text string |
|---|
# Dual annealing unit tests implementation.
# Copyright (c) 2018 <NAME> <<EMAIL>>,
# <NAME> <<EMAIL>>
# Author: <NAME>, PMP S.A.
"""
Unit tests for the dual annealing global optimizer
"""
from scipy.optimize import dual_annealing
from scipy.optimize._dual_annealing import VisitingDistribution
from scipy.optimize._dual_... |
from os import path
import neurokit2 as nk
import numpy as np
import plotly.express as px
import plotly.graph_objects as go
import wfdb
from scipy.signal import resample_poly
from detection.preprocessing.dataset import Cinc2017Dataset, Cpsc2018Dataset
from detection.utils.filesystem import ensure_directory_exists, im... |
import numpy as np
import pandas as pd
import scanpy as sc
import sklearn as sk
from anndata import AnnData
from numbers import Number
import warnings
from typing import Union, Optional, Tuple, Collection, Sequence, Iterable
import scipy as sp
from scipy.spatial import distance
from scipy.sparse import issparse, isspma... |
import os.path
import cv2
import logging
import numpy as np
from datetime import datetime
from collections import OrderedDict
from scipy.io import loadmat
from scipy import ndimage
import scipy.io as scio
import torch
from utils import utils_deblur
from utils import utils_logger
from utils import utils_sisr as sr
fr... |
<reponame>chem-william/find_nodal
import utilities
import export_jmol
import argparse
import shutil
import os
import warnings
from PIL import Image
from matplotlib.animation import FuncAnimation
from mpl_toolkits.mplot3d import Axes3D # noqa
from scipy import stats
from tqdm import tqdm
import matplotlib.pyplot as p... |
<filename>3DLSCPTR/db/tools/utils.py<gh_stars>10-100
"""
Utility functions and default settings
Author: <NAME> (<EMAIL>)
Date: March, 2020
"""
import argparse
import errno
import os
import sys
import cv2
import matplotlib
import numpy as np
import torch
import torch.nn.init as init
import torch.opti... |
"""Tests for computational algebraic number field theory. """
from sympy import S, Rational, Symbol, Poly, sin, sqrt, I, oo
from sympy.utilities.pytest import raises
from sympy.polys.numberfields import (
minimal_polynomial,
primitive_element,
is_isomorphism_possible,
field_isomorphism_pslq,
field... |
<filename>pygsm/utilities/block_tensor.py
import numpy as np
from scipy.linalg import block_diag
from .nifty import printcool,pvec1d
import sys
from .math_utils import orthogonalize,conjugate_orthogonalize
class block_tensor(object):
def __init__(self,matlist,cnorms=None):
self.matlist = matlist
... |
<filename>notebooks/lorenz.py
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
from scipy import integrate
def solve_lorenz(sigma=10.0, beta=8./3, rho=28.0):
"""Plot a solution to the Lorenz differential equations."""
max_time = 4.0
N = 30
fig = plt.figu... |
<filename>fave/plot_jul_16_overtaking_rds_1.py<gh_stars>10-100
import numpy as np
import scipy.io as sio
from scipy import interpolate
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import capsule_distance
capsule = capsule_distance.Capsule(0.18, -0.5, 0.45)
y_reference_point = 0.18
tau = 1.5
folder_path... |
import __folder_params
import sys
sys.path.insert(0, __folder_params.home)
import utils
from skimage.feature import ORB
from scipy.stats import itemfreq
import cv2
import pickle
def processOrb(img_path):
final_path = utils.adress_file(img_path, "ORB", end='.p')
# http://opencv-python-tutroals.readthedocs.io... |
<reponame>sjk0709/Electrophysiology
from math import log, sqrt
from typing import List
from math import log, exp
import numpy as np
from scipy import integrate
from mod_cell_model import CellModel
from mod_current_models import KernikCurrents, Ishi
from mod_model_initial import kernik_model_initial
import mod_trace ... |
import os
import sys
import glob
import pickle as pkl
import warnings
from pathlib import Path
import numpy as np
import pandas as pd
from scipy.stats import ttest_rel
def load_stratified_prediction_results(results_dir, experiment_descriptor):
"""Load results of stratified prediction experiments.
Arguments
... |
#!/usr/bin/env python
"""
Modified by <NAME>
"""
"""scoring.py: Script that demonstrates the multi-label classification used."""
import copy
import numpy
import pickle
from argparse import ArgumentParser, FileType, ArgumentDefaultsHelpFormatter
from sklearn.multiclass import OneVsRestClassifier
from sklearn.linear_mo... |
"""
Generic utility routines for number handling and calculating (specific)
variances used by the TKP sourcefinder.
"""
import numpy
from numpy.ma import MaskedArray
from scipy.special import erf
from scipy.special import erfcinv
from .utils import calculate_correlation_lengths
# CODE & NUMBER HANDLING ROUTINES
#
de... |
# Copyright 2019 1QBit
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in ... |
<reponame>mederrata/probability<filename>tensorflow_probability/python/math/interpolation_test.py
# Copyright 2018 The TensorFlow Probability 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 Lic... |
<reponame>telegraphic/pygdsm
import numpy as np
from astropy import units
import healpy as hp
from scipy.interpolate import interp1d
from .component_data import LFSM_FILEPATH
from .base_skymodel import BaseSkyModel
from .base_observer import BaseObserver
def rotate_equatorial_to_galactic(map):
"""
Given a ma... |
#!/usr/bin/python3.6
import multiprocessing as mp
from functools import partial
import numpy as np
import pandas as pd
import scipy
from sofa_config import *
from sofa_print import *
def overlap(pa, pb, pc, pd):
if pb - pc >= 0 and pd - pa >= 0:
return min(pb, pd) - max(pa, pc)
def partial_sum(df):
... |
<filename>bbn_primitives/time_series/cluster_curve_fitting_kmeans.py
import typing
import numpy as np
import stopit
import sys, os
import logging
from .time_series_common import *
from .segmentation_common import *
from .signal_framing import SignalFramer
import scipy.cluster
from sklearn.cluster import MiniBatchKMe... |
import configparser
import datetime
import errno
import json
import logging
import math
import os.path
import pyperf
import re
import shlex
import shutil
import statistics
import subprocess
import sys
import time
from urllib.error import HTTPError
from urllib.parse import urlencode
from urllib.request import urlopen
i... |
<filename>fair_dag.py
from flask import Flask, render_template, redirect, url_for, request, session, flash, Markup
import os
from collections import defaultdict
import inspect
import pandas as pd
import numpy as np
from scipy import stats
import re
from graphviz import Digraph
import plotly
from plotly.subplots import ... |
<gh_stars>0
from statistics import mean
import numpy as np
from nnreslib.utils.metrics.categorial_metrics import (
CalcCategorialMetrics,
CategorialMetrics,
CategorialMetricsAggregation,
)
def test_cat_metrics_add():
cat_1 = CategorialMetrics(1, 2, 3, 4)
cat_2 = CategorialMetrics(10, 20, 30, 40)... |
from PurePython import swconstrained as swnumba
from pySeqAlign import swconstrained as swcython
import seaborn as sns
from scipy import stats
import numpy as np
import matplotlib.pyplot as plt
import scipy.io as sio
import timeit
import sys
def getRandomCSM(N, M):
D = np.random.rand(N, M)
D = D < 0.1
D = ... |
#!/usr/bin/env python3
import os, sys, time, json
from itertools import repeat
import wfdb
import numpy as np
import torch
import scipy.signal as SS
from easydict import EasyDict as ED
try:
import torch_ecg
except ModuleNotFoundError:
import sys
from os.path import dirname, abspath
sys.path.insert(0,... |
# encoding: utf-8
from __future__ import absolute_import, division, print_function
import warnings
from datetime import timedelta
import numpy as np
import sgp4.io
import sgp4.propagation
from astropy import time
from numpy import arctan, cos, degrees, sin, sqrt
from represent import ReprMixin
from scipy.constants im... |
<gh_stars>1-10
"""
Organize the worst-case adversary results into a single csv.
"""
import os
import sys
import argparse
from datetime import datetime
from itertools import product
import numpy as np
import pandas as pd
from scipy.stats import sem
from tqdm import tqdm
here = os.path.abspath(os.path.dirname(__file__)... |
#!/usr/bin python
# -*- coding: utf-8 -*-
from __future__ import (print_function)
import os
import sys
import warnings
import argparse
import numpy as np
path = os.path.normpath(os.path.join(os.path.dirname(sys.argv[0]), '..'))
sys.path.insert(0, path)
from uvmod import stats
from uvmod import models
from uvmod import... |
<gh_stars>10-100
import os
import shutil
import unittest
from fractions import Fraction
import vapoursynth as vs
core = vs.core
import acsuite
class ACsuiteTests(unittest.TestCase):
BLANK_CLIP = core.std.BlankClip(format=vs.YUV420P8, length=100, fpsnum=5, fpsden=1)
VFR_CLIP = core.std.BlankClip(fpsnum=2400... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Jul 4 18:51:20 2018
@author: cham
"""
import emcee
# %pylab qt5
import matplotlib.pyplot as plt
import numpy as np
from scipy.interpolate import interp1d
from scipy.stats import skewtest, skew, anderson
"""
teff, logg, feh, mags(W1)
varpi, sigma_varp... |
import numpy as np
import math
import torch
import torch.nn as nn
import torch.optim as optim
import torch.autograd as autograd
import torch.nn.functional as F
import pickle
from lib.model import *
from lib.zfilter import ZFilter
from lib.util import *
from lib.trpo import trpo_step
from lib.data import *
import s... |
from types import SimpleNamespace
import numpy as np
from scipy import stats
import matplotlib.pyplot as plt
import ipywidgets as widgets
from matplotlib import cm
from mpl_toolkits.mplot3d import Axes3D
from mpl_toolkits.mplot3d.art3d import Poly3DCollection, Line3DCollection
def bivariate_normal(continuous_update=T... |
<reponame>mp4096/fastmat
# -*- coding: utf-8 -*-
'''
demo/edgeDetect.py
-------------------------------------------------- part of the fastmat demos
Author : sempersn
Introduced :
------------------------------------------------------------------------------
Copyright 2016 <NAME>, <NAME>
http... |
# -*- coding: utf-8 -*-
"""
Created on Mon Oct 24 15:55:28 2016
@author: sasha
"""
import os
from .init import QTVer
if QTVer == 4:
from PyQt4 import QtGui, QtCore
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.backends.backend_qt4agg import ... |
from __future__ import print_function, division
"""The temporal-modules contain the functions needed to comute the advancement in time
of the physical variables simulated. We need a specific temporal scheme to
advance a system of variables. Here, each scheme is implemented in a class. The
class is supposed to be insta... |
<filename>utils/utils.py<gh_stars>1-10
from utils.loggerer import Loggerer
import torch
from torch.autograd import Variable
import time
import numpy as np
from scipy.ndimage.filters import uniform_filter
def to_np(x):
return x.data.cpu().numpy()
def decibel_to_linear(band):
# convert to linear units
retu... |
<gh_stars>1-10
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""Calculate fiberloss fractions.
Fiberloss fractions are computed as the overlap between the light profile
illuminating a fiber and the on-sky aperture of the fiber.
"""
from __future__ import print_function, division
import numpy as np
i... |
# -*- coding: utf-8 -*-
__all__ = ["optimize"]
import os
import sys
import numpy as np
import pymc3 as pm
import theano
from pymc3.blocking import ArrayOrdering, DictToArrayBijection
from pymc3.model import Point
from pymc3.theanof import inputvars
from pymc3.util import (
get_default_varnames,
get_untransfo... |
#############################################################
##### Simulates a pseudo-Premier League season
##### Scoring controlled by 3 ratings per team
##### Home team advantage not instituted
#############################################################
import sys
import numpy as np
import pandas as pd
import ran... |
<gh_stars>10-100
from ._stopping_criterion import StoppingCriterion
from ..accumulate_data import MeanVarData
from ..discrete_distribution import IIDStdUniform
from ..true_measure import Gaussian, BrownianMotion, Uniform
from ..integrand import Keister, AsianOption, CustomFun
from ..util import MaxSamplesWarning
from n... |
import math
from numpy import ma
from numpy.core.getlimits import _register_type
from numpy.lib.function_base import cov
from transformers import BertTokenizer, BertForMaskedLM
from torch.nn import functional as F
import torch
import scipy.stats as stats
from sentence_transformers import SentenceTransformer, util
from... |
<reponame>matthieuheitz/wot
import argparse
import numpy as np
import pandas as pd
import scipy.sparse
import wot
CELL_SET_HELP = 'gmt, gmx, or grp file of cell sets.'
CELL_DAYS_HELP = 'File with headers "id" and "day" corresponding to cell id and days'
TMAP_HELP = 'Directory of transport maps as produced by optimal ... |
import logging
from pathlib import Path
import uuid
import numpy as np
import matplotlib.pyplot as plt
from scipy import interpolate
from brainbox.core import Bunch
import ibllib.exceptions as err
import ibllib.plots as plots
import ibllib.io.spikeglx
import ibllib.dsp as dsp
import alf.io
from ibllib.io.spikeglx im... |
<filename>wa_gdal/davgis/functions.py
# -*- coding: utf-8 -*-
"""
Authors: <NAME>
Contact: <EMAIL>, <EMAIL>
Repository: https://github.com/gespinoza/davgis
Module: davgis
Description:
This module is a python wrapper to simplify scripting and automation of common
GIS workflows used in water resources.
"""
from __futur... |
<filename>tests/test.py
"""
Automatically run tests for this library.
Simply execute
python test.py
or execute
nosetests --verbose
from within tests/
or add @attr("now") in front of a test and then execute
nosetests --verbose -a now
to only execute a specific test.
"""
from __future__ import print_function,... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Jul 27 15:59:17 2020
Calibrate the fragmentation model to the data by Song et al. (2017)
Figure 5 of Kaandorp et al. (2021): Modelling size distributions
of marine plastics under the influence of continuous cascading fragmentation
@author: kaandorp
""... |
import warnings as _warnings
import typing as _typing
from scipy import optimize as _opt
import inspect as _inspect
import numpy as _np
import matplotlib.pyplot as _plt
import pandas as _pd
import global_funcs as _gf
import global_enums as _ge
DEFAULT_DATASET_NAME = 'v'
class Dataset(object):
def __init__(self,... |
<filename>geoapps/simpegEM1D/Survey.py
from geoapps.simpegPF import Maps, Survey, Utils
import numpy as np
import scipy.sparse as sp
from scipy.constants import mu_0
from .EM1DAnalytics import ColeCole
from .DigFilter import (
transFilt,
transFiltImpulse,
transFiltInterp,
transFiltImpulseInterp,
)
from ... |
from abc import ABC, abstractmethod
import scipy
import numpy as np
class Server(ABC):
def __init__(self, server_model, merged_update):
self.model = server_model
self.merged_update = merged_update
self.total_weight = 0
@abstractmethod
def train_model(self, my_round, num_syncs, cli... |
<filename>utils/lukas_kanade.py
import numpy as np
from scipy import interpolate
from utils import se3
def calcResiduals(IRef, DRef, I, D, xi, K, norm_param, use_hubernorm):
T = se3.se3Exp(xi)
R = T[0:3, 0:3]
t = T[0:3, 3]
KInv = np.linalg.inv(K)
xImg = np.zeros_like(IRef) - 10
yImg = np.zero... |
# -*- coding: utf-8 -*-
"""
Created on Sat Apr 13 21:09:01 2019
@author: <NAME> (<EMAIL>)
"""
'''
Utility functions to make regression plots
'''
import os
import numpy as np
from sklearn.metrics import mean_squared_error, r2_score
from scipy.stats import norm
import seaborn as sns
#matplotlib.use('Agg') # Must be be... |
#!/usr/bin/env python
import argparse
import sys
import numpy as np
from scipy.linalg import fractional_matrix_power
from brnolm.oov_clustering.embeddings_io import all_embs_by_key
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--show-cov', action='store_true')
parser... |
<reponame>aqutor/RecSys_Algo
import data
from collections import defaultdict
from itertools import combinations
import numpy as np
from scipy.stats import pearsonr
import math
import time
import pickle
def generate_seq(df, users):
# key:user val: (item, rating) in sorted order
seq = defaultdict(list)
# ke... |
<filename>0/6/4.py
#!/usr/bin/env python
# https://projecteuler.net/problem=64
# Discussion: https://projecteuler.net/thread=64
from __future__ import division
import unittest
from fractions import gcd
from math import sqrt
def period_length(i):
sq = sqrt(i)
a0 = a = int(sq)
if sq == a:
... |
# -*- coding: utf-8 -*-
"""Benchmark Text-ID for discriminative quality"""
import logging
import time
import iscc
from statistics import mean
from iscc_bench.algos.slide import sliding_window
from iscc_bench.readers.gutenberg import gutenberg
from os.path import basename
from iscc_bench.textid import textid
from iscc_b... |
#!/usr/bin/env python
import numpy as np
from scipy import interpolate
from matplotlib import pyplot as plt
predefined_fp = [1/4, 1/2, 1, 2, 4, 8]
def froc(
tp_prob: np.array,
fp_prob: np.array,
gt_count: int,
image_count: int,
predefined_fp: np.array
... |
# pylint: disable=no-member
import torch
import torch.nn as nn
import torch.optim as optim
import numpy as np
import pytorch_lightning as pl
from PCM.utils import CensoredMSELoss
from scipy import stats
from sklearn.metrics import r2_score
class PCM_MT(pl.LightningModule):
def __init__(self, hparams):
su... |
<reponame>Ericmas001/hq-machines-taker-docker
from time import sleep
from fractions import Fraction
from datetime import datetime
import os
import json
import io
import sys
import traceback
from util import Console
from models import PictureConfig
from models import TakenPicture
path_last_config = "{0}{1}_last_config... |
#!/usr/bin/python
# The following functions are copyright (c) 2013-2014, <NAME> and Massachusetts Institute of Technology
#
# 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 ret... |
<filename>kdsphere/kdsphere.py
import numpy as np
from scipy.spatial import cKDTree, KDTree
from .utils import spherical_to_cartesian
class KDSphere(object):
"""KD Tree for Spherical Data, built on scipy's cKDTree
Parameters
----------
data : array_like, shape (N, 2)
(lon, lat) pairs measure... |
# Copyright 2019 Xilinx 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 law or agreed to in writing, ... |
from fractions import Fraction as Q
def fraction_to_index(q: Q) -> int:
num = q.numerator
den = q.denominator
assert 0 <= num < den
return (den - 1) * (den - 2) // 2 + num
def next_fraction(q: Q) -> Q:
assert 0 <= q.numerator < q.denominator
dq = Q(1, q.denominator)
while True:
... |
<filename>MNIST-veri/RobustnessTest.py
import warnings, logging, sys
import cv2
import gc
import os
import time
import shutil
import random
import argparse
import pickle
import numpy as np
import pandas as pd
from scipy.misc import imsave
import matplotlib.pyplot as plt
import tensorflow as tf
from tensorflow.example... |
<reponame>MIT-REALM/neural_clbf
import torch
from scipy import interpolate
class LidarMonitor(object):
"""A class to monitor lidar data and save the most recent set"""
def __init__(
self,
num_rays: int = 32,
):
super(LidarMonitor, self).__init__()
self.num_rays = num_rays
... |
#! /usr/bin/env python
from __future__ import division, print_function
import argparse
import collections
import logging
import os
import random
import threading
import numpy as np
import pandas as pd
from itertools import cycle, islice
import keras
from keras import backend as K
from keras import optimizers
from ... |
__all__ = [
'vector',
'CoordinateSym', 'ReferenceFrame', 'Dyadic', 'Vector', 'Point', 'cross',
'dot', 'express', 'time_derivative', 'outer', 'kinematic_equations',
'get_motion_params', 'partial_velocity', 'dynamicsymbols', 'vprint',
'vsstrrepr', 'vsprint', 'vpprint', 'vlatex', 'init_vprinting', 'cu... |
r"""
Contains probability density functions (PDF) from Random Matrix Theory (RMT).
.. currentmodule:: quanguru.QuantumToolbox.rmtDistributions
Functions
---------
.. autosummary::
EigenVectorDist
.. autosummary::
WignerDyson
WignerSurmise
Poissonian
.. |c... |
#! /usr/bin/env python3
"""
fekete - Estimation of Fekete points on a unit sphere
This module implements the core algorithm put forward in [1],
allowing users to estimate the locations of N equidistant points on a
unit sphere.
[1] <NAME>., <NAME>., <NAME>., & <NAME>. Estimation of
F... |
<reponame>nahushr/Computer-Vision
#!/usr/bin/env python3
from PIL import Image, ImageOps
import numpy as np
from scipy import fftpack
import warnings
warnings.filterwarnings('ignore') ##nothing but to supress warning of complex numbers
##this program takes around 20 seconds to run
def boxing(): ##function to get filter... |
<filename>analysis_for_AlleleHMM_manuscript/alleledb_pipeline_mouse/GetSnpCounts.py
import pdb
import sys, bisect, scipy.stats, gc, os
from string import maketrans
import getNew1000GSNPAnnotations, InBindingSite, GetCNVAnnotations, Mapping2
import binom
MAXREADLEN=75
#tmp_trans={"paternal":0, "maternal":1}
# This is... |
<reponame>IsengardCTF/IsengardCTF.github.io<filename>assets/ctfFiles/2021/fword2021/login/cleanerSolver.py
from pwn import *
from Crypto.Util.number import bytes_to_long, long_to_bytes, inverse, getPrime, GCD
import os, hashlib, sys, signal
#https://github.com/stephenbradshaw/hlextend
import hlextend
from math import g... |
# -*- coding: UTF-8 -*-
__all__ = ['agregation']
import numpy as np
import scipy
from scipy.sparse import csr_matrix, coo_matrix, isspmatrix_csr, isspmatrix_csc
from pyamg.relaxation import gauss_seidel
#from pyamg.util.linalg import residual_norm
# ...
try:
from petsc4py import PETSc
importPETSc=True
except I... |
# Author: <NAME>: <EMAIL>
# Subsidiary file for the simulators to work
import numpy as np
import sympy as sp
def DHMatrix2Homo_and_Jacob(Hmat, prismatic=[]):
# RETURN: Homogeneous Tranformation Matrix, Jacobian Matrix
# Arguments:
#Hmat: DH parameter matrix
# DH Parameter... |
<reponame>FanChiMao/Pytorch-2021-AICUP-YOLOv4
import torch
from torch import nn
from unet import UNet
from c_utils.data_vis import plot_img_and_mask
from c_utils.dataset import BasicDataset
import torch.nn.functional as F
from torchvision import transforms
import cv2
import numpy as np
def mask_to_image(mask... |
import pandas as pd
import re
import wandb
from scipy.stats import wilcoxon
api = wandb.Api()
runs = api.runs("cuichenx/hmong-seq-tagging")
def get_values(root_name, column="test_full/FB1", max_match=9):
regex = re.compile(fr"^(grpd[1-3]_{root_name}_run[1-3])$")
res = {}
for run in runs:
if regex... |
import sys
homeCodePath=r"H:\10_Python\005_Scripts_from_others\Laurent\wicking_pnm"
if homeCodePath not in sys.path:
sys.path.append(homeCodePath)
import random
import xarray as xr
import numpy as np
import scipy as sp
import networkx as nx
import time
from collections import deque
from skimage.morphology import c... |
<filename>parse_season.py
import numpy, os, sys, matplotlib, datetime
# matplotlib.use("GTK")
import pylab
from operator import itemgetter
from L2regression import LogisticRegression
from math import exp, log
from scipy.optimize import leastsq, fmin
if len(sys.argv) != 4:
print >>sys.stderr, "usage: python %s cbbg... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# BCDI: tools for pre(post)-processing Bragg coherent X-ray diffraction imaging data
# (c) 07/2017-06/2019 : CNRS UMR 7344 IM2NP
# (c) 07/2019-present : DESY PHOTON SCIENCE
# authors:
# <NAME>, <EMAIL>
import fabio
from matplotlib import pyplot as plt
f... |
"""Class for symbolic expression object or program."""
import array
import os
import warnings
from textwrap import indent
import numpy as np
from sympy.parsing.sympy_parser import parse_expr
from sympy import pretty
from dsr.functions import PlaceholderConstant
from dsr.const import make_const_optimizer
... |
<filename>run_demo.py
"""
Pipeline for PDVR
"""
from __future__ import division
from __future__ import print_function
import argparse
import multiprocessing
import numpy as np
import torch
import tqdm
import json
from torch.utils.data import DataLoader
from Lstm import Lstm
from segmentation_DNN_model import MyDat... |
<filename>PyMOTW/source/fractions/fractions_arithmetic.py
#!/usr/bin/env python3
# encoding: utf-8
#
# Copyright (c) 2009 <NAME> All rights reserved.
#
"""
"""
#end_pymotw_header
import fractions
f1 = fractions.Fraction(1, 2)
f2 = fractions.Fraction(3, 4)
print('{} + {} = {}'.format(f1, f2, f1 + f2))
print('{} - {} ... |
<filename>data_processing/LUNA_code/classify_nodes.py
# usage: python classify_nodes.py nodes.npy
import numpy as np
import pickle
from skimage.measure import label,regionprops
from sklearn import cross_validation
from sklearn.cross_validation import StratifiedKFold as KFold
from sklearn.metrics import classificati... |
#!/usr/bin/python3
# MIT License
#
# Copyright (c) 2021 <NAME>, <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 the rights
# to use... |
# -*- coding: utf-8 -*-
"""
Created on Fri Nov 27 23:41:40 2015
@author: Owner
"""
import numpy as np
import pandas as pd
import patsy
from scipy.spatial import distance
roster = pd.read_csv("data/output/dataset.csv", encoding='ISO-8859-1')
roster = roster.dropna()
user = pd.read_json("data/input.json")
roster = r... |
<gh_stars>10-100
# coding: utf-8
# Copyright (c) Pymatgen Development Team.
# Distributed under the terms of the MIT License.
from __future__ import unicode_literals, division, print_function, \
absolute_import
import string
import random
import numpy as np
"""
function for calculating the convergence of an x, y ... |
# std
import csv
from copy import deepcopy
from hashlib import md5
from time import time
# ext libs
import numpy as np
from scipy import stats
from graph_tool import Graph, GraphView
from graph_tool.topology import shortest_distance, label_largest_component
from graph_tool.clustering import global_clustering
# local
fr... |
<gh_stars>1-10
import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split, StratifiedKFold, KFold
from sklearn.preprocessing import LabelEncoder
from sklearn.metrics import f1_score, accuracy_score
from sklearn.utils import shuffle
from keras.models import Sequential
from keras.layers... |
## PLOTTING OPERATOR MATRICES
from __future__ import print_function
path = '/home/mkloewer/python/swm/'
import os; os.chdir(path) # change working directory
import numpy as np
from scipy import sparse
import time as tictoc
import matplotlib.pyplot as plt
from cmocean import cm
# import functions
exec(open(path+'swm_op... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
.. codeauthor:: <NAME> <<EMAIL>>
.. codeauthor:: <NAME> <<EMAIL>>
"""
import argparse as ap
import json
import os
import pickle
import shlex
import numpy as np
import pandas as pd
from scipy.stats import rankdata
import sklearn.metrics as metrics
import torch
from tqd... |
<filename>video_production/annotations/vectors.py
# imports
import cv2
import numpy as np
from PIL import ImageFont, ImageDraw, Image
from scipy.spatial import distance as dist
# typically we'll import modularly
try:
from .annotation import Annotation
unit_test = False
# otherwise, we're running main test cod... |
<filename>ada/adamodel_v12.py
# This import you need
from models.adatk_model import ADAModel
# Everything else depends on what your model requires
import numpy as np
from scipy.ndimage.filters import minimum_filter
from scipy.ndimage.filters import maximum_filter
from scipy.ndimage.filters import median_filter
f... |
import os
import numpy as np
from itertools import chain
from pathlib import Path
from functools import wraps, partial
from collections import namedtuple
import matplotlib.pyplot as plt
from matplotlib.patches import Ellipse
from scipy.optimize import curve_fit
from astropy.stats import mad_std
from astropy.wcs impo... |
import itertools
import time
import h5py
import sys
import os
import scipy.special
import numpy as np
sys.path.append('partools')
sys.path.append('scitools')
sys.path.append('util')
import parallel as par
import tensorflow as tf
import tensorflowUtils as tfu
from plotsUtil import *
from myProgressBar import printProgre... |
<reponame>kxxdhdn/MISSILE
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
This is the visualization of correlations
"""
import os, pathlib
import numpy as np
from scipy.optimize import curve_fit
import matplotlib.pyplot as plt
## rapyuta
from rapyuta.inout import read_hdf5, h5ext
from rapyuta.plots import pplot,... |
<gh_stars>1-10
from scipy.interpolate import interp1d
import numpy as np
import healpy as hp
import errno, os
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
omegab = 0.049
omegac = 0.261
omegam = omegab + omegac
h = 0.68
ns = 0.965
sigma8 = 0.81
c = 3e5
H0 = 100*h
nz = 100000
z1 = ... |
<filename>robot/library/StateSpaceController.py
import control as cnt
import numpy as np
import scipy as sp
class StateSpaceController:
__default = object()
def __init__(self, sys, u_min, u_max, dt):
# System
self.sysc = sys
self.sysd = sys.sample(dt)
self.dt = dt
# ... |
import json
from datetime import datetime, timedelta, timezone
from statistics import quantiles
import click
from humanfriendly import parse_timespan
from lain_cli.utils import RequestClientMixin, ensure_str, tell_cluster_info, warn
LAIN_LINT_PROMETHEUS_QUERY_RANGE = '2d'
LAIN_LINT_PROMETHEUS_QUERY_STEP = int(
i... |
#!/usr/bin/env python3
import torch
import numpy as np
from .curve import *
def geodesic_minimizing_energy(curve, manifold, optimizer=torch.optim.Adam,
max_iter=150, eval_grid=20):
"""
Compute a geodesic curve connecting two points by minimizing its energy.
Mandatory inputs:... |
<filename>src/interface/Python/paramonte/_AutoCorr.py
####################################################################################################################################
####################################################################################################################################
... |
<gh_stars>0
from __future__ import print_function
from __future__ import division
from __future__ import absolute_import
# --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by <NAME>
# ---------------... |
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