repo_name stringclasses 400
values | branch_name stringclasses 4
values | file_content stringlengths 16 72.5k | language stringclasses 1
value | num_lines int64 1 1.66k | avg_line_length float64 6 85 | max_line_length int64 9 949 | path stringlengths 5 103 | alphanum_fraction float64 0.29 0.89 | alpha_fraction float64 0.27 0.89 |
|---|---|---|---|---|---|---|---|---|---|
leopesi/pool_budget | refs/heads/master | # Generated by Django 3.0.3 on 2020-05-04 18:29
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0008_remove_precificacaomodel_custo'),
]
operations = [
migrations.DeleteModel(
name='PrecificacaoModel',
)... | Python | 31 | 26.032259 | 61 | /projeto/dimensoes/migrations/0009_auto_20200504_1529.py | 0.570406 | 0.538186 |
leopesi/pool_budget | refs/heads/master | # Generated by Django 3.0.3 on 2020-06-04 18:56
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0013_remove_dimensaomodel_profundidade_media'),
]
operations = [
migrations.AddField(
model_name='dimensaomodel',
... | Python | 18 | 23.277779 | 70 | /projeto/dimensoes/migrations/0014_dimensaomodel_profundidade_media.py | 0.622426 | 0.572082 |
leopesi/pool_budget | refs/heads/master | # Generated by Django 3.0.3 on 2020-05-11 18:21
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0009_auto_20200504_1529'),
]
operations = [
migrations.AlterField(
model_name='dimensaomodel',
name='co... | Python | 48 | 26.604166 | 49 | /projeto/dimensoes/migrations/0010_auto_20200511_1521.py | 0.535849 | 0.510943 |
leopesi/pool_budget | refs/heads/master | # Generated by Django 3.0.3 on 2020-06-11 21:59
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0016_auto_20200611_1852'),
]
operations = [
migrations.RenameField(
model_name='clientemodel',
old_name='numero... | Python | 18 | 20.111111 | 49 | /projeto/dimensoes/migrations/0017_auto_20200611_1859.py | 0.584211 | 0.502632 |
leopesi/pool_budget | refs/heads/master | # Generated by Django 3.0.3 on 2020-06-04 18:33
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0012_auto_20200603_1916'),
]
operations = [
migrations.RemoveField(
model_name='dimensaomodel',
name='profundid... | Python | 17 | 19.529411 | 49 | /projeto/dimensoes/migrations/0013_remove_dimensaomodel_profundidade_media.py | 0.601719 | 0.512894 |
leopesi/pool_budget | refs/heads/master | # Generated by Django 3.0.3 on 2020-03-16 18:43
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='ClienteModel',
fields=[
('id', models.AutoF... | Python | 67 | 55.805969 | 230 | /projeto/dimensoes/migrations/0001_initial.py | 0.555439 | 0.527588 |
leopesi/pool_budget | refs/heads/master | # Generated by Django 3.0.3 on 2020-03-17 12:33
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0003_remove_dimensaomodel_data'),
]
operations = [
migrations.AlterField(
model_name='dimensaomodel',
n... | Python | 38 | 28.631578 | 61 | /projeto/dimensoes/migrations/0004_auto_20200317_0933.py | 0.568384 | 0.538188 |
leopesi/pool_budget | refs/heads/master | # Generated by Django 3.0.3 on 2020-05-16 18:18
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0010_auto_20200511_1521'),
]
operations = [
migrations.AlterField(
model_name='clientemodel',
name='tel... | Python | 18 | 21.833334 | 65 | /projeto/dimensoes/migrations/0011_auto_20200516_1518.py | 0.603406 | 0.523114 |
leopesi/pool_budget | refs/heads/master | # Generated by Django 3.0.3 on 2020-03-18 21:31
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0005_dimensaomodel_data'),
]
operations = [
migrations.AlterField(
model_name='dimensaomodel',
name='pr... | Python | 18 | 22.222221 | 61 | /projeto/dimensoes/migrations/0006_auto_20200318_1831.py | 0.610048 | 0.559809 |
leopesi/pool_budget | refs/heads/master | # Generated by Django 3.0.3 on 2020-04-29 20:30
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0007_auto_20200408_1540'),
]
operations = [
migrations.RemoveField(
model_name='precificacaomodel',
name='custo... | Python | 17 | 19 | 49 | /projeto/dimensoes/migrations/0008_remove_precificacaomodel_custo.py | 0.594118 | 0.502941 |
leopesi/pool_budget | refs/heads/master | # Generated by Django 3.0.3 on 2020-03-16 21:38
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0002_auto_20200316_1609'),
]
operations = [
migrations.RemoveField(
model_name='dimensaomodel',
name='data',
... | Python | 17 | 18.705883 | 49 | /projeto/dimensoes/migrations/0003_remove_dimensaomodel_data.py | 0.58806 | 0.495522 |
leopesi/pool_budget | refs/heads/master | # Generated by Django 3.0.3 on 2020-06-11 21:52
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0015_auto_20200604_1710'),
]
operations = [
migrations.RemoveField(
model_name='dimensaomodel',
name='s... | Python | 22 | 22.5 | 61 | /projeto/dimensoes/migrations/0016_auto_20200611_1852.py | 0.576402 | 0.514507 |
leopesi/pool_budget | refs/heads/master | # Generated by Django 3.0.3 on 2020-04-08 18:40
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0006_auto_20200318_1831'),
]
operations = [
migrations.CreateModel(
name='PrecificacaoModel',
fields=[
... | Python | 157 | 44.923569 | 116 | /projeto/dimensoes/migrations/0007_auto_20200408_1540.py | 0.561165 | 0.533148 |
leopesi/pool_budget | refs/heads/master | # Generated by Django 3.0.3 on 2020-06-04 20:10
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0014_dimensaomodel_profundidade_media'),
]
operations = [
migrations.RemoveField(
model_name='dimensaomodel',
n... | Python | 53 | 25.113207 | 63 | /projeto/dimensoes/migrations/0015_auto_20200604_1710.py | 0.524566 | 0.509393 |
leopesi/pool_budget | refs/heads/master | # Generated by Django 3.0.3 on 2020-06-18 18:20
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0018_auto_20200611_1905'),
]
operations = [
migrations.AlterField(
model_name='clientemodel',
name='num... | Python | 18 | 21.833334 | 62 | /projeto/dimensoes/migrations/0019_auto_20200618_1520.py | 0.600973 | 0.520681 |
huzhaoyangcode/myAllWorkUsefullCode | refs/heads/master | #!/usr/bin/env python3
import xml.etree.ElementTree as ET
import os
import copy
import json
#读取序列文件，得到dir处理序列
with open('dirQueue.txt', 'r') as queueFile:
handleList = queueFile.readlines()
#设置用来做test的图片开始位置和结束位置
testStartId = 1000
testEndId = 6000
strJson = "{\"images\": "
strTestJson = "{\"images\": "
# prin... | Python | 173 | 37.878613 | 335 | /xmlToJson/xmlToJson_new_12_24.py | 0.597532 | 0.586084 |
huzhaoyangcode/myAllWorkUsefullCode | refs/heads/master | #!/usr/bin/env python
import threading
import time
import os
import sys
import signal
#Write First thread of creating raw file
class ThreadCreateFile (threading.Thread):
def __init__(self, threadID, name, counter):
threading.Thread.__init__(self)
self.threadID = threadID
self.name = name
... | Python | 171 | 35.695908 | 166 | /TwoThread/TwoThread.py | 0.599841 | 0.580398 |
jettaponB/Practice | refs/heads/main | import tkinter as tk
def show_output():
number = int(number_input.get())
if number == 0:
output_label.configure(text='ผิด')
return
output = ''
for i in range(1, 13):
output += str(number) + ' * ' + str(i)
output += ' = ' + str(number * i) + '\n'
output_label.confi... | Python | 38 | 19.473684 | 56 | /Test07.py | 0.633205 | 0.610039 |
jettaponB/Practice | refs/heads/main | class Tank:
def __init__(self, name, ammo) -> None:
self.name = name
self.ammo = ammo
first_tank = Tank('Serie1', 3)
print(first_tank.name)
second_tank = Tank('Serie2', 5)
print(second_tank.name) | Python | 10 | 20.9 | 43 | /Test13.py | 0.614679 | 0.59633 |
jettaponB/Practice | refs/heads/main | class Tank:
def __init__(self, name, ammo) -> None:
self.name = name
self.ammo = ammo
def add_ammo(self, ammo):
if self.ammo + ammo <= 10:
self.ammo += ammo
def fire_ammo(self):
if self.ammo > 0:
self.ammo -= 1 | Python | 10 | 26.9 | 43 | /class_tank.py | 0.492806 | 0.478417 |
jettaponB/Practice | refs/heads/main | # message = 'วัชราวลี'
# result = len(message)
# print(result)
# message = 'วัชราวลี'
# result = 'วัช' in message
# print(result)
# message = '0982612325'
# result = message.isdigit()
# print(result)
# message = 'Just Python'
# result = message.replace('Python', 'Rabbit')
# print(result)
message = 'กระต่าย, กระรอก,... | Python | 21 | 19.095238 | 46 | /Test12.py | 0.656398 | 0.632701 |
jettaponB/Practice | refs/heads/main | # quests = ['ปลูกต้นมะม่วง', 'ล้างปลา', 'เผาถ่าน']
# if 'ล้างปลา' in quests:
# print('ทำงานเสร็จ')
#----------------------------------------------------
# quests = ['ปลูกต้นมะม่วง', 'ล้างปลา', 'เผาถ่าน']
# max_quests = 5
# if len(quests) < max_quests:
# quests.append('จับปลาดุก')
# print(quests)
#---------... | Python | 19 | 32.210526 | 53 | /Test10.py | 0.419304 | 0.416139 |
jettaponB/Practice | refs/heads/main | def get_circle_area(radius):
return 22 / 7 * (radius ** 2)
def get_triangle_area(width, heigth):
return 1 / 2 * width * heigth
def get_rectangle_area(width, heigth):
return width * heigth | Python | 8 | 24.25 | 38 | /shape.py | 0.661692 | 0.631841 |
jettaponB/Practice | refs/heads/main | import class_tank as CT
first_tank = CT.Tank('Serie1', 3)
first_tank.fire_ammo()
print(first_tank.ammo)
first_tank.fire_ammo()
first_tank.fire_ammo()
print(first_tank.ammo)
first_tank.add_ammo(4)
print(first_tank.ammo)
| Python | 12 | 17.583334 | 34 | /Test14.py | 0.730942 | 0.717489 |
jettaponB/Practice | refs/heads/main | import tkinter as tk
def show_output():
number = int(input_number.get())
output = ''
for i in range(1, 13):
output += str(number) + ' * ' + str(i) + ' = ' + str(number * i) + '\n'
output_label.configure(text=output)
window = tk.Tk()
window.title('โปรแกรมคำนวนสูตรคูณ')
window.minsize(widt... | Python | 28 | 22.428572 | 79 | /test09.py | 0.662595 | 0.648855 |
jettaponB/Practice | refs/heads/main | score = 55
if score >= 80:
print('Grade A')
print('dafdaf')
elif score >= 70:
print('Grade B')
elif score >= 60:
print('Grade C')
else:
print('Grade F')
| Python | 11 | 14.818182 | 20 | /Test02.py | 0.557471 | 0.511494 |
jettaponB/Practice | refs/heads/main | # number = 1
# double = number * 2
# print(number)
# for i in range(1, 7):
# double = i * 2
# print(double)
# for i in range(1, 7):
# if i % 3 == 0:
# continue
# print(i)
for i in range(1, 7):
if i % 3 == 0:
break
print(i) | Python | 17 | 14.647058 | 23 | /Test03.py | 0.467925 | 0.418868 |
jettaponB/Practice | refs/heads/main | # x = '4.5'
# y = str(12)
# z = x + y
# print(z)
# final_score = 15
#
# age = 25 # ตัวเลขจำนวนเต็ม (integer)
# weight = 66.6 # ตัวเลขทศนิยม (Float)
# first_name = 'ศักรินทร์' # ข้อความ (String)
# has_notebook = True # Boolean
x = 5
y = 2
a1 = x + y # 7
a2 = x - y # 3
a3 = x *... | Python | 27 | 16.629629 | 53 | /Test01.py | 0.395789 | 0.32 |
jettaponB/Practice | refs/heads/main | import tkinter as tk
def set_message():
text = text_input.get()
title_label.configure(text=text)
window = tk.Tk()
window.title('Desktop Application')
window.minsize(width=300, height=400)
title_label = tk.Label(master=window, text='กรุณาระบุข้อความ')
title_label.pack()
text_input = tk.Entry(master=window)
t... | Python | 20 | 21.15 | 68 | /Test08.py | 0.714286 | 0.700893 |
jettaponB/Practice | refs/heads/main | # def get_box_area(width, length, height):
# box_area = width * length * height
# print(box_area)
#
# get_box_area(4, 4, 2)
# get_box_area(width=1, length=1, height=2)
def get_box_area(width, length, height):
if width < 0 or length < 0 or height < 0:
return 0
box_area = width * length * heig... | Python | 20 | 21.1 | 48 | /Test04.py | 0.619048 | 0.573696 |
jettaponB/Practice | refs/heads/main | book = {
'name': 'C++',
'price': '299',
'page': '414'
}
# #ตัวแปลทีละตัว ... ตัวแปรจะเยอะเกิน
# book_name = 'C++'
# book_price = 299
# book_page = 414
# #เก็บใน List ... ลืมว่าข้อมูลไหนอยู่ที่ index ไหน
# book_data = ['C++', 299, 414]
#book['place'] = 'MU Salaya'
book.pop('price')
print(book) | Python | 18 | 16.222221 | 51 | /Test11.py | 0.530744 | 0.472492 |
jettaponB/Practice | refs/heads/main | import shape as sh
circle = sh.get_circle_area(10)
print(circle)
triangle = sh.get_triangle_area(width=6, heigth=7)
print(triangle) | Python | 7 | 18.142857 | 50 | /Test05.py | 0.75188 | 0.721804 |
gitclub-data/Alarm_clock | refs/heads/master | from tkinter import *
import tkinter.filedialog as fd
root = Tk()
def browsefunc():
filename = fd.askopenfilename()
pathlabel.config(text=filename)
browsebutton = Button(root, text="Browse", command=browsefunc)
browsebutton.pack()
pathlabel = Label(root)
pathlabel.pack()
root.mainloop() | Python | 15 | 19 | 62 | /test.py | 0.745819 | 0.745819 |
gitclub-data/Alarm_clock | refs/heads/master | import tkinter as tk
from tkinter import ttk
class Alarm():
def __init__(self):
#Setting The Whole Window
self.root=tk.Tk()
self.root.geometry("852x552+250+80")
self.root.minsize("852","552")
self.root.maxsize("852","552")
self.root.title("Alarm Clock")
Icon ... | Python | 89 | 43.033707 | 130 | /Alarm.py | 0.604645 | 0.54441 |
manatbay/IxNetwork | refs/heads/master |
# PLEASE READ DISCLAIMER
#
# This is a sample script for demo and reference purpose only.
# It is subject to change for content updates without warning.
#
# REQUIREMENTS
# - Python2.7 - Python 3.6
# - Python module: requests
#
# DESCRIPTION
# Capturing packets. Make sure traffic is running in continuou... | Python | 87 | 37.827587 | 119 | /RestApi/Python/SampleScripts/packetCapture.py | 0.696952 | 0.682154 |
martkins/images_exif_viewer | refs/heads/master | from kivy.uix.button import Button
from kivy.uix.label import Label
from kivy.lang import Builder
from kivy.event import EventDispatcher
class LabelModel(Label):
def __init__(self, **kwargs):
super(Label, self).__init__(**kwargs)
| Python | 9 | 26.111111 | 45 | /labelmodel.py | 0.712551 | 0.712551 |
martkins/images_exif_viewer | refs/heads/master | from kivy.uix.image import Image
from kivy.properties import NumericProperty
class ImageModel(Image):
ang = NumericProperty()
def __init__(self, **kwargs):
super(Image, self).__init__(**kwargs)
def rotate_right(self):
self.ang += 90
def rotate_left(self):
self.ang -= 90
... | Python | 19 | 18.263159 | 45 | /imagemodel.py | 0.60929 | 0.595628 |
martkins/images_exif_viewer | refs/heads/master | from kivy.app import App
from kivy.uix.image import Image
from kivy.properties import ObjectProperty
from kivy.uix.listview import ListView, SimpleListAdapter
from kivy.uix.label import Label
from imagemodel import ImageModel
from kivy.uix.button import Button
from kivy.factory import Factory
from buttonmodel import Bu... | Python | 94 | 32.936169 | 85 | /main.py | 0.614734 | 0.612853 |
martkins/images_exif_viewer | refs/heads/master | import exifread
from kivy.uix.button import Button
from kivy.lang import Builder
from tkinter.filedialog import askopenfilenames
from kivy.properties import DictProperty, ListProperty, NumericProperty
import webbrowser
from tkinter import Tk
root = Tk()
root.withdraw()
Builder.load_file('./actionbutton.kv')
def _con... | Python | 103 | 31.019417 | 113 | /buttonmodel.py | 0.552624 | 0.542918 |
Peroxidess/Ablation-Time-Prediction-Model | refs/heads/main | # Copyright (c) 2017 - 2019 Uber Technologies, Inc.
#
# Licensed under the Uber Non-Commercial License (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at the root directory of this project.
#
# See the License for the specific language governing... | Python | 197 | 40.659897 | 103 | /Regression/src/learn_rewieght/reweight.py | 0.575241 | 0.555136 |
Peroxidess/Ablation-Time-Prediction-Model | refs/heads/main | from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
from sklearn.preprocessing import LabelEncoder, MinMaxScaler, StandardScaler
import pandas as pd
import numpy as np
from preprocess import plot_tabel
def get_dataset_(nor, train_data, test_data, clean_ratio, test_retio, se... | Python | 112 | 44.723213 | 121 | /Regression/src/preprocess/get_dataset.py | 0.60738 | 0.601523 |
Peroxidess/Ablation-Time-Prediction-Model | refs/heads/main | # Copyright (c) 2017 - 2019 Uber Technologies, Inc.
#
# Licensed under the Uber Non-Commercial License (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at the root directory of this project.
#
# See the License for the specific language governing... | Python | 441 | 33.253967 | 100 | /Regression/src/learn_rewieght/mnist_train.py | 0.557593 | 0.53343 |
Peroxidess/Ablation-Time-Prediction-Model | refs/heads/main | import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import math
plt.rc('font', family='Times New Roman')
font_size = 16
def plot_metric_df(history_list, task_name, val_flag='test_'):
if 'relapse_risk' in task_name:
metric_list = ['loss', 'f1']
else:
met... | Python | 126 | 37.317459 | 112 | /Regression/src/model/history_.py | 0.583057 | 0.570215 |
Peroxidess/Ablation-Time-Prediction-Model | refs/heads/main | # Copyright (c) 2017 - 2019 Uber Technologies, Inc.
#
# Licensed under the Uber Non-Commercial License (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at the root directory of this project.
#
# See the License for the specific language governing... | Python | 503 | 37.608349 | 120 | /Regression/src/learn_weight_main.py | 0.561586 | 0.542482 |
Peroxidess/Ablation-Time-Prediction-Model | refs/heads/main | import numpy as np
import pandas as pd
from sklearn.metrics import mean_absolute_error, mean_squared_error, \
confusion_matrix, precision_score, recall_score, f1_score, r2_score, accuracy_score
from sklearn.preprocessing import MinMaxScaler
def evaluate_classification(model, train_sets, train_label, val_sets, val... | Python | 83 | 51.385544 | 104 | /Regression/src/model/evaluate.py | 0.633165 | 0.612925 |
Peroxidess/Ablation-Time-Prediction-Model | refs/heads/main | import pandas as pd
import numpy as np
from tqdm import tqdm
import six
import tensorflow as tf
from keras import losses
from keras import backend as K
from keras import optimizers
from keras.models import Sequential
from keras.layers import Dense
from sklearn.preprocessing import LabelEncoder, MinMaxScaler
from sklear... | Python | 157 | 45.305733 | 143 | /Regression/src/useless/ave_logsit_baseline.py | 0.605777 | 0.588996 |
Peroxidess/Ablation-Time-Prediction-Model | refs/heads/main | import copy
import pandas as pd
import matplotlib.pyplot as plt
from model.history_ import plot_history_df, plot_metric_df
import numpy as np
from scipy.stats import ttest_ind, levene
from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score
def mape(y_true, y_pred):
return np.mean(np.abs((y_t... | Python | 126 | 46.674603 | 127 | /Regression/src/preprocess/plot_tabel.py | 0.554779 | 0.531136 |
Peroxidess/Ablation-Time-Prediction-Model | refs/heads/main | #coding=gb18030
import numpy as np
import pandas as pd
def load_data_(datasets, task_name='', seed=2020):
if datasets == 'winequality_white':
data_path = '../DataSet/wine/{}.csv'.format(datasets)
data = pd.read_csv(data_path)
data.rename(columns={'quality': 'label'}, inplace=True)
... | Python | 61 | 48.360657 | 120 | /Regression/src/preprocess/load_data.py | 0.61541 | 0.582863 |
Peroxidess/Ablation-Time-Prediction-Model | refs/heads/main | import pandas as pd
import numpy as np
from tqdm import tqdm
import six
import tensorflow as tf
from keras import losses
from keras import backend as K
from keras import optimizers
from keras.models import Sequential, Model
from keras.callbacks import EarlyStopping
from keras.layers import Input, Dense, Multiply, Activ... | Python | 216 | 37.666668 | 118 | /Regression/src/useless/keras_att.py | 0.617816 | 0.601173 |
Peroxidess/Ablation-Time-Prediction-Model | refs/heads/main | import copy
import pandas as pd
import numpy as np
import lightgbm as lgb
from sklearn.linear_model import RidgeClassifierCV, LogisticRegressionCV, RidgeCV, LassoCV, LinearRegression
from keras.models import load_model
from keras import backend as K
from keras.optimizers import Adam, RMSprop, SGD
from keras.callbacks i... | Python | 213 | 48.685448 | 119 | /Regression/src/model/training_.py | 0.534159 | 0.517245 |
Peroxidess/Ablation-Time-Prediction-Model | refs/heads/main | from model.history_ import plot_metric_df
import pandas as pd
import matplotlib.pyplot as plt
import os
xx = os.getcwd()
path_root = '../report/result/'
task_name = 'ablation_time_all'
metric_list = []
metric_list_dir = ['metric_ablation_time_enh_10nrun_1Fold.csv',
'metric_ablation_time_vanilla_10nrun_1Fold.csv',
'me... | Python | 22 | 25.681818 | 63 | /Regression/src/eval.py | 0.71891 | 0.698467 |
Peroxidess/Ablation-Time-Prediction-Model | refs/heads/main | import tensorflow as tf
import numpy as np
import pandas as pd
from keras import backend as K
from keras import regularizers, activations
from keras.layers import Dense, Input, Add, Concatenate, Dropout, \
BatchNormalization, Activation, Multiply, Embedding, Layer, GlobalAveragePooling1D
from keras.models import Mo... | Python | 474 | 38.405064 | 118 | /Regression/src/model/bulid_model.py | 0.567864 | 0.543931 |
Peroxidess/Ablation-Time-Prediction-Model | refs/heads/main | import numpy as np
import pandas as pd
import six
from tqdm import tqdm
from sklearn.model_selection import KFold
import matplotlib.pyplot as plt
from preprocess.load_data import load_data_
from preprocess.get_dataset import get_dataset_, data_preprocessing, anomaly_dectection
from model.training_ import training_model... | Python | 103 | 54.815533 | 123 | /Regression/src/main.py | 0.567229 | 0.558184 |
deepikaasharma/string-concat-for-numbers | refs/heads/master | first_num = '123'
second_num = '456'
third_num = '789'
# Replace `None` with your code
final_num = (first_num+second_num+third_num)
print(int(final_num)) | Python | 7 | 21.142857 | 44 | /main.py | 0.688312 | 0.62987 |
islamaf/Software-development-exercise | refs/heads/main | import os
from tkinter import Tk, ttk, filedialog
import pandas as pd
from win32 import win32api
root = Tk()
root.title('Ahram Exam')
root.resizable(True, True)
root.frame_header = ttk.Frame()
root.geometry("350x250")
root.eval('tk::PlaceWindow . center')
ttk.Label(root.frame_header, text='Browse file to open:', sty... | Python | 62 | 30.161291 | 122 | /gui_main.py | 0.633868 | 0.610564 |
CENSOREDd/test_fk | refs/heads/master | #!/usr/bin/python3
from time import sleep
print("what the fuck???")
if __name__ == "__main__":
print("here is python code!!!")
print("Executing code...")
sleep(2)
| Python | 10 | 16.799999 | 35 | /fk.py | 0.578652 | 0.567416 |
CENSOREDd/test_fk | refs/heads/master | #!/usr/bin/python3
import fk
print("here is test")
| Python | 5 | 9.6 | 21 | /test.py | 0.679245 | 0.660377 |
hui98/opencv | refs/heads/master | import cv2
import numpy as np
import random
from math import *
# import an image
class image:
def __init__(self,na):
self.dir='/home/hui/Pictures/'
# self.name=raw_input('please input the picture name')
self.name=na
self.mode=cv2.IMREAD_COLOR
self.im=cv2.imread(self.dir+self.n... | Python | 173 | 25.757225 | 99 | /opencvtest.py | 0.568932 | 0.514995 |
rodelrod/pomodoro-report | refs/heads/master | #!/usr/bin/env python
import unittest
from notebook_parser import *
import os
import errno
from datetime import datetime
def mkdir_p(path):
try:
os.makedirs(path)
except OSError as exc:
if exc.errno == errno.EEXIST:
pass
else:
raise
class TestParser(unittest... | Python | 130 | 33.607693 | 66 | /test_notebook_parser.py | 0.498778 | 0.454545 |
rodelrod/pomodoro-report | refs/heads/master | #!/usr/bin/env python
import re
import os
NOTEBOOK_PATH = '/home/rrodrigues/.rednotebook/data'
class EmptyDayException(Exception):
"""No info was entered for this date."""
class Parser(object):
"""Parses RedNotebook monthly files.
This is a very basic parser used to extract Pomodoro referen... | Python | 94 | 31.957447 | 80 | /notebook_parser.py | 0.525806 | 0.525484 |
shashi/phosphene | refs/heads/master | #
# This script plays an mp3 file and communicates via serial.Serial
# with devices in the Technites psychedelic room to visualize the
# music on them.
#
# It talks to 4 devices
# WaterFall -- tubes with LEDs and flying stuff fanned to music
# DiscoBall -- 8 60 watt bulbs wrapped in colored paper
# LEDWall -- a... | Python | 115 | 23.347826 | 77 | /src/apps/psychroom.py | 0.664286 | 0.646786 |
shashi/phosphene | refs/heads/master | # Functions to help you lift and fold
from .signal import *
from dsp import *
import numpy
import pdb
import math
def setup(signal, horizon=576):
# Note of awesome: this only sets up dependencies,
# things absolutely necessary are evaluated.
signal.fft = lift(lambda s: \
fft(s.A[-horizon/2:hor... | Python | 111 | 30.972973 | 74 | /src/phosphene/signalutil.py | 0.5255 | 0.506622 |
shashi/phosphene | refs/heads/master | import os
from setuptools import setup
def read(fname):
return open(os.path.join(os.path.dirname(__file__), fname)).read()
setup(
name = "phosphene",
version = "0.0.1",
author = "Shashi Gowda",
author_email = "shashigowda91@gmail.com",
description = ("A library for music processing and visuali... | Python | 23 | 28.347826 | 71 | /src/setup.py | 0.611852 | 0.605926 |
shashi/phosphene | refs/heads/master | import serial
import numpy
import math
from device import Device
from cubelib import emulator
from cubelib import mywireframe as wireframe
from animations import *
import time
import threading
# A class for the cube
class Cube(Device):
def __init__(self, port, dimension=10, emulator=False):
Device.__init__... | Python | 113 | 27.212389 | 66 | /src/apps/devices/cube.py | 0.530574 | 0.500784 |
shashi/phosphene | refs/heads/master | import scipy
import numpy
from util import *
def fftIdx(Fs, Hz, n):
assert(Hz <= Fs / 2);
return round(Fs / n * Hz)
memFftIdx = memoize(fftIdx)
def getNotes():
return [0] \
+ [16.35 * pow(2, i/12.0) + 1 for i in range(0, 101)] \
+ [11050, 22100]
def group(n, fft, grouping=lambda i:... | Python | 75 | 26.146667 | 81 | /src/phosphene/dsp.py | 0.556483 | 0.52554 |
shashi/phosphene | refs/heads/master | import os
from hashlib import sha1
import scipy.io.wavfile as wav
import pygame.mixer
from pygame.sndarray import make_sound
# Set mixer defaults
pygame.mixer.pre_init(44100, 16, 2, 4096)
__all__ = ["read", "makeSound"]
def digest(string):
return sha1(string).hexdigest()
def read(fname):
""" Reads an audio ... | Python | 44 | 26.704546 | 77 | /src/phosphene/audio.py | 0.654098 | 0.633607 |
shashi/phosphene | refs/heads/master | import numpy
import random
import time
from cubelib import mywireframe
from cubelib import emulator
# TODO:
# shiftPlane(axis, plane, delta)
# moves the plane along the axis by delta steps, if it exceeds dimensions, just clear it out, don't rotate.
# swapPlanes(axis1, plane1, axis2, plane2)
# rain should set random... | Python | 992 | 26.765121 | 138 | /src/apps/devices/animations.py | 0.493211 | 0.440096 |
shashi/phosphene | refs/heads/master | import os, sys
dirname = os.path.dirname
here = os.path.abspath(__file__)
parentdir = dirname(dirname(here))
sys.path.append(parentdir)
| Python | 6 | 21.833334 | 34 | /src/apps/pathsetup.py | 0.737226 | 0.737226 |
shashi/phosphene | refs/heads/master | import numpy
from threading import Thread # this is for the repl
__all__ = ['memoize', 'memoizeBy', 'numpymap', 'indexable', 'reverse']
# Helper functions
def memoize(f, key=None):
mem = {}
def g(*args):
k = str(args)
if mem.has_key(k):
return mem[k]
else:
r = f(... | Python | 63 | 26.206348 | 79 | /src/phosphene/util.py | 0.497376 | 0.493294 |
shashi/phosphene | refs/heads/master | from devices.cubelib import emulator
from devices.cubelib import mywireframe as wireframe
from devices.animations import *
pv = emulator.ProjectionViewer(640,480)
wf = wireframe.Wireframe()
def cubeProcess(cube, signal, count):
pv.createCube(wf)
start = (0, 0, 0)
point = (0,0)
#planeBounce(cube,(count... | Python | 23 | 27.304348 | 52 | /src/apps/cube.py | 0.680492 | 0.645161 |
shashi/phosphene | refs/heads/master | import device
from phosphene.signal import *
from phosphene.signalutil import *
from phosphene.graphs import *
class LEDWall(device.Device):
def __init__(self, port):
device.Device.__init__(self, "LEDWall", port)
def setupSignal(self, signal):
CHANNELS = 6
val = lambda s: [max(0, scip... | Python | 24 | 34.708332 | 112 | /src/apps/devices/ledwall.py | 0.614936 | 0.585764 |
shashi/phosphene | refs/heads/master | #!/bin/env python
#using the wireframe module downloaded from http://www.petercollingridge.co.uk/
import mywireframe as wireframe
import pygame
from pygame import display
from pygame.draw import *
import time
import numpy
key_to_function = {
pygame.K_LEFT: (lambda x: x.translateAll('x', -10)),
pygame.K_RIGHT... | Python | 164 | 33.298782 | 254 | /src/apps/devices/cubelib/emulator.py | 0.594172 | 0.559879 |
shashi/phosphene | refs/heads/master | __all__ = ["emulator", "mywireframe"]
| Python | 1 | 37 | 37 | /src/apps/devices/cubelib/__init__.py | 0.578947 | 0.578947 |
shashi/phosphene | refs/heads/master | __all__ = ["discoball", "cube", "waterfall"]
| Python | 1 | 44 | 44 | /src/apps/devices/__init__.py | 0.555556 | 0.555556 |
shashi/phosphene | refs/heads/master | import time
import numpy
from util import indexable
__all__ = [
'Signal',
'lift',
'foldp',
'perceive'
]
class lift:
""" Annotate an object as lifted """
def __init__(self, f, t_indexable=None):
self.f = f
if hasattr(f, '__call__'):
self._type = 'lambda'
e... | Python | 169 | 26.035503 | 70 | /src/phosphene/signal.py | 0.525717 | 0.521777 |
shashi/phosphene | refs/heads/master | import pdb
import scipy
import numpy
import pygame
from pygame import display
from pygame.draw import *
from pygame import Color
import math
def barGraph(data):
"""
drawing contains (x, y, width, height)
"""
def f(surface, rectangle):
x0, y0, W, H = rectangle
try:
l = l... | Python | 85 | 24.6 | 76 | /src/phosphene/graphs.py | 0.413603 | 0.377298 |
shashi/phosphene | refs/heads/master | import device
from phosphene.signal import *
from phosphene.signalutil import *
from phosphene.graphs import *
class DiscoBall(device.Device):
def __init__(self, port):
device.Device.__init__(self, "DiscoBall", port)
def setupSignal(self, signal):
signal.discoball = lift(lambda s: numpymap(lam... | Python | 19 | 31.947369 | 120 | /src/apps/devices/discoball.py | 0.662939 | 0.638978 |
shashi/phosphene | refs/heads/master | import device
from phosphene.signal import *
import scipy, numpy
from phosphene.graphs import barGraph
class Waterfall(device.Device):
def __init__(self, port):
device.Device.__init__(self, "Waterfall", port)
def setupSignal(self, signal):
def waterfall(s):
lights = [s.avg8[i] * 15... | Python | 26 | 28.5 | 65 | /src/apps/devices/waterfall.py | 0.601043 | 0.58279 |
shashi/phosphene | refs/heads/master | import serial
import numpy
from threading import Thread
class Device:
def __init__(self, name, port):
self.array = []
try:
self.port = serial.Serial(port)
self.isConnected = True
print "Connected to", name
except Exception as e:
self.port = No... | Python | 42 | 26.285715 | 63 | /src/apps/devices/device.py | 0.584132 | 0.579773 |
shashi/phosphene | refs/heads/master | __all__ = ["audio", "dsp", "signal", "graphs", "util"]
| Python | 1 | 54 | 54 | /src/phosphene/__init__.py | 0.490909 | 0.490909 |
shashi/phosphene | refs/heads/master | import sys
import pdb
import pygame
from pygame import display
from pygame.draw import *
import scipy
import time
from phosphene import audio, util, signalutil, signal
from phosphene.graphs import barGraph, boopGraph, graphsGraphs
from threading import Thread
if len(sys.argv) < 2:
print "Usage: %s file.mp3" % sy... | Python | 81 | 26.234568 | 77 | /src/demo.py | 0.662738 | 0.644152 |
TaegamJung/mannam | refs/heads/master | from django.shortcuts import render
# View에 Model(Post 게시글) 가져오기
from .models import Post
from django.views.generic.base import TemplateView
from django.views.generic.edit import CreateView
from django.contrib.auth.forms import UserCreationForm
from django.urls import reverse_lazy
from django.views.generic.edit imp... | Python | 63 | 29.619047 | 115 | /main/views.py | 0.700828 | 0.700828 |
hjtree0825/stroke_network_ctmc_simulations | refs/heads/main | from stroke_functions import *
# Initialize
T = 10000
repl_num = 100
service_rate_h = 1./7
service_rate_i = 1./3
Mean1_psc_cap = []
STD1_psc_cap = []
Mean2_psc_cap = []
STD2_psc_cap = []
Mean3_psc_cap = []
STD3_psc_cap = []
Mean4_psc_cap = []
STD4_psc_cap = []
Mean5_psc_cap = []
STD5_psc_cap = []
... | Python | 76 | 33.039474 | 90 | /stroke_expanded_add_capacity.py | 0.596998 | 0.532458 |
hjtree0825/stroke_network_ctmc_simulations | refs/heads/main | from stroke_source import *
g = r.Random(1234)
def next_arrival(arrival_rate):
U = g.uniform(0,1)
arrival_time = -1./arrival_rate * m.log(U)
return arrival_time
def next_service(service_rate):
U = g.uniform(0,1)
service_time = -1./service_rate * m.log(U)
return service_time
... | Python | 726 | 33.280991 | 181 | /stroke_functions.py | 0.455259 | 0.423831 |
hjtree0825/stroke_network_ctmc_simulations | refs/heads/main | from stroke_functions import *
repl_num = 100
# Base case
open_file = open("base_mean.pkl", "rb")
loaded_list = pickle.load(open_file)
open_file.close()
Mean1 = loaded_list[0]
Mean2 = loaded_list[1]
Mean3 = loaded_list[2]
open_file = open("base_std.pkl", "rb")
loaded_list = pickle.load(open_file)
open_... | Python | 102 | 38.911766 | 294 | /stroke_overall_comparison.py | 0.659162 | 0.591377 |
hjtree0825/stroke_network_ctmc_simulations | refs/heads/main | from stroke_functions import *
# Initialize
T = 10000
repl_num = 10
service_rate_h = 1./7
service_rate_i = 1./3
Mean1_psc = []
STD1_psc = []
Mean2_psc = []
STD2_psc = []
Mean3_psc = []
STD3_psc = []
Mean4_psc = []
STD4_psc = []
Mean5_psc = []
STD5_psc = []
Mean6_psc = []
STD6_psc = []
cc0 = 15... | Python | 93 | 31.67742 | 82 | /stroke_expanded.py | 0.575893 | 0.505102 |
hjtree0825/stroke_network_ctmc_simulations | refs/heads/main | from stroke_functions import *
import stroke_base
import stroke_base_add_capacity
import stroke_expanded
import stroke_expanded_reduced_rate
import stroke_expanded_add_capacity
import stroke_overall_comparison
| Python | 7 | 29 | 35 | /stroke_main.py | 0.817352 | 0.817352 |
hjtree0825/stroke_network_ctmc_simulations | refs/heads/main | import numpy as np
import random as r
import math as m
import matplotlib.pyplot as plt
import pickle | Python | 5 | 19.200001 | 31 | /stroke_source.py | 0.788462 | 0.788462 |
hjtree0825/stroke_network_ctmc_simulations | refs/heads/main | from stroke_functions import *
# Initialize
T = 10000
repl_num = 100
service_rate_h = 1./7
service_rate_i = 1./3
Mean1_cap = []
STD1_cap = []
Mean2_cap = []
STD2_cap = []
Mean3_cap = []
STD3_cap = []
Mean4_cap = []
STD4_cap = []
Mean5_cap = []
STD5_cap = []
Mean6_cap = []
STD6_cap = []
cc0 = 1... | Python | 93 | 31.860214 | 82 | /stroke_base_add_capacity.py | 0.577594 | 0.506823 |
hjtree0825/stroke_network_ctmc_simulations | refs/heads/main | from stroke_functions import *
# Initialize
T = 10000
repl_num = 100
service_rate_h = 1./7
service_rate_i = 1./3
Mean1_psc_red = []
STD1_psc_red = []
Mean2_psc_red = []
STD2_psc_red = []
Mean3_psc_red = []
STD3_psc_red = []
Mean4_psc_red = []
STD4_psc_red = []
Mean5_psc_red = []
STD5_psc_red = []
... | Python | 80 | 33.299999 | 90 | /stroke_expanded_reduced_rate.py | 0.574664 | 0.508493 |
hjtree0825/stroke_network_ctmc_simulations | refs/heads/main | from stroke_functions import *
# Initialize
T = 10000
repl_num = 100
service_rate_h = 1./7
service_rate_i = 1./3
Mean1 = []
STD1 = []
Mean2 = []
STD2 = []
Mean3 = []
STD3 = []
Mean4 = []
STD4 = []
Mean5 = []
STD5 = []
Mean6 = []
STD6 = []
MeanBed1 = []
MeanBed2 = []
MeanBed3 = []
MeanBed4 =... | Python | 139 | 29.093525 | 82 | /stroke_base.py | 0.558306 | 0.490745 |
hjtree0825/stroke_network_ctmc_simulations | refs/heads/main | from stroke_functions import *
############################################################################
############################################################################
############################################################################
# Simply change the numbers in this section.
# ... | Python | 65 | 29.169231 | 76 | /stroke_customization.py | 0.557692 | 0.527613 |
MayankAgarwal/Word-ladder | refs/heads/master | ''' Implements various search mechanisms '''
from node import Node
import os
class Search(object):
''' Contains search methods '''
def __init__(self, start_state, end_state):
self.start_state = start_state
self.end_state = end_state
# Path to absolute english dictionary
dir_p... | Python | 92 | 23.293478 | 79 | /search/search.py | 0.561074 | 0.557047 |
MayankAgarwal/Word-ladder | refs/heads/master | ''' Heuristic class holds the heuristic functions used for A* search '''
def levenshtein_distance(word1, word2, i=None, j=None):
'''
Returns the levenshtein distance between the two words
Args:
1) word1: 1st word
2) word2: 2nd word
'''
if i is None:
i = len(word1)
if j... | Python | 30 | 22.433332 | 72 | /search/heuristic.py | 0.584637 | 0.534851 |
MayankAgarwal/Word-ladder | refs/heads/master | ''' Search specification for Word ladder problem '''
import os
import re
import heuristic
class Node(object):
''' Represents a node in the word ladder graph i.e. a word '''
def __init__(self, state, depth, result_state, parent=None):
self.state = state # current state
self.depth = depth ... | Python | 74 | 30.472973 | 87 | /search/node.py | 0.596228 | 0.594085 |
covertspatandemos/git_demo_2 | refs/heads/main | #!/usr/bin/env python
print('a')
print('b')
print('c')
print('w')
print('x')
print('1')
print('2')
print('3')
print('4')
print('5')
| Python | 12 | 10.083333 | 21 | /demo.py | 0.56391 | 0.526316 |
lukemadera/ml-learning | refs/heads/master | import numpy as np
import os
import random
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
import torch.autograd as autograd
# Implementing a function to make sure the models share the same gradient
# def ensure_shared_grads(model, shared_model):
# for param, shared_p... | Python | 273 | 42.153847 | 126 | /breakout_ai_a2c.py | 0.614973 | 0.598167 |
lukemadera/ml-learning | refs/heads/master | # Decimal is causing rounding errors? E.g. 1/3 is 3.333333333334 and 1/3 of 30 is 9.9999999999990
# We want to keep precision at a max, but don't increase precision for numbers that start as less.
# For example, change 33.33333333333334 to 33.33333333 and keep 1 as 1 (not 1.0000000001)
from decimal import *
# decimal... | Python | 80 | 31.225 | 98 | /number.py | 0.639255 | 0.592708 |
lukemadera/ml-learning | refs/heads/master | import gym
import logging
import numpy as np
import torch
import time
import breakout_ai_a2c as ai_a2c
import date_time
import number
from subproc_vec_env import SubprocVecEnv
from atari_wrappers import make_atari, wrap_deepmind, Monitor
def updateState(obs, state, nc):
# Do frame-stacking here instead of the Fra... | Python | 165 | 35.660606 | 117 | /breakout_run_train.py | 0.6082 | 0.592495 |
lukemadera/ml-learning | refs/heads/master | import datetime
import dateutil.parser
import dateparser
import math
import pytz
def now(tz = 'UTC', microseconds = False):
# return pytz.utc.localize(datetime.datetime.utcnow())
dt = datetime.datetime.now(pytz.timezone(tz))
if not microseconds:
dt = dt.replace(microsecond = 0)
return dt
def n... | Python | 166 | 37.945782 | 117 | /date_time.py | 0.633565 | 0.607889 |
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