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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
14malbright/music-utils | 14,611,478,786,129 | e99098280a8059e7982bd1525538a973faec6d3d | 795c7200bc283b9fee80dba1b6499d5104e40984 | /music_tools/utils.py | 6cbdc487f57a743ca7667ff5e2e6a17cb3f8babf | []
| no_license | https://github.com/14malbright/music-utils | 8dc1f63f2280d8847c5d452c22db9a03f524c440 | 097975cfbbd07df4ef5bd09967572d565f4ca450 | refs/heads/master | 2022-02-17T19:33:52.305064 | 2022-02-15T02:30:32 | 2022-02-15T02:30:32 | 180,013,121 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | # -*- coding: utf-8 -*-
from functools import wraps
import requests
def no_timeout(func):
@wraps(func)
def wrapped(*args, **kwargs):
while True:
try:
return func(*args, **kwargs)
except requests.ConnectionError:
print(f"ConnectionError on {func.__name__}. Retrying...")
continue
except requests.ReadTimeout:
print(f"ReadTimout on {func.__name__}. Retrying...")
continue
return wrapped
def take_x_at_a_time(items, x):
sequence = list(items)
quotient, remainder = divmod(len(sequence), x)
for i in range(quotient + bool(remainder)):
yield sequence[i * x : (i + 1) * x]
| UTF-8 | Python | false | false | 729 | py | 27 | utils.py | 21 | 0.554184 | 0.55144 | 0 | 27 | 26 | 73 |
kdheepak89/pypdevs | 7,868,380,096,290 | 67db3e6854bcc87a53114c9fce7b0cdd345047f6 | 823909fb73fb3b721385e59b22f021be4183198b | /performance/benchmarks/PHOLD.py | ebbc9128b2bc79eb23e9d11171f53908cdef070d | [
"Apache-2.0"
]
| permissive | https://github.com/kdheepak89/pypdevs | 302c69757b8eca443ca5993af287543f190185d9 | 979d708a184d342313cc7c2b6bd24225e475af3b | refs/heads/master | 2021-05-24T06:52:42.774852 | 2015-06-18T21:33:57 | 2015-06-18T21:33:57 | 37,686,146 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | # Copyright 2014 Modelling, Simulation and Design Lab (MSDL) at
# McGill University and the University of Antwerp (http://msdl.cs.mcgill.ca/)
#
# 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.
import sys
import os.path
import random
import pypdevs
from pypdevs.DEVS import AtomicDEVS, CoupledDEVS
class PHOLDModelState(object):
def __init__(self):
self.event = []
def copy(self):
a = PHOLDModelState()
a.event = [list(b) for b in self.event]
return a
def __eq__(self, other):
return other.event == self.event
def getProcTime(event):
random.seed(event)
return random.random()
def getNextDestination(event, nodenum, local, remote, percentageremotes):
random.seed(event)
if random.random() > percentageremotes or len(remote) == 0:
return local[int(random.uniform(0, len(local)))]
else:
return remote[int(random.uniform(0, len(remote)))]
def getRand(event):
# For determinism with a global random number generator
# This only works because each node runs its own Python interpreter
random.seed(event)
return int(random.uniform(0, 60000))
class HeavyPHOLDProcessor(AtomicDEVS):
def __init__(self, name, iterations, totalAtomics, modelnumber, local, remote, percentageremotes):
AtomicDEVS.__init__(self, name)
self.inport = self.addInPort("inport")
self.percentageremotes = percentageremotes
self.outports = []
self.totalAtomics = totalAtomics
self.modelnumber = modelnumber
for i in xrange(totalAtomics):
self.outports.append(self.addOutPort("outport_" + str(i)))
self.state = PHOLDModelState()
ev = modelnumber
self.state.event = [[ev, getProcTime(ev)]]
self.iterations = iterations
self.local = local
self.remote = remote
def timeAdvance(self):
if len(self.state.event) > 0:
return self.state.event[0][1]
else:
return float('inf')
def confTransition(self, inputs):
if len(self.state.event) > 1:
self.state.event = self.state.event[1:]
else:
self.state.event = []
for i in inputs[self.inport]:
self.state.event.append([i, getProcTime(i)])
for _ in xrange(self.iterations):
pass
return self.state
def intTransition(self):
self.state.event = self.state.event[1:]
return self.state
def extTransition(self, inputs):
if len(self.state.event) > 0:
self.state.event[0][1] -= self.elapsed
for i in inputs[self.inport]:
self.state.event.append([i, getProcTime(i)])
# Just keep ourself busy for some time
for _ in xrange(self.iterations):
pass
return self.state
def outputFnc(self):
if len(self.state.event) > 0:
i = self.state.event[0]
return {self.outports[getNextDestination(i[0], self.modelnumber, self.local, self.remote, self.percentageremotes)]: [getRand(i[0])]}
else:
return {}
class PHOLD(CoupledDEVS):
def __init__(self, nodes, atomicsPerNode, iterations, percentageremotes):
CoupledDEVS.__init__(self, "PHOLD")
self.processors = []
have = 0
destinations = []
cntr = 0
totalAtomics = nodes * atomicsPerNode
procs = []
for node in range(nodes):
procs.append([])
for i in range(atomicsPerNode):
procs[-1].append(atomicsPerNode*node+i)
cntr = 0
global distributed
for e, i in enumerate(procs):
allnoi = []
for e2, j in enumerate(procs):
if e2 != e:
allnoi.extend(j)
for j in i:
inoj = list(i)
inoj.remove(j)
self.processors.append(self.addSubModel(HeavyPHOLDProcessor("Processor_%d" % cntr, iterations, totalAtomics, cntr, inoj, allnoi, percentageremotes), e if distributed else 0))
cntr += 1
# All nodes created, now create all connections
for i in range(len(self.processors)):
for j in range(len(self.processors)):
if i == j:
continue
self.connectPorts(self.processors[i].OPorts[j], self.processors[j].inport)
try:
from mpi4py import MPI
distributed = MPI.COMM_WORLD.Get_size() > 1
except:
distributed = False
| UTF-8 | Python | false | false | 5,030 | py | 17 | PHOLD.py | 9 | 0.612326 | 0.604374 | 0 | 144 | 33.930556 | 190 |
syurskyi/Python_Topics | 18,167,711,666,390 | 680ddb6e52c93299793252fa5b7f5a0d9a3e0180 | e23a4f57ce5474d468258e5e63b9e23fb6011188 | /125_algorithms/_exercises/templates/_algorithms_challenges/leetcode/leetCode/BinarySearch/34_SearchForRange.py | 0e5cb506f050a5583b6d6c9fe898279cdd9dabb2 | []
| no_license | https://github.com/syurskyi/Python_Topics | 52851ecce000cb751a3b986408efe32f0b4c0835 | be331826b490b73f0a176e6abed86ef68ff2dd2b | refs/heads/master | 2023-06-08T19:29:16.214395 | 2023-05-29T17:09:11 | 2023-05-29T17:09:11 | 220,583,118 | 3 | 2 | null | false | 2023-02-16T03:08:10 | 2019-11-09T02:58:47 | 2022-11-03T01:22:28 | 2023-02-16T03:08:09 | 198,671 | 2 | 2 | 33 | Python | false | false | #! /usr/bin/env python
# -*- coding: utf-8 -*-
c.. Solution o..
# log(n) here.
___ firstAppear nums, target
left, right = 0, l..(nums) - 1
_____ left <= right:
mid = (left + right) / 2
__ target __ nums[mid] a.. mid - 1 >= left a.. target __ nums[mid - 1]:
right = mid - 1
____ target __ nums[mid]:
r_ mid
____ target > nums[mid]:
left = mid + 1
____
right = mid - 1
r_ -1
# log(n) again.
___ lastAppear(s.., nums, target
left, right = 0, l..(nums) - 1
_____ left <= right:
mid = (left + right) / 2
__ target __ nums[mid] a.. mid + 1 <= right a.. target __ nums[mid + 1]:
left = mid + 1
____ target __ nums[mid]:
r_ mid
____ target > nums[mid]:
left = mid + 1
____
right = mid - 1
r_ -1
___ searchRange nums, target
r_ (self.firstAppear(nums, target), self.lastAppear(nums, target))
"""
[]
0
[1,1,1,1]
1
[1,2,3,4,5]
3
[1,2,3,4,5]
6
"""
| UTF-8 | Python | false | false | 1,167 | py | 15,362 | 34_SearchForRange.py | 14,734 | 0.384747 | 0.353042 | 0 | 48 | 23.3125 | 84 |
wzx120606/TensorFlowTest | 13,486,197,312,993 | 17ff1bf8d15b4074f90373efbc5a3331a8273712 | 9805e2a9a6a2b5c4545adf7ef266d94a15850cd5 | /TensorFlow/查看模型训练动态图2.py | bb6ebb683d3e3d89d8b22cb0d1c761cde1088819 | []
| no_license | https://github.com/wzx120606/TensorFlowTest | 46a1552c067bf3866ddc195219b2da071e319294 | f54a9df2648f1e5c9b6d415e7b8743e6222d1c78 | refs/heads/master | 2022-01-12T10:18:59.242898 | 2019-06-27T02:57:56 | 2019-06-27T02:57:56 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
from tensorflow.contrib.tensorboard.plugins import projector
# 载入数据集，如果没有则会将mnist数据下载到对应路径下
mnist = input_data.read_data_sets("MNIST_data",one_hot=True)
# number of cycles
max_steps = 1001
# number of pictures
image_num = 3000
# file directory
DIR = "C:/Users/admin/PycharmProjects/TensorFlowTestNew/TensorFlow/"
# define session
sess = tf.Session()
# load pictures
embedding = tf.Variable(tf.stack(mnist.test.images[:image_num]), trainable=False, name='embedding')
# 命名空间
with tf.name_scope('base_values'):
# 批次大小
batch_size = 100
# 批次数
n_batch = mnist.train.num_examples // batch_size
keep_prob=tf.placeholder(tf.float32)
lr = tf.Variable(0.001,dtype=tf.float32)#步长
# 命名空间
with tf.name_scope('input'):
x=tf.placeholder(tf.float32,[None,784],name='x-input')
y=tf.placeholder(tf.float32,[None,10],name='y-input')
# show images 在tensorboard中显示
with tf.name_scope('input_reshape'):
image_shaped_input = tf.reshape(x, [-1, 28, 28, 1])
tf.summary.image('input', image_shaped_input, 10)
with tf.name_scope('first_layer'):
# 使用tf.truncated_normal初始化很多时候会比使用tf.zeros好很多
# tf.truncated_normal(shape, mean, stddev) :shape表示生成张量的维度，mean是均值，stddev是标准差。
# 这个函数产生正太分布，均值和标准差自己设定。这是一个截断的产生正太分布的函数，就是说产生正太分布的值如果与均值的差值大于两倍的标准差，那就重新生成。
# 和一般的正太分布的产生随机数据比起来，这个函数产生的随机数与均值的差距不会超过两倍的标准差，但是一般的别的函数是可能的。
w1 = tf.Variable(tf.truncated_normal(shape=[784,500],stddev=0.1),name="w1")
b1 = tf.Variable(tf.zeros([500])+0.1,name="b1")
L1 = tf.nn.tanh(tf.matmul(x,w1)+b1,name="L1")
L1_drop=tf.nn.dropout(L1,keep_prob)#相当于下一层的特征输入
with tf.name_scope('second_layer'):
w2 = tf.Variable(tf.truncated_normal(shape=[500,300],stddev=0.1),name="w2")
b2 = tf.Variable(tf.zeros([300])+0.1,name="b2")
L2 = tf.nn.tanh(tf.matmul(L1_drop,w2)+b2,name="L2")
L2_drop=tf.nn.dropout(L2,keep_prob,name="L2_drop")#相当于下一层的特征输入
with tf.name_scope('output_layer'):
w3 = tf.Variable(tf.truncated_normal(shape=[300,10],stddev=0.1),name="w3")
b3 = tf.Variable(tf.zeros([10])+0.1,name="b3")
prediction = tf.nn.softmax(tf.matmul(L2_drop,w3)+b3,name="prediction")
with tf.name_scope('train'):
with tf.name_scope('loss'):
# loss = tf.reduce_mean(tf.square(y-prediction))#二次代价函数
loss = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(labels=y,logits=prediction))#对数似然代价函数（）或者说叫做用于softmax的交叉熵代价函数
with tf.name_scope('train_step'):
# train_step = tf.train.GradientDescentOptimizer(.1).minimize(loss)#梯度下降训练
# train_step = tf.train.AdadeltaOptimizer(1e-3).minimize(loss)#Adadelta算法优化器训练
train_step = tf.train.AdamOptimizer(lr).minimize(loss)#Adam算法优化器训练
with tf.name_scope('accuracy'):
# 结果存放布尔列表中
correct_predition = tf.equal(tf.argmax(y,1),tf.argmax(prediction,1))
# 准确率
accuracy = tf.reduce_mean(tf.cast(correct_predition,tf.float32))
with tf.name_scope('init_value'):
inti = tf.global_variables_initializer()
# create metadata file
if tf.gfile.Exists(DIR + 'projector/projector/metadata.tsv'):
tf.gfile.DeleteRecursively(DIR + 'projector/projector')
tf.gfile.MkDir(DIR + 'projector/projector')
with open(DIR + 'projector/projector/metadata.tsv', 'w') as f:
labels = sess.run(tf.argmax(mnist.test.labels[:], 1))
for i in range(image_num):
f.write(str(labels[i]) + '\n')
# combine all summaries
merged = tf.summary.merge_all()
projector_writer = tf.summary.FileWriter(DIR + 'projector/projector', sess.graph)
saver = tf.train.Saver()
config = projector.ProjectorConfig()
embed = config.embeddings.add()
embed.tensor_name = embedding.name
embed.metadata_path = DIR + 'projector/projector/metadata.tsv'#测试集中对应的前image_num的label值
embed.sprite.image_path = DIR + 'projector/data/numbers.jpg'#这张图片顺序对应测试集的样本（测试集也是10000个样本）
# embed.sprite.image_path = DIR + 'projector/data/numberschild.jpg'
embed.sprite.single_image_dim.extend([28, 28])
projector.visualize_embeddings(projector_writer, config)
with tf.Session() as sess:
sess.run(inti)
tf.summary.FileWriter('logs/',sess.graph)#在terminal视图运行命令：tensorboard --logdir=C:\Users\admin\PycharmProjects\TensorFlowTestNew\TensorFlow\logs
for epoch in range(1):
sess.run(tf.assign(lr,lr*0.95))
for batch in range(n_batch):
batch_xs,batch_ys = mnist.train.next_batch(batch_size)
run_options = tf.RunOptions(trace_level=tf.RunOptions.FULL_TRACE)
run_metadata = tf.RunMetadata()
sess.run([merged,train_step],feed_dict={x:batch_xs,y:batch_ys,keep_prob:1.0}, options=run_options,run_metadata=run_metadata)
l_r = sess.run(lr);
acc = sess.run(accuracy,feed_dict={x:mnist.test.images,y:mnist.test.labels,keep_prob:1.0})
print("epoch:",epoch," acc:",acc,"l_r:",l_r)
saver.save(sess, DIR + 'projector/projector/a_model.ckpt', global_step=max_steps)
projector_writer.close | UTF-8 | Python | false | false | 5,621 | py | 38 | 查看模型训练动态图2.py | 35 | 0.706942 | 0.681239 | 0 | 112 | 43.125 | 147 |
jcafiero/Courses | 4,690,104,324,787 | 45c8658784dff7f0988340eb7bc631687669a7d6 | 4f9e30387653a61cdc7c02fa1731c02aaea8aa59 | /CS115/Homework/hw6.py | de60b9ed8d1434571401d8c55973265c5ce984bb | []
| no_license | https://github.com/jcafiero/Courses | 03a09e9f32e156b37de6da2a0b052ded99ca4d07 | c82bc4bbc5657643dabc3a01fadfd961c33ebf5e | refs/heads/master | 2022-02-17T14:40:27.073191 | 2019-10-06T23:58:23 | 2019-10-06T23:58:23 | 103,605,315 | 1 | 1 | null | false | 2019-10-07T00:05:39 | 2017-09-15T02:36:30 | 2019-10-06T23:58:26 | 2019-10-07T00:05:29 | 26,596 | 0 | 2 | 3 | JavaScript | false | false | '''
Created on March 9, 2015
@author: Jennifer Cafiero, Ayse Akin
Pledge: I pledge my honor that I have abided by the Stevens Honor System.
CS115 - Hw 6
'''
# Number of bits for data in the run-length encoding format.
# The assignment refers to this as k.
COMPRESSED_BLOCK_SIZE = 5
# Number of bits for data in the original format.
MAX_RUN_LENGTH = 2 ** COMPRESSED_BLOCK_SIZE - 1
# Do not change the variables above.
# Write your functions here. You may use those variables in your code.
def numToBinary(s):
'''Converts a decimal number to binary'''
if s == 0:
return ""
return numToBinary(s/2) + str(s % 2)
def numBits(s, k):
'''Utilizes the numToBinary function to create binary strings that are k number of bits'''
if len(numToBinary(s)) < k:
return '0' * (k - len(numToBinary(s))) + numToBinary(s)
return numToBinary(s)
def compress(s):
'''Takes a binary string of length 64 and returns a run-length encoding of the input string.'''
def compressHelper(s, curr, count):
if s == "":
return ''
if count == 31:
return numToBinary(count) + compressHelper(s, str(1-int(curr)), 0)
if s[0] != curr:
return numToBinary(count) + compressHelper(s, str(1-int(curr)), 0)
return compressHelper(s, curr, count+1)
return compressHelper(s,'0', 0)
print compress('10'*32)
| UTF-8 | Python | false | false | 1,603 | py | 287 | hw6.py | 138 | 0.562695 | 0.542732 | 0 | 58 | 25.482759 | 99 |
phongluudn1997/leet_code | 11,802,570,146,311 | f178f1d7a021341180cf409f506d440d0be39c5a | c583fbc131307c4f868c14c08525efec0f325bef | /magic_index.py | 28e73a06306f0da59c1feb3770dfbe595d7f722c | []
| no_license | https://github.com/phongluudn1997/leet_code | 8c7ccc8597c754c3ce0f794667777c3acea50fa2 | c0fc0a53f44967b66afb101daaf6be05dedec24d | refs/heads/master | 2021-03-28T11:56:02.646965 | 2021-03-13T10:57:09 | 2021-03-13T10:57:09 | 247,861,580 | 1 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | def magic_index(array):
if not len(array):
return "No magic index found."
middle_index = len(array) // 2
if array[middle_index] == middle_index:
return middle_index
if array[middle_index] > middle_index:
return magic_index(array[:middle_index])
else:
return magic_index(array[middle_index:])
print(magic_index([-1, 1, 2, 4])) | UTF-8 | Python | false | false | 379 | py | 74 | magic_index.py | 74 | 0.622691 | 0.609499 | 0 | 13 | 28.230769 | 48 |
ndkmbsr/L2 | 14,620,068,726,073 | 86e3de44dd62da5d29d28148cc1c9c7fa6c86b4c | adb773515e226668e086c77a4d2ff2e4c65838d8 | /goruntu_isleme/MNIST_HOG_SVM.py | fc5139376a08f51ead9bac281b82dfd600db7a87 | []
| no_license | https://github.com/ndkmbsr/L2 | d455e5ece503c25963d0e35dd70982d4a697250d | 2c9bcfa1ba860e3c475b877cfdef7abd913c169a | refs/heads/master | 2020-04-11T16:23:45.796337 | 2018-12-15T17:15:09 | 2018-12-15T17:15:09 | 161,922,660 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from skimage.feature import hog
from sklearn import svm
import numpy as np
from sklearn.metrics import confusion_matrix
from datetime import datetime
import warnings
warnings.filterwarnings('ignore')
''''Main Function'''
start_time=datetime.now()
train_images=np.load('train_images.npy')
test_images=np.load('test_images.npy')
train_labels=np.load('train_labels.npy')
test_labels=np.load('test_labels.npy')
n=1152;
hog_feature_train=np.zeros([len(train_images),n]);
hog_feature_test=np.zeros([len(test_images),n]);
for i in range(len(train_images)):
hog_values = hog(train_images[i,:,:], orientations=8, pixels_per_cell=(4,4),cells_per_block=(2,2))
hog_feature_train[i]=hog_values
for i in range(len(test_images)):
hog_values = hog(test_images[i,:,:], orientations=8, pixels_per_cell=(4,4),cells_per_block=(2,2))
hog_feature_test[i]=hog_values
model = svm.SVC(decision_function_shape='ovo')
#model = svm.SVC()
model.fit(hog_feature_train,train_labels)
label_estimate=model.predict(hog_feature_test)
conf_matrix=confusion_matrix(test_labels,label_estimate)
accuracy_rate=(sum(np.diag(conf_matrix)))/np.sum(conf_matrix)*100;
print("Accuracy Rate: " ,accuracy_rate)
'stop time'
stop_time=datetime.now()
elapsed_time=stop_time-start_time
print("Elapsed Time: " +str(elapsed_time))
| UTF-8 | Python | false | false | 1,324 | py | 39 | MNIST_HOG_SVM.py | 3 | 0.72432 | 0.71148 | 0 | 44 | 29.090909 | 105 |
ponyatov/metaLold | 12,902,081,787,796 | 2ab2b717db41f7774a514546fb316f5f3e289faa | a20a1bb293c18897133e6f4e6dde75f803654c94 | /book/prolog/yield00.py | 6731898851d3f8c33826af69e5d5fdd2d72c3d09 | []
| no_license | https://github.com/ponyatov/metaLold | e7c0fe94002251e982f003d167a64a5fee2e2fed | e2f0680c945cf4fe44747d0102647740b6b1f740 | refs/heads/master | 2023-04-10T07:30:20.818855 | 2020-10-01T11:12:55 | 2020-10-01T11:12:55 | 173,776,238 | 0 | 2 | null | false | 2021-04-20T18:33:06 | 2019-03-04T16:00:23 | 2020-10-01T11:12:59 | 2021-04-20T18:33:06 | 19,202 | 5 | 2 | 4 | TeX | false | false | def person():
yield "Chelsea"
yield "Hillary"
yield "Bill"
def main():
for p in person():
print(p)
main() | UTF-8 | Python | false | false | 130 | py | 283 | yield00.py | 93 | 0.546154 | 0.546154 | 0 | 9 | 13.555556 | 22 |
FidelAlberto/Jarvis | 8,452,495,676,054 | 0b48fd2ec120a332be882d50d2be8f70e7cb64b4 | 857e986c54550246006b3b5c120e285ff6604680 | /Program_Files/nlp/lemmatizer.py | f84553100653998e9ab27c79550bff760c11fac1 | []
| no_license | https://github.com/FidelAlberto/Jarvis | f8166c264a162b4aec15f4bb83d77c855938fa7b | 6218809f15bef844647f745e623e5e61dd725315 | refs/heads/master | 2022-04-07T23:26:26.075591 | 2020-02-26T20:16:18 | 2020-02-26T20:16:18 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from nltk.stem import WordNetLemmatizer
lemmatizer = WordNetLemmatizer()
my_tokens = ["leaves","calves","books","surprising","data mining","girls","goes","puppies"]
for word in my_tokens:
print(lemmatizer.lemmatize(word))
| UTF-8 | Python | false | false | 226 | py | 15 | lemmatizer.py | 14 | 0.743363 | 0.743363 | 0 | 5 | 44.2 | 91 |
iut-ibk/PowerVIBe | 3,221,225,510,993 | 1705adedee64755654e2da502b4582969becad03 | 58a167111cd91f21715b2ab0810833781ff77fb9 | /scripts/PowerVIBe/importDAE.py | b44c53a00467dea6a8e8ffe76763382c58158188 | []
| no_license | https://github.com/iut-ibk/PowerVIBe | 33fd68bd219925e7a704d8833b8ab3463a257bcb | fb820fe77a6311fe20bf286943ebb82a8da5f48b | refs/heads/master | 2016-09-03T07:26:44.500093 | 2014-04-10T14:53:07 | 2014-04-10T14:53:07 | 5,998,512 | 1 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | # -*- coding: utf-8 -*-
"""
Created on Thu Nov 15 10:00:56 2012
@author: christianurich
"""
import collada
from pydynamind import *
class ImportDAE(Module):
def __init__(self):
Module.__init__(self)
self.createParameter("FileName", FILENAME, "filename")
self.FileName = ""
self.dummy = View("dummy", SUBSYSTEM, MODIFY)
self.object = View("Objects", COMPONENT, WRITE)
self.geometry = View("Geometry", FACE, WRITE)
self.datastream = []
self.datastream.append(self.object)
self.datastream.append(self.geometry)
self.datastream.append(self.dummy)
self.createParameter("OffsetX", DOUBLE, "offsetx")
self.OffsetX = 0.0
self.createParameter("OffsetY", DOUBLE, "offsety")
self.OffsetY = 0.0
self.createParameter("ScaleX", DOUBLE, "scalesetx")
self.ScaleX = 1.0
self.createParameter("ScaleY", DOUBLE, "scalesety")
self.ScaleY = 1.0
self.createParameter("ScaleZ", DOUBLE, "scalesetz")
self.ScaleZ = 1.0
self.addData("sys", self.datastream)
def run(self):
sys = self.getData("sys")
cmp = Component()
cmp = sys.addComponent(cmp, self.object)
print self.FileName
col = collada.Collada(self.FileName, ignore=[collada.DaeUnsupportedError, collada.DaeBrokenRefError])
for geom in col.geometries:
for triset in geom.primitives:
trilist = list(triset)
elements = len(trilist)
for i in range(elements):
nl = nodevector()
for j in range(3):
node = triset.vertex[triset.vertex_index][i][j]
n = sys.addNode(float(node[0]* self.ScaleX + self.OffsetX), float(node[1]* self.ScaleY+self.OffsetY), float(node[2])* self.ScaleZ)
nl.append(n)
nl.append(nl[0])
f = sys.addFace(nl, self.geometry)
cmp.getAttribute("Geometry").setLink("Geometry", f.getUUID())
| UTF-8 | Python | false | false | 2,297 | py | 83 | importDAE.py | 73 | 0.522421 | 0.510231 | 0 | 57 | 38.22807 | 154 |
UwePabst91052/Exercises | 10,204,842,343,394 | 638cf943746a1595d727f8d9a30098346ff7adc4 | 3e6fbf27b5b4dac9a26589343981230c3214c5c8 | /TeeUhr.py | 7b269ebf28a0d02121f220a63b127618dc45eb57 | []
| no_license | https://github.com/UwePabst91052/Exercises | 9c08c6a6ee83e5be77eebcc579fef6cea8750cc1 | 9ea430599d63b4da53ddc2c103d2adeae9c105e5 | refs/heads/master | 2023-05-26T13:20:11.493249 | 2023-05-10T14:31:01 | 2023-05-10T14:31:01 | 264,718,193 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'C:\Users\pabst\PycharmProjects\Übungen\TeeUhr.ui'
#
# Created by: PyQt5 UI code generator 5.14.2
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_MainWindow(object):
def setupUi(self, MainWindow):
MainWindow.setObjectName("MainWindow")
MainWindow.resize(235, 217)
MainWindow.setWindowTitle("Tee Uhr")
self.centralwidget = QtWidgets.QWidget(MainWindow)
self.centralwidget.setObjectName("centralwidget")
self.label = QtWidgets.QLabel(self.centralwidget)
self.label.setGeometry(QtCore.QRect(50, 10, 131, 61))
font = QtGui.QFont()
font.setFamily("Impact")
font.setPointSize(30)
font.setItalic(False)
font.setKerning(True)
self.label.setFont(font)
self.label.setLayoutDirection(QtCore.Qt.LeftToRight)
self.label.setFrameShape(QtWidgets.QFrame.WinPanel)
self.label.setFrameShadow(QtWidgets.QFrame.Sunken)
self.label.setLineWidth(3)
self.label.setMidLineWidth(0)
self.label.setText("00:00")
self.label.setScaledContents(False)
self.label.setAlignment(QtCore.Qt.AlignRight|QtCore.Qt.AlignTrailing|QtCore.Qt.AlignVCenter)
self.label.setObjectName("label")
self.pb_inc_seconds = QtWidgets.QPushButton(self.centralwidget)
self.pb_inc_seconds.setGeometry(QtCore.QRect(180, 10, 21, 23))
self.pb_inc_seconds.setObjectName("pb_inc_seconds")
self.pb_dec_seconds = QtWidgets.QPushButton(self.centralwidget)
self.pb_dec_seconds.setGeometry(QtCore.QRect(180, 50, 21, 23))
self.pb_dec_seconds.setObjectName("pb_dec_seconds")
self.pb_inc_minute = QtWidgets.QPushButton(self.centralwidget)
self.pb_inc_minute.setGeometry(QtCore.QRect(30, 10, 21, 23))
self.pb_inc_minute.setObjectName("pb_inc_minute")
self.pb_dec_minute = QtWidgets.QPushButton(self.centralwidget)
self.pb_dec_minute.setGeometry(QtCore.QRect(30, 50, 21, 23))
self.pb_dec_minute.setObjectName("pb_dec_minute")
self.pb_start_timer = QtWidgets.QPushButton(self.centralwidget)
self.pb_start_timer.setGeometry(QtCore.QRect(70, 150, 75, 23))
self.pb_start_timer.setObjectName("pb_start_timer")
self.pb_seven = QtWidgets.QPushButton(self.centralwidget)
self.pb_seven.setGeometry(QtCore.QRect(20, 90, 75, 23))
self.pb_seven.setObjectName("pb_seven")
self.pb_three = QtWidgets.QPushButton(self.centralwidget)
self.pb_three.setGeometry(QtCore.QRect(130, 90, 75, 23))
self.pb_three.setObjectName("pb_three")
self.pb_five = QtWidgets.QPushButton(self.centralwidget)
self.pb_five.setGeometry(QtCore.QRect(20, 120, 75, 23))
self.pb_five.setObjectName("pb_five")
self.pb_six_30 = QtWidgets.QPushButton(self.centralwidget)
self.pb_six_30.setGeometry(QtCore.QRect(130, 120, 75, 23))
self.pb_six_30.setObjectName("pb_six_30")
MainWindow.setCentralWidget(self.centralwidget)
self.menubar = QtWidgets.QMenuBar(MainWindow)
self.menubar.setGeometry(QtCore.QRect(0, 0, 235, 21))
self.menubar.setObjectName("menubar")
MainWindow.setMenuBar(self.menubar)
self.statusbar = QtWidgets.QStatusBar(MainWindow)
self.statusbar.setObjectName("statusbar")
MainWindow.setStatusBar(self.statusbar)
self.retranslateUi(MainWindow)
self.pb_inc_minute.clicked.connect(MainWindow.increment_minutes)
self.pb_dec_minute.clicked.connect(MainWindow.decrement_minutes)
self.pb_inc_seconds.clicked.connect(MainWindow.increment_seconds)
self.pb_dec_seconds.clicked.connect(MainWindow.decrement_seconds)
self.pb_start_timer.clicked.connect(MainWindow.start_timer)
self.pb_seven.clicked.connect(MainWindow.start_seven_minutes)
self.pb_three.clicked.connect(MainWindow.start_three_minutes)
self.pb_five.clicked.connect(MainWindow.start_five_minutes)
self.pb_six_30.clicked.connect(MainWindow.start_six_thirty_minutes)
QtCore.QMetaObject.connectSlotsByName(MainWindow)
def retranslateUi(self, MainWindow):
_translate = QtCore.QCoreApplication.translate
self.pb_inc_seconds.setText(_translate("MainWindow", "+"))
self.pb_dec_seconds.setText(_translate("MainWindow", "-"))
self.pb_inc_minute.setText(_translate("MainWindow", "+"))
self.pb_dec_minute.setText(_translate("MainWindow", "-"))
self.pb_start_timer.setText(_translate("MainWindow", "Start"))
self.pb_seven.setText(_translate("MainWindow", "7 min"))
self.pb_three.setText(_translate("MainWindow", "3 min"))
self.pb_five.setText(_translate("MainWindow", "5 min"))
self.pb_six_30.setText(_translate("MainWindow", "6:30 min"))
if __name__ == "__main__":
import sys
app = QtWidgets.QApplication(sys.argv)
MainWindow = QtWidgets.QMainWindow()
ui = Ui_MainWindow()
ui.setupUi(MainWindow)
MainWindow.show()
sys.exit(app.exec_())
| UTF-8 | Python | false | false | 5,179 | py | 26 | TeeUhr.py | 16 | 0.688104 | 0.662225 | 0 | 105 | 48.314286 | 103 |
bregnery/UFDiMuonsAnalyzer | 16,664,473,119,817 | 08232cbb4433e6dfa6554306a3393c0a9f9c906e | 6c53d1eefbcddd4d2fbc3caca02616af14dae5d9 | /UFDiMuonsAnalyzer/test/UFDiMuonAnalyzer.py | 72802a0c0a3f3d6d4e41324ab0a285713d65730b | []
| no_license | https://github.com/bregnery/UFDiMuonsAnalyzer | 691950774bf7496980cca5ca709b8c51ebc7bc32 | 91813ccc4f309b9be46f1ee0d3a59121c66ec949 | refs/heads/master | 2020-12-12T06:49:39.015086 | 2016-03-11T23:20:53 | 2016-03-11T23:20:53 | 40,377,298 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import FWCore.ParameterSet.Config as cms
process = cms.Process("UFDiMuonAnalyzer")
thisIsData = False
if thisIsData:
print 'Running over data sample'
else:
print 'Running over MC sample'
process.load("FWCore.MessageService.MessageLogger_cfi")
#process.MessageLogger.cerr.FwkReport.reportEvery = 1000
##process.MessageLogger.destinations.append("detailedInfo")
##process.MessageLogger.detailedInfo = cms.untracked.PSet(
## threshold = cms.untracked.string("INFO"),
## categories = cms.untracked.vstring("UFHLTTests")
##)
process.load("Configuration.StandardSequences.MagneticField_38T_cff")
## Geometry and Detector Conditions (needed for a few patTuple production steps)
process.load("Configuration.Geometry.GeometryIdeal_cff")
process.load('Configuration.EventContent.EventContent_cff')
process.load("Configuration.StandardSequences.FrontierConditions_GlobalTag_cff")
from Configuration.AlCa.autoCond import autoCond
# Get a sample from our collection of samples
from Samples_v3 import ggToHToMuMu_PU40bx50 as s
# global tag, should get this automatically from the sample data structure
globalTag = "PLS170_V6AN2"
print 'Loading Global Tag: '+globalTag
process.load("Configuration.StandardSequences.FrontierConditions_GlobalTag_cff")
process.GlobalTag.globaltag = globalTag+"::All"
# ------------ PoolSource -------------
readFiles = cms.untracked.vstring();
# Get list of files from the sample we loaded
readFiles.extend(s.files);
process.maxEvents = cms.untracked.PSet( input = cms.untracked.int32(100) )
process.source = cms.Source("PoolSource",fileNames = readFiles)
process.options = cms.untracked.PSet( wantSummary = cms.untracked.bool(False) )
process.source.lumisToProcess = cms.untracked.VLuminosityBlockRange()
# use a JSON file locally
#import FWCore.PythonUtilities.LumiList as LumiList
#process.source.lumisToProcess = LumiList.LumiList(filename = 'goodList.json').getVLuminosityBlockRange()
# -------- PoolSource END -------------
#===============================================================================
# Clean the Jets from good muons, apply loose jet Id
ccMuPreSel = "pt > 15. && isGlobalMuon "
ccMuPreSel += " && globalTrack().normalizedChi2 < 10 "
ccMuPreSel += " && isPFMuon "
ccMuPreSel += " && innerTrack().hitPattern().trackerLayersWithMeasurement > 5 "
ccMuPreSel += " && innerTrack().hitPattern().numberOfValidPixelHits > 0 "
ccMuPreSel += " && globalTrack().hitPattern().numberOfValidMuonHits > 0 "
ccMuPreSel += " && numberOfMatchedStations > 1 && dB < 0.2 && abs(eta) < 2.4 "
ccMuPreSel += " && ( chargedHadronIso + max(0.,neutralHadronIso + photonIso - 0.5*puChargedHadronIso) ) < 0.12 * pt"
jetSelection = 'neutralEmEnergy/energy < 0.99 '
jetSelection += ' && neutralHadronEnergy/energy < 0.99 '
jetSelection += ' && (chargedMultiplicity + neutralMultiplicity) > 1 '
jetSelection += ' && ((abs(eta)>2.4) || (chargedMultiplicity > 0 '
jetSelection += ' && chargedHadronEnergy/energy > 0.0'
jetSelection += ' && chargedEmEnergy/energy < 0.99))'
process.cleanJets = cms.EDProducer("PATJetCleaner",
src = cms.InputTag("slimmedJets"),
preselection = cms.string(jetSelection),
checkOverlaps = cms.PSet(
muons = cms.PSet(
src = cms.InputTag("slimmedMuons"),
algorithm = cms.string("byDeltaR"),
preselection = cms.string(ccMuPreSel),
deltaR = cms.double(0.5),
checkRecoComponents = cms.bool(False),
pairCut = cms.string(""),
requireNoOverlaps = cms.bool(True),
),
#electrons = cms.PSet(
# src = cms.InputTag("slimmedElectrons"),
# algorithm = cms.string("byDeltaR"),
# preselection = cms.string(ccElePreSel),
# deltaR = cms.double(0.5),
# checkRecoComponents = cms.bool(False),
# pairCut = cms.string(""),
# requireNoOverlaps = cms.bool(True),
#),
),
finalCut = cms.string('')
)
process.TFileService = cms.Service("TFileService", fileName = cms.string("stage_1_"+s.name+".root") )
#===============================================================================
# UFDiMuonAnalyzer
if thisIsData:
process.load("UfHMuMuCode.UFDiMuonsAnalyzer.UFDiMuonAnalyzer_cff")
else:
process.load("UfHMuMuCode.UFDiMuonsAnalyzer.UFDiMuonAnalyzer_MC_cff")
process.dimuons = process.DiMuons.clone()
process.dimuons.pfJetsTag = cms.InputTag("cleanJets")
#===============================================================================
process.p = cms.Path(#
process.cleanJets*
process.dimuons
)
#process.outpath = cms.EndPath()
## #Test to dump file content
## process.output = cms.OutputModule("PoolOutputModule",
## outputCommands = cms.untracked.vstring("keep *"),
## fileName = cms.untracked.string('dump.root')
## )
##
## process.out_step = cms.EndPath(process.output)
#===============================================================================
#process.source.fileNames.extend(
#[
##'file:/data/0b/digiovan/code/higgs/dev/addEle/CMSSW_5_3_3_patch3/src/UserArea/test/DYJetsToLL.root'
##"file:/data/uftrig01b/jhugon/hmumu/devNtupler/testFiles/VBFHToMM_M125_8TeV-powheg-pythia6-tauola-RECO_1.root"
##"file:/data/uftrig01b/digiovan/root/higgs/CMSSW_5_3_3_patch3/testPriVtxConstr/TTJetsSkims/TTJets_10_1_crI.root"
##"file:/home/jhugon/scratchRaid7/hmumu/recoData/VBFHToMM_M125_8TeV-powheg-pythia6-tauola-RECO_1.root"
#]
#)
#process.out.outputCommands = cms.untracked.vstring("keep *")
#process.outpath = cms.EndPath(process.out)
#process.maxEvents = cms.untracked.PSet( input = cms.untracked.int32(20) )
| UTF-8 | Python | false | false | 5,924 | py | 2 | UFDiMuonAnalyzer.py | 2 | 0.6342 | 0.618501 | 0 | 145 | 39.841379 | 116 |
ShayLn/py-fighter | 17,944,373,399,712 | e9ae4aaf3ae4d097e2d66a903ae07922421af2b2 | 52a8ba52146c6943e00b34b8f5823b21f2622fe3 | /pyfighter.py | f03166b36baa6fdfa97506d30d43369b33911b6c | [
"MIT"
]
| permissive | https://github.com/ShayLn/py-fighter | 718db5d6f889abd2f078b2c11ad0ffd9d219cd24 | 01ace29afb066e6d5965d1fd460c5939c8b8c81b | refs/heads/master | 2023-03-29T12:11:56.412382 | 2021-01-05T10:42:12 | 2021-01-05T10:42:12 | 327,468,085 | 0 | 0 | MIT | true | 2021-01-07T14:18:40 | 2021-01-07T01:09:33 | 2021-01-07T01:09:34 | 2021-01-05T10:42:16 | 106,958 | 0 | 0 | 1 | null | false | false | ''' Pyfighter (working title)
A long time ago in a galaxy far, far away there existed in person
tuition. But in the year 2020, COVID struck. All semester modules have
been 100% online and you haven't seen your professors.
So do they exist? Are they just a figment of your imagination?
To cut costs, the university created AI professors to deliver your
lectures and set your coursework. Exam season approaches and the evil
Darth Virus has hacked your professors, multiplying them and making your
exams harder.
Only you can save your degree...
Pyfighter is an 8-bit side scrolling, infinite level platform game,
produced in python using PyGame as part on an MSc by R. Soane, R.
Danevicius, and S. Mistry. Inspired by super street fighter, super
smash bros and Mario, they created a customisable and addictive game
that gets progressively harder.
This file forms a start menu for the game. When selected, the game
function is loaded as a new instance of pygame within the same window.
Implemented in this way so that whenever the player quits the game, it
goes back to the menu.
'''
### Library Imports
import os
import webbrowser
import json
import pygame
from screens.game import pyfighterGame
from screens.settings import SettingsMenu
from classes.generalfunctions import quitGame
from classes.menu import Menu
from classes.menu import Button
from classes.text import Text
### Important Game Variables from JSON
with open('json/config.JSON') as config_file:
config = json.load(config_file)
# Colour tuples and font sizesd
colour = config['colour']
font_size = config['font_size']
# Important screen variables
screen_width = config['screen_dims'][0]
screen_height = config['screen_dims'][1]
max_fps = config['max_fps']
game_name = config['game_name']
### Setting up Screen and clock
menu_screen = pygame.display.set_mode((screen_width, screen_height))
pygame.display.set_caption(game_name)
clock = pygame.time.Clock()
### Setting Icon
logo_image = pygame.image.load(config['logo_location'])
pygame.display.set_icon(logo_image)
menu_background = config['start_menu_background']
menu_background_path = config['menu_music']
### Setting up Menu
# Menu Functions - These functions are passed into each menu button
def playGame():
pyfighterGame()
playMusic(menu_background_path)
def playMusic(music_path):
### Setting up game music
# - Music code inspired by code here:
# https://riptutorial.com/pygame/example/24563/example-to-add-musi
# c-in-pygame
# - Found detail on setting volume on pygame docs
pygame.mixer.init()
pygame.mixer.music.load(music_path)
pygame.mixer.music.play(-1)
def loadAbout():
webbrowser.open('https://www.pyfighter.xyz/',
new=2)
def runSettings():
return 'settings'
# String names
menu_title = game_name
play_text = 'Play'
about_text = 'About'
settings_text = 'Settings'
quit_text = 'Quit'
# Title position
title_x = screen_width // 2
title_y = screen_height // 9
# Calculating (x,y) coords of buttons
width_unit = screen_width // 6
height_unit = screen_height // 2
major_button_dims = (192, 64)
offset = 20
about_position = (screen_width - 64 - offset, 32 + offset)
# Creating pygame string objects
title_obj = Text(menu_screen, (title_x, title_y),
font_size['title'], menu_title, 'purple')
play_button = Button(menu_screen, play_text,
(1 * width_unit, height_unit), playGame, 35, major_button_dims)
settings_button = Button(menu_screen, settings_text,(3 * width_unit, height_unit), runSettings, 30, major_button_dims)
about_button = Button(menu_screen, about_text,
about_position, loadAbout, 30)
quit_button = Button(menu_screen, quit_text,
(5 * width_unit, height_unit), quitGame, 35, major_button_dims)
# Initialising StartMenu class
start_menu = Menu(menu_screen, title_obj, menu_background, play_button,
settings_button, about_button, quit_button)
# Start Music
playMusic(menu_background_path)
# Found on pygame docs
# https://www.pygame.org/docs/ref/cursors.html
# Believe it makes the cursor look nicer in the game
pygame.mouse.set_cursor(*pygame.cursors.tri_left)
### Main Game Loop
while start_menu.playing:
# Limit frame rate
clock.tick(max_fps)
# Get/action events
for event in pygame.event.get():
# Send each event to the start menu
button_out = start_menu.do(event)
if button_out == 'settings':
SettingsMenu(menu_screen, max_fps)
# Refresh screen
menu_screen.fill(colour['black'])
### Code to re-display items on screen will go here
start_menu.display()
# Display everything on screen
pygame.display.flip()
quitGame()
| UTF-8 | Python | false | false | 4,821 | py | 35 | pyfighter.py | 20 | 0.702136 | 0.693217 | 0 | 159 | 29.308176 | 118 |
131131yhx/rchol | 3,607,772,552,183 | ee8e0cb1cae095068d05b5416d0569e64d179e82 | 498b99130944b81809627ffcf9bf3ae95eaa2660 | /python/ex_reuse_partition.py | 3fe180882beca002f447c93b3b221a22e0951e55 | [
"BSD-3-Clause"
]
| permissive | https://github.com/131131yhx/rchol | f5759b3ae04ed77eabfbf9be06437626bcc905b3 | 100c6264958beba9d7d87e93d1f8808a6cc6df34 | refs/heads/master | 2023-04-28T12:13:13.980643 | 2021-04-24T19:34:55 | 2021-04-24T19:34:55 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import sys
sys.path.append('rchol/')
import numpy as np
from scipy.sparse import identity
from numpy.linalg import norm
from rchol import *
from util import *
# Initial problem: 3D-Poisson
n = 20
A = laplace_3d(n) # see ./rchol/util.py
# random RHS
N = A.shape[0]
b = np.random.rand(N)
print("Initial problem:")
# compute preconditioner after reordering (multi thread)
nthreads = 2
G, perm, part = rchol(A, nthreads)
Aperm = A[perm[:, None], perm]
print('fill-in ratio: {:.2}'.format(2*G.nnz/A.nnz))
# solve with PCG
tol = 1e-6
maxit = 200
x, relres, itr = pcg(Aperm, b[perm], tol, maxit, G, G.transpose().tocsr())
print('# CG iterations: {}'.format(itr))
print('Relative residual: {:.2e}\n'.format(relres))
# perturb the original matrix
B = A + 1e-3*identity(N)
print('New problem (same sparsity) ...')
# compute preconditioner with existing permutation/partition
L = rchol(B, nthreads, perm, part)[0]
print('fill-in ratio: {:.2}'.format(2*L.nnz/A.nnz))
# solve the new problem
Bperm = B[perm[:, None], perm]
x, relres, itr = pcg(Bperm, b[perm], tol, maxit, L, L.transpose().tocsr())
print('# CG iterations: {}'.format(itr))
print('Relative residual: {:.2e}\n'.format(relres))
| UTF-8 | Python | false | false | 1,190 | py | 48 | ex_reuse_partition.py | 25 | 0.679832 | 0.663025 | 0 | 44 | 25.977273 | 74 |
qwertyuu/old-code-backup | 644,245,107,622 | d418f6a30acd2535a28407674eb42201a24bfbea | af396ad814ec4bf1849908c7f83b402ae191fab2 | /2k16/QualityContent/QualityContent/QualityContent.py | c1024dbcb08871672c54a221d0ce3ace14469ac7 | []
| no_license | https://github.com/qwertyuu/old-code-backup | bab805dda171814bf72aa9b3693827667819f56c | 6a47b8d9f18e01a90be2de9267d955851e413f9a | refs/heads/main | 2023-02-20T04:52:28.362866 | 2021-01-22T08:36:54 | 2021-01-22T08:36:54 | 331,884,338 | 1 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import requests
import json
import pprint
def login(username, password, header):
"""logs into reddit, saves cookie"""
print 'begin log in'
#username and password
UP = {'user': username, 'passwd': password, 'api_type': 'json',}
#POST with user/pwd
client = requests.session()
client.headers.update(header)
r = client.post('http://www.reddit.com/api/login', data=UP)
#print r.text
#print r.cookies
#gets and saves the modhash
print r.text
j = json.loads(r.text)
client.modhash = j['json']['data']['modhash']
print '{USER}\'s modhash is: {mh}'.format(USER=username, mh=client.modhash)
client.user = username
def name():
return '{}\'s client'.format(username)
#pp2(j)
return client
header={'user-agent' : 'qualitybot/2.0',}
chose = login('Quality_Posts', 'qw3rtyui0p', header)
r = chose.post('http://www.reddit.com/api/comment', data={'api_type': 'json', 'text' : '\>/r/DotA2\n\n\>Quality Content\n\nPick one.', 'thing_id' : 't3_2817zd', 'uh' : chose.modhash, })
print json.loads(r.text)
raw_input()
| UTF-8 | Python | false | false | 1,099 | py | 409 | QualityContent.py | 33 | 0.631483 | 0.621474 | 0 | 40 | 26.45 | 185 |
ufomysis/cartbot | 8,667,244,019,518 | 8673d830589b49d954e94a57c883a13254edd9da | 401900b0ed64dc00775ef4bb39ff9d37fc7566b4 | /remove_invalid.py | 200d361ad489f4d5b756a2929c918836a57ff21a | []
| no_license | https://github.com/ufomysis/cartbot | 9e6c6809008c1b3b9565949b8dcd4fdf0ff3e4dc | 14b8544b7586df22025674a7dfa0d4b38cfcaca4 | refs/heads/master | 2021-01-23T20:12:12.574211 | 2013-04-13T14:37:54 | 2013-04-13T14:37:54 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import sys,json
import os.path
file_in = open(sys.argv[1], 'r')
obj = json.load(file_in)
for x in list(obj.keys()):
if not os.path.exists(obj[x][0]):
del(obj[x])
file_out = open(sys.argv[2], 'w')
json.dump(obj,file_out)
| UTF-8 | Python | false | false | 235 | py | 8 | remove_invalid.py | 6 | 0.617021 | 0.604255 | 0 | 12 | 18.583333 | 37 |
sajanraj/Optical-Character-Recognition | 13,589,276,565,562 | 4d8acbb045c482a90fc7a67577b9fed8ce3139ba | 474e4059af0858ddcafaa61f61eeecb2626888df | /pancheck.py | a7e014f5b811b13ebf3db931e47099708147f10e | [
"MIT"
]
| permissive | https://github.com/sajanraj/Optical-Character-Recognition | 258416fa3a5ab97623fad2e4cdc904ccaf96dbef | a21064457322089a1ddeaedd49ffe4bc619000a5 | refs/heads/master | 2023-03-20T07:17:47.326224 | 2021-02-28T05:04:36 | 2021-02-28T05:04:36 | 213,962,684 | 1 | 0 | null | false | 2021-02-28T05:04:36 | 2019-10-09T16:02:02 | 2020-05-07T12:59:12 | 2021-02-28T05:04:36 | 3,123 | 0 | 0 | 0 | Python | false | false | # -*- coding: utf-8 -*-
# import the necessary packages
# construct the argument parse and parse the arguments
def ocr(imgdata,pan,preprs):
print('path1=',imgdata)
from PIL import Image
import pytesseract
import cv2
import os
path=os.getcwd()
print('pathos=',str(path))
from pdf2image import convert_from_path
# load the example image and convert it to grayscale
if imgdata.lower().endswith(('.pdf')):
filename = "{}.jpg".format(os.getpid())
pages = convert_from_path(imgdata, 200)
for page in pages:
page.save(filename, 'JPEG')
image = cv2.imread(filename)
else:
image = cv2.imread(imgdata)
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# check to see if we should apply thresholding to preprocess the
# image
if preprs == "thresh":
gray = cv2.threshold(gray, 0, 255,
cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]
# make a check to see if median blurring should be done to remove
# noise
elif argspreprs == "blur":
gray = cv2.medianBlur(gray, 3)
# write the grayscale image to disk as a temporary file so we can
# apply OCR to it
filename = "{}.png".format(os.getpid())
cv2.imwrite(filename, gray)
# load the image as a PIL/Pillow image, apply OCR, and then delete
# the temporary file
text = pytesseract.image_to_string(Image.open(filename))
os.remove(filename)
flagis=0
text = text.lower()
print(text)
word = text.find(pan.lower())
if (word > 0):
flagis=1
print(flagis)
return text,flagis
#Return url
# show the output images
#cv2.imshow("Image", image)
#cv2.imshow("Output", gray)
#cv2.waitKey(0)
| UTF-8 | Python | false | false | 1,804 | py | 4 | pancheck.py | 3 | 0.609202 | 0.592572 | 0 | 61 | 27.540984 | 70 |
abeljim/SSDK | 19,327,352,840,960 | 5a9417108f96f7dc42392b87f93f004e41a65202 | 6effe32673d1dcb7d86a81991ea3a35e82ed4533 | /SA_cap_figures.py | 4b208b81b46504d767828151cd941ad5d807688b | []
| no_license | https://github.com/abeljim/SSDK | 406eb903a8349a11cf3aedddcd45444e9ce9d8f3 | 84edc24e27a6b0b69831f1eae7b8ad668ae217e4 | refs/heads/master | 2020-09-10T20:04:32.910237 | 2019-11-15T16:35:11 | 2019-11-15T16:35:11 | 221,822,185 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import numpy as np
from zipfile import ZipFile
import matplotlib.pyplot as plt
import scipy
from scipy import signal
import mdat
def plothot(i, run, steps, cvmin, cvmax, plotmin, plotmax, plot, alpha=1):
sweeprate = steps[i]
# Create a dummy array onto which we can append data
buffer = [run[s] for s in run.keys() if i in s][0][0:1]
# In the dictionary Run01, there are steps that are named (Step01, etc)
# similarly to the step that was identified as having a sweep rate of 5
# take these arrays and process them in the following loop
for iv in [run[s] for s in run.keys() if i in s]:
# iv[:,2] = iv[:,2] * 1000 # Convert A to mA
iv = iv[np.where(iv[:,1] > plotmin)]
iv = iv[np.where(iv[:,1] < plotmax)]
buffer = np.concatenate((buffer, iv))
plot.plot(iv[:,1],
scipy.signal.savgol_filter(iv[:,2], 7, 2)*1000,
mdat.colors1[steps[i]],
alpha=alpha)
iv = iv[:,1:3]
iv = iv[np.where(iv[:,0] > cvmin)]
iv = iv[np.where(iv[:,0] < cvmax)]
# if len(buffer) >= 2:
buffer = buffer[1:]
buffer = buffer[np.where(buffer[:,1] > cvmin)]
buffer = buffer[np.where(buffer[:,1] < cvmax)]
potmax = np.nan
try:
if buffer[0,1] > buffer[-1,1]: # A 'true' here indicates sweep down
potmax = buffer[np.where(buffer[:,2] == np.amin(buffer[:,2]))][0][1]
imax = np.mean(buffer[np.where(np.abs(buffer[:,1]-potmax) <= 0.005)][:,2])
return potmax, imax*1000, sweeprate
elif buffer[0,1] < buffer[-1,1]: # A 'true' here indicates sweep up
potmax = buffer[np.where(buffer[:,2] == np.amax(buffer[:,2]))][0][1]
imax = np.mean(buffer[np.where(np.abs(buffer[:,1]-potmax) <= 0.005)][:,2])
return potmax, imax*1000, sweeprate
except:
return buffer
#### #### #### #### #### #### Set variables for the program here
wdir = "C:/Users/MummLab/Sierra/CV/"
file_names = [
'6-21-18_ME.mdat',
'7-26-18_planar_pellet_CV.mdat',
'7-16-18_P_powder_CV.mdat',
'8-14-18_bijel#10_CV.zip',
'7-26-18_planar_bijels_CV.zip'
]
#### #### #### #### #### #### Start the program
figure, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(10, 3))
ax1.set_yticklabels([])
ax2.set_yticklabels([])
ax3.set_yticklabels([])
plotmin, plotmax = -0.5, 0.8 # Set the limits for the plot here
results = np.asarray([['data'], [5],[-5],[10],[-10],[25],[-25],[50],[-50],[100],[-100],[250],[-250]])
"""
"""
file_path= str(wdir + file_names[0])
run, runlist = mdat.importdata(file_path)
steps = {} # make a dictionary with steps and sweep rates
for line in runlist:
if line.startswith(b'Potentiodynamic'):
steps[str(line)[str(line).find("Step"):str(line).find("Step")+6]] = str(line)[str(line).find(",", str(line).find("mV/S")-5, str(line).find("mV/S"))+1:str(line).find("mV/S")]
try:
del steps['Step02'] # remove the first (Step02) wchich is technically potentiodynamic but not the CV section
except:
print('No Step02!')
sweeps = []
if 'ME' in file_names[0]:
cvmin, cvmax = 0.2, 0.4 # Set the limits for the duck curve here
elif 'MicroElec' in file_names[0]:
cvmin, cvmax = 0.2, 0.4 # Set the limits for the duck curve here
elif '#' in file_names[0]:
cvmin, cvmax = -0.2, 0.55 # Set the limits for the duck curve here
elif 'powder' in file_names[0]:
cvmin, cvmax = -0.2, 0.8 # Set the limits for the duck curve here
elif 'med' in file_names[0]:
cvmin, cvmax = 0.2, 0.6 # Set the limits for the duck curve here
elif 'planar' in file_names[0]:
cvmin, cvmax = 0.2, 0.6 # Set the limits for the duck curve here
# For every named step in the steps dictionary (Step01, Step02, etc)
for i in steps.keys():
#print(i)
"""
Cathodic peaks are simple to find, but the anodic peaks can be convoluted
by gas evolution. Use these peaks for SA with caution! Because of this
convolution, the peaks must be selected by finding either where the first
derivative makes a minima, or where the second derivative crosses the x axis
"""
sweep = run[i + '_Rp01'][:,1:3]
# first derivative
sweep = np.concatenate((run[i + '_Rp01'][:,1:3], np.zeros((len(sweep),1))), axis=1)
sweep[:,1] = scipy.signal.savgol_filter(sweep[:,1], 71, 2)
for i_n in np.arange(5,len(sweep)-5):
sweep[i_n, 2] = (sweep[i_n+5,1] - sweep[i_n-5,1]) / (sweep[i_n+5,0] - sweep[i_n-5,0])
sweep = sweep[10:-10]
sweep[:,2] = scipy.signal.savgol_filter(sweep[:,2], 71, 2)
# second derivative
sweep = np.concatenate((sweep, np.zeros((len(sweep),1))), axis=1)
for i_n in np.arange(1,len(sweep)-1):
sweep[i_n, 3] = (sweep[i_n+1,2] - sweep[i_n-1,2]) / (sweep[i_n+1,0] - sweep[i_n-1,0])
sweep = sweep[1:-1]
sweep[:,3] = scipy.signal.savgol_filter(sweep[:,3], 51, 3)
sweep = sweep[np.where(sweep[:,0] >= 0.4)]
if sweep[0,0] <= sweep[-1,0]:
n = len(sweep) - 1
if sweep[np.where(sweep[:,1] == np.amin(sweep[:,1])),0][0][0] >= cvmax:
cvmax1 = sweep[np.where(sweep[:,1] == np.amin(sweep[:,1])),0][0][0]
elif sweep[np.where(sweep[:,2] == np.amin(sweep[:,2])),0][0][0] >= 0.4:
cvmax1 = sweep[np.where(sweep[:,2] == np.amin(sweep[:,2])),0][0][0]
else:
cvmax1 = sweep[np.where(((np.roll(np.sign(sweep[:,3]), 1) - np.sign(sweep[:,3])) != 0).astype(int) == 1)[0][-1]][0]
cvmin1 = cvmin
else:
cvmin1, cvmax1 = cvmin, cvmax
point = plothot(i, run, steps, cvmin1, cvmax1, plotmin, plotmax, ax1, mdat.alpha)
try:
ax1.scatter(point[0],
point[1],
s=150,
c=mdat.colors3[point[2]],
zorder=4)
point = np.asarray(point)
sweeps.append(point)
point[2] = float(point[2])
#ax1.ylabel('Current (mA)', fontproperties=mdat.font)
ax1.xlabel('Potential (V) vs Ag/AgCl (1M KCl)', fontproperties=mdat.font)
except:
print(' No peak for ' + i)
dlayer_cap = np.asarray(sweeps, dtype=float)
dlayer_cap[np.where(dlayer_cap[:,1] < 0)[0]][:,2] = dlayer_cap[np.where(dlayer_cap[:,1] < 0)[0]][:,2] * -1
cathodic = np.asarray([point for point in dlayer_cap if float(point[1]) <= 0])
anodic = np.asarray([point for point in dlayer_cap if float(point[1]) >= 0])
ax1.set_ylim([1.1 * cathodic[-1,1], 1.1 * anodic[-1,1]])
"""
"""
file_path= str(wdir + file_names[1])
run, runlist = mdat.importdata(file_path)
steps = {} # make a dictionary with steps and sweep rates
for line in runlist:
if line.startswith(b'Potentiodynamic'):
steps[str(line)[str(line).find("Step"):str(line).find("Step")+6]] = str(line)[str(line).find(",", str(line).find("mV/S")-5, str(line).find("mV/S"))+1:str(line).find("mV/S")]
try:
del steps['Step02'] # remove the first (Step02) wchich is technically potentiodynamic but not the CV section
except:
print('No Step02!')
sweeps = []
if 'ME' in file_names[1]:
cvmin, cvmax = 0.2, 0.4 # Set the limits for the duck curve here
elif 'MicroElec' in file_names[1]:
cvmin, cvmax = 0.2, 0.4 # Set the limits for the duck curve here
elif '#' in file_names[1]:
cvmin, cvmax = -0.2, 0.55 # Set the limits for the duck curve here
elif 'powder' in file_names[1]:
cvmin, cvmax = -0.2, 0.8 # Set the limits for the duck curve here
elif 'med' in file_names[1]:
cvmin, cvmax = 0.2, 0.6 # Set the limits for the duck curve here
elif 'planar' in file_names[1]:
cvmin, cvmax = 0.2, 0.6 # Set the limits for the duck curve here
# For every named step in the steps dictionary (Step01, Step02, etc)
for i in steps.keys():
#print(i)
"""
Cathodic peaks are simple to find, but the anodic peaks can be convoluted
by gas evolution. Use these peaks for SA with caution! Because of this
convolution, the peaks must be selected by finding either where the first
derivative makes a minima, or where the second derivative crosses the x axis
"""
sweep = run[i + '_Rp01'][:,1:3]
# first derivative
sweep = np.concatenate((run[i + '_Rp01'][:,1:3], np.zeros((len(sweep),1))), axis=1)
sweep[:,1] = scipy.signal.savgol_filter(sweep[:,1], 71, 2)
for i_n in np.arange(5,len(sweep)-5):
sweep[i_n, 2] = (sweep[i_n+5,1] - sweep[i_n-5,1]) / (sweep[i_n+5,0] - sweep[i_n-5,0])
sweep = sweep[10:-10]
sweep[:,2] = scipy.signal.savgol_filter(sweep[:,2], 71, 2)
# second derivative
sweep = np.concatenate((sweep, np.zeros((len(sweep),1))), axis=1)
for i_n in np.arange(1,len(sweep)-1):
sweep[i_n, 3] = (sweep[i_n+1,2] - sweep[i_n-1,2]) / (sweep[i_n+1,0] - sweep[i_n-1,0])
sweep = sweep[1:-1]
sweep[:,3] = scipy.signal.savgol_filter(sweep[:,3], 51, 3)
sweep = sweep[np.where(sweep[:,0] >= 0.4)]
if sweep[0,0] <= sweep[-1,0]:
n = len(sweep) - 1
if sweep[np.where(sweep[:,1] == np.amin(sweep[:,1])),0][0][0] >= cvmax:
cvmax1 = sweep[np.where(sweep[:,1] == np.amin(sweep[:,1])),0][0][0]
elif sweep[np.where(sweep[:,2] == np.amin(sweep[:,2])),0][0][0] >= 0.4:
cvmax1 = sweep[np.where(sweep[:,2] == np.amin(sweep[:,2])),0][0][0]
else:
cvmax1 = sweep[np.where(((np.roll(np.sign(sweep[:,3]), 1) - np.sign(sweep[:,3])) != 0).astype(int) == 1)[0][-1]][0]
cvmin1 = cvmin
else:
cvmin1, cvmax1 = cvmin, cvmax
point = plothot(i, run, steps, cvmin1, cvmax1, plotmin, plotmax, ax2, mdat.alpha)
try:
ax2.scatter(point[0],
point[1],
s=150,
c=mdat.colors3[point[2]],
zorder=4)
point = np.asarray(point)
sweeps.append(point)
point[2] = float(point[2])
#ax1.ylabel('Current (mA)', fontproperties=mdat.font)
ax2.xlabel('Potential (V) vs Ag/AgCl (1M KCl)', fontproperties=mdat.font)
except:
print(' No peak for ' + i)
dlayer_cap = np.asarray(sweeps, dtype=float)
dlayer_cap[np.where(dlayer_cap[:,1] < 0)[0]][:,2] = dlayer_cap[np.where(dlayer_cap[:,1] < 0)[0]][:,2] * -1
cathodic = np.asarray([point for point in dlayer_cap if float(point[1]) <= 0])
anodic = np.asarray([point for point in dlayer_cap if float(point[1]) >= 0])
ax2.set_xlim(plotmin, plotmax)
ax2.set_ylim([1.1 * cathodic[-1,1], 1.1 * anodic[-1,1]])
"""
"""
file_path= str(wdir + file_names[2])
run, runlist = mdat.importdata(file_path)
steps = {} # make a dictionary with steps and sweep rates
for line in runlist:
if line.startswith(b'Potentiodynamic'):
steps[str(line)[str(line).find("Step"):str(line).find("Step")+6]] = str(line)[str(line).find(",", str(line).find("mV/S")-5, str(line).find("mV/S"))+1:str(line).find("mV/S")]
try:
del steps['Step02'] # remove the first (Step02) wchich is technically potentiodynamic but not the CV section
except:
print('No Step02!')
sweeps = []
if 'ME' in file_names[2]:
cvmin, cvmax = 0.2, 0.4 # Set the limits for the duck curve here
elif 'MicroElec' in file_names[2]:
cvmin, cvmax = 0.2, 0.4 # Set the limits for the duck curve here
elif '#' in file_names[2]:
cvmin, cvmax = -0.2, 0.55 # Set the limits for the duck curve here
elif 'powder' in file_names[2]:
cvmin, cvmax = -0.2, 0.8 # Set the limits for the duck curve here
elif 'med' in file_names[2]:
cvmin, cvmax = 0.2, 0.6 # Set the limits for the duck curve here
elif 'planar' in file_names[2]:
cvmin, cvmax = 0.2, 0.6 # Set the limits for the duck curve here
# For every named step in the steps dictionary (Step01, Step02, etc)
for i in steps.keys():
#print(i)
"""
Cathodic peaks are simple to find, but the anodic peaks can be convoluted
by gas evolution. Use these peaks for SA with caution! Because of this
convolution, the peaks must be selected by finding either where the first
derivative makes a minima, or where the second derivative crosses the x axis
"""
sweep = run[i + '_Rp01'][:,1:3]
# first derivative
sweep = np.concatenate((run[i + '_Rp01'][:,1:3], np.zeros((len(sweep),1))), axis=1)
sweep[:,1] = scipy.signal.savgol_filter(sweep[:,1], 71, 2)
for i_n in np.arange(5,len(sweep)-5):
sweep[i_n, 2] = (sweep[i_n+5,1] - sweep[i_n-5,1]) / (sweep[i_n+5,0] - sweep[i_n-5,0])
sweep = sweep[10:-10]
sweep[:,2] = scipy.signal.savgol_filter(sweep[:,2], 71, 2)
# second derivative
sweep = np.concatenate((sweep, np.zeros((len(sweep),1))), axis=1)
for i_n in np.arange(1,len(sweep)-1):
sweep[i_n, 3] = (sweep[i_n+1,2] - sweep[i_n-1,2]) / (sweep[i_n+1,0] - sweep[i_n-1,0])
sweep = sweep[1:-1]
sweep[:,3] = scipy.signal.savgol_filter(sweep[:,3], 51, 3)
sweep = sweep[np.where(sweep[:,0] >= 0.4)]
if sweep[0,0] <= sweep[-1,0]:
n = len(sweep) - 1
if sweep[np.where(sweep[:,1] == np.amin(sweep[:,1])),0][0][0] >= cvmax:
cvmax1 = sweep[np.where(sweep[:,1] == np.amin(sweep[:,1])),0][0][0]
elif sweep[np.where(sweep[:,2] == np.amin(sweep[:,2])),0][0][0] >= 0.4:
cvmax1 = sweep[np.where(sweep[:,2] == np.amin(sweep[:,2])),0][0][0]
else:
cvmax1 = sweep[np.where(((np.roll(np.sign(sweep[:,3]), 1) - np.sign(sweep[:,3])) != 0).astype(int) == 1)[0][-1]][0]
cvmin1 = cvmin
else:
cvmin1, cvmax1 = cvmin, cvmax
point = plothot(i, run, steps, cvmin1, cvmax1, plotmin, plotmax, ax3, mdat.alpha)
try:
ax3.scatter(point[0],
point[1],
s=150,
c=mdat.colors3[point[2]],
zorder=4)
point = np.asarray(point)
sweeps.append(point)
point[2] = float(point[2])
#ax1.ylabel('Current (mA)', fontproperties=mdat.font)
ax3.xlabel('Potential (V) vs Ag/AgCl (1M KCl)', fontproperties=mdat.font)
except:
print(' No peak for ' + i)
dlayer_cap = np.asarray(sweeps, dtype=float)
dlayer_cap[np.where(dlayer_cap[:,1] < 0)[0]][:,2] = dlayer_cap[np.where(dlayer_cap[:,1] < 0)[0]][:,2] * -1
cathodic = np.asarray([point for point in dlayer_cap if float(point[1]) <= 0])
anodic = np.asarray([point for point in dlayer_cap if float(point[1]) >= 0])
ax3.set_ylim([1.1 * cathodic[-1,1], 1.1 * anodic[-1,1]])
| UTF-8 | Python | false | false | 14,569 | py | 44 | SA_cap_figures.py | 40 | 0.576086 | 0.528863 | 0 | 354 | 40.155367 | 185 |
dunsmoorlab/fearcon | 15,015,205,699,726 | 35941350cfb0f33adaa76efd1a956291043ad957 | 51a8770d852af6d01158a1dba6ca37ea96eb7ed8 | /estimate_bs.py | 9308ea7620cb88e947e74c8c882f272939c3f45e | []
| no_license | https://github.com/dunsmoorlab/fearcon | 4c322db3f3634a1c4f98918b9157725421786f48 | 78282c4f9b987d302b68d3dc4d78c05778fe5b14 | refs/heads/master | 2022-12-12T11:31:51.810749 | 2020-09-18T20:47:44 | 2020-09-18T20:47:44 | 102,023,350 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from glob import glob
import os
from fc_config import *
from glm_timing import *
from preprocess_library import meta
from shutil import copytree, move
from argparse import ArgumentParser, RawTextHelpFormatter
from mvpa2.misc.fsl.base import FslGLMDesign, read_fsl_design
from mvpa2.datasets.mri import fmri_dataset, map2nifti
import numpy as np
import scipy.stats
from scipy.stats.mstats import zscore
def group_beta(phases=None, subs=None):
#ptsd or controls
if subs == 'p':
subs = p_sub_args
elif subs == 'c':
subs = sub_args
elif subs == 'no107':
subs = no107
elif subs == 'all':
subs = all_sub_args
for phase in phases:
print(phase)
#set the number of trials
n_trials = beta_n_trials[phase]
print(n_trials)
for sub in subs:
print(sub)
subj = meta(sub)
#check to make sure all the timing files are there
onsets = glob('%s/%s/model/GLM/onsets/%s/betaseries/trial**.txt'%(data_dir, subj.fsub, py_run_key[phase]))
if len(onsets) != n_trials * len(subs): pop_beta_timing(phase=phase, subs=[sub])
#check to make sure all of the fsf design files are there
fsfs = glob('%s/%s/bold/%s/fsl_betas/%s_beta.fsf'%(data_dir, subj.fsub, phase2rundir[phase], py_run_key[phase]))
if len(fsfs) != len(subs): populate_beta_fsf(phase=phase, subs=[sub])
#now were ready to estimate the betas!
estimate_betaseries(sub=sub,n_trials=n_trials,phase=phase,mask=None,no_zscore=True)
def pop_beta_timing(phase=None, subs=None):
print('Populating beta timing files')
if isinstance(phase, str): phase = [phase]
for sub in subs:
for run in phase:
# if 'localizer' in run: glm_timing(sub, run).loc_blocks(beta=True)
# if 'extinction_recall' in run: glm_timing(sub, run).betaseries(er_start=True)
glm_timing(sub, run).betaseries()
def populate_beta_fsf(phase=None, subs=None):
print('Populating beta design files')
template = os.path.join(data_dir,'beta_templates',py_run_key[phase] + '_template.fsf')
for sub in subs:
subj = meta(sub)
outdir = os.path.join(subj.bold_dir,phase2rundir[phase],'fsl_betas')
if not os.path.exists(outdir): os.mkdir(outdir)
outfile = os.path.join(outdir, py_run_key[phase] + '_beta.fsf')
replacements = {'SUBJID':subj.fsub, 'RUNID':py_run_key[phase]}
with open(template) as temp:
with open(outfile,'w') as out:
for line in temp:
for src, target in replacements.items():
line = line.replace(src, target)
out.write(line)
def estimate_betaseries(sub=0,n_trials=0,phase=None,mask=None,no_zscore=True):
subj = meta(sub)
# find FSF files for this subject
model_dir = os.path.join(subj.bold_dir,phase2rundir[phase],'fsl_betas')
if not os.path.exists(model_dir): os.mkdir(model_dir)
'''
pattern = os.path.join(model_dir, 'fsf',
'{}_{}*.fsf'.format(args.model, args.subject))
fsf_files = glob(pattern)
if not fsf_files:
raise IOError('No FSF files found matching: {}'.format(pattern))
fsf_files.sort()
log.start()
'''
fsf_files = [os.path.join(model_dir,'%s_beta.fsf'%(py_run_key[phase]))]
# temporary subject directory for individual beta images
'''
out_dir = os.path.join(model_dir, 'beta', args.subject)
log.run('mkdir -p {}'.format(out_dir))
'''
out_dir = model_dir
beta_files = []
for f in fsf_files:
# use a feat utility to create the design matrix
(base, ext) = os.path.splitext(f)
name = os.path.basename(base)
os.system('feat_model {}'.format(base))
design = read_fsl_design(f)
bold = design['feat_files']
if not bold.endswith('.nii.gz'):
bold += '.nii.gz'
if not os.path.exists(bold):
raise IOError('BOLD file not found: {}'.format(bold))
# obtain individual trial estimates
betaseries(base=base, out_dir=out_dir, n_trials=n_trials, mask=mask, no_zscore=no_zscore)
# # get one file with estimates for each trial/stimulus
beta_file = os.path.join(out_dir, name + '.nii.gz')
ev_files = []
for i in range(n_trials):
ev_files.append(os.path.join(out_dir, 'ev{:03d}.nii.gz'.format(i)))
os.system('fslmerge -t {} {}'.format(beta_file, ' '.join(ev_files)))
beta_files.append(beta_file)
# remove temp files
os.system('rm {}'.format(' '.join(ev_files)))
os.system('rm {}*.{{con,png,ppm,frf,mat,min,trg}}'.format(base))
def betaseries(base=None,out_dir=None,n_trials=0,mask=None,no_zscore=True):
s = """Estimate betaseries using LS-S regression.
See Mumford et al. 2014 for details.
Specify the base for a design generated by FEAT. For example, if you
have a .fsf file in mydesign.fsf, specify mydesign as the modelbase.
The trial regressors are assumed to be in your original EVs (as opposed
to the real EVs, which include for example temporal derivatives of the
original EVs). The trials to model are assumed to be the first ones listed.
For example, if 30 orig EVs are included in the model, and ntrials is set
to 20, then the last 10 EVs are assumed to be modeling things other than
the individual trials. The exception are temporal derivatives of the trial
EVs, which are assumed to be interleaved with the original trial EVs.
If derivatives are included in the model, they will be included as
additional regressors. If --sep-derivs is included as an option, then the
current trial derivative and other trial derivatives will be estimated
separately.
For unknown reasons, each trial image is z-scored over voxels. This
means that the value o f a voxel in a given trial image will depend on
things like the size of the mask and values at other voxels. For
legacy purposes, for now that is still the default. To write raw
betaseries estimates, use the --no-zscore flag.
You may also specify confound regressors (defined in the fsf file under
'confoundev_files'), which will be included as regressors of no interest.
"""
# parser = ArgumentParser(description="Estimate betaseries using LS-S regression (Mumford et al. 2014).")
# parser.add_argument('modelbase', type=str,
# help="path to model files, without file extension")
# parser.add_argument('betadir', type=str,
# help="path to directory in which to save betaseries image")
# parser.add_argument('ntrials', type=int,
# help="number of trials to be estimated")
# parser.add_argument('-m', '--mask', type=str,
# help="(optional) path to mask image, indicating included voxels")
# parser.add_argument('-n', '--no-zscore', action="store_true",
# help="do not z-score trial images over voxels")
# parser.add_argument('-s', '--sep-derivs', action="store_true",
# help="use separate trial and other derivative regressors")
# args = parser.parse_args()
fsffile = base + '.fsf'
matfile = base + '.mat'
betadir = out_dir
n_trial = n_trials
print("Loading design...")
design = read_fsl_design(fsffile)
desmat = FslGLMDesign(matfile)
n_tp, n_evs = desmat.mat.shape
# number of original regressors and all regressors including
# derivatives
n_orig = design['fmri(evs_orig)']
# check which trial regressors have temporal derivatives
isderiv = np.zeros(n_orig, dtype=bool)
for i in range(n_orig):
f = 'fmri(deriv_yn{:d})'.format(i+1)
isderiv[i] = design[f]
# check if derivatives are included for all trials
n_trial_deriv = np.sum(isderiv)
if n_trial_deriv == n_trial:
deriv = True
elif n_trial_deriv == 0:
deriv = False
else:
raise ValueError('Must either include derivatives for all trials or none.')
if deriv:
# temporal derivatives are included. FEAT interleaves them with
# the original ones, starting with the first original regressor
n_trial_evs = n_trial * 2
trial_evs = range(0, n_trial_evs, 2)
deriv_evs = range(1, n_trial_evs, 2)
print("Using derivatives of trial regressors.")
else:
# trial regressors are just the first N regressors
n_trial_evs = n_trial
trial_evs = range(0, n_trial)
deriv_evs = []
# find input bold data
print("Loading data...")
bold = design['feat_files']
if not bold.endswith('.nii.gz'):
bold += '.nii.gz'
if not os.path.exists(bold):
raise IOError('BOLD file not found: {}'.format(bold))
#if args.mask is not None:
if mask is not None:
# user specified a mask
if not mask.endswith('.nii.gz'):
mask += '.nii.gz'
if not os.path.exists(mask):
raise IOError('Mask file not found: {}'.format(mask))
data = fmri_dataset(bold, mask=mask)
else:
# load all voxels
data = fmri_dataset(bold)
# everything after the trial EVs is regressors of no interest
dm_extra = desmat.mat[:,n_trial_evs:]
# additional confound regressors
if 'confoundev_files' in design:
conf_file = design['confoundev_files']
print("Loading confound file {}...".format(conf_file))
dm_nuisance = np.loadtxt(conf_file)
else:
print("No confound file indicated. Including no confound regressors...")
dm_nuisance = None
# create a beta-forming vector for each trial
print("Creating design matrices...")
beta_maker = np.zeros((n_trial, n_tp))
sep_derivs = False
for i, ev in enumerate(trial_evs):
# this trial
if deriv and sep_derivs:
# if using separate derivatives, include a dedicated regressor
# for this trial
dm_trial = np.hstack((desmat.mat[:,ev,np.newaxis],
desmat.mat[:,deriv_evs[i],np.newaxis]))
else:
# just the one regressor for this trial
dm_trial = desmat.mat[:,ev,np.newaxis]
# other trials, summed together
other_trial_evs = [x for x in trial_evs if x != ev]
if deriv:
if args.sep_derivs:
# only include derivatives except for this trial
other_deriv_evs = [x for x in deriv_evs if x != deriv_evs[i]]
dm_otherevs = np.hstack((
np.sum(desmat.mat[:,other_trial_evs,np.newaxis],1),
np.sum(desmat.mat[:,other_deriv_evs,np.newaxis],1)))
else:
# put all derivatives in one regressor
dm_otherevs = np.hstack((
np.sum(desmat.mat[:,other_trial_evs,np.newaxis],1),
np.sum(desmat.mat[:,deriv_evs,np.newaxis],1)))
else:
# just one regressor for all other trials
dm_otherevs = np.sum(desmat.mat[:,other_trial_evs,np.newaxis],1)
# put together the design matrix
if dm_nuisance is not None:
dm_full = np.hstack((dm_trial, dm_otherevs, dm_nuisance, dm_extra))
else:
dm_full = np.hstack((dm_trial, dm_otherevs, dm_extra))
s = dm_full.shape
dm_full = dm_full - np.kron(np.ones(s), np.mean(dm_full,0))[:s[0],:s[1]]
dm_full = np.hstack((dm_full, np.ones((n_tp,1))))
# calculate beta-forming vector
beta_maker_loop = np.linalg.pinv(dm_full)
beta_maker[i,:] = beta_maker_loop[0,:]
print("Estimating model...")
# this uses Jeanette's trick of extracting the beta-forming vector for each
# trial and putting them together, which allows estimation for all trials
# at once
glm_res_full = np.dot(beta_maker, data.samples)
# map the data into images and save to betaseries directory
for i in range(len(glm_res_full)):
if no_zscore:
ni = map2nifti(data, glm_res_full[i])
else:
outdata = zscore(glm_res_full[i])
ni = map2nifti(data, data=outdata)
ni.to_filename(os.path.join(betadir,
'ev{:03d}.nii.gz'.format(i)))
def clean_old_betas(p=False):
if p: subs = working_subs
else: subs = sub_args
for sub in subs:
subj = meta(sub)
for phase in ['localizer_1','localizer_2']:
rundir = subj.bold_dir + phase2rundir[phase]
target = os.path.join(rundir,'old_betas')
os.mkdir(target)
move(os.path.join(rundir,'ls-s_betas'),target)
move(os.path.join(rundir,'new_ls-s_betas'),target) | UTF-8 | Python | false | false | 11,385 | py | 341 | estimate_bs.py | 122 | 0.691085 | 0.686166 | 0 | 350 | 31.531429 | 115 |
fylein/fyle-qbo-api | 15,229,954,032,034 | cdf4434dcd92938adf008bcb777003f69c17c518 | a5564fbf541b4fb602f5ad47aa5d06441bcf9f0a | /apps/tasks/migrations/0005_tasklog_qbo_expense.py | 5a7e3bb569647b23f62149a6a4aeabcd48a35872 | [
"MIT"
]
| permissive | https://github.com/fylein/fyle-qbo-api | 1fc222501276ebf0f316f43bb278a6adcc0e08ce | b4c464cc6442ead91ceb3b2840103b27af3e029c | refs/heads/master | 2023-08-31T06:26:07.296341 | 2023-08-24T15:45:55 | 2023-08-24T15:45:55 | 243,419,752 | 1 | 3 | MIT | false | 2023-09-07T13:31:53 | 2020-02-27T03:15:01 | 2023-07-25T14:33:19 | 2023-09-07T13:31:52 | 9,991 | 1 | 3 | 3 | Python | false | false | # Generated by Django 3.0.3 on 2021-05-04 19:13
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [('quickbooks_online', '0010_qboexpense_qboexpenselineitem'), ('tasks', '0004_tasklog_bill_payment')]
operations = [migrations.AddField(model_name='tasklog', name='qbo_expense', field=models.ForeignKey(help_text='Reference to QBO Expense', null=True, on_delete=django.db.models.deletion.PROTECT, to='quickbooks_online.QBOExpense'))]
| UTF-8 | Python | false | false | 522 | py | 279 | 0005_tasklog_qbo_expense.py | 242 | 0.760536 | 0.716475 | 0 | 11 | 46.454545 | 234 |
IgorFedchenko/TicketSystem | 9,062,380,994,598 | ee9ac034d58d2cb77e7a54b73052eca5c169d45d | a94409c79b9ca3ecbbe5fe82971470c58aa3e57f | /TicketSystem/urls.py | 5d163447865edb0c4a875adf828c1058c3e6ec3b | []
| no_license | https://github.com/IgorFedchenko/TicketSystem | d26e57774ba20a07ec9926b32f14e2a583d231a7 | 3038c62e4fb205b1b9687022c512256b256c3391 | refs/heads/master | 2016-09-02T04:35:21.934804 | 2015-06-26T11:26:20 | 2015-06-26T11:26:20 | 27,052,482 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from django.conf.urls import patterns, include, url
from django.contrib import admin
from tickets import views
from tickets import api
urlpatterns = patterns('',
# Examples:
# url(r'^$', 'TicketSystem.views.home', name='home'),
# url(r'^blog/', include('blog.urls')),
url(r'^$', views.tickets_list),
url(r'^api/$', api.ExternalApi.as_view()),
url(r'^admin/', include(admin.site.urls)),
url(r'^login/$', 'django.contrib.auth.views.login', {'template_name': 'tickets/login.html'}),
url(r'^password_change/$', 'django.contrib.auth.views.password_change', {'post_change_redirect':'/tickets/'}, name='password_change'),
url(r'^password_change_done/$', 'django.contrib.auth.views.password_change_done', name='password_change_done'),
url(r'^logout/$', 'django.contrib.auth.views.logout', {'next_page': '/login/'}, name='logout'),
url(r'^create/$', views.create_ticket, name='create_ticket'),
url(r'^tickets/$', views.tickets_list, name='tickets_list'),
url(r'^tickets/(?P<pk>[\d]+)/$', views.TicketDetailView.as_view(), name = 'ticket_detail'),
url(r'^download/(?P<pk>[\d]+)/$', views.downloader, name='downloader'),
url(r'^close/(?P<pk>[\d]+)/$', views.close_ticket, name = 'close_ticket'),
url(r'^statistics/(?P<pref>.{2})/(?P<num>[\d]+)/', views.statistics, name='statistics'),
url(r'^to_excel/$', views.to_excel, name='to_excel'),
url(r'^docs/$', views.docs, name='docs'),
)
| UTF-8 | Python | false | false | 1,447 | py | 17 | urls.py | 7 | 0.63718 | 0.636489 | 0 | 27 | 52.592593 | 138 |
mohiitaa/synthesis-and-optimisation-of-digital-circuits | 3,642,132,305,626 | d1e9e200e285359d843018203668319bbe176df4 | 083af5989edd689b34d75f6cbe45c352a8eeeccc | /Operations_URP/Cofactor/Cofactor/op_notor.py | 95b5bf88d9fb683e28b3cfa557e9ccd6a4015aae | []
| no_license | https://github.com/mohiitaa/synthesis-and-optimisation-of-digital-circuits | 3382c66a98ee97edff62e2598caf9a5c36c5a8be | ff9d8da4ce306227c437ed42c39af463cf098ca2 | refs/heads/master | 2022-04-10T06:38:58.068952 | 2020-03-13T17:48:02 | 2020-03-13T17:48:02 | 116,579,416 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | '''
# Simple OR operation between a and c.
# Constraint:Neither a nor c can be null("00")
# c is complemented in the begining (b=c') .Then we proceed
# ahead by following these simple steps:
#
# i) If a and b are equal, the result is equal to one of them
# ii) If a="11" the result is "11"
# iii) If b="00", the result is a
# iii)Otherwise the result is "11"
'''
def op_notor(a,c):
if a=="00" or c=="00":
print "ERROR! 00 not a valid input"
return
if c=="11":
b="00"
elif c=="01":
b="10"
else:
b="01"
if a=="11":
s="11"
elif a==b:
s=a
elif b=="00":
s=a
else:
s="11"
return s
| UTF-8 | Python | false | false | 739 | py | 21 | op_notor.py | 13 | 0.491204 | 0.445196 | 0 | 35 | 19.114286 | 62 |
BenDoan/playground | 12,859,132,131,464 | f39a6e9220018de7cd840b6823edb4b9bdef9c04 | 4945fef321f2823683378d71b49b3d2fae222d0d | /python/email-transaction-to-budget/email_transaction_to_budget.py | 09dbc91c8c207ddd9df0671b59348b9b4014c9ff | [
"MIT"
]
| permissive | https://github.com/BenDoan/playground | 0c1fc4cfca81be68dfafde6974f95a6564366948 | 28fd14f08090023a6cb2cbcf98c16b4f041e2050 | refs/heads/master | 2023-05-26T07:26:28.374004 | 2023-04-30T16:14:07 | 2023-04-30T16:14:07 | 29,168,104 | 1 | 0 | MIT | false | 2023-02-22T21:14:19 | 2015-01-13T02:11:46 | 2021-12-16T05:51:33 | 2023-02-22T21:14:17 | 2,879 | 1 | 0 | 66 | Jupyter Notebook | false | false | #!/usr/bin/env python
import argparse
from googleapiclient.discovery import build
from google_auth_oauthlib.flow import InstalledAppFlow
from google.auth.transport.requests import Request
import configparser
import datetime
import imaplib
import json
import os.path
import pickle
import re
import traceback
import enum
from bs4 import BeautifulSoup
import time
HAVE_READ_MIDS_FILE = "have-processed-mids.json"
HAVE_READ_TRANSACTIONS_FILE = "have-processed-transactions.json"
# If modifying these scopes, delete the file token.pickle.
SCOPES = ["https://www.googleapis.com/auth/spreadsheets"]
# The ID and range of a sample spreadsheet.
SPREADSHEET_ID = "1h-GBpn__5CG-jlG1LuQbooNaOm_rLQmBmz6OS1GdaeM"
TEMPLATE_SHEET_ID = "740803055"
BudgetCategory = enum.Enum("BudgetCategory", "food shopping recurring")
FOOD_RANGE = "B6:C"
SHOPPING_RANGE = "E6:F"
RECURRING_RANGE = ""
# keep lowercase
food_vendors = ["hy-vee", "doordash", "chipotle", "jimmy johns"]
def main(dry_run, proc_all):
config = configparser.ConfigParser()
config.read("imap-creds.ini")
username = config.get("creds", "username")
password = config.get("creds", "password")
hostname = config.get("server", "hostname")
have_processed_mids = {}
have_processed_transactions = {}
try:
if not proc_all:
have_processed_mids = json.load(open(HAVE_READ_MIDS_FILE))
have_processed_transactions = json.load(open(HAVE_READ_TRANSACTIONS_FILE))
except:
pass
service = get_sheets_service()
with imaplib.IMAP4_SSL(hostname) as M:
M.login(username, password)
M.select("Transactions", readonly=True)
now = datetime.datetime.now()
month_ago = datetime.timedelta(days=-7) + now
formatted_date = month_ago.strftime("%d-%b-%Y")
message_ids_from_chase = M.search(
"NONE", "FROM", '"chase.com"', "SINCE", formatted_date
)[1][0].split()
print(f"Found {len(message_ids_from_chase)} messages")
entries = []
for mid in message_ids_from_chase:
d_mid = mid.decode("utf-8")
if d_mid not in have_processed_mids:
try:
message = M.fetch(d_mid, "(BODY.PEEK[TEXT])")[1][0][1]
decoded_message = message.decode("UTF-8")
scrubbed_message = decoded_message.replace("=", "").replace(
"\n", ""
)
if "credit card statement is ready" in scrubbed_message:
have_processed_mids[d_mid] = True
continue
soup = BeautifulSoup(scrubbed_message, "html.parser")
tables = soup.findAll("table")
merchant = None
amount = None
datestr = None
for table in tables:
tds = table.findAll("td")
if len(tds) < 2:
continue
text1 = tds[0].text
text2 = tds[1].text
if text1 == "Merchant":
merchant = clean(text2)
if text1 == "Amount":
amount = clean(text2)
if text1 == "Date":
datestr = clean(text2)
ident = f"{merchant}-{amount}-{datestr}"
if amount is None or merchant is None:
print("failed to process")
print(soup.prettify())
merchant = "ERROR"
have_processed_mids[d_mid] = True
if ident in have_processed_transactions:
continue
entries.append([merchant, amount])
have_processed_transactions[ident] = True
print(d_mid, amount, merchant, datestr)
except Exception as e:
print("Couldn't process: {}".format(decoded_message))
traceback.print_exc()
if not dry_run:
add_to_spreadsheet(service, entries)
if not dry_run:
with open(HAVE_READ_MIDS_FILE, "w+") as f:
json.dump(have_processed_mids, f)
with open(HAVE_READ_TRANSACTIONS_FILE, "w+") as f:
json.dump(have_processed_transactions, f)
def clean(s):
t = s.replace("\r", "")
t = re.sub(r"</?\w+>", "", t)
t = t.strip()
return t
def get_sheets_service():
creds = None
# The file token.pickle stores the user's access and refresh tokens, and is
# created automatically when the authorization flow completes for the first
# time.
if os.path.exists("token.pickle"):
with open("token.pickle", "rb") as token:
creds = pickle.load(token)
# If there are no (valid) credentials available, let the user log in.
if not creds or not creds.valid:
if creds and creds.expired and creds.refresh_token:
creds.refresh(Request())
else:
flow = InstalledAppFlow.from_client_secrets_file("credentials.json", SCOPES)
creds = flow.run_local_server(port=0)
# Save the credentials for the next run
with open("token.pickle", "wb") as token:
pickle.dump(creds, token)
service = build("sheets", "v4", credentials=creds)
return service
def get_curr_month_str():
return datetime.datetime.now().strftime("%Y-%m")
def get_current_month_sheet(service):
resp = service.spreadsheets().get(spreadsheetId=SPREADSHEET_ID).execute()
sheets = resp.get("sheets", [])
curr_month_str = get_curr_month_str()
for sheet in sheets:
if sheet.get("properties", {}).get("title") == curr_month_str:
return sheet
return None
def add_to_spreadsheet(service, entries):
curr_month_sheet = get_current_month_sheet(service)
if not curr_month_sheet:
copy_sheet(service, TEMPLATE_SHEET_ID)
curr_month_str = get_curr_month_str()
for entry in entries:
cat = classify(entry[0], entry[1])
if cat == BudgetCategory.food:
RANGE_NAME = f"{curr_month_str}!{FOOD_RANGE}"
else:
RANGE_NAME = f"{curr_month_str}!{SHOPPING_RANGE}"
body = {
"range": RANGE_NAME,
"majorDimension": "ROWS",
"values": [entry],
}
result = (
service.spreadsheets()
.values()
.append(
spreadsheetId=SPREADSHEET_ID,
range=RANGE_NAME,
valueInputOption="USER_ENTERED",
body=body,
)
.execute()
)
def copy_sheet(service, old_sheet_id):
resp = (
service.spreadsheets()
.sheets()
.copyTo(
spreadsheetId=SPREADSHEET_ID,
sheetId=old_sheet_id,
body={"destinationSpreadsheetId": SPREADSHEET_ID},
)
.execute()
)
sheet_id = resp["sheetId"]
change_tab_index(service, sheet_id, 0)
change_tab_title(service, sheet_id, get_curr_month_str())
return sheet_id
def change_tab_index(service, sheet_id, index):
resp = (
service.spreadsheets()
.batchUpdate(
spreadsheetId=SPREADSHEET_ID,
body={
"requests": [
{
"updateSheetProperties": {
"properties": {
"sheetId": sheet_id,
"index": 0,
},
"fields": "index",
}
}
]
},
)
.execute()
)
def change_tab_title(service, sheet_id, title):
resp = (
service.spreadsheets()
.batchUpdate(
spreadsheetId=SPREADSHEET_ID,
body={
"requests": [
{
"updateSheetProperties": {
"properties": {
"sheetId": sheet_id,
"title": title,
},
"fields": "title",
}
}
]
},
)
.execute()
)
"""
TODO
- auto create tab for new month
- add transactions to category for cur month
- scrape recurring list from spreadsheet
- stretch: decorate amazon transactions
"""
def classify(merchant, amount):
merchant_l = merchant.lower()
if merchant.startswith("TST*"):
return BudgetCategory.food
for food_vendor in food_vendors:
if food_vendor in merchant_l:
return BudgetCategory.food
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("-d", "--dry-run", action="store_true")
parser.add_argument("-a", "--all", action="store_true")
args = parser.parse_args()
main(dry_run=args.dry_run, proc_all=args.all)
| UTF-8 | Python | false | false | 9,170 | py | 123 | email_transaction_to_budget.py | 52 | 0.529662 | 0.524973 | 0 | 301 | 29.465116 | 88 |
ritheshbhat/flask-restful | 5,531,917,899,142 | 073c04e7163b1921f24e02a762f4d50aabb13bb6 | 92dfdc573ddb703306b0ba05a5bbcbefd8647a11 | /setup.py | 97563642b1c4abfe73ca6b8a32832637d34da9ca | []
| no_license | https://github.com/ritheshbhat/flask-restful | 35a136eb57477b9e3e005e05081c409f59c176b6 | af3d420b043edcb7ddb4c135e0ce5352b2792ae4 | refs/heads/main | 2023-06-17T07:01:47.291384 | 2021-07-11T10:41:09 | 2021-07-11T10:41:09 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from __future__ import print_function
from os import path
from setuptools import find_namespace_packages, setup
here = path.abspath(path.dirname(__file__))
with open(path.join(here, 'README.md'), encoding='utf-8') as f:
long_description = f.read()
with open(path.join(here, 'src/wisecoder/version.txt'), encoding='utf-8') as f:
version = f.read()
with open('requirements.txt') as f:
required = f.read().splitlines()
setup(
name = 'wisecoder',
version = version,
description = long_description,
python_requires = '>=3.6, <4',
package_dir = {"": "src"},
packages = find_namespace_packages(where = "src"),
install_requires = required
)
| UTF-8 | Python | false | false | 679 | py | 8 | setup.py | 5 | 0.662739 | 0.655376 | 0 | 25 | 26.16 | 79 |
rodrigowerberich/TaskAllocation | 19,172,734,037,700 | c7e54a379149a21b01c693f893d04f205da98ce8 | c1f28fa6e77dd9acba75cf6c5aa65168ebbe479c | /task.py | 5b9a9aff89c7349f4fe3e96816fdd8b03dd93ee8 | []
| no_license | https://github.com/rodrigowerberich/TaskAllocation | 163067076cd48d9b76b3407f8fe291844dfa8de0 | 408add66320ef496c542566ea0d83afda732ea72 | refs/heads/master | 2020-04-24T06:45:04.085279 | 2019-02-27T17:31:21 | 2019-02-27T17:31:21 | 171,775,818 | 1 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from functools import reduce
class Task:
def __init__(self, name, mu_tasks, priority, deadline):
self.name = name
self.mu_tasks = mu_tasks
self.priority = priority
self.deadline = deadline
def __str__(self):
return 'T'+str(self.name)
def __repr__(self):
return str(self) | UTF-8 | Python | false | false | 333 | py | 28 | task.py | 25 | 0.582583 | 0.582583 | 0 | 14 | 22.857143 | 59 |
duplodemo/demoservice | 4,904,852,669,637 | 73eb3c0be52e9ced86baf5a4a52dfbc1c8e733d0 | 2750060dc44575bf2a324ad6cd5e0bfc38716e6a | /mysite/mysite/s3_utils.py2.7.py | 23c8f6e22a6e54b2fdfc63d48c63e450eba40bcb | []
| no_license | https://github.com/duplodemo/demoservice | 179325b6f5c32284127cd0b0b99134b26b9bdd54 | 9b32551c31bb62eddd93c43a6d194f66dbf60161 | refs/heads/master | 2023-04-14T09:37:20.307891 | 2023-04-04T08:51:42 | 2023-04-04T08:51:42 | 70,591,728 | 0 | 8 | null | false | 2023-04-04T12:43:38 | 2016-10-11T12:38:14 | 2021-11-02T16:34:21 | 2023-04-04T12:43:37 | 189 | 0 | 7 | 25 | Python | false | false | # import boto
# import sys, os
# from boto.s3.key import Key
# from boto.exception import S3ResponseError
# from django.conf import settings
#
# class S3Utils:
#
# ############ s3 file list #######
# def get_s3_list_default(self):
# s3_bucket = settings.S3_BUCKET_DEMO
# if s3_bucket is None or s3_bucket=="":
# return ["ERROR: 'S3_BUCKET_DEMO' setting is missing"]
# return self.get_s3_list(s3_bucket)
#
# def get_s3_list(self, s3_bucket):
# conn = boto.connect_s3()
# bucket = conn.get_bucket(s3_bucket)
# bucket_list = bucket.list()
# results = []
# for file in bucket_list:
# key_string = str(file.key)
# results.append(key_string)
# print(file)
#
# return results
#
# ############ s3 file #######
# def get_s3_file_default(self):
# s3_bucket = settings.S3_BUCKET_DEMO
# s3_file = settings.S3_FILE_DEMO
# if s3_bucket is None or s3_bucket=="" or s3_file is None or s3_file=="":
# return "ERROR: 'S3_BUCKET_DEMO' and 'S3_FILE_DEMO' settings are missing"
# return self.get_s3_file(s3_file, s3_bucket)
#
# def get_s3_file(self, s3_file, s3_bucket ):
# if s3_bucket is None or s3_bucket=="" or s3_file is None or s3_file=="":
# return "ERROR: 's3_bucket' and 's3_file' parameter are required"
# conn = boto.connect_s3()
# bucket = conn.get_bucket(s3_bucket)
# key = bucket.get_key(s3_file)
# response = key.get_contents_as_string()
# return response
#
# # if __name__ == "__main__":
# # s3_utils = S3Utils()
# # os.environ['S3_BUCKET_DEMO'] = "duploservices-default-demoservice"
# # os.environ['S3_FILE_DEMO'] = "duplo-text.txt"
# # files= s3_utils.get_s3_list()
# # print(files)
# # response = s3_utils.get_s3_file()
# # print(response)
| UTF-8 | Python | false | false | 1,917 | py | 18 | s3_utils.py2.7.py | 12 | 0.561815 | 0.535211 | 0 | 52 | 35.865385 | 86 |
tomguy04/Algo_Repo | 8,478,265,485,785 | ea1ff8c12f888594d4eae95ce11610c3f6a7dbfc | 2fbd6f5c4fd129c6e22eb716fedacd2729271ad4 | /17_RotateMatrix.py | e47276ef7eb614cd34bbaa57ab991660660c9937 | []
| no_license | https://github.com/tomguy04/Algo_Repo | e4479fc4a2fdd073cd3251065aa1ffa2179c2d7b | cee7126130c3874c2963dfda4f491edb2782962c | refs/heads/master | 2020-03-29T20:08:47.514646 | 2018-09-25T16:39:55 | 2018-09-25T16:39:55 | 150,297,855 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | matrix =[
[1, 1, 1, 2],
[4, 0, 0, 2],
[4, 0, 0, 2],
[4, 3, 3, 3]
]
for row in matrix:
print row
matrixSize =len(matrix)
print ('this is a '+ str(matrixSize) +' by ' + str(matrixSize) + ' picture')
number = 0
row = 0
temp1 = 0
temp2 = 0
#solution 1
#copy top row to array then copy left to top, bottom to left, right to bottom, temp array (old top) to right
oldTopEdge = matrix[0]
#left edge to top
for row in range(matrixSize-1,0,-1):
# print (row) #3,2,1
# print (str(matrix[row][0]) +" "+ str(matrix[0][row]))
matrix[0][row]=matrix[row][0]
for row in matrix:
print row
#bottom edge to left
for row in range(matrixSize-1,0,-1):
# print (row) #3,2,1
print (str(matrixSize-1)+str(row)+str(matrixSize-1-row)+str(0)+"--->"+str(matrix[matrixSize-1][row]) +" "+ str(matrix[matrixSize-1-row][0]))
matrix[matrixSize-1-row][0]=matrix[matrixSize-1][row]
# matrix[0][row]=matrix[row][0]
for row in matrix:
print row
# for rowIndex in matrix:
# number = rowIndex[-1]
# print ('looking at '+ str(number))
# if row+1 < matrixSize:
# temp = matrix[row+1][matrixSize-1]
# print ('replacing '+ str(temp) +' with '+ str(number))
# matrix[row+1][matrixSize-1] = number
# row+=1
| UTF-8 | Python | false | false | 1,377 | py | 23 | 17_RotateMatrix.py | 23 | 0.548293 | 0.506173 | 0 | 49 | 25.816327 | 144 |
hinamaladkar/BE_project | 17,016,660,440,422 | 2cd3aca3a46bff4104f92e07004cf73aaa1275b7 | fac25298f2f78c7f680ed399fa57544c957a8011 | /get_val_so.py | 4d4fa45db2d90c0ce5658bded42492e99934c2d1 | []
| no_license | https://github.com/hinamaladkar/BE_project | 50acec58e82e5185ee227f3a99ba736c91962c5d | 2e6515b59f0a0c3a0bc7217b8d866a1f60f02144 | refs/heads/master | 2020-05-21T22:06:49.942771 | 2016-09-26T11:54:30 | 2016-09-26T11:54:30 | 65,819,555 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from bs4 import BeautifulSoup
import requests
url = "https://www.google.com/finance/historical?cid=13564339&startdate=Jan+01%2C+2015&" \
"enddate=Aug+18%2C+2016&num=30&ei=ilC1V6HlPIasuASP9Y7gAQ&start={}"
#url = 'https://www.google.com/finance/historical?cid=13564339&startdate=Aug+21%2C+2014&enddate=Aug+19%2C+2016&num=30&ei=Zva2V6mlC8WsugSomoS4Ag'
with requests.session() as s:
start = 0
req = s.get(url.format(start))
soup = BeautifulSoup(req.content, "lxml")
table = soup.select_one("table.gf-table.historical_price")
all_rows = table.find_all("tr")
while True:
start += 30
soup = BeautifulSoup(s.get(url.format(start)).content, "lxml")
table = soup.select_one("table.gf-table.historical_price")
if not table:
break
all_rows.extend(table.find_all("tr"))
| UTF-8 | Python | false | false | 843 | py | 7 | get_val_so.py | 5 | 0.676157 | 0.604982 | 0 | 22 | 37.318182 | 144 |
DDFaller/INF1771_Trab1 | 7,825,430,417,573 | 8b325ef7077f45ac4d0058dface32b4d11c69974 | 17042850060c679af708ebb0a226aba008c87697 | /Processingpy/AValues.py | ae8e7d4bdfefb02feba08805928444052367aaf1 | []
| no_license | https://github.com/DDFaller/INF1771_Trab1 | 9870d55941f91d3b6f11b25bb55f04c2c8f19b9d | 30b1c8820df647a5c07fd931740576a536facb62 | refs/heads/master | 2022-12-29T05:49:10.934551 | 2020-10-19T08:10:02 | 2020-10-19T08:10:02 | 296,998,558 | 1 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null |
class AValues:
def __init__(self):
self.f = 0
self.g = 0
self.h = 0
self.previous = None
def heuristic(self,position,breakpointsList):
lowestDistance = 1000
for pos in breakpointsList:
x = pos[0] - position[0]
y = pos[1] - position[1]
x = x**2
y = y**2
distance =(x + y)**(1/2)
if distance < lowestDistance:
lowestDistance = distance
return lowestDistance
def SetPrevious(self,previousSquare):
self.previous = previousSquare
| UTF-8 | Python | false | false | 592 | py | 21 | AValues.py | 19 | 0.518581 | 0.493243 | 0 | 21 | 27.142857 | 49 |
EvilBorsch/homework-4 | 12,635,793,801,609 | e18ec070c485ea389e29cff21f6d65582ca061f8 | 4640b2d6e727941957351aabdc5769e375b0c097 | /pages/FoldersPage.py | 2031b86bf75cad641e500db2f2f31460010532d3 | []
| no_license | https://github.com/EvilBorsch/homework-4 | f33c85c117f57e66ddae6cffc1e6522cc2000778 | 2ffd4d6ca913bfb9d00eef77d77eaaa28c908ebf | refs/heads/master | 2023-02-15T05:47:17.355737 | 2021-01-09T22:09:50 | 2021-01-09T22:09:50 | 310,119,397 | 0 | 0 | null | true | 2021-01-08T18:15:34 | 2020-11-04T21:15:29 | 2021-01-08T17:57:42 | 2021-01-08T18:15:34 | 19,061 | 0 | 0 | 1 | Python | false | false | from components.folders.AddFolderForm import AddFolderForm
from steps.MainPageFoldersSteps import MainPageFoldersSteps
from .BasePage import *
class FoldersPage(Page):
BASE_URL = "https://e.mail.ru"
PATH = "/settings/folders"
@property
def add_folder(self):
return AddFolderForm(self.driver)
@property
def pop3_steps(self):
return MainPageFoldersSteps(self.driver)
def click_change_checkbox_pop3(self) -> bool:
"""
:return: True если checked, else False
"""
classes_list = self.pop3_steps.toggle_checkbox_POP3()
if len(classes_list.split()) == 2:
return True
return False
def click_pencil_icon(self) -> bool:
"""
:return: True если открылось окно
"""
return self.pop3_steps.click_pencil_button()
| UTF-8 | Python | false | false | 863 | py | 38 | FoldersPage.py | 37 | 0.635392 | 0.628266 | 0 | 31 | 26.16129 | 61 |
NutKaewnak/main_state | 42,949,689,755 | 019425c0eb3baf07ca2585988415c9f05220b95f | 0859d6eb51c7d84b3f60df80d7dc1ed162d1b973 | /nodes/include/old_method_in_manipulator_controller.py | 4f1f6f6b7f7547afd0d960aac4ea4d2fc40bc698 | []
| no_license | https://github.com/NutKaewnak/main_state | b95001cf8e38c935a8de492ca4e6b35854f8a4ae | 9ce4875e97f71a08c2cc2be804a93aa943bc94af | refs/heads/master | 2021-03-27T11:13:25.465496 | 2017-04-27T12:49:36 | 2017-04-27T12:49:36 | 54,113,012 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | def init_position(self, point):
"""
Init position and flip y-axis for invert kinematic
:param point: (geometry/Point)
:return: None
"""
rospy.loginfo("-----INVK INIT POSITION-----")
if self.arm_group == 'right_arm':
pass
elif self.arm_group == 'left_arm':
point.y *= -1
self.obj_pos = point
self.obj_pos.x -= 0.15
self.obj_pos.y += 0.04
self.obj_pos.z += 0.02
self.pos = self.obj_pos
def transform_point(self, pos, origin_frame='base_link'):
"""
Transform point from origin frame (Default: 'base_link') to 'mani_link'
:param pos: (geometry_msgs.msg.PointStamped)
:param origin_frame:
:return: (geometry_msgs.msg.PointStamped), False if input arm_group is incorrect
"""
if "right" in self.arm_side:
destination_frame = "right_mani_link"
elif "left" in self.arm_side:
destination_frame = "left_mani_link"
tf_points = PointStamped()
tf_points.point.x = pos.x
tf_points.point.y = pos.y
tf_points.point.z = pos.z
tf_points.header.stamp = rospy.Time(0)
tf_points.header.frame_id = origin_frame
rospy.loginfo("Waiting For Transform")
self.tf_listener.waitForTransform(destination_frame, origin_frame, rospy.Time(0), rospy.Duration(4.00))
rospy.loginfo("Success Waiting")
point_out = self.tf_listener.transformPoint(destination_frame, tf_points)
return point_out.point
def manipulate(self, pose_target, orientation_rpy=[0, 0, 0], ref_frame="base_link", planning_time=50.00):
self.arm_group.set_planning_time(planning_time)
self.arm_group.clear_pose_targets()
self.arm_group.set_goal_position_tolerance(0.05)
self.arm_group.set_goal_orientation_tolerance(0.1)
self.arm_group.set_pose_reference_frame(ref_frame)
self.arm_group.set_pose_target(pose_target)
self.arm_group.go(False) # async_move
def get_joint_status(self):
joint_state = {}
group_joint_names = None
group_current_joint_values = None
group_joint_names = self.arm_group.get_joints()
group_current_joint_values = self.arm_group.get_current_joint_values()
for i in range(0, len(group_joint_names)):
joint_state[group_joint_names[i]] = group_current_joint_values[i]
return joint_state
def move_relative(self, relative_goal_translation, relative_goal_rotation):
# respect to efflink
last_pose = self.arm_group.get_current_pose()
rospy.loginfo(str(type(last_pose)) + '\n' + str(last_pose))
rpy = tf.transformations.euler_from_quaternion([last_pose.pose.orientation.x,
last_pose.pose.orientation.y,
last_pose.pose.orientation.z,
last_pose.pose.orientation.w])
new_pose = Pose()
new_pose.position.x = last_pose.pose.position.x + relative_goal_translation[0]
new_pose.position.y = last_pose.pose.position.y + relative_goal_translation[1]
new_pose.position.z = last_pose.pose.position.z + relative_goal_translation[2]
new_pose.orientation.x = rpy[0] + relative_goal_rotation[0]
new_pose.orientation.y = rpy[1] + relative_goal_rotation[1]
new_pose.orientation.z = rpy[2] + relative_goal_rotation[2]
self.manipulate(new_pose)
def move_joint(self, joint_name, joint_value):
print 'joint_name', joint_name
print 'joint_value', joint_value
print 'self.arm_side', self.arm_side
print 'self.arm_group', self.arm_group
if (type(joint_name) == str) and (type(joint_value) == float):
self.arm_group.clear_pose_targets()
self.arm_group.set_joint_value_target(joint_name, joint_value)
self.arm_group.go(False)
else:
rospy.logwarn("Invalid Argument")
return False
return True
# PICKING PROCEDURE pregrasp -> open_gripper -> reach -> grasp
def move_arm_group(self, angles):
"""
Move array of arm joints with specific angle.
:param angles: (dict()) dict of angle and arm_joint
:return: (None)
"""
for x in angles:
if x in self.arm_group.get_joints():
self.move_joint(x, angles[x])
def static_pose(self, posture, tolerance=[0.05, 0.1]):
self.arm_group.clear_pose_targets()
self.arm_group.set_goal_position_tolerance(tolerance[0])
self.arm_group.set_goal_orientation_tolerance(tolerance[1])
self.arm_group.set_named_target(posture)
self.arm_group.go(False) # async_move
def move_arm_pick_object_first(self):
"""
Move arm to object position : x - 25 cm
:param (none)
:return: (none)
"""
self.pos.x = self.obj_pos.x
print "obj_pos.x 1 = " + str(self.obj_pos.x)
print "pos.x 1 = " + str(self.pos.x)
self.pos.y = self.obj_pos.y
self.pos.z = self.obj_pos.z+0.1
angle = inverse_kinematics.inverse_kinematic(self.transform_point(self.pos), 0)
self.move_arm_pick(angle)
def move_arm_pick_object_second(self):
"""
Move arm to object position
:param (none)
:return: (None)
"""
self.pos.x = self.obj_pos.x
self.pos.y = self.obj_pos.y
self.pos.z = self.obj_pos.z
angle = inverse_kinematics.inverse_kinematic(self.transform_point(self.pos), 0)
self.move_arm_pick(angle)
def move_arm_pick(self, angle):
"""
Move arm joints with specific angle.
:param angle: (dict()) dict of angle and arm_joint
:return: (None)
"""
self.move_joint('right_shoulder_1_joint', inverse_kinematics.in_bound('right_shoulder_1_joint', angle['right_shoulder_1_joint']))
self.move_joint('right_shoulder_2_joint', inverse_kinematics.in_bound('right_shoulder_2_joint', angle['right_shoulder_2_joint']))
self.move_joint('right_elbow_joint', inverse_kinematics.in_bound('right_elbow_joint', angle['right_elbow_joint']))
self.move_joint('right_wrist_1_joint', inverse_kinematics.in_bound('right_wrist_1_joint', angle['right_wrist_1_joint']))
self.move_joint('right_wrist_2_joint', inverse_kinematics.in_bound('right_wrist_2_joint', angle['right_wrist_2_joint']))
self.move_joint('right_wrist_3_joint', inverse_kinematics.in_bound('right_wrist_3_joint', angle['right_wrist_3_joint']))
def move_arm_before_pick_cloth(self):
"""
Move arm joints with specific angle.
:param angle: (dict()) dict of angle and arm_joint
:return: (None)
"""
self.pos.x = self.obj_pos.x
self.pos.y = self.obj_pos.y
self.pos.z = self.obj_pos.z
angle = inverse_kinematics.inverse_kinematic(self.transform_point(self.pos), 1.0/6.0*math.pi)
self.move_arm_pick(angle)
def move_arm_after_pick_cloth(self):
self.static_pose('right_after_pick_cloth')
def move_arm_turn_left(self):
self.static_pose('turn_arm_left')
def move_arm_turn_right(self):
self.static_pose('turn_arm_right') | UTF-8 | Python | false | false | 6,791 | py | 232 | old_method_in_manipulator_controller.py | 175 | 0.656015 | 0.64556 | 0 | 169 | 39.189349 | 133 |
adityabalu/trimesh | 3,977,139,744,436 | 1f354b735a1b68a014d7fcd8082a2a82331326dd | e3eb5e6c52465e78c27550db275238d7059ac8f9 | /trimesh/version.py | d55e3e6e53023f103812a5fc715155a1dacaf6c1 | [
"MIT"
]
| permissive | https://github.com/adityabalu/trimesh | 1ce1210918c3ed8c53105aa1614dccfc2c9ab697 | b64f9763e48f09efbd1d4195bc34bf2cb7eb9c71 | refs/heads/master | 2020-04-23T05:44:24.895089 | 2019-02-15T15:53:15 | 2019-02-15T15:53:15 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | __version__ = '2.36.28'
| UTF-8 | Python | false | false | 24 | py | 4 | version.py | 4 | 0.5 | 0.291667 | 0 | 1 | 23 | 23 |
Jung-Yuna/ClassRaspberryPi | 15,393,162,807,852 | 1269640f8f4af6b04de2955625fd818b1d8aaf48 | 2b59789818d6478d074db58193d71c7ce03267ef | /LED.py | e050db0c095d08a0d6644c7c7d7d8343e6b6a268 | []
| no_license | https://github.com/Jung-Yuna/ClassRaspberryPi | 9deed195068dacd5e7c7cb74d6348fb368004a0f | 152749aeb473b81092e2850f22b9d40ff6c868de | refs/heads/main | 2023-06-01T12:11:13.222461 | 2021-06-21T05:29:52 | 2021-06-21T05:29:52 | 370,293,096 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import RPi.GPIO as GPIO
import time
GPIO.setmode(GPIO.BOARD)
LED1 = 12
LED2 = 10
def main():
GPIO.setup(LED1, GPIO.OUT, initial=GPIO.LOW)
GPIO.setup(LED2, GPIO.OUT, initial=GPIO.LOW)
while 1:
GPIO.output(LED1, GPIO.HIGH)
GPIO.output(LED2, GPIO.LOW)
time.sleep(1)
GPIO.output(LED1, GPIO.LOW)
GPIO.output(LED2, GPIO.HIGH)
time.sleep(1)
if __name__=='__main__':
main()
| UTF-8 | Python | false | false | 387 | py | 4 | LED.py | 3 | 0.677003 | 0.638243 | 0 | 22 | 16.590909 | 45 |
liuluyang/miller | 7,103,875,936,182 | e41513b8c43a6c24e1cd6831b80fd230f69b9ebd | 3fc7a6ffc39390c8228b30b6d53a3429104bf5f3 | /education/10-16/字典.py | 7514f2419bef4d93d9cf5056fe3336553e53027c | []
| no_license | https://github.com/liuluyang/miller | a5463c0f9625570de2cf16a9844ed4c7f82dde76 | 786f286749972fb2c3a66e068a3874a00aa0f2ee | refs/heads/master | 2020-09-21T22:20:22.987833 | 2019-11-30T03:20:13 | 2019-11-30T03:20:13 | 224,952,326 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | # staff_list = [
# [“miller”, 23, ‘CEO’, ‘88888’],
# [‘黑姑娘’, 24, ‘行政’, ‘55555’],
# [‘liuser’, 25, ‘讲师’, ‘44444’],
# [‘egon’, ‘33’, ‘组长’, ‘77777’],
# xxxxxx
# xxxx
# xxxxx
# ]
# for i in staff_list:
# if i[0] == "黑姑娘":
# print()
# user_info1 = {"username": "miller", "password": 123564789}
# user_info2 = dict(username="miller", password=123456789)
#
# user_info3 = {}.fromkeys([1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 100)
# print(user_info3)
# names = {"miller": [23, "CEO", 66666], "blackgirl": [24, "行政", 40000]}
# names["liusir"] = [26, "teacher", 5555]
# names.setdefault("old_driver", [50, 'driver', 10000])
# print(names.pop("blackgirl"))
# print(names)
# print(names.popitem())
#
# print(names)
# dic1 = {"key1": "value1", "key2": "value2", "key3": "value3"}
# dic2 = {"key3": "xxxxxx", "key4": "value4"}
#
# dic1.update(dic2)
#
# print(dic1)
# dic1 = {"key1": "value1", "key2": "value2", "key3": "value3"}
# print(dic1["xxxxx"]) # 查询不存在的key 会抛出异常
# print(dic1.get("xxxxx"))
# print(dic1.items())
# dic = {"name": "miller", "age": 28, "phone": 132467468, "position": "CEO", "salary": 2222}
# li = list(dic.keys())
# for i in enumerate(li):
# print(i)
# dic = {}
# for i in range(100):
# dic[i] = i*2
#
# print(dic)
dic = {"k0": 0, "k1": 1, "k2": 2, "k3": 3, "k4": 4, "k5": 5, "k6": 6, "k7": 7, "k8": 8, "k9": 9}
for i in dic:
if 5 < int(i.replace("k", "")):
print(dic[i])
# for k, v in dic.items():
# if v % 2 == 0 and v != 0:
# dic[k] = -1
#
# print(dic)
| UTF-8 | Python | false | false | 1,629 | py | 190 | 字典.py | 180 | 0.519319 | 0.414538 | 0 | 76 | 19.065789 | 96 |
jaycodeco/ntube | 2,087,354,123,848 | 675304d234a2dea270f8365e01206be35f259a87 | d9a327f9f8376ba8e244d385fd37b4963582e6bc | /nBack/search.py | 2e1cebebafa1ff5bfa03a75335f64d4e1ab866bd | []
| no_license | https://github.com/jaycodeco/ntube | 0e16c7e66273a563e48b2ce33d98e9fd5a43f7fc | 2becddc3d61a3192860b312c22e8f4e8cf276b3e | refs/heads/master | 2023-05-25T22:23:27.178331 | 2021-05-27T15:33:13 | 2021-05-27T15:33:13 | 360,448,773 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import argparse
from googleapiclient.discovery import build
from googleapiclient.errors import HttpError
DEVELOPER_KEY = 'AIzaSyD6FMCZQyNq0qmnVW_CofjVe-uf3P7DIB0'
YOUTUBE_API_SERVICE_NAME = 'youtube'
YOUTUBE_API_VERSION = 'v3'
videos = []
def youtube_search(options):
youtube = build(YOUTUBE_API_SERVICE_NAME, YOUTUBE_API_VERSION,
developerKey=DEVELOPER_KEY)
search_response = youtube.search().list(
q=options,
part='id,snippet',
maxResults=20
).execute()
for search_result in search_response.get('items', []):
if search_result['id']['kind'] == 'youtube#video':
videos.append(f"{(search_result['id']['videoId'])} ^ {(search_result['snippet']['title'])} ^ {(search_result['snippet']['thumbnails']['medium']['url'])}")
def register_search():
file = open("./nBack/search_results.txt", "w")
end_vid = ""
for video in videos:
try:
file.write(video.replace('\U0001f525', '').replace('\U0001f34b',''))
file.write(" =")
end_vid = video
except Exception as e:
pass
file.write(end_vid.replace('\U0001f525', '').replace('\U0001f34b',''))
file.close()
def search_vids(search_term):
try:
youtube_search(search_term)
register_search()
print("yo")
except HttpError:
print ('An HTTP error occurred')
| UTF-8 | Python | false | false | 1,416 | py | 26 | search.py | 4 | 0.603814 | 0.579802 | 0 | 57 | 23.701754 | 166 |
ChenhongyiYang/Gibson_Detection_Depth | 14,929,306,323,968 | daac7c9d9d5c662c8230bd2cd5659b049e278101 | e9048785bf4f8af1f6baae3f14c1e0f0bfe8e5ce | /visulization/box_vis.py | 969ed8132174d06b8cb74bb6ea68cd29f0bc5b78 | []
| no_license | https://github.com/ChenhongyiYang/Gibson_Detection_Depth | 0d5e9fbce4f781aa2117eb039bcd312d03b6c318 | 8359a9738d3e7eb61d26bb51bb562d1d6f08a05b | refs/heads/master | 2020-06-11T02:58:19.849410 | 2019-06-26T05:03:33 | 2019-06-26T05:03:33 | 193,832,498 | 1 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import cv2
import numpy as np
import random
import os
img_width, img_height = 600, 600
def rand_color():
return (random.randint(0,255), random.randint(0,255), random.randint(0,255))
def draw_img(img_file, txt, out_dir):
img = cv2.imread(img_file)
img = cv2.resize(img, (img_height,img_width))
f = open(txt,'r')
lines = f.readlines()
rois = []
colors = []
for line in lines:
line = line.strip().split(' ')
if len(line) == 6 or len(line) == 7:
c = int(line[0])
ymin = int(line[1])
xmin = int(line[2])
ymax = int(line[3])
xmax = int(line[4])
score = float(line[5])
rois.append([ymin,xmin,ymax,xmax])
#col = rand_color()
col = (0,255,0)
colors.append(col)
cv2.rectangle(img, (xmin,ymin), (xmax,ymax), color=col, thickness=2)
cv2.putText(img, '%.3f'%(score), (xmin,ymin), cv2.FONT_HERSHEY_PLAIN, 1, color=col,thickness=2)
if len(line) == 7:
cv2.putText(img, '%s'%(line[6]), (xmin, ymax), cv2.FONT_HERSHEY_PLAIN, 1, color=col,thickness=2)
else:
continue
out_name = os.path.join(out_dir,os.path.split(img_file)[-1])
cv2.imwrite(out_name, img)
def run(txt_dir, img_dir, out_dir):
if not os.path.isdir(out_dir):
os.mkdir(out_dir)
for name in os.listdir(txt_dir):
txt = os.path.join(txt_dir,name)
img = os.path.join(img_dir,name.replace('txt', 'png'))
draw_img(img, txt, out_dir)
| UTF-8 | Python | false | false | 1,587 | py | 13 | box_vis.py | 12 | 0.540013 | 0.509137 | 0 | 54 | 28.074074 | 112 |
kml27/graphics_algos | 13,580,686,612,543 | 663d69ba486c2cea9baa9031b8f4e73c1de1a95b | 735f86b9abcb9e863b26b14abe395eeed172c72c | /archimedes.py | 31c2b1511b8ff52ddb4bf40f2f3a61676d661b01 | []
| no_license | https://github.com/kml27/graphics_algos | 79f2e9656da71a24e99f7e2883790f9dee05e27d | fe9f913b13aca0d03490c0353569eaa192b2bce8 | refs/heads/master | 2022-07-20T00:43:53.234599 | 2018-04-21T21:39:44 | 2018-04-21T21:39:44 | 264,089,091 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | # -*- coding: utf-8 -*-
"""
Created on Wed Jun 17 12:21:48 2015
@author: Kenny
"""
from __future__ import division
import math, turtle
#archimedes spiral (ish)
turtle.speed(0)
turtle.getscreen().tracer(16, 5)
#iterate from this number of divisions to the min (triangle)
max_divisions = 10
triangle_min = 2
just_degrees=360
#full_circle_radians = 2*math.pi
#180/pi
turtle.home()
turtle.clear()
iterations=10
#check if there's a relationship between the ratio of geometric sides to interior angles
#and the argand(polar) graph of riemman zeta(critical line)
#z=x+iy
#for set_i in range(-2, 5):
for set_i in range(1,2):
turtle.pencolor((0,0,0))
for num_fragments in range(triangle_min, max_divisions):
#turtle.clear()
outer_diameter=math.pow(2, set_i)
#dec_amt = 10
turtle.penup()
turtle.home()
turtle.seth(90)
turtle.forward(outer_diameter)
turtle.pendown()
#interior_angle =(num_fragments-2)*180/num_fragments
#works for 4,5,6,?
#one_fragment =(num_fragments-2)*180/num_fragments
scale_den=num_fragments*iterations
scale_den=num_fragments*(1/iterations)
scale_den=1/iterations
print "scale den", scale_den
#one_fragment = full_circle_radians/divisions
#works for 3
#one_fragment= just_degrees//(num_fragments*2)
one_fragment=just_degrees/num_fragments
print "sides: ", num_fragments
print "one arc: ", one_fragment
cur_heading=0#one_fragment
# scale_inc = 360//scale_den
scale_dec=(1/iterations)/scale_den
print "scale dec",scale_dec
scale= 1
for d_it in range(0,num_fragments*iterations):
#turtle.pencolor((0.5,0.5,0.5))
#turtle.circle(outer_diameter)
length=outer_diameter*scale#*math.cos(scale)
turtle.seth(cur_heading)
#turtle.left(cur_heading)
print "heading ", cur_heading
print "scale: ", scale#, math.cos(cur_heading)
turtle.forward(length)
scale=scale-scale_dec
cur_heading=cur_heading-one_fragment#*-1
#print "diameter: ", outer_diameter | UTF-8 | Python | false | false | 2,520 | py | 20 | archimedes.py | 19 | 0.547222 | 0.519444 | 0 | 96 | 24.270833 | 88 |
trassir/scripts | 14,267,881,405,454 | 7fcafcbd948c661ec769b3ba5c14b57652e37704 | 0189e2f620de20ae5d087a3d3921332afdabb141 | /scripts/universal/alarm_monitor/ts_generator.py | aa6ed95a00a5a60cbc4ef6375f08b3b45e4e5cd9 | []
| no_license | https://github.com/trassir/scripts | 8ef6ee1f249a4e24390434e979e6aaf067998430 | 20f8336de76160b65f08e65ec71c3c186e01fb5e | refs/heads/main | 2023-04-16T07:31:23.557848 | 2021-04-28T13:14:25 | 2021-04-28T13:14:25 | 344,463,871 | 0 | 1 | null | null | null | null | null | null | null | null | null | null | null | null | null | import os
import sys
import argparse
from datetime import datetime
from difflib import get_close_matches
sys.path.append('resources')
sys.path.append('../../../../')
os.environ["SAVE_ORIGINALS"] = "True"
from localization.translation_base import load_translation
parser = argparse.ArgumentParser()
parser.add_argument("target", help="Target lang (ru,en,cn,...)")
parser.add_argument("-s", "--source", help="Source language, default: en", default="en")
args = parser.parse_args()
ts_path = r"resources\%s.ts" % args.target
try:
load_translation(ts_path)
except Exception as err:
print("Can't load translation %s" % ts_path)
print("Got error: %s" % err)
continue_ = raw_input("Would you like to continue? [y/N]: ").lower() or "n"
if continue_ != "y":
exit()
import localization as loc
from localization.translation_base import Translated
__xml_version__ = "1.0"
__encoding__ = "utf-8"
__ts_version__ = "2.1"
__version__ = "1.0.0"
with open("resources/%s.ts" % args.target, "w") as tf:
tf.write(
'<?xml version="{xml_ver}" encoding="{enc}"?>\n'
"<!DOCTYPE TS>\n"
"<!-- Automatically generated by ts_generator v{ver} at {today} -->\n"
'<TS version="{ts_ver}" language="{a.target}" sourcelanguage="{a.source}">\n'
" <context>\n".format(
ver=__version__,
today=datetime.today().date(),
a=args,
xml_ver=__xml_version__,
enc=__encoding__,
ts_ver=__ts_version__,
)
)
main = getattr(loc, "main", None)
if main:
script_name = main.script_name
if script_name != Translated.build_default_message("script_name"):
tf.write(" <name>%s</name>\n" % script_name)
saved_data = {}
_all_values = set(loc.translation_base._translation.keys())
for key in sorted(loc.__dict__.keys()):
item = loc.__dict__[key]
if isinstance(item, Translated):
tf.write("\n <!-- %s -->\n" % item.__class__.__name__)
# raise ValueError("for instance name: %s, originals: %s" % (item.__class__.__name__, item.originals))
_originals = {value: key for key, value in item.originals.iteritems()}
for value in sorted(_originals.keys()):
key = _originals[value]
translation = loc.translation_base._translation.get(value)
if translation:
msg = (
" <message>\n"
" <source>{source}</source>\n"
" <translation>{target}</translation>\n"
" </message>\n".format(source=value, target=translation)
)
try:
_all_values.remove(value)
except KeyError:
pass
else:
msg = (
" <message>\n"
" <source>{source}</source>\n"
" <translation>[{lang}]{source}</translation>\n"
" </message>\n".format(source=value, lang=args.target)
)
if saved_data.get(value):
msg = (" <!-- Translated in '%s' block\n%s -->\n") % (
saved_data[value],
msg,
)
else:
close_match = get_close_matches(
value, saved_data.keys(), n=1, cutoff=0.81
)
if close_match:
print(
"WARNING: '%s' is close match to '%s'"
% (value, close_match[0])
)
saved_data[value] = item.__class__.__name__
tf.write(msg)
_all_values = list(_all_values)
if _all_values:
_all_values.sort()
msg = "Found %s not used translations in %s (%s" % (len(_all_values), ts_path, ", ".join(_all_values[:3]))
if len(_all_values) > 3:
msg += "..."
print(msg + ")")
continue_ = raw_input("Would you like to save them in new file? [Y/n]: ").lower() or "y"
if continue_ == "y":
tf.write("\n <!-- Not used in current script -->\n")
for value in _all_values:
translation = loc.translation_base._translation.get(value)
msg = (
" <message>\n"
" <source>{source}</source>\n"
" <translation>{target}</translation>\n"
" </message>\n".format(source=value, target=translation)
)
tf.write(msg)
tf.write(" </context>\n" "</TS>")
| UTF-8 | Python | false | false | 4,840 | py | 265 | ts_generator.py | 165 | 0.47686 | 0.47376 | 0 | 135 | 34.851852 | 114 |
agnunez/IQMon | 16,303,695,896,477 | 770e67f9fdc29004d402de1f4c5b509d3913be86 | 3c86c755055ca02a0092507e9779eabbe9c3ab0f | /setup.py | 772181bc215889c8bbbac74ac0f7bd2b7b16751a | [
"LicenseRef-scancode-unknown-license-reference",
"BSD-2-Clause"
]
| permissive | https://github.com/agnunez/IQMon | da3c15bc2116d5268f5377b5961d48f298f2e983 | 14fade394389e4d9ebe9f7c0fe637033a3ebdc12 | refs/heads/master | 2020-04-07T08:17:19.284403 | 2016-12-12T01:13:12 | 2016-12-12T01:13:12 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from setuptools import setup, find_packages
from IQMon import __version__
setup(
name = "IQMon",
version=__version__,
author='Josh Walawender',
packages = find_packages(),
)
| UTF-8 | Python | false | false | 190 | py | 9 | setup.py | 4 | 0.668421 | 0.668421 | 0 | 8 | 22.75 | 43 |
sevencrime/python | 13,159,779,841,593 | caf419343eba365fe5d0fa353dc2f0b4725551f4 | 91ac41baf7b0a91efd8ee657e9fe44fe1835979b | /示例/播放音乐/play_music_demo.py | 80f35cab9fd03590a47f9ebe7ff1939a3149b32d | []
| no_license | https://github.com/sevencrime/python | 0c3b27e25da1d48ac37950756be5bad821d0948c | 2ee80e467cd57db5d113b65eb9dfae2d5a561a43 | refs/heads/master | 2021-12-15T11:42:16.781369 | 2021-12-12T13:25:00 | 2021-12-12T13:25:00 | 160,919,719 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | #!/usr/bin/env python
# -*- coding: utf-8 -*-
'''
pygame.init() 进行全部模块的初始化，
pygame.mixer.init() 或者只初始化音频部分
pygame.mixer.music.load('xx.mp3') 使用文件名作为参数载入音乐 ,音乐可以是ogg、mp3等格式。载入的音乐不会全部放到内容中，而是以流的形式播放的，即在播放的时候才会一点点从文件中读取。
pygame.mixer.music.play()播放载入的音乐。该函数立即返回，音乐播放在后台进行。
play方法还可以使用两个参数
pygame.mixer.music.play(loops=0, start=0.0) loops和start分别代表重复的次数和开始播放的位置，如果是-1表示循环播放，省略表示只播放1次。第二个参数和第三个参数分别表示播放的起始和结束位置。
pygame.mixer.music.stop() 停止播放，
pygame.mixer.music.pause() 暂停播放。
pygame.mixer.music.unpause() 取消暂停。
pygame.mixer.music.fadeout(time) 用来进行淡出，在time毫秒的时间内音量由初始值渐变为0，最后停止播放。
pygame.mixer.music.set_volume(value) 来设置播放的音量，音量value的范围为0.0到1.0。
pygame.mixer.music.get_busy() 判断是否在播放音乐,返回1为正在播放。
pygame.mixer.music.set_endevent(pygame.USEREVENT + 1) 在音乐播放完成时，用事件的方式通知用户程序，设置当音乐播放完成时发送pygame.USEREVENT+1事件给用户程序。 pygame.mixer.music.queue(filename) 使用指定下一个要播放的音乐文件，当前的音乐播放完成后自动开始播放指定的下一个。一次只能指定一个等待播放的音乐文件。
'''
import pygame
import time
file = "F:\python\示例\播放音乐\POWDER_SNOW.mp3"
pygame.mixer.init()
print("播放音乐")
pygame.mixer.music.load(file)
pygame.mixer.music.play(start = 20)
time.sleep(10)
# pygame.mixer.music.stop()
| UTF-8 | Python | false | false | 1,895 | py | 43 | play_music_demo.py | 40 | 0.788039 | 0.769569 | 0 | 29 | 38.068966 | 207 |
trtnk/audio_classification_by_tf2 | 1,915,555,450,677 | 7c7cc0ae789bb0d432a32219833f75bb91085be8 | 0f866a525fde956ca418efd05b2a7a5f56c384a1 | /util/create_cvset.py | 52722f4224b7e934fea6f3e5c11f13c41a6d1a44 | [
"MIT"
]
| permissive | https://github.com/trtnk/audio_classification_by_tf2 | 7bb2cdfabbe04334962af3fecd3da27eb6fbd67e | 3d18c68315f3d6509bb36ef15d4ec4f9c8f07f61 | refs/heads/main | 2023-03-12T10:16:31.244991 | 2021-03-03T02:30:31 | 2021-03-03T02:30:31 | 343,843,017 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from util.common import *
import pandas as pd
from sklearn.model_selection import StratifiedKFold, KFold
from iterstrat.ml_stratifiers import MultilabelStratifiedKFold
def get_cv_df_from_yaml(config_yaml_path, output_csv_path=None):
config = yaml_load(config_yaml_path)
directory_label_name = config["directory_label_name"] if "directory_label_name" in config else []
file_label_name = config["file_label_name"] if "file_label_name" in config else []
# create file information df
info_df = get_file_info_df(config["data_base_directory"],
config["data_extension"],
label_csv_path=config["label_csv_path"],
directory_label_name=directory_label_name,
file_label_name=file_label_name)
# filter
if "data_constraint" in config:
info_df = df_extractor(info_df, config["data_constraint"])
# main label setting
if "default_main_label" in config["main_label"]:
main_label = config["main_label"]
elif "create_main_label" in config["main_label"]:
info_df = add_new_column(info_df, "_main_label_", config["main_label"]["create_main_label"], dropna=True)
main_label = "_main_label_"
if "test_id_path" in config:
test_id_list = list(pd.read_csv(config["test_id_path"], header=None)[0].values)
else:
test_id_list = None
if "multi_file_input" in config:
multi_file_input = True
multi_file_input_config = config["multi_file_input"]
else:
multi_file_input = False
multi_file_input_config = {}
random_state = config["cv"]["random_state"] if "random_state" in config["cv"] else None
grouped_label = config["cv"]["grouped_label"] if "grouped_label" in config["cv"] else None
# create cvset df
cv_df = get_cv_df(info_df, main_label, n_splits=config["cv"]["n_splits"], shuffle=bool(config["cv"]["shuffle"]),
test_id_list=test_id_list, id_column=config["id_column"],
grouped_label=grouped_label,
balanced=config["cv"]["balanced"], balanced_other_label=config["cv"]["balanced_other_label"],
stratified=config["cv"]["stratified"], stratified_other_labels=config["cv"]["stratified_other_labels"],
multi_file_input=multi_file_input,
multi_file_identification_info=multi_file_input_config,
random_state=random_state,
output_csv_path=output_csv_path)
return cv_df
def get_cv_df(info_df, main_label,
n_splits=5, shuffle=True,
test_id_list=None, id_column=None,
grouped_label=None,
balanced=True, balanced_other_label=None,
stratified=False, stratified_other_labels=None,
multi_file_input=False,
multi_file_identification_info={"base_column": "", "divide_column": "", "order":[]},
random_state=None,
output_csv_path=None):
cv_df = info_df.copy()
cv_df.loc[:, "cvset"] = pd.NA
info_df_ = info_df.copy()
if test_id_list is not None:
test_idx = info_df_[info_df_[id_column].isin(test_id_list)].index
cv_df.loc[test_idx, "cvset"] = "test"
info_df_ = info_df_[~info_df_[id_column].isin(test_id_list)]
# grouped
if grouped_label is not None:
key_df = info_df_.drop_duplicates(subset=grouped_label)
else:
key_df = info_df_.copy()
# balanced
if balanced:
label_vals = list(dict.fromkeys(key_df[main_label].values))
min_sample_num = key_df[main_label].value_counts().min()
key_df_ = pd.DataFrame({})
for label_val in label_vals:
each_label_key_df = key_df[key_df[main_label] == label_val]
if balanced_other_label is None:
key_df_ = key_df_.append(each_label_key_df.sample(min_sample_num, random_state=random_state)).reset_index(drop=True)
else:
key_df_ = key_df_.append(sample_balanced(each_label_key_df, min_sample_num, balanced_other_label, random_state=random_state)).reset_index(drop=True)
else:
key_df_ = key_df
# stratified
if stratified:
if stratified_other_labels is not None:
kf = MultilabelStratifiedKFold(n_splits=n_splits, shuffle=shuffle, random_state=random_state).split(key_df_, key_df_[[main_label]+stratified_other_labels])
else:
kf = StratifiedKFold(n_splits=n_splits, shuffle=shuffle, random_state=random_state).split(key_df_, key_df_[main_label])
else:
kf = KFold(n_splits=n_splits, shuffle=shuffle, random_state=random_state).split(key_df_, key_df_[main_label])
# create cv set
for cvset, (_, eval_idx) in enumerate(kf, start=1):
if grouped_label is None:
grouped_label = id_column
eval_keys = key_df_.loc[eval_idx, :][grouped_label]
cv_df.loc[cv_df[grouped_label].isin(eval_keys), "cvset"] = f"cv{cvset}"
cv_df = cv_df.dropna(subset=["cvset"])
if multi_file_input:
base_column = multi_file_identification_info["base_column"]
divide_column = multi_file_identification_info["divide_column"]
order = multi_file_identification_info["order"]
cv_df_ = cv_df.copy()
cv_df_ = cv_df_.drop_duplicates(subset=base_column)
for id_, new_df in cv_df.groupby(base_column):
file_paths = [new_df[new_df[divide_column] == val]["filepath"].values[0] for val in order]
idx = cv_df_.loc[cv_df_[base_column] == id_, "filepath"].index[0]
cv_df_.at[idx, "filepath"] = file_paths
cv_df = cv_df_.reset_index(drop=True)
if output_csv_path is not None:
cv_df.to_csv(output_csv_path, index=False)
return cv_df
| UTF-8 | Python | false | false | 5,877 | py | 10 | create_cvset.py | 10 | 0.603199 | 0.602348 | 0 | 136 | 42.213235 | 167 |
liangxuCHEN/A2Z_python | 10,393,820,905,610 | 17fb76eb004ef4c2115bb767ab1d50f0036d324d | ae201b67ef7762623a7b02d324f41f5b283a97ee | /file/db_test.py | 3876930ee185adc691e6762e85988555fe1f11c4 | []
| no_license | https://github.com/liangxuCHEN/A2Z_python | dfb9c1df5d4f97d1d0588402fce8479881675b7a | b609f0ecdf88929f60745671e3cbb594217a2325 | refs/heads/master | 2020-09-23T20:25:38.065725 | 2020-03-31T09:10:32 | 2020-03-31T09:10:32 | 225,578,825 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from sqlalchemy import Column, String, Integer, create_engine, ForeignKey
from sqlalchemy.orm import sessionmaker,relationship
from sqlalchemy.ext.declarative import declarative_base
# 创建对象的基类:
Base = declarative_base()
# 数据库连接字符串
DB_CONNECT_STRING = 'sqlite:///db_test.sqlite'
# 定义User对象:
class User(Base):
# 表的名字:
__tablename__ = 'user'
# 表的结构:
id = Column(Integer, primary_key=True)
name = Column(String(20))
# 另外写法
age = Column("age", Integer, default=0)
books = relationship('Book')
# 创建一个书的类
class Book(Base):
__tablename__ = 'book'
id = Column(Integer, primary_key=True)
name = Column(String(20))
# “多”的一方的book表是通过外键关联到user表的:
user_id = Column(String(20), ForeignKey('user.id'))
# 初始化数据库连接:
engine = create_engine(DB_CONNECT_STRING)
# 创建DBSession类型:
DBSession = sessionmaker(bind=engine)
# 删除所有表
# Base.metadata.drop_all(engine)
# 创建数据表，如果数据表存在则忽视！！！
Base.metadata.create_all(engine)
def add_user(name, age=0):
# 创建session对象:
session = DBSession()
# 创建新User对象:
new_user = User(name=name, age=age)
# 添加到session:
session.add(new_user)
# 提交即保存到数据库:
session.commit()
print("user id", new_user.id)
# 关闭session:
session.close()
return new_user
def add_book(book_name, user_id):
# 创建session对象:
session = DBSession()
# 添加到session:
# TODO: 写你们的代码
# 提交即保存到数据库:
session.commit()
# 关闭session:
print("book id", new_book.id)
session.close()
return new_book
def get_book(book_id):
"""
输入书本ｉｄ，输出书名和人名
:param book_id:
:return:
"""
pass
if __name__ == '__main__':
user1 = add_user(name="小灵", age=10)
user2 = add_user(name="大鸿", age=18)
#book = add_book(book_name='鼠标', user_id=user.id)
#print(book.id)
#get_book(5)
| UTF-8 | Python | false | false | 2,123 | py | 29 | db_test.py | 4 | 0.636565 | 0.628255 | 0 | 84 | 20.488095 | 73 |
ravina-gelda/arith | 6,416,681,145,719 | 40d5a9b972de4fba18a8e19f3cdfde5ec0b8a8c0 | b338af96eeecf70bc18004a0c73b465cc649f919 | /arith.py | 72384ec159d21e11ff403760f6cae975cff8e5b6 | []
| no_license | https://github.com/ravina-gelda/arith | d4954e7cd8ee8972b72b0d3da29577eabc497f9b | d8b4dc21e253d65475e118d138e08c88c23f7c27 | refs/heads/master | 2022-04-13T12:53:59.398504 | 2020-04-11T00:16:06 | 2020-04-11T00:16:06 | 254,487,479 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | #!/usr/bin/env python3
import sys
sys.tracebacklimit = 0
class node():
def __init__(self, left, right, op):
self.left = left
self.right = right
self.op = op
class parser():
def __init__(self, input):
self.input_list = input.split(" ")
# print(self.input_list)
def AST(self):
curr_node = node(None, None, "root")
for i in self.input_list:
# print(i.lstrip('-+'))
if i.lstrip('-+').isdigit():
new_node = node(None, None, i)
if curr_node.op == "root":
curr_node = new_node
elif curr_node.op == "*":
curr_node.right = new_node
if parent_node.op != None:
curr_node = parent_node
else:
curr_node.right = new_node
# print("integer",curr_node.op)
elif i == "+":
new_node = node(None, None, "+")
new_node.left = curr_node
curr_node = new_node
# print("+",curr_node.op)
elif i == "*":
new_node = node(None, None, "*")
parent_node = node(None, None, None)
if curr_node.op.lstrip('-+').isdigit():
new_node.left = curr_node
curr_node = new_node
else:
parent_node = curr_node
new_node.left = curr_node.right
curr_node.right = new_node
curr_node = new_node
# print("*", curr_node.op)
elif i == "-":
new_node = node(None, None, "-")
new_node.left = curr_node
curr_node = new_node
# print("-", curr_node.op)
else:
Exception("Not a valid operator")
return curr_node
def evaluate_AST(self, curr_node):
# print(curr_node.op)
if curr_node.op == "+":
return (self.evaluate_AST(curr_node.left) + self.evaluate_AST(curr_node.right))
elif curr_node.op == "-":
return (self.evaluate_AST(curr_node.left) - self.evaluate_AST(curr_node.right))
elif curr_node.op == "*":
return (self.evaluate_AST(curr_node.left) * self.evaluate_AST(curr_node.right))
else:
return int(curr_node.op)
def main():
while True:
try:
# Taking raw inputs
text = input("")
except EOFError:
break
object = parser(text)
root_node = object.AST()
output2 = object.evaluate_AST(root_node)
print(str(output2))
if __name__ == '__main__':
main()
| UTF-8 | Python | false | false | 2,850 | py | 3 | arith.py | 2 | 0.442807 | 0.441404 | 0 | 99 | 26.787879 | 91 |
eduns/Fatec | 4,930,622,469,223 | 423b6d0bf56a4c2beb31c05e84459efa830c14b0 | 59ca455b0cb6fc31e8cf2359044d7ba35ea8ba5e | /lista_II.py | 16e0b26597299ab95f572e87d0cab971d49fb5a0 | []
| no_license | https://github.com/eduns/Fatec | 4d298de36e8cad859e91b4204c5da5ae86309275 | 67ad3caa442cb9008521a8201c492d204f1dee39 | refs/heads/master | 2020-03-07T16:37:49.998655 | 2019-03-03T21:16:02 | 2019-03-03T21:16:02 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | #-------------------------------------------------------
# Exercício 1
print("============== Exercício 1 ==============")
ladoA = int(input("Lado A: "))
ladoB = int(input("Lado B: "))
ladoC = int(input("Lado C: "))
if ladoA < ladoB + ladoC or ladoB < ladoA + ladoC or ladoC < ladoA + ladoB:
if ladoA == ladoB == ladoC:
print("Equilátero")
elif ladoA == ladoB or ladoA == ladoC or ladoB == ladoC:
print("Isósceles")
elif ladoA != ladoB and ladoA != ladoC and ladoB != ladoC:
print("Escaleno")
else: print("Não é um triângulo")
#-------------------------------------------------------
#-------------------------------------------------------
# Exercício 2
print("\n\n============== Exercício 2 ==============")
ano = int(input("ano: "))
if ano % 4 == 0:
if ano % 100 != 0:
print(f"{ano} é bissexto")
else:
print(f"{ano} não é bissexto")
elif ano % 400 == 0:
print(f"{ano} é bissexto!")
else: print(f"{ano} não é bissexto")
#-------------------------------------------------------
#-------------------------------------------------------
# Exercício 3
print("\n\n============== Exercício 3 ==============")
peso = int(input("peso: "))
excesso = multa = 0
if peso > 50:
excesso = peso - 50
multa = excesso * 4
print(f"Excesso de peso: {excesso}kg\nMulta: R${multa}")
#-------------------------------------------------------
#-------------------------------------------------------
# Exercício 4
print("\n\n============== Exercício 4 ==============")
num1 = int(input("número 1: "))
num2 = int(input("número 2: "))
num3 = int(input("número 3: "))
if num1 > num2 and num1 > num3:
print(f"{num1} é o maior")
elif num2 > num1 and num2 > num3:
print(f"{num2} é o maior")
elif num3 > num1 and num3 > num2:
print(f"{num3} é o maior")
#-------------------------------------------------------
#-------------------------------------------------------
# Exercício 5
print("\n\n============== Exercício 5 ==============")
num1 = int(input("número 1: "))
num2 = int(input("número 2: "))
num3 = int(input("número 3: "))
if num1 > num2 and num1 > num3:
print(f"{num1} é o maior")
elif num2 > num3:
print(f"{num2} é o maior")
else: print(f"{num3} é o maior")
if num1 < num2 and num1 < num3:
print(f"{num1} é o menor")
elif num2 < num3:
print(f"{num2} é o menor")
else: print(f"{num3} é o menor")
#-------------------------------------------------------
#-------------------------------------------------------
# Exercício 6
print("\n\n============== Exercício 6 ==============")
valor_hora = int(input("valor por hora: "))
horas_trabalhadas = int(input("horas trabalhadas: "))
salario = valor_hora * horas_trabalhadas
imposto_renda = salario * 0.11
inss = salario * 0.08
sindicato = salario * 0.05
salario = salario - sindicato - inss - imposto_renda
print(f"salário bruto: R${valor_hora * horas_trabalhadas}")
print(f"INSS: R${inss:.2f}")
print(f"sindicato: R${sindicato:.2f}")
print(f"imposto de renda: R${imposto_renda:.2f}")
print(f"salário líquido: R${salario:.2f}")
#-------------------------------------------------------
#-------------------------------------------------------
# Exercício 7
print("\n\n============== Exercício 7 ==============")
area = int(input("área: "))
if area % 54 == 0:
latas = area / 54
else:
latas = int(area / 54) + 1
print(f"preço total: R${latas * 80}\nlatas: {latas}")
#-------------------------------------------------------
| UTF-8 | Python | false | false | 3,607 | py | 7 | lista_II.py | 6 | 0.429253 | 0.401741 | 0 | 102 | 32.921569 | 75 |
simon-cutts/message-broker | 7,258,494,751,870 | d30b68ef0244f4f90bc3b25e7de8b78a03191aa3 | d9216275d4c9be88a57d4b0a8b63146ca741193a | /Wlst/wlst/GetParam.py | 8d56969c8cf290cc4683356d1bf1a3a49c23ba19 | []
| no_license | https://github.com/simon-cutts/message-broker | 9fd0363e85d21398048b1f0c4907da7ef3bb8358 | 8c8a20bf56fd8e101b5e7114f2e8bdd9721c2683 | refs/heads/master | 2021-04-02T03:41:13.572300 | 2020-03-18T13:53:07 | 2020-03-18T13:53:07 | 248,239,797 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null |
if __name__ == '__main__':
from wlstModule import *#@UnusedWildImport
import sys
from java.lang import System
from java.io import FileInputStream
print sys.argv[1]
| UTF-8 | Python | false | false | 174 | py | 163 | GetParam.py | 56 | 0.706897 | 0.701149 | 0 | 8 | 20.375 | 46 |
swipswaps/alexa-controlled-drone | 6,090,263,657,327 | d03ac135bf2f18a74863aeff3766909b013f50b6 | e21df1066e239d16faf60298e7fd43009d84cc0b | /pi-alexa-code/start.py | 2cc035aecf7d0f3e0bed1c8273ee514a03aeede6 | []
| no_license | https://github.com/swipswaps/alexa-controlled-drone | 054a8292a563fdd04b94a364e59337fc69c7799f | 00aa987dd792fe14e6cf0d2226e8f1026d69e67c | refs/heads/master | 2022-03-28T09:48:24.846275 | 2020-01-18T07:06:49 | 2020-01-18T07:06:49 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import json
import logging
import threading
import time
import tellopy
import queue
from command import command
from iot_client import awsIoTClient
logger = logging.getLogger()
logger.setLevel(logging.INFO)
aws_client = None
speed = 80
drone = None
prev_flight_data = None
flight_data = None
log_data = None
is_drone_connected = False
command_queue = None
initial_data = 'ALT: 0 | SPD: 0 | BAT: 0 | WIFI: 0 | CAM: 0 | MODE: 0'
##############################
# Configurations
##############################
config = {
'host': '<REST API Endpoint>',
'rootCAName': '<Root certificate file name>',
'certificateName': '<Certificate file name>',
'privateKeyName': '<Private key file name>',
'clientId': 'drone_alexa_client',
'port': 8883
}
thing_name = "<THING_NAME>"
device_shadow_update_topic = "$aws/things/" + thing_name + "/shadow/update"
device_shadow_update_accepted_topic = "$aws/things/" + thing_name + "/shadow/update/accepted"
device_shadow_update_rejected_topic = "$aws/things/" + thing_name + "/shadow/update/rejected"
##############################
# Drone connection
##############################
def connect_drone():
my_drone = tellopy.Tello()
my_drone.subscribe(my_drone.EVENT_CONNECTED, drone_event_handler)
my_drone.subscribe(my_drone.EVENT_DISCONNECTED, drone_event_handler)
my_drone.subscribe(my_drone.EVENT_FLIGHT_DATA, drone_event_handler)
my_drone.subscribe(my_drone.EVENT_LOG_DATA, drone_event_handler)
my_drone.connect()
# my_drone.wait_for_connection(60.0)
return my_drone
def drone_event_handler(event, sender, data, **args):
global prev_flight_data, flight_data, log_data, is_drone_connected
my_drone = sender
if event is my_drone.EVENT_CONNECTED:
logging.info("Connected to drone!...")
is_drone_connected = True
elif event is my_drone.EVENT_DISCONNECTED:
logging.warning("Disconnected from drone!...")
is_drone_connected = False
elif event is my_drone.EVENT_FLIGHT_DATA:
if prev_flight_data != str(data):
logging.info(data)
prev_flight_data = str(data)
flight_data = data
elif event is my_drone.EVENT_LOG_DATA:
if log_data != str(data):
logging.debug(data)
log_data = str(data)
else:
logging.debug('event="%s" data=%s' % (event.getname(), str(data)))
##############################
# Telemetry
##############################
def compute_telemetry(raw_data, drone_connected):
message = {}
# flight_data= 'ALT: 0 | SPD: 0 | BAT: 94 | WIFI: 90 | CAM: 0 | MODE: 1'
if raw_data is None or len(raw_data) < 1:
return message
telemetry = {}
tele_arr = raw_data.split('|')
for element in tele_arr:
element = element.replace(" ", "")
kv = element.split(':')
telemetry[kv[0]] = int(kv[1])
pass
message['state'] = {}
message['state']['reported'] = {}
for key in telemetry:
message['state']['reported'][key] = telemetry[key]
pass
message['state']['reported']['ISONLINE'] = drone_connected
return message
def send_telemetry_loop():
logging.info("Starting telemetry loop " + str(is_drone_connected))
while is_drone_connected:
try:
send_telemetry(prev_flight_data, True)
time.sleep(500e-3) # 500ms
except Exception as e:
logging.error("Error occurred while sending telemetry " + str(e))
logging.info("Exiting telemetry loop " + str(is_drone_connected))
def send_telemetry(raw_data, drone_connected):
message_json = json.dumps(compute_telemetry(raw_data, drone_connected))
aws_client.publish_message(device_shadow_update_topic, message_json)
##############################
# Callback
##############################
def message_callback(client, userdata, message):
try:
topic = message.topic
rawdata = str(message.payload.decode("utf-8"))
jsondata = json.loads(rawdata)
if topic == device_shadow_update_rejected_topic:
logging.warning("Telemetry message got rejected...")
else:
logging.info("Topic: " + message.topic + "\nMessage: " + rawdata)
create_commands(jsondata, topic)
except Exception as e:
logging.error("Error occurred " + str(e))
##################################
# Queue Based Command processing
##################################
def create_commands(jsondata, topic):
command_delay = 1
stop_delay = 100e-3 # 100ms
data = jsondata["value"]
if topic == "drone/takeoff":
enqueue_command(lambda: drone.takeoff(), 0)
elif topic == "drone/land":
enqueue_command(lambda: drone.land(), 0)
elif topic == "drone/direction":
if data == "right":
enqueue_command(lambda: drone.right(speed), command_delay)
enqueue_command(lambda: drone.right(0), stop_delay)
elif data == "left":
enqueue_command(lambda: drone.left(speed), command_delay)
enqueue_command(lambda: drone.left(0), stop_delay)
elif data == "forward":
enqueue_command(lambda: drone.forward(speed), command_delay)
enqueue_command(lambda: drone.forward(0), stop_delay)
elif data == "back":
enqueue_command(lambda: drone.backward(speed), command_delay)
enqueue_command(lambda: drone.backward(0), stop_delay)
elif data == "up":
enqueue_command(lambda: drone.up(speed), command_delay)
enqueue_command(lambda: drone.up(0), stop_delay)
elif data == "down":
enqueue_command(lambda: drone.down(speed), command_delay)
enqueue_command(lambda: drone.down(0), stop_delay)
else:
pass
elif topic == "drone/flip":
enqueue_command(lambda: drone.flip_forward(), 0)
elif topic == "drone/rotate":
if data == "left":
enqueue_command(lambda: drone.counter_clockwise(speed), command_delay)
enqueue_command(lambda: drone.counter_clockwise(0), stop_delay)
elif data == "right":
enqueue_command(lambda: drone.clockwise(speed), command_delay)
enqueue_command(lambda: drone.clockwise(0), stop_delay)
else:
pass
else:
pass
# Enqueuing commands
def enqueue_command(command_callback, delay):
command_object = command(command_callback, delay)
command_queue.put(command_object)
def process_command():
while True:
try:
command_item = command_queue.get_nowait()
if command_item is None:
break
command_item.command_function()
time.sleep(command_item.delay)
command_queue.task_done()
except queue.Empty: # ignore empty queue exceptions
pass
except Exception as ex:
logging.error(str(ex))
logging.info("Command loop finished")
def create_wait_threads():
global command_queue
command_queue = queue.Queue()
command_processor_thread = threading.Thread(target=process_command) # Define a thread
command_processor_thread.setDaemon(
True) # 'True' means it is a front thread,it would close when the mainloop() closes
command_processor_thread.start()
drone_telemetry_thread = threading.Thread(target=send_telemetry_loop) # Define a thread
drone_telemetry_thread.setDaemon(
True) # 'True' means it is a front thread,it would close when the mainloop() closes
drone_telemetry_thread.start()
# Block the thread
drone_telemetry_thread.join()
# Block the queue
command_queue.join()
##############################
# Entry point
##############################
if __name__ == "__main__":
try:
aws_client = awsIoTClient(config)
drone = connect_drone()
aws_client.subscribe([
'drone/takeoff',
'drone/land',
'drone/direction',
'drone/rotate',
'drone/flip'
# device_shadow_update_rejected_topic
],
message_callback)
send_telemetry(initial_data, False)
logging.info('Initial telemetry sent...')
# Waiting for drone connection...
while is_drone_connected is False:
print("Waiting for connection...", end="\r")
time.sleep(100e-3)
pass
create_wait_threads()
# cancelling command loop
command_queue.put(None)
logging.warning('Sending final telemetry sent...')
send_telemetry(initial_data, False)
except KeyboardInterrupt:
logging.warning('KeyboardInterrupt...')
logging.warning('Sending final telemetry sent...')
send_telemetry(initial_data, False)
time.sleep(1)
except Exception as e:
# exc_type, exc_value, exc_traceback = sys.exc_info()
# traceback.print_exception(exc_type, exc_value, exc_traceback)
logging.error(str(e))
finally:
if drone is not None:
drone.land()
drone.quit()
if aws_client is not None:
aws_client.disconnect()
logging.info('Exiting program...')
exit(1)
| UTF-8 | Python | false | false | 9,239 | py | 6 | start.py | 3 | 0.597359 | 0.590973 | 0 | 287 | 31.191638 | 93 |
karthikpappu/pyc_source | 5,858,335,414,464 | 861ca8f8ae68498e8ddce47b05d8fa8b11a6894f | 91fa095f423a3bf47eba7178a355aab3ca22cf7f | /pypi_install_script/python-simpledaemon-0.1.tar/setup.py | 5e9b61d707e9f7e8def38562c686373556af4b89 | []
| no_license | https://github.com/karthikpappu/pyc_source | 0ff4d03e6d7f88c1aca7263cc294d3fa17145c9f | 739e7e73180f2c3da5fd25bd1304a3fecfff8d6e | refs/heads/master | 2023-02-04T11:27:19.098827 | 2020-12-27T04:51:17 | 2020-12-27T04:51:17 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | #!/usr/bin/env python
__version__ = '0.1'
__author__ = 'Richard Hoop'
import sys
try:
from setuptools import setup
except ImportError:
print("python-simpledaemon needs setuptools in order to build. Install it using"
" your package manager (usually python-setuptools) or via pip (pip"
" install setuptools).")
sys.exit(1)
setup(
name='python-simpledaemon',
version=__version__,
description='Easy Python Daemon',
author=__author__,
author_email='richard@projecticeland.net',
license='GPLv3',
data_files=[],
url="https://github.com/gemini/python-simpledaemon",
packages=['simpledaemon']
)
| UTF-8 | Python | false | false | 658 | py | 114,545 | setup.py | 111,506 | 0.661094 | 0.655015 | 0 | 26 | 24.307692 | 84 |
plasticine/cobracommander-henchman | 2,061,584,330,668 | 1337657dddff70c1ab8b5b09432ab351a1a719fa | 5d2c0a3549f394d855c2a2c07db6adc38e62a5d8 | /henchman/buildqueue.py | 02803fd49f9475b015fad50fb0c5080ed7859b38 | []
| no_license | https://github.com/plasticine/cobracommander-henchman | a74abd71e7853b8db2aba4247bdf76611fb5bffb | afe26810a2dfb093d917e64b02b88295a83db174 | refs/heads/master | 2020-06-09T03:43:57.336757 | 2012-02-21T07:05:36 | 2012-02-21T07:05:36 | 2,833,997 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import gevent
import json
from .minion import Minion
from .utils.logger import get_logger
class BuildQueue(object):
"""
The BuildQueue class is used to manage Minions either currently being built
or waiting to be built.
Defines socket.io methods for subscribing and updating the build queue. These
are wrapped up on django-socketio events.
"""
def __init__(self):
self._queue = []
self._completed = []
self._monitor_sleep_time = 1
self._monitor_hibernate_time = 5
self._current_item = 0
self._logger = get_logger(__name__)
self._logger.info('Monitoring queue for incoming builds')
gevent.spawn(self._monitor)
def __len__(self):
return len(self._queue)
def __iter__(self):
return self
def __getitem__(self, key):
return self._queue[key]
def next(self):
if (self._current_item == len(self._queue)):
self._current_item = 0
raise StopIteration
else:
data = self._queue[self._current_item]
self._current_item += 1
return data
def append(self, id):
"""
Create a new Minion instance for `id` and append it to the internal
queue list.
"""
self._queue.append(self._wrap_minion(id))
self._logger.info('Appended new build to queue with id:%s, queue length is now %s', id, len(self._queue))
def _wrap_minion(self, id):
return Minion(id=id)
def _monitor(self):
"""
Poll `_queue` to see if we need to start a new Minion.
"""
while True:
# filter queue for only items that are waiting to execute.
if len(self._queue):
if len(filter(lambda x: not x.is_waiting, self._queue)) < 1:
minion = self._queue[0]
self._logger.info('Putting minion to work')
minion.start()
self._clean_queue()
self._hibernate()
gevent.sleep(self._monitor_sleep_time)
def _hibernate(self):
self._logger.info('Hibernating for %s seconds', self._monitor_hibernate_time)
gevent.sleep(self._monitor_hibernate_time)
def _clean_queue(self):
"""
remove completed Minions from the build queue and prepend them to the
complete queue for reference.
"""
self._logger.info('Cleaning internal build queue')
completed = self._completed
complete = [i for i, x in enumerate(self._queue) if x.is_complete]
[completed.insert(0, self._queue[x]) for x in complete]
self._completed = completed[:5]
self._queue[:] = [x for x in self._queue if not x.is_complete]
| UTF-8 | Python | false | false | 2,489 | py | 38 | buildqueue.py | 30 | 0.64323 | 0.639614 | 0 | 84 | 28.630952 | 109 |
dayjaby/CrowdAnki | 9,921,374,484,194 | 62151f11e05ae017685e8afd3b111ef0f612057b | c604da64c262d6d0244abeaf169ae91e3119884e | /crowd_anki/anki_exporter.py | 39a02870d9dddd68eecbcba3dc39de2655298b54 | [
"MIT"
]
| permissive | https://github.com/dayjaby/CrowdAnki | 27d2d7c31d403f6ee98cc2cb8f44fd6f7b4bc395 | 39c9666d58b16483631c13521597ae38a9d66cfa | refs/heads/master | 2021-01-21T08:33:22.067652 | 2016-09-07T09:59:00 | 2016-09-07T09:59:00 | 67,587,160 | 0 | 0 | null | true | 2016-09-07T08:23:13 | 2016-09-07T08:23:12 | 2016-09-07T06:04:47 | 2016-08-31T19:12:32 | 70 | 0 | 0 | 0 | null | null | null | import json
import os
import shutil
from thirdparty.pathlib import Path
from crowd_anki.utils.constants import DECK_FILE_EXTENSION, MEDIA_SUBDIRECTORY_NAME
from crowd_anki.representation.deck import Deck
class AnkiJsonExporter(object):
def __init__(self, collection):
self.collection = collection
def export_deck_to_directory(self, deck_name, output_dir=Path("."), copy_media=True):
deck_directory = output_dir.joinpath(deck_name)
deck_directory.mkdir(parents=True, exist_ok=True)
deck = Deck.from_collection(self.collection, deck_name)
deck_filename = deck_directory.joinpath(deck_name).with_suffix(DECK_FILE_EXTENSION)
with deck_filename.open(mode='w') as deck_file:
deck_file.write(unicode(json.dumps(deck,
default=Deck.default_json,
sort_keys=True,
indent=4,
ensure_ascii=False)))
self._save_changes()
if copy_media:
self._copy_media(deck, deck_directory)
def _save_changes(self):
"""Save updates that were maid during the export. E.g. UUID fields"""
# This saves decks and deck configurations
self.collection.decks.save()
self.collection.decks.flush()
self.collection.models.save()
self.collection.models.flush()
# Notes?
def _copy_media(self, deck, deck_directory):
media_directory = deck_directory.joinpath(MEDIA_SUBDIRECTORY_NAME)
media_directory.mkdir(parents=True, exist_ok=True)
for file_src in deck.get_media_file_list():
shutil.copy(os.path.join(self.collection.media.dir(), file_src),
str(media_directory.resolve()))
| UTF-8 | Python | false | false | 1,853 | py | 6 | anki_exporter.py | 5 | 0.602806 | 0.602267 | 0 | 51 | 35.333333 | 91 |
Tomoki-Kikuta/atcoder | 8,718,783,628,295 | 583d1eb54819c35a4c2ededdec99cf69f4b027c6 | 796198b4613ae30ff7735d7a8473064b8ecb0247 | /atcoder過去問/all_pairs_shortest_path.py | 0a59511165ac86b03aa16ed23df703cdd8f36781 | []
| no_license | https://github.com/Tomoki-Kikuta/atcoder | 993cb13ae30435d02ea2e743cf3cead1a7882830 | 97b886de867575084bd1a70310a2a9c1c514befe | refs/heads/master | 2021-07-16T15:14:00.706609 | 2020-06-29T06:15:13 | 2020-06-29T06:15:13 | 184,001,549 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | def warshall_floyd(dp, v):
for k in range(v):
for i in range(v):
for j in range(v):
dp[i][j] = min(dp[i][j], dp[i][k] + dp[k][j])
def check(dp, v):
for k in range(v):
for i in range(v):
for j in range(v):
if dp[i][j] > dp[i][k] + dp[k][j]:
return False
return True
def main():
v, e = map(int, input().split())
INF = 10 ** 10
MAX = 2 * (10 ** 7)
MIN = -2 * (10 ** 7)
dp = [[INF for i in range(v)] for j in range(v)]
for i in range(e):
s, t, d = map(int, input().split())
dp[s][t] = d
for i in range(v):
for j in range(v):
if i == j:
dp[i][j] = 0
warshall_floyd(dp, v)
if not check(dp, v):
print("NEGATIVE CYCLE")
else:
for i in range(v):
for j in range(v):
if j > 0:
print(end=' ')
if dp[i][j] > MAX * v or dp[i][j] < MIN * v:
print("INF", end='')
else:
print(dp[i][j], end='')
print()
if __name__ == '__main__':
main()
| UTF-8 | Python | false | false | 1,174 | py | 178 | all_pairs_shortest_path.py | 178 | 0.38586 | 0.373935 | 0 | 47 | 23.978723 | 61 |
reachgsreeja/school_management | 10,849,087,397,633 | d2e63cbff7af8e994a872c8c0942bf89062c3e8f | a2a042e26c2603f1fd831df355f90607eddc0b98 | /schoolboard/school_1/admission/models.py | 947a96eba6f3a64263b590ec0fb5b6391918a7c0 | []
| no_license | https://github.com/reachgsreeja/school_management | 8f2f4a0b9aec896881aaded63367d026dcf0d0ef | a20b8b9717a48e49c59efe8b5a2c7dc3fd99cc83 | refs/heads/master | 2021-01-26T03:11:53.777891 | 2020-02-27T14:54:13 | 2020-02-27T14:54:13 | 243,285,359 | 0 | 0 | null | false | 2020-02-28T13:28:18 | 2020-02-26T14:40:09 | 2020-02-27T14:54:43 | 2020-02-28T13:20:40 | 26,650 | 0 | 0 | 1 | JavaScript | false | false | from django.db import models
from datetime import datetime
# Create your models here.
class StudentInfo(models.Model):
first_name = models.CharField(max_length=255)
last_name = models.CharField(max_length=255)
student_class = models.PositiveIntegerField()
date_of_birth = models.DateField(null=False)
acadamic_year = models.PositiveIntegerField(null=True, blank=False)
gender = models.CharField(max_length=50)
student_image = models.ImageField(null=True, blank=True)
def __str__(self):
return ( self.first_name + ' ' + self.last_name )
class StudentParentInfo(models.Model):
student = models.ForeignKey(StudentInfo, on_delete=models.CASCADE)
father_name = models.CharField(max_length=255)
mother_name = models.CharField(max_length=255)
contact_info = models.CharField(max_length=10)
email_id = models.EmailField(max_length=255)
address1 = models.CharField(max_length=255)
address2 = models.CharField(max_length=255)
city = models.CharField(max_length=50)
state = models.CharField(max_length=100)
country_code = models.CharField(max_length=10)
postal_code = models.CharField(max_length=10)
def __str__(self):
return self.father_name + self.email_id
class TeacherInfo(models.Model):
first_name = models.CharField(max_length=255)
last_name = models.CharField(max_length=255)
gender = models.CharField(max_length=50)
date_of_birth = models.DateField()
qualifications = models.CharField(max_length=255)
subject_teaches = models.CharField(max_length=10)
contact_num = models.CharField(max_length=10)
email_id = models.EmailField(max_length=100)
address = models.CharField(max_length=255)
city = models.CharField(max_length=50)
state = models.CharField(max_length=100)
country = models.CharField(max_length=20)
postal_code = models.CharField(max_length=50)
def __str__(self):
return self.first_name + self.gender
class Results(models.Model):
semester_choices = (
('quarterly', 'Quarterly Exam'),
('half_yearly', 'Half Yearly Exam'),
('yearly', 'Yearly Exam'),
)
student = models.ForeignKey(StudentInfo, on_delete=models.CASCADE)
telugu = models.IntegerField(default=0)
hindi = models.IntegerField(default=0)
english = models.IntegerField(default=0)
maths = models.IntegerField(default=0)
science = models.IntegerField(default=0)
social = models.IntegerField(default=0)
semester = models.CharField(max_length=100, blank=True, choices=semester_choices)
def total_marks(self):
return self.telugu + self.hindi + self.english + self.maths + self.science + self.social
| UTF-8 | Python | false | false | 2,706 | py | 30 | models.py | 16 | 0.703252 | 0.675536 | 0 | 69 | 38.15942 | 96 |
luimaking/Agriculture | 18,519,898,985,401 | 9832f1fa10e6042f8cbf7334b6b30cccfa2c6a5b | 6e971d53fa4e2c37d853a3516a282db00ea70b55 | /agricultura/agro/agro/urls.py | fc8e4fa94506d284b1a1d5238962e78a6f3b5248 | []
| no_license | https://github.com/luimaking/Agriculture | 1522a589e47996fb76ba4396b15252f1bf29fd34 | 2c4af741e6e5f2b2bf238f213aa9bbf1e083c6bc | refs/heads/master | 2015-08-07T14:04:35.529690 | 2013-04-05T23:30:53 | 2013-04-05T23:30:53 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from django.conf.urls import patterns, include, url
from django.contrib import admin
from django.conf import settings
admin.autodiscover()
urlpatterns = patterns('',
url(r'^$','miapp.views.clientes_reciente'),
url(r'^herramienta/nueva/$','miapp.views.nueva_herramienta'),
url(r'^insumo/nuevo/$','miapp.views.nuevo_insumo'),
url(r'^empleado/nuevo/$','miapp.views.nuevo_empleado'),
url(r'^proveedor/nuevo/$','miapp.views.nuevo_proveedor'),
url(r'^galpon/nuevo/$','miapp.views.nuevo_galpones'),
url(r'^campo/nuevo/$','miapp.views.nuevo_campo'),
url(r'^stock/nuevo/$','miapp.views.nuevo_stock'),
url(r'^cliente/nuevo/$','miapp.views.nuevo_cliente'),
url(r'^clientes/$','miapp.views.lista_clientes'),
url(r'^detalle/cliente/(?P<id_clt>\d+)$','miapp.views.detalle_cliente'),
url(r'^telefono/cliente/(?P<id_clt>\d+)$','miapp.views.telefono_cliente'),
url(r'^borrar/(?P<id_cliente>\d+)$','miapp.views.borrar_cliente'),
url(r'^editar/(?P<id_cliente>\d+)$','miapp.views.editar_cliente'),
url(r'^admin/doc/', include('django.contrib.admindocs.urls')),
url(r'^admin/', include(admin.site.urls)),
)
| UTF-8 | Python | false | false | 1,125 | py | 14 | urls.py | 5 | 0.683556 | 0.683556 | 0 | 25 | 44 | 76 |
gercaballero/U5-PRACTICO-WEB | 8,495,445,354,453 | 50268cabca8e5bcacf2b76da2a8a2d17804bb8f2 | 15149551d64b767d7c776c2bc81811f6ee5aaef3 | /app.py | d75490eff089686ba56e20d1fa6afab16ba1aa63 | []
| no_license | https://github.com/gercaballero/U5-PRACTICO-WEB | 7ef04b87a5d8e4d4c8aa55de5d96f9fab0fd0a72 | 133c1fee99d61a0cfc6c51f1cae510af858020ba | refs/heads/main | 2023-08-23T19:51:46.423705 | 2021-10-05T21:26:39 | 2021-10-05T21:26:39 | 376,780,631 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from datetime import datetime
from flask import Flask, redirect, request, render_template, flash,session, url_for
from flask_sqlalchemy import SQLAlchemy
from werkzeug.security import generate_password_hash, check_password_hash
import hashlib
app = Flask(__name__)
app.config.from_pyfile('config.py')
from models import db
from models import Usuario,Viaje, Movil
@app.route('/')
def inicio():
return render_template('inicio.html')
'''REGISTRO DE USUARIO'''
@app.route('/registro_usuario', methods= ['GET','POST'])
def registro_usuario():
if request.method=='POST':
if not request.form['DNI'] or not request.form['password']:
return render_template('error.html', error="Los datos ingresados no son correctos...")
else:
usuario_actual = Usuario.query.filter_by(DNI = request.form['DNI']).first()
if usuario_actual is not None:
return render_template('error.html', error="ERROR: USUARIO CON DNI EXISTENTE")
else:
clave= request.form['password']
Clave=hashlib.md5(bytes(clave, encoding='utf-8'))
nuevo_usuario = Usuario(DNI=request.form['DNI'],nombre=request.form['nombre'], clave=Clave.hexdigest(), tipo=request.form['tipo'])
db.session.add(nuevo_usuario)
db.session.commit()
return render_template('error.html', error="Usuario Registrado con exito...")
return render_template('registro.html')
'''INICIAR SESION'''
@app.route('/login', methods = ['GET','POST'])
def login():
if request.method == 'POST':
if not request.form['DNI'] or not request.form['password']:
return render_template('error.html', error="Por favor ingrese los datos requeridos")
else:
usuario_actual = Usuario.query.filter_by(DNI = request.form['DNI']).first()
if usuario_actual is None:
return render_template('error.html', error="El DNI no está registrado")
else:
verif=request.form['password']
verificacion = hashlib.md5(bytes(verif, encoding='utf-8'))
if verificacion.hexdigest() ==usuario_actual.clave:
if usuario_actual.tipo == 'cli':
return redirect(url_for('cliente', cliente_dni = usuario_actual.DNI))
elif usuario_actual.tipo == 'op':
return redirect(url_for('operador',operador_dni=usuario_actual.DNI))
else: return render_template('error.html', error="El tipo no es Valido")
else:
return render_template('error.html', error="La contraseña no es válida")
else:
return render_template('login.html')
'''FUNCIONALIDADES CLIENTE'''
@app.route('/cliente/<cliente_dni>',methods=['GET','POST'])
def cliente(cliente_dni):
usuario_actual = Usuario.query.filter_by(DNI = cliente_dni).first()
return render_template('vistaCliente.html',usuario=usuario_actual)
@app.route('/cliente/<cliente_dni>/solicitarMovil/', methods = ['POST', 'GET'])
def solicitarMovil(cliente_dni):
usuario_actual = Usuario.query.filter_by(DNI = cliente_dni).first()
if request.method == 'POST':
listadeviajes = Viaje.query.all()
id = int(len(listadeviajes)) + 1
fecha1=datetime.now()
fecha = datetime.strftime(fecha1, '%Y-%m-%d %H:%M:%S')
fecha = datetime.strptime(fecha, '%Y-%m-%d %H:%M:%S')
importe = 0 # sin calcular
origen = request.form['origen']
destino = request.form['destino']
numeromovil = 0
demora = 0
duracion = 0
viaje = Viaje(IDViaje = id, origen = origen, destino = destino, fecha = fecha, demora = demora, duracion = duracion, importe = importe, DNICliente = cliente_dni, numMovil = numeromovil)
db.session.add(viaje)
db.session.commit()
usuario_actual = Usuario.query.filter_by(DNI = cliente_dni).first()
return render_template('alerta_cli.html', error='Se ha solicitado el movil de forma correcta', usuario=usuario_actual)
return render_template('solicitarMovil.html',usuario=usuario_actual)
@app.route('/cliente/<cliente_dni>/consultar_movil/', methods = ['POST', 'GET'])
def consultar_movil(cliente_dni):
usuario_actual = Usuario.query.filter_by(DNI = cliente_dni).first()
lista = Viaje.query.filter_by(importe = 0).all()
listaMoviles = Movil.query.all()
listaViajes=[]
for viaje in lista:
if viaje.duracion==0 and viaje.DNICliente == usuario_actual.DNI:
listaViajes.append(viaje)
longitud=len(listaViajes)
return render_template('consultar_movil.html', usuario=usuario_actual,viajes=listaViajes,moviles=listaMoviles,len=longitud)
'''FUNCIONALIDADES OPERADOR'''
@app.route('/operador/<operador_dni>')
def operador(operador_dni):
usuario_actual = Usuario.query.filter_by(DNI = operador_dni).first()
return render_template('vistaOperador.html',usuario=usuario_actual)
@app.route('/operador/<operador_dni>/asigno', methods = ['POST', 'GET'])
def asigno(operador_dni):
usuario_actual = Usuario.query.filter_by(DNI = operador_dni).first()
listadeviajes = Viaje.query.filter_by(numMovil = 0).all()
longitud=len(listadeviajes)
return render_template('asignar_movil.html', usuario=usuario_actual,viajes = listadeviajes,len=longitud)
@app.route('/operador/<operador_dni>/asigno/<viajeID>/elegirMovil', methods = ['POST', 'GET'])
def elegirMovil(operador_dni,viajeID):
usuario_actual = Usuario.query.filter_by(DNI = operador_dni).first()
viaje_actual= Viaje.query.filter_by(IDViaje=int(viajeID)).first()
lista=Movil.query.all()
listademoviles=[]
for movil in lista:
if movil.viajeBool==0:
listademoviles.append(movil)
longitud=len(listademoviles)
if request.method == 'POST':
num=int(request.form['MovilNum'])
movil_actual =Movil.query.filter_by(numero = request.form['MovilNum']).first()
demora=int(request.form['espera'])
viaje_actual.numMovil=num
viaje_actual.demora=demora
movil_actual.viajeBool = int(viajeID)
db.session.commit()
return render_template('alerta_op.html', error='MOVIL ASIGNADO',usuario=usuario_actual)
else:
return render_template('elegirMovil.html',moviles=listademoviles,usuario=usuario_actual,viaje=viaje_actual,len=longitud)
@app.route('/operador/<operador_dni>/finalizar_viaje', methods = ['POST', 'GET'])
def finalizar_viaje(operador_dni):
usuario_actual = Usuario.query.filter_by(DNI = operador_dni).first()
if request.method == 'POST':
viaje = Viaje.query.filter_by(IDViaje = int(request.form['finalizar'])).first()
duracion=int(request.form['duracion'])
movil = Movil.query.filter_by(numero = str(viaje.numMovil)).first()
movil.viajeBool = int(0)
importe=100.0+(duracion*5)
if viaje.demora>15:
importe+=importe*0.10
viaje.duracion=duracion
viaje.importe=importe
db.session.commit()
return render_template ('alerta_op.html',usuario=usuario_actual ,error='Viaje Finalizado',aviso=('Importe final:{}'.format(importe)))
else:
listaViajes = Viaje.query.filter_by(duracion = 0).all()
listaDef=[]
print(listaViajes)
for viaje in listaViajes:
if viaje.numMovil != 0:
listaDef.append(viaje)
longitud=len(listaDef)
return render_template('finalizar_viaje.html',usuario=usuario_actual,viajes=listaDef,len=longitud)
@app.route('/operador/<operador_dni>/consultar_viaje_movil', methods = ['POST', 'GET'])
def consultar_viaje_movil(operador_dni):
usuario_actual = Usuario.query.filter_by(DNI = operador_dni).first()
if request.method == 'POST':
impTotal=0
movilNum=int(request.form['ElegirMovil'])
fecha=request.form['fecha_elegir']
listademoviles = Movil.query.all()
listaViajes = Viaje.query.all()
listaViajesFinalizados=[]
for viaje in listaViajes:
if viaje.duracion>0:
listaViajesFinalizados.append(viaje)
listaViajesDeMovil=[]
for viaje in listaViajesFinalizados:
if int(viaje.numMovil)==movilNum:
fechaSinHORA=datetime.strftime(viaje.fecha, '%Y-%m-%d')
if fechaSinHORA==fecha:
impTotal=impTotal+viaje.importe
listaViajesDeMovil.append(viaje)
longitud=len(listaViajesDeMovil)
return render_template('consultar_viaje2.html',usuario=usuario_actual,viajes=listaViajesDeMovil,importe=impTotal,len=longitud )
else:
listademoviles = Movil.query.all()
return render_template('consultar_viaje.html',usuario=usuario_actual,moviles=listademoviles)
if __name__ == '__main__':
db.create_all()
app.run(debug = True)
| UTF-8 | Python | false | false | 9,297 | py | 19 | app.py | 3 | 0.625457 | 0.622122 | 0 | 201 | 44.238806 | 197 |
vodolazik/CC-homework-1 | 10,995,116,325,785 | 4db80cc62c2435fcdb84c43afc8418117fb3a6fd | 620157db586d43cf27bc93ae08a1d3219dc71c0b | /Code Club. Homework1.py | ba143981a783eb7902d77210797f0b628de541dd | []
| no_license | https://github.com/vodolazik/CC-homework-1 | 7905df1727226d7134e4c4d64186002dabf22f94 | 88e80bc449cee24d000f4ce781e64ca290decd69 | refs/heads/master | 2022-12-11T21:11:19.861469 | 2020-08-29T16:10:44 | 2020-08-29T16:10:44 | 291,304,280 | 1 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import tkinter as tk
import json
import requests
response = requests.get("https://bank.gov.ua/NBUStatService/v1/statdirectory/exchangenew?json&valcode=USD")
todos = json.loads(response.text)
a = todos[0]
b = a['rate']
class SampleApp(tk.Tk):
def __init__(self):
tk.Tk.__init__(self)
self.lable1 = tk.Label(text="Курс доллара на сегодня " + str(a['rate']))
self.lable1.pack()
self.lable2 = tk.Label(text="Введите цену товара в Долларах США")
self.lable2.pack()
self.entry = tk.Entry(self)
self.button = tk.Button(self, text="Рассчитать", command=self.on_button)
self.entry.pack()
self.button.pack()
def on_button(self):
content = float((self.entry.get()))
c = int(content * b)
self.lable3 = tk.Label(text="Цена товара в Гривнах: " + str(c))
self.lable3.pack()
app = SampleApp()
app.mainloop() | UTF-8 | Python | false | false | 1,016 | py | 1 | Code Club. Homework1.py | 1 | 0.604899 | 0.596379 | 0 | 31 | 28.354839 | 107 |
Delta-Lyceum/Delta-Lyceum | 111,669,168,370 | f0485b35c01744120b09622bd2be9c65954eb4f4 | 056f615b2911f2f144ba25dfc69f7429f8b73de8 | /nexus/urls.py | ea13bb5d607f36d8801a6bd9225a5f76fda9358a | [
"Apache-2.0"
]
| permissive | https://github.com/Delta-Lyceum/Delta-Lyceum | 3067430de45ed10a89a62ae9f6bd1f5b6e2bf7d6 | 534fc6fa82b831d13bb3fe34980d29da42746e37 | refs/heads/master | 2020-03-21T21:14:13.838939 | 2019-02-19T03:47:11 | 2019-02-19T03:47:11 | 139,053,778 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from django.urls import path, include
from . import views
app_name = 'nexus'
urlpatterns = [
path('nexus/create/', views.create_nexus, name='create_nexus'),
path('nexus/<int:nexus_id>/edit/', views.edit_nexus, name='edit_nexus'),
path('nexus/<int:nexus_id>/view/', views.view_nexus, name='view_nexus'),
path('nexus/<int:nexus_id>/media/upload/', views.upload_media, name='upload_media'),
path('nexus/<int:nexus_id>/image/load/', views.load_image, name='load_image'),
path('nexus/<int:nexus_id>/audio/load/', views.load_audio, name='load_audio'),
path('nexus/<int:nexus_id>/video/load/', views.load_video, name='load_video'),
path('nexus/<int:nexus_id>/image/remove/', views.remove_image, name='remove_image'),
path('nexus/<int:nexus_id>/audio/remove/', views.remove_audio, name='remove_audio'),
path('nexus/<int:nexus_id>/video/remove/', views.remove_video, name='remove_video'),
path('nexus/<int:nexus_id>/applause/', views.display_applause, name='display_applause'),
path('nexus/<int:nexus_id>/reverbs/', views.display_reverbs, name='display_reverbs'),
path('nexus/<int:nexus_id>/delete/', views.delete_nexus, name='delete_nexus'),
#Ajax
path('ajax/nexus/feed/views/', views.add_feed_views, name='add_feed_views'),
path('ajax/nexus/tags/track/', views.track_tags, name='track_tags'),
path('ajax/nexus/<int:nexus_id>/update/', views.update_nexus, name='update_nexus'),
path('ajax/nexus/<int:nexus_id>/image/save/', views.save_image, name='save_image'),
path('ajax/nexus/<int:nexus_id>/youtube/save/', views.save_youtube_video, name='save_youtube_video'),
path('ajax/nexus/<int:nexus_id>/score/remove/', views.remove_score, name='remove_score'),
path('ajax/nexus/<int:nexus_id>/notio/remove/', views.remove_notio, name='remove_notio'),
path('ajax/nexus/<int:nexus_id>/tags/search/', views.search_tags, name='search_tags'),
path('ajax/nexus/<int:nexus_id>/tags/add/', views.add_tag, name='add_tag'),
path('ajax/nexus/<int:nexus_id>/tags/remove/', views.remove_tag, name='remove_tag'),
path('ajax/nexus/<int:nexus_id>/info/', views.get_nexus_info, name='get_nexus_info'),
path('ajax/nexus/<int:nexus_id>/applaud/', views.applaud_nexus, name='applaud_nexus'),
path('ajax/nexus/<int:nexus_id>/reverb/', views.reverb_nexus, name='reverb_nexus'),
path('ajax/nexus/<int:nexus_id>/reverb/user/', views.get_reverb_user, name='get_reverb_user'),
path('ajax/nexus/<int:nexus_id>/comment/', views.nexus_comment, name='nexus_comment'),
]
| UTF-8 | Python | false | false | 2,543 | py | 240 | urls.py | 90 | 0.679512 | 0.679512 | 0 | 36 | 69.638889 | 105 |
lepy/phuzzy | 3,753,801,453,100 | b7c95f3f0a70a610b41a5f6991eb0d7c7db531d2 | 4e77443a5659825a53b94014462afc9fcb1b4dc9 | /tests/test_regression.py | fec222d581786ef447ab776887beaf2a691b6b1c | [
"MIT"
]
| permissive | https://github.com/lepy/phuzzy | f745c5619f9efca45c9f5f8340514e2117e65c78 | 22321dadc1d70b25d1213ddabcdbb99c40d15d6d | refs/heads/master | 2023-08-19T02:59:43.627881 | 2020-12-11T07:08:59 | 2020-12-11T07:08:59 | 95,642,408 | 2 | 3 | MIT | false | 2020-12-07T17:22:07 | 2017-06-28T07:38:13 | 2020-12-03T18:40:32 | 2020-12-07T17:22:05 | 6,714 | 2 | 2 | 3 | Jupyter Notebook | false | false | # -*- coding: utf-8 -*-
import numpy as np
import xgboost
from sklearn.model_selection import RandomizedSearchCV
from sklearn.metrics import make_scorer
from scipy.stats import spearmanr
def spearman_score(x, y):
return spearmanr(x, y)[0]
def test_CV2():
def func(X):
return ((X[:,0]+0.1)*(X[:,1]-2.2))**2
np.random.seed(101)
X_train = np.random.random((1000, 2))
y_train = func(X_train)
# print(y_train)
params = {'learning_rate':[0.5, 0.2, 0.1, 0.05, 0.02, 0.01],
'gamma':[0.1, 0.2, 0.5, 1, 2, 5],
'reg_alpha':10. * np.arange(-8, 2, .25),
'reg_lambda':10. * np.arange(-8, 2, .25),
'subsample': [0.1, 0.2, 0.5, 0.7, 0.9],
'max_depth': [1, 2, 3]
}
model = RandomizedSearchCV(xgboost.XGBRegressor(), param_distributions=params, n_iter=100,
scoring=make_scorer(spearman_score), cv=5, n_jobs=-1, verbose=1, random_state=1001)
model.fit(X_train, y_train)
def test_CV():
import numpy as np
from time import time
from scipy.stats import randint as sp_randint
from sklearn.model_selection import GridSearchCV
from sklearn.model_selection import RandomizedSearchCV
from sklearn.datasets import load_digits
from sklearn.ensemble import RandomForestClassifier
# get some data
digits = load_digits()
X, y = digits.data, digits.target
# build a classifier
clf = RandomForestClassifier(n_estimators=20)
# Utility function to report best scores
def report(results, n_top=3):
for i in range(1, n_top + 1):
candidates = np.flatnonzero(results['rank_test_score'] == i)
for candidate in candidates:
print("Model with rank: {0}".format(i))
print("Mean validation score: {0:.3f} (std: {1:.3f})".format(
results['mean_test_score'][candidate],
results['std_test_score'][candidate]))
print("Parameters: {0}".format(results['params'][candidate]))
print("")
# specify parameters and distributions to sample from
param_dist = {"max_depth": [3, None],
"max_features": sp_randint(1, 11),
"min_samples_split": sp_randint(2, 11),
"min_samples_leaf": sp_randint(1, 11),
"bootstrap": [True, False],
"criterion": ["gini", "entropy"]}
# run randomized search
n_iter_search = 20
random_search = RandomizedSearchCV(clf, param_distributions=param_dist,
n_iter=n_iter_search)
start = time()
random_search.fit(X, y)
print("RandomizedSearchCV took %.2f seconds for %d candidates"
" parameter settings." % ((time() - start), n_iter_search))
report(random_search.cv_results_)
# use a full grid over all parameters
param_grid = {"max_depth": [3, None],
"max_features": [1, 3, 10],
"min_samples_split": [2, 3, 10],
"min_samples_leaf": [1, 3, 10],
"bootstrap": [True, False],
"criterion": ["gini", "entropy"]}
# run grid search
grid_search = GridSearchCV(clf, param_grid=param_grid)
start = time()
grid_search.fit(X, y)
print("GridSearchCV took %.2f seconds for %d candidate parameter settings."
% (time() - start, len(grid_search.cv_results_['params'])))
report(grid_search.cv_results_)
| UTF-8 | Python | false | false | 3,526 | py | 91 | test_regression.py | 57 | 0.568633 | 0.536018 | 0 | 100 | 34.26 | 114 |
boringPpl/Crash-Course-on-Python | 9,569,187,164,388 | 430dfe6d1636c691e37695eb83fd33bb396ce0c4 | f7afcb4c1022b685364d7dfac01b07e6a5ced73f | /Exercises on IDE/2 Data types, Variables, Expressions/ex2_4_expression.py | ee0ccb6be0c96d53e6e34526361fc8fa161f8d9a | []
| no_license | https://github.com/boringPpl/Crash-Course-on-Python | 8d65c22f2a11483f21c136365903bdc8d6c81982 | d42c37fac9b34d3b87ff6527a7fb847b31d69586 | refs/heads/master | 2023-04-21T01:59:58.615826 | 2021-05-17T10:40:21 | 2021-05-17T10:40:21 | 281,635,893 | 0 | 1 | null | null | null | null | null | null | null | null | null | null | null | null | null | ''' Question 2.4:
Keeping in mind there are 86400 seconds per day,
write a program that calculates how many seconds there are in a year,
if a year is 365 days.Print the result on the screen.
Note: Your result should be in the format of just a number, not a sentence.
'''
| UTF-8 | Python | false | false | 277 | py | 40 | ex2_4_expression.py | 39 | 0.736462 | 0.700361 | 0 | 7 | 38.142857 | 75 |
0xchase/angr-ctf | 14,903,536,533,422 | 2f37553757a5cb9ad226bc7143d635677dcc28a9 | 9f17f11bf247a7751952ef624ab42b8d7b3d1f30 | /07_angr_symbolic_file/solve.py | 32050a9b4ae35b948175f8085cd68042e7dcfcbd | []
| no_license | https://github.com/0xchase/angr-ctf | 27deaf271a704b395eb710ff3ea878abe3ac74d2 | f080003bf99b13596357a8e0b25c6736c5687639 | refs/heads/master | 2022-03-30T01:16:40.227595 | 2020-02-04T13:55:41 | 2020-02-04T13:55:41 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | #!/usr/bin/python3
import angr
project = angr.Project("07_angr_symbolic_file")
state = project.factory.entry_state()
simgr = project.factory.simgr(state)
simgr.explore(find=0x80489b2, avoid=0x8048998)
if simgr.found:
print(simgr.found[0].posix.dumps(0).decode())
else:
print("No solution found")
| UTF-8 | Python | false | false | 308 | py | 11 | solve.py | 10 | 0.730519 | 0.665584 | 0 | 14 | 21 | 49 |
sunniee/OMGEmotionChallengeCode | 3,109,556,352,716 | 38d9dae169368862edaf4939d72bf8bbb2fb9721 | 05e805726cfdf7a40e2d49e4fcef4417b88e92b7 | /codes/CNN_model.py | cf8a07606c2304358311fede5ac0789d881ec39b | []
| no_license | https://github.com/sunniee/OMGEmotionChallengeCode | 0943aff3326e7bf30628e31d66487df19644bfa7 | 1f893b38afa7e160fb6ea3ec3a030ef5596b2765 | refs/heads/master | 2020-08-01T19:52:14.597775 | 2018-04-30T18:59:07 | 2018-04-30T18:59:07 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import tensorflow as tf
from keras.models import *
from keras.layers import *
from keras.optimizers import *
from keras import regularizers
def model(timesteps=64, dim=512, unit=256, filters=128, ac='sigmoid',mode='pred'):
inputs = Input((timesteps, dim))
x1 = Conv1D(filters, 5, strides=1, padding='valid', input_shape=(timesteps, dim),name='conv1')(inputs)
x1 = BatchNormalization(name='bn1')(x1)
x1 = Activation('relu')(x1)
x1 = GlobalMaxPooling1D()(x1)
x2 = Conv1D(filters, 4, strides=1, padding='valid', input_shape=(timesteps, dim),name='conv2')(inputs)
x2 = BatchNormalization(name='bn2')(x2)
x2 = Activation('relu')(x2)
x2 = GlobalMaxPooling1D()(x2)
x3 = Conv1D(filters, 3, strides=1, padding='valid', input_shape=(timesteps, dim),name='conv3')(inputs)
x3 = BatchNormalization(name='bn3')(x3)
x3 = Activation('relu')(x3)
x3 = GlobalMaxPooling1D()(x3)
x4 = Conv1D(filters, 2, strides=1, padding='valid', input_shape=(timesteps, dim),name='conv4')(inputs)
x4 = BatchNormalization(name='bn4')(x4)
x4 = Activation('relu')(x4)
x4 = GlobalMaxPooling1D()(x4)
x = Concatenate()([x1, x2, x3, x4])
x = Dense(256, activation='relu',name='dense1')(x)
if mode=='feat':
output=x
else:
x = Dropout(0.25)(x)
if ac == 'tanh':
output = Dense(1, activation='tanh',name='last_dense')(x)
elif ac == 'tanh+sigmoid' or ac == 'sigmoid+tanh':
x1 = Dense(1, activation='sigmoid',name='last_dense_1')(x)
x2 = Dense(1, activation='tanh',name='last_dense_2')(x)
output = [x1, x2]
else:
output = Dense(1, activation='sigmoid',name='last_dense')(x)
return Model(inputs=inputs, outputs=output) | UTF-8 | Python | false | false | 1,771 | py | 9 | CNN_model.py | 7 | 0.621683 | 0.574252 | 0 | 44 | 39.272727 | 106 |
KirillGordievich/mas_framework | 11,862,699,718,234 | 2dbb4d18b4e880b81a2b93216d16ad49b3436ac0 | 2dfa266ca8dd3bc17bf0cb0c6d292ecff5756649 | /src/spawn_turtle.py | 568879006be43f63d7debd5f96f0a002adc70a1f | []
| no_license | https://github.com/KirillGordievich/mas_framework | 66d944eca1f88a445ddc790f8ac6b34f0fca2f6e | 0d3cb556a504f46cef52165cd75a50d6dc8da979 | refs/heads/master | 2020-04-21T09:05:13.500200 | 2019-02-13T15:35:09 | 2019-02-13T15:35:09 | 169,438,024 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | #!/usr/bin/python
import rospy
import math
import random
import geometry_msgs.msg
from turtlesim.srv import Spawn
from mas_framework.msg import base
from mas_framework.msg import status
import turtlesim.msg as turtle
class Turtle:
def __init__(self, number):
self.number = number
self.name = 'turtle'+str(self.number)
self.status = "wait"
self.base_msg = base()
self.geometry_msg = geometry_msgs.msg.Twist()
self.subscriber_pose = rospy.Subscriber(str(
self.name)+'/pose', turtle.Pose, self.callback_pose, queue_size=1)
self.velocity_publisher = rospy.Publisher("/turtle"+str(
self.number)+"/cmd_vel", geometry_msgs.msg.Twist, queue_size=1)
self.coordinate_publisher = rospy.Publisher(
"/environment", base, queue_size=1)
self.action_publisher = rospy.Publisher("/turtle"+str(
self.number)+"/action", base, queue_size=1)
self.subscriber_coordinate = rospy.Subscriber(
"/environment", base, self.callback_coordinate, queue_size=10)
self.subscriber_status_msg = rospy.Subscriber(
"/status", status, self.callback_status, queue_size=1)
self.general_goal_name = "turtle1"
self.local_goal_name = None
self.x = 0
self.y = 0
self.phi = 0
self.linear_velocity = 1
self.angular_velocity = 1
self.turtles = {self.name: [self.x, self.y, self.phi]}
self.borders_points = {"first_point": [0, 10], "second_point": [10, 0]}
def start(self):
while self.general_goal_name not in self.turtles:
rospy.sleep(3)
if self.name != self.general_goal_name:
self.trade()
self.status = "move"
while not rospy.is_shutdown():
if self.name != self.general_goal_name:
if self.status == "move":
if self.detect_border():
self.border()
rospy.loginfo("border")
self.move()
def move(self):
x_goal = self.turtles[self.local_goal_name][0]
y_goal = self.turtles[self.local_goal_name][1]
if self.phi > math.pi:
self.phi = self.phi - 2*math.pi
if self.phi < -math.pi:
self.phi = self.phi + 2*math.pi
phi = self.phi
theta = self.get_angle(y_goal - self.y, x_goal - self.x)
distance = self.get_distance(x_goal, y_goal, self.x, self.y)
angular = self.angular_velocity
linear = self.linear_velocity
if distance > 1:
angular, linear = self.get_velocity(phi, theta)
self.geometry_msg.angular.z = angular
self.geometry_msg.linear.x = linear
else:
self.geometry_msg.angular.z = 0
self.geometry_msg.linear.x = 0
self.velocity_publisher.publish(self.geometry_msg)
def detect_border(self):
for point in self.borders_points:
if abs(self.x-self.borders_points[point][0]) < 1:
return True
for point in self.borders_points:
if abs(self.y - self.borders_points[point][1]) < 1:
return True
def border(self):
while self.detect_border():
if self.phi > math.pi:
self.phi = self.phi - 2*math.pi
if self.phi < -math.pi:
self.phi = self.phi + 2*math.pi
phi = self.phi
theta = self.get_angle(5 - self.y, 5 - self.x)
delta = phi - theta
angular, linear = self.get_velocity(phi, theta)
self.geometry_msg.angular.z = angular
self.geometry_msg.linear.x = linear
self.velocity_publisher.publish(self.geometry_msg)
def callback_pose(self, data):
self.x = data.x
self.y = data.y
self.phi = data.theta
self.base_msg.x = data.x
self.base_msg.y = data.y
self.base_msg.theta = data.theta
self.base_msg.load = self.name
self.coordinate_publisher.publish(self.base_msg)
def callback_coordinate(self, data):
self.turtles[data.load] = [data.x, data.y, data.theta]
def trade(self):
turtles = (sorted(self.turtles.items(), key=lambda item: (
item[1][0] - self.turtles[self.general_goal_name][0]) ** 2 + (
item[1][1] - self.turtles[self.general_goal_name][1]) ** 2))
turtles_order = dict(
[(turtles[i][0], i) for i in range(0, len(self.turtles))])
inv_turtles_order = {v: k for k, v in turtles_order.items()}
self.local_goal_name = inv_turtles_order[turtles_order[self.name]-1]
def callback_status(self, data):
if self.name != self.general_goal_name:
self.trade()
self.status = data.status
rospy.sleep(1)
def get_distance(self, x1, y1, x2, y2):
return math.sqrt((x1 - x2) ** 2 + (y1 - y2) ** 2)
def get_angle(self, y, x):
return math.atan2(y, x)
def get_velocity(self, phi, theta):
delta = phi - theta
linear = self.linear_velocity
angular = self.angular_velocity
if abs(delta) > 0.1:
if phi > 0:
if theta > 0:
if delta > 0:
return -angular, linear
else:
return angular, linear
else:
if delta > math.pi:
return angular, linear
else:
return -angular, linear
else:
if theta > 0:
if delta > -math.pi:
return angular, linear
else:
return -angular, linear
else:
if delta > 0:
return -angular, linear
else:
return angular, linear
else:
return 0, linear
if __name__ == "__main__":
rospy.init_node("~turtle", anonymous=True)
number = rospy.get_param("~number")
rospy.wait_for_service('spawn')
if number != 1:
x = rospy.get_param("~x_coordinate")
y = rospy.get_param("~y_coordinate")
theta = rospy.get_param("~theta_coordinate")
spawn_turtle_x = rospy.ServiceProxy('/spawn', Spawn)
spawn_turtle_x(x, y, theta, '')
x = Turtle(number)
x.start()
rospy.spin()
| UTF-8 | Python | false | false | 6,551 | py | 2 | spawn_turtle.py | 1 | 0.532743 | 0.522516 | 0 | 229 | 27.606987 | 79 |
medularis/medularis-django-utils | 7,146,825,614,877 | 47b92d89def489076ac9b6f410faa7fbf53f49f7 | eeee39dbf68c1863548de8240fd47dcc93c1f487 | /med_djutils/model_fields.py | 6ced563fe79e6e37b14626a7d34f50b1d2dbc3e5 | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
]
| permissive | https://github.com/medularis/medularis-django-utils | 7c3d819ee3d690d446e47e9dc33df7a4433b0581 | 7b8cde7bea1f45850f1e587eccfb5e6e3444ab58 | refs/heads/master | 2021-01-15T22:47:56.327687 | 2015-03-17T00:56:02 | 2015-03-17T00:56:02 | 32,344,730 | 0 | 1 | BSD-3-Clause | true | 2018-03-04T20:51:06 | 2015-03-16T18:28:06 | 2015-03-17T00:57:39 | 2015-03-26T14:55:00 | 171 | 0 | 1 | 1 | Python | false | null | # coding: utf-8
"""Some useful Django model fields.
Source: lookup_www.common.fields (but just a subset).
"""
from __future__ import absolute_import, print_function, unicode_literals
import django.db.models
import django.forms
import med_djutils.hex
class Hex32Field(django.db.models.CharField):
"""Hex digits string of length 32, very practical for hash keys.
Default value is calculated by :func:`med_djutils.hex.random_hex_32` (UUID version 4).
Although it's very unlikely that it returns a repeated value,
uniqueness is enforced at database level as precautionary measure.
"""
description = "32-hex-digits string"
def __init__(self, *args, **kwargs):
kwargs['blank'] = False
kwargs['default'] = med_djutils.hex.random_hex_32
kwargs['max_length'] = 32
kwargs['unique'] = True
kwargs.setdefault('editable', False)
super(Hex32Field, self).__init__(*args, **kwargs)
class Hex6Field(django.db.models.CharField):
"""Hex digits string of length 6.
Default value is calculated by :func:`med_djutils.hex.random_hex_6`
(substring of UUID version 4).
Uniqueness is enforced at database level as precautionary measure.
"""
description = "6-hex-digits string"
def __init__(self, *args, **kwargs):
kwargs['blank'] = False
kwargs['default'] = med_djutils.hex.random_hex_6
kwargs['max_length'] = 6
kwargs['unique'] = True
kwargs.setdefault('editable', False)
super(Hex6Field, self).__init__(*args, **kwargs)
# Tell South about the custom field. Since it's essentially an IntegerField (as
# South and DB are concerned), the definitions are as simple as they can be.
# Read:
# * http://south.readthedocs.org/en/latest/customfields.html#extending-introspection
# * http://south.readthedocs.org/en/latest/tutorial/part4.html#simple-inheritance
from south.modelsinspector import add_introspection_rules
add_introspection_rules([], ["^common\.fields\.Hex32Field"])
add_introspection_rules([], ["^common\.fields\.Hex6Field"])
| UTF-8 | Python | false | false | 2,079 | py | 24 | model_fields.py | 17 | 0.688312 | 0.674844 | 0 | 64 | 31.484375 | 90 |
ArijitBasu/streamlit | 4,458,176,101,304 | a388002f33e1ec124f7b5569b44f5f3493274b2d | 8ca47ca4f36d829d9045aa203a78eba1e9f5d5e3 | /apps/data.py | 5122a592bd83b61d26cc078207a5b741a4fe2594 | []
| no_license | https://github.com/ArijitBasu/streamlit | dc0e87b906b8393412e22a5c952b5e9b391c979d | 944d478c64f4e80934c6b89f4bfa6762650f0b9b | refs/heads/main | 2023-04-15T05:42:19.745065 | 2021-04-27T14:58:32 | 2021-04-27T14:58:32 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import streamlit as st
import pandas as pd
from PIL import Image
def app():
data = st.beta_container()
df = pd.read_csv('Books_universe.csv')
with data:
st.write("""In this project, we navigate through [GoodReads](https://www.goodreads.com/list/show/264.Books_That_Everyone_Should_Read_At_Least_Once)
to scrape data of the best books that everyone should read at least once in their life time. From the scraped data,
we got some interesting insights that you might be curious to know and stored the answers in a readable format for your convinience.""")
st.title('Data')
st.markdown("")
if st.checkbox('Reveal The Library'):
st.subheader('Books')
st.write(df) #.header(50) inside the the ()
| UTF-8 | Python | false | false | 948 | py | 8 | data.py | 6 | 0.675105 | 0.639241 | 0 | 21 | 42.904762 | 161 |
SergeyParamonov/sketching | 12,627,203,889,950 | 5f80306e264bcd28666cb3c22659f12e2cc1000d | ee0973b340e9e7eb4b3544105245bd39a6e989cf | /solver/asp_py_parsetab.py | 8b086d964531d1b6b1d8d5e4b278bb381ebe0ad5 | []
| no_license | https://github.com/SergeyParamonov/sketching | cd89fb604a584336e92b1510a1ee391a631d15f6 | 750bbf9f81741237b210ff72f4615f317f7b06f0 | refs/heads/master | 2021-06-02T01:45:41.579907 | 2020-04-13T18:28:00 | 2020-04-13T18:28:00 | 90,079,587 | 1 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null |
# asp_py_parsetab.py
# This file is automatically generated. Do not edit.
_tabversion = '3.2'
_lr_method = 'LALR'
_lr_signature = b'H<\t\xc8tV\xb4?\x0e/8*\xe5\xcc\x8a\x82'
_lr_action_items = {'STRING':([6,7,16,17,],[13,13,13,13,]),'SPACE':([1,2,3,15,18,],[5,-4,-6,-3,-5,]),'LP':([2,3,12,],[6,7,17,]),'NUM':([6,7,16,17,],[11,11,11,11,]),'IDENT':([0,5,6,7,16,17,],[2,2,12,12,12,12,]),'COMMA':([10,11,12,13,21,],[16,-12,-11,-10,-9,]),'MIDENT':([0,5,],[3,3,]),'RP':([9,10,11,12,13,14,19,20,21,],[15,-8,-12,-11,-10,18,-7,21,-9,]),'$end':([1,2,3,4,8,15,18,],[-2,-4,-6,0,-1,-3,-5,]),}
_lr_action = { }
for _k, _v in _lr_action_items.items():
for _x,_y in zip(_v[0],_v[1]):
if not _x in _lr_action: _lr_action[_x] = { }
_lr_action[_x][_k] = _y
del _lr_action_items
_lr_goto_items = {'atom':([0,5,],[1,1,]),'terms':([6,7,16,17,],[9,14,19,20,]),'term':([6,7,16,17,],[10,10,10,10,]),'answerset':([0,5,],[4,8,]),}
_lr_goto = { }
for _k, _v in _lr_goto_items.items():
for _x,_y in zip(_v[0],_v[1]):
if not _x in _lr_goto: _lr_goto[_x] = { }
_lr_goto[_x][_k] = _y
del _lr_goto_items
_lr_productions = [
("S' -> answerset","S'",1,None,None,None),
('answerset -> atom SPACE answerset','answerset',3,'p_answerset','/home/sergey/.local/lib/python3.4/site-packages/pyasp/asp.py',188),
('answerset -> atom','answerset',1,'p_answerset','/home/sergey/.local/lib/python3.4/site-packages/pyasp/asp.py',189),
('atom -> IDENT LP terms RP','atom',4,'p_atom','/home/sergey/.local/lib/python3.4/site-packages/pyasp/asp.py',194),
('atom -> IDENT','atom',1,'p_atom','/home/sergey/.local/lib/python3.4/site-packages/pyasp/asp.py',195),
('atom -> MIDENT LP terms RP','atom',4,'p_atom','/home/sergey/.local/lib/python3.4/site-packages/pyasp/asp.py',196),
('atom -> MIDENT','atom',1,'p_atom','/home/sergey/.local/lib/python3.4/site-packages/pyasp/asp.py',197),
('terms -> term COMMA terms','terms',3,'p_terms','/home/sergey/.local/lib/python3.4/site-packages/pyasp/asp.py',211),
('terms -> term','terms',1,'p_terms','/home/sergey/.local/lib/python3.4/site-packages/pyasp/asp.py',212),
('term -> IDENT LP terms RP','term',4,'p_term','/home/sergey/.local/lib/python3.4/site-packages/pyasp/asp.py',220),
('term -> STRING','term',1,'p_term','/home/sergey/.local/lib/python3.4/site-packages/pyasp/asp.py',221),
('term -> IDENT','term',1,'p_term','/home/sergey/.local/lib/python3.4/site-packages/pyasp/asp.py',222),
('term -> NUM','term',1,'p_term','/home/sergey/.local/lib/python3.4/site-packages/pyasp/asp.py',223),
]
| UTF-8 | Python | false | false | 2,549 | py | 67 | asp_py_parsetab.py | 29 | 0.596312 | 0.494704 | 0.002746 | 40 | 62.7 | 405 |
xingxu21/Yale_CPSC | 6,296,422,066,724 | 5d54f6906b99608ce9077e26a7a4792ae6f9a612 | f53a17c670cd73068169705ceb7b87d137c6d0ab | /CPSC_327/P4/board.py | 61743f30e0d4d3e7226893e8b4650fb657216326 | []
| no_license | https://github.com/xingxu21/Yale_CPSC | f75e15093270097d870b415cfb251a19278a6045 | 5fa80ebd65a5def21328ac22d0f6fcc56672496c | refs/heads/master | 2023-01-29T01:29:55.471333 | 2020-12-08T09:22:14 | 2020-12-08T09:22:14 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | #board
import piece_factory
from constants import *
import constants
class game_state:
#stack for keeping track of past states
orig_board = []
past_states = []
future_states = []
size = 0
all_pieces = None
def __init__(self, size, player = WHITE):
#generate board of specified size
self.player = player
self.board = []
first_row = [1*(-1)**i for i in range(size)]
self.board.append(first_row)
for i in range(1, size):
new_row = [i * -1 for i in self.board[-1]]
self.board.append(new_row)
for row in range(size):
for column in range(size):
if self.board[row][column] == 1:
self.board[row][column] = BLACK_SQUARE
else:
self.board[row][column] = WHITE_SQUARE
game_state.size = size
for row in self.board:
game_state.orig_board.append(row[:])
def print_board(self):
"shows the current board"
count = 1
alph = 'abcdefghijklmnopqrstuvwxyz'
for row in self.board:
print(count, end = " ")
for e in row:
print (e, end = " ")
count +=1
print("\n", end="")
print(" ", end = "")
for i in range(count-1):
print(alph[i], end = " ")
print("\n", end = "")
if self.player == WHITE:
color = "white"
else:
color = "black"
string = "Turn: %s, %s"%(constants.TURN, color)
print(string)
def undo_move(self):
"return the previous game state"
return game_state.past_states.pop()
def valid_position(self, position):
"returns truth value of whether a position is on the board"
row = position[0]
col = position[1]
row_truth = row >= 0 and row < game_state.size
col_truth = col >= 0 and col < game_state.size
return col_truth and row_truth
def set_up(self):
"sets up board and creates all_pieces object with all of the checker pieces. This is stored in game_state.all_pieces"
all_pieces = piece_factory.all_checker_pieces()
factory = piece_factory.checkers_factory()
for row in range(game_state.size):
for column in range(game_state.size):
factory.create_checkers(self.board, (row, column), all_pieces)
game_state.all_pieces = all_pieces
| UTF-8 | Python | false | false | 2,080 | py | 139 | board.py | 38 | 0.648077 | 0.641346 | 0 | 87 | 22.83908 | 119 |
priyankagandhi996/lawyer | 5,128,190,958,682 | 3c49f58012aac8d92250e2074bb288673906b2a4 | 81fe5b46549bb716f677e200847b6438918b9592 | /law/app/urls.py | 97d9e9bda1fb6e60f5557899508dcb6ed301d136 | []
| no_license | https://github.com/priyankagandhi996/lawyer | 59dbdf8692640a22ca86d4364c74d04a481ce449 | 6dab8e4886b577fd5e300d12bcecae7b5028abba | refs/heads/master | 2020-03-25T14:35:37.637502 | 2018-08-07T11:51:49 | 2018-08-07T11:51:49 | 143,862,519 | 1 | 1 | null | null | null | null | null | null | null | null | null | null | null | null | null |
from django.conf.urls import url
from . import views
urlpatterns = [
url(r'^$', views.home,name='home'),
url(r'/signup/admin/$', views.CreateAdmin,name='adminsignup'),
url(r'/signup/user/$', views.CreateCustomer,name='customer'),
]
| UTF-8 | Python | false | false | 246 | py | 6 | urls.py | 5 | 0.670732 | 0.670732 | 0 | 8 | 29.625 | 66 |
tarunrockr/python-pytest | 16,569,983,866,358 | 714f86fff20a70694c4edab8a5668c60444d3c69 | aad597c1b3cd4ba8b9af91d094dc6505a7c89db9 | /parameterized_test.py | 11540332723069b5b6dac4d896890618d2f2031d | []
| no_license | https://github.com/tarunrockr/python-pytest | ad93b329471ffa87afd3aa8ed4220299fe913a35 | ab477535665229bf436e8c31f6e19106b25ad54b | refs/heads/master | 2023-07-09T02:56:27.998290 | 2021-08-15T18:20:57 | 2021-08-15T18:20:57 | 396,436,867 | 1 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import pytest
# ------------------ Run Command for following function | pytest parameterized_test.py ----------------------
@pytest.mark.parametrize('x,y,z',[(10,20,200),(20,40,200)])
def test_function(x,y,z):
assert x*y == z | UTF-8 | Python | false | false | 232 | py | 6 | parameterized_test.py | 6 | 0.568966 | 0.508621 | 0 | 5 | 45.6 | 112 |
eDeliveryApp/edelivery-api | 2,851,858,290,915 | 73f4cbb6ef71bf888c6467e17373fc32b0337ac3 | 557cae0c1aca5ca775ea3fc38438e1d981e44f80 | /manage.py | 34d4d9b6790339ff8ca568fe2420224a8c6d7bc7 | []
| no_license | https://github.com/eDeliveryApp/edelivery-api | 8ed1c1a27f048bb393aabee77ab361e532a56c10 | a96a0b8d048a22260f812383962c979b7c78fb6d | refs/heads/master | 2021-01-02T06:31:35.119810 | 2015-07-05T03:36:49 | 2015-07-05T03:36:49 | 38,555,588 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | #!/usr/bin/env python
from flask.ext.script import Manager
from api.app import create_app
from api.models import db
manager = Manager(create_app)
@manager.command
def createdb():
app = create_app()
with app.app_context():
db.drop_all()
db.create_all()
@manager.command
def test():
from subprocess import call
call(['nosetests', '-v',
'--with-coverage', '--cover-package=api', '--cover-branches',
'--cover-erase', '--cover-html', '--cover-html-dir=cover'])
if __name__ == '__main__':
manager.run()
| UTF-8 | Python | false | false | 561 | py | 7 | manage.py | 7 | 0.613191 | 0.613191 | 0 | 26 | 20.538462 | 71 |
alejocano22/TETbigdata | 5,909,875,023,843 | b9bf9a3135fc8f7306aff27e407e730383693e8b | 4f122900ac54def923b25767e8e729d1714ebd1a | /Programas/Stocks/stocks-risenstable-mr.py | 7669bd22de4e0f3bbe6818668a6b843ff1b41e2d | []
| no_license | https://github.com/alejocano22/TETbigdata | c585bf599b8242b382e464f0fe0402bbd3966fd4 | c7d58ca5e91ec037ab6c86a61250e7fa25a1bd23 | refs/heads/master | 2021-06-13T15:58:49.583685 | 2020-05-04T02:06:33 | 2020-05-04T02:06:33 | 254,438,158 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from mrjob.job import MRJob
from operator import itemgetter
class RisenStable(MRJob):
def mapper(self, _, line):
company, price, date = line.split(',')
data = [price, date]
yield company, data
def reducer(self, company, values):
data = list(values)
data = sorted(data, key=itemgetter(1))
for i in range(len(data)-1):
if float(data[i+1][0]) < float(data[i][0]):
return
yield company, "Raise or stable all time."
if __name__ == '__main__':
RisenStable.run()
| UTF-8 | Python | false | false | 558 | py | 12 | stocks-risenstable-mr.py | 3 | 0.569892 | 0.560932 | 0 | 22 | 24.363636 | 55 |
kayjayk/Algorithms_py | 4,715,874,127,582 | ab8115257b076fa9477dad9b61f4468338a29fc4 | 16147cb4f47d8a4fadaa8c9b5778f6581ff1871f | /Exam10989.py | a22e7bbf4cc419111bf32a74d1dec92349e4506f | []
| no_license | https://github.com/kayjayk/Algorithms_py | 45acaf189ac9f0ed7e3ae4829d15c5b059edea1a | d1189937c59deb3eeed8e1d0ad0efe56ea7ac160 | refs/heads/master | 2023-03-17T22:19:44.378677 | 2021-03-19T09:44:10 | 2021-03-19T09:44:10 | 204,250,000 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import sys
from collections import defaultdict
N = int(sys.stdin.readline())
num_dict = defaultdict(int)
for i in range(N):
num_dict[int(sys.stdin.readline())] += 1
num_keys = []
for key in num_dict.keys():
num_keys.append(key)
sorted_keys = sorted(num_keys)
for i in range(len(sorted_keys)):
key = sorted_keys[i]
for j in range(num_dict[key]):
print(key) | UTF-8 | Python | false | false | 384 | py | 53 | Exam10989.py | 52 | 0.658854 | 0.65625 | 0 | 19 | 19.263158 | 44 |
epigen-UCSD/MERlin | 18,683,107,771,026 | 722e1c6a68b37664567f507afcec6f8d907defa0 | 942aea94961e56340c526c46eecf236f3fcbb368 | /merlin/plots/__init__.py | 0f3a244f2a2ee5ab3ebfda771c986b00cf4a676b | [
"MIT"
]
| permissive | https://github.com/epigen-UCSD/MERlin | 562a1eb9f31a90a5979063a2a13375b78281b1c8 | 1479c9605c6e4ede9c15eb9f11d8d70fc691bf7d | refs/heads/master | 2023-08-08T20:52:29.979999 | 2023-08-07T22:44:03 | 2023-08-07T22:44:03 | 254,443,213 | 1 | 2 | NOASSERTION | true | 2021-04-06T22:27:59 | 2020-04-09T18:00:59 | 2020-04-24T19:58:31 | 2021-04-06T22:27:58 | 16,810 | 0 | 0 | 1 | null | false | false | import importlib
import inspect
import pkgutil
from typing import List, Set
import merlin
from merlin.plots._base import AbstractPlot
def get_available_plots() -> Set:
"""Get all plots defined within any submodule of merlin.plots.
Returns: a set of references to the plots
"""
plots = set()
for _, modname, _ in pkgutil.iter_modules(merlin.plots.__path__):
module = importlib.import_module(merlin.plots.__name__ + "." + modname)
for _, obj in inspect.getmembers(module):
if inspect.isclass(obj) and issubclass(obj, AbstractPlot) and obj != AbstractPlot:
plots.add(obj)
return plots
class PlotEngine:
def __init__(self, plot_task, tasks):
"""Create a new plot engine.
Args:
plot_task: the analysis task to save the plots and plot
metadata into
tasks: a dictionary containing references to the analysis
tasks to use for plotting results.
"""
self.tasks = tasks
available_plots = [x(plot_task) for x in get_available_plots()]
self.plots = [x for x in available_plots if x.is_relevant(tasks)]
required_metadata = {m for p in self.plots for m in p.required_metadata if m}
self.metadata = {x.metadata_name(): x(plot_task, tasks) for x in required_metadata}
for metadata in self.metadata.values():
metadata.load_state()
def get_plots(self) -> List[AbstractPlot]:
"""Get a list of the plots that this plot engine will generate.
Returns: A list of the plot objects that will be generated by this
plot engine.
"""
return self.plots
def take_step(self) -> bool:
"""Generate metadata and plots from newly available analysis results.
Returns: True if all plots have been generated and otherwise false.
"""
incomplete_plots = [p for p in self.plots if not p.is_complete()]
if len(incomplete_plots) == 0:
return True
for m in self.metadata.values():
m.update()
complete_tasks = [k for k, v in self.tasks.items() if v.is_complete()]
complete_metadata = [k for k, v in self.metadata.items() if v.is_complete()]
ready_plots = [p for p in incomplete_plots if p.is_ready(complete_tasks, complete_metadata)]
for p in ready_plots:
p.plot(self.tasks, self.metadata)
return len([p for p in self.plots if not p.is_complete()]) == 0
| UTF-8 | Python | false | false | 2,510 | py | 93 | __init__.py | 65 | 0.622709 | 0.621912 | 0 | 69 | 35.376812 | 100 |
NCiobo/iem | 8,203,387,556,550 | 654926add63d15bac2ee5a9f45873efad374d0f7 | fd877cb919622d6a4efa305fb9eaec8a31e8dd37 | /scripts/outgoing/kcci/wxc_top5gusts.py | 5aead76f3c803b963e02d1ededb5da2414b98528 | [
"MIT"
]
| permissive | https://github.com/NCiobo/iem | 37df9bc466ffcbe4f6b1f9c29c6b5266559f200c | 75da5e681b073c6047f5a2fb76721eaa0964c2ed | refs/heads/master | 2021-01-23T09:39:33.090955 | 2017-09-05T16:34:12 | 2017-09-05T16:34:12 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import os
import subprocess
import datetime
import sys
import tempfile
import pyiem.tracker as tracker
qc = tracker.loadqc()
import psycopg2
IEM = psycopg2.connect(database="iem", host='iemdb', user='nobody')
icursor = IEM.cursor()
icursor.execute("""SELECT t.id as station from current c, stations t
WHERE t.network = 'KCCI' and
valid > 'TODAY' and t.iemid = c.iemid ORDER by gust DESC""")
data = {}
data['timestamp'] = datetime.datetime.now()
i = 1
for row in icursor:
if i == 6:
break
if qc.get(row[0], {}).get('wind', False):
continue
data['sid%s' % (i,)] = row[0]
i += 1
if 'sid5' not in data:
sys.exit()
fd, path = tempfile.mkstemp()
os.write(fd, open('top5gusts.tpl', 'r').read() % data)
os.close(fd)
subprocess.call("/home/ldm/bin/pqinsert -p 'auto_top5gusts.scn' %s" % (path,),
shell=True)
os.remove(path)
fd, path = tempfile.mkstemp()
os.write(fd, open('top5gusts_time.tpl', 'r').read() % data)
os.close(fd)
subprocess.call(("/home/ldm/bin/pqinsert -p 'auto_top5gusts_time.scn' %s"
"") % (path, ), shell=True)
os.remove(path)
| UTF-8 | Python | false | false | 1,120 | py | 144 | wxc_top5gusts.py | 134 | 0.633929 | 0.623214 | 0 | 44 | 24.454545 | 78 |
expert360/consumerism | 14,319,420,975,885 | 7cae467dfec42baf838417f831afa4a082c5be91 | ef877a0ebf805bf38b5bf15254f3034e3d3d4d5e | /setup.py | 6858d03c5911d16e7d5ff75b181a6c1e871ce496 | [
"MIT"
]
| permissive | https://github.com/expert360/consumerism | 51045a642d80da79453f42b8cce894ddcee130c0 | 412847e6ff6f3087decf4212b32842ec017cc344 | refs/heads/master | 2016-09-06T01:42:23.960512 | 2016-01-11T05:53:00 | 2016-01-11T05:53:00 | 31,235,106 | 4 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from setuptools import setup, find_packages
setup(
name='consumerism',
version='0.3.11',
description='Expert360 Python SQS consumer library',
author='Expert360',
author_email='info@expert360.com',
license='MIT',
classifiers=[
'Development Status :: 5 - Production/Stable',
'Intended Audience :: Developers',
'License :: OSI Approved :: MIT License',
'Programming Language :: Python :: 2.7',
],
keywords='boto sqs consumer',
url='https://github.com/expert360/consumerism',
packages=find_packages(exclude=['tests']),
install_requires=[
'boto>=2.34.0',
],
)
| UTF-8 | Python | false | false | 649 | py | 20 | setup.py | 18 | 0.624037 | 0.588598 | 0 | 23 | 27.217391 | 56 |
RevansChen/online-judge | 10,746,008,206,908 | 48394dd68432ba18150e70a7c98a9ec8f5b0944e | abad82a1f487c5ff2fb6a84059a665aa178275cb | /Codewars/8kyu/crash-override/Python/solution1.py | 052b13e1287ea3ea75a577a1280bb1ffc2657c8c | [
"MIT"
]
| permissive | https://github.com/RevansChen/online-judge | 8ae55f136739a54f9c9640a967ec931425379507 | ad1b07fee7bd3c49418becccda904e17505f3018 | refs/heads/master | 2021-01-19T23:02:58.273081 | 2019-07-05T09:42:40 | 2019-07-05T09:42:40 | 88,911,035 | 9 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | # Python - 3.6.0
def alias_gen(f_name, l_name):
f = f_name[0].upper()
l = l_name[0].upper()
if (f in FIRST_NAME) and (l in SURNAME):
return f'{FIRST_NAME[f]} {SURNAME[l]}'
return 'Your name must start with a letter from A - Z.'
| UTF-8 | Python | false | false | 254 | py | 2,569 | solution1.py | 1,607 | 0.574803 | 0.555118 | 0 | 9 | 27.222222 | 59 |
amar-jain/fluence | 4,715,874,135,532 | 4c45e5b6ed6ed54002e06af81440cab7718dc0b5 | 1090105e9be55a2806b4586b4c17e525c188ee55 | /deploy/docker.py | f53bbde3472ab94ad9402a3f38b18ce7b64bbb43 | [
"Apache-2.0"
]
| permissive | https://github.com/amar-jain/fluence | 0b1c181ebad17d6ba67dc148b868d7eb4a1633b4 | ee2b2aad5290247a2c7e679020abb2337ab1b399 | refs/heads/master | 2023-04-12T00:27:28.634027 | 2021-05-17T11:08:10 | 2021-05-17T11:08:10 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | # Copyright 2020 Fluence Labs Limited
#
# 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 __future__ import with_statement
from fabric.api import *
from utils import *
from docker import *
import json
@task
@runs_once
def install_docker():
load_config()
execute(do_install_docker)
@task
@parallel
def do_install_docker():
puts("TODO: WRITE LOGGING DRIVER SETUP TO daemon.json https://docs.docker.com/config/containers/logging/json-file/")
with hide('running'):
sudo("apt-get remove --yes docker docker-engine docker.io containerd runc || true")
sudo("apt-get update")
puts("preparing to install docker")
sudo("apt-get install --yes haveged apt-transport-https ca-certificates curl gnupg-agent software-properties-common")
sudo("curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -")
sudo("apt-key fingerprint 0EBFCD88")
sudo("""add-apt-repository -y "deb [arch=amd64] https://download.docker.com/linux/ubuntu focal stable" """)
sudo("apt-get update")
puts("installing docker")
sudo("apt-get install --yes docker-ce docker-ce-cli containerd.io")
puts("installing docker-compose")
sudo("""curl -L "https://github.com/docker/compose/releases/download/1.26.0/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose """)
sudo("chmod +x /usr/local/bin/docker-compose")
@task
@runs_once
def deploy_watchdog():
load_config()
execute(do_deploy_watchdog)
@task
@parallel
def do_deploy_watchdog():
# 'running', 'output'
with hide('running', 'output'):
run("docker rm -f docker_watchdog || true")
run(
"docker run --name docker_watchdog --detach --restart=unless-stopped " +
"-e HOST={} ".format(env.host_string) +
"-e SLACK_CHANNEL='#endurance' " +
"-e SLACK_URL=SECRET " +
"-v /var/run/docker.sock:/var/run/docker.sock " +
"leonardofalk/docker-watchdog"
)
@task
@parallel
def deploy_caddy():
load_config()
for node in env.config['caddy']['nodes']:
env.hosts = [node['addr']]
puts("node: {}".format(node))
execute(do_deploy_caddy, node['ports'], node['host'])
@task
def do_deploy_caddy(ports, host):
ip = env.host_string
fname = 'Caddyfile'
prefix = '1'
container = 'caddy'
run('rm {} || true'.format(fname))
def append(line):
run('echo "{}" >> {}'.format(line, fname))
# Generated config will be as follows:
#
# {
# email alexey@fluence.one
# }
#
# host:prefixport { # add 'prefix', e.g.: 9001 => 19001
# log {
# format console
# }
# reverse_proxy ip:port
# }
append('''
{
email alexey@fluence.one
}
''')
for port in ports:
append('''
wss://{}:{}{} {{
log {{
format console
}}
reverse_proxy wss://{}:{}
}}'''.format(host, prefix, port, ip, port))
# -p prefixport:prefixport
open_ports = " ".join("-p {}{}:{}{}".format(prefix, p, prefix, p) for p in ports)
run('docker rm -f {} || true'.format(container))
run('docker pull caddy:latest')
run('docker run --name {} -d -p 80:80 {} -v $PWD/Caddyfile:/etc/caddy/Caddyfile -v caddy_data:/data caddy:latest'.format(container, open_ports))
| UTF-8 | Python | false | false | 3,881 | py | 47 | docker.py | 27 | 0.620201 | 0.612213 | 0 | 121 | 31.07438 | 161 |
linbarbell/ProjectEuler | 4,002,909,569,670 | a63cd8a01b38ba2e378c52428ac3923a129d0a62 | e9f142b9839732f1a4cdda69d6fd8382b4457356 | /Code/39.py | d91880d42624d8464b9c8ca1a99a28783fa2ce20 | []
| no_license | https://github.com/linbarbell/ProjectEuler | 89561d3c85b92944af14fa478ff8a9890787cdf2 | b54e01d18ca8517b11b7595bfecd7930528f282a | refs/heads/master | 2021-09-28T20:09:01.066898 | 2018-11-20T01:57:14 | 2018-11-20T01:57:14 | 29,401,770 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | pmax = 0
solmax = 0
for i in range(12, 1001):
currmax = 0
c_min = i//3 + 1 if i % 3 == 0 else i//3
c_max = i//2 + 1 if i % 2 == 0 else i//2
for c in range(c_min, c_max+1):
a_max = (i-c)//2
for a in range(1, a_max+1):
b = i-c-a
if a*a + b*b == c*c:
currmax += 1
if currmax > solmax:
solmax = currmax
pmax = i
print(pmax) | UTF-8 | Python | false | false | 343 | py | 69 | 39.py | 65 | 0.521866 | 0.451895 | 0 | 17 | 19.235294 | 41 |
BazBazz/elih | 5,935,644,807,873 | c7ab7a110e69bf596aeefddbf9c89804ebfef576 | ccdaa8577dc6b9e49d16420ea9c929dabf1db45b | /elih/__init__.py | 530f84a511bc79d575e40d276be9c9a60a3ca029 | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
]
| permissive | https://github.com/BazBazz/elih | e470e2a74e8d3a166551c78e00ca457a5c535d5f | 99d7066091b7709c77b515b96f0643700582d78f | refs/heads/master | 2021-01-19T17:10:39.904582 | 2017-08-13T21:14:36 | 2017-08-13T21:14:36 | 101,055,825 | 0 | 0 | null | true | 2017-08-22T11:31:16 | 2017-08-22T11:31:16 | 2017-05-16T17:04:14 | 2017-08-13T21:14:42 | 565 | 0 | 0 | 0 | null | null | null | # -*- encoding: utf-8 -*-
from __future__ import absolute_import
__version__ = '0.1'
from .explanation import HumanExplanation
from .features import apply_rules_layer
from .features import FeatureWeightGroup
from .scoring import score
from .formatters import (
percent,
delta_percent,
value,
text,
integer,
value_simplified
)
| UTF-8 | Python | false | false | 337 | py | 2 | __init__.py | 2 | 0.738872 | 0.72997 | 0 | 20 | 15.85 | 41 |
poojas1992/Classification-Algorithm | 85,899,345,999 | 0b13048e86805a66edca8dfbbb4ee629f408c254 | dc1e1321e5d3439fe90c496cc8b5c81e8e32d2b2 | /KNN_Digital_Sky.py | 83687e7a80af2d27ba0008a9b07bf1b1bf9e2166 | []
| no_license | https://github.com/poojas1992/Classification-Algorithm | 4a4e0a8841afc2dbf9d934ea65b81a0ea0645dab | 1f724390507f0d8b6908de66bd76321792431f6b | refs/heads/master | 2020-05-16T09:45:07.953499 | 2019-04-23T08:06:19 | 2019-04-23T08:06:19 | 182,960,107 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | #!/usr/bin/env python
# coding: utf-8
# In[2]:
import pandas as pd
import numpy as np
# In[3]:
#Step 1
#import dataset using pandas
sky_data = pd.read_csv()
sky_data.head()
# In[4]:
#Step 2
#Dropping the id feature
sky_data.drop(columns = ['objid'], inplace = True)
sky_data.head()
#Converting non-numeric data to numeric dataset
diag_map = {'STAR':1, 'GALAXY':2, 'QSO':3}
sky_data['class'] = sky_data['class'].map(diag_map)
#Preparing the data set
class_all = list(sky_data.shape)[0]
class_categories = list(sky_data['class'].value_counts())
print("The dataset has {} classes, {} stars, {} galaxies and {} quasars.".format(class_all,
class_categories[0],
class_categories[1],
class_categories[2]))
sky_data.describe()
# In[5]:
#Creating training and test datasets
from sklearn.model_selection import train_test_split, cross_val_score
from sklearn.metrics import accuracy_score
y = sky_data["class"].values
X = sky_data.drop(["class"], axis = 1)
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state = 41)
# In[6]:
#Step 3
#Training Model
from sklearn.neighbors import KNeighborsClassifier
classifier = KNeighborsClassifier(n_neighbors=4)
classifier.fit(X_train, y_train)
# In[7]:
#Step 4
#Testing the model
from sklearn.metrics import classification_report, confusion_matrix
y_pred = classifier.predict(X_test)
print(np.mean(y_pred != y_test))
print(confusion_matrix(y_test, y_pred))
print(classification_report(y_test, y_pred))
# In[8]:
#Step 5
#Improve Model Performance
#z-score transformed
from sklearn.preprocessing import StandardScaler
scaler = StandardScaler()
scaler.fit(X_train)
#Training the model
X_train = scaler.transform(X_train)
X_test = scaler.transform(X_test)
classifier = KNeighborsClassifier(n_neighbors=4)
classifier.fit(X_train, y_train)
#Testing the model
y_pred = classifier.predict(X_test)
print(np.mean(y_pred != y_test))
print(confusion_matrix(y_test, y_pred))
print(classification_report(y_test, y_pred))
# In[21]:
import matplotlib.pyplot as plt
error = []
# Calculating error for K values between 1 and 300
for i in range(1, 300):
knn = KNeighborsClassifier(n_neighbors=i)
knn.fit(X_train, y_train)
pred_i = knn.predict(X_test)
error.append(np.mean(pred_i != y_test))
plt.figure(figsize=(12, 6))
plt.plot(range(1, 300), error, color='red', linestyle='dashed', marker='o',
markerfacecolor='blue', markersize=10)
plt.title('Error Rate K Value')
plt.xlabel('K Value')
plt.ylabel('Mean Error')
plt.show()
# In[22]:
#Training Model
from sklearn.neighbors import KNeighborsClassifier
classifier = KNeighborsClassifier(n_neighbors=11)
classifier.fit(X_train, y_train)
#Testing the model
from sklearn.metrics import classification_report, confusion_matrix
y_pred = classifier.predict(X_test)
print(np.mean(y_pred != y_test))
print(confusion_matrix(y_test, y_pred))
print(classification_report(y_test, y_pred))
# In[13]:
#Training Model
from sklearn.neighbors import KNeighborsClassifier
classifier = KNeighborsClassifier(n_neighbors=50)
classifier.fit(X_train, y_train)
#Testing the model
from sklearn.metrics import classification_report, confusion_matrix
y_pred = classifier.predict(X_test)
print(np.mean(y_pred != y_test))
print(confusion_matrix(y_test, y_pred))
print(classification_report(y_test, y_pred))
# In[14]:
#Training Model
from sklearn.neighbors import KNeighborsClassifier
classifier = KNeighborsClassifier(n_neighbors=100)
classifier.fit(X_train, y_train)
#Testing the model
from sklearn.metrics import classification_report, confusion_matrix
y_pred = classifier.predict(X_test)
print(np.mean(y_pred != y_test))
print(confusion_matrix(y_test, y_pred))
print(classification_report(y_test, y_pred))
# In[ ]:
| UTF-8 | Python | false | false | 4,102 | py | 8 | KNN_Digital_Sky.py | 8 | 0.671624 | 0.65724 | 0 | 179 | 21.893855 | 102 |
avinashjsap/GFG | 4,157,528,372,425 | bbf38c8f55e47d85b51793a8a29aa1a2db8326c3 | b1c91f772b3d6310190133ebf866ae4ec55386a2 | /GFG/DataStructures/LinkedList/Make_middle_node_head_in_a_linked_list.py | 6320eb5eaefe72d016bd817804e43f193ac75602 | []
| no_license | https://github.com/avinashjsap/GFG | 43dbc1dc7c5d03ef77f747759803d821a224398b | da327238a0dad6bf550bdccdce17009531d3435c | refs/heads/master | 2020-04-24T18:37:51.223670 | 2019-02-23T07:38:26 | 2019-02-23T07:38:26 | 172,185,890 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | """ Python Script to make middle node
as head of Linked list """
class Node:
"""Class representing a Node"""
def __init__(self, data):
self.data = data
self.next = None
def link_node(self, node):
"""Links the next node with the current node
Args:
node (Node): Node which is to be linked
"""
self.next = node
def create_nodes(number):
"""Creates a linked list with the given number
Args:
number (int): Number of nodes to be created and chained
Returns:
Node : First and foremost Node
"""
head = None
while number:
new_node = Node(number)
new_node.link_node(head)
head = new_node
number -= 1
return head
def print_nodes(head):
"""Prints the linked list
Args:
head (Node): Node from which the list is to be printed
"""
while head:
print(head.data, end=" ")
head = head.next
print()
def set_middle_as_head(head):
"""Exchanges the middle node value with the head node
Args:
head (Node) : Node where the linked list begins
Returns:
Node : Head node after exchange of value with the middle
"""
if head is None: # Return if head is None
return None
node_1 = node_2 = head # assigns the reference of head to node_1 and node_2
while node_2 and node_2.next: # Stop when "node_2 is None" or "node_2 is valid but node_2.next is None"
node_1 = node_1.next # Traverse one node each iteration
node_2 = node_2.next.next # Traverse two node each iteration
head.data, node_1.data = node_1.data, head.data # Swap Data
return head
# Main Boiler plate where execution begins
if __name__ == "__main__":
NUMBER_OF_NODES = 6
head_node = create_nodes(NUMBER_OF_NODES)
print_nodes(head_node)
head_node = set_middle_as_head(head_node)
print_nodes(head_node)
| UTF-8 | Python | false | false | 2,070 | py | 3 | Make_middle_node_head_in_a_linked_list.py | 3 | 0.567633 | 0.55942 | 0 | 83 | 22.939759 | 109 |
Elbagoury/eyefashion | 377,957,157,154 | ca2f771a33ac29a53e67e42e92701c3754876367 | d207c1fe9bb534419ae16d5d1cbc650597a092fd | /pos_parent_discount/models/__init__.py | a66e62ba0e08b1628ad934b468698568d84670ee | []
| no_license | https://github.com/Elbagoury/eyefashion | 6bad9d27a0337e7eae688f66ae8b6322bfcfa80c | e5796f80c2c5854cda5bcbb879c586254c9378c6 | refs/heads/master | 2020-04-19T17:55:26.547757 | 2018-10-06T15:12:04 | 2018-10-06T15:12:04 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | # -*- coding: utf-8 -*-
from . import res_partner
from . import account_journal
from . import pos_order
from . import pos_session
| UTF-8 | Python | false | false | 132 | py | 150 | __init__.py | 88 | 0.69697 | 0.689394 | 0 | 6 | 20.833333 | 29 |
lowlandresearch/larcutils | 12,068,858,124,509 | 578801543d91d51cada1d4b003eb7e8da7a7d8db | 9cb4e52d1df02347791a66155fd0ac18da375105 | /larcutils/logging.py | 483ad172ace4297b182bebedd2321919141f60fb | [
"MIT"
]
| permissive | https://github.com/lowlandresearch/larcutils | 21a5eea762cb1147fbde1c0b887a3b3d1dd071c3 | 66e68ce566f47b7c2f806ae3008a3e9d66c937ea | refs/heads/master | 2020-04-17T18:48:54.167898 | 2019-10-21T03:47:24 | 2019-10-21T03:47:24 | 166,842,583 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import logging
import coloredlogs
def setup_logging(loglevel: str):
level = logging.getLevelName(loglevel.upper())
fmt = (
'{asctime} {levelname: <8} [{name}]:{lineno: >4}: {message}'
)
datefmt = '%Y-%m-%d %H:%M:%S'
coloredlogs.install(level=level)
logging.basicConfig(level=level, datefmt=datefmt, format=fmt, style='{')
| UTF-8 | Python | false | false | 356 | py | 10 | logging.py | 8 | 0.640449 | 0.634831 | 0 | 11 | 31.272727 | 76 |
OhadRubin/Awesome-System-Design | 16,320,875,747,386 | 569980416707bbc47ec7fc3d094de0cec64602a6 | 4c0330fab17c6babb4f1fcc84afb073e30a9c8db | /asd/parsers/__init__.py | 7889ca184ec542a7881844a1ce96a62d7057d852 | []
| no_license | https://github.com/OhadRubin/Awesome-System-Design | 1912685b2efe23d929b8b87873ad2661a51f2b7f | 9696320e4516cba2ea97743a36bc023df8108d7f | refs/heads/master | 2022-12-09T13:52:55.014245 | 2020-06-06T20:18:17 | 2020-06-06T20:18:17 | 227,002,991 | 0 | 2 | null | false | 2022-12-08T07:28:48 | 2019-12-10T01:33:03 | 2020-06-06T20:18:44 | 2022-12-08T07:28:47 | 82,954 | 0 | 1 | 20 | Jupyter Notebook | false | false | import types
import pathlib
from os.path import dirname, isfile, join
import asd.utils.asd_pb2 as asd_pb2
import os
from asd.utils import mq
import glob
import json
modules = {}
modules_list = glob.glob(join(dirname(__file__), "*.py"))
for path in modules_list:
if isfile(path) and not path.endswith('__init__.py') and not path.endswith('__main__.py'):
mod_name = pathlib.Path(path).name[:-3]
module = types.ModuleType(mod_name)
with open(path) as f:
module_str = f.read()
exec(module_str, module.__dict__)
modules[mod_name] = module
parser_list = {}
snapshot_fields = set()
for module_name, module in modules.items():
for el in dir(module):
if el.endswith("Parser"):
obj = module.__dict__[el]()
parser_list[module_name] = obj.parse
snapshot_fields.add(obj.field)
if el.startswith("parse"):
parser_list[module_name] = module.__dict__[el]
snapshot_fields.add(module.__dict__[el].field)
snapshot_fields = list(snapshot_fields)
class Context:
def __init__(self, user_id, timestamp):
self.user_id = user_id
self.timestamp = timestamp
def path(self, filename):
# print(self.timestamp)
os.makedirs(f"data/{self.user_id}/{self.timestamp}", exist_ok=True)
return f"data/{self.user_id}/{self.timestamp}/{filename}"
def save(self, filename, data):
filename = self.path(filename)
os.makedirs(os.path.dirname(filename), exist_ok=True)
with open(filename, "w") as f:
f.write(data)
def run_parser(parser_name, packet):
parse_method = parser_list[parser_name]
packet = asd_pb2.Packet.FromString(packet)
context = Context(user_id=packet.user.user_id, timestamp=packet.snapshot.datetime)
res = parse_method(context=context, snapshot=packet.snapshot)
user = dict(username=packet.user.username, user_id=packet.user.user_id,
gender=packet.user.gender, birthday=packet.user.birthday)
return json.dumps({"parser_name": parser_name, "data": {"user": user,
"timestamp": packet.snapshot.datetime,
"result": res}})
def parse(parser_name, path):
assert isinstance(path, str) and path.endswith(".raw")
with open(path, "rb") as x:
return run_parser(parser_name, packet=x.read())
| UTF-8 | Python | false | false | 2,465 | py | 35 | __init__.py | 23 | 0.609331 | 0.607708 | 0 | 71 | 33.704225 | 98 |
muraleo/django-practice | 16,801,912,077,542 | 6b28b45273c372621da750f417fd95c05a48abbe | 0743fa60ed316325c89c65a127ca5b365a1fcb0b | /first_app/views.py | 5db9a91f8e11cc9fc1724b80a40e660c00b8e8f3 | []
| no_license | https://github.com/muraleo/django-practice | a93c7202ae4edb04a52b7c465926d703bdd30379 | 05e4f6a89c08de955b19fb1b2fa140b585566886 | refs/heads/master | 2020-04-05T02:45:51.635556 | 2018-11-08T02:13:09 | 2018-11-08T02:13:09 | 156,489,350 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from django.shortcuts import render
from django.http import HttpResponse
from first_app.models import Topic, Webpage, AccessRecord
# Create your views here.
def index(req):
webpages_list = Webpage.objects.order_by('name')
# my_dict = {'insert_me': "Hello I am from the views.py"}
date_dict = {'access_record':webpages_list}
return render(req, 'first_app/index.html', context = date_dict) | UTF-8 | Python | false | false | 404 | py | 1 | views.py | 1 | 0.725248 | 0.725248 | 0 | 10 | 39.5 | 67 |
nathanmargaglio/bfds | 9,105,330,672,621 | 1bd95486bbb2885cacdaedb6f276a00dc2454803 | 0842ff1fc6e57fedd864318be0784faf212a4161 | /server/rest/migrations/0001_initial.py | 620c6e6784a9470a8ccc5a2270f3b84125dcf466 | []
| no_license | https://github.com/nathanmargaglio/bfds | f21dd54255ceec171b2313a6d6ab3752eda55a1c | 355b4a5edc4d785ef570dc84f033040f7ebad37d | refs/heads/master | 2021-04-27T09:59:24.511584 | 2018-03-13T12:53:18 | 2018-03-13T12:53:18 | 122,527,216 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | # Generated by Django 2.0.2 on 2018-02-23 01:23
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Owner',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('first_name', models.CharField(max_length=128)),
('last_name', models.CharField(max_length=128)),
('phone', models.CharField(max_length=128)),
('email', models.CharField(max_length=128)),
('street_number', models.IntegerField()),
('route', models.CharField(max_length=128)),
('locality', models.CharField(max_length=128)),
('county', models.CharField(max_length=128)),
('state', models.CharField(max_length=128)),
('postal_code', models.CharField(max_length=128)),
('lat', models.FloatField()),
('lon', models.FloatField()),
],
),
]
| UTF-8 | Python | false | false | 1,143 | py | 19 | 0001_initial.py | 16 | 0.538058 | 0.501312 | 0 | 32 | 34.71875 | 114 |
ccsourcecode/Blockchain_Survival_Guide | 17,300,128,273,794 | 93c01311d3274fe94dd32f6a181bc0cf16d0709c | 248f9e4f0f9de0413ca950d61dc81a4699beefd5 | /2_1.py | ff7dd274dce0039be43e150269b8418392f9fc20 | []
| no_license | https://github.com/ccsourcecode/Blockchain_Survival_Guide | 6f413859b9d4d7c9747534007b41e7f83e6391dd | 1d619f4ceccef610b8648372baa542c4099c29ae | refs/heads/main | 2023-03-27T12:20:54.632777 | 2021-03-16T08:34:43 | 2021-03-16T08:34:43 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import time
class Transaction:
def __init__(self, sender, receiver, amounts, fee, message):
self.sender = sender
self.receiver = receiver
self.amounts = amounts
self.fee = fee
self.message = message
class Block:
def __init__(self, previous_hash, difficulty, miner, miner_rewards):
self.previous_hash = previous_hash
self.hash = ''
self.difficulty = difficulty
self.nonce = 0
self.timestamp = int(time.time())
self.transactions = []
self.miner = miner
self.miner_rewards = miner_rewards
class BlockChain:
def __init__(self):
self.adjust_difficulty_blocks = 10
self.difficulty = 1
self.block_time = 30
self.miner_rewards = 10
self.block_limitation = 32
self.chain = []
self.pending_transactions = []
| UTF-8 | Python | false | false | 876 | py | 8 | 2_1.py | 7 | 0.590183 | 0.578767 | 0 | 33 | 25.545455 | 72 |
Tribal1012/mipsHex | 12,455,405,199,016 | dc9b3efd6fbac4e90c2cda62ecb9b21f763b792a | cb6eb98d07724e0603d8bce7366d5ce5aee20c30 | /old/base/error.py | 5f3843682f68e90aaf256c59cec7e33eed0f2f71 | []
| no_license | https://github.com/Tribal1012/mipsHex | 7720f4670ad81783621e997a064f03ea56bca2e3 | 23c307db5230dc470ee4baa9cb1a184f826949e6 | refs/heads/master | 2020-03-21T05:45:50.826039 | 2018-10-22T12:28:31 | 2018-10-22T12:28:31 | 138,178,456 | 12 | 2 | null | null | null | null | null | null | null | null | null | null | null | null | null | import sys
'''
print error and exit
'''
def error(msg):
print msg
sys.exit(-1)
'''
for assert check
'''
def check_assert(tag, result):
try:
assert result
except:
error(tag)
| UTF-8 | Python | false | false | 186 | py | 31 | error.py | 28 | 0.639785 | 0.634409 | 0 | 18 | 9.333333 | 30 |
chyidl/chyidlTutorial | 6,708,738,930,670 | 23dff31b1cb5ce21827d2f2ef3d3958296c1b910 | 96bf2ec5c1536831b6a3e08675286770d44d858c | /root/python/PythonPyCon/Python_Concurrency_From_the_Ground_Up/threading_communication.py | 14a2abab67433575aa0549351b698cf65e4a1e8b | [
"MIT"
]
| permissive | https://github.com/chyidl/chyidlTutorial | aa15d6c8526e87a34ed63f79bd541d10ee43b820 | d7f74280725149be11d818b4fbca6cb23ffa4e25 | refs/heads/master | 2022-05-11T13:33:47.015661 | 2022-05-04T13:42:20 | 2022-05-04T13:42:20 | 156,686,624 | 4 | 3 | MIT | false | 2021-04-14T13:58:38 | 2018-11-08T10:02:35 | 2021-04-14T01:00:00 | 2021-04-14T13:58:37 | 83,671 | 3 | 2 | 0 | Python | false | false | #! /usr/bin/env python3
# -*- coding: utf-8 -*-
# ____
# / . .\
# Life is short \ ---<
# I use Python \ /
# __________/ /
# -=:___________/
# threading_communication.py
# Python_Concurrency_From_the_Ground_Up
#
# Created by Chyi Yaqing on 05/23/19 18:46.
# Copyright © 2019. Chyi Yaqing.
# All rights reserved.
#
# Distributed under terms of the MIT
"""
Python threads: communication and stopping
1. How to stop / kill a thread
2. How to safely pass data to a thread and back
Here's a sample "worker" thread implementation. It can be given tasks,
where each task is a directory name, and it does useful work. This work is
recursively listing all the files contained in the given directory and
its sub-directories
"""
import os
import time
import threading
from queue import Queue
class WorkerThread(threading.Thread):
"""A worker thread that takes"""
| UTF-8 | Python | false | false | 907 | py | 751 | threading_communication.py | 389 | 0.655629 | 0.635762 | 0 | 34 | 25.647059 | 74 |
v2psv/crowd_count | 12,051,678,238,159 | 6a295f8be10ab81b8937b5df153755b155b27b16 | e3aae0e629504b8a4f8cd5612e9b74d9fda00243 | /loss.py | 1bc538506b9eda9f22349189ebda71f9e06e86e8 | []
| no_license | https://github.com/v2psv/crowd_count | 7f9d0b7fa7753d331e257d0d501f0faafcdb7a91 | 082c9bf5b6252b1465c88e6dca71b7397755ed3a | refs/heads/master | 2021-01-19T14:50:51.797133 | 2018-04-11T18:50:25 | 2018-04-11T18:50:25 | 100,930,786 | 2 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import torch
import numpy as np
import torch.nn as nn
from torch.nn.modules.loss import _Loss
import torch.nn.functional as F
class ContrastiveLoss(torch.nn.Module):
def __init__(self, margin=2.0):
super(ContrastiveLoss, self).__init__()
self.margin = margin
def forward(self, output1, output2, label):
euclidean_distance = F.pairwise_distance(output1, output2)
loss_contrastive = torch.mean((1-label) * torch.pow(euclidean_distance, 2) +
(label) * torch.pow(torch.clamp(self.margin - euclidean_distance, min=0.0), 2))
return loss_contrastive
class ContrastiveLoss2(torch.nn.Module):
def __init__(self):
super(ContrastiveLoss2, self).__init__()
def forward(self, output1, output2, label):
euclidean_distance = F.pairwise_distance(output1, output2)
loss_contrastive = torch.mean(torch.pow(euclidean_distance-label, 2))
return loss_contrastive
class MSELoss(_Loss):
def __init__(self):
super(MSELoss, self).__init__()
def forward(self, pred, target):
# _assert_no_grad(target)
loss = torch.sum((pred - target)**2) / pred.size(0)
return loss
class RelativeLoss(_Loss):
def forward(self, pred, target):
# _assert_no_grad(target)
loss = torch.sum(((pred-target)/(target+1))**2) / pred.size(0)
return loss
class LogMSELoss(_Loss):
def forward(self, pred, target):
# _assert_no_grad(target)
loss = torch.sum((torch.log(pred+1) - torch.log(target+1))**2) / pred.size(0)
return loss
class L1Loss(_Loss):
def __init__(self, size_average=True, reduce=True, relative=False):
super(L1Loss, self).__init__(size_average)
self.reduce = reduce
self.size_average = size_average
self.relative = relative
def forward(self, input, target):
# _assert_no_grad(target)
if self.relative:
input = input / target
target = target / target
return F.l1_loss(input, target, size_average=self.size_average)
class PmapLoss(_Loss):
def __init__(self, ksize=15):
self.ksize = ksize
self.avg_pool = nn.AvgPool1d(kernel_size=ksize, stride=ksize)
def forward(self, pred, target, avg_density, mask):
x = self.avg_pool(torch.sum(pred, dim=3)) * self.ksize
y = self.avg_pool(torch.sum(target, dim=3)) * self.ksize
n1 = y[:, :, :-1]
n2 = y[:, :, 1:]
class GradientLoss(_Loss):
def __init__(self, alpha=1):
super(GradientLoss, self).__init__()
self.alpha = alpha
self.pad_left = nn.ConstantPad2d((1,0,0,0), 0)
self.pad_top = nn.ConstantPad2d((0,0,1,0), 0)
def forward(self, pred, true):
x1 = torch.abs(pred[:,:,:,1:] - pred[:,:,:,:-1])
x2 = torch.abs(true[:,:,:,1:] - true[:,:,:,:-1])
y1 = torch.abs(pred[:,:,1:,:] - pred[:,:,:-1,:])
y2 = torch.abs(true[:,:,1:,:] - true[:,:,:-1,:])
x1 = self.pad_left(x1)
x2 = self.pad_left(x2)
y1 = self.pad_top(y1)
y2 = self.pad_top(y2)
loss = torch.sum(torch.abs(x1-x2)**self.alpha+torch.abs(y1-y2)**self.alpha) / pred.size(0)
return loss
class L2_Grad_Loss(_Loss):
def __init__(self, alpha=1, lambda_g=1):
super(L2_Grad_Loss, self).__init__()
self.lambda_g = lambda_g
self.alpha = alpha
self.pad_left = nn.ConstantPad2d((1,0,0,0), 0)
self.pad_top = nn.ConstantPad2d((0,0,1,0), 0)
def forward(self, pred, true):
l2_loss = torch.sum((pred - true)**2) / pred.size(0)
x1 = torch.abs(pred[:,:,:,1:] - pred[:,:,:,:-1])
x2 = torch.abs(true[:,:,:,1:] - true[:,:,:,:-1])
y1 = torch.abs(pred[:,:,1:,:] - pred[:,:,:-1,:])
y2 = torch.abs(true[:,:,1:,:] - true[:,:,:-1,:])
x1 = self.pad_left(x1)
x2 = self.pad_left(x2)
y1 = self.pad_top(y1)
y2 = self.pad_top(y2)
grad_loss = torch.sum((x1-x2)**self.alpha + (y1-y2)**self.alpha) / pred.size(0)
return l2_loss + self.lambda_g * grad_loss
class KLLoss(_Loss):
def forward(self, pred, target):
loss = torch.sum(target*(torch.log(target+1e-6) - torch.log(pred+1e-6))) / pred.size(0)
return loss
class CrossEntropyLoss2d(nn.Module):
def __init__(self, weight=None, size_average=True, ignore_index=255):
super(CrossEntropyLoss2d, self).__init__()
self.nll_loss = nn.NLLLoss2d(weight, size_average, ignore_index)
def forward(self, inputs, targets):
return self.nll_loss(F.log_softmax(inputs, dim=1), targets)
class FocalLoss2d(nn.Module):
def __init__(self, gamma=2, weight=[1,3,10,100,1000], size_average=True, ignore_index=255):
super(FocalLoss2d, self).__init__()
self.gamma = gamma
weight = torch.from_numpy(np.array(weight)).type(torch.cuda.FloatTensor)
self.nll_loss = nn.NLLLoss2d(weight, size_average, ignore_index)
def forward(self, inputs, targets):
inputs += 1e-6
if targets.dim() == 4:
n, c, h, w = targets.size()
targets = targets.contiguous().view(n, h, w)
return self.nll_loss((1 - F.softmax(inputs, dim=1)) ** self.gamma * F.log_softmax(inputs, dim=1), targets)
class OrderLoss(_Loss):
def __init__(self, num=[1,1,1,1]):
super(OrderLoss, self).__init__()
n = np.sqrt(num)
self.weight = torch.from_numpy(n/np.sum(n))
def forward(self, pred, target):
n, c, h, w = target.size()
W = self.weight.clone().repeat(n, h, w, 1).transpose(2, 3).transpose(1, 2).contiguous()
W = torch.autograd.Variable(W, requires_grad=False).type(torch.cuda.FloatTensor)
target = target.type(torch.cuda.FloatTensor)
# cross_entropy = nn.BCELoss(weight=W)
# loss = cross_entropy(pred, target)
loss = F.binary_cross_entropy(pred, target, weight=W)
# loss = torch.log(pred + 1e-10).mul(target) + torch.log(1 - pred + 1e-10).mul((1-target))
# loss = loss * W
# loss = -loss.mean()
return loss
| UTF-8 | Python | false | false | 6,122 | py | 33 | loss.py | 27 | 0.579059 | 0.550474 | 0 | 169 | 35.224852 | 117 |
Intervencion/-PKMNFCbot | 14,181,982,032,069 | c01cd34bd17cce73df321d88c1adc69719c9bc49 | 3eaf2b0f95f8af34d81cc0f261781ff025f7126b | /Bot/NOTOCAR/info.py | 7d951426d63b11b1f4a36a9b6c03dbd7a4c45bd6 | []
| no_license | https://github.com/Intervencion/-PKMNFCbot | a14cfa41ff753cc91c3688fb425b9f5a0c54d787 | b21d04e37a1b9f7b63fb1cfcf6814214e61ad2a4 | refs/heads/master | 2020-06-12T17:37:00.316130 | 2019-02-27T13:20:15 | 2019-02-27T13:20:15 | 75,786,677 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from config import *
@bot.message_handler(commands=['info'])
def command_info(m):
cid = m.chat.id
try:
dex = m.text.split(' ', 1)[1].replace(" ","_")
bot.reply_to(m,f'https://www.wikidex.net/wiki/{dex}', disable_web_page_preview=True)
try:
c.execute("SELECT Contador FROM TContador WHERE Nombre ='info'")
for i in c:
print(i[0])
increment = i[0] +1
c.execute("UPDATE TContador SET Contador = Contador + 1 WHERE Nombre = 'info'")
except:
mensaje = f"No he contado bien mamá.\n"
mensaje += f"User: {ufm}\n"
mensaje += f"Chat: {mct}\n"
mensaje += f"Hora: {hora}\n"
mensaje += f"UserID: [{uid}]"
mensaje += f" ChatID: [{cid}]"
mensaje += "\n"
mensaje += f"Mensaje: {texto}\n"
mensaje += "-------------------------------\n"
bot.send_message(admins[0], mensaje, parse_mode = "Markdown")
except:
bot.send_message(cid, "El formato del comando es /info *X* donde X es el nombre del pokémon, movimiento u objeto.", parse_mode = "Markdown") | UTF-8 | Python | false | false | 993 | py | 25 | info.py | 23 | 0.607467 | 0.600404 | 0 | 27 | 35.740741 | 142 |
harsh7742/music_system | 11,338,713,679,638 | b80913b74e623f023de64c5e5eb0af7c1040534a | 038abb327e31acae36a5933111611592846895fa | /musicplayer.py | 26517479fc6974ae6c1f9abec4e5c1ee40b5ce8e | []
| no_license | https://github.com/harsh7742/music_system | f980324746e6becc2c4b92dd7cc285bdecaa2680 | 679a9916416a675254d9aa8eb50159e695ae3c56 | refs/heads/main | 2023-06-26T16:14:42.379152 | 2021-07-28T06:16:57 | 2021-07-28T06:16:57 | 390,235,973 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | def resumemusic():
root.pauseButton.grid()
root.resumeButton.grid_remove()
def volumeup():
vol = mixer.music.get_volume()
mixer.music.set_volume(vol+0.1)
def volumedown():
vol = mixer.music.get_volume()
mixer.music.set_volume(vol-0.1)
def stopmusic():
mixer.music.stop()
def pausemusic():
mixer.music.pause()
root.resumeButton.grid()
root.pauseButton.grid_remove()
def playmusic():
h=audiotrack.get()
mixer.music.load(h)
mixer.music.play()
def music():
d=filedialog.askopenfilename()
audiotrack.set(d)
def createwidthes():
global imbrowse,impause,imbrowse,imvolumeup,imvolumedown,imstop,implay,iresume
#images res=gister
implay=PhotoImage(file='play.png')
impause=PhotoImage(file='pause1.png')
imbrowse=PhotoImage(file='browse.png')
imstop=PhotoImage(file='stop1.png')
imvolumeup=PhotoImage(file='volumeup.png')
imvolumedown=PhotoImage(file='volumedown.png')
imresume = PhotoImage(file='play.png')
#change size of imgae
imbrowse =imbrowse.subsample(1,1)
impause = impause.subsample(20,20)
imvolumeup = imvolumeup.subsample(1, 1)
imvolumedown = imvolumedown.subsample(2,2)
implay = implay.subsample(2,2)
imstop = imstop.subsample(110,110)
imresume = imresume.subsample(2,2)
#labels
TrackLabel = Label(root,text='Audio Track :',bg='azure',font=('verdana',14,'italic bold'))
TrackLabel.grid(row=0,column=0,padx=22,pady=22)
#entry box
LabelEntry=Entry(root,font=('verdana',14,'italic bold'),width=30,textvariable=audiotrack)
LabelEntry.grid(row=0,column=1,padx=22,pady=22)
#button
browsseButton=Button(root,text='Search',bg='azure',font=('verdana',14,'italic bold'),width=200,relief='solid',
activebackground='lightskyblue3',image=imbrowse,compound=RIGHT,command=music)
browsseButton.grid(row=0,column=2,padx=22,pady=22)
playButton=Button(root,text='Play',bg='azure',font=('verdana',14,'italic bold'),width=200,relief='solid',
activebackground='lightskyblue3',image=implay,compound=RIGHT,command=playmusic)
playButton.grid(row=1,column=0,padx=22,pady=22)
root.pasueButton = Button(root, text='Pause', bg='azure', font=('verdana', 14, 'italic bold'), width=200, relief='solid',
activebackground='lightskyblue3',image=impause,compound=RIGHT,command=pausemusic)
root.pasueButton.grid(row=1, column=1, padx=22, pady=22)
root.resumeButton = Button(root, text='resume', bg='azure', font=('verdana', 14, 'italic bold'), width=200, relief='solid',
activebackground='lightskyblue3', image=imresume, compound=RIGHT, command=resumemusic)
root.resumeButton.grid(row=1, column=1, padx=22, pady=22)
root.resumeButton.grid_remove()
stopButton=Button(root,text='Stop',bg='azure',font=('verdana',14,'italic bold'),width=200,relief='solid',
activebackground='lightskyblue3',image=imstop,compound=RIGHT,command=stopmusic)
stopButton.grid(row=2,column=0,padx=22,pady=22)
volumeupButton = Button(root, text='VolumeUp', bg='azure', font=('verdana', 14, 'italic bold'), width=200, relief='solid',
activebackground='lightskyblue3',image=imvolumeup,compound=RIGHT,command=volumeup)
volumeupButton.grid(row=1, column=2, padx=22, pady=22)
volumedownButton = Button(root, text='Volumedown', bg='azure', font=('verdana', 14, 'italic bold'), width=200, relief='solid',
activebackground='lightskyblue3',image=imvolumedown,compound=RIGHT,command=volumedown)
volumedownButton.grid(row=2, column=2, padx=22, pady=22)
#############################################################
from tkinter import *
from tkinter import filedialog
from pygame import mixer
root = Tk()
root.geometry('1100x500+200+50')
root.title('Music Player')
root.iconbitmap('music.ico')
root.resizable(False,False)
root.configure(bg='aqua')
#gobal variable
audiotrack = StringVar()
#create a slider
h="Developed by Harsh Sharma"
count=0
text =''
sliderLabel=Label(root,text=h,bg='aqua', font=('verdana', 32, 'italic bold'))
sliderLabel.grid(row=3,column=0,padx=22,pady=22,columnspan=3)
def IntroLabelTrick():
global count,text
if(count>=len(h)):
count = -1
text=''
sliderLabel.configure(text=text)
else:
text= text+h[count]
sliderLabel.configure(text=text)
count +=1
sliderLabel.after(200,IntroLabelTrick)
IntroLabelTrick()
mixer.init()
createwidthes()
root.mainloop() | UTF-8 | Python | false | false | 4,657 | py | 1 | musicplayer.py | 1 | 0.665879 | 0.632596 | 0 | 113 | 39.230088 | 130 |
epi052/recon-pipeline | 3,229,815,430,894 | 6af8caf22e1a8bcd201df027eff66aa975af4ebf | 67e7c0f06e8aef9579bf3761ff6af76e5eafb590 | /tests/test_web/test_waybackurls.py | 8c08f028d779221a76d93b115017cd81d7a77b91 | [
"MIT"
]
| permissive | https://github.com/epi052/recon-pipeline | d1c711f5fd7ceccc95eda13004287d030452fe90 | 4930f4064ca42c4b3669444b92dee355dd68b81e | refs/heads/main | 2023-02-23T06:02:26.055102 | 2023-01-27T00:20:30 | 2023-01-27T00:20:30 | 205,856,988 | 413 | 102 | MIT | false | 2023-02-13T16:35:28 | 2019-09-02T12:54:26 | 2023-02-05T12:43:20 | 2023-02-13T16:35:28 | 63,776 | 375 | 89 | 12 | Python | false | false | import shutil
import tempfile
from pathlib import Path
from unittest.mock import MagicMock, patch
from pipeline.recon.web import WaybackurlsScan, GatherWebTargets
class TestGatherWebTargets:
def setup_method(self):
self.tmp_path = Path(tempfile.mkdtemp())
self.scan = WaybackurlsScan(
target_file=__file__, results_dir=str(self.tmp_path), db_location=str(self.tmp_path / "testing.sqlite")
)
self.scan.exception = False
def teardown_method(self):
shutil.rmtree(self.tmp_path)
def test_scan_requires(self):
with patch("pipeline.recon.web.GatherWebTargets"):
with patch("pipeline.recon.web.waybackurls.meets_requirements"):
retval = self.scan.requires()
assert isinstance(retval, GatherWebTargets)
def test_scan_creates_database(self):
assert self.scan.db_mgr.location.exists()
assert self.tmp_path / "testing.sqlite" == self.scan.db_mgr.location
def test_scan_creates_results_dir(self):
assert self.scan.results_subfolder == self.tmp_path / "waybackurls-results"
def test_scan_run(self):
with patch("subprocess.run", autospec=True) as mocked_run:
self.scan.results_subfolder = self.tmp_path / "waybackurls-results"
self.scan.db_mgr.get_all_hostnames = MagicMock()
self.scan.db_mgr.get_all_hostnames.return_value = ["google.com"]
completed_process_mock = MagicMock()
completed_process_mock.stdout.return_value = b"https://drive.google.com\nhttps://maps.google.com\n\n"
completed_process_mock.stdout.decode.return_value = "https://drive.google.com\nhttps://maps.google.com\n\n"
completed_process_mock.stdout.decode.splitlines.return_value = [
"https://drive.google.com",
"https://maps.google.com",
]
mocked_run.return_value = completed_process_mock
self.scan.db_mgr.add = MagicMock()
self.scan.db_mgr.get_or_create = MagicMock()
self.scan.db_mgr.get_or_create_target_by_ip_or_hostname = MagicMock()
self.scan.run()
assert mocked_run.called
assert self.scan.db_mgr.add.called
assert self.scan.db_mgr.get_or_create.called
assert self.scan.db_mgr.get_or_create_target_by_ip_or_hostname.called
| UTF-8 | Python | false | false | 2,396 | py | 1,013 | test_waybackurls.py | 48 | 0.64399 | 0.64399 | 0 | 59 | 39.610169 | 119 |
zhangsong1417/xx | 8,169,027,819,964 | 7fd68afe645e538bf19f62db1d4506c5fac8372a | 27ff7fec0ae3f29f58089a2acab0aa3bc4e6e1f7 | /RIDE-python3/utest/ui/test_namedialogs.py | 0576cfc0057ce75ed9d33e0992c36f1859fca2d5 | [
"Apache-2.0"
]
| permissive | https://github.com/zhangsong1417/xx | 01435d6057364991b649c1acc00b36ab13debe5a | c40cfdede194daf3bdf91b36c1936150577128b9 | refs/heads/master | 2020-04-06T14:06:23.011363 | 2019-07-09T02:38:02 | 2019-07-09T02:38:02 | 157,528,207 | 1 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import unittest
from nose.tools import assert_equal
from robotide.controller.filecontrollers import TestCaseFileController
from robotide.editor.editordialogs import (
TestCaseNameDialog, UserKeywordNameDialog)
from robotide.robotapi import TestCaseFile
from resources import PYAPP_REFERENCE, wx
def file_controller():
return TestCaseFileController(TestCaseFile())
class TestNameDialogTest(unittest.TestCase):
_frame = wx.Frame(None)
def test_creation(self):
test_ctrl = file_controller().create_test('A test')
dlg = TestCaseNameDialog(test_ctrl)
assert_equal(dlg.get_name(), '')
class UserKeywordNameDialogTest(unittest.TestCase):
def test_creation(self):
kw_ctrl = file_controller().create_keyword('Keyword it is')
dlg = UserKeywordNameDialog(kw_ctrl)
assert_equal(dlg.get_name(), '')
def test_arguments_are_returned(self):
kw_ctrl = file_controller().create_keyword('Keyword it is')
dlg = UserKeywordNameDialog(kw_ctrl)
assert_equal(dlg.get_args(), '')
| UTF-8 | Python | false | false | 1,062 | py | 176 | test_namedialogs.py | 157 | 0.717514 | 0.717514 | 0 | 35 | 29.342857 | 70 |
alekseystryukov/simple-chat | 11,982,958,765,732 | ea0a865357b93e130fbfc8950153d18d6d17d83c | aafc464037938a5c32cf83e63107e946f49de8f2 | /simple_chat/models.py | 5e87f890cbd23196fe5cfad18caad3afb1f3849b | []
| no_license | https://github.com/alekseystryukov/simple-chat | ca53bd6dc95531248ff9907907f07a1dd9472305 | 623568a25eaa250e56fc20402763e9fc1bbdcad8 | refs/heads/master | 2016-08-12T06:37:43.484252 | 2015-11-09T16:16:59 | 2015-11-09T16:16:59 | 45,549,375 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from collections import deque
from datetime import datetime
class Message:
"""
Instances of this class keep info about every message from chat.
Class doesn't inherit django.db.models, because we do not need to save them to db.
Instances keep the data in slots, it saves a bit memory.
Class property last_id saves last message id. It useful for recipients to track messages, that they already received
"""
__slots__ = ('id', 'name', 'message', 'time')
last_id = 0
@staticmethod
def get_id():
"""
Method returns incremented message_id
Return: int: next message id
"""
Message.last_id += 1
return Message.last_id
def to_json(self):
"""
Method that returns the message data in format suited for json.dumps function
Return: dict: message data that will be send to chat message recipients
"""
return {'id': self.id, 'name': self.name, 'message': self.message, 'time': self.time.strftime('%d %b %Y %H:%M:%S')}
def __init__(self, **kwargs):
self.id = self.get_id()
self.name = kwargs['name']
self.message = kwargs['message']
self.time = datetime.now()
def __repr__(self):
return u"[{}] #{} {}: <{}>".format(self.time, self.id, self.name, self.message)
MessagesPoll = deque(maxlen=500) #messages queue
| UTF-8 | Python | false | false | 1,382 | py | 12 | models.py | 6 | 0.617221 | 0.613603 | 0 | 41 | 32.682927 | 123 |
peter302/password-locker | 15,839,839,417,472 | 655c048edc9ae1bb7ea84f595cae4486c0c1dbba | 46102c1049ccc6447e4e69867ce3997d7bd3999d | /user.py | 2f6141e9ed9eb68cf27948a765fe0c22cb23f7c4 | [
"MIT"
]
| permissive | https://github.com/peter302/password-locker | 356a8bcdb48e8dad31a7375ce1b91ec16177d806 | 1fa10dafb6aa95511044543c5673a6212fe13fbc | refs/heads/master | 2020-11-23T22:31:19.636350 | 2019-12-16T14:16:33 | 2019-12-16T14:16:33 | 227,847,593 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import pyperclip,string,random
class User:
user_list=[] #a list to hold user details
def __init__(self,f_name,l_name,password):
"a method acting as constructor to initalize instances of a class"
self.f_name=f_name
self.l_name=l_name
self.password=password
def user_save(self):
"a method to save a new user object when ceated"
User.user_list.append(self)
class Credentials:
"this class will hold users details including names and passwords for user's site plus funtions and method to alter those dtails"
Credentials_list=[]
user_credentials_list=[]
@classmethod
def user_auth(cls,f_name,password):
'''this method will authenticate user'''
loged_user=''
for user in User.user_list:
if(user.f_name==f_name and user.password==password):
loded_user=user.f_name
return loged_user
def __init__(self,user_name,web_site,account_name,password):
"this method initializes our credentials class with the propertis for user credentials"
self.user_name=user_name
self.web_site=web_site
self.account_name=account_name
self.password=password
def save_credentials(self):
"this method will save a newly user created credentials"
Credentials.Credentials_list.append(self)
def pass_gen(pass_size=6,char=string.ascii_uppercase+string.ascii_lowercase+string.digits):
"this function will generate a password if user chooses automatic pass word generation"
pass_choice=''.join(random.choice(char) for _ in range(pass_size))
return pass_choice
@classmethod
def show_credentials(cls,user_name):
"this method will show all credentials stored for the loged user"
for j in cls.user_credetials_list:
if j.user_name==user_name:
user_credetials_list.append(j)
return user_credetials_list
@classmethod
def search_site_name(cls,web_site):
"this method will search a web_site by name"
for k in cls.Credentials_list:
if k.web_site==web_site:
return k
def copy_site(cls,web_site):
"class methods to copy a site name to our clip board"
copy_credentials=Credentials.search_site_name(web_site)
return pyperclip.copy(copy_credentials.password)
| UTF-8 | Python | false | false | 2,567 | py | 4 | user.py | 3 | 0.613557 | 0.613167 | 0 | 61 | 41.081967 | 137 |
jemmelot/Heuristieken | 3,453,153,716,571 | dd6ab2c37098d5d71a48cc5a6381feefa90d7cab | 94bf3533dea38ed3c6ee0501a16e180b53cb700d | /classes/ScoreIntegrated.py | 2cd8e23d1f0c3c1aaf844af822db2ef12b0c1389 | []
| no_license | https://github.com/jemmelot/Heuristieken | 71572f8194da7c94ea55e371d685a8894ee64758 | e89adf9b47d7761cf08a81b646845de27a42f661 | refs/heads/master | 2021-08-30T22:09:47.928773 | 2017-12-19T16:14:05 | 2017-12-19T16:14:05 | 109,595,024 | 1 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | #!/usr/bin/python3
# https://github.com/jemmelot/Heuristieken.git
import numpy as np
import csv
import sys
sys.path.append('../classes/')
sys.path.append('../functions/')
sys.path.append('../algorithms/')
import matplotlib.pyplot as plt
class score_integrated():
def __init__(self, main_array, visited_connections, stations, route, critical_stations, trains, iteration):
self.main_array = main_array
self.visited_connections = visited_connections
self.stations = stations
self.route = route
self.critical_stations = critical_stations
self.trains = trains
self.iteration = iteration
self.t = self.t()
self.min = self.min()
self.p = self.p()
self.totalscore = self.totalscore(self.p, self.t, self.min)
def __float__(self):
return self.totalscore
def t(self):
t = self.trains
return t
def min(self):
min = 0
for i in range(self.iteration):
min += self.route[i][0]
return min
def p(self):
if len(self.critical_stations) != len(self.stations):
all_criticals = 0
missed_criticals = 0
# compare the t array to the main array to check for missed critical connections
for i in range(len(self.stations)):
if self.stations[i] in self.critical_stations:
x = np.count_nonzero(self.main_array[i, :] > 0)
all_criticals += x
y = np.count_nonzero(self.visited_connections[i, :] > 0)
if not x == y:
missed_criticals += (x - y)
p = ((all_criticals - missed_criticals)/all_criticals)
else:
all_criticals = 0
missed_criticals = 0
for i in range(len(self.visited_connections)):
x = np.count_nonzero(self.main_array[i, :] > 0)
all_criticals += x
y = np.count_nonzero(self.visited_connections[i, :] > 0)
if not x == y:
missed_criticals += (x - y)
p = ((all_criticals - missed_criticals)/all_criticals)
return p
def totalscore(self, p, t, min):
totalscore = (p * 10000) - ((t * 20) + (min/10000))
return totalscore
| UTF-8 | Python | false | false | 1,995 | py | 21 | ScoreIntegrated.py | 11 | 0.643108 | 0.631579 | 0 | 78 | 24.576923 | 108 |
pkofod/vfi | 4,286,377,387,604 | 875554747ce520bf8f63a067015b3f9adb6bc80d | 38452ad0e05ed8b8755717e7710b55108e438156 | /vfi/optimize_1d.py | 4e53f14e9d0447a484bc32d7bb480b359fb2acd8 | [
"MIT"
]
| permissive | https://github.com/pkofod/vfi | c6ffda4e4d4f0e71f1ddc40587b041434b4fd2ca | 38a0dd02b9a01c37f5a11252feaebad13c2010aa | refs/heads/master | 2020-03-28T23:02:15.522151 | 2018-08-09T20:01:05 | 2018-08-09T20:01:05 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import math
import numba
# constants
inv_phi = (math.sqrt(5) - 1) / 2 # 1/phi
inv_phi_sq = (3 - math.sqrt(5)) / 2 # 1/phi^2
# create
def create_optimizer(f):
@numba.njit
def golden_section_search(a,b,tol,*args):
# a. distance
dist = b - a
if dist <= tol:
return (a+b)/2
# b. number of iterations
n = int(math.ceil(math.log(tol/dist)/math.log(inv_phi)))
# c. potential new mid-points
c = a + inv_phi_sq * dist
d = a + inv_phi * dist
yc = f(c,*args)
yd = f(d,*args)
# d. loop
for _ in range(n-1):
if yc < yd:
b = d
d = c
yd = yc
dist = inv_phi*dist
c = a + inv_phi_sq * dist
yc = f(c,*args)
else:
a = c
c = d
yc = yd
dist = inv_phi*dist
d = a + inv_phi * dist
yd = f(d,*args)
# e. return
if yc < yd:
return (a+d)/2
else:
return (c+b)/2
return golden_section_search | UTF-8 | Python | false | false | 1,102 | py | 10 | optimize_1d.py | 5 | 0.424682 | 0.412886 | 0 | 51 | 20.627451 | 159 |
alimirakim/sbade | 6,382,321,433,072 | 4740d9d6c037d13b54ac7a1049d37daf972a851a | b351351bc1f643ce9645e2c5c91eef5caaa3eb76 | /skeleton/migrations/versions/5f553ea80cc6_new_seeder_data.py | 53250c51d098795bb4b8f44ac5dfdee4a0ffe7a2 | []
| no_license | https://github.com/alimirakim/sbade | 64051ac366fb5aa8b8cfc6434c94fb446213e43e | 137bc7fed59472658872de4fbfdf227ff4c22283 | refs/heads/main | 2023-01-24T09:04:33.752364 | 2020-12-04T17:21:06 | 2020-12-04T17:21:06 | 313,983,847 | 0 | 0 | null | false | 2020-12-01T15:33:41 | 2020-11-18T15:55:57 | 2020-12-01T15:01:11 | 2020-12-01T15:33:41 | 3,045 | 1 | 0 | 0 | Python | false | false | """new seeder data
Revision ID: 5f553ea80cc6
Revises:
Create Date: 2020-12-01 03:14:35.021979
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = '5f553ea80cc6'
down_revision = None
branch_labels = None
depends_on = None
def upgrade():
# ### commands auto generated by Alembic - please adjust! ###
op.create_table('colors',
sa.Column('id', sa.Integer(), nullable=False),
sa.Column('hex', sa.String(length=7), nullable=False),
sa.Column('name', sa.String(length=50), nullable=True),
sa.Column('mode', sa.String(length=50), nullable=True),
sa.PrimaryKeyConstraint('id'),
sa.UniqueConstraint('hex'),
sa.UniqueConstraint('name')
)
op.create_table('stamps',
sa.Column('id', sa.Integer(), nullable=False),
sa.Column('stamp', sa.String(length=50), nullable=False),
sa.Column('type', sa.String(length=50), nullable=False),
sa.PrimaryKeyConstraint('id'),
sa.UniqueConstraint('stamp')
)
op.create_table('users',
sa.Column('id', sa.Integer(), nullable=False),
sa.Column('username', sa.String(length=50), nullable=False),
sa.Column('first_name', sa.String(length=50), nullable=False),
sa.Column('last_name', sa.String(length=50), nullable=True),
sa.Column('email', sa.String(length=50), nullable=False),
sa.Column('color_id', sa.Integer(), nullable=True),
sa.Column('stamp_id', sa.Integer(), nullable=False),
sa.Column('birthday', sa.Date(), nullable=True),
sa.Column('hashed_password', sa.String(length=255), nullable=False),
sa.Column('created_at', sa.DateTime(), nullable=False),
sa.ForeignKeyConstraint(['color_id'], ['colors.id'], ),
sa.ForeignKeyConstraint(['stamp_id'], ['stamps.id'], ),
sa.PrimaryKeyConstraint('id'),
sa.UniqueConstraint('email'),
sa.UniqueConstraint('username')
)
op.create_table('bonds',
sa.Column('id', sa.Integer(), nullable=False),
sa.Column('user1_id', sa.Integer(), nullable=False),
sa.Column('user2_id', sa.Integer(), nullable=False),
sa.Column('created_at', sa.DateTime(), nullable=True),
sa.ForeignKeyConstraint(['user1_id'], ['users.id'], ),
sa.ForeignKeyConstraint(['user2_id'], ['users.id'], ),
sa.PrimaryKeyConstraint('id')
)
op.create_table('programs',
sa.Column('id', sa.Integer(), nullable=False),
sa.Column('program', sa.String(length=50), nullable=False),
sa.Column('description', sa.String(length=250), nullable=True),
sa.Column('color_id', sa.Integer(), nullable=True),
sa.Column('stamp_id', sa.Integer(), nullable=False),
sa.Column('creator_id', sa.Integer(), nullable=False),
sa.Column('created_at', sa.DateTime(), nullable=False),
sa.ForeignKeyConstraint(['color_id'], ['colors.id'], ),
sa.ForeignKeyConstraint(['creator_id'], ['users.id'], ),
sa.ForeignKeyConstraint(['stamp_id'], ['stamps.id'], ),
sa.PrimaryKeyConstraint('id')
)
op.create_table('habits',
sa.Column('id', sa.Integer(), nullable=False),
sa.Column('habit', sa.String(length=50), nullable=False),
sa.Column('description', sa.String(length=250), nullable=True),
sa.Column('frequency', sa.String(length=7), nullable=False),
sa.Column('color_id', sa.Integer(), nullable=True),
sa.Column('stamp_id', sa.Integer(), nullable=False),
sa.Column('program_id', sa.Integer(), nullable=True),
sa.Column('creator_id', sa.Integer(), nullable=False),
sa.Column('created_at', sa.DateTime(), nullable=False),
sa.ForeignKeyConstraint(['color_id'], ['colors.id'], ),
sa.ForeignKeyConstraint(['creator_id'], ['users.id'], ),
sa.ForeignKeyConstraint(['program_id'], ['programs.id'], ),
sa.ForeignKeyConstraint(['stamp_id'], ['stamps.id'], ),
sa.PrimaryKeyConstraint('id')
)
op.create_table('members',
sa.Column('id', sa.Integer(), nullable=False),
sa.Column('program_id', sa.Integer(), nullable=False),
sa.Column('member_id', sa.Integer(), nullable=False),
sa.Column('stamper_id', sa.Integer(), nullable=True),
sa.Column('points', sa.Integer(), nullable=False),
sa.Column('joined_at', sa.DateTime(), nullable=False),
sa.ForeignKeyConstraint(['member_id'], ['users.id'], ),
sa.ForeignKeyConstraint(['program_id'], ['programs.id'], ),
sa.ForeignKeyConstraint(['stamper_id'], ['users.id'], ),
sa.PrimaryKeyConstraint('id')
)
op.create_table('rewards',
sa.Column('id', sa.Integer(), nullable=False),
sa.Column('type', sa.String(length=50), nullable=False),
sa.Column('reward', sa.String(length=50), nullable=False),
sa.Column('description', sa.String(length=250), nullable=True),
sa.Column('cost', sa.Integer(), nullable=False),
sa.Column('color_id', sa.Integer(), nullable=True),
sa.Column('limit_per_member', sa.Integer(), nullable=False),
sa.Column('quantity', sa.Integer(), nullable=False),
sa.Column('stamp_id', sa.Integer(), nullable=False),
sa.Column('program_id', sa.Integer(), nullable=True),
sa.Column('creator_id', sa.Integer(), nullable=True),
sa.Column('created_at', sa.DateTime(), nullable=False),
sa.ForeignKeyConstraint(['color_id'], ['colors.id'], ),
sa.ForeignKeyConstraint(['creator_id'], ['users.id'], ),
sa.ForeignKeyConstraint(['program_id'], ['programs.id'], ),
sa.ForeignKeyConstraint(['stamp_id'], ['stamps.id'], ),
sa.PrimaryKeyConstraint('id')
)
op.create_table('daily_stamps',
sa.Column('id', sa.Integer(), nullable=False),
sa.Column('date', sa.Date(), nullable=False),
sa.Column('status', sa.Enum('unstamped', 'pending', 'stamped', name='status'), nullable=True),
sa.Column('habit_id', sa.Integer(), nullable=False),
sa.Column('member_id', sa.Integer(), nullable=False),
sa.Column('updated_at', sa.DateTime(), nullable=False),
sa.ForeignKeyConstraint(['habit_id'], ['habits.id'], ),
sa.ForeignKeyConstraint(['member_id'], ['members.id'], ),
sa.PrimaryKeyConstraint('id')
)
op.create_table('redeemed',
sa.Column('id', sa.Integer(), nullable=False),
sa.Column('user_id', sa.Integer(), nullable=False),
sa.Column('reward_id', sa.Integer(), nullable=False),
sa.Column('redeemed_at', sa.DateTime(), nullable=False),
sa.ForeignKeyConstraint(['reward_id'], ['rewards.id'], ),
sa.ForeignKeyConstraint(['user_id'], ['users.id'], ),
sa.PrimaryKeyConstraint('id')
)
# ### end Alembic commands ###
def downgrade():
# ### commands auto generated by Alembic - please adjust! ###
op.drop_table('redeemed')
op.drop_table('daily_stamps')
op.execute('drop type status;')
op.drop_table('rewards')
op.drop_table('members')
op.drop_table('habits')
op.drop_table('programs')
op.drop_table('bonds')
op.drop_table('users')
op.drop_table('stamps')
op.drop_table('colors')
# ### end Alembic commands ###
| UTF-8 | Python | false | false | 6,892 | py | 40 | 5f553ea80cc6_new_seeder_data.py | 32 | 0.648433 | 0.637406 | 0 | 159 | 42.345912 | 98 |
1299172402/up366 | 970,662,640,119 | 9b28ba1a709bffcbec4a3e69957a125a5c00aac7 | 2eff86f2b5ed6ca040c35ce360caff2238ae5cca | /load.py | b81124f8a5e6719666f14b09cedefe0d27e119e0 | []
| no_license | https://github.com/1299172402/up366 | 2fdc816df83e5444bd2cb0762b918bcf4df7d44b | 1fe7748d6cb680c2f7c9e5652f05ee4c17010b4e | refs/heads/master | 2020-12-22T07:49:13.793663 | 2020-02-13T13:22:36 | 2020-02-13T13:22:36 | 236,716,689 | 2 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import requests
from bs4 import BeautifulSoup
import urllib.request
from lxml import html
etree = html.etree
# 欢迎文字
print('\n\n')
print('####### 天学网登录程序 #######\n')
# print('Author~~')
print('Jellow 看见我请一定一定叫我学习')
print('Creative By ZhiyuShang With Love\n')
# print('Thanks for being addicted')
print('')
headers = {
'Accept': 'application/json, text/javascript, */*; q=0.01',
'Content-Type': 'application/x-www-form-urlencoded;charset=UTF-8',
'Host': 'live-api.up366.cn',
'Origin': 'http://me.up366.cn',
'Referer': 'http://me.up366.cn/center/student/course/liveclasses.html?courseId=89440&createTime=undefined',
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.108 Safari/537.36',
'X-Requested-With': 'XMLHttpRequest',
'Cookie': 'acw_tc=7b39758215802092127684930e1234175f6acbea06d4bbf933eca866daecde; BIGipServercn_liveclass-api_pool=2467735744.38175.0000; SESSION=301df37e-80f0-4372-b3a1-2ab37363de0e'
}
print('测试获取直播课列表\n')
print('出现我校直播课名称即为获取成功\n')
play_url = 'http://live-api.up366.cn/client/liveclass/list'
s = requests.session()
response = s.get(play_url, headers=headers).content
s = BeautifulSoup(response, 'lxml')
print(s) | UTF-8 | Python | false | false | 1,339 | py | 5 | load.py | 2 | 0.709237 | 0.604819 | 0 | 38 | 30.815789 | 184 |
rcrowther/Gravel | 11,553,462,038,408 | 431998f40f0227dfbacb0ea4567d670c7e9ce5a5 | a07694aab30198bc11965d0dae11471b0a004957 | /interpreter/__init__.py | 3c16d9a645d7378407efdd76dac36d151cda0256 | []
| no_license | https://github.com/rcrowther/Gravel | 6fccf500f680ea70371c4d889d6f2930c1a7727e | 86f22a2c1d561983020949cf5dc75cfb3004919b | refs/heads/master | 2021-08-25T06:21:34.317932 | 2021-06-11T19:14:24 | 2021-06-11T19:14:24 | 135,619,592 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | from .Engines import FileEngine
| UTF-8 | Python | false | false | 32 | py | 175 | __init__.py | 147 | 0.84375 | 0.84375 | 0 | 1 | 31 | 31 |
CmJustice/Mc-Admin | 7,215,545,084,499 | 2dd41bc03518a4ce04285888242a069f2179b386 | 4552ca62b4b47a10da893f009f5bf25323fe30df | /main.py | 7012971d431f6dc8b92c78429b450d73a339a8d1 | []
| no_license | https://github.com/CmJustice/Mc-Admin | 8e566273254659c36eec477aba9c913da02f7d57 | be0e6fa888bb46f5cf8477d4fa8d1acfd74a08d2 | refs/heads/master | 2016-09-09T19:13:32.766843 | 2015-09-15T17:14:51 | 2015-09-15T17:14:51 | 42,507,912 | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | #-*- coding: utf-8 -*-
__author__ = 'Cem'
import sys
import os
import utils.screenutils.screen
import utils.screenutils.errors
import utils.color
color = utils.color
import konsol
screenutil = utils.screenutils.screen
print "MC-ADMIN VERSIYON 0.1"
print "Hosgeldin!"
print "\nLütfen giris yapin!"
def selamla(isim):
print "Hoşgeldiniz", isim, "bey"
print "Umarım iyi vakit geçirirsiniz."
print("")
print("")
print("")
print("")
print("")
print("")
print("")
konsol.konsol()
while True:
id = raw_input("Kullanici adi:")
sifre = raw_input("Sifre:")
if id == 'Cem' and sifre == '1234' :
selamla(id)
break
else:
print color.bcolors.FAIL + "Sifre veya Kullanici Adi hatali!"
| UTF-8 | Python | false | false | 775 | py | 5 | main.py | 4 | 0.614786 | 0.605707 | 0 | 50 | 14.36 | 69 |
coolsnake/JupyterNotebook | 7,619,271,986,562 | 1114def8a5f97064b9d83e97085660ccded181ed | da29f1f5b4459fbfec968bb694bedb9586f87b14 | /new_algs/Graph+algorithms/Dijkstra's+algorithm/Dijsktra's.py | 47b7ea49a77d30c80ff268b241a34013b2e3ef3e | [
"BSD-3-Clause",
"Apache-2.0"
]
| permissive | https://github.com/coolsnake/JupyterNotebook | 547806a45a663f090f313dc3e70f779ad9b213c0 | 20d8df6172906337f81583dabb841d66b8f31857 | refs/heads/master | 2023-01-13T18:55:38.615312 | 2020-11-17T22:55:12 | 2020-11-17T22:55:12 | null | 0 | 0 | null | null | null | null | null | null | null | null | null | null | null | null | null | import math
import copy
import time
def searchForLeastCost(costs, processed):
lowestCost = math.inf
lowestCostNode = None
for node in costs:
cost = costs[node]
#check if cheapest
if cost < lowestCost and node not in processed:
lowestCost = cost
lowestCostNode = node
return(lowestCostNode)
def formulate(graph, startNode):
costs = {}
parents = {}
processed = []
#making costs
for w in graph:
costs[w] = math.inf
#adding costs from start node
costs[startNode] = 0
for x in graph[startNode]:
costs[x] = graph[startNode][x]
#creating parents
for y in graph:
parents[y] = None
#adding parents from start node
parents[startNode] = 0
for z in graph[startNode]:
parents[z] = startNode
#creating processed
processed.append(startNode)
return(parents, costs, processed)
def dijkstra(graph, startNode):
parents, costs, processed = formulate(graph, startNode)
node = searchForLeastCost(costs, processed)
#if while loop over nodes all processed
while node is not None:
#get all neighbours from node & their total costs
cost = costs[node]
neighbours = graph[node]
for n in neighbours:
newCost = cost + neighbours[n]
#if newcost less than previous noted 'shortest' cost...
if costs[n] > newCost:
#then update costs and parents to say so
costs[n] = newCost
parents[n] = node
#now all neighbours noted node has been processed
processed.append(node)
#find next node
node = searchForLeastCost(costs, processed)
return(parents, costs, processed)
def main():
'''
target = "End"
#make graph
graph = {}
#nodes
graph["Start"] = {}
graph["A"] = {}
graph["B"] = {}
graph["End"] = {}
#node connections
graph["Start"]["A"] = 6
graph["Start"]["B"] = 2
graph["A"]["End"] = 1
graph["B"]["A"] = 3
graph["B"]["End"] = 5
'''
#travelling salesman
#make graph
graph = {}
#nodes
graph["A"] = {}
graph["B"] = {}
graph["C"] = {}
graph["D"] = {}
graph["E"] = {}
graph["F"] = {}
#node connections
graph["A"]["B"] = 5
graph["A"]["C"] = 3
graph["A"]["D"] = 3
graph["B"]["A"] = 5
graph["B"]["F"] = 2
graph["C"]["A"] = 3
graph["C"]["F"] = 3
graph["C"]["E"] = 3
graph["D"]["A"] = 3
graph["D"]["E"] = 2
graph["E"]["C"] = 3
graph["E"]["D"] = 2
graph["F"]["B"] = 2
graph["F"]["C"] = 3
graphList = []
for v in graph:
graphList.append(v)
graphString = ", ".join(graphList)
print("The nodes are", graphString)
inputLoop = True
while inputLoop == True:
startNode = input("Please enter the start node: \n").upper()
targetNode = input("Please enter the target node: \n").upper()
if startNode in graph and targetNode in graph:
print("\n")
target = targetNode
inputLoop = False
else:
print("\nPlease enter a nodes in the graph")
#Start the clock!
startTime = time.time()
#use dijkstras
parents, costs, processed = dijkstra(graph, startNode) # Node must be in graph
#Stop the clock!
endTime = time.time() - startTime
#give answer
travelList = [target]
parent = parents[target]
if parent == 0:
pass
else:
travelList.insert(0, parent)
while parent != 0:
parent = parents[parent]
if parent == 0:
pass
else:
travelList.insert(0, parent)
#formatting the answers
print("The path of "+", ".join(travelList)+" was taken")
print("With a total cost of "+str(costs[target]))
print("The nodes were processed in the order "+", ".join(parents))
print("The program took", endTime , "second/s")
mainLoop = True
print("----------- Welcome To Dijsktra's Algorithm -----------")
while mainLoop == True:
main()
print("\n")
userSelect = input("Please press enter to continue, or E to exit")
if userSelect == "e" or userSelect == "E":
mainLoop = False
| UTF-8 | Python | false | false | 4,533 | py | 1,523 | Dijsktra's.py | 1,515 | 0.52195 | 0.516214 | 0 | 156 | 26.608974 | 82 |
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