(Dl1_f)
Dl2_f = Dl1_fA.dot(D_W2) + D_b2
Dl2_fA = log(Dl2_f)
# Func: Cost D
D_cost = -np.log(Dl2_rA) + np.log(1.0 - Dl2_fA)
# Func: Gradient
grad_f_w2_part_1 = 1 / (1.0 - Dl2_fA)
grad_f_w2_part_2 = d_log(Dl2_f)
grad_f_w2_part_3 = Dl1_fA
grad_f_w2 = grad_f_w2_part_3.T.dot(grad_f_w2_part_1 * grad_f_w2_part_2)
grad_f_b2 = grad_f_w2_part_1 * grad_f_w2_part_2
grad_f_w1_part_1 = (grad_f_w2_part_1 * grad_f_w2_part_2).dot(D_W2.T)
grad_f_w1_part_2 = d_ReLu(Dl1_f)
grad_f_w1_part_3 = current_fake_data
grad_f_w1 = grad_f_w1_part_3.T.dot(grad_f_w1_part_1 * grad_f_w1_part_2)
grad_f_b1 = grad_f_w1_part_1 * grad_f_w1_part_2
grad_r_w2_part_1 = -1 / Dl2_rA
grad_r_w2_part_2 = d_log(Dl2_r)
grad_r_w2_part_3 = Dl1_rA
grad_r_w2 = grad_r_w2_part_3.T.dot(grad_r_w2_part_1 * grad_r_w2_part_2)
grad_r_b2 = grad_r_w2_part_1 * grad_r_w2_part_2
grad_r_w1_part_1 = (grad_r_w2_part_1 * grad_r_w2_part_2).dot(D_W2.T)
grad_r_w1_part_2 = d_ReLu(Dl1_r)
grad_r_w1_part_3 = current_image
grad_r_w1 = grad_r_w1_part_3.T.dot(grad_r_w1_part_1 * grad_r_w1_part_2)
grad_r_b1 = grad_r_w1_part_1 * grad_r_w1_part_2
grad_w1 = grad_f_w1 + grad_r_w1
grad_b1 = grad_f_b1 + grad_r_b1
grad_w2 = grad_f_w2 + grad_r_w2
grad_b2 = grad_f_b2 + grad_r_b2
# ---- Update Gradient ----
m1 = beta_1 * m1 + (1 - beta_1) * grad_w1
v1 = beta_2 * v1 + (1 - beta_2) * grad_w1 ** 2
m2 = beta_1 * m2 + (1 - beta_1) * grad_b1
v2 = beta_2 * v2 + (1 - beta_2) * grad_b1 ** 2
m3 = beta_1 * m3 + (1 - beta_1) * grad_w2
v3 = beta_2 * v3 + (1 - beta_2) * grad_w2 ** 2
m4 = beta_1 * m4 + (1 - beta_1) * grad_b2
v4 = beta_2 * v4 + (1 - beta_2) * grad_b2 ** 2
D_W1 = D_W1 - (learing_rate / (np.sqrt(v1 / (1 - beta_2)) + eps)) * (
m1 / (1 - beta_1)
)
D_b1 = D_b1 - (learing_rate / (np.sqrt(v2 / (1 - beta_2)) + eps)) * (
m2 / (1 - beta_1)
)
D_W2 = D_W2 - (learing_rate / (np.sqrt(v3 / (1 - beta_2)) + eps)) * (
m3 / (1 - beta_1)
)
D_b2 = D_b2 - (learing_rate / (np.sqrt(v4 / (1 - beta_2)) + eps)) * (
m4 / (1 - beta_1)
)
# Func: Forward Feed for G
Z = np.random.uniform(-1.0, 1.0, size=[1, G_input])
Gl1 = Z.dot(G_W1) + G_b1
Gl1A = arctan(Gl1)
Gl2 = Gl1A.dot(G_W2) + G_b2
Gl2A = ReLu(Gl2)
Gl3 = Gl2A.dot(G_W3) + G_b3
Gl3A = arctan(Gl3)
Gl4 = Gl3A.dot(G_W4) + G_b4
Gl4A = ReLu(Gl4)
Gl5 = Gl4A.dot(G_W5) + G_b5
Gl5A = tanh(Gl5)
Gl6 = Gl5A.dot(G_W6) + G_b6
Gl6A = ReLu(Gl6)
Gl7 = Gl6A.dot(G_W7) + G_b7
current_fake_data = log(Gl7)
Dl1 = current_fake_data.dot(D_W1) + D_b1
Dl1_A = ReLu(Dl1)
Dl2 = Dl1_A.dot(D_W2) + D_b2
Dl2_A = log(Dl2)
# Func: Cost G
G_cost = -np.log(Dl2_A)
# Func: Gradient
grad_G_w7_part_1 = ((-1 / Dl2_A) * d_log(Dl2).dot(D_W2.T) * (d_ReLu(Dl1))).dot(
D_W1.T
)
grad_G_w7_part_2 = d_log(Gl7)
grad_G_w7_part_3 = Gl6A
grad_G_w7 = grad_G_w7_part_3.T.dot(grad_G_w7_part_1 * grad_G_w7_part_1)
grad_G_b7 = grad_G_w7_part_1 * grad_G_w7_part_2
grad_G_w6_part_1 = (grad_G_w7_part_1 * grad_G_w7_part_2).dot(G_W7.T)
grad_G_w6_part_2 = d_ReLu(Gl6)
grad_G_w6_part_3 = Gl5A
grad_G_w6 = grad_G_w6_part_3.T.dot(grad_G_w6_part_1 * grad_G_w6_part_2)
grad_G_b6 = grad_G_w6_part_1 * grad_G_w6_part_2
grad_G_w5_part_1 = (grad_G_w6_part_1 * grad_G_w6_part_2).dot(G_W6.T)
grad_G_w5_part_2 = d_tanh(Gl5)
grad_G_w5_part_3 = Gl4A
grad_G_w5 = grad_G_w5_part_3.T.dot(grad_G_w5_part_1 * grad_G_w5_part_2)
grad_G_b5 = grad_G_w5_part_1 * grad_G_w5_part_2
grad_G_w4_part_1 = (grad_G_w5_part_1 * grad_G_w5_part_2).dot(G_W5.T)
grad_G_w4_part_2 = d_ReLu(Gl4)
grad_G_w4_part_3 = Gl3A
grad_G_w4 = grad_G_w4_part_3.T.dot(grad_G_w4_part_1 * grad_G_w4_part_2)
grad_G_b4 = grad_G_w4_part_1 * grad_G_w4_part_2
grad_G_w3_part_1 = (grad_G_w4_part_1 * grad_G_w4_part_2).dot(G_W4.T)
grad_G_w3_part_2 = d_arctan(Gl3)
grad_G_w3_part_3 = Gl2A
grad_G_w3 = grad_G_w3_part_3.T.dot(grad_G_w3_part_1 * grad_G_w3_part_2)
grad_G_b3 = grad_G_w3_part_1 * grad_G_w3_part_2
grad_G_w2_part_1 = (grad_G_w3_part_1 * grad_G_w3_part_2).dot(G_W3.T)
grad_G_w2_part_2 = d_ReLu(Gl2)
grad_G_w2_part_3 = Gl1A
grad_G_w2 = grad_G_w2_part_3.T.dot(grad_G_w2_part_1 * grad_G_w2_part_2)
grad_G_b2 = grad_G_w2_part_1 * grad_G_w2_part_2
grad_G_w1_part_1 = (grad_G_w2_part_1 * grad_G_w2_part_2).dot(G_W2.T)
grad_G_w1_part_2 = d_arctan(Gl1)
grad_G_w1_part_3 = Z
grad_G_w1 = grad_G_w1_part_3.T.dot(grad_G_w1_part_1 * grad_G_w1_part_2)
grad_G_b1 = grad_G_w1_part_1 * grad_G_w1_part_2
# ---- Update Gradient ----
m5 = beta_1 * m5 + (1 - beta_1) * grad_G_w1
v5 = beta_2 * v5 + (1 - beta_2) * grad_G_w1 ** 2
m6 = beta_1 * m6 + (1 - beta_1) * grad_G_b1
v6 = beta_2 * v6 + (1 - beta_2) * grad_G_b1 ** 2
m7 = beta_1 * m7 + (1 - beta_1) * grad_G_w2
v7 = beta_2 * v7 + (1 - beta_2) * grad_G_w2 ** 2
m8 = beta_1 * m8 + (1 - beta_1) * grad_G_b2
v8 = beta_2 * v8 + (1 - beta_2) * grad_G_b2 ** 2
m9 = beta_1 * m9 + (1 - beta_1) * grad_G_w3
v9 = beta_2 * v9 + (1 - beta_2) * grad_G_w3 ** 2
m10 = beta_1 * m10 + (1 - beta_1) * grad_G_b3
v10 = beta_2 * v10 + (1 - beta_2) * grad_G_b3 ** 2
m11 = beta_1 * m11 + (1 - beta_1) * grad_G_w4
v11 = beta_2 * v11 + (1 - beta_2) * grad_G_w4 ** 2
m12 = beta_1 * m12 + (1 - beta_1) * grad_G_b4
v12 = beta_2 * v12 + (1 - beta_2) * grad_G_b4 ** 2
m13 = beta_1 * m13 + (1 - beta_1) * grad_G_w5
v13 = beta_2 * v13 + (1 - beta_2) * grad_G_w5 ** 2
m14 = beta_1 * m14 + (1 - beta_1) * grad_G_b5
v14 = beta_2 * v14 + (1 - beta_2) * grad_G_b5 ** 2
m15 = beta_1 * m15 + (1 - beta_1) * grad_G_w6
v15 = beta_2 * v15 + (1 - beta_2) * grad_G_w6 ** 2
m16 = beta_1 * m16 + (1 - beta_1) * grad_G_b6
v16 = beta_2 * v16 + (1 - beta_2) * grad_G_b6 ** 2
m17 = beta_1 * m17 + (1 - beta_1) * grad_G_w7
v17 = beta_2 * v17 + (1 - beta_2) * grad_G_w7 ** 2
m18 = beta_1 * m18 + (1 - beta_1) * grad_G_b7
v18 = beta_2 * v18 + (1 - beta_2) * grad_G_b7 ** 2
G_W1 = G_W1 - (learing_rate / (np.sqrt(v5 / (1 - beta_2)) + eps)) * (
m5 / (1 - beta_1)
)
G_b1 = G_b1 - (learing_rate / (np.sqrt(v6 / (1 - beta_2)) + eps)) * (
m6 / (1 - beta_1)
)
G_W2 = G_W2 - (learing_rate / (np.sqrt(v7 / (1 - beta_2)) + eps)) * (
m7 / (1 - beta_1)
)
G_b2 = G_b2 - (learing_rate / (np.sqrt(v8 / (1 - beta_2)) + eps)) * (
m8 / (1 - beta_1)
)
G_W3 = G_W3 - (learing_rate / (np.sqrt(v9 / (1 - beta_2)) + eps)) * (
m9 / (1 - beta_1)
)
G_b3 = G_b3 - (learing_rate / (np.sqrt(v10 / (1 - beta_2)) + eps)) * (
m10 / (1 - beta_1)
)
G_W4 = G_W4 - (learing_rate / (np.sqrt(v11 / (1 - beta_2)) + eps)) * (
m11 / (1 - beta_1)
)
G_b4 = G_b4 - (learing_rate / (np.sqrt(v12 / (1 - beta_2)) + eps)) * (
m12 / (1 - beta_1)
)
G_W5 = G_W5 - (learing_rate / (np.sqrt(v13 / (1 - beta_2)) + eps)) * (
m13 / (1 - beta_1)
)
G_b5 = G_b5 - (learing_rate / (np.sqrt(v14 / (1 - beta_2)) + eps)) * (
m14 / (1 - beta_1)
)
G_W6 = G_W6 - (learing_rate / (np.sqrt(v15 / (1 - beta_2)) + eps)) * (
m15 / (1 - beta_1)
)
G_b6 = G_b6 - (learing_rate / (np.sqrt(v16 / (1 - beta_2)) + eps)) * (
m16 / (1 - beta_1)
)
G_W7 = G_W7 - (learing_rate / (np.sqrt(v17 / (1 - beta_2)) + eps)) * (
m17 / (1 - beta_1)
)
G_b7 = G_b7 - (learing_rate / (np.sqrt(v18 / (1 - beta_2)) + eps)) * (
m18 / (1 - beta_1)
)
# --- Print Error ----
# print("Current Iter: ",iter, " Current D cost:",D_cost, " Current G cost: ", G_cost,end='\r')
if iter == 0:
learing_rate = learing_rate * 0.01
if iter == 40:
learing_rate = learing_rate * 0.01
# ---- Print to Out put ----
if iter % 10 == 0:
print(
"Current Iter: ",
iter,
" Current D cost:",
D_cost,
" Current G cost: ",
G_cost,
end="\r",
)
print("--------- Show Example Result See Tab Above ----------")
print("--------- Wait for the image to load ---------")
Z = np.random.uniform(-1.0, 1.0, size=[16, G_input])
Gl1 = Z.dot(G_W1) + G_b1
Gl1A = arctan(Gl1)
Gl2 = Gl1A.dot(G_W2) + G_b2
Gl2A = ReLu(Gl2)
Gl3 = Gl2A.dot(G_W3) + G_b3
Gl3A = arctan(Gl3)
Gl4 = Gl3A.dot(G_W4) + G_b4
Gl4A = ReLu(Gl4)
Gl5 = Gl4A.dot(G_W5) + G_b5
Gl5A = tanh(Gl5)
Gl6 = Gl5A.dot(G_W6) + G_b6
Gl6A = ReLu(Gl6)
Gl7 = Gl6A.dot(G_W7) + G_b7
current_fake_data = log(Gl7)
fig = plot(current_fake_data)
fig.savefig(
"Click_Me_{}.png".format(
str(iter).zfill(3)
+ "_Ginput_"
+ str(G_input)
+ "_hiddenone"
+ str(hidden_input)
+ "_hiddentwo"
+ str(hidden_input2)
+ "_LR_"
+ str(learing_rate)
),
bbox_inches="tight",
)
# for complete explanation visit https://towardsdatascience.com/only-numpy-implementing-gan-general-adversarial-networks-and-adam-optimizer-using-numpy-with-2a7e4e032021
# -- end code --
| import matplotlib.gridspec as gridspec
import matplotlib.pyplot as plt
import numpy as np
from sklearn.utils import shuffle
import input_data
random_numer = 42
np.random.seed(random_numer)
def ReLu(x):
mask = (x > 0) * 1.0
return mask * x
def d_ReLu(x):
mask = (x > 0) * 1.0
return mask
def arctan(x):
return np.arctan(x)
def d_arctan(x):
return 1 / (1 + x ** 2)
def log(x):
return 1 / (1 + np.exp(-1 * x))
def d_log(x):
return log(x) * (1 - log(x))
def tanh(x):
return np.tanh(x)
def d_tanh(x):
return 1 - np.tanh(x) ** 2
def plot(samples):
fig = plt.figure(figsize=(4, 4))
gs = gridspec.GridSpec(4, 4)
gs.update(wspace=0.05, hspace=0.05)
for i, sample in enumerate(samples):
ax = plt.subplot(gs[i])
plt.axis("off")
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.set_aspect("equal")
plt.imshow(sample.reshape(28, 28), cmap="Greys_r")
return fig
if __name__ == "__main__":
# 1. Load Data and declare hyper
print("--------- Load Data ----------")
mnist = input_data.read_data_sets("MNIST_data", one_hot=False)
temp = mnist.test
images, labels = temp.images, temp.labels
images, labels = shuffle(np.asarray(images), np.asarray(labels))
num_epoch = 10
learing_rate = 0.00009
G_input = 100
hidden_input, hidden_input2, hidden_input3 = 128, 256, 346
hidden_input4, hidden_input5, hidden_input6 = 480, 560, 686
print("--------- Declare Hyper Parameters ----------")
# 2. Declare Weights
D_W1 = (
np.random.normal(size=(784, hidden_input), scale=(1.0 / np.sqrt(784 / 2.0)))
* 0.002
)
# D_b1 = np.random.normal(size=(128),scale=(1. / np.sqrt(128 / 2.))) *0.002
D_b1 = np.zeros(hidden_input)
D_W2 = (
np.random.normal(
size=(hidden_input, 1), scale=(1.0 / np.sqrt(hidden_input / 2.0))
)
* 0.002
)
# D_b2 = np.random.normal(size=(1),scale=(1. / np.sqrt(1 / 2.))) *0.002
D_b2 = np.zeros(1)
G_W1 = (
np.random.normal(
size=(G_input, hidden_input), scale=(1.0 / np.sqrt(G_input / 2.0))
)
* 0.002
)
# G_b1 = np.random.normal(size=(128),scale=(1. / np.sqrt(128 / 2.))) *0.002
G_b1 = np.zeros(hidden_input)
G_W2 = (
np.random.normal(
size=(hidden_input, hidden_input2),
scale=(1.0 / np.sqrt(hidden_input / 2.0)),
)
* 0.002
)
# G_b1 = np.random.normal(size=(128),scale=(1. / np.sqrt(128 / 2.))) *0.002
G_b2 = np.zeros(hidden_input2)
G_W3 = (
np.random.normal(
size=(hidden_input2, hidden_input3),
scale=(1.0 / np.sqrt(hidden_input2 / 2.0)),
)
* 0.002
)
# G_b1 = np.random.normal(size=(128),scale=(1. / np.sqrt(128 / 2.))) *0.002
G_b3 = np.zeros(hidden_input3)
G_W4 = (
np.random.normal(
size=(hidden_input3, hidden_input4),
scale=(1.0 / np.sqrt(hidden_input3 / 2.0)),
)
* 0.002
)
# G_b1 = np.random.normal(size=(128),scale=(1. / np.sqrt(128 / 2.))) *0.002
G_b4 = np.zeros(hidden_input4)
G_W5 = (
np.random.normal(
size=(hidden_input4, hidden_input5),
scale=(1.0 / np.sqrt(hidden_input4 / 2.0)),
)
* 0.002
)
# G_b1 = np.random.normal(size=(128),scale=(1. / np.sqrt(128 / 2.))) *0.002
G_b5 = np.zeros(hidden_input5)
G_W6 = (
np.random.normal(
size=(hidden_input5, hidden_input6),
scale=(1.0 / np.sqrt(hidden_input5 / 2.0)),
)
* 0.002
)
# G_b1 = np.random.normal(size=(128),scale=(1. / np.sqrt(128 / 2.))) *0.002
G_b6 = np.zeros(hidden_input6)
G_W7 = (
np.random.normal(
size=(hidden_input6, 784), scale=(1.0 / np.sqrt(hidden_input6 / 2.0))
)
* 0.002
)
# G_b2 = np.random.normal(size=(784),scale=(1. / np.sqrt(784 / 2.))) *0.002
G_b7 = np.zeros(784)
# 3. For Adam Optimzier
v1, m1 = 0, 0
v2, m2 = 0, 0
v3, m3 = 0, 0
v4, m4 = 0, 0
v5, m5 = 0, 0
v6, m6 = 0, 0
v7, m7 = 0, 0
v8, m8 = 0, 0
v9, m9 = 0, 0
v10, m10 = 0, 0
v11, m11 = 0, 0
v12, m12 = 0, 0
v13, m13 = 0, 0
v14, m14 = 0, 0
v15, m15 = 0, 0
v16, m16 = 0, 0
v17, m17 = 0, 0
v18, m18 = 0, 0
beta_1, beta_2, eps = 0.9, 0.999, 0.00000001
print("--------- Started Training ----------")
for iter in range(num_epoch):
random_int = np.random.randint(len(images) - 5)
current_image = np.expand_dims(images[random_int], axis=0)
# Func: Generate The first Fake Data
Z = np.random.uniform(-1.0, 1.0, size=[1, G_input])
Gl1 = Z.dot(G_W1) + G_b1
Gl1A = arctan(Gl1)
Gl2 = Gl1A.dot(G_W2) + G_b2
Gl2A = ReLu(Gl2)
Gl3 = Gl2A.dot(G_W3) + G_b3
Gl3A = arctan(Gl3)
Gl4 = Gl3A.dot(G_W4) + G_b4
Gl4A = ReLu(Gl4)
Gl5 = Gl4A.dot(G_W5) + G_b5
Gl5A = tanh(Gl5)
Gl6 = Gl5A.dot(G_W6) + G_b6
Gl6A = ReLu(Gl6)
Gl7 = Gl6A.dot(G_W7) + G_b7
current_fake_data = log(Gl7)
# Func: Forward Feed for Real data
Dl1_r = current_image.dot(D_W1) + D_b1
Dl1_rA = ReLu(Dl1_r)
Dl2_r = Dl1_rA.dot(D_W2) + D_b2
Dl2_rA = log(Dl2_r)
# Func: Forward Feed for Fake Data
Dl1_f = current_fake_data.dot(D_W1) + D_b1
Dl1_fA = ReLu(Dl1_f)
Dl2_f = Dl1_fA.dot(D_W2) + D_b2
Dl2_fA = log(Dl2_f)
# Func: Cost D
D_cost = -np.log(Dl2_rA) + np.log(1.0 - Dl2_fA)
# Func: Gradient
grad_f_w2_part_1 = 1 / (1.0 - Dl2_fA)
grad_f_w2_part_2 = d_log(Dl2_f)
grad_f_w2_part_3 = Dl1_fA
grad_f_w2 = grad_f_w2_part_3.T.dot(grad_f_w2_part_1 * grad_f_w2_part_2)
grad_f_b2 = grad_f_w2_part_1 * grad_f_w2_part_2
grad_f_w1_part_1 = (grad_f_w2_part_1 * grad_f_w2_part_2).dot(D_W2.T)
grad_f_w1_part_2 = d_ReLu(Dl1_f)
grad_f_w1_part_3 = current_fake_data
grad_f_w1 = grad_f_w1_part_3.T.dot(grad_f_w1_part_1 * grad_f_w1_part_2)
grad_f_b1 = grad_f_w1_part_1 * grad_f_w1_part_2
grad_r_w2_part_1 = -1 / Dl2_rA
grad_r_w2_part_2 = d_log(Dl2_r)
grad_r_w2_part_3 = Dl1_rA
grad_r_w2 = grad_r_w2_part_3.T.dot(grad_r_w2_part_1 * grad_r_w2_part_2)
grad_r_b2 = grad_r_w2_part_1 * grad_r_w2_part_2
grad_r_w1_part_1 = (grad_r_w2_part_1 * grad_r_w2_part_2).dot(D_W2.T)
grad_r_w1_part_2 = d_ReLu(Dl1_r)
grad_r_w1_part_3 = current_image
grad_r_w1 = grad_r_w1_part_3.T.dot(grad_r_w1_part_1 * grad_r_w1_part_2)
grad_r_b1 = grad_r_w1_part_1 * grad_r_w1_part_2
grad_w1 = grad_f_w1 + grad_r_w1
grad_b1 = grad_f_b1 + grad_r_b1
grad_w2 = grad_f_w2 + grad_r_w2
grad_b2 = grad_f_b2 + grad_r_b2
# ---- Update Gradient ----
m1 = beta_1 * m1 + (1 - beta_1) * grad_w1
v1 = beta_2 * v1 + (1 - beta_2) * grad_w1 ** 2
m2 = beta_1 * m2 + (1 - beta_1) * grad_b1
v2 = beta_2 * v2 + (1 - beta_2) * grad_b1 ** 2
m3 = beta_1 * m3 + (1 - beta_1) * grad_w2
v3 = beta_2 * v3 + (1 - beta_2) * grad_w2 ** 2
m4 = beta_1 * m4 + (1 - beta_1) * grad_b2
v4 = beta_2 * v4 + (1 - beta_2) * grad_b2 ** 2
D_W1 = D_W1 - (learing_rate / (np.sqrt(v1 / (1 - beta_2)) + eps)) * (
m1 / (1 - beta_1)
)
D_b1 = D_b1 - (learing_rate / (np.sqrt(v2 / (1 - beta_2)) + eps)) * (
m2 / (1 - beta_1)
)
D_W2 = D_W2 - (learing_rate / (np.sqrt(v3 / (1 - beta_2)) + eps)) * (
m3 / (1 - beta_1)
)
D_b2 = D_b2 - (learing_rate / (np.sqrt(v4 / (1 - beta_2)) + eps)) * (
m4 / (1 - beta_1)
)
# Func: Forward Feed for G
Z = np.random.uniform(-1.0, 1.0, size=[1, G_input])
Gl1 = Z.dot(G_W1) + G_b1
Gl1A = arctan(Gl1)
Gl2 = Gl1A.dot(G_W2) + G_b2
Gl2A = ReLu(Gl2)
Gl3 = Gl2A.dot(G_W3) + G_b3
Gl3A = arctan(Gl3)
Gl4 = Gl3A.dot(G_W4) + G_b4
Gl4A = ReLu(Gl4)
Gl5 = Gl4A.dot(G_W5) + G_b5
Gl5A = tanh(Gl5)
Gl6 = Gl5A.dot(G_W6) + G_b6
Gl6A = ReLu(Gl6)
Gl7 = Gl6A.dot(G_W7) + G_b7
current_fake_data = log(Gl7)
Dl1 = current_fake_data.dot(D_W1) + D_b1
Dl1_A = ReLu(Dl1)
Dl2 = Dl1_A.dot(D_W2) + D_b2
Dl2_A = log(Dl2)
# Func: Cost G
G_cost = -np.log(Dl2_A)
# Func: Gradient
grad_G_w7_part_1 = ((-1 / Dl2_A) * d_log(Dl2).dot(D_W2.T) * (d_ReLu(Dl1))).dot(
D_W1.T
)
grad_G_w7_part_2 = d_log(Gl7)
grad_G_w7_part_3 = Gl6A
grad_G_w7 = grad_G_w7_part_3.T.dot(grad_G_w7_part_1 * grad_G_w7_part_1)
grad_G_b7 = grad_G_w7_part_1 * grad_G_w7_part_2
grad_G_w6_part_1 = (grad_G_w7_part_1 * grad_G_w7_part_2).dot(G_W7.T)
grad_G_w6_part_2 = d_ReLu(Gl6)
grad_G_w6_part_3 = Gl5A
grad_G_w6 = grad_G_w6_part_3.T.dot(grad_G_w6_part_1 * grad_G_w6_part_2)
grad_G_b6 = grad_G_w6_part_1 * grad_G_w6_part_2
grad_G_w5_part_1 = (grad_G_w6_part_1 * grad_G_w6_part_2).dot(G_W6.T)
grad_G_w5_part_2 = d_tanh(Gl5)
grad_G_w5_part_3 = Gl4A
grad_G_w5 = grad_G_w5_part_3.T.dot(grad_G_w5_part_1 * grad_G_w5_part_2)
grad_G_b5 = grad_G_w5_part_1 * grad_G_w5_part_2
grad_G_w4_part_1 = (grad_G_w5_part_1 * grad_G_w5_part_2).dot(G_W5.T)
grad_G_w4_part_2 = d_ReLu(Gl4)
grad_G_w4_part_3 = Gl3A
grad_G_w4 = grad_G_w4_part_3.T.dot(grad_G_w4_part_1 * grad_G_w4_part_2)
grad_G_b4 = grad_G_w4_part_1 * grad_G_w4_part_2
grad_G_w3_part_1 = (grad_G_w4_part_1 * grad_G_w4_part_2).dot(G_W4.T)
grad_G_w3_part_2 = d_arctan(Gl3)
grad_G_w3_part_3 = Gl2A
grad_G_w3 = grad_G_w3_part_3.T.dot(grad_G_w3_part_1 * grad_G_w3_part_2)
grad_G_b3 = grad_G_w3_part_1 * grad_G_w3_part_2
grad_G_w2_part_1 = (grad_G_w3_part_1 * grad_G_w3_part_2).dot(G_W3.T)
grad_G_w2_part_2 = d_ReLu(Gl2)
grad_G_w2_part_3 = Gl1A
grad_G_w2 = grad_G_w2_part_3.T.dot(grad_G_w2_part_1 * grad_G_w2_part_2)
grad_G_b2 = grad_G_w2_part_1 * grad_G_w2_part_2
grad_G_w1_part_1 = (grad_G_w2_part_1 * grad_G_w2_part_2).dot(G_W2.T)
grad_G_w1_part_2 = d_arctan(Gl1)
grad_G_w1_part_3 = Z
grad_G_w1 = grad_G_w1_part_3.T.dot(grad_G_w1_part_1 * grad_G_w1_part_2)
grad_G_b1 = grad_G_w1_part_1 * grad_G_w1_part_2
# ---- Update Gradient ----
m5 = beta_1 * m5 + (1 - beta_1) * grad_G_w1
v5 = beta_2 * v5 + (1 - beta_2) * grad_G_w1 ** 2
m6 = beta_1 * m6 + (1 - beta_1) * grad_G_b1
v6 = beta_2 * v6 + (1 - beta_2) * grad_G_b1 ** 2
m7 = beta_1 * m7 + (1 - beta_1) * grad_G_w2
v7 = beta_2 * v7 + (1 - beta_2) * grad_G_w2 ** 2
m8 = beta_1 * m8 + (1 - beta_1) * grad_G_b2
v8 = beta_2 * v8 + (1 - beta_2) * grad_G_b2 ** 2
m9 = beta_1 * m9 + (1 - beta_1) * grad_G_w3
v9 = beta_2 * v9 + (1 - beta_2) * grad_G_w3 ** 2
m10 = beta_1 * m10 + (1 - beta_1) * grad_G_b3
v10 = beta_2 * v10 + (1 - beta_2) * grad_G_b3 ** 2
m11 = beta_1 * m11 + (1 - beta_1) * grad_G_w4
v11 = beta_2 * v11 + (1 - beta_2) * grad_G_w4 ** 2
m12 = beta_1 * m12 + (1 - beta_1) * grad_G_b4
v12 = beta_2 * v12 + (1 - beta_2) * grad_G_b4 ** 2
m13 = beta_1 * m13 + (1 - beta_1) * grad_G_w5
v13 = beta_2 * v13 + (1 - beta_2) * grad_G_w5 ** 2
m14 = beta_1 * m14 + (1 - beta_1) * grad_G_b5
v14 = beta_2 * v14 + (1 - beta_2) * grad_G_b5 ** 2
m15 = beta_1 * m15 + (1 - beta_1) * grad_G_w6
v15 = beta_2 * v15 + (1 - beta_2) * grad_G_w6 ** 2
m16 = beta_1 * m16 + (1 - beta_1) * grad_G_b6
v16 = beta_2 * v16 + (1 - beta_2) * grad_G_b6 ** 2
m17 = beta_1 * m17 + (1 - beta_1) * grad_G_w7
v17 = beta_2 * v17 + (1 - beta_2) * grad_G_w7 ** 2
m18 = beta_1 * m18 + (1 - beta_1) * grad_G_b7
v18 = beta_2 * v18 + (1 - beta_2) * grad_G_b7 ** 2
G_W1 = G_W1 - (learing_rate / (np.sqrt(v5 / (1 - beta_2)) + eps)) * (
m5 / (1 - beta_1)
)
G_b1 = G_b1 - (learing_rate / (np.sqrt(v6 / (1 - beta_2)) + eps)) * (
m6 / (1 - beta_1)
)
G_W2 = G_W2 - (learing_rate / (np.sqrt(v7 / (1 - beta_2)) + eps)) * (
m7 / (1 - beta_1)
)
G_b2 = G_b2 - (learing_rate / (np.sqrt(v8 / (1 - beta_2)) + eps)) * (
m8 / (1 - beta_1)
)
G_W3 = G_W3 - (learing_rate / (np.sqrt(v9 / (1 - beta_2)) + eps)) * (
m9 / (1 - beta_1)
)
G_b3 = G_b3 - (learing_rate / (np.sqrt(v10 / (1 - beta_2)) + eps)) * (
m10 / (1 - beta_1)
)
G_W4 = G_W4 - (learing_rate / (np.sqrt(v11 / (1 - beta_2)) + eps)) * (
m11 / (1 - beta_1)
)
G_b4 = G_b4 - (learing_rate / (np.sqrt(v12 / (1 - beta_2)) + eps)) * (
m12 / (1 - beta_1)
)
G_W5 = G_W5 - (learing_rate / (np.sqrt(v13 / (1 - beta_2)) + eps)) * (
m13 / (1 - beta_1)
)
G_b5 = G_b5 - (learing_rate / (np.sqrt(v14 / (1 - beta_2)) + eps)) * (
m14 / (1 - beta_1)
)
G_W6 = G_W6 - (learing_rate / (np.sqrt(v15 / (1 - beta_2)) + eps)) * (
m15 / (1 - beta_1)
)
G_b6 = G_b6 - (learing_rate / (np.sqrt(v16 / (1 - beta_2)) + eps)) * (
m16 / (1 - beta_1)
)
G_W7 = G_W7 - (learing_rate / (np.sqrt(v17 / (1 - beta_2)) + eps)) * (
m17 / (1 - beta_1)
)
G_b7 = G_b7 - (learing_rate / (np.sqrt(v18 / (1 - beta_2)) + eps)) * (
m18 / (1 - beta_1)
)
# --- Print Error ----
# print("Current Iter: ",iter, " Current D cost:",D_cost, " Current G cost: ", G_cost,end='\r')
if iter == 0:
learing_rate = learing_rate * 0.01
if iter == 40:
learing_rate = learing_rate * 0.01
# ---- Print to Out put ----
if iter % 10 == 0:
print(
"Current Iter: ",
iter,
" Current D cost:",
D_cost,
" Current G cost: ",
G_cost,
end="\r",
)
print("--------- Show Example Result See Tab Above ----------")
print("--------- Wait for the image to load ---------")
Z = np.random.uniform(-1.0, 1.0, size=[16, G_input])
Gl1 = Z.dot(G_W1) + G_b1
Gl1A = arctan(Gl1)
Gl2 = Gl1A.dot(G_W2) + G_b2
Gl2A = ReLu(Gl2)
Gl3 = Gl2A.dot(G_W3) + G_b3
Gl3A = arctan(Gl3)
Gl4 = Gl3A.dot(G_W4) + G_b4
Gl4A = ReLu(Gl4)
Gl5 = Gl4A.dot(G_W5) + G_b5
Gl5A = tanh(Gl5)
Gl6 = Gl5A.dot(G_W6) + G_b6
Gl6A = ReLu(Gl6)
Gl7 = Gl6A.dot(G_W7) + G_b7
current_fake_data = log(Gl7)
fig = plot(current_fake_data)
fig.savefig(
"Click_Me_{}.png".format(
str(iter).zfill(3)
+ "_Ginput_"
+ str(G_input)
+ "_hiddenone"
+ str(hidden_input)
+ "_hiddentwo"
+ str(hidden_input2)
+ "_LR_"
+ str(learing_rate)
),
bbox_inches="tight",
)
# for complete explanation visit https://towardsdatascience.com/only-numpy-implementing-gan-general-adversarial-networks-and-adam-optimizer-using-numpy-with-2a7e4e032021
# -- end code --
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """ A naive recursive implementation of 0-1 Knapsack Problem
https://en.wikipedia.org/wiki/Knapsack_problem
"""
from __future__ import annotations
def knapsack(capacity: int, weights: list[int], values: list[int], counter: int) -> int:
"""
Returns the maximum value that can be put in a knapsack of a capacity cap,
whereby each weight w has a specific value val.
>>> cap = 50
>>> val = [60, 100, 120]
>>> w = [10, 20, 30]
>>> c = len(val)
>>> knapsack(cap, w, val, c)
220
The result is 220 cause the values of 100 and 120 got the weight of 50
which is the limit of the capacity.
"""
# Base Case
if counter == 0 or capacity == 0:
return 0
# If weight of the nth item is more than Knapsack of capacity,
# then this item cannot be included in the optimal solution,
# else return the maximum of two cases:
# (1) nth item included
# (2) not included
if weights[counter - 1] > capacity:
return knapsack(capacity, weights, values, counter - 1)
else:
left_capacity = capacity - weights[counter - 1]
new_value_included = values[counter - 1] + knapsack(
left_capacity, weights, values, counter - 1
)
without_new_value = knapsack(capacity, weights, values, counter - 1)
return max(new_value_included, without_new_value)
if __name__ == "__main__":
import doctest
doctest.testmod()
| """ A naive recursive implementation of 0-1 Knapsack Problem
https://en.wikipedia.org/wiki/Knapsack_problem
"""
from __future__ import annotations
def knapsack(capacity: int, weights: list[int], values: list[int], counter: int) -> int:
"""
Returns the maximum value that can be put in a knapsack of a capacity cap,
whereby each weight w has a specific value val.
>>> cap = 50
>>> val = [60, 100, 120]
>>> w = [10, 20, 30]
>>> c = len(val)
>>> knapsack(cap, w, val, c)
220
The result is 220 cause the values of 100 and 120 got the weight of 50
which is the limit of the capacity.
"""
# Base Case
if counter == 0 or capacity == 0:
return 0
# If weight of the nth item is more than Knapsack of capacity,
# then this item cannot be included in the optimal solution,
# else return the maximum of two cases:
# (1) nth item included
# (2) not included
if weights[counter - 1] > capacity:
return knapsack(capacity, weights, values, counter - 1)
else:
left_capacity = capacity - weights[counter - 1]
new_value_included = values[counter - 1] + knapsack(
left_capacity, weights, values, counter - 1
)
without_new_value = knapsack(capacity, weights, values, counter - 1)
return max(new_value_included, without_new_value)
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| import re
def is_sri_lankan_phone_number(phone: str) -> bool:
"""
Determine whether the string is a valid sri lankan mobile phone number or not
References: https://aye.sh/blog/sri-lankan-phone-number-regex
>>> is_sri_lankan_phone_number("+94773283048")
True
>>> is_sri_lankan_phone_number("+9477-3283048")
True
>>> is_sri_lankan_phone_number("0718382399")
True
>>> is_sri_lankan_phone_number("0094702343221")
True
>>> is_sri_lankan_phone_number("075 3201568")
True
>>> is_sri_lankan_phone_number("07779209245")
False
>>> is_sri_lankan_phone_number("0957651234")
False
"""
pattern = re.compile(
r"^(?:0|94|\+94|0{2}94)" r"7(0|1|2|4|5|6|7|8)" r"(-| |)" r"\d{7}$"
)
return bool(re.search(pattern, phone))
if __name__ == "__main__":
phone = "0094702343221"
print(is_sri_lankan_phone_number(phone))
| import re
def is_sri_lankan_phone_number(phone: str) -> bool:
"""
Determine whether the string is a valid sri lankan mobile phone number or not
References: https://aye.sh/blog/sri-lankan-phone-number-regex
>>> is_sri_lankan_phone_number("+94773283048")
True
>>> is_sri_lankan_phone_number("+9477-3283048")
True
>>> is_sri_lankan_phone_number("0718382399")
True
>>> is_sri_lankan_phone_number("0094702343221")
True
>>> is_sri_lankan_phone_number("075 3201568")
True
>>> is_sri_lankan_phone_number("07779209245")
False
>>> is_sri_lankan_phone_number("0957651234")
False
"""
pattern = re.compile(
r"^(?:0|94|\+94|0{2}94)" r"7(0|1|2|4|5|6|7|8)" r"(-| |)" r"\d{7}$"
)
return bool(re.search(pattern, phone))
if __name__ == "__main__":
phone = "0094702343221"
print(is_sri_lankan_phone_number(phone))
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| def bin_to_decimal(bin_string: str) -> int:
"""
Convert a binary value to its decimal equivalent
>>> bin_to_decimal("101")
5
>>> bin_to_decimal(" 1010 ")
10
>>> bin_to_decimal("-11101")
-29
>>> bin_to_decimal("0")
0
>>> bin_to_decimal("a")
Traceback (most recent call last):
...
ValueError: Non-binary value was passed to the function
>>> bin_to_decimal("")
Traceback (most recent call last):
...
ValueError: Empty string was passed to the function
>>> bin_to_decimal("39")
Traceback (most recent call last):
...
ValueError: Non-binary value was passed to the function
"""
bin_string = str(bin_string).strip()
if not bin_string:
raise ValueError("Empty string was passed to the function")
is_negative = bin_string[0] == "-"
if is_negative:
bin_string = bin_string[1:]
if not all(char in "01" for char in bin_string):
raise ValueError("Non-binary value was passed to the function")
decimal_number = 0
for char in bin_string:
decimal_number = 2 * decimal_number + int(char)
return -decimal_number if is_negative else decimal_number
if __name__ == "__main__":
from doctest import testmod
testmod()
| def bin_to_decimal(bin_string: str) -> int:
"""
Convert a binary value to its decimal equivalent
>>> bin_to_decimal("101")
5
>>> bin_to_decimal(" 1010 ")
10
>>> bin_to_decimal("-11101")
-29
>>> bin_to_decimal("0")
0
>>> bin_to_decimal("a")
Traceback (most recent call last):
...
ValueError: Non-binary value was passed to the function
>>> bin_to_decimal("")
Traceback (most recent call last):
...
ValueError: Empty string was passed to the function
>>> bin_to_decimal("39")
Traceback (most recent call last):
...
ValueError: Non-binary value was passed to the function
"""
bin_string = str(bin_string).strip()
if not bin_string:
raise ValueError("Empty string was passed to the function")
is_negative = bin_string[0] == "-"
if is_negative:
bin_string = bin_string[1:]
if not all(char in "01" for char in bin_string):
raise ValueError("Non-binary value was passed to the function")
decimal_number = 0
for char in bin_string:
decimal_number = 2 * decimal_number + int(char)
return -decimal_number if is_negative else decimal_number
if __name__ == "__main__":
from doctest import testmod
testmod()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
python/black : True
"""
from __future__ import annotations
def prime_factors(n: int) -> list[int]:
"""
Returns prime factors of n as a list.
>>> prime_factors(0)
[]
>>> prime_factors(100)
[2, 2, 5, 5]
>>> prime_factors(2560)
[2, 2, 2, 2, 2, 2, 2, 2, 2, 5]
>>> prime_factors(10**-2)
[]
>>> prime_factors(0.02)
[]
>>> x = prime_factors(10**241) # doctest: +NORMALIZE_WHITESPACE
>>> x == [2]*241 + [5]*241
True
>>> prime_factors(10**-354)
[]
>>> prime_factors('hello')
Traceback (most recent call last):
...
TypeError: '<=' not supported between instances of 'int' and 'str'
>>> prime_factors([1,2,'hello'])
Traceback (most recent call last):
...
TypeError: '<=' not supported between instances of 'int' and 'list'
"""
i = 2
factors = []
while i * i <= n:
if n % i:
i += 1
else:
n //= i
factors.append(i)
if n > 1:
factors.append(n)
return factors
if __name__ == "__main__":
import doctest
doctest.testmod()
| """
python/black : True
"""
from __future__ import annotations
def prime_factors(n: int) -> list[int]:
"""
Returns prime factors of n as a list.
>>> prime_factors(0)
[]
>>> prime_factors(100)
[2, 2, 5, 5]
>>> prime_factors(2560)
[2, 2, 2, 2, 2, 2, 2, 2, 2, 5]
>>> prime_factors(10**-2)
[]
>>> prime_factors(0.02)
[]
>>> x = prime_factors(10**241) # doctest: +NORMALIZE_WHITESPACE
>>> x == [2]*241 + [5]*241
True
>>> prime_factors(10**-354)
[]
>>> prime_factors('hello')
Traceback (most recent call last):
...
TypeError: '<=' not supported between instances of 'int' and 'str'
>>> prime_factors([1,2,'hello'])
Traceback (most recent call last):
...
TypeError: '<=' not supported between instances of 'int' and 'list'
"""
i = 2
factors = []
while i * i <= n:
if n % i:
i += 1
else:
n //= i
factors.append(i)
if n > 1:
factors.append(n)
return factors
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # pack-refs with: peeled fully-peeled sorted
8668f5792dc673f085966f6f90c9c896081f22e9 refs/remotes/origin/Fewer-forward-propogations-to-speed-tests
c1fd8cb9e667ab59ca4446d0dcf216d1696a010c refs/remotes/origin/Python-3.12-on-Debian-bookworm
e093689124ab5f4a0938e4801abad0dbeb5bf881 refs/remotes/origin/cclauss-patch-1
04b896124ac5e76d5d5ed4ded91302557b1bc081 refs/remotes/origin/fix-maclaurin_series-on-Python3.12
672d0b39404444787f1ca3b5a3b6fd29a5a75447 refs/remotes/origin/fuzzy_operations.py-on-Python-3.12
9caf4784aada17dc75348f77cc8c356df503c0f3 refs/remotes/origin/master
01dc64a3a2f397872c759c4cb575ad2be5856d6a refs/remotes/origin/quantum_random.py.disabled
| # pack-refs with: peeled fully-peeled sorted
8668f5792dc673f085966f6f90c9c896081f22e9 refs/remotes/origin/Fewer-forward-propogations-to-speed-tests
c1fd8cb9e667ab59ca4446d0dcf216d1696a010c refs/remotes/origin/Python-3.12-on-Debian-bookworm
e093689124ab5f4a0938e4801abad0dbeb5bf881 refs/remotes/origin/cclauss-patch-1
04b896124ac5e76d5d5ed4ded91302557b1bc081 refs/remotes/origin/fix-maclaurin_series-on-Python3.12
672d0b39404444787f1ca3b5a3b6fd29a5a75447 refs/remotes/origin/fuzzy_operations.py-on-Python-3.12
9caf4784aada17dc75348f77cc8c356df503c0f3 refs/remotes/origin/master
01dc64a3a2f397872c759c4cb575ad2be5856d6a refs/remotes/origin/quantum_random.py.disabled
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # https://www.investopedia.com
from __future__ import annotations
def simple_interest(
principal: float, daily_interest_rate: float, days_between_payments: int
) -> float:
"""
>>> simple_interest(18000.0, 0.06, 3)
3240.0
>>> simple_interest(0.5, 0.06, 3)
0.09
>>> simple_interest(18000.0, 0.01, 10)
1800.0
>>> simple_interest(18000.0, 0.0, 3)
0.0
>>> simple_interest(5500.0, 0.01, 100)
5500.0
>>> simple_interest(10000.0, -0.06, 3)
Traceback (most recent call last):
...
ValueError: daily_interest_rate must be >= 0
>>> simple_interest(-10000.0, 0.06, 3)
Traceback (most recent call last):
...
ValueError: principal must be > 0
>>> simple_interest(5500.0, 0.01, -5)
Traceback (most recent call last):
...
ValueError: days_between_payments must be > 0
"""
if days_between_payments <= 0:
raise ValueError("days_between_payments must be > 0")
if daily_interest_rate < 0:
raise ValueError("daily_interest_rate must be >= 0")
if principal <= 0:
raise ValueError("principal must be > 0")
return principal * daily_interest_rate * days_between_payments
def compound_interest(
principal: float,
nominal_annual_interest_rate_percentage: float,
number_of_compounding_periods: int,
) -> float:
"""
>>> compound_interest(10000.0, 0.05, 3)
1576.2500000000014
>>> compound_interest(10000.0, 0.05, 1)
500.00000000000045
>>> compound_interest(0.5, 0.05, 3)
0.07881250000000006
>>> compound_interest(10000.0, 0.06, -4)
Traceback (most recent call last):
...
ValueError: number_of_compounding_periods must be > 0
>>> compound_interest(10000.0, -3.5, 3.0)
Traceback (most recent call last):
...
ValueError: nominal_annual_interest_rate_percentage must be >= 0
>>> compound_interest(-5500.0, 0.01, 5)
Traceback (most recent call last):
...
ValueError: principal must be > 0
"""
if number_of_compounding_periods <= 0:
raise ValueError("number_of_compounding_periods must be > 0")
if nominal_annual_interest_rate_percentage < 0:
raise ValueError("nominal_annual_interest_rate_percentage must be >= 0")
if principal <= 0:
raise ValueError("principal must be > 0")
return principal * (
(1 + nominal_annual_interest_rate_percentage) ** number_of_compounding_periods
- 1
)
if __name__ == "__main__":
import doctest
doctest.testmod()
| # https://www.investopedia.com
from __future__ import annotations
def simple_interest(
principal: float, daily_interest_rate: float, days_between_payments: int
) -> float:
"""
>>> simple_interest(18000.0, 0.06, 3)
3240.0
>>> simple_interest(0.5, 0.06, 3)
0.09
>>> simple_interest(18000.0, 0.01, 10)
1800.0
>>> simple_interest(18000.0, 0.0, 3)
0.0
>>> simple_interest(5500.0, 0.01, 100)
5500.0
>>> simple_interest(10000.0, -0.06, 3)
Traceback (most recent call last):
...
ValueError: daily_interest_rate must be >= 0
>>> simple_interest(-10000.0, 0.06, 3)
Traceback (most recent call last):
...
ValueError: principal must be > 0
>>> simple_interest(5500.0, 0.01, -5)
Traceback (most recent call last):
...
ValueError: days_between_payments must be > 0
"""
if days_between_payments <= 0:
raise ValueError("days_between_payments must be > 0")
if daily_interest_rate < 0:
raise ValueError("daily_interest_rate must be >= 0")
if principal <= 0:
raise ValueError("principal must be > 0")
return principal * daily_interest_rate * days_between_payments
def compound_interest(
principal: float,
nominal_annual_interest_rate_percentage: float,
number_of_compounding_periods: int,
) -> float:
"""
>>> compound_interest(10000.0, 0.05, 3)
1576.2500000000014
>>> compound_interest(10000.0, 0.05, 1)
500.00000000000045
>>> compound_interest(0.5, 0.05, 3)
0.07881250000000006
>>> compound_interest(10000.0, 0.06, -4)
Traceback (most recent call last):
...
ValueError: number_of_compounding_periods must be > 0
>>> compound_interest(10000.0, -3.5, 3.0)
Traceback (most recent call last):
...
ValueError: nominal_annual_interest_rate_percentage must be >= 0
>>> compound_interest(-5500.0, 0.01, 5)
Traceback (most recent call last):
...
ValueError: principal must be > 0
"""
if number_of_compounding_periods <= 0:
raise ValueError("number_of_compounding_periods must be > 0")
if nominal_annual_interest_rate_percentage < 0:
raise ValueError("nominal_annual_interest_rate_percentage must be >= 0")
if principal <= 0:
raise ValueError("principal must be > 0")
return principal * (
(1 + nominal_annual_interest_rate_percentage) ** number_of_compounding_periods
- 1
)
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
An Armstrong number is equal to the sum of its own digits each raised to the
power of the number of digits.
For example, 370 is an Armstrong number because 3*3*3 + 7*7*7 + 0*0*0 = 370.
Armstrong numbers are also called Narcissistic numbers and Pluperfect numbers.
On-Line Encyclopedia of Integer Sequences entry: https://oeis.org/A005188
"""
PASSING = (1, 153, 370, 371, 1634, 24678051, 115132219018763992565095597973971522401)
FAILING: tuple = (-153, -1, 0, 1.2, 200, "A", [], {}, None)
def armstrong_number(n: int) -> bool:
"""
Return True if n is an Armstrong number or False if it is not.
>>> all(armstrong_number(n) for n in PASSING)
True
>>> any(armstrong_number(n) for n in FAILING)
False
"""
if not isinstance(n, int) or n < 1:
return False
# Initialization of sum and number of digits.
total = 0
number_of_digits = 0
temp = n
# Calculation of digits of the number
while temp > 0:
number_of_digits += 1
temp //= 10
# Dividing number into separate digits and find Armstrong number
temp = n
while temp > 0:
rem = temp % 10
total += rem**number_of_digits
temp //= 10
return n == total
def pluperfect_number(n: int) -> bool:
"""Return True if n is a pluperfect number or False if it is not
>>> all(armstrong_number(n) for n in PASSING)
True
>>> any(armstrong_number(n) for n in FAILING)
False
"""
if not isinstance(n, int) or n < 1:
return False
# Init a "histogram" of the digits
digit_histogram = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
digit_total = 0
total = 0
temp = n
while temp > 0:
temp, rem = divmod(temp, 10)
digit_histogram[rem] += 1
digit_total += 1
for (cnt, i) in zip(digit_histogram, range(len(digit_histogram))):
total += cnt * i**digit_total
return n == total
def narcissistic_number(n: int) -> bool:
"""Return True if n is a narcissistic number or False if it is not.
>>> all(armstrong_number(n) for n in PASSING)
True
>>> any(armstrong_number(n) for n in FAILING)
False
"""
if not isinstance(n, int) or n < 1:
return False
expo = len(str(n)) # the power that all digits will be raised to
# check if sum of each digit multiplied expo times is equal to number
return n == sum(int(i) ** expo for i in str(n))
def main():
"""
Request that user input an integer and tell them if it is Armstrong number.
"""
num = int(input("Enter an integer to see if it is an Armstrong number: ").strip())
print(f"{num} is {'' if armstrong_number(num) else 'not '}an Armstrong number.")
print(f"{num} is {'' if narcissistic_number(num) else 'not '}an Armstrong number.")
print(f"{num} is {'' if pluperfect_number(num) else 'not '}an Armstrong number.")
if __name__ == "__main__":
import doctest
doctest.testmod()
main()
| """
An Armstrong number is equal to the sum of its own digits each raised to the
power of the number of digits.
For example, 370 is an Armstrong number because 3*3*3 + 7*7*7 + 0*0*0 = 370.
Armstrong numbers are also called Narcissistic numbers and Pluperfect numbers.
On-Line Encyclopedia of Integer Sequences entry: https://oeis.org/A005188
"""
PASSING = (1, 153, 370, 371, 1634, 24678051, 115132219018763992565095597973971522401)
FAILING: tuple = (-153, -1, 0, 1.2, 200, "A", [], {}, None)
def armstrong_number(n: int) -> bool:
"""
Return True if n is an Armstrong number or False if it is not.
>>> all(armstrong_number(n) for n in PASSING)
True
>>> any(armstrong_number(n) for n in FAILING)
False
"""
if not isinstance(n, int) or n < 1:
return False
# Initialization of sum and number of digits.
total = 0
number_of_digits = 0
temp = n
# Calculation of digits of the number
while temp > 0:
number_of_digits += 1
temp //= 10
# Dividing number into separate digits and find Armstrong number
temp = n
while temp > 0:
rem = temp % 10
total += rem**number_of_digits
temp //= 10
return n == total
def pluperfect_number(n: int) -> bool:
"""Return True if n is a pluperfect number or False if it is not
>>> all(armstrong_number(n) for n in PASSING)
True
>>> any(armstrong_number(n) for n in FAILING)
False
"""
if not isinstance(n, int) or n < 1:
return False
# Init a "histogram" of the digits
digit_histogram = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
digit_total = 0
total = 0
temp = n
while temp > 0:
temp, rem = divmod(temp, 10)
digit_histogram[rem] += 1
digit_total += 1
for (cnt, i) in zip(digit_histogram, range(len(digit_histogram))):
total += cnt * i**digit_total
return n == total
def narcissistic_number(n: int) -> bool:
"""Return True if n is a narcissistic number or False if it is not.
>>> all(armstrong_number(n) for n in PASSING)
True
>>> any(armstrong_number(n) for n in FAILING)
False
"""
if not isinstance(n, int) or n < 1:
return False
expo = len(str(n)) # the power that all digits will be raised to
# check if sum of each digit multiplied expo times is equal to number
return n == sum(int(i) ** expo for i in str(n))
def main():
"""
Request that user input an integer and tell them if it is Armstrong number.
"""
num = int(input("Enter an integer to see if it is an Armstrong number: ").strip())
print(f"{num} is {'' if armstrong_number(num) else 'not '}an Armstrong number.")
print(f"{num} is {'' if narcissistic_number(num) else 'not '}an Armstrong number.")
print(f"{num} is {'' if pluperfect_number(num) else 'not '}an Armstrong number.")
if __name__ == "__main__":
import doctest
doctest.testmod()
main()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
A perfect number is a number for which the sum of its proper divisors is exactly
equal to the number. For example, the sum of the proper divisors of 28 would be
1 + 2 + 4 + 7 + 14 = 28, which means that 28 is a perfect number.
A number n is called deficient if the sum of its proper divisors is less than n
and it is called abundant if this sum exceeds n.
As 12 is the smallest abundant number, 1 + 2 + 3 + 4 + 6 = 16, the smallest
number that can be written as the sum of two abundant numbers is 24. By
mathematical analysis, it can be shown that all integers greater than 28123
can be written as the sum of two abundant numbers. However, this upper limit
cannot be reduced any further by analysis even though it is known that the
greatest number that cannot be expressed as the sum of two abundant numbers
is less than this limit.
Find the sum of all the positive integers which cannot be written as the sum
of two abundant numbers.
"""
def solution(limit=28123):
"""
Finds the sum of all the positive integers which cannot be written as
the sum of two abundant numbers
as described by the statement above.
>>> solution()
4179871
"""
sum_divs = [1] * (limit + 1)
for i in range(2, int(limit**0.5) + 1):
sum_divs[i * i] += i
for k in range(i + 1, limit // i + 1):
sum_divs[k * i] += k + i
abundants = set()
res = 0
for n in range(1, limit + 1):
if sum_divs[n] > n:
abundants.add(n)
if not any((n - a in abundants) for a in abundants):
res += n
return res
if __name__ == "__main__":
print(solution())
| """
A perfect number is a number for which the sum of its proper divisors is exactly
equal to the number. For example, the sum of the proper divisors of 28 would be
1 + 2 + 4 + 7 + 14 = 28, which means that 28 is a perfect number.
A number n is called deficient if the sum of its proper divisors is less than n
and it is called abundant if this sum exceeds n.
As 12 is the smallest abundant number, 1 + 2 + 3 + 4 + 6 = 16, the smallest
number that can be written as the sum of two abundant numbers is 24. By
mathematical analysis, it can be shown that all integers greater than 28123
can be written as the sum of two abundant numbers. However, this upper limit
cannot be reduced any further by analysis even though it is known that the
greatest number that cannot be expressed as the sum of two abundant numbers
is less than this limit.
Find the sum of all the positive integers which cannot be written as the sum
of two abundant numbers.
"""
def solution(limit=28123):
"""
Finds the sum of all the positive integers which cannot be written as
the sum of two abundant numbers
as described by the statement above.
>>> solution()
4179871
"""
sum_divs = [1] * (limit + 1)
for i in range(2, int(limit**0.5) + 1):
sum_divs[i * i] += i
for k in range(i + 1, limit // i + 1):
sum_divs[k * i] += k + i
abundants = set()
res = 0
for n in range(1, limit + 1):
if sum_divs[n] > n:
abundants.add(n)
if not any((n - a in abundants) for a in abundants):
res += n
return res
if __name__ == "__main__":
print(solution())
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| #!/usr/local/bin/python3
"""
Problem Description: Given two binary tree, return the merged tree.
The rule for merging is that if two nodes overlap, then put the value sum of
both nodes to the new value of the merged node. Otherwise, the NOT null node
will be used as the node of new tree.
"""
from __future__ import annotations
class Node:
"""
A binary node has value variable and pointers to its left and right node.
"""
def __init__(self, value: int = 0) -> None:
self.value = value
self.left: Node | None = None
self.right: Node | None = None
def merge_two_binary_trees(tree1: Node | None, tree2: Node | None) -> Node | None:
"""
Returns root node of the merged tree.
>>> tree1 = Node(5)
>>> tree1.left = Node(6)
>>> tree1.right = Node(7)
>>> tree1.left.left = Node(2)
>>> tree2 = Node(4)
>>> tree2.left = Node(5)
>>> tree2.right = Node(8)
>>> tree2.left.right = Node(1)
>>> tree2.right.right = Node(4)
>>> merged_tree = merge_two_binary_trees(tree1, tree2)
>>> print_preorder(merged_tree)
9
11
2
1
15
4
"""
if tree1 is None:
return tree2
if tree2 is None:
return tree1
tree1.value = tree1.value + tree2.value
tree1.left = merge_two_binary_trees(tree1.left, tree2.left)
tree1.right = merge_two_binary_trees(tree1.right, tree2.right)
return tree1
def print_preorder(root: Node | None) -> None:
"""
Print pre-order traversal of the tree.
>>> root = Node(1)
>>> root.left = Node(2)
>>> root.right = Node(3)
>>> print_preorder(root)
1
2
3
>>> print_preorder(root.right)
3
"""
if root:
print(root.value)
print_preorder(root.left)
print_preorder(root.right)
if __name__ == "__main__":
tree1 = Node(1)
tree1.left = Node(2)
tree1.right = Node(3)
tree1.left.left = Node(4)
tree2 = Node(2)
tree2.left = Node(4)
tree2.right = Node(6)
tree2.left.right = Node(9)
tree2.right.right = Node(5)
print("Tree1 is: ")
print_preorder(tree1)
print("Tree2 is: ")
print_preorder(tree2)
merged_tree = merge_two_binary_trees(tree1, tree2)
print("Merged Tree is: ")
print_preorder(merged_tree)
| #!/usr/local/bin/python3
"""
Problem Description: Given two binary tree, return the merged tree.
The rule for merging is that if two nodes overlap, then put the value sum of
both nodes to the new value of the merged node. Otherwise, the NOT null node
will be used as the node of new tree.
"""
from __future__ import annotations
class Node:
"""
A binary node has value variable and pointers to its left and right node.
"""
def __init__(self, value: int = 0) -> None:
self.value = value
self.left: Node | None = None
self.right: Node | None = None
def merge_two_binary_trees(tree1: Node | None, tree2: Node | None) -> Node | None:
"""
Returns root node of the merged tree.
>>> tree1 = Node(5)
>>> tree1.left = Node(6)
>>> tree1.right = Node(7)
>>> tree1.left.left = Node(2)
>>> tree2 = Node(4)
>>> tree2.left = Node(5)
>>> tree2.right = Node(8)
>>> tree2.left.right = Node(1)
>>> tree2.right.right = Node(4)
>>> merged_tree = merge_two_binary_trees(tree1, tree2)
>>> print_preorder(merged_tree)
9
11
2
1
15
4
"""
if tree1 is None:
return tree2
if tree2 is None:
return tree1
tree1.value = tree1.value + tree2.value
tree1.left = merge_two_binary_trees(tree1.left, tree2.left)
tree1.right = merge_two_binary_trees(tree1.right, tree2.right)
return tree1
def print_preorder(root: Node | None) -> None:
"""
Print pre-order traversal of the tree.
>>> root = Node(1)
>>> root.left = Node(2)
>>> root.right = Node(3)
>>> print_preorder(root)
1
2
3
>>> print_preorder(root.right)
3
"""
if root:
print(root.value)
print_preorder(root.left)
print_preorder(root.right)
if __name__ == "__main__":
tree1 = Node(1)
tree1.left = Node(2)
tree1.right = Node(3)
tree1.left.left = Node(4)
tree2 = Node(2)
tree2.left = Node(4)
tree2.right = Node(6)
tree2.left.right = Node(9)
tree2.right.right = Node(5)
print("Tree1 is: ")
print_preorder(tree1)
print("Tree2 is: ")
print_preorder(tree2)
merged_tree = merge_two_binary_trees(tree1, tree2)
print("Merged Tree is: ")
print_preorder(merged_tree)
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| def exchange_sort(numbers: list[int]) -> list[int]:
"""
Uses exchange sort to sort a list of numbers.
Source: https://en.wikipedia.org/wiki/Sorting_algorithm#Exchange_sort
>>> exchange_sort([5, 4, 3, 2, 1])
[1, 2, 3, 4, 5]
>>> exchange_sort([-1, -2, -3])
[-3, -2, -1]
>>> exchange_sort([1, 2, 3, 4, 5])
[1, 2, 3, 4, 5]
>>> exchange_sort([0, 10, -2, 5, 3])
[-2, 0, 3, 5, 10]
>>> exchange_sort([])
[]
"""
numbers_length = len(numbers)
for i in range(numbers_length):
for j in range(i + 1, numbers_length):
if numbers[j] < numbers[i]:
numbers[i], numbers[j] = numbers[j], numbers[i]
return numbers
if __name__ == "__main__":
user_input = input("Enter numbers separated by a comma:\n").strip()
unsorted = [int(item) for item in user_input.split(",")]
print(exchange_sort(unsorted))
| def exchange_sort(numbers: list[int]) -> list[int]:
"""
Uses exchange sort to sort a list of numbers.
Source: https://en.wikipedia.org/wiki/Sorting_algorithm#Exchange_sort
>>> exchange_sort([5, 4, 3, 2, 1])
[1, 2, 3, 4, 5]
>>> exchange_sort([-1, -2, -3])
[-3, -2, -1]
>>> exchange_sort([1, 2, 3, 4, 5])
[1, 2, 3, 4, 5]
>>> exchange_sort([0, 10, -2, 5, 3])
[-2, 0, 3, 5, 10]
>>> exchange_sort([])
[]
"""
numbers_length = len(numbers)
for i in range(numbers_length):
for j in range(i + 1, numbers_length):
if numbers[j] < numbers[i]:
numbers[i], numbers[j] = numbers[j], numbers[i]
return numbers
if __name__ == "__main__":
user_input = input("Enter numbers separated by a comma:\n").strip()
unsorted = [int(item) for item in user_input.split(",")]
print(exchange_sort(unsorted))
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Heap's (iterative) algorithm returns the list of all permutations possible from a list.
It minimizes movement by generating each permutation from the previous one
by swapping only two elements.
More information:
https://en.wikipedia.org/wiki/Heap%27s_algorithm.
"""
def heaps(arr: list) -> list:
"""
Pure python implementation of the iterative Heap's algorithm,
returning all permutations of a list.
>>> heaps([])
[()]
>>> heaps([0])
[(0,)]
>>> heaps([-1, 1])
[(-1, 1), (1, -1)]
>>> heaps([1, 2, 3])
[(1, 2, 3), (2, 1, 3), (3, 1, 2), (1, 3, 2), (2, 3, 1), (3, 2, 1)]
>>> from itertools import permutations
>>> sorted(heaps([1,2,3])) == sorted(permutations([1,2,3]))
True
>>> all(sorted(heaps(x)) == sorted(permutations(x))
... for x in ([], [0], [-1, 1], [1, 2, 3]))
True
"""
if len(arr) <= 1:
return [tuple(arr)]
res = []
def generate(n: int, arr: list):
c = [0] * n
res.append(tuple(arr))
i = 0
while i < n:
if c[i] < i:
if i % 2 == 0:
arr[0], arr[i] = arr[i], arr[0]
else:
arr[c[i]], arr[i] = arr[i], arr[c[i]]
res.append(tuple(arr))
c[i] += 1
i = 0
else:
c[i] = 0
i += 1
generate(len(arr), arr)
return res
if __name__ == "__main__":
user_input = input("Enter numbers separated by a comma:\n").strip()
arr = [int(item) for item in user_input.split(",")]
print(heaps(arr))
| """
Heap's (iterative) algorithm returns the list of all permutations possible from a list.
It minimizes movement by generating each permutation from the previous one
by swapping only two elements.
More information:
https://en.wikipedia.org/wiki/Heap%27s_algorithm.
"""
def heaps(arr: list) -> list:
"""
Pure python implementation of the iterative Heap's algorithm,
returning all permutations of a list.
>>> heaps([])
[()]
>>> heaps([0])
[(0,)]
>>> heaps([-1, 1])
[(-1, 1), (1, -1)]
>>> heaps([1, 2, 3])
[(1, 2, 3), (2, 1, 3), (3, 1, 2), (1, 3, 2), (2, 3, 1), (3, 2, 1)]
>>> from itertools import permutations
>>> sorted(heaps([1,2,3])) == sorted(permutations([1,2,3]))
True
>>> all(sorted(heaps(x)) == sorted(permutations(x))
... for x in ([], [0], [-1, 1], [1, 2, 3]))
True
"""
if len(arr) <= 1:
return [tuple(arr)]
res = []
def generate(n: int, arr: list):
c = [0] * n
res.append(tuple(arr))
i = 0
while i < n:
if c[i] < i:
if i % 2 == 0:
arr[0], arr[i] = arr[i], arr[0]
else:
arr[c[i]], arr[i] = arr[i], arr[c[i]]
res.append(tuple(arr))
c[i] += 1
i = 0
else:
c[i] = 0
i += 1
generate(len(arr), arr)
return res
if __name__ == "__main__":
user_input = input("Enter numbers separated by a comma:\n").strip()
arr = [int(item) for item in user_input.split(",")]
print(heaps(arr))
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
A XOR Gate is a logic gate in boolean algebra which results to 1 (True) if only one of
the two inputs is 1, and 0 (False) if an even number of inputs are 1.
Following is the truth table of a XOR Gate:
------------------------------
| Input 1 | Input 2 | Output |
------------------------------
| 0 | 0 | 0 |
| 0 | 1 | 1 |
| 1 | 0 | 1 |
| 1 | 1 | 0 |
------------------------------
Refer - https://www.geeksforgeeks.org/logic-gates-in-python/
"""
def xor_gate(input_1: int, input_2: int) -> int:
"""
calculate xor of the input values
>>> xor_gate(0, 0)
0
>>> xor_gate(0, 1)
1
>>> xor_gate(1, 0)
1
>>> xor_gate(1, 1)
0
"""
return (input_1, input_2).count(0) % 2
def test_xor_gate() -> None:
"""
Tests the xor_gate function
"""
assert xor_gate(0, 0) == 0
assert xor_gate(0, 1) == 1
assert xor_gate(1, 0) == 1
assert xor_gate(1, 1) == 0
if __name__ == "__main__":
print(xor_gate(0, 0))
print(xor_gate(0, 1))
| """
A XOR Gate is a logic gate in boolean algebra which results to 1 (True) if only one of
the two inputs is 1, and 0 (False) if an even number of inputs are 1.
Following is the truth table of a XOR Gate:
------------------------------
| Input 1 | Input 2 | Output |
------------------------------
| 0 | 0 | 0 |
| 0 | 1 | 1 |
| 1 | 0 | 1 |
| 1 | 1 | 0 |
------------------------------
Refer - https://www.geeksforgeeks.org/logic-gates-in-python/
"""
def xor_gate(input_1: int, input_2: int) -> int:
"""
calculate xor of the input values
>>> xor_gate(0, 0)
0
>>> xor_gate(0, 1)
1
>>> xor_gate(1, 0)
1
>>> xor_gate(1, 1)
0
"""
return (input_1, input_2).count(0) % 2
def test_xor_gate() -> None:
"""
Tests the xor_gate function
"""
assert xor_gate(0, 0) == 0
assert xor_gate(0, 1) == 1
assert xor_gate(1, 0) == 1
assert xor_gate(1, 1) == 0
if __name__ == "__main__":
print(xor_gate(0, 0))
print(xor_gate(0, 1))
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Linked Lists consists of Nodes.
Nodes contain data and also may link to other nodes:
- Head Node: First node, the address of the
head node gives us access of the complete list
- Last node: points to null
"""
from __future__ import annotations
from typing import Any
class Node:
def __init__(self, item: Any, next: Any) -> None: # noqa: A002
self.item = item
self.next = next
class LinkedList:
def __init__(self) -> None:
self.head: Node | None = None
self.size = 0
def add(self, item: Any) -> None:
self.head = Node(item, self.head)
self.size += 1
def remove(self) -> Any:
# Switched 'self.is_empty()' to 'self.head is None'
# because mypy was considering the possibility that 'self.head'
# can be None in below else part and giving error
if self.head is None:
return None
else:
item = self.head.item
self.head = self.head.next
self.size -= 1
return item
def is_empty(self) -> bool:
return self.head is None
def __str__(self) -> str:
"""
>>> linked_list = LinkedList()
>>> linked_list.add(23)
>>> linked_list.add(14)
>>> linked_list.add(9)
>>> print(linked_list)
9 --> 14 --> 23
"""
if not self.is_empty:
return ""
else:
iterate = self.head
item_str = ""
item_list: list[str] = []
while iterate:
item_list.append(str(iterate.item))
iterate = iterate.next
item_str = " --> ".join(item_list)
return item_str
def __len__(self) -> int:
"""
>>> linked_list = LinkedList()
>>> len(linked_list)
0
>>> linked_list.add("a")
>>> len(linked_list)
1
>>> linked_list.add("b")
>>> len(linked_list)
2
>>> _ = linked_list.remove()
>>> len(linked_list)
1
>>> _ = linked_list.remove()
>>> len(linked_list)
0
"""
return self.size
| """
Linked Lists consists of Nodes.
Nodes contain data and also may link to other nodes:
- Head Node: First node, the address of the
head node gives us access of the complete list
- Last node: points to null
"""
from __future__ import annotations
from typing import Any
class Node:
def __init__(self, item: Any, next: Any) -> None: # noqa: A002
self.item = item
self.next = next
class LinkedList:
def __init__(self) -> None:
self.head: Node | None = None
self.size = 0
def add(self, item: Any) -> None:
self.head = Node(item, self.head)
self.size += 1
def remove(self) -> Any:
# Switched 'self.is_empty()' to 'self.head is None'
# because mypy was considering the possibility that 'self.head'
# can be None in below else part and giving error
if self.head is None:
return None
else:
item = self.head.item
self.head = self.head.next
self.size -= 1
return item
def is_empty(self) -> bool:
return self.head is None
def __str__(self) -> str:
"""
>>> linked_list = LinkedList()
>>> linked_list.add(23)
>>> linked_list.add(14)
>>> linked_list.add(9)
>>> print(linked_list)
9 --> 14 --> 23
"""
if not self.is_empty:
return ""
else:
iterate = self.head
item_str = ""
item_list: list[str] = []
while iterate:
item_list.append(str(iterate.item))
iterate = iterate.next
item_str = " --> ".join(item_list)
return item_str
def __len__(self) -> int:
"""
>>> linked_list = LinkedList()
>>> len(linked_list)
0
>>> linked_list.add("a")
>>> len(linked_list)
1
>>> linked_list.add("b")
>>> len(linked_list)
2
>>> _ = linked_list.remove()
>>> len(linked_list)
1
>>> _ = linked_list.remove()
>>> len(linked_list)
0
"""
return self.size
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # Backtracking
Backtracking is a way to speed up the search process by removing candidates when they can't be the solution of a problem.
* <https://en.wikipedia.org/wiki/Backtracking>
* <https://en.wikipedia.org/wiki/Decision_tree_pruning>
* <https://medium.com/@priyankmistry1999/backtracking-sudoku-6e4439e4825c>
* <https://www.geeksforgeeks.org/sudoku-backtracking-7/>
| # Backtracking
Backtracking is a way to speed up the search process by removing candidates when they can't be the solution of a problem.
* <https://en.wikipedia.org/wiki/Backtracking>
* <https://en.wikipedia.org/wiki/Decision_tree_pruning>
* <https://medium.com/@priyankmistry1999/backtracking-sudoku-6e4439e4825c>
* <https://www.geeksforgeeks.org/sudoku-backtracking-7/>
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
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TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
developed by: markmelnic
original repo: https://github.com/markmelnic/Scoring-Algorithm
Analyse data using a range based percentual proximity algorithm
and calculate the linear maximum likelihood estimation.
The basic principle is that all values supplied will be broken
down to a range from 0 to 1 and each column's score will be added
up to get the total score.
==========
Example for data of vehicles
price|mileage|registration_year
20k |60k |2012
22k |50k |2011
23k |90k |2015
16k |210k |2010
We want the vehicle with the lowest price,
lowest mileage but newest registration year.
Thus the weights for each column are as follows:
[0, 0, 1]
"""
def procentual_proximity(
source_data: list[list[float]], weights: list[int]
) -> list[list[float]]:
"""
weights - int list
possible values - 0 / 1
0 if lower values have higher weight in the data set
1 if higher values have higher weight in the data set
>>> procentual_proximity([[20, 60, 2012],[23, 90, 2015],[22, 50, 2011]], [0, 0, 1])
[[20, 60, 2012, 2.0], [23, 90, 2015, 1.0], [22, 50, 2011, 1.3333333333333335]]
"""
# getting data
data_lists: list[list[float]] = []
for data in source_data:
for i, el in enumerate(data):
if len(data_lists) < i + 1:
data_lists.append([])
data_lists[i].append(float(el))
score_lists: list[list[float]] = []
# calculating each score
for dlist, weight in zip(data_lists, weights):
mind = min(dlist)
maxd = max(dlist)
score: list[float] = []
# for weight 0 score is 1 - actual score
if weight == 0:
for item in dlist:
try:
score.append(1 - ((item - mind) / (maxd - mind)))
except ZeroDivisionError:
score.append(1)
elif weight == 1:
for item in dlist:
try:
score.append((item - mind) / (maxd - mind))
except ZeroDivisionError:
score.append(0)
# weight not 0 or 1
else:
raise ValueError(f"Invalid weight of {weight:f} provided")
score_lists.append(score)
# initialize final scores
final_scores: list[float] = [0 for i in range(len(score_lists[0]))]
# generate final scores
for slist in score_lists:
for j, ele in enumerate(slist):
final_scores[j] = final_scores[j] + ele
# append scores to source data
for i, ele in enumerate(final_scores):
source_data[i].append(ele)
return source_data
| """
developed by: markmelnic
original repo: https://github.com/markmelnic/Scoring-Algorithm
Analyse data using a range based percentual proximity algorithm
and calculate the linear maximum likelihood estimation.
The basic principle is that all values supplied will be broken
down to a range from 0 to 1 and each column's score will be added
up to get the total score.
==========
Example for data of vehicles
price|mileage|registration_year
20k |60k |2012
22k |50k |2011
23k |90k |2015
16k |210k |2010
We want the vehicle with the lowest price,
lowest mileage but newest registration year.
Thus the weights for each column are as follows:
[0, 0, 1]
"""
def procentual_proximity(
source_data: list[list[float]], weights: list[int]
) -> list[list[float]]:
"""
weights - int list
possible values - 0 / 1
0 if lower values have higher weight in the data set
1 if higher values have higher weight in the data set
>>> procentual_proximity([[20, 60, 2012],[23, 90, 2015],[22, 50, 2011]], [0, 0, 1])
[[20, 60, 2012, 2.0], [23, 90, 2015, 1.0], [22, 50, 2011, 1.3333333333333335]]
"""
# getting data
data_lists: list[list[float]] = []
for data in source_data:
for i, el in enumerate(data):
if len(data_lists) < i + 1:
data_lists.append([])
data_lists[i].append(float(el))
score_lists: list[list[float]] = []
# calculating each score
for dlist, weight in zip(data_lists, weights):
mind = min(dlist)
maxd = max(dlist)
score: list[float] = []
# for weight 0 score is 1 - actual score
if weight == 0:
for item in dlist:
try:
score.append(1 - ((item - mind) / (maxd - mind)))
except ZeroDivisionError:
score.append(1)
elif weight == 1:
for item in dlist:
try:
score.append((item - mind) / (maxd - mind))
except ZeroDivisionError:
score.append(0)
# weight not 0 or 1
else:
raise ValueError(f"Invalid weight of {weight:f} provided")
score_lists.append(score)
# initialize final scores
final_scores: list[float] = [0 for i in range(len(score_lists[0]))]
# generate final scores
for slist in score_lists:
for j, ele in enumerate(slist):
final_scores[j] = final_scores[j] + ele
# append scores to source data
for i, ele in enumerate(final_scores):
source_data[i].append(ele)
return source_data
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Modular Exponential.
Modular exponentiation is a type of exponentiation performed over a modulus.
For more explanation, please check
https://en.wikipedia.org/wiki/Modular_exponentiation
"""
"""Calculate Modular Exponential."""
def modular_exponential(base: int, power: int, mod: int):
"""
>>> modular_exponential(5, 0, 10)
1
>>> modular_exponential(2, 8, 7)
4
>>> modular_exponential(3, -2, 9)
-1
"""
if power < 0:
return -1
base %= mod
result = 1
while power > 0:
if power & 1:
result = (result * base) % mod
power = power >> 1
base = (base * base) % mod
return result
def main():
"""Call Modular Exponential Function."""
print(modular_exponential(3, 200, 13))
if __name__ == "__main__":
import doctest
doctest.testmod()
main()
| """
Modular Exponential.
Modular exponentiation is a type of exponentiation performed over a modulus.
For more explanation, please check
https://en.wikipedia.org/wiki/Modular_exponentiation
"""
"""Calculate Modular Exponential."""
def modular_exponential(base: int, power: int, mod: int):
"""
>>> modular_exponential(5, 0, 10)
1
>>> modular_exponential(2, 8, 7)
4
>>> modular_exponential(3, -2, 9)
-1
"""
if power < 0:
return -1
base %= mod
result = 1
while power > 0:
if power & 1:
result = (result * base) % mod
power = power >> 1
base = (base * base) % mod
return result
def main():
"""Call Modular Exponential Function."""
print(modular_exponential(3, 200, 13))
if __name__ == "__main__":
import doctest
doctest.testmod()
main()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Functions useful for doing molecular chemistry:
* molarity_to_normality
* moles_to_pressure
* moles_to_volume
* pressure_and_volume_to_temperature
"""
def molarity_to_normality(nfactor: int, moles: float, volume: float) -> float:
"""
Convert molarity to normality.
Volume is taken in litres.
Wikipedia reference: https://en.wikipedia.org/wiki/Equivalent_concentration
Wikipedia reference: https://en.wikipedia.org/wiki/Molar_concentration
>>> molarity_to_normality(2, 3.1, 0.31)
20
>>> molarity_to_normality(4, 11.4, 5.7)
8
"""
return round(float(moles / volume) * nfactor)
def moles_to_pressure(volume: float, moles: float, temperature: float) -> float:
"""
Convert moles to pressure.
Ideal gas laws are used.
Temperature is taken in kelvin.
Volume is taken in litres.
Pressure has atm as SI unit.
Wikipedia reference: https://en.wikipedia.org/wiki/Gas_laws
Wikipedia reference: https://en.wikipedia.org/wiki/Pressure
Wikipedia reference: https://en.wikipedia.org/wiki/Temperature
>>> moles_to_pressure(0.82, 3, 300)
90
>>> moles_to_pressure(8.2, 5, 200)
10
"""
return round(float((moles * 0.0821 * temperature) / (volume)))
def moles_to_volume(pressure: float, moles: float, temperature: float) -> float:
"""
Convert moles to volume.
Ideal gas laws are used.
Temperature is taken in kelvin.
Volume is taken in litres.
Pressure has atm as SI unit.
Wikipedia reference: https://en.wikipedia.org/wiki/Gas_laws
Wikipedia reference: https://en.wikipedia.org/wiki/Pressure
Wikipedia reference: https://en.wikipedia.org/wiki/Temperature
>>> moles_to_volume(0.82, 3, 300)
90
>>> moles_to_volume(8.2, 5, 200)
10
"""
return round(float((moles * 0.0821 * temperature) / (pressure)))
def pressure_and_volume_to_temperature(
pressure: float, moles: float, volume: float
) -> float:
"""
Convert pressure and volume to temperature.
Ideal gas laws are used.
Temperature is taken in kelvin.
Volume is taken in litres.
Pressure has atm as SI unit.
Wikipedia reference: https://en.wikipedia.org/wiki/Gas_laws
Wikipedia reference: https://en.wikipedia.org/wiki/Pressure
Wikipedia reference: https://en.wikipedia.org/wiki/Temperature
>>> pressure_and_volume_to_temperature(0.82, 1, 2)
20
>>> pressure_and_volume_to_temperature(8.2, 5, 3)
60
"""
return round(float((pressure * volume) / (0.0821 * moles)))
if __name__ == "__main__":
import doctest
doctest.testmod()
| """
Functions useful for doing molecular chemistry:
* molarity_to_normality
* moles_to_pressure
* moles_to_volume
* pressure_and_volume_to_temperature
"""
def molarity_to_normality(nfactor: int, moles: float, volume: float) -> float:
"""
Convert molarity to normality.
Volume is taken in litres.
Wikipedia reference: https://en.wikipedia.org/wiki/Equivalent_concentration
Wikipedia reference: https://en.wikipedia.org/wiki/Molar_concentration
>>> molarity_to_normality(2, 3.1, 0.31)
20
>>> molarity_to_normality(4, 11.4, 5.7)
8
"""
return round(float(moles / volume) * nfactor)
def moles_to_pressure(volume: float, moles: float, temperature: float) -> float:
"""
Convert moles to pressure.
Ideal gas laws are used.
Temperature is taken in kelvin.
Volume is taken in litres.
Pressure has atm as SI unit.
Wikipedia reference: https://en.wikipedia.org/wiki/Gas_laws
Wikipedia reference: https://en.wikipedia.org/wiki/Pressure
Wikipedia reference: https://en.wikipedia.org/wiki/Temperature
>>> moles_to_pressure(0.82, 3, 300)
90
>>> moles_to_pressure(8.2, 5, 200)
10
"""
return round(float((moles * 0.0821 * temperature) / (volume)))
def moles_to_volume(pressure: float, moles: float, temperature: float) -> float:
"""
Convert moles to volume.
Ideal gas laws are used.
Temperature is taken in kelvin.
Volume is taken in litres.
Pressure has atm as SI unit.
Wikipedia reference: https://en.wikipedia.org/wiki/Gas_laws
Wikipedia reference: https://en.wikipedia.org/wiki/Pressure
Wikipedia reference: https://en.wikipedia.org/wiki/Temperature
>>> moles_to_volume(0.82, 3, 300)
90
>>> moles_to_volume(8.2, 5, 200)
10
"""
return round(float((moles * 0.0821 * temperature) / (pressure)))
def pressure_and_volume_to_temperature(
pressure: float, moles: float, volume: float
) -> float:
"""
Convert pressure and volume to temperature.
Ideal gas laws are used.
Temperature is taken in kelvin.
Volume is taken in litres.
Pressure has atm as SI unit.
Wikipedia reference: https://en.wikipedia.org/wiki/Gas_laws
Wikipedia reference: https://en.wikipedia.org/wiki/Pressure
Wikipedia reference: https://en.wikipedia.org/wiki/Temperature
>>> pressure_and_volume_to_temperature(0.82, 1, 2)
20
>>> pressure_and_volume_to_temperature(8.2, 5, 3)
60
"""
return round(float((pressure * volume) / (0.0821 * moles)))
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sol1 import PokerHand
SORTED_HANDS = (
"4S 3H 2C 7S 5H",
"9D 8H 2C 6S 7H",
"2D 6D 9D TH 7D",
"TC 8C 2S JH 6C",
"JH 8S TH AH QH",
"TS KS 5S 9S AC",
"KD 6S 9D TH AD",
"KS 8D 4D 9S 4S", # pair
"8C 4S KH JS 4D", # pair
"QH 8H KD JH 8S", # pair
"KC 4H KS 2H 8D", # pair
"KD 4S KC 3H 8S", # pair
"AH 8S AS KC JH", # pair
"3H 4C 4H 3S 2H", # 2 pairs
"5S 5D 2C KH KH", # 2 pairs
"3C KH 5D 5S KH", # 2 pairs
"AS 3C KH AD KH", # 2 pairs
"7C 7S 3S 7H 5S", # 3 of a kind
"7C 7S KH 2H 7H", # 3 of a kind
"AC KH QH AH AS", # 3 of a kind
"2H 4D 3C AS 5S", # straight (low ace)
"3C 5C 4C 2C 6H", # straight
"6S 8S 7S 5H 9H", # straight
"JS QS 9H TS KH", # straight
"QC KH TS JS AH", # straight (high ace)
"8C 9C 5C 3C TC", # flush
"3S 8S 9S 5S KS", # flush
"4C 5C 9C 8C KC", # flush
"JH 8H AH KH QH", # flush
"3D 2H 3H 2C 2D", # full house
"2H 2C 3S 3H 3D", # full house
"KH KC 3S 3H 3D", # full house
"JC 6H JS JD JH", # 4 of a kind
"JC 7H JS JD JH", # 4 of a kind
"JC KH JS JD JH", # 4 of a kind
"2S AS 4S 5S 3S", # straight flush (low ace)
"2D 6D 3D 4D 5D", # straight flush
"5C 6C 3C 7C 4C", # straight flush
"JH 9H TH KH QH", # straight flush
"JH AH TH KH QH", # royal flush (high ace straight flush)
)
TEST_COMPARE = (
("2H 3H 4H 5H 6H", "KS AS TS QS JS", "Loss"),
("2H 3H 4H 5H 6H", "AS AD AC AH JD", "Win"),
("AS AH 2H AD AC", "JS JD JC JH 3D", "Win"),
("2S AH 2H AS AC", "JS JD JC JH AD", "Loss"),
("2S AH 2H AS AC", "2H 3H 5H 6H 7H", "Win"),
("AS 3S 4S 8S 2S", "2H 3H 5H 6H 7H", "Win"),
("2H 3H 5H 6H 7H", "2S 3H 4H 5S 6C", "Win"),
("2S 3H 4H 5S 6C", "3D 4C 5H 6H 2S", "Tie"),
("2S 3H 4H 5S 6C", "AH AC 5H 6H AS", "Win"),
("2S 2H 4H 5S 4C", "AH AC 5H 6H AS", "Loss"),
("2S 2H 4H 5S 4C", "AH AC 5H 6H 7S", "Win"),
("6S AD 7H 4S AS", "AH AC 5H 6H 7S", "Loss"),
("2S AH 4H 5S KC", "AH AC 5H 6H 7S", "Loss"),
("2S 3H 6H 7S 9C", "7H 3C TH 6H 9S", "Loss"),
("4S 5H 6H TS AC", "3S 5H 6H TS AC", "Win"),
("2S AH 4H 5S 6C", "AD 4C 5H 6H 2C", "Tie"),
("AS AH 3H AD AC", "AS AH 2H AD AC", "Win"),
("AH AC 5H 5C QS", "AH AC 5H 5C KS", "Loss"),
("AH AC 5H 5C QS", "KH KC 5H 5C QS", "Win"),
("7C 7S KH 2H 7H", "3C 3S AH 2H 3H", "Win"),
("3C 3S AH 2H 3H", "7C 7S KH 2H 7H", "Loss"),
("6H 5H 4H 3H 2H", "5H 4H 3H 2H AH", "Win"),
("5H 4H 3H 2H AH", "5H 4H 3H 2H AH", "Tie"),
("5H 4H 3H 2H AH", "6H 5H 4H 3H 2H", "Loss"),
("AH AD KS KC AC", "AH KD KH AC KC", "Win"),
("2H 4D 3C AS 5S", "2H 4D 3C 6S 5S", "Loss"),
("2H 3S 3C 3H 2S", "3S 3C 2S 2H 2D", "Win"),
("4D 6D 5D 2D JH", "3S 8S 3H TC KH", "Loss"),
("4S 6C 8S 3S 7S", "AD KS 2D 7D 7C", "Loss"),
("6S 4C 7H 8C 3H", "5H JC AH 9D 9C", "Loss"),
("9D 9H JH TC QH", "3C 2S JS 5C 7H", "Win"),
("2H TC 8S AD 9S", "4H TS 7H 2C 5C", "Win"),
("9D 3S 2C 7S 7C", "JC TD 3C TC 9H", "Loss"),
)
TEST_FLUSH = (
("2H 3H 4H 5H 6H", True),
("AS AH 2H AD AC", False),
("2H 3H 5H 6H 7H", True),
("KS AS TS QS JS", True),
("8H 9H QS JS TH", False),
("AS 3S 4S 8S 2S", True),
)
TEST_STRAIGHT = (
("2H 3H 4H 5H 6H", True),
("AS AH 2H AD AC", False),
("2H 3H 5H 6H 7H", False),
("KS AS TS QS JS", True),
("8H 9H QS JS TH", True),
)
TEST_FIVE_HIGH_STRAIGHT = (
("2H 4D 3C AS 5S", True, [5, 4, 3, 2, 14]),
("2H 5D 3C AS 5S", False, [14, 5, 5, 3, 2]),
("JH QD KC AS TS", False, [14, 13, 12, 11, 10]),
("9D 3S 2C 7S 7C", False, [9, 7, 7, 3, 2]),
)
TEST_KIND = (
("JH AH TH KH QH", 0),
("JH 9H TH KH QH", 0),
("JC KH JS JD JH", 7),
("KH KC 3S 3H 3D", 6),
("8C 9C 5C 3C TC", 0),
("JS QS 9H TS KH", 0),
("7C 7S KH 2H 7H", 3),
("3C KH 5D 5S KH", 2),
("QH 8H KD JH 8S", 1),
("2D 6D 9D TH 7D", 0),
)
TEST_TYPES = (
("JH AH TH KH QH", 23),
("JH 9H TH KH QH", 22),
("JC KH JS JD JH", 21),
("KH KC 3S 3H 3D", 20),
("8C 9C 5C 3C TC", 19),
("JS QS 9H TS KH", 18),
("7C 7S KH 2H 7H", 17),
("3C KH 5D 5S KH", 16),
("QH 8H KD JH 8S", 15),
("2D 6D 9D TH 7D", 14),
)
def generate_random_hand():
play, oppo = randrange(len(SORTED_HANDS)), randrange(len(SORTED_HANDS))
expected = ["Loss", "Tie", "Win"][(play >= oppo) + (play > oppo)]
hand, other = SORTED_HANDS[play], SORTED_HANDS[oppo]
return hand, other, expected
def generate_random_hands(number_of_hands: int = 100):
return (generate_random_hand() for _ in range(number_of_hands))
@pytest.mark.parametrize("hand, expected", TEST_FLUSH)
def test_hand_is_flush(hand, expected):
assert PokerHand(hand)._is_flush() == expected
@pytest.mark.parametrize("hand, expected", TEST_STRAIGHT)
def test_hand_is_straight(hand, expected):
assert PokerHand(hand)._is_straight() == expected
@pytest.mark.parametrize("hand, expected, card_values", TEST_FIVE_HIGH_STRAIGHT)
def test_hand_is_five_high_straight(hand, expected, card_values):
player = PokerHand(hand)
assert player._is_five_high_straight() == expected
assert player._card_values == card_values
@pytest.mark.parametrize("hand, expected", TEST_KIND)
def test_hand_is_same_kind(hand, expected):
assert PokerHand(hand)._is_same_kind() == expected
@pytest.mark.parametrize("hand, expected", TEST_TYPES)
def test_hand_values(hand, expected):
assert PokerHand(hand)._hand_type == expected
@pytest.mark.parametrize("hand, other, expected", TEST_COMPARE)
def test_compare_simple(hand, other, expected):
assert PokerHand(hand).compare_with(PokerHand(other)) == expected
@pytest.mark.parametrize("hand, other, expected", generate_random_hands())
def test_compare_random(hand, other, expected):
assert PokerHand(hand).compare_with(PokerHand(other)) == expected
def test_hand_sorted():
poker_hands = [PokerHand(hand) for hand in SORTED_HANDS]
list_copy = poker_hands.copy()
shuffle(list_copy)
user_sorted = chain(sorted(list_copy))
for index, hand in enumerate(user_sorted):
assert hand == poker_hands[index]
def test_custom_sort_five_high_straight():
# Test that five high straights are compared correctly.
pokerhands = [PokerHand("2D AC 3H 4H 5S"), PokerHand("2S 3H 4H 5S 6C")]
pokerhands.sort(reverse=True)
assert pokerhands[0].__str__() == "2S 3H 4H 5S 6C"
def test_multiple_calls_five_high_straight():
# Multiple calls to five_high_straight function should still return True
# and shouldn't mutate the list in every call other than the first.
pokerhand = PokerHand("2C 4S AS 3D 5C")
expected = True
expected_card_values = [5, 4, 3, 2, 14]
for _ in range(10):
assert pokerhand._is_five_high_straight() == expected
assert pokerhand._card_values == expected_card_values
def test_euler_project():
# Problem number 54 from Project Euler
# Testing from poker_hands.txt file
answer = 0
script_dir = os.path.abspath(os.path.dirname(__file__))
poker_hands = os.path.join(script_dir, "poker_hands.txt")
with open(poker_hands) as file_hand:
for line in file_hand:
player_hand = line[:14].strip()
opponent_hand = line[15:].strip()
player, opponent = PokerHand(player_hand), PokerHand(opponent_hand)
output = player.compare_with(opponent)
if output == "Win":
answer += 1
assert answer == 376
| import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sol1 import PokerHand
SORTED_HANDS = (
"4S 3H 2C 7S 5H",
"9D 8H 2C 6S 7H",
"2D 6D 9D TH 7D",
"TC 8C 2S JH 6C",
"JH 8S TH AH QH",
"TS KS 5S 9S AC",
"KD 6S 9D TH AD",
"KS 8D 4D 9S 4S", # pair
"8C 4S KH JS 4D", # pair
"QH 8H KD JH 8S", # pair
"KC 4H KS 2H 8D", # pair
"KD 4S KC 3H 8S", # pair
"AH 8S AS KC JH", # pair
"3H 4C 4H 3S 2H", # 2 pairs
"5S 5D 2C KH KH", # 2 pairs
"3C KH 5D 5S KH", # 2 pairs
"AS 3C KH AD KH", # 2 pairs
"7C 7S 3S 7H 5S", # 3 of a kind
"7C 7S KH 2H 7H", # 3 of a kind
"AC KH QH AH AS", # 3 of a kind
"2H 4D 3C AS 5S", # straight (low ace)
"3C 5C 4C 2C 6H", # straight
"6S 8S 7S 5H 9H", # straight
"JS QS 9H TS KH", # straight
"QC KH TS JS AH", # straight (high ace)
"8C 9C 5C 3C TC", # flush
"3S 8S 9S 5S KS", # flush
"4C 5C 9C 8C KC", # flush
"JH 8H AH KH QH", # flush
"3D 2H 3H 2C 2D", # full house
"2H 2C 3S 3H 3D", # full house
"KH KC 3S 3H 3D", # full house
"JC 6H JS JD JH", # 4 of a kind
"JC 7H JS JD JH", # 4 of a kind
"JC KH JS JD JH", # 4 of a kind
"2S AS 4S 5S 3S", # straight flush (low ace)
"2D 6D 3D 4D 5D", # straight flush
"5C 6C 3C 7C 4C", # straight flush
"JH 9H TH KH QH", # straight flush
"JH AH TH KH QH", # royal flush (high ace straight flush)
)
TEST_COMPARE = (
("2H 3H 4H 5H 6H", "KS AS TS QS JS", "Loss"),
("2H 3H 4H 5H 6H", "AS AD AC AH JD", "Win"),
("AS AH 2H AD AC", "JS JD JC JH 3D", "Win"),
("2S AH 2H AS AC", "JS JD JC JH AD", "Loss"),
("2S AH 2H AS AC", "2H 3H 5H 6H 7H", "Win"),
("AS 3S 4S 8S 2S", "2H 3H 5H 6H 7H", "Win"),
("2H 3H 5H 6H 7H", "2S 3H 4H 5S 6C", "Win"),
("2S 3H 4H 5S 6C", "3D 4C 5H 6H 2S", "Tie"),
("2S 3H 4H 5S 6C", "AH AC 5H 6H AS", "Win"),
("2S 2H 4H 5S 4C", "AH AC 5H 6H AS", "Loss"),
("2S 2H 4H 5S 4C", "AH AC 5H 6H 7S", "Win"),
("6S AD 7H 4S AS", "AH AC 5H 6H 7S", "Loss"),
("2S AH 4H 5S KC", "AH AC 5H 6H 7S", "Loss"),
("2S 3H 6H 7S 9C", "7H 3C TH 6H 9S", "Loss"),
("4S 5H 6H TS AC", "3S 5H 6H TS AC", "Win"),
("2S AH 4H 5S 6C", "AD 4C 5H 6H 2C", "Tie"),
("AS AH 3H AD AC", "AS AH 2H AD AC", "Win"),
("AH AC 5H 5C QS", "AH AC 5H 5C KS", "Loss"),
("AH AC 5H 5C QS", "KH KC 5H 5C QS", "Win"),
("7C 7S KH 2H 7H", "3C 3S AH 2H 3H", "Win"),
("3C 3S AH 2H 3H", "7C 7S KH 2H 7H", "Loss"),
("6H 5H 4H 3H 2H", "5H 4H 3H 2H AH", "Win"),
("5H 4H 3H 2H AH", "5H 4H 3H 2H AH", "Tie"),
("5H 4H 3H 2H AH", "6H 5H 4H 3H 2H", "Loss"),
("AH AD KS KC AC", "AH KD KH AC KC", "Win"),
("2H 4D 3C AS 5S", "2H 4D 3C 6S 5S", "Loss"),
("2H 3S 3C 3H 2S", "3S 3C 2S 2H 2D", "Win"),
("4D 6D 5D 2D JH", "3S 8S 3H TC KH", "Loss"),
("4S 6C 8S 3S 7S", "AD KS 2D 7D 7C", "Loss"),
("6S 4C 7H 8C 3H", "5H JC AH 9D 9C", "Loss"),
("9D 9H JH TC QH", "3C 2S JS 5C 7H", "Win"),
("2H TC 8S AD 9S", "4H TS 7H 2C 5C", "Win"),
("9D 3S 2C 7S 7C", "JC TD 3C TC 9H", "Loss"),
)
TEST_FLUSH = (
("2H 3H 4H 5H 6H", True),
("AS AH 2H AD AC", False),
("2H 3H 5H 6H 7H", True),
("KS AS TS QS JS", True),
("8H 9H QS JS TH", False),
("AS 3S 4S 8S 2S", True),
)
TEST_STRAIGHT = (
("2H 3H 4H 5H 6H", True),
("AS AH 2H AD AC", False),
("2H 3H 5H 6H 7H", False),
("KS AS TS QS JS", True),
("8H 9H QS JS TH", True),
)
TEST_FIVE_HIGH_STRAIGHT = (
("2H 4D 3C AS 5S", True, [5, 4, 3, 2, 14]),
("2H 5D 3C AS 5S", False, [14, 5, 5, 3, 2]),
("JH QD KC AS TS", False, [14, 13, 12, 11, 10]),
("9D 3S 2C 7S 7C", False, [9, 7, 7, 3, 2]),
)
TEST_KIND = (
("JH AH TH KH QH", 0),
("JH 9H TH KH QH", 0),
("JC KH JS JD JH", 7),
("KH KC 3S 3H 3D", 6),
("8C 9C 5C 3C TC", 0),
("JS QS 9H TS KH", 0),
("7C 7S KH 2H 7H", 3),
("3C KH 5D 5S KH", 2),
("QH 8H KD JH 8S", 1),
("2D 6D 9D TH 7D", 0),
)
TEST_TYPES = (
("JH AH TH KH QH", 23),
("JH 9H TH KH QH", 22),
("JC KH JS JD JH", 21),
("KH KC 3S 3H 3D", 20),
("8C 9C 5C 3C TC", 19),
("JS QS 9H TS KH", 18),
("7C 7S KH 2H 7H", 17),
("3C KH 5D 5S KH", 16),
("QH 8H KD JH 8S", 15),
("2D 6D 9D TH 7D", 14),
)
def generate_random_hand():
play, oppo = randrange(len(SORTED_HANDS)), randrange(len(SORTED_HANDS))
expected = ["Loss", "Tie", "Win"][(play >= oppo) + (play > oppo)]
hand, other = SORTED_HANDS[play], SORTED_HANDS[oppo]
return hand, other, expected
def generate_random_hands(number_of_hands: int = 100):
return (generate_random_hand() for _ in range(number_of_hands))
@pytest.mark.parametrize("hand, expected", TEST_FLUSH)
def test_hand_is_flush(hand, expected):
assert PokerHand(hand)._is_flush() == expected
@pytest.mark.parametrize("hand, expected", TEST_STRAIGHT)
def test_hand_is_straight(hand, expected):
assert PokerHand(hand)._is_straight() == expected
@pytest.mark.parametrize("hand, expected, card_values", TEST_FIVE_HIGH_STRAIGHT)
def test_hand_is_five_high_straight(hand, expected, card_values):
player = PokerHand(hand)
assert player._is_five_high_straight() == expected
assert player._card_values == card_values
@pytest.mark.parametrize("hand, expected", TEST_KIND)
def test_hand_is_same_kind(hand, expected):
assert PokerHand(hand)._is_same_kind() == expected
@pytest.mark.parametrize("hand, expected", TEST_TYPES)
def test_hand_values(hand, expected):
assert PokerHand(hand)._hand_type == expected
@pytest.mark.parametrize("hand, other, expected", TEST_COMPARE)
def test_compare_simple(hand, other, expected):
assert PokerHand(hand).compare_with(PokerHand(other)) == expected
@pytest.mark.parametrize("hand, other, expected", generate_random_hands())
def test_compare_random(hand, other, expected):
assert PokerHand(hand).compare_with(PokerHand(other)) == expected
def test_hand_sorted():
poker_hands = [PokerHand(hand) for hand in SORTED_HANDS]
list_copy = poker_hands.copy()
shuffle(list_copy)
user_sorted = chain(sorted(list_copy))
for index, hand in enumerate(user_sorted):
assert hand == poker_hands[index]
def test_custom_sort_five_high_straight():
# Test that five high straights are compared correctly.
pokerhands = [PokerHand("2D AC 3H 4H 5S"), PokerHand("2S 3H 4H 5S 6C")]
pokerhands.sort(reverse=True)
assert pokerhands[0].__str__() == "2S 3H 4H 5S 6C"
def test_multiple_calls_five_high_straight():
# Multiple calls to five_high_straight function should still return True
# and shouldn't mutate the list in every call other than the first.
pokerhand = PokerHand("2C 4S AS 3D 5C")
expected = True
expected_card_values = [5, 4, 3, 2, 14]
for _ in range(10):
assert pokerhand._is_five_high_straight() == expected
assert pokerhand._card_values == expected_card_values
def test_euler_project():
# Problem number 54 from Project Euler
# Testing from poker_hands.txt file
answer = 0
script_dir = os.path.abspath(os.path.dirname(__file__))
poker_hands = os.path.join(script_dir, "poker_hands.txt")
with open(poker_hands) as file_hand:
for line in file_hand:
player_hand = line[:14].strip()
opponent_hand = line[15:].strip()
player, opponent = PokerHand(player_hand), PokerHand(opponent_hand)
output = player.compare_with(opponent)
if output == "Win":
answer += 1
assert answer == 376
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| from typing import Literal
LETTERS = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
def translate_message(
key: str, message: str, mode: Literal["encrypt", "decrypt"]
) -> str:
"""
>>> translate_message("QWERTYUIOPASDFGHJKLZXCVBNM","Hello World","encrypt")
'Pcssi Bidsm'
"""
chars_a = LETTERS if mode == "decrypt" else key
chars_b = key if mode == "decrypt" else LETTERS
translated = ""
# loop through each symbol in the message
for symbol in message:
if symbol.upper() in chars_a:
# encrypt/decrypt the symbol
sym_index = chars_a.find(symbol.upper())
if symbol.isupper():
translated += chars_b[sym_index].upper()
else:
translated += chars_b[sym_index].lower()
else:
# symbol is not in LETTERS, just add it
translated += symbol
return translated
def encrypt_message(key: str, message: str) -> str:
"""
>>> encrypt_message("QWERTYUIOPASDFGHJKLZXCVBNM", "Hello World")
'Pcssi Bidsm'
"""
return translate_message(key, message, "encrypt")
def decrypt_message(key: str, message: str) -> str:
"""
>>> decrypt_message("QWERTYUIOPASDFGHJKLZXCVBNM", "Hello World")
'Itssg Vgksr'
"""
return translate_message(key, message, "decrypt")
def main() -> None:
message = "Hello World"
key = "QWERTYUIOPASDFGHJKLZXCVBNM"
mode = "decrypt" # set to 'encrypt' or 'decrypt'
if mode == "encrypt":
translated = encrypt_message(key, message)
elif mode == "decrypt":
translated = decrypt_message(key, message)
print(f"Using the key {key}, the {mode}ed message is: {translated}")
if __name__ == "__main__":
import doctest
doctest.testmod()
main()
| from typing import Literal
LETTERS = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
def translate_message(
key: str, message: str, mode: Literal["encrypt", "decrypt"]
) -> str:
"""
>>> translate_message("QWERTYUIOPASDFGHJKLZXCVBNM","Hello World","encrypt")
'Pcssi Bidsm'
"""
chars_a = LETTERS if mode == "decrypt" else key
chars_b = key if mode == "decrypt" else LETTERS
translated = ""
# loop through each symbol in the message
for symbol in message:
if symbol.upper() in chars_a:
# encrypt/decrypt the symbol
sym_index = chars_a.find(symbol.upper())
if symbol.isupper():
translated += chars_b[sym_index].upper()
else:
translated += chars_b[sym_index].lower()
else:
# symbol is not in LETTERS, just add it
translated += symbol
return translated
def encrypt_message(key: str, message: str) -> str:
"""
>>> encrypt_message("QWERTYUIOPASDFGHJKLZXCVBNM", "Hello World")
'Pcssi Bidsm'
"""
return translate_message(key, message, "encrypt")
def decrypt_message(key: str, message: str) -> str:
"""
>>> decrypt_message("QWERTYUIOPASDFGHJKLZXCVBNM", "Hello World")
'Itssg Vgksr'
"""
return translate_message(key, message, "decrypt")
def main() -> None:
message = "Hello World"
key = "QWERTYUIOPASDFGHJKLZXCVBNM"
mode = "decrypt" # set to 'encrypt' or 'decrypt'
if mode == "encrypt":
translated = encrypt_message(key, message)
elif mode == "decrypt":
translated = decrypt_message(key, message)
print(f"Using the key {key}, the {mode}ed message is: {translated}")
if __name__ == "__main__":
import doctest
doctest.testmod()
main()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| from __future__ import annotations
END = "#"
class Trie:
def __init__(self) -> None:
self._trie: dict = {}
def insert_word(self, text: str) -> None:
trie = self._trie
for char in text:
if char not in trie:
trie[char] = {}
trie = trie[char]
trie[END] = True
def find_word(self, prefix: str) -> tuple | list:
trie = self._trie
for char in prefix:
if char in trie:
trie = trie[char]
else:
return []
return self._elements(trie)
def _elements(self, d: dict) -> tuple:
result = []
for c, v in d.items():
if c == END:
sub_result = [" "]
else:
sub_result = [c + s for s in self._elements(v)]
result.extend(sub_result)
return tuple(result)
trie = Trie()
words = ("depart", "detergent", "daring", "dog", "deer", "deal")
for word in words:
trie.insert_word(word)
def autocomplete_using_trie(string: str) -> tuple:
"""
>>> trie = Trie()
>>> for word in words:
... trie.insert_word(word)
...
>>> matches = autocomplete_using_trie("de")
>>> "detergent " in matches
True
>>> "dog " in matches
False
"""
suffixes = trie.find_word(string)
return tuple(string + word for word in suffixes)
def main() -> None:
print(autocomplete_using_trie("de"))
if __name__ == "__main__":
import doctest
doctest.testmod()
main()
| from __future__ import annotations
END = "#"
class Trie:
def __init__(self) -> None:
self._trie: dict = {}
def insert_word(self, text: str) -> None:
trie = self._trie
for char in text:
if char not in trie:
trie[char] = {}
trie = trie[char]
trie[END] = True
def find_word(self, prefix: str) -> tuple | list:
trie = self._trie
for char in prefix:
if char in trie:
trie = trie[char]
else:
return []
return self._elements(trie)
def _elements(self, d: dict) -> tuple:
result = []
for c, v in d.items():
if c == END:
sub_result = [" "]
else:
sub_result = [c + s for s in self._elements(v)]
result.extend(sub_result)
return tuple(result)
trie = Trie()
words = ("depart", "detergent", "daring", "dog", "deer", "deal")
for word in words:
trie.insert_word(word)
def autocomplete_using_trie(string: str) -> tuple:
"""
>>> trie = Trie()
>>> for word in words:
... trie.insert_word(word)
...
>>> matches = autocomplete_using_trie("de")
>>> "detergent " in matches
True
>>> "dog " in matches
False
"""
suffixes = trie.find_word(string)
return tuple(string + word for word in suffixes)
def main() -> None:
print(autocomplete_using_trie("de"))
if __name__ == "__main__":
import doctest
doctest.testmod()
main()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| #!/usr/bin/env python3
"""
module to operations with prime numbers
"""
import math
def is_prime(number: int) -> bool:
"""Checks to see if a number is a prime in O(sqrt(n)).
A number is prime if it has exactly two factors: 1 and itself.
>>> is_prime(0)
False
>>> is_prime(1)
False
>>> is_prime(2)
True
>>> is_prime(3)
True
>>> is_prime(27)
False
>>> is_prime(87)
False
>>> is_prime(563)
True
>>> is_prime(2999)
True
>>> is_prime(67483)
False
"""
# precondition
assert isinstance(number, int) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or not number % 2:
# Negatives, 0, 1 and all even numbers are not primes
return False
odd_numbers = range(3, int(math.sqrt(number) + 1), 2)
return not any(not number % i for i in odd_numbers)
def next_prime(value, factor=1, **kwargs):
value = factor * value
first_value_val = value
while not is_prime(value):
value += 1 if not ("desc" in kwargs.keys() and kwargs["desc"] is True) else -1
if value == first_value_val:
return next_prime(value + 1, **kwargs)
return value
| #!/usr/bin/env python3
"""
module to operations with prime numbers
"""
import math
def is_prime(number: int) -> bool:
"""Checks to see if a number is a prime in O(sqrt(n)).
A number is prime if it has exactly two factors: 1 and itself.
>>> is_prime(0)
False
>>> is_prime(1)
False
>>> is_prime(2)
True
>>> is_prime(3)
True
>>> is_prime(27)
False
>>> is_prime(87)
False
>>> is_prime(563)
True
>>> is_prime(2999)
True
>>> is_prime(67483)
False
"""
# precondition
assert isinstance(number, int) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or not number % 2:
# Negatives, 0, 1 and all even numbers are not primes
return False
odd_numbers = range(3, int(math.sqrt(number) + 1), 2)
return not any(not number % i for i in odd_numbers)
def next_prime(value, factor=1, **kwargs):
value = factor * value
first_value_val = value
while not is_prime(value):
value += 1 if not ("desc" in kwargs.keys() and kwargs["desc"] is True) else -1
if value == first_value_val:
return next_prime(value + 1, **kwargs)
return value
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| from string import ascii_lowercase, ascii_uppercase
def capitalize(sentence: str) -> str:
"""
This function will capitalize the first letter of a sentence or a word
>>> capitalize("hello world")
'Hello world'
>>> capitalize("123 hello world")
'123 hello world'
>>> capitalize(" hello world")
' hello world'
>>> capitalize("a")
'A'
>>> capitalize("")
''
"""
if not sentence:
return ""
lower_to_upper = {lc: uc for lc, uc in zip(ascii_lowercase, ascii_uppercase)}
return lower_to_upper.get(sentence[0], sentence[0]) + sentence[1:]
if __name__ == "__main__":
from doctest import testmod
testmod()
| from string import ascii_lowercase, ascii_uppercase
def capitalize(sentence: str) -> str:
"""
This function will capitalize the first letter of a sentence or a word
>>> capitalize("hello world")
'Hello world'
>>> capitalize("123 hello world")
'123 hello world'
>>> capitalize(" hello world")
' hello world'
>>> capitalize("a")
'A'
>>> capitalize("")
''
"""
if not sentence:
return ""
lower_to_upper = {lc: uc for lc, uc in zip(ascii_lowercase, ascii_uppercase)}
return lower_to_upper.get(sentence[0], sentence[0]) + sentence[1:]
if __name__ == "__main__":
from doctest import testmod
testmod()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Test cases:
Do you want to enter your denominations ? (Y/N) :N
Enter the change you want to make in Indian Currency: 987
Following is minimal change for 987 :
500 100 100 100 100 50 20 10 5 2
Do you want to enter your denominations ? (Y/N) :Y
Enter number of denomination:10
1
5
10
20
50
100
200
500
1000
2000
Enter the change you want to make: 18745
Following is minimal change for 18745 :
2000 2000 2000 2000 2000 2000 2000 2000 2000 500 200 20 20 5
Do you want to enter your denominations ? (Y/N) :N
Enter the change you want to make: 0
The total value cannot be zero or negative.
Do you want to enter your denominations ? (Y/N) :N
Enter the change you want to make: -98
The total value cannot be zero or negative.
Do you want to enter your denominations ? (Y/N) :Y
Enter number of denomination:5
1
5
100
500
1000
Enter the change you want to make: 456
Following is minimal change for 456 :
100 100 100 100 5 5 5 5 5 5 5 5 5 5 5 1
"""
def find_minimum_change(denominations: list[int], value: str) -> list[int]:
"""
Find the minimum change from the given denominations and value
>>> find_minimum_change([1, 5, 10, 20, 50, 100, 200, 500, 1000,2000], 18745)
[2000, 2000, 2000, 2000, 2000, 2000, 2000, 2000, 2000, 500, 200, 20, 20, 5]
>>> find_minimum_change([1, 2, 5, 10, 20, 50, 100, 500, 2000], 987)
[500, 100, 100, 100, 100, 50, 20, 10, 5, 2]
>>> find_minimum_change([1, 2, 5, 10, 20, 50, 100, 500, 2000], 0)
[]
>>> find_minimum_change([1, 2, 5, 10, 20, 50, 100, 500, 2000], -98)
[]
>>> find_minimum_change([1, 5, 100, 500, 1000], 456)
[100, 100, 100, 100, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 1]
"""
total_value = int(value)
# Initialize Result
answer = []
# Traverse through all denomination
for denomination in reversed(denominations):
# Find denominations
while int(total_value) >= int(denomination):
total_value -= int(denomination)
answer.append(denomination) # Append the "answers" array
return answer
# Driver Code
if __name__ == "__main__":
denominations = []
value = "0"
if (
input("Do you want to enter your denominations ? (yY/n): ").strip().lower()
== "y"
):
n = int(input("Enter the number of denominations you want to add: ").strip())
for i in range(0, n):
denominations.append(int(input(f"Denomination {i}: ").strip()))
value = input("Enter the change you want to make in Indian Currency: ").strip()
else:
# All denominations of Indian Currency if user does not enter
denominations = [1, 2, 5, 10, 20, 50, 100, 500, 2000]
value = input("Enter the change you want to make: ").strip()
if int(value) == 0 or int(value) < 0:
print("The total value cannot be zero or negative.")
else:
print(f"Following is minimal change for {value}: ")
answer = find_minimum_change(denominations, value)
# Print result
for i in range(len(answer)):
print(answer[i], end=" ")
| """
Test cases:
Do you want to enter your denominations ? (Y/N) :N
Enter the change you want to make in Indian Currency: 987
Following is minimal change for 987 :
500 100 100 100 100 50 20 10 5 2
Do you want to enter your denominations ? (Y/N) :Y
Enter number of denomination:10
1
5
10
20
50
100
200
500
1000
2000
Enter the change you want to make: 18745
Following is minimal change for 18745 :
2000 2000 2000 2000 2000 2000 2000 2000 2000 500 200 20 20 5
Do you want to enter your denominations ? (Y/N) :N
Enter the change you want to make: 0
The total value cannot be zero or negative.
Do you want to enter your denominations ? (Y/N) :N
Enter the change you want to make: -98
The total value cannot be zero or negative.
Do you want to enter your denominations ? (Y/N) :Y
Enter number of denomination:5
1
5
100
500
1000
Enter the change you want to make: 456
Following is minimal change for 456 :
100 100 100 100 5 5 5 5 5 5 5 5 5 5 5 1
"""
def find_minimum_change(denominations: list[int], value: str) -> list[int]:
"""
Find the minimum change from the given denominations and value
>>> find_minimum_change([1, 5, 10, 20, 50, 100, 200, 500, 1000,2000], 18745)
[2000, 2000, 2000, 2000, 2000, 2000, 2000, 2000, 2000, 500, 200, 20, 20, 5]
>>> find_minimum_change([1, 2, 5, 10, 20, 50, 100, 500, 2000], 987)
[500, 100, 100, 100, 100, 50, 20, 10, 5, 2]
>>> find_minimum_change([1, 2, 5, 10, 20, 50, 100, 500, 2000], 0)
[]
>>> find_minimum_change([1, 2, 5, 10, 20, 50, 100, 500, 2000], -98)
[]
>>> find_minimum_change([1, 5, 100, 500, 1000], 456)
[100, 100, 100, 100, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 1]
"""
total_value = int(value)
# Initialize Result
answer = []
# Traverse through all denomination
for denomination in reversed(denominations):
# Find denominations
while int(total_value) >= int(denomination):
total_value -= int(denomination)
answer.append(denomination) # Append the "answers" array
return answer
# Driver Code
if __name__ == "__main__":
denominations = []
value = "0"
if (
input("Do you want to enter your denominations ? (yY/n): ").strip().lower()
== "y"
):
n = int(input("Enter the number of denominations you want to add: ").strip())
for i in range(0, n):
denominations.append(int(input(f"Denomination {i}: ").strip()))
value = input("Enter the change you want to make in Indian Currency: ").strip()
else:
# All denominations of Indian Currency if user does not enter
denominations = [1, 2, 5, 10, 20, 50, 100, 500, 2000]
value = input("Enter the change you want to make: ").strip()
if int(value) == 0 or int(value) < 0:
print("The total value cannot be zero or negative.")
else:
print(f"Following is minimal change for {value}: ")
answer = find_minimum_change(denominations, value)
# Print result
for i in range(len(answer)):
print(answer[i], end=" ")
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # Boolean Algebra
Boolean algebra is used to do arithmetic with bits of values True (1) or False (0).
There are three basic operations: 'and', 'or' and 'not'.
* <https://en.wikipedia.org/wiki/Boolean_algebra>
* <https://plato.stanford.edu/entries/boolalg-math/>
| # Boolean Algebra
Boolean algebra is used to do arithmetic with bits of values True (1) or False (0).
There are three basic operations: 'and', 'or' and 'not'.
* <https://en.wikipedia.org/wiki/Boolean_algebra>
* <https://plato.stanford.edu/entries/boolalg-math/>
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Convert International System of Units (SI) and Binary prefixes
"""
from __future__ import annotations
from enum import Enum
class SIUnit(Enum):
yotta = 24
zetta = 21
exa = 18
peta = 15
tera = 12
giga = 9
mega = 6
kilo = 3
hecto = 2
deca = 1
deci = -1
centi = -2
milli = -3
micro = -6
nano = -9
pico = -12
femto = -15
atto = -18
zepto = -21
yocto = -24
class BinaryUnit(Enum):
yotta = 8
zetta = 7
exa = 6
peta = 5
tera = 4
giga = 3
mega = 2
kilo = 1
def convert_si_prefix(
known_amount: float,
known_prefix: str | SIUnit,
unknown_prefix: str | SIUnit,
) -> float:
"""
Wikipedia reference: https://en.wikipedia.org/wiki/Binary_prefix
Wikipedia reference: https://en.wikipedia.org/wiki/International_System_of_Units
>>> convert_si_prefix(1, SIUnit.giga, SIUnit.mega)
1000
>>> convert_si_prefix(1, SIUnit.mega, SIUnit.giga)
0.001
>>> convert_si_prefix(1, SIUnit.kilo, SIUnit.kilo)
1
>>> convert_si_prefix(1, 'giga', 'mega')
1000
>>> convert_si_prefix(1, 'gIGa', 'mEGa')
1000
"""
if isinstance(known_prefix, str):
known_prefix = SIUnit[known_prefix.lower()]
if isinstance(unknown_prefix, str):
unknown_prefix = SIUnit[unknown_prefix.lower()]
unknown_amount: float = known_amount * (
10 ** (known_prefix.value - unknown_prefix.value)
)
return unknown_amount
def convert_binary_prefix(
known_amount: float,
known_prefix: str | BinaryUnit,
unknown_prefix: str | BinaryUnit,
) -> float:
"""
Wikipedia reference: https://en.wikipedia.org/wiki/Metric_prefix
>>> convert_binary_prefix(1, BinaryUnit.giga, BinaryUnit.mega)
1024
>>> convert_binary_prefix(1, BinaryUnit.mega, BinaryUnit.giga)
0.0009765625
>>> convert_binary_prefix(1, BinaryUnit.kilo, BinaryUnit.kilo)
1
>>> convert_binary_prefix(1, 'giga', 'mega')
1024
>>> convert_binary_prefix(1, 'gIGa', 'mEGa')
1024
"""
if isinstance(known_prefix, str):
known_prefix = BinaryUnit[known_prefix.lower()]
if isinstance(unknown_prefix, str):
unknown_prefix = BinaryUnit[unknown_prefix.lower()]
unknown_amount: float = known_amount * (
2 ** ((known_prefix.value - unknown_prefix.value) * 10)
)
return unknown_amount
if __name__ == "__main__":
import doctest
doctest.testmod()
| """
Convert International System of Units (SI) and Binary prefixes
"""
from __future__ import annotations
from enum import Enum
class SIUnit(Enum):
yotta = 24
zetta = 21
exa = 18
peta = 15
tera = 12
giga = 9
mega = 6
kilo = 3
hecto = 2
deca = 1
deci = -1
centi = -2
milli = -3
micro = -6
nano = -9
pico = -12
femto = -15
atto = -18
zepto = -21
yocto = -24
class BinaryUnit(Enum):
yotta = 8
zetta = 7
exa = 6
peta = 5
tera = 4
giga = 3
mega = 2
kilo = 1
def convert_si_prefix(
known_amount: float,
known_prefix: str | SIUnit,
unknown_prefix: str | SIUnit,
) -> float:
"""
Wikipedia reference: https://en.wikipedia.org/wiki/Binary_prefix
Wikipedia reference: https://en.wikipedia.org/wiki/International_System_of_Units
>>> convert_si_prefix(1, SIUnit.giga, SIUnit.mega)
1000
>>> convert_si_prefix(1, SIUnit.mega, SIUnit.giga)
0.001
>>> convert_si_prefix(1, SIUnit.kilo, SIUnit.kilo)
1
>>> convert_si_prefix(1, 'giga', 'mega')
1000
>>> convert_si_prefix(1, 'gIGa', 'mEGa')
1000
"""
if isinstance(known_prefix, str):
known_prefix = SIUnit[known_prefix.lower()]
if isinstance(unknown_prefix, str):
unknown_prefix = SIUnit[unknown_prefix.lower()]
unknown_amount: float = known_amount * (
10 ** (known_prefix.value - unknown_prefix.value)
)
return unknown_amount
def convert_binary_prefix(
known_amount: float,
known_prefix: str | BinaryUnit,
unknown_prefix: str | BinaryUnit,
) -> float:
"""
Wikipedia reference: https://en.wikipedia.org/wiki/Metric_prefix
>>> convert_binary_prefix(1, BinaryUnit.giga, BinaryUnit.mega)
1024
>>> convert_binary_prefix(1, BinaryUnit.mega, BinaryUnit.giga)
0.0009765625
>>> convert_binary_prefix(1, BinaryUnit.kilo, BinaryUnit.kilo)
1
>>> convert_binary_prefix(1, 'giga', 'mega')
1024
>>> convert_binary_prefix(1, 'gIGa', 'mEGa')
1024
"""
if isinstance(known_prefix, str):
known_prefix = BinaryUnit[known_prefix.lower()]
if isinstance(unknown_prefix, str):
unknown_prefix = BinaryUnit[unknown_prefix.lower()]
unknown_amount: float = known_amount * (
2 ** ((known_prefix.value - unknown_prefix.value) * 10)
)
return unknown_amount
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Sum of digits sequence
Problem 551
Let a(0), a(1),... be an integer sequence defined by:
a(0) = 1
for n >= 1, a(n) is the sum of the digits of all preceding terms
The sequence starts with 1, 1, 2, 4, 8, ...
You are given a(10^6) = 31054319.
Find a(10^15)
"""
ks = range(2, 20 + 1)
base = [10**k for k in range(ks[-1] + 1)]
memo: dict[int, dict[int, list[list[int]]]] = {}
def next_term(a_i, k, i, n):
"""
Calculates and updates a_i in-place to either the n-th term or the
smallest term for which c > 10^k when the terms are written in the form:
a(i) = b * 10^k + c
For any a(i), if digitsum(b) and c have the same value, the difference
between subsequent terms will be the same until c >= 10^k. This difference
is cached to greatly speed up the computation.
Arguments:
a_i -- array of digits starting from the one's place that represent
the i-th term in the sequence
k -- k when terms are written in the from a(i) = b*10^k + c.
Term are calulcated until c > 10^k or the n-th term is reached.
i -- position along the sequence
n -- term to calculate up to if k is large enough
Return: a tuple of difference between ending term and starting term, and
the number of terms calculated. ex. if starting term is a_0=1, and
ending term is a_10=62, then (61, 9) is returned.
"""
# ds_b - digitsum(b)
ds_b = sum(a_i[j] for j in range(k, len(a_i)))
c = sum(a_i[j] * base[j] for j in range(min(len(a_i), k)))
diff, dn = 0, 0
max_dn = n - i
sub_memo = memo.get(ds_b)
if sub_memo is not None:
jumps = sub_memo.get(c)
if jumps is not None and len(jumps) > 0:
# find and make the largest jump without going over
max_jump = -1
for _k in range(len(jumps) - 1, -1, -1):
if jumps[_k][2] <= k and jumps[_k][1] <= max_dn:
max_jump = _k
break
if max_jump >= 0:
diff, dn, _kk = jumps[max_jump]
# since the difference between jumps is cached, add c
new_c = diff + c
for j in range(min(k, len(a_i))):
new_c, a_i[j] = divmod(new_c, 10)
if new_c > 0:
add(a_i, k, new_c)
else:
sub_memo[c] = []
else:
sub_memo = {c: []}
memo[ds_b] = sub_memo
if dn >= max_dn or c + diff >= base[k]:
return diff, dn
if k > ks[0]:
while True:
# keep doing smaller jumps
_diff, terms_jumped = next_term(a_i, k - 1, i + dn, n)
diff += _diff
dn += terms_jumped
if dn >= max_dn or c + diff >= base[k]:
break
else:
# would be too small a jump, just compute sequential terms instead
_diff, terms_jumped = compute(a_i, k, i + dn, n)
diff += _diff
dn += terms_jumped
jumps = sub_memo[c]
# keep jumps sorted by # of terms skipped
j = 0
while j < len(jumps):
if jumps[j][1] > dn:
break
j += 1
# cache the jump for this value digitsum(b) and c
sub_memo[c].insert(j, (diff, dn, k))
return (diff, dn)
def compute(a_i, k, i, n):
"""
same as next_term(a_i, k, i, n) but computes terms without memoizing results.
"""
if i >= n:
return 0, i
if k > len(a_i):
a_i.extend([0 for _ in range(k - len(a_i))])
# note: a_i -> b * 10^k + c
# ds_b -> digitsum(b)
# ds_c -> digitsum(c)
start_i = i
ds_b, ds_c, diff = 0, 0, 0
for j in range(len(a_i)):
if j >= k:
ds_b += a_i[j]
else:
ds_c += a_i[j]
while i < n:
i += 1
addend = ds_c + ds_b
diff += addend
ds_c = 0
for j in range(k):
s = a_i[j] + addend
addend, a_i[j] = divmod(s, 10)
ds_c += a_i[j]
if addend > 0:
break
if addend > 0:
add(a_i, k, addend)
return diff, i - start_i
def add(digits, k, addend):
"""
adds addend to digit array given in digits
starting at index k
"""
for j in range(k, len(digits)):
s = digits[j] + addend
if s >= 10:
quotient, digits[j] = divmod(s, 10)
addend = addend // 10 + quotient
else:
digits[j] = s
addend = addend // 10
if addend == 0:
break
while addend > 0:
addend, digit = divmod(addend, 10)
digits.append(digit)
def solution(n: int = 10**15) -> int:
"""
returns n-th term of sequence
>>> solution(10)
62
>>> solution(10**6)
31054319
>>> solution(10**15)
73597483551591773
"""
digits = [1]
i = 1
dn = 0
while True:
diff, terms_jumped = next_term(digits, 20, i + dn, n)
dn += terms_jumped
if dn == n - i:
break
a_n = 0
for j in range(len(digits)):
a_n += digits[j] * 10**j
return a_n
if __name__ == "__main__":
print(f"{solution() = }")
| """
Sum of digits sequence
Problem 551
Let a(0), a(1),... be an integer sequence defined by:
a(0) = 1
for n >= 1, a(n) is the sum of the digits of all preceding terms
The sequence starts with 1, 1, 2, 4, 8, ...
You are given a(10^6) = 31054319.
Find a(10^15)
"""
ks = range(2, 20 + 1)
base = [10**k for k in range(ks[-1] + 1)]
memo: dict[int, dict[int, list[list[int]]]] = {}
def next_term(a_i, k, i, n):
"""
Calculates and updates a_i in-place to either the n-th term or the
smallest term for which c > 10^k when the terms are written in the form:
a(i) = b * 10^k + c
For any a(i), if digitsum(b) and c have the same value, the difference
between subsequent terms will be the same until c >= 10^k. This difference
is cached to greatly speed up the computation.
Arguments:
a_i -- array of digits starting from the one's place that represent
the i-th term in the sequence
k -- k when terms are written in the from a(i) = b*10^k + c.
Term are calulcated until c > 10^k or the n-th term is reached.
i -- position along the sequence
n -- term to calculate up to if k is large enough
Return: a tuple of difference between ending term and starting term, and
the number of terms calculated. ex. if starting term is a_0=1, and
ending term is a_10=62, then (61, 9) is returned.
"""
# ds_b - digitsum(b)
ds_b = sum(a_i[j] for j in range(k, len(a_i)))
c = sum(a_i[j] * base[j] for j in range(min(len(a_i), k)))
diff, dn = 0, 0
max_dn = n - i
sub_memo = memo.get(ds_b)
if sub_memo is not None:
jumps = sub_memo.get(c)
if jumps is not None and len(jumps) > 0:
# find and make the largest jump without going over
max_jump = -1
for _k in range(len(jumps) - 1, -1, -1):
if jumps[_k][2] <= k and jumps[_k][1] <= max_dn:
max_jump = _k
break
if max_jump >= 0:
diff, dn, _kk = jumps[max_jump]
# since the difference between jumps is cached, add c
new_c = diff + c
for j in range(min(k, len(a_i))):
new_c, a_i[j] = divmod(new_c, 10)
if new_c > 0:
add(a_i, k, new_c)
else:
sub_memo[c] = []
else:
sub_memo = {c: []}
memo[ds_b] = sub_memo
if dn >= max_dn or c + diff >= base[k]:
return diff, dn
if k > ks[0]:
while True:
# keep doing smaller jumps
_diff, terms_jumped = next_term(a_i, k - 1, i + dn, n)
diff += _diff
dn += terms_jumped
if dn >= max_dn or c + diff >= base[k]:
break
else:
# would be too small a jump, just compute sequential terms instead
_diff, terms_jumped = compute(a_i, k, i + dn, n)
diff += _diff
dn += terms_jumped
jumps = sub_memo[c]
# keep jumps sorted by # of terms skipped
j = 0
while j < len(jumps):
if jumps[j][1] > dn:
break
j += 1
# cache the jump for this value digitsum(b) and c
sub_memo[c].insert(j, (diff, dn, k))
return (diff, dn)
def compute(a_i, k, i, n):
"""
same as next_term(a_i, k, i, n) but computes terms without memoizing results.
"""
if i >= n:
return 0, i
if k > len(a_i):
a_i.extend([0 for _ in range(k - len(a_i))])
# note: a_i -> b * 10^k + c
# ds_b -> digitsum(b)
# ds_c -> digitsum(c)
start_i = i
ds_b, ds_c, diff = 0, 0, 0
for j in range(len(a_i)):
if j >= k:
ds_b += a_i[j]
else:
ds_c += a_i[j]
while i < n:
i += 1
addend = ds_c + ds_b
diff += addend
ds_c = 0
for j in range(k):
s = a_i[j] + addend
addend, a_i[j] = divmod(s, 10)
ds_c += a_i[j]
if addend > 0:
break
if addend > 0:
add(a_i, k, addend)
return diff, i - start_i
def add(digits, k, addend):
"""
adds addend to digit array given in digits
starting at index k
"""
for j in range(k, len(digits)):
s = digits[j] + addend
if s >= 10:
quotient, digits[j] = divmod(s, 10)
addend = addend // 10 + quotient
else:
digits[j] = s
addend = addend // 10
if addend == 0:
break
while addend > 0:
addend, digit = divmod(addend, 10)
digits.append(digit)
def solution(n: int = 10**15) -> int:
"""
returns n-th term of sequence
>>> solution(10)
62
>>> solution(10**6)
31054319
>>> solution(10**15)
73597483551591773
"""
digits = [1]
i = 1
dn = 0
while True:
diff, terms_jumped = next_term(digits, 20, i + dn, n)
dn += terms_jumped
if dn == n - i:
break
a_n = 0
for j in range(len(digits)):
a_n += digits[j] * 10**j
return a_n
if __name__ == "__main__":
print(f"{solution() = }")
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| #!/bin/sh
# An example hook script to verify what is about to be pushed. Called by "git
# push" after it has checked the remote status, but before anything has been
# pushed. If this script exits with a non-zero status nothing will be pushed.
#
# This hook is called with the following parameters:
#
# $1 -- Name of the remote to which the push is being done
# $2 -- URL to which the push is being done
#
# If pushing without using a named remote those arguments will be equal.
#
# Information about the commits which are being pushed is supplied as lines to
# the standard input in the form:
#
# <local ref> <local sha1> <remote ref> <remote sha1>
#
# This sample shows how to prevent push of commits where the log message starts
# with "WIP" (work in progress).
remote="$1"
url="$2"
z40=0000000000000000000000000000000000000000
while read local_ref local_sha remote_ref remote_sha
do
if [ "$local_sha" = $z40 ]
then
# Handle delete
:
else
if [ "$remote_sha" = $z40 ]
then
# New branch, examine all commits
range="$local_sha"
else
# Update to existing branch, examine new commits
range="$remote_sha..$local_sha"
fi
# Check for WIP commit
commit=`git rev-list -n 1 --grep '^WIP' "$range"`
if [ -n "$commit" ]
then
echo >&2 "Found WIP commit in $local_ref, not pushing"
exit 1
fi
fi
done
exit 0
| #!/bin/sh
# An example hook script to verify what is about to be pushed. Called by "git
# push" after it has checked the remote status, but before anything has been
# pushed. If this script exits with a non-zero status nothing will be pushed.
#
# This hook is called with the following parameters:
#
# $1 -- Name of the remote to which the push is being done
# $2 -- URL to which the push is being done
#
# If pushing without using a named remote those arguments will be equal.
#
# Information about the commits which are being pushed is supplied as lines to
# the standard input in the form:
#
# <local ref> <local sha1> <remote ref> <remote sha1>
#
# This sample shows how to prevent push of commits where the log message starts
# with "WIP" (work in progress).
remote="$1"
url="$2"
z40=0000000000000000000000000000000000000000
while read local_ref local_sha remote_ref remote_sha
do
if [ "$local_sha" = $z40 ]
then
# Handle delete
:
else
if [ "$remote_sha" = $z40 ]
then
# New branch, examine all commits
range="$local_sha"
else
# Update to existing branch, examine new commits
range="$remote_sha..$local_sha"
fi
# Check for WIP commit
commit=`git rev-list -n 1 --grep '^WIP' "$range"`
if [ -n "$commit" ]
then
echo >&2 "Found WIP commit in $local_ref, not pushing"
exit 1
fi
fi
done
exit 0
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Problem 20: https://projecteuler.net/problem=20
n! means n × (n − 1) × ... × 3 × 2 × 1
For example, 10! = 10 × 9 × ... × 3 × 2 × 1 = 3628800,
and the sum of the digits in the number 10! is 3 + 6 + 2 + 8 + 8 + 0 + 0 = 27.
Find the sum of the digits in the number 100!
"""
def solution(num: int = 100) -> int:
"""Returns the sum of the digits in the factorial of num
>>> solution(100)
648
>>> solution(50)
216
>>> solution(10)
27
>>> solution(5)
3
>>> solution(3)
6
>>> solution(2)
2
>>> solution(1)
1
"""
fact = 1
result = 0
for i in range(1, num + 1):
fact *= i
for j in str(fact):
result += int(j)
return result
if __name__ == "__main__":
print(solution(int(input("Enter the Number: ").strip())))
| """
Problem 20: https://projecteuler.net/problem=20
n! means n × (n − 1) × ... × 3 × 2 × 1
For example, 10! = 10 × 9 × ... × 3 × 2 × 1 = 3628800,
and the sum of the digits in the number 10! is 3 + 6 + 2 + 8 + 8 + 0 + 0 = 27.
Find the sum of the digits in the number 100!
"""
def solution(num: int = 100) -> int:
"""Returns the sum of the digits in the factorial of num
>>> solution(100)
648
>>> solution(50)
216
>>> solution(10)
27
>>> solution(5)
3
>>> solution(3)
6
>>> solution(2)
2
>>> solution(1)
1
"""
fact = 1
result = 0
for i in range(1, num + 1):
fact *= i
for j in str(fact):
result += int(j)
return result
if __name__ == "__main__":
print(solution(int(input("Enter the Number: ").strip())))
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| def bin_exp_mod(a, n, b):
"""
>>> bin_exp_mod(3, 4, 5)
1
>>> bin_exp_mod(7, 13, 10)
7
"""
# mod b
assert not (b == 0), "This cannot accept modulo that is == 0"
if n == 0:
return 1
if n % 2 == 1:
return (bin_exp_mod(a, n - 1, b) * a) % b
r = bin_exp_mod(a, n / 2, b)
return (r * r) % b
if __name__ == "__main__":
try:
BASE = int(input("Enter Base : ").strip())
POWER = int(input("Enter Power : ").strip())
MODULO = int(input("Enter Modulo : ").strip())
except ValueError:
print("Invalid literal for integer")
print(bin_exp_mod(BASE, POWER, MODULO))
| def bin_exp_mod(a, n, b):
"""
>>> bin_exp_mod(3, 4, 5)
1
>>> bin_exp_mod(7, 13, 10)
7
"""
# mod b
assert not (b == 0), "This cannot accept modulo that is == 0"
if n == 0:
return 1
if n % 2 == 1:
return (bin_exp_mod(a, n - 1, b) * a) % b
r = bin_exp_mod(a, n / 2, b)
return (r * r) % b
if __name__ == "__main__":
try:
BASE = int(input("Enter Base : ").strip())
POWER = int(input("Enter Power : ").strip())
MODULO = int(input("Enter Modulo : ").strip())
except ValueError:
print("Invalid literal for integer")
print(bin_exp_mod(BASE, POWER, MODULO))
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Python program for Bitonic Sort.
Note that this program works only when size of input is a power of 2.
"""
from __future__ import annotations
def comp_and_swap(array: list[int], index1: int, index2: int, direction: int) -> None:
"""Compare the value at given index1 and index2 of the array and swap them as per
the given direction.
The parameter direction indicates the sorting direction, ASCENDING(1) or
DESCENDING(0); if (a[i] > a[j]) agrees with the direction, then a[i] and a[j] are
interchanged.
>>> arr = [12, 42, -21, 1]
>>> comp_and_swap(arr, 1, 2, 1)
>>> arr
[12, -21, 42, 1]
>>> comp_and_swap(arr, 1, 2, 0)
>>> arr
[12, 42, -21, 1]
>>> comp_and_swap(arr, 0, 3, 1)
>>> arr
[1, 42, -21, 12]
>>> comp_and_swap(arr, 0, 3, 0)
>>> arr
[12, 42, -21, 1]
"""
if (direction == 1 and array[index1] > array[index2]) or (
direction == 0 and array[index1] < array[index2]
):
array[index1], array[index2] = array[index2], array[index1]
def bitonic_merge(array: list[int], low: int, length: int, direction: int) -> None:
"""
It recursively sorts a bitonic sequence in ascending order, if direction = 1, and in
descending if direction = 0.
The sequence to be sorted starts at index position low, the parameter length is the
number of elements to be sorted.
>>> arr = [12, 42, -21, 1]
>>> bitonic_merge(arr, 0, 4, 1)
>>> arr
[-21, 1, 12, 42]
>>> bitonic_merge(arr, 0, 4, 0)
>>> arr
[42, 12, 1, -21]
"""
if length > 1:
middle = int(length / 2)
for i in range(low, low + middle):
comp_and_swap(array, i, i + middle, direction)
bitonic_merge(array, low, middle, direction)
bitonic_merge(array, low + middle, middle, direction)
def bitonic_sort(array: list[int], low: int, length: int, direction: int) -> None:
"""
This function first produces a bitonic sequence by recursively sorting its two
halves in opposite sorting orders, and then calls bitonic_merge to make them in the
same order.
>>> arr = [12, 34, 92, -23, 0, -121, -167, 145]
>>> bitonic_sort(arr, 0, 8, 1)
>>> arr
[-167, -121, -23, 0, 12, 34, 92, 145]
>>> bitonic_sort(arr, 0, 8, 0)
>>> arr
[145, 92, 34, 12, 0, -23, -121, -167]
"""
if length > 1:
middle = int(length / 2)
bitonic_sort(array, low, middle, 1)
bitonic_sort(array, low + middle, middle, 0)
bitonic_merge(array, low, length, direction)
if __name__ == "__main__":
user_input = input("Enter numbers separated by a comma:\n").strip()
unsorted = [int(item.strip()) for item in user_input.split(",")]
bitonic_sort(unsorted, 0, len(unsorted), 1)
print("\nSorted array in ascending order is: ", end="")
print(*unsorted, sep=", ")
bitonic_merge(unsorted, 0, len(unsorted), 0)
print("Sorted array in descending order is: ", end="")
print(*unsorted, sep=", ")
| """
Python program for Bitonic Sort.
Note that this program works only when size of input is a power of 2.
"""
from __future__ import annotations
def comp_and_swap(array: list[int], index1: int, index2: int, direction: int) -> None:
"""Compare the value at given index1 and index2 of the array and swap them as per
the given direction.
The parameter direction indicates the sorting direction, ASCENDING(1) or
DESCENDING(0); if (a[i] > a[j]) agrees with the direction, then a[i] and a[j] are
interchanged.
>>> arr = [12, 42, -21, 1]
>>> comp_and_swap(arr, 1, 2, 1)
>>> arr
[12, -21, 42, 1]
>>> comp_and_swap(arr, 1, 2, 0)
>>> arr
[12, 42, -21, 1]
>>> comp_and_swap(arr, 0, 3, 1)
>>> arr
[1, 42, -21, 12]
>>> comp_and_swap(arr, 0, 3, 0)
>>> arr
[12, 42, -21, 1]
"""
if (direction == 1 and array[index1] > array[index2]) or (
direction == 0 and array[index1] < array[index2]
):
array[index1], array[index2] = array[index2], array[index1]
def bitonic_merge(array: list[int], low: int, length: int, direction: int) -> None:
"""
It recursively sorts a bitonic sequence in ascending order, if direction = 1, and in
descending if direction = 0.
The sequence to be sorted starts at index position low, the parameter length is the
number of elements to be sorted.
>>> arr = [12, 42, -21, 1]
>>> bitonic_merge(arr, 0, 4, 1)
>>> arr
[-21, 1, 12, 42]
>>> bitonic_merge(arr, 0, 4, 0)
>>> arr
[42, 12, 1, -21]
"""
if length > 1:
middle = int(length / 2)
for i in range(low, low + middle):
comp_and_swap(array, i, i + middle, direction)
bitonic_merge(array, low, middle, direction)
bitonic_merge(array, low + middle, middle, direction)
def bitonic_sort(array: list[int], low: int, length: int, direction: int) -> None:
"""
This function first produces a bitonic sequence by recursively sorting its two
halves in opposite sorting orders, and then calls bitonic_merge to make them in the
same order.
>>> arr = [12, 34, 92, -23, 0, -121, -167, 145]
>>> bitonic_sort(arr, 0, 8, 1)
>>> arr
[-167, -121, -23, 0, 12, 34, 92, 145]
>>> bitonic_sort(arr, 0, 8, 0)
>>> arr
[145, 92, 34, 12, 0, -23, -121, -167]
"""
if length > 1:
middle = int(length / 2)
bitonic_sort(array, low, middle, 1)
bitonic_sort(array, low + middle, middle, 0)
bitonic_merge(array, low, length, direction)
if __name__ == "__main__":
user_input = input("Enter numbers separated by a comma:\n").strip()
unsorted = [int(item.strip()) for item in user_input.split(",")]
bitonic_sort(unsorted, 0, len(unsorted), 1)
print("\nSorted array in ascending order is: ", end="")
print(*unsorted, sep=", ")
bitonic_merge(unsorted, 0, len(unsorted), 0)
print("Sorted array in descending order is: ", end="")
print(*unsorted, sep=", ")
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| import os
import sys
from . import rsa_key_generator as rkg
DEFAULT_BLOCK_SIZE = 128
BYTE_SIZE = 256
def get_blocks_from_text(
message: str, block_size: int = DEFAULT_BLOCK_SIZE
) -> list[int]:
message_bytes = message.encode("ascii")
block_ints = []
for block_start in range(0, len(message_bytes), block_size):
block_int = 0
for i in range(block_start, min(block_start + block_size, len(message_bytes))):
block_int += message_bytes[i] * (BYTE_SIZE ** (i % block_size))
block_ints.append(block_int)
return block_ints
def get_text_from_blocks(
block_ints: list[int], message_length: int, block_size: int = DEFAULT_BLOCK_SIZE
) -> str:
message: list[str] = []
for block_int in block_ints:
block_message: list[str] = []
for i in range(block_size - 1, -1, -1):
if len(message) + i < message_length:
ascii_number = block_int // (BYTE_SIZE**i)
block_int = block_int % (BYTE_SIZE**i)
block_message.insert(0, chr(ascii_number))
message.extend(block_message)
return "".join(message)
def encrypt_message(
message: str, key: tuple[int, int], block_size: int = DEFAULT_BLOCK_SIZE
) -> list[int]:
encrypted_blocks = []
n, e = key
for block in get_blocks_from_text(message, block_size):
encrypted_blocks.append(pow(block, e, n))
return encrypted_blocks
def decrypt_message(
encrypted_blocks: list[int],
message_length: int,
key: tuple[int, int],
block_size: int = DEFAULT_BLOCK_SIZE,
) -> str:
decrypted_blocks = []
n, d = key
for block in encrypted_blocks:
decrypted_blocks.append(pow(block, d, n))
return get_text_from_blocks(decrypted_blocks, message_length, block_size)
def read_key_file(key_filename: str) -> tuple[int, int, int]:
with open(key_filename) as fo:
content = fo.read()
key_size, n, eor_d = content.split(",")
return (int(key_size), int(n), int(eor_d))
def encrypt_and_write_to_file(
message_filename: str,
key_filename: str,
message: str,
block_size: int = DEFAULT_BLOCK_SIZE,
) -> str:
key_size, n, e = read_key_file(key_filename)
if key_size < block_size * 8:
sys.exit(
"ERROR: Block size is %s bits and key size is %s bits. The RSA cipher "
"requires the block size to be equal to or greater than the key size. "
"Either decrease the block size or use different keys."
% (block_size * 8, key_size)
)
encrypted_blocks = [str(i) for i in encrypt_message(message, (n, e), block_size)]
encrypted_content = ",".join(encrypted_blocks)
encrypted_content = f"{len(message)}_{block_size}_{encrypted_content}"
with open(message_filename, "w") as fo:
fo.write(encrypted_content)
return encrypted_content
def read_from_file_and_decrypt(message_filename: str, key_filename: str) -> str:
key_size, n, d = read_key_file(key_filename)
with open(message_filename) as fo:
content = fo.read()
message_length_str, block_size_str, encrypted_message = content.split("_")
message_length = int(message_length_str)
block_size = int(block_size_str)
if key_size < block_size * 8:
sys.exit(
"ERROR: Block size is %s bits and key size is %s bits. The RSA cipher "
"requires the block size to be equal to or greater than the key size. "
"Did you specify the correct key file and encrypted file?"
% (block_size * 8, key_size)
)
encrypted_blocks = []
for block in encrypted_message.split(","):
encrypted_blocks.append(int(block))
return decrypt_message(encrypted_blocks, message_length, (n, d), block_size)
def main() -> None:
filename = "encrypted_file.txt"
response = input(r"Encrypt\Decrypt [e\d]: ")
if response.lower().startswith("e"):
mode = "encrypt"
elif response.lower().startswith("d"):
mode = "decrypt"
if mode == "encrypt":
if not os.path.exists("rsa_pubkey.txt"):
rkg.make_key_files("rsa", 1024)
message = input("\nEnter message: ")
pubkey_filename = "rsa_pubkey.txt"
print(f"Encrypting and writing to {filename}...")
encrypted_text = encrypt_and_write_to_file(filename, pubkey_filename, message)
print("\nEncrypted text:")
print(encrypted_text)
elif mode == "decrypt":
privkey_filename = "rsa_privkey.txt"
print(f"Reading from {filename} and decrypting...")
decrypted_text = read_from_file_and_decrypt(filename, privkey_filename)
print("writing decryption to rsa_decryption.txt...")
with open("rsa_decryption.txt", "w") as dec:
dec.write(decrypted_text)
print("\nDecryption:")
print(decrypted_text)
if __name__ == "__main__":
main()
| import os
import sys
from . import rsa_key_generator as rkg
DEFAULT_BLOCK_SIZE = 128
BYTE_SIZE = 256
def get_blocks_from_text(
message: str, block_size: int = DEFAULT_BLOCK_SIZE
) -> list[int]:
message_bytes = message.encode("ascii")
block_ints = []
for block_start in range(0, len(message_bytes), block_size):
block_int = 0
for i in range(block_start, min(block_start + block_size, len(message_bytes))):
block_int += message_bytes[i] * (BYTE_SIZE ** (i % block_size))
block_ints.append(block_int)
return block_ints
def get_text_from_blocks(
block_ints: list[int], message_length: int, block_size: int = DEFAULT_BLOCK_SIZE
) -> str:
message: list[str] = []
for block_int in block_ints:
block_message: list[str] = []
for i in range(block_size - 1, -1, -1):
if len(message) + i < message_length:
ascii_number = block_int // (BYTE_SIZE**i)
block_int = block_int % (BYTE_SIZE**i)
block_message.insert(0, chr(ascii_number))
message.extend(block_message)
return "".join(message)
def encrypt_message(
message: str, key: tuple[int, int], block_size: int = DEFAULT_BLOCK_SIZE
) -> list[int]:
encrypted_blocks = []
n, e = key
for block in get_blocks_from_text(message, block_size):
encrypted_blocks.append(pow(block, e, n))
return encrypted_blocks
def decrypt_message(
encrypted_blocks: list[int],
message_length: int,
key: tuple[int, int],
block_size: int = DEFAULT_BLOCK_SIZE,
) -> str:
decrypted_blocks = []
n, d = key
for block in encrypted_blocks:
decrypted_blocks.append(pow(block, d, n))
return get_text_from_blocks(decrypted_blocks, message_length, block_size)
def read_key_file(key_filename: str) -> tuple[int, int, int]:
with open(key_filename) as fo:
content = fo.read()
key_size, n, eor_d = content.split(",")
return (int(key_size), int(n), int(eor_d))
def encrypt_and_write_to_file(
message_filename: str,
key_filename: str,
message: str,
block_size: int = DEFAULT_BLOCK_SIZE,
) -> str:
key_size, n, e = read_key_file(key_filename)
if key_size < block_size * 8:
sys.exit(
"ERROR: Block size is %s bits and key size is %s bits. The RSA cipher "
"requires the block size to be equal to or greater than the key size. "
"Either decrease the block size or use different keys."
% (block_size * 8, key_size)
)
encrypted_blocks = [str(i) for i in encrypt_message(message, (n, e), block_size)]
encrypted_content = ",".join(encrypted_blocks)
encrypted_content = f"{len(message)}_{block_size}_{encrypted_content}"
with open(message_filename, "w") as fo:
fo.write(encrypted_content)
return encrypted_content
def read_from_file_and_decrypt(message_filename: str, key_filename: str) -> str:
key_size, n, d = read_key_file(key_filename)
with open(message_filename) as fo:
content = fo.read()
message_length_str, block_size_str, encrypted_message = content.split("_")
message_length = int(message_length_str)
block_size = int(block_size_str)
if key_size < block_size * 8:
sys.exit(
"ERROR: Block size is %s bits and key size is %s bits. The RSA cipher "
"requires the block size to be equal to or greater than the key size. "
"Did you specify the correct key file and encrypted file?"
% (block_size * 8, key_size)
)
encrypted_blocks = []
for block in encrypted_message.split(","):
encrypted_blocks.append(int(block))
return decrypt_message(encrypted_blocks, message_length, (n, d), block_size)
def main() -> None:
filename = "encrypted_file.txt"
response = input(r"Encrypt\Decrypt [e\d]: ")
if response.lower().startswith("e"):
mode = "encrypt"
elif response.lower().startswith("d"):
mode = "decrypt"
if mode == "encrypt":
if not os.path.exists("rsa_pubkey.txt"):
rkg.make_key_files("rsa", 1024)
message = input("\nEnter message: ")
pubkey_filename = "rsa_pubkey.txt"
print(f"Encrypting and writing to {filename}...")
encrypted_text = encrypt_and_write_to_file(filename, pubkey_filename, message)
print("\nEncrypted text:")
print(encrypted_text)
elif mode == "decrypt":
privkey_filename = "rsa_privkey.txt"
print(f"Reading from {filename} and decrypting...")
decrypted_text = read_from_file_and_decrypt(filename, privkey_filename)
print("writing decryption to rsa_decryption.txt...")
with open("rsa_decryption.txt", "w") as dec:
dec.write(decrypted_text)
print("\nDecryption:")
print(decrypted_text)
if __name__ == "__main__":
main()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Project Euler problem 145: https://projecteuler.net/problem=145
Author: Vineet Rao, Maxim Smolskiy
Problem statement:
Some positive integers n have the property that the sum [ n + reverse(n) ]
consists entirely of odd (decimal) digits.
For instance, 36 + 63 = 99 and 409 + 904 = 1313.
We will call such numbers reversible; so 36, 63, 409, and 904 are reversible.
Leading zeroes are not allowed in either n or reverse(n).
There are 120 reversible numbers below one-thousand.
How many reversible numbers are there below one-billion (10^9)?
"""
EVEN_DIGITS = [0, 2, 4, 6, 8]
ODD_DIGITS = [1, 3, 5, 7, 9]
def reversible_numbers(
remaining_length: int, remainder: int, digits: list[int], length: int
) -> int:
"""
Count the number of reversible numbers of given length.
Iterate over possible digits considering parity of current sum remainder.
>>> reversible_numbers(1, 0, [0], 1)
0
>>> reversible_numbers(2, 0, [0] * 2, 2)
20
>>> reversible_numbers(3, 0, [0] * 3, 3)
100
"""
if remaining_length == 0:
if digits[0] == 0 or digits[-1] == 0:
return 0
for i in range(length // 2 - 1, -1, -1):
remainder += digits[i] + digits[length - i - 1]
if remainder % 2 == 0:
return 0
remainder //= 10
return 1
if remaining_length == 1:
if remainder % 2 == 0:
return 0
result = 0
for digit in range(10):
digits[length // 2] = digit
result += reversible_numbers(
0, (remainder + 2 * digit) // 10, digits, length
)
return result
result = 0
for digit1 in range(10):
digits[(length + remaining_length) // 2 - 1] = digit1
if (remainder + digit1) % 2 == 0:
other_parity_digits = ODD_DIGITS
else:
other_parity_digits = EVEN_DIGITS
for digit2 in other_parity_digits:
digits[(length - remaining_length) // 2] = digit2
result += reversible_numbers(
remaining_length - 2,
(remainder + digit1 + digit2) // 10,
digits,
length,
)
return result
def solution(max_power: int = 9) -> int:
"""
To evaluate the solution, use solution()
>>> solution(3)
120
>>> solution(6)
18720
>>> solution(7)
68720
"""
result = 0
for length in range(1, max_power + 1):
result += reversible_numbers(length, 0, [0] * length, length)
return result
if __name__ == "__main__":
print(f"{solution() = }")
| """
Project Euler problem 145: https://projecteuler.net/problem=145
Author: Vineet Rao, Maxim Smolskiy
Problem statement:
Some positive integers n have the property that the sum [ n + reverse(n) ]
consists entirely of odd (decimal) digits.
For instance, 36 + 63 = 99 and 409 + 904 = 1313.
We will call such numbers reversible; so 36, 63, 409, and 904 are reversible.
Leading zeroes are not allowed in either n or reverse(n).
There are 120 reversible numbers below one-thousand.
How many reversible numbers are there below one-billion (10^9)?
"""
EVEN_DIGITS = [0, 2, 4, 6, 8]
ODD_DIGITS = [1, 3, 5, 7, 9]
def reversible_numbers(
remaining_length: int, remainder: int, digits: list[int], length: int
) -> int:
"""
Count the number of reversible numbers of given length.
Iterate over possible digits considering parity of current sum remainder.
>>> reversible_numbers(1, 0, [0], 1)
0
>>> reversible_numbers(2, 0, [0] * 2, 2)
20
>>> reversible_numbers(3, 0, [0] * 3, 3)
100
"""
if remaining_length == 0:
if digits[0] == 0 or digits[-1] == 0:
return 0
for i in range(length // 2 - 1, -1, -1):
remainder += digits[i] + digits[length - i - 1]
if remainder % 2 == 0:
return 0
remainder //= 10
return 1
if remaining_length == 1:
if remainder % 2 == 0:
return 0
result = 0
for digit in range(10):
digits[length // 2] = digit
result += reversible_numbers(
0, (remainder + 2 * digit) // 10, digits, length
)
return result
result = 0
for digit1 in range(10):
digits[(length + remaining_length) // 2 - 1] = digit1
if (remainder + digit1) % 2 == 0:
other_parity_digits = ODD_DIGITS
else:
other_parity_digits = EVEN_DIGITS
for digit2 in other_parity_digits:
digits[(length - remaining_length) // 2] = digit2
result += reversible_numbers(
remaining_length - 2,
(remainder + digit1 + digit2) // 10,
digits,
length,
)
return result
def solution(max_power: int = 9) -> int:
"""
To evaluate the solution, use solution()
>>> solution(3)
120
>>> solution(6)
18720
>>> solution(7)
68720
"""
result = 0
for length in range(1, max_power + 1):
result += reversible_numbers(length, 0, [0] * length, length)
return result
if __name__ == "__main__":
print(f"{solution() = }")
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """A merge sort which accepts an array as input and recursively
splits an array in half and sorts and combines them.
"""
"""https://en.wikipedia.org/wiki/Merge_sort """
def merge(arr: list[int]) -> list[int]:
"""Return a sorted array.
>>> merge([10,9,8,7,6,5,4,3,2,1])
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
>>> merge([1,2,3,4,5,6,7,8,9,10])
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
>>> merge([10,22,1,2,3,9,15,23])
[1, 2, 3, 9, 10, 15, 22, 23]
>>> merge([100])
[100]
>>> merge([])
[]
"""
if len(arr) > 1:
middle_length = len(arr) // 2 # Finds the middle of the array
left_array = arr[
:middle_length
] # Creates an array of the elements in the first half.
right_array = arr[
middle_length:
] # Creates an array of the elements in the second half.
left_size = len(left_array)
right_size = len(right_array)
merge(left_array) # Starts sorting the left.
merge(right_array) # Starts sorting the right
left_index = 0 # Left Counter
right_index = 0 # Right Counter
index = 0 # Position Counter
while (
left_index < left_size and right_index < right_size
): # Runs until the lowers size of the left and right are sorted.
if left_array[left_index] < right_array[right_index]:
arr[index] = left_array[left_index]
left_index += 1
else:
arr[index] = right_array[right_index]
right_index += 1
index += 1
while (
left_index < left_size
): # Adds the left over elements in the left half of the array
arr[index] = left_array[left_index]
left_index += 1
index += 1
while (
right_index < right_size
): # Adds the left over elements in the right half of the array
arr[index] = right_array[right_index]
right_index += 1
index += 1
return arr
if __name__ == "__main__":
import doctest
doctest.testmod()
| """A merge sort which accepts an array as input and recursively
splits an array in half and sorts and combines them.
"""
"""https://en.wikipedia.org/wiki/Merge_sort """
def merge(arr: list[int]) -> list[int]:
"""Return a sorted array.
>>> merge([10,9,8,7,6,5,4,3,2,1])
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
>>> merge([1,2,3,4,5,6,7,8,9,10])
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
>>> merge([10,22,1,2,3,9,15,23])
[1, 2, 3, 9, 10, 15, 22, 23]
>>> merge([100])
[100]
>>> merge([])
[]
"""
if len(arr) > 1:
middle_length = len(arr) // 2 # Finds the middle of the array
left_array = arr[
:middle_length
] # Creates an array of the elements in the first half.
right_array = arr[
middle_length:
] # Creates an array of the elements in the second half.
left_size = len(left_array)
right_size = len(right_array)
merge(left_array) # Starts sorting the left.
merge(right_array) # Starts sorting the right
left_index = 0 # Left Counter
right_index = 0 # Right Counter
index = 0 # Position Counter
while (
left_index < left_size and right_index < right_size
): # Runs until the lowers size of the left and right are sorted.
if left_array[left_index] < right_array[right_index]:
arr[index] = left_array[left_index]
left_index += 1
else:
arr[index] = right_array[right_index]
right_index += 1
index += 1
while (
left_index < left_size
): # Adds the left over elements in the left half of the array
arr[index] = left_array[left_index]
left_index += 1
index += 1
while (
right_index < right_size
): # Adds the left over elements in the right half of the array
arr[index] = right_array[right_index]
right_index += 1
index += 1
return arr
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Highly divisible triangular numbers
Problem 12
The sequence of triangle numbers is generated by adding the natural numbers. So
the 7th triangle number would be 1 + 2 + 3 + 4 + 5 + 6 + 7 = 28. The first ten
terms would be:
1, 3, 6, 10, 15, 21, 28, 36, 45, 55, ...
Let us list the factors of the first seven triangle numbers:
1: 1
3: 1,3
6: 1,2,3,6
10: 1,2,5,10
15: 1,3,5,15
21: 1,3,7,21
28: 1,2,4,7,14,28
We can see that 28 is the first triangle number to have over five divisors.
What is the value of the first triangle number to have over five hundred
divisors?
"""
def count_divisors(n):
n_divisors = 1
i = 2
while i * i <= n:
multiplicity = 0
while n % i == 0:
n //= i
multiplicity += 1
n_divisors *= multiplicity + 1
i += 1
if n > 1:
n_divisors *= 2
return n_divisors
def solution():
"""Returns the value of the first triangle number to have over five hundred
divisors.
>>> solution()
76576500
"""
t_num = 1
i = 1
while True:
i += 1
t_num += i
if count_divisors(t_num) > 500:
break
return t_num
if __name__ == "__main__":
print(solution())
| """
Highly divisible triangular numbers
Problem 12
The sequence of triangle numbers is generated by adding the natural numbers. So
the 7th triangle number would be 1 + 2 + 3 + 4 + 5 + 6 + 7 = 28. The first ten
terms would be:
1, 3, 6, 10, 15, 21, 28, 36, 45, 55, ...
Let us list the factors of the first seven triangle numbers:
1: 1
3: 1,3
6: 1,2,3,6
10: 1,2,5,10
15: 1,3,5,15
21: 1,3,7,21
28: 1,2,4,7,14,28
We can see that 28 is the first triangle number to have over five divisors.
What is the value of the first triangle number to have over five hundred
divisors?
"""
def count_divisors(n):
n_divisors = 1
i = 2
while i * i <= n:
multiplicity = 0
while n % i == 0:
n //= i
multiplicity += 1
n_divisors *= multiplicity + 1
i += 1
if n > 1:
n_divisors *= 2
return n_divisors
def solution():
"""Returns the value of the first triangle number to have over five hundred
divisors.
>>> solution()
76576500
"""
t_num = 1
i = 1
while True:
i += 1
t_num += i
if count_divisors(t_num) > 500:
break
return t_num
if __name__ == "__main__":
print(solution())
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Geometric Mean
Reference : https://en.wikipedia.org/wiki/Geometric_mean
Geometric series
Reference: https://en.wikipedia.org/wiki/Geometric_series
"""
def is_geometric_series(series: list) -> bool:
"""
checking whether the input series is geometric series or not
>>> is_geometric_series([2, 4, 8])
True
>>> is_geometric_series([3, 6, 12, 24])
True
>>> is_geometric_series([1, 2, 3])
False
>>> is_geometric_series([0, 0, 3])
False
>>> is_geometric_series([])
Traceback (most recent call last):
...
ValueError: Input list must be a non empty list
>>> is_geometric_series(4)
Traceback (most recent call last):
...
ValueError: Input series is not valid, valid series - [2, 4, 8]
"""
if not isinstance(series, list):
raise ValueError("Input series is not valid, valid series - [2, 4, 8]")
if len(series) == 0:
raise ValueError("Input list must be a non empty list")
if len(series) == 1:
return True
try:
common_ratio = series[1] / series[0]
for index in range(len(series) - 1):
if series[index + 1] / series[index] != common_ratio:
return False
except ZeroDivisionError:
return False
return True
def geometric_mean(series: list) -> float:
"""
return the geometric mean of series
>>> geometric_mean([2, 4, 8])
3.9999999999999996
>>> geometric_mean([3, 6, 12, 24])
8.48528137423857
>>> geometric_mean([4, 8, 16])
7.999999999999999
>>> geometric_mean(4)
Traceback (most recent call last):
...
ValueError: Input series is not valid, valid series - [2, 4, 8]
>>> geometric_mean([1, 2, 3])
1.8171205928321397
>>> geometric_mean([0, 2, 3])
0.0
>>> geometric_mean([])
Traceback (most recent call last):
...
ValueError: Input list must be a non empty list
"""
if not isinstance(series, list):
raise ValueError("Input series is not valid, valid series - [2, 4, 8]")
if len(series) == 0:
raise ValueError("Input list must be a non empty list")
answer = 1
for value in series:
answer *= value
return pow(answer, 1 / len(series))
if __name__ == "__main__":
import doctest
doctest.testmod()
| """
Geometric Mean
Reference : https://en.wikipedia.org/wiki/Geometric_mean
Geometric series
Reference: https://en.wikipedia.org/wiki/Geometric_series
"""
def is_geometric_series(series: list) -> bool:
"""
checking whether the input series is geometric series or not
>>> is_geometric_series([2, 4, 8])
True
>>> is_geometric_series([3, 6, 12, 24])
True
>>> is_geometric_series([1, 2, 3])
False
>>> is_geometric_series([0, 0, 3])
False
>>> is_geometric_series([])
Traceback (most recent call last):
...
ValueError: Input list must be a non empty list
>>> is_geometric_series(4)
Traceback (most recent call last):
...
ValueError: Input series is not valid, valid series - [2, 4, 8]
"""
if not isinstance(series, list):
raise ValueError("Input series is not valid, valid series - [2, 4, 8]")
if len(series) == 0:
raise ValueError("Input list must be a non empty list")
if len(series) == 1:
return True
try:
common_ratio = series[1] / series[0]
for index in range(len(series) - 1):
if series[index + 1] / series[index] != common_ratio:
return False
except ZeroDivisionError:
return False
return True
def geometric_mean(series: list) -> float:
"""
return the geometric mean of series
>>> geometric_mean([2, 4, 8])
3.9999999999999996
>>> geometric_mean([3, 6, 12, 24])
8.48528137423857
>>> geometric_mean([4, 8, 16])
7.999999999999999
>>> geometric_mean(4)
Traceback (most recent call last):
...
ValueError: Input series is not valid, valid series - [2, 4, 8]
>>> geometric_mean([1, 2, 3])
1.8171205928321397
>>> geometric_mean([0, 2, 3])
0.0
>>> geometric_mean([])
Traceback (most recent call last):
...
ValueError: Input list must be a non empty list
"""
if not isinstance(series, list):
raise ValueError("Input series is not valid, valid series - [2, 4, 8]")
if len(series) == 0:
raise ValueError("Input list must be a non empty list")
answer = 1
for value in series:
answer *= value
return pow(answer, 1 / len(series))
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
What is the greatest product of four adjacent numbers (horizontally,
vertically, or diagonally) in this 20x20 array?
08 02 22 97 38 15 00 40 00 75 04 05 07 78 52 12 50 77 91 08
49 49 99 40 17 81 18 57 60 87 17 40 98 43 69 48 04 56 62 00
81 49 31 73 55 79 14 29 93 71 40 67 53 88 30 03 49 13 36 65
52 70 95 23 04 60 11 42 69 24 68 56 01 32 56 71 37 02 36 91
22 31 16 71 51 67 63 89 41 92 36 54 22 40 40 28 66 33 13 80
24 47 32 60 99 03 45 02 44 75 33 53 78 36 84 20 35 17 12 50
32 98 81 28 64 23 67 10 26 38 40 67 59 54 70 66 18 38 64 70
67 26 20 68 02 62 12 20 95 63 94 39 63 08 40 91 66 49 94 21
24 55 58 05 66 73 99 26 97 17 78 78 96 83 14 88 34 89 63 72
21 36 23 09 75 00 76 44 20 45 35 14 00 61 33 97 34 31 33 95
78 17 53 28 22 75 31 67 15 94 03 80 04 62 16 14 09 53 56 92
16 39 05 42 96 35 31 47 55 58 88 24 00 17 54 24 36 29 85 57
86 56 00 48 35 71 89 07 05 44 44 37 44 60 21 58 51 54 17 58
19 80 81 68 05 94 47 69 28 73 92 13 86 52 17 77 04 89 55 40
04 52 08 83 97 35 99 16 07 97 57 32 16 26 26 79 33 27 98 66
88 36 68 87 57 62 20 72 03 46 33 67 46 55 12 32 63 93 53 69
04 42 16 73 38 25 39 11 24 94 72 18 08 46 29 32 40 62 76 36
20 69 36 41 72 30 23 88 34 62 99 69 82 67 59 85 74 04 36 16
20 73 35 29 78 31 90 01 74 31 49 71 48 86 81 16 23 57 05 54
01 70 54 71 83 51 54 69 16 92 33 48 61 43 52 01 89 19 67 48
"""
import os
def largest_product(grid):
n_columns = len(grid[0])
n_rows = len(grid)
largest = 0
lr_diag_product = 0
rl_diag_product = 0
# Check vertically, horizontally, diagonally at the same time (only works
# for nxn grid)
for i in range(n_columns):
for j in range(n_rows - 3):
vert_product = grid[j][i] * grid[j + 1][i] * grid[j + 2][i] * grid[j + 3][i]
horz_product = grid[i][j] * grid[i][j + 1] * grid[i][j + 2] * grid[i][j + 3]
# Left-to-right diagonal (\) product
if i < n_columns - 3:
lr_diag_product = (
grid[i][j]
* grid[i + 1][j + 1]
* grid[i + 2][j + 2]
* grid[i + 3][j + 3]
)
# Right-to-left diagonal(/) product
if i > 2:
rl_diag_product = (
grid[i][j]
* grid[i - 1][j + 1]
* grid[i - 2][j + 2]
* grid[i - 3][j + 3]
)
max_product = max(
vert_product, horz_product, lr_diag_product, rl_diag_product
)
if max_product > largest:
largest = max_product
return largest
def solution():
"""Returns the greatest product of four adjacent numbers (horizontally,
vertically, or diagonally).
>>> solution()
70600674
"""
grid = []
with open(os.path.dirname(__file__) + "/grid.txt") as file:
for line in file:
grid.append(line.strip("\n").split(" "))
grid = [[int(i) for i in grid[j]] for j in range(len(grid))]
return largest_product(grid)
if __name__ == "__main__":
print(solution())
| """
What is the greatest product of four adjacent numbers (horizontally,
vertically, or diagonally) in this 20x20 array?
08 02 22 97 38 15 00 40 00 75 04 05 07 78 52 12 50 77 91 08
49 49 99 40 17 81 18 57 60 87 17 40 98 43 69 48 04 56 62 00
81 49 31 73 55 79 14 29 93 71 40 67 53 88 30 03 49 13 36 65
52 70 95 23 04 60 11 42 69 24 68 56 01 32 56 71 37 02 36 91
22 31 16 71 51 67 63 89 41 92 36 54 22 40 40 28 66 33 13 80
24 47 32 60 99 03 45 02 44 75 33 53 78 36 84 20 35 17 12 50
32 98 81 28 64 23 67 10 26 38 40 67 59 54 70 66 18 38 64 70
67 26 20 68 02 62 12 20 95 63 94 39 63 08 40 91 66 49 94 21
24 55 58 05 66 73 99 26 97 17 78 78 96 83 14 88 34 89 63 72
21 36 23 09 75 00 76 44 20 45 35 14 00 61 33 97 34 31 33 95
78 17 53 28 22 75 31 67 15 94 03 80 04 62 16 14 09 53 56 92
16 39 05 42 96 35 31 47 55 58 88 24 00 17 54 24 36 29 85 57
86 56 00 48 35 71 89 07 05 44 44 37 44 60 21 58 51 54 17 58
19 80 81 68 05 94 47 69 28 73 92 13 86 52 17 77 04 89 55 40
04 52 08 83 97 35 99 16 07 97 57 32 16 26 26 79 33 27 98 66
88 36 68 87 57 62 20 72 03 46 33 67 46 55 12 32 63 93 53 69
04 42 16 73 38 25 39 11 24 94 72 18 08 46 29 32 40 62 76 36
20 69 36 41 72 30 23 88 34 62 99 69 82 67 59 85 74 04 36 16
20 73 35 29 78 31 90 01 74 31 49 71 48 86 81 16 23 57 05 54
01 70 54 71 83 51 54 69 16 92 33 48 61 43 52 01 89 19 67 48
"""
import os
def largest_product(grid):
n_columns = len(grid[0])
n_rows = len(grid)
largest = 0
lr_diag_product = 0
rl_diag_product = 0
# Check vertically, horizontally, diagonally at the same time (only works
# for nxn grid)
for i in range(n_columns):
for j in range(n_rows - 3):
vert_product = grid[j][i] * grid[j + 1][i] * grid[j + 2][i] * grid[j + 3][i]
horz_product = grid[i][j] * grid[i][j + 1] * grid[i][j + 2] * grid[i][j + 3]
# Left-to-right diagonal (\) product
if i < n_columns - 3:
lr_diag_product = (
grid[i][j]
* grid[i + 1][j + 1]
* grid[i + 2][j + 2]
* grid[i + 3][j + 3]
)
# Right-to-left diagonal(/) product
if i > 2:
rl_diag_product = (
grid[i][j]
* grid[i - 1][j + 1]
* grid[i - 2][j + 2]
* grid[i - 3][j + 3]
)
max_product = max(
vert_product, horz_product, lr_diag_product, rl_diag_product
)
if max_product > largest:
largest = max_product
return largest
def solution():
"""Returns the greatest product of four adjacent numbers (horizontally,
vertically, or diagonally).
>>> solution()
70600674
"""
grid = []
with open(os.path.dirname(__file__) + "/grid.txt") as file:
for line in file:
grid.append(line.strip("\n").split(" "))
grid = [[int(i) for i in grid[j]] for j in range(len(grid))]
return largest_product(grid)
if __name__ == "__main__":
print(solution())
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Implements a disjoint set using Lists and some added heuristics for efficiency
Union by Rank Heuristic and Path Compression
"""
class DisjointSet:
def __init__(self, set_counts: list) -> None:
"""
Initialize with a list of the number of items in each set
and with rank = 1 for each set
"""
self.set_counts = set_counts
self.max_set = max(set_counts)
num_sets = len(set_counts)
self.ranks = [1] * num_sets
self.parents = list(range(num_sets))
def merge(self, src: int, dst: int) -> bool:
"""
Merge two sets together using Union by rank heuristic
Return True if successful
Merge two disjoint sets
>>> A = DisjointSet([1, 1, 1])
>>> A.merge(1, 2)
True
>>> A.merge(0, 2)
True
>>> A.merge(0, 1)
False
"""
src_parent = self.get_parent(src)
dst_parent = self.get_parent(dst)
if src_parent == dst_parent:
return False
if self.ranks[dst_parent] >= self.ranks[src_parent]:
self.set_counts[dst_parent] += self.set_counts[src_parent]
self.set_counts[src_parent] = 0
self.parents[src_parent] = dst_parent
if self.ranks[dst_parent] == self.ranks[src_parent]:
self.ranks[dst_parent] += 1
joined_set_size = self.set_counts[dst_parent]
else:
self.set_counts[src_parent] += self.set_counts[dst_parent]
self.set_counts[dst_parent] = 0
self.parents[dst_parent] = src_parent
joined_set_size = self.set_counts[src_parent]
self.max_set = max(self.max_set, joined_set_size)
return True
def get_parent(self, disj_set: int) -> int:
"""
Find the Parent of a given set
>>> A = DisjointSet([1, 1, 1])
>>> A.merge(1, 2)
True
>>> A.get_parent(0)
0
>>> A.get_parent(1)
2
"""
if self.parents[disj_set] == disj_set:
return disj_set
self.parents[disj_set] = self.get_parent(self.parents[disj_set])
return self.parents[disj_set]
| """
Implements a disjoint set using Lists and some added heuristics for efficiency
Union by Rank Heuristic and Path Compression
"""
class DisjointSet:
def __init__(self, set_counts: list) -> None:
"""
Initialize with a list of the number of items in each set
and with rank = 1 for each set
"""
self.set_counts = set_counts
self.max_set = max(set_counts)
num_sets = len(set_counts)
self.ranks = [1] * num_sets
self.parents = list(range(num_sets))
def merge(self, src: int, dst: int) -> bool:
"""
Merge two sets together using Union by rank heuristic
Return True if successful
Merge two disjoint sets
>>> A = DisjointSet([1, 1, 1])
>>> A.merge(1, 2)
True
>>> A.merge(0, 2)
True
>>> A.merge(0, 1)
False
"""
src_parent = self.get_parent(src)
dst_parent = self.get_parent(dst)
if src_parent == dst_parent:
return False
if self.ranks[dst_parent] >= self.ranks[src_parent]:
self.set_counts[dst_parent] += self.set_counts[src_parent]
self.set_counts[src_parent] = 0
self.parents[src_parent] = dst_parent
if self.ranks[dst_parent] == self.ranks[src_parent]:
self.ranks[dst_parent] += 1
joined_set_size = self.set_counts[dst_parent]
else:
self.set_counts[src_parent] += self.set_counts[dst_parent]
self.set_counts[dst_parent] = 0
self.parents[dst_parent] = src_parent
joined_set_size = self.set_counts[src_parent]
self.max_set = max(self.max_set, joined_set_size)
return True
def get_parent(self, disj_set: int) -> int:
"""
Find the Parent of a given set
>>> A = DisjointSet([1, 1, 1])
>>> A.merge(1, 2)
True
>>> A.get_parent(0)
0
>>> A.get_parent(1)
2
"""
if self.parents[disj_set] == disj_set:
return disj_set
self.parents[disj_set] = self.get_parent(self.parents[disj_set])
return self.parents[disj_set]
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
https://en.wikipedia.org/wiki/Combination
"""
from math import factorial
def combinations(n: int, k: int) -> int:
"""
Returns the number of different combinations of k length which can
be made from n values, where n >= k.
Examples:
>>> combinations(10,5)
252
>>> combinations(6,3)
20
>>> combinations(20,5)
15504
>>> combinations(52, 5)
2598960
>>> combinations(0, 0)
1
>>> combinations(-4, -5)
...
Traceback (most recent call last):
ValueError: Please enter positive integers for n and k where n >= k
"""
# If either of the conditions are true, the function is being asked
# to calculate a factorial of a negative number, which is not possible
if n < k or k < 0:
raise ValueError("Please enter positive integers for n and k where n >= k")
return factorial(n) // (factorial(k) * factorial(n - k))
if __name__ == "__main__":
print(
"The number of five-card hands possible from a standard",
f"fifty-two card deck is: {combinations(52, 5)}\n",
)
print(
"If a class of 40 students must be arranged into groups of",
f"4 for group projects, there are {combinations(40, 4)} ways",
"to arrange them.\n",
)
print(
"If 10 teams are competing in a Formula One race, there",
f"are {combinations(10, 3)} ways that first, second and",
"third place can be awarded.",
)
| """
https://en.wikipedia.org/wiki/Combination
"""
from math import factorial
def combinations(n: int, k: int) -> int:
"""
Returns the number of different combinations of k length which can
be made from n values, where n >= k.
Examples:
>>> combinations(10,5)
252
>>> combinations(6,3)
20
>>> combinations(20,5)
15504
>>> combinations(52, 5)
2598960
>>> combinations(0, 0)
1
>>> combinations(-4, -5)
...
Traceback (most recent call last):
ValueError: Please enter positive integers for n and k where n >= k
"""
# If either of the conditions are true, the function is being asked
# to calculate a factorial of a negative number, which is not possible
if n < k or k < 0:
raise ValueError("Please enter positive integers for n and k where n >= k")
return factorial(n) // (factorial(k) * factorial(n - k))
if __name__ == "__main__":
print(
"The number of five-card hands possible from a standard",
f"fifty-two card deck is: {combinations(52, 5)}\n",
)
print(
"If a class of 40 students must be arranged into groups of",
f"4 for group projects, there are {combinations(40, 4)} ways",
"to arrange them.\n",
)
print(
"If 10 teams are competing in a Formula One race, there",
f"are {combinations(10, 3)} ways that first, second and",
"third place can be awarded.",
)
| -1 |
TheAlgorithms/Python | 7,945 | Raise error not string | ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-02T16:49:17Z" | "2022-11-06T14:54:44Z" | 51708530b6a46a5e53d12e750521a11c6bf5c986 | daa1c7529ac6491338adb81622d5041a4ba1f446 | Raise error not string. ### Describe your change:
Replaces string errors with raising exceptions
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| [pytest]
markers =
mat_ops: tests for matrix operations
| [pytest]
markers =
mat_ops: tests for matrix operations
| -1 |
TheAlgorithms/Python | 7,932 | refactor: Move pascals triange to maths/ | ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-01T07:28:48Z" | "2022-11-01T19:25:39Z" | 4e6c1c049dffdc984232fe1fce1e4791fc527d11 | f512b4d105b6f3188deced19761b6ed288378f0d | refactor: Move pascals triange to maths/. ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| name: "build"
on:
pull_request:
schedule:
- cron: "0 0 * * *" # Run everyday
jobs:
build:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- uses: actions/setup-python@v4
with:
python-version: 3.11
- uses: actions/cache@v3
with:
path: ~/.cache/pip
key: ${{ runner.os }}-pip-${{ hashFiles('requirements.txt') }}
- name: Install dependencies
run: |
python -m pip install --upgrade pip setuptools six wheel
python -m pip install pytest-cov -r requirements.txt
- name: Run tests
# See: #6591 for re-enabling tests on Python v3.11
run: pytest
--ignore=computer_vision/cnn_classification.py
--ignore=machine_learning/forecasting/run.py
--ignore=machine_learning/lstm/lstm_prediction.py
--ignore=quantum/
--ignore=project_euler/
--ignore=scripts/validate_solutions.py
--cov-report=term-missing:skip-covered
--cov=. .
- if: ${{ success() }}
run: scripts/build_directory_md.py 2>&1 | tee DIRECTORY.md
| name: "build"
on:
pull_request:
schedule:
- cron: "0 0 * * *" # Run everyday
jobs:
build:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- uses: actions/setup-python@v4
with:
python-version: 3.11
- uses: actions/cache@v3
with:
path: ~/.cache/pip
key: ${{ runner.os }}-pip-${{ hashFiles('requirements.txt') }}
- name: Install dependencies
run: |
python -m pip install --upgrade pip setuptools six wheel
python -m pip install pytest-cov -r requirements.txt
- name: Run tests
# See: #6591 for re-enabling tests on Python v3.11
run: pytest
--ignore=computer_vision/cnn_classification.py
--ignore=machine_learning/lstm/lstm_prediction.py
--ignore=quantum/
--ignore=project_euler/
--ignore=scripts/validate_solutions.py
--cov-report=term-missing:skip-covered
--cov=. .
- if: ${{ success() }}
run: scripts/build_directory_md.py 2>&1 | tee DIRECTORY.md
| 1 |
TheAlgorithms/Python | 7,932 | refactor: Move pascals triange to maths/ | ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-01T07:28:48Z" | "2022-11-01T19:25:39Z" | 4e6c1c049dffdc984232fe1fce1e4791fc527d11 | f512b4d105b6f3188deced19761b6ed288378f0d | refactor: Move pascals triange to maths/. ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # XGBoost Classifier Example
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def data_handling(data: dict) -> tuple:
# Split dataset into features and target
# data is features
"""
>>> data_handling(({'data':'[5.1, 3.5, 1.4, 0.2]','target':([0])}))
('[5.1, 3.5, 1.4, 0.2]', [0])
>>> data_handling(
... {'data': '[4.9, 3.0, 1.4, 0.2], [4.7, 3.2, 1.3, 0.2]', 'target': ([0, 0])}
... )
('[4.9, 3.0, 1.4, 0.2], [4.7, 3.2, 1.3, 0.2]', [0, 0])
"""
return (data["data"], data["target"])
def xgboost(features: np.ndarray, target: np.ndarray) -> XGBClassifier:
"""
>>> xgboost(np.array([[5.1, 3.6, 1.4, 0.2]]), np.array([0]))
XGBClassifier(base_score=0.5, booster='gbtree', callbacks=None,
colsample_bylevel=1, colsample_bynode=1, colsample_bytree=1,
early_stopping_rounds=None, enable_categorical=False,
eval_metric=None, gamma=0, gpu_id=-1, grow_policy='depthwise',
importance_type=None, interaction_constraints='',
learning_rate=0.300000012, max_bin=256, max_cat_to_onehot=4,
max_delta_step=0, max_depth=6, max_leaves=0, min_child_weight=1,
missing=nan, monotone_constraints='()', n_estimators=100,
n_jobs=0, num_parallel_tree=1, predictor='auto', random_state=0,
reg_alpha=0, reg_lambda=1, ...)
"""
classifier = XGBClassifier()
classifier.fit(features, target)
return classifier
def main() -> None:
"""
>>> main()
Url for the algorithm:
https://xgboost.readthedocs.io/en/stable/
Iris type dataset is used to demonstrate algorithm.
"""
# Load Iris dataset
iris = load_iris()
features, targets = data_handling(iris)
x_train, x_test, y_train, y_test = train_test_split(
features, targets, test_size=0.25
)
names = iris["target_names"]
# Create an XGBoost Classifier from the training data
xgboost_classifier = xgboost(x_train, y_train)
# Display the confusion matrix of the classifier with both training and test sets
ConfusionMatrixDisplay.from_estimator(
xgboost_classifier,
x_test,
y_test,
display_labels=names,
cmap="Blues",
normalize="true",
)
plt.title("Normalized Confusion Matrix - IRIS Dataset")
plt.show()
if __name__ == "__main__":
import doctest
doctest.testmod(verbose=True)
main()
| # XGBoost Classifier Example
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def data_handling(data: dict) -> tuple:
# Split dataset into features and target
# data is features
"""
>>> data_handling(({'data':'[5.1, 3.5, 1.4, 0.2]','target':([0])}))
('[5.1, 3.5, 1.4, 0.2]', [0])
>>> data_handling(
... {'data': '[4.9, 3.0, 1.4, 0.2], [4.7, 3.2, 1.3, 0.2]', 'target': ([0, 0])}
... )
('[4.9, 3.0, 1.4, 0.2], [4.7, 3.2, 1.3, 0.2]', [0, 0])
"""
return (data["data"], data["target"])
def xgboost(features: np.ndarray, target: np.ndarray) -> XGBClassifier:
"""
# THIS TEST IS BROKEN!! >>> xgboost(np.array([[5.1, 3.6, 1.4, 0.2]]), np.array([0]))
XGBClassifier(base_score=0.5, booster='gbtree', callbacks=None,
colsample_bylevel=1, colsample_bynode=1, colsample_bytree=1,
early_stopping_rounds=None, enable_categorical=False,
eval_metric=None, gamma=0, gpu_id=-1, grow_policy='depthwise',
importance_type=None, interaction_constraints='',
learning_rate=0.300000012, max_bin=256, max_cat_to_onehot=4,
max_delta_step=0, max_depth=6, max_leaves=0, min_child_weight=1,
missing=nan, monotone_constraints='()', n_estimators=100,
n_jobs=0, num_parallel_tree=1, predictor='auto', random_state=0,
reg_alpha=0, reg_lambda=1, ...)
"""
classifier = XGBClassifier()
classifier.fit(features, target)
return classifier
def main() -> None:
"""
>>> main()
Url for the algorithm:
https://xgboost.readthedocs.io/en/stable/
Iris type dataset is used to demonstrate algorithm.
"""
# Load Iris dataset
iris = load_iris()
features, targets = data_handling(iris)
x_train, x_test, y_train, y_test = train_test_split(
features, targets, test_size=0.25
)
names = iris["target_names"]
# Create an XGBoost Classifier from the training data
xgboost_classifier = xgboost(x_train, y_train)
# Display the confusion matrix of the classifier with both training and test sets
ConfusionMatrixDisplay.from_estimator(
xgboost_classifier,
x_test,
y_test,
display_labels=names,
cmap="Blues",
normalize="true",
)
plt.title("Normalized Confusion Matrix - IRIS Dataset")
plt.show()
if __name__ == "__main__":
import doctest
doctest.testmod(verbose=True)
main()
| 1 |
TheAlgorithms/Python | 7,932 | refactor: Move pascals triange to maths/ | ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-01T07:28:48Z" | "2022-11-01T19:25:39Z" | 4e6c1c049dffdc984232fe1fce1e4791fc527d11 | f512b4d105b6f3188deced19761b6ed288378f0d | refactor: Move pascals triange to maths/. ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| beautifulsoup4
fake_useragent
keras
lxml
matplotlib
numpy
opencv-python
pandas
pillow
projectq
qiskit; python_version < "3.11"
requests
rich
scikit-fuzzy
sklearn
statsmodels; python_version < "3.11"
sympy
tensorflow; python_version < "3.11"
texttable
tweepy
xgboost
yulewalker
| beautifulsoup4
cython>=0.29.28 # For statsmodels on Python 3.11
fake_useragent
keras
lxml
matplotlib
numpy
opencv-python
pandas
pillow
projectq
qiskit; python_version < "3.11"
requests
rich
scikit-fuzzy
sklearn
statsmodels
sympy
tensorflow; python_version < "3.11"
texttable
tweepy
xgboost
yulewalker
| 1 |
TheAlgorithms/Python | 7,932 | refactor: Move pascals triange to maths/ | ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-01T07:28:48Z" | "2022-11-01T19:25:39Z" | 4e6c1c049dffdc984232fe1fce1e4791fc527d11 | f512b4d105b6f3188deced19761b6ed288378f0d | refactor: Move pascals triange to maths/. ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
The convex hull problem is problem of finding all the vertices of convex polygon, P of
a set of points in a plane such that all the points are either on the vertices of P or
inside P. TH convex hull problem has several applications in geometrical problems,
computer graphics and game development.
Two algorithms have been implemented for the convex hull problem here.
1. A brute-force algorithm which runs in O(n^3)
2. A divide-and-conquer algorithm which runs in O(n log(n))
There are other several other algorithms for the convex hull problem
which have not been implemented here, yet.
"""
from __future__ import annotations
from collections.abc import Iterable
class Point:
"""
Defines a 2-d point for use by all convex-hull algorithms.
Parameters
----------
x: an int or a float, the x-coordinate of the 2-d point
y: an int or a float, the y-coordinate of the 2-d point
Examples
--------
>>> Point(1, 2)
(1.0, 2.0)
>>> Point("1", "2")
(1.0, 2.0)
>>> Point(1, 2) > Point(0, 1)
True
>>> Point(1, 1) == Point(1, 1)
True
>>> Point(-0.5, 1) == Point(0.5, 1)
False
>>> Point("pi", "e")
Traceback (most recent call last):
...
ValueError: could not convert string to float: 'pi'
"""
def __init__(self, x, y):
self.x, self.y = float(x), float(y)
def __eq__(self, other):
return self.x == other.x and self.y == other.y
def __ne__(self, other):
return not self == other
def __gt__(self, other):
if self.x > other.x:
return True
elif self.x == other.x:
return self.y > other.y
return False
def __lt__(self, other):
return not self > other
def __ge__(self, other):
if self.x > other.x:
return True
elif self.x == other.x:
return self.y >= other.y
return False
def __le__(self, other):
if self.x < other.x:
return True
elif self.x == other.x:
return self.y <= other.y
return False
def __repr__(self):
return f"({self.x}, {self.y})"
def __hash__(self):
return hash(self.x)
def _construct_points(
list_of_tuples: list[Point] | list[list[float]] | Iterable[list[float]],
) -> list[Point]:
"""
constructs a list of points from an array-like object of numbers
Arguments
---------
list_of_tuples: array-like object of type numbers. Acceptable types so far
are lists, tuples and sets.
Returns
--------
points: a list where each item is of type Point. This contains only objects
which can be converted into a Point.
Examples
-------
>>> _construct_points([[1, 1], [2, -1], [0.3, 4]])
[(1.0, 1.0), (2.0, -1.0), (0.3, 4.0)]
>>> _construct_points([1, 2])
Ignoring deformed point 1. All points must have at least 2 coordinates.
Ignoring deformed point 2. All points must have at least 2 coordinates.
[]
>>> _construct_points([])
[]
>>> _construct_points(None)
[]
"""
points: list[Point] = []
if list_of_tuples:
for p in list_of_tuples:
if isinstance(p, Point):
points.append(p)
else:
try:
points.append(Point(p[0], p[1]))
except (IndexError, TypeError):
print(
f"Ignoring deformed point {p}. All points"
" must have at least 2 coordinates."
)
return points
def _validate_input(points: list[Point] | list[list[float]]) -> list[Point]:
"""
validates an input instance before a convex-hull algorithms uses it
Parameters
---------
points: array-like, the 2d points to validate before using with
a convex-hull algorithm. The elements of points must be either lists, tuples or
Points.
Returns
-------
points: array_like, an iterable of all well-defined Points constructed passed in.
Exception
---------
ValueError: if points is empty or None, or if a wrong data structure like a scalar
is passed
TypeError: if an iterable but non-indexable object (eg. dictionary) is passed.
The exception to this a set which we'll convert to a list before using
Examples
-------
>>> _validate_input([[1, 2]])
[(1.0, 2.0)]
>>> _validate_input([(1, 2)])
[(1.0, 2.0)]
>>> _validate_input([Point(2, 1), Point(-1, 2)])
[(2.0, 1.0), (-1.0, 2.0)]
>>> _validate_input([])
Traceback (most recent call last):
...
ValueError: Expecting a list of points but got []
>>> _validate_input(1)
Traceback (most recent call last):
...
ValueError: Expecting an iterable object but got an non-iterable type 1
"""
if not hasattr(points, "__iter__"):
raise ValueError(
f"Expecting an iterable object but got an non-iterable type {points}"
)
if not points:
raise ValueError(f"Expecting a list of points but got {points}")
return _construct_points(points)
def _det(a: Point, b: Point, c: Point) -> float:
"""
Computes the sign perpendicular distance of a 2d point c from a line segment
ab. The sign indicates the direction of c relative to ab.
A Positive value means c is above ab (to the left), while a negative value
means c is below ab (to the right). 0 means all three points are on a straight line.
As a side note, 0.5 * abs|det| is the area of triangle abc
Parameters
----------
a: point, the point on the left end of line segment ab
b: point, the point on the right end of line segment ab
c: point, the point for which the direction and location is desired.
Returns
--------
det: float, abs(det) is the distance of c from ab. The sign
indicates which side of line segment ab c is. det is computed as
(a_xb_y + c_xa_y + b_xc_y) - (a_yb_x + c_ya_x + b_yc_x)
Examples
----------
>>> _det(Point(1, 1), Point(1, 2), Point(1, 5))
0.0
>>> _det(Point(0, 0), Point(10, 0), Point(0, 10))
100.0
>>> _det(Point(0, 0), Point(10, 0), Point(0, -10))
-100.0
"""
det = (a.x * b.y + b.x * c.y + c.x * a.y) - (a.y * b.x + b.y * c.x + c.y * a.x)
return det
def convex_hull_bf(points: list[Point]) -> list[Point]:
"""
Constructs the convex hull of a set of 2D points using a brute force algorithm.
The algorithm basically considers all combinations of points (i, j) and uses the
definition of convexity to determine whether (i, j) is part of the convex hull or
not. (i, j) is part of the convex hull if and only iff there are no points on both
sides of the line segment connecting the ij, and there is no point k such that k is
on either end of the ij.
Runtime: O(n^3) - definitely horrible
Parameters
---------
points: array-like of object of Points, lists or tuples.
The set of 2d points for which the convex-hull is needed
Returns
------
convex_set: list, the convex-hull of points sorted in non-decreasing order.
See Also
--------
convex_hull_recursive,
Examples
---------
>>> convex_hull_bf([[0, 0], [1, 0], [10, 1]])
[(0.0, 0.0), (1.0, 0.0), (10.0, 1.0)]
>>> convex_hull_bf([[0, 0], [1, 0], [10, 0]])
[(0.0, 0.0), (10.0, 0.0)]
>>> convex_hull_bf([[-1, 1],[-1, -1], [0, 0], [0.5, 0.5], [1, -1], [1, 1],
... [-0.75, 1]])
[(-1.0, -1.0), (-1.0, 1.0), (1.0, -1.0), (1.0, 1.0)]
>>> convex_hull_bf([(0, 3), (2, 2), (1, 1), (2, 1), (3, 0), (0, 0), (3, 3),
... (2, -1), (2, -4), (1, -3)])
[(0.0, 0.0), (0.0, 3.0), (1.0, -3.0), (2.0, -4.0), (3.0, 0.0), (3.0, 3.0)]
"""
points = sorted(_validate_input(points))
n = len(points)
convex_set = set()
for i in range(n - 1):
for j in range(i + 1, n):
points_left_of_ij = points_right_of_ij = False
ij_part_of_convex_hull = True
for k in range(n):
if k != i and k != j:
det_k = _det(points[i], points[j], points[k])
if det_k > 0:
points_left_of_ij = True
elif det_k < 0:
points_right_of_ij = True
else:
# point[i], point[j], point[k] all lie on a straight line
# if point[k] is to the left of point[i] or it's to the
# right of point[j], then point[i], point[j] cannot be
# part of the convex hull of A
if points[k] < points[i] or points[k] > points[j]:
ij_part_of_convex_hull = False
break
if points_left_of_ij and points_right_of_ij:
ij_part_of_convex_hull = False
break
if ij_part_of_convex_hull:
convex_set.update([points[i], points[j]])
return sorted(convex_set)
def convex_hull_recursive(points: list[Point]) -> list[Point]:
"""
Constructs the convex hull of a set of 2D points using a divide-and-conquer strategy
The algorithm exploits the geometric properties of the problem by repeatedly
partitioning the set of points into smaller hulls, and finding the convex hull of
these smaller hulls. The union of the convex hull from smaller hulls is the
solution to the convex hull of the larger problem.
Parameter
---------
points: array-like of object of Points, lists or tuples.
The set of 2d points for which the convex-hull is needed
Runtime: O(n log n)
Returns
-------
convex_set: list, the convex-hull of points sorted in non-decreasing order.
Examples
---------
>>> convex_hull_recursive([[0, 0], [1, 0], [10, 1]])
[(0.0, 0.0), (1.0, 0.0), (10.0, 1.0)]
>>> convex_hull_recursive([[0, 0], [1, 0], [10, 0]])
[(0.0, 0.0), (10.0, 0.0)]
>>> convex_hull_recursive([[-1, 1],[-1, -1], [0, 0], [0.5, 0.5], [1, -1], [1, 1],
... [-0.75, 1]])
[(-1.0, -1.0), (-1.0, 1.0), (1.0, -1.0), (1.0, 1.0)]
>>> convex_hull_recursive([(0, 3), (2, 2), (1, 1), (2, 1), (3, 0), (0, 0), (3, 3),
... (2, -1), (2, -4), (1, -3)])
[(0.0, 0.0), (0.0, 3.0), (1.0, -3.0), (2.0, -4.0), (3.0, 0.0), (3.0, 3.0)]
"""
points = sorted(_validate_input(points))
n = len(points)
# divide all the points into an upper hull and a lower hull
# the left most point and the right most point are definitely
# members of the convex hull by definition.
# use these two anchors to divide all the points into two hulls,
# an upper hull and a lower hull.
# all points to the left (above) the line joining the extreme points belong to the
# upper hull
# all points to the right (below) the line joining the extreme points below to the
# lower hull
# ignore all points on the line joining the extreme points since they cannot be
# part of the convex hull
left_most_point = points[0]
right_most_point = points[n - 1]
convex_set = {left_most_point, right_most_point}
upper_hull = []
lower_hull = []
for i in range(1, n - 1):
det = _det(left_most_point, right_most_point, points[i])
if det > 0:
upper_hull.append(points[i])
elif det < 0:
lower_hull.append(points[i])
_construct_hull(upper_hull, left_most_point, right_most_point, convex_set)
_construct_hull(lower_hull, right_most_point, left_most_point, convex_set)
return sorted(convex_set)
def _construct_hull(
points: list[Point], left: Point, right: Point, convex_set: set[Point]
) -> None:
"""
Parameters
---------
points: list or None, the hull of points from which to choose the next convex-hull
point
left: Point, the point to the left of line segment joining left and right
right: The point to the right of the line segment joining left and right
convex_set: set, the current convex-hull. The state of convex-set gets updated by
this function
Note
----
For the line segment 'ab', 'a' is on the left and 'b' on the right.
but the reverse is true for the line segment 'ba'.
Returns
-------
Nothing, only updates the state of convex-set
"""
if points:
extreme_point = None
extreme_point_distance = float("-inf")
candidate_points = []
for p in points:
det = _det(left, right, p)
if det > 0:
candidate_points.append(p)
if det > extreme_point_distance:
extreme_point_distance = det
extreme_point = p
if extreme_point:
_construct_hull(candidate_points, left, extreme_point, convex_set)
convex_set.add(extreme_point)
_construct_hull(candidate_points, extreme_point, right, convex_set)
def convex_hull_melkman(points: list[Point]) -> list[Point]:
"""
Constructs the convex hull of a set of 2D points using the melkman algorithm.
The algorithm works by iteratively inserting points of a simple polygonal chain
(meaning that no line segments between two consecutive points cross each other).
Sorting the points yields such a polygonal chain.
For a detailed description, see http://cgm.cs.mcgill.ca/~athens/cs601/Melkman.html
Runtime: O(n log n) - O(n) if points are already sorted in the input
Parameters
---------
points: array-like of object of Points, lists or tuples.
The set of 2d points for which the convex-hull is needed
Returns
------
convex_set: list, the convex-hull of points sorted in non-decreasing order.
See Also
--------
Examples
---------
>>> convex_hull_melkman([[0, 0], [1, 0], [10, 1]])
[(0.0, 0.0), (1.0, 0.0), (10.0, 1.0)]
>>> convex_hull_melkman([[0, 0], [1, 0], [10, 0]])
[(0.0, 0.0), (10.0, 0.0)]
>>> convex_hull_melkman([[-1, 1],[-1, -1], [0, 0], [0.5, 0.5], [1, -1], [1, 1],
... [-0.75, 1]])
[(-1.0, -1.0), (-1.0, 1.0), (1.0, -1.0), (1.0, 1.0)]
>>> convex_hull_melkman([(0, 3), (2, 2), (1, 1), (2, 1), (3, 0), (0, 0), (3, 3),
... (2, -1), (2, -4), (1, -3)])
[(0.0, 0.0), (0.0, 3.0), (1.0, -3.0), (2.0, -4.0), (3.0, 0.0), (3.0, 3.0)]
"""
points = sorted(_validate_input(points))
n = len(points)
convex_hull = points[:2]
for i in range(2, n):
det = _det(convex_hull[1], convex_hull[0], points[i])
if det > 0:
convex_hull.insert(0, points[i])
break
elif det < 0:
convex_hull.append(points[i])
break
else:
convex_hull[1] = points[i]
i += 1
for j in range(i, n):
if (
_det(convex_hull[0], convex_hull[-1], points[j]) > 0
and _det(convex_hull[-1], convex_hull[0], points[1]) < 0
):
# The point lies within the convex hull
continue
convex_hull.insert(0, points[j])
convex_hull.append(points[j])
while _det(convex_hull[0], convex_hull[1], convex_hull[2]) >= 0:
del convex_hull[1]
while _det(convex_hull[-1], convex_hull[-2], convex_hull[-3]) <= 0:
del convex_hull[-2]
# `convex_hull` is contains the convex hull in circular order
return sorted(convex_hull[1:] if len(convex_hull) > 3 else convex_hull)
def main():
points = [
(0, 3),
(2, 2),
(1, 1),
(2, 1),
(3, 0),
(0, 0),
(3, 3),
(2, -1),
(2, -4),
(1, -3),
]
# the convex set of points is
# [(0, 0), (0, 3), (1, -3), (2, -4), (3, 0), (3, 3)]
results_bf = convex_hull_bf(points)
results_recursive = convex_hull_recursive(points)
assert results_bf == results_recursive
results_melkman = convex_hull_melkman(points)
assert results_bf == results_melkman
print(results_bf)
if __name__ == "__main__":
main()
| """
The convex hull problem is problem of finding all the vertices of convex polygon, P of
a set of points in a plane such that all the points are either on the vertices of P or
inside P. TH convex hull problem has several applications in geometrical problems,
computer graphics and game development.
Two algorithms have been implemented for the convex hull problem here.
1. A brute-force algorithm which runs in O(n^3)
2. A divide-and-conquer algorithm which runs in O(n log(n))
There are other several other algorithms for the convex hull problem
which have not been implemented here, yet.
"""
from __future__ import annotations
from collections.abc import Iterable
class Point:
"""
Defines a 2-d point for use by all convex-hull algorithms.
Parameters
----------
x: an int or a float, the x-coordinate of the 2-d point
y: an int or a float, the y-coordinate of the 2-d point
Examples
--------
>>> Point(1, 2)
(1.0, 2.0)
>>> Point("1", "2")
(1.0, 2.0)
>>> Point(1, 2) > Point(0, 1)
True
>>> Point(1, 1) == Point(1, 1)
True
>>> Point(-0.5, 1) == Point(0.5, 1)
False
>>> Point("pi", "e")
Traceback (most recent call last):
...
ValueError: could not convert string to float: 'pi'
"""
def __init__(self, x, y):
self.x, self.y = float(x), float(y)
def __eq__(self, other):
return self.x == other.x and self.y == other.y
def __ne__(self, other):
return not self == other
def __gt__(self, other):
if self.x > other.x:
return True
elif self.x == other.x:
return self.y > other.y
return False
def __lt__(self, other):
return not self > other
def __ge__(self, other):
if self.x > other.x:
return True
elif self.x == other.x:
return self.y >= other.y
return False
def __le__(self, other):
if self.x < other.x:
return True
elif self.x == other.x:
return self.y <= other.y
return False
def __repr__(self):
return f"({self.x}, {self.y})"
def __hash__(self):
return hash(self.x)
def _construct_points(
list_of_tuples: list[Point] | list[list[float]] | Iterable[list[float]],
) -> list[Point]:
"""
constructs a list of points from an array-like object of numbers
Arguments
---------
list_of_tuples: array-like object of type numbers. Acceptable types so far
are lists, tuples and sets.
Returns
--------
points: a list where each item is of type Point. This contains only objects
which can be converted into a Point.
Examples
-------
>>> _construct_points([[1, 1], [2, -1], [0.3, 4]])
[(1.0, 1.0), (2.0, -1.0), (0.3, 4.0)]
>>> _construct_points([1, 2])
Ignoring deformed point 1. All points must have at least 2 coordinates.
Ignoring deformed point 2. All points must have at least 2 coordinates.
[]
>>> _construct_points([])
[]
>>> _construct_points(None)
[]
"""
points: list[Point] = []
if list_of_tuples:
for p in list_of_tuples:
if isinstance(p, Point):
points.append(p)
else:
try:
points.append(Point(p[0], p[1]))
except (IndexError, TypeError):
print(
f"Ignoring deformed point {p}. All points"
" must have at least 2 coordinates."
)
return points
def _validate_input(points: list[Point] | list[list[float]]) -> list[Point]:
"""
validates an input instance before a convex-hull algorithms uses it
Parameters
---------
points: array-like, the 2d points to validate before using with
a convex-hull algorithm. The elements of points must be either lists, tuples or
Points.
Returns
-------
points: array_like, an iterable of all well-defined Points constructed passed in.
Exception
---------
ValueError: if points is empty or None, or if a wrong data structure like a scalar
is passed
TypeError: if an iterable but non-indexable object (eg. dictionary) is passed.
The exception to this a set which we'll convert to a list before using
Examples
-------
>>> _validate_input([[1, 2]])
[(1.0, 2.0)]
>>> _validate_input([(1, 2)])
[(1.0, 2.0)]
>>> _validate_input([Point(2, 1), Point(-1, 2)])
[(2.0, 1.0), (-1.0, 2.0)]
>>> _validate_input([])
Traceback (most recent call last):
...
ValueError: Expecting a list of points but got []
>>> _validate_input(1)
Traceback (most recent call last):
...
ValueError: Expecting an iterable object but got an non-iterable type 1
"""
if not hasattr(points, "__iter__"):
raise ValueError(
f"Expecting an iterable object but got an non-iterable type {points}"
)
if not points:
raise ValueError(f"Expecting a list of points but got {points}")
return _construct_points(points)
def _det(a: Point, b: Point, c: Point) -> float:
"""
Computes the sign perpendicular distance of a 2d point c from a line segment
ab. The sign indicates the direction of c relative to ab.
A Positive value means c is above ab (to the left), while a negative value
means c is below ab (to the right). 0 means all three points are on a straight line.
As a side note, 0.5 * abs|det| is the area of triangle abc
Parameters
----------
a: point, the point on the left end of line segment ab
b: point, the point on the right end of line segment ab
c: point, the point for which the direction and location is desired.
Returns
--------
det: float, abs(det) is the distance of c from ab. The sign
indicates which side of line segment ab c is. det is computed as
(a_xb_y + c_xa_y + b_xc_y) - (a_yb_x + c_ya_x + b_yc_x)
Examples
----------
>>> _det(Point(1, 1), Point(1, 2), Point(1, 5))
0.0
>>> _det(Point(0, 0), Point(10, 0), Point(0, 10))
100.0
>>> _det(Point(0, 0), Point(10, 0), Point(0, -10))
-100.0
"""
det = (a.x * b.y + b.x * c.y + c.x * a.y) - (a.y * b.x + b.y * c.x + c.y * a.x)
return det
def convex_hull_bf(points: list[Point]) -> list[Point]:
"""
Constructs the convex hull of a set of 2D points using a brute force algorithm.
The algorithm basically considers all combinations of points (i, j) and uses the
definition of convexity to determine whether (i, j) is part of the convex hull or
not. (i, j) is part of the convex hull if and only iff there are no points on both
sides of the line segment connecting the ij, and there is no point k such that k is
on either end of the ij.
Runtime: O(n^3) - definitely horrible
Parameters
---------
points: array-like of object of Points, lists or tuples.
The set of 2d points for which the convex-hull is needed
Returns
------
convex_set: list, the convex-hull of points sorted in non-decreasing order.
See Also
--------
convex_hull_recursive,
Examples
---------
>>> convex_hull_bf([[0, 0], [1, 0], [10, 1]])
[(0.0, 0.0), (1.0, 0.0), (10.0, 1.0)]
>>> convex_hull_bf([[0, 0], [1, 0], [10, 0]])
[(0.0, 0.0), (10.0, 0.0)]
>>> convex_hull_bf([[-1, 1],[-1, -1], [0, 0], [0.5, 0.5], [1, -1], [1, 1],
... [-0.75, 1]])
[(-1.0, -1.0), (-1.0, 1.0), (1.0, -1.0), (1.0, 1.0)]
>>> convex_hull_bf([(0, 3), (2, 2), (1, 1), (2, 1), (3, 0), (0, 0), (3, 3),
... (2, -1), (2, -4), (1, -3)])
[(0.0, 0.0), (0.0, 3.0), (1.0, -3.0), (2.0, -4.0), (3.0, 0.0), (3.0, 3.0)]
"""
points = sorted(_validate_input(points))
n = len(points)
convex_set = set()
for i in range(n - 1):
for j in range(i + 1, n):
points_left_of_ij = points_right_of_ij = False
ij_part_of_convex_hull = True
for k in range(n):
if k != i and k != j:
det_k = _det(points[i], points[j], points[k])
if det_k > 0:
points_left_of_ij = True
elif det_k < 0:
points_right_of_ij = True
else:
# point[i], point[j], point[k] all lie on a straight line
# if point[k] is to the left of point[i] or it's to the
# right of point[j], then point[i], point[j] cannot be
# part of the convex hull of A
if points[k] < points[i] or points[k] > points[j]:
ij_part_of_convex_hull = False
break
if points_left_of_ij and points_right_of_ij:
ij_part_of_convex_hull = False
break
if ij_part_of_convex_hull:
convex_set.update([points[i], points[j]])
return sorted(convex_set)
def convex_hull_recursive(points: list[Point]) -> list[Point]:
"""
Constructs the convex hull of a set of 2D points using a divide-and-conquer strategy
The algorithm exploits the geometric properties of the problem by repeatedly
partitioning the set of points into smaller hulls, and finding the convex hull of
these smaller hulls. The union of the convex hull from smaller hulls is the
solution to the convex hull of the larger problem.
Parameter
---------
points: array-like of object of Points, lists or tuples.
The set of 2d points for which the convex-hull is needed
Runtime: O(n log n)
Returns
-------
convex_set: list, the convex-hull of points sorted in non-decreasing order.
Examples
---------
>>> convex_hull_recursive([[0, 0], [1, 0], [10, 1]])
[(0.0, 0.0), (1.0, 0.0), (10.0, 1.0)]
>>> convex_hull_recursive([[0, 0], [1, 0], [10, 0]])
[(0.0, 0.0), (10.0, 0.0)]
>>> convex_hull_recursive([[-1, 1],[-1, -1], [0, 0], [0.5, 0.5], [1, -1], [1, 1],
... [-0.75, 1]])
[(-1.0, -1.0), (-1.0, 1.0), (1.0, -1.0), (1.0, 1.0)]
>>> convex_hull_recursive([(0, 3), (2, 2), (1, 1), (2, 1), (3, 0), (0, 0), (3, 3),
... (2, -1), (2, -4), (1, -3)])
[(0.0, 0.0), (0.0, 3.0), (1.0, -3.0), (2.0, -4.0), (3.0, 0.0), (3.0, 3.0)]
"""
points = sorted(_validate_input(points))
n = len(points)
# divide all the points into an upper hull and a lower hull
# the left most point and the right most point are definitely
# members of the convex hull by definition.
# use these two anchors to divide all the points into two hulls,
# an upper hull and a lower hull.
# all points to the left (above) the line joining the extreme points belong to the
# upper hull
# all points to the right (below) the line joining the extreme points below to the
# lower hull
# ignore all points on the line joining the extreme points since they cannot be
# part of the convex hull
left_most_point = points[0]
right_most_point = points[n - 1]
convex_set = {left_most_point, right_most_point}
upper_hull = []
lower_hull = []
for i in range(1, n - 1):
det = _det(left_most_point, right_most_point, points[i])
if det > 0:
upper_hull.append(points[i])
elif det < 0:
lower_hull.append(points[i])
_construct_hull(upper_hull, left_most_point, right_most_point, convex_set)
_construct_hull(lower_hull, right_most_point, left_most_point, convex_set)
return sorted(convex_set)
def _construct_hull(
points: list[Point], left: Point, right: Point, convex_set: set[Point]
) -> None:
"""
Parameters
---------
points: list or None, the hull of points from which to choose the next convex-hull
point
left: Point, the point to the left of line segment joining left and right
right: The point to the right of the line segment joining left and right
convex_set: set, the current convex-hull. The state of convex-set gets updated by
this function
Note
----
For the line segment 'ab', 'a' is on the left and 'b' on the right.
but the reverse is true for the line segment 'ba'.
Returns
-------
Nothing, only updates the state of convex-set
"""
if points:
extreme_point = None
extreme_point_distance = float("-inf")
candidate_points = []
for p in points:
det = _det(left, right, p)
if det > 0:
candidate_points.append(p)
if det > extreme_point_distance:
extreme_point_distance = det
extreme_point = p
if extreme_point:
_construct_hull(candidate_points, left, extreme_point, convex_set)
convex_set.add(extreme_point)
_construct_hull(candidate_points, extreme_point, right, convex_set)
def convex_hull_melkman(points: list[Point]) -> list[Point]:
"""
Constructs the convex hull of a set of 2D points using the melkman algorithm.
The algorithm works by iteratively inserting points of a simple polygonal chain
(meaning that no line segments between two consecutive points cross each other).
Sorting the points yields such a polygonal chain.
For a detailed description, see http://cgm.cs.mcgill.ca/~athens/cs601/Melkman.html
Runtime: O(n log n) - O(n) if points are already sorted in the input
Parameters
---------
points: array-like of object of Points, lists or tuples.
The set of 2d points for which the convex-hull is needed
Returns
------
convex_set: list, the convex-hull of points sorted in non-decreasing order.
See Also
--------
Examples
---------
>>> convex_hull_melkman([[0, 0], [1, 0], [10, 1]])
[(0.0, 0.0), (1.0, 0.0), (10.0, 1.0)]
>>> convex_hull_melkman([[0, 0], [1, 0], [10, 0]])
[(0.0, 0.0), (10.0, 0.0)]
>>> convex_hull_melkman([[-1, 1],[-1, -1], [0, 0], [0.5, 0.5], [1, -1], [1, 1],
... [-0.75, 1]])
[(-1.0, -1.0), (-1.0, 1.0), (1.0, -1.0), (1.0, 1.0)]
>>> convex_hull_melkman([(0, 3), (2, 2), (1, 1), (2, 1), (3, 0), (0, 0), (3, 3),
... (2, -1), (2, -4), (1, -3)])
[(0.0, 0.0), (0.0, 3.0), (1.0, -3.0), (2.0, -4.0), (3.0, 0.0), (3.0, 3.0)]
"""
points = sorted(_validate_input(points))
n = len(points)
convex_hull = points[:2]
for i in range(2, n):
det = _det(convex_hull[1], convex_hull[0], points[i])
if det > 0:
convex_hull.insert(0, points[i])
break
elif det < 0:
convex_hull.append(points[i])
break
else:
convex_hull[1] = points[i]
i += 1
for j in range(i, n):
if (
_det(convex_hull[0], convex_hull[-1], points[j]) > 0
and _det(convex_hull[-1], convex_hull[0], points[1]) < 0
):
# The point lies within the convex hull
continue
convex_hull.insert(0, points[j])
convex_hull.append(points[j])
while _det(convex_hull[0], convex_hull[1], convex_hull[2]) >= 0:
del convex_hull[1]
while _det(convex_hull[-1], convex_hull[-2], convex_hull[-3]) <= 0:
del convex_hull[-2]
# `convex_hull` is contains the convex hull in circular order
return sorted(convex_hull[1:] if len(convex_hull) > 3 else convex_hull)
def main():
points = [
(0, 3),
(2, 2),
(1, 1),
(2, 1),
(3, 0),
(0, 0),
(3, 3),
(2, -1),
(2, -4),
(1, -3),
]
# the convex set of points is
# [(0, 0), (0, 3), (1, -3), (2, -4), (3, 0), (3, 3)]
results_bf = convex_hull_bf(points)
results_recursive = convex_hull_recursive(points)
assert results_bf == results_recursive
results_melkman = convex_hull_melkman(points)
assert results_bf == results_melkman
print(results_bf)
if __name__ == "__main__":
main()
| -1 |
TheAlgorithms/Python | 7,932 | refactor: Move pascals triange to maths/ | ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-01T07:28:48Z" | "2022-11-01T19:25:39Z" | 4e6c1c049dffdc984232fe1fce1e4791fc527d11 | f512b4d105b6f3188deced19761b6ed288378f0d | refactor: Move pascals triange to maths/. ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| def get_word_pattern(word: str) -> str:
"""
>>> get_word_pattern("pattern")
'0.1.2.2.3.4.5'
>>> get_word_pattern("word pattern")
'0.1.2.3.4.5.6.7.7.8.2.9'
>>> get_word_pattern("get word pattern")
'0.1.2.3.4.5.6.7.3.8.9.2.2.1.6.10'
"""
word = word.upper()
next_num = 0
letter_nums = {}
word_pattern = []
for letter in word:
if letter not in letter_nums:
letter_nums[letter] = str(next_num)
next_num += 1
word_pattern.append(letter_nums[letter])
return ".".join(word_pattern)
if __name__ == "__main__":
import pprint
import time
start_time = time.time()
with open("dictionary.txt") as in_file:
word_list = in_file.read().splitlines()
all_patterns: dict = {}
for word in word_list:
pattern = get_word_pattern(word)
if pattern in all_patterns:
all_patterns[pattern].append(word)
else:
all_patterns[pattern] = [word]
with open("word_patterns.txt", "w") as out_file:
out_file.write(pprint.pformat(all_patterns))
total_time = round(time.time() - start_time, 2)
print(f"Done! {len(all_patterns):,} word patterns found in {total_time} seconds.")
# Done! 9,581 word patterns found in 0.58 seconds.
| def get_word_pattern(word: str) -> str:
"""
>>> get_word_pattern("pattern")
'0.1.2.2.3.4.5'
>>> get_word_pattern("word pattern")
'0.1.2.3.4.5.6.7.7.8.2.9'
>>> get_word_pattern("get word pattern")
'0.1.2.3.4.5.6.7.3.8.9.2.2.1.6.10'
"""
word = word.upper()
next_num = 0
letter_nums = {}
word_pattern = []
for letter in word:
if letter not in letter_nums:
letter_nums[letter] = str(next_num)
next_num += 1
word_pattern.append(letter_nums[letter])
return ".".join(word_pattern)
if __name__ == "__main__":
import pprint
import time
start_time = time.time()
with open("dictionary.txt") as in_file:
word_list = in_file.read().splitlines()
all_patterns: dict = {}
for word in word_list:
pattern = get_word_pattern(word)
if pattern in all_patterns:
all_patterns[pattern].append(word)
else:
all_patterns[pattern] = [word]
with open("word_patterns.txt", "w") as out_file:
out_file.write(pprint.pformat(all_patterns))
total_time = round(time.time() - start_time, 2)
print(f"Done! {len(all_patterns):,} word patterns found in {total_time} seconds.")
# Done! 9,581 word patterns found in 0.58 seconds.
| -1 |
TheAlgorithms/Python | 7,932 | refactor: Move pascals triange to maths/ | ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-01T07:28:48Z" | "2022-11-01T19:25:39Z" | 4e6c1c049dffdc984232fe1fce1e4791fc527d11 | f512b4d105b6f3188deced19761b6ed288378f0d | refactor: Move pascals triange to maths/. ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
https://en.wikipedia.org/wiki/Strongly_connected_component
Finding strongly connected components in directed graph
"""
test_graph_1 = {0: [2, 3], 1: [0], 2: [1], 3: [4], 4: []}
test_graph_2 = {0: [1, 2, 3], 1: [2], 2: [0], 3: [4], 4: [5], 5: [3]}
def topology_sort(
graph: dict[int, list[int]], vert: int, visited: list[bool]
) -> list[int]:
"""
Use depth first search to sort graph
At this time graph is the same as input
>>> topology_sort(test_graph_1, 0, 5 * [False])
[1, 2, 4, 3, 0]
>>> topology_sort(test_graph_2, 0, 6 * [False])
[2, 1, 5, 4, 3, 0]
"""
visited[vert] = True
order = []
for neighbour in graph[vert]:
if not visited[neighbour]:
order += topology_sort(graph, neighbour, visited)
order.append(vert)
return order
def find_components(
reversed_graph: dict[int, list[int]], vert: int, visited: list[bool]
) -> list[int]:
"""
Use depth first search to find strongliy connected
vertices. Now graph is reversed
>>> find_components({0: [1], 1: [2], 2: [0]}, 0, 5 * [False])
[0, 1, 2]
>>> find_components({0: [2], 1: [0], 2: [0, 1]}, 0, 6 * [False])
[0, 2, 1]
"""
visited[vert] = True
component = [vert]
for neighbour in reversed_graph[vert]:
if not visited[neighbour]:
component += find_components(reversed_graph, neighbour, visited)
return component
def strongly_connected_components(graph: dict[int, list[int]]) -> list[list[int]]:
"""
This function takes graph as a parameter
and then returns the list of strongly connected components
>>> strongly_connected_components(test_graph_1)
[[0, 1, 2], [3], [4]]
>>> strongly_connected_components(test_graph_2)
[[0, 2, 1], [3, 5, 4]]
"""
visited = len(graph) * [False]
reversed_graph: dict[int, list[int]] = {vert: [] for vert in range(len(graph))}
for vert, neighbours in graph.items():
for neighbour in neighbours:
reversed_graph[neighbour].append(vert)
order = []
for i, was_visited in enumerate(visited):
if not was_visited:
order += topology_sort(graph, i, visited)
components_list = []
visited = len(graph) * [False]
for i in range(len(graph)):
vert = order[len(graph) - i - 1]
if not visited[vert]:
component = find_components(reversed_graph, vert, visited)
components_list.append(component)
return components_list
| """
https://en.wikipedia.org/wiki/Strongly_connected_component
Finding strongly connected components in directed graph
"""
test_graph_1 = {0: [2, 3], 1: [0], 2: [1], 3: [4], 4: []}
test_graph_2 = {0: [1, 2, 3], 1: [2], 2: [0], 3: [4], 4: [5], 5: [3]}
def topology_sort(
graph: dict[int, list[int]], vert: int, visited: list[bool]
) -> list[int]:
"""
Use depth first search to sort graph
At this time graph is the same as input
>>> topology_sort(test_graph_1, 0, 5 * [False])
[1, 2, 4, 3, 0]
>>> topology_sort(test_graph_2, 0, 6 * [False])
[2, 1, 5, 4, 3, 0]
"""
visited[vert] = True
order = []
for neighbour in graph[vert]:
if not visited[neighbour]:
order += topology_sort(graph, neighbour, visited)
order.append(vert)
return order
def find_components(
reversed_graph: dict[int, list[int]], vert: int, visited: list[bool]
) -> list[int]:
"""
Use depth first search to find strongliy connected
vertices. Now graph is reversed
>>> find_components({0: [1], 1: [2], 2: [0]}, 0, 5 * [False])
[0, 1, 2]
>>> find_components({0: [2], 1: [0], 2: [0, 1]}, 0, 6 * [False])
[0, 2, 1]
"""
visited[vert] = True
component = [vert]
for neighbour in reversed_graph[vert]:
if not visited[neighbour]:
component += find_components(reversed_graph, neighbour, visited)
return component
def strongly_connected_components(graph: dict[int, list[int]]) -> list[list[int]]:
"""
This function takes graph as a parameter
and then returns the list of strongly connected components
>>> strongly_connected_components(test_graph_1)
[[0, 1, 2], [3], [4]]
>>> strongly_connected_components(test_graph_2)
[[0, 2, 1], [3, 5, 4]]
"""
visited = len(graph) * [False]
reversed_graph: dict[int, list[int]] = {vert: [] for vert in range(len(graph))}
for vert, neighbours in graph.items():
for neighbour in neighbours:
reversed_graph[neighbour].append(vert)
order = []
for i, was_visited in enumerate(visited):
if not was_visited:
order += topology_sort(graph, i, visited)
components_list = []
visited = len(graph) * [False]
for i in range(len(graph)):
vert = order[len(graph) - i - 1]
if not visited[vert]:
component = find_components(reversed_graph, vert, visited)
components_list.append(component)
return components_list
| -1 |
TheAlgorithms/Python | 7,932 | refactor: Move pascals triange to maths/ | ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-01T07:28:48Z" | "2022-11-01T19:25:39Z" | 4e6c1c049dffdc984232fe1fce1e4791fc527d11 | f512b4d105b6f3188deced19761b6ed288378f0d | refactor: Move pascals triange to maths/. ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # https://www.tutorialspoint.com/python3/bitwise_operators_example.htm
def binary_xor(a: int, b: int) -> str:
"""
Take in 2 integers, convert them to binary,
return a binary number that is the
result of a binary xor operation on the integers provided.
>>> binary_xor(25, 32)
'0b111001'
>>> binary_xor(37, 50)
'0b010111'
>>> binary_xor(21, 30)
'0b01011'
>>> binary_xor(58, 73)
'0b1110011'
>>> binary_xor(0, 255)
'0b11111111'
>>> binary_xor(256, 256)
'0b000000000'
>>> binary_xor(0, -1)
Traceback (most recent call last):
...
ValueError: the value of both inputs must be positive
>>> binary_xor(0, 1.1)
Traceback (most recent call last):
...
TypeError: 'float' object cannot be interpreted as an integer
>>> binary_xor("0", "1")
Traceback (most recent call last):
...
TypeError: '<' not supported between instances of 'str' and 'int'
"""
if a < 0 or b < 0:
raise ValueError("the value of both inputs must be positive")
a_binary = str(bin(a))[2:] # remove the leading "0b"
b_binary = str(bin(b))[2:] # remove the leading "0b"
max_len = max(len(a_binary), len(b_binary))
return "0b" + "".join(
str(int(char_a != char_b))
for char_a, char_b in zip(a_binary.zfill(max_len), b_binary.zfill(max_len))
)
if __name__ == "__main__":
import doctest
doctest.testmod()
| # https://www.tutorialspoint.com/python3/bitwise_operators_example.htm
def binary_xor(a: int, b: int) -> str:
"""
Take in 2 integers, convert them to binary,
return a binary number that is the
result of a binary xor operation on the integers provided.
>>> binary_xor(25, 32)
'0b111001'
>>> binary_xor(37, 50)
'0b010111'
>>> binary_xor(21, 30)
'0b01011'
>>> binary_xor(58, 73)
'0b1110011'
>>> binary_xor(0, 255)
'0b11111111'
>>> binary_xor(256, 256)
'0b000000000'
>>> binary_xor(0, -1)
Traceback (most recent call last):
...
ValueError: the value of both inputs must be positive
>>> binary_xor(0, 1.1)
Traceback (most recent call last):
...
TypeError: 'float' object cannot be interpreted as an integer
>>> binary_xor("0", "1")
Traceback (most recent call last):
...
TypeError: '<' not supported between instances of 'str' and 'int'
"""
if a < 0 or b < 0:
raise ValueError("the value of both inputs must be positive")
a_binary = str(bin(a))[2:] # remove the leading "0b"
b_binary = str(bin(b))[2:] # remove the leading "0b"
max_len = max(len(a_binary), len(b_binary))
return "0b" + "".join(
str(int(char_a != char_b))
for char_a, char_b in zip(a_binary.zfill(max_len), b_binary.zfill(max_len))
)
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,932 | refactor: Move pascals triange to maths/ | ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-01T07:28:48Z" | "2022-11-01T19:25:39Z" | 4e6c1c049dffdc984232fe1fce1e4791fc527d11 | f512b4d105b6f3188deced19761b6ed288378f0d | refactor: Move pascals triange to maths/. ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| from __future__ import annotations
def n31(a: int) -> tuple[list[int], int]:
"""
Returns the Collatz sequence and its length of any positive integer.
>>> n31(4)
([4, 2, 1], 3)
"""
if not isinstance(a, int):
raise TypeError(f"Must be int, not {type(a).__name__}")
if a < 1:
raise ValueError(f"Given integer must be greater than 1, not {a}")
path = [a]
while a != 1:
if a % 2 == 0:
a = a // 2
else:
a = 3 * a + 1
path += [a]
return path, len(path)
def test_n31():
"""
>>> test_n31()
"""
assert n31(4) == ([4, 2, 1], 3)
assert n31(11) == ([11, 34, 17, 52, 26, 13, 40, 20, 10, 5, 16, 8, 4, 2, 1], 15)
assert n31(31) == (
[
31,
94,
47,
142,
71,
214,
107,
322,
161,
484,
242,
121,
364,
182,
91,
274,
137,
412,
206,
103,
310,
155,
466,
233,
700,
350,
175,
526,
263,
790,
395,
1186,
593,
1780,
890,
445,
1336,
668,
334,
167,
502,
251,
754,
377,
1132,
566,
283,
850,
425,
1276,
638,
319,
958,
479,
1438,
719,
2158,
1079,
3238,
1619,
4858,
2429,
7288,
3644,
1822,
911,
2734,
1367,
4102,
2051,
6154,
3077,
9232,
4616,
2308,
1154,
577,
1732,
866,
433,
1300,
650,
325,
976,
488,
244,
122,
61,
184,
92,
46,
23,
70,
35,
106,
53,
160,
80,
40,
20,
10,
5,
16,
8,
4,
2,
1,
],
107,
)
if __name__ == "__main__":
num = 4
path, length = n31(num)
print(f"The Collatz sequence of {num} took {length} steps. \nPath: {path}")
| from __future__ import annotations
def n31(a: int) -> tuple[list[int], int]:
"""
Returns the Collatz sequence and its length of any positive integer.
>>> n31(4)
([4, 2, 1], 3)
"""
if not isinstance(a, int):
raise TypeError(f"Must be int, not {type(a).__name__}")
if a < 1:
raise ValueError(f"Given integer must be greater than 1, not {a}")
path = [a]
while a != 1:
if a % 2 == 0:
a = a // 2
else:
a = 3 * a + 1
path += [a]
return path, len(path)
def test_n31():
"""
>>> test_n31()
"""
assert n31(4) == ([4, 2, 1], 3)
assert n31(11) == ([11, 34, 17, 52, 26, 13, 40, 20, 10, 5, 16, 8, 4, 2, 1], 15)
assert n31(31) == (
[
31,
94,
47,
142,
71,
214,
107,
322,
161,
484,
242,
121,
364,
182,
91,
274,
137,
412,
206,
103,
310,
155,
466,
233,
700,
350,
175,
526,
263,
790,
395,
1186,
593,
1780,
890,
445,
1336,
668,
334,
167,
502,
251,
754,
377,
1132,
566,
283,
850,
425,
1276,
638,
319,
958,
479,
1438,
719,
2158,
1079,
3238,
1619,
4858,
2429,
7288,
3644,
1822,
911,
2734,
1367,
4102,
2051,
6154,
3077,
9232,
4616,
2308,
1154,
577,
1732,
866,
433,
1300,
650,
325,
976,
488,
244,
122,
61,
184,
92,
46,
23,
70,
35,
106,
53,
160,
80,
40,
20,
10,
5,
16,
8,
4,
2,
1,
],
107,
)
if __name__ == "__main__":
num = 4
path, length = n31(num)
print(f"The Collatz sequence of {num} took {length} steps. \nPath: {path}")
| -1 |
TheAlgorithms/Python | 7,932 | refactor: Move pascals triange to maths/ | ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-01T07:28:48Z" | "2022-11-01T19:25:39Z" | 4e6c1c049dffdc984232fe1fce1e4791fc527d11 | f512b4d105b6f3188deced19761b6ed288378f0d | refactor: Move pascals triange to maths/. ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,932 | refactor: Move pascals triange to maths/ | ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-01T07:28:48Z" | "2022-11-01T19:25:39Z" | 4e6c1c049dffdc984232fe1fce1e4791fc527d11 | f512b4d105b6f3188deced19761b6ed288378f0d | refactor: Move pascals triange to maths/. ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,932 | refactor: Move pascals triange to maths/ | ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-01T07:28:48Z" | "2022-11-01T19:25:39Z" | 4e6c1c049dffdc984232fe1fce1e4791fc527d11 | f512b4d105b6f3188deced19761b6ed288378f0d | refactor: Move pascals triange to maths/. ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # Created by sarathkaul on 17/11/19
# Modified by Arkadip Bhattacharya(@darkmatter18) on 20/04/2020
from collections import defaultdict
from typing import DefaultDict
def word_occurrence(sentence: str) -> dict:
"""
>>> from collections import Counter
>>> SENTENCE = "a b A b c b d b d e f e g e h e i e j e 0"
>>> occurence_dict = word_occurrence(SENTENCE)
>>> all(occurence_dict[word] == count for word, count
... in Counter(SENTENCE.split()).items())
True
>>> dict(word_occurrence("Two spaces"))
{'Two': 1, 'spaces': 1}
"""
occurrence: DefaultDict[str, int] = defaultdict(int)
# Creating a dictionary containing count of each word
for word in sentence.split():
occurrence[word] += 1
return occurrence
if __name__ == "__main__":
for word, count in word_occurrence("INPUT STRING").items():
print(f"{word}: {count}")
| # Created by sarathkaul on 17/11/19
# Modified by Arkadip Bhattacharya(@darkmatter18) on 20/04/2020
from collections import defaultdict
from typing import DefaultDict
def word_occurrence(sentence: str) -> dict:
"""
>>> from collections import Counter
>>> SENTENCE = "a b A b c b d b d e f e g e h e i e j e 0"
>>> occurence_dict = word_occurrence(SENTENCE)
>>> all(occurence_dict[word] == count for word, count
... in Counter(SENTENCE.split()).items())
True
>>> dict(word_occurrence("Two spaces"))
{'Two': 1, 'spaces': 1}
"""
occurrence: DefaultDict[str, int] = defaultdict(int)
# Creating a dictionary containing count of each word
for word in sentence.split():
occurrence[word] += 1
return occurrence
if __name__ == "__main__":
for word, count in word_occurrence("INPUT STRING").items():
print(f"{word}: {count}")
| -1 |
TheAlgorithms/Python | 7,932 | refactor: Move pascals triange to maths/ | ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-01T07:28:48Z" | "2022-11-01T19:25:39Z" | 4e6c1c049dffdc984232fe1fce1e4791fc527d11 | f512b4d105b6f3188deced19761b6ed288378f0d | refactor: Move pascals triange to maths/. ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| from __future__ import annotations
END = "#"
class Trie:
def __init__(self) -> None:
self._trie: dict = {}
def insert_word(self, text: str) -> None:
trie = self._trie
for char in text:
if char not in trie:
trie[char] = {}
trie = trie[char]
trie[END] = True
def find_word(self, prefix: str) -> tuple | list:
trie = self._trie
for char in prefix:
if char in trie:
trie = trie[char]
else:
return []
return self._elements(trie)
def _elements(self, d: dict) -> tuple:
result = []
for c, v in d.items():
if c == END:
sub_result = [" "]
else:
sub_result = [c + s for s in self._elements(v)]
result.extend(sub_result)
return tuple(result)
trie = Trie()
words = ("depart", "detergent", "daring", "dog", "deer", "deal")
for word in words:
trie.insert_word(word)
def autocomplete_using_trie(string: str) -> tuple:
"""
>>> trie = Trie()
>>> for word in words:
... trie.insert_word(word)
...
>>> matches = autocomplete_using_trie("de")
>>> "detergent " in matches
True
>>> "dog " in matches
False
"""
suffixes = trie.find_word(string)
return tuple(string + word for word in suffixes)
def main() -> None:
print(autocomplete_using_trie("de"))
if __name__ == "__main__":
import doctest
doctest.testmod()
main()
| from __future__ import annotations
END = "#"
class Trie:
def __init__(self) -> None:
self._trie: dict = {}
def insert_word(self, text: str) -> None:
trie = self._trie
for char in text:
if char not in trie:
trie[char] = {}
trie = trie[char]
trie[END] = True
def find_word(self, prefix: str) -> tuple | list:
trie = self._trie
for char in prefix:
if char in trie:
trie = trie[char]
else:
return []
return self._elements(trie)
def _elements(self, d: dict) -> tuple:
result = []
for c, v in d.items():
if c == END:
sub_result = [" "]
else:
sub_result = [c + s for s in self._elements(v)]
result.extend(sub_result)
return tuple(result)
trie = Trie()
words = ("depart", "detergent", "daring", "dog", "deer", "deal")
for word in words:
trie.insert_word(word)
def autocomplete_using_trie(string: str) -> tuple:
"""
>>> trie = Trie()
>>> for word in words:
... trie.insert_word(word)
...
>>> matches = autocomplete_using_trie("de")
>>> "detergent " in matches
True
>>> "dog " in matches
False
"""
suffixes = trie.find_word(string)
return tuple(string + word for word in suffixes)
def main() -> None:
print(autocomplete_using_trie("de"))
if __name__ == "__main__":
import doctest
doctest.testmod()
main()
| -1 |
TheAlgorithms/Python | 7,932 | refactor: Move pascals triange to maths/ | ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-01T07:28:48Z" | "2022-11-01T19:25:39Z" | 4e6c1c049dffdc984232fe1fce1e4791fc527d11 | f512b4d105b6f3188deced19761b6ed288378f0d | refactor: Move pascals triange to maths/. ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| #!/usr/bin/env python3
"""
Build a half-adder quantum circuit that takes two bits as input,
encodes them into qubits, then runs the half-adder circuit calculating
the sum and carry qubits, observed over 1000 runs of the experiment
.
References:
https://en.wikipedia.org/wiki/Adder_(electronics)
https://qiskit.org/textbook/ch-states/atoms-computation.html#4.2-Remembering-how-to-add-
"""
import qiskit
def half_adder(bit0: int, bit1: int) -> qiskit.result.counts.Counts:
"""
>>> half_adder(0, 0)
{'00': 1000}
>>> half_adder(0, 1)
{'01': 1000}
>>> half_adder(1, 0)
{'01': 1000}
>>> half_adder(1, 1)
{'10': 1000}
"""
# Use Aer's simulator
simulator = qiskit.Aer.get_backend("aer_simulator")
qc_ha = qiskit.QuantumCircuit(4, 2)
# encode inputs in qubits 0 and 1
if bit0 == 1:
qc_ha.x(0)
if bit1 == 1:
qc_ha.x(1)
qc_ha.barrier()
# use cnots to write XOR of the inputs on qubit2
qc_ha.cx(0, 2)
qc_ha.cx(1, 2)
# use ccx / toffoli gate to write AND of the inputs on qubit3
qc_ha.ccx(0, 1, 3)
qc_ha.barrier()
# extract outputs
qc_ha.measure(2, 0) # extract XOR value
qc_ha.measure(3, 1) # extract AND value
# Execute the circuit on the qasm simulator
job = qiskit.execute(qc_ha, simulator, shots=1000)
# Return the histogram data of the results of the experiment
return job.result().get_counts(qc_ha)
if __name__ == "__main__":
counts = half_adder(1, 1)
print(f"Half Adder Output Qubit Counts: {counts}")
| #!/usr/bin/env python3
"""
Build a half-adder quantum circuit that takes two bits as input,
encodes them into qubits, then runs the half-adder circuit calculating
the sum and carry qubits, observed over 1000 runs of the experiment
.
References:
https://en.wikipedia.org/wiki/Adder_(electronics)
https://qiskit.org/textbook/ch-states/atoms-computation.html#4.2-Remembering-how-to-add-
"""
import qiskit
def half_adder(bit0: int, bit1: int) -> qiskit.result.counts.Counts:
"""
>>> half_adder(0, 0)
{'00': 1000}
>>> half_adder(0, 1)
{'01': 1000}
>>> half_adder(1, 0)
{'01': 1000}
>>> half_adder(1, 1)
{'10': 1000}
"""
# Use Aer's simulator
simulator = qiskit.Aer.get_backend("aer_simulator")
qc_ha = qiskit.QuantumCircuit(4, 2)
# encode inputs in qubits 0 and 1
if bit0 == 1:
qc_ha.x(0)
if bit1 == 1:
qc_ha.x(1)
qc_ha.barrier()
# use cnots to write XOR of the inputs on qubit2
qc_ha.cx(0, 2)
qc_ha.cx(1, 2)
# use ccx / toffoli gate to write AND of the inputs on qubit3
qc_ha.ccx(0, 1, 3)
qc_ha.barrier()
# extract outputs
qc_ha.measure(2, 0) # extract XOR value
qc_ha.measure(3, 1) # extract AND value
# Execute the circuit on the qasm simulator
job = qiskit.execute(qc_ha, simulator, shots=1000)
# Return the histogram data of the results of the experiment
return job.result().get_counts(qc_ha)
if __name__ == "__main__":
counts = half_adder(1, 1)
print(f"Half Adder Output Qubit Counts: {counts}")
| -1 |
TheAlgorithms/Python | 7,932 | refactor: Move pascals triange to maths/ | ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-01T07:28:48Z" | "2022-11-01T19:25:39Z" | 4e6c1c049dffdc984232fe1fce1e4791fc527d11 | f512b4d105b6f3188deced19761b6ed288378f0d | refactor: Move pascals triange to maths/. ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
https://projecteuler.net/problem=51
Prime digit replacements
Problem 51
By replacing the 1st digit of the 2-digit number *3, it turns out that six of
the nine possible values: 13, 23, 43, 53, 73, and 83, are all prime.
By replacing the 3rd and 4th digits of 56**3 with the same digit, this 5-digit
number is the first example having seven primes among the ten generated numbers,
yielding the family: 56003, 56113, 56333, 56443, 56663, 56773, and 56993.
Consequently 56003, being the first member of this family, is the smallest prime
with this property.
Find the smallest prime which, by replacing part of the number (not necessarily
adjacent digits) with the same digit, is part of an eight prime value family.
"""
from __future__ import annotations
from collections import Counter
def prime_sieve(n: int) -> list[int]:
"""
Sieve of Erotosthenes
Function to return all the prime numbers up to a certain number
https://en.wikipedia.org/wiki/Sieve_of_Eratosthenes
>>> prime_sieve(3)
[2]
>>> prime_sieve(50)
[2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47]
"""
is_prime = [True] * n
is_prime[0] = False
is_prime[1] = False
is_prime[2] = True
for i in range(3, int(n**0.5 + 1), 2):
index = i * 2
while index < n:
is_prime[index] = False
index = index + i
primes = [2]
for i in range(3, n, 2):
if is_prime[i]:
primes.append(i)
return primes
def digit_replacements(number: int) -> list[list[int]]:
"""
Returns all the possible families of digit replacements in a number which
contains at least one repeating digit
>>> digit_replacements(544)
[[500, 511, 522, 533, 544, 555, 566, 577, 588, 599]]
>>> digit_replacements(3112)
[[3002, 3112, 3222, 3332, 3442, 3552, 3662, 3772, 3882, 3992]]
"""
number_str = str(number)
replacements = []
digits = ["0", "1", "2", "3", "4", "5", "6", "7", "8", "9"]
for duplicate in Counter(number_str) - Counter(set(number_str)):
family = [int(number_str.replace(duplicate, digit)) for digit in digits]
replacements.append(family)
return replacements
def solution(family_length: int = 8) -> int:
"""
Returns the solution of the problem
>>> solution(2)
229399
>>> solution(3)
221311
"""
numbers_checked = set()
# Filter primes with less than 3 replaceable digits
primes = {
x for x in set(prime_sieve(1_000_000)) if len(str(x)) - len(set(str(x))) >= 3
}
for prime in primes:
if prime in numbers_checked:
continue
replacements = digit_replacements(prime)
for family in replacements:
numbers_checked.update(family)
primes_in_family = primes.intersection(family)
if len(primes_in_family) != family_length:
continue
return min(primes_in_family)
return -1
if __name__ == "__main__":
print(solution())
| """
https://projecteuler.net/problem=51
Prime digit replacements
Problem 51
By replacing the 1st digit of the 2-digit number *3, it turns out that six of
the nine possible values: 13, 23, 43, 53, 73, and 83, are all prime.
By replacing the 3rd and 4th digits of 56**3 with the same digit, this 5-digit
number is the first example having seven primes among the ten generated numbers,
yielding the family: 56003, 56113, 56333, 56443, 56663, 56773, and 56993.
Consequently 56003, being the first member of this family, is the smallest prime
with this property.
Find the smallest prime which, by replacing part of the number (not necessarily
adjacent digits) with the same digit, is part of an eight prime value family.
"""
from __future__ import annotations
from collections import Counter
def prime_sieve(n: int) -> list[int]:
"""
Sieve of Erotosthenes
Function to return all the prime numbers up to a certain number
https://en.wikipedia.org/wiki/Sieve_of_Eratosthenes
>>> prime_sieve(3)
[2]
>>> prime_sieve(50)
[2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47]
"""
is_prime = [True] * n
is_prime[0] = False
is_prime[1] = False
is_prime[2] = True
for i in range(3, int(n**0.5 + 1), 2):
index = i * 2
while index < n:
is_prime[index] = False
index = index + i
primes = [2]
for i in range(3, n, 2):
if is_prime[i]:
primes.append(i)
return primes
def digit_replacements(number: int) -> list[list[int]]:
"""
Returns all the possible families of digit replacements in a number which
contains at least one repeating digit
>>> digit_replacements(544)
[[500, 511, 522, 533, 544, 555, 566, 577, 588, 599]]
>>> digit_replacements(3112)
[[3002, 3112, 3222, 3332, 3442, 3552, 3662, 3772, 3882, 3992]]
"""
number_str = str(number)
replacements = []
digits = ["0", "1", "2", "3", "4", "5", "6", "7", "8", "9"]
for duplicate in Counter(number_str) - Counter(set(number_str)):
family = [int(number_str.replace(duplicate, digit)) for digit in digits]
replacements.append(family)
return replacements
def solution(family_length: int = 8) -> int:
"""
Returns the solution of the problem
>>> solution(2)
229399
>>> solution(3)
221311
"""
numbers_checked = set()
# Filter primes with less than 3 replaceable digits
primes = {
x for x in set(prime_sieve(1_000_000)) if len(str(x)) - len(set(str(x))) >= 3
}
for prime in primes:
if prime in numbers_checked:
continue
replacements = digit_replacements(prime)
for family in replacements:
numbers_checked.update(family)
primes_in_family = primes.intersection(family)
if len(primes_in_family) != family_length:
continue
return min(primes_in_family)
return -1
if __name__ == "__main__":
print(solution())
| -1 |
TheAlgorithms/Python | 7,932 | refactor: Move pascals triange to maths/ | ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-11-01T07:28:48Z" | "2022-11-01T19:25:39Z" | 4e6c1c049dffdc984232fe1fce1e4791fc527d11 | f512b4d105b6f3188deced19761b6ed288378f0d | refactor: Move pascals triange to maths/. ### Describe your change:
Moves the pascal triangle from `other/` to `maths/` because it is very much math related and should 100% be there, next to `perfect_cube`, `perfect_number`, etc
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| import bs4
import requests
def get_movie_data_from_soup(soup: bs4.element.ResultSet) -> dict[str, str]:
return {
"name": soup.h3.a.text,
"genre": soup.find("span", class_="genre").text.strip(),
"rating": soup.strong.text,
"page_link": f"https://www.imdb.com{soup.a.get('href')}",
}
def get_imdb_top_movies(num_movies: int = 5) -> tuple:
"""Get the top num_movies most highly rated movies from IMDB and
return a tuple of dicts describing each movie's name, genre, rating, and URL.
Args:
num_movies: The number of movies to get. Defaults to 5.
Returns:
A list of tuples containing information about the top n movies.
>>> len(get_imdb_top_movies(5))
5
>>> len(get_imdb_top_movies(-3))
0
>>> len(get_imdb_top_movies(4.99999))
4
"""
num_movies = int(float(num_movies))
if num_movies < 1:
return ()
base_url = (
"https://www.imdb.com/search/title?title_type="
f"feature&sort=num_votes,desc&count={num_movies}"
)
source = bs4.BeautifulSoup(requests.get(base_url).content, "html.parser")
return tuple(
get_movie_data_from_soup(movie)
for movie in source.find_all("div", class_="lister-item mode-advanced")
)
if __name__ == "__main__":
import json
num_movies = int(input("How many movies would you like to see? "))
print(
", ".join(
json.dumps(movie, indent=4) for movie in get_imdb_top_movies(num_movies)
)
)
| import bs4
import requests
def get_movie_data_from_soup(soup: bs4.element.ResultSet) -> dict[str, str]:
return {
"name": soup.h3.a.text,
"genre": soup.find("span", class_="genre").text.strip(),
"rating": soup.strong.text,
"page_link": f"https://www.imdb.com{soup.a.get('href')}",
}
def get_imdb_top_movies(num_movies: int = 5) -> tuple:
"""Get the top num_movies most highly rated movies from IMDB and
return a tuple of dicts describing each movie's name, genre, rating, and URL.
Args:
num_movies: The number of movies to get. Defaults to 5.
Returns:
A list of tuples containing information about the top n movies.
>>> len(get_imdb_top_movies(5))
5
>>> len(get_imdb_top_movies(-3))
0
>>> len(get_imdb_top_movies(4.99999))
4
"""
num_movies = int(float(num_movies))
if num_movies < 1:
return ()
base_url = (
"https://www.imdb.com/search/title?title_type="
f"feature&sort=num_votes,desc&count={num_movies}"
)
source = bs4.BeautifulSoup(requests.get(base_url).content, "html.parser")
return tuple(
get_movie_data_from_soup(movie)
for movie in source.find_all("div", class_="lister-item mode-advanced")
)
if __name__ == "__main__":
import json
num_movies = int(input("How many movies would you like to see? "))
print(
", ".join(
json.dumps(movie, indent=4) for movie in get_imdb_top_movies(num_movies)
)
)
| -1 |
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