text string |
|---|
<gh_stars>0
import pandas as pd
import numpy as np
import scipy.stats as ss
def cramers_v(confusion_matrix: pd.DataFrame) -> int:
"""
Calculate Cramers V statistic for categorial-categorial association.
uses correction from Bergsma and Wicher,
Journal of the Korean Statistical Society 42 (2013): 323-3... |
# uncompyle6 version 3.7.4
# Python bytecode 3.7 (3394)
# Decompiled from: Python 3.7.9 (tags/v3.7.9:13c94747c7, Aug 17 2020, 18:58:18) [MSC v.1900 64 bit (AMD64)]
# Embedded file name: T:\InGame\Gameplay\Scripts\Server\routing\object_routing\object_routing_behavior_actions.py
# Compiled at: 2020-04-14 00:05:30
# Size ... |
from scipy.io import loadmat
import numpy as np
from matplotlib import pyplot as plt
# This script prints selected frames of the stored escalator video sequence
data = loadmat('escalator_130p.mat')
X = data["X"]
dimensions = data["dimensions"][0]
framenumbers = [1806, 1813, 1820]
for framenumber in framenumbers:
... |
<filename>HCTSA Vital Proccessing/Operations.py
#© 2020 By The Rector And Visitors Of The University Of Virginia
#Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including wit... |
from pudzu.charts import *
from scipy import ndimage
import seaborn as sns
import tqdm
MAP = "maps/Europe.png"
MERGE = { 'Gibraltar': 'UK', 'Jersey': 'UK', 'Guernsey': 'UK', 'Faroe Islands': 'Denmark' }
COLOR = { 'Sea': '#E0E0FF', 'Borders': 'white', 'Land': 'white' }
PALETTE_ARGS = { 'start': 0.2, 'rot': -0.75, 'hue'... |
from subprocess import call
import sys
import os
from PIL import Image
import numpy as np
from scipy import ndimage
from subprocess import call
import sys
import os
from PIL import Image
from datetime import datetime
import cv2
from object_detection.utils import visualization_utils as vis_util
from objec... |
import os.path
import numpy as np
import astropy.io.ascii
import re
import scipy.interpolate
import pkg_resources
class MeanStars:
def __init__(self, datapath=None):
"""MeanStars implements an automated lookup and interpolation
functionality over th data from: "A Modern Mean Dwarf Stellar Color
... |
<filename>calcium_analysis/modules.py
from collections import OrderedDict
import pyqtgraph as pg
from pyqtgraph.Qt import QtGui, QtCore
#import pyqtgraph.flowchart
import pyqtgraph.parametertree as pt
import numpy as np
import scipy.ndimage as ndi
import functions as fn
class CellSelector(QtCore.QObject):
"""Se... |
#!/usr/bin/env python
import rospy
import rospkg
from transition_srv.srv import *
from transition_srv.msg import *
from std_msgs.msg import String
from baxter_core_msgs.msg import EndpointState
from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter
import numpy as np
import scipy.io
import glob
import os
... |
<reponame>microsoft/Turtlebot3-Photo-Collection<gh_stars>1-10
#!/usr/bin/env python3
from azure.cognitiveservices.vision.customvision.training import CustomVisionTrainingClient
from azure.cognitiveservices.vision.customvision.training.models import *
from msrest.authentication import ApiKeyCredentials
from turtlebot3_... |
# -*- coding: utf-8 -*-
import os
import sys
import h5py
from matplotlib import rcParams
import matplotlib.pyplot as plt
import numpy as np
from scipy.optimize import curve_fit
from presto.utils import rotate_opt
rcParams['figure.dpi'] = 108.8
if len(sys.argv) == 2:
load_filename = sys.argv[1]
print(f"Loadi... |
#!/usr/bin/python
"""Create a consensus dataset.
Create a set of images, sampling N images per attribute.
"""
import json
import time
import pickle
import sys
import csv
import argparse
import os
import os.path as osp
import shutil
import numpy as np
import matplotlib.pyplot as plt
from PIL import Image
from scipy.m... |
<filename>src/processing.py
"""
Pre-processing and post-processing
"""
import numpy as np
import scipy.ndimage as ndi
import torch
from scipy.ndimage.morphology import distance_transform_edt
from skimage.morphology import (
skeletonize_3d, remove_small_objects, remove_small_holes
)
def create_signal(mask):
... |
<filename>eda.py<gh_stars>1-10
import random
from random import shuffle
from kmeans import random_deletion as crandom_deletion
from kmeans import random_swap as crandom_swap
from scipy.sparse import csr_matrix, vstack
random.seed(1)
########################################################################
# Random del... |
<reponame>Guzpenha/DomainRegularizedDeepMatchingNetworks
# -*- coding: utf8 -*-
import os
import sys
import time
import json
import argparse
import random
# random.seed(49999)
import numpy
# numpy.random.seed(49999)
import tensorflow
# tensorflow.set_random_seed(49999)
from collections import OrderedDict
import keras... |
<filename>acq4/analysis/modules/PSPReversal/PSPReversal.py
# -*- coding: utf-8 -*-
from __future__ import print_function
"""
PSPReversal: Analysis module that analyzes the current-voltage relationships
relationships of PSPs from voltage clamp data.
This is part of Acq4
Based on IVCurve (as of 5/2014)
<NAME>, Ph.D.
201... |
<reponame>wellcometrust/deep_reference_parser
#!/usr/bin/env python3
# coding: utf-8
"""
Runs the model using configuration defined in a config file. This is suitable for
running model versions < 2019.10.8
"""
import plac
import wasabi
from deep_reference_parser import load_tsv
from deep_reference_parser.common impor... |
<reponame>OneGneissGuy/detrend-ec
# -*- coding: utf-8 -*-
"""
Created on Thu Dec 6 12:38:52 2018
script to read in conductivity data and correct for drift due to evaporation
@author: jsaracen
"""
import numpy as np
import pandas as pd
from scipy.signal import detrend
input_data_file = 'sc1000_data.csv'
#read... |
<reponame>HBOMAT/AglaUndZufall
#!/usr/bin/python
# -*- coding utf-8 -*-
#
# Kurve - Klasse von agla
#
#
# This file is part of agla
#
#
# Copyright (c) 2019 <NAME> <EMAIL>
#
#
# Licensed under the Apache L... |
import numpy as np
from math import ceil, sqrt
import sys
sys.path.append('..')
from scipy.stats import multivariate_normal, uniform, norm
from scipy.optimize import Bounds
from itertools import product
from scipy.special import erf
class ToyMVNMultiDSimpleHypLoader:
def __init__(self, alt_mu_norm=1, d_obs=2, ... |
import numpy as np
from .HDPModel import HDPModel
from bnpy.suffstats import SuffStatBag
from bnpy.util import NumericUtil, NumericHardUtil
import scipy.sparse
import logging
Log = logging.getLogger('bnpy')
class HDPSoft2Hard(HDPModel):
######################################################### Local Params
###... |
<filename>demoSfM.py<gh_stars>100-1000
import torch
import numpy as np
import BPnP
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import torchvision
from scipy.io import loadmat, savemat
device = 'cuda'
pl = 0.00000586
f = 0.0005
u = 0
v = 0
K = torch.tensor(
[[f, 0, u],
[0, f, v],
... |
<filename>baobab/bnn_priors/models.py
import numpy as np
from scipy.special import gamma
import astropy.units as u
def velocity_dispersion_function_CPV2007(vel_disp_grid):
"""Evaluate the velocity dispersion function from the fit on SDSS DR6
by [1]_ on a provided grid.
Parameters
----------
vel_di... |
import numpy as np
import pandas as pd
import matplotlib.cm as cm
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import seaborn as sns
from scipy import stats
import warnings
import os
from itertools import combinations
import multiprocessing
from multiprocessing import Pool
from ... |
# -*- coding: utf-8 -*-
import glob, os, json, pickle
import pandas as pd
import numpy as np
from scipy import ones,arange,floor
from sklearn.linear_model import SGDClassifier
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.model_selection import train_test_split
from sklearn.grid_search import... |
<filename>server/app/outputs/led.py
import socket
import logging
import time
import random
import numpy as np
from scipy.ndimage.filters import gaussian_filter1d
from . import Output
from app.effects import Effect
from app.lib.dsp import ExpFilter
from app.lib.misc import FPSCounter
logger = logging.getLogger()
#... |
from __future__ import division
import logging
import math
from datetime import datetime
# import itertools
# pyplot is not thread safe since it rely on global parameters: https://github.com/matplotlib/matplotlib/issues/757
from matplotlib.figure import Figure
from matplotlib.artist import setp
from matplo... |
<reponame>mtopalid/Neurosciences
# -*- coding: utf-8 -*-
# -----------------------------------------------------------------------------
# Copyright INRIA
# Contributors: <NAME> (<EMAIL>)
# <NAME> (<EMAIL>)
#
# This software is governed by the CeCILL license under French law and abiding
# by the rules of ... |
<gh_stars>0
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Wed Apr 11 09:54:02 2018
@author: frico
"""
#==============================================================================
# Plotting - HC3N*
#==============================================================================
version = '8'
# Th... |
import scipy.stats as st
import gzip
import argparse
from signal import signal, SIGPIPE, SIG_DFL
signal(SIGPIPE,SIG_DFL)
parser = argparse.ArgumentParser(description = "Keep one minimal p-value per position to make fgwas annotations.", formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument("--qtlt... |
<reponame>Wei2624/pcl_post_processing
import os
import cv2
import numpy as np
import sys
import scipy.io
import pcl
import image_geometry
import random
# from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import math
import pickle
from pcl_pixel_processing import pcl_processing
from pcl_pixel_proc... |
<filename>localisation.py
# !/usr/bin/env python
#
# 'localisation.py' has a simple implementation of calculation for
# disorder-averaged amplitudes of a 1d-tight binding model with
# the nearest neighbor couplings being perturbed by disorder.
#
#
# MIT License. Copyright (c) 2020 <NAME>
#
# Source code at
# <htt... |
<gh_stars>0
from scipy.stats import pearsonr
import matplotlib.pyplot as plt
import pickle
import numpy as np
import csv
import os,sys
# changeable inputs
# choices are: euclid, corr, dtw, and norm (for manhattan)
matrix_type = 'dtw'
no_buffer = False
# open linkage matrix
with open(os.path.join('data',matrix_type+'... |
import sys
import time
from orangecontrib.shadow.als.widgets.gui.shadow4_ow_electron_beam import OWElectronBeam
from orangecontrib.shadow.als.widgets.gui.shadow4_plots import plot_data1D
from oasys.widgets import gui as oasysgui
from orangewidget import gui as orangegui
from orangewidget.settings import Setting
# fr... |
<filename>fe/utils.py
import numpy as np
import simtk.unit
def set_velocities_to_temperature(n_atoms, temperature, masses):
assert 0 # don't call this yet until its
v_t = np.random.normal(size=(n_atoms, 3))
velocity_scale = np.sqrt(constants.BOLTZ*temperature/np.expand_dims(masses, -1))
return v_t*velo... |
<filename>gui_and_analytics/analytics/power/solar.py
import numpy as np
import scipy.integrate
from datetime import datetime
import analytics.forecast.forecast as fc
import analytics.location.path as ap
import analytics.definitions as adef
def ghi_total_over_path(path: ap.Path) -> float:
""" Returned value is Wa... |
'''
Created on Dec 6, 2018
'''
# System imports
import os
# Standard imports
import numpy as np
import tensorflow as tf
import keras.backend as K
from scipy import stats
# Plotting libraries
import matplotlib.pyplot as plt
# Project library imports
from modules.deltavae.deltavae_latent_spaces.deltavae_parent import... |
<reponame>vyatu/Hanabi-AI-Engineering-Thesis
# -*- coding: utf-8 -*-
from framework import BasePlayer, Choice, ChoiceDetails, utils, HintDetails
import random
import math
from copy import deepcopy
import statistics
debug = True
random_action = 0.01
exploration_param = math.sqrt(2)
class Reinforced:
def __init__... |
<reponame>DenisAltruist/NEFreeSamplesFinder
from scipy.optimize import linprog
import time
import numpy as np
def solve(A, b):
c = np.zeros(len(A[0])).tolist()
res = linprog(c=c, A_ub=A, b_ub=b, bounds=(None, None), method='interior-point')
return res['success'], np.array(res['x']).tolist()
def is_feasible(A,... |
<gh_stars>1-10
from numpy import exp, median
from scipy.sparse.csgraph import laplacian
from sklearn.manifold.locally_linear import (
null_space, LocallyLinearEmbedding)
from sklearn.metrics.pairwise import pairwise_distances, rbf_kernel
from sklearn.neighbors import kneighbors_graph, NearestNeighbors
def ler(X, ... |
<reponame>rodriguesrenato/CarND-Capstone
#!/usr/bin/env python
import numpy as np
import rospy
from std_msgs.msg import Int32
from geometry_msgs.msg import PoseStamped, TwistStamped
from styx_msgs.msg import Lane, Waypoint
from scipy.spatial import KDTree
from lowpass import LowPassFilter
import math
'''
This node wi... |
<reponame>kevinlacaille/Galaxy-Disc-Fitting<gh_stars>1-10
import numpy
import scipy
import astropy
import matplotlib
import bottleneck
import galpak
import asciitable
from astropy.io import fits
from galpak import run
import time
#Set the beam and check parameters
#restoring beam = 0.749", 0.665", 5.826deg
ALMA_b7 = ... |
import numpy as np
import matplotlib.pyplot as plt
from scipy import linalg
import sys
def read_geometry_local(file_name):
f = open(file_name,'r')
file_raw = f.read()
file_lines = file_raw.split('\n')
parameters = {}
l = 1
while '/' not in file_lines[l] and len(file_lines[l])>0:
lsplit... |
"""Arnold-Winther elements on simplices.
Thse elements definitions appear in https://doi.org/10.1007/s002110100348
(Arnold, Winther, 2002) [conforming] and https://doi.org/10.1142/S0218202503002507
(<NAME>, 2003) [nonconforming]
"""
import sympy
from ..finite_element import CiarletElement
from ..polynomials import po... |
#coding:utf-8
# trial estimation of glottal source spectrum condition by inverse radiation filter and anti-formant filter
# under following hypotheses.
# (1) glottal source spectrum (frequency response) characterizes simply descending rightwards without sharp peak.
# (2) resonance strength of formant is roughly... |
<gh_stars>0
import numpy as np
import os
import random
from scipy import io as sio
import sys
import torch
from torch.utils import data
from PIL import Image, ImageOps
import pandas as pd
import glob
from config import cfg
from .setting import cfg_data
def letterbox(img,den, new_shape=(640, 640), color=(114, 114, 1... |
#!/usr/bin/env python3
from collections import defaultdict as dd
from itertools import product
import os
import pysam
import argparse
import pandas as pd
import numpy as np
import scipy.stats as ss
import matplotlib
# Force matplotlib to not use any Xwindows backend.
matplotlib.use('Agg')
# Illustrator compatibil... |
"""
@author: frode
This file contains functions for solving the tumour problem in both 1D and 2D.
The main-function calls to smaller trial-functions, which call the solver
functions using some initial conditions, and then plot the outputs.
What remains to be done: Alter the
"""
import numpy as np
from scipy.sparse... |
import glob
import json
import numpy as np
import pandas as pd
from scipy.stats.mstats import gmean
metric_names = [
'node-is-malicious-accuracy', 'node-is-malicious-auc',
'node-is-attacked-accuracy', 'node-is-attacked-auc',
'edge-is-malicious-accuracy', 'edge-is-malicious-auc'
]
def read_results(path):
... |
<reponame>monte-flora/wofs_ml_severe<gh_stars>0
"""Calibration of predicted probabilities."""
# Author: <NAME> <<EMAIL>>
# <NAME> <<EMAIL>>
# <NAME> <<EMAIL>>
# <NAME> <<EMAIL>>
#
# License: BSD 3 clause
import warnings
from inspect import signature
from math import log
import numpy as np
fro... |
"""
A set of convenience functions to download datasets for illustrative examples
"""
import os
import os.path as op
import sys
import itertools
import numpy as np
from scipy.special import comb
from urllib.request import urlretrieve
_rgcs_license_text = """
License
-------
This tutorial dataset (RGC spikes data) is ... |
#!/usr/bin/env python
from pydy import *
from sympy import factor
# Create a Newtonian reference frame
N = NewtonianReferenceFrame('N')
# Declare parameters, coordinates, speeds
params = N.declare_parameters('l1 l2 l3 ma mb g I11 I22 I33 I12 I23 I13 I J K T')
q, qd = N.declare_coords('q', 7)
u, ud = N.declare_speeds(... |
import numpy as np
import scipy.linalg as scipy_linalg
import cocos.device
import cocos.numerics as cn
import cocos.numerics.linalg
def compare_cocos_numpy(cocos_array, numpy_array):
return np.allclose(np.array(cocos_array), numpy_array)
def test_cholesky():
cocos.device.init()
A_numpy = np.array([[1.... |
import matplotlib.pyplot as plt
import numpy as np
from scipy.stats import multivariate_normal
import random as rn
import iso
mean = [0, 0]
cov = [[1, 0], [0, 1]] # diagonal covariance
Nobjs = 2000
x, y = np.random.multivariate_normal(mean, cov, Nobjs).T
x[0]=3
y[0]=3
X=np.array([x,y]).T
ntrees=500
CT=[]
sample = 256... |
from scipy import stats
import numpy as np
from .DoubleHyp import DoubleHyp
class Z2Hyp(DoubleHyp):
"""double Z-test hypothesis"""
def __init__(self, kind, sigma1, sigma2):
dist = stats.norm(0, 1)
super(Z2Hyp, self).__init__(dist, kind=kind)
self.sigma1 = sigma1
self.sigma2 = s... |
<filename>xrayvision/clean.py<gh_stars>1-10
"""
CLEAN algorithms.
The CLEAN algorithm solves the deconvolution problem by assuming equation by assuming a model
for the true sky intensity which is a collection of point sources or in the case of multiscale
clean a collection of appropriate component shapes at different ... |
import sympy
f = lambda x, r=0: r + 1 - x - sympy.exp(-x)
from normal_forms import normal_form
h = normal_form(f, x=0, k=2)
print h.fun
print h(2)
|
from sklearn.svm import LinearSVC
from scipy.special import erf
import nest
import pylab
#
#
#
# Create neurons
neuron1 = nest.Create("iaf_psc_alpha")
nest.SetStatus(neuron1 , {"I_e": 376.})
neuron2 = nest.Create("iaf_psc_alpha")
nest.SetStatus(neuron2 , {"I_e": 378.})
multimeter = nest.Create("multimeter")
nest.S... |
<reponame>7gang/7synth
import numpy as np
from scipy import signal
notes = { # maps keyboard keys to musical notes
"a": 440, # A4
"s": 494, # B4
"d": 523, # C4
"f": 587, # D4
"g": 660, # E4
"h": 698, # F4
"j": 784, # G4
"k": 880 # A5
}
def wave(note, duration=1):
""" Bas... |
<reponame>LeoIV/sparse-ho
import pytest
import numpy as np
from scipy.sparse import csc_matrix
from sklearn import linear_model
from sklearn.model_selection import KFold
import celer
from celer.datasets import make_correlated_data
from sparse_ho.utils import Monitor
from sparse_ho.models import Lasso
from sparse_ho.cr... |
#***************************************************#
# This file is part of PFNET. #
# #
# Copyright (c) 2015, <NAME>. #
# #
# PFNET is released under the BSD 2-clause license. #
#***********... |
<gh_stars>1-10
import numpy as np
from scipy import stats
import plotly.offline as py
import plotly.graph_objs as go
# Create surfaces Z1 and Z2
n = 100
r = 10
x = np.linspace(-1.8, 1.8, n)
y = np.linspace(-1.8, 1.8, n)
X, Y = np.meshgrid(x, y)
XY = np.empty((n * n, 2))
XY[:, 0] = X.flatten()
XY[:, 1] = Y.flatten(... |
<filename>run_exp.py
from scipy.special import logsumexp
import numpy as np
import ctypes
import os
import platform
import sys
import functions
import time
import hashlib
from shutil import copyfile
config_file = sys.argv[1]
exp_type = sys.argv[2] # options: model, pg
rep_begin = int(sys.argv[3])
rep_end = int(sys.ar... |
"""
.. class:: LineLuminosityFunctionFromSimulations
.. moduleauthor:: <NAME> <johan.comparat__at__gmail.com>
The class LineLuminosityFunctionFromSimulations is dedicated to measuring the line luminosity functions obtained from simulations.
"""
from os.path import join
import os
import astropy.cosmology as co
cosmo=c... |
<reponame>googlearchive/rgc-models
# Copyright 2018 Google LLC
#
# 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 applic... |
import pandas as pd
from sklearn import preprocessing
from sklearn.decomposition import TruncatedSVD
from sklearn.feature_extraction.text import CountVectorizer, HashingVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
from sklearn.feature_extraction.text import ENGLISH_STOP_WORDS
from sklearn.svm... |
# Copyright 2021 Sony Group Corporation
#
# 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 i... |
import numpy as np
from scipy.optimize import minimize_scalar, minimize
from scipy.stats import norm, multivariate_normal
def sample_data():
dt = 1/12
maturity = np.array([1,3,5,10,20])
data = np.array([
[0.01995,0.02039,0.02158,0.02415,0.02603],
[0.01981,0.02024,0.02116,0.02346,0.02518],
... |
<gh_stars>1-10
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
@author: <NAME>
"""
import pandas as pd
import pickle
import os
import seaborn as sns
import matplotlib.pyplot as plt
import scipy.stats
save_plots = True
#%%load data
analysis_folder=os.path.dirname(__file__)
plot_folder=os.path.join(analysis_folder,... |
<filename>python/homography.py
import argparse
import json
import logging
import pyflann
import scipy.io as sio
from util.iou_util import IouUtil
from util.projective_camera import ProjectiveCamera
from util.synthetic_util import SyntheticUtil
LOGGER = logging.getLogger(__name__)
def retrieve_homography(retrieved_... |
<filename>deeplook/regularization/tikhonov.py
"""
Tikhonov regularization
"""
import scipy.sparse
class Damping():
"""
Damping regularization.
"""
def __init__(self, regul_param, nparams):
self.regul_param = regul_param
self.nparams = nparams
def hessian(self, params=None): # py... |
<reponame>BenedictIrwin/ExactLearning
import numpy as np
from scipy.special import ellipk
from matplotlib import pyplot as plt
x = np.random.exponential(size=(1000000))
y = np.random.exponential(size=(1000000))
mean = 0.25*np.pi*(x+y)/ellipk((x-y)/(x+y))
plt.hist(mean,bins=500,density=True)
x = np.linspa... |
import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import root_scalar
from tqdm.auto import tqdm
import jax.numpy as jnp
from pydd.analysis import calculate_SNR
from pydd.binary import *
"""
Plots SNRs for GR-in-vacuum binaries as a function of chirp mass and luminosity
distance.
Produces `figur... |
from __future__ import print_function, division
import os
import sys
sys.path.append(os.path.dirname(sys.path[0]))
import warnings
import numpy as np
from scipy import interpolate
from scipy.ndimage import interpolation as spinterp
from scipy.stats import threshold
import geometry
import density
def cart2pol(*coor... |
<gh_stars>1-10
# -*- coding: utf-8 -*-
"""
Created on Mon Feb 1 07:55:39 2021
@author: kpapke
"""
import numpy
from scipy.interpolate import interp1d
from ..log import logmanager
from .hs_formats import HSFormatFlag, HSFormatDefault, convert
logger = logmanager.getLogger(__name__)
__all__ = ['HSComponent']
cla... |
<reponame>TatianaOvsiannikova/ostap
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# =============================================================================
# Copyright (c) Ostap developpers.
# =============================================================================
# @file ostap/histos/tests/test_histos_pa... |
<reponame>gitter-badger/mlmodels
#!/usr/bin/env python
# coding: utf-8
# In[1]:
import json
import os
import numpy as np
import tensorflow as tf
import tensorflow.contrib.slim as slim
from scipy.misc import imread, imresize
import inception_v1
# just remove line below if want to use GPU
# os.environ['CUDA_VISIBLE... |
<filename>netNMFsc/run_netNMF-sc.py
# run netNMF-sc from command line and save outputs to specified directory
from __future__ import print_function
import numpy as np
from warnings import warn
from joblib import Parallel, delayed
import copy,argparse,os,math,random,time
from scipy import sparse, io,linalg
from scipy.sp... |
import numpy as np
import os
import glob
import healpy as hp
from rubin_sim.photUtils import Sed, Bandpass
from .twilightFunc import twilightFunc
from scipy.interpolate import InterpolatedUnivariateSpline, interp1d
from rubin_sim.data import get_data_dir
# Make backwards compatible with healpy
if hasattr(hp, 'get_inte... |
'''
파일 이름 : 2108.py
제작자 : 정지운
제작 날짜 : 2018년 6월 5일
'''
"""
lst = []
n = int(input())
for i in range(n):
lst.append(int(input))
print(round(sum(lst) / len(lst)))
print(lst[len(lst) // 2])
print(max(lst) - min(lst))
"""
# statistics module을 python tutorial에서 보고 난 후 재도전
from statistics import mean, median, mod... |
<gh_stars>1-10
import unittest
from revenue_maximization_ranking.cascade.revenue import expected_revenue
from scipy.stats import randint
class TestExpectedRevenue(unittest.TestCase):
def test_revenue(self):
g = randint(1, 4)
ranking = [("A", {"revenue": 1.2, "probability": 0.1}),
... |
import serial
import time
import threading
from myUtil import serialBaud, serialPort
from myUtil import MHz, kHz, minUkw, maxUkw, minKw, maxKw, minMw, maxMw, minLw, maxLw
from myUtil import minCap, maxCap
from myUtil import capToLw, capToMw, capToKw, capToUkw
from myLog import log, elog, slog
import myRadios
import myN... |
"""
This script receives a BedGraphFile file as input and smoothes it out using
convolution with a window of the user's choosing. It also contains
supplementary functionality such as changing the loci coordinates of the given
BedGraph.
"""
import pathlib
from enum import Enum
from typing import Callable, MutableMapping... |
<filename>Scripts/functions.py
from initialise_parameters import params, control_data, categories, calculated_categories, change_in_categories
from math import exp, ceil, log, floor, sqrt
import numpy as np
from scipy.integrate import ode
from scipy.stats import norm, gamma
import pandas as pd
import statistics
import ... |
<reponame>Bridge-The-Gap-Series/PSK-00-JobMyers<gh_stars>0
import statistics
name=input("Enter your name: ")
age=int(input("Enter your age(20+): "))
print("\n\n")
print("Hello world\n")
print("my name is",name)
print("I am ",age," years of age.Young, right?\U0001F600\n")
numlist=[]
numlist.append(12)
numlist.append(4)
... |
from ctypes import *
import math
import random
import os
import cv2
import numpy as np
import time
import darknet
import pytesseract
from skimage import measure
import threading
from scipy.spatial import distance as dist
from collections import OrderedDict
from multiprocessing import Process, Lock
lic_pl = cv2.imread(... |
import json,copy,datetime,numbers
import numpy as np
from scipy.sparse import csr_matrix
from scipy.sparse.csgraph import connected_components
from scipy.spatial.transform import Rotation as R
import ase
from ase import Atoms
from ase.data import atomic_numbers,atomic_masses_iupac2016,chemical_symbols
fro... |
<gh_stars>0
import re
import random
import numpy as np
import os.path
import scipy.misc
import shutil
import zipfile
import time
import tensorflow as tf
from glob import glob
from urllib.request import urlretrieve
from tqdm import tqdm
from tensorflow.python.platform import gfile
from tensorflow.core.protobuf import s... |
# -*- coding: utf-8 -*-
"""
Created on Tue Jun 25 08:19:27 2019
@author: SESA539950
"""
from scipy.optimize import fsolve
import numpy as np
simulation = ["AC Unit", "Ventilation Fans (Economizer Mode)"]
simulation_options = ["AC Fans on UPS", "Vent Fans on UPS"]
simulation01 = [
"AC Unit",
"Front Ventilati... |
# -*- coding: utf-8 -*-
"""
Created on Thu Jul 28 12:11:07 2016
@author: Eric
"""
import argparse
import pickle
import TopoSparsenet
import numpy as np
import scipy.io as io
parser = argparse.ArgumentParser(description="Learn dictionaries for Topographic Sparsenet with given parameters.")
parser.add_ar... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Aug 23 17:31:19 2020
@author: skyjones
"""
import os
import numpy as np
import pandas as pd
import scipy
import gbs
# for generating a default model
master_csv = '/Users/manusdonahue/Documents/Sky/segmentations_sci/pt_data/move_and_prepare_tabular... |
<gh_stars>0
# !/usr/bin/python3
# -*- coding: utf-8 -*-
# *****************************************************************************/
# * Authors: <NAME>, <NAME>
# *****************************************************************************/
"""visualizeTS.py
This module contains the basic functions for plotting t... |
<reponame>hamishgibbs/facebook_mobility_uk
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Aug 10 09:39:32 2020
@author: hamishgibbs
Which matrices are closest to eachother?
Then - cluster the matrices to see what are the dominant patterns in travel network over time?
Date x Date matrix of canberr... |
<reponame>sjwenn/holmuskWorkspace
from logs import logDecorator as lD
import jsonref, pprint
import matplotlib
matplotlib.use('Qt5Agg')
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
sns.set(style="dark")
sns.set_palette(sns.diverging_palette(240, 120, l=60, n=3, center="dark"))
from scipy im... |
# coding: utf-8
# In[78]:
import matplotlib.pyplot as plt
from scipy.stats import multivariate_normal
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
plt.rcParams['figure.figsize']=(12,12)
# In[89]:
x,y = np.mgrid[-4:4:.01,-4:4:.01]
# In[90]:
pos = np.dstack((x,y))
# In[91]:
fig=plt.figure()
... |
# 3D IoU caculate code for 3D object detection
# Kent 2018/12
# https://github.com/AlienCat-K/3D-IoU-Python/blob/master/3D-IoU-Python.py
import numpy as np
from scipy.spatial import ConvexHull
from numpy import *
def polygon_clip(subjectPolygon, clipPolygon):
""" Clip a polygon with another polygon.
... |
from .Element import Element
from sympy import symbols, cosh, sinh, sqrt, lambdify
from sympy.matrices import Matrix
from ruamel import yaml
from collections import UserList
# TODO: Have StructuredBeamline inherit from UserList and remove the sequence attribute and just use self
# This may break the current self._t... |
import os
import scipy.io
import numpy as np
from tqdm import tqdm
import matplotlib.pyplot as plt
data_path = os.path.join("Data-HWK3-2020","Problem-4","SymptomDisease.mat")
data=scipy.io.loadmat(data_path)
#print(data.keys())
W = data['W']
b = data['b']
p = data['p']
s = data['s'] # symptoms
def check_data():
... |
import numpy as np
import pandas as pd
import pytest
from pandas.testing import assert_frame_equal
from scipy.sparse import csr_matrix
from feature_engine.dataframe_checks import (
_check_contains_inf,
_check_contains_na,
_check_X_matches_training_df,
check_X,
)
def test_check_X_returns_df(df_vartype... |
# emailAlert = EmailAlert()
# ledAlert = LEDAlert()
# maxThreshold = 10.5
# statsAlerter = StatsAlerter(maxThreshold, [emailAlert, ledAlert])
# statsAlerter.checkAndAlert([22.6, 12.5, 3.7])
# self.assertTrue(emailAlert.emailSent)
# self.assertTrue(ledAlert.ledGlows)
import statistics
class ... |
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