text string |
|---|
<gh_stars>100-1000
from __future__ import division
import numpy as np
import scipy.sparse as ssp
def top_k(values, k, exclude=[]):
''' Return the indices of the k items with the highest value in the list of values.
Exclude the ids from the list "exclude".
'''
# Put low similarity to viewed items to exclude them f... |
import pandas as pd
import numpy as np
import itertools
import os
from scipy import interpolate
from matplotlib import pyplot as plt
import matplotlib.ticker as ticker
from mpl_toolkits.mplot3d import Axes3D
''' Get directory '''
dir_config = '/home/hector/ros/ual_ws/src/upat_follower/config/'
dir_data = '/home/hector... |
#!/usr/bin/env python
# -*- coding: utf8 -*-
from __future__ import division, print_function
from builtins import input
import argparse
import threading
import sys
from astropy.io import fits as pyfits
from scipy import signal
import numpy as np
from .tools import io, version
log = io.MyLogger(__name__)
__autho... |
import argparse
import torch
import torch.nn as nn
import torchvision.transforms as transforms
from PIL import Image
import cv2
import datetime
from model_final_mv3 import DABLNet
import statistics as stat
from visualize import get_color_pallete
import os
parse = argparse.ArgumentParser()
parse.add_argument(
'... |
# Jack12
import os
import pathlib
from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter
import numpy as np
import torch
from scipy import linalg
from torch.nn.functional import adaptive_avg_pool2d
from PIL import Image
import pickle
from .inception import InceptionV3
from .fid_score import calculate_... |
<gh_stars>0
import numpy as np
import meshio
from gdist import compute_gdist as geo_dist
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import open3d as o3d
from scipy import sparse
from scipy.stats import uniform
#o3d.geometry.TriangleMesh.compute_vertex_normals
# write mesh to obj
def ... |
<reponame>letaylor/limix
# Copyright(c) 2014, The LIMIX developers (<NAME>, <NAME>, <NAME>)
#
#Licensed under the Apache License, Version 2.0 (the "License");
#you may not use this file except in compliance with the License.
#You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
#U... |
<gh_stars>1-10
from glob import glob
from os.path import dirname, join
import os
from scipy.misc import imread
from masque.utils import read_landmarks
import masque
def interactive(fn):
def wrapped(*args, **kwargs):
if os.environ.get('INTERACTIVE'):
return fn(*args, **kwargs)
else: ... |
####################################################################################################
# File: sp.py
# Purpose: Signal processing tools (including spectrogram plotting).
#
# Author: <NAME>
#
# Location: Kent, 2021
#####################################################################################... |
<reponame>jsleb333/hypergeometric_tail_inversion<filename>hypergeo/hypergeometric_distribution.py
import numpy as np
from scipy.special import comb, gammaln
from scipy.stats import hypergeom
import math
import warnings
warnings.filterwarnings('error')
from hypergeo.utils import close_to, close_to_or_less_than
def ... |
<reponame>discardthree/PyQPECgen<gh_stars>1-10
# pylint: disable=E1101
#
# qpecgen/helpers.py
#
# Copyright (c) 2016 <NAME>
#
# This software is released under the MIT License.
#
# http://opensource.org/licenses/mit-license.php
#
import scipy
import scipy.linalg
import numpy as np
try:
from numba import jit
except... |
<reponame>fjcasti1/src_PhD
import glob,natsort
import multiprocessing as mp
import pandas as pd
import sys,os
from numpy import *
from pylab import *
from scipy.signal import blackman as blk
NPROCS = 10
PLOT_THRESHOLD = 1e-25
LEGEND_THRESHOLD = 1e-30
titlesize = 18
legendfontsize = 12
labelsize = 20
labelpadx = 6
labe... |
import pyaudio
import math
import scipy.io.wavfile
import numpy as np
class Player:
def __init__(self, sr, buffer_size, input_op, all_output_operators):
self.input_op = input_op
self.all_output_operators = all_output_operators
self.current_offset = 0
self.stream = None
self... |
<filename>hera_cal/vis_clean.py
# -*- coding: utf-8 -*-
# Copyright 2019 the HERA Project
# Licensed under the MIT License
import numpy as np
from collections import OrderedDict as odict
import datetime
from uvtools import dspec
import argparse
from astropy import constants
import copy
import fnmatch
from scipy import... |
# Third-party
import astropy.units as u
from astropy.utils.misc import isiterable
from astropy.constants import G
import numpy as np
# Project
from .utils import format_doc
__all__ = ['a_P_to_m', 'a_m_to_P', 'P_m_to_a', 'get_m2_min']
doc_a = """a : quantity_like [length]
Semi-major axis.
"""
doc_P = """P ... |
<filename>deprecated/Time-Series/dataset.py
import torch
from torch.utils.data import Dataset, DataLoader
from torchvision import transforms, utils
import cv2
from scipy import signal, stats
import matplotlib
from matplotlib import pyplot as plt
from tqdm import tqdm # Displays a progress bar
import pandas as pd
impo... |
<gh_stars>10-100
import os
import numpy as np
import matplotlib.pyplot as plt
import scipy.integrate as integ
'''All meshes are 2 dimensional. The first dimension is the membrane potential v, in whatever
units you chose to deliver them. In order for these scripts to work you need to provide a two dimensional vector
fi... |
<reponame>n-longuetmarx/tbip
"""PyTorch implementation of the text-based ideal point model (TBIP).
Let y_{dv} denote the counts of word v in document d. Let x_d refer to the
ideal point of the author of document d. Then we model:
theta, beta ~ Gamma(alpha, alpha)
x, eta ~ N(0, 1)
y_{dv} ~ Pois(sum_k theta_dk beta_kv... |
<filename>src/benchmark.py
import numpy as np
import pandas as pd
import os
import subprocess
import scipy.special
from sklearn.metrics.cluster import adjusted_rand_score
from sklearn.metrics.cluster import normalized_mutual_info_score
from sklearn.metrics.cluster import silhouette_samples, silhouette_score
from skle... |
<filename>mlmodels/model_tf/misc/tf_nlp/Classification Comparison/NB-SVM/NB-SVM.py
#!/usr/bin/env python
# coding: utf-8
# In[1]:
import re
import numpy as np
import sklearn.datasets
from scipy import sparse
from sklearn import metrics
from sklearn.base import BaseEstimator, ClassifierMixin
from sklearn.cross_valid... |
<filename>data_recording_software/pulse_recorder.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Script for recording pulses of the DIY Particle Detector connected to an audio input.
A live view of triggering pulses is provided via an oscilloscope plot if the pulse
amplitude is larger than the threshold level.
... |
<gh_stars>1-10
import torch
import torchaudio
import torchaudio.functional as F
import torchaudio.transforms as T
from torch import nn
from torch.utils.data import Dataset, DataLoader
import io
import os
import math
import glob
import tarfile
import multiprocessing
import scipy
import librosa
import librosa.display
i... |
import time, sys, cv2, json
from datetime import date
from datetime import datetime
from detection import detection
import numpy as np
import scipy.spatial.distance as scipydist
from munkres import Munkres
from tracks import track
from simulation import SimulationEngine
#initalize tracking
strikelimit = 6
threshold =... |
<reponame>wutobias/collection
#!/usr/bin/env python
'''
#################################################################
# #
# mapconv.py is written by <NAME> and comes #
# with no warrenty. This python-script can do different #
# opera... |
<reponame>Spacebody/MCM-ICM-2018-Problem-C
#! usr/bin/python3
import pandas as pd
import re
import numpy as np
import os
import sys
from collections import OrderedDict, defaultdict
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns
from scipy import stats, integrate
from exp_es_data import ... |
from jax import lax
import numpy as np
from scipy.integrate import solve_ivp
from sklearn.preprocessing import StandardScaler
from .utils import generate_diff_kernels
__all__ = ["generate_dataset"]
def generate_dataset(dt=1e-2, tmax=None, num_visible=2, num_der=2, raw_sol=False):
if tmax is None:
tmax =... |
#!/usr/bin/env python
from __future__ import print_function
from __future__ import absolute_import
from __future__ import division
from builtins import next
from builtins import hex
from builtins import str
from builtins import zip
from builtins import range
from builtins import object
# standard lib
import glob
impor... |
<filename>drlhp/utils.py
import queue
import random
import socket
import time
import gym
import numpy as np
import pyglet
import pdb
import sys
from drlhp.deprecated.a2c.common.atari_wrappers import wrap_deepmind
from drlhp.deprecated.a2c.common.misc_util import set_global_seeds
from drlhp.deprecated.a2c.common.vec_e... |
""" Unit Testing for LaTeX Parser """
# Author: <NAME>
# Email: ksible *at* outlook *dot* com
# pylint: disable=import-error,protected-access
# import sys; sys.path.append('..')
from latex_parser import Tensor, OverrideWarning
from latex_parser import Parser, parse_expr, parse
from sympy import Function, Symbol, Matr... |
<gh_stars>10-100
"""
..
Copyright (c) 2014-2017, Magni developers.
All rights reserved.
See LICENSE.rst for further information.
Module providing fast linear operations wrapped in matrix emulators.
Routine listings
----------------
get_DCT(shape, overcomplete_shape=None)
Get the DCT fast operation dic... |
<gh_stars>0
# Karoo GP Base Class
# Define the methods and global variables used by Karoo GP
# by <NAME>, MSc; see LICENSE.md
# Thanks to <NAME> and <NAME> for support during 2014-15 devel; TensorFlow support provided by <NAME>
# version 2.1.2
'''
A NOTE TO THE NEWBIE, EXPERT, AND BRAVE
Even if you are highly experien... |
'''
Created on Jan 4, 2017
@author: safdar
'''
import numpy as np
import scipy.misc as smp
import cv2
# Create a 1024x1024x3 array of 8 bit unsigned integers
data = np.zeros( (1024,1024,3), dtype=np.uint8 )
data[512,512] = [254,0,0] # Makes the middle pixel red
data[512,513] = [0,0,255] # Makes the next ... |
from pyrep import PyRep
from pyrep.objects import VisionSensor
from pyrep.const import Verbosity
import multiprocessing as mp
import os
from pathlib import Path
from collections import defaultdict
from custom_shapes import TapShape, ButtonShape, LeverShape, Kuka
import numpy as np
from contextlib import contextmanager
... |
from utils.utils import change_ds_transform, get_label_dist, get_random_idx, get_unique_counts, timer
from sampler.ranking import get_items_idx_of_min_segment, get_norm_subset_idx
from utils.log import Log
import torch
from torch.utils.data import Dataset, Subset
from modeling.feature_extractor import FeatureExtractor
... |
<filename>devito/passes/clusters/blocking.py
from sympy import sympify
from devito.ir.clusters import Queue
from devito.ir.support import (AFFINE, PARALLEL, PARALLEL_IF_ATOMIC, PARALLEL_IF_PVT,
SEQUENTIAL, SKEWABLE, TILABLE, Interval, IntervalGroup,
Iterati... |
"""Author: J.H.Cao
Computational Biology group
Biomedical Engineering
Eindhoven University of Technology"""
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from kf_filter_seird import kf_filtering_seird, plot_seirdmodel, seird_model_test
from estimating_compmod_params import read_data, ... |
<filename>imputer.py<gh_stars>0
import itertools
import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
from scipy.sparse import csgraph
class Imputer(nn.Module):
"""Impute missing data based on type."""
def __init__(self, impute_type, n_nodes, n_dim, seq_len=12,
... |
<reponame>phunc20/dsp
import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import hamming, triang, blackmanharris
import sys, os, functools, time
sys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)), '../../../software/models/'))
import sineModel as SM
import stft as STFT
import util... |
<reponame>ZendriXXX/predict-python
import statistics
from collections import defaultdict, OrderedDict
from pm4py.objects.log.log import EventLog
TIMESTAMP_CLASSIFIER = "time:timestamp"
NAME_CLASSIFIER = "concept:name"
def events_by_date(log: EventLog) -> OrderedDict:
"""Creates dict of events by date ordered by... |
<gh_stars>1-10
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2016 <NAME> and <NAME>
#
# 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 without l... |
<reponame>LinXueyuanStdio/MyTransE
import math
import random
import pickle
from time import sleep
import numpy as np
import sys
from scipy import spatial
# lang = sys.argv[1]
# w = float(sys.argv[2])
lang = 'fr_en'
# w = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9] #
# w = [0.1, 0.2, 0.5, 0.7, 0.75, 0.8, 0.85, 0.... |
"""
Dissimilarity measures for clustering
"""
import numpy as np
def matching_dissim(a, b, **_):
"""Simple matching dissimilarity function"""
return np.sum(a != b, axis=1)
def jaccard_dissim_binary(a, b, **__):
"""Jaccard dissimilarity function for binary encoded variables"""
if ((a == 0) | (a == 1... |
import numpy as np
import numpy.random as rnd
from scipy import stats
rng = rnd.default_rng(0)
x = np.ones([30, 50])
mu, sigma = 0, 1
mu_biased, sigma_biased = 0.5, 1
noise = rng.normal(mu, sigma, x.shape)
print(noise)
bias_bits = np.array([0, 5, 10, 15, 20, 25])
n, n_trials = x.shape
for i in range(len(bias_bits... |
<gh_stars>0
""" convenience.py
Define constant mappings and lookup tables and other simple shortcuts
"""
import re
import os
import pickle
import pandas as pd
import numpy as np
from statistics import StatisticsError
from scipy.stats import tmean, tstd
from pygest.rawdata import miscellaneous
# A list of the data f... |
<filename>server/enums/trim_size.py
from enum import Enum
from fractions import Fraction
class TrimSize(Enum):
"""
A simple enum class representing the different trim sizes
"""
THIRD = Fraction(1, 3)
HALF = Fraction(1, 2) |
<gh_stars>1-10
import torch
import time
import matplotlib.pyplot as plt
import scipy as sp
sp_version = sp.__version__.split('.')
if (int(sp_version[0]) >= 1) and (int(sp_version[1]) >= 3):
from imageio import imread
else:
from scipy.misc import imread
from lib_stereo import compute_terms
class MRFParams():
def... |
# import the necessary packages
from scipy.spatial import distance as dist
from imutils.video import VideoStream
from imutils import face_utils
from threading import Thread
import numpy as np
import imutils
import time
import dlib
import cv2
#initializing dlib's shape_predictor_68_face_landmarks.dat and then create th... |
<reponame>bgallag6/specFit
# -*- coding: utf-8 -*-
"""
Created on Tue Dec 20 22:30:43 2016
@author: <NAME>
Usage:
python paramPlot.py --processed_dir DIR [--save_fig [True]|False]
"""
import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.axes_grid1 import make_axes_locatable
from scipy.stats import ... |
## Python class for estimates of Shapley population variable importance
## compute estimates and confidence intervals, do hypothesis testing
## import required libraries
import numpy as np
from scipy.stats import norm
from .predictiveness_measures import cv_predictiveness, compute_ic
from .spvim_ic import shapley_infl... |
<filename>src/plot_geo.py
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from scipy.spatial import voronoi_plot_2d
DEFAULT_GEO_ARGS = {
'lng_bound': (121.44, 121.64),
'lat_bound': (24.95, 25.15),
'lng_granularity': 0.02,
'lat_granularity': 0.02,
}
DEFAULT_PLOT_ARGS = {
'a... |
#!/usr/bin/python
"""This is a short description.
Replace this with a more detailed description of what this file contains.
"""
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 ... |
import numpy as np
import scipy.misc
import tensorflow as tf
from keras.layers import Input, Dense
from keras.models import Model
import NeuralNet
"""
This script loads mnist data, then trains a simple autoencoder using first NeuralNet.py (using Numpy as back end),
then using Keras with TensorFlow as back end as ben... |
import argparse
import pandas as pd
import rdkit
import scipy
from rdkit import Chem
from sklearn.metrics import mean_absolute_error, mean_squared_error
def add_args(parser):
parser.add_argument(
"--prediction",
type=str,
required=True,
help="The path to prediction result to be ev... |
<reponame>bio-ontology-research-group/deeppheno<filename>mp_evaluate.py<gh_stars>1-10
#!/usr/bin/env python
import numpy as np
import pandas as pd
import click as ck
from sklearn.metrics import classification_report
from sklearn.metrics.pairwise import cosine_similarity
import sys
from collections import deque
import ... |
<gh_stars>1-10
__copyright__ = """
Copyright (C) 2020 <NAME>
Copyright (C) 2020 <NAME>
"""
__license__ = """
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 without ... |
# AUTOGENERATED! DO NOT EDIT! File to edit: nbs/00_io.ipynb (unless otherwise specified).
__all__ = ['dicom_dataframe', 'get_plane', 'is_axial', 'is_sagittal', 'is_coronal', 'is_fat_suppressed', 'load_mat',
'load_h5']
# Cell
from fastscript import call_parse, Param, bool_arg
from scipy import ndimage
impo... |
# allows to import own functions
import sys
import os
import re
root_project = re.findall(r'(^\S*TFM)', os.getcwd())[0]
sys.path.append(root_project)
from sklearn.pipeline import Pipeline
from sklearn.impute import SimpleImputer
from src.utils.help_func import get_model_data
from sklearn.feature_selection import RFECV... |
import random
from math import inf
from matplotlib import pyplot as plt
from statistics import median
REPRODUCTION_AGE = (15,60)
PARTNER_AGE_DEVIATION = 15
REPRODUCTION_BREAK = 10
MAX_BABIES = inf
SIM_STEPS = 10000
SIM_BLOBS = 1000
death_rate = lambda age: 10/1000
step = 0
id = 0
def roundTo(n, num):
# Smal... |
#!/usr/bin/env python
# this script:
# 1) outputs each TE insertion call into new files based on family
# 2) collapses TEs of same famly within 50 base pairs of one another
# 3) outputs all the unqiue TE positions to a new file
# 4) calculates the coverage for each sample at each insertion postion +/- 25 base pairs
# 5... |
from __future__ import division
import matplotlib.pyplot as plt
from scipy.interpolate import interp1d
import numpy as np
from numpy import linalg
import sympy
def ajuste(X,Y):
#Ordem da matriz
ordem = n[0]+1
A = np.zeros((ordem,ordem))
for i in range(ordem):
for j in range(ordem):
... |
<reponame>Xiaoming94/TIFX05-MScThesis-HenryYang
import utils
import ANN as ann
import keras.losses as klosses
import matplotlib.pyplot as plt
import numpy as np
from scipy.stats import entropy
import gc
ensemble_size = 100
chunksize = 20
trials = 5
network_model2 = '''
{
"input_shape" : [28,28,1],
"layers" :... |
<reponame>zsyOAOA/VIRNet<filename>demo_test_denoising_real.py<gh_stars>1-10
#!/usr/bin/env python
# -*- coding:utf-8 -*-
# Power by <NAME> 2019-05-16 16:20:01
import torch
import numpy as np
from utils import imshow
from skimage import img_as_float
from scipy.io import loadmat
from networks.VIRNet import VIRNetU
prin... |
<reponame>tracijo32/lensing
'''
lensing.py
author: <NAME>
date: 3/17/2016
Library of useful lensing functions
'''
import numpy as np
from astropy.cosmology import FlatLambdaCDM
from scipy import interpolate
def dlsds(zl,zs,Om0=0.3,H0=70):
# computes the lensing ratio for a lens redshift and source redshift
# ... |
import os.path
import os.path as osp
import sys
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
import numpy as np
from scipy import stats
from sklearn.metrics import average_precision_score
from sklearn.metrics import roc_auc_score
from . import anom_utils
def eval_ood_measure(conf, pred, seg_label... |
<reponame>charlesblakemore/opt_lev_analysis
import numpy as np
import bead_util as bu
import matplotlib.pyplot as plt
import os
import scipy.signal as sig
import scipy
import glob
from scipy.optimize import curve_fit
data_dir1 = "/data/20180529/imaging_tests/p0/xprofile"
def spatial_bin(xvec, yvec, bin_size = .13):
... |
<filename>apps/chisquare.py
from typing import ClassVar
import streamlit as st
import pandas as pd
import scipy as sp
import numpy as np
from plotnine import *
def app():
# title of the app
st.markdown("Chi-Square")
t_choice = st.sidebar.radio("Chi-Square Test",["Chi-Square Test","Goodness of Fit"])
... |
from sympy.solvers import solve
from sympy import symbols
x, y = symbols('x, y')
result = solve(x**3 - y, x)
print(result)
|
import sys, os
from io import BytesIO
import sympy
from PIL import Image, ImageOps, ImageChops
rootdir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
srcdir = os.path.join(rootdir, 'src')
sys.path.insert(0, srcdir)
latexsources = []
import fitfunctions
for name in fitfunctions.__all__:
cls = geta... |
# Copyright 2016 <NAME>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, s... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sat Jun 6 14:40:17 2020
@author: lukepinkel
"""
import numpy as np
import scipy as sp
def fo_fc_fd(f, x, eps=None, args=()):
if eps is None:
eps = (np.finfo(float).eps)**(1.0/3.0)
n = len(np.asarray(x))
g, h = np.zeros(n), np.zeros(n)... |
<reponame>cagrell/HAL
# Optimization functions
# ADD TO /Utils/Optimize..
from scipy import random
from scipy.optimize import minimize
from .div import scale_to_bounds
def gopt_min(fun, bounds, n_warmup = 1000, n_local = 10):
"""
Global optimization (minimization) based on:
1. Sampling 'n_warmup' uni... |
import numpy as np
from scipy import signal
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from pyatac.tracks import InsertionTrack
#import pyximport; pyximport.install(setup_args={"include_dirs":np.get_include()})
from pyatac.fragments import makeFragmentMat
class ChunkMat2D:
"""Class that stores frag... |
"""
@author: MatteoRaso
"""
from math import pi, sqrt
from random import uniform
from statistics import mean
from typing import Callable
def pi_estimator(iterations: int):
"""
An implementation of the Monte Carlo method used to find pi.
1. Draw a 2x2 square centred at (0,0).
2. Inscribe a circle withi... |
<reponame>grst/diffxpy
import abc
try:
import anndata
except ImportError:
anndata = None
import batchglm.api as glm
import logging
import numpy as np
import patsy
import pandas as pd
from random import sample
import scipy.sparse
from typing import Union, Dict, Tuple, List, Set
from .utils import split_x, dmat_... |
<gh_stars>0
import copy
from collections import namedtuple
from fractions import gcd
Position = namedtuple("Position", "x y z")
Velocity = namedtuple("Velocity", "x y z")
X = 0
Y = 1
Z = 2
POS = 1
VEL = 2
x_states = set([])
y_states = set([])
z_states = set([])
states = [x_states, y_states, z_states]
def lcm(a, ... |
import argparse
from typing import Dict, Iterator, Tuple, Union
from typing import *
from asapp.ml_common.embedders import FastTextEmbedder
from asapp.ml_common.embedders import IndexBatchEmbedder, WordBatchEmbedder
from asapp.ml_common.interfaces import Embedder, Preprocessor
from tqdm import tqdm, trange
impor... |
# -*- coding: utf-8 -*-
"""
Speaker Stuff Calculator main module.
hosted on "github.com/kbasaran/Speaker-Stuff-Calculator"
"""
import os
import sys
import numpy as np
import pandas as pd
from scipy import signal
from dataclasses import dataclass
import pickle
from PySide2.QtCore import SIGNAL, SLOT, QObject, Qt # Qt i... |
<filename>VOE.py<gh_stars>1-10
import numpy as np
import SimpleITK as sitk
import itk
import SimpleITK as sitk
import pandas as pd
import quandl, math
import numpy as np
from sklearn import preprocessing, svm
from sklearn.model_selection._validation import cross_validate
from sklearn.linear_model import LinearRegres... |
# python3
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in... |
import os
import argparse
import random
from statistics import mean
import xml.etree.ElementTree as ET
random.seed(42)
#
# config
#
parser = argparse.ArgumentParser()
parser.add_argument('--train-dir', action='store', dest='train_dir',
help='train directory location', required=True)
... |
<reponame>ablavatski/draw
from __future__ import print_function, division
import logging
import theano
import theano.tensor as T
import cPickle as pickle
import numpy as np
import scipy as sc
from PIL import Image, ImageDraw
from svhn import SVHN
from fuel.streams import DataStream
from fuel.schemes import SequentialS... |
<gh_stars>0
import math
import logging
from itertools import product
import mahotas as mt
import numpy as np
from scipy import linalg
from skimage.feature.texture import greycomatrix
from skimage.util.shape import view_as_windows
from enum import Enum, IntEnum
logger = logging.getLogger('collageradiomics')
def _svd_d... |
<reponame>nsabine/openshift-batch-demo<gh_stars>1-10
#!/usr/bin/env python
import numpy as np
import scipy.special as spc
import scipy.fftpack as sff
import scipy.stats as sst
def sumi(x): return 2 * x - 1
def su(x, y): return x + y
def sus(x): return (x - 0.5) ** 2
def sq(x): return int(x) ** 2
def logo(x): return x... |
from flask import current_app as app
from .product import Product
import io
import matplotlib.pyplot as plt
from scipy import stats
import base64
class ProductReview:
def __init__(self, reviewer_id, rating, review, product_id, seller_id, time_posted, upvotes, reports):
self.reviewer_id = reviewer_id
... |
<filename>cgp/functions/mathematics.py
import numpy as np
import scipy.stats
from cgp.functions.support import is_scalar
from cgp.functions.support import is_np
from cgp.functions.support import min_dim
FUNCTIONS = []
FUNCTION_NAMES = []
def add(x, y, p):
if is_np(x) and is_np(y):
new_dim = min_dim(x, y... |
import time
import numpy as np
from scipy.sparse import csr_matrix
from scipy.sparse.csgraph import connected_components
import pandas as pd
from rdkit import Chem
from . import chem
class BlockMoleculeData:
def __init__(self):
self.blockidxs = [] # indexes of every block
self.blocks = [] ... |
import linvpy as lp
import mestimator_marta as marta
import generate_random as gen
import numpy as np
import matplotlib.pyplot as plt
import optimal as opt
from scipy.sparse.linalg import lsmr
import toolboxutilities as util
import toolboxinverse as inv
import copy
import random
gen.gen_noise(2,3)
#genA, geny = g... |
<reponame>ohannuks/lenstronomy<gh_stars>0
import numpy as np
import lenstronomy.Util.util as util
import lenstronomy.Util.image_util as image_util
from scipy.optimize import minimize
from lenstronomy.LensModel.Solver.epl_shear_solver import solve_lenseq_pemd
from lenstronomy.LensModel.Solver.lens_equation_solver import... |
<filename>scripts/matcher.py
import pickle
import numpy as np
import scipy
import torch
from scipy import spatial
import operator
from auto_encoder.lstm_network import AutoLSTM
from configs.config import get_config
from tools.utils import extract_video_features
class Matcher(object):
def __init__(self):
self.c... |
import matplotlib.pyplot as plt
import numpy as np
import math
from PIL import Image
from scipy import misc
def greyAvg(image):
gray = np.zeros((image.shape[0], image.shape[1]), dtype= np.float)
gray = (image[...,0]+image[...,1]+image[...,2])/3
return gray
def luminanceGrey(image):
gray = np.zeros((im... |
<filename>propnet/core/models.py
"""
Module containing classes and methods for Model functionality in propnet code.
"""
import os
import re
import logging
from abc import ABC, abstractmethod
from itertools import chain
import six
from monty.serialization import loadfn
from monty.json import MSONable, MontyDecoder
imp... |
# -*- coding: utf-8 -*-
# Copyright (C) 2016-2017 by <NAME> <<EMAIL>>
# <NAME> <<EMAIL>>
# All rights reserved. BSD 3-clause License.
# This file is part of the SPORCO package. Details of the copyright
# and user license can be found in the 'LICENSE.txt' file distributed
# with the package.
... |
<gh_stars>0
import numpy as np
import scipy as sp
from quaternion import from_rotation_matrix, quaternion
from rlbench.environment import Environment
from rlbench.action_modes import ArmActionMode, ActionMode
from rlbench.observation_config import ObservationConfig
from rlbench.tasks import *
from pyrep.const import ... |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn import linear_model
from matplotlib.pyplot import figure
from scipy import stats
def homoscedasticity_test(X, y, threshold = 0.05):
"""This function recieves a linear regression model and outputs a
scatter plot figure of residu... |
<filename>python/testing/covariance_test.py
# Copyright(c) 2014, The LIMIX developers (<NAME>, <NAME>, <NAME>)
#
#Licensed under the Apache License, Version 2.0 (the "License");
#you may not use this file except in compliance with the License.
#You may obtain a copy of the License at
#
# http://www.apache.org/licens... |
import numpy as NP
import scipy as sp
import scipy.linalg as LA
import numpy.linalg as nla
import os
import sys
import glob
sys.path.append("./../../pyplink")
from fastlmm.pyplink.plink import *
from pysnptools.util.pheno import *
from fastlmm.util.mingrid import *
#import pdb
import scipy.stats as ST
import fastlmm.ut... |
<gh_stars>0
# Authors:
# <NAME> <<EMAIL>>
# <NAME> <<EMAIL>>
#
# License: BSD 3 clause
"""
Module for LBM boundary conditions
"""
import collections
import logging
import types
import numpy as np
from sympy import symbols, IndexedBase, Idx, Eq
from .storage import Array
log = logging.getLogger(__name__) #py... |
<reponame>galizia-lab/pyview<filename>log2list_examples/log2settings_VTK2021_old_for_reference.py
# -*- coding: utf-8 -*-
"""
Program to read Till vision .log files
and write .settings.csv files
the program works like this (not all implemented yet):
- set flag settings that are default values
- read .log files and par... |
# ======================================================================== #
#
# Copyright (c) 2017 - 2020 scVAE authors
#
# 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.apac... |
<reponame>PeterChenYijie/MachineLearningZeroToALL<gh_stars>1-10
#-*- coding: utf-8 -*-
import numpy as np
import matplotlib.pyplot as plt
import scipy.io as spio
from scipy import optimize
from matplotlib.font_manager import FontProperties
font = FontProperties(fname=r"c:\windows\fonts\simsun.ttc", size=14) # 解决wind... |
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