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e172c4d221cb93b78fdf15d990b35e7e7e7fd500 | 48894ae68f0234e263d325470178d67ab313c73e | /scripts/noc-wf.py | 9a461df838cfb1119d145697b6241de9a1a2e87f | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | permissive | DreamerDDL/noc | 7f949f55bb2c02c15ac2cc46bc62d957aee43a86 | 2ab0ab7718bb7116da2c3953efd466757e11d9ce | refs/heads/master | 2021-05-10T18:22:53.678588 | 2015-06-29T12:28:20 | 2015-06-29T12:28:20 | 118,628,133 | 0 | 0 | null | 2018-01-23T15:19:51 | 2018-01-23T15:19:51 | null | UTF-8 | Python | false | false | 663 | py | #!./bin/python
# -*- coding: utf-8 -*-
##----------------------------------------------------------------------
## noc-wf daemon
##----------------------------------------------------------------------
## Copyright (C) 2007-2011 The NOC Project
## See LICENSE for details
##----------------------------------------------------------------------
if __name__ == "__main__":
from noc.wf.wf.daemon import WFDaemon
from noc.lib.debug import error_report
from noc.main.models import CustomField
CustomField.install_fields()
try:
WFDaemon().process_command()
except SystemExit:
pass
except Exception:
error_report()
| [
"[email protected]"
] | |
d8d41ae91224bf4537d44f0b7ab5700facdbe029 | 7be65d5792bcb270673c7b0279fecdb82ba6bbac | /server-minimal.py | 1c382f34cb22e9ec4ccd08d567e31896a03d0792 | [] | no_license | niko9797/make_opcua | 63dcb6796a5ded50015b8c03cf2a19189c564d3b | eff4fd2c124699d6519022c29ced3a962d0beb09 | refs/heads/master | 2021-01-24T03:52:46.148866 | 2018-02-26T13:52:23 | 2018-02-26T13:52:23 | 122,910,789 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 960 | py | import sys
sys.path.insert(0, "..")
import time
from opcua import ua, Server
if __name__ == "__main__":
# setup our server
server = Server()
server.set_endpoint("opc.tcp://localhost:4841/freeopcua/server/")
# setup our own namespace, not really necessary but should as spec
uri = "http://examples.freeopcua.github.io"
idx = server.register_namespace(uri)
# get Objects node, this is where we should put our nodes
objects = server.get_objects_node()
# populating our address space
myobj = objects.add_object(idx, "MyObject")
myvar = myobj.add_variable(idx, "MyVariable", 6.7)
myvar.set_writable() # Set MyVariable to be writable by clients
# starting!
server.start()
try:
count = 0
while True:
time.sleep(1)
count += 0.1
myvar.set_value(count)
finally:
#close connection, remove subcsriptions, etc
server.stop()
| [
"[email protected]"
] | |
2b5ac8164f91997e6ead1e624f33df2c4683565b | 6eb957a3690c3c758feb84725ccccded529bd50b | /POO/Seccion.py | 196a144aef94039a3d3bb6103a9c122167d4855a | [] | no_license | MRpintoM/Ejercicio_3Py | 38b8c13a8946cf57f47bd3c341dbc4504c709766 | 5e90e36e43632b5bf8c9560805d329bedf3bdeac | refs/heads/master | 2023-03-08T01:37:18.861742 | 2021-02-23T02:19:42 | 2021-02-23T02:19:42 | 341,399,662 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 164 | py | class Seccion():
def registerSeccion(self):
__seccion=input("Ingresa una sección:")
__regseccion= (str(__seccion))
return __regseccion
| [
"[email protected]"
] | |
31640ba88e52306b8f9a5469864d401ce4d992e4 | f101fe75892da8d7b5258d22bd31534d47f39ec1 | /feature.py | 039980b31ea2d443121913c748e60ed024f11554 | [] | no_license | xianjunxia/Acoustic-event-detection-with-feature-space-attention-based-convolution-recurrent-neural-network | 2ae9d4d0148f5082cc6739f753bf750e1940ecfb | d2a7b36700e798e0da02d3efebb27cd340235f36 | refs/heads/master | 2020-03-22T17:11:53.028900 | 2018-07-10T05:15:32 | 2018-07-10T05:15:32 | 140,379,734 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 8,150 | py | import wave
import numpy as np
import utils
#import librosa
from IPython import embed
import os
from sklearn import preprocessing
import scipy.io as sio
def load_audio(filename, mono=True, fs=44100):
file_base, file_extension = os.path.splitext(filename)
if file_extension == '.wav':
_audio_file = wave.open(filename)
# Audio info
sample_rate = _audio_file.getframerate()
sample_width = _audio_file.getsampwidth()
number_of_channels = _audio_file.getnchannels()
number_of_frames = _audio_file.getnframes()
# Read raw bytes
data = _audio_file.readframes(number_of_frames)
_audio_file.close()
# Convert bytes based on sample_width
num_samples, remainder = divmod(len(data), sample_width * number_of_channels)
if remainder > 0:
raise ValueError('The length of data is not a multiple of sample size * number of channels.')
if sample_width > 4:
raise ValueError('Sample size cannot be bigger than 4 bytes.')
if sample_width == 3:
# 24 bit audio
a = np.empty((num_samples, number_of_channels, 4), dtype=np.uint8)
raw_bytes = np.fromstring(data, dtype=np.uint8)
a[:, :, :sample_width] = raw_bytes.reshape(-1, number_of_channels, sample_width)
a[:, :, sample_width:] = (a[:, :, sample_width - 1:sample_width] >> 7) * 255
audio_data = a.view('<i4').reshape(a.shape[:-1]).T
else:
# 8 bit samples are stored as unsigned ints; others as signed ints.
dt_char = 'u' if sample_width == 1 else 'i'
a = np.fromstring(data, dtype='<%s%d' % (dt_char, sample_width))
audio_data = a.reshape(-1, number_of_channels).T
if mono:
# Down-mix audio
audio_data = np.mean(audio_data, axis=0)
# Convert int values into float
audio_data = audio_data / float(2 ** (sample_width * 8 - 1) + 1)
# Resample
if fs != sample_rate:
audio_data = librosa.core.resample(audio_data, sample_rate, fs)
sample_rate = fs
return audio_data, sample_rate
return None, None
def load_desc_file(_desc_file):
_desc_dict = dict()
cnt = 1
for line in open(_desc_file):
#print(cnt)
cnt = cnt + 1
words = line.strip().split('\t')
name = words[0].split('/')[-1]
if name not in _desc_dict:
_desc_dict[name] = list()
_desc_dict[name].append([float(words[2]), float(words[3]), __class_labels[words[-1]]])
return _desc_dict
def extract_mbe(_y, _sr, _nfft, _nb_mel):
spec, n_fft = librosa.core.spectrum._spectrogram(y=_y, n_fft=_nfft, hop_length=_nfft/2, power=1)
'''
import matplotlib.pyplot as plot
print(y.shape)
plot.subplot(411)
Pxx, freqs, bins, im = plot.specgram(y, NFFT=_nfft, Fs=44100, noverlap=_nfft/2)
print('freqs_{}'.format(freqs))
print(freqs.shape)
print(spec.shape)
plot.subplot(412)
mel_basis = librosa.filters.mel(sr=_sr, n_fft=_nfft, n_mels=_nb_mel)
print(mel_basis.shape)
import scipy.io as sio
sio.savemat("/data/users/21799506/Data/DCASE2017_Data/Evaluation/feat/Melbank",{'arr_0':mel_basis})
plot.plot(mel_basis[:,500])
plot.subplot(413)
plot.plot(mel_basis[1,:])
plot.subplot(414)
mbe = np.log(np.dot(mel_basis, spec))
print(mbe.shape)
plot.plot(np.log(np.dot(mel_basis, spec)))
plot.show()
exit()
'''
mel_basis = librosa.filters.mel(sr=_sr, n_fft=_nfft, n_mels=_nb_mel)
return np.log(np.dot(mel_basis, spec))
# ###################################################################
# Main script starts here
# ###################################################################
is_mono = True
__class_labels = {
'brakes squeaking': 0,
'car': 1,
'children': 2,
'large vehicle': 3,
'people speaking': 4,
'people walking': 5
}
# location of data.
#folds_list = [1, 2, 3, 4]
folds_list = [0]
evaluation_setup_folder = '/data/users/21799506/Data/DCASE2017_Data/Evaluation/evaluation_setup/'
audio_folder = '/data/users/21799506/Data/DCASE2017_Data/Evaluation/audio/'
# Output
feat_folder = '/data/users/21799506/Data/DCASE2017_Data/Evaluation/feat/'
utils.create_folder(feat_folder)
# User set parameters
nfft = 2048
win_len = nfft
hop_len = win_len / 2
nb_mel_bands = 40
sr = 44100
# -----------------------------------------------------------------------
# Feature extraction and label generation
# -----------------------------------------------------------------------
# Load labels
train_file = os.path.join(evaluation_setup_folder, 'street_fold{}_train.txt'.format(0))
evaluate_file = os.path.join(evaluation_setup_folder, 'street_fold{}_evaluate.txt'.format(0))
print(train_file)
desc_dict = load_desc_file(train_file)
desc_dict.update(load_desc_file(evaluate_file)) # contains labels for all the audio in the dataset
'''
# Extract features for all audio files, and save it along with labels
for audio_filename in os.listdir(audio_folder):
audio_file = os.path.join(audio_folder, audio_filename)
print('Extracting features and label for : {}'.format(audio_file))
y, sr = load_audio(audio_file, mono=is_mono, fs=sr)
mbe = None
if is_mono:
mbe = extract_mbe(y, sr, nfft, nb_mel_bands).T
else:
for ch in range(y.shape[0]):
mbe_ch = extract_mbe(y[ch, :], sr, nfft, nb_mel_bands).T
if mbe is None:
mbe = mbe_ch
else:
mbe = np.concatenate((mbe, mbe_ch), 1)
label = np.zeros((mbe.shape[0], len(__class_labels)))
tmp_data = np.array(desc_dict[audio_filename])
frame_start = np.floor(tmp_data[:, 0] * sr / hop_len).astype(int)
frame_end = np.ceil(tmp_data[:, 1] * sr / hop_len).astype(int)
se_class = tmp_data[:, 2].astype(int)
for ind, val in enumerate(se_class):
label[frame_start[ind]:frame_end[ind], val] = 1
tmp_feat_file = os.path.join(feat_folder, '{}_{}.npz'.format(audio_filename, 'mon' if is_mono else 'bin'))
np.savez(tmp_feat_file, mbe, label)
'''
# -----------------------------------------------------------------------
# Feature Normalization
# -----------------------------------------------------------------------
for fold in folds_list:
train_file = os.path.join(evaluation_setup_folder, 'street_fold{}_train.txt'.format(0))
evaluate_file = os.path.join(evaluation_setup_folder, 'street_fold{}_evaluate.txt'.format(0))
train_dict = load_desc_file(train_file)
test_dict = load_desc_file(evaluate_file)
X_train, Y_train, X_test, Y_test = None, None, None, None
for key in train_dict.keys():
tmp_feat_file = os.path.join(feat_folder, '{}_{}.npz'.format(key, 'mon' if is_mono else 'bin'))
dmp = np.load(tmp_feat_file)
tmp_mbe, tmp_label = dmp['arr_0'], dmp['arr_1']
if X_train is None:
X_train, Y_train = tmp_mbe, tmp_label
else:
X_train, Y_train = np.concatenate((X_train, tmp_mbe), 0), np.concatenate((Y_train, tmp_label), 0)
for key in test_dict.keys():
tmp_feat_file = os.path.join(feat_folder, '{}_{}.npz'.format(key, 'mon' if is_mono else 'bin'))
dmp = np.load(tmp_feat_file)
tmp_mbe, tmp_label = dmp['arr_0'], dmp['arr_1']
if X_test is None:
X_test, Y_test = tmp_mbe, tmp_label
else:
X_test, Y_test = np.concatenate((X_test, tmp_mbe), 0), np.concatenate((Y_test, tmp_label), 0)
# Normalize the training data, and scale the testing data using the training data weights
scaler = preprocessing.StandardScaler()
X_train = scaler.fit_transform(X_train)
X_test = scaler.transform(X_test)
normalized_feat_file = os.path.join(feat_folder, 'mbe_{}_fold{}_GAN_allthreeclass.npz'.format('mon' if is_mono else 'bin', fold))
np.savez(normalized_feat_file, X_train, Y_train, X_test, Y_test)
print(X_train.shape)
print('normalized_feat_file : {}'.format(normalized_feat_file))
| [
"[email protected]"
] | |
44856c368483e969256dc97c44a426028c3bbf50 | 980841fc87bba9a00d849f372528b888453b89ba | /Python 3 Scripting for System Administrators/Accepting Simple Positional Arguments.py | 20e611ada99bb5acedb5953be31816bf9a56f018 | [] | no_license | Frijke1978/LinuxAcademy | c682eedb48ed637ffe28a55cdfbc7d33ba635779 | 5100f96b5ba56063042ced3b2737057016caaff3 | refs/heads/master | 2022-03-24T12:28:25.413483 | 2019-12-21T12:27:02 | 2019-12-21T12:27:02 | 229,418,319 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 2,205 | py | Accepting Simple Positional Arguments
Most of the scripts and utilities that we work with accept positional arguments instead of prompting us for information after we’ve run the command. The simplest way for us to do this in Python is to use the sys module’s argv attribute. Let’s try this out by writing a small script that echoes our first argument back to us:
~/bin/param_echo
#!/usr/bin/env python3.6
import sys
print(f"First argument {sys.argv[0]}")
After we make this executable and give it a shot, we see that the first argument is the script itself:
$ chmod u+x ~/bin/param_echo
$ param_echo testing
First argument /home/user/bin/param_echo
That’s not quite what we wanted, but now we know that argv will contain the script and we’ll need to get the index of 1 for our first argument. Let’s adjust our script to echo all of the arguments except the script name and then echo the first positional argument by itself:
~/bin/param_echo
#!/usr/bin/env python3.6
import sys
print(f"Positional arguments: {sys.argv[1:]}")
print(f"First argument: {sys.argv[1]}")
Trying the same command again, we get a much different result:
$ param_echo testing
Positional arguments: ['testing']
First argument: testing
$ param_echo testing testing12 'another argument'
Positional arguments: ['testing', 'testing12', 'another argument']
First argument: testing
$ param_echo
Positional arguments: []
Traceback (most recent call last):
File "/home/user/bin/param_echo", line 6, in
print(f"First argument: {sys.argv[1]}")
IndexError: list index out of range
This shows us a few things about working with argv:
Positional arguments are based on spaces unless we explicitly wrap the argument in quotes.
We can get a slice of the first index and after without worrying about it being empty.
We risk an IndexError if we assume that there will be an argument for a specific position and one isn’t given.
Using sys.argv is the simplest way to allow our scripts to accept positional arguments. In the next video, we’ll explore a standard library package that will allow us to provide a more robust command line experience with help text, named arguments, and flags. | [
"[email protected]"
] | |
d3905ca9265658e5bf4b7a91a378ed0ea340b520 | ac5e52a3fc52dde58d208746cddabef2e378119e | /exps-gsn-edf/gsn-edf_ut=3.0_rd=1_rw=0.04_rn=4_u=0.075-0.35_p=harmonic-2/sched=RUN_trial=82/sched.py | 304905f0cc9f12230fa3ed58eca351b59ad910a9 | [] | no_license | ricardobtxr/experiment-scripts | 1e2abfcd94fb0ef5a56c5d7dffddfe814752eef1 | 7bcebff7ac2f2822423f211f1162cd017a18babb | refs/heads/master | 2023-04-09T02:37:41.466794 | 2021-04-25T03:27:16 | 2021-04-25T03:27:16 | 358,926,457 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 337 | py | -X FMLP -Q 0 -L 2 105 400
-X FMLP -Q 0 -L 2 85 250
-X FMLP -Q 0 -L 2 70 250
-X FMLP -Q 1 -L 2 66 200
-X FMLP -Q 1 -L 2 64 250
-X FMLP -Q 1 -L 2 50 200
-X FMLP -Q 2 -L 1 41 150
-X FMLP -Q 2 -L 1 40 125
-X FMLP -Q 2 -L 1 34 100
-X FMLP -Q 3 -L 1 33 200
-X FMLP -Q 3 -L 1 20 250
-X FMLP -Q 3 -L 1 10 100
| [
"[email protected]"
] | |
c52b1c6c264352ca8f6c39666cd4b3d7f7e23005 | 555944b5b196fc6e52db6abd913c8cd7eaa00c0a | /HW7/test_FizzBuzz.py | 6537d71235828ab0a8b797cdae6248a4aba9fce4 | [] | no_license | shinhoj01/CS362 | bdd4d8fd1ee5e5f866d5a3432478701890204af6 | 34dddbb108eff3448af84f8687772202f0dcbfef | refs/heads/main | 2023-03-22T00:45:15.184379 | 2021-03-03T10:19:33 | 2021-03-03T10:19:33 | 334,580,473 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 381 | py | import pytest
from FizzBuzz import fizzbuzz
class TestCase:
def test(self):
# lists of inputs and outputs
inp = (2,3,5,9,10,15,55,75,99,100)
otp = [2,"Fizz","Buzz","Fizz","Buzz","FizzBuzz",
"Buzz","FizzBuzz","Fizz","Buzz"]
# Used map to apply the function to list
res = list(map(fizzbuzz, inp))
assert res == otp
| [
"[email protected]"
] | |
84ea5c637ee27630e4f66977e073aaeeb817e3da | d127e063dd6578a08f48cd4fdff626047a6ee080 | /todo/admin.py | 9f2b1bfd5e480f55eac46b92ed7cef23e5a60730 | [] | no_license | nagarjunnas/Todo | 571c33fd6eac3dc603da7283e4d60e88c9362910 | 2610b86243056b4e8d0d84c61deae8a3518e7307 | refs/heads/master | 2020-04-01T04:56:22.858222 | 2018-10-13T15:37:25 | 2018-10-13T15:37:25 | 152,882,708 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,171 | py | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
import csv
from django.http import HttpResponse
from django.contrib import admin
from .models import Todo
# Register your models here.
class TodoAdmin(admin.ModelAdmin):
search_fields = ['title']
list_filter = ('status','created_at', 'modified_at', 'created_date_time')
actions = ["export_as_csv"]
list_display = ('title', 'description','created_date_time' , 'status', 'created_at', 'modified_at')
def export_as_csv(self, request, queryset):
meta = self.model._meta
field_names_headers = [field.name.title().replace('_', ' ') for field in meta.fields]
field_names = [field.name for field in meta.fields]
response = HttpResponse(content_type='text/csv')
response['Content-Disposition'] = 'attachment; filename=todos.csv'
writer = csv.writer(response)
writer.writerow(field_names_headers)
for obj in queryset:
row = writer.writerow([getattr(obj, field) for field in field_names])
return response
export_as_csv.short_description = "Export Selected as CSV"
admin.site.register(Todo, TodoAdmin) | [
"[email protected]"
] | |
0e647dd279872f9ca98db25c23550b1a1e7e5fb4 | df83f97ed2c6dd199005e96bc7c494cfb3b49f8c | /GeeksForGeeks/String Rotations.py | 42ed217509cdfcaf23e1e662e437f71bfb0dfa7b | [] | no_license | poojan14/Python-Practice | 45f0b68b0ad2f92bbf0b92286602d64f3b1ae992 | ed98acc788ba4a1b53bec3d0757108abb5274c0f | refs/heads/master | 2022-03-27T18:24:18.130598 | 2019-12-25T07:26:09 | 2019-12-25T07:26:09 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 469 | py | '''
Given strings s1 and s2, you need to find if s2 is a rotated version of the string s1. The strings are lowercase.
'''
if __name__ == '__main__':
T = int(input())
for _ in range(T):
s1 = input()
s2 = input()
if len(s1)==len(s2):
tmp = s1+s1 # It gives all possible rotations
if s2 in tmp : print(1) # of a string.
else : print(0)
else:
print(0)
| [
"[email protected]"
] | |
7bd9dbb485425614b3b564465bc42b23de0ad1ab | 6cf7035780de933f98ad533ecbaf18744f5546a6 | /src/apps/accounts/apps.py | 770feb5cbdc38a5ec0883c47455350c1d452abed | [] | no_license | Lakanbi37/Social | 2a21ac7a7507f1e762c8261950539f946f956b8e | 6221d34dac6fd31d68866c76c8f1d19afaffe49f | refs/heads/master | 2023-01-30T18:55:38.200523 | 2020-04-30T04:18:58 | 2020-04-30T04:18:58 | 259,552,475 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 149 | py | from django.apps import AppConfig
class AccountsConfig(AppConfig):
name = 'apps.accounts'
label = "accounts"
verbose_name = "Accounts"
| [
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] | |
7c9975bd2527fff01822ea1ebc940d8c3c0a8bc8 | 37d8a02e4976a8ca516500d5b9d2fa6626c2b9e3 | /A_Scorecard/example/test/scorecard_functions_V3_test.py | 6bb0dd6dc82772ca9a4635b439dd71e7090a3287 | [] | no_license | sucre111/xiaoxiang_fengkong_peixun | b0bb59243346fc02fea8126d729af1fb29bf907d | 5eac4e3011e5bbc7e59e79296c12e81074166551 | refs/heads/master | 2021-09-17T05:16:19.362017 | 2018-06-28T11:33:29 | 2018-06-28T11:33:29 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 986 | py | #conding = utf-8
import pandas as pd
target = "y"
from example.scorecard_functions_V3 import *
train_data_file = "D:/conf_test/A_Scorecard/application.csv"
def BadRateEncodingTest():
df = pd.read_csv(train_data_file, encoding = 'latin1')
# 处理标签：Fully Paid是正常用户；Charged Off是违约用户
df['y'] = df['loan_status'].map(lambda x: int(x == 'Charged Off'))
col = "home_ownership"
regroup = BinBadRate(df, col, target, grantRateIndicator=0)[1]
print("regroup:")
print(regroup)
temp_regroup = regroup[[col,'bad_rate']].set_index([col])
print("temp group:")
print(temp_regroup)
br_dict = regroup[[col,'bad_rate']].set_index([col]).to_dict(orient='index')
print("br_dict:")
print(br_dict)
for k, v in br_dict.items():
print(k)
print(v)
br_dict[k] = v['bad_rate']
badRateEnconding = df[col].map(lambda x: br_dict[x])
if __name__ == "__main__":
BadRateEncodingTest() | [
"[email protected]"
] | |
af34fd1034f5561c8b73ec840986022f67f088ed | 803f0fbc5973ff31fd5faca5c0f2981b2c52a591 | /Python/tensorflow/variable.py | c1d7bc9416c924c4de82917774c881ca2d032ea4 | [] | no_license | MiohitoKiri5474/CodesBackUp | 00ab52bd55732b8164a42cffd664407878f4390e | 4247fa032c8e88259dcc3992a21c510b6f2e8850 | refs/heads/master | 2023-08-09T14:46:10.445697 | 2023-08-04T01:12:58 | 2023-08-04T01:12:58 | 126,162,563 | 3 | 1 | null | null | null | null | UTF-8 | Python | false | false | 313 | py | import tensorflow as tf
B = tf.Variable ( 10 )
with tf.Session() as sess:
sess.run ( tf.global_variables_initializer() )
# 用變數要先把變數初始化
print ( sess.run ( B ) )
print ( sess.run ( B.assign ( 100 ) ) )
# 變數可用assign初始化，且一定要開Session run過一次
| [
"[email protected]"
] | |
67d99b5c3eced18b0bdf7022c3511339e5b942b1 | e79c8521fb55586e356e17caef7358152ab3a21f | /ismo/bin/generate_samples.py | 294b1cb7a48b322adb5a2e97d43c94f586d54277 | [
"MIT"
] | permissive | kjetil-lye/iterative_surrogate_optimization | 1e06a0727b8385926eab81bbf3d8133b8ceed1f1 | f5de412daab1180612837f4c950203ad87d62f7e | refs/heads/master | 2023-04-14T03:28:42.715302 | 2020-10-20T07:25:26 | 2020-10-20T07:25:26 | 187,802,115 | 6 | 3 | MIT | 2023-02-02T06:47:00 | 2019-05-21T09:08:20 | Python | UTF-8 | Python | false | false | 2,211 | py | #!/bin/env python
import os.path
if __name__ == '__main__':
import argparse
from ismo.samples import create_sample_generator
import numpy as np
parser = argparse.ArgumentParser(description="""
Generate samples and write them to file using numpy.savetxt. Each row repesents a single sample, and each value
represents each component of the given sample.
Example use would be:
y = numpy.loadtxt('filename.txt')
# y[k,i] is component i of sample k
""")
parser.add_argument('--generator', type=str, default='monte-carlo',
help='Name of generator to use, either "monte-carlo" or "sobol"')
parser.add_argument('--dimension', type=int, required=True,
help="Number of dimensions")
parser.add_argument('--number_of_samples', type=int, required=True,
help='Number of samples to generate')
parser.add_argument('--start', type=int, default=0,
help='The first sample (in other words, number of samples to skip first)')
parser.add_argument('--output_file', type=str, required=True,
help='Output filename (full path)')
parser.add_argument('--output_append', action='store_true',
help='Append output to end of file')
args = parser.parse_args()
generator = create_sample_generator(args.generator)
samples = generator(args.number_of_samples,
args.dimension,
start=args.start)
if args.output_append:
if os.path.exists(args.output_file):
previous_samples = np.loadtxt(args.output_file)
if len(previous_samples.shape) == 1:
# In case of a 1D array, we need to make sure to treat is a two-dim array.
previous_samples = previous_samples.reshape((previous_samples.shape[0], 1))
new_samples = np.zeros((samples.shape[0] + previous_samples.shape[0], args.dimension))
new_samples[:previous_samples.shape[0], :] = previous_samples
new_samples[previous_samples.shape[0]:, :] = samples
samples = new_samples
np.savetxt(args.output_file, samples)
| [
"[email protected]"
] | |
67db2b1feed5ce6b57cddb306d4a56163cf97ada | 27b599705364707392d66cff4df9e38f28e54433 | /ex50/projects/gothonweb/app.py | 9114cef9a3766c083c1378c783d9f2d0113410e6 | [] | no_license | huanglao2002/lphw | a615598568fe089dda230829c323a2cbe2c1af4f | 4fce5374613e713c02b5b86fc39c290c496ed1ba | refs/heads/master | 2023-01-23T15:17:13.442619 | 2020-11-25T13:30:55 | 2020-11-25T13:30:55 | 315,808,466 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 292 | py | from flask import Flask
from flask import render_template
app = Flask(__name__)
@app.route('/')
def index():
#greeting = "Hello Jim"
#return render_template("index.html", greeting=greeting)
return render_template("index.html")
if __name__ == "__main__":
app.run() | [
"[email protected]"
] | |
76848a321556dc72d28c4478cf14ea644c690541 | 11194e8da8d5d496bdadd82ae03c9b6109dc4f6a | /id_PERM/AH/019_AH_PERM.py | 0d47195763f7e9d9c25cce4cdf9a89e2897bc8fc | [] | no_license | prepiscak/beatson_rosalind | f4e37ec87dd6d6206c09dbdb78a6ae829efb69fb | 529465bdc2edb83eafb687a729513e2e50aff4db | refs/heads/master | 2020-04-27T01:31:10.631357 | 2019-09-26T09:58:27 | 2019-09-26T09:58:27 | 173,968,130 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 328 | py | #!/usr/bin/python3
#usage 019_PERM.py n
#improt some stuff
import sys
from itertools import permutations as perm
#get int from command line
n=int(sys.argv[1])
#get all the permutations of the set 1:n in a list of lists
perm_list=list(perm(set(range(1,n+1))))
#print
print(len(perm_list))
for p in perm_list:
print(*p)
| [
"[email protected]"
] | |
9bfe15dacc41979c5b07071075e289d74a471d5f | ac2a27debbc62fb4ccd71e550d4cdeb167674d43 | /firewall/test/sim_firewall_tcp/run.py | 88080576ee170f4b67a4b9e6ed1eb48ac6e28e5c | [] | no_license | TopologyMapping/netfpga-tutorial | 8a4227594e96d1f68443c3bc241165abadb051a1 | 3457b3dda94b5a90d3dbc66cb367764adb826f14 | refs/heads/master | 2020-04-12T14:55:27.511141 | 2016-05-18T15:38:29 | 2016-05-18T15:38:29 | 31,033,110 | 2 | 2 | null | null | null | null | UTF-8 | Python | false | false | 2,415 | py | #!/bin/env python
from NFTest import *
from NFTest import simReg
phy2loop0 = ('../connections/conn', 'nf2c0')
nftest_init(sim_loop = [], hw_config = [phy2loop0])
nftest_start()
pdrop = [1210, 80, 22, 667]
#Ports to drop 1210, 80, 22, 667
nftest_regwrite((reg_defines.FIREWALL_DPORT1_REG()),pdrop[0])
nftest_regwrite((reg_defines.FIREWALL_DPORT2_REG()),pdrop[1])
nftest_regwrite((reg_defines.FIREWALL_DPORT3_REG()),pdrop[2])
nftest_regwrite((reg_defines.FIREWALL_DPORT4_REG()),pdrop[3])
nftest_regread_expect((reg_defines.FIREWALL_DPORT1_REG()),pdrop[0])
nftest_regread_expect((reg_defines.FIREWALL_DPORT2_REG()),pdrop[1])
nftest_regread_expect((reg_defines.FIREWALL_DPORT3_REG()),pdrop[2])
nftest_regread_expect((reg_defines.FIREWALL_DPORT4_REG()),pdrop[3])
simReg.regDelay(1000) #1us
nftest_regread_expect((reg_defines.SRAM_BASE_ADDR()),(pdrop[2]<<16|pdrop[3]))
nftest_regread_expect((reg_defines.SRAM_BASE_ADDR()+4),(pdrop[0]<<16|pdrop[1]))
HDR=scapy.TCP()
TTL = 64
eth_hdr = 14
ipv4_hdr=20
tcp_hdr=20
LOAD = ''
length = 10
for genr in range (length):
LOAD += chr(randint(0,255))
#DA = "0xD0:0x27:0x88:0xBC:0xA8:0xE9"
#SA = "0x0:0x4E:0x46:0x32:0x43:0x0"
#DST_IP = '192.168.101.10'
#SRC_IP = '192.168.101.20'
PORTS = [567, pdrop[0], 876, pdrop[3], 21, pdrop[2], 37, pdrop[1]]
NUM_PKTS = len(PORTS)
NUM_PKTS_DROPPED = 4
i=0
while(i < NUM_PKTS):
HDR.dport = PORTS[i]
HDR.sport = PORTS[NUM_PKTS-1-i]
HDR.flags = 0b00010
DA = "0xD0:0x27:0x88:0xBC:0xA8:0x%02x"%(i)
SA = "0x0:0x4E:0x46:0x32:0x43:0x%02x"%(i)
DST_IP = '192.168.101.%0.3i'%(i)
SRC_IP = '192.168.101.%0.3i'%(i+1)
pkt = scapy.Ether(dst=DA, src=SA)/scapy.IP(dst=DST_IP,
src=SRC_IP, ttl=TTL)/HDR/LOAD
#pkt.len = (len(LOAD))+eth_hdr+ipv4_hdr+tcp_hdr
#pkt.seq = i*(50)
nftest_send_phy('nf2c0', pkt)
print "SRC_IP: %s" %(SRC_IP)
# if(PORTS[i] not in pdrop):
if(PORTS[i] != pdrop[0] and PORTS[i] != pdrop[1] and PORTS[i] != pdrop[2] and PORTS[i] != pdrop[3]):
pkt = scapy.Ether(dst=DA, src=SA)/scapy.IP(dst=DST_IP,
src=SRC_IP, ttl=TTL-1)/HDR/LOAD
#pkt.len = (len(LOAD))+eth_hdr+ipv4_hdr+tcp_hdr
#pkt.seq = i*(50)
nftest_expect_dma('nf2c0', pkt)
i = i+1
nftest_barrier()
simReg.regDelay(1000) #1us
print "Checking pkt errors"
# check counter values
nftest_regread_expect(reg_defines.MAC_GRP_0_RX_QUEUE_NUM_PKTS_STORED_REG(), NUM_PKTS)
nftest_finish()
| [
"bob@crunchbang"
] | bob@crunchbang |
d68125104a4b0d63b31ac8183cc83ed87465a499 | c7f6f03449bc1cdbda9f62db66ac4aefefd836ea | /preprocessing.py | 032424323a888ee4c19e23d1b9c650231c21b5e9 | [] | no_license | paul-freeman/aars | d8d382b1f11ed2e25c72e811fd8bac1a5459b298 | f054a8cb7fdc27bbca8e2001329b6a5cfbc470ad | refs/heads/master | 2021-11-21T20:51:23.462501 | 2021-08-09T06:36:24 | 2021-08-09T06:36:24 | 229,409,003 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 9,576 | py | import sys
import glob
import os.path
import json
AA_LIST = ['ala', 'asn', 'asp', 'gln', 'leu', 'glu', 'gly', 'his', 'ile', 'lys',
'arg', 'met', 'phe', 'pro', 'pyl', 'sep', 'ser', 'thr', 'val', 'cys', 'trp', 'tyr']
KINGDOM_LIST = ['bact', 'arch']
def parse_fasta(path):
fasta_data = []
with open(path) as lines:
for line in lines:
if line[0] == '>':
xs = line[1:].strip().split('_')
if not (xs and xs[0] and xs[0].lower() in AA_LIST):
raise RuntimeError(
"Amino Acid ({}) not recognized in {}".format(
xs[0], line
)
)
aa = xs.pop(0).lower()
if (xs and xs[0] and xs[0].lower() == 'reg'):
xs.pop(0)
regions = True
else:
regions = False
if not (xs and xs[0] and xs[0].lower() in KINGDOM_LIST):
raise RuntimeError(
"Kingdom ({}) not recognized in {}".format(
xs[0], line
)
)
kingdom = xs.pop(0).lower()
pdb = None
if xs and xs[0] and len(xs[0]) == 4:
pdb = xs.pop(0).lower()
if not (xs and xs[0] and len(xs[0]) == 1):
raise RuntimeError(
"'{}' not recognized as first letter of genus in {}".format(
xs[0], line
)
)
letter = xs.pop(0).upper()
try:
genus, num = '_'.join(xs).lower().split('/')
if genus[-3:] == "aln":
genus = genus[:-4]
except ValueError:
genus, num = xs[0].lower(), "0"
fasta_data.append({
'aa': aa,
'kingdom': kingdom,
'regions': regions,
'pdb': pdb,
'letter': letter,
'genus': genus,
'num': num
})
return fasta_data
def search_data_folder(fasta_data, ext):
"""Glob the `data` folder looking for matches"""
if fasta_data['pdb']:
f1 = '{}*_'.format(fasta_data['pdb']) + ext
else:
f1 = '{}{}_{}_{}'.format(
fasta_data['letter'],
fasta_data['genus'],
fasta_data['aa'],
ext
)
return glob.glob('data/**/*' + f1, recursive=True)
def search_supplemental_folder(fasta_data, ext):
"""Glob the `supplemental` folder looking for matches"""
if fasta_data['pdb']:
f = '{}_*_{}_*_{}.fasta'.format(
fasta_data['aa'],
fasta_data['pdb'],
('aa' if ext == 'aa' else 'nuc')
)
else:
f = '{}_{}_{}_{}_{}.fasta'.format(
fasta_data['aa'],
fasta_data['kingdom'],
fasta_data['letter'],
fasta_data['genus'],
('aa' if ext == 'aa' else 'nuc')
)
fastas = glob.glob('data/supplemental/*' + f, recursive=False)
if fastas:
return fastas
# nothing found: check for txt extension
if fasta_data['pdb']:
f = '{}_*_{}_*_{}.txt'.format(
fasta_data['aa'],
fasta_data['pdb'],
('aa' if ext == 'aa' else 'nuc')
)
else:
f = '{}_{}_{}_{}_{}.txt'.format(
fasta_data['aa'],
fasta_data['kingdom'],
fasta_data['letter'],
fasta_data['genus'],
('aa' if ext == 'aa' else 'nuc')
)
txts = glob.glob('data/supplemental/*' + f, recursive=False)
return txts
def search_downloads_folder(fasta_data, ext):
"""Search the Downloads folder looking for matches"""
downloads = os.path.join(os.path.expanduser('~'), 'Downloads')
if fasta_data['pdb']:
f = '{}_*_{}_*_{}.fasta'.format(
fasta_data['aa'],
fasta_data['pdb'],
('aa' if ext == 'aa' else 'nuc')
)
else:
f = '{}_{}_{}_{}_{}.fasta'.format(
fasta_data['aa'],
fasta_data['kingdom'],
fasta_data['letter'],
fasta_data['genus'],
('aa' if ext == 'aa' else 'nuc')
)
return glob.glob('{}/*'.format(downloads) + f, recursive=False)
def write_standardized_data(fasta_data):
"""Look through Alex's data and write file (if found) in standard format."""
for ext in ['aa', 'nuc']:
out_path = 'data/{}.{}'.format(make_filename(fasta_data), ext)
if not os.path.exists(out_path):
g1 = search_downloads_folder(fasta_data, ext)
if not g1:
g1 = search_supplemental_folder(fasta_data, ext)
# possible location in Alex's data
g2 = []
if not g1:
g2 = search_data_folder(fasta_data, ext)
# SPECIAL CASE 1
if fasta_data['genus'] == 'obscuriglobus':
f = 'Gemmata_{}_{}'.format(
fasta_data['aa'], ext
)
g2 = glob.glob('data/**/*' + f, recursive=True)
# SPECIAL CASE 2
if fasta_data['aa'] == 'leu' and not g2:
f = '{}{}_{}ALPHA_{}'.format(
fasta_data['letter'],
fasta_data['genus'],
fasta_data['aa'],
ext
)
g2 = glob.glob('data/**/*' + f, recursive=True)
# SPECIAL CASE 3
if fasta_data['genus'] == 'asiaticus':
f = 'CAmoebophilusAsiaticus_{}_{}'.format(
fasta_data['aa'],
ext
)
g2 = glob.glob('data/**/*' + f, recursive=True)
g = g1 + g2
if not g:
# print('Missing data for: {}'.format(out_path))
continue
else:
with open(g[0]) as f_in:
with open(out_path, 'w') as f_out:
for line in f_in:
f_out.write(line)
def write_binary_data(filename):
dat = parse_fasta(filename)
new_dat = []
isMissingData = False
for fasta_data in dat:
prefix = make_filename(fasta_data)
aa_file = 'data/{}.aa'.format(prefix)
nuc_file = 'data/{}.nuc'.format(prefix)
try:
os.remove(aa_file + '.bad')
except FileNotFoundError:
pass
try:
os.remove(nuc_file + '.bad')
except FileNotFoundError:
pass
aa_dat = read_fasta_file(aa_file)[2]
nuc_dat = read_fasta_file(nuc_file)[2]
if not aa_dat or not nuc_dat:
if not aa_dat:
print("Missing aa data for " + prefix)
if not nuc_dat:
print("Missing nuc data for " + prefix)
isMissingData = True
continue
if len(aa_dat) * 3 + 3 == len(nuc_dat):
nuc_dat = nuc_dat[:-3]
elif len(aa_dat) * 3 != len(nuc_dat):
err = "Data incorrect length: {}: ({} aas) ({} nucs): expected ({} nucs)".format(
prefix,
len(aa_dat),
len(nuc_dat),
len(aa_dat) * 3
)
try:
os.rename(aa_file, aa_file + '.bad')
except FileExistsError:
pass
try:
os.rename(nuc_file, nuc_file + '.bad')
except FileExistsError:
pass
print(err)
isMissingData = True
continue
raise RuntimeError(err)
fasta_data['aa_dat'] = aa_dat
fasta_data['nuc_dat'] = nuc_dat
new_dat.append(fasta_data)
if isMissingData:
pass
with open(filename + '.json', 'w') as json_file:
json.dump(new_dat, json_file, indent=2)
def make_filename(fasta_data):
return '_'.join(
[x for x in [
fasta_data['aa'],
fasta_data['kingdom'],
fasta_data['pdb'],
fasta_data['letter'],
fasta_data['genus'],
# fasta_data['num']
] if x]
)
def read_fasta_file(path):
"""read the data from the fasta file"""
if path is None:
return None, None, None
try:
header, gi, dat = None, None, ''
with open(path) as path_p:
for next_dat in path_p.readlines():
if next_dat.strip() == '':
continue
if next_dat[0] == '>':
header = next_dat.strip()
if next_dat[0:4] == '>gi|':
try:
gi = next_dat[4:].split('|')[0].split()[0]
except IndexError:
gi = None
else:
gi = None
continue
else:
dat += next_dat.strip()
return header, gi, dat
except FileNotFoundError:
return None, None, None
def main(filename):
for fasta_data in parse_fasta(filename):
write_standardized_data(fasta_data)
write_binary_data(filename)
if __name__ == "__main__":
main(sys.argv[1])
| [
"[email protected]"
] | |
7befe330fcfccd5eda39f24b075dfc42fad72e4e | 895a414a8467be8532bbac52eaa199ed2cfd5d75 | /greedy/PriyankaAndToys.py | 8d9ec6347229a25186662a215f599e9822c284c8 | [] | no_license | burakkurt/Hackerrank_Python | 92e0c4c17edd8a3e57ad9ae1ba4e2e2dd459f983 | a22e632c59100bcebb775b2c1c4551640336ba38 | refs/heads/master | 2021-01-12T14:16:41.608708 | 2016-10-06T15:53:57 | 2016-10-06T15:53:57 | 70,005,682 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 362 | py |
numToys = int(raw_input());
toys = map(int, raw_input().split());
toys.sort();
priceLeft = toys[0];
priceRight = priceLeft + 4;
numToysToBuy=1;
for i in range(1,numToys):
if(toys[i]>=priceLeft and toys[i]<=priceRight):
continue;
else:
numToysToBuy += 1;
priceLeft=toys[i];
priceRight=priceLeft+4;
print numToysToBuy;
| [
"[email protected]"
] | |
d8edf4a0202d663a88b7fda1373d4c25ec1d3f06 | b183c98f7749a015ca420940be85f8af6c004bb3 | /medium/78.py | 0ce95a3bbd0bad7e58ef50181285396d20b4dc60 | [
"Apache-2.0"
] | permissive | oneTaken/leetcode | b8cfa7e0ff42de2eaef8b64cceef4f183006612e | f9357d839ac8fa6333b0d7eeb2028ba28a63764c | refs/heads/master | 2020-03-12T10:08:12.200753 | 2018-05-05T05:12:24 | 2018-05-05T05:12:24 | 130,566,847 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 352 | py | class Solution:
def subsets(self, nums):
"""
:type nums: List[int]
:rtype: List[List[int]]
"""
import itertools
ans = []
for i in range(len(nums) + 1):
_ans = itertools.combinations(nums, i)
_ans = list(map(list, _ans))
ans.extend(_ans)
return ans | [
"[email protected]"
] | |
049ada4f72aaa8b3ab20c0db52e19f9c60c95d9d | 7343859ea0cd609a74a5683aaa3729398c329d43 | /visitors/admin.py | e40ec64eb3ff609de7c64fd3573e9bac1e9c71d8 | [] | no_license | qiubite31/tw_visitor | 6a7ab00bad476ef8180d5888290a7895a93b49d0 | b08715d32096c9139d396efc15077666ce1cd5e9 | refs/heads/master | 2020-05-20T07:27:19.842678 | 2019-03-07T15:13:30 | 2019-03-07T15:13:30 | 63,789,216 | 2 | 0 | null | null | null | null | UTF-8 | Python | false | false | 132 | py | from django.contrib import admin
from .models import ArrivalRecord
# Register your models here.
admin.site.register(ArrivalRecord)
| [
"Dragon Lin"
] | Dragon Lin |
ad03c6c89d53f7c088759d2f9b0a1bb92b0aa033 | 654aba6352851ff88d8acfa04658529c75509b74 | /scrapy_sample/scrapy_sample/items.py | 885749a754e1d85322e9cb98999bc35d4b94340c | [
"Apache-2.0"
] | permissive | neilnee/octopus | 2ecb93b6a83a85826782238f515cebba9c0c72a9 | 7981e8a926f0ea9d5a09bea6e4828fdc0f7f0e62 | refs/heads/master | 2021-08-31T16:22:18.744762 | 2017-12-22T02:10:17 | 2017-12-22T02:10:17 | 104,200,838 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 308 | py | # -*- coding: utf-8 -*-
# Define here the models for your scraped items
#
# See documentation in:
# http://doc.scrapy.org/en/latest/topics/items.html
import scrapy
class HuxiuItem(scrapy.Item):
title = scrapy.Field()
link = scrapy.Field()
desc = scrapy.Field()
posttime = scrapy.Field()
| [
"[email protected]"
] | |
3b04f91b01c4c46ccf2a29e2a33fa5ec59f1e0e0 | 16c24cba9ca47b27dafed2595159b5970fbebbd2 | /shan/build_dataset.py | b608756cb823e9f56c47209f56d0fad525ba939c | [] | no_license | jakisou/SHAN | 834c80271c2a0ad85c12667d7ddd0187d3aa431a | 7e5b5f4970808407f2dc9498e8600bc85b18a4c9 | refs/heads/master | 2022-04-07T23:49:11.382667 | 2020-02-29T07:50:12 | 2020-02-29T07:50:12 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,115 | py | import random
import pickle
import numpy as np
import copy
max_length = 90
random.seed(1234)
with open('../Data/remap.pkl', 'rb') as f:
reviews_df = pickle.load(f)
item_cate_list = pickle.load(f)
user_count, item_count, cate_count, example_count = pickle.load(f)
train_set = []
test_set = []
for reviewerID, hist in reviews_df.groupby('reviewerID'):
pos_list = hist['asin'].tolist()
tim_list = hist['unixReviewTime'].tolist()
def gen_neg():
neg = pos_list[0]
while neg in pos_list:
neg = random.randint(0, item_count-1)
return neg
neg_list = [gen_neg() for i in range(len(pos_list))]
length = len(pos_list)
valid_length = min(length, max_length)
i = 0
tim_list_session = list(set(tim_list))
tim_list_session.sort()
pre_session = []
for t in tim_list_session:
count = tim_list.count(t)
new_session = pos_list[i:i+count]
if t == tim_list_session[0]:
pre_session.extend(new_session)
else:
if i+count < valid_length-1:
pre_session_copy = copy.deepcopy(pre_session)
train_set.append((reviewerID, pre_session_copy, new_session, pos_list[i+count], 1))
train_set.append((reviewerID, pre_session_copy, new_session, neg_list[i+count], 0))
pre_session.extend(new_session)
else:
pos_item = pos_list[i]
if count > 1:
pos_item = random.choice(new_session)
new_session.remove(pos_item)
neg_index = pos_list.index(pos_item)
pos_neg = (pos_item, neg_list[neg_index])
test_set.append((reviewerID, pre_session, new_session, pos_neg))
break
i += count
random.shuffle(train_set)
random.shuffle(test_set)
assert len(test_set) == user_count
with open('dataset.pkl', 'wb') as f:
pickle.dump(train_set, f, pickle.HIGHEST_PROTOCOL)
pickle.dump(test_set, f, pickle.HIGHEST_PROTOCOL)
pickle.dump((user_count, item_count), f, pickle.HIGHEST_PROTOCOL)
| [
"[email protected]"
] | |
ccb94a4d32c9ff95e32281b681554a1c8059a209 | 79d41f92e0c0018bd83fc1fafed8e481fc5d3d41 | /migrations/versions/84084dd1c091_.py | 72d4fb99e71faf80c704c0595eefb4eadde8471e | [] | no_license | fiveCubes/udacity_Fyyur | 9cc109778fa8d8d7cd6c19f09384d8e65401de68 | 0228a85bacc0c563805ef300ea3899bd0ce5a293 | refs/heads/master | 2022-12-06T15:50:10.583937 | 2020-09-04T22:18:28 | 2020-09-04T22:18:28 | 292,956,940 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,242 | py | """empty message
Revision ID: 84084dd1c091
Revises: 4192e26b4382
Create Date: 2020-09-02 15:37:31.769251
"""
from alembic import op
import sqlalchemy as sa
from sqlalchemy.dialects import postgresql
# revision identifiers, used by Alembic.
revision = '84084dd1c091'
down_revision = '4192e26b4382'
branch_labels = None
depends_on = None
def upgrade():
# ### commands auto generated by Alembic - please adjust! ###
op.drop_table('Show')
# ### end Alembic commands ###
def downgrade():
# ### commands auto generated by Alembic - please adjust! ###
op.create_table('Show',
sa.Column('id', sa.INTEGER(), server_default=sa.text('nextval(\'"Show_id_seq"\'::regclass)'), autoincrement=True, nullable=False),
sa.Column('venue_id', sa.INTEGER(), autoincrement=False, nullable=False),
sa.Column('artist_id', sa.INTEGER(), autoincrement=False, nullable=False),
sa.Column('start_time', postgresql.TIMESTAMP(), autoincrement=False, nullable=False),
sa.ForeignKeyConstraint(['artist_id'], ['Artist.id'], name='Show_artist_id_fkey'),
sa.ForeignKeyConstraint(['venue_id'], ['Venue.id'], name='Show_venue_id_fkey'),
sa.PrimaryKeyConstraint('id', name='Show_pkey')
)
# ### end Alembic commands ###
| [
"[email protected]"
] | |
067c502cd6a0bed78cd8a82684f8da8fa51c15dc | 1c85f6ba14b7762cf14fc5453b07a93dc735afc2 | /python/algorithms/hw0/randomhw/insertion_sort.py | 1a0f8c31c2d4e29570591ab625bf0c579d84a1ff | [] | no_license | jashook/ev6 | 557bceb82d4e0e241c51f7ba27cc4cfa00f98408 | 97e7787b23fae38719538daf19a6ab119519e662 | refs/heads/master | 2021-01-22T23:16:06.702451 | 2013-10-12T18:39:44 | 2013-10-12T18:39:44 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,003 | py | #!/usr/bin/python
################################################################################
################################################################################
#
# Author: Jarret Shook
#
# Module: insertion_sort.py
#
# Modifications:
#
# 29-Jan-13: Version 1.0: Created
#
# Timeperiod: ev6
#
################################################################################
################################################################################
import sys
################################################################################
################################################################################
def insertion_sort(s):
"""
Input: list s to be sorted
Output: sorted list
"""
arr = range(len(s));
del arr[0];
for i in arr:
j = i
data = s[j]
while (j > 0 and s[j] < s[j-1]):
s[j] = s[j - 1]
s[j-1] = data
j = j - 1;
return s
#if __name__ == "__main__":
| [
"[email protected]"
] | |
92c64ad45c5b329b5722db23cdfe5a17175b703f | 8ea3fbf18c58e4905a894b7c44059b726f9d522a | /ch4ex2.py | 7b917d45392afc2e801a6064fabbbc0e9b7811f5 | [] | no_license | leslieawicke/thinkpython | ecc17f91d173462b77da96f9a9ed72cda65cf9f5 | 231468f471df696561fbe81085f109c0a7fc8373 | refs/heads/master | 2021-04-29T07:23:59.413862 | 2018-03-09T02:04:13 | 2018-03-09T02:04:13 | 121,819,725 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 562 | py | import math
import turtle
from ch4ex import arc
bob = turtle.Turtle()
radius = 250
n = 5
overlap = 45
def petal(t, r, n, o):
"""draws a petal shape with given radius (r) and angle (a) derived from the number of petals desired (n).
t = turtle"""
a = 360/n + o
arc(t, r, a)
bob.lt(180 - a)
arc(t, r, a)
bob.lt(180 - o)
def flower(t, r, n, o):
for i in range(n):
petal(t, r, n, o)
flower(bob, radius, n, overlap)
turtle.mainloop()
# the angle of bob's turn at the end of his first arc should be 180 degrees minus the angle of the arc he just drew. | [
"[email protected]"
] | |
1a95afb8fe2a0cbbec27d84d31a8ca32f302e201 | d1847e96c14a7d06aeab2a557eb25b1c6d5170d7 | /Python Web App/myapp.py | 65c164ffd18f5fef19f59380536518c22555e13e | [] | no_license | ANA-POTJE/WEB_Applications | 5dc043b9b63ed5ddb1cc8a17dba4d5de6fb68712 | c9c0869b9f8787eb8e400a4f774f9ba387e3bf71 | refs/heads/master | 2022-11-09T07:53:30.720297 | 2020-06-18T14:27:53 | 2020-06-18T14:27:53 | 273,253,091 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,230 | py | import yfinance as yf
import streamlit as st
st.write("""
# Simple Stock Price App
Shown are the stock closing price and volume of Google!
""")
# https://towardsdatascience.com/how-to-get-stock-data-using-python-c0de1df17e75
#define the ticker symbol
tickerSymbol = 'GOOGL'
#get data on this ticker
tickerData = yf.Ticker(tickerSymbol)
#get the historical prices for this ticker
tickerDf = tickerData.history(period='1d', start='2010-5-31', end='2020-5-31')
# Open High Low Close Volume Dividends Stock Splits
st.line_chart(tickerDf.Close)
st.line_chart(tickerDf.Volume)
#Running the web app
#After saving the code into a file called myapp.py, fire up the command prompt
#(or Power Shell in Microsoft Windows) and run the following command:
#####
##### WORKED IN ANACONDA PROMPT!!! (conda activate env first!)
#####
# streamlit run myapp.py
#Next, we should see the following message:
#> streamlit run myapp.py
#You can now view your Streamlit app in your browser.
#Local URL: http://localhost:8501
#Network URL: http://10.0.0.11:8501
#In a short moment, an internet browser window should pop-up and directs you to the
#created web app by taking you to [http://localhost:8501.]http://localhost:8501 as shown below.
| [
"[email protected]"
] | |
cb6129890bf338a65a0d59e425a58c5f8b914d32 | 498c3189f21f4545eb9829a9c63c6ef6dcce229e | /Algorithms/Strings/Palindrome-Index.py | e5274a4cd869d229daf74495d91fbd15ff84551e | [] | no_license | Damian1724/Hackerrank | af83c74a5a5aa6b4e1684c7a7133571c8dd7d2f8 | 9c58363e6214eabb4b55330e276c7b414273beee | refs/heads/master | 2020-03-17T12:26:18.543723 | 2018-12-06T23:52:43 | 2018-12-06T23:52:43 | 133,103,693 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 896 | py | /*
Author: Damian Cruz
source: HackerRank(https://www.hackerrank.com)
problem name:Algorithms>Strings>Palindrome-Index
problem url: https://www.hackerrank.com/challenges/palindrome-index/problem
*/
def checking(word,pos):
a=0
b=len(word)-1
while a<b:
if a==pos:a+=1
if b==pos:b-=1
if word[a]!=word[b]:
return False
a+=1
b-=1
return True
cases=int(input())
for i in range(cases):
s=input()
j=0
k=len(s)-1
answer=0
valor=False
while j < k:
if s[j]!=s[k] and s[j+1]==s[k]:
valor=checking(s,j)
if valor:
answer=j
break
if s[j]!=s[k] and s[j]==s[k-1]:
valor=checking(s,k)
if valor:
answer=k
break
j+=1
k-=1
if valor:print(answer)
else:print(-1)
| [
"[email protected]"
] | |
070bacfa4034a83dfc962b353c22e495e86f20fd | 31ae8cf31da9729a93155fff20f079caf853df98 | /objects.py | 22bb6a1b37da920c06e7828cf0553a7de20b89e4 | [] | no_license | cuthb3rt/physics_sim | afd3ac1e00f64fdefb1ea10c9c1223f60f34c4b9 | 39cee1ca7457ea7a90cdafef41b795210fa7697e | refs/heads/master | 2021-01-19T02:05:37.173117 | 2016-07-21T20:39:17 | 2016-07-21T20:39:17 | 29,778,320 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,301 | py | __author__ = 'Andy'
import physics
import vec_math as vm
class Particle():
"""
Particle class
mass = float
i_p = 3vec
i_v = 3vec
"""
NUM_PARTICLES = 1
ALL_PARTICLES = []
def __repr__(self):
# return "ID: %s; Mass: %s; Position: %s; Velocity: %s; Acceleration: %s" % (self.id, self.m, self.x, self.v, self.a)
return "%s\tm: %s\tx: %s\tv: %s\ta: %s" % (self.id, self.m, vm.v_pretty(self.x), vm.v_pretty(self.v), vm.v_pretty(self.a))
def __init__(self, m, i_x, i_v):
self.id = Particle.NUM_PARTICLES
Particle.NUM_PARTICLES += 1
Particle.ALL_PARTICLES.append(self)
self.m = m
self.x = [float(i) for i in i_x]
self.v = [float(i) for i in i_v]
self.a = vm.NULL_VEC
self.proper_time = 0
def update_acceleration(self):
"""
Calculate acceleration due to all other particles
TODO
force_dict = {self.id: [0, 0, 0]}
set up a dictionary of the force due to each particle
then can have already calculated the force due to most particles by the end time...
will almost halve sim times
:return:
"""
res_f = [0, 0, 0] # resultant force so far
for particle in Particle.ALL_PARTICLES:
if not particle.id == self.id: # don't count force due to itself...
force = physics.calculate_force(self, particle)
res_f = vm.v_add(res_f, force)
# print "Force on %s due to %s = %s" % (self.id, particle.id, res_f)
# print res_f
self.a = vm.v_div(res_f, self.m)
def update_velocity(self, delta_t):
"""
Assume that velocity is initial plus acceleration*time interval
:return:
"""
# print self.a
self.v = vm.v_add(self.v, vm.v_mult(self.a, delta_t))
def update_position(self, delta_t):
"""
Assume that new position is old position plus velocity*time interval
:return:
"""
self.x = vm.v_add(self.x, vm.v_mult(self.v, delta_t))
def iterate(self, delta_t):
self.update_acceleration()
self.update_velocity(delta_t)
self.update_position(delta_t)
self.proper_time += delta_t
| [
"[email protected]"
] | |
a17893e3403ed935e013c8026c259ffe22a74959 | 64ef95039cec3c508b8e3ab911a3318121778119 | /day_3_ai_boot_camp_.py | 40deaa3367a0ea97035e9ce5b03d418a833f1188 | [] | no_license | ALEENA-KT/Practical-AI-Bootcamp | c98f752112e8febb7e7d324ded177f5d36dd0180 | 0a12a5124e4587decec21354f0f0dbbc40ea4fc9 | refs/heads/main | 2023-08-18T02:40:34.992591 | 2021-09-13T18:22:45 | 2021-09-13T18:22:45 | 404,694,854 | 0 | 0 | null | 2021-09-09T12:13:57 | 2021-09-09T11:25:19 | null | UTF-8 | Python | false | false | 3,442 | py | # -*- coding: utf-8 -*-
"""Day 3 AI BOOT CAMP .ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1e_Ee9jcv9rIfmnVXTXQAktNKBwu0GejP
"""
import tensorflow_datasets as tfds
print(tfds.list_builders())
dataloader = tfds.load("cifar10", as_supervised=True)
train, test = dataloader["train"], dataloader["test"]
import tensorflow as tf
directory_url = 'https://storage.googleapis.com/download.tensorflow.org/data/illiad/'
file_names = ['cowper.txt', 'derby.txt', 'butler.txt']
file_paths = [
tf.keras.utils.get_file(file_name, directory_url + file_name)
for file_name in file_names
]
dataset = tf.data.TextLineDataset(file_paths)
import torch
from torch.utils.data import Dataset
from torchvision import datasets
from torchvision.transforms import ToTensor
import matplotlib.pyplot as plt
training_data = datasets.FashionMNIST(
root="data",
train=True,
download=True,
transform=ToTensor()
)
test_data = datasets.FashionMNIST(
root="data",
train=False,
download=True,
transform=ToTensor()
)
import tensorflow as tf
directory_url = 'https://storage.googleapis.com/download.tensorflow.org/data/illiad/'
file_names = ['cowper.txt', 'derby.txt', 'butler.txt']
file_paths = [
tf.keras.utils.get_file(file_name, directory_url + file_name)
for file_name in file_names
]
dataset = tf.data.TextLineDataset(file_paths)
for line in dataset.take(5):
print(line.numpy())
import torch
from torch.utils.data import Dataset
from torchvision import datasets
from torchvision.transforms import ToTensor
from torch.utils.data import DataLoader
import matplotlib.pyplot as plt
training_data = datasets.FashionMNIST(
root="data",
train=True,
download=True,
transform=ToTensor()
)
test_data = datasets.FashionMNIST(
root="data",
train=False,
download=True,
transform=ToTensor()
)
train_dataloader = DataLoader(training_data, batch_size=64, shuffle=True)
test_dataloader = DataLoader(test_data, batch_size=64, shuffle=True)
train_features, train_labels = next(iter(train_dataloader))
print(f"Feature batch shape: {train_features.size()}")
print(f"Labels batch shape: {train_labels.size()}")
img = train_features[0].squeeze()
label = train_labels[0]
plt.imshow(img, cmap="gray")
plt.show()
print(f"Label: {label}")
import tensorflow_datasets as tfds
dataloader = tfds.load("cifar10", as_supervised=True)
train, test = dataloader["train"], dataloader["test"]
train = train.map(
lambda image, label: (tf.image.convert_image_dtype(image, tf.float32), label)
).cache().map(
lambda image, label: (tf.image.random_flip_left_right(image), label)
).map(
lambda image, label: (tf.image.random_contrast(image, lower=0.0, upper=1.0), label)
).shuffle(
100
).batch(
64
).repeat()
import tensorflow as tf
directory_url = 'https://storage.googleapis.com/download.tensorflow.org/data/illiad/'
file_names = ['cowper.txt', 'derby.txt', 'butler.txt']
file_paths = [
tf.keras.utils.get_file(file_name, directory_url + file_name)
for file_name in file_names
]
dataset = tf.data.TextLineDataset(file_paths)
import tensorflow_datasets as tfds
from tensorflow.keras.utils import to_categorical
import tensorflow as tf
import matplotlib.pyplot as plt
from tensorflow.keras.callbacks import EarlyStopping
import tensorflow.keras.backend as K
import numpy as np
from lrfinder import LRFinder | [
"[email protected]"
] | |
95a262821a56a75e0139657f3d8ad7f45772edde | b1edca0e9ea6171493d8cb4232f5c1fc35e853ed | /SVF/tissue-bw-prop.py | 3c9aa9a048fcd01b451a31f5b95daed9a591e3d3 | [] | no_license | leoguignard/Mouse-Atlas | bcceeb2ba56d5adeb1ab2a5590c28b73f84dd865 | d2985fbb6251b60a5830a4d5e7e112a92738a665 | refs/heads/master | 2018-12-20T03:58:10.587284 | 2018-09-17T05:59:33 | 2018-09-17T05:59:33 | 123,352,501 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 14,741 | py | # This file is subject to the terms and conditions defined in
# file 'LICENSE', which is part of this source code package.
# Author: Leo Guignard (guignardl...@[email protected])
from IO import imread, imsave, SpatialImage
from scipy import ndimage as nd
import numpy as np
import os
from multiprocessing import Pool
from TGMMlibraries import lineageTree
from scipy import interpolate
import sys
def get_spherical_coordinates(x, y, z):
''' Computes spherical coordinates for an x, y, z Cartesian position
'''
r = np.linalg.norm([x, y, z])
theta = np.arctan2(y, x)
phi = np.arccos(z/r)
alpha = (np.pi/2 + np.arctan2(x, z)) % (2*np.pi)
return r, theta, phi, alpha
def write_header_am_2(f, nb_points, length):
''' Header for Amira .am files
'''
f.write('# AmiraMesh 3D ASCII 2.0\n')
f.write('define VERTEX %d\n'%(nb_points*2))
f.write('define EDGE %d\n'%nb_points)
f.write('define POINT %d\n'%((length)*nb_points))
f.write('Parameters {\n')
f.write('\tContentType "HxSpatialGraph"\n')
f.write('}\n')
f.write('VERTEX { float[3] VertexCoordinates } @1\n')
f.write('EDGE { int[2] EdgeConnectivity } @2\n')
f.write('EDGE { int NumEdgePoints } @3\n')
f.write('POINT { float[3] EdgePointCoordinates } @4\n')
f.write('VERTEX { float Vcolor } @5\n')
f.write('VERTEX { int Vbool } @6\n')
f.write('EDGE { float Ecolor } @7\n')
f.write('VERTEX { int Vbool2 } @8\n')
def write_to_am_2(path_format, LT_to_print, t_b = None, t_e = None, length = 5, manual_labels = None,
default_label = 5, new_pos = None):
''' Writes a lineageTree into an Amira readable data (.am format).
Args:
path_format: string, path to the output. It should contain 1 %03d where the time step will be entered
LT_to_print: lineageTree, lineageTree to write
t_b: int, first time point to write (if None, min(LT.to_take_time) is taken)
t_e: int, last time point to write (if None, max(LT.to_take_time) is taken)
note: if there is no 'to_take_time' attribute, LT_to_print.time_nodes is considered instead
(historical)
length: int, length of the track to print (how many time before).
manual_labels: {id: label, }, dictionary that maps cell ids to
default_label: int, default value for the manual label
new_pos: {id: [x, y, z]}, dictionary that maps a 3D position to a cell ID.
if new_pos == None (default) then LT_to_print.pos is considered.
'''
if not hasattr(LT_to_print, 'to_take_time'):
LT_to_print.to_take_time = LT_to_print.time_nodes
if t_b is None:
t_b = min(LT_to_print.to_take_time.keys())
if t_e is None:
t_e = max(LT_to_print.to_take_time.keys())
if new_pos is None:
new_pos = LT_to_print.pos
if manual_labels is None:
manual_labels = {}
for t in range(t_b, t_e + 1):
f = open(path_format%t, 'w')
nb_points = len(LT_to_print.to_take_time[t])
write_header_am_2(f, nb_points, length)
points_v = {}
for C in LT_to_print.to_take_time[t]:
C_tmp = C
positions = []
for i in xrange(length):
C_tmp = LT_to_print.predecessor.get(C_tmp, [C_tmp])[0]
positions.append(new_pos[C_tmp])
points_v[C] = positions
f.write('@1\n')
for i, C in enumerate(LT_to_print.to_take_time[t]):
f.write('%f %f %f\n'%tuple(points_v[C][0]))
f.write('%f %f %f\n'%tuple(points_v[C][-1]))
f.write('@2\n')
for i, C in enumerate(LT_to_print.to_take_time[t]):
f.write('%d %d\n'%(2*i, 2*i+1))
f.write('@3\n')
for i, C in enumerate(LT_to_print.to_take_time[t]):
f.write('%d\n'%(length))
f.write('@4\n')
tmp_velocity = {}
for i, C in enumerate(LT_to_print.to_take_time[t]):
for p in points_v[C]:
f.write('%f %f %f\n'%tuple(p))
f.write('@5\n')
for i, C in enumerate(LT_to_print.to_take_time[t]):
f.write('%f\n'%(manual_labels.get(C, default_label)))
f.write('%f\n'%(0))
f.write('@6\n')
for i, C in enumerate(LT_to_print.to_take_time[t]):
f.write('%d\n'%(int(manual_labels.get(C, default_label) != default_label)))
f.write('%d\n'%(0))
f.write('@7\n')
for i, C in enumerate(LT_to_print.to_take_time[t]):
f.write('%f\n'%(np.linalg.norm(points_v[C][0] - points_v[C][-1])))
f.write('@8\n')
for i, C in enumerate(LT_to_print.to_take_time[t]):
f.write('%d\n'%(1))
f.write('%d\n'%(0))
f.close()
def read_param_file():
''' Asks for, reads and formats the parameter file
'''
p_param = raw_input('Please enter the path to the parameter file/folder:\n')
p_param = p_param.replace('"', '')
p_param = p_param.replace("'", '')
p_param = p_param.replace(" ", '')
if p_param[-4:] == '.csv':
f_names = [p_param]
else:
f_names = [os.path.join(p_param, f) for f in os.listdir(p_param) if '.csv' in f and not '~' in f]
for file_name in f_names:
f = open(file_name)
lines = f.readlines()
f.close()
param_dict = {}
i = 0
nb_lines = len(lines)
while i < nb_lines:
l = lines[i]
split_line = l.split(',')
param_name = split_line[0]
if param_name in ['labels', 'downsampling']:
name = param_name
out = []
while (name == param_name or param_name == '') and i < nb_lines:
if split_line[1].isdigit():
out += [int(split_line[1])]
else:
out += [float(split_line[1])]
i += 1
if i < nb_lines:
l = lines[i]
split_line = l.split(',')
param_name = split_line[0]
param_dict[name] = np.array(out)
elif param_name in ['label_names']:
name = param_name
out = []
while (name == param_name or param_name == '') and i < nb_lines:
out += [split_line[1].replace('\n', '').replace('\r', '')]
i += 1
if i < nb_lines:
l = lines[i]
split_line = l.split(',')
param_name = split_line[0]
param_dict[name] = np.array(out)
else:
param_dict[param_name] = split_line[1].strip()
i += 1
if param_name == 'time':
param_dict[param_name] = int(split_line[1])
path_LT = param_dict.get('path_to_LT', '.')
path_VF = param_dict.get('path_to_VF', '.')
path_mask = param_dict.get('path_to_mask', '.')
t = param_dict.get('time', 0)
path_out_am = param_dict.get('path_to_am', '.')
labels = param_dict.get('labels', [])
DS = param_dict.get('downsampling', [])
ani = np.float(param_dict.get('anisotropy', 1.))
path_DB = param_dict.get('path_DB', '.')
path_div = param_dict.get('path_div', None)
path_bary = param_dict.get('path_bary', None)
label_names = param_dict.get('label_names', None)
invert = param_dict.get('invert', '1') != '0'
return (path_LT, path_VF, path_mask, t, path_out_am,
labels, DS, path_DB, path_div, path_bary,
label_names, ani, invert)
def get_division_mapping(path_div, VF):
''' Computes the mapping between found divisions and SVF objects
Args:
path_div: sting, name of the division file
VF: lineageTree
'''
ass_div = {}
if path_div is not None:
f = open(path_div)
lines = f.readlines()
f.close()
divisions_per_time = {}
for l in lines[1:]:
x, y, z, t = np.array(l.split(',')[:-1]).astype(float)
if t in VF.time_nodes:
divisions_per_time.setdefault(int(t), []).append(np.array([x, y, z]) * [1, 1, 5])
div_in_VF = {}
dist_to_div = {}
for t, d in divisions_per_time.iteritems():
idx3d, data = VF.get_idx3d(t)
dist, idxs = idx3d.query(d)
div_C = np.array(data)[idxs]
dist_to_div.update(dict(zip(div_C, dist)))
ass_div.update(dict(zip(div_C, d)))
return ass_div
def write_DB(path_DB, path_div, VF, tracking_value, tb, te):
''' Write the csv database in Database.csv
Args:
path_DB: string, path to the output database
path_div: string, path to the potential division file
VF: lineageTree
tracking_value: {int: int, }, dictionary that maps an object id to a label
tb: int, first time point to write
te: int, last time point to write
'''
ass_div = get_division_mapping(path_div)
f2 = open(path_DB + 'Database.csv', 'w')
f2.write('id, mother_id, x, y, z, r, theta, phi, t, label, D-x, D-y, D-z, D-r, D-theta, D-phi\n')
for t in range(tb, te+1):
for c in VF.time_nodes[t]:
S_p = (-1, -1, -1)
if VF.predecessor.get(c, []) != []:
M_id = VF.predecessor[c][0]
else:
M_id = -1
P = tuple(VF.pos[c])
if path_bary is not None:
S_p = tuple(get_spherical_coordinates(*(barycenters[t] - VF.pos[c]))[:-1])
L = tracking_value.get(c, -1)
D_P = tuple(ass_div.get(c, [-1, -1, -1]))
if path_bary is not None:
D_S_p = (-1, -1, -1) if not c in ass_div else tuple(get_spherical_coordinates(*(barycenters[t] - ass_div[c]))[:-1])
else:
D_S_p = (-1, -1, -1)
f2.write(('%d, %d, %.5f, %.5f, %.5f, %.5f, %.5f, %.5f, %d, %d,' +
'%.5f, %.5f, %.5f, %.5f, %.5f, %.5f\n')%((c, M_id) + P + S_p + (t, L) + D_P + D_S_p))
f2.close()
def get_barycenter(fname, tb, te):
''' Reads and coes a linear piecewise interpolation/extrapolation barycenters
Args:
fname: string, name of the barycenter file (each line as 'x, y, z, t')
tb: first time point to interpolate
te: last time point to interpolate
Returns:
barycenters_interp: {int:[float, float, float], }, dictionary mapping
a time point to the interpolated barycenter at that time
barycenters: {int:[float, float, float], }, dictionary mapping
a time point to the barycenter for each time in fname
'''
f = open(fname)
lines = f.readlines()
f.close()
barycenters = {}
for l in lines:
split_l = l.split(',')
try:
barycenters[int(split_l[-1])] = tuple(float(v) for v in split_l[:-1])
except Exception as e:
pass
times = sorted(barycenters)
Xb, Yb, Zb = np.array([barycenters[t] for t in times]).T
Xb_f = interpolate.InterpolatedUnivariateSpline(times, Xb, k=1)
Yb_f = interpolate.InterpolatedUnivariateSpline(times, Yb, k=1)
Zb_f = interpolate.InterpolatedUnivariateSpline(times, Zb, k=1)
Ti = np.arange(tb - 1, te + 2)
barycenters_interp = dict(zip(Ti, zip(Xb_f(Ti), Yb_f(Ti), Zb_f(Ti))))
return barycenters_interp, barycenters
if __name__ == '__main__':
(path_LT, path_VF, path_mask, t, path_out_am,
labels, DS, path_DB, path_div, path_bary,
label_names, ani, invert) = read_param_file()
if not os.path.exists(path_out_am):
os.makedirs(path_out_am)
if not os.path.exists('mask_images/'):
os.makedirs('mask_images/')
VF = lineageTree(path_VF)
tb = VF.t_b
te = VF.t_e
if path_bary is not None:
try:
barycenters, b_dict = get_barycenter(path_bary, tb, te)
except Exception as e:
print "Wrong file path to barycenter, please specify the path to the .csv file."
print "The process will continue as if no barycenter were provided,"
print "disabling the computation of the spherical coordinates"
print "error raised: ", e
path_bary = None
im = imread(path_mask)
for l in labels:
masked_im = im == l
tmp = nd.binary_opening(masked_im, iterations = 3)
tmp = nd.binary_closing(tmp, iterations = 4)
imsave('mask_images/%03d.tif'%l, SpatialImage(tmp).astype(np.uint8))
mask_dir = 'mask_images/'
masks = sorted([('mask_images/%03d.tif'%l, label_names[i]) for i, l in enumerate(labels)], cmp=lambda x1, x2:cmp(x1[1], x2[1]))
masks = [m[0] for m in masks]
init_cells = {m: set() for m in range(len(masks))}
x_max, y_max, z_max = 0, 0, 0
for i, path_mask in enumerate(masks):
if invert:
mask = imread(path_mask).transpose(1, 0, 2)
mask = mask[:,::-1,:]
else:
mask = imread(path_mask)
max_vals = np.array(mask.shape) - 1
for c in VF.time_nodes[t]:
pos_rounded = np.floor(VF.pos[c]/(np.array(DS)*[1.,1.,ani])).astype(np.int)
pos_rounded = tuple(np.min([max_vals, pos_rounded], axis = 0))
if mask[pos_rounded]:
init_cells[i].add(c)
tracking_value = {}
for t, cs in init_cells.iteritems():
for c in cs:
to_treat = [c]
tracking_value.setdefault(c, set()).add(t)
while to_treat != []:
c_tmp = to_treat.pop()
next_cells = VF.successor.get(c_tmp, [])
to_treat += next_cells
for n in next_cells:
tracking_value.setdefault(n, set()).add(t)
to_treat = [c]
tracking_value.setdefault(c, set()).add(t)
while to_treat != []:
c_tmp = to_treat.pop()
next_cells = VF.predecessor.get(c_tmp, [])
to_treat += next_cells
for n in next_cells:
tracking_value.setdefault(n, set()).add(t)
tracking_value = {k:np.sum(list(v)) for k, v in tracking_value.iteritems() if len(v) == 1}
write_to_am_2(path_out_am + '/seg_t%04d.am', VF, t_b= tb, t_e= te,
manual_labels = tracking_value, default_label = np.max(tracking_value.values())+1,
length = 7)
for im_p in masks:
os.remove(im_p)
write_DB(path_DB, path_div, VF, tracking_value, tb, te)
| [
"[email protected]"
] | |
5f8e1a0fa5bcf1fa053e4be9b091e851fbbb20e0 | 63870f39c2fd700e5474247a4dfc3cb7cbfea7ac | /Power.py | b66588bdb8fe3987dcee302c91a7948cac0ff742 | [] | no_license | DaviPMello27/PythonImageProcessing | 2616e306a79d0d26c7af5106ee0110b6e7bd1d3d | c348cf1a38880a76ddb3e8a8edd3cfbbc21e5df3 | refs/heads/master | 2020-08-23T14:15:59.250354 | 2019-11-08T20:49:10 | 2019-11-08T20:49:10 | 216,636,278 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,307 | py | import matplotlib.pyplot as plt
import cv2
def showImage(title, pos, effect = None):
image = plt.subplot(pos)
image.set_title(title)
image.set_yticks([]), image.set_xticks([])
image.imshow(cv2.cvtColor(img, cv2.COLOR_BGR2RGB), cmap = effect)
def calculateIntensity(image, plot):
intervals = ()
intensities = []
for i in range(256):
intervals = intervals + (i,)
intensities.append(0)
for y in range(image.shape[0]):
for x in range(image.shape[1]):
g = image[y, x]
intensities[g] += 100/(image.shape[0] * image.shape[1])
graph.set_title("Intensity")
graph.set_xlabel("Intensity")
plot.bar(intervals, intensities, align = "edge", width = 0.3)
def transformPow(image, fact):
for y in range(image.shape[0]):
for x in range(image.shape[1]):
image[y,x] = (255/255**fact) * (image[y,x] ** fact)
imgName = input("Filename: ")
intens = float(input("Type the value of the intensity factor: "))
img = cv2.imread(imgName)
graph, graph2 = plt.subplot(224), plt.subplot(223)
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
showImage("Grayscale Image", 221, "gray")
calculateIntensity(img, graph2)
transformPow(img, intens)
showImage("Pow Image", 222)
calculateIntensity(img, graph)
plt.show()
| [
"[email protected]"
] | |
5273b3149612f78e9ebeacd06c2f9328d000c15e | 56c5cbd3629c206fe31da740a3213040464a5483 | /driver/views.py | fce79dd6a5c59fe9aa1c00a9f05c50185b4b3a9e | [] | no_license | AhmedYasser27/Fleet-MS | f211df471743eb78130ebc858d52a6016f8951f1 | 06e2395406956482f56de1df5029985bf37c4441 | refs/heads/master | 2022-12-10T01:16:59.008445 | 2020-09-04T20:56:45 | 2020-09-04T20:56:45 | 292,945,204 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,378 | py | from django.shortcuts import render,get_object_or_404,redirect
from django.http import HttpResponse
from django.http import Http404
from django.template import loader
from .models import Driver
from .forms import DriverForm
# Create your views here.
def index(request):
if request.user.is_authenticated:
form=DriverForm()
return render(request,'driver/index.html',{'form':form})
else:
return redirect("http://localhost:8000/home/404")
def driver(request):
if request.POST:
form=DriverForm(request.POST)
if form.is_valid():
form.save()
success_message='Driver registered'
form=DriverForm()
return render(request,'driver/index.html',{'form':form,'success' : success_message})
else:
if request.user.is_authenticated:
form=DriverForm()
error_message='Something went wrong error'
return render(request,'driver/index.html',{ 'form' : form ,'error':error_message})
else:
return redirect("http://localhost:8000/home/404")
def drivers(request):
if request.POST:
form=DriverForm(request.POST)
return render(request,'driver/index.html',{'form':form})
else:
if request.user.is_authenticated:
drivers = Driver.objects.all()
return render(request,'driver/driverlist.html',{ 'drivers' : drivers ,'user':request.user})
else:
return redirect("http://localhost:8000/home/404")
def delete(request,id):
if request.POST:
return render(request,'driver/index.html',{'form':form})
else:
if request.user.is_authenticated:
drivers = Driver.objects.get(id=id)
drivers.delete()
return redirect('http://localhost:8000/driver/drivers')
else:
return redirect("http://localhost:8000/home/404")
def edit(request,id):
if request.method == "POST":
driver=Driver.objects.get(id=id)
form=DriverForm(request.POST,instance=driver)
if form.is_valid():
form.save()
return redirect('http://localhost:8000/driver/drivers')
elif request.user.is_authenticated:
driver=Driver.objects.get(id=id)
form=DriverForm(instance=driver)
return render(request,'driver/driverEdit.html',{ 'form' : form ,'id':id})
| [
"[email protected]"
] | |
9c726b92873e564d1807d53aeb25eb416f88fba3 | e6c65e2e354336a4bea5b6a4ccbccd3682915fe2 | /out-bin/py/google/fhir/seqex/bundle_to_seqex_test.runfiles/pypi__apache_beam_2_9_0/apache_beam/runners/worker/sideinputs_test.py | 57d59bfa69ad81880b5237c6baf3ea3f0406a320 | [
"Apache-2.0"
] | permissive | rasalt/fhir-datalab | c30ab773d84983dd04a37e9d0ddec8bf2824b8a4 | 3e329fc8b4226d3e3a4a7c23c306a86e7a9ea0de | refs/heads/master | 2021-10-09T05:51:04.593416 | 2018-12-21T18:11:03 | 2018-12-22T05:38:32 | 162,744,237 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 155 | py | /home/rkharwar/.cache/bazel/_bazel_rkharwar/0ddaa3627472ad9d1367a008236ce2f5/external/pypi__apache_beam_2_9_0/apache_beam/runners/worker/sideinputs_test.py | [
"[email protected]"
] | |
9b65587d2edd34c01f8d3c9311f82ec3d053bda6 | 0d54e167332199c80e75fa00489dac6c590e3ff3 | /MFE.py | 15057e6203a76b55cfff767ae4d8b46692216e6f | [] | no_license | TudorCretu/PI-LSTM | 4ab1cea8e2ec62a31ce41f6c49b367ca9e47f638 | ea2efa71f722746900915c38bb2729805282c82a | refs/heads/master | 2022-07-22T15:01:57.924019 | 2020-05-18T16:32:28 | 2020-05-18T16:32:28 | 264,999,161 | 4 | 0 | null | null | null | null | UTF-8 | Python | false | false | 15,477 | py | import numpy as np
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import h5py
Lx = 1.75 * np.pi
Lz = 1.2 * np.pi
Re = 600
X = 0
Y = 1
Z = 2
alpha = 2 * np.pi / Lx
beta = np.pi / 2
gamma = 2 * np.pi / Lz
Kay = np.sqrt(alpha ** 2 + gamma ** 2)
Kby = np.sqrt(beta ** 2 + gamma ** 2)
Kaby = np.sqrt(alpha ** 2 + beta ** 2 + gamma ** 2)
N8 = 2 * np.sqrt(2) / np.sqrt((alpha ** 2 + gamma ** 2) * (4 * alpha ** 2 + 4 * gamma ** 2 + np.pi ** 2))
# Domain is 0 < x < Lx ; -1 < y < 1; 0 < z < Lz
def da1(a):
return beta ** 2 / Re - beta ** 2 / Re * a[0] - np.sqrt(3 / 2) * beta * gamma / Kaby * a[5] * a[7] + np.sqrt(
3 / 2) * beta * gamma / Kby * a[1] * a[2]
def da2(a):
return -(4 * beta ** 2 / 3 + gamma ** 2) * a[1] / Re + 5 * np.sqrt(2) * gamma ** 2 / (3 * np.sqrt(3) * Kay) * a[3] \
* a[5] - \
gamma ** 2 / (np.sqrt(6) * Kay) * a[4] * a[6] - alpha * beta * gamma / (np.sqrt(6) * Kay * Kaby) * a[4] * a[
7] - \
np.sqrt(3 / 2) * beta * gamma / Kby * (a[0] * a[2] + a[2] * a[8])
def da3(a):
return -(beta ** 2 + gamma ** 2) / Re * a[2] + 2 / np.sqrt(6) * alpha * beta * gamma / (Kay * Kby) * (
a[3] * a[6] + a[4] * a[5]) + \
(beta ** 2 * (3 * alpha ** 2 + gamma ** 2) - 3 * gamma ** 2 * (alpha ** 2 + gamma ** 2)) / (
np.sqrt(6) * Kaby * Kby * Kay) * a[3] * a[7]
def da4(a):
return -(3 * alpha ** 2 + 4 * beta ** 2) / (3 * Re) * a[3] - alpha / np.sqrt(6) * a[0] * a[4] - 10 / (
3 * np.sqrt(6)) * alpha ** 2 / Kay * a[1] * a[5] - \
np.sqrt(3 / 2) * alpha * beta * gamma / (Kay * Kby) * a[2] * a[6] - np.sqrt(
3 / 2) * alpha ** 2 * beta ** 2 / (Kay * Kby * Kaby) * a[2] * a[7] - \
alpha / np.sqrt(6) * a[4] * a[8]
def da5(a):
return -(alpha ** 2 + beta ** 2) / Re * a[4] + alpha / np.sqrt(6) * a[0] * a[3] + alpha ** 2 / (np.sqrt(6) * Kay) \
* a[1] * a[6] - \
alpha * beta * gamma / (np.sqrt(6) * Kay * Kaby) * a[1] * a[7] + alpha / np.sqrt(6) * a[3] * a[
8] + 2 / np.sqrt(6) * alpha * beta * gamma / (Kay * Kby) * a[2] * a[5]
def da6(a):
return -(3 * alpha ** 2 + 4 * beta ** 2 + 3 * gamma ** 2) / (3 * Re) * a[5] + alpha / np.sqrt(6) * a[0] * a[6] + \
np.sqrt(3 / 2) * beta * gamma / Kaby * a[0] * a[7] + 10 / (3 * np.sqrt(6)) * (
alpha ** 2 - gamma ** 2) / Kay * a[1] * a[3] - \
2 * np.sqrt(2 / 3) * alpha * beta * gamma / (Kay * Kby) * a[2] * a[4] + alpha / np.sqrt(6) * a[6] * a[
8] + np.sqrt(3 / 2) * beta * gamma / Kaby * a[7] * a[8]
def da7(a):
return -(alpha ** 2 + beta ** 2 + gamma ** 2) / Re * a[6] - alpha / np.sqrt(6) * (a[0] * a[5] + a[5] * a[8]) + \
np.sqrt(1 / 6) * (gamma ** 2 - alpha ** 2) / Kay * a[1] * a[4] + np.sqrt(1 / 6) * alpha * beta * gamma / (
Kay * Kby) * a[2] * a[3]
def da8(a):
return -(alpha ** 2 + beta ** 2 + gamma ** 2) / Re * a[7] + 2 / np.sqrt(6) * alpha * beta * gamma / (Kay * Kaby) * \
a[1] * a[4] + \
gamma ** 2 * (3 * alpha ** 2 - beta ** 2 + 3 * gamma ** 2) / (np.sqrt(6) * Kay * Kby * Kaby) * a[2] * a[3]
def da9(a):
return -9 * beta ** 2 / Re * a[8] + np.sqrt(3 / 2) * beta * gamma / Kby * a[1] * a[2] - np.sqrt(
3 / 2) * beta * gamma / Kaby * a[5] * a[7]
def model(a):
return np.array([da1(a),
da2(a),
da3(a),
da4(a),
da5(a),
da6(a),
da7(a),
da8(a),
da9(a)])
def u1(p):
return np.array([np.sqrt(2) * np.sin(np.pi * p[Y] / 2),
0,
0])
def u2(p):
return np.array([4/np.sqrt(3) * np.cos(np.pi * p[Y] / 2)**2 * np.cos(gamma*p[Z]),
0,
0])
def u3(p):
return 2/np.sqrt(4 * gamma**2 + np.pi**2) * np.array([0,
2 * gamma * np.cos(np.pi * p[Y] / 2) * np.cos(gamma*p[Z]),
np.pi * np.sin(np.pi * p[Y] / 2) * np.sin(gamma * p[Z])])
def u4(p):
return np.array([0,
0,
4/np.sqrt(3) * np.cos(alpha * p[X]) * np.cos(np.pi * p[Y] / 2)**2])
def u5(p):
return np.array([0,
0,
2 * np.sin(alpha * p[X]) * np.sin(np.pi * p[Y] / 2)])
def u6(p):
return 4*np.sqrt(2)/np.sqrt(3 * (alpha**2 + gamma**2)) * np.array([
-gamma*np.cos(alpha*p[X])*np.cos(np.pi*p[Y]/2)**2*np.sin(gamma*p[Z]),
0,
alpha*np.sin(alpha*p[X])*np.cos(np.pi*p[Y]/2)**2*np.cos(gamma*p[Z])])
def u7(p):
return 2*np.sqrt(2)/np.sqrt(alpha**2 + gamma**2) * np.array([
gamma*np.sin(alpha*p[X])*np.sin(np.pi*p[Y]/2)*np.sin(gamma*p[Z]),
0,
alpha*np.cos(alpha*p[X])*np.sin(np.pi*p[Y]/2)*np.cos(gamma*p[Z])])
def u8(p):
return N8 * np.array([np.pi * alpha * np.sin(alpha*p[X])*np.sin(np.pi*p[Y]/2)*np.sin(gamma*p[Z]),
2*(alpha**2 + gamma**2) * np.cos(alpha*p[X]) * np.cos(np.pi*p[Y]/2) * np.sin(gamma*p[Z]),
-np.pi * gamma * np.cos(alpha*p[X]) * np.sin(np.pi*p[Y]/2) * np.cos(gamma*p[Z])])
def u9(p):
return np.array([np.sqrt(2) * np.sin(3 * np.pi * p[Y] / 2),
0,
0])
def make_grid(nx, ny, nz):
x = np.linspace(0, Lx, nx)
y = np.linspace(-1, 1, ny)
z = np.linspace(0, Lz, nz)
return x, y, z
def generate_u(x, y, z):
u_0 = np.zeros([9, len(x), len(y), len(z), 3])
for ix, px in enumerate(x):
for iy, py in enumerate(y):
for iz, pz in enumerate(z):
u_0[0][ix][iy][iz] = u1([px, py, pz])
u_0[1][ix][iy][iz] = u2([px, py, pz])
u_0[2][ix][iy][iz] = u3([px, py, pz])
u_0[3][ix][iy][iz] = u4([px, py, pz])
u_0[4][ix][iy][iz] = u5([px, py, pz])
u_0[5][ix][iy][iz] = u6([px, py, pz])
u_0[6][ix][iy][iz] = u7([px, py, pz])
u_0[7][ix][iy][iz] = u8([px, py, pz])
u_0[8][ix][iy][iz] = u9([px, py, pz])
return u_0
def calculate_velocities(x, y, z, a0, u_0):
u = np.zeros([len(x), len(y), len(z), 3])
for ix, px in enumerate(x):
for iy, py in enumerate(y):
for iz, pz in enumerate(z):
u[ix][iy][iz] += a0[0] * u_0[0, ix, iy, iz]
u[ix][iy][iz] += a0[1] * u_0[1, ix, iy, iz]
u[ix][iy][iz] += a0[2] * u_0[2, ix, iy, iz]
u[ix][iy][iz] += a0[3] * u_0[3, ix, iy, iz]
u[ix][iy][iz] += a0[4] * u_0[4, ix, iy, iz]
u[ix][iy][iz] += a0[5] * u_0[5, ix, iy, iz]
u[ix][iy][iz] += a0[6] * u_0[6, ix, iy, iz]
u[ix][iy][iz] += a0[7] * u_0[7, ix, iy, iz]
u[ix][iy][iz] += a0[8] * u_0[8, ix, iy, iz]
return u
def calculate_vorticity(x, y, z, u):
w = np.zeros([len(u), len(x), len(y), len(z), 3])
dx = x[1] - x[0]
dy = y[1] - y[0]
dz = z[1] - z[0]
dux_dy, dux_dz = np.gradient(u[:, :, :, :, X], dy, dz, axis=(2, 3))
duy_dx, duy_dz = np.gradient(u[:, :, :, :, Y], dx, dz, axis=(1, 3))
duz_dx, duz_dy = np.gradient(u[:, :, :, :, Z], dx, dy, axis=(1, 2))
w[:, :, :, :, X] = duz_dy - duy_dz
w[:, :, :, :, Y] = dux_dz - duz_dx
w[:, :, :, :, Z] = duy_dx - dux_dy
return w
def plot_mean_profile(a):
x, y, z = make_grid(10, 100, 10)
u_0 = generate_u(x, y, z)
u = calculate_velocities(x, y, z, a, u_0)
ux_mean = np.zeros([len(y)])
for ix, px in enumerate(x):
for iy, py in enumerate(y):
for iz, pz in enumerate(z):
ux_mean[iy] += u[ix][iy][iz][X]
N = len(x) * len(z)
ux_mean /= N
axes = plt.gca()
axes.set_xlim([-1, 1])
axes.set_ylim([-1, 1])
axes.set(xlabel="$u_x$", ylabel='y')
axes.plot(ux_mean, y)
plt.show()
def plot_statistics(history, true_future, prediction, model_name=None):
fig, axs = plt.subplots(nrows=3, ncols=3, figsize=(12, 12))
gs1 = gridspec.GridSpec(3, 3)
print("started statistics")
x, y, z = make_grid(25, 50, 25)
u_0 = generate_u(x, y, z)
sl = slice(0, None, 50)
true_future = true_future[sl]
prediction = prediction[sl]
true_u = []
for a in true_future:
true_u.append(calculate_velocities(x, y, z, a, u_0))
true_u = np.array(true_u)
predicted_u = []
for a in prediction:
predicted_u.append(calculate_velocities(x, y, z, a, u_0))
predicted_u = np.array(predicted_u)
print("started plotting")
u_mean_true = np.average(true_u, axis=(0, 1, 3))
u_mean_predicted = np.average(predicted_u, axis=(0, 1, 3))
ux_mean_true = u_mean_true[:, X]
ux_mean_predicted = u_mean_predicted[:, X]
ux_square_mean_true = np.average(np.square(true_u - np.mean(true_u, axis=0)), axis=(0, 1, 3))[:, X]
ux_square_mean_predicted = np.average(np.square(predicted_u - np.mean(predicted_u, axis=0)), axis=(0, 1, 3))[:, X]
ux_third_mean_true = np.average(np.power(true_u, 3), axis=(0, 1, 3))[:, X]
ux_third_mean_predicted = np.average(np.power(predicted_u, 3), axis=(0, 1, 3))[:, X]
ux_fourth_mean_true = np.average(np.power(true_u, 4), axis=(0, 1, 3))[:, X]
ux_fourth_mean_predicted = np.average(np.power(predicted_u, 4), axis=(0, 1, 3))[:, X]
# # v_square_true = np.add(np.square(true_u[:,:,:,:,Y]), np.square(true_u[:,:,:,:,Z]))
# v_square_true =
# # v_square_predicted = np.add(np.square(predicted_u[:,:,:,:,Y]), np.square(predicted_u[:,:,:,:,Z]))
# v_square_predicted =
v_square_mean_true = np.average(np.square(true_u[:, :, :, :, Y]), axis=(0, 1, 3))
v_square_mean_predicted = np.average(np.square(predicted_u[:, :, :, :, Y]), axis=(0, 1, 3))
uv_mean_true = np.average(np.multiply(true_u[:, :, :, :, Y], true_u[:,:,:,:,X]), axis=(0, 1, 3))
uv_mean_predicted = np.average(np.multiply(predicted_u[:, :, :, :, Y], predicted_u[:,:,:,:,X]), axis=(0, 1, 3))
w_true = calculate_vorticity(x, y, z, true_u)
w_pred = calculate_vorticity(x, y, z, predicted_u)
wx_rms_true = np.std(w_true[:, :, :, :, X] - np.mean(w_true[:, :, :, :, X], axis=0), axis=(0, 1, 3))
wy_rms_true = np.std(w_true[:, :, :, :, Y] - np.mean(w_true[:, :, :, :, Y], axis=0), axis=(0, 1, 3))
wz_rms_true = np.std(w_true[:, :, :, :, Z] - np.mean(w_true[:, :, :, :, Z], axis=0), axis=(0, 1, 3))
wx_rms_pred = np.std(w_pred[:, :, :, :, X] - np.mean(w_pred[:, :, :, :, X], axis=0), axis=(0, 1, 3))
wy_rms_pred = np.std(w_pred[:, :, :, :, Y] - np.mean(w_pred[:, :, :, :, Y], axis=0), axis=(0, 1, 3))
wz_rms_pred = np.std(w_pred[:, :, :, :, Z] - np.mean(w_pred[:, :, :, :, Z], axis=0), axis=(0, 1, 3))
ax = plt.subplot(gs1[0])
# ax.set_xlim([-1, 1])
ax.set_ylim([-1, 1])
ax.set(xlabel=r"$\overline{u}$", ylabel='y')
ax.plot(ux_mean_true, y, label='True profile')
ax.plot(ux_mean_predicted, y, label='Predicted Profile')
ax.legend(loc='upper left')
ax = plt.subplot(gs1[1])
# ax.set_xlim([-1, 1])
ax.set_ylim([-1, 1])
ax.set(xlabel=r"$\overline{u^2}$", ylabel='y')
ax.plot(ux_square_mean_true, y, label='True profile')
ax.plot(ux_square_mean_predicted, y, label='Predicted Profile')
ax.legend(loc='upper left')
ax = plt.subplot(gs1[2])
# ax.set_xlim([-1, 1])
ax.set_ylim([-1, 1])
ax.set(xlabel=r"$\overline{uv}$", ylabel='y')
ax.plot(uv_mean_true, y, label='True profile')
ax.plot(uv_mean_predicted, y, label='Predicted Profile')
ax.legend(loc='upper left')
ax = plt.subplot(gs1[3])
# ax.set_xlim([-1, 1])
ax.set_ylim([-1, 1])
ax.set(xlabel=r"$\overline{v^2}$", ylabel='y')
ax.plot(v_square_mean_true, y, label='True profile')
ax.plot(v_square_mean_predicted, y, label='Predicted Profile')
ax.legend(loc='upper left')
ax = plt.subplot(gs1[4])
# ax.set_xlim([-1, 1])
ax.set_ylim([-1, 1])
ax.set(xlabel=r"$\overline{u^3}$", ylabel='y')
ax.plot(ux_third_mean_true, y, label='True profile')
ax.plot(ux_third_mean_predicted, y, label='Predicted Profile')
ax.legend(loc='upper left')
ax = plt.subplot(gs1[5])
# ax.set_xlim([-1, 1])
ax.set_ylim([-1, 1])
ax.set(xlabel=r"$\overline{u^4}$", ylabel='y')
ax.plot(ux_fourth_mean_true, y, label='True profile')
ax.plot(ux_fourth_mean_predicted, y, label='Predicted Profile')
ax.legend(loc='upper left')
ax = plt.subplot(gs1[6])
# ax.set_xlim([-1, 1])
ax.set_ylim([-1, 1])
ax.set(xlabel=r"$\omega_{x,rms}$", ylabel='y')
ax.plot(wx_rms_true, y, label='True profile')
ax.plot(wx_rms_pred, y, label='Predicted Profile')
ax.legend(loc='upper left')
ax = plt.subplot(gs1[7])
# ax.set_xlim([-1, 1])
ax.set_ylim([-1, 1])
ax.set(xlabel=r"$\omega_{y,rms}$", ylabel='y')
ax.plot(wy_rms_true, y, label='True profile')
ax.plot(wy_rms_pred, y, label='Predicted Profile')
ax.legend(loc='upper left')
ax = plt.subplot(gs1[8])
# ax.set_xlim([-1, 1])
ax.set_ylim([-1, 1])
ax.set(xlabel=r"$\omega_{z,rms}$", ylabel='y')
ax.plot(wz_rms_true, y, label='True profile')
ax.plot(wz_rms_pred, y, label='Predicted Profile')
ax.legend(loc='upper left')
plt.show()
def plot_dataset(fln):
# train time 0 -> 52K
# valid time 52K -> 68K
# test time 68K -> 80K
# train time 0 -> 208K
# valid time 208K -> 272K
# test time 272K -> 320K
hf = h5py.File(fln, 'r')
u = np.array(hf.get('/u'))
t = np.array(hf.get('/t'))
plt.figure(1)
plt.subplot(511)
plt.plot(t, u[:, 0])
plt.subplot(512)
plt.plot(t, u[:, 1])
plt.subplot(513)
plt.plot(t, u[:, 2])
plt.subplot(514)
plt.plot(t, u[:, 3])
plt.subplot(515)
plt.plot(t, u[:, 4])
plt.figure(2)
plt.subplot(511)
plt.plot(t, u[:, 5])
plt.subplot(512)
plt.plot(t, u[:, 6])
plt.subplot(513)
plt.plot(t, u[:, 7])
plt.subplot(514)
plt.plot(t, u[:, 8])
plt.show()
plt.figure(3)
from scipy.signal import find_peaks
u0 = u[:, 0]
peaks, properties = find_peaks(u0, prominence=0.3, width=100)
plt.plot(u0)
plt.plot(peaks, u0[peaks], "x")
plt.vlines(x=peaks, ymin=u0[peaks] - properties["prominences"],
ymax = u0[peaks], color = "C1")
plt.hlines(y=properties["width_heights"], xmin=properties["left_ips"],
xmax = properties["right_ips"], color = "C1")
plt.show()
print(peaks)
plt.figure(4)
from scipy.signal import find_peaks
u0 = u[:, 0]
peaks, properties = find_peaks(u0, prominence=0.5, width=100)
plt.plot(u0)
plt.plot(peaks, u0[peaks], "x")
plt.vlines(x=peaks, ymin=u0[peaks] - properties["prominences"],
ymax = u0[peaks], color = "C1")
plt.hlines(y=properties["width_heights"], xmin=properties["left_ips"],
xmax = properties["right_ips"], color = "C1")
plt.show()
print(peaks)
if __name__ == '__main__':
plot_dataset('data/MFE.h5')
| [
"[email protected]"
] | |
450531988b753188c27f8d2709248ab92e7c0e5c | cf0fd44aa791b5ee547b436c14700ff45ac7944e | /panorama-stitching/stitch.py | 4c22bdf66a48c93a0d58684e9c4257931d5308df | [] | no_license | danield0garu/computer-vision | 1186e2ba76312af4382df6663961f45635aa4e3d | b0805859c8ae1fa255b7e6c892394adc06e749cc | refs/heads/master | 2021-09-10T21:21:49.679892 | 2018-04-02T12:01:12 | 2018-04-02T12:01:12 | 112,088,082 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,226 | py | from pyimagesearch.panorama import Stitcher
import argparse
import imutils
import cv2
# construct the argument parse and parse the arguments
"""
ap = argparse.ArgumentParser()
ap.add_argument("-f", "--first", required=True,
help="path to the first image")
ap.add_argument("-s", "--second", required=True,
help="path to the second image")
args = vars(ap.parse_args())
"""
# load the two images and resize them to have a width of 400 pixels
# (for faster processing)
imageA = cv2.imread("images/image1.jpg")
imageB = cv2.imread("images/image2.jpg")
#imageA = cv2.imread("images/office2.jpg")
#imageB = cv2.imread("images/office1.jpg")
#imageA = cv2.imread("images/officeOutsideLeft.jpg")
#imageB = cv2.imread("images/officeOutsideRight.jpg")
#imageA = cv2.imread("images/colegLeft.jpg")
#imageB = cv2.imread("images/colegRight.jpg")
imageA = imutils.resize(imageA, width=400)
imageB = imutils.resize(imageB, width=400)
# stitch the images together to create a panorama
stitcher = Stitcher()
(result, vis) = stitcher.stitch([imageA, imageB], showMatches=True)
# show the images
cv2.imshow("Image A", imageA)
cv2.imshow("Image B", imageB)
cv2.imshow("Keypoint Matches", vis)
cv2.imshow("Result", result)
cv2.waitKey(0) | [
"[email protected]"
] | |
8835abd75b08767de42f6adfcaa8726b27a17627 | 2a40963fc6af9a2fcf917bb2dba4d223d3249987 | /apps/course/urls.py | 0c5515c5bd2dc6260c06a37e53cfe06aa8dee805 | [] | no_license | hiimkelvin/courses_django | 63736337a50919b6948811ffd51fdaa5fe7b7c74 | 6f3fd0d2d85dd918b1154ac63de891bd61e9caad | refs/heads/master | 2021-01-20T01:32:59.570678 | 2017-04-24T18:26:44 | 2017-04-24T18:26:44 | 89,293,991 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 239 | py | from django.conf.urls import url
from . import views
urlpatterns = [
url(r'^$', views.index),
url(r'^addnew$', views.addnew),
url(r'^confirm/(?P<id>\d+)$', views.confirm_page),
url(r'^remove/(?P<id>\d+)$', views.remove)
]
| [
"[email protected]"
] | |
7af9568b63838fbfb2206906589c9512df1ae16a | 6512957d7a359c633aaaed63b9fd44eb132b0d0f | /parser.py | 2db19836c75dfd97b0365cdb2154995535083a95 | [] | no_license | j-ibad/cpsc323-compiler-py | 78aabb57de8af4e7399c0a51454e465ec90d9ac8 | 6f9835ff74cc9b74ccb93733aef65ae7ba189318 | refs/heads/main | 2023-04-20T13:49:31.690254 | 2021-05-13T02:28:05 | 2021-05-13T02:28:05 | 361,184,289 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 24,447 | py | #!/usr/bin/env python3
'''
Project Name: Project 2 - Syntax Analyzer
Class: CPSC 323 - 02, Spring 2021
Professor: Prof. Anthony Le
Authors: Winnie Pan
Josh Ibad
Titus Sudarno
Thomas-James Le
'''
import lexer
import sys
import re
import getopt
#Global variable to help when multiple files are processed
firstFile = True
#List of types recognized by compiler
types = ["int", "float", "bool"]
''' TreeNode class
TreeNode class, for representing non-leaf nodes for the internal Parse Tree.
The internal Parse Tree uses the TreeNode clas for non-leaf nodes, storing the
type of the non-terminal expression, along with an adjacency list of its
children. Leaf nodes are simply stored as tokens.
'''
class TreeNode:
'''Constructor:
Creates an internal, non-leaf node for the ParseTree storing the non-terminal
expression, and instantiates an empty adjacency list of its children.
@param val - Non-terminal expression of node
'''
def __init__(self, val):
self.val = val
self.children = []
'''
Adds a child to the adjacency list of the TreeNode. By default, adds the
new child to the tail of the list.
@param child - Child of TreeNode to be added to the adjacency list
@param index - Index at list in which to add child. Defaults to tail
'''
def addChild(self, child, index=None):
if index is None:
self.children.append(child)
else:
self.children.insert(index, child)
'''
Prints the subtree recursively, in preorder fashion. First prints the type
of the current node, then prints its children. If the child is a non-leaf
node, then the function is called recursively on the non-leaf TreeNode. If
the child is a leaf node, the token is simply printed. Printing keeps track
of the level of the tree, and formats the output with the spacer.
@param level - Current height of the tree. Defaults to 0 for root
@param spacer - String to prepend to all print statements for spacing
'''
def printSubtree(self, level=0, spacer=""):
print(spacer + '["%s"\theight: %d, ' % (self.val, level) + "Children: {")
for child in self.children:
if isinstance(child, TreeNode):
child.printSubtree(level+1, spacer + " ")
else:
print(spacer, end=" ")
print(child)
print(spacer + "} End of (%s, %d)]" % (self.val, level))
''' Parser Class
Class for parsing a file and performing syntax analysis. The class internally
calls a lexer on the input file. The resultant token-lexeme list is then passed
to the Parser for Syntax Analysis, using the Recursive Descent Parser method.
The Parser prints tokens along with production grammar rules matched to them.
After the whole file is analyzed, the resultant parse tree is also printed.
'''
class Parser:
# Constructor
# Runs the lexer to analyze the input file. Then, performs syntax analysis
# on the tokens received, outputting to the output file.
# Generates a parse tree.
def __init__(self, fIn, fOut):
#Initilize tracking variables
self.index = 0
self.filename = fIn
self.token = None
self.printBuffer = []
#Perform lexical analysis
self.tokens = lexer.lexer(fIn)
if self.tokens is None or self.tokens[0][0] == -1:
print("Could not analyze file. Check if file exists and is readable.")
exit()
self.realStdOut = sys.stdout
#File output
global firstFile
if fOut:
sys.stdout = open(fOut, "w" if firstFile else "a+")
firstFile = False
#PARSE TREE VARIABLES
print("[---Analysis of \"%s\"---]\n" % fIn)
self.parseTree = self.statementList()
print("\nPrinting Parse Tree:\n")
self.parseTree.printSubtree()
print("\n[---Successful end of \"%s\"---]\n" % fIn)
sys.stdout = self.realStdOut
# Iterates to the next token in the list, printing it to output.
# If no more tokens to iterate over, an error is printed.
def nextToken(self):
if self.index >= len(self.tokens):
#No more tokens error
self.printError("Unexpected end of file. Expected more tokens.")
self.token = self.tokens[self.index]
#Write token
#print("Token:\t%-16s Lexeme:\t%s" % (self.token[0], self.token[1]))
print("Token:\t%-10s @%4d,%-4d Lexeme:\t%s" % (self.token[0], self.token[2][0], self.token[2][1], self.token[1]))
self.index += 1
# Peeks at the next token if one exists. Otherwise, None is returned
def peekToken(self):
if self.index < len(self.tokens):
return self.tokens[self.index]
else:
return None
# Removes the next token from the token list, and sets it as current token.
# Used for removing tokens which are appended to others when reinterpretted.
def popNextToken(self):
if self.index < len(self.tokens):
self.token = self.tokens.pop(self.index)
#Write token
print("Token:\t%-16s @%4d,%-4d Lexeme:\t%s" % (self.token[0], self.token[2][0], self.token[2][1], self.token[1]))
return self.token
else:
self.printError("Unexpected end of file. Expected more tokens.")
# Prints an error message
def printError(self, errorMsg):
print("%s:%d:%d: Error: %s" % (self.filename, self.token[2][0], self.token[2][1], errorMsg))
if sys.stdout != self.realStdOut:
sys.stdout = self.realStdOut
print("%s:%d:%d: Error: %s" % (self.filename, self.token[2][0], self.token[2][1], errorMsg))
exit()
# Special error that prints the unexpected token along with the error message
def printUnexpectedError(self, errorMsg, errorType="Error"):
print('%s:%d:%d: %s: Unexpected %s token "%s". %s' % (self.filename, self.token[2][0], self.token[2][1], errorType, self.token[0], self.token[1], errorMsg))
if sys.stdout != self.realStdOut:
sys.stdout = self.realStdOut
print('%s:%d:%d: %s: Unexpected %s token "%s". %s' % (self.filename, self.token[2][0], self.token[2][1], errorType, self.token[0], self.token[1], errorMsg))
exit()
# Prints everything in the print buffer
def flushPrintBuffer(self):
while self.printBuffer:
print( self.printBuffer.pop(0) )
# Expression
# Production rules: <StatementList> -> <Statement> <StatementList> | <empty>
# Represented in parse tree as non-leaf node with value "SL"
# The root of the parse tree is a statement list
def statementList(self, ending=None):
subRoot = None
currNode = None
if isinstance(ending, list):
while (self.peekToken() is not None) and (self.peekToken()[1] not in ending):
#Create new Tree Node for SL
nxtNode = TreeNode('SL')
if subRoot is None:
currNode = nxtNode
subRoot = currNode
else:
currNode.addChild(nxtNode) #Adds SL as child of parent
currNode = nxtNode
self.printBuffer.append("\t<StatementList> -> <Statement> <StatementList> | <empty>")
currNode.addChild( self.statement() )
if (self.peekToken() is not None) and (self.peekToken()[1] == ';'):
self.nextToken()
currNode.addChild( self.token )
elif isinstance(ending, str):
while (self.peekToken() is not None) and (self.peekToken()[1] != ending):
#Create new Tree Node for SL
nxtNode = TreeNode('SL')
if subRoot is None:
currNode = nxtNode
subRoot = currNode
else:
currNode.addChild(nxtNode) #Adds SL as child of parent
currNode = nxtNode
self.printBuffer.append("\t<StatementList> -> <Statement> <StatementList> | <empty>")
currNode.addChild( self.statement() )
if (self.peekToken() is not None) and (self.peekToken()[1] == ';'):
self.nextToken()
currNode.addChild( self.token )
else:
while self.peekToken() is not None:
#Create new Tree Node for SL
nxtNode = TreeNode('SL')
if subRoot is None:
currNode = nxtNode
subRoot = currNode
else:
currNode.addChild(nxtNode) #Adds SL as child of parent
currNode = nxtNode
self.printBuffer.append("\t<StatementList> -> <Statement> <StatementList> | <empty>")
currNode.addChild( self.statement() )
if (self.peekToken() is not None) and (self.peekToken()[1] == ';'):
self.nextToken()
currNode.addChild( self.token )
self.flushPrintBuffer()
return subRoot
# Statement
# Production rules: <Statement> -> <Assign> | <Declarative> | begin <StatementList> end
# if <Conditional> then <StatementList> else <StatementList> endif |
# if <Conditional> then <StatementList> endif |
# while <Conditional> do <StatementList> whileend | begin <StatementList> end
# Represented in parse tree as non-leaf node with value "S"
def statement(self):
currNode = TreeNode("S")
print("") #Padding between statements for a cleaner look
self.nextToken()
self.flushPrintBuffer()
if self.token[1] == "begin":
print("\t<Statement> -> begin <StatementList> end")
currNode.addChild( self.token )
currNode.addChild( self.statementList("end") )
if self.peekToken() is not None and self.peekToken()[1] == "end":
self.nextToken()
currNode.addChild( self.token )
else: #ERROR: Needs "end"
self.printError('Expected keyword "end" after statement-list')
#Assignment and Declarations
elif self.token[0] == "IDENTIFIER":
print("\t<Statement> -> <Assign>")
tmpToken = self.token
tmpNode = self.assign()
tmpNode.addChild( tmpToken, 0 )
currNode.addChild(tmpNode)
elif self.token[1] in types:
print("\t<Statement> -> <Declarative>")
tmpToken = self.token
tmpNode = self.declarative()
tmpNode.addChild( tmpToken, 0 )
currNode.addChild(tmpNode)
#Control structures
elif self.token[1] == "if":
currNode.addChild( self.token )
print("\t<Statement> -> if <Conditional> then <StatementList> endif | if <Conditional> then <StatementList> else <StatementList> endif")
currNode.addChild( self.conditional() )
if self.peekToken() is not None and self.peekToken()[1] == "then":
self.nextToken()
currNode.addChild( self.token )
currNode.addChild( self.statementList(["else", "endif"]) )
if self.peekToken() is not None and self.peekToken()[1] == "else":
self.nextToken()
currNode.addChild( self.token )
currNode.addChild( self.statementList("endif") )
if self.peekToken() is not None and self.peekToken()[1] == "endif":
self.nextToken()
currNode.addChild( self.token )
else: #ERROR: Needs endif
self.printError('Expected keyword "endif" after statement-list')
else: #ERROR: Needs "then"
self.printError('Expected keyword "then" before statement-list')
elif self.token[1] == "while":
currNode.addChild( self.token )
print("\t<Statement> -> while <Conditional> do <StatementList> whileend")
currNode.addChild( self.conditional() )
if self.peekToken() is not None and self.peekToken()[1] == "do":
self.nextToken()
currNode.addChild( self.token )
currNode.addChild( self.statementList('whileend') )
if self.peekToken() is not None and self.peekToken()[1] == 'whileend':
self.nextToken()
currNode.addChild( self.token )
else: #ERROR: Needs "whileend"
self.printError('Expected keyword "whileend" after statement-list')
else: #ERROR: should have "do"
self.printError('Expected keyword "do" before statement-list')
elif self.token[1] == 'input':
currNode.addChild( self.token )
self.nextToken()
currNode.addChild( self.token )
if self.token[1] != '(':
self.printUnexpectedError("Expected SEPARATOR '('.")
self.nextToken()
currNode.addChild( self.token )
if self.token[0] != 'IDENTIFIER':
self.printUnexpectedError("Expected IDENTIFIER.")
self.nextToken()
currNode.addChild( self.token )
if self.token[1] != ')':
self.printUnexpectedError("Expected SEPARATOR ')'.")
elif self.token[1] == 'output':
currNode.addChild( self.token )
self.nextToken()
currNode.addChild( self.token )
if self.token[1] != '(':
self.printUnexpectedError("Expected SEPARATOR '('.")
currNode.addChild( self.expression() )
self.nextToken()
currNode.addChild( self.token )
if self.token[1] != ')':
self.printUnexpectedError("Expected SEPARATOR ')'.")
else: #ERROR: Next token does not form a statement
self.printUnexpectedError(' Was expecting a statement.')
return currNode
# Assign
# Production rules: <Assign> -> <ID> = <Expression>;
# Represented in parse tree as non-leaf node with value "A"
def assign(self):
currNode = TreeNode("A")
tmpTok = self.peekToken()
if tmpTok is not None and tmpTok[1] == "=":
print("\t<Assign> -> <ID> = <Expression>;")
self.nextToken()
currNode.addChild( self.token )
currNode.addChild( self.expression() )
else: #ERROR: Expecting "=" for assignment statement.
self.printUnexpectedError('Was expecting operator "=" for assignment statement')
return currNode
# Declarative
# Production rules: <Declarative> -> <Type> <ID> <MoreIds>; | <empty>
# <MoreIds> -> , <ID> <MoreIds> | <empty
# Represented in parse tree as non-leaf node with value "D"
# MoreIDs are represented as "MI"
def declarative(self):
subRoot = TreeNode("D")
print("\t<Declarative> -> <Type> <ID> <MoreIds>; | <empty>")
self.nextToken() #ID
subRoot.addChild( self.token )
currNode = subRoot
while self.peekToken() is not None and self.peekToken()[1] == ',':
tmpNode = TreeNode("MI")
self.nextToken()
tmpNode.addChild( self.token )
if self.peekToken() is not None and (self.peekToken()[0] != "IDENTIFIER"): #ERROR: Invalid multiple declarative statement
self.nextToken()
self.printUnexpectedError('Was expecting an IDENTIFIER token for more declarations')
print("\t<MoreIds> -> , <ID> <MoreIds> | <empty>")
self.nextToken()
tmpNode.addChild( self.token )
currNode.addChild( tmpNode )
currNode = tmpNode
currNode.addChild( "<empty>" )
return subRoot
# Expression
# Production rules: <Expression> -> <Term> | <Term> + <Expression> | <Term> - <Expression>
# Represented in parse tree as non-leaf node with value "E"
# Note: Removal of left recursion is not performed. Rather, the grammar is flipped to not have
# left recursion. This will be handled later by the object code generator.
def expression(self):
currNode = TreeNode("E")
self.printBuffer.append("\t<Expression> -> <Term> | <Term> + <Expression> | <Term> - <Expression>")
currNode.addChild( self.term() )
tmpTok = self.peekToken()
if tmpTok is not None and tmpTok[1] in ['+', '-']:
self.nextToken()
currNode.addChild( self.token )
currNode.addChild( self.expression() )
self.flushPrintBuffer()
return currNode
# Term:
# Production rules: <Term> -> <Factor> * <Term> | <Factor> / <Term> | <Factor>
# Represented in parse tree as non-leaf node with value "T"
# Note: Removal of left recursion is not performed. Rather, the grammar is flipped to not have
# left recursion. This will be handled later by the object code generator.
def term(self):
currNode = TreeNode("T")
self.printBuffer.append("\t<Term> -> <Factor> * <Term> | <Factor> / <Term> | <Factor>")
currNode.addChild( self.factor() )
tmpTok = self.peekToken()
if tmpTok is not None and tmpTok[1] in ['*', '/']:
self.nextToken()
currNode.addChild( self.token )
currNode.addChild( self.term() )
self.flushPrintBuffer()
return currNode
# Factor:
# Production rules: <Factor> -> '(' <Expression> ')' | <ID> | ('+' | '-')?(<FLOAT> | ('.')?<INT>) | 'True' | 'False'
# Represented in parse tree as non-leaf node with value "F"
# Note: Additional processing of numbers are performed here to recognize all forms of numericals
def factor(self):
currNode = TreeNode("F")
self.nextToken()
currNode.addChild( self.token )
self.flushPrintBuffer()
print("\t<Factor> -> '(' <Expression> ')' | <ID> | ('+' | '-')?(<FLOAT> | ('.')?<INT>) | 'True' | 'False' | input(ID) | output(E)")
if self.token[1] == '(':
currNode.addChild( self.expression() )
self.nextToken()
currNode.addChild( self.token )
if self.token[1] != ')': #ERROR: Expected ')' after expression
self.printUnexpectedError("Expected SEPARATOR ')' after expression")
elif self.token[0] in ['IDENTIFIER', 'INTEGER', 'FLOAT'] or self.token[1] in ['True', 'False']:
return currNode #IS VALID. Return to go back to callee function
elif self.token[1] in ['+', '-']: #Treat as part of number
tmpTok = self.popNextToken()
if tmpTok[1] == '.':
tmpTok2 = self.popNextToken()
if tmpTok2[0] == 'INTEGER':
self.tokens[self.index-1][1] = self.tokens[self.index-1][1] + tmpTok[1] + tmpTok2[1]#Append to front of number
self.tokens[self.index-1][0] = 'FLOAT'
else:
self.printUnexpectedError("Expected float.")
elif tmpTok[0] in ['INTEGER', 'FLOAT']:
self.tokens[self.index-1][1] = self.tokens[self.index-1][1] + tmpTok[1] #Append to front of number
self.tokens[self.index-1][0] = tmpTok[0]
else:
self.printUnexpectedError("Expected numerical token.")
#self.printUnexpectedError("Expected a Factor in the form of ( <Expression> ), or an IDENTIFIER, or NUMERIC token", "Error: Invalid Factor")
elif self.token[1] == '.':
tmpTok = self.popNextToken()
if tmpTok[0] == 'INTEGER':
self.tokens[self.index-1][1] = self.tokens[self.index-1][1] + tmpTok[1]#Append to front of number
self.tokens[self.index-1][0] = 'FLOAT'
else:
self.printUnexpectedError("Expected float.")
else: #ERROR: Not a valid Factor.
self.printUnexpectedError("Expected a Factor in the form of ( <Expression> ), or an IDENTIFIER, or NUMERIC token", "Error: Invalid Factor")
return currNode
# Conditional
# Production rules: <Conditional> -> <Expression> <Relop> <Expression> | <Expression> | ( <Conditional> )
# Represented in parse tree as non-leaf node with value "C"
def conditional(self):
wrappedInParenthesis = (self.peekToken()[1] == '(')
if wrappedInParenthesis:
self.nextToken();
self.printBuffer.append("\t<Conditional> -> <Expression> <Relop> <Expression> | <Expression> | ( <Conditional> )")
currNode = TreeNode("C")
self.printBuffer.append("\t<Conditional> -> <Expression> <Relop> <Expression> | <Expression> | ( <Conditional> )")
currNode.addChild( self.expression() )
tmpTok = self.peekToken()
if tmpTok is not None:
if tmpTok[1] == "<":
self.nextToken()
currNode.addChild( self.token )
tmpTok2 = self.peekToken()
if tmpTok2 is not None and tmpTok2[1] in ['=', '>']:
self.nextToken() #Eval as "<=" or "<>"
currNode.addChild( self.token )
currNode.addChild( self.expression() ) #Eval as "<"
elif tmpTok[1] == ">":
self.nextToken()
currNode.addChild( self.token )
tmpTok2 = self.peekToken()
if tmpTok2 is not None and tmpTok2[1] == "=":
self.nextToken() # Eval as >=
currNode.addChild( self.token )
currNode.addChild( self.expression() ) #Eval as >
elif tmpTok[1] == "=":
self.nextToken()
currNode.addChild( self.token )
tmpTok2 = self.peekToken()
if tmpTok2 is not None:
if tmpTok2[1] == '=':
self.nextToken()
currNode.addChild( self.token )
currNode.addChild( self.expression() )#Eval as ==
else: #Eval as assignment, counted as invalid
self.printUnexpectedError("Expected RELATIVE OPERATOR between expressions. Did you mean '=='?")
#OTHERWISE just a lone expression. (Valid)
if wrappedInParenthesis:
self.nextToken()
if self.token[1] != ')':
self.printUnexpectedError("Expected ')'.")
self.flushPrintBuffer()
return currNode
def main():
#Read command line arguments
mFlags, files = getopt.gnu_getopt(sys.argv[1:], "ho:", ["help"])
outFile = None
#Process command line arguments
for opt, arg in mFlags:
if opt in ('-h', "--help"):
print("USAGE: parser.py <FILE> [<FILE> ...] [-o <OUTFILE>]")
exit()
elif opt == '-o':
outFile = arg
else:
print("Option '%s' not recognized" % opt)
#Prompt for input if none given
if len(files) < 1: #Prompt user for file name
files = input("Input filename(s): ").split(",")
if files is None or len(files[0]) == 0:
print("A valid filename must be entered.")
exit()
for i in range(0, len(files)):
files[i] = files[i].strip() #Remove leading and heading whitespace
if not outFile:
outFile = input("Output filename (default: console): ")
if not outFile:
outFile = None
print("\tDefaulting to standard output.")
#Perform syntax analysis on all input files
parseForest = []
for filename in files:
parser = Parser(filename, outFile)
parseForest.append(parser.parseTree)
#Return parse forest (list of parse trees from all input files)
return parseForest
#Execute main function only when directly executing script
if __name__ == "__main__":
main()
| [
"[email protected]"
] | |
5fb69116e48dca7461402838a90ce882b621c688 | 6fa0c940edffaeb325205673b4c7643b2ebfffc4 | /clicker/admin.py | dfb60e1999dfce5cae2f0891a8b4978f8c49920c | [] | no_license | RustamMullayanov/myDjangoClicker | 5f564bab3cd067eebc712f2fff82939e63f6c8b7 | caaa47f36904de92be0e16187b0acc707a4497ad | refs/heads/master | 2023-05-29T00:22:59.039925 | 2021-06-13T09:30:49 | 2021-06-13T09:30:49 | 367,644,274 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 120 | py | from django.contrib import admin
from . import models
# Register your models here.
admin.site.register(models.Clicker)
| [
"[email protected]"
] | |
d20beb7361baa30e1f49b5bce1bc4a1d3158cbba | 7c61f236f81c642b43abeee79bd36802d92df7d9 | /sandbox/envs/maze/point_env.py | 4048496a5296e5d875c986a502a17f9cae4bd722 | [] | no_license | ZiyeHu/goalgail | e9044b3863c608d2ccd4d49241cf3d0c09962eef | 1d940c8efffd519a0a77c58c8adf03b9967aa81a | refs/heads/master | 2022-12-11T14:26:28.781537 | 2020-09-17T16:08:24 | 2020-09-17T16:08:24 | 296,116,076 | 0 | 0 | null | 2020-09-16T18:30:54 | 2020-09-16T18:30:53 | null | UTF-8 | Python | false | false | 7,554 | py | from rllab.envs.base import Step
from rllab.envs.mujoco.mujoco_env import MujocoEnv
from rllab.core.serializable import Serializable
from rllab.misc.overrides import overrides
from rllab.misc import logger
import numpy as np
import math
import random
from sandbox.envs.base import StateGenerator
from sandbox.envs.goal_env import GoalEnv
from sandbox.envs.rewards import linear_threshold_reward
#
# def auto_str(cls):
# def __str__(self):
# return '%s(%s)' % (
# type(self).__name__,
# ', '.join('%s=%s' % item for item in vars(self).items())
# )
# cls.__str__ = __str__
# return cls
class PointEnv(GoalEnv, MujocoEnv, Serializable):
FILE = 'point2.xml'
def __str__(self):
return '%s(%s)' % (
type(self).__name__,
', '.join('%s=%s' % item for item in vars(self).items())
)
def __init__(self,
goal_generator=None, reward_dist_threshold=0.1, indicator_reward=True, append_goal=False,
control_mode='linear',
*args, **kwargs):
"""
:param goal_generator: Proceedure to sample and keep the goals
:param reward_dist_threshold:
:param control_mode:
"""
Serializable.quick_init(self, locals())
GoalEnv.__init__(self, goal_generator=goal_generator)
self.control_mode = control_mode
if goal_generator is None:
self.update_goal_generator(StateGenerator())
else:
self.update_goal_generator(goal_generator)
self.reward_dist_threshold = reward_dist_threshold
self.indicator_reward = indicator_reward
self.append_goal = append_goal
MujocoEnv.__init__(self, *args, **kwargs)
@overrides
def get_current_obs(self):
"""Append obs with current_goal"""
pos = self.model.data.qpos.flat[:2]
vel = self.model.data.qvel.flat[:2]
if self.append_goal:
return np.concatenate([
pos,
vel,
self.current_goal,
])
else:
if self.control_mode == 'pos':
return pos
else:
return np.concatenate([pos, vel])
@overrides
def reset(self, init_state=None, goal=(1, 0), *args, **kwargs): # reset called when __init__, so needs goal!
# import pdb; pdb.set_trace()
"""This does both the reset of mujoco, the forward and reset goal"""
self.update_goal(goal=goal)
qpos = np.zeros((self.model.nq, 1))
qvel = np.zeros((self.model.nv, 1)) # 0 velocity
if init_state is not None: # you can reset only the com position!
qpos[:2] = np.array(init_state[:2]).reshape((2, 1))
if np.array(init_state).size == 4:
qvel[:2] = np.array(init_state[2:]).reshape((2, 1))
qpos[2:, :] = np.array(self.current_goal).reshape((2, 1)) # the goal is part of the mujoco!!
self.set_state(qpos, qvel)
# this is usually the usual reset
self.current_com = self.model.data.com_subtree[0] # CF: this is very weird... gets 0, 2, 0.1 even when it's 0
self.dcom = np.zeros_like(self.current_com)
return self.get_current_obs()
def step(self, action):
# print('PointEnv, the action taken is: ', action)
if self.control_mode == 'linear': # action is directly the acceleration
self.forward_dynamics(action)
elif self.control_mode == 'angular': # action[0] is accel in forward (vel) direction, action[1] in orthogonal.
vel = self.model.data.qvel.flat[:2]
# Get the unit vector for velocity
if np.linalg.norm(vel) < 1e-10:
vel = np.array([1., 0.])
else:
vel = vel / np.linalg.norm(vel)
acc = np.zeros_like(vel)
acc += action[0] * vel
acc += action[1] * np.array([-vel[1], vel[0]])
self.forward_dynamics(acc)
elif self.control_mode == 'pos':
desired_pos = self.get_xy() + np.clip(action, -2, 2) / 10.
for _ in range(200):
self.forward_dynamics(desired_pos)
# print(str(self.get_xy()))
# print(str(self.model.data.qvel.flat[:2]))
# print("desired_pos" + str(desired_pos))
# pos = self.get_xy()
# pos += np.clip(action, -2, 2) / 10. # limit the action range to -0.2, 0.2
# self.set_xy(pos)
else:
raise NotImplementedError("Control mode not supported!")
reward_dist = self._compute_dist_reward() # 1000 * self.reward_dist_threshold at goal, decreases with 1000 coef
# print("reward", reward_dist)
reward_ctrl = - np.square(action).sum()
# reward = reward_dist + reward_ctrl
reward = reward_dist
dist = np.linalg.norm(
self.get_body_com("torso") - self.get_body_com("target")
)
ob = self.get_current_obs()
# print('current obs:', ob)
done = False
if dist < self.reward_dist_threshold and self.indicator_reward:
# print("**DONE***")
done = True
# print("reward", reward)
return Step(
ob, reward, done,
reward_dist=reward_dist,
reward_ctrl=reward_ctrl,
distance=dist,
)
@overrides
@property
def goal_observation(self): # transforms a state into a goal (projection, for example)
return self.get_body_com("torso")[:2]
def _compute_dist_reward(self):
"""Transforms dist to goal with linear_threshold_reward: gets -threshold * coef at dist=0, and decreases to 0"""
dist = np.linalg.norm(
self.get_body_com("torso") - self.get_body_com("target")
)
if self.indicator_reward and dist <= self.reward_dist_threshold:
return 1000 * self.reward_dist_threshold
else:
# return linear_threshold_reward(dist, threshold=self.reward_dist_threshold, coefficient=-10)
return -10 * dist
def set_state(self, qpos, qvel):
assert qpos.shape == (self.model.nq, 1) and qvel.shape == (self.model.nv, 1)
self.model.data.qpos = qpos
self.model.data.qvel = qvel
# self.model._compute_subtree() #pylint: disable=W0212
self.model.forward()
def get_xy(self):
qpos = self.model.data.qpos
return qpos[0, 0], qpos[1, 0]
def set_xy(self, xy):
qpos = np.copy(self.model.data.qpos)
qpos[0, 0] = xy[0]
qpos[1, 0] = xy[1]
self.model.data.qpos = qpos
self.model.forward()
@overrides
def log_diagnostics(self, paths):
# Process by time steps
distances = [
np.mean(path['env_infos']['distance'])
for path in paths
]
goal_distances = [
path['env_infos']['distance'][0] for path in paths
]
reward_dist = [
np.mean(path['env_infos']['reward_dist'])
for path in paths
]
reward_ctrl = [
np.mean(path['env_infos']['reward_ctrl'])
for path in paths
]
# Process by trajectories
logger.record_tabular('GoalDistance', np.mean(goal_distances))
logger.record_tabular('MeanDistance', np.mean(distances))
logger.record_tabular('MeanRewardDist', np.mean(reward_dist))
logger.record_tabular('MeanRewardCtrl', np.mean(reward_ctrl))
| [
"[email protected]"
] | |
30394348b699ec0d39eb02cb0fca340cdf880ae9 | ab1998970b4977b93466820e7a41227a57b21563 | /local_lib/pykrige/ok3d.py | 7298d0d67801077c78ed146584778128cbc036a1 | [] | no_license | kamccormack/PEFiredrake | 95b76f0c4e12b9b840fecb98e672621c4047455f | 329bb214268fa04fbebd5b6d219941273a849728 | refs/heads/master | 2020-03-09T19:44:00.191375 | 2018-04-10T16:38:18 | 2018-04-10T16:38:18 | 128,964,966 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 35,858 | py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
__doc__ = """Code by Benjamin S. Murphy
[email protected]
Dependencies:
numpy
scipy
matplotlib
Classes:
OrdinaryKriging3D: Support for 3D Ordinary Kriging.
References:
P.K. Kitanidis, Introduction to Geostatistcs: Applications in Hydrogeology,
(Cambridge University Press, 1997) 272 p.
Copyright (c) 2015 Benjamin S. Murphy
"""
import numpy as np
import scipy.linalg
from scipy.spatial.distance import cdist
import matplotlib.pyplot as plt
from . import variogram_models
from . import core
class OrdinaryKriging3D:
"""class OrdinaryKriging3D
Three-dimensional ordinary kriging
Dependencies:
numpy
scipy
matplotlib
Inputs:
X (array-like): X-coordinates of data points.
Y (array-like): Y-coordinates of data points.
Z (array-like): Z-coordinates of data points.
Val (array-like): Values at data points.
variogram_model (string, optional): Specified which variogram model to use;
may be one of the following: linear, power, gaussian, spherical,
exponential. Default is linear variogram model. To utilize as custom variogram
model, specify 'custom'; you must also provide variogram_parameters and
variogram_function.
variogram_parameters (list, optional): Parameters that define the
specified variogram model. If not provided, parameters will be automatically
calculated such that the root-mean-square error for the fit variogram
function is minimized.
linear - [slope, nugget]
power - [scale, exponent, nugget]
gaussian - [sill, range, nugget]
spherical - [sill, range, nugget]
exponential - [sill, range, nugget]
For a custom variogram model, the parameters are required, as custom variogram
models currently will not automatically be fit to the data. The code does not
check that the provided list contains the appropriate number of parameters for
the custom variogram model, so an incorrect parameter list in such a case will
probably trigger an esoteric exception someplace deep in the code.
variogram_function (callable, optional): A callable function that must be provided
if variogram_model is specified as 'custom'. The function must take only two
arguments: first, a list of parameters for the variogram model; second, the
distances at which to calculate the variogram model. The list provided in
variogram_parameters will be passed to the function as the first argument.
nlags (int, optional): Number of averaging bins for the semivariogram.
Default is 6.
weight (boolean, optional): Flag that specifies if semivariance at smaller lags
should be weighted more heavily when automatically calculating variogram model.
True indicates that weights will be applied. Default is False.
(Kitanidis suggests that the values at smaller lags are more important in
fitting a variogram model, so the option is provided to enable such weighting.)
anisotropy_scaling_y (float, optional): Scalar stretching value to take
into account anisotropy in the y direction. Default is 1 (effectively no stretching).
Scaling is applied in the y direction in the rotated data frame
(i.e., after adjusting for the anisotropy_angle_x/y/z, if anisotropy_angle_x/y/z
is/are not 0).
anisotropy_scaling_z (float, optional): Scalar stretching value to take
into account anisotropy in the z direction. Default is 1 (effectively no stretching).
Scaling is applied in the z direction in the rotated data frame
(i.e., after adjusting for the anisotropy_angle_x/y/z, if anisotropy_angle_x/y/z
is/are not 0).
anisotropy_angle_x (float, optional): CCW angle (in degrees) by which to
rotate coordinate system about the x axis in order to take into account anisotropy.
Default is 0 (no rotation). Note that the coordinate system is rotated. X rotation
is applied first, then y rotation, then z rotation. Scaling is applied after rotation.
anisotropy_angle_y (float, optional): CCW angle (in degrees) by which to
rotate coordinate system about the y axis in order to take into account anisotropy.
Default is 0 (no rotation). Note that the coordinate system is rotated. X rotation
is applied first, then y rotation, then z rotation. Scaling is applied after rotation.
anisotropy_angle_z (float, optional): CCW angle (in degrees) by which to
rotate coordinate system about the z axis in order to take into account anisotropy.
Default is 0 (no rotation). Note that the coordinate system is rotated. X rotation
is applied first, then y rotation, then z rotation. Scaling is applied after rotation.
verbose (Boolean, optional): Enables program text output to monitor
kriging process. Default is False (off).
enable_plotting (Boolean, optional): Enables plotting to display
variogram. Default is False (off).
Callable Methods:
display_variogram_model(): Displays semivariogram and variogram model.
update_variogram_model(variogram_model, variogram_parameters=None, nlags=6,
anisotropy_scaling=1.0, anisotropy_angle=0.0):
Changes the variogram model and variogram parameters for
the kriging system.
Inputs:
variogram_model (string): May be any of the variogram models
listed above. May also be 'custom', in which case variogram_parameters
and variogram_function must be specified.
variogram_parameters (list, optional): List of variogram model
parameters, as listed above. If not provided, a best fit model
will be calculated as described above.
variogram_function (callable, optional): A callable function that must be
provided if variogram_model is specified as 'custom'. See above for
more information.
nlags (int, optional): Number of averaging bins for the semivariogram.
Defualt is 6.
weight (boolean, optional): Flag that specifies if semivariance at smaller lags
should be weighted more heavily when automatically calculating variogram model.
True indicates that weights will be applied. Default is False.
anisotropy_scaling (float, optional): Scalar stretching value to
take into account anisotropy. Default is 1 (effectively no
stretching). Scaling is applied in the y-direction.
anisotropy_angle (float, optional): Angle (in degrees) by which to
rotate coordinate system in order to take into account
anisotropy. Default is 0 (no rotation).
switch_verbose(): Enables/disables program text output. No arguments.
switch_plotting(): Enables/disable variogram plot display. No arguments.
get_epsilon_residuals(): Returns the epsilon residuals of the
variogram fit. No arguments.
plot_epsilon_residuals(): Plots the epsilon residuals of the variogram
fit in the order in which they were calculated. No arguments.
get_statistics(): Returns the Q1, Q2, and cR statistics for the
variogram fit (in that order). No arguments.
print_statistics(): Prints out the Q1, Q2, and cR statistics for
the variogram fit. NOTE that ideally Q1 is close to zero,
Q2 is close to 1, and cR is as small as possible.
execute(style, xpoints, ypoints, mask=None): Calculates a kriged grid.
Inputs:
style (string): Specifies how to treat input kriging points.
Specifying 'grid' treats xpoints, ypoints, and zpoints as
arrays of x, y,z coordinates that define a rectangular grid.
Specifying 'points' treats xpoints, ypoints, and zpoints as arrays
that provide coordinates at which to solve the kriging system.
Specifying 'masked' treats xpoints, ypoints, zpoints as arrays of
x, y, z coordinates that define a rectangular grid and uses mask
to only evaluate specific points in the grid.
xpoints (array-like, dim N): If style is specific as 'grid' or 'masked',
x-coordinates of LxMxN grid. If style is specified as 'points',
x-coordinates of specific points at which to solve kriging system.
ypoints (array-like, dim M): If style is specified as 'grid' or 'masked',
y-coordinates of LxMxN grid. If style is specified as 'points',
y-coordinates of specific points at which to solve kriging system.
Note that in this case, xpoints, ypoints, and zpoints must have the
same dimensions (i.e., L = M = N).
zpoints (array-like, dim L): If style is specified as 'grid' or 'masked',
z-coordinates of LxMxN grid. If style is specified as 'points',
z-coordinates of specific points at which to solve kriging system.
Note that in this case, xpoints, ypoints, and zpoints must have the
same dimensions (i.e., L = M = N).
mask (boolean array, dim LxMxN, optional): Specifies the points in the rectangular
grid defined by xpoints, ypoints, and zpoints that are to be excluded in the
kriging calculations. Must be provided if style is specified as 'masked'.
False indicates that the point should not be masked; True indicates that
the point should be masked.
backend (string, optional): Specifies which approach to use in kriging.
Specifying 'vectorized' will solve the entire kriging problem at once in a
vectorized operation. This approach is faster but also can consume a
significant amount of memory for large grids and/or large datasets.
Specifying 'loop' will loop through each point at which the kriging system
is to be solved. This approach is slower but also less memory-intensive.
Default is 'vectorized'.
Outputs:
kvalues (numpy array, dim LxMxN or dim Nx1): Interpolated values of specified grid
or at the specified set of points. If style was specified as 'masked',
kvalues will be a numpy masked array.
sigmasq (numpy array, dim LxMxN or dim Nx1): Variance at specified grid points or
at the specified set of points. If style was specified as 'masked', sigmasq
will be a numpy masked array.
References:
P.K. Kitanidis, Introduction to Geostatistcs: Applications in Hydrogeology,
(Cambridge University Press, 1997) 272 p.
"""
eps = 1.e-10 # Cutoff for comparison to zero
variogram_dict = {'linear': variogram_models.linear_variogram_model,
'power': variogram_models.power_variogram_model,
'gaussian': variogram_models.gaussian_variogram_model,
'spherical': variogram_models.spherical_variogram_model,
'exponential': variogram_models.exponential_variogram_model}
def __init__(self, x, y, z, val, variogram_model='linear', variogram_parameters=None,
variogram_function=None, nlags=6, weight=False, anisotropy_scaling_y=1.0,
anisotropy_scaling_z=1.0, anisotropy_angle_x=0.0, anisotropy_angle_y=0.0,
anisotropy_angle_z=0.0, verbose=False, enable_plotting=False):
# Code assumes 1D input arrays. Ensures that any extraneous dimensions
# don't get in the way. Copies are created to avoid any problems with
# referencing the original passed arguments.
self.X_ORIG = np.atleast_1d(np.squeeze(np.array(x, copy=True)))
self.Y_ORIG = np.atleast_1d(np.squeeze(np.array(y, copy=True)))
self.Z_ORIG = np.atleast_1d(np.squeeze(np.array(z, copy=True)))
self.VALUES = np.atleast_1d(np.squeeze(np.array(val, copy=True)))
self.verbose = verbose
self.enable_plotting = enable_plotting
if self.enable_plotting and self.verbose:
print("Plotting Enabled\n")
self.XCENTER = (np.amax(self.X_ORIG) + np.amin(self.X_ORIG))/2.0
self.YCENTER = (np.amax(self.Y_ORIG) + np.amin(self.Y_ORIG))/2.0
self.ZCENTER = (np.amax(self.Z_ORIG) + np.amin(self.Z_ORIG))/2.0
self.anisotropy_scaling_y = anisotropy_scaling_y
self.anisotropy_scaling_z = anisotropy_scaling_z
self.anisotropy_angle_x = anisotropy_angle_x
self.anisotropy_angle_y = anisotropy_angle_y
self.anisotropy_angle_z = anisotropy_angle_z
if self.verbose:
print("Adjusting data for anisotropy...")
self.X_ADJUSTED, self.Y_ADJUSTED, self.Z_ADJUSTED = \
core.adjust_for_anisotropy_3d(np.copy(self.X_ORIG), np.copy(self.Y_ORIG), np.copy(self.Z_ORIG),
self.XCENTER, self.YCENTER, self.ZCENTER, self.anisotropy_scaling_y,
self.anisotropy_scaling_z, self.anisotropy_angle_x, self.anisotropy_angle_y,
self.anisotropy_angle_z)
self.variogram_model = variogram_model
if self.variogram_model not in self.variogram_dict.keys() and self.variogram_model != 'custom':
raise ValueError("Specified variogram model '%s' is not supported." % variogram_model)
elif self.variogram_model == 'custom':
if variogram_function is None or not callable(variogram_function):
raise ValueError("Must specify callable function for custom variogram model.")
else:
self.variogram_function = variogram_function
else:
self.variogram_function = self.variogram_dict[self.variogram_model]
if self.verbose:
print("Initializing variogram model...")
self.lags, self.semivariance, self.variogram_model_parameters = \
core.initialize_variogram_model_3d(self.X_ADJUSTED, self.Y_ADJUSTED, self.Z_ADJUSTED, self.VALUES,
self.variogram_model, variogram_parameters, self.variogram_function,
nlags, weight)
if self.verbose:
if self.variogram_model == 'linear':
print("Using '%s' Variogram Model" % 'linear')
print("Slope:", self.variogram_model_parameters[0])
print("Nugget:", self.variogram_model_parameters[1], '\n')
elif self.variogram_model == 'power':
print("Using '%s' Variogram Model" % 'power')
print("Scale:", self.variogram_model_parameters[0])
print("Exponent:", self.variogram_model_parameters[1])
print("Nugget:", self.variogram_model_parameters[2], '\n')
elif self.variogram_model == 'custom':
print("Using Custom Variogram Model")
else:
print("Using '%s' Variogram Model" % self.variogram_model)
print("Sill:", self.variogram_model_parameters[0])
print("Range:", self.variogram_model_parameters[1])
print("Nugget:", self.variogram_model_parameters[2], '\n')
if self.enable_plotting:
self.display_variogram_model()
if self.verbose:
print("Calculating statistics on variogram model fit...")
self.delta, self.sigma, self.epsilon = core.find_statistics_3d(self.X_ADJUSTED, self.Y_ADJUSTED,
self.Z_ADJUSTED, self.VALUES,
self.variogram_function,
self.variogram_model_parameters)
self.Q1 = core.calcQ1(self.epsilon)
self.Q2 = core.calcQ2(self.epsilon)
self.cR = core.calc_cR(self.Q2, self.sigma)
if self.verbose:
print("Q1 =", self.Q1)
print("Q2 =", self.Q2)
print("cR =", self.cR, '\n')
def update_variogram_model(self, variogram_model, variogram_parameters=None, variogram_function=None,
nlags=6, weight=False, anisotropy_scaling_y=1.0, anisotropy_scaling_z=1.0,
anisotropy_angle_x=0.0, anisotropy_angle_y=0.0, anisotropy_angle_z=0.0):
"""Allows user to update variogram type and/or variogram model parameters."""
if anisotropy_scaling_y != self.anisotropy_scaling_y or anisotropy_scaling_z != self.anisotropy_scaling_z or \
anisotropy_angle_x != self.anisotropy_angle_x or anisotropy_angle_y != self.anisotropy_angle_y or \
anisotropy_angle_z != self.anisotropy_angle_z:
if self.verbose:
print("Adjusting data for anisotropy...")
self.anisotropy_scaling_y = anisotropy_scaling_y
self.anisotropy_scaling_z = anisotropy_scaling_z
self.anisotropy_angle_x = anisotropy_angle_x
self.anisotropy_angle_y = anisotropy_angle_y
self.anisotropy_angle_z = anisotropy_angle_z
self.X_ADJUSTED, self.Y_ADJUSTED, self.Z_ADJUSTED = \
core.adjust_for_anisotropy_3d(np.copy(self.X_ORIG), np.copy(self.Y_ORIG), np.copy(self.Z_ORIG),
self.XCENTER, self.YCENTER, self.ZCENTER, self.anisotropy_scaling_y,
self.anisotropy_scaling_z, self.anisotropy_angle_x,
self.anisotropy_angle_y, self.anisotropy_angle_z)
self.variogram_model = variogram_model
if self.variogram_model not in self.variogram_dict.keys() and self.variogram_model != 'custom':
raise ValueError("Specified variogram model '%s' is not supported." % variogram_model)
elif self.variogram_model == 'custom':
if variogram_function is None or not callable(variogram_function):
raise ValueError("Must specify callable function for custom variogram model.")
else:
self.variogram_function = variogram_function
else:
self.variogram_function = self.variogram_dict[self.variogram_model]
if self.verbose:
print("Updating variogram mode...")
self.lags, self.semivariance, self.variogram_model_parameters = \
core.initialize_variogram_model_3d(self.X_ADJUSTED, self.Y_ADJUSTED, self.Z_ADJUSTED, self.VALUES,
self.variogram_model, variogram_parameters, self.variogram_function,
nlags, weight)
if self.verbose:
if self.variogram_model == 'linear':
print("Using '%s' Variogram Model" % 'linear')
print("Slope:", self.variogram_model_parameters[0])
print("Nugget:", self.variogram_model_parameters[1], '\n')
elif self.variogram_model == 'power':
print("Using '%s' Variogram Model" % 'power')
print("Scale:", self.variogram_model_parameters[0])
print("Exponent:", self.variogram_model_parameters[1])
print("Nugget:", self.variogram_model_parameters[2], '\n')
elif self.variogram_model == 'custom':
print("Using Custom Variogram Model")
else:
print("Using '%s' Variogram Model" % self.variogram_model)
print("Sill:", self.variogram_model_parameters[0])
print("Range:", self.variogram_model_parameters[1])
print("Nugget:", self.variogram_model_parameters[2], '\n')
if self.enable_plotting:
self.display_variogram_model()
if self.verbose:
print("Calculating statistics on variogram model fit...")
self.delta, self.sigma, self.epsilon = core.find_statistics_3d(self.X_ADJUSTED, self.Y_ADJUSTED,
self.Z_ADJUSTED, self.VALUES,
self.variogram_function,
self.variogram_model_parameters)
self.Q1 = core.calcQ1(self.epsilon)
self.Q2 = core.calcQ2(self.epsilon)
self.cR = core.calc_cR(self.Q2, self.sigma)
if self.verbose:
print("Q1 =", self.Q1)
print("Q2 =", self.Q2)
print("cR =", self.cR, '\n')
def display_variogram_model(self):
"""Displays variogram model with the actual binned data"""
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(self.lags, self.semivariance, 'r*')
ax.plot(self.lags,
self.variogram_function(self.variogram_model_parameters, self.lags), 'k-')
plt.show()
def switch_verbose(self):
"""Allows user to switch code talk-back on/off. Takes no arguments."""
self.verbose = not self.verbose
def switch_plotting(self):
"""Allows user to switch plot display on/off. Takes no arguments."""
self.enable_plotting = not self.enable_plotting
def get_epsilon_residuals(self):
"""Returns the epsilon residuals for the variogram fit."""
return self.epsilon
def plot_epsilon_residuals(self):
"""Plots the epsilon residuals for the variogram fit."""
fig = plt.figure()
ax = fig.add_subplot(111)
ax.scatter(range(self.epsilon.size), self.epsilon, c='k', marker='*')
ax.axhline(y=0.0)
plt.show()
def get_statistics(self):
return self.Q1, self.Q2, self.cR
def print_statistics(self):
print("Q1 =", self.Q1)
print("Q2 =", self.Q2)
print("cR =", self.cR)
def _get_kriging_matrix(self, n):
"""Assembles the kriging matrix."""
xyz = np.concatenate((self.X_ADJUSTED[:, np.newaxis], self.Y_ADJUSTED[:, np.newaxis],
self.Z_ADJUSTED[:, np.newaxis]), axis=1)
d = cdist(xyz, xyz, 'euclidean')
a = np.zeros((n+1, n+1))
a[:n, :n] = - self.variogram_function(self.variogram_model_parameters, d)
np.fill_diagonal(a, 0.)
a[n, :] = 1.0
a[:, n] = 1.0
a[n, n] = 0.0
return a
def _exec_vector(self, a, bd, mask):
"""Solves the kriging system as a vectorized operation. This method
can take a lot of memory for large grids and/or large datasets."""
npt = bd.shape[0]
n = self.X_ADJUSTED.shape[0]
zero_index = None
zero_value = False
a_inv = scipy.linalg.inv(a)
if np.any(np.absolute(bd) <= self.eps):
zero_value = True
zero_index = np.where(np.absolute(bd) <= self.eps)
b = np.zeros((npt, n+1, 1))
b[:, :n, 0] = - self.variogram_function(self.variogram_model_parameters, bd)
if zero_value:
b[zero_index[0], zero_index[1], 0] = 0.0
b[:, n, 0] = 1.0
if (~mask).any():
mask_b = np.repeat(mask[:, np.newaxis, np.newaxis], n+1, axis=1)
b = np.ma.array(b, mask=mask_b)
x = np.dot(a_inv, b.reshape((npt, n+1)).T).reshape((1, n+1, npt)).T
kvalues = np.sum(x[:, :n, 0] * self.VALUES, axis=1)
sigmasq = np.sum(x[:, :, 0] * -b[:, :, 0], axis=1)
return kvalues, sigmasq
def _exec_loop(self, a, bd_all, mask):
"""Solves the kriging system by looping over all specified points.
Less memory-intensive, but involves a Python-level loop."""
npt = bd_all.shape[0]
n = self.X_ADJUSTED.shape[0]
kvalues = np.zeros(npt)
sigmasq = np.zeros(npt)
a_inv = scipy.linalg.inv(a)
for j in np.nonzero(~mask)[0]: # Note that this is the same thing as range(npt) if mask is not defined,
bd = bd_all[j] # otherwise it takes the non-masked elements.
if np.any(np.absolute(bd) <= self.eps):
zero_value = True
zero_index = np.where(np.absolute(bd) <= self.eps)
else:
zero_value = False
zero_index = None
b = np.zeros((n+1, 1))
b[:n, 0] = - self.variogram_function(self.variogram_model_parameters, bd)
if zero_value:
b[zero_index[0], 0] = 0.0
b[n, 0] = 1.0
x = np.dot(a_inv, b)
kvalues[j] = np.sum(x[:n, 0] * self.VALUES)
sigmasq[j] = np.sum(x[:, 0] * -b[:, 0])
return kvalues, sigmasq
def _exec_loop_moving_window(self, a_all, bd_all, mask, bd_idx):
"""Solves the kriging system by looping over all specified points. Uses only a certain number of
closest points. Not very memory intensive, but the loop is done in pure Python.
"""
import scipy.linalg.lapack
npt = bd_all.shape[0]
n = bd_idx.shape[1]
kvalues = np.zeros(npt)
sigmasq = np.zeros(npt)
for i in np.nonzero(~mask)[0]:
b_selector = bd_idx[i]
bd = bd_all[i]
a_selector = np.concatenate((b_selector, np.array([a_all.shape[0] - 1])))
a = a_all[a_selector[:, None], a_selector]
if np.any(np.absolute(bd) <= self.eps):
zero_value = True
zero_index = np.where(np.absolute(bd) <= self.eps)
else:
zero_value = False
zero_index = None
b = np.zeros((n+1, 1))
b[:n, 0] = - self.variogram_function(self.variogram_model_parameters, bd)
if zero_value:
b[zero_index[0], 0] = 0.0
b[n, 0] = 1.0
x = scipy.linalg.solve(a, b)
kvalues[i] = x[:n, 0].dot(self.VALUES[b_selector])
sigmasq[i] = - x[:, 0].dot(b[:, 0])
return kvalues, sigmasq
def execute(self, style, xpoints, ypoints, zpoints, mask=None, backend='vectorized', n_closest_points=None):
"""Calculates a kriged grid and the associated variance.
This is now the method that performs the main kriging calculation. Note that currently
measurements (i.e., z values) are considered 'exact'. This means that, when a specified
coordinate for interpolation is exactly the same as one of the data points, the variogram
evaluated at the point is forced to be zero. Also, the diagonal of the kriging matrix is
also always forced to be zero. In forcing the variogram evaluated at data points to be zero,
we are effectively saying that there is no variance at that point (no uncertainty,
so the value is 'exact').
In the future, the code may include an extra 'exact_values' boolean flag that can be
adjusted to specify whether to treat the measurements as 'exact'. Setting the flag
to false would indicate that the variogram should not be forced to be zero at zero distance
(i.e., when evaluated at data points). Instead, the uncertainty in the point will be
equal to the nugget. This would mean that the diagonal of the kriging matrix would be set to
the nugget instead of to zero.
Inputs:
style (string): Specifies how to treat input kriging points.
Specifying 'grid' treats xpoints, ypoints, and zpoints as arrays of
x, y, and z coordinates that define a rectangular grid.
Specifying 'points' treats xpoints, ypoints, and zpoints as arrays
that provide coordinates at which to solve the kriging system.
Specifying 'masked' treats xpoints, ypoints, and zpoints as arrays of
x, y, and z coordinates that define a rectangular grid and uses mask
to only evaluate specific points in the grid.
xpoints (array-like, dim N): If style is specific as 'grid' or 'masked',
x-coordinates of LxMxN grid. If style is specified as 'points',
x-coordinates of specific points at which to solve kriging system.
ypoints (array-like, dim M): If style is specified as 'grid' or 'masked',
y-coordinates of LxMxN grid. If style is specified as 'points',
y-coordinates of specific points at which to solve kriging system.
Note that in this case, xpoints, ypoints, and zpoints must have the
same dimensions (i.e., L = M = N).
zpoints (array-like, dim L): If style is specified as 'grid' or 'masked',
z-coordinates of LxMxN grid. If style is specified as 'points',
z-coordinates of specific points at which to solve kriging system.
Note that in this case, xpoints, ypoints, and zpoints must have the
same dimensions (i.e., L = M = N).
mask (boolean array, dim LxMxN, optional): Specifies the points in the rectangular
grid defined by xpoints, ypoints, zpoints that are to be excluded in the
kriging calculations. Must be provided if style is specified as 'masked'.
False indicates that the point should not be masked, so the kriging system
will be solved at the point.
True indicates that the point should be masked, so the kriging system should
will not be solved at the point.
backend (string, optional): Specifies which approach to use in kriging.
Specifying 'vectorized' will solve the entire kriging problem at once in a
vectorized operation. This approach is faster but also can consume a
significant amount of memory for large grids and/or large datasets.
Specifying 'loop' will loop through each point at which the kriging system
is to be solved. This approach is slower but also less memory-intensive.
Default is 'vectorized'.
n_closest_points (int, optional): For kriging with a moving window, specifies the number
of nearby points to use in the calculation. This can speed up the calculation for large
datasets, but should be used with caution. As Kitanidis notes, kriging with a moving
window can produce unexpected oddities if the variogram model is not carefully chosen.
Outputs:
kvalues (numpy array, dim LxMxN or dim Nx1): Interpolated values of specified grid
or at the specified set of points. If style was specified as 'masked',
kvalues will be a numpy masked array.
sigmasq (numpy array, dim LxMxN or dim Nx1): Variance at specified grid points or
at the specified set of points. If style was specified as 'masked', sigmasq
will be a numpy masked array.
"""
if self.verbose:
print("Executing Ordinary Kriging...\n")
if style != 'grid' and style != 'masked' and style != 'points':
raise ValueError("style argument must be 'grid', 'points', or 'masked'")
xpts = np.atleast_1d(np.squeeze(np.array(xpoints, copy=True)))
ypts = np.atleast_1d(np.squeeze(np.array(ypoints, copy=True)))
zpts = np.atleast_1d(np.squeeze(np.array(zpoints, copy=True)))
n = self.X_ADJUSTED.shape[0]
nx = xpts.size
ny = ypts.size
nz = zpts.size
a = self._get_kriging_matrix(n)
if style in ['grid', 'masked']:
if style == 'masked':
if mask is None:
raise IOError("Must specify boolean masking array when style is 'masked'.")
if mask.ndim != 3:
raise ValueError("Mask is not three-dimensional.")
if mask.shape[0] != nz or mask.shape[1] != ny or mask.shape[2] != nx:
if mask.shape[0] == nx and mask.shape[2] == nz and mask.shape[1] == ny:
mask = mask.swapaxes(0, 2)
else:
raise ValueError("Mask dimensions do not match specified grid dimensions.")
mask = mask.flatten()
npt = nz * ny * nx
grid_z, grid_y, grid_x = np.meshgrid(zpts, ypts, xpts, indexing='ij')
xpts = grid_x.flatten()
ypts = grid_y.flatten()
zpts = grid_z.flatten()
elif style == 'points':
if xpts.size != ypts.size and ypts.size != zpts.size:
raise ValueError("xpoints, ypoints, and zpoints must have same dimensions "
"when treated as listing discrete points.")
npt = nx
else:
raise ValueError("style argument must be 'grid', 'points', or 'masked'")
xpts, ypts, zpts = core.adjust_for_anisotropy_3d(xpts, ypts, zpts, self.XCENTER, self.YCENTER, self.ZCENTER,
self.anisotropy_scaling_y, self.anisotropy_scaling_z,
self.anisotropy_angle_x, self.anisotropy_angle_y,
self.anisotropy_angle_z)
if style != 'masked':
mask = np.zeros(npt, dtype='bool')
xyz_points = np.concatenate((zpts[:, np.newaxis], ypts[:, np.newaxis], xpts[:, np.newaxis]), axis=1)
xyz_data = np.concatenate((self.Z_ADJUSTED[:, np.newaxis], self.Y_ADJUSTED[:, np.newaxis],
self.X_ADJUSTED[:, np.newaxis]), axis=1)
bd = cdist(xyz_points, xyz_data, 'euclidean')
if n_closest_points is not None:
from scipy.spatial import cKDTree
tree = cKDTree(xyz_data)
bd, bd_idx = tree.query(xyz_points, k=n_closest_points, eps=0.0)
if backend == 'loop':
kvalues, sigmasq = self._exec_loop_moving_window(a, bd, mask, bd_idx)
else:
raise ValueError("Specified backend '{}' not supported for moving window.".format(backend))
else:
if backend == 'vectorized':
kvalues, sigmasq = self._exec_vector(a, bd, mask)
elif backend == 'loop':
kvalues, sigmasq = self._exec_loop(a, bd, mask)
else:
raise ValueError('Specified backend {} is not supported for 3D ordinary kriging.'.format(backend))
if style == 'masked':
kvalues = np.ma.array(kvalues, mask=mask)
sigmasq = np.ma.array(sigmasq, mask=mask)
if style in ['masked', 'grid']:
kvalues = kvalues.reshape((nz, ny, nx))
sigmasq = sigmasq.reshape((nz, ny, nx))
return kvalues, sigmasq
| [
"[email protected]"
] | |
fcf1f6548924e0a7b8d556c5614e9aee7511b172 | ffea8d9c5a742170fb21c5c95e3f84ce9ab2f3bd | /algorithms_find_unique_chars.py | 43ee638f4f6311ce56d55f48d9b623bd298e71d9 | [] | no_license | catechnix/greentree | 3b8583bd4ccb1a506f3e24f03a6c1592f1664518 | ffcd7b1b26fa6552b4f58ac9645151afb591628b | refs/heads/master | 2023-04-08T23:41:15.502014 | 2021-04-03T03:48:07 | 2021-04-03T03:48:07 | 288,299,640 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,043 | py | # Given a string, find the first non-repeating character in it and return its index.
# If it doesn't exist, return -1. # Note: all the input strings are already lowercase.
#Approach 1
def solution(s):
frequency = {}
for i in s:
if i not in frequency:
frequency[i] = 1
else:
frequency[i] +=1
for i in range(len(s)):
if frequency[s[i]] == 1:
return i
return -1
print(solution('alphabet'))
print(solution('barbados'))
print(solution('crunchy'))
print('###')
#Approach 2
import collections
def solution(s):
# build hash map : character and how often it appears
count = collections.Counter(s) # <-- gives back a dictionary with words occurrence count
#Counter({'l': 1, 'e': 3, 't': 1, 'c': 1, 'o': 1, 'd': 1})
# find the index
for idx, ch in enumerate(s):
if count[ch] == 1:
return idx
return -1
print(solution('alphabet'))
print(solution('barbados'))
print(solution('crunchy')) | [
"[email protected]"
] | |
537cc1b377a1a29fe985de13d1284703ca373594 | ebcc40516adba151e6a1c772223b0726899a26eb | /slicedimage/url/__init__.py | 903fa8c5d102018aed1a5b5cd312397b50a9e499 | [
"MIT"
] | permissive | spacetx/slicedimage | acf4a767f87b6ab78e657d85efad22ee241939f4 | eb8e1d3899628db66cffed1370f2a7e6dd729c4f | refs/heads/master | 2021-04-09T10:53:15.057821 | 2020-05-26T17:40:11 | 2020-05-26T17:40:11 | 125,316,414 | 7 | 4 | MIT | 2020-05-26T17:40:15 | 2018-03-15T05:24:24 | Python | UTF-8 | Python | false | false | 19 | py | from . import path
| [
"[email protected]"
] | |
ade4325ffae0867072eb07d5294917e637b30a23 | de4d26a724b966ca8d0b95ec3063b5b784129028 | /UserData/UserApp/migrations/0002_auto_20190402_0505.py | cc02790701761a7d0486f6803b359929ae666412 | [] | no_license | ChetanKoranga/UserRESTapi | 88904a326a093842ad68628eed98ea5ca2a95de0 | 11342bef21be163c4faf79744e90e9848e3a89bf | refs/heads/master | 2020-05-04T00:01:22.998117 | 2019-04-02T05:51:18 | 2019-04-02T05:51:18 | 178,876,580 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 373 | py | # Generated by Django 2.2 on 2019-04-02 05:05
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('UserApp', '0001_initial'),
]
operations = [
migrations.AlterField(
model_name='usermodel',
name='zip',
field=models.CharField(max_length=10),
),
]
| [
"[email protected]"
] | |
e1ff873dc7162e68805ea496e18d054103fd202b | 6246f61c6bb4143fc88d74c72f6d2e7936433ee9 | /saper.py | d8ce9e5291c0319c76368b2ce8e78d6c68c45df6 | [] | no_license | aramann/mineswapper | 0663d1189d38ec0704d39e6b97f8690e80367b38 | 8fab851d7e948924e88c4101bc35e4745d7971b3 | refs/heads/master | 2021-06-13T20:36:39.147322 | 2017-03-06T14:28:31 | 2017-03-06T14:28:31 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,094 | py | import random
import tkinter as tk
def gen_bomb(field):
i = random.randint(1, m - 1)
j = random.randint(1, n - 1)
while field[i][j] == 'b':
i = random.randint(1, m - 1)
j = random.randint(1, n - 1)
field[i][j] = 'b'
return field
# if field[i][j] == 'b':
# return gen_field(field)
# else:
# field[i][j] = 'b'
# return field
def gen_field(field):
for i in range(1, m):
for j in range(1, n):
cnt = 0
if field[i][j] == 'b':
continue
else:
if field[i - 1][j - 1] == 'b':
cnt += 1
if field[i - 1][j] == 'b':
cnt += 1
if field[i - 1][j + 1] == 'b':
cnt += 1
if field[i][j - 1] == 'b':
cnt += 1
if field[i][j + 1] == 'b':
cnt += 1
if field[i + 1][j - 1] == 'b':
cnt += 1
if field[i + 1][j] == 'b':
cnt += 1
if field[i + 1][j + 1] == 'b':
cnt += 1
field[i][j] = cnt
return field
def opencell(i, j):
if field[i][j] == 'b':
for k in range(1, n):
for l in range(1, m):
if field[k][l] == 'b':
buttons[k][l]["bg"] = 'red'
buttons[k][l]["text"] = 'bomb'
# exit()
if field[i][j] == -1:
return
if field[i][j] == 0 and (i, j) not in walken:
walken.append((i, j))
opencell(i - 1, j - 1)
opencell(i - 1, j)
opencell(i - 1, j - 1)
opencell(i, j - 1)
opencell(i, j + 1)
opencell(i + 1, j - 1)
opencell(i + 1, j)
opencell(i + 1, j + 1)
if field[i][j] == 0:
buttons[i][j]["text"] = 'no'
else:
buttons[i][j]["text"] = field[i][j]
if buttons[i][j] == 1:
buttons[i][j]["fg"] = 'azure'
elif buttons[i][j] == 2:
buttons[i][j]["fg"] = 'green'
elif buttons[i][j] == 3:
buttons[i][j]["fg"] = 'red'
elif buttons[i][j] == 4:
buttons[i][j]["fg"] = 'purple'
elif buttons[i][j] == 5:
buttons[i][j]["fg"] = 'brown'
elif buttons[i][j] == 6:
buttons[i][j]["fg"] = 'yellow'
elif buttons[i][j] == 7:
buttons[i][j]["fg"] = 'orange'
elif buttons[i][j] == 8:
buttons[i][j]["fg"] = 'white'
buttons[i][j]["bg"] = 'grey'
def setflag(i, j):
if buttons[i][j]["text"] == 'b':
buttons[i][j]["text"] = '?'
elif buttons[i][j]["text"] == '?':
buttons[i][j]["text"] = ''
else:
buttons[i][j]["text"] = 'b'
def _opencell(i, j):
def opencell_(event):
opencell(i, j)
return opencell_
def _setflag(i, j):
def setflag_(event):
setflag(i, j)
return setflag_
root = tk.Tk()
print('Select level of difficulty(1 - easy (9x9 10 mines), 2 - medium (16x16 40 mines), 3 - hard (30x16 99 mines), 4 - custom')
lvl = int(input())
if lvl == 1:
n, m, bombs = 9, 9, 10
elif lvl == 2:
n, m, bombs = 16, 16, 40
elif lvl == 3:
n, m, bombs = 30, 16, 99
else:
print('Enter size of the field (x, y) and number of bombs, spliting with space')
n, m, bombs = map(int, input().split())
if n * m <= bombs:
bombs = n * m - 1
field = [[0 for i in range(n + 1)] for j in range(m + 1)]
for i in range(n + 1):
field[0][i] = -1
field[-1][i] = -1
for i in range(m + 1):
field[i][0] = -1
field[i][-1] = -1
for i in range(bombs):
field = gen_bomb(field)
field = gen_field(field)
for i in range(m + 1):
print(*field[i])
buttons = [[0 for i in range(0, n + 1)] for j in range(0, m + 1)]
for i in range(n + 1):
buttons[0][i] = -1
buttons[-1][i] = -1
for i in range(m + 1):
buttons[i][0] = -1
buttons[i][-1] = -1
for i in range(1, m):
for j in range(1, n):
btn = tk.Button(root, text='', bg='grey')
btn.bind("<Button-1>", _opencell(i, j))
btn.bind("<Button-2>", _setflag(i, j))
btn.grid(row=i, column=j)
buttons[i][j] = btn
walken = []
# btn = tk.Button(root, #родительское окно
# text="Click me", #надпись на кнопке
# width=30,height=5, #ширина и высота
# bg="white",fg="black")
# btn.bind("<Button-1>", opencell)
# btn.pack()
root.mainloop()
# root = tk.Tk()
# def Hello(event):
# print("Yet another hello world")
#
# btn = tk.Button(root, #родительское окно
# text="Click me", #надпись на кнопке
# width=30,height=5, #ширина и высота
# bg="white",fg="black") #цвет фона и надписи
# btn.bind("<Button-1>", Hello) #при нажатии ЛКМ на кнопку вызывается функция Hello
# btn.pack() #расположить кнопку на главном окне
# root.mainloop() | [
"[email protected]"
] | |
b1755b3e3660b7295bc811bc77f3610c15e76d96 | 5f8b40db6465a2d28a2369d8b99c8d0db9d06e90 | /samples/pad.py | 9632098c4f8b2c26d1502e92c9d4ec77e99e9779 | [] | no_license | asherkobin/GameOfLife | 4d816ef8b7fcd46ddb3ef055ccfd172a53db9446 | 4fc9a9e568b58bb412b0586698c614211efc168a | refs/heads/master | 2022-11-24T02:10:30.081982 | 2020-07-13T21:35:32 | 2020-07-13T21:35:32 | 267,113,638 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,004 | py | import curses
import curses.panel
def main(win):
global stdscr
global max_y,max_x,mult
stdscr = win
curses.initscr()
curses.cbreak()
curses.noecho()
stdscr.keypad(1)
curses.curs_set(0)
y,x = 0,1
mult = 40
maxcoords = stdscr.getmaxyx()
max_y, max_x = maxcoords[y],maxcoords[x]
pad = curses.newpad(max_y,2000)
drawstuff(pad)
running = True
while running:
mvmt = stdscr.getch()
if mvmt == ord('a'):
mult += 1
pad.refresh(1,1,1,1,max_y,mult)
if mvmt == ord('b'):
mult += 1
pad.refresh(1,1,1,1,max_y,mult)
if mvmt == ord('Q'):
running = False
return
curses.doupdate()
curses.endwin()
def drawstuff(pad):
for i in range(max_x):
for j in range(max_y):
if i % 2 == 0:
pad.addch(j,i,'+')
else:
pad.addch(j,i,'-')
if __name__ == '__main__':
curses.wrapper(main) | [
"[email protected]"
] | |
843eaba7ba980ea2096e0e19da78db3ac8be4534 | 41682d817cd6aab0e73e9c0733a515d77ae7c540 | /worker.py | 8d3c50e7af3f697054a683db8b6a68711b57b3c1 | [] | no_license | subhamsps/testRepo | d2cd328ec40ab5b37b220a0f449f8cbcf14993bc | 3046507cb893e0d58a8722561118b494e06b5c3a | refs/heads/master | 2020-04-29T02:33:56.717073 | 2019-04-08T17:47:20 | 2019-04-08T17:47:20 | 175,773,978 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 839 | py | # A simple Python program for traversal of a linked list
# Node class
class Node:
# Function to initialise the node object
def __init__(self, data):
self.data = data # Assign data
self.next = None # Initialize next as null
# Linked List class contains a Node object
class LinkedList:
# Function to initialize head
def __init__(self):
self.head = None
# This function prints contents of linked list
# starting from head
def printList(self):
temp = self.head
while (temp):
print(temp.data)
temp = temp.next
# Code execution starts here
if __name__=='__main__':
# Start with the empty list
llist = LinkedList()
llist.head = Node(1)
second = Node(2)
third = Node(3)
llist.head.next = second; # Link first node with second
second.next = third; # Link second node with the third node
llist.printList()
| [
"[email protected]"
] | |
51c188fc3582d89f30984fe761bd4de74c07d286 | 711756b796d68035dc6a39060515200d1d37a274 | /output_cog/optimized_24247.py | f41dd9eb54effc2fae8b2b76ddc93da38babc1a1 | [] | no_license | batxes/exocyst_scripts | 8b109c279c93dd68c1d55ed64ad3cca93e3c95ca | a6c487d5053b9b67db22c59865e4ef2417e53030 | refs/heads/master | 2020-06-16T20:16:24.840725 | 2016-11-30T16:23:16 | 2016-11-30T16:23:16 | 75,075,164 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 10,840 | py | import _surface
import chimera
try:
import chimera.runCommand
except:
pass
from VolumePath import markerset as ms
try:
from VolumePath import Marker_Set, Link
new_marker_set=Marker_Set
except:
from VolumePath import volume_path_dialog
d= volume_path_dialog(True)
new_marker_set= d.new_marker_set
marker_sets={}
surf_sets={}
if "Cog2_GFPN" not in marker_sets:
s=new_marker_set('Cog2_GFPN')
marker_sets["Cog2_GFPN"]=s
s= marker_sets["Cog2_GFPN"]
mark=s.place_marker((591.127, 550.172, 433.724), (0.89, 0.1, 0.1), 18.4716)
if "Cog2_0" not in marker_sets:
s=new_marker_set('Cog2_0')
marker_sets["Cog2_0"]=s
s= marker_sets["Cog2_0"]
mark=s.place_marker((558.151, 528.977, 490.027), (0.89, 0.1, 0.1), 17.1475)
if "Cog2_1" not in marker_sets:
s=new_marker_set('Cog2_1')
marker_sets["Cog2_1"]=s
s= marker_sets["Cog2_1"]
mark=s.place_marker((514.189, 493.443, 549.935), (0.89, 0.1, 0.1), 17.1475)
if "Cog2_GFPC" not in marker_sets:
s=new_marker_set('Cog2_GFPC')
marker_sets["Cog2_GFPC"]=s
s= marker_sets["Cog2_GFPC"]
mark=s.place_marker((541.078, 422.008, 433.053), (0.89, 0.1, 0.1), 18.4716)
if "Cog2_Anch" not in marker_sets:
s=new_marker_set('Cog2_Anch')
marker_sets["Cog2_Anch"]=s
s= marker_sets["Cog2_Anch"]
mark=s.place_marker((416.095, 453.45, 712.259), (0.89, 0.1, 0.1), 18.4716)
if "Cog3_GFPN" not in marker_sets:
s=new_marker_set('Cog3_GFPN')
marker_sets["Cog3_GFPN"]=s
s= marker_sets["Cog3_GFPN"]
mark=s.place_marker((560.441, 539.013, 466.666), (1, 1, 0), 18.4716)
if "Cog3_0" not in marker_sets:
s=new_marker_set('Cog3_0')
marker_sets["Cog3_0"]=s
s= marker_sets["Cog3_0"]
mark=s.place_marker((560.484, 539.715, 465.403), (1, 1, 0.2), 17.1475)
if "Cog3_1" not in marker_sets:
s=new_marker_set('Cog3_1')
marker_sets["Cog3_1"]=s
s= marker_sets["Cog3_1"]
mark=s.place_marker((552.11, 550.537, 440.768), (1, 1, 0.2), 17.1475)
if "Cog3_2" not in marker_sets:
s=new_marker_set('Cog3_2')
marker_sets["Cog3_2"]=s
s= marker_sets["Cog3_2"]
mark=s.place_marker((528.693, 538.373, 431.649), (1, 1, 0.2), 17.1475)
if "Cog3_3" not in marker_sets:
s=new_marker_set('Cog3_3')
marker_sets["Cog3_3"]=s
s= marker_sets["Cog3_3"]
mark=s.place_marker((511.774, 558.115, 441.881), (1, 1, 0.2), 17.1475)
if "Cog3_4" not in marker_sets:
s=new_marker_set('Cog3_4')
marker_sets["Cog3_4"]=s
s= marker_sets["Cog3_4"]
mark=s.place_marker((491.711, 546.71, 425.922), (1, 1, 0.2), 17.1475)
if "Cog3_5" not in marker_sets:
s=new_marker_set('Cog3_5')
marker_sets["Cog3_5"]=s
s= marker_sets["Cog3_5"]
mark=s.place_marker((490.69, 571.213, 412.926), (1, 1, 0.2), 17.1475)
if "Cog3_GFPC" not in marker_sets:
s=new_marker_set('Cog3_GFPC')
marker_sets["Cog3_GFPC"]=s
s= marker_sets["Cog3_GFPC"]
mark=s.place_marker((585.097, 551.597, 459.839), (1, 1, 0.4), 18.4716)
if "Cog3_Anch" not in marker_sets:
s=new_marker_set('Cog3_Anch')
marker_sets["Cog3_Anch"]=s
s= marker_sets["Cog3_Anch"]
mark=s.place_marker((395.497, 593.978, 372.046), (1, 1, 0.4), 18.4716)
if "Cog4_GFPN" not in marker_sets:
s=new_marker_set('Cog4_GFPN')
marker_sets["Cog4_GFPN"]=s
s= marker_sets["Cog4_GFPN"]
mark=s.place_marker((354.731, 547.327, 564.438), (0, 0, 0.8), 18.4716)
if "Cog4_0" not in marker_sets:
s=new_marker_set('Cog4_0')
marker_sets["Cog4_0"]=s
s= marker_sets["Cog4_0"]
mark=s.place_marker((354.731, 547.327, 564.438), (0, 0, 0.8), 17.1475)
if "Cog4_1" not in marker_sets:
s=new_marker_set('Cog4_1')
marker_sets["Cog4_1"]=s
s= marker_sets["Cog4_1"]
mark=s.place_marker((381.51, 546.932, 552.901), (0, 0, 0.8), 17.1475)
if "Cog4_2" not in marker_sets:
s=new_marker_set('Cog4_2')
marker_sets["Cog4_2"]=s
s= marker_sets["Cog4_2"]
mark=s.place_marker((408.798, 544.379, 541.772), (0, 0, 0.8), 17.1475)
if "Cog4_3" not in marker_sets:
s=new_marker_set('Cog4_3')
marker_sets["Cog4_3"]=s
s= marker_sets["Cog4_3"]
mark=s.place_marker((436.698, 538.561, 532.225), (0, 0, 0.8), 17.1475)
if "Cog4_4" not in marker_sets:
s=new_marker_set('Cog4_4')
marker_sets["Cog4_4"]=s
s= marker_sets["Cog4_4"]
mark=s.place_marker((464.967, 534.516, 524.764), (0, 0, 0.8), 17.1475)
if "Cog4_5" not in marker_sets:
s=new_marker_set('Cog4_5')
marker_sets["Cog4_5"]=s
s= marker_sets["Cog4_5"]
mark=s.place_marker((492.885, 537.772, 518.397), (0, 0, 0.8), 17.1475)
if "Cog4_6" not in marker_sets:
s=new_marker_set('Cog4_6')
marker_sets["Cog4_6"]=s
s= marker_sets["Cog4_6"]
mark=s.place_marker((513.156, 551.557, 503.757), (0, 0, 0.8), 17.1475)
if "Cog4_GFPC" not in marker_sets:
s=new_marker_set('Cog4_GFPC')
marker_sets["Cog4_GFPC"]=s
s= marker_sets["Cog4_GFPC"]
mark=s.place_marker((263.588, 534.134, 438.154), (0, 0, 0.8), 18.4716)
if "Cog4_Anch" not in marker_sets:
s=new_marker_set('Cog4_Anch')
marker_sets["Cog4_Anch"]=s
s= marker_sets["Cog4_Anch"]
mark=s.place_marker((762.458, 564.868, 573.574), (0, 0, 0.8), 18.4716)
if "Cog5_GFPN" not in marker_sets:
s=new_marker_set('Cog5_GFPN')
marker_sets["Cog5_GFPN"]=s
s= marker_sets["Cog5_GFPN"]
mark=s.place_marker((516.971, 541.55, 550.287), (0.3, 0.3, 0.3), 18.4716)
if "Cog5_0" not in marker_sets:
s=new_marker_set('Cog5_0')
marker_sets["Cog5_0"]=s
s= marker_sets["Cog5_0"]
mark=s.place_marker((516.971, 541.55, 550.287), (0.3, 0.3, 0.3), 17.1475)
if "Cog5_1" not in marker_sets:
s=new_marker_set('Cog5_1')
marker_sets["Cog5_1"]=s
s= marker_sets["Cog5_1"]
mark=s.place_marker((524.701, 520.043, 532.301), (0.3, 0.3, 0.3), 17.1475)
if "Cog5_2" not in marker_sets:
s=new_marker_set('Cog5_2')
marker_sets["Cog5_2"]=s
s= marker_sets["Cog5_2"]
mark=s.place_marker((518.156, 496.095, 517.283), (0.3, 0.3, 0.3), 17.1475)
if "Cog5_3" not in marker_sets:
s=new_marker_set('Cog5_3')
marker_sets["Cog5_3"]=s
s= marker_sets["Cog5_3"]
mark=s.place_marker((522.974, 469.313, 527.494), (0.3, 0.3, 0.3), 17.1475)
if "Cog5_GFPC" not in marker_sets:
s=new_marker_set('Cog5_GFPC')
marker_sets["Cog5_GFPC"]=s
s= marker_sets["Cog5_GFPC"]
mark=s.place_marker((597.329, 492.17, 431.012), (0.3, 0.3, 0.3), 18.4716)
if "Cog5_Anch" not in marker_sets:
s=new_marker_set('Cog5_Anch')
marker_sets["Cog5_Anch"]=s
s= marker_sets["Cog5_Anch"]
mark=s.place_marker((450.148, 440.633, 626.042), (0.3, 0.3, 0.3), 18.4716)
if "Cog6_GFPN" not in marker_sets:
s=new_marker_set('Cog6_GFPN')
marker_sets["Cog6_GFPN"]=s
s= marker_sets["Cog6_GFPN"]
mark=s.place_marker((567.05, 508.111, 472.181), (0.21, 0.49, 0.72), 18.4716)
if "Cog6_0" not in marker_sets:
s=new_marker_set('Cog6_0')
marker_sets["Cog6_0"]=s
s= marker_sets["Cog6_0"]
mark=s.place_marker((567.18, 507.83, 472.003), (0.21, 0.49, 0.72), 17.1475)
if "Cog6_1" not in marker_sets:
s=new_marker_set('Cog6_1')
marker_sets["Cog6_1"]=s
s= marker_sets["Cog6_1"]
mark=s.place_marker((539.941, 505.099, 467.782), (0.21, 0.49, 0.72), 17.1475)
if "Cog6_2" not in marker_sets:
s=new_marker_set('Cog6_2')
marker_sets["Cog6_2"]=s
s= marker_sets["Cog6_2"]
mark=s.place_marker((516.22, 513.736, 455.831), (0.21, 0.49, 0.72), 17.1475)
if "Cog6_3" not in marker_sets:
s=new_marker_set('Cog6_3')
marker_sets["Cog6_3"]=s
s= marker_sets["Cog6_3"]
mark=s.place_marker((495.42, 532.128, 457.926), (0.21, 0.49, 0.72), 17.1475)
if "Cog6_4" not in marker_sets:
s=new_marker_set('Cog6_4')
marker_sets["Cog6_4"]=s
s= marker_sets["Cog6_4"]
mark=s.place_marker((478.453, 554.246, 457.003), (0.21, 0.49, 0.72), 17.1475)
if "Cog6_5" not in marker_sets:
s=new_marker_set('Cog6_5')
marker_sets["Cog6_5"]=s
s= marker_sets["Cog6_5"]
mark=s.place_marker((483.011, 579.139, 445.049), (0.21, 0.49, 0.72), 17.1475)
if "Cog6_6" not in marker_sets:
s=new_marker_set('Cog6_6')
marker_sets["Cog6_6"]=s
s= marker_sets["Cog6_6"]
mark=s.place_marker((500.654, 596.305, 432.034), (0.21, 0.49, 0.72), 17.1475)
if "Cog6_GFPC" not in marker_sets:
s=new_marker_set('Cog6_GFPC')
marker_sets["Cog6_GFPC"]=s
s= marker_sets["Cog6_GFPC"]
mark=s.place_marker((545.229, 600.839, 505.286), (0.21, 0.49, 0.72), 18.4716)
if "Cog6_Anch" not in marker_sets:
s=new_marker_set('Cog6_Anch')
marker_sets["Cog6_Anch"]=s
s= marker_sets["Cog6_Anch"]
mark=s.place_marker((453.3, 585.077, 359.443), (0.21, 0.49, 0.72), 18.4716)
if "Cog7_GFPN" not in marker_sets:
s=new_marker_set('Cog7_GFPN')
marker_sets["Cog7_GFPN"]=s
s= marker_sets["Cog7_GFPN"]
mark=s.place_marker((569.881, 572.648, 532.303), (0.7, 0.7, 0.7), 18.4716)
if "Cog7_0" not in marker_sets:
s=new_marker_set('Cog7_0')
marker_sets["Cog7_0"]=s
s= marker_sets["Cog7_0"]
mark=s.place_marker((564.77, 547.607, 527.181), (0.7, 0.7, 0.7), 17.1475)
if "Cog7_1" not in marker_sets:
s=new_marker_set('Cog7_1')
marker_sets["Cog7_1"]=s
s= marker_sets["Cog7_1"]
mark=s.place_marker((551.494, 493.359, 514.045), (0.7, 0.7, 0.7), 17.1475)
if "Cog7_2" not in marker_sets:
s=new_marker_set('Cog7_2')
marker_sets["Cog7_2"]=s
s= marker_sets["Cog7_2"]
mark=s.place_marker((536.082, 439.216, 501.45), (0.7, 0.7, 0.7), 17.1475)
if "Cog7_GFPC" not in marker_sets:
s=new_marker_set('Cog7_GFPC')
marker_sets["Cog7_GFPC"]=s
s= marker_sets["Cog7_GFPC"]
mark=s.place_marker((608.487, 438.957, 465.359), (0.7, 0.7, 0.7), 18.4716)
if "Cog7_Anch" not in marker_sets:
s=new_marker_set('Cog7_Anch')
marker_sets["Cog7_Anch"]=s
s= marker_sets["Cog7_Anch"]
mark=s.place_marker((461.56, 366.071, 509.789), (0.7, 0.7, 0.7), 18.4716)
if "Cog8_0" not in marker_sets:
s=new_marker_set('Cog8_0')
marker_sets["Cog8_0"]=s
s= marker_sets["Cog8_0"]
mark=s.place_marker((575.251, 474.626, 465.989), (1, 0.5, 0), 17.1475)
if "Cog8_1" not in marker_sets:
s=new_marker_set('Cog8_1')
marker_sets["Cog8_1"]=s
s= marker_sets["Cog8_1"]
mark=s.place_marker((595.039, 471.362, 485.911), (1, 0.5, 0), 17.1475)
if "Cog8_2" not in marker_sets:
s=new_marker_set('Cog8_2')
marker_sets["Cog8_2"]=s
s= marker_sets["Cog8_2"]
mark=s.place_marker((591.024, 491.415, 505.418), (1, 0.5, 0), 17.1475)
if "Cog8_3" not in marker_sets:
s=new_marker_set('Cog8_3')
marker_sets["Cog8_3"]=s
s= marker_sets["Cog8_3"]
mark=s.place_marker((580.611, 493.353, 531.521), (1, 0.5, 0), 17.1475)
if "Cog8_4" not in marker_sets:
s=new_marker_set('Cog8_4')
marker_sets["Cog8_4"]=s
s= marker_sets["Cog8_4"]
mark=s.place_marker((564.708, 490.26, 555.028), (1, 0.5, 0), 17.1475)
if "Cog8_5" not in marker_sets:
s=new_marker_set('Cog8_5')
marker_sets["Cog8_5"]=s
s= marker_sets["Cog8_5"]
mark=s.place_marker((553.024, 482.707, 580.407), (1, 0.5, 0), 17.1475)
if "Cog8_GFPC" not in marker_sets:
s=new_marker_set('Cog8_GFPC')
marker_sets["Cog8_GFPC"]=s
s= marker_sets["Cog8_GFPC"]
mark=s.place_marker((570.894, 525.42, 514.688), (1, 0.6, 0.1), 18.4716)
if "Cog8_Anch" not in marker_sets:
s=new_marker_set('Cog8_Anch')
marker_sets["Cog8_Anch"]=s
s= marker_sets["Cog8_Anch"]
mark=s.place_marker((533.826, 440.217, 648.202), (1, 0.6, 0.1), 18.4716)
for k in surf_sets.keys():
chimera.openModels.add([surf_sets[k]])
| [
"[email protected]"
] | |
9ef7705adfd20289b94d32e635c9782513a6bf09 | 22168b5ae3a347f3a310ac23c87ffe4d313534bb | /s3backupper.py | 2d4542231ca6bc4f31c20983b275a66a6e42f306 | [] | no_license | iamanders/s3backupper | f93b8ae96b83524fdb0b5e07f5ef882bfa5d45b6 | a2870eeaa93753246f7498d1af1dc591b605f082 | refs/heads/master | 2021-01-19T07:55:07.968577 | 2010-01-22T13:53:00 | 2010-01-22T13:53:00 | 482,263 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,164 | py | #!/usr/bin/python
# -*- coding: utf-8 -*-
import os
import time
import tarfile
from boto.s3.connection import S3Connection
from boto.s3.key import Key
class uploader:
"""Class for gzip and upload files to Amazon S3"""
def __init__(self, access_key, secret_key, crypt_key):
self.access_key = access_key
self.secret_key = secret_key
self.crypt_key = crypt_key
self.s3connection = S3Connection(access_key, secret_key)
def the_magic(self, id, path_to_bup, bucketname, date_in_filename, crypt):
file_contents = os.listdir(path_to_bup)
if date_in_filename:
s3_filename = "%s_%s.tar.gz" % (id, time.strftime("%Y-%m-%d-%H%M%S"))
else:
s3_filename = id + '.tar.gz'
temp_filename = '/tmp/backup.tar.gz'
#tar files
files = os.listdir(path_to_bup)
tar = tarfile.open(temp_filename, 'w:gz')
for f in files:
tar.add(path_to_bup + f)
tar.close()
#crypt the file?
if crypt:
os.system("gpg -c --passphrase '%s' --yes /tmp/backup.tar.gz" % self.crypt_key)
temp_filename += '.gpg'
s3_filename += '.gpg'
#upload
bucket = self.s3connection.get_bucket(bucketname)
s3key = Key(bucket)
s3key.key = s3_filename
s3key.set_contents_from_filename(temp_filename)
#clean the tmp folder
os.remove('/tmp/backup.tar.gz')
if crypt:
os.remove('/tmp/backup.tar.gz.gpg')
if __name__ == '__main__':
access_key = 'PUT YOUR AMAZON ACCESS KEY HERE'
secret_key = 'PUT YOUR AMAZON SECRET KEY HERE'
crypt_key = 'PUT-A-SECRET-CRYPT-CODE-HERE'
uploader = uploader(access_key, secret_key, crypt_key)
#To backup
to_backup = [
{ 'id': 'foo', 'path': '/path/to/files1/', 'bucket': 'bucket1', 'date': True, 'crypt': True },
#{ 'id': 'bar', 'path': '/path/to/files2/', 'bucket': 'bucket2', 'date': False, 'Crypt': False },
]
print ''
#Loop and upload
for b in to_backup:
print '%s - start backup %s' % (time.strftime("%Y-%m-%d %H:%M:%S"), b['id'])
try:
uploader.the_magic(b['id'], b['path'], b['bucket'], b['date'], b['crypt'])
except:
print '%s - FAIL %s' % (time.strftime("%Y-%m-%d %H:%M:%S"), b['id'])
print ''
print '%s - DONE!' % time.strftime("%Y-%m-%d %H:%M:%S")
print '' | [
"[email protected]"
] | |
f3c5d20d29dd9b88627ce522e66785298e8855f1 | 498fcf34fa4482be5c9fefc488666e60edcf46c7 | /supervised_learning/0x08-deep_cnns/6-transition_layer.py | b1f56c159fcbde725fe51e00dbf6f594f96be8dd | [] | no_license | MansourKef/holbertonschool-machine_learning | 7dbc465def04c311c1afb0e8b8903cbe34c72ad3 | 19f78fc09f0ebeb9f27f3f76b98e7a0e9212fd22 | refs/heads/main | 2023-03-12T16:18:08.919099 | 2021-03-05T09:42:09 | 2021-03-05T09:42:09 | 317,303,125 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 659 | py | #!/usr/bin/env python3
"""module"""
import tensorflow.keras as K
def transition_layer(X, nb_filters, compression):
"""function"""
BN1 = K.layers.BatchNormalization(axis=3)(X)
Relu1 = K.layers.Activation("relu")(BN1)
conv1 = K.layers.Conv2D(int(compression * nb_filters),
kernel_size=(1, 1),
padding="same",
kernel_initializer="he_normal",
strides=(1, 1))(Relu1)
pool5 = K.layers.AveragePooling2D(pool_size=(2, 2),
strides=(2, 2))(conv1)
return pool5, int(compression * nb_filters)
| [
"[email protected]"
] | |
e2143b19b050bbbb72261ab6e4bd8ec5639ae272 | 9cc3011ae618d43f6f09a98f2ea4577bb57b3482 | /week8/3.2.Цикл while/a.py | d927561ceda36772314c4c577b15165260fde5a5 | [] | no_license | Alexey929/web-development | 2992db5f18917641740886d8920c1486f61b84e9 | c50a394734614bb5b05cfc0d43cb7ccd9e4087af | refs/heads/master | 2023-01-13T20:29:06.663877 | 2020-04-28T13:41:32 | 2020-04-28T13:41:32 | 236,985,130 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 120 | py | import math
x = int(input())
i = 1
root = math.sqrt(x)
while i <= root:
print(str(i * i) + " ", end='')
i += 1
| [
"[email protected]"
] | |
19e02e30a90fc1c0781c84ee261b118d7bd1b1bb | 91652afbc75037f6c631dbe9c14c343514d07469 | /examples/static.py | 80e29ed6bb54b099e5dd92eeaef8911dc9804300 | [] | no_license | BitTheByte/Pybook | beb2186077cdecd821a25b015522beeb3e1d4426 | 8385a9006b4c8577412fa75d7c2196e0e0c539a5 | refs/heads/master | 2023-06-11T02:57:21.458411 | 2023-06-04T18:58:26 | 2023-06-04T18:58:26 | 148,077,126 | 4 | 2 | null | 2023-06-04T18:58:27 | 2018-09-10T00:15:29 | Python | UTF-8 | Python | false | false | 717 | py | """
please move this example to the root directory
"""
from lib.session import *
from lib.parser import *
from lib.engine import *
fbsession = login("[email protected]","Secret_Password123") # login with facebook
def hi(msg):
print msg
return "HELLO FROM FUNCTION"
"""
def custom(message):
print message
return message + " WOW!"
"""
myreplies = {
"hi":"Hello from python!",
"failReply":"Sorry i don't understand :(",
"func_hello":hi
}
options = {
"keysearch" :1, # find the closest key replies
"failReply" :0, # use a fail reply
#"replyHook" :custom, use a custom function to generate answers
}
StaticMessageHook(fbsession,options,myreplies)
| [
"[email protected]"
] | |
47204ab5273867d202c0c4bdbd8c953a99b17499 | f9c223341e3c052705cc08291d2246399121f037 | /LSR/lsr.py | 3e5ea30d0781c904bd887def9f5932d263d6258a | [] | no_license | andreaeliasc/Lab3-Redes | 185155d91e7f0eec6c59956751c830a19e2e197e | 037f06a632d0e5972f150dc005c29cae232dcf48 | refs/heads/main | 2023-07-15T14:57:28.684337 | 2021-09-01T03:03:57 | 2021-09-01T03:03:57 | 401,242,615 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 7,107 | py | import asyncio
from asyncio.tasks import sleep
import slixmpp
from getpass import getpass
from aioconsole import ainput, aprint
import time
from utils import *
class LSRClient(slixmpp.ClientXMPP):
def __init__(self, jid, password, topo_file,names_file):
slixmpp.ClientXMPP.__init__(self, jid, password)
self.add_event_handler("session_start", self.start)
self.add_event_handler("message", self.message)
self.topo_file = topo_file
self.names_file = names_file
self.network = []
self.echo_sent = None
self.LSP = {
'type': lsp,
'from': self.boundjid.bare,
'sequence': 1,
'neighbours':{}
}
self.id = get_ID(self.names_file, jid)
self.neighbours_IDS = get_neighbors(self.topo_file, self.id)
self.neighbours = []
self.neighbours_JID()
async def start(self, event):
self.send_presence()
await self.get_roster()
print("Press enter to start:")
start = await ainput()
for neighbour in self.neighbours:
await self.send_hello_msg(neighbour)
for neighbour in self.neighbours:
await self.send_echo_message(neighbour, echo_send)
self.network.append(self.LSP)
self.loop.create_task(self.send_LSP())
await sleep(2)
print("Type the jid of the user you want to message (or wait until someone messages you!)")
send = await ainput()
if send != None:
message = await ainput('Type your message: ')
#Waiting some time so that the network converges
print("Waiting for network to converge")
await sleep(17)
print("Network converged, sending message")
self.send_chat_message(self.boundjid.bare,send,steps=1,visited_nodes=[self.boundjid.bare],message=message)
print("press enter to exit")
exit = await ainput()
self.disconnect()
def neighbours_JID(self):
for id in self.neighbours_IDS:
neighbour_JID = get_JID(self.names_file, id)
self.neighbours.append(neighbour_JID)
async def message(self, msg):
body = json_to_object(msg['body'])
if body['type'] == hello:
print("Hello from: ", msg['from'])
elif body['type'] == echo_send:
print("Echoing back to: ", msg['from'])
await self.send_echo_message(body['from'],echo_response)
elif body['type'] == echo_response:
distance = time.time()-self.echo_sent
print("Distance to ", msg['from'], ' is ', distance)
self.LSP['neighbours'][body['from']] = distance
elif body['type'] == lsp:
new = await self.update_network(body)
await self.flood_LSP(body, new)
elif body['type'] == message_type:
if body['to'] != self.boundjid.bare:
print('Got a message that is not for me, sending it ')
self.send_chat_message(source = body['from'],to = body['to'], steps=body['steps'] +1, distance=body['distance'],visited_nodes= body['visited_nodes'].append(self.boundjid.bare),message=body['mesage'])
elif body['to'] == self.boundjid.bare:
print('Got a message!')
print(body['from'], " : ", body['mesage'])
print(body)
async def send_hello_msg(self,to, steps = 1):
you = self.boundjid.bare
to = to
json = {
'type': hello,
'from':you,
'to': to,
'steps': steps
}
to_send = object_to_json(json)
self.send_message(mto = to, mbody=to_send, mtype='chat')
async def send_echo_message(self, to, type ,steps = 1):
you = self.boundjid.bare
to = to
json = {
'type': type,
'from':you,
'to': to,
'steps': steps
}
to_send = object_to_json(json)
self.send_message(mto = to, mbody=to_send, mtype='chat')
self.echo_sent = time.time()
async def send_LSP(self):
while True:
for neighbour in self.neighbours:
lsp_to_send = object_to_json(self.LSP)
self.send_message(mto =neighbour,mbody=lsp_to_send,mtype='chat')
await sleep(2)
self.LSP['sequence'] += 1
def send_chat_message(self,source,to,steps=0, distance = 0, visited_nodes = [],message="Hola mundo"):
body ={
'type':message_type,
'from': source,
'to': to,
'steps': steps,
'distance': distance,
'visited_nodes':visited_nodes,
'mesage':message
}
path = self.calculate_path(self.boundjid.bare, to)
body['distance'] += self.LSP['neighbours'][path[1]['from']]
to_send = object_to_json(body)
self.send_message(mto=path[1]['from'],mbody = to_send,mtype='chat')
async def update_network(self, lsp):
for i in range(0,len(self.network)):
node = self.network[i]
if lsp['from'] == node['from']:
if lsp['sequence'] > node['sequence']:
node['sequence'] = lsp['sequence']
node['neighbours'] = lsp['neighbours']
return 1
if lsp['sequence'] <= node['sequence']:
return None
self.network.append(lsp)
return 1
def calculate_path(self, source, dest):
distance = 0
visited = []
current_node = self.find_node_in_network(source)
while current_node['from'] != dest:
node_distances = []
neighbours = current_node['neighbours']
for neighbour in neighbours.keys():
if neighbour == dest:
visited.append(current_node)
current_node = self.find_node_in_network(neighbour)
visited.append(current_node)
return visited
elif neighbour not in visited:
distance_to_neighbour = neighbours[neighbour]
node_distances.append(distance_to_neighbour)
min_distance = min(node_distances)
node_index = node_distances.index(min_distance)
all_nodes = list(current_node['neighbours'].keys())
next_node_id = all_nodes[node_index]
visited.append(current_node)
next_node = self.find_node_in_network(next_node_id)
current_node = next_node
distance += min_distance
return visited
def find_node_in_network(self, id):
for i in range(len(self.network)):
node = self.network[i]
if id in node['from']:
return node
return False
async def flood_LSP(self, lsp, new):
for neighbour in self.neighbours:
if new and neighbour != lsp['from']:
self.send_message(mto =neighbour,mbody=object_to_json(lsp),mtype='chat') | [
"[email protected]"
] | |
a003a04f25ae531bcff5fcc6b77658dab1d893f8 | ca82e3c6084e697ecbdbf32d96c08293c5540287 | /courses/python_data_structures_linked_lists/Exercise Files/Ch05/05_01/End/dll.py | 50cac5b09fdcbb4bdfd6e43e8d6640dcd496bb4e | [] | no_license | bheki-maenetja/small-projects-py | 8c8b35444ff2ecef7ad77e709392a9c860967ecc | 18504d2e1f1ea48b612a4e469828682f426c9704 | refs/heads/master | 2023-08-17T00:38:06.208787 | 2023-08-16T16:25:22 | 2023-08-16T16:25:22 | 131,871,876 | 1 | 0 | null | 2023-08-14T23:44:23 | 2018-05-02T15:37:58 | Python | UTF-8 | Python | false | false | 1,390 | py | class DLLNode:
def __init__(self, data):
self.data = data
self.next = None
self.previous = None
def __repr__(self):
return "DLLNode object: data={}".format(self.data)
def get_data(self):
"""Return the self.data attribute."""
return self.data
def set_data(self, new_data):
"""Replace the existing value of the self.data attribute with new_data
parameter."""
self.data = new_data
def get_next(self):
"""Return the self.next attribute"""
return self.next
def set_next(self, new_next):
"""Replace the existing value of the self.next attribute with new_next
parameter."""
self.next = new_next
def get_previous(self):
"""Return the self.previous attribute"""
return self.previous
def set_previous(self, new_previous):
"""Replace the existing value of the self.previous attribute with
new_previous parameter."""
self.previous = new_previous
class DLL:
def __init__(self):
self.head = None
def __repr__(self):
return "<DLL object: head=>".format(self.head)
def is_empty(self):
return self.head is None
def size(self):
pass
def search(self, data):
pass
def add_front(self, data):
pass
def remove(self, data):
pass
| [
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] | |
c32ad72dc0b1b7022ee645d091b9a96888d5760e | 373ecb4548a8412b50b685d1ec0e5cea59a9425f | /Week 13/gallons_convert.py | 1b8e1392e2709b2e5541696f6c477f0ab07e0127 | [] | no_license | stewartrowley/CSE110 | 847c04c036b62f718952a12a65163281e23fac2c | 57c744aa1f2b40c5f9b13b26b6558196aef3d515 | refs/heads/main | 2023-08-15T22:25:50.487798 | 2021-09-29T02:34:24 | 2021-09-29T02:34:24 | 411,504,145 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 978 | py | def convert_gallons_to_ounces(gallon):
"""
Functions: convert_gallon_to_ounces
Description: convert gallons to ounces
Params:
gallons (float) - The amoun in gallons
returns:
Float - The amoun in ounces
"""
return gallon * 128
def convert_gallons_to_litiets(gallons):
"""
Functions: convert_gallons_to_litiers
Description: Converts gallons to litiers
Params:
gallons (float) - The amount in gallons
Returns:
float: The amount in litiers
"""
return gallons * 3.751
def main():
starting_number = int(input("How many bottles of milk do you want to start with? "))
for bottle_count in range(starting_number, 0, -1):
ounces = convert_gallons_to_ounces(bottle_count)
litiers = convert_gallons_to_litiets(bottle_count)
print(f"{bottle_count} gallons ({ounces} oz, {litiers:.2f} litiers) of milk on the wall... ")
main()
# print(convert_gallons_to_litiers()) | [
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] | |
21821ff603c4c08ad1e79cfc45c19e207342a87f | da8e3af2bfbad7109c19e37efe6b10bd5b1e0f56 | /이코테/DP/q32_정수삼각형.py | b6fb0e0512b1f63802f795516949612640493eb5 | [] | no_license | cheonyeji/algorithm_study | fead92b52e42d98a0fdf7f3395ed0a6676c8b972 | ef2f5e50f874751a9ba8e9157a13f832f439618b | refs/heads/master | 2023-09-01T00:41:24.600614 | 2023-08-31T07:39:45 | 2023-08-31T07:39:45 | 234,265,247 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 521 | py | # 2022-01-19
# 이코테 ch16 다이나믹 프로그래밍
# https://www.acmicpc.net/problem/1932
n = int(input())
tri = []
for _ in range(n):
tri.append(list(map(int, input().split())))
for i in range(1, n):
for j in range(0, i + 1):
if j == 0:
tri[i][j] += tri[i - 1][j]
elif j == i:
tri[i][j] += tri[i - 1][i - 1]
else:
tri[i][j] += max(tri[i - 1][j - 1], tri[i - 1][j])
print(max(tri[n - 1]))
"""
TC -> 30
5
7
3 8
8 1 0
2 7 4 4
4 5 2 6 5
"""
| [
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] | |
8ad86d60b83d577d0c3cb1c91bfc2655109ff2b6 | 60130f382f2ffff27994a6fc573cd56c87d99450 | /Requests/requeststests.py | 336a072034b6c8686021d63c8e3b9100eff94194 | [] | no_license | hellknight87/python | 4be75dc8ffee810edaa485366f423d24f0fdec0a | ced1ff205e21ba5e73dfd35dcbefad5ba4d4a3cf | refs/heads/master | 2021-04-03T06:28:36.208338 | 2018-05-09T06:11:30 | 2018-05-09T06:11:30 | 125,104,124 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 197 | py | import requests
params = {"q": "pizza"}
r = requests.get("http://www.bing.com/search", params=params)
print("Status:", r.status_code)
print(r.url)
f = open("./page.html", "w+")
f.write(r.text)
| [
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] | |
ccd8398a6f0d223f5b36f6d68625ad6b7499eeec | 0d42d967b732a789705f9e08e538090f69808706 | /flaskr/__init__.py | 1ada9012763c5ef7962dc17079683c63cf8938b6 | [
"MIT"
] | permissive | aicioara-old/flask_tutorial2 | f812ed25f57430b48669587dd2e6905760df33bb | acb5c6fa2743f2f060ad6a3a26cc7eef56b6490b | refs/heads/master | 2020-05-23T16:31:32.983214 | 2019-05-14T17:35:23 | 2019-05-14T17:35:23 | 186,851,392 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,170 | py | import os
import datetime
import click
from flask import Flask
from flask import current_app, g
def create_app(test_config=None):
# create and configure the app
app = Flask(__name__, instance_relative_config=True)
app.config.from_mapping(
SECRET_KEY='dev',
DATABASE=os.path.join(app.instance_path, 'flaskr.sqlite'),
SQLALCHEMY_DATABASE_URI='sqlite:///' + os.path.join(app.instance_path, 'flaskr2.sqlite'),
SQLALCHEMY_TRACK_MODIFICATIONS=False,
)
if test_config is None:
# load the instance config, if it exists, when not testing
app.config.from_pyfile('config.py', silent=True)
else:
# load the test config if passed in
app.config.from_mapping(test_config)
# ensure the instance folder exists
try:
os.makedirs(app.instance_path)
except OSError:
pass
from flaskr import commands
commands.init_app(app)
from .models import db
db.init_app(app)
from .views import auth
app.register_blueprint(auth.bp)
from .views import blog
app.register_blueprint(blog.bp)
app.add_url_rule('/', endpoint='index')
return app
| [
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] | |
14de26357470049d34384244bc6dfe2cabc076b9 | a80ce010d5d9b459d07bc4ff838123e3d9e8a394 | /conftest.py | 82c66e9c1664f34e156e8abc834440a12310ad01 | [] | no_license | teola/mail-test | df20e7d7e2f3ef178a85c777320222183f7a3eeb | 6594455a1a9f5323cadb20bc4997327cca171c88 | refs/heads/main | 2023-05-07T00:44:42.754919 | 2021-06-01T14:10:36 | 2021-06-01T14:18:13 | 372,849,095 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 193 | py | import pytest
import time
from selenium import webdriver
@pytest.fixture(scope="session")
def browser():
driver = webdriver.Firefox()
yield driver
time.sleep(3)
driver.quit()
| [
"[email protected]"
] | |
1a7945122da319698aab18dff3ea548ff1990001 | cd7557f4daedf3447673c67e13b1c67220905b0e | /Judgment Classifier.py | 718395714852f46853f26e330aace481d2f0abae | [] | no_license | Jason1286/Copyright_88_Classifier | 5774703773ac5816401ba2256777f74d0f9a0859 | 02ba028235c21aa79cae00727effb15a111b8568 | refs/heads/main | 2023-06-02T01:51:59.552419 | 2021-06-25T07:12:30 | 2021-06-25T07:12:30 | 380,103,097 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 7,381 | py | #!/usr/bin/env python
# coding: utf-8
# 使用套件
import os
import re
import pandas as pd
import numpy as np
from itertools import compress
# 人工標記結果
manual_label_df = pd.read_excel(r'C:\Users\ASUS VivoBook\Desktop\計算與法律分析\Final_Project\判決標註.xlsx', sheet_name = '工作表1') # read all sheets
manual_label_id = list(manual_label_df['檔案編號'])
manual_filename = ['verdict_' + str('{:03}'.format(x)) + '.txt' for x in sorted(manual_label_id)]
# 建立自動判決結果dataframe
dict2df = {'verdict':manual_filename,
'判決書案號':list(manual_label_df['判決書案號']),
'駁回_Auto':None,'駁回_Manual':manual_label_df['駁回'],
'原告引用法條_Auto':None,'法官判決法條_Auto':None,
'原告引用法條_Manual':manual_label_df['原告引用法條'],
'法官判決法條_Manual':manual_label_df['法官判決法條'],
'駁回_Diff':None,'原告引用法條_Diff':None,'法官判決法條_Diff':None
}
label_df = pd.DataFrame.from_dict(dict2df)
label_df = label_df.set_index(['verdict'])
# 讀去判決書
def read_verdict(entry):
os.chdir(r'C:\Users\ASUS VivoBook\Desktop\計算與法律分析\Final_Project\All_Verdicts')
f = open(entry, 'r', encoding = 'utf-8-sig')
txt = f.readlines()
txt = [re.sub('\n', '', x) for x in txt]
txt = [x for x in txt if x != '']
return txt
# 著作權法第88條項目提取
def case_detection(txt):
c23_regex = re.compile(r'著作權法(第\d+條)?(、)?第(88|八十八)條(第)?(1|一)?(項)?(、)?(第)?(2|二)(項)?(、)?(或)?(第)?(3|三)項')
c2_regex = re.compile(r'著作權法(第\d+條)?(、)?第(88|八十八)條第(1|一)?(項)?(、)?(第)?(2|二)項')
c3_regex = re.compile(r'著作權法(第\d+條)?(、)?第(88|八十八)條第(1|一)?(項)?(、)?(第)?(3|三)項')
cX_regex = re.compile(r'著作權法(第\d+條)?(、)?第(88|八十八)條(\S+)?')
if bool(c23_regex.search(txt)) == True:
return 4
elif bool(c2_regex.search(txt)) == True:
return 2
elif bool(c3_regex.search(txt)) == True:
return 3
else:
return 99
def fill_dataframe(classify_, colname, filename):
if 4 in classify_:
label_df.loc[filename,colname] = 4
elif 3 in classify_:
label_df.loc[filename,colname] = 3
elif 2 in classify_:
label_df.loc[filename,colname] = 2
elif 99 in classify_:
label_df.loc[filename,colname] = 99
elif classify_ == []:
label_df.loc[filename,colname] = 99
# 著作權法第88條項目分類
def Classify(filename):
current_verdict = read_verdict(filename)
# dissmiss detection
main_rex = re.compile('^主文')
main_txt = [current_verdict[i] for i, x in enumerate(current_verdict) if main_rex.search(x) != None]
rex1 = re.compile(r'(應?(連帶)?給付)(周年利率|週年利率|年息|年利率)?(百分之五|百分之5|5％|5%)?')
if bool(rex1.search(main_txt[0])) == True:
label_df.loc[filename,'駁回_Auto'] = 0
else:
label_df.loc[filename,'駁回_Auto'] = 1
# 提取著作權法第88條相關條文
rex88 = re.compile(r'著作權法(第\d+條)?(、)?(第\d+項)?(、)?第(88|八十八)(、\d+-\d)?(、\d+){0,2}?條(第)?(1|一|2|二|3|三)?(項)?(及)?((、)?第(2|二)項)?((、)?第(3|三)項)?((、)?(2|二)項)?((、)?(3|三)項)?')
filter1 = [current_verdict[i] for i, x in enumerate(current_verdict) if rex88.search(x) != None]
filter1
# 原告引用法條
copyright88 = [filter1[i] for i, x in enumerate(filter1) if re.search(r'(原告|被告|被上訴人|上訴人|被害人|公司)', x) != None]
copyright88 = [copyright88[i] for i, x in enumerate(copyright88) if not bool(re.search(r'(二造|爭點|抗辯|\?|\？|定有明文)', x)) == True]
plaintiff = [copyright88[i] for i, x in enumerate(copyright88) if bool(re.search('請求(原告|被告|被害人|上訴人|被上訴人)?(等連帶負損害賠償責任)?', x)) == True]
# 法官判決法條
court = [copyright88[i] for i, x in enumerate(copyright88) if bool(re.search('(為有理由|即有理由|洵屬正當|即非不合|核屬正當|應予准許|核屬合法適當|核屬有據|於法有據|即無不合)(，)?(應予准許)?', x)) == True]
court_ = [x for x in court if x in plaintiff]
plaintiff_ = [x for x in plaintiff if x not in court_]
plaintiff_classify = list(set([case_detection(x) for x in plaintiff_]))
court_classify = list(set([case_detection(x) for x in court_]))
# 填入dataframe
fill_dataframe(plaintiff_classify, '原告引用法條_Auto', filename)
fill_dataframe(court_classify, '法官判決法條_Auto', filename)
# 判斷分類對錯
if label_df.loc[filename, '駁回_Auto'] != label_df.loc[filename, '駁回_Manual']:
label_df.loc[filename, '駁回_Diff'] = 1
else:
label_df.loc[filename, '駁回_Diff'] = 0
if label_df.loc[filename, '原告引用法條_Auto'] != label_df.loc[filename, '原告引用法條_Manual']:
label_df.loc[filename, '原告引用法條_Diff'] = 1
else:
label_df.loc[filename, '原告引用法條_Diff'] = 0
if label_df.loc[filename, '法官判決法條_Auto'] != label_df.loc[filename, '法官判決法條_Manual']:
label_df.loc[filename, '法官判決法條_Diff'] = 1
else:
label_df.loc[filename, '法官判決法條_Diff'] = 0
def Copyright_88_Classifier(filename_lst):
# 將挑選判決進行分類並填入表格
for filename in filename_lst:
Classify(filename)
# 結果分析
dismiss_wrong = label_df.loc[label_df['駁回_Diff'] == 1,:]
both_wrong = label_df.loc[label_df.loc[:,['原告引用法條_Diff','法官判決法條_Diff']].sum(axis = 1) == 2,:]
tmp = label_df.loc[label_df['原告引用法條_Diff'] == 1,:]
plaintiff_wrong = tmp.loc[[ind for ind in list(tmp.index) if ind not in list(both_wrong.index)],:]
tmp = label_df.loc[label_df['法官判決法條_Diff'] == 1,:]
court_wrong = tmp.loc[[ind for ind in list(tmp.index) if ind not in list(both_wrong.index)],:]
both_right = label_df.loc[label_df.loc[:,['原告引用法條_Diff','法官判決法條_Diff']].sum(axis = 1) == 0,:]
cases_dct = {'both_wrong':both_wrong,
'plaintiff_wrong':plaintiff_wrong,
'court_wrong': court_wrong,
'both_right': both_right,
'dismiss_wrong': dismiss_wrong}
summary_dict = {'Case':['僅原告引用法條分錯', '僅法官判決法條分錯','皆分錯','皆分對','總和'],
'amount':None,'proportion':None}
summary_df = pd.DataFrame.from_dict(summary_dict)
summary_df = summary_df.set_index(['Case'])
summary_df.iloc[0,0:2] = [len(plaintiff_wrong), len(plaintiff_wrong)/len(label_df)]
summary_df.iloc[1,0:2] = [len(court_wrong), len(court_wrong)/len(label_df)]
summary_df.iloc[2,0:2] = [len(both_wrong), len(both_wrong)/len(label_df)]
summary_df.iloc[3,0:2] = [len(both_right), len(both_right)/len(label_df)]
summary_df.iloc[4,0:2] = summary_df.iloc[0:4,].sum(axis = 0)
summary_df
return label_df, summary_df, cases_dct
label_df, summary_df, cases_dct = Copyright_88_Classifier(manual_filename)
| [
"[email protected]"
] | |
4d4174c05cd9b20b5c5012cc3f5ba7fd0900d63d | 669660bee94af2f9312ca84fb5ea956e35e551ac | /quickstart/views.py | f7fe0ca0347e4d744beeb57d36c23e64e4c4a31c | [] | no_license | jaymodi-ntech/demo3 | d8bc9746788927fc7dc5cd72352c85f552b32ce7 | f930bfe2b087a0a446ed9deeddf8205d895a18bd | refs/heads/master | 2021-01-02T09:34:39.014444 | 2014-10-06T11:13:34 | 2014-10-06T11:13:34 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 591 | py | __author__ = 'mj'
from django.shortcuts import render
# Create your views here.
from django.contrib.auth.models import User, Group
from rest_framework import viewsets
from quickstart.serializers import *
class UserViewSet(viewsets.ModelViewSet):
"""
API endpoint that allows users to be viewed or edited.
"""
queryset = User.objects.all()
serializer_class = UserSerializer
class GroupViewSet(viewsets.ModelViewSet):
"""
API endpoint that allows groups to be viewed or edited.
"""
queryset = Group.objects.all()
serializer_class = GroupSerializer | [
"ntech@n-tech.(none)"
] | ntech@n-tech.(none) |
2282495d9f9f1ac8079c3e9d8dbe84bc6f9a1e8d | edbf80fb7ae7f411aaa1bdc58c1c5ed96c7aeec5 | /app/gateways/OwlveyGateway.py | cd8c37ae458588cbdbea35a4e823f9290733298f | [
"Apache-2.0"
] | permissive | owlvey/power_tools | 3eff4339855e6731b600915732f2a0a011688de8 | cec83fb13a21ebd0592f8d203cc3705101c109b8 | refs/heads/master | 2022-07-18T07:55:17.259885 | 2020-05-15T14:21:20 | 2020-05-15T14:21:20 | 263,683,971 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 8,664 | py | import datetime
import requests
from app.components.ConfigurationComponent import ConfigurationComponent
class OwlveyGateway:
def __init__(self, configuration_component: ConfigurationComponent):
self.host = configuration_component.owlvey_url
self.identity = configuration_component.owlvey_identity
self.token = None
self.token_on = None
self.client_id = configuration_component.owlvey_client
self.client_secret = configuration_component.owlvey_secret
@staticmethod
def __validate_status_code(response):
if response.status_code > 299:
raise ValueError(response.text)
def generate_token(self):
payload = {
"grant_type": "client_credentials",
"scope": "api",
"client_id": self.client_id,
"client_secret": self.client_secret
}
response = requests.post(self.identity + "/connect/token",
data=payload)
OwlveyGateway.__validate_status_code(response)
self.token_on = datetime.datetime.now()
self.token = response.json()
def __build_authorization_header(self):
if self.token:
expires_in = self.token["expires_in"]
if (self.token_on + datetime.timedelta(seconds=expires_in + 30)) > datetime.datetime.now():
self.generate_token()
else:
self.generate_token()
return {
"Authorization": "Bearer " + self.token["access_token"]
}
def __internal_get(self, url):
response = requests.get(url,
headers=self.__build_authorization_header(),
verify=False)
OwlveyGateway.__validate_status_code(response)
return response.json()
def __internal_put(self, url, payload):
response = requests.put(url, json=payload,
headers=self.__build_authorization_header(),
verify=False)
OwlveyGateway.__validate_status_code(response)
def __internal_delete(self, url, payload):
response = requests.delete(url, json=payload,
headers=self.__build_authorization_header(),
verify=False)
OwlveyGateway.__validate_status_code(response)
def __internal_post(self, url, payload):
response = requests.post(url, json=payload,
headers=self.__build_authorization_header(),
verify=False)
OwlveyGateway.__validate_status_code(response)
return response.json()
def get_customers(self):
return self.__internal_get(self.host + "/customers")
def get_customer(self, name):
customers = self.get_customers()
for cus in customers:
if cus['name'] == name:
return cus
return None
def get_products(self, organization_id):
return self.__internal_get(self.host + '/products?customerId={}'.format(organization_id))
def get_product(self, organization_id, name):
products = self.get_products(organization_id)
for product in products:
if product['name'] == name:
return product
return None
def get_syncs(self, product_id):
return self.__internal_get(self.host + "/products/{}/sync".format(product_id))
def post_sync(self, product_id, name):
return self.__internal_post(self.host + "/products/{}/sync/{}".format(product_id, name), {})
def put_last_anchor(self, product_id, name, target):
self.__internal_put(self.host + "/products/{}/sync/{}".format(product_id, name),
{"target": target.isoformat()})
def get_features(self, product_id):
return self.__internal_get(self.host + "/features?productId={}".format(product_id))
def get_feature_detail(self, feature_id):
return self.__internal_get(self.host + "/features/{}".format(feature_id))
def create_customer(self, name):
return self.__internal_post(self.host + "/customers", {"name": name})
def create_product(self, customer_id, name):
return self.__internal_post(self.host + "/products", {"customerId": customer_id, "name": name})
def create_service(self, product_id, name, slo):
service = self.__internal_post(self.host + "/services", {"productId": product_id, "name": name})
service_id = service["id"]
service["slo"] = slo
self.__internal_put(self.host + "/services/" + str(service_id), service)
return service
def assign_indicator(self, feature_id, source_id):
return self.__internal_put(self.host + "/features/{}/indicators/{}".format(feature_id, source_id), {})
def un_assign_indicator(self, feature_id, source_id):
return self.__internal_delete(self.host + "/features/{}/indicators/{}".format(feature_id, source_id), {})
def create_feature(self, product_id, name):
return self.__internal_post(self.host + "/features", {"productId": product_id, "name": name})
def create_incident(self, product_id, key, title, resolution_on: datetime, ttd, tte, ttf, url):
response = requests.post(self.host + "/incidents", json={"productId": product_id,
"key": key,
"title": title
},
verify=False)
OwlveyGateway.__validate_status_code(response)
incident_id = response.json()["id"]
response = requests.put(self.host + "/incidents/{}".format(incident_id),
json={"title": title, "ttd": ttd, "tte": tte, "ttf": ttf, "url": url,
"affected": 1,
"end": resolution_on.isoformat()},
verify=False)
OwlveyGateway.__validate_status_code(response)
return response.json()
def assign_incident_feature(self, incident_id, feature_id):
response = requests.put(self.host + "/incidents/{}/features/{}".format(incident_id, feature_id),
verify=False)
OwlveyGateway.__validate_status_code(response)
def get_sources(self, product_id):
return self.__internal_get(self.host + "/sources?productId={}".format(product_id))
def create_source(self, product_id, name, kind, group,
good_definition: str = "", total_definition: str = ""):
result = self.__internal_post(self.host + "/sources",
{
"productId": product_id,
"name": name,
"kind": kind,
"group": group
})
result["goodDefinition"] = good_definition
result["totalDefinition"] = total_definition
self.__internal_put(self.host + "/sources/{}".format(result["id"]), result)
return result
def create_sli(self, feature_id, source_id):
self.__internal_put(self.host + "/features/{}/indicators/{}".format(feature_id, source_id), {})
def search_feature(self, product_id, name):
return self.__internal_get(self.host + "/features/search?productId={}&name={}".format(product_id, name))
def create_source_item(self, source_id, start, total, good):
return self.__internal_post(self.host + "/sourceItems",
{
"sourceId": source_id,
"start": start.isoformat(),
"end": start.isoformat(),
"total": int(total),
"good": int(good)
})
def create_source_item_proportion(self, source_id, start, percent):
result = self.__internal_post(self.host + "/sourceItems/proportion",
{
"sourceId": source_id,
"start": start.isoformat(),
"end": start.isoformat(),
"proportion": percent,
})
return result
| [
"[email protected]"
] | |
270b750136f37b35a8ec6301de7546fe80dc514e | 8186514b510a801863229e3f9711c0c657e727e5 | /assembly/qtable/qlist_q.py | c4d46f59661410f1d3c06c6df3d6c2b23370a997 | [] | no_license | masknugget/mypyqt | 274b2cbbf66c04927453815248f9c1bc5e65ca17 | b86a49e4b8c7c8c3d8546ce1b49f8f3bb6332307 | refs/heads/main | 2023-08-17T13:30:11.451066 | 2021-09-27T14:14:54 | 2021-09-27T14:14:54 | 355,904,935 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,241 | py | # 自定义控件--实现了一个带全选功能的复选框
import sys
from PyQt5.QtWidgets import QApplication, QListWidget, QCheckBox, QListWidgetItem
from PyQt5.QtCore import Qt
class FilteredList(QListWidget):
# 继承自列表控件
def __init__(self, textList, parent=None):
super().__init__(parent)
self.selectAll_ch = QCheckBox("全选(selectAll)")
self.selectAll_ch.setCheckState(Qt.Checked)
self.selectAll_ch.stateChanged[int].connect(self.on_selectAll) #
item = QListWidgetItem(self)
self.setItemWidget(item, self.selectAll_ch) # 列表控件的项设为 QCheckBox
self.dict = dict()
self.boxes = set()
for index, text in enumerate(textList):
ch = QCheckBox(text)
ch.setCheckState(Qt.Unchecked)
ch.stateChanged[int].connect(self.on_stateChanged)
# item.setCheckState(Qt.Unchecked)#
item = QListWidgetItem(self)
self.setItemWidget(item, ch)
self.boxes.add(ch)
self.dict[index] = ch
def on_selectAll(self, state):
if state == 2:
for ch in self.boxes:
ch.setCheckState(2)
if state == 0:
for ch in self.boxes:
ch.setCheckState(0)
def on_stateChanged(self, state):
ch = self.sender()
if state:
if len([ch for ch in self.boxes if ch.checkState()]) == self.count() - 1:
# 0 不选中， 1 部分选中，2 全选中 #Qt.Unchecked #Qt.PartiallyChecked #Qt.Checked
self.selectAll_ch.setCheckState(2)
else:
self.selectAll_ch.setCheckState(1)
else:
if len([k for k in self.boxes if k.checkState()]):
self.selectAll_ch.setCheckState(1)
else:
self.selectAll_ch.setCheckState(0)
def keyPressEvent(self, event):
# Ctrl+A 全选
if event.modifiers() & Qt.ControlModifier and event.key() == Qt.Key_A:
self.selectAll_ch.setCheckState(2)
if __name__ == '__main__':
app = QApplication(sys.argv)
myList = FilteredList(textList=["a", "b", "c", "d"])
myList.show()
sys.exit(app.exec_()) | [
"[email protected]"
] | |
6ff2f7bbff706bd61e5fbd3eab9118c72980e899 | a7723fa70d4a7701b038b37d1913d917fd2e8e8f | /codeif/app/dashboard/writer/post/apps.py | f64003df9a3ac78b305400cd0e393cb9a0f03ee8 | [] | no_license | Nym-Git/codeif-internship | e3f8656b1eb0a1baf095f80d262eb172cf88a027 | 5af8597cadf02b670dd593a804dcc0e0b3f6bb53 | refs/heads/master | 2023-07-16T03:03:55.343589 | 2021-08-26T14:11:48 | 2021-08-26T14:11:48 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 104 | py | from django.apps import AppConfig
class PostConfig(AppConfig):
name = 'app.dashboard.writer.post'
| [
"[email protected]"
] | |
12655a75caf61802783410d883ae5ec5680cefe5 | b77cc1448ae2c68589c5ee24e1a0b1e53499e606 | /asset/migrations/0005_auto_20171026_1532.py | eb4e2ea65956f0a359a6c7516eb7dbb444b94e2a | [] | no_license | PregTech-c/Hrp_system | a5514cf6b4c778bf7cc58e8a6e8120ac7048a0a7 | 11d8dd3221497c536dd7df9028b9991632055b21 | refs/heads/master | 2022-10-09T07:54:49.538270 | 2018-08-21T11:12:04 | 2018-08-21T11:12:04 | 145,424,954 | 1 | 1 | null | 2022-10-01T09:48:53 | 2018-08-20T13:58:31 | JavaScript | UTF-8 | Python | false | false | 664 | py | # -*- coding: utf-8 -*-
# Generated by Django 1.10 on 2017-10-26 12:32
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('asset', '0004_auto_20171022_1404'),
]
operations = [
migrations.AddField(
model_name='asset',
name='model',
field=models.CharField(default='test', max_length=32),
preserve_default=False,
),
migrations.AlterField(
model_name='asset',
name='description',
field=models.CharField(max_length=256, null=True),
),
]
| [
"[email protected]"
] | |
069a57e3df39d947bfd19a9af8fff7b242cce5d6 | 04b1faa6394131c8119700f731894d607a88a100 | /loja/models.py | 7720d2797da7e27eb8189382485d3582eed88e0c | [] | no_license | tamilly/loja_pe | c9ae340cbbbb5df86fb27dca89e6cd8f6a2fff10 | 453becffc74a853a616ee005ad00fff9ecc56d41 | refs/heads/master | 2022-11-06T23:05:29.740496 | 2020-07-06T23:05:08 | 2020-07-06T23:05:08 | 277,662,440 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,255 | py | #Tamilly's code / 2020-01-07
from django.db import models
from django.conf import settings
from django.utils import timezone
class User(models.Model):
cpf = models.BigIntegerField(primary_key=True)
name = models.CharField(max_length=100)
email = models.EmailField(max_length=100)
birth_date = models.DateField(auto_now=False, auto_now_add=False)
password = models.CharField(max_length=20)
admin = models.BooleanField()
def add_user(self):
self.save()
def __str__(self):
return self.name
class Product(models.Model): # Model definition
# Attributes type definition
user = models.ForeignKey(User, on_delete=models.CASCADE)
bar_code = models.IntegerField()
name = models.CharField(max_length=100)
description = models.TextField()
created_date = models.DateTimeField(default=timezone.now)
price = models.DecimalField(max_digits=10, decimal_places=3)
categories = models.TextChoices('Categoria', 'BELEZA LIMPEZA ALIMENTO CASA OUTROS')
category = models.CharField(blank=True, choices=categories.choices, max_length=10)
validity = models.DateField(auto_now=False, auto_now_add=False)
# Methods definition
def add_product(self):
self.created_date = timezone.now()
self.save()
def __str__(self):
return self.name
| [
"[email protected]"
] | |
ff81fb06f2512900c9797697d5792d8253d5a9af | a5631fae399c750eb4f8de58bcc16da0edb2e33d | /lessons/lesson14_RegressionDiagnostics_Imputations/Diagnostics_Walkthrough.py | a883a00d9e82960b5c8d4a34817556a3dbeee4e7 | [] | no_license | robertdavidwest/GADS11-NYC-Summer2014 | 1fa50b577b1f6c62c43522d0823bc6fa50dcace2 | d9cbdcef0f9f94a01597b04b9a24d867b127ce30 | refs/heads/master | 2020-12-24T23:28:17.395587 | 2014-08-20T01:46:09 | 2014-08-20T01:46:09 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,717 | py | #<<<<<<< HEAD
import csv
import numpy as np
import pandas as pd
from dateutil import parser
import pylab as pl
import statsmodels.api as sm
import matplotlib.pyplot as plt
import random
from sklearn.preprocessing import scale
from numpy import inf
import scipy.stats as stats
import pylab
#=======
### IMPORT DATA ###
batting_salary = pd.read_csv("/Users/patrickmcnamara/Documents/GA_DataScience/Teaching/Summer14/GADS11-NYC-Summer2014/projects/Project2/baseball.csv")
pitching = pd.read_csv("/Users/patrickmcnamara/Documents/GA_DataScience/Teaching/Summer14/GADS11-NYC-Summer2014/projects/Project2/pitching.csv")
# DROP UNWANTED VARIABLES #
batting_salary = batting_salary.drop(['lahmanID', 'managerID', 'birthYear', 'birthMonth', 'birthDay',
'birthCountry', 'birthState', 'birthCity', 'deathYear', 'deathMonth', 'deathDay', 'deathCountry',
'deathState', 'deathCity', 'nameFirst','nameLast', 'nameNote', 'nameGiven', 'nameNick','bats',
'throws', 'debut', 'finalGame', 'college','lahman40ID', 'lahman45ID', 'retroID', 'holtzID',
'bbrefID', 'deathDate', 'birthDate','teamID', 'lgID', 'stint','G_batting','X2B', 'X3B',
'CS', 'SO', 'IBB', 'HBP', 'SH', 'SF', 'GIDP', 'G_old', 'hofID'], axis =1)
# KEEP VARIABLES IN PITCHING DATA THAT AREN'T IN BATTING DATA #
keep_cols = list(set(pitching.columns)-set(batting_salary.columns))
keep_cols = keep_cols + ['playerID','yearID']
pitching = pitching[keep_cols]
pitching = pitching.drop(['GIDP','SH','SF'], axis=1)
pitching = pitching[['ERA','playerID','yearID']]
# MERGE DATASETS #
data = pd.merge(batting_salary, pitching, on=['playerID','yearID'], how='outer')
data = data.drop(['playerID','yearID'], axis=1)
# DROP PITCHERS FROM DATASET #
index = data['ERA'].index[data['ERA'].apply(np.isnan)]
slimdata = data.loc[index]
slimdata = slimdata.drop(['ERA'], axis=1)
### CHECKING VARIABLE RELATIONSHIPS ###
# SHRINKING THE DATA TO MAKE VISUALIZATIONS EASIER #
slimdata['random'] = np.random.randn(len(slimdata))
slimdata = slimdata[slimdata.random > 1]
del slimdata['random']
# COLLINEARITY HISTOGRAM #
pd.tools.plotting.scatter_matrix(slimdata, alpha=0.2, diagonal='hist')
plt.show()
# LOG TRANSFORMATIONS WHERE NECESSARY #
slimdata.SB = np.log(slimdata.SB)
slimdata.HR = np.log(slimdata.HR)
slimdata.BB = np.log(slimdata.BB)
slimdata.RBI = np.log(slimdata.RBI)
slimdata.salary = np.log(slimdata.salary)
# REPLACE INF VALUES WITH NAN #
slimdata = slimdata.replace([inf, -inf], np.nan)
# DROP NAN #
slimdata = slimdata.dropna()
### PLOTTING SCATTERPLOT MATRIX FOR COLLINEARITY ###
# HISTOGRAM #
pd.tools.plotting.scatter_matrix(slimdata, alpha=0.2, diagonal='hist')
plt.show()
# KERNEL DENSITY #
pd.tools.plotting.scatter_matrix(slimdata, alpha=0.2, diagonal='kde')
plt.show()
### RUNNING REGRESSION MODEL ###
# CREATING INTERCEPT #
slimdata['intercept'] = 1
# DEFINING IVs & DVs #
X = slimdata.drop(['salary', 'intercept'], axis = 1)
y = slimdata['salary']
# RUNNING REGRESSION #
model = sm.OLS(y, X)
results = model.fit()
results.summary()
### NORMALIZATION ###
# BOX PLOT FOR OUTLIERS #
slimdata.boxplot()
plt.show()
# SCALING # Mean-center then divide by std dev
data_norm = pd.DataFrame(scale(slimdata), index=slimdata.index, columns=slimdata.columns)
data_norm.boxplot()
plt.show()
### RUNNING REGRESSION MODEL AGAIN ###
data_norm['intercept'] = 1
X = data_norm.drop(['salary'], axis = 1)
y = data_norm['salary']
model2 = sm.OLS(y, X)
results2 = model2.fit()
results2.summary()
### INFLUENCE PLOT FOR SINGLE OBSERVATIONS ###
fig, ax = plt.subplots(figsize=(10,10))
fig = sm.graphics.influence_plot(results2, ax=ax, criterion="cooks")
plt.show()
# INFLUENCE TABLE #
influence = results2.get_influence()
influence.summary_frame()['cooks_d'].order()
# THE EFFECT OF RESHAPING/DROPPING VARIABLES #
res_dropped = results.params / results2.params * 100 - 100
'''Create new regressions and see what these look like
after dropping extremely influential variables'''
### RESIDUALS PLOT ###
plt.scatter(results2.norm_resid(), results2.fittedvalues)
plt.xlabel('Fitted Values')
plt.ylabel('Normalized residuals')
plt.show()
'''Here we're looking for something resembling a shotgun blast.
Random points with no identifiable structure'''
### LOOKING AT INDIVIDUAL VARIABLES ###
# PARTIAL REGRESSION PLOTS #
fig = plt.figure(figsize=(10,10))
fig = sm.graphics.plot_partregress_grid(results2, fig=fig)
plt.show()
'''Here we want to see a linear relationship'''
fig = plt.figure(figsize=(10,10))
fig = sm.graphics.plot_regress_exog(results, 'RBI', fig=fig)
plt.show()
'''2x2 plot containing DV and fitted values with CIs vs. selected IV,
residuals vs. the IV, a partial regression plot, and a CCPR plot.
Don't worry about the CCPR plot'''
| [
"[email protected]"
] | |
2906ecce75b2ac95aa33a8672781a51b33e0c125 | 93e42a3c0f546694992844b7f24668538fcfb01e | /controller.py | e36a7d116f3c83778b2186b56a18296dcafafbf7 | [] | no_license | zongjunhao/tencent_relationship_map | a89def2fdf151e12cd2b6d599451a37ac611dab8 | 61d2c808f1e3f4ea014be5192cec56ee386780c2 | refs/heads/master | 2023-08-23T20:10:22.132142 | 2021-10-24T10:17:08 | 2021-10-24T10:17:08 | 416,812,111 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,396 | py | from flask import Flask, redirect, url_for, request
from flask_cors import CORS
import util
app = Flask(__name__, static_folder="visualization", static_url_path="")
CORS(app, supports_credentials=True)
@app.route('/get_init_data')
def get_init_data():
return util.generate_graph_data()
@app.route('/get_raw_data')
def get_raw_data():
return util.generate_raw_data()
@app.route('/get_node_distribution')
def get_node_distribution():
G = util.load_raw_relation()
degree_distribution = util.get_degree_distribution(G)
return degree_distribution
@app.route('/get_degree_of_node')
def get_degree_of_node():
node_id = request.args.get("node_id")
G = util.load_raw_relation()
return str(util.get_degree_of_node(G, int(node_id)))
@app.route('/get_clustering_of_node')
def get_clustering_of_node():
node_id = request.args.get("node_id")
G = util.load_raw_relation()
return str(util.get_clustering_of_node(G, int(node_id)))
@app.route('/get_core_of_node')
def get_core_of_node():
node_id = request.args.get("node_id")
G = util.load_raw_relation()
return str(util.get_core_of_node(G, int(node_id)))
@app.route('/attack_graph', methods=['POST'])
def attack_graph():
node_id = request.form['node_id']
graph = request.form['graph']
return util.attack_graph(graph, node_id)
if __name__ == '__main__':
app.run(debug=True)
| [
"[email protected]"
] | |
d7a80960660ed56f591c130f94a6772a5d9f6e60 | c30450b7794e8ae888a5916e20c74c17d014c6fa | /parser/summary.py | c8a0a835fa2b440f48949edd4f73d0a609967c61 | [] | no_license | zacateras/yansp | cc9cfc49c1ee5e1558a5a8bddb6dd2f523b3a508 | 20e094047364a5cfcb0f5a293fbd979f14411023 | refs/heads/master | 2020-04-22T18:11:53.363848 | 2019-05-12T21:33:44 | 2019-05-12T21:33:44 | 170,569,331 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,215 | py | from utils.model import count_variables
def summary_for_parser(parser):
return {
'variables_all': count_variables(parser.variables),
'variables_all_trainable': count_variables(parser.trainable_variables),
'variables_word': count_variables(parser.word_model.variables) if hasattr(parser, 'word_model') else 0,
'variables_word_trainable': count_variables(parser.word_model.trainable_variables) if hasattr(parser, 'word_model') else 0,
'variables_char': count_variables(parser.char_model.variables) if hasattr(parser, 'char_model') else 0,
'variables_char_trainable': count_variables(parser.char_model.trainable_variables) if hasattr(parser, 'char_model') else 0,
'variables_core': count_variables(parser.core_model.variables) if hasattr(parser, 'core_model') else 0,
'variables_core_trainable': count_variables(parser.core_model.trainable_variables) if hasattr(parser, 'core_model') else 0,
'variables_lemma': count_variables(parser.lemma_model.variables) if hasattr(parser, 'lemma_model') else 0,
'variables_lemma_trainable': count_variables(parser.lemma_model.trainable_variables) if hasattr(parser, 'lemma_model') else 0,
'variables_upos': count_variables(parser.upos_model.variables) if hasattr(parser, 'upos_model') else 0,
'variables_upos_trainable': count_variables(parser.upos_model.trainable_variables) if hasattr(parser, 'upos_model') else 0,
'variables_feats': count_variables(parser.feats_model.variables) if hasattr(parser, 'feats_model') else 0,
'variables_feats_trainable': count_variables(parser.feats_model.trainable_variables) if hasattr(parser, 'feats_model') else 0,
'variables_head': count_variables(parser.head_model.variables) if hasattr(parser, 'head_model') else 0,
'variables_head_trainable': count_variables(parser.head_model.trainable_variables) if hasattr(parser, 'head_model') else 0,
'variables_deprel': count_variables(parser.deprel_model.variables) if hasattr(parser, 'deprel_model') else 0,
'variables_deprel_trainable': count_variables(parser.deprel_model.trainable_variables) if hasattr(parser, 'deprel_model') else 0,
} | [
"[email protected]"
] | |
33282c89da89f060278ed17e50013ffdb1f88707 | 455c1cec4101254a0b7f50349e915411033a0af1 | /supervised_learning/0x00-binary_classification/9-neural_network.py | 5f65dc0fea7fe410b59fbce3194f1ddcd97e815b | [] | no_license | Daransoto/holbertonschool-machine_learning | 30c9f2753463d57cac87f245b77c8d6655351e75 | 1e7cd1589e6e4896ee48a24b9ca85595e16e929d | refs/heads/master | 2021-03-10T14:32:09.419389 | 2020-10-23T19:47:31 | 2020-10-23T19:47:31 | 246,461,514 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 1,290 | py | #!/usr/bin/env python3
""" Creates a neural network. """
import numpy as np
class NeuralNetwork:
""" Neural network class. """
def __init__(self, nx, nodes):
""" Initializer for the neural network. """
if type(nx) != int:
raise TypeError('nx must be an integer')
if nx < 1:
raise ValueError('nx must be a positive integer')
if type(nodes) != int:
raise TypeError('nodes must be an integer')
if nodes < 1:
raise ValueError('nodes must be a positive integer')
self.__W1 = np.random.randn(nodes, nx)
self.__b1 = np.zeros((nodes, 1))
self.__A1 = 0
self.__W2 = np.random.randn(1, nodes)
self.__b2 = 0
self.__A2 = 0
@property
def W1(self):
""" Getter for W1. """
return self.__W1
@property
def b1(self):
""" Getter for b1. """
return self.__b1
@property
def A1(self):
""" Getter for A1. """
return self.__A1
@property
def W2(self):
""" Getter for W2. """
return self.__W2
@property
def b2(self):
""" Getter for b2. """
return self.__b2
@property
def A2(self):
""" Getter for A2. """
return self.__A2
| [
"[email protected]"
] | |
e46294ff8a6718f3fb4b012273d0b1ce052e33ed | ca5334081b6fc6298becc0aac4b6ef5872b484e2 | /comments/validators.py | 079e918c70c9b1ce25fbb81d90f9340ac85afa63 | [] | no_license | tachiefab/codewithtm | 1b575f9884b19124303419fb5c5029e4ab7b3306 | 42ea8d761103a695c4428a5a1204a176cef2e3b5 | refs/heads/master | 2023-03-15T17:28:45.582101 | 2021-03-08T04:41:31 | 2021-03-08T04:41:31 | 284,474,285 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 197 | py | from django.core.exceptions import ValidationError
def validate_content(value):
content = value
if content == "":
raise ValidationError("Content cannot be blank")
return value
| [
"[email protected]"
] | |
82bf4f9dd14a53dadeab63ace0b26d76c4989687 | 866d527d9264765dc2ada2fcd523163e9d686061 | /practices/baby_shark.py | c01dc9e39c3901d132766be6c7f50e4862e58490 | [
"MIT"
] | permissive | kimjiwook0129/Coding-Interivew-Cheatsheet | 910d245b83039d59302df71ac5776425ab1b92c2 | 574e6acecdb617b9c3cef7ec3b154ab183d8b99a | refs/heads/main | 2023-08-21T03:57:43.328811 | 2021-10-02T08:59:27 | 2021-10-02T08:59:27 | 371,915,448 | 3 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,835 | py | # https://www.acmicpc.net/problem/16236
from collections import deque
def bfs(table, curRow, curCol, N, sharkSize):
visited = [[False] * N for _ in range(N)]
q = deque([(0, curRow, curCol)])
dx, dy = [-1, 0, 0, 1], [0, -1, 1, 0]
arrayOfPossibilities = []
while q:
dis, row, col = q.popleft()
visited[row][col] = True
if len(arrayOfPossibilities) > 0 and dis > arrayOfPossibilities[0][2]:
break
if table[row][col] > 0 and table[row][col] < sharkSize:
arrayOfPossibilities.append((row, col, dis))
for i in range(4):
nx = row + dx[i]
ny = col + dy[i]
if nx >= 0 and nx < N and ny >= 0 and ny < N:
if not visited[nx][ny]:
if table[nx][ny] <= sharkSize:
q.append((dis + 1, nx, ny))
else:
visited[nx][ny] = True
if len(arrayOfPossibilities) > 0:
arrayOfPossibilities.sort()
thisOne = arrayOfPossibilities[0]
return ((thisOne[0], thisOne[1]), thisOne[2])
return ((1, 1), -1)
if __name__ == "__main__":
N = int(input())
table = []
curRow, curCol = 0, 0
for i in range(N):
data = list(map(int, input().split()))
if 9 in data:
j = data.index(9)
curRow, curCol = i, j
table.append(data)
sharkSize, sharkFeed = 2, 0
time = 0
while True:
nextCoord, distance = bfs(table, curRow, curCol, N, sharkSize)
if distance == -1:
break
time += distance
table[curRow][curCol] = 0
curRow, curCol = nextCoord
table[curRow][curCol] = 9
sharkFeed += 1
if sharkFeed == sharkSize:
sharkSize += 1
sharkFeed = 0
print(time)
| [
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] | |
8982cf56ab7561232b24afc577a5d47a1a120f37 | 57d9d4e881ea308db01938c39afc20091d87a1ab | /src/web/views.py | f96b8cb43a75b61fe5d479b89a92e0b96f0a90c3 | [] | no_license | logworthy/parku | 14eea4351c366d5b0a03e56fa385fb8df0d71b90 | e2fc9323d42abc4e616ac717ab4e7d009c1abe87 | refs/heads/master | 2020-04-06T06:54:25.282258 | 2014-08-30T03:56:39 | 2014-08-30T03:56:39 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 102 | py | from django.shortcuts import render
def index(request):
return render(request, "web/index.html") | [
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] | |
c0fd1993ef34225c74db2d83b77f92209b7547fb | 08355c36cafc4ad86a5e85a6a70204796a6722f6 | /api/entity/image.py | 219bd7cfa852a70ffeb8bf1b98f43b22c530210b | [] | no_license | vankcdhv/CosinSimilarity | 0a3d114be3cfc8dec3e80ec88dbbea7d0f4bd690 | 70cb59329e55eecc0c57e9e9dbcca04e39ff3ea5 | refs/heads/main | 2023-04-19T22:08:03.653394 | 2021-05-11T02:07:48 | 2021-05-11T02:07:48 | 366,228,611 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 703 | py | from multipledispatch import dispatch
class Image:
@dispatch()
def __init__(self):
self.__id = 0
self.__postID = 0
self.__url = ''
@dispatch(object)
def __init__(self, row):
self.__id = row[0]
self.__postID = row[1]
self.__url = row[2]
@property
def id(self):
return self.__id
@id.setter
def id(self, value):
self.__id = value
@property
def postID(self):
return self.__postID
@postID.setter
def postID(self, value):
self.__postID = value
@property
def url(self):
return self.__url
@url.setter
def url(self, value):
self.__url = value
| [
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] | |
06f952c695c3533ca0dd029f3e93895af5b02c59 | 5c8139f1e57e06c7eaf603bd8fe74d9f22620513 | /PartB/py删除链表的倒数第n个节点的位置的值2.py | ab9093a8ca2755b9b1f62111641d210996e07d4a | [] | no_license | madeibao/PythonAlgorithm | c8a11d298617d1abb12a72461665583c6a44f9d2 | b4c8a75e724a674812b8a38c0202485776445d89 | refs/heads/master | 2023-04-03T07:18:49.842063 | 2021-04-11T12:02:40 | 2021-04-11T12:02:40 | 325,269,130 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 915 | py |
# 把一个链表的倒数的第n个节点来进行删除。
class ListNode(object):
def __init__(self, x):
self.val = x
self.next = None
class Solution(object):
def remove(self, head, n):
dummy = ListNode(-1)
dummy.next = head
slow = dummy
fast = dummy
for i in range(n):
fast = fast.next
while fast and fast.next:
fast = fast.next
slow = slow.next
slow.next = slow.next.next
return dummy.next
if __name__ == "__main__":
s = Solution()
n1 = ListNode(1)
n2 = ListNode(2)
n3 = ListNode(3)
n4 = ListNode(4)
n5 = ListNode(5)
n6 = ListNode(6)
n1.next = n2
n2.next = n3
n3.next = n4
n4.next = n5
n5.next = n6
n6.next = None
k = 2
res = s.remove(n1, k)
while res:
print(res.val, end="->")
res = res.next
| [
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] | |
47e8f9432798989895c7cbfef00d209e0fdc4bb3 | 45c870a3edf37781efd6059a3d879aedf9da7f7f | /custom_resize_drag_toolbar_pyqt5/example.py | cd9c9f2dad5a08e344715d5aaa95e6dcedafa101 | [] | no_license | saladeen/custom_resize_drag_toolbar_pyqt5 | e6dc8598df6b7d58bf3114bfa348db38c2b1512b | f38aa8b263b08fd0f94ea2e1428e873cdadce80e | refs/heads/main | 2023-08-11T04:44:53.349929 | 2021-10-01T19:10:20 | 2021-10-01T19:10:20 | 412,588,371 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 618 | py | from PyQt5.QtWidgets import QApplication, QWidget, QHBoxLayout
from PyQt5.QtCore import Qt
import resizable_qwidget
import toolbar
import sys
class ExampleWindow(resizable_qwidget.TestWindow):
def __init__(self):
super().__init__()
layout = QHBoxLayout()
layout.addWidget(toolbar.CustomToolbar(self, "Example"))
layout.setAlignment(Qt.AlignTop)
self.setLayout(layout)
self.move(300, 300)
self.resize(300, 300)
if __name__ == "__main__":
app = QApplication(sys.argv)
mw = ExampleWindow()
mw.show()
sys.exit(app.exec_()) | [
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] | |
4611dd4f883110ac156a9299f169d60ae6b42feb | 12a47a2aca78086c76dc4e669abfe00fa012f6c5 | /day9.py | f51e18f0fadb0285ed3c50cf564b13ddd53747dc | [] | no_license | susieir/advent_of_code_2020 | 67e155ffff57b662b3edde0235da6290cfb2c331 | f1881dad8c7d790654357c2cdb5a1830af560c12 | refs/heads/main | 2023-02-20T05:18:33.991166 | 2021-01-21T15:56:05 | 2021-01-21T15:56:05 | 330,618,452 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,480 | py | """ Advent of code puzzle - Day 9"""
def create_input_list(filename):
""" Reads the input data and stores as a list"""
with open(filename, 'r') as fp:
return [int(x) for x in fp.read().splitlines()]
def inspect_check_number(filename, step=5, inc=0):
""" Function that inspects whether the check number is valid by checking against a list of valid numbers"""
# Set up the list
cypher = create_input_list(filename)
# Find the check number to be inspected
check_number = cypher[step + inc]
# Initialise check_list - stores possible valid check_numbers
check_list = []
# Loop through the previous numbers
for i in cypher[inc : step + inc]:
for j in cypher[inc : step + inc]:
if i != j:
check_list.append(i + j)
# Check if check_number is in check_list
if check_number in check_list:
return (check_number, "ok")
else:
return (check_number, "test failed")
def main(filename, step = 5):
"""Iterates through each item in cypher"""
c = 0 # initialise c
cypher = create_input_list(filename)
for c in range(len(cypher) - step):
if inspect_check_number(filename, step, inc = c)[1] == "test failed":
return inspect_check_number(filename, step, inc = c)
break
#print(inspect_check_number('day9.txt', inc = 9))
if __name__ == '__main__':
print(main('day9.txt', step=25)) | [
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] | |
b0ebd397cc8459a46dd0ef18c330ccdc2c8d2efb | bef4b43dc0a93697dfb7befdf4434994d109d242 | /extract_features.py | 0bb7bcc29969f2399ab42483e98a35287f5e4aac | [] | no_license | karanjsingh/Object-detector | 69d9e5154b9f73028760d6d76da1a0f55038cfea | 9114e95f79e2dd77a3cbbbee92e4432e5c237362 | refs/heads/master | 2020-06-25T22:31:14.941147 | 2020-01-14T23:36:22 | 2020-01-14T23:36:22 | 199,440,746 | 1 | 0 | null | 2019-07-29T11:43:34 | 2019-07-29T11:34:47 | null | UTF-8 | Python | false | false | 3,513 | py | #import necessary packages
from __future__ import print_function
from sklearn.feature_extraction.image import extract_patches_2d
from pyimagesearch.object_detection import helpers
from pyimagesearch.utils import dataset
from pyimagesearch.utils import conf
from pyimagesearch.descriptors import hog
from imutils import paths
from scipy import io
import numpy as np
import argparse
import random
import cv2
import progressbar
# construct an argument parser
ap = argparse.ArgumentParser()
ap.add_argument("-c","--conf",required=True,help="path to configuration file")
args = vars(ap.parse_args())
#load configuration file
conf= conf.Conf(args["conf"])
hog = hog.HOG(orientations=conf["orientations"], pixelsPerCell = tuple(conf["pixels_per_cell"]),
cellsPerBlock=tuple(conf["cells_per_block"]) , normalise = conf["normalize"])
data=[]
labels=[]
#grab the ground truth of in=mages and select a percentage of them for training
trnPaths=list(paths.list_images(conf["image_dataset"]))
trnPaths= random.sample(trnPaths, int(len(trnPaths)*conf["percent_gt_images"]))
print("[info] describing training ROI.........")
# set up the progress bar
widgets = ["Extracting: ", progressbar.Percentage(), " ", progressbar.Bar(), " ", progressbar.ETA()]
pbar = progressbar.ProgressBar(maxval=len(trnPaths), widgets=widgets).start()
#loop over training paths
for (i,trnPath) in enumerate(trnPaths):
#load image cvt it into gray scl , extractthe image ID from the path
image = cv2.imread(trnPath)
image = cv2.cvtColor(image , cv2.COLOR_BGR2GRAY)
imageID = trnPath[trnPath.rfind("_")+1:].replace(".jpg","")
#load the annotation file and extract the bb
p="{}/annotation_{}.mat".format(conf["image_annotations"], imageID)
bb=io.loadmat(p)["box_coord"][0]
roi = helpers.crop_ct101_bb(image,bb,padding=conf["offset"],dstSize=tuple(conf["window_dim"]))
# define the list of ROIs that will be described, based on whether or not the
# horizontal flip of the image should be used
rois = (roi, cv2.flip(roi, 1)) if conf["use_flip"] else (roi,)
#loop over the ROIs
for roi in rois:
#extractfeatures from the ROI and update the list of features and labels
features = hog.describe(roi)
data.append(features)
labels.append(1)
#update the process bar
pbar.update(i)
## grab the disttraction(-ve) image path and reset the process bar
pbar.finish()
dstPaths= list(paths.list_images(conf["image_distractions"]))
pbar = progressbar.ProgressBar(maxval=conf["num_distraction_images"], widgets=widgets).start()
print("[INFO] describing distraction ROIs...")
#Loop over desired number of distraction images
for i in np.arange(0,conf["num_distraction_images"]):
# randomly select a distraction image, load it, convert it to grayscale, and
# then extract random patches from the image
image = cv2.imread(random.choice(dstPaths))
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
patches = extract_patches_2d(image, tuple(conf["window_dim"]),
max_patches=conf["num_distractions_per_image"])
# loop over the patches
for patch in patches:
# extract features from the patch, then update the data and label list
features = hog.describe(patch)
data.append(features)
labels.append(-1)
# update the progress bar
pbar.update(i)
#dump the dataset to file
pbar.finish()
print("[INFO] dumping features and labels to file...")
dataset.dump_dataset(data, labels, conf["features_path"], "features")
| [
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] | |
d41314fca2d3cdd3ddb87acbf55bd346e0642cd2 | 05b598f07c5f58c4278fd7d3e31b2a74f84d7fcb | /SConstruct | 429244eff91806e3da6047183f46ddd3e9f0a1f8 | [] | no_license | jpcummins/sortr | 1e604e1a0b9aecf8ae4456489c7d6e692008b97f | 329f0f1c9a89002088673945f2464740637f5612 | refs/heads/master | 2020-05-16T21:08:18.930490 | 2010-11-22T01:04:38 | 2010-11-22T01:04:38 | 957,342 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 94 | import os
env = Environment(CCFLAGS = '-g -Wall -pedantic')
env.Program('test', Glob('*.c')) | [
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] | ||
3add78b720f640eb549c134985d2b3184558de5d | 151f71970df1e6e3734b1a9f834db51d02bdf2db | /tools/validator.py | 6c54b18254dbdae4f036144f4dfdbc4dff7b9cf9 | [] | no_license | mbiparva/slowfast-networks-pytorch | 20e6ea77f58f4c67c40cda1234e6f30a234ef8aa | 27da5fc479e38d7440d9651ee236bf4a296e7a55 | refs/heads/master | 2020-07-07T17:42:30.538222 | 2019-08-20T18:59:08 | 2019-08-20T18:59:08 | 203,425,393 | 21 | 4 | null | null | null | null | UTF-8 | Python | false | false | 545 | py | from tv_abc import TVBase
import torch
class Validator(TVBase):
def __init__(self, mode, meters, device):
super().__init__(mode, meters, device)
def set_net_mode(self, net):
net.eval()
def batch_main(self, net, x_slow, x_fast, annotation):
with torch.no_grad():
p = net.forward((x_slow, x_fast))
a = self.generate_gt(annotation)
loss = net.loss_update(p, a, step=False)
acc = self.evaluate(p, a)
return {'loss': loss,
'label_accuracy': acc}
| [
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] | |
b7f47856158c111a86a9df8272bdabd459f506dc | 8d0e0fa1062d575a0370bb842f7cafd85dc58ff9 | /Graphics/Players_Graphic.py | 3e9fece82cadf4d62cc54acc9677149cc92b6134 | [] | no_license | KorneevVladislav/Blackjack | 4aa1418bed12ddb17e0abd2324d814007939ac2a | abeeceba061e1fc874286ce002611694083ec0d9 | refs/heads/master | 2021-05-17T18:38:16.106196 | 2020-04-27T17:29:49 | 2020-04-27T17:29:49 | 250,922,343 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 61 | py | import pygame
#def PlayerGraphics():
#def DeilerGraphics(): | [
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] | |
68ad4b3925c2279ab9c55e808cc56b98321c3f2a | 042688362e547b2c45427f90723196f5d9f56792 | /応用編/37.改行コードの取得/os.linesep.py | a60233ee7ad6f2da8f510d8e3f3cb0754b671128 | [] | no_license | Watapon1704/python_study | 5a0b482f2cd5f4b02f4411a812b30ef260a8a7c5 | a196c692ff5b232c108f301ce5e165bc781df55e | refs/heads/master | 2020-03-12T00:59:31.671306 | 2019-03-27T12:48:44 | 2019-03-27T12:48:44 | 130,363,832 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 85 | py | import os
test_str = 'python-izm.com'
print(test_str.replace('.', os.linesep)) | [
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] | |
f10d585c637387ccc269aab61ce295e13ab11663 | 321e58ab3e6b2385bb3549aaaefd56a58c2a51e7 | /python/atpic/perf_postgres.py | 3c2b1312c886a38a2fa3d9e62deeb883a4697fb5 | [] | no_license | alexmadon/atpic_photosharing | 7829118d032344bd9a67818cd50e2c27a228d028 | 9fdddeb78548dadf946b1951aea0d0632e979156 | refs/heads/master | 2020-06-02T15:00:29.282979 | 2017-06-12T17:09:52 | 2017-06-12T17:09:52 | 94,095,494 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,408 | py | import atpic.database
import time
import pycurl
import StringIO
import cStringIO
time1=time.time()
for i in range(1,100):
print i
con=atpic.database.connect()
listofdict=atpic.database.query("select 1",con)
con.close()
time2=time.time()
print "=========="
con=atpic.database.connect()
for i in range(1,100):
print i
query="select id from artist_pic where id='%i'" % i
listofdict=atpic.database.query(query,con)
con.close()
time3=time.time()
# using Solr + curl new curl handle each time (new socket)
#fp=open("/dev/null","w")
fp=cStringIO.StringIO()
for i in range(1,100):
print i
url="http://localhost:8983/solr/select/?q=pid:%i&fl=pid" % i
c=pycurl.Curl()
# c.setopt(c.WRITEDATA,fp);
c.setopt(c.WRITEFUNCTION, fp.write)
c.setopt(c.URL, url);
c.perform()
c.close()
# print data
fp.close()
time4=time.time()
# using Solr + curl same curl handle
c=pycurl.Curl()
fp=cStringIO.StringIO()
for i in range(1,100):
print i
#c.setopt(c.WRITEDATA,fp);
url="http://localhost:8983/solr/select/?q=pid:%i&fl=pid" % i
c.setopt(c.WRITEFUNCTION, fp.write)
c.setopt(c.URL, url);
c.perform()
c.close()
fp.close()
time5=time.time()
print "Time1 %s" % (time2-time1)
print "Time2 %s" % (time3-time2)
print "Ratio=%f" % ((time2-time1)/(time3-time2))
print "Time3 %s" % (time4-time3)
print "Time4 %s" % (time5-time4)
| [
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] | |
9ac60f6dc3755d4c8f3c20fd4d1cd54718994a90 | 2faf152deabb0476ac43d4754f3b529fd678a36d | /ch_18.py | 3d923149df97df02941390334db1bf1ff1f74392 | [] | no_license | Sakartu/matasano | 46cba1325a01c41f6272f80b9fa698c6338c2e50 | b42e5a2ce5daa2fcc6691873e995a4b0d05e03d2 | refs/heads/master | 2021-01-23T09:51:50.305296 | 2015-08-10T15:37:59 | 2015-08-10T15:37:59 | 32,535,769 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 542 | py | #!/usr/bin/env python3
# -*- coding: utf8 -*-
"""
Usage:
test_ctr.py
"""
import base64
import util
__author__ = 'peter'
def main():
test = base64.b64decode('L77na/nrFsKvynd6HzOoG7GHTLXsTVu9qvY/2syLXzhPweyyMTJULu/6/kXX0KSvoOLSFQ==')
assert util.aes_ctr_decrypt(test, b"YELLOW SUBMARINE") == b"Yo, VIP Let's kick it Ice, Ice, baby Ice, Ice, baby "
k = util.get_random_bytes(16)
m = b'This is an interesting message'
assert util.aes_ctr_decrypt(util.aes_ctr_encrypt(m, k), k) == m
if __name__ == '__main__':
main()
| [
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] | |
68cfaa5dc120b4df33a466b592bd6685a7dceb21 | 83aca2c2e2608d3a44b43c2bc9fa396e290580f9 | /Faculty/PlagueGame/src/repository/file_repository.py | 0007ecd2807ac5d2d2e4d86144fef2d96e340587 | [] | no_license | biancadragomir/school-work | b91fb2e947435b9030d7e5ef8e2f5e362698d5eb | ca43abc656d2e0d87bc5a389d77de038fa220fdd | refs/heads/master | 2020-04-03T05:49:58.245702 | 2018-10-28T10:07:46 | 2018-10-28T10:07:46 | 155,057,194 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,359 | py | from domain.entities import Person
from repository.person_repository import PersonRepository
class FileRepoException(Exception):
def __init__(self, msg):
self.__msg = msg
def __str__(self):
return self.__msg
class FileRepo(PersonRepository):
def __init__(self, fileName):
PersonRepository.__init__(self)
self.__fName = fileName
self.__readFromFile()
def __readFromFile(self):
try:
f = open(self.__fName, 'r')
line = f.readline().strip()
while line != "":
args = line.split(",")
person = Person(args[0], args[1], args[2])
PersonRepository.add(self, person)
line = f.readline().strip()
except IOError:
raise FileRepoException("sth is not ok... ")
finally:
f.close()
def __writeToFile(self):
f = open(self.__fName, 'w')
persons = PersonRepository.get_all(self)
for p in persons:
pers = str(p.id) + "," + p.immunization + "," + p.status
pers += "\n"
f.write(pers)
f.close()
def add(self, person):
PersonRepository.add(self, person)
self.__writeToFile()
def remove(self, person):
PersonRepository.remove(self, person)
self.__writeToFile()
| [
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] | |
fd910a171a8cf2b17e59bea547030c2eb288ab75 | 32c993540a42ac5110e82ee9f23b1c7c9ce32332 | /logicaldoc/__init__.py | 2f8ffb535901cf92a58100dcf389fa5cab41f57e | [] | no_license | OpenCode/logicaldoc | 2f7ef4287eac677b5033e4ed9b8c4eefd68c67f0 | 089a35c86db9c0bb024bc6bfcee699f84b8169ad | refs/heads/master | 2020-05-21T06:00:46.577484 | 2019-03-27T13:54:30 | 2019-03-27T13:54:30 | 84,583,273 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 203 | py | # -*- coding: utf-8 -*-
# © 2016 Francesco Apruzzese <[email protected]>
# License AGPL-3.0 or later (http://www.gnu.org/licenses/agpl.html).
from .logicaldoc import LogicalDoc
from .constant import *
| [
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] | |
abe8946f42327bcd1a8465e567045df15152ea4d | 5e5a301bbd9887dee50d416e2a0de61b5c8133ad | /webhelper/models.py | 85b0fce4b4ec05e137f39107ff5fca70e91959a7 | [] | no_license | dmalikcs/django-webhelper | a3965656e1b95a9d715b442919dcd80ba45baa2f | d2f0e7ac3f72b16ba696525f7ac903c8d8c876ee | refs/heads/master | 2020-06-02T08:28:33.194264 | 2014-04-15T16:56:45 | 2014-04-15T16:56:45 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,603 | py | from django.db import models
from django.contrib.sites.models import Site
from django.core.validators import RegexValidator
class SocialLinks(models.Model):
'''
facebook
linkedin
twitter
gluse
rss
'''
facebook = models.URLField(
max_length=100,
blank=True,
null=True
)
linkedin = models.URLField(
max_length=100,
blank=True,
null=True
)
twitter = models.URLField(
max_length=100,
blank=True,
null=True
)
gpluse = models.URLField(
max_length=100,
blank=True,
null=True
)
rss = models.URLField(
max_length=100,
blank=True,
null=True
)
site = models.OneToOneField(Site)
class Meta:
verbose_name = 'Social Links'
verbose_name_plural = 'Soical Links'
def __unicode__(self):
return self.site.domain
class BaseAddress(models.Model):
'''
BaseAddress model extend in OfficeAddress/RegisterAddress
'''
name = models.CharField(
max_length=30,
blank=True,
null=True
)
street_1 = models.CharField(
max_length=500,
blank=True,
null=True
)
street_2 = models.CharField(
max_length=200,
blank=True,
null=True
)
city = models.CharField(
max_length=100,
blank=True,
null=True
)
country = models.CharField(
max_length=100,
blank=True,
null=True
)
site = models.OneToOneField(Site)
class Meta:
abstract = True
class RegisterAddress(BaseAddress):
class Meta:
verbose_name = 'Register Address'
verbose_name_plural = 'Register Address'
def __unicode__(self):
return self.name
class OfficeAddress(BaseAddress):
class Meta:
verbose_name = 'office Address'
verbose_name = 'office Address'
def __unicode__(self):
return self.name
class GeneralInfo(models.Model):
phone_1 = models.CharField(
max_length=15,
blank=True,
null=True,
validators=[
RegexValidator(
r'^[-\d+]+$',
'Enter the valid phone number'
),
]
)
phone_2 = models.CharField(
max_length=15,
blank=True,
null=True,
validators=[
RegexValidator(
r'^[-\d+]+$',
'Enter the valid phone number'
),
]
)
phone_3 = models.CharField(
max_length=15,
blank=True,
null=True,
validators=[
RegexValidator(
r'^[-\d+]+$',
'Enter the valid phone number'
),
]
)
fax = models.CharField(
max_length=15,
blank=True,
null=True,
validators=[
RegexValidator(
r'^[-\d+]+$',
'Enter the valid Fax number'
),
]
)
tollfree = models.CharField(
max_length=11,
blank=True,
null=True
)
support_email = models.EmailField(
blank=True,
null=True
)
sales_email = models.EmailField(
blank=True,
null=True
)
Billing_email = models.EmailField(
blank=True,
null=True
)
Website = models.URLField()
site = models.OneToOneField(Site)
class Meta:
verbose_name = 'general Info'
verbose_name_plural = 'general infos'
def __unicode__(self):
return self.site.domain
| [
"[email protected]"
] | |
052349cced621bbf4fe2950e0da1e1f43cdde479 | ece5aafef31d93ad9e344f71f5d33d19a7a87651 | /model/pspnet2/cil.pspnet2.R101/eval_all.py | e2620a6800f92f1d3190d77d02c16e18fd42762b | [
"MIT"
] | permissive | lxxue/TorchSeg | f8325b97b55d4da7ea4a25ea812b122ab9ce661c | da5eae8c2c3734924a5178cf3c9e4dafb9c6c16f | refs/heads/master | 2022-11-27T11:39:11.302225 | 2020-08-01T07:57:56 | 2020-08-01T07:57:56 | 274,429,653 | 0 | 2 | MIT | 2020-08-01T13:39:10 | 2020-06-23T14:37:22 | Python | UTF-8 | Python | false | false | 360 | py | import os
import numpy as np
epoch_nums = np.arange(200, 4100, step=200)
print(epoch_nums)
for e in epoch_nums:
print("-----------------------------------------------------------------")
print(e)
os.system("python eval.py -e {} -p results_eval/epoch{}/".format(e, e))
print("-----------------------------------------------------------------")
| [
"[email protected]"
] | |
4d9688118734773d4a204a1b601cc1ffda2a036e | dc987f2153345dfb383de804c112aa54be2199d7 | /Code buoi hoc/Buoi 7/bt.py | a3530b4d9ecee6edfc2ad920e627c86ecbde8793 | [] | no_license | lva123/python101-sinh-vien | c2d204a7dec26bcff2f212372468bb658beed0ac | cdc177f30404cd2175b11e6ad0e9877df7252497 | refs/heads/main | 2023-09-03T00:51:35.641239 | 2021-11-20T03:19:10 | 2021-11-20T03:19:10 | 429,988,208 | 0 | 0 | null | 2021-11-20T02:23:03 | 2021-11-20T02:23:02 | null | UTF-8 | Python | false | false | 351 | py | #!/bin/python3
import math
import os
import random
import re
import sys
if __name__ == '__main__':
n = int(input().strip())
if n % 2 != 0:
print("Weird")
else:
if 2 <= n <= 5:
print("Not weird")
elif 6 <= n <= 20:
print("Weird")
elif 20 < n:
print("Not weird")
| [
"[email protected]"
] | |
532a4c353a1544432b498ed028eb0f65b6b9fc4d | e2860eb874db045fb8d0279566a935af907e5bdf | /ml/ml07_1_boston.py | b245a54bef04d78667e33b52f33e63088f0a8179 | [] | no_license | MinseokCHAE/Bitcamp2_new | dda7990907cb136c2e709a345eec634dfdb6ac02 | 849adb5a330b621f1c681f0b5e92005d1281a44d | refs/heads/main | 2023-08-31T03:28:18.068561 | 2021-10-05T00:48:52 | 2021-10-05T00:48:52 | 390,228,262 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,847 | py | import numpy as np
import time
from sklearn.metrics import r2_score
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import MinMaxScaler, StandardScaler, RobustScaler, QuantileTransformer, OneHotEncoder
from sklearn.datasets import load_boston
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Input, Conv1D, Flatten, MaxPooling1D, GlobalAveragePooling1D, Dropout
from tensorflow.keras.callbacks import EarlyStopping
from tensorflow.keras.utils import to_categorical
#1. data preprocessing
boston = load_boston()
x = boston.data
y = boston.target
x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.2, random_state=21)
scaler = MinMaxScaler()
scaler.fit(x_train)
x_train = scaler.transform(x_train)
x_test = scaler.transform(x_test)
from sklearn.model_selection import KFold, cross_val_score, GridSearchCV
from sklearn.ensemble import RandomForestRegressor
from sklearn.metrics import accuracy_score
n_splits = 5
kfold = KFold(n_splits=n_splits, shuffle=True, random_state=21)
parameter = [
{'n_estimators': [100,200]},
{'max_depth': [6, 8, 10, 12]},
{'min_samples_leaf': [3, 5, 7, 10]},
{'min_samples_split': [2, 3, 5, 10]},
{'n_jobs': [-1, 2, 4]}
]
model = RandomForestRegressor()
grid = GridSearchCV(model, parameter, cv=kfold)
grid.fit(x_train, y_train)
best_estimator = grid.best_estimator_
best_score = grid.best_score_
# y_pred = grid.predict(x_test)
# acc_score = accuracy_score(y_test, y_pred)
grid_score = grid.score(x_test, y_test)
print('best parameter = ', best_estimator)
print('best score = ', best_score)
# print('acc score = ', acc_score)
print('grid score = ', grid_score)
# best parameter = RandomForestRegressor(min_samples_split=5)
# best score = 0.830591307770115
# grid score = 0.8783616408326427
| [
"[email protected]"
] | |
dbb6da85866332dca534ebaa601baddbff1949fb | 059742e69e6842eea5fff25acc8329a08ea3eb86 | /OauthDemo/bloggo/posts/urls.py | 28d10dcf290be21c565343a95fdf034bcb0bbb13 | [] | no_license | commanderchewbacca/Guides | 856aa556fa263f32282b4607d64f1f02f98316d3 | e07a5d71c556d46cebb54dc404dc73ce16057b7a | refs/heads/master | 2020-03-11T00:22:07.701088 | 2018-04-15T02:08:32 | 2018-04-15T02:08:32 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 380 | py | from django.conf.urls import url
from . import views
app_name="posts"
urlpatterns = [
url(r'^/$', views.index, name='index'),
url(r'^about/$', views.about, name='about'),
url(r'^details/(?P<pk>\d+)$', views.post_details, name='post_details'),
url(r'^fitbitinfo', views.fitbit_info, name='registerfitbit'),
url(r'^getactivitydata/', views.fitbit_callback),
] | [
"[email protected]"
] | |
78b580625bf05f9a4e3f617d22606d8993dc1471 | 07c27cbba56ffb1f2e391d2aaceefba039f68667 | /bin/svg.py | 0f7e900113122f37f95eb346261053c090c4287c | [] | no_license | rheiland/tool4nanobio | beb3914ad23638bb856454832c83ab3c6535ae86 | e872ae02e7df784bcde0481b30c6d97a0ae3a517 | refs/heads/master | 2020-04-25T17:11:52.995649 | 2020-01-16T11:32:47 | 2020-01-16T11:32:47 | 172,938,698 | 3 | 3 | null | null | null | null | UTF-8 | Python | false | false | 13,242 | py | # SVG (Cell Plot) Tab
import os
from ipywidgets import Layout, Label, Text, Checkbox, Button, HBox, VBox, Box, \
FloatText, BoundedIntText, BoundedFloatText, HTMLMath, Dropdown, interactive, Output
from collections import deque
import xml.etree.ElementTree as ET
import matplotlib.pyplot as plt
import matplotlib.colors as mplc
import numpy as np
import zipfile
import glob
import platform
from debug import debug_view
hublib_flag = True
if platform.system() != 'Windows':
try:
# print("Trying to import hublib.ui")
from hublib.ui import Download
except:
hublib_flag = False
else:
hublib_flag = False
class SVGTab(object):
def __init__(self):
# tab_height = '520px'
# tab_layout = Layout(width='900px', # border='2px solid black',
# height=tab_height, overflow_y='scroll')
self.output_dir = '.'
constWidth = '180px'
# self.fig = plt.figure(figsize=(6, 6))
# self.fig = plt.figure(figsize=(7, 7))
max_frames = 1
self.svg_plot = interactive(self.plot_svg, frame=(0, max_frames), continuous_update=False)
plot_size = '500px'
plot_size = '700px'
self.svg_plot.layout.width = plot_size
self.svg_plot.layout.height = plot_size
self.use_defaults = True
self.show_nucleus = 0 # 0->False, 1->True in Checkbox!
self.show_edge = 1 # 0->False, 1->True in Checkbox!
self.scale_radius = 1.0
self.axes_min = 0.0
self.axes_max = 2000 # hmm, this can change (TODO?)
self.max_frames = BoundedIntText(
min=0, max=99999, value=max_frames,
description='Max',
layout=Layout(width='160px'),
# layout=Layout(flex='1 1 auto', width='auto'), #Layout(width='160px'),
)
self.max_frames.observe(self.update_max_frames)
self.show_nucleus_checkbox= Checkbox(
description='nucleus', value=False, disabled=False,
layout=Layout(width=constWidth),
# layout=Layout(flex='1 1 auto', width='auto'), #Layout(width='160px'),
)
self.show_nucleus_checkbox.observe(self.show_nucleus_cb)
self.show_edge_checkbox= Checkbox(
description='edge', value=True, disabled=False,
layout=Layout(width=constWidth),
# layout=Layout(flex='1 1 auto', width='auto'), #Layout(width='160px'),
)
self.show_edge_checkbox.observe(self.show_edge_cb)
# row1 = HBox([Label('(select slider: drag or left/right arrows)'),
# self.max_frames, VBox([self.show_nucleus_checkbox, self.show_edge_checkbox])])
# self.max_frames, self.show_nucleus_checkbox], layout=Layout(width='500px'))
# self.tab = VBox([row1,self.svg_plot], layout=tab_layout)
items_auto = [Label('select slider: drag or left/right arrows'),
self.max_frames,
self.show_nucleus_checkbox,
self.show_edge_checkbox,
]
#row1 = HBox([Label('(select slider: drag or left/right arrows)'),
# max_frames, show_nucleus_checkbox, show_edge_checkbox],
# layout=Layout(width='800px'))
box_layout = Layout(display='flex',
flex_flow='row',
align_items='stretch',
width='70%')
row1 = Box(children=items_auto, layout=box_layout)
if (hublib_flag):
self.download_button = Download('svg.zip', style='warning', icon='cloud-download',
tooltip='You need to allow pop-ups in your browser', cb=self.download_cb)
download_row = HBox([self.download_button.w, Label("Download all cell plots (browser must allow pop-ups).")])
# self.tab = VBox([row1, self.svg_plot, self.download_button.w], layout=tab_layout)
# self.tab = VBox([row1, self.svg_plot, self.download_button.w])
self.tab = VBox([row1, self.svg_plot, download_row])
else:
self.tab = VBox([row1, self.svg_plot])
def update(self, rdir=''):
# with debug_view:
# print("SVG: update rdir=", rdir)
if rdir:
self.output_dir = rdir
all_files = sorted(glob.glob(os.path.join(self.output_dir, 'snapshot*.svg')))
if len(all_files) > 0:
last_file = all_files[-1]
self.max_frames.value = int(last_file[-12:-4]) # assumes naming scheme: "snapshot%08d.svg"
# with debug_view:
# print("SVG: added %s files" % len(all_files))
def download_cb(self):
file_str = os.path.join(self.output_dir, '*.svg')
# print('zip up all ',file_str)
with zipfile.ZipFile('svg.zip', 'w') as myzip:
for f in glob.glob(file_str):
myzip.write(f, os.path.basename(f)) # 2nd arg avoids full filename path in the archive
def show_nucleus_cb(self, b):
global current_frame
if (self.show_nucleus_checkbox.value):
self.show_nucleus = 1
else:
self.show_nucleus = 0
# self.plot_svg(self,current_frame)
self.svg_plot.update()
def show_edge_cb(self, b):
if (self.show_edge_checkbox.value):
self.show_edge = 1
else:
self.show_edge = 0
self.svg_plot.update()
def update_max_frames(self,_b):
self.svg_plot.children[0].max = self.max_frames.value
def plot_svg(self, frame):
# global current_idx, axes_max
global current_frame
current_frame = frame
fname = "snapshot%08d.svg" % frame
full_fname = os.path.join(self.output_dir, fname)
# with debug_view:
# print("plot_svg:", full_fname)
if not os.path.isfile(full_fname):
print("Once output files are generated, click the slider.")
return
xlist = deque()
ylist = deque()
rlist = deque()
rgb_list = deque()
# print('\n---- ' + fname + ':')
# tree = ET.parse(fname)
tree = ET.parse(full_fname)
root = tree.getroot()
# print('--- root.tag ---')
# print(root.tag)
# print('--- root.attrib ---')
# print(root.attrib)
# print('--- child.tag, child.attrib ---')
numChildren = 0
for child in root:
# print(child.tag, child.attrib)
# print("keys=",child.attrib.keys())
if self.use_defaults and ('width' in child.attrib.keys()):
self.axes_max = float(child.attrib['width'])
# print("debug> found width --> axes_max =", axes_max)
if child.text and "Current time" in child.text:
svals = child.text.split()
# title_str = "(" + str(current_idx) + ") Current time: " + svals[2] + "d, " + svals[4] + "h, " + svals[7] + "m"
# title_str = "Current time: " + svals[2] + "d, " + svals[4] + "h, " + svals[7] + "m"
title_str = svals[2] + "d, " + svals[4] + "h, " + svals[7] + "m"
# print("width ",child.attrib['width'])
# print('attrib=',child.attrib)
# if (child.attrib['id'] == 'tissue'):
if ('id' in child.attrib.keys()):
# print('-------- found tissue!!')
tissue_parent = child
break
# print('------ search tissue')
cells_parent = None
for child in tissue_parent:
# print('attrib=',child.attrib)
if (child.attrib['id'] == 'cells'):
# print('-------- found cells, setting cells_parent')
cells_parent = child
break
numChildren += 1
num_cells = 0
# print('------ search cells')
for child in cells_parent:
# print(child.tag, child.attrib)
# print('attrib=',child.attrib)
for circle in child: # two circles in each child: outer + nucleus
# circle.attrib={'cx': '1085.59','cy': '1225.24','fill': 'rgb(159,159,96)','r': '6.67717','stroke': 'rgb(159,159,96)','stroke-width': '0.5'}
# print(' --- cx,cy=',circle.attrib['cx'],circle.attrib['cy'])
xval = float(circle.attrib['cx'])
s = circle.attrib['fill']
# print("s=",s)
# print("type(s)=",type(s))
if (s[0:3] == "rgb"): # if an rgb string, e.g. "rgb(175,175,80)"
rgb = list(map(int, s[4:-1].split(",")))
rgb[:] = [x / 255. for x in rgb]
else: # otherwise, must be a color name
rgb_tuple = mplc.to_rgb(mplc.cnames[s]) # a tuple
rgb = [x for x in rgb_tuple]
# test for bogus x,y locations (rwh TODO: use max of domain?)
too_large_val = 10000.
if (np.fabs(xval) > too_large_val):
print("bogus xval=", xval)
break
yval = float(circle.attrib['cy'])
if (np.fabs(yval) > too_large_val):
print("bogus xval=", xval)
break
rval = float(circle.attrib['r'])
# if (rgb[0] > rgb[1]):
# print(num_cells,rgb, rval)
xlist.append(xval)
ylist.append(yval)
rlist.append(rval)
rgb_list.append(rgb)
# For .svg files with cells that *have* a nucleus, there will be a 2nd
if (self.show_nucleus == 0):
#if (not self.show_nucleus):
break
num_cells += 1
# if num_cells > 3: # for debugging
# print(fname,': num_cells= ',num_cells," --- debug exit.")
# sys.exit(1)
# break
# print(fname,': num_cells= ',num_cells)
xvals = np.array(xlist)
yvals = np.array(ylist)
rvals = np.array(rlist)
rgbs = np.array(rgb_list)
# print("xvals[0:5]=",xvals[0:5])
# print("rvals[0:5]=",rvals[0:5])
# print("rvals.min, max=",rvals.min(),rvals.max())
# rwh - is this where I change size of render window?? (YES - yipeee!)
# plt.figure(figsize=(6, 6))
# plt.cla()
title_str += " (" + str(num_cells) + " agents)"
# plt.title(title_str)
# plt.xlim(axes_min,axes_max)
# plt.ylim(axes_min,axes_max)
# plt.scatter(xvals,yvals, s=rvals*scale_radius, c=rgbs)
# self.fig = plt.figure(figsize=(6, 6))
self.fig = plt.figure(figsize=(7, 7))
# axx = plt.axes([0, 0.05, 0.9, 0.9]) # left, bottom, width, height
# axx = fig.gca()
# print('fig.dpi=',fig.dpi) # = 72
# im = ax.imshow(f.reshape(100,100), interpolation='nearest', cmap=cmap, extent=[0,20, 0,20])
# ax.xlim(axes_min,axes_max)
# ax.ylim(axes_min,axes_max)
# convert radii to radii in pixels
# ax2 = fig.gca()
ax2 = self.fig.gca()
N = len(xvals)
rr_pix = (ax2.transData.transform(np.vstack([rvals, rvals]).T) -
ax2.transData.transform(np.vstack([np.zeros(N), np.zeros(N)]).T))
rpix, _ = rr_pix.T
markers_size = (144. * rpix / self.fig.dpi)**2 # = (2*rpix / fig.dpi * 72)**2
# markers_size = (2*rpix / fig.dpi * 72)**2
markers_size = markers_size/4000000.
# print('max=',markers_size.max())
# ax.scatter(xvals,yvals, s=rvals*self.scale_radius, c=rgbs)
# axx.scatter(xvals,yvals, s=markers_size, c=rgbs)
#rwh - temp fix - Ah, error only occurs when "edges" is toggled on
if (self.show_edge):
try:
plt.scatter(xvals,yvals, s=markers_size, c=rgbs, edgecolor='black', linewidth=0.5)
except (ValueError):
pass
else:
plt.scatter(xvals,yvals, s=markers_size, c=rgbs)
plt.xlim(self.axes_min, self.axes_max)
plt.ylim(self.axes_min, self.axes_max)
# ax.grid(False)
# axx.set_title(title_str)
plt.title(title_str)
# video-style widget - perhaps for future use
# svg_play = widgets.Play(
# interval=1,
# value=50,
# min=0,
# max=100,
# step=1,
# description="Press play",
# disabled=False,
# )
# def svg_slider_change(change):
# print('svg_slider_change: type(change)=',type(change),change.new)
# plot_svg(change.new)
#svg_play
# svg_slider = widgets.IntSlider()
# svg_slider.observe(svg_slider_change, names='value')
# widgets.jslink((svg_play, 'value'), (svg_slider,'value')) # (svg_slider, 'value'), (plot_svg, 'value'))
# svg_slider = widgets.IntSlider()
# widgets.jslink((play, 'value'), (slider, 'value'))
# widgets.HBox([svg_play, svg_slider])
# Using the following generates a new mpl plot; it doesn't use the existing plot!
#svg_anim = widgets.HBox([svg_play, svg_slider])
#svg_tab = widgets.VBox([svg_dir, svg_plot, svg_anim], layout=tab_layout)
#svg_tab = widgets.VBox([svg_dir, svg_anim], layout=tab_layout)
#---------------------
| [
"[email protected]"
] | |
8332e30937e9e1b5e5122db696b4431f00c38374 | 6223dc2e5de7921696cb34fb62142fd4a4efe361 | /.metadata/.plugins/org.eclipse.core.resources/.history/51/40e6c6177739001412b5c17ef71e72e3 | 6db0fb731998676d3ddb05dbce7d5249db6922c6 | [] | no_license | Mushirahmed/python_workspace | 5ef477b2688e8c25b1372f546752501ee53d93e5 | 46e2ed783b17450aba29e4e2df7b656522b2b03b | refs/heads/master | 2021-03-12T19:24:50.598982 | 2015-05-25T10:23:54 | 2015-05-25T10:23:54 | 24,671,376 | 0 | 1 | null | 2015-02-06T09:27:40 | 2014-10-01T08:40:33 | Python | UTF-8 | Python | false | false | 1,442 | #!/usr/bin/env python
import wx
def slider(parent, min, max, callback):
"""
Return a wx.Slider object.
@param min: minimum slider value
@type min: float
@param max: maximum slider value
@type max: float
@param callback: function of one arg invoked when slider moves.
@rtype: wx.Slider
"""
new_id = wx.NewId()
s = wx.Slider(parent, new_id, (max+min)/2, min, max, wx.DefaultPosition,
wx.Size(250,-1), wx.SL_HORIZONTAL | wx.SL_LABELS)
wx.EVT_COMMAND_SCROLL(parent, new_id,
lambda evt : callback(evt.GetInt()))
return s
# ----------------------------------------------------------------
# Demo app
# ----------------------------------------------------------------
if __name__ == '__main__':
from gnuradio.wxgui import stdgui2
class demo_graph(stdgui.gui_flow_graph):
def __init__(self, frame, panel, vbox, argv):
stdgui.gui_flow_graph.__init__ (self, frame, panel, vbox, argv)
vbox.Add(slider(panel, 23, 47, self.my_callback1), 1, wx.ALIGN_CENTER)
vbox.Add(slider(panel, -100, 100, self.my_callback2), 1, wx.ALIGN_CENTER)
def my_callback1(self, val):
print "cb1 = ", val
def my_callback2(self, val):
print "cb2 = ", val
def main ():
app = stdgui.stdapp (demo_graph, "Slider Demo")
app.MainLoop ()
main ()
| [
"[email protected]"
] | ||
a161266ee413fb7f3bb8b94466c9d03314de7ee9 | 633b695a03e789f6aa644c7bec7280367a9252a8 | /lmfit_gallery/documentation/fitting_withreport.py | 412f4c07159b2a6fb06c2af10b0d239b29d68e3f | [] | no_license | tnakaicode/PlotGallery | 3d831d3245a4a51e87f48bd2053b5ef82cf66b87 | 5c01e5d6e2425dbd17593cb5ecc973982f491732 | refs/heads/master | 2023-08-16T22:54:38.416509 | 2023-08-03T04:23:21 | 2023-08-03T04:23:21 | 238,610,688 | 5 | 2 | null | null | null | null | UTF-8 | Python | false | false | 1,206 | py | """
doc_fitting_withreport.py
=========================
"""
# <examples/doc_fitting_withreport.py>
from numpy import exp, linspace, pi, random, sign, sin
from lmfit import Parameters, fit_report, minimize
p_true = Parameters()
p_true.add('amp', value=14.0)
p_true.add('period', value=5.46)
p_true.add('shift', value=0.123)
p_true.add('decay', value=0.032)
def residual(pars, x, data=None):
"""Model a decaying sine wave and subtract data."""
vals = pars.valuesdict()
amp = vals['amp']
per = vals['period']
shift = vals['shift']
decay = vals['decay']
if abs(shift) > pi/2:
shift = shift - sign(shift)*pi
model = amp * sin(shift + x/per) * exp(-x*x*decay*decay)
if data is None:
return model
return model - data
random.seed(0)
x = linspace(0.0, 250., 1001)
noise = random.normal(scale=0.7215, size=x.size)
data = residual(p_true, x) + noise
fit_params = Parameters()
fit_params.add('amp', value=13.0)
fit_params.add('period', value=2)
fit_params.add('shift', value=0.0)
fit_params.add('decay', value=0.02)
out = minimize(residual, fit_params, args=(x,), kws={'data': data})
print(fit_report(out))
# <end examples/doc_fitting_withreport.py>
| [
"[email protected]"
] | |
2472d991874e1382b2a57fe70f66ab353ff64c6b | 1ec1d20f16a9bd9d51b8a7be9b7fa5fcec6a4f02 | /main.py | 79809bf14ee1eb4fa881034b745157b21fdc73eb | [] | no_license | billyjia1/UnfairBulletHell | b676f66a3c033e765f832e57a0f1bb3d8acbc394 | 8d623113ec1491e949164599e9db77217bb8c35d | refs/heads/main | 2023-08-15T00:09:45.935440 | 2021-09-27T21:39:09 | 2021-09-27T21:39:09 | 409,778,226 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 10,077 | py | import pygame
import os
import time
import random
pygame.font.init()
WIDTH, HEIGHT = 750, 750
WIN = pygame.display.set_mode((WIDTH, HEIGHT))
pygame.display.set_caption("Space Shooter Tutorial")
# Load images
RED_SPACE_SHIP = pygame.image.load(os.path.join("assets", "pixel_ship_red_small.png"))
GREEN_SPACE_SHIP = pygame.image.load(os.path.join("assets", "pixel_ship_green_small.png"))
BLUE_SPACE_SHIP = pygame.image.load(os.path.join("assets", "pixel_ship_blue_small.png"))
# Player player
YELLOW_SPACE_SHIP = pygame.image.load(os.path.join("assets", "pixel_ship_yellow.png"))
# Lasers
RED_LASER = pygame.image.load(os.path.join("assets", "pixel_laser_red.png"))
GREEN_LASER = pygame.image.load(os.path.join("assets", "pixel_laser_green.png"))
BLUE_LASER = pygame.image.load(os.path.join("assets", "pixel_laser_blue.png"))
YELLOW_LASER = pygame.image.load(os.path.join("assets", "pixel_laser_yellow.png"))
# Background
BG = pygame.transform.scale(pygame.image.load(os.path.join("assets", "background-black.png")), (WIDTH, HEIGHT))
class Laser:
def __init__(self, x, y, img):
self.x = x
self.y = y
self.img = img
self.mask = pygame.mask.from_surface(self.img)
def draw(self, window):
window.blit(self.img, (self.x, self.y))
def move(self, vel):
self.y += vel
self.x += random.randrange(-20,20, 5)
def move_friendly(self, vel):
self.y += vel
def off_screen(self, height):
return not(self.y <= height and self.y >= 0)
def collision(self, obj):
return collide(self, obj)
class Ship:
COOLDOWN = 30
def __init__(self, x, y, health=100):
self.x = x
self.y = y
self.health = health
self.ship_img = None
self.laser_img = None
self.lasers = []
self.cool_down_counter = 0
def draw(self, window):
window.blit(self.ship_img, (self.x, self.y))
for laser in self.lasers:
laser.draw(window)
def move_lasers(self, vel, obj):
self.cooldown()
for laser in self.lasers:
laser.move(vel)
if laser.off_screen(HEIGHT):
self.lasers.remove(laser)
elif laser.collision(obj):
obj.health -= 10
self.lasers.remove(laser)
def cooldown(self):
if self.cool_down_counter >= self.COOLDOWN:
self.cool_down_counter = 0
elif self.cool_down_counter > 0:
self.cool_down_counter += 1
def shoot(self):
if self.cool_down_counter == 0:
laser = Laser(self.x, self.y, self.laser_img)
self.lasers.append(laser)
self.cool_down_counter = 1
def get_width(self):
return self.ship_img.get_width()
def get_height(self):
return self.ship_img.get_height()
class Player(Ship):
def __init__(self, x, y, health=1000):
super().__init__(x, y, health)
self.ship_img = YELLOW_SPACE_SHIP
self.laser_img = YELLOW_LASER
self.mask = pygame.mask.from_surface(self.ship_img)
self.max_health = health
def move_lasers(self, vel, objs):
self.cooldown()
for laser in self.lasers:
laser.move_friendly(vel)
if laser.off_screen(HEIGHT):
self.lasers.remove(laser)
else:
for obj in objs:
if laser.collision(obj):
obj.health -= 10
if obj.health <= 0:
objs.remove(obj)
if laser in self.lasers:
self.lasers.remove(laser)
def draw(self, window):
super().draw(window)
self.healthbar(window)
def healthbar(self, window):
pygame.draw.rect(window, (255,0,0), (self.x, self.y + self.ship_img.get_height() + 10, self.ship_img.get_width(), 10))
pygame.draw.rect(window, (0,255,0), (self.x, self.y + self.ship_img.get_height() + 10, self.ship_img.get_width() * (self.health/self.max_health), 10))
# class Enemy(Ship):
# COLOR_MAP = {
# "red": (RED_SPACE_SHIP, RED_LASER),
# "green": (GREEN_SPACE_SHIP, GREEN_LASER),
# "blue": (BLUE_SPACE_SHIP, BLUE_LASER)
# }
# def __init__(self, x, y, color, health=100):
# super().__init__(x, y, health)
# self.ship_img, self.laser_img = self.COLOR_MAP[color]
# self.mask = pygame.mask.from_surface(self.ship_img)
# def move(self, vel):
# self.y += vel
# def shoot(self):
# if self.cool_down_counter == 0:
# laser = Laser(self.x-20, self.y, self.laser_img)
# self.lasers.append(laser)
# self.cool_down_counter = 1
class Red_Enemy(Ship):
def __init__(self, x, y, health=100):
super().__init__(x, y, health=health)
self.ship_img, self.laser_img = RED_SPACE_SHIP, RED_LASER
self.mask = pygame.mask.from_surface(self.ship_img)
def move(self, vel):
self.y += vel + 5
self.x += vel
def shoot(self):
if self.cool_down_counter == 0:
laser = Laser(self.x - 100, self.y, self.laser_img)
self.lasers.append(laser)
self.cool_down_counter = 1
class Blue_Enemy(Ship):
def __init__(self, x, y, health=100):
super().__init__(x, y, health=health)
self.ship_img, self.laser_img = BLUE_SPACE_SHIP, BLUE_LASER
self.mask = pygame.mask.from_surface(self.ship_img)
def move(self, vel):
self.y += vel + 2
self.x += vel
def shoot(self):
if self.cool_down_counter == 0:
laser = Laser(self.x - 100, self.y, self.laser_img)
self.lasers.append(laser)
self.cool_down_counter = 1
class Green_Enemy(Ship):
def __init__(self, x, y, health=100):
super().__init__(x, y, health=health)
self.ship_img, self.laser_img = GREEN_SPACE_SHIP, GREEN_LASER
self.mask = pygame.mask.from_surface(self.ship_img)
def move(self, vel):
self.y += vel
def shoot(self):
if self.cool_down_counter == 0:
laser = Laser(self.x - 50, self.y, self.laser_img)
self.lasers.append(laser)
self.cool_down_counter = 1
def collide(obj1, obj2):
offset_x = obj2.x - obj1.x
offset_y = obj2.y - obj1.y
return obj1.mask.overlap(obj2.mask, (offset_x, offset_y)) != None
def main():
run = True
FPS = 60
level = 0
lives = 5
main_font = pygame.font.SysFont("comicsans", 50)
lost_font = pygame.font.SysFont("comicsans", 60)
enemies = []
wave_length = 5
enemy_vel = 1
player_vel = 5
laser_vel = 5
player = Player(300, 630)
clock = pygame.time.Clock()
lost = False
lost_count = 0
def redraw_window():
WIN.blit(BG, (0,0))
# draw text
lives_label = main_font.render(f"Lives: {lives}", 1, (255,255,255))
level_label = main_font.render(f"Level: {level}", 1, (255,255,255))
WIN.blit(lives_label, (10, 10))
WIN.blit(level_label, (WIDTH - level_label.get_width() - 10, 10))
for enemy in enemies:
enemy.draw(WIN)
player.draw(WIN)
if lost:
lost_label = lost_font.render("You Lost!!", 1, (255,255,255))
WIN.blit(lost_label, (WIDTH/2 - lost_label.get_width()/2, 350))
pygame.display.update()
while run:
clock.tick(FPS)
redraw_window()
if lives <= 0 or player.health <= 0:
lost = True
lost_count += 1
if lost:
if lost_count > FPS * 3:
run = False
else:
continue
if len(enemies) == 0:
level += 1
wave_length += 5
for i in range(wave_length):
enemy_r = Red_Enemy(random.randrange(50, WIDTH-100), random.randrange(-1500, -100))
enemy_b = Blue_Enemy(random.randrange(50, WIDTH-100), random.randrange(-1500, -100))
enemy_g = Green_Enemy(random.randrange(50, WIDTH-100), random.randrange(-1500, -100))
enemy_list = (enemy_b, enemy_r, enemy_g)
enemies.append(random.choice(enemy_list))
for event in pygame.event.get():
if event.type == pygame.QUIT:
quit()
keys = pygame.key.get_pressed()
if keys[pygame.K_a] and player.x - player_vel > 0: # left
player.x -= player_vel
if keys[pygame.K_d] and player.x + player_vel + player.get_width() < WIDTH: # right
player.x += player_vel
if keys[pygame.K_w] and player.y - player_vel > 0: # up
player.y -= player_vel
if keys[pygame.K_s] and player.y + player_vel + player.get_height() + 15 < HEIGHT: # down
player.y += player_vel
if keys[pygame.K_SPACE]:
player.shoot()
for enemy in enemies[:]:
enemy.move(enemy_vel)
enemy.move_lasers(laser_vel, player)
if random.randrange(0, 120) == 1:
enemy.shoot()
if collide(player, enemy):
enemy.health -= 50
player.health -= 10
if enemy.health <= 0:
enemies.remove(enemy)
elif enemy.y + enemy.get_height() > HEIGHT:
lives -= 1
enemies.remove(enemy)
player.move_lasers(-laser_vel, enemies)
def main_menu():
title_font = pygame.font.SysFont("comicsans", 70)
run = True
while run:
WIN.blit(BG, (0,0))
title_label = title_font.render("Press the mouse to begin...", 1, (255,255,255))
WIN.blit(title_label, (WIDTH/2 - title_label.get_width()/2, 350))
pygame.display.update()
for event in pygame.event.get():
if event.type == pygame.QUIT:
run = False
if event.type == pygame.MOUSEBUTTONDOWN:
main()
pygame.quit()
main_menu() | [
"[email protected]"
] | |
2d96b9e44c4d5cf68a3afe6db0a8a384018a4a30 | 0dafa1dff4429bb8893445d05202061ff4f9f710 | /plotting_scripts/plot_sigloss_modeloop.py | 1aba5bcdf53def99fce4f45924bf9b849ed55c96 | [] | no_license | carinacheng/PAPERMethods_paper | 8d879291eb4d30e3a0d98286fbab4dd42bba3ef7 | 9b657e0274842477643407db89916781ac948f80 | refs/heads/master | 2021-07-23T21:59:29.331251 | 2018-11-01T23:25:08 | 2018-11-01T23:25:08 | 95,481,809 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 6,724 | py | #! /usr/bin/env python
import numpy as n
import matplotlib.pyplot as p
from scipy.optimize import curve_fit
# Reads in power spectrum results from projecting out 0,1,2... modes
# Plots power spectrum results before and after signal loss correction as a function of modes removed
if True: # eigenmodes set to 1
path = 'plot_sigloss_modeloop_mode'
startmode=0
nmodes=22
deltamode=1
xlabel='Number of modes down-weighted using inverse covariance weighting'
f1 = '/project_'
f2 = '_modes'
loop = n.arange(startmode,nmodes,deltamode)
if True: # added identity parameters in LOG space
path_add = 'plot_sigloss_modeloop_add'
startmode_add=-4
endmode_add=0
nmodes_add=20 #20000
xlabel_add='Strength of identity added: $\mathbf{\widehat{C}}$ + $\gamma$Tr$(\mathbf{\widehat{C}})\mathbf{I}$'
f1_add = '/add_'
f2_add = '_identity'
loop_add = n.logspace(startmode_add,endmode_add,nmodes_add)
# Read files
sense=14419782.9029*2 #/ n.sqrt(2) # XXX from plotting one of the "project_#_modes" directories (divide by sqrt(2) for folded case)
#sense=14419782.9029*2 # unfolded version
PS_i_up = []
PS_f_up = []
PS_i = []
PS_f = []
k_ind = -3
# Read in range of projected eigenmodes
for mode_num in loop:
filename = path + f1 + str(mode_num) + f2
print 'Reading', filename
print mode_num
f = n.load(filename+'/pspec_final_sep0,1_full.npz')
#kpl = f['kpl_fold'] # folded version
kpl = f['kpl'] # unfolded version
k = kpl[k_ind]
#PS_i_up.append(2*n.array(f['pCv_fold_err_old'])[k_ind]) # folded version
#PS_f_up.append(2*n.array(f['pCv_fold_err'])[k_ind])
#PS_i.append(n.abs(f['pCv_fold_old'])[k_ind])
#PS_f.append(n.abs(f['pCv_fold'])[k_ind])
PS_i_up.append(2*n.array(f['pCv_err_old'])[k_ind]) # unfolded version
PS_f_up.append(2*n.array(f['pCv_err'])[k_ind])
PS_i.append(n.abs(f['pCv_old'])[k_ind])
PS_f.append(n.abs(f['pCv'])[k_ind])
# Read in added identity case as a second curve being plotted
PS_i_up_add = []
PS_f_up_add = []
PS_i_add = []
PS_f_add = []
for mode_num in loop_add:
filename = path_add + f1_add + str(mode_num) + f2_add
print 'Reading', filename
print mode_num
f = n.load(filename + '/pspec_final_sep0,1_full.npz')
#kpl = f['kpl_fold'] # folded version
kpl = f['kpl']
k = kpl[k_ind]
#PS_i_up_add.append(2*n.array(f['pCv_fold_err_old'])[k_ind]) # folded version
#PS_f_up_add.append(2*n.array(f['pCv_fold_err'])[k_ind])
#PS_i_add.append(n.abs(f['pCv_fold_old'])[k_ind])
#PS_f_add.append(n.abs(f['pCv_fold'])[k_ind])
PS_i_up_add.append(2*n.array(f['pCv_err_old'])[k_ind]) # unfolded version
PS_f_up_add.append(2*n.array(f['pCv_err'])[k_ind])
PS_i_add.append(n.abs(f['pCv_old'])[k_ind])
PS_f_add.append(n.abs(f['pCv'])[k_ind])
"""
# Theory from Switzer et al. - first term only
fixmode = 3 # start fix at 3rd mode since first few modes are dominated by systematics
xs = n.arange(fixmode,nmodes,1.) # number of modes removed
err_theory_firstterm = 1./(1 - xs/nmodes)
normalization = PS_f_up[fixmode]/err_theory_firstterm[0]
err_theory_firstterm = err_theory_firstterm*normalization
# Fit N_ind (number of independent modes) in second term
def func(mode_num, N_ind):
fit = 1./((1-mode_num/nmodes)*(1-mode_num/N_ind))*PS_f_up[fixmode]
normalization = PS_f_up[fixmode]/fit[0]
return fit*normalization
N_ind,_ = curve_fit(func, xs, PS_f_up[fixmode:], bounds=(0,1000))
err_theory_fit = 1./((1 - xs/nmodes)*(1 - xs/N_ind))
normalization = PS_f_up[fixmode]/err_theory_fit[0]
err_theory_fit = err_theory_fit*normalization
print "Fit for number of independent modes =", N_ind
# Force fit for full equation
if True:
N_ind = 15
err_theory_fit = 1./((1 - xs/nmodes)*(1 - xs/N_ind))
normalization = PS_f_up[fixmode]/err_theory_fit[0]
err_theory_fit = err_theory_fit*normalization
"""
# Best PS (Identity Mult)
f = n.load('plot_sigloss_modeloop_identitymult.npz')
#ps_mult = n.abs(f['pCv'][k_ind]) + 2*f['pCv_err'][k_ind] # point + 2err
#ps_mult = 2*f['pCv_fold_err'][k_ind] # 2sigma upper limit
ps_mult = 2*f['pCv_err'][k_ind] # unfolded case
# Plot
p.figure(figsize=(8,10))
p.subplot(211)
# plot before/after for # eigenmodes down-weighted
p.plot(loop, n.array(PS_i) + n.array(PS_i_up), color='red', linestyle='--', linewidth=2, label='Pre-signal loss estimation')
p.plot(loop, n.array(PS_f_up), 'r-', linewidth=2, label='Post-signal loss estimation')
p.xlim(loop[0], loop[-1])
# plot unweighted
#p.axhline(f['pIv_old'][k_ind]+2*f['pIv_err_old'][k_ind],color='b',linestyle='-',linewidth=2)
#p.axhline(2*f['pIv_fold_err'][k_ind],color='b',linestyle='-',linewidth=2)
p.axhline(2*f['pIv_err'][k_ind],color='b',linestyle='-',linewidth=2)
# plot inverse variance
p.axhline(ps_mult,color='k',linestyle='-',linewidth=2)
# plot analytic
p.axhline(sense,color='g',linestyle='-',linewidth=2)
p.xlabel(xlabel,fontsize=14)
p.ylabel('$P(k)$ [mK$^{2}$($h^{-1}$ Mpc)$^{3}$]',fontsize=16)
p.ylim(1e5,1e11)
p.legend(prop={'size':12}, loc=2, numpoints=1)
p.tick_params(axis='both', which='major', labelsize=12)
p.yscale('log')
p.grid()
p.title('k = ' +str(round(k,3)) + ' $h$ Mpc$^{-1}$')
p.subplot(212)
# plot before/after for added identity
p.plot(loop_add, n.array(PS_i_add) + n.array(PS_i_up_add), color='red', linewidth=2, linestyle='--', label='Pre-signal loss estimation')
p.plot(loop_add, n.array(PS_f_up_add), color='r', linewidth=2, linestyle='-', label='Post-signal loss estimation')
p.xlim(loop_add[0], loop_add[-1])
p.gca().invert_xaxis()
# plot unweighted
#p.axhline(f['pIv_old'][k_ind]+2*f['pIv_err_old'][k_ind],color='b',linestyle='-',linewidth=2,label='Uniform weighting')
#p.axhline(2*f['pIv_fold_err'][k_ind],color='b',linestyle='-',linewidth=2,label='Uniform weighting')
p.axhline(2*f['pIv_err'][k_ind],color='b',linestyle='-',linewidth=2,label='Uniform weighting')
# plot inverse variance
p.axhline(ps_mult,color='k',linestyle='-',linewidth=2,label='$\hat{C} = \hat{C} \circ I$')
# plot analytic
p.axhline(sense,color='g',linestyle='-',linewidth=2,label='Analytical $2\sigma$ Error')
# plot theory
#p.plot(n.arange(fixmode,nmodes,1), err_theory_firstterm, 'b--', label='Theory from Switzer et al., only frequency modes')
#p.plot(n.arange(fixmode,nmodes,1), err_theory_fit, 'b-', label='Theory from Switzer et al., both frequency and time modes')
p.xlabel(xlabel_add,fontsize=14)
p.ylabel('$P(k)$ [mK$^{2}$($h^{-1}$ Mpc)$^{3}$]',fontsize=16)
p.legend(prop={'size':12}, loc=2, numpoints=1, ncol=2)
p.tick_params(axis='both', which='major', labelsize=12)
p.yscale('log')
p.xscale('log')
p.ylim(1e5,1e11)
p.grid()
p.subplots_adjust(hspace=0.3)
#p.tight_layout()
p.show()
| [
"[email protected]"
] | |
7c851f6cf3c45e4effa984c2a42fc8551f5c800e | a40950330ea44c2721f35aeeab8f3a0a11846b68 | /INTERACTIONS_V1/INTERACTION2/AppSBC/UI/UI.py | d3fdd88cbfb7142e29190f9222894fe2a9977d87 | [] | no_license | huang443765159/kai | 7726bcad4e204629edb453aeabcc97242af7132b | 0d66ae4da5a6973e24e1e512fd0df32335e710c5 | refs/heads/master | 2023-03-06T23:13:59.600011 | 2023-03-04T06:14:12 | 2023-03-04T06:14:12 | 233,500,005 | 3 | 1 | null | null | null | null | UTF-8 | Python | false | false | 35,377 | py | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'UI.ui'
#
# Created by: PyQt5 UI code generator 5.15.0
#
# WARNING: Any manual changes made to this file will be lost when pyuic5 is
# run again. Do not edit this file unless you know what you are doing.
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_SBC(object):
def setupUi(self, SBC):
SBC.setObjectName("SBC")
SBC.resize(395, 602)
self.SBC_2 = QtWidgets.QWidget(SBC)
self.SBC_2.setObjectName("SBC_2")
self.tab_device = QtWidgets.QTabWidget(self.SBC_2)
self.tab_device.setGeometry(QtCore.QRect(10, 20, 371, 91))
self.tab_device.setTabPosition(QtWidgets.QTabWidget.West)
self.tab_device.setTabShape(QtWidgets.QTabWidget.Triangular)
self.tab_device.setElideMode(QtCore.Qt.ElideLeft)
self.tab_device.setObjectName("tab_device")
self.device = QtWidgets.QWidget()
self.device.setObjectName("device")
self.label_pump_station = QtWidgets.QLabel(self.device)
self.label_pump_station.setGeometry(QtCore.QRect(0, 20, 91, 14))
self.label_pump_station.setMinimumSize(QtCore.QSize(0, 14))
self.label_pump_station.setMaximumSize(QtCore.QSize(16777215, 14))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(False)
font.setWeight(50)
self.label_pump_station.setFont(font)
self.label_pump_station.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
self.label_pump_station.setObjectName("label_pump_station")
self.ip_local = QtWidgets.QLabel(self.device)
self.ip_local.setGeometry(QtCore.QRect(180, 20, 150, 14))
self.ip_local.setMinimumSize(QtCore.QSize(75, 14))
self.ip_local.setMaximumSize(QtCore.QSize(150, 14))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(False)
font.setWeight(50)
self.ip_local.setFont(font)
self.ip_local.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
self.ip_local.setObjectName("ip_local")
self.ip_nuc = QtWidgets.QLabel(self.device)
self.ip_nuc.setGeometry(QtCore.QRect(180, 50, 160, 14))
self.ip_nuc.setMinimumSize(QtCore.QSize(160, 14))
self.ip_nuc.setMaximumSize(QtCore.QSize(170, 14))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(False)
font.setWeight(50)
self.ip_nuc.setFont(font)
self.ip_nuc.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
self.ip_nuc.setObjectName("ip_nuc")
self.led_pump_station = QtWidgets.QToolButton(self.device)
self.led_pump_station.setGeometry(QtCore.QRect(100, 20, 50, 14))
self.led_pump_station.setMinimumSize(QtCore.QSize(50, 0))
self.led_pump_station.setMaximumSize(QtCore.QSize(50, 14))
font = QtGui.QFont()
font.setPointSize(8)
self.led_pump_station.setFont(font)
self.led_pump_station.setToolTip("")
self.led_pump_station.setToolTipDuration(-1)
self.led_pump_station.setObjectName("led_pump_station")
self.label_guides = QtWidgets.QLabel(self.device)
self.label_guides.setGeometry(QtCore.QRect(0, 50, 91, 14))
self.label_guides.setMinimumSize(QtCore.QSize(0, 14))
self.label_guides.setMaximumSize(QtCore.QSize(16777215, 14))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(False)
font.setWeight(50)
self.label_guides.setFont(font)
self.label_guides.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
self.label_guides.setObjectName("label_guides")
self.led_guides = QtWidgets.QToolButton(self.device)
self.led_guides.setGeometry(QtCore.QRect(100, 50, 50, 14))
self.led_guides.setMinimumSize(QtCore.QSize(50, 0))
self.led_guides.setMaximumSize(QtCore.QSize(50, 14))
font = QtGui.QFont()
font.setPointSize(8)
self.led_guides.setFont(font)
self.led_guides.setToolTip("")
self.led_guides.setToolTipDuration(-1)
self.led_guides.setObjectName("led_guides")
self.tab_device.addTab(self.device, "")
self.tab_device_2 = QtWidgets.QTabWidget(self.SBC_2)
self.tab_device_2.setGeometry(QtCore.QRect(10, 120, 371, 111))
self.tab_device_2.setTabPosition(QtWidgets.QTabWidget.West)
self.tab_device_2.setTabShape(QtWidgets.QTabWidget.Triangular)
self.tab_device_2.setElideMode(QtCore.Qt.ElideLeft)
self.tab_device_2.setObjectName("tab_device_2")
self.device_2 = QtWidgets.QWidget()
self.device_2.setObjectName("device_2")
self.gridLayoutWidget_4 = QtWidgets.QWidget(self.device_2)
self.gridLayoutWidget_4.setGeometry(QtCore.QRect(-10, 20, 361, 40))
self.gridLayoutWidget_4.setObjectName("gridLayoutWidget_4")
self.gridLayout_4 = QtWidgets.QGridLayout(self.gridLayoutWidget_4)
self.gridLayout_4.setContentsMargins(0, 0, 0, 0)
self.gridLayout_4.setObjectName("gridLayout_4")
self.ui_stage_show = QtWidgets.QLineEdit(self.gridLayoutWidget_4)
self.ui_stage_show.setMaximumSize(QtCore.QSize(250, 14))
font = QtGui.QFont()
font.setPointSize(9)
self.ui_stage_show.setFont(font)
self.ui_stage_show.setObjectName("ui_stage_show")
self.gridLayout_4.addWidget(self.ui_stage_show, 0, 1, 1, 1)
self.label_stage_show = QtWidgets.QLabel(self.gridLayoutWidget_4)
self.label_stage_show.setMinimumSize(QtCore.QSize(0, 14))
self.label_stage_show.setMaximumSize(QtCore.QSize(70, 14))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(False)
font.setWeight(50)
self.label_stage_show.setFont(font)
self.label_stage_show.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
self.label_stage_show.setObjectName("label_stage_show")
self.gridLayout_4.addWidget(self.label_stage_show, 0, 0, 1, 1)
self.label_stage_show_btn = QtWidgets.QLabel(self.gridLayoutWidget_4)
self.label_stage_show_btn.setMinimumSize(QtCore.QSize(0, 14))
self.label_stage_show_btn.setMaximumSize(QtCore.QSize(70, 14))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(False)
font.setWeight(50)
self.label_stage_show_btn.setFont(font)
self.label_stage_show_btn.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
self.label_stage_show_btn.setObjectName("label_stage_show_btn")
self.gridLayout_4.addWidget(self.label_stage_show_btn, 1, 0, 1, 1)
self.btn_welcome = QtWidgets.QPushButton(self.device_2)
self.btn_welcome.setGeometry(QtCore.QRect(10, 60, 80, 20))
self.btn_welcome.setMaximumSize(QtCore.QSize(80, 25))
font = QtGui.QFont()
font.setPointSize(9)
self.btn_welcome.setFont(font)
self.btn_welcome.setObjectName("btn_welcome")
self.btn_forward = QtWidgets.QPushButton(self.device_2)
self.btn_forward.setGeometry(QtCore.QRect(120, 60, 80, 20))
self.btn_forward.setMaximumSize(QtCore.QSize(80, 25))
font = QtGui.QFont()
font.setPointSize(9)
self.btn_forward.setFont(font)
self.btn_forward.setObjectName("btn_forward")
self.btn_stop_forward = QtWidgets.QPushButton(self.device_2)
self.btn_stop_forward.setGeometry(QtCore.QRect(230, 60, 80, 20))
self.btn_stop_forward.setMaximumSize(QtCore.QSize(80, 25))
font = QtGui.QFont()
font.setPointSize(9)
self.btn_stop_forward.setFont(font)
self.btn_stop_forward.setObjectName("btn_stop_forward")
self.btn_back_driving = QtWidgets.QPushButton(self.device_2)
self.btn_back_driving.setGeometry(QtCore.QRect(10, 80, 80, 20))
self.btn_back_driving.setMaximumSize(QtCore.QSize(80, 25))
font = QtGui.QFont()
font.setPointSize(9)
self.btn_back_driving.setFont(font)
self.btn_back_driving.setObjectName("btn_back_driving")
self.btn_washing = QtWidgets.QPushButton(self.device_2)
self.btn_washing.setGeometry(QtCore.QRect(120, 80, 80, 20))
self.btn_washing.setMaximumSize(QtCore.QSize(80, 25))
font = QtGui.QFont()
font.setPointSize(9)
self.btn_washing.setFont(font)
self.btn_washing.setObjectName("btn_washing")
self.btn_washing_end = QtWidgets.QPushButton(self.device_2)
self.btn_washing_end.setGeometry(QtCore.QRect(230, 80, 80, 20))
self.btn_washing_end.setMaximumSize(QtCore.QSize(80, 25))
font = QtGui.QFont()
font.setPointSize(9)
self.btn_washing_end.setFont(font)
self.btn_washing_end.setObjectName("btn_washing_end")
self.gridLayoutWidget_2 = QtWidgets.QWidget(self.device_2)
self.gridLayoutWidget_2.setGeometry(QtCore.QRect(0, 0, 341, 17))
self.gridLayoutWidget_2.setObjectName("gridLayoutWidget_2")
self.gridLayout_2 = QtWidgets.QGridLayout(self.gridLayoutWidget_2)
self.gridLayout_2.setContentsMargins(0, 0, 0, 0)
self.gridLayout_2.setObjectName("gridLayout_2")
self.ui_guides_data1 = QtWidgets.QLineEdit(self.gridLayoutWidget_2)
self.ui_guides_data1.setMaximumSize(QtCore.QSize(16777215, 15))
font = QtGui.QFont()
font.setPointSize(9)
self.ui_guides_data1.setFont(font)
self.ui_guides_data1.setObjectName("ui_guides_data1")
self.gridLayout_2.addWidget(self.ui_guides_data1, 0, 1, 1, 1)
self.label_guides_2 = QtWidgets.QLabel(self.gridLayoutWidget_2)
self.label_guides_2.setMinimumSize(QtCore.QSize(0, 14))
self.label_guides_2.setMaximumSize(QtCore.QSize(16777215, 14))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(False)
font.setWeight(50)
self.label_guides_2.setFont(font)
self.label_guides_2.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
self.label_guides_2.setObjectName("label_guides_2")
self.gridLayout_2.addWidget(self.label_guides_2, 0, 0, 1, 1)
self.ui_guides_data2 = QtWidgets.QLineEdit(self.gridLayoutWidget_2)
self.ui_guides_data2.setMaximumSize(QtCore.QSize(16777215, 15))
font = QtGui.QFont()
font.setPointSize(9)
self.ui_guides_data2.setFont(font)
self.ui_guides_data2.setObjectName("ui_guides_data2")
self.gridLayout_2.addWidget(self.ui_guides_data2, 0, 2, 1, 1)
self.tab_device_2.addTab(self.device_2, "")
self.tab_pumps_station = QtWidgets.QTabWidget(self.SBC_2)
self.tab_pumps_station.setGeometry(QtCore.QRect(10, 370, 371, 221))
self.tab_pumps_station.setTabPosition(QtWidgets.QTabWidget.West)
self.tab_pumps_station.setTabShape(QtWidgets.QTabWidget.Triangular)
self.tab_pumps_station.setElideMode(QtCore.Qt.ElideLeft)
self.tab_pumps_station.setObjectName("tab_pumps_station")
self.device_3 = QtWidgets.QWidget()
self.device_3.setObjectName("device_3")
self.gridLayoutWidget = QtWidgets.QWidget(self.device_3)
self.gridLayoutWidget.setGeometry(QtCore.QRect(10, 10, 321, 17))
self.gridLayoutWidget.setObjectName("gridLayoutWidget")
self.gridLayout = QtWidgets.QGridLayout(self.gridLayoutWidget)
self.gridLayout.setContentsMargins(0, 0, 0, 0)
self.gridLayout.setObjectName("gridLayout")
self.ui_drain_data1 = QtWidgets.QLineEdit(self.gridLayoutWidget)
self.ui_drain_data1.setMaximumSize(QtCore.QSize(16777215, 15))
font = QtGui.QFont()
font.setPointSize(9)
self.ui_drain_data1.setFont(font)
self.ui_drain_data1.setObjectName("ui_drain_data1")
self.gridLayout.addWidget(self.ui_drain_data1, 0, 1, 1, 1)
self.DRAIN = QtWidgets.QLabel(self.gridLayoutWidget)
self.DRAIN.setMinimumSize(QtCore.QSize(0, 14))
self.DRAIN.setMaximumSize(QtCore.QSize(16777215, 14))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(False)
font.setWeight(50)
self.DRAIN.setFont(font)
self.DRAIN.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
self.DRAIN.setObjectName("DRAIN")
self.gridLayout.addWidget(self.DRAIN, 0, 0, 1, 1)
self.ui_drain_data2 = QtWidgets.QLineEdit(self.gridLayoutWidget)
self.ui_drain_data2.setMaximumSize(QtCore.QSize(16777215, 15))
font = QtGui.QFont()
font.setPointSize(9)
self.ui_drain_data2.setFont(font)
self.ui_drain_data2.setObjectName("ui_drain_data2")
self.gridLayout.addWidget(self.ui_drain_data2, 0, 2, 1, 1)
self.gridLayoutWidget_3 = QtWidgets.QWidget(self.device_3)
self.gridLayoutWidget_3.setGeometry(QtCore.QRect(10, 40, 321, 173))
self.gridLayoutWidget_3.setObjectName("gridLayoutWidget_3")
self.gridLayout_3 = QtWidgets.QGridLayout(self.gridLayoutWidget_3)
self.gridLayout_3.setContentsMargins(0, 0, 0, 0)
self.gridLayout_3.setObjectName("gridLayout_3")
self.ui_wheel_data = QtWidgets.QLineEdit(self.gridLayoutWidget_3)
self.ui_wheel_data.setMaximumSize(QtCore.QSize(35, 15))
font = QtGui.QFont()
font.setPointSize(9)
self.ui_wheel_data.setFont(font)
self.ui_wheel_data.setObjectName("ui_wheel_data")
self.gridLayout_3.addWidget(self.ui_wheel_data, 4, 1, 1, 1)
self.DRAIN_6 = QtWidgets.QLabel(self.gridLayoutWidget_3)
self.DRAIN_6.setMinimumSize(QtCore.QSize(0, 14))
self.DRAIN_6.setMaximumSize(QtCore.QSize(25, 14))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(False)
font.setWeight(50)
self.DRAIN_6.setFont(font)
self.DRAIN_6.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
self.DRAIN_6.setObjectName("DRAIN_6")
self.gridLayout_3.addWidget(self.DRAIN_6, 2, 2, 1, 1)
self.DRAIN_10 = QtWidgets.QLabel(self.gridLayoutWidget_3)
self.DRAIN_10.setMinimumSize(QtCore.QSize(0, 14))
self.DRAIN_10.setMaximumSize(QtCore.QSize(25, 14))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(False)
font.setWeight(50)
self.DRAIN_10.setFont(font)
self.DRAIN_10.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
self.DRAIN_10.setObjectName("DRAIN_10")
self.gridLayout_3.addWidget(self.DRAIN_10, 4, 2, 1, 1)
self.ui_acid_data = QtWidgets.QLineEdit(self.gridLayoutWidget_3)
self.ui_acid_data.setMaximumSize(QtCore.QSize(35, 15))
font = QtGui.QFont()
font.setPointSize(9)
self.ui_acid_data.setFont(font)
self.ui_acid_data.setObjectName("ui_acid_data")
self.gridLayout_3.addWidget(self.ui_acid_data, 3, 1, 1, 1)
self.ui_alkali_data = QtWidgets.QLineEdit(self.gridLayoutWidget_3)
self.ui_alkali_data.setMaximumSize(QtCore.QSize(35, 15))
font = QtGui.QFont()
font.setPointSize(9)
self.ui_alkali_data.setFont(font)
self.ui_alkali_data.setObjectName("ui_alkali_data")
self.gridLayout_3.addWidget(self.ui_alkali_data, 2, 1, 1, 1)
self.DRAIN_4 = QtWidgets.QLabel(self.gridLayoutWidget_3)
self.DRAIN_4.setMinimumSize(QtCore.QSize(0, 14))
self.DRAIN_4.setMaximumSize(QtCore.QSize(25, 14))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(False)
font.setWeight(50)
self.DRAIN_4.setFont(font)
self.DRAIN_4.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
self.DRAIN_4.setObjectName("DRAIN_4")
self.gridLayout_3.addWidget(self.DRAIN_4, 1, 2, 1, 1)
self.DRAIN_8 = QtWidgets.QLabel(self.gridLayoutWidget_3)
self.DRAIN_8.setMinimumSize(QtCore.QSize(0, 14))
self.DRAIN_8.setMaximumSize(QtCore.QSize(25, 14))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(False)
font.setWeight(50)
self.DRAIN_8.setFont(font)
self.DRAIN_8.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
self.DRAIN_8.setObjectName("DRAIN_8")
self.gridLayout_3.addWidget(self.DRAIN_8, 3, 2, 1, 1)
self.label_chem = QtWidgets.QLabel(self.gridLayoutWidget_3)
self.label_chem.setMinimumSize(QtCore.QSize(0, 14))
self.label_chem.setMaximumSize(QtCore.QSize(40, 14))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(False)
font.setWeight(50)
self.label_chem.setFont(font)
self.label_chem.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
self.label_chem.setObjectName("label_chem")
self.gridLayout_3.addWidget(self.label_chem, 0, 0, 1, 1)
self.ui_wax_data = QtWidgets.QLineEdit(self.gridLayoutWidget_3)
self.ui_wax_data.setMaximumSize(QtCore.QSize(35, 15))
font = QtGui.QFont()
font.setPointSize(9)
self.ui_wax_data.setFont(font)
self.ui_wax_data.setObjectName("ui_wax_data")
self.gridLayout_3.addWidget(self.ui_wax_data, 5, 1, 1, 1)
self.label_wheel_data = QtWidgets.QLabel(self.gridLayoutWidget_3)
self.label_wheel_data.setMinimumSize(QtCore.QSize(0, 14))
self.label_wheel_data.setMaximumSize(QtCore.QSize(40, 14))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(False)
font.setWeight(50)
self.label_wheel_data.setFont(font)
self.label_wheel_data.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
self.label_wheel_data.setObjectName("label_wheel_data")
self.gridLayout_3.addWidget(self.label_wheel_data, 4, 0, 1, 1)
self.label_wax_data = QtWidgets.QLabel(self.gridLayoutWidget_3)
self.label_wax_data.setMinimumSize(QtCore.QSize(0, 14))
self.label_wax_data.setMaximumSize(QtCore.QSize(40, 14))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(False)
font.setWeight(50)
self.label_wax_data.setFont(font)
self.label_wax_data.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
self.label_wax_data.setObjectName("label_wax_data")
self.gridLayout_3.addWidget(self.label_wax_data, 5, 0, 1, 1)
self.label_acid_data = QtWidgets.QLabel(self.gridLayoutWidget_3)
self.label_acid_data.setMinimumSize(QtCore.QSize(0, 14))
self.label_acid_data.setMaximumSize(QtCore.QSize(40, 14))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(False)
font.setWeight(50)
self.label_acid_data.setFont(font)
self.label_acid_data.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
self.label_acid_data.setObjectName("label_acid_data")
self.gridLayout_3.addWidget(self.label_acid_data, 3, 0, 1, 1)
self.label_water_data = QtWidgets.QLabel(self.gridLayoutWidget_3)
self.label_water_data.setMinimumSize(QtCore.QSize(0, 14))
self.label_water_data.setMaximumSize(QtCore.QSize(40, 14))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(False)
font.setWeight(50)
self.label_water_data.setFont(font)
self.label_water_data.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
self.label_water_data.setObjectName("label_water_data")
self.gridLayout_3.addWidget(self.label_water_data, 1, 0, 1, 1)
self.label_alkali_data = QtWidgets.QLabel(self.gridLayoutWidget_3)
self.label_alkali_data.setMinimumSize(QtCore.QSize(0, 14))
self.label_alkali_data.setMaximumSize(QtCore.QSize(40, 14))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(False)
font.setWeight(50)
self.label_alkali_data.setFont(font)
self.label_alkali_data.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
self.label_alkali_data.setObjectName("label_alkali_data")
self.gridLayout_3.addWidget(self.label_alkali_data, 2, 0, 1, 1)
self.ui_water_data = QtWidgets.QLineEdit(self.gridLayoutWidget_3)
self.ui_water_data.setMaximumSize(QtCore.QSize(35, 15))
font = QtGui.QFont()
font.setPointSize(9)
self.ui_water_data.setFont(font)
self.ui_water_data.setObjectName("ui_water_data")
self.gridLayout_3.addWidget(self.ui_water_data, 1, 1, 1, 1)
self.DRAIN_12 = QtWidgets.QLabel(self.gridLayoutWidget_3)
self.DRAIN_12.setMinimumSize(QtCore.QSize(0, 14))
self.DRAIN_12.setMaximumSize(QtCore.QSize(25, 14))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(False)
font.setWeight(50)
self.DRAIN_12.setFont(font)
self.DRAIN_12.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
self.DRAIN_12.setObjectName("DRAIN_12")
self.gridLayout_3.addWidget(self.DRAIN_12, 5, 2, 1, 1)
self.led_water = QtWidgets.QToolButton(self.gridLayoutWidget_3)
self.led_water.setMaximumSize(QtCore.QSize(150, 15))
font = QtGui.QFont()
font.setPointSize(9)
self.led_water.setFont(font)
self.led_water.setObjectName("led_water")
self.gridLayout_3.addWidget(self.led_water, 1, 3, 1, 1)
self.led_alkali = QtWidgets.QToolButton(self.gridLayoutWidget_3)
self.led_alkali.setMaximumSize(QtCore.QSize(150, 15))
font = QtGui.QFont()
font.setPointSize(9)
self.led_alkali.setFont(font)
self.led_alkali.setObjectName("led_alkali")
self.gridLayout_3.addWidget(self.led_alkali, 2, 3, 1, 1)
self.led_acid = QtWidgets.QToolButton(self.gridLayoutWidget_3)
self.led_acid.setMaximumSize(QtCore.QSize(150, 15))
font = QtGui.QFont()
font.setPointSize(9)
self.led_acid.setFont(font)
self.led_acid.setObjectName("led_acid")
self.gridLayout_3.addWidget(self.led_acid, 3, 3, 1, 1)
self.led_wheel = QtWidgets.QToolButton(self.gridLayoutWidget_3)
self.led_wheel.setMaximumSize(QtCore.QSize(150, 15))
font = QtGui.QFont()
font.setPointSize(9)
self.led_wheel.setFont(font)
self.led_wheel.setObjectName("led_wheel")
self.gridLayout_3.addWidget(self.led_wheel, 4, 3, 1, 1)
self.led_wax = QtWidgets.QToolButton(self.gridLayoutWidget_3)
self.led_wax.setMaximumSize(QtCore.QSize(150, 15))
font = QtGui.QFont()
font.setPointSize(9)
self.led_wax.setFont(font)
self.led_wax.setObjectName("led_wax")
self.gridLayout_3.addWidget(self.led_wax, 5, 3, 1, 1)
self.tab_pumps_station.addTab(self.device_3, "")
self.tab_device_3 = QtWidgets.QTabWidget(self.SBC_2)
self.tab_device_3.setGeometry(QtCore.QRect(10, 230, 371, 141))
self.tab_device_3.setTabPosition(QtWidgets.QTabWidget.West)
self.tab_device_3.setTabShape(QtWidgets.QTabWidget.Triangular)
self.tab_device_3.setElideMode(QtCore.Qt.ElideLeft)
self.tab_device_3.setObjectName("tab_device_3")
self.pumpswitch = QtWidgets.QWidget()
self.pumpswitch.setObjectName("pumpswitch")
self.btn_all_stop = QtWidgets.QCheckBox(self.pumpswitch)
self.btn_all_stop.setGeometry(QtCore.QRect(0, 60, 91, 16))
font = QtGui.QFont()
font.setPointSize(10)
self.btn_all_stop.setFont(font)
self.btn_all_stop.setObjectName("btn_all_stop")
self.btn_high_water = QtWidgets.QCheckBox(self.pumpswitch)
self.btn_high_water.setGeometry(QtCore.QRect(70, 60, 91, 16))
font = QtGui.QFont()
font.setPointSize(10)
self.btn_high_water.setFont(font)
self.btn_high_water.setObjectName("btn_high_water")
self.btn_wheel = QtWidgets.QCheckBox(self.pumpswitch)
self.btn_wheel.setGeometry(QtCore.QRect(170, 60, 71, 16))
font = QtGui.QFont()
font.setPointSize(10)
self.btn_wheel.setFont(font)
self.btn_wheel.setObjectName("btn_wheel")
self.btn_alkali = QtWidgets.QCheckBox(self.pumpswitch)
self.btn_alkali.setGeometry(QtCore.QRect(240, 60, 71, 16))
font = QtGui.QFont()
font.setPointSize(10)
self.btn_alkali.setFont(font)
self.btn_alkali.setObjectName("btn_alkali")
self.btn_acid = QtWidgets.QCheckBox(self.pumpswitch)
self.btn_acid.setGeometry(QtCore.QRect(0, 80, 71, 16))
font = QtGui.QFont()
font.setPointSize(10)
self.btn_acid.setFont(font)
self.btn_acid.setObjectName("btn_acid")
self.btn_water_wax = QtWidgets.QCheckBox(self.pumpswitch)
self.btn_water_wax.setGeometry(QtCore.QRect(70, 80, 91, 16))
font = QtGui.QFont()
font.setPointSize(10)
self.btn_water_wax.setFont(font)
self.btn_water_wax.setObjectName("btn_water_wax")
self.btn_drain = QtWidgets.QCheckBox(self.pumpswitch)
self.btn_drain.setGeometry(QtCore.QRect(170, 80, 91, 16))
font = QtGui.QFont()
font.setPointSize(10)
self.btn_drain.setFont(font)
self.btn_drain.setObjectName("btn_drain")
self.btn_water_inflow = QtWidgets.QCheckBox(self.pumpswitch)
self.btn_water_inflow.setGeometry(QtCore.QRect(240, 80, 101, 16))
font = QtGui.QFont()
font.setPointSize(10)
self.btn_water_inflow.setFont(font)
self.btn_water_inflow.setObjectName("btn_water_inflow")
self.label_pump_1 = QtWidgets.QLabel(self.pumpswitch)
self.label_pump_1.setGeometry(QtCore.QRect(0, 10, 51, 14))
self.label_pump_1.setMinimumSize(QtCore.QSize(0, 14))
self.label_pump_1.setMaximumSize(QtCore.QSize(16777215, 14))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(False)
font.setWeight(50)
self.label_pump_1.setFont(font)
self.label_pump_1.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
self.label_pump_1.setObjectName("label_pump_1")
self.ui_log_pump = QtWidgets.QLineEdit(self.pumpswitch)
self.ui_log_pump.setGeometry(QtCore.QRect(40, 10, 251, 15))
self.ui_log_pump.setMaximumSize(QtCore.QSize(16777215, 15))
font = QtGui.QFont()
font.setPointSize(9)
self.ui_log_pump.setFont(font)
self.ui_log_pump.setText("")
self.ui_log_pump.setObjectName("ui_log_pump")
self.led_high_water = QtWidgets.QToolButton(self.pumpswitch)
self.led_high_water.setGeometry(QtCore.QRect(40, 30, 50, 14))
self.led_high_water.setMinimumSize(QtCore.QSize(50, 0))
self.led_high_water.setMaximumSize(QtCore.QSize(55, 14))
font = QtGui.QFont()
font.setPointSize(8)
self.led_high_water.setFont(font)
self.led_high_water.setToolTip("")
self.led_high_water.setToolTipDuration(-1)
self.led_high_water.setObjectName("led_high_water")
self.led_ch_alkali = QtWidgets.QToolButton(self.pumpswitch)
self.led_ch_alkali.setGeometry(QtCore.QRect(90, 30, 50, 14))
self.led_ch_alkali.setMinimumSize(QtCore.QSize(50, 0))
self.led_ch_alkali.setMaximumSize(QtCore.QSize(55, 14))
font = QtGui.QFont()
font.setPointSize(8)
self.led_ch_alkali.setFont(font)
self.led_ch_alkali.setToolTip("")
self.led_ch_alkali.setToolTipDuration(-1)
self.led_ch_alkali.setObjectName("led_ch_alkali")
self.led_ch_acid = QtWidgets.QToolButton(self.pumpswitch)
self.led_ch_acid.setGeometry(QtCore.QRect(140, 30, 50, 14))
self.led_ch_acid.setMinimumSize(QtCore.QSize(50, 0))
self.led_ch_acid.setMaximumSize(QtCore.QSize(55, 14))
font = QtGui.QFont()
font.setPointSize(8)
self.led_ch_acid.setFont(font)
self.led_ch_acid.setToolTip("")
self.led_ch_acid.setToolTipDuration(-1)
self.led_ch_acid.setObjectName("led_ch_acid")
self.led_ch1_wheel = QtWidgets.QToolButton(self.pumpswitch)
self.led_ch1_wheel.setGeometry(QtCore.QRect(190, 30, 50, 14))
self.led_ch1_wheel.setMinimumSize(QtCore.QSize(50, 0))
self.led_ch1_wheel.setMaximumSize(QtCore.QSize(55, 14))
font = QtGui.QFont()
font.setPointSize(8)
self.led_ch1_wheel.setFont(font)
self.led_ch1_wheel.setToolTip("")
self.led_ch1_wheel.setToolTipDuration(-1)
self.led_ch1_wheel.setObjectName("led_ch1_wheel")
self.led_ch1_wax = QtWidgets.QToolButton(self.pumpswitch)
self.led_ch1_wax.setGeometry(QtCore.QRect(240, 30, 50, 14))
self.led_ch1_wax.setMinimumSize(QtCore.QSize(50, 0))
self.led_ch1_wax.setMaximumSize(QtCore.QSize(55, 14))
font = QtGui.QFont()
font.setPointSize(8)
self.led_ch1_wax.setFont(font)
self.led_ch1_wax.setToolTip("")
self.led_ch1_wax.setToolTipDuration(-1)
self.led_ch1_wax.setObjectName("led_ch1_wax")
self.label_pump_2 = QtWidgets.QLabel(self.pumpswitch)
self.label_pump_2.setGeometry(QtCore.QRect(10, 110, 51, 14))
self.label_pump_2.setMinimumSize(QtCore.QSize(0, 14))
self.label_pump_2.setMaximumSize(QtCore.QSize(16777215, 14))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(False)
font.setWeight(50)
self.label_pump_2.setFont(font)
self.label_pump_2.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
self.label_pump_2.setObjectName("label_pump_2")
self.ui_log_pump_countdown = QtWidgets.QLineEdit(self.pumpswitch)
self.ui_log_pump_countdown.setGeometry(QtCore.QRect(50, 110, 121, 15))
self.ui_log_pump_countdown.setMaximumSize(QtCore.QSize(16777215, 15))
font = QtGui.QFont()
font.setPointSize(9)
self.ui_log_pump_countdown.setFont(font)
self.ui_log_pump_countdown.setText("")
self.ui_log_pump_countdown.setObjectName("ui_log_pump_countdown")
self.label_pump_3 = QtWidgets.QLabel(self.pumpswitch)
self.label_pump_3.setGeometry(QtCore.QRect(190, 110, 71, 14))
self.label_pump_3.setMinimumSize(QtCore.QSize(0, 14))
self.label_pump_3.setMaximumSize(QtCore.QSize(16777215, 14))
font = QtGui.QFont()
font.setPointSize(10)
font.setBold(False)
font.setWeight(50)
self.label_pump_3.setFont(font)
self.label_pump_3.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
self.label_pump_3.setObjectName("label_pump_3")
self.pump_countdown_box = QtWidgets.QSpinBox(self.pumpswitch)
self.pump_countdown_box.setGeometry(QtCore.QRect(260, 110, 48, 16))
font = QtGui.QFont()
font.setPointSize(10)
self.pump_countdown_box.setFont(font)
self.pump_countdown_box.setObjectName("pump_countdown_box")
self.tab_device_3.addTab(self.pumpswitch, "")
SBC.setCentralWidget(self.SBC_2)
self.retranslateUi(SBC)
self.tab_device.setCurrentIndex(0)
self.tab_device_2.setCurrentIndex(0)
self.tab_pumps_station.setCurrentIndex(0)
self.tab_device_3.setCurrentIndex(0)
QtCore.QMetaObject.connectSlotsByName(SBC)
def retranslateUi(self, SBC):
_translate = QtCore.QCoreApplication.translate
SBC.setWindowTitle(_translate("SBC", "SBC"))
self.label_pump_station.setText(_translate("SBC", "PUMP STATION"))
self.ip_local.setText(_translate("SBC", "LocalIP : 0.0.0.0"))
self.ip_nuc.setText(_translate("SBC", "NucIP : 0.0.0.0"))
self.led_pump_station.setText(_translate("SBC", "OFF"))
self.label_guides.setText(_translate("SBC", "GUIDES"))
self.led_guides.setText(_translate("SBC", "OFF"))
self.tab_device.setTabText(self.tab_device.indexOf(self.device), _translate("SBC", "DEVICE"))
self.label_stage_show.setText(_translate("SBC", "STAGE SHOW"))
self.label_stage_show_btn.setText(_translate("SBC", "SHOW BTN"))
self.btn_welcome.setText(_translate("SBC", "欢迎光临"))
self.btn_forward.setText(_translate("SBC", "向前行驶"))
self.btn_stop_forward.setText(_translate("SBC", "停止行驶"))
self.btn_back_driving.setText(_translate("SBC", "向后行驶"))
self.btn_washing.setText(_translate("SBC", "正在清洗"))
self.btn_washing_end.setText(_translate("SBC", "清洗结束"))
self.label_guides_2.setText(_translate("SBC", "GUIDES"))
self.tab_device_2.setTabText(self.tab_device_2.indexOf(self.device_2), _translate("SBC", "GUIDES"))
self.DRAIN.setText(_translate("SBC", "DRAIN"))
self.DRAIN_6.setText(_translate("SBC", "mm"))
self.DRAIN_10.setText(_translate("SBC", "mm"))
self.DRAIN_4.setText(_translate("SBC", "mm"))
self.DRAIN_8.setText(_translate("SBC", "mm"))
self.label_chem.setText(_translate("SBC", "LIQUID"))
self.label_wheel_data.setText(_translate("SBC", "WHEEL"))
self.label_wax_data.setText(_translate("SBC", "WAX"))
self.label_acid_data.setText(_translate("SBC", "ACID"))
self.label_water_data.setText(_translate("SBC", "WATER"))
self.label_alkali_data.setText(_translate("SBC", "ALKALI"))
self.DRAIN_12.setText(_translate("SBC", "mm"))
self.led_water.setText(_translate("SBC", "full"))
self.led_alkali.setText(_translate("SBC", "full"))
self.led_acid.setText(_translate("SBC", "full"))
self.led_wheel.setText(_translate("SBC", "full"))
self.led_wax.setText(_translate("SBC", "full"))
self.tab_pumps_station.setTabText(self.tab_pumps_station.indexOf(self.device_3), _translate("SBC", "PUMPS STATION"))
self.btn_all_stop.setText(_translate("SBC", "ALL STOP"))
self.btn_high_water.setText(_translate("SBC", "HIGH WATER"))
self.btn_wheel.setText(_translate("SBC", "WHEEL"))
self.btn_alkali.setText(_translate("SBC", "ALKALI "))
self.btn_acid.setText(_translate("SBC", "ACID"))
self.btn_water_wax.setText(_translate("SBC", "WATER WAX"))
self.btn_drain.setText(_translate("SBC", "DRAIN"))
self.btn_water_inflow.setText(_translate("SBC", "WATER INFLOW"))
self.label_pump_1.setText(_translate("SBC", "PUMP"))
self.led_high_water.setText(_translate("SBC", "P"))
self.led_ch_alkali.setText(_translate("SBC", "C1"))
self.led_ch_acid.setText(_translate("SBC", "C2"))
self.led_ch1_wheel.setText(_translate("SBC", "WE"))
self.led_ch1_wax.setText(_translate("SBC", "WX"))
self.label_pump_2.setText(_translate("SBC", "PUMP"))
self.label_pump_3.setText(_translate("SBC", "剩余延迟时间"))
self.tab_device_3.setTabText(self.tab_device_3.indexOf(self.pumpswitch), _translate("SBC", "PUMPSWITCH"))
| [
"[email protected]"
] | |
d4ae3c0ec0b6138ccbc71c51af7764f03636fedc | f2bd7e127de1a49407858bfa24e2dacdf8a2159a | /exercises/ex3_1.py | f83e013df042248baedc94da8f381edfa85a83ed | [] | no_license | eddyhuyhp/ThreeCat | 795b808040540fb14773938ccb9d4aca2a1c5d0a | 81d51938ea5080f286decf3011493487e2639713 | refs/heads/master | 2020-03-16T13:31:25.208675 | 2018-05-09T03:19:44 | 2018-05-09T03:19:44 | 132,692,766 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 743 | py | #!/usr/bin/env python3
def solve(input_data):
'''Đầu vào: một số nguyên dương
Đầu ra: số nguyên tạo bởi phần từ số 1 cuối cùng trở về bên
phải - của dạng binary của số đầu vào.
Ví dụ::
input_data = 5 # (0101)
output = 1
input_data = 24 (11000)
output = 1000
input_data = 9 (1001)
output = 1
Hàm có sẵn: bin(10) == '0b1010'
Hàm có sẵn tạo ra integer từ string: 69 == int('69')
'''
result = None
a = bin(input_data)
result = a[len(a)-a[::-1].find('1')-1:len(a)]
return result
def main():
i = input('Nhap vao so nguyen:')
print(solve(int(i)))
if __name__ == "__main__":
main()
| [
"[email protected]"
] | |
4e37a9db4d23fe3b02b8714633e4e1eb463a253b | a67f928aea79cfceca16cb40e62e51dd7e484dd4 | /analysis/analysisLog.py | ad6ade7d698ca4e0aa19a76b6a049ee594142bb2 | [] | no_license | daniyuu/LatticeLSTM | 2b6293d35f8ed674854bda8611d91992fa2fbd59 | 03953e576db12c741e804b1c36aa461696d018b9 | refs/heads/master | 2020-03-22T19:38:56.944213 | 2018-09-14T07:09:47 | 2018-09-14T07:09:47 | 140,542,239 | 2 | 0 | null | 2018-09-14T07:09:49 | 2018-07-11T08:04:15 | Python | UTF-8 | Python | false | false | 3,079 | py | import os
from datetime import date
import pygal
log_folder_path = "./log/"
result_folder_path = "./result/"
if not os.path.exists(result_folder_path):
os.makedirs(result_folder_path)
def analysis_overall(file_name):
logFile = open(log_folder_path + '{0}.txt'.format(file_name), 'r')
y_test_p = []
y_test_r = []
y_test_f = []
y_test_acc = []
for line in logFile.readlines():
if "*** Test: " in line:
items = line.split('; ')
f = float(items[-1].split(': ')[1])
r = float(items[-2].split(': ')[1])
p = float(items[-3].split(': ')[1])
acc = float(items[-4].split(': ')[1])
y_test_f.append(f)
y_test_r.append(r)
y_test_p.append(p)
y_test_acc.append(acc)
line_chart = pygal.Line()
line_chart.title = "Overall performance"
# line_chart.x_labels = x
line_chart.add("acc", y_test_acc)
line_chart.add("p", y_test_p)
line_chart.add("r", y_test_r)
line_chart.add("f", y_test_f)
line_chart.render_to_file(result_folder_path + 'Overall_{0}.svg'.format(file_name))
return y_test_p, y_test_r, y_test_f, y_test_acc
def analysis_acc(file_name):
logFile = open(log_folder_path + '{0}.txt'.format(file_name), 'r')
index = 0
x = []
y_acc = []
for line in logFile.readlines():
if "Instance" in line:
index += 1
acc = line.split('=')[1].split('\n')[0]
x.append(index)
y_acc.append(float(acc))
line_chart = pygal.Line()
line_chart.title = "Acc Performance"
# line_chart.x_labels = x
line_chart.add("Acc", y_acc)
line_chart.render_to_file(result_folder_path + 'Acc_{0}.svg'.format(file_name))
return
def compare_logs(*file_names):
p_chart = pygal.Line()
p_chart.title = "Precious compare"
r_chart = pygal.Line()
r_chart.title = "Recall compare"
f_chart = pygal.Line()
f_chart.title = "F1 Score compare"
acc_chart = pygal.Line()
acc_chart.title = "Acc Score compare"
for file_name in file_names:
p, r, f, acc = analysis_overall(file_name)
acc_chart.add(file_name, acc)
p_chart.add(file_name, p)
r_chart.add(file_name, r)
f_chart.add(file_name, f)
acc_chart.render_to_file(
result_folder_path + 'Compare_{0}_Acc_{1}.svg'.format(date.today().isoformat(), '_'.join(file_names)))
p_chart.render_to_file(
result_folder_path + 'Compare_{0}_P_{1}.svg'.format(date.today().isoformat(), '_'.join(file_names)))
r_chart.render_to_file(
result_folder_path + 'Compare_{0}_R_{1}.svg'.format(date.today().isoformat(), '_'.join(file_names)))
f_chart.render_to_file(
result_folder_path + 'Compare_{0}_F_{1}.svg'.format(date.today().isoformat(), '_'.join(file_names)))
return
def analysis(file_name):
analysis_overall(file_name)
analysis_acc(file_name)
return
#
# analysis('2018-08-10')
# analysis('2018-08-13')
# analysis('2018-08-21')
compare_logs('2018-08-10', '2018-08-24')
| [
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] | |
9b8aae38ac4636bc7486232355f8895685ede2c4 | 042f1fe8d0b89b0df7043af0d37f24ef5508784c | /websphere-traditional/virtual-host.py | d1099de42f1326bdeca2ecc44c1ec019fba1a7b0 | [] | no_license | pdprof/icp4a-helloworld | 2e6eeeb25e665f32d2dc86c03d1a2332501cb847 | 849b4bc07b70fd78c28539326c8df48421b671f2 | refs/heads/master | 2023-08-10T09:21:36.404230 | 2021-09-13T09:41:31 | 2021-09-13T09:41:31 | 319,898,688 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 521 | py | print "set default-host..."
AdminConfig.create('HostAlias', AdminConfig.getid('/Cell:DefaultCell01/VirtualHost:admin_host/'), '[[hostname "twas-admin-route-default.apps-crc.testing"] [port "80"]]')
print "delete *:80..."
AdminConfig.remove('(cells/DefaultCell01|virtualhosts.xml#HostAlias_2)')
print "set admin-host..."
AdminConfig.create('HostAlias', AdminConfig.getid('/Cell:DefaultCell01/VirtualHost:default_host/'), '[[hostname "twas-route-default.apps-crc.testing"] [port "80"]]')
print "save..."
AdminConfig.save()
| [
"[email protected]"
] | |
e5825d77166ea761d10b731b739736acb581c092 | f061602595a78bdbdbf32e2dfdcfe623db5b8efd | /graph/models.py | e48f2ed8c0b90fc6e2e06d8ee764bb75c38b0d6f | [] | no_license | NorbertMichalski/utilities | b9e0643d4b8e0097e0c774d63adbeaa66d3da06b | da27a23add9c42d62ae21a5e74eef920bbd3d839 | refs/heads/master | 2020-05-14T19:04:23.262384 | 2014-01-27T13:45:28 | 2014-01-27T13:45:28 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 7,937 | py | from django.db import models
from django.template.loader import render_to_string
from prices.models import Product, Result
from scrapers import ClickyScraper, RankScraper, OrderScraper, CashScraper
import datetime
# Create your models here.
class OverviewGraph(models.Model):
brand = models.CharField(max_length=50, unique=True)
class Meta:
ordering = ['id']
def __unicode__(self):
return self.brand
def chart(self):
graph_pk = self.pk % 5
if graph_pk == 0:
graph_pk = 5
stats = OverviewStat.objects.filter(graph=graph_pk).order_by('date')
title = self.__unicode__().capitalize() + ' Statistics'
prices = []
ranks = []
all_sales = []
all_visits = []
dates = []
money = []
if 'weekly' in self.brand:
current_week = stats[0].date.isocalendar()[1]
weekly_money, weekly_price, weekly_rank, weekly_visits, weekly_sales = 0, 0, 0, 0, 0
counter = 1
for stat in stats:
week = stat.date.isocalendar()[1]
if week != current_week:
if self.brand == 'All weekly':
money.append(float('%.2f' %weekly_money))
prices.append(float('%.2f' %(weekly_price/counter, )))
ranks.append(float('%.2f' %(weekly_rank/counter, )))
dates.append(stat.get_date())
all_visits.append(weekly_visits)
all_sales.append(weekly_sales)
current_week = week
counter = 1
weekly_money, weekly_price, weekly_rank, weekly_visits, weekly_sales = 0, 0, 0, 0, 0
continue
if self.brand == 'All weekly':
weekly_money += float('%.2f' %(stat.get_money()/10,))
weekly_price += float('%.2f' %(stat.get_price()/10,))
weekly_rank += stat.get_rank()
weekly_visits += stat.get_visits()
weekly_sales += stat.get_sales()
counter += 1
else:
for stat in stats:
if stat.is_weekend():
continue
if self.brand == 'All':
money.append(float('%.2f' %(stat.get_money()/10,)))
prices.append(float('%.2f' %(stat.get_price()/10,)))
ranks.append(stat.get_rank())
dates.append(stat.get_date())
all_visits.append(stat.get_visits())
all_sales.append(stat.get_sales())
data = { 'title' : '"' + title + '"',
'dates' : dates,
'prices' : prices,
'ranks' : ranks,
'sales' : all_sales,
'visits' : all_visits,
'dates' : dates,
'money' : money,
}
return render_to_string('admin/graph/overviewgraph/chart.html', data )
chart.allow_tags = True
def week_chart(self):
stats = OverviewStat.objects.filter(graph=self.pk).order_by('date')
title = self.__unicode__().capitalize() + ' Statistics'
prices = []
ranks = []
all_sales = []
all_visits = []
dates = []
money = []
if 'weekly' in self.brand:
current_week = stats[0].date.isocalendar()[1]
weekly_money, weekly_price, weekly_rank, weekly_visits, weekly_sales = 0, 0, 0, 0, 0
for stat in stats:
week = stat.date.isocalendar()[1]
counter = 1
if week != current_week:
if 'All' in self.brand:
money.append(weekly_money)
prices.append(float('%.2f' %(weekly_price/counter, )))
ranks.append(float('%.2f' %(weekly_rank/counter, )))
dates.append(stat.get_date())
all_visits.append(weekly_visits)
all_sales.append(weekly_sales)
current_week = week
counter = 1
weekly_money, weekly_price, weekly_rank, weekly_visits, weekly_sales = 0, 0, 0, 0, 0
if 'All' in self.brand:
weekly_money += float('%.2f' %(stat.get_money()/10,))
weekly_price = float('%.2f' %(stat.get_price()/10,))
weekly_rank += stat.get_rank()
weekly_visits += stat.get_visits()
weekly_sales = stat.get_sales()
data = { 'title' : '"' + title + '"',
'dates' : dates,
'prices' : prices,
'ranks' : ranks,
'sales' : all_sales,
'visits' : all_visits,
'dates' : dates,
'money' : money,
}
return render_to_string('admin/graph/overviewgraph/chart.html', data )
week_chart.allow_tags = True
class OverviewStat(models.Model):
graph = models.ForeignKey(OverviewGraph)
price = models.DecimalField(max_digits=6, decimal_places=2, default=0)
rank = models.DecimalField(max_digits=5, decimal_places=2, default=0)
visits = models.IntegerField(default=0)
sales = models.IntegerField(default=0)
money = models.DecimalField(max_digits=9, decimal_places=2, default=0)
date = models.DateField('date last updated', default=datetime.date.today)
class Meta:
unique_together = ("graph", "date")
def get_price(self):
return float(self.price)
def get_rank(self):
return float(self.rank)
def get_date(self):
return self.date.strftime("%Y-%m-%d")
def is_weekend(self):
if self.date.weekday()==5 or self.date.weekday()==6:
return True
return False
def get_sales(self):
return int(self.sales)
def get_visits(self):
return int(self.visits)
def get_money(self):
return float(self.money)
def __unicode__(self):
return self.get_date() + ' ' + str(self.graph)
def update_price(self):
brand_name = self.graph.brand.lower()
if brand_name == 'all':
all_products = Product.objects.all().count()
cheaper_results = Product.objects.all().filter(is_cheaper=True).count()
else:
all_products = Product.objects.filter(brand__name=brand_name).count()
cheaper_results = Product.objects.filter(brand__name=brand_name,
is_cheaper=True).count()
ratio = 100 - float(cheaper_results)/float(all_products) * 100
print 'market share', brand_name, ratio
self.price = '%.2f' %ratio
def update_visits(self, date=datetime.date.today()):
brand_name = self.graph.brand.lower()
scraper = ClickyScraper()
visits = scraper.brand_visits(brand_name, date)
print 'visits', brand_name, visits
self.visits = visits
def update_rank(self, date=datetime.date.today()):
brand_name = self.graph.brand.lower()
scraper = RankScraper()
rank = scraper.get_rank(brand_name)
print 'rank', brand_name, rank
if rank:
self.rank = float(rank)
def update_sales(self, date=datetime.date.today()):
brand_name = self.graph.brand.lower()
scraper = OrderScraper()
sales = scraper.get_sales(brand_name, date)
print 'sales', brand_name, sales
self.sales = sales
def update_money(self, date=datetime.date.today()):
brand_name = self.graph.brand.lower()
scraper = CashScraper()
sales = scraper.get_money(date)
print 'sales', brand_name, sales
self.money = sales | [
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] |
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