text string |
|---|
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import networkx as networkx
import numpy as numpy
import scipy as scipy
import scipy.integrate
import pandas as pd
from random import choices
import matplotlib
import matplotlib.pyplot as plt
import matplotlib... |
<filename>src/TIE_navigation/plan_manage/script/calc.py<gh_stars>1-10
import numpy as np
import sympy as sp
def calcInv():
dt = sp.symbols('dt')
A = sp.Matrix([[1 / 6.0, 2 / 3.0, 1 / 6.0],
[-1 / (2.0 * dt), 0, 1 / (2.0 * dt)],
[1 / (dt * dt), -2 / (dt * dt), 1 / (dt * dt... |
"""
Semiclassical equations of motion
"""
__all__ = [
'generate_eqm',
'eqm_to_semi_classical',
'sc_eqm_to_ode',
'sc_ode_to_matrix'
]
from sympy import (Add, Mul, Pow, exp, Symbol, I, pi, simplify, oo,
Function, Derivative, Eq,
Matrix, MatMul, linear_eq_to_ma... |
<filename>python/amici/petab_import.py
"""
Import a model in the PEtab (https://github.com/ICB-DCM/PEtab/) format into
AMICI
"""
import argparse
import logging
import math
import os
import time
from typing import List, Dict, Union, Optional
import amici
import libsbml
import pandas as pd
import petab
from colorama im... |
<filename>code_v1.0.6/cluster_byAccesson.py
#!/usr/bin/python
import warnings
warnings.filterwarnings("ignore")
#
import os,numpy,pandas,random,time,copy
from optparse import OptionParser
import scipy.spatial.distance
import scipy.io,scipy.sparse,scipy.stats
from sklearn.decomposition import PCA
from sklearn.manifold i... |
# Author: vkaff
# E-mail: <EMAIL>
import numpy as np
from scipy.stats import randint as sp_randint, expon, truncnorm
#: Relative path to the test dataset. This value is used only when the *dtest* cmd argument is None.
# test_dataset = 'datasets/dataset-string-similarity-test.txt'
test_dataset = 'datasets/dataset-str... |
import os
import random
import numpy as np
from itertools import cycle
from keras.utils.np_utils import to_categorical
from keras.engine.training import generator_queue
from SpectrogramGenerator import SpectrogramGenerator
class DirectoryLoader(object):
def __init__(self, source_directory, config, shuffle=True):... |
<gh_stars>0
import numpy as np
import numpy.random as npr
import util_doucet as util
from scipy.special import factorial
class RBFN(object):
def __init__(self, x, y, k, k_fixed=False, l=1, iota=0, \
nu_0=1, gamma_0=1, sig2 = None,\
alpha_del2=2, beta_del2=1, del2 = None,\
eps1=.1, eps2=.1):
'''
x: N x d fe... |
"""
References:
[1] <NAME> and <NAME>, Superposition of vortex cylinders for steady and unsteady simulation of rotors of finite tip-speed ratio - Wind Energy, 2014
[X] <NAME>, <NAME> - Cylindrical vortex wake model: right cylinder - Wind Energy, 2014
[X] <NAME>, <NAME> - Cylindrical vortex wake model: skew... |
<filename>vossMap.py
import requests
def vossMap(s):
def voss(s,c):
return 1 if s == c else 0
Cn = [ voss(s,'C') for s in S ]
Gn = [ voss(s,'G') for s in S ]
An = [ voss(s,'A') for s in S ]
Tn = [ voss(s,'T') for s in S ]
return Cn, Gn, An, Tn
SEQUENCES_URL = 'https://raw.githubuserc... |
<filename>src/tasks/task5/5_3_meler_apply.py<gh_stars>0
import sys
from typing import List, Callable, Protocol
import pandas as pd
import streamlit as st
import seaborn as sns
import sympy as sp
from sympy.abc import x as x_symbol
import matplotlib.pyplot as plt
import numpy as np
from numpy.polynomial import Polynomi... |
import librosa
import os
import re
import soundfile
import numpy as np
from scipy import signal
from scipy import interpolate
from scipy.io import wavfile
class Audio:
def __init__(self, audio_hparams):
self.hps = audio_hparams
def load_wav(self, path):
return librosa.core.load... |
from notebooks.profiles import BaseProfile
import numpy as np
from scipy.stats import norm
# Note: Classes like this aren't going to completely follow Bayes rule or perfectly
# calculate the normal PDF, because they don't have to. They just have to
# calculate something proportional so that a good thresho... |
import os
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import skimage.io
import functools
from skimage import measure
from scipy.spatial import distance
from sklearn.metrics import pairwise_distances_argmin_min
from loguru import logger
import numpy as np
import matplotli... |
<filename>html/team25ev/similarity_clustering/clusters_main.py
import scipy.cluster.hierarchy as hcl
from scipy.spatial.distance import squareform
import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
from scipy.cluster.hierarchy import dendrogram
import scipy
import json
def fancy_dendrogram(*ar... |
<filename>DIP/fluo_beads_sim/fluorescent_beads.py
# -*- coding: utf-8 -*-
"""
Experiments with simulation of images of fluorescent beads for evaluation of precision of their localization.
In other words, for generationg ground truth data for tracking / segmentation evaluations.
@author: ssklykov
"""
# %% General impor... |
<reponame>machism0/non-bonded-periodic<filename>nbp/sysmodule.py<gh_stars>0
import numpy as np
import scipy as sp
import nbp
from scipy.special import erfc
class System:
"""This class represents the system itself: the box and its content.
It's a wrapper containing SystemInfo and all the SystemStates, mostly... |
<reponame>matthewtrotter/adaptive-asset-allocator-simulator
from typing import Dict, List
from assetuniverse import AssetUniverse
import numpy as np
import scipy.optimize as opt
import pandas as pd
class Subportfolio(object):
def __init__(self, params: Dict, au: AssetUniverse, assets: pd.DataFrame, id: int, total_... |
"""
Name : c11_01_normal_density_function.py
Book : Python for Finance (2nd ed.)
Publisher: Packt Publishing Ltd.
Author : <NAME>
Date : 6/6/2017
email : <EMAIL>
<EMAIL>
"""
import scipy.stats as stats
from scipy import sqrt, exp,pi
d1=stats.norm.pdf(0,0.1,0.05)
print("... |
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you ... |
<filename>machine-learning-ex3/ex3/oneVsAll.py
import scipy.optimize as opt
import lrCostFunction as lCF
from sigmoid import *
def one_vs_all(X, y, num_labels, lmd):
# Some useful variables
(m, n) = X.shape
# You need to return the following variables correctly
initial_theta = np.zeros(n + 1)
all... |
import copy
import numpy as np
import numpy.linalg as la
from scipy.optimize import linprog # TODO: REMOVE
from _errors import ConvergenceError
# ======================================================================================================================
# Root-finding Methods
# ================... |
# System libs
import os, csv, torch, numpy, scipy.io, PIL.Image, torchvision.transforms
# Our libs
from mit_semseg.models import ModelBuilder, SegmentationModule
from mit_semseg.utils import colorEncode
import cv2
import math
from math import atan2, degrees
import time
def initialize():
colors = scipy.io.loadmat('... |
import numpy as np
from pyyeti import psd
from nose.tools import *
import scipy.signal as signal
def test_get_freq_oct():
assert np.allclose(
np.array(psd.get_freq_oct(1, [1, 5])),
np.array(
[
[1.0, 1.99526231, 3.98107171],
[0.70794578, 1.41253754, 2.818... |
<reponame>stevenmaclean94/Home-Assistant
import mqttapi as mqtt
import hassapi as hass
import json
import re
import numpy as np
from scipy.optimize import minimize
from pykalman import KalmanFilter
class RoomDetection(mqtt.Mqtt):
def initialize(self):
self.set_namespace("mqtt")
self.hass = self.g... |
import argparse
import functools
import io
import librosa
import librosa.display
import matplotlib.pyplot as plt
import numpy as np
import os
import scipy.io.wavfile as wavfile
import sklearn
import sys
import torch
import torch.utils.data
from multiprocessing import Pool
def to_mfcc(sig, rate, n_mfcc=13, n_fft=2048,... |
<reponame>danibene/NeuroKit
import numpy as np
import pandas as pd
import scipy.integrate
from ..stats import density
def entropy_power(signal, **kwargs):
"""**Entropy Power (PowEn)**
The Shannon Entropy Power (PowEn or SEP) is a measure of the effective variance of a random
vector. It is based on the e... |
<reponame>turingbirds/howland_vccs
# -*- coding: utf-8 -*-
import matplotlib as mpl
import matplotlib.font_manager as fm
import matplotlib.ticker as plticker
# mpl.rc('font', **{'family': 'serif', 'serif': ['Computer Modern']})
# mpl.rcParams["text.usetex"] = True
# mpl.rcParams["text.latex.unicode"] = True
#mpl.rcPar... |
# -*- coding: utf-8 -*-
"""
Created on Sun Jan 21 15:39:49 2018
@author: ZMJ
"""
import numpy as np
import time
from scipy.ndimage import gaussian_filter
from skimage.morphology import reconstruction
##ROF去噪
def denoise_rof(im, U_init, tolerance=0.1, tau=0.125, tv_weight=100):
""" An implementation of ... |
<reponame>WSWUP/MACA-ETr<filename>macaetr/maca.py
# -*- coding: utf-8 -*-
"""
Python tools for downloading and using MACA downscaled and bias corrected climate data including the calculation of ASCE reference evapotranspiration.
"""
import pkg_resources
import numpy as np
import pandas as pd
import refet
import xarray... |
<reponame>HackersForHarambe/Python-Repository
import pygame
import cmath
import math as m
from pygame import *
from cmath import *
import matplotlib as mat
import numpy as np
xmax = 20
ymax = 16
inter = 1
interx = 1
tmax = 10
intert = 10
j = sqrt(-1)
WOUT_Last = [ 0, 0]
def ln(x):
try:
return log(abs(... |
<reponame>vishalbelsare/SocialMediaIE<gh_stars>10-100
import warnings
from functools import partial
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from scipy import stats
from sklearn import datasets
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.... |
#!/usr/bin/env python
"""
Created on Tir 29 Oct 2013.
Uses the Crank Nicolson scheme to solve the time dependent Schrodinger equation
for a center potential spike (delta potential).
Animation is done using the matplotlib.pyplot library.
Usage:
python CrankNicolsonPotentialSpike.py
or equivalent:
./CrankNicol... |
<reponame>damslab/reproducibility<filename>temp-uplift-submission/scikit-learn/adult_sk.py
import sys
import time
import json
import numpy as np
import scipy as sp
from scipy.sparse import csr_matrix
import pandas as pd
import math
import warnings
from sklearn.pipeline import make_pipeline
from sklearn.compose import C... |
<gh_stars>0
# -*- coding: utf-8 -*-
"""
Automated Tool for Optimized Modelling (ATOM)
Author: Mavs
Description: Module containing all available models. All classes must
have the following structure:
Name
----
Name of the model's class in camel case format.
C... |
<reponame>NengLu/topopy
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Jan 24 09:42:34 2018
@author: vicen
"""
import sys
sys.path.append("../../")
from topopy import Flow, Grid
import numpy as np
from scipy.sparse import csc_matrix
fd = Flow()
fd.load_gtiff("../data/tunez_fd.tif")
threshold = 1000... |
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Wed Mar 14 18:25:54 2018
@author: paul
"""
import numpy as np
import matplotlib.pyplot as plt
from scipy.interpolate import griddata
fs = 14
def plots(model):
# =============================================================================
# h... |
import argparse
import pickle
from collections import defaultdict
from clustering_genomic_signatures.dbtools.get_signature_metadata import (
get_metadata_for,
)
from scipy import stats
from ete3 import NCBITaxa
rank_dict = {
'species':'genus',
'superkingdom': None,
'class': None,
'... |
<gh_stars>1-10
"""
Module for working with Bernstein polynomials.
"""
import numpy as np
import sympy as sp
import typing
import vorpy.symbolic
def bernstein_polynomial (t:typing.Any, *, degree:int, k:int) -> typing.Any:
"""
Returns the kth Bernstein polynomial of given degree in the given symbol.
It's as... |
<reponame>lovaulonze/paper.2D_dielectric<filename>src/gpaw_analysis/alpha_mass.py
import ase.db
import warnings
import numpy
import matplotlib.pyplot as plt
from ase.data import covalent_radii
from scipy.stats import linregress
import os, os.path
from scipy.constants import pi, epsilon_0
db_file = "../../data/gpaw_dat... |
import numpy as np
import scipy.sparse as sp
from tophat.utils.sparse_utils import get_row_nz
from tophat.sampling.utils import neg_samp_bsearch
from typing import Sequence
def sample_weighted(weights_cs: np.array,
batch_size: int = 1, n_neg: int = 1):
"""Sample negatives uniformly over entire... |
<reponame>Roald87/ev_forecast<filename>forecast.py
import matplotlib.pyplot as plt
import numpy as np
from typing import TypeVar
from scipy import optimize
NumpyArray = TypeVar('numpy.ndarray')
class Forecast(object):
""" Model to forecast marketshare of a product with time.
The model is from Nederlands Tij... |
import pytest
import numpy as np
from scipy.optimize import check_grad
from scipy.stats import ttest_rel
from cblearn.datasets import make_random_triplets
from cblearn.embedding._soe import SOE, _soe_loss
def test_soe_repeat():
""" Test that the repeated initialization leads to stable results. """
n, d = 20,... |
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Mon Jun 11 12:50:13 2018
@author: madcas
"""
import math
import numpy as np
import h5py
import matplotlib.pyplot as plt
import scipy
from PIL import Image
from scipy import ndimage
import tensorflow as tf
from tensorflow.python.framework import ops
from cn... |
#!/usr/bin/env python3
import os
import argparse
import time
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
plt.style.use('clint.mpl')
from pprint import pprint
import scipy.signal as signal
import itertools
from pygama import DataSet
import pygama.utils as pu
import pygama.analysis.histograms ... |
<filename>benchmark_gamut_map.py
#!/usr/bin/env python3
"""Benchmarks different optimization methods for gamut mapping."""
from functools import partial
import time
import numpy as np
from scipy import optimize
import cam
try:
import sys
from IPython.core.ultratb import AutoFormattedTB
sys.excepthook ... |
import sys
import os.path
sys.path.insert(0, os.path.abspath("./simple-dnn"))
#Import the libraries we will need.
import tensorflow as tf
import tensorflow.contrib.slim as slim
import numpy as np
from tensorflow.examples.tutorials.mnist import input_data
import scipy.misc
import scipy
import scipy.io
from sklearn impo... |
<gh_stars>0
#import libraries
import nibabel as nib
import numpy as np
import pylab as pl
from scipy import stats
import scipy
import os
import pandas as pd
import csv
from sklearn import linear_model #for regression analysis
from sklearn.metrics import mean_squared_error, r2_score
from sklearn.model_selection import... |
# -*- coding: utf-8 -*-
"""
Created on Mon May 25 22:33:04 2020
@author: kkrao
"""
import pandas as pd
from init import dir_data, lc_dict, color_dict
import seaborn as sns
import os
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import mannwhitneyu, pearsonr
from sklearn.ensemble import RandomFo... |
import scipy.misc
import plotload as pl
import numpy as np
import pygame, sys
from PIL import Image
import os
"""
Code inspired from:
https://stackoverflow.com/questions/6136588/image-cropping-using-python/8696558
"""
def _gui_displayImage(screen, px,brush,mask_array,startmouse,prior):
# ensure that the rect alw... |
<reponame>frostburn/frostsynth<filename>experiments/theta.py
from __future__ import division
from math import pi, exp, cosh, cos, log, floor
from cmath import rect as from_polar, exp as cexp
__author__ = "<NAME>"
__copyright__ = "Copyright 2014, <NAME>"
__credits__ = ["<NAME>"]
__license__ = "MIT"
__version__ = "1.0"... |
<gh_stars>0
import sys
from statistics import mean
class StatPrinter(object):
def __init__(self, exercise, file=sys.stdout):
self.exercise = exercise
self.file = file
def print_stats(self, graph=True):
avg_delay = mean(m.delay() for m in self.exercise.all())
avg_left_delay = ... |
from scipy.stats import norm
import random
import numpy as np
"""
Given the current block index, return the corresponding position in SAVE method
For example,
for current_block_idx = (1,2), which means the first block of samples in second time block.
it will return the start position of first block of samp... |
#! /usr/bin/python
# -*- coding: utf-8 -*-
##########################################################################
# Fault Displacement Slip-Curve (FDSC) v1.0 #
# #
# Copyright (C) (2013-2014) <NAME> <EMAIL> ... |
<gh_stars>0
from glob import glob
import numpy as np
import scipy.misc
import os
class LSUN(object):
def __init__(self, path, cat=None):
self.path = path
self.train_images = np.empty((0))
self.train_label = None
if cat:
self.categories = cat
else:
se... |
from scipy import misc
import numpy as np
from scipy import ndimage
import matplotlib.pyplot as plt
image = misc.imread('A_adding210',mode="L")#put your path and name of image
# convert image into a array
image = np.asarray(image)
# put pixels in a 1D array by flattening out image array
flat = image.flatten()
# it sh... |
from speakingfacespy.imtools import make_dir
from imutils import paths
import scipy.io.wavfile
import argparse
import cv2
import os
def extract_frame(video_path, duration, path_to_image, sub_id, trial_id, pos_id, cmd_id, stream_id):
# initialize the video stream and
# pointer to output video file
vs = c... |
<reponame>pauxy-qmc/pauxy
import numpy
import pandas as pd
import scipy.stats
import scipy.optimize
from pauxy.analysis.extraction import extract_data, set_info, get_metadata
from pauxy.analysis.blocking import average_ratio
def analyse_energy(files):
sims = []
files = sorted(files)
for f in files:
... |
#!/usr/bin/env python
# coding: utf-8
## Generate HTML reports with D3 graphs using Python, Plotly, and Pandas
# You can download the example report that this script generate from this link.
# <a href="d3.js">d3.js</a> is an amazing JavaScript library for creating interactive, online graphics and charts. Plotly l... |
<gh_stars>10-100
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.path
import numexpr as ne
import scipy as sp
import scipy.sparse
plt.ion()
import pybie2d
"""
Demonstrate how to use the pybie2d package to solve an interior/exterior
Laplace problem on a complicated domain u... |
<reponame>jtbuch/ml-fires<filename>notebooks/ml_utils.py<gh_stars>1-10
import numpy as np
import pandas as pd
#from time import clock
from datetime import date, datetime, timedelta
from cftime import num2date, date2num, DatetimeGregorian
from tqdm import tqdm
from copy import deepcopy
#Import and write files
import cs... |
"""
Script to help load EEG data files, separating files by class type
"""
import mne
import glob
import pandas
import shutil
import numpy as np
import math
import os
import re
from scipy import signal
CWD = os.path.dirname(os.path.realpath(__file__))
class DataLoader(object):
"""
Data Loader class t... |
### Importing dependencies
# Gaussian sampler
from sampler import samplerz
# Gaussian sampler with repetitions
from sampler_rep import samplerz_rep
# Imports Falcon signature scheme
from falcon import falcon
# Estimators for moments
from scipy.stats import skew, kurtosis, moment
# Statistical (normality) t... |
<filename>charts/charts/charts/base.py
import math
import statistics
import time
import traceback
from operator import itemgetter
from charts.orm.base import Base as ORMBase
class Base:
def __init__(self, create_db_connection, data, publisher, logger):
self.logger = logger
self.create_db_connectio... |
#!/usr/bin/env python
'''
qvalue: A python port of the qvalue package for R
'''
__author__ = "<NAME>"
__copyright__ = "Copyright 2011"
__credits__ = ["<NAME>", "<NAME>"]
__license__ = "FreeBSD"
__version__ = "0.2"
__maintainer__ = "<NAME>"
__email__ = "<EMAIL>"
try:
from scipy import interpolate
from scipy.i... |
import numpy
from scipy.ndimage import convolve
from skimage.data import camera
from skimage.util import random_noise
from dexp.processing.filters.fft_convolve import fft_convolve
from dexp.utils.backends import Backend, CupyBackend, NumpyBackend
def demo_fft_convolve_numpy():
with NumpyBackend():
_demo_... |
import numpy as np
import os, sys, time, shutil, tempfile
from tqdm import trange, tqdm
from urllib.request import urlopen
from urllib.parse import urlparse
import tempfile
from scipy.ndimage import median_filter
import cv2
from mxnet import gluon, nd
from mxnet.gluon import nn
import mxnet as mx
from . import trans... |
# This program creates FIR filter signals from the the recordings in folder
# "recordings".
# Main libraries
import numpy as np
from scipy.io import wavfile
# System libraries
import os
import sys
def exit():
print(50*'-')
sys.exit()
# Plotting libraries and settings
import matplotlib.pyplot as plt
import s... |
# Test QP solver against Maros Mezaros Benchmark suite
import numpy as np
import numpy.linalg as la
import scipy.io as spio
import osqppurepy
import matplotlib.pyplot as plt
# Get data
f = '../../../../extra/difficult_problems/data/polish_fail.mat'
m = spio.loadmat(f)
P = m['P']
A = m['A']
q = m['q'].T.flatten()
l = m... |
#!/usr/bin/python
import re
import os
import sys
import scipy
import argparse
from HTMLParser import HTMLParser
from nltk.tokenize.treebank import TreebankWordTokenizer
from nltk.tokenize.punkt import PunktSentenceTokenizer
from nltk.tag.stanford import StanfordTagger
from nltk.stem.snowball import SnowballStemmer
de... |
import os
import h5py
import matplotlib.pyplot as plt
import numpy as np
from scipy import signal
from scipy.fft import irfft, rfft, rfftfreq
from scipy.interpolate import interp1d
import tensorflow as tf
from . import gw_utils as gwu
class GwTimeseries:
def __init__(self, ts, freq, epoch=0, name=''):
se... |
import pickle
from pathlib import Path
from typing import List, Union
from nptyping import Array
from scipy.sparse import lil_matrix
from Node import Node
class Graph:
def __init__(self, nodes: Array[Node]):
assert isinstance(nodes, Array[Node])
self.__set_node_ids(nodes)
self.__nodes =... |
<reponame>annawzz/barbecue<gh_stars>0
# -*- coding: utf-8 -*-
from fractions import Fraction
def vnmax(features):
return sum([max([j['value'] for j in i['enum']]) for i in features])
def calculate_coeficient(features, parameters):
vmax = Fraction(vnmax(features))
vn = sum([Fraction(i['value']) for i in... |
<filename>pp_sketch/__main__.py
# Copyright 2019-2020 <NAME>
'''Wrapper around sketch functions'''
import os, sys
import numpy as np
from scipy.sparse import save_npz
import pickle
import h5py
import pp_sketchlib
from .matrix import ijv_to_coo
from .__init__ import __version__
def iterDistRows(refSeqs, querySeqs... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Feb 17 10:06:36 2021
@author: patrice
"""
import numpy as np
import glob
import seaborn as sns
import statistics
import matplotlib.pyplot as plt
import os
ScorePath1 = '/media/patrice/DataDrive/SEE_ICE/FullData_Revision/Jak_VGG16_joint_50_RGBNIR_fp16... |
#
# Copyright (c) 2017, Intel Corporation.
#
# This program is free software; you can redistribute it and/or modify it
# under the terms and conditions of the GNU General Public License,
# version 2, as published by the Free Software Foundation.
#
# This program is distributed in the hope it will be useful, but WITHOUT... |
import sys,time,datetime,copy,subprocess,itertools,pickle,warnings
import numpy as np
import scipy as sp
import pandas as pd
from matplotlib import pyplot as plt
import matplotlib as mpl
class Data_Fin(pd.core.frame.DataFrame):
_metadata = ['t','dt']
@property
def _constructor(self):
ret... |
import numpy
import scipy.interpolate
def nearest_index(array, value):
"""
Returns the index from array that is less than the value specified.
"""
array = numpy.asarray(array)
idx = (numpy.abs(array - value)).argmin()
return idx
def find_nearest(array, value):
"""
Returns the value fro... |
import cv2
import os
from scipy.io import loadmat
import os.path as osp
import numpy as np
import json
from PIL import Image
import pickle
import re
import sys
#from numba import jit
from sklearn.metrics import average_precision_score
from sklearn.preprocessing import normalize
from iou_utils import get_max_iou
def ... |
#!/usr/bin/env python
# Copyright 2014-2019 The PySCF Developers. All Rights Reserved.
#
# 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... |
from numpy.testing import *
import numpy.core.umath as ncu
import numpy as np
import nose
from numpy import inf, nan, pi
class TestDivision(TestCase):
def test_division_int(self):
# int division should return the floor of the result, a la Python
x = np.array([5, 10, 90, 100, -5, -10, -90, -100, -12... |
<reponame>tomwhite/anndata<filename>anndata/tests/readwrite.py
from importlib.util import find_spec
from pathlib import Path
import numpy as np
import pandas as pd
import pytest
from scipy.sparse import csr_matrix
import anndata as ad
HERE = Path(__file__).parent
# -------------------------------------------------... |
<reponame>Clinical-Genomics/scout
import datetime
import logging
import re
from fractions import Fraction
from glob import glob
from pathlib import Path
from pprint import pprint as pp
from ped_parser import FamilyParser
from scout.constants import PHENOTYPE_MAP, SEX_MAP
from scout.exceptions import PedigreeError
fro... |
<filename>zippy/benchmarks/src/benchmarks/sympy/sympy/printing/jscode.py
"""
Javascript code printer
The JavascriptCodePrinter converts single sympy expressions into single
Javascript expressions, using the functions defined in the Javascript
Math object where possible.
"""
from __future__ import print_function, div... |
import numpy as np
import torch
import torch.nn as nn
from scipy import linalg
from tqdm import tqdm
from basicsr.archs.inception import InceptionV3
def load_patched_inception_v3(device='cuda',
resize_input=True,
normalize_input=False):
# we may not res... |
import argparse
import functools
import json
import logging
import numpy as np
import os
import random
from overrides import overrides
from scipy.stats import kendalltau, pearsonr, spearmanr
from typing import Dict, List, Tuple, Union
from sacrerouge.commands import RootSubcommand
from sacrerouge.commands.correlate im... |
<filename>src/generative_model/metrics.py
"""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 distribution is given b... |
<reponame>Tapot/evidently
#!/usr/bin/env python
# coding: utf-8
import json
from typing import Optional
import pandas as pd
import numpy as np
from scipy.stats import probplot
import plotly.graph_objs as go
from evidently import ColumnMapping
from evidently.analyzers.regression_performance_analyzer import Regressio... |
<gh_stars>0
from glia import libglia
from feat_extr import get_features
from hed.run import Network
import torch
import params
from pascal_voc_loader import pascalVOCLoader
from loader import Loader
import matplotlib.pyplot as plt
from skimage import io, segmentation, color
import numpy as np
import os
from os.path imp... |
import numpy as np
import time
import torch
from lietorch import SE3, LieGroupParameter
from scipy.spatial.transform import Rotation as R
import cv2
import configargparse
import os, sys
sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
from utils import *
from render_utils i... |
<gh_stars>1-10
import os
import re
import gzip
import json
from collections import defaultdict
from itertools import groupby
from subprocess import run
import numpy as np
import pandas as pd
import pysam
from scipy.sparse import coo_matrix
from scipy.io import mmwrite
def read_gtf(gtf):
gene_table = []
mt_rege... |
from __future__ import absolute_import
from __future__ import print_function
import autograd.numpy as np
from autograd import value_and_grad
from scipy.optimize import minimize
import matplotlib.pyplot as plt
import os
from six.moves import range
rows, cols = 40, 60
# Fluid simulation code based on
# "Real-Time Flu... |
#! /usr/bin/env python
#
# Author: <NAME>
# Date: April 17, 2008
#
# Copyright (C) 2008 <NAME>
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
#
# 1. Redistributions of source code must retain the above copyright
# ... |
import numpy as np
from scipy.stats import rankdata
from functools import partial
from nptyping import Array
from sklearn.metrics import pairwise_distances
from sklearn.base import BaseEstimator, TransformerMixin
class BoostedSURF(BaseEstimator, TransformerMixin):
"""sklearn compatible implementation of the boost... |
from __future__ import print_function, division
import copy
from collections import defaultdict
from sympy.core.containers import Dict
from sympy.core.compatibility import is_sequence, as_int, range
from sympy.core.logic import fuzzy_and
from sympy.core.singleton import S
from sympy.functions.elementary.miscellaneous... |
import unittest
import numpy
try:
import scipy.sparse
scipy_available = True
except ImportError:
scipy_available = False
import cupy
import cupy.sparse
from cupy import testing
def _make(xp, sp, dtype):
data = xp.array([0, 1, 2, 3], dtype)
row = xp.array([0, 0, 1, 2], 'i')
col = xp.array([0,... |
<gh_stars>0
#!/usr/bin/env spcli
# <NAME> <<EMAIL>>
#
# create an He file with the following format:
# dHe He POP1 POP2 POP3 ...
from seqpy import cout, cerr
from seqpy.cmds import arg_parser
from seqpy.core.bioio import tabparser
import allel
import numpy as np
import scipy.spatial
def init_argparser(p=None):
... |
<reponame>wangyusu/pymatgen
# coding: utf-8
# Copyright (c) Pymatgen Development Team.
# Distributed under the terms of the MIT License.
"""
This module provides classes for non-standard space-group settings
"""
import re
from fractions import Fraction
from typing import List, Tuple, Union
import numpy as np
from p... |
import numpy as np
from numba import njit
import scipy.sparse as sp
import scipy.linalg as spl
import tensorflow as tf
from graphgallery import functional as gf
from graphgallery.attack.targeted import Common
from graphgallery.attack.utils.estimate_utils import (
estimate_loss_with_delta_eigenvals,
estimate_l... |
import numpy as np
from scipy.stats.distributions import chi2
from abc import ABC, abstractmethod
class NoiseObject(ABC):
def __init__(self, **kwargs):
self.arguments = kwargs
super().__init__()
@abstractmethod
def calc(self, raw_data):
pass
class CalculateGaussia... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.