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office365/sharepoint/portal/group_site_manager.py | rikeshtailor/Office365-REST-Python-Client | 0 | 9312 | <reponame>rikeshtailor/Office365-REST-Python-Client
from office365.runtime.client_object import ClientObject
from office365.runtime.client_result import ClientResult
from office365.runtime.http.http_method import HttpMethod
from office365.runtime.queries.service_operation_query import ServiceOperationQuery
from office365.runtime.resource_path import ResourcePath
from office365.sharepoint.portal.group_creation_params import GroupCreationInformation
from office365.sharepoint.portal.group_site_info import GroupSiteInfo
class GroupSiteManager(ClientObject):
def __init__(self, context):
super(GroupSiteManager, self).__init__(context, ResourcePath("GroupSiteManager"), None)
def create_group_ex(self, display_name, alias, is_public, optional_params=None):
"""
Create a modern site
:param str display_name:
:param str alias:
:param bool is_public:
:param office365.sharepoint.portal.group_creation_params.GroupCreationParams or None optional_params:
"""
payload = GroupCreationInformation(display_name, alias, is_public, optional_params)
result = ClientResult(self.context, GroupSiteInfo())
qry = ServiceOperationQuery(self, "CreateGroupEx", None, payload, None, result)
self.context.add_query(qry)
return result
def delete(self, site_url):
"""
Deletes a SharePoint Team site
:type site_url: str
"""
payload = {
"siteUrl": site_url
}
qry = ServiceOperationQuery(self, "Delete", None, payload)
self.context.add_query(qry)
return self
def get_status(self, group_id):
"""Get the status of a SharePoint site
:type group_id: str
"""
result = ClientResult(self.context, GroupSiteInfo())
qry = ServiceOperationQuery(self, "GetSiteStatus", None, {'groupId': group_id}, None, result)
self.context.add_query(qry)
def _construct_status_request(request):
request.method = HttpMethod.Get
request.url += "?groupId='{0}'".format(group_id)
self.context.before_execute(_construct_status_request)
return result
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python/cracking_codes_with_python/k_columnar_transposition_cipher_hack.py | MerrybyPractice/book-challanges-and-tutorials | 0 | 48975 | # Columnar Transposition Hack per Cracking Codes with Python
# https://www.nostarch.com/crackingcodes/ (BSD Licensed)
import pyperclip
from j_detect_english import is_english
from g_decrypt_columnar_transposition_cipher import decrypt_message as decrypt
def hack_transposition(text):
print('Press Ctrl-C to quit at any time.')
print('Hacking...')
for key in range(1, len(text)):
print('Trying key #%s...' % (key))
print()
print('...')
decrypted_text = decrypt(key, text)
print()
print('...')
if is_english(decrypted_text):
print()
print('Possible encryption hack:')
print('Key %s: %s' % (key, decrypted_text[:100]))
print()
print('Enter D if done, anything else to continue the hack:')
response = input('>')
if response.strip().upper().startswith('D'):
return decrypted_text
return None
def main(text):
hacked_text = hack_transposition(text)
if hacked_text == None:
print('Failed to hack the Columnar Transposition Encryption')
else:
print('Copying hacked string to clipboard:')
print(hacked_text)
pyperclip.copy(hacked_text)
if __name__ == '__main__':
text = input('What would you like to decrypt? ')
main(text)
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btree.py | chrisconley/python-data-structures | 0 | 1607164 | from collections import deque
class BinarySearchTree:
def __init__(self):
self.root = None
def get(self, key):
return self._get(self.root, key)
def _get(self, node, key):
if node is None:
return None
if key < node.key:
return self._get(node.left, key)
elif key > node.key:
return self._get(node.right, key)
else:
return node.value
def put(self, key, value):
self.root = self._put(self.root, key, value)
def _put(self, node, key, value):
if node is None:
return _Node(key, value, 1)
if key < node.key:
node.left = self._put(node.left, key, value)
elif key > node.key:
node.right = self._put(node.right, key, value)
else:
node.value = value
node.num_nodes = self._size(node.left) + self._size(node.right) + 1
return node
def delete(self, key):
self.root = self._delete(self.root, key)
def _delete(self, node, key):
if node is None:
return None
if key < node.key:
node.left = self._delete(node.left, key)
elif key > node.key:
node.right = self._delete(node.right, key)
else:
if node.right is None:
return node.left
if node.left is None:
return node.right
tmp = node
node = self._min(tmp.right)
node.right = self._delete_min(tmp.right)
node.left = tmp.left
node.num_nodes = self._size(node.left) + self._size(node.right) + 1
return node
def _delete_min(self, node):
if node.left is None:
return node.right
node.left = self._delete_min(node.left)
node.num_nodes = self._size(node.left) + self._size(node.right) + 1
return node
def _min(self, node):
if node.left is None:
return node
return self._min(node.left)
@property
def size(self):
return self._size(self.root)
def _size(self, node):
return node.size if node else 0
def serialize(self):
height = self.height
queue = deque([(self.root, 0)])
result = []
while len(queue) > 0:
parent, level = queue.popleft()
ret = parent and parent.key
if level == -1:
result.append(parent)
continue
result.append(ret)
if level != height-1:
if parent.left is None:
queue.append((None, -1))
else:
queue.append((parent.left, level+1))
if parent.right is None:
queue.append((None, -1))
else:
queue.append((parent.right, level+1))
return result
@property
def height(self):
return self._height(self.root)
def _height(self, node):
if node is not None:
if node.left is None and node.right is None:
return 1
else:
return 1 + max(self._height(node.left), self._height(node.right))
else:
return 0
class _Node:
def __init__(self, key, value, num_nodes):
self.key = key
self.value = value
self.num_nodes = num_nodes
self.left, self.right = None, None
@property
def size(self):
return self.num_nodes | [
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] |
pastebin/migrations/0006_auto_20170129_1502.py | johannessarpola/django-pastebin | 0 | 47244 | <reponame>johannessarpola/django-pastebin<filename>pastebin/migrations/0006_auto_20170129_1502.py<gh_stars>0
# -*- coding: utf-8 -*-
# Generated by Django 1.11a1 on 2017-01-29 15:02
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('pastebin', '0005_auto_20170129_1333'),
]
operations = [
migrations.AlterField(
model_name='paste',
name='creation_date',
field=models.DateTimeField(verbose_name='creation date'),
),
migrations.AlterField(
model_name='paste',
name='expiry_date',
field=models.DateTimeField(verbose_name='expiration date'),
),
]
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3_2_HelloWorld.py | Asurada2015/TensorFlowactual-combat_code | 4 | 159118 | <reponame>Asurada2015/TensorFlowactual-combat_code
#%%
# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets("MNIST_data/", one_hot=True)
print(mnist.train.images.shape, mnist.train.labels.shape)
print(mnist.test.images.shape, mnist.test.labels.shape)
print(mnist.validation.images.shape, mnist.validation.labels.shape)
"""(55000, 784) (55000, 10)
(10000, 784) (10000, 10)
(5000, 784) (5000, 10)"""
import tensorflow as tf
sess = tf.InteractiveSession()
x = tf.placeholder(tf.float32, [None, 784])
# 数据类型，数据的格式，none表示不限制输入数据的条目，784表示每条输入是一个784维的数据
#
W = tf.Variable(tf.zeros([784, 10]))
b = tf.Variable(tf.zeros([10]))
y = tf.nn.softmax(tf.matmul(x, W) + b) # 关于这里二维数组和一维数组相加的事情，我还纠结了半天
y_ = tf.placeholder(tf.float32, [None, 10])
cross_entropy = tf.reduce_mean(-tf.reduce_sum(y_ * tf.log(y), reduction_indices=[1]))
train_step = tf.train.GradientDescentOptimizer(0.5).minimize(cross_entropy)
tf.global_variables_initializer().run()
for i in range(1000):
batch_xs, batch_ys = mnist.train.next_batch(100)
train_step.run({x: batch_xs, y_: batch_ys})
correct_prediction = tf.equal(tf.argmax(y, 1), tf.argmax(y_, 1))
accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
print(accuracy.eval({x: mnist.test.images, y_: mnist.test.labels}))
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DQN DDQN Dueling/network.py | eayvali/DeepRL | 2 | 21356 | # -*- coding: utf-8 -*-
"""
Created on Sun Jan 19 23:19:43 2020
@author: elif.ayvali
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
from collections import OrderedDict
class deep_Q_net(nn.Module):
"""Actor (Policy) Model."""
def __init__(self, state_size, action_size, seed):
"""Initialize parameters and build model.
Params
======
state_size (int): Dimension of each state
action_size (int): Dimension of each action
seed (int): Random seed
fc1_units (int): Number of nodes in first hidden layer
fc2_units (int): Number of nodes in second hidden layer
"""
super(deep_Q_net, self).__init__()
self.seed = torch.manual_seed(seed)
self.dqn_net = nn.Sequential(OrderedDict([
('fc1', nn.Linear(state_size, 256)),
('relu1', nn.ReLU()),
('fc2', nn.Linear(256, 128)),
('relu2', nn.ReLU()),
('fc3', nn.Linear(128, 64)),
('relu3', nn.ReLU()),
('fc4', nn.Linear(64, action_size))
]))
def forward(self, state):
"""Build a network that maps state -> action values."""
return self.dqn_net(state)
class dueling_Q_net(nn.Module):
"""Actor (Policy) Model."""
def __init__(self, state_size, action_size, seed):
"""Params
======
state_size (int): Dimension of each state
action_size (int): Dimension of each action
seed (int): Random seed
"""
super(dueling_Q_net, self).__init__()
self.feature_modules = nn.Sequential(OrderedDict([
('fc1', nn.Linear(state_size, 256)),
('relu1', nn.ReLU()),
('fc2', nn.Linear(256, 128)),
('relu2', nn.ReLU()),
('fc3', nn.Linear(128, 64)),
]))
self.value_modules = nn.Sequential(OrderedDict([
('fc_v1', nn.Linear(64, 32)),
('relu)v1', nn.ReLU()),
('fc_v2', nn.Linear(32, 1)),
]))
self.advantage_modules = nn.Sequential(OrderedDict([
('fc_a1', nn.Linear(64, 32)),
('relu_a1', nn.ReLU()),
('fc_a2', nn.Linear(32, action_size)),
]))
def forward(self, state):
#Get common features
common_layers=self.feature_modules(state)
advantage=self.advantage_modules(common_layers)# batch_size x action_size
value=self.value_modules(common_layers) #batch_size x 1
return value + advantage - advantage.mean(dim=1).unsqueeze(1)
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javascript/forms.py | uadson/studies | 0 | 99561 | <reponame>uadson/studies<gh_stars>0
from django import forms
class CalcImcForm(forms.Form):
peso = forms.CharField(
required=False)
altura = forms.CharField(
required=False) | [
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src/bot/handlers/essence_part_handler.py | nchursin/claimant | 3 | 34211 | from typing import Optional, List
from aiogram import types, Dispatcher, filters
from aiogram.dispatcher import FSMContext
from aiogram.dispatcher.filters.state import StatesGroup, State
from aiogram.types import ReplyKeyboardMarkup
from handlers.common_actions_handlers import process_manual_enter, process_option_selection, \
process_complete_part_editing, claim_tmp_option_chosen, show_claim_tmp_example
from keyboards import emojis, get_common_start_kb, get_next_actions_kb, get_claim_parts_kb
from repository import Repository
from statistics import collect_statistic
CLAIM_PART: str = "essence"
class EssencePart(StatesGroup):
waiting_for_user_action = State()
waiting_for_option_chosen = State()
@collect_statistic(event_name="essence:start")
async def essence_start(message: types.Message, state: FSMContext):
repository: Repository = Repository()
claim_data: dict = repository.get_claim_data(message.from_user.id)
required_parts: List[str] = ["story"]
if claim_data.get("claim_data") is None or \
not any([part_name in claim_data["claim_data"].keys() for part_name in required_parts]):
claim_parts_kb: ReplyKeyboardMarkup = get_claim_parts_kb(message.from_user.id)
await message.reply("Пожалуйста, сперва заполните раздел 'фабула'.",
reply_markup=claim_parts_kb)
return
await EssencePart.waiting_for_user_action.set()
start_kb: ReplyKeyboardMarkup = get_common_start_kb()
await message.reply("Опишите суть нарушения. "
"Введите, почему вы считаете, что ваши права нарушают. "
"Или выберите одну из следующий опций.",
reply_markup=start_kb)
@collect_statistic(event_name="essence:show_example")
async def show_example(message: types.Message, state: FSMContext):
await show_claim_tmp_example(message, CLAIM_PART)
async def action_selected(message: types.Message, state: FSMContext):
option: Optional[str] = message.text
if option.endswith("выбрать из списка") or option.endswith("добавить еще из списка"):
await process_option_selection(message, CLAIM_PART, EssencePart)
return
if option.endswith("закончить заполнение"):
await process_complete_part_editing(message, state, CLAIM_PART)
return
await process_manual_enter(message, state, EssencePart)
async def option_chosen(callback_query: types.CallbackQuery, state: FSMContext):
await claim_tmp_option_chosen(callback_query, state, CLAIM_PART)
async def finish_option_choosing(callback_query: types.CallbackQuery):
await callback_query.answer()
await EssencePart.waiting_for_user_action.set()
next_actions_kb: ReplyKeyboardMarkup = get_next_actions_kb()
await callback_query.message.answer("Введите свой вариант самостоятельно. "
"Или выберите дальнейшее действие с помощью клавиатуры",
reply_markup=next_actions_kb)
def register_handlers(dp: Dispatcher):
dp.register_message_handler(essence_start, filters.Regexp(f"^{emojis.key} суть нарушения"))
dp.register_message_handler(show_example,
filters.Regexp(f"^{emojis.red_question_mark} показать пример"),
state=EssencePart.states)
dp.register_message_handler(action_selected, state=EssencePart.waiting_for_user_action)
dp.register_callback_query_handler(
option_chosen,
filters.Text(startswith="option"),
state=EssencePart.waiting_for_option_chosen
)
dp.register_callback_query_handler(finish_option_choosing,
filters.Text(equals="complete options"),
state=EssencePart.waiting_for_option_chosen)
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] |
piccel/ui/__init__.py | lesca-research/piccel | 2 | 188313 | from .generated import access_ui
from .generated import data_sheet_ui
from .generated import form_item_ui
from .generated import form_ui
from .generated import item_boolean_checkboxes_ui
from .generated import item_choice_radio_ui
from .generated import item_datetime_ui
from .generated import item_single_line_ui
from .generated import item_text_multi_line_ui
from .generated import login_ui
from .generated import progress_bar_ui
from .generated import resources
from .generated import section_ui
from .generated import selector_ui
from .generated import text_editor_ui
from .generated import workbook_ui
from .generated import workbook_creation_ui
from .generated import sheet_creation_ui
# from .generated import dynamic_vlist_ui
# from .generated import dynamic_vlist_item_ui
from .generated import form_editor_widget_ui
from .generated import form_editor_file_ui
from .generated import form_editor_sheet_ui
from .generated import form_edit_ui
from .generated import section_edit_ui
from .generated import item_edit_ui
from .generated import choice_edit_ui
from .generated import variable_edit_ui
from .generated import section_transition_edit_ui
from . import widgets
from . import main_qss
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] |
locan/data/hulls/__init__.py | super-resolution/Locan | 8 | 9558 | <filename>locan/data/hulls/__init__.py
"""
Hull objects of localization data.
Submodules:
-----------
.. autosummary::
:toctree: ./
hull
alpha_shape
"""
from locan.data.hulls.alpha_shape import *
from locan.data.hulls.hull import *
__all__ = []
__all__.extend(hull.__all__)
__all__.extend(alpha_shape.__all__)
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09-PiDay2022/IBM_quantum_randomness.py | StrangeGirlMurph/CodingProjects | 0 | 175546 | from qiskit import *
from qiskit import IBMQ
from qiskit.tools.monitor import job_monitor
from qiskit.providers.ibmq import least_busy
def random_qubit():
IBMQ.load_account()
provider = IBMQ.get_provider("ibm-q")
small_devices = provider.backends(
filters=lambda x: x.configuration().n_qubits == 5
and not x.configuration().simulator
)
qcomp = least_busy(small_devices)
qr = QuantumRegister(1)
cr = ClassicalRegister(1)
circuit = QuantumCircuit(qr, cr)
circuit.h(0)
circuit.measure(0, 0)
job = execute(circuit, backend=qcomp, shots=1)
job_monitor(job)
return str(list(job.result().get_counts().keys())[0])
print(random_qubit())
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moredata/enricher/elasticsearch_connector/__init__.py | thomassonobe/more-data | 0 | 57654 | from .elasticsearch_connector import *
from .index_handler import *
from .policy_handler import *
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scripts/03_glove_build_counts.py | svlandeg/sense2vec | 1,140 | 124120 | <reponame>svlandeg/sense2vec<gh_stars>1000+
#!/usr/bin/env python
import os
from pathlib import Path
from wasabi import msg
import typer
def main(
# fmt: off
glove_dir: str = typer.Argument(..., help="Directory containing the GloVe build"),
in_dir: str = typer.Argument(..., help="Directory with preprocessed .s2v files"),
out_dir: str = typer.Argument(..., help="Path to output directory"),
min_count: int = typer.Option(5, "--min-count", "-c", help="Minimum count for inclusion in vocab"),
memory: float = typer.Option(4.0, "--memory", "-m", help="Soft limit for memory consumption, in GB"),
window_size: int = typer.Option(15, "--window-size", "-w", help="Number of context words on either side"),
verbose: int = typer.Option(2, "--verbose", "-v", help="Set verbosity: 0, 1, or 2"),
# fmt: on
):
"""
Step 3: Build vocabulary and frequency counts
Expects a directory of preprocessed .s2v input files and will use GloVe to
collect unigram counts and construct and shuffle cooccurrence data. See here
for installation instructions: https://github.com/stanfordnlp/GloVe
Note that this script will call into GloVe and expects you to pass in the
GloVe build directory (/build if you run the Makefile). The commands will
also be printed if you want to run them separately.
"""
input_path = Path(in_dir)
output_path = Path(out_dir)
if not Path(glove_dir).exists():
msg.fail("Can't find GloVe build directory", glove_dir, exits=1)
if not input_path.exists() or not input_path.is_dir():
msg.fail("Not a valid input directory", in_dir, exits=1)
input_files = [str(fp) for fp in input_path.iterdir() if fp.suffix == ".s2v"]
if not input_files:
msg.fail("No .s2v files found in input directory", in_dir, exits=1)
msg.info(f"Using {len(input_files)} input files")
if not output_path.exists():
output_path.mkdir(parents=True)
msg.good(f"Created output directory {out_dir}")
vocab_file = output_path / f"vocab.txt"
cooc_file = output_path / f"cooccurrence.bin"
cooc_shuffle_file = output_path / f"cooccurrence.shuf.bin"
msg.info("Creating vocabulary counts")
cmd = (
f"cat {' '.join(input_files)} | {glove_dir}/vocab_count "
f"-min-count {min_count} -verbose {verbose} > {vocab_file}"
)
print(cmd)
vocab_cmd = os.system(cmd)
if vocab_cmd != 0 or not Path(vocab_file).exists():
msg.fail("Failed creating vocab counts", exits=1)
msg.good("Created vocab counts", vocab_file)
msg.info("Creating cooccurrence statistics")
cmd = (
f"cat {' '.join(input_files)} | {glove_dir}/cooccur -memory {memory} "
f"-vocab-file {vocab_file} -verbose {verbose} "
f"-window-size {window_size} > {cooc_file}"
)
print(cmd)
cooccur_cmd = os.system(cmd)
if cooccur_cmd != 0 or not Path(cooc_file).exists():
msg.fail("Failed creating cooccurrence statistics", exits=1)
msg.good("Created cooccurrence statistics", cooc_file)
msg.info("Shuffling cooccurrence file")
cmd = (
f"{glove_dir}/shuffle -memory {memory} -verbose {verbose} "
f"< {cooc_file} > {cooc_shuffle_file}"
)
print(cmd)
shuffle_cmd = os.system(cmd)
if shuffle_cmd != 0 or not Path(cooc_shuffle_file).exists():
msg.fail("Failed to shuffle cooccurrence file", exits=1)
msg.good("Shuffled cooccurrence file", cooc_shuffle_file)
if __name__ == "__main__":
typer.run(main)
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542,
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1445,
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13,
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13,
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13,
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13,
13,
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3888,
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26841,
934,
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9920,
353,
313,
13,
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285,
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29912,
29887,
417,
345,
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3972,
6822,
845,
21897,
448,
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426,
14834,
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448,
369,
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426,
369,
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376,
13,
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285,
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426,
1111,
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13,
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9006,
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13,
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528,
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353,
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5205,
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9006,
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13,
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565,
528,
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2804,
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29900,
470,
451,
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1111,
542,
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13,
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304,
528,
21897,
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934,
613,
429,
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13,
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29889,
16773,
703,
2713,
3096,
839,
1302,
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26841,
934,
613,
1302,
542,
29918,
845,
21897,
29918,
1445,
29897,
13,
13,
13,
361,
4770,
978,
1649,
1275,
376,
1649,
3396,
1649,
1115,
13,
1678,
7911,
546,
29889,
3389,
29898,
3396,
29897,
13,
2
] |
Lib/vanilla/vanillaGradientButton.py | miguelsousa/vanilla | 21 | 97761 | from AppKit import *
from vanillaButton import ImageButton
class GradientButton(ImageButton):
nsBezelStyle = NSSmallSquareBezelStyle
| [
1,
515,
2401,
13117,
1053,
334,
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29885,
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29903,
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3629,
10533,
5568,
13,
13,
2
] |
ui_test/user_flows.py | uktrade/dit-contact-forms | 2 | 156652 | from ui_test.selectors.questionnaire import QUESTIONNAIRE
from ui_test.selectors.form import FORM
def select_questionnaire(browser, options):
for key, value in options.items():
browser.find_by_css(QUESTIONNAIRE[key][value]).click()
browser.find_by_css(QUESTIONNAIRE["continue"]).click()
def submit_form(browser, options):
browser.find_by_css(FORM["message"]).first.type(options["message"])
browser.find_by_css(FORM["name"]).first.type(options["name"])
browser.find_by_css(FORM["email"]).first.type(options["email"])
browser.find_by_css(FORM["accept_terms"]).click()
browser.find_by_css(QUESTIONNAIRE["continue"]).click()
| [
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3521,
29902,
1525,
3366,
19878,
3108,
467,
3808,
580,
13,
2
] |
pybomberman/__init__.py | pybomberman/pybomberman | 2 | 32978 | from .map import Map
print("Soon... https://github.com/pybomberman/pybomberman")
| [
1,
515,
869,
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1053,
7315,
13,
13,
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29889,
510,
29914,
2272,
29890,
290,
495,
1171,
29914,
2272,
29890,
290,
495,
1171,
1159,
13,
2
] |
base_python/tests/test_flatten.py | cogment/cogment-verse | 23 | 106746 | <reponame>cogment/cogment-verse
# Copyright 2021 AI Redefined Inc. <<EMAIL>>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from data_pb2 import Space
from cogment_verse.spaces import flattened_dimensions
def test_flattened_dimensions_discrete():
assert flattened_dimensions(Space(properties=[Space.Property(discrete=Space.Discrete(num=2))])) == 2
assert (
flattened_dimensions(
Space(
properties=[
Space.Property(
discrete=Space.Discrete(
labels=["brake", "accelerate", "do nothing"],
num=2, # Will be ignored as there are more labels
)
)
]
)
)
== 3
)
assert (
flattened_dimensions(
Space(
properties=[
Space.Property(discrete=Space.Discrete(labels=["brake", "accelerate", "do nothing"], num=12))
]
)
)
== 12
)
assert (
flattened_dimensions(
Space(
properties=[
Space.Property(key="a", discrete=Space.Discrete(labels=["brake", "accelerate", "do nothing"])),
Space.Property(key="b", discrete=Space.Discrete(num=5)),
]
)
)
== 8
)
def test_flattened_dimensions_box():
assert flattened_dimensions(Space(properties=[Space.Property(box=Space.Box(shape=[2]))])) == 2
assert flattened_dimensions(Space(properties=[Space.Property(box=Space.Box(shape=[4]))])) == 4
assert flattened_dimensions(Space(properties=[Space.Property(box=Space.Box(shape=[2, 3, 4]))])) == 24
assert (
flattened_dimensions(
Space(
properties=[
Space.Property(key="a", box=Space.Box(shape=[10])),
Space.Property(key="b", box=Space.Box(shape=[2, 3, 4])),
]
)
)
== 34
)
def test_flattened_dimensions_mixed():
assert (
flattened_dimensions(
Space(
properties=[
Space.Property(key="a", box=Space.Box(shape=[10])),
Space.Property(key="b", discrete=Space.Discrete(labels=["brake", "accelerate", "do nothing"])),
Space.Property(key="c", box=Space.Box(shape=[2, 3, 4])),
]
)
)
== 37
)
| [
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29941,
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29946,
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12622,
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29946,
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13,
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4974,
313,
13,
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1652,
8606,
287,
29918,
6229,
5580,
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13,
9651,
14121,
29898,
13,
18884,
4426,
11759,
13,
462,
1678,
14121,
29889,
4854,
29898,
1989,
543,
29874,
613,
3800,
29922,
14936,
29889,
3313,
29898,
12181,
11759,
29896,
29900,
2314,
511,
13,
462,
1678,
14121,
29889,
4854,
29898,
1989,
543,
29890,
613,
3800,
29922,
14936,
29889,
3313,
29898,
12181,
11759,
29906,
29892,
29871,
29941,
29892,
29871,
29946,
2314,
511,
13,
18884,
4514,
13,
9651,
1723,
13,
4706,
1723,
13,
4706,
1275,
29871,
29941,
29946,
13,
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1723,
13,
13,
13,
1753,
1243,
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511,
13,
462,
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4854,
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543,
29890,
613,
19554,
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14936,
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4205,
9084,
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21134,
29922,
3366,
2634,
446,
613,
376,
562,
2242,
261,
403,
613,
376,
1867,
3078,
20068,
511,
13,
462,
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3800,
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3313,
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12181,
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29906,
29892,
29871,
29941,
29892,
29871,
29946,
2314,
511,
13,
18884,
4514,
13,
9651,
1723,
13,
4706,
1723,
13,
4706,
1275,
29871,
29941,
29955,
13,
1678,
1723,
13,
2
] |
cbh.py | jensengroup/fragreact | 2 | 33656 | <reponame>jensengroup/fragreact<gh_stars>1-10
#!/usr/bin/env python
import numpy as np
import re
from rdkit import Chem
from rdkit.Chem import rdMolDescriptors
from itertools import combinations
import copy
def print_smiles(smiles_list, human=False):
smiles_dict = count_smiles(smiles_list)
keys = smiles_dict.keys()
keys.sort()
out = []
for key in keys:
out += [str(smiles_dict[key]) + " " + key]
return " ".join(out)
def print_reaction(reactants, products, human=False):
if not human:
reaction = ">>".join([".".join(reactants), ".".join(products)])
else:
reactants = print_smiles(reactants)
products = print_smiles(products)
reaction = reactants+ ">>"+ products
return reaction
def canonical(smiles):
"""
SMILES provided is canonical, so the output should be the same no matter
how a particular molecule is input
"""
m = Chem.MolFromSmiles(smiles)
smiles = Chem.MolToSmiles(m)
return smiles
def kekulize(smiles):
m = Chem.MolFromSmiles(smiles)
Chem.Kekulize(m)
smiles = Chem.MolToSmiles(m, kekuleSmiles=True)
return smiles
def count_hydrogens(smiles):
""" """
m = Chem.MolFromSmiles(smiles)
n_hydrogen = 0
for a in m.GetAtoms():
n_hydrogen += a.GetTotalNumHs()
# print a.GetAtomicNum()
# print a.GetTotalNumHs()
# print a.GetNumExplicitHs()
# print a.GetNumImplicitHs()
return n_hydrogen
def count_smiles(smiles_list):
"""
Count SMILES by creating a dictionary with SMILES as keys, point to the
number of that particular SMILES.
e.i. dict[smiles] = # of smiles
"""
smiles_dict = {}
components, components_count = np.unique(smiles_list, return_counts=True)
for comp, count in zip(components, components_count):
smiles_dict[comp] = count
return smiles_dict
def substract_smiles(A, B):
"""
A - B = Cp + Cn
where Cp has positive results
and Cn has negative results
"""
if isinstance(A, str): A = A.split(".")
if isinstance(B, str): B = B.split(".")
Cp = []
Cn = []
A = count_smiles(A)
B = count_smiles(B)
for key in np.unique(list(A.keys()) + list(B.keys())):
if key not in A:
Cn += [key] * B[key]
continue
if key not in B:
Cp += [key] * A[key]
continue
diff = A[key] - B[key]
if diff == 0:
continue
elif diff > 0:
Cp += [key]*diff
elif diff < 0:
Cn += [key]*abs(diff)
return Cp, Cn
def tuning(left_side, right_side):
corrected_left = []
corrected_right = []
left_side = count_smiles(left_side)
right_side = count_smiles(right_side)
for key in np.unique(list(left_side.keys()) + list(right_side.keys())):
if key not in left_side:
print("hello")
quit()
if key not in right_side:
print("hello2")
quit()
diff = right_side[key] - left_side[key]
if diff == 0:
continue
elif diff > 0:
corrected_left += [key] * diff
elif diff < 0:
corrected_right += [key] * diff
return corrected_left, corrected_right
def get_bond_type(m, a, b):
# NOTE
# If m is not kekulized then bonds can be AROMATIC
# which is a problem for the component schemes
try:
bond_type = str(m.GetBondBetweenAtoms(a, b).GetBondType())
except AttributeError:
return False
if bond_type == "SINGLE":
bond = ""
elif bond_type == "DOUBLE":
bond = "="
elif bond_type == "TRIPLE":
bond = "#"
else:
bond = False
return bond
def get_atoms(smiles, ignore_hydrogen=True):
smiles = kekulize(smiles)
p = re.compile(r"[A-Z][a-z]?")
atoms = p.findall(smiles)
if ignore_hydrogen:
atoms = [atom for atom in atoms if atom != "H"]
return atoms
def add_neighbours(mol, substructures):
substructures = list(substructures)
for j, idx in enumerate(substructures):
for i in idx:
A = mol.GetAtomWithIdx(i)
for B in A.GetNeighbors():
k = B.GetIdx()
substructures[j] += (k,)
return substructures
def get_components_neighbors(mol, atoms):
atoms = list(atoms)
for idx in atoms:
idx, = idx
A = mol.GetAtomWithIdx(idx)
for B in A.GetNeighbors():
idx_b = B.GetIdx()
atom = B.GetAtomicNum()
charge = B.GetFormalCharge()
bond = Chem.GetBondBetweenAtoms(mol, idx, idx_b)
return
def get_components(smiles, smart, kekulize=True, add=False):
m = Chem.MolFromSmiles(smiles)
smart = Chem.MolFromSmarts(smart)
if kekulize:
Chem.Kekulize(m)
substructures = m.GetSubstructMatches(smart)
components = []
if add:
substructures = add_neighbours(m, substructures)
for sub in substructures:
if add:
m_new = copy.copy(m)
m_new = Chem.RWMol(m_new)
for B, C in combinations(sub[1:], 2):
m_new.RemoveBond(B, C)
else:
m_new = m
component = Chem.MolFragmentToSmiles(m_new,
atomsToUse=sub,
isomericSmiles=True,
kekuleSmiles=True,
canonical=True)
A = m.GetAtomWithIdx(sub[0])
mc = Chem.MolFromSmiles(component)
n_atoms = mc.GetNumAtoms()
n_bonds = len(mc.GetBonds())
component = Chem.MolToSmiles(mc)
if "+" in component or "-" in component or "H" in component:
# Very awful hack to fix the charged molecules and their explicit
# hydrogens
charges = np.zeros(n_atoms, dtype=int)
for idx in range(n_atoms):
atom = mc.GetAtomWithIdx(idx)
atom.SetNumExplicitHs(0)
charge = atom.GetFormalCharge()
charges[idx] = charge
atom.SetFormalCharge(0)
component = Chem.MolToSmiles(mc, canonical=False)
component = component.replace("[", "").replace("]","")
mc = Chem.MolFromSmiles(component)
for idx, charge in zip(range(n_atoms), charges):
atom = mc.GetAtomWithIdx(idx)
charge = int(charge)
atom.SetFormalCharge(charge)
component = Chem.MolToSmiles(mc)
if n_atoms <= n_bonds:
mw = Chem.RWMol(m)
if len(sub) == 3:
mw.RemoveBond(sub[0], sub[-1])
elif len(sub) == 4 or len(sub) == 5:
for i in range(0, n_atoms):
for j in range(i+1, n_atoms):
if i == 1 or j == 1: continue
mw.RemoveBond(sub[i], sub[j])
component = Chem.MolFragmentToSmiles(mw,
atomsToUse=sub,
isomericSmiles=True,
kekuleSmiles=True,
canonical=True)
if "1" in component:
quit("Error connectivity")
else:
component = Chem.MolToSmiles(mc)
# charge = Chem.GetFormalCharge(mc)
#
# if not charge == 0:
# # NOTE
# # Lots of lots of if case down this road
#
# n_atoms = mc.GetNumAtoms()
#
# for i in range(n_atoms):
#
# atom = mc.GetAtomWithIdx(i)
# charge = atom.GetFormalCharge()
#
# if not charge == 0:
# atom.SetFormalCharge(0)
component = canonical(component)
components += [component]
return components
def get_components_scheme1(smiles, kekulize=True):
c1 = "[*]~[*]"
if "+" in smiles or "-" in smiles:
pass
else:
return get_components(smiles, c1)
# The code below doesn't get charges
return get_components(smiles, c1)
c1 = Chem.MolFromSmarts(c1)
m = Chem.MolFromSmiles(smiles)
if kekulize:
Chem.Kekulize(m)
substructures = m.GetSubstructMatches(c1)
components = []
for sub in substructures:
a, b = sub
ab = get_bond_type(m, a, b)
a = m.GetAtomWithIdx(a).GetSymbol()
b = m.GetAtomWithIdx(b).GetSymbol()
component = a + ab + b
components.append(component)
components = [canonical(component) for component in components]
return components
def get_components_scheme2(smiles, kekulize=True):
c1 = "[D2]"
c2 = "[*]~[D2]~[*]"
c3 = "[*]~[D3](~[*])~[*]"
c4 = "[*]~[*](~[*])(~[*])~[*]"
# if "+" in smiles or "-" in smiles:
# pass
# else:
components = []
components += get_components(smiles, c1, add=True)
# components += get_components(smiles, c2)
components += get_components(smiles, c3)
components += get_components(smiles, c4)
return components
c2 = Chem.MolFromSmarts(c2)
c3 = Chem.MolFromSmarts(c3)
c4 = Chem.MolFromSmarts(c4)
m = Chem.MolFromSmiles(smiles)
if kekulize:
Chem.Kekulize(m)
substructures = m.GetSubstructMatches(c2)
components = []
for sub in substructures:
a, b, c = sub
ab = get_bond_type(m, a, b)
bc = get_bond_type(m, b, c)
a = m.GetAtomWithIdx(a).GetSymbol()
b = m.GetAtomWithIdx(b).GetSymbol()
c = m.GetAtomWithIdx(c).GetSymbol()
component = a + ab + b + bc + c
components.append(component)
substructures = m.GetSubstructMatches(c3)
for sub in substructures:
a, b, c, d = sub
ab = get_bond_type(m, a, b)
bc = get_bond_type(m, b, c)
bd = get_bond_type(m, b, d)
a = m.GetAtomWithIdx(a).GetSymbol()
b = m.GetAtomWithIdx(b).GetSymbol()
c = m.GetAtomWithIdx(c).GetSymbol()
d = m.GetAtomWithIdx(d).GetSymbol()
component = a + ab + b + "(" + bc + c + ")" + bd + d
components.append(component)
substructures = m.GetSubstructMatches(c4)
for sub in substructures:
a, b, c, d, e = sub
ab = get_bond_type(m, a, b)
bc = get_bond_type(m, b, c)
bd = get_bond_type(m, b, d)
be = get_bond_type(m, b, e)
a = m.GetAtomWithIdx(a).GetSymbol()
b = m.GetAtomWithIdx(b).GetSymbol()
c = m.GetAtomWithIdx(c).GetSymbol()
d = m.GetAtomWithIdx(d).GetSymbol()
e = m.GetAtomWithIdx(e).GetSymbol()
component = a + ab + b
component += "(" + bc + c + ")"
component += "(" + bd + d + ")"
component += be + e
components.append(component)
components = [canonical(component) for component in components]
return components
def decompontent(smiles, scheme=1):
if scheme == 1: decompontent_scheme = decompontent_scheme1
elif scheme == 2: decompontent_scheme = decompontent_scheme2
left, right = decompontent_scheme(smiles)
return left, right
def decompontent_scheme1(smiles):
"""
Tune the equation
A (bb) => aa
where
A (target) is big smiles
aa (scheme1 components) is scheme2 components
bb (atoms) is additional bonds required, to have equald bonds on each side
this is done for each A which consists of len(aa) > 0
"""
components = get_components_scheme1(smiles)
if len(components) == 0:
return [], []
bonds_leftside = get_atoms(smiles)
bonds_rightside = []
for component in components:
bonds_rightside += get_atoms(component)
left, right = tuning(bonds_leftside, bonds_rightside)
right += components
return left, right
def decompontent_scheme2(smiles):
"""
Tune the equation
A (bb) => aa
where
A (target) is big smiles
aa (scheme2 components) is scheme2 components
bb (single bonds) is additional bonds required, to have equald bonds on each side
this is done for each A which consists of len(aa) > 0
"""
components = get_components_scheme2(smiles)
if len(components) == 0:
return [], []
bonds_leftside = get_components_scheme1(smiles)
bonds_rightside = []
for component in components:
bonds_rightside += get_components_scheme1(component)
left, right = tuning(bonds_leftside, bonds_rightside)
right += components
if not check_atoms([smiles] + left, right):
print("Error in fragreact tuneing:", smiles)
print([smiles], left, right)
quit()
return left, right
def resultant(reactants, products, scheme=1):
"""
assummed that smiles lists are both split(".") and canonical at this point
"""
reactants_leftside = []
reactants_rightside = []
products_leftside = []
products_rightside = []
reactants_missing = []
products_missing = []
if scheme == 1:
decompontent_scheme = decompontent_scheme1
elif scheme == 2:
decompontent_scheme = decompontent_scheme2
for reactant in reactants:
left, right = decompontent_scheme(reactant)
if len(left) == 0 and len(right) == 0:
reactants_missing += [reactant]
reactants_leftside += left
reactants_rightside += right
for product in products:
left, right = decompontent_scheme(product)
if len(left) == 0 and len(right) == 0:
products_missing += [product]
products_leftside += left
products_rightside += right
left_positive, left_negative = substract_smiles(products_leftside, reactants_leftside)
right_positive, right_negative = substract_smiles(products_rightside, reactants_rightside)
left = left_positive + right_negative + reactants_missing
right = right_positive + left_negative + products_missing
left, right = substract_smiles(left, right)
hydrogens_left = 0
hydrogens_right = 0
for each in left:
hydrogens_left += count_hydrogens(each)
for each in right:
hydrogens_right += count_hydrogens(each)
tune_hydrogens = hydrogens_left - hydrogens_right
if tune_hydrogens < 0:
left += ['[H+]']*abs(tune_hydrogens)
if tune_hydrogens > 0:
right += ['[H+]']*tune_hydrogens
return left, right
def split_smiles(smiles, num_sep=None):
"""
number seperator num_sep (e.g. 3xCC, num_spe="x")
"""
if type(smiles) == type(""):
smiles_list = smiles.split(".")
else:
smiles_list = smiles
for i, smiles in enumerate(smiles_list):
smiles = smiles.split(".")
if len(smiles) > 1:
smiles_list[i] = smiles[0]
smiles_list += smiles[1:]
if num_sep:
for i, smiles in enumerate(smiles_list):
if num_sep in smiles:
num, smiles = smiles.split(num_sep)
num = int(num)
smiles_list[i] = smiles
smiles_list += [smiles]*(num-1)
return smiles_list
def cbh_n(reactants, products, scheme, do_canonical=True):
"""
Use connectivity-based hieracy for reaction (reactants -> products)
in:
reactants -- list of SMILES
products -- list of SMILES
scheme -- int level of connecitivty
out:
left -- list of smiles for the reactant part of the CBHn reaction
right -- list of smiles for the product part of the CBHn reaction
"""
if do_canonical:
reactants = [canonical(smiles) for smiles in reactants]
products = [canonical(smiles) for smiles in products]
left, right = resultant(reactants, products, scheme=scheme)
return left, right
def check_atoms(reactants, products):
"""
Check the validity of the reaction.
Reaction should have eq. no. of atoms for both reactants and products.
"""
ratoms = [get_atoms(smiles) for smiles in reactants]
patoms = [get_atoms(smiles) for smiles in products]
# flatten
ratoms = sum(ratoms, [])
patoms = sum(patoms, [])
ratoms.sort()
patoms.sort()
return ratoms == patoms
def check_reaction(reactants, products):
"""
"""
if isinstance(reactants, list): reactants = ".".join(reactants)
if isinstance(products, list): products = ".".join(products)
reactants = Chem.MolFromSmiles(reactants)
products = Chem.MolFromSmiles(products)
return rdMolDescriptors.CalcMolFormula(reactants) == rdMolDescriptors.CalcMolFormula(products)
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] |
mlcomp/parallelm/pipeline/component_dir_helper.py | lisapm/mlpiper | 7 | 198337 | <filename>mlcomp/parallelm/pipeline/component_dir_helper.py<gh_stars>1-10
import pkg_resources
import logging
import os
from parallelm.common.base import Base
class ComponentDirHelper(Base):
def __init__(self, pkg, main_program):
"""
Extract component directory outside of egg, so an external command can run
:param main_program: The main program to run. E.g. main.py
:param pkg: The package the main_program is in, this is required in order to extract the files of the componenbt
outisde the egg
"""
super(ComponentDirHelper, self).__init__(logging.getLogger(self.logger_name()))
self._logger.debug("pkg: {}, main_program: {}".format(pkg, main_program))
self._pkg = pkg
self._main_program = main_program
def extract_component_out_of_egg(self):
"""
The artifact dir will contain all the files needed to run the R code.
This method will copy the files outside of the egg into the artifact dir
:return:
"""
# TODO: check what happens if we have a directory inside the component dir
ll = pkg_resources.resource_listdir(self._pkg, "")
for file_name in ll:
real_file_name = pkg_resources.resource_filename(self._pkg, file_name)
self._logger.debug("file: {}".format(file_name))
self._logger.debug("real_file: {}".format(real_file_name))
# Finding the directory we need to CD into
base_file = os.path.basename(self._main_program)
self._logger.debug("base_file: ".format(base_file))
real_file_name = pkg_resources.resource_filename(self._pkg, base_file)
component_extracted_dir = os.path.dirname(real_file_name)
self._logger.debug("Extraction dir: {}".format(component_extracted_dir))
self._logger.debug("Done building artifact dir:")
self._logger.debug("======================")
return component_extracted_dir
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test.py | nerdingitout/STT-- | 0 | 28057 | <gh_stars>0
import pandas as pd
import json
import csv
# importing the module
import json
# Opening JSON file
with open('response.json') as json_file:
data = json.load(json_file)
# for reading nested data [0] represents
# the index value of the list
print(data['results'][0]['alternatives']['transcript'])
# for printing the key-value pair of
# nested dictionary for looop can be used
print("\nPrinting nested dicitonary as a key-value pair\n")
for i in data['people1']:
print("Name:", i['name'])
print("Website:", i['website'])
print("From:", i['from'])
print()
#def json_csv(filename):
# with open(filename) as data_file: #opening json file
# data = json.load(data_file) #loading json data
# normalized_df = pd.json_normalize(data)
# print(normalized_df['results'][0])
# normalized_df.to_csv('my_csv_file.csv',index=False)
# return pd.DataFrame(data['results'])
json_csv('response.json') #calling the json_csv function, paramter is the source json file
#file = open('response.json')
#obj = json.load(file)
#for element in obj['results']:
# for alternative in element['alternatives']:
# for stamp in alternative['timestamps']:
# name, value1, value2 = stamp
# print(stamp)
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vulnerable_people_form/integrations/google_analytics.py | uk-gov-mirror/alphagov.govuk-shielded-vulnerable-people-service | 3 | 125960 | import requests
import sentry_sdk
from flask import current_app
def track_event(category, action, label=None, value=0):
data = {
"v": "1", # API Version.
"tid": current_app.config["GA_TRACKING_ID"], # Tracking ID / Property ID.
# Anonymous Client Identifier. Ideally, this should be a UUID that
# is associated with particular user, device, or browser instance.
"cid": "555",
"t": "event", # Event hit type.
"ec": category, # Event category.
"ea": action, # Event action.
"el": label, # Event label.
"ev": value, # Event value, must be an integer
"ua": "Opera/9.80 (Windows NT 6.0) Presto/2.12.388 Version/12.14",
}
response = requests.post("https://www.google-analytics.com/collect", data=data)
# If the request fails, this will raise a RequestException. Depending
# on your application's needs, this may be a non-error and can be caught
# by the caller.
response.raise_for_status()
def track_nhs_userinfo_and_form_answers_differs():
try:
track_event("NHS info retrieved via oidc and form differs", "registration")
except Exception as e:
sentry_sdk.capture_exception(e)
def track_nhs_number_and_form_value_differs():
try:
track_event("NHS number retrieved via oidc and that in form differs", "registration")
except Exception as e:
sentry_sdk.capture_exception(e)
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assignment3/code/q4.1.py | liusida/ds2 | 0 | 121156 | # requirements.txt:
# pyro 1.6.0
# torch 1.8.0
import pyro
from pyro.distributions import Normal,Gamma,InverseGamma,Bernoulli,Poisson
import matplotlib.pyplot as plt
# import pyro.poutine as poutine
pyro.set_rng_seed(101)
def normal_density_estimation(obs, N):
assert obs is None or N==obs.shape[0]
loc = pyro.sample("loc", Normal(0,1))
inverse_scale = pyro.sample("inverse_scale", Gamma(3,2))
with pyro.plate("n", N):
data = pyro.sample(f"data", Normal(loc, 1/inverse_scale), obs=obs)
return data
if __name__ == "__main__":
# simple test
data = normal_density_estimation(None, 100000)
plt.hist(data.detach().numpy(), bins="auto")
plt.show() | [
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openrave/docs/source/tutorials/openravepy_examples/simple_environment_loading.py | jdsika/TUM_HOly | 2 | 88903 | <gh_stars>1-10
"""Loads up an environment, attaches a viewer, loads a scene, and requests information about the robot.
"""
from openravepy import *
env = Environment() # create openrave environment
env.SetViewer('qtcoin') # attach viewer (optional)
env.Load('data/lab1.env.xml') # load a simple scene
robot = env.GetRobots()[0] # get the first robot
with env: # lock the environment since robot will be used
raveLogInfo("Robot "+robot.GetName()+" has "+repr(robot.GetDOF())+" joints with values:\n"+repr(robot.GetDOFValues()))
robot.SetDOFValues([0.5],[0]) # set joint 0 to value 0.5
T = robot.GetLinks()[1].GetTransform() # get the transform of link 1
raveLogInfo("The transformation of link 1 is:\n"+repr(T))
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TestMatrices.py | Tsyrema/Computing-the-Distance-Matrix-and-the-Covariance-Matrix-of-Data | 0 | 108405 | # script to test your computation code
# do not change this file
from ComputeMatrices import compute_distance_naive, \
compute_distance_smart, compute_correlation_naive, \
compute_correlation_smart
import numpy as np
from sklearn.datasets import load_iris
# my computation
def my_comp_distance(X):
N = X.shape[0]
D = X[0].shape[0]
M = np.zeros([N,N])
return M
# an example code for testing
def main():
iris = load_iris()
X = iris.data
distance_true = my_comp_distance(X)
distance_loop = compute_distance_naive(X)
distance_cool = compute_distance_smart(X)
print np.allclose(distance_true, distance_loop)
print np.allclose(distance_true, distance_cool)
if __name__ == "__main__": main()
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sailfish/solvers/scdg_1d.py | Javk5pakfa/sailfish | 1 | 94987 | <reponame>Javk5pakfa/sailfish
"""
An n-th order discontinuous Galerkin solver for 1D scalar advection.
"""
from typing import NamedTuple
from numpy.polynomial.legendre import leggauss, Legendre
from sailfish.mesh import PlanarCartesianMesh
from sailfish.solver import SolverBase
class CellData:
"""
Gauss weights, quadrature points, and tabulated Legendre polonomials.
This class works for n-th order Gaussian quadrature in 1D.
"""
def __init__(self, order=1):
import numpy as np
if order <= 0:
raise ValueError("cell order must be at least 1")
def leg(x, n, m=0):
c = [(2 * n + 1) ** 0.5 if i is n else 0.0 for i in range(n + 1)]
return Legendre(c).deriv(m)(x)
f = [-1.0, 1.0] # xsi-coordinate of faces
g, w = leggauss(order)
self.gauss_points = g
self.weights = w
self.phi_faces = np.array([[leg(x, n, m=0) for n in range(order)] for x in f])
self.phi_value = np.array([[leg(x, n, m=0) for n in range(order)] for x in g])
self.phi_deriv = np.array([[leg(x, n, m=1) for n in range(order)] for x in g])
self.order = order
def to_weights(self, ux):
w = self.weights
p = self.phi_value
o = self.order
return [sum(ux[j] * p[j][n] * w[j] for j in range(o)) * 0.5 for n in range(o)]
def sample(self, uw, j):
return dot(uw, self.phi_value[j])
@property
def num_points(self):
return self.order
def dot(u, p):
return sum(u[i] * p[i] for i in range(u.shape[0]))
def rhs(physics, uw, cell, dx, uwdot):
import numpy as np
if physics.equation == "advection":
wavespeed = physics.wavespeed
def flux(ux):
return wavespeed * ux
def upwind(ul, ur):
if wavespeed > 0.0:
return flux(ul)
else:
return flux(ur)
elif physics.equation == "burgers":
def flux(ux):
return 0.5 * ux * ux
def upwind(ul, ur):
al = ul
ar = ur
if al > 0.0 and ar > 0.0:
return flux(ul)
elif al < 0.0 and ar < 0.0:
return flux(ur)
else:
return 0.0
nz = uw.shape[0]
pv = cell.phi_value
pf = cell.phi_faces
pd = cell.phi_deriv
w = cell.weights
h = [-1.0, 1.0]
for i in range(nz):
im1 = (i - 1 + nz) % nz
ip1 = (i + 1 + nz) % nz
uimh_l = dot(uw[im1], pf[1])
uimh_r = dot(uw[i], pf[0])
uiph_l = dot(uw[i], pf[1])
uiph_r = dot(uw[ip1], pf[0])
fimh = upwind(uimh_l, uimh_r)
fiph = upwind(uiph_l, uiph_r)
fs = [fimh, fiph]
ux = [cell.sample(uw[i], j) for j in range(cell.order)]
fx = [flux(u) for u in ux]
for n in range(cell.order):
udot_s = -sum(fs[j] * pf[j][n] * h[j] for j in range(2)) / dx
udot_v = +sum(fx[j] * pd[j][n] * w[j] for j in range(cell.num_points)) / dx
uwdot[i, n] = udot_s + udot_v
class Options(NamedTuple):
order: int = 1
integrator: str = "rk2"
class Physics(NamedTuple):
wavespeed: float = 1.0
equation: str = "advection" # or burgers
class Solver(SolverBase):
"""
An n-th order, discontinuous Galerkin solver for 1D scalar advection.
Time-advance integrator options:
- :code:`rk1`: Forward Euler
- :code:`rk2`: SSP-RK2 of Shu & Osher (1988; Eq. 2.15)
- :code:`rk3`: SSP-RK3 of Shu & Osher (1988; Eq. 2.18)
- :code:`rk3-sr02`: four-stage 3rd Order SSP-4RK3 of Spiteri & Ruuth (2002)
"""
def __init__(
self,
setup=None,
mesh=None,
time=0.0,
solution=None,
num_patches=1,
mode="cpu",
physics=dict(),
options=dict(),
):
import numpy as np
options = Options(**options)
physics = Physics(**physics)
cell = CellData(order=options.order)
if num_patches != 1:
raise ValueError("only works on one patch")
if type(mesh) != PlanarCartesianMesh:
raise ValueError("only the planar cartesian mesh is supported")
if mode != "cpu":
raise ValueError("only cpu mode is supported")
if setup.boundary_condition != "periodic":
raise ValueError("only periodic boundaries are supported")
if physics.equation not in ["advection", "burgers"]:
raise ValueError("physics.equation must be advection or burgers")
if options.integrator not in ["rk1", "rk2", "rk3", "rk3-sr02"]:
raise ValueError("options.integrator must be rk1|rk2|rk3|rk3-sr02")
if options.order <= 0:
raise ValueError("option.order must be greater than 0")
if solution is None:
num_zones = mesh.shape[0]
xf = mesh.faces(0, num_zones) # face coordinates
px = np.zeros([num_zones, cell.num_points, 1])
ux = np.zeros([num_zones, cell.num_points, 1])
uw = np.zeros([num_zones, cell.order, 1])
dx = mesh.dx
for i in range(num_zones):
for j in range(cell.num_points):
xsi = cell.gauss_points[j]
xj = xf[i] + (xsi + 1.0) * 0.5 * dx
setup.primitive(time, xj, px[i, j])
ux[...] = px[...] # the conserved variable is also the primitive
for i in range(num_zones):
uw[i] = cell.to_weights(ux[i])
self.conserved_w = uw
else:
self.conserved_w = solution
self.t = time
self.mesh = mesh
self.cell = cell
self._options = options
self._physics = physics
@property
def solution(self):
return self.conserved_w
@property
def primitive(self):
return self.conserved_w[:, 0]
@property
def time(self):
return self.t
@property
def maximum_cfl(self):
return 1.0
@property
def options(self):
return self._options._asdict()
@property
def physics(self):
return self._physics._asdict()
@property
def maximum_cfl(self):
k = self.cell.order - 1
if self._options.integrator == "rk1":
return 1.0 / (2 * k + 1)
if self._options.integrator == "rk2":
return 1.0 / (2 * k + 1)
if self._options.integrator == "rk3":
return 1.0 / (2 * k + 1)
if self._options.integrator == "rk3-sr02":
return 2.0 / (2 * k + 1)
def maximum_wavespeed(self):
if self._physics.equation == "advection":
return abs(self._physics.wavespeed)
elif self._physics.equation == "burgers":
return abs(self.conserved_w[:, 0]).max()
def advance(self, dt):
import numpy as np
def udot(u):
udot = np.zeros_like(u)
rhs(self._physics, u, self.cell, self.mesh.dx, udot)
return udot
if self._options.integrator == "rk1":
u = self.conserved_w
u += dt * udot(u)
if self._options.integrator == "rk2":
b1 = 0.0
b2 = 0.5
u = u0 = self.conserved_w.copy()
u = u0 * b1 + (1.0 - b1) * (u + dt * udot(u))
u = u0 * b2 + (1.0 - b2) * (u + dt * udot(u))
if self._options.integrator == "rk3":
b1 = 0.0
b2 = 3.0 / 4.0
b3 = 1.0 / 3.0
u = u0 = self.conserved_w.copy()
u = u0 * b1 + (1.0 - b1) * (u + dt * udot(u))
u = u0 * b2 + (1.0 - b2) * (u + dt * udot(u))
u = u0 * b3 + (1.0 - b3) * (u + dt * udot(u))
if self._options.integrator == "rk3-sr02":
u = u0 = self.conserved_w.copy()
u = u0 + 0.5 * dt * udot(u)
u = u + 0.5 * dt * udot(u)
u = 2.0 / 3.0 * u0 + 1.0 / 3.0 * (u + 0.5 * dt * udot(u))
u = u + 0.5 * dt * udot(u)
self.conserved_w = u
self.t += dt
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] |
pychron/lasers/power/composite_calibration_manager.py | ASUPychron/pychron | 31 | 2675 | <reponame>ASUPychron/pychron
# ===============================================================================
# Copyright 2012 <NAME>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ===============================================================================
# ============= enthought library imports =======================
from __future__ import absolute_import
from traits.api import HasTraits, Instance, DelegatesTo, Button, List, Any, Float
from traitsui.api import View, Item, VGroup, HGroup, Group, spring, TabularEditor
# ============= standard library imports ========================
import pickle
import os
from numpy import polyval
# ============= local library imports ==========================
from pychron.managers.manager import Manager
from pychron.database.selectors.power_calibration_selector import (
PowerCalibrationSelector,
)
from pychron.database.adapters.power_calibration_adapter import PowerCalibrationAdapter
from pychron.paths import paths
from pychron.graph.graph import Graph
from pychron.hardware.meter_calibration import MeterCalibration
"""
use a dbselector to select data
"""
class BoundsSelector(HasTraits):
graph = Instance(Graph)
def traits_view(self):
v = View(
Item("graph", show_label=False, style="custom"),
buttons=["OK", "Cancel"],
kind="livemodal",
)
return v
class CompositeCalibrationManager(Manager):
db = Instance(PowerCalibrationAdapter)
selector = Instance(PowerCalibrationSelector)
append = Button
replace = Button
load_graph = Button
save = Button
selected_calibrations = List
selected = Any
results = DelegatesTo("selector")
graph = Instance(Graph)
dclicked = Any
parent_name = "FusionsDiode"
power = Float
input = Float
def _power_changed(self):
pc = self._load_calibration()
pc
if pc is not None:
self.input, _ = pc.get_input(self.power)
def _load_calibration(self):
try:
p = self._get_calibration_path()
with open(p, "rb") as f:
pc = pickle.load(f)
except:
return
return pc
def _dclicked_changed(self):
s = self.selected
if s is not None:
s.bounds = None
s.load_graph()
s.graph.add_range_selector()
bc = BoundsSelector(graph=s.graph)
info = bc.edit_traits()
if info.result:
bounds = s.graph.plots[0].default_index.metadata["selections"]
s.bounds = bounds
s.calibration_bounds = (
polyval(s.coefficients, bounds[0]),
polyval(s.coefficients, bounds[1]),
)
def _append_fired(self):
s = self.selector.selected
if s is not None:
for si in s:
trs = list(si.traits().keys()).remove("graph")
self.selected_calibrations.append(si.clone_traits(traits=trs))
def _replace_fired(self):
s = self.selector.selected
trs = list(s.traits().keys()).remove("graph")
self.selected_calibrations = s.clone_traits(traits=trs)
def _save_fired(self):
self._dump_calibration()
def _dump_calibration(self):
pc = MeterCalibration()
coeffs = []
bounds = []
for s in self.selected_calibrations:
coeffs.append(s.coefficients)
bounds.append(s.calibration_bounds)
pc.coefficients = coeffs
pc.bounds = bounds
p = self._get_calibration_path()
self.info("saving calibration to {}".format(p))
with open(p, "wb") as f:
pickle.dump(pc, f)
def _get_calibration_path(self):
p = os.path.join(
paths.hidden_dir, "{}_power_calibration".format(self.parent_name)
)
return p
def _load_graph_fired(self):
g = self.graph
g.clear()
# g.new_plot(zoom=True, pan=True,
# padding=[40, 10, 10, 40]
# )
has_bounds = False
for i, s in enumerate(self.selected_calibrations):
if s.bounds:
has_bounds = True
elif has_bounds:
g.clear()
self._plot_factory(g)
self.warning_dialog("{} does not have its bounds set".format(s.rid))
break
s.load_graph(graph=g, new_plot=i == 0)
g.redraw()
def traits_view(self):
selector_grp = Group(Item("selector", style="custom", show_label=False))
transfer_grp = VGroup(
spring,
VGroup(Item("append", show_label=False), Item("replace", show_label=False)),
spring,
)
editor = TabularEditor(
adapter=self.selector.tabular_adapter(),
editable=False,
dclicked="object.dclicked",
selected="object.selected",
)
selected_grp = Item("selected_calibrations", editor=editor, show_label=False)
data_tab = Group(
HGroup(selector_grp, transfer_grp, selected_grp),
show_border=True,
label="Data",
)
process_tab = Group(
HGroup(
Item("power"),
Item("input", format_str=" %0.3f ", style="readonly"),
spring,
Item("save", show_label=False),
Item("load_graph", show_label=False),
),
Item("graph", style="custom", show_label=False),
show_border=True,
label="Process",
)
v = View(
VGroup(data_tab, process_tab),
resizable=True,
title="Composite {} Power Calibration".format(self.parent_name),
)
return v
def _graph_default(self):
g = Graph(
container_dict={
# 'fill_padding':True,
# 'bgcolor':'red',
"padding": 5
}
)
self._plot_factory(g)
return g
def _plot_factory(self, graph):
graph.new_plot(
zoom=True,
pan=True,
padding=[50, 10, 10, 40],
xtitle="Setpoint (%)",
ytitle="Measured Power (W)",
)
def _db_default(self):
if self.parent_name == "FusionsDiode":
name = paths.diodelaser_db
else:
name = paths.co2laser_db
db = PowerCalibrationAdapter(name=name, kind="sqlite")
db.connect()
return db
def _selector_default(self):
return self.db._selector_factory()
if __name__ == "__main__":
ccm = CompositeCalibrationManager()
ccm.configure_traits()
# ============= EOF =============================================
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library/modulemanager.py | l29ah/vk4xmpp | 77 | 94195 | <reponame>l29ah/vk4xmpp
# coding: utf-8
# This file is a part of VK4XMPP transport
# © simpleApps, 2015.
"""
Manages python modules as xmpppy handlers
"""
__author__ = "mrDoctorWho <<EMAIL>>"
__version__ = "1.1"
import os
from writer import *
from __main__ import Component, TransportFeatures, UserFeatures
def proxy(func):
def wrapper(type, *args):
if type:
for (handler, typ, ns, makefirst) in args:
if isinstance(ns, list):
while ns:
func(type, handler, typ, ns.pop(), makefirst=makefirst)
else:
func(type, handler, typ, ns, makefirst=makefirst)
return wrapper
@proxy
def register(*args, **kwargs):
Component.RegisterHandler(*args, **kwargs)
@proxy
def unregister(*args, **kwargs):
Component.UnregisterHandler(*args)
def addFeatures(features, list=TransportFeatures):
for feature in features:
list.add(feature)
def removeFeatures(features, list=TransportFeatures):
for feature in features:
if feature in list:
list.remove(feature)
class ModuleManager(object):
"""
A complete module manager.
You can easy load, reload and unload any module using it.
Modules are different from extensions:
While extensions works in main globals() and have their callbacks,
modules works in their own globals() and they're not affect to the core.
Unfortunately, most of modules are not protected from harm
so they may have affect on the connection
"""
loaded = set([])
@staticmethod
def getFeatures(module):
return getattr(module, "MOD_FEATURES_USER", [])
@classmethod
def __register(cls, module):
register(module.MOD_TYPE, *module.MOD_HANDLERS)
addFeatures(module.MOD_FEATURES)
addFeatures(cls.getFeatures(module), UserFeatures)
cls.loaded.add(module.__name__)
@classmethod
def __unregister(cls, module):
unregister(module.MOD_TYPE, *module.MOD_HANDLERS)
removeFeatures(module.MOD_FEATURES)
removeFeatures(cls.getFeatures(module), UserFeatures)
cls.loaded.remove(module.__name__)
@classmethod
def list(cls):
modules = []
for file in os.listdir("modules"):
name, ext = os.path.splitext(file)
if ext == ".py":
modules.append(name)
return modules
@classmethod
def __load(cls, name, reload_=False):
try:
if reload_:
module = sys.modules[name]
cls.__unregister(module)
module = reload(module)
else:
module = __import__(name, globals(), locals())
except Exception:
crashLog("modulemanager.load")
module = None
return module
@classmethod
def load(cls, list=[]):
result = []
errors = []
for name in list:
loaded = name in cls.loaded
module = cls.__load(name, loaded)
if not module:
errors.append(name)
continue
result.append(name)
cls.__register(module)
return (result, errors)
@classmethod
def unload(cls, list=[]):
result = []
for name in list:
if name in sys.modules:
cls.__unregister(sys.modules[name])
del sys.modules[name]
result.append(name)
return result
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] |
appengine-compat/exported_appengine_sdk/google/storage/speckle/proto/jdbc_type.py | speedplane/python-compat-runtime | 26 | 6849 | #!/usr/bin/env python
#
# Copyright 2007 Google Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
"""Python equivalent of jdbc_type.h.
Python definition of the JDBC type constant values defined in Java class
java.sql.Types. Since the values don't fall into the range allowed by
a protocol buffer enum, we use Python constants instead.
If you update this, update jdbc_type.py also.
"""
BIT = -7
TINYINT = -6
SMALLINT = 5
INTEGER = 4
BIGINT = -5
FLOAT = 6
REAL = 7
DOUBLE = 8
NUMERIC = 2
DECIMAL = 3
CHAR = 1
VARCHAR = 12
LONGVARCHAR = -1
DATE = 91
TIME = 92
TIMESTAMP = 93
BINARY = -2
VARBINARY = -3
LONGVARBINARY = -4
NULL = 0
OTHER = 1111
JAVA_OBJECT = 2000
DISTINCT = 2001
STRUCT = 2002
ARRAY = 2003
BLOB = 2004
CLOB = 2005
REF = 2006
DATALINK = 70
BOOLEAN = 16
ROWID = -8
NCHAR = -15
NVARCHAR = -9
LONGNVARCHAR = -16
NCLOB = 2011
SQLXML = 2009
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