text string |
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<reponame>WajihCZ/NearPy<gh_stars>1-10
# -*- coding: utf-8 -*-
# Copyright (c) 2013 <NAME>
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation ... |
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from scipy.stats import t
if __name__ == "__main__":
# PDFs for the exponential distribution
sns.set_palette("deep", desat=.6)
sns.set_context(rc={"figure.figsize": (8, 4)})
x = np.linspace(0.0, 5.0, 100)
lambdas = [0.5, 1.0... |
# utility function meant specifically for the 6OHDA project
# written by <NAME>
# last edited 10/10/2018 (most code originally written nov. 2017)
import numpy as np
import warnings
from scipy.signal import butter, filtfilt, lfilter
from scipy import interpolate
from scipy import signal
from chronux import *
from numpy... |
<filename>lib/residual_analysis.py
import math
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import scipy.stats as stats
from scipy.stats import t
from scipy.stats import norm
import lib.residuals as res
import lib.least_squares as ls
import lib.p_from_ad as pad
def residual_analysis(x, y, d, ... |
################################
########### Imports ############
################################
import sys
import traceback
import numpy as np
import scipy.special as ss
import scipy.optimize as so
import scipy.integrate as si
import scipy.interpolate as inter
try:
import h5py as h5
h5py = 1
except ModuleNot... |
# -*- coding: utf-8 -*-
"""
Created on Fri Mar 26 09:24:51 2021
@author: Monique
"""
import numpy as np
# import math as math
import copy
import scipy.stats
import auxiliary_functions.f_aux as aux
from filterpy.kalman import ExtendedKalmanFilter as filterpy_EKF
from filterpy.kalman import UnscentedKalmanFilter as f... |
<reponame>DavidT3/XGA
# This code is a part of XMM: Generate and Analyse (XGA), a module designed for the XMM Cluster Survey (XCS).
# Last modified by <NAME> (<EMAIL>) 02/08/2021, 17:28. Copyright (c) <NAME>
import os
import warnings
from typing import Tuple, List, Union
import numpy as np
import pandas as pd
from ... |
<filename>scikitplot/plotters.py
"""
This module contains a more flexible API for Scikit-plot users, exposing
simple functions to generate plots.
"""
from __future__ import absolute_import, division, print_function, \
unicode_literals
import warnings
import itertools
import matplotlib.pyplot as plt
import numpy ... |
# -*- coding: utf-8 -*-
# <nbformat>3.0</nbformat>
# <markdowncell>
# # Testing Glider DAC access in Python
#
# This is a url from Kerfooot's TDS server, using the multidimensional NetCDF datasets created by a private ERDDAP instance. These multidimensonal datasets are also available from ERDDAP, along with a flatt... |
print(__doc__)
import numpy as np
from scipy import interp
import matplotlib.pyplot as plt
from sklearn import svm, datasets
from sklearn.metrics import roc_curve, auc
from sklearn.cross_validation import StratifiedKFold
###############################################################################
# Data IO and ge... |
<filename>code/test_reactor.py
import numpy as np
import matplotlib.pyplot as plt
from scipy.integrate import odeint
# Steady State Initial Condition
u_ss = 280.0
# Feed Temperature (K)
Tf = 350
# Feed Concentration (mol/m^3)
Caf = 1
# Steady State Initial Conditions for the States
Ca_ss = 1
T_ss = 304
x0 = np.empty(... |
def calderon(A, interior_op, exterior_op, interior_projector, scaled_exterior_projector, formulation, preconditioning_type):
if formulation == "alpha_beta":
if preconditioning_type == "calderon_squared":
A_conditioner = A
elif preconditioning_type == "calderon_interior_operator":
... |
<filename>sklearn/discriminant_analysis.py
"""
Linear Discriminant Analysis and Quadratic Discriminant Analysis
"""
# Authors: <NAME>
# <NAME>
# <NAME>
# <NAME>
# License: BSD 3-Clause
from __future__ import print_function
import warnings
import numpy as np
from scipy import linalg
from .e... |
def beta(dep):
if dep>6000:
dep=6000
import scipy.io as sio
v=sio.loadmat('velocity')
b=v['vs']/1000
return(b[int(dep)][0])
|
import numpy as num
from random import randrange
from scipy.sparse.linalg import gmres
import matplotlib.pyplot as plt
import math
import datetime
def gen_matrix(n1) :
a1 = ''
for i in range(n1):
for j in range(n1):
a1 += str(randrange(n1*10))
a1 += ' '
if i != n... |
import scipy.stats
import numpy as np
import pandas as pd
import scipy
print(scipy.__version__)
# 1.7.1
a = np.array([2**n for n in range(10)])
print(a)
# [ 1 2 4 8 16 32 64 128 256 512]
print(type(a))
# <class 'numpy.ndarray'>
print(a.mean())
# 102.3
print(np.mean(a))
# 102.3
print(scipy.stats.trim_me... |
<reponame>Permanganant/Raman-Spectrometer<filename>Raman_Spectrometer.py<gh_stars>1-10
#Raman1 Spectrometer
#Librarys
import numpy as np
import cv2
import matplotlib.pyplot as plt
from matplotlib import cm
#import peakutils
def find_nearest_index(arr, value):
"""For a given value, the funct... |
"""!
@brief A dataset creation which is compatible with pytorch framework
@author <NAME> {<EMAIL>}
@copyright University of illinois at Urbana Champaign
"""
import torch
import argparse
import os
import sys
import glob2
import numpy as np
from sklearn.externals import joblib
import scipy.io.wavfile as wavfile
from to... |
import os
import numpy as np
import pylab as pl
from scipy.interpolate import interp1d
files = ['fiberloss-elg.dat',\
'fiberloss-qso.dat',\
'fiberloss-lrg.dat',\
'fiberloss-sky.dat',\
'fiberloss-perfect.dat',\
'fiberloss-star.dat']
fo... |
<reponame>princeton-computational-imaging/MaskToF<filename>utils/tof.py<gh_stars>10-100
import torch
import numpy as np
from scipy.constants import speed_of_light
from itertools import product, combinations
def sim_quad(depth, f, T, g, e): # convert
"""Simulate quad amplitude for 3D time-of-flight cameras
Arg... |
from scipy import *
from scipy import linalg
import sys
import copy
def mprint(Us):
for i in range(shape(Us)[0]):
for j in range(shape(Us)[1]):
print "%11.8f %11.8f " % (real(Us[i,j]), imag(Us[i,j])),
print
def MakeOrthogonal(a, b, ii):
a -= (a[ii]/b[ii])*b
a *= 1/sqrt(dot(a,a... |
<reponame>pengyanghua/mxnet<filename>tests/python/unittest/test_random.py<gh_stars>0
# 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... |
<gh_stars>1-10
import shutil
import numpy as np
from pathlib import Path
import os
import sys
import glob
from natsort import os_sorted
import scipy.io as spio
import h5py
import matplotlib.pyplot as plt
import pandas as pd
import copy
import time
from whacc import image_tools
import whacc
def isnotebook():
try... |
"""
Generalized Least Squares with AR Errors
6 examples for GLSAR with artificial data
"""
#.. note: These examples were written mostly to cross-check results. It is still being
# written, and GLSAR is still being worked on.
import numpy as np
import numpy.testing as npt
from scipy import signal
import statsmod... |
import numpy as np
import statsmodels.api as sm
from scipy.stats import poisson, nbinom
from numpy.testing import assert_allclose
class TestGenpoisson_p(object):
"""
Test Generalized Poisson Destribution
"""
def test_pmf_p1(self):
poisson_pmf = poisson.pmf(1, 1)
genpoisson_pmf = sm.di... |
<reponame>birlrobotics/rostopics_to_timeseries
#!/usr/bin/env python
from rostopics_to_timeseries import (
RosTopicFilteringScheme,
TopicMsgFilter,
OnlineRostopicsToTimeseries,
)
from rostopics_to_timeseries.TopicMsgFilter import BaxterEndpointStateFilter, BaxterEndpointStateFilterForTwistLinear
import ... |
"""Visualize an absorption lookup table.
Author: <EMAIL>
"""
import re
from itertools import zip_longest
import matplotlib.pyplot as plt
import numpy as np
from cycler import cycler
from matplotlib.lines import Line2D
from scipy.interpolate import interp1d
import typhon.constants
from typhon.plots import (ScalingFor... |
import numpy as np
import os
import scipy.io
import falco.config.ModelParameters
import falco.config.DeformableMirrorParameters
import falco.tests.test_masks
def _get_default_LC_config_data():
_LC_default_LC_config_data_file = os.path.join(os.path.dirname(os.path.abspath(__file__)), "_default_LC_config_data.mat")
... |
<filename>10_pcap_to_point_cloud/01_hi_freq_data_to_csv.py
#!/usr/bin/env python
# coding: utf-8
"""
This script has to be executed after join_files_to_pcap.py has succesfully run.
This script should be called with 1 argument.
The 1st argument is the ABSOLUTE path of the top directory for the flight campai... |
import http.server
import socketserver
import webbrowser
import json
import shutil
import logging
from functools import partial
from collections import defaultdict
import numpy as np
import scipy
from scipy.cluster.hierarchy import linkage
from cblaster.classes import Session
from cblaster.helpers import get_project... |
<reponame>ktw361/homan
# Copyright (c) Facebook, Inc. and its affiliates.
"""
Utilities for computing initial object pose fits from instance masks.
"""
# pylint: disable=broad-except,too-many-statements,too-many-branches,logging-fstring-interpolation
# pylint: disable=no-member,import-error,abstract-method,missing-func... |
<filename>laika/raw_gnss.py
import scipy.optimize as opt
import constants
import numpy as np
import datetime
from lib.coordinates import LocalCoord
from gps_time import GPSTime
from helpers import rinex3_obs_from_rinex2_obs, \
get_nmea_id_from_prn, \
get_prn_from_nmea_id, \
... |
<filename>gammapy/maps/axes.py
# Licensed under a 3-clause BSD style license - see LICENSE.rst
import copy
import inspect
from collections.abc import Sequence
import numpy as np
import scipy
import astropy.units as u
from astropy.io import fits
from astropy.table import Column, Table, hstack
from astropy.time import Ti... |
<gh_stars>0
import numpy as np
from sklearn.base import RegressorMixin, BaseEstimator
import six
from sklearn.linear_model._base import LinearModel, LinearClassifierMixin
from sklearn.utils import check_X_y,check_array,as_float_array
from sklearn.utils.multiclass import check_classification_targets
from sklearn.utils.e... |
<gh_stars>1-10
from __future__ import division, absolute_import
__copyright__ = "Copyright (C) 2009-2013 <NAME>"
__license__ = """
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restrict... |
<filename>artssat/retrieval/a_priori.py
"""
artssat.retrieval.a_priori
--------------------------
The :code:`retrieval.a_priori` sub-module provides modular data provider
object that can be used to build a priori data providers.
"""
from artssat.data_provider import DataProviderBase
from artssat.sensor import ActiveSe... |
# global
import numpy as np
from typing import Optional, Callable
import functools
# local
import ivy
try:
from scipy.special import erf as _erf
except (ImportError, ModuleNotFoundError):
_erf = None
# when inputs are 0 dimensional, numpy's functions return scalars
# so we use this wrapper to ensure outputs... |
from skimage.color import rgb2gray
from skimage import io
import numpy as np
import glob
import sys
import timeit
import argparse
import scipy
import cv2
import get_maps
import preprocessing
import descriptor
import os
import template
import minutiae_AEC_modified as minutiae_AEC
import json
import descriptor_PQ
import ... |
<gh_stars>1-10
import numpy as np
import scipy.sparse as sparse
import matplotlib.pyplot as plt
import cv2 as cv2
import scipy.sparse.linalg as slinalg
import time as time
import scipy.optimize as opt
# Default arguments:
# dx: Numpy array of length 3 containing the difference of coordinates
# ... |
<filename>sourcecode/GW_PN.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Nov 7 06:39:55 2021
@author: vitor
"""
import numpy as np
from scipy.integrate import solve_ivp
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.tri as mtri
import matplotlib.color... |
<filename>cusp_data_stage3.py<gh_stars>10-100
import numpy as np
import time
from multiprocessing import Pool
from scipy.optimize import minimize
###STAGE 3###
import sys
from config import CODE_DIRECTORY
sys.path.append(CODE_DIRECTORY)
# User settings for CUSP
import settings
from set_settings import *
from cusp_dem... |
import numpy as np
from scipy import fft
def fft_amplitude(x: np.ndarray):
""" Average amplitude of FFT
:param x: a 1-d numeric vector
:return: scalar feature
"""
amplitude = np.abs(fft.fft(x) / len(x))
average_amplitude = np.mean(amplitude)
return average_amplitude
|
import requests
from statistics import mean
from predict_salary import predict_rub_salary
def get_hh_salary(item, salaries):
salary = item['salary']
if salary and salary['currency'] == "RUR":
payment_from = salary['from']
payment_to = salary['to']
salary = predict_rub_salary(payment... |
<reponame>UVA-DSI-2019-Capstones/CHRC
# coding: utf-8
# In[1]:
import csv
import os
import glob
import re
from pandas import DataFrame, Series
from openslide import open_slide
from PIL import Image
import timeit
import time
import math
import numpy as np
from scipy.ndimage.morphology import binary_fill_holes
from sk... |
#!/usr/bin/env python3
'''
Deterministic numerical solver for ODE systems
<NAME>.
used for
Cardenas & Santos-Vega, 2021
Coded by github.com/pablocarderam
Creates heatmaps of contact rate and mutant fitness cost used in Figure 3b-c
'''
### Imports ###
import numpy as np # handle arrays
import pandas as pd
from scipy... |
<filename>candidate_matching/libs/CollMetric/utils.py
from collections import defaultdict
import numpy as np
from scipy.sparse import dok_matrix, lil_matrix
from tqdm import tqdm
def citeulike(tag_occurence_thres=10):
user_dict = defaultdict(set)
for u, item_list in enumerate(open("citeulike-t/users.dat").re... |
# Copyright 2020 The TensorFlow Authors. 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
#
# Unless required by applica... |
<filename>extra/pythoncode.py
from os import stat
from networkx.algorithms.components.connected import is_connected
from networkx.classes.function import neighbors
from networkx.linalg.algebraicconnectivity import fiedler_vector
import scipy as sp
import networkx as nx
from scipy.io import mmread
from scipy.sparse.coo ... |
import h5py # HDF5 support
import os
import glob
import numpy as n
from scipy.interpolate import interp1d
import astropy.io.fits as fits
from astropy.cosmology import FlatLambdaCDM
import astropy.units as u
cosmoMD = FlatLambdaCDM(H0=67.77*u.km/u.s/u.Mpc, Om0=0.307115, Ob0=0.048206)
def write_fits_lc(path_to_lc, ... |
import numpy as np
import scipy as sp
import pylab as plt
def gen_grid(nx,ny,nz):
i_f=np.arange(nx)
i_c=np.arange(nx)+0.5
j_f=np.arange(ny)
j_c=np.arange(ny)+0.5
dxx=dyy=2e3
dx=np.ones((ny,nx))*dxx
dy=np.ones((ny,nx))*dyy
x_f=i_f*dxx
x_c=i_c*dxx
y_f=j_f*dxx
y_c=j_c*dxx
... |
import pandas as pd
import numpy as np
from scipy.stats import truncnorm
from patsy import dmatrix
from collections import OrderedDict
from hddm.simulators.basic_simulator import *
from hddm.model_config import model_config
from functools import partial
# Helper
def hddm_preprocess(
simulator_data=None,
subj_i... |
<filename>idaes/surrogate/alamopy_depr/almconfidence.py
#################################################################################
# The Institute for the Design of Advanced Energy Systems Integrated Platform
# Framework (IDAES IP) was produced under the DOE Institute for the
# Design of Advanced Energy Systems ... |
#!/usr/bin/python
# Copyright (C) 2011 <NAME>
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# any later version.
# This program is distributed in the ho... |
<filename>model/transforms.py<gh_stars>1-10
""" Transformation of variable component of TANs.
- Transformations are function that
- take in:
- an input `[N x d]`
- (and possibly) a conditioning value `[N x p]`
- return:
- transformed covariates `[N x d]`
- log determinant of the Jacobian `[N]` or sc... |
"""A layered graph, backed by redis.
Licensed under the 3-clause BSD License:
Copyright (c) 2013, <NAME> (<EMAIL>)
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code m... |
import numpy as np
from numpy.linalg import slogdet, solve
from numpy import log, pi
import pandas as pd
from scipy.special import expit
from .constants import mass_pion
from .kinematics import momentum_transfer_cm, cos0_cm_from_lab, omega_cm_from_lab
from .constants import omega_lab_cusp, dsg_label, DesignLabels
from ... |
from statistics import mean
import os
import csv
import numpy as np
import shutil
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
TRAINING_UPDATE_FREQUENCY = 1000
RUN_UPDATE_FREQUENCY = 10
MAX_LOSS = 5
class Logger:
def __init__(self, header, directory_path):
directory_path = dir... |
<filename>canonicalTrainTestMultimod.py
from src import utils, models
import json
import numpy as np
import math
import pickle
import time
from scipy.stats import kendalltau, spearmanr
from scipy.stats import rankdata
from sklearn.metrics import classification_report
from sklearn.metrics import precision_recall_fsco... |
<gh_stars>0
import copy
import json
import math
import os.path
from os import path
import matplotlib.pyplot as plt
import numpy
import numpy as np
import pandas as pd
import torch
import tqdm
from scipy import stats
from termcolor import colored
from torch.utils.data.dataloader import DataLoader
import global_vars as... |
import os
import sys
import json
import pickle
import argparse
import torch
import shutil
import glob
import numpy as np
import time
np.set_printoptions(precision=4,suppress=False)
import importlib
import imageio
import math
from tensorboardX import SummaryWriter
import datetime
BASE_DIR = os.path.dirname(os.path.ab... |
<gh_stars>100-1000
import itertools
import matplotlib
import numpy as np
from scipy.optimize import curve_fit
from scipy import interpolate
from astropy import units
from astropy.io import fits
from astropy.convolution import convolve, Gaussian1DKernel
from matplotlib import pyplot as plt
# Imports for fast_runnin... |
from numpy.lib.financial import nper
from pandas.core.frame import DataFrame
from engine.core.SystemEntity import SystemEntity
from engine.core.JourneyEntity import journeys_to_features_sources_dataframe
from engine.core.SourceEntity import sources_to_dataframe
from engine.core.SquadEntity import squads_to_features_dat... |
#!/usr/bin/env python
# coding: utf-8
"""
N.T.Basse 2019
Based on paper:
Turbulence Intensity Scaling: A Fugue
https://www.mdpi.com/2311-5521/4/4/180
"""
import numpy as np
from scipy.optimize import fsolve
def smooth(x):
r"""smooth friction factor (Eq. 19 in paper)"""
out = [np.power(x[0], -0.5)... |
"""
This module contains useful functions for circular statistics
"""
__all__ = ['circular_mean', ' circular_correlation', 'circular_variance',
'mises', 'mises_params', 'phasecorr', 'p2torus', 'torus2p',
'p2dtorus', 'm_vec2mat', 'm2kappa', 'kappa2m']
import os,sys
import numpy as np
... |
"""
=========================================================
Distance Restraints Filter (:mod:`drsip.dist_restraints`)
=========================================================
Module contains the function implementing the distance restraints (DR)
filter.
Functions
---------
.. autofunction:: dist_restra... |
# -*- coding: utf-8 -*-
from __future__ import (absolute_import, division,
print_function)
import numpy as np
import scipy.stats as scistats
import scipy.linalg as sl
from enterprise import constants as const
from enterprise.signals import signal_base
try:
import cPickle as pickle
except:
... |
<reponame>ea42gh/holoviews
from types import FunctionType
from collections import defaultdict
import param
import numpy as np
from ..core import Dimension, Dataset, Element2D
from ..core.accessors import Redim
from ..core.util import max_range, search_indices
from ..core.operation import Operation
from .chart import ... |
"""
``revscoring extract -h``
::
Extracts a list of `dependent` for a set of revisions.
Reads file containing revision observations, extracts dependents
(Features and Datasources), and writes extended observations out for future
use.
Usage:
extract -h | --help
extract <dependent>.... |
<filename>scipyExercise/maximumFilter/mfilter.py<gh_stars>0
from itertools import product
import numpy as np
from scipy.ndimage import maximum_filter
def scipy_case(domain):
window_size = 3
result = maximum_filter(
domain, size=3)
return result
def maximum_filter(domain, size=3):
"""
nai... |
from dataclasses import dataclass
import typing
import numpy as np
from scipy.integrate import quad
from scipy.special import erf
import numpy.testing as npt
import pytest
import cara.monte_carlo as mc
from cara import models,data
from cara.utils import method_cache
from cara.models import _VectorisedFloat,Interval,S... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Utility functions to convert pg SparseMatrices from and to numpy objects"""
import numpy as np
import pygimli as pg
def sparseMatrix2csr(A):
"""Convert SparseMatrix to scipy.csr_matrix.
Compressed Sparse Row matrix, i.e., Compressed Row Storage (CRS)
... |
<filename>python_research/experiments/image_generator/selector.py<gh_stars>10-100
import os
from random import shuffle
import gdal
import numpy as np
import osr
from scipy.io import loadmat
def load_data(path: str) -> np.ndarray:
"""
Load data for image generation.
:param path: Path to the dataset.
... |
<filename>A3/A3v2.py
import numpy as np
import random
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
N = 10_000
X = 100
def f(x):
return 4*x*(1 - x)
def g(x, A):
return A / np.sqrt(x*(1 - x)) # Domain (0, 1)
x_cache = {}
def x(n):
if n in x_cache:
return x... |
<filename>python/smurff/test/test_noisemodels.py
import unittest
import numpy as np
import pandas as pd
import scipy.sparse
import smurff
import itertools
import collections
verbose = 0
class TestNoiseModels():
# Python 2.7 @unittest.skip fix
__name__ = "TestNoiseModels"
def run_session(self, noise_model... |
"""
This script creates a boolean mask based on rules
1. is it boreal forest zone
2. In 2000, was there sufficent forest
"""
#==============================================================================
__title__ = "FRI calculator for the other datasets"
__author__ = "<NAME>"
__version__ = "v1.0(21.08.2019)"
__emai... |
<reponame>dips4717/gcn-cnn
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Nov 20 11:01:07 2019
Compute the performance metrics for graphencoder model
performance metrics includes iou, pixelAccuracy
@author: dipu
"""
import torch
from torchvision import transforms
import torch.nn.functional as F
im... |
<filename>src/util/plotting.py
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from scipy import stats as scipystats
from src.stats import sleepStats, hbStats
NAMES={'sleep_inefficiency':'Sleep Inefficiency (%)',
'sleep_efficiency':'Sleep Efficiency (%)',
... |
# -*- coding: utf-8 -*-
"""
Created on Fri Aug 20 16:06:58 2021
@author: rimmler
"""
#_____________________________________________________________________________
# INPUT
'''
IP Data must be PPMS .dat file of measurement Rxx/Rxy vs. IP/OP angle
Units:
'''
sampleID = 'MA2959-2-D4'
effect = 'amr'
#__________________... |
import argparse
import logging
import math
import os
import random
import numpy as np
import torch
import torch.cuda
from scipy.stats import t
def get_stats(array, conf_interval=False, name=None, stdout=False, logout=False):
"""Compute mean and standard deviation from an numerical array
Args:
ar... |
<gh_stars>0
"""
Python implementation of the LiNGAM algorithms.
The LiNGAM Project: https://sites.google.com/site/sshimizu06/lingam
"""
import itertools
import numbers
import warnings
import numpy as np
from sklearn.utils import check_array, resample
from sklearn.linear_model import LinearRegression
from scipy.stats ... |
<gh_stars>0
#!/usr/bin/env python
# Basic
import numpy as np
from scipy.signal import medfilt
import glob
import os
import pandas as pd
from matplotlib import pyplot as plt
# pyFAI
import pyFAI
import pygix
from pygix import plotting as ppl
import fabio
data_dir = "/Users/nils/CC/CMS Data/Nils/insitu_air"
calib_csv ... |
"""
Copyright 2018 Johns Hopkins University (Author: <NAME>)
Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
from six.moves import xrange
import numpy as np
from scipy import linalg as sla
from... |
<reponame>natalie-robinson/MG-RAST-Tools
#!/usr/bin/env python
def test_dependencies():
try:
import numpy
except ImportError:
print("numpy not found. ")
try:
import requests
except ImportError:
print("requests not found. ")
try:
import scipy
except Impor... |
import cv2
from model.loss import *
import math
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
import torchvision
from torch.autograd import Variable
from torchvision import transforms,utils,models
from argparse import Namespace
import matplotlib.pyplot as plt
import pdb
import sc... |
import argparse
from scipy.sparse import dok_matrix, csr_matrix
import numpy as np
import random
import struct
import sys
from multiprocessing import Process, Queue
from Queue import Empty
import ioutils
def worker(proc_num, queue, out_dir, count_dir):
print "counts2bin"
while True:
try:
... |
<filename>Starfish/grid_tools/instruments.py
from dataclasses import dataclass
from typing import Tuple
import pandas as pd
from Starfish import INSTDIR
from scipy.interpolate import interp1d
# TODO convert to dataclass
# Convert R to FWHM in km/s by \Delta v = c/R
@dataclass
class Instrument:
"""
Object desc... |
<gh_stars>1-10
# coding=utf-8
# Copyright 2020 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... |
<gh_stars>0
from __future__ import division
from collections import OrderedDict
import time
import datetime
import os
import re
import pdb
import pickle
import tables
import math
import traceback
import numpy as np
import pandas as pd
import random
import multiprocessing as mp
import subprocess
from random import shuf... |
from sympy import *
r, theta = symbols('r, theta')
# polar to cartesian
fx = r * cos(theta)
fy = r * sin(theta)
# base vector
erx = diff(fx, r)
ery = diff(fy, r)
etx = diff(fx, theta)
ety = diff(fy, theta)
# base vector changes.
erxr = diff(erx, r)
eryr = diff(ery, r)
etxr = diff(etx, r)
etyr = diff(ety, r)
erxt = ... |
<reponame>stevenrbrandt/nrpytutorial
# finite_difference.py:
# As documented in the NRPy+ tutorial notebook:
# Tutorial-Finite_Difference_Derivatives.ipynb ,
# This module generates C kernels for numerically
# solving PDEs with finite differences.
#
# Depends primarily on: outputC.py and grid.py.
# Author: <NAM... |
import gym
import numpy as np
from scipy.linalg import circulant
from gym.spaces import Tuple, Box, Dict
from copy import deepcopy
class SplitMultiAgentActions(gym.ActionWrapper):
'''
Splits mujoco generated actions into a dict of tuple actions.
'''
def __init__(self, env):
super().__init_... |
import scipy.misc
import math
if hasattr(scipy.misc, 'comb'):
scipy_comb = scipy.misc.comb
else:
import scipy.special
scipy_comb = scipy.special.comb
def try_fnc(fnc):
try:
return fnc()
except:
pass
def chunks(items, size):
for i in range(0, len(items), size):
yield ... |
"""
Copyright (c) 2021, FireEye, Inc.
Copyright (c) 2021 <NAME>
This module contains code that is needed in the attack phase.
"""
import os
import json
import time
import copy
from multiprocessing import Pool
from collections import OrderedDict
import tqdm
import scipy
import numpy as np
import pandas as pd
import l... |
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import chi2, norm
import pickle
plt.style.use('../../plot/paper.mplstyle')
from matplotlib import rcParams
def comparison(datasets, method):
defaultfontsize = rcParams['font.size']
rcParams['font.size'] = 14
f, (axes) = plt.... |
# Copyright 2017 The dm_control Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to i... |
<reponame>ynop/evalmate
import numpy as np
import scipy
from evalmate.utils import label
from . import utils
from . import aligner
from . import candidates
class BipartiteMatchingAligner(aligner.EventAligner):
"""
Create event-based alignment, based on bipartite matching.
1. In a first step for every p... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Mar 20 10:39:08 2019
@author: bressler
"""
import SBCcode as sbc
from os import listdir
from os.path import isfile,join
import numpy as np
import matplotlib.pyplot as plt
import scipy
from random import randrange
import PMT_NIM_trig_efficiency as effic... |
from __future__ import print_function
import numpy as np
import scipy.sparse as sp
from six import string_types
from .Utils.SolverUtils import *
from . import Utils
norm = np.linalg.norm
__all__ = [
'Minimize', 'Remember', 'SteepestDescent', 'BFGS', 'GaussNewton',
'InexactGaussNewton', 'ProjectedGradient',... |
##########################################################################
#
# This file is part of Lilith
# made by <NAME> and <NAME>
#
# Web page: http://lpsc.in2p3.fr/projects-th/lilith/
#
# In case of questions email <EMAIL>
#
#
# Lilith is free software: you can redistribute it and/or modify
# it under ... |
<filename>REMARKs/BayerLuetticke/Assets/Two/FluctuationsTwoAsset.py<gh_stars>0
# -*- coding: utf-8 -*-
'''
State Reduction, SGU_solver, Plot
'''
from __future__ import print_function
import sys
sys.path.insert(0,'../')
import numpy as np
from numpy.linalg import matrix_rank
import scipy as sc
from scipy.stats import... |
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