text string |
|---|
# Copyright (c) Pymatgen Development Team.
# Distributed under the terms of the MIT License.
"""
Classes for reading/manipulating/writing VASP ouput files.
"""
import datetime
import glob
import itertools
import json
import logging
import math
import os
import re
import warnings
import xml.etree.ElementTree as ET
fro... |
<filename>sympy/core/tests/test_power.py
from sympy.core import (
Basic, Rational, Symbol, S, Float, Integer, Mul, Number, Pow,
Expr, I, nan, pi, symbols, oo, zoo, N)
from sympy.core.tests.test_evalf import NS
from sympy.core.function import expand_multinomial
from sympy.functions.elementary.miscellaneous impor... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri, 25 May 2018 20:29:09
@author: luohao
"""
"""
CVPR2017 paper:<NAME>, <NAME>, <NAME>, et al. Re-ranking Person Re-identification with k-reciprocal Encoding[J]. 2017.
url:http://openaccess.thecvf.com/content_cvpr_2017/papers/Zhong_Re-Ranking_Person_Re-Id... |
# -*- coding: utf-8 -*-
# Owner(s): ["module: linear algebra"]
import torch
import numpy as np
import unittest
import itertools
import warnings
import math
from math import inf, nan, isnan
import random
from random import randrange
from itertools import product
from functools import reduce, partial, wraps
from torch... |
"""Rank genes according to differential expression.
"""
import numpy as np
import pandas as pd
from math import sqrt, floor
from scipy.sparse import issparse
from .. import utils
from .. import settings
from .. import logging as logg
from ..preprocessing._simple import _get_mean_var
def rank_genes_groups(
a... |
import emcee
import logging
import numpy as np
from scipy import optimize
from robo.models.base_model import BaseModel
from robo.priors.bayesian_linear_regression_prior import BayesianLinearRegressionPrior
def linear_basis_func(x):
return np.append(x, np.ones([x.shape[0], 1]), axis=1)
def quadratic_basis_func... |
"""Module for indexing many-body states using Lin tables."""
import itertools
import numpy as np
try:
from scipy.special import factorial
except ImportError:
# For backwards compatibility with older versions of SciPy
from scipy.misc import factorial
from .wrappers.mytypes import boolnp
from .wrappers.myt... |
import pandas as pd
import numpy as np
from scipy import stats
from sklearn.linear_model import LinearRegression
import pickle
dat = pd.read_csv('Linear_Reg_Dat.csv')
dat.dropna(subset = ['Salary'], axis=0, inplace=True)
z = np.abs(stats.zscore(dat))
dat = dat[(z < 3).all(axis=1)]
x = dat[['YearsExperi... |
'''
problems/healthy_skin_fixed_pads/runner.py
Problem
-------
Healthy skin extension
Boundary conditions:
--------------------
right pad: fixed displacements
left pad: fixed displacements
Maybe should start with some prestress because at zero displacement, the force
is not zero
'''
from dolfin import *
import dol... |
from copy import copy
from sympy.tensor.array.dense_ndim_array import ImmutableDenseNDimArray
from sympy import Symbol, Rational, SparseMatrix, Dict, diff, symbols, Indexed, IndexedBase, S
from sympy.core.compatibility import long
from sympy.matrices import Matrix
from sympy.tensor.array.sparse_ndim_array import Immut... |
import logging
log = logging.getLogger(__name__)
from fractions import math
from math import gcd
import numpy as np
import pandas as pd
from scipy import signal
def as_numeric(x):
if not isinstance(x, (np.ndarray, pd.DataFrame, pd.Series)):
x = np.asanyarray(x)
return x
def db(target, reference=1)... |
<reponame>anjohan/dscribe<gh_stars>1-10
# -*- coding: utf-8 -*-
"""Copyright 2019 DScribe developers
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
... |
#!/usr/bin/env python3
import os
import cv2
import torch
import os.path
import numpy as np
import torchvision.transforms as transforms
from PIL import Image
from common import Config
import pickle as pkl
from utils.basic_utils import Basic_Utils
import scipy.io as scio
import scipy.misc
try:
from neupeak.utils.webc... |
<gh_stars>10-100
########################################################################################
# <NAME>, 2017 #
# Optic disc in a retina image detection in TensorFlow #
#####################################... |
<filename>deep_rl/agent/PCPG2_agent.py
# PCPG2 Agent
from ..network import *
from ..component import *
from .BaseAgent import *
import math, random, pdb, copy, sys
import numpy as np
from gym.spaces.discrete import Discrete
from gym.spaces.box import Box
from torch.utils.data import DataLoader, TensorDataset
import... |
<filename>kernelmethods/operations.py
# -*- coding: utf-8 -*-
"""
This module implements the common kernel operations such as
- normalization of a kernel matrix (KM),
- centering (one- and two-sample cases),
- evaluating similarity, computing alignment,
- frobenius norms,
- linear combinations and
- checking wh... |
import cPickle
from scipy import signal
import librosa
import adaptfilt
from sys import argv
with open("netFile.pkl", "rb") as arch:
net = cPickle.load(arch)
y,sr = librosa.load(argv[1], duration=10.0)
w = y
for i in xrange(int(argv[2])):
r, s, n = net.activate(w)
r = abs(int(round(r)))
s = abs(int(... |
import numpy as np
import subprocess
import sys
TEST_BODY = r"""
import pytest
import numpy as np
from numpy.testing import assert_allclose
import scipy
import sys
import pytest
if hasattr(scipy, 'fft'):
raise AssertionError("scipy.fft should require an explicit import")
np.random.seed(1234)
x = np.random.randn(... |
<filename>lsml/data/dim2/hamburger.py
import logging
import numpy as np
from scipy.stats import beta
from scipy.ndimage import gaussian_filter
logger = logging.getLogger(__name__)
def make(n=101, r=25, ishift=0, jshift=0,
sigma_noise=0.1, sigma_smooth=2,
cut_b=0, cut_theta=0, cut_thickness=5, rs... |
import cStringIO, sys, csv, copy, ImageDraw, Image, ImageClass
from FindCenter import findCenter, showIm, getBiImList, getEllipse, getView
from PyQt4 import QtGui
from myFunc import detect_peaks, pil16pil8, a16a8, getStrVal
from myMath import fitLine, fitCirc
from myFigure import myFigure
from scipy import ndimage, opt... |
#from collections.abc import Sequence
#import itertools
import numpy as np
import types
#import xarray
#from pleque.utils.decorators import deprecated
class FluxFunctions:
# def interpolate(self, coords, data)
# def interpolate(self, R, Z, data):
# pass
def __init__(self, equi):
# _flux... |
<reponame>wanxinjin/Safe-PDP<filename>Examples/SPlan/SPlan_Rocket.py<gh_stars>10-100
import numpy as np
from SafePDP import SafePDP
from SafePDP import PDP
from JinEnv import JinEnv
from casadi import *
import scipy.io as sio
import matplotlib.pyplot as plt
import time
import random
# --------------------------- load... |
<reponame>barentsen/photutils
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
This module implements classes, called Finders, for detecting stars in
an astronomical image. The convention is that all Finders are subclasses
of an abstract class called ``StarFinderBase``. Each Finder class
should defi... |
<reponame>nilax97/col774<filename>assignment4/src/svm.py
import os
import scipy.io
import json
import cv2
import numpy as np
import pickle
from sklearn.decomposition import PCA
from sklearn.model_selection import train_test_split
from sklearn.svm import SVC, LinearSVC
from sklearn.metrics import classification_report, ... |
<reponame>keithfma/somerville-slope<filename>somerville_slope.py
"""
Somerville MA LiDAR Slope Analysis
This (importable) module contains all subroutines used
"""
# TODO: too many spurious results -- try a morphological filter on the gridded
# elev / slope results to handle ugly edges of house footprints -- try
# ... |
<gh_stars>100-1000
import glob
import os
import cv2
import numpy as np
import scipy.io as sio
from tqdm import tqdm
from mmhuman3d.core.conventions.keypoints_mapping import convert_kps
from mmhuman3d.data.data_structures.human_data import HumanData
from .base_converter import BaseConverter
from .builder import DATA_C... |
<reponame>BSchilperoort/python-dts-calibration
# coding=utf-8
import os
import numpy as np
import scipy.sparse as sp
from scipy import stats
from dtscalibration import DataStore
from dtscalibration import read_xml_dir
from dtscalibration.calibrate_utils import wls_sparse
from dtscalibration.calibrate_utils import wls... |
"""
Tests for :func:`nilearn.plotting.plot_connectome` and
deprecated :func:`nilearn.plotting.plot_connectome_strength`.
"""
import os
import pytest
import numpy as np
import matplotlib.pyplot as plt
from scipy import sparse
from matplotlib.patches import FancyArrow
from nilearn.plotting import plot_connectome, plot_c... |
import numpy as np
from scipy.optimize import fsolve
from astropy.utils import isiterable
def stellarmass_from_halomass(log_Mhalo, z=0):
""" Stellar mass from Halo Mass from Moster+2013
https://doi.org/10.1093/mnras/sts261
Args:
log_Mhalo (float): log_10 halo mass
in solar mass units.... |
#!/usr/bin/env python
import math
import numpy as np
import signal
import scipy.ndimage as ndimage
import pdb
"""
This file contains scripts to filter ALOS data.
"""
def enhanced_lee_filter(img, window_size = 5, n_looks = 16):
'''
Filters a masked array with the enhanced lee filter.
Based on formulatio... |
<filename>2018/d23.py
#!/usr/bin/env python3
import sys
import re
import itertools
import z3
from scipy.spatial import distance
from pprint import pprint
INPUTS = ['d23-input.txt', 'd23-input-example1.txt', 'd23-input-example2.txt']
DEBUG = False
INPUT = INPUTS[2] if DEBUG else INPUTS[0]
input_re = re.compile(r'pos=<... |
import os
import sys
import yaml
import numpy as np
import matplotlib.pyplot as plt
import scipy.linalg as scli
from mpl_toolkits.mplot3d import Axes3D
import seaborn as sns
import pandas as pd
from rdkit import Chem
kcal_to_eV=0.0433641153
kB=8.6173303e-5 #eV/K
T=298.15
kBT=kB*T
def readXYZ(filename):
infile=ope... |
<filename>compute_distances.py<gh_stars>0
import scipy as sp
import sys
import os, glob
import os.path as path
import scipy.spatial.distance as spd
from scipy.io import loadmat, savemat
import json
import torch
import numpy as np
import argparse
def compute_channel_distances(mean_vector, features):
mean_vector ... |
# Figure 3, panels (c) and (d)
import sys
sys.path.append("../../")
device_str, lang, _dpi = sys.argv[1], sys.argv[2], int(sys.argv[3])
###########################################################
from pathlib import Path
reproduced_results = Path("reproduced-results")
from sympy import exp as sp_exp
from sympy imp... |
<filename>caserec/recommenders/rating_prediction/base_rating_prediction.py
# coding=utf-8
""""
This class is base for rating prediction algorithms.
"""
# © 2018. Case Recommender (MIT License)
from scipy.spatial.distance import squareform, pdist
import numpy as np
from caserec.evaluation.rating_prediction impo... |
import os
import tarfile
import zipfile
from os import path
from sacred import Experiment
from scipy.io import loadmat
from torchvision.datasets.utils import download_url
ex1 = Experiment('Prepare CUB')
@ex1.config
def config():
cub_dir = path.join('data', 'CUB_200_2011')
cub_url = 'http://www.vision.caltec... |
import argparse
import tensorflow as tf
from tensorflow.keras.layers import *
from tensorflow.keras.models import Model, load_model
from tensorflow.keras.optimizers import Adam
from tensorflow.keras.losses import BinaryCrossentropy
from tqdm import tqdm
import numpy as np
import robots_core
from robots_core.train i... |
"""Bayesian Gaussian Mixture Models and
Dirichlet Process Gaussian Mixture Models"""
from __future__ import print_function
# Author: <NAME> (<EMAIL>)
# <NAME> <<EMAIL>>
#
# Based on mixture.py by:
# <NAME> <<EMAIL>>
# <NAME> <<EMAIL>>
#
# Important note for the deprecation cleaning of 0.20 :
#... |
<gh_stars>1-10
import compiler
import parser
from compiler.transformer import Transformer
from compiler.ast import CallFunc, Name, Const
from compiler.pycodegen import ExpressionCodeGenerator
import re
#this is python stdlib symbol, not SymPy symbol:
import symbol
from sympy.core.basic import Basic
from sympy.core.sy... |
<gh_stars>0
##########################################################################################################
# #
# This code "ODE model simulation" is written by <NAME> for "a model of lysosomal acidificatio... |
<filename>data/reactor_anu_spectra/Mueller/offeq/mueller_offequilibrium.py
#!/usr/bin/env python
import numpy as N
from matplotlib import pyplot as P
from collections import OrderedDict
from scipy.interpolate import interp1d
energy = N.concatenate([[1.8], N.linspace( 2., 4.5, 6 )])
"""First and last poinst are added ... |
import argparse
import string
import os
import time
from multiprocessing import Pool
from itertools import repeat
from scipy.stats import bernoulli
import pandas as pd
import numpy as np
import sys
from tqdm import tqdm
np.random.seed(0)
def parse_args():
parser = argparse.ArgumentParser(description='Reverse subs... |
import anndata
import scipy.sparse
import numpy as np
from sklearn.decomposition import TruncatedSVD
from sklearn.neighbors import NearestNeighbors
# VIASH START
par = {
"input_mod1": "../../../../resources_test/common/pbmc_1k_protein_v3.censored_rna.h5ad",
"input_mod2": "../../../../resources_test/common/pbm... |
#!/usr/bin/env python
from fractions import Fraction as F
notes = "C C# D D# E F F# G G# A A# B".split()
pythagoras = [F(1,1), F(2187,2048), F(9,8), F(32,27), F(81,64), F(4,3),
F(729,512), F(3,2), F(6561,4096), F(27,16), F(16,9), F(243,128)]
just_intonation = [F(1,1), F(16,15), F(9,8), F(6,5), F(5,4)... |
from typing import Union, List, Tuple, Sequence, Dict, Any, Optional, Collection
from copy import copy
from pathlib import Path
import pickle as pkl
import logging
import random
import lmdb
import numpy as np
import torch
import torch.nn.functional as F
from torch.utils.data import Dataset
from scipy.spatial.distance ... |
#!/usr/bin/env ipython
#
# untitled.py
#
# Copyright (c) 2020 <NAME>
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the MIT License.
#
# See accompanying LICENSE.md or https://opensource.org/licenses/MIT.
#
import sys
import atexit
import logging
import numpy as np
f... |
#
# Compare masks produced by BBs, axis-aligned ellipses and full ellipses
# with the GT maks. Also explores OBBs from segmentation masks
#
# IMPORTANT: ignores segmentation masks that formed by mopre than one connected component
#
#
import cv2, os, pickle
import numpy as np
from numpy import sqrt
import matplotli... |
<gh_stars>0
# Tests of the quasiisothermaldf module
from __future__ import print_function, division
import numpy
#fiducial setup uses these
from galpy.potential import MWPotential, vcirc, omegac, epifreq, verticalfreq
from galpy.actionAngle import actionAngleAdiabatic, actionAngleStaeckel
from galpy.df import quasiisot... |
from datetime import datetime
import numpy as np
import pandas as pd
from scipy.stats import pearsonr
from scipy.stats import zscore
import matplotlib.pyplot as pyplot
def drawHist(x):
#创建散点图
#第一个参数为点的横坐标
#第二个参数为点的纵坐标
pyplot.hist(x, 100)
pyplot.xlabel('x')
pyplot.ylabel('y')
pyplot.title('... |
import numpy as np
from scipy import ndimage as nd
from scipy.interpolate import interp1d
from astropy import units as u
from astropy.io import fits
from starkit.gridkit.io.process import BaseProcessGrid
from starkit.gridkit.util import convolve_to_resolution
class PhoenixProcessGrid(BaseProcessGrid):
uv_wave... |
"""Tests for dense recursive polynomials' basic tools. """
from sympy.polys.densebasic import (
dup_LC,
dmp_LC,
dup_TC,
dmp_TC,
dmp_ground_LC,
dmp_ground_TC,
dmp_true_LT,
dup_degree,
dmp_degree,
dmp_degree_in,
dmp_degree_list,
dup_strip,
dmp_strip,
dmp_validate,
... |
<reponame>viathor/OpenFermion-Cirq
# 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 t... |
# -*- coding: utf-8 -*-
"""
Created on Sun Sep 11 19:29:11 2016
@author: DIP
"""
from normalization import normalize_corpus
from utils import build_feature_matrix
import numpy as np
toy_corpus = ['The sky is blue',
'The sky is blue and beautiful',
'Look at the bright blue sky!',
'Python is a great Programming lang... |
<filename>process/util.py
import os
import numpy as np
from scipy.io import loadmat, savemat
import neurokit2 as nk
import matplotlib.pyplot as plt
# Find Challenge files.
def load_label_files(label_directory):
label_files = list()
for f in sorted(os.listdir(label_directory)):
F = os.path.join(label_di... |
# Script to perform decoding analyses on the trained layer activations and the recurrent flow
# Requires tensorflow 1.13, python 3.7, scikit-learn, and pytorch 1.6.0
############################# IMPORTING MODULES ##################################
import torch
import torch.nn as nn
import torch.nn.functional as F
im... |
<filename>mne/viz/_3d.py<gh_stars>0
"""Functions to make 3D plots with M/EEG data
"""
from __future__ import print_function
# Authors: <NAME> <<EMAIL>>
# <NAME> <<EMAIL>>
# <NAME> <<EMAIL>>
# <NAME> <<EMAIL>>
# <NAME> <<EMAIL>>
#
# License: Simplified BSD
from ..externals.six impor... |
"""
The util module provides a collection of general purpose methods.
"""
from . import numeric
import sys
import os
import numpy
import collections.abc
import inspect
import functools
import operator
import numbers
import pathlib
import ctypes
import io
import contextlib
supports_outdirfd = os.open in os.supports_di... |
<filename>model/needs.py
"""
Things to do with the needs of consumers for products
"""
import numpy as np
from scipy.stats import beta
from .beta_distr import get_beta_params
from .utility import multinomial
def discretize_a_composite_beta(modes, vars, n_bins=500):
"""
Computes the weight of a composite bet... |
import numpy as np
import scipy
import math
class frame:
def __init__(self, R, t):
self.R = R
self.t = t
r_t = np.concatenate((R, t), 1)
bot = np.array([0, 0, 0, 1])
self.F = np.concatenate((r_t, bot))
def get_R(self):
return self.R
def get_t(self):
r... |
<gh_stars>10-100
from __future__ import print_function, division
import os
import torch
import pandas as pd
from skimage import io, transform
import numpy as np
import matplotlib.pyplot as plt
from torch.utils.data import Dataset, DataLoader, TensorDataset
from torchvision import transforms, utils
import torch.nn as nn... |
#!/usr/bin/env python
"""
This module implements more advanced transformations.
"""
from __future__ import division
__author__ = "<NAME>, <NAME>"
__copyright__ = "Copyright 2012, The Materials Project"
__version__ = "1.0"
__maintainer__ = "<NAME>"
__email__ = "<EMAIL>"
__date__ = "Jul 24, 2012"
import numpy as np
f... |
<reponame>KristapsE/DP4-AI<gh_stars>10-100
import numpy as np
import qml
from qml.fchl import get_atomic_kernels
from scipy.stats import gaussian_kde as kde
import pickle
from scipy.stats import gmean
from pathlib import Path
from scipy import stats
import os
import pathos.multiprocessing as mp
import copy
import gzip
... |
"""Utils to check the samplers and compatibility with scikit-learn
"""
# Adapted from imbalanced-learn
# Adapated from scikit-learn
# Authors: <NAME> <<EMAIL>>
# License: MIT
import sys
import traceback
import warnings
from collections import Counter
from functools import partial
import pytest
import numpy as np
f... |
import os
import numpy as np
from astropy.cosmology import FlatLambdaCDM
from lenstronomy.Cosmo.lens_cosmo import LensCosmo
from hierarc.Sampling.mcmc_sampling import MCMCSampler
import corner
import matplotlib.pyplot as plt
from scipy.stats import norm, median_abs_deviation
__all__ = ["reorder_to_tdlmc", "pred_to_nat... |
<gh_stars>0
from scipy.spatial import cKDTree
import pandas as pd
import torch
import numpy as np
def nearest_neighbours(data, query_data, k):
kdtree = cKDTree(data)
return (kdtree.query(query_data, k)[1]).T
def load_meta_data(textfile):
meta_data = pd.read_csv(textfile, header=0)
return meta_data.values.tol... |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import mxnet as mx
from scipy.signal import savgol_filter
import pandas as pd
import numpy as np
def add_nan_trajectories(trajectories, max_frame):
"""Add np.nan to frame where the x,y coordinates are mis... |
<reponame>joelphillips/pypyramid
'''
Created on Oct 25, 2010
@author: joel
'''
import pypyr.functions as pf
import pypyr.utils as pu
import scipy.linalg as sl
import math
import pylab
import matplotlib.pyplot as mp
#import enthought.mayavi.mlab as emm
import numpy as np
def poisson(N, points):
''' Solves lap u ... |
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
from sklearn.feature_extraction.text import CountVectorizer
from nltk.corpus import stopwords
from scipy import spatial
import re
import random
import operator
import itertools
import numpy as np
i... |
from scipy.io import loadmat as loadmat
import os
import subprocess
import pandas as pd
import numpy as np
class RAW():
"""Creates a pandas dataframe out fo eyetrace data
This DF contains feature1, feature2, xmotion, ymotion, and timesecs
"""
def __init__(self, data_dir, dt_chopout=0):
files =... |
<gh_stars>0
# Copyright 2019 Xanadu Quantum Technologies Inc.
# 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... |
from __future__ import division
from scipy.optimize import minimize_scalar
import numpy as np
def vbmf(Y, cacb=1024, sigma2=None, H=None):
"""Implementation of the analytical solution to Variational Bayes Matrix Factorization.
This function can be used to calculate the analytical solution to VBMF.
This ... |
<reponame>RoshanRane/ML_for_IMAGEN
#################################################################################
#!/usr/bin/env python
# coding: utf-8
""" IMAGEN Post hoc analysis Helper in all Session """
# Author: <NAME>, <<EMAIL>>
# : <NAME>, <<EMAIL>>
# Last modified: 17th January 2022
import os, sys, ins... |
<gh_stars>0
# -------------------------------------------------------------
# Authors: <NAME> (10784012)
# <NAME> (10542590)
# Date: 11 April 2016
# File: naive_bayes.py
# -------------------------------------------------------------
import numpy as np
import scipy.stats as sp
import matplotlib.pyplot as... |
<filename>downstream/voxceleb2_ge2e/utils.py
import numpy as np
import pickle
from scipy.optimize import brentq
from scipy.interpolate import interp1d
from sklearn.metrics import roc_curve ,auc
import IPython
import pdb
from itertools import accumulate
from functools import partial
def EER(labels, scores):
"""
... |
<reponame>srio/paper-transfocators-resources
import numpy
from srxraylib.plot.gol import plot
import matplotlib.pylab as plt
beam_dimension_at_slit_in_um = 565 # needed for calculating Fresnel number
LENS_RADII_IN_MICRONS = [100, 500, 1000]
LENS_RADII_IN_MICRONS = [400, 200, 100, 50, 25]
for j in range(len(LE... |
import sys
from random import random, randint
from scipy.linalg import eigh_tridiagonal
UPPER = 100
def generate_symmetric_matrix(size: int) -> list:
main_diag = [random()*UPPER for elem in range(size)]
sym_diag = [random() for elem in range(size-1)]
return (main_diag, sym_diag)
if __name__ == "__main_... |
<filename>dataset.py
import pandas as pd
import matplotlib.pyplot as plt
from datetime import datetime
from matplotlib.figure import Figure
from region import Region
import numpy as np
from scipy.signal import savgol_filter
from state import State
from datetime import datetime, timedelta
import sys
def datePadding(... |
<gh_stars>0
import logging
import pprint
import os
import sys
import math
import torch
import time
import random
from sklearn.metrics import average_precision_score, roc_auc_score
from scipy.sparse import coo_matrix
import numpy as np
import utils
import joblib # import Parallel, delayed
from torch.utils.tensorboard i... |
<filename>fractopo_subsampling/plotting_utils.py
"""
Plotting utilities.
"""
import warnings
from itertools import count
from textwrap import wrap
from typing import Dict, Generator, Sequence, Tuple, Union
import geopandas as gpd
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import scipy.stats... |
<gh_stars>1-10
import logging
import os
import re
from typing import Any, Dict, List, Optional, Text, Type, Tuple
import numpy as np
import scipy.sparse
import rasa.shared.utils.io
import rasa.utils.io
import rasa.nlu.utils.pattern_utils as pattern_utils
from rasa.nlu import utils
from rasa.nlu.components import Comp... |
New Algorithms for Simulating Dynamical Friction
<NAME>, <NAME>, <NAME> — RadiaSoft, LLC
This notebook describes—and documents in code—algorithms for simulating
the dynamical friction experienced by ions in the presence of magnetized electrons.
The $\LaTeX$ preamble is here. $$ %% math text \newcommand{\hmhsp}{\mspa... |
import scipy.io as sio
import numpy as np
from feedforward_backprop import feedforward_backprop
digit_data = sio.loadmat('digit_data.mat')
X = digit_data['X']
y = digit_data['y']
_, num_cases = X.shape
train_num_cases = num_cases * 4 // 5
X = X.reshape((400, num_cases))
X = X.reshape((num_cases, 400))
# X has the shape... |
<gh_stars>0
"""Core of arithgen."""
import math
import random
from fractions import Fraction
from arithgen import ntheory
from arithgen.expr import (
Integer,
Addition,
Subtraction,
Multiplication,
Division,
)
def weighted_choice(choices):
"""Return a weighted random element from a non-empty... |
<gh_stars>1-10
#!/usr/bin/env python
# Written by <NAME>
# See readme.pdf for documentation
# Or go to http://www.isi.edu/~gregv/npeet.html
import scipy.spatial as ss
from scipy.special import digamma
from math import log
import numpy.random as nr
import numpy as np
import random
# CONTINUOUS ESTIMATORS
def entrop... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from backpack import extensions
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.autograd as autograd
from torch.autograd import Variable
import random
from statistics import mean
import math
import copy
import numpy... |
<filename>experiments/notebooks/augment_3d.py
# ---
# jupyter:
# jupytext:
# formats: ipynb,py
# text_representation:
# extension: .py
# format_name: light
# format_version: '1.4'
# jupytext_version: 1.2.4
# kernelspec:
# display_name: Python 3
# language: python
# name: ... |
from __future__ import absolute_import
from perses.dispersed import feptasks
from perses.utils.openeye import *
from perses.utils.data import load_smi
from perses.annihilation.relative import HybridTopologyFactory
from perses.annihilation.lambda_protocol import RelativeAlchemicalState, LambdaProtocol
from perses.rjmc.... |
#coding=utf-8
import pandas as pd
import numpy as np
import sys
import os
from sklearn import preprocessing
import datetime
import scipy as sc
from sklearn.preprocessing import MinMaxScaler,StandardScaler
from sklearn.externals import joblib
#import joblib
class FEbase(object):
"""description of class"""
def ... |
<filename>src/libs_v0/bddc.py
import numpy as np
import math
import scipy.sparse.linalg
from scipy.sparse import csr_matrix as csr
from scipy.sparse import bmat
# Class containing all the data that should be distributed per proc
class fineProc():
def __init__(self):
self.nI = 0 # Number of interi... |
<gh_stars>1-10
"""
Contains the function 'iterative_tikhonov' and the accompanying class.
"""
import numpy as np
import scipy.linalg as scilin
from inversion.solver import ClassicSolver
def iterative_tikhonov(fwd, y, x0, c0_root, delta, options):
"""
Implements the iterative Tikhonov method, which Tikhonov ... |
<reponame>gyulka/bashair<filename>db/influx.py
from pprint import pprint
from statistics import mean
from influxdb_client import InfluxDBClient, BucketRetentionRules
from config import settings
client = InfluxDBClient(
url=settings.INFLUXDB_V2_URL,
org=settings.INFLUXDB_V2_ORG,
token=settings.INFLUXDB_V2... |
<gh_stars>1-10
import pandas as pd
import numpy as np
from scipy import stats, linalg
from statsmodels.stats import multitest
def calculate_median_absolute(x):
"""Calculate Absolute median"""
return (x - x.median()).abs().median()
def fdr(x, alpha=0.05, method='fdr_bh'):
'''
Apply FDR correction to... |
import numpy as np
from scipy import interpolate
def fate_parfor(plist,fate_fname_base,time_interp):
radius = np.zeros((len(time_interp),len(plist)))
theta = np.zeros((len(time_interp),len(plist)))
v_rad = np.zeros((len(time_interp),len(plist)))
v_theta = np.zeros((len(time_interp... |
# coding=utf-8
"""Implement Part Affinity Fields
:param centerA: int with shape (2,), centerA will pointed by centerB.
:param centerB: int with shape (2,), centerB will point to centerA.
:param accumulate_vec_map: one channel of paf.
:param count: store how many pafs overlaped in one coordinate of accumulate_vec_map.
:... |
<gh_stars>10-100
# Copyright 2015 Novo Nordisk Foundation Center for Biosustainability, DTU.
# 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
# Un... |
#!/usr/bin/env python
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
# Acknowledgement: Part of the codes are adapted from Unnat Jain
import os
import numpy as np
impo... |
<gh_stars>1-10
from __future__ import (absolute_import, print_function)
import sympy as sp
from sympy.core.compatibility import exec_, PY3
from sympy.codegen.ast import Assignment
from sympy.codegen.algorithms import newtons_method, newtons_method_function
from sympy.codegen.fnodes import bind_C
from sympy.codegen.fu... |
<reponame>rebcabin/mathics-core<gh_stars>0
# cython: language_level=3
# -*- coding: utf-8 -*-
import sympy
import mpmath
import math
import re
import typing
from typing import Any, Optional
from functools import lru_cache
from mathics.core.formatter import encode_mathml, encode_tex, extra_operators
from mathics.core... |
<filename>examples/process_viral_data.py
import sys
import numpy as np
import pandas as pd
import scipy.stats as stats
# Individual,Position,n_percent,dip_percent,Mutation,BadReads
df = pd.read_csv(sys.stdin, usecols = ['Individual', 'Position', 'Mutation', 'BadReads'])
# df = df[df.Position >= 6558][df.Position <= ... |
#Copyright (c) 2009,2010 <NAME>
import numpy as num
import cudamat as cm
from cudamat import reformat
from scipy.io import loadmat, savemat
def logOnePlusExp(x, temp, targ = None):
"""
When this function is done, x should contain log(1+exp(x)). We
clobber the value of temp. We compute log(1+exp(x)) as... |
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