text string |
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<reponame>GustavePate/perfectpythonbatch
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
import logging
import matplotlib.dates as mdates
import numpy as np
np.random.seed(9221999)
import pandas as pd
from scipy import stats, optimize
import matplotlib.pyplot as plt
import seaborn as sns
sns.set(palett... |
from datetime import datetime, timedelta
from os import PathLike
from pathlib import Path
from typing import Collection
import fiona
import fiona.crs
import numpy
import rasterio
from rasterio.enums import Resampling
import scipy.interpolate
import xarray
import PyOFS
from PyOFS import CRS_EPSG, LEAFLET_NODATA_VALUE,... |
<reponame>saroudant/Percolate
import torch, os
import numpy as np
from copy import deepcopy
from sklearn.model_selection import GridSearchCV, KFold
from sklearn.neighbors import KNeighborsRegressor
from sklearn.pipeline import Pipeline
from sklearn.kernel_ridge import KernelRidge
from sklearn.preprocessing import Stand... |
<reponame>jd-jones/kinemparse<gh_stars>0
import argparse
import os
import inspect
import yaml
import joblib
import numpy as np
import scipy
from mathtools import utils
def main(out_dir=None, data_dir=None, detections_dir=None, modality=None, normalization=None):
data_dir = os.path.expanduser(data_dir)
out_d... |
<filename>Oszilloskop/Oszi-Data to Graph all Channels universal.py
'''
imput file: .csv-Datei aus Osziloskop
output file: #eine Datei mit allen Kennzahlen, die nach Glattung einer berechnet wurden
'''
#written by <NAME>
import os
import numpy as np
import pandas as pd
import scipy.signal
import plotly
from plotly imp... |
"""
gsm.py
======
Python interface for the Global Sky Model (GSM) or Oliveira-Costa et. al.
This is a python-based equivalent to the Fortran `gsm.f` that comes with the
original data. Instead of the original ASCII DAT files that contain the PCA
data, data are stored in HDF5, which is more efficient.
References
------... |
from fractions import Fraction
import argparse
class block:
def __init__(self, position, mass):
self.x = position # block position
self.m = mass # block mass
self.v = Fraction(0, 1) # block velocity
def reflect(self):
"""
reverses velocity for elast... |
from keras.preprocessing.text import text_to_word_sequence
from keras.layers import Layer
import keras.utils
import keras.backend as K
from nltk import FreqDist
import numpy as np
from keras.preprocessing import sequence
from scipy.misc import logsumexp
from collections import defaultdict, Counter, OrderedDict
imp... |
<gh_stars>0
from aoc import data
from statistics import median, mean
def part1(inputData):
goal = int(median(inputData))
fuel = lambda crab, goal: abs(crab-goal)
return sum(fuel(crab, goal) for crab in inputData)
def part2(inputData):
goalLowerBound = int(mean(inputData))
goalUpperBound = goalLowe... |
<filename>libkloudtrader/analysis.py
from libkloudtrader.equities.data import *
import ta
from datetime import datetime
import pandas as pd
import talib
import numpy as np
from pyti.hull_moving_average import hull_moving_average as hma
from pyti.function_helper import fill_for_noncomputable_vals
from pyti.vertical_hori... |
<gh_stars>0
import numpy as np
import scipy as sp
import os
import pickle
from scipy import sparse
from subprocess import CalledProcessError, TimeoutExpired
#
from .. import format_text
from . import config
len_str = 25
max_len = 1e4
t_out = 30
tuple3errors = (TimeoutExpired, CalledProcessError, ValueError... |
<filename>Notebooks_Teoricos/Image-Processing-Operations/CommonClasses/fft.py
import numpy as np
import matplotlib.pyplot as plt
#%matplotlib inline
#import matplotlib.image as img
#import PIL.Image as Image
from PIL import Image
import math
import cmath
import time
import csv
from numpy import binary_repr
from ... |
<reponame>AyeshaSadiqa/thesis<gh_stars>10-100
import os
import os.path as osp
import sys
import time
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
import ffmpeg
import random
import logging
import collections
import numpy as np
import cv2
from PIL import Image
from datetime import datet... |
#!/usr/bin/env python3
import os
from datetime import datetime, timezone, timedelta
from lib.config import cfg
from statistics import mean
latest_event = None
event_queue = []
class event():
first_trigger:datetime
last_trigger:datetime
id:int
def __init__(self):
global latest_even... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Transforming a time series into a uniform deviate is harmful.
Uniform deviate transformation is a nonlinear transformation, and
thus, it does not preserve the linear properties of a time series.
In the example below, we see that the power spectra of the surrogates
don'... |
"""P2S10 TD3 v5 with 40x40 front and orientation from ac3.ipynb
Automatically generated by Colaboratory.
# Twin-Delayed DDPG
On a custom car env
state:
1. 40x40 cutout: 25 embeddings || car is at mid ( grid embeddings)
2. 25 cnn embeddings `+` [distance, orientation, -orientation, self.angle, -self.angle]
NOTE: Emb... |
#Note the contest names are case-senstive
from bs4 import BeautifulSoup
from statistics import NormalDist
import requests
import argparse
import math
import sys
def analysis(contest_name, l, div):
base = 'https://competitiveprogramming.info'
source = requests.get(base + '/topcoder/srm/').text
soup = BeautifulSoup(... |
# 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 applicable law or agreed to in writing, s... |
import random as rnd
import statistics as stat
class Consensus:
def __init__(self,number_of_byzantine_nodes = 0,update_rule = "3M"):
# Coloring values are integers from 0 to k
self.coloring = {}
self.t_consensus = None
self.converged = None
self.started = False
self.... |
<gh_stars>0
#This script does the following:
# (1) Find the cell lines that are covered by both CCLE RNAseq data (RPKM) and DepMap gene dependecy data
# (2) Save the RPKM data and gene dependency data of cell lines found in both datasets to seperate tsv files for downstream analysis
# (3) Plot the expression distri... |
from __future__ import print_function
import numpy as np
import pandas as pd
import scipy.stats
from parallelm.mlops import StatCategory as st
from parallelm.mlops import mlops as pm
from parallelm.mlops.examples import utils
from parallelm.mlops.examples.utils import RunModes
from parallelm.mlops.stats.graph import M... |
<filename>keras-image-classification/img_clf.py
from keras.preprocessing.image import ImageDataGenerator, array_to_img, img_to_array, load_img
from keras.models import Sequential, model_from_json
from keras.layers import Convolution2D, MaxPooling2D, ZeroPadding2D, Activation, Dropout, Flatten, Dense
from keras.callback... |
from tqdm import tqdm
import numpy as np
import pandas as pd
from scipy.ndimage import shift
import glob
import os
from .utils import load_fits, img_to_patches, patches_means, MoonContamination
np.random.seed(42)
def extract_features_from_fits(path, save_path, patch_shape, with_noise=False, with_offset=False):
if ... |
import scipy
import numpy as np
from ..util import BaseCase
from pygsti.objects import Circuit
from pygsti.objects.processorspec import ProcessorSpec
class ProcessorSpecTester(BaseCase):
def test_construct_with_nonstd_gate_unitary_factory(self):
nQubits = 2
def fn(args):
if args is ... |
import petsc4py
import sys
petsc4py.init(sys.argv)
from petsc4py import PETSc
import numpy as np
from dolfin import tic, toc
import HiptmairSetup
import PETScIO as IO
import scipy.sparse as sp
import MatrixOperations as MO
import HiptmairSetup
class BaseMyPC(object):
def setup(self, pc):
pass
def reset... |
<reponame>flurincoretti/adjoint_example
import numpy as np
from scipy.optimize import minimize
import cmocean
import cmocean.cm as cmo
import matplotlib.pyplot as plt
import logging
plt.rcParams['figure.figsize'] = [10, 6]
plt.rcParams["figure.dpi"] = 100
# Configure logging
logging.basicConfig(
level=logging.INF... |
"""
simple IFC wrapper
"""
from scipy.linalg import eigh
import numpy as np
#from minimulti.ioput.ifc_netcdf import read_ifc_from_netcdf, save_ifc_to_netcdf
from banddownfolder.plot import plot_band
import matplotlib.pyplot as plt
class IFC():
def __init__(self, atoms, Rlist, ifc):
self.atoms = atoms
... |
<reponame>m2march/beats2audio
'''
Library to create audio from onset lists.
'''
import magic
import os
import tempfile
import pkg_resources
import subprocess
import numpy as np
from pydub import AudioSegment
from subprocess import call
from scipy.io import wavfile
CLICK_FILE = pkg_resources.resource_filename(__name... |
<reponame>clara-risk/fire_weather_interpolate<gh_stars>0
#coding: utf-8
"""
Summary
-------
Interpolation functions for thin plate splines using the radial basis function from SciPy.
References
----------
<NAME>., & <NAME>. (1989). A study of interpolation methods for forest fire danger rating in Canada.
Ca... |
# Datasets loaders for tracking package,including training and testing and running the tracker
import glob
import torch
import numpy as np
from collections import OrderedDict
from skimage.measure import regionprops, label
from skimage.io import imread
from skimage.transform import resize
import matplotlib.pyplot as plt... |
<reponame>edervishaj/spotify-recsys-challenge
import logging
import scipy.sparse as sps
from boosts.hole_boost import HoleBoost
from boosts.tail_boost import TailBoost
from utils.datareader import Datareader
from utils.definitions import ROOT_DIR
from utils.evaluator import Evaluator
from utils.post_processing import... |
#!/usr/bin/python
# -*- coding:utf-8 -*-
# @author : East
# @time : 2019/7/16 21:04
# @file : mesh2d.py
# @project : fempy
# software : PyCharm
# imports
import numpy as np
from scipy.spatial import Delaunay
from matplotlib.tri import Triangulation, UniformTriRefiner
# functions
def rect_tri(x_opt, y_opt=Non... |
<filename>run_dataset.py
"""NVIDIA end-to-end deep learning inference for self-driving cars.
This script loads a pretrained model and performs inference based on that model
using jpeg images as input and produces an output of steering wheel angle as
proportions of a full turn.
"""
import tensorflow as tf
import scipy.... |
<reponame>SebastianoF/calie
import os
import time
from os.path import join as jph
from collections import OrderedDict
import tabulate
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
from sympy.core.cache import clear_cache
from calie.t... |
import pickle as pickle
from scipy.special import erf
import glob
import os
import matplotlib.pyplot as plt
from matplotlib import animation
import numpy as np
from skimage.feature import register_translation
import matplotlib.pyplot as plt
import scipy.stats
import numpy as np
from scipy.fftpack import ff... |
'''
from a given operator, looking to project the operator into the constant
symmetry spaces
'''
from hqca.tools import *
import numpy as np
import sys
from copy import deepcopy as copy
from hqca.tools.quantum_strings import FermiString as Fermi
from hqca.tools.quantum_strings import PauliString as Pauli
import scipy... |
# -*- coding:utf8 -*-
import os
import json
import tensorflow as tf
from scipy import spatial
from nlp.text_representation.doc2vec.model import Doc2Vec
from nlp.text_representation.doc2vec.dataset.data_utils import *
def train(args):
docs = read_doc(os.path.join(args.data_file, "train.txt"))
doc_ids, word_id... |
# -*- coding: utf-8 -*-
"""
Quantarhei package (http://www.github.com/quantarhei)
abs module
This module contains classes to support calculation of linear absorption
spectra.
"""
import numpy
import scipy
import matplotlib.pyplot as plt
#from scipy.optimize import minimize, leastsq, curve_fit
... |
<filename>algoritmoRainAgsWithMun.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Sep 28 08:38:15 2017
@author: jorgemauricio
"""
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
from scipy.interpolate import griddata as gd
#%% read ... |
#!/usr/bin/env python
"""
Electronic structure solver.
Type:
$ ./schroedinger.py
for usage and help.
"""
import os
import os.path as op
from optparse import OptionParser
from math import pi
from scipy.optimize import broyden3
try:
from scipy.optimize import bisect
except ImportError:
from scipy.optimize im... |
import importlib
import os
import time
import yaml
import numpy as np
from scipy import stats
import matplotlib.pyplot as plt
import tensorflow as tf
def import_model(gan_name):
gan_module = importlib.import_module("gan4hep."+gan_name)
return gan_module
def create_gan(gan_type, noise_dim, batch_size, layer... |
<gh_stars>0
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on 06/03/17 at 3:53 PM
@author: neil
Program description here
Version 0.0.0
"""
import numpy as np
from scipy.signal import convolve
from astropy.io import fits
import time as tt
try:
from fastDFT import dft_l, dft_l_ne
USE = "FAST"
exce... |
<filename>Software/Recognition/DataAcqusiton/udpclientv3.py
import socket
import sys
import time
import serial
import threading
import numpy as np
from scipy import signal
from scipy.signal import lfilter , iirnotch , butter , medfilt , filtfilt
import csv
writeToFile = True
read = True
calibration = True
calibrated ... |
<reponame>sakamotosan/pipeline_grid_search
"""
Provides PipelineGridSearchCV, as class for
doing efficient grid search in a Pipeline estimator
while avoiding unnecessary repeated calls to fit and score.
Updated for sklearn 0.16.1
License: BSD 3-Clause (see LICENSE)
This file contains partly rewritten source code from... |
import argparse
import os
import numpy as np
import scipy.io
import networkx as nx
import node2vec
from gensim.models import Word2Vec
def parse_args():
'''
Parses the node2vec arguments.
'''
parser = argparse.ArgumentParser(description="Run node2vec.")
parser.add_argument('--input', nargs='?', default='mat/POS.m... |
<filename>assignment-1/code/test_filters.py<gh_stars>0
from unittest import TestCase
import numpy as np
import scipy.signal
import tensorflow as tf
import filters
def naive_sepia(x):
x = tf.cast(x, tf.float32)
r, g, b = tf.split(x, 3, axis=-1)
y = tf.concat((0.393 * r + 0.769 * g + 0.189 * b,
... |
<gh_stars>0
import numpy as np
from sklearn import datasets
iris = datasets.load_iris()
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(iris.data, iris.target, test_size=0.4, random_state=0)
from sklearn.neighbors import KNeighborsClassifier
knn = KNeighborsClass... |
<reponame>amaanabbasi/LicensePlateDetectionRecognition<gh_stars>1-10
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier
from sklearn.externals import joblib
from matplotlib import pyplot as plt
import scipy.ndimage
import numpy as np
import cv2
import os
def binariz... |
<reponame>Gibbsdavidl/miergolf
import timeit
setup = '''
import scipy.sparse as sp
import numpy as np
from bisect import bisect
from numpy.random import rand, randint
import submatrix as s
r = [10,20,30]
A = s.randomMatrix()
'''
t = timeit.Timer("s.subMatrix(r,r,A)", setup).repeat(3, 10)
print t
#print t.timeit(... |
import numpy as np
from scipy.interpolate import interp2d, NearestNDInterpolator
from nbodykit.utils import DistributedArray
from nbodykit.lab import BigFileCatalog, MultipleSpeciesCatalog
from nbodykit.cosmology.cosmology import Cosmology
from pmesh.pm import ParticleMesh
from sfr import logSFR_Behroozi
gb_k_B = 1.38... |
<reponame>ameya30/IMaX_pole_data_scripts
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Dec 18 16:32:05 2017
@author: prabhu
"""
#%%
from scipy.ndimage import convolve
import numpy as np
import matplotlib.pyplot as plt
from scipy.io import readsav
from astropy.io impor... |
import numpy as np
from scipy.stats import spearmanr, pearsonr
#X = np.random.uniform(16, 1.00000000001, 98)
#Y = np.random.uniform(1, 1.00000000001, 98)
X, Y = [], []
for i in range(1, 99):
X.append(-i)
Y.append(i)
X = np.insert(X, 0, -10000000)
X = np.insert(X, 99, 10000000)
Y = np.insert(Y, 0, -10000000)
... |
#! /usr/bin/env python3
import numpy as np
import matplotlib.pyplot as plt
import scipy.misc
import cv2
import time
d_max = 7
with open('adaptive_median.out.test', 'r') as file:
data = file.read().split('\n')
pix = np.zeros(len(data))
for ind in range(len(data)):
pix[ind] = np.packbits(list(map(... |
<gh_stars>10-100
"""
Gene ontology
"""
from __future__ import (absolute_import, division,
print_function, unicode_literals)
try:
basestring
except NameError:
basestring = str
from collections import defaultdict, Iterable
import warnings
import numpy as np
import pandas as pd
from scipy... |
'''
Outline of the test:
1. Generate one image with a G.
2. Load up the LIME explainer with D,
2.2. Map D output to two classes and limit with sigmoid.
The ultimate goal is to make outputs like that:
for every G:
for every D:
generate 20 images with explanations.
also do the same with real images:
for ev... |
from __future__ import division
from __future__ import print_function
from pathlib import Path
from random import random
import sys
project_path = Path(__file__).resolve().parents[1]
sys.path.append(str(project_path))
import tensorflow as tf
import os
import scipy.sparse as sp
imp... |
### This script calculates the flux of mass and tracer through the 4 boundaries of the domain as an advective flux.
### o-KRM-o
# o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o-o
from math import *
import matplotlib.pyplot as plt
impor... |
<gh_stars>1-10
# -*- coding: utf-8 -*-
#
import numpy
import orthopy
from ..tools import scheme_from_rc
class GaussLobatto(object):
"""
Gauss-Lobatto quadrature.
"""
def __init__(self, n, a=0.0, b=0.0):
assert n >= 2
self.degree = 2 * n - 3
# TODO use symbolic=False instead o... |
from typing import Callable, Iterator, List, Optional, Tuple
import sympy
from comb_spec_searcher import Constructor
from comb_spec_searcher.typing import (
Parameters,
RelianceProfile,
SubObjects,
SubRecs,
SubSamplers,
SubTerms,
Terms,
)
from tilings import GriddedPerm
class DummyConstr... |
<reponame>matttyb80/signal<gh_stars>0
from cadCAD.configuration import Experiment #.append_configs
# from cadCAD.configuration import append_configs
from cadCAD.configuration.utils import config_sim
# if test notebook is in parent above /src
from src.sim.model.state_variables import genesis_states
from src.sim.model.p... |
import PIL
import matplotlib.pyplot as plt
import numpy as np
import os
import scipy.io as sio
import math
import operator
from collections import defaultdict, OrderedDict
from dataset import dist_cal
import glob
RPASCAL_DIR = "/home/peth/Databases/rPascal"
# RIMAGENET_DIR = "/home/peth/Databases/rImageNet"
IM_EXT = '... |
from sympy import pretty, sqrt, cbrt
num, indiceRaiz = input().split(" ")
if indiceRaiz == '2':
print(pretty(sqrt(int(num))))
else:
print(pretty(cbrt(int(num))))
|
#%%
#%matplotlib auto
import numpy as np
import matplotlib.pyplot as plt
import sensor_fusion as sf
import robot_n_measurement_functions as rnmf
import pathlib
import seaborn as sns
import matplotlib.patches as mpatches
from scipy.linalg import expm
import lsqSolve as lsqS
import pathlib
sns.set()
#%%
parent_path = pat... |
<reponame>David-webb/MDPI_Data_mining
#!/usr/bin/python
# -*- coding: UTF-8 -*-
# this py is used to analysis the submission data from mdpi
import pandas as pd
from scipy import stats as ss
import matplotlib.pyplot as plt
import seaborn as sns
# Reading data from web
data_url = "https://raw.githubusercontent.com/als... |
<gh_stars>0
import sys
import numpy as np
import scipy as sp
import gensim
def main():
# print("Loading weight...")
model = gensim.models.keyedvectors.KeyedVectors.load_word2vec_format(sys.argv[1], binary=True)
# print("Calculate similarities...")
global_similarities = []
true_similarities = []
... |
import scipy.sparse.csgraph as csg
import scipy.sparse as sp
from warnings import warn as Warn
import numpy as np
def check_weights(W, X=None, transform=None):
if X is not None:
assert (
W.shape[0] == X.shape[0]
), "W does not have the same number of samples as X"
graph = sp.csc_ma... |
<filename>IFCB_tools/manual2csv.py
#!/usr/bin/python
import psycopg2 as pg
from scipy.io import loadmat
import numpy
from numpy import squeeze, isnan
from os import path
import os
import math
import sys
import re
def sq(thang):
return map(squeeze, thang)
def intNan(f):
if math.isnan(f):
return None
... |
<filename>VISUALIZE/examples/nb_nbody_chaos.py
import numpy as np
import random, time
from scipy.integrate import ode
from UTILS.tensor_ops import distance_matrix, repeat_at, delta_matrix
from VISUALIZE.mcom import mcom
PI = np.pi
def run():
# 可视化界面初始化
可视化桥 = mcom(path='RECYCLE/v2d_logger/', draw_mode='... |
<reponame>mcmorre/placerg
#funcs.py
from blis.py import gemm # for
import numpy as np
import pickle
import os
import nbformat
import nbparameterise
from nbconvert.preprocessors import ExecutePreprocessor
from scipy.special import gamma as gammafunc
import matplotlib.pyplot as plt
"""
Generating jupyter notebooks from... |
<filename>pymicro/core/utils/SDZsetUtils/SDmeshers.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""SD meshers module to allow mesher tools & SampleData instances interactions
"""
## Imports
import os
import shutil
import numpy as np
from subprocess import run
from pathlib import Path
from string import Template... |
# -*- coding: utf-8 -*-
"""
Created on Thu Feb 28 15:37:53 2013
Author: <NAME>
"""
import numpy as np
from scipy import stats
from statsmodels.stats.gof import (chisquare, chisquare_power,
chisquare_effectsize)
from numpy.testing import assert_almost_equal
nobs = 30000
n_bins = 5... |
<reponame>Inars/Developing_MC_for_ZSL<filename>ESZSL/eszsl.py
import numpy as np
import argparse
from scipy import io
from sklearn.metrics import confusion_matrix, log_loss, f1_score
parser = argparse.ArgumentParser(description="ESZSL")
parser.add_argument('-data', '--dataset', help='choose between APY, AWA2, AWA1, C... |
## import csv
import json
import itertools
import pprint
import random
from collections import Counter
import itertools
import numpy as np
import pandas as pd
import pandas as pd
import matplotlib.pyplot as plt
import scipy as sp
from neo4j import GraphDatabase
from neo4j import unit_of_work
from tqdm import tqdm
impo... |
<reponame>johnpeterflynn/surface-texture-inpainting-net
"""Calculates the Frechet Inception Distance (FID) to evalulate GANs
The FID metric calculates the distance between two distributions of images.
Typically, we have summary statistics (mean & covariance matrix) of one
of these distributions, while the 2nd distribu... |
# -*- coding: utf-8 -*-
"""
Created on Sun Jul 14 18:03:35 2019
@author: constatza
"""
import matplotlib.pyplot as plt
import numpy as np
import mathematics.manilearn as ml
import mathematics.stochastic as stat
import smartplot as smartplot
from mpl_toolkits.mplot3d import Axes3D
from sklearn import manifold
from sc... |
<reponame>LiosK/gncxml<gh_stars>1-10
# vim: set fileencoding=utf-8 :
from decimal import Decimal
from fractions import Fraction
import collections
import gzip
import re
import xml.etree.ElementTree as ET
import pandas as pd
import gncxml._iso4217 as iso4217
class Book:
"""Parse GnuCash XML data file and provid... |
import os
import copy
import math
import errno
import torch
#import trimesh
import skimage
import numpy as np
import urllib.request
import skimage.filters
import matplotlib.colors as colors
from tqdm import tqdm
from PIL import Image
#from inside_mesh import inside_mesh
from torch.utils.data import Dataset
from data_... |
from scipy import *
from scipy.interpolate import lagrange
from numpy import *
def equispaced(order):
'''
Takes input d and returns the vector of d equispaced points in [-1,1]
And the integral of the basis functions interpolated in those points
'''
nodes= linspace(-1,1,order)
w= zeros(order... |
<reponame>siddheshmhatre/cuml<filename>python/cuml/explainer/sampling.py
# Copyright (c) 2021, NVIDIA 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.or... |
"""This module implements the Lotka/Volterra (predator-prey) model."""
# pylint: disable=too-many-arguments
# General Purpose
import numpy as np
from matplotlib import pyplot as plt
from scipy.integrate import solve_ivp
# Jupyter Specifics
from ipywidgets.widgets import interact, IntRangeSlider, FloatSlider, Layout
s... |
# -*- coding: utf-8 -*-
"""[kmeans] modelTrain1_ver3 (function version).ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1TWvO-Kja184Oq9FUOpoizSIbLkK8dKKR
"""
import numpy as np
import pandas as pd
from sklearn.cluster import KMeans
from sklearn i... |
<gh_stars>1-10
from datetime import datetime, timedelta
import numpy as np
import pandas as pd
import ujson as json
import wikipedia
from redis import StrictRedis
from scipy.interpolate import interp1d
from statsmodels.tsa.seasonal import seasonal_decompose
from hortiradar import TOKEN, Tweety, time_format
from horti... |
<reponame>johnaparker/stoked<filename>tests/harmonic_potential.py
from stoked import brownian_dynamics, trajectory_animation, drag_sphere
from functools import partial
import matplotlib.pyplot as plt
from tqdm import tqdm
import numpy as np
from scipy.constants import k as kb
no_force = None
def harmonic_force(t, rvec... |
<filename>sunkit_image/utils/noise.py
"""
This module implements a series of functions for noise level estimation.
"""
import numpy as np
from scipy.ndimage import correlate
from scipy.stats import gamma
from skimage.util import view_as_windows
__all__ = ["noise_estimation", "noiselevel", "conv2d_matrix", "weak_textu... |
import unittest
import numpy as np
from scipy.ndimage.morphology import distance_transform_edt
import phathom.segmentation.graphcuts as graphcuts
from phathom import utils
import zarr
import tempfile
import os
class TestPoissonPdf(unittest.TestCase):
def test_zero(self):
p = graphcuts.poisson_pdf(0, 1)
... |
"""
@author: pritesh-mehta
"""
from pathlib import Path
import numpy as np
import scipy.ndimage as sy
import math
import preprocessing_utilities.nifti_utilities as nutil
def pcf_mask_crop_dir(image_dir, mask_dir, output_dir, border=(5, 5, 0), extension='nii.gz'):
"""
square crop x and y, crop z + border
"... |
import argparse
import os
import subprocess
import pdb
import hashlib
import time
import glob
import tarfile
from zipfile import ZipFile
from tqdm import tqdm
from scipy.io import wavfile
import soundfile
import numpy
import random
def loadWAV(filename, max_frames, evalmode=True, num_eval=10):
# Maximum audio le... |
<reponame>criteo-research/optimization-continuous-action-crm
import os
import sys
import scipy as sp
import autograd.numpy as np
from autograd import grad, jacobian, hessian
from cyanure import Regression
base_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), "../..")
sys.path.append(base_dir)
from util... |
<reponame>Mulns/Whale-Identification
import os
import numpy as np
from tensorflow import keras
from skimage.filters import gaussian
from scipy.misc import imresize, imsave
import image_utils as iu
from PIL import Image
import random
from tqdm import tqdm
import time
import image_utils as iu
# from keras.utils.data_util... |
# -*- coding: utf-8 -*-
# PyVkFFT
# (c) 2021- : ESRF-European Synchrotron Radiation Facility
# authors:
# <NAME>, <EMAIL>
#
#
# pyvkfft unit tests.
import sys
import unittest
import multiprocessing
import sqlite3
import socket
import time
import timeit
import numpy as np
try:
from scipy.misc impor... |
<filename>analyzer.py<gh_stars>0
#!/usr/bin/python3
import os
import re
import statistics
from datetime import datetime, timedelta
import texttable as tt
import plot_util
SEC = 1
MIN = SEC * 60
HOUR = MIN * 60
DAY = HOUR * 24
LOG_FILE_PATTERN = r"\d{4}-\d{2}-\d{2}-\d{2}:\d{2}:\d{2}\.log"
LOG_FILE_TIME_STR = "%Y-%m-... |
<filename>tests/test_avg_2means.py
import sigclust.avg_2means
import numpy as np
from sklearn.cluster import KMeans
from pandas import Series
from unittest import TestCase
import scipy.stats
from scipy.spatial.distance import pdist, squareform
class TestAvg2Means(TestCase):
"Test the Avg2Means class"
def setUp... |
<filename>python-packages/core/src/tsv_data_analytics/tsv.py
"""TSV Class"""
import re
import statistics
import math
import pandas as pd
import gzip
import mmh3
import random
import json
import urllib
from tsv_data_analytics import tsvutils
from tsv_data_analytics import utils
from tsv_data_analytics import funclib
i... |
<filename>ts_processing.py
import numpy as np
import string
from scipy.stats import norm
"""
Some time-series preprocessing
NOTE: THIS FUNCTIONS ASSUME TIME SERIES OF EQUAL LENGTH
"""
def z_normalization(array, axis=0):
""" Applies z-normalization to input array as (array - mean)/std
"""
array = np.array... |
<filename>fit_VFA_CLI.py
# ///////////////////////////////////////////////////////////////////////////////////////////////
# // <NAME>, PhD, Aix Marseille Univ, CNRS, CRMBM, Marseille, France
# // Contact: <EMAIL>
# // Acknowledgement: <NAME>, PhD, Université de Strasbourg, CNRS, ICube, Strasbourg, France
# ///////... |
<reponame>nimRobotics/FEM
from sympy.solvers import solve
from sympy import Symbol
from sympy import *
import matplotlib.pyplot as plt
import numpy as np
from scipy.sparse import *
from numpy.linalg import inv
from array import *
from scipy import linalg
x=Symbol('x')
# function to find k and f for linear elements
def... |
<reponame>shiaki/valses-nobles-et-sentimentales
#!/usr/bin/env python
import pickle
from sympy import *
init_printing(use_unicode=True)
if __name__ == '__main__':
# read existing variables.
with open('simplified.pk', 'rb') as f:
for k, v in pickle.load(f).items():
globals()[k] = pickle.lo... |
<filename>dynopy/workspace/workspace.py
import csv
import os
from math import cos, sin, atan2
import matplotlib.pyplot as plt
import numpy as np
import scipy.integrate as sp_integrate
from dynopy.datahandling.objects import GroundTruth, Input, Measurement, get_noisy_measurement
from dynopy.estimationtools.importance_... |
<filename>model.py<gh_stars>1-10
import os
from scipy.io import wavfile
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
from keras.layers import Conv2D, MaxPool2D, Flatten, LSTM, Reshape, Permute
from keras.layers import Dropout, Dense, TimeDistributed
from keras.models import Sequential
from ke... |
import image as im
import pylab as pl
import numpy as np
import calculations as calc
from scipy.spatial import ConvexHull
def findNNdistances(centers):
centers = np.array(centers)
nearestDist = []
for c in centers:
nearestC = sorted(centers - c, key= lambda m: sum(np.abs(m)) )[1]... |
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