text string |
|---|
"""
Tools for creating and manipulating 1,2, and 3D meshes.
.. inheritance-diagram:: proteus.MeshTools
:parts: 1
"""
from __future__ import print_function
from __future__ import absolute_import
from __future__ import division
from builtins import input
from builtins import zip
from builtins import next
from builtin... |
"""
Visitor hierarchy to inspect and/or create IETs.
The main Visitor class is adapted from https://github.com/coneoproject/COFFEE.
"""
from collections import OrderedDict
from collections.abc import Iterable
import cgen as c
from devito.exceptions import VisitorException
from devito.ir.iet.nodes import Node, Itera... |
from numpy import zeros
from numpy.linalg import eigvals
import time
import numpy as np
import scipy as sp
import scipy.signal as signal
import scipy.sparse as sparse
import osqp
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from .controller import Controller
from ..learning.edmd import Edmd
class MP... |
from imblearn import under_sampling, over_sampling
from sklearn import base, model_selection, metrics, preprocessing
import numpy as np
import matplotlib.pyplot as plt
from scipy import stats
class UndersampledEnsemble():
"""
Shuffled K-fold undersampled ensemble.
"""
def __init__(self, base_clf, dbnam... |
<reponame>yudhik11/Rootnet_3DMPPE
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import axes3d, Axes3D
import numpy as np
import sys
from scipy.signal import savgol_filter
#python utils_plt.py data/horizontal.npy
def plt_lines(filename = 'data/ch_2.npy', data=None):
if data is None:
data = np.l... |
<gh_stars>1-10
import numpy as np
from scipy import constants
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import matplotlib as mpl
import meep
import meep_ext
from numpipe import scheduler, pbar
import miepy
from matplotlib.backends.backend_pdf import PdfPages
job = scheduler()
nm = 1e-9
u... |
# !
# * Copyright (c) Microsoft Corporation. All rights reserved.
# * Licensed under the MIT License. See LICENSE file in the
# * project root for license information.
import time
import numpy as np
import pandas as pd
from sklearn.metrics import (
mean_squared_error,
r2_score,
roc_auc_score,
... |
# Copyright 2018 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 law or agre... |
import sys
try:
from StringIO import StringIO
except ImportError:
from io import StringIO
import numpy as np
from numpy.testing import (assert_, assert_array_equal, assert_allclose,
assert_equal)
from pytest import raises as assert_raises
from scipy.sparse import coo_matrix
from sc... |
<reponame>rickyim/ceviche
import unittest
import numpy as np
import matplotlib.pylab as plt
import autograd.numpy as npa
import sys
sys.path.append('../')
from ceviche import fdfd_hz, fdfd_ez, jacobian
from ceviche.utils import imarr
import scipy.sparse.linalg as spl
import scipy.sparse as sp
from ceviche.utils import ... |
from __future__ import division
import itertools
import logging
import numpy as np
import time
import cv2 as cv
import sys
import tqdm
from scipy import stats
def exhaustive_search_block_matching(reference_img, search_img, block_size=16, max_search_range=16, norm='l1',
verbose... |
<filename>hera_cal/smooth_cal.py
# -*- coding: utf-8 -*-
# Copyright 2018 the HERA Project
# Licensed under the MIT License
import numpy as np
import scipy
from hera_cal import io, utils
from collections import OrderedDict as odict
from copy import deepcopy
import warnings
import uvtools
import argparse
from hera_cal.... |
import numpy as np
import scipy.signal as signal
from desidlas.datasets.datasetting import split_sightline_into_samples,select_samples_50p_pos_neg,pad_sightline
from desidlas.datasets.preprocess import label_sightline
from desidlas.dla_cnn.spectra_utils import get_lam_data
from desidlas.dla_cnn import defs
REST_RANGE =... |
from imports import *
from scipy.io.wavfile import read as readwav
from numpy.lib.stride_tricks import as_strided
sample_rate = 48000 # sample rate for samples and input
def load_wavs_from_dir(path):
fnames = map(lambda f: f.path,
filter(
lambda f: f.is_file(),
... |
"""Filter design.
"""
from __future__ import division, print_function, absolute_import
import warnings
import numpy
from numpy import (atleast_1d, poly, polyval, roots, real, asarray, allclose,
resize, pi, absolute, logspace, r_, sqrt, tan, log10,
arctan, arcsinh, sin, e... |
'''
------------------------------------------------------------------------
Last updated 7/13/2015
Functions for generating omega, the T x S array which describes the
demographics of the population
This py-file calls the following other file(s):
utils.py
data\demographic\demographic_data.csv
... |
<reponame>duttashi/Data-Analysis-Visualization<gh_stars>1-10
# coding: utf-8
# ## K-means clustering
# #### This notebook presents the machine learning analysis of the gapminder dataset accessible from http://www.gapminder.org/data/
# In[1]:
get_ipython().magic(u'matplotlib inline')
# import the necessary librarie... |
<gh_stars>0
#!/usr/local/bin/ python3
# This script is to compare the any FAT fitting directory and produce the plots of the Current_Status report.
#Last processed is pyFAT V0.0.3
#The config file should be the only input required. The script assumes that the model/high resolution fit is in ModelInput.def
#FATInput='/... |
# PnP Node
#
# <NAME> <<EMAIL>>
# <NAME> <<EMAIL>>
from scipy.spatial import transform
import torch
from kornia.geometry import conversions
import open3d
import numpy as np
import random
from scipy.spatial.transform import Rotation
import copy
from ddn.pytorch.node import *
import ddn.pytorch.geometry_utilities as g... |
<filename>exoplanet_transit_snr/snr_estimate.py
# -*- coding: utf-8 -*-
from ctypes import c_long
from glob import glob
from itertools import combinations
from os import makedirs
from os.path import basename, dirname, join, realpath
from typing import Tuple, Union
import matplotlib.pyplot as plt
import numpy as np
imp... |
import argparse
import random,os,sys
import numpy as np
import csv
from scipy import stats
import time
from sklearn.model_selection import train_test_split
from sklearn import metrics
from sklearn.metrics import roc_auc_score
from sklearn import preprocessing
import pandas as pd
import keras.backend as K
from keras.mod... |
import pandas as pd
import math
import datetime
import numpy as np
import statistics as stat
#from portfolio import Portfolio
class Finance:
"""
Contains methods to calculate important statistical characeristics
of securities and their relationships to each other to build efficient
portfolios
"""... |
"""Define the Problem class and a FakeComm class for non-MPI users."""
import sys
import pprint
import os
import logging
import weakref
import time
from collections import defaultdict, namedtuple, OrderedDict
from fnmatch import fnmatchcase
from itertools import product
from io import StringIO
import numpy as np
im... |
'''
Created on Mar 23, 2016
This module is used for multi-dimensional scaling.
@author: mernberger
'''
import matplotlib
#from matplotlib.mlab import PCA as mlabPCA
from matplotlib import pyplot as plt
from matplotlib import offsetbox
from mpl_toolkits.mplot3d import Axes3D
import pandas as pd
import pypipegraph as pp... |
<filename>utils/RX.py
###################################################
# FILE: rx.py #
# AUTHOR: NotPike #
# Function: Handles audio record, functions #
# refered from alijamaliz. #
# https://github.com/alijamaliz/DTMF... |
#!/usr/bin/env python
# coding: utf-8
# The decision which model to use or what hyperparameters are most suitable is often based on some Cross-Validation technique producing an estimate of the out-of-sample prediction error $\bar{Err}$.
#
# An alternative technique to produce an estimate of the out-of-sample error i... |
# -*- coding: utf-8 -*-
"""
Created on Mon Apr 13 20:05:29 2020
@author: gosl241
"""
import argparse
import sys
#SG: once you install the package this is unecessariy
#sys.path.insert(0, "../../")
import hyphalnet.hypha as hyp
from hyphalnet.hypha import hyphalNetwork
import hyphalnet.proteomics as prot
import hyph... |
import os
from PIL import Image
import pandas as pd
import numpy as np
import time, threading
from multiprocessing import Pool
import scipy.io as sio
import my_transform as T
import scipy.stats as st
import time
def transform():
# base_size = args.img_size + 64
# crop_size = args.img_size
transforms = []
# ... |
<gh_stars>1-10
import os
import numpy as np
import torch
import torchvision
import albumentations as A
import pandas as pd
import matplotlib.pyplot as plt
import pandas as pd
import random
from random import Random
from datetime import datetime
from torch.utils.data import Dataset
from glob import glob
from PIL impor... |
<reponame>TechnicalConsultant123/financial-maths<gh_stars>1-10
import numpy as np
from scipy import stats
def european_call(x, rb, T, d1, K, rq, d2):
return x * np.exp(-rb * T) * stats.norm.cdf(d1) - K * np.exp(-rq * T) * stats.norm.cdf(d2)
def calc_d1(x, K, rq, sg, T, rb):
return (np.log(x / K) + (rq - rb ... |
"""Example of a devito forward/gradient implementation for a single source with odl."""
import numpy as np
import matplotlib.pyplot as plt
from scipy import ndimage
import odl
from devito import Function
from examples.seismic import Model, RickerSource, Receiver, TimeAxis, PointSource
from examples.seismic.acoustic im... |
<gh_stars>1-10
import numpy as np
import sg_utils as utils
from scipy.interpolate import interp1d
from IPython.core.debugger import Tracer
def calc_pr_ovr(counts, out, K):
"""
[P, R, score, ap] = calc_pr_ovr(counts, out, K)
Input :
counts : number of occurrences of this word in the ith image
out :... |
<reponame>bergkvist/pandapower
# -*- coding: utf-8 -*-
# Copyright (c) 2016-2020 by University of Kassel and Fraunhofer Institute for Energy Economics
# and Energy System Technology (IEE), Kassel. All rights reserved.
from scipy.optimize import minimize
from pandapower.estimation.algorithm.base import BaseAlgorithm
... |
import numpy as np
from scipy import linalg
import matplotlib as mpl
import matplotlib.pyplot as plt
# from plt import cm
from matplotlib import rc
import time
import IPython
# rc('font', **{'family': 'sans-serif', 'sans-serif': ['Helvetica']})
# rc('text', usetex=True)
def make_meshgrid(x, y, h=.02):
"""Create... |
# -*- coding: utf-8 -*-
"""
Created on Wed Nov 7 15:47:38 2018
@author: jdietric
"""
#pyqt import
#from PyQt5 import QtCore, QtGui, QtWidgets
# other imports
import os
import sys
import numpy as np
import pandas as pd
import sympy.geometry as spg
import matplotlib.path as mplPath
from datetime import datetime
from ... |
<reponame>MingtaoGuo/-Chinese-Character-and-Calligraphic-Image-Processing
import numpy as np
import matplotlib.pyplot as plt
from PIL import Image
import scipy.misc as misc
import os
def find_row(img):
row_locs = []
locs = np.zeros([2])
y = np.sum(img, axis=1, dtype=np.int32) - 10
y = np.... |
<reponame>rukmal/FE-621-Homework<filename>fe621/black_scholes/call.py
from .util import computeD1D2
from scipy.stats import norm
import numpy as np
def blackScholesCall(current: float, volatility: float, ttm: float,
strike: float, rf: float) -> float:
"""Function to compute the Black-Scholes... |
<filename>delphi/AnalysisGraph.py
import os
import json
import pickle
import random
from math import exp, log, pi
from datetime import date
from functools import partial
from itertools import permutations, cycle, chain
from typing import Dict, Optional, Union, Callable, Tuple, List, Iterable
from uuid import uuid4
impo... |
<reponame>Yin-YinjianZhao/WarpX<filename>Examples/Modules/space_charge_initialization/analysis.py
#!/usr/bin/env python3
# Copyright 2019-2020 <NAME>, <NAME>
#
# This file is part of WarpX.
#
# License: BSD-3-Clause-LBNL
"""
This script checks the space-charge initialization routine, by
verifying that the space-charg... |
from PIL import Image, ImageDraw, ImageFont
import io
import numpy as np
import pandas as pd
import folium
from matplotlib.colors import LinearSegmentedColormap, rgb_to_hsv, hsv_to_rgb
import scipy.ndimage.filters
from pathlib import Path
pd.options.display.max_columns = 50
def main(dir):
# Loading Data Set
p... |
<filename>ndispers/media/glasses/_caf2.py<gh_stars>1-10
import sympy
from sympy.utilities import lambdify
from ndispers._baseclass import Medium, wl, T
from ndispers.helper import vars2
class CaF2(Medium):
"""
Ca F_2 (Calcium fluolide) crystal
- Point group : Fm3m
- Crystal system : cubic
- Tranpa... |
<gh_stars>10-100
#################################################################
# One-nearest neighbor classifier
#################################################################
from optparse import OptionParser
import sklearn
from sklearn.neighbors import NearestNeighbors
import scipy
from scipy.stats import ... |
import numpy as np
from kamodo import Kamodo, kamodofy, gridify
from scipy.interpolate import RegularGridInterpolator, interp1d
from netCDF4 import Dataset
import time
from datetime import datetime,timedelta,timezone
import numpy.ma as ma
# constants and dictionaries
ctipe_kamodo_variable_names = dict( density='rho'... |
<reponame>LucasGab/Plane-Generator
'''
Programa desenvolvido por: <NAME> - 1º Semestre
NºUSP: 11218880
Curso: Ciências da Computação - USP
Matéria: Geometria Analítica
Professor: <NAME>
Código da matéria: SMA0300
Descrição: Programa que faz o gráfico de 3 planos e sua intersecção.
Data de desenvolvimento: 25 - 27 de ab... |
#!/usr/bin/env python
from __future__ import print_function
import math
import matplotlib
matplotlib.use("PDF")
fig_size = [8.3,11.7] # din A4
params = {'backend': 'pdf',
'axes.labelsize': 10,
'text.fontsize': 10,
'legend.fontsize': 10,
'xtick.labelsize': 8,
'ytick.labelsize... |
<filename>quspin/basis/base.py
from __future__ import print_function
import numpy as _np
import scipy.sparse as _sp
import warnings,numba
@numba.njit
def _coo_dot(v_in,v_out,row,col,ME):
n = row.shape[0]
m = v_in.shape[1]
for i in range(n):
r = row[i]
c = col[i]
me = ME[i]
for j in range(m):
v_out[r,j] ... |
# linha de comando python convolutions.py --image 3d_pokemon.png
# pacotes necessários
from skimage.exposure import rescale_intensity
import numpy as np
import argparse
import cv2
import pdb
import time
from scipy import stats
# método de convulsão
def convolve(image, kernel):
# dimensões espaciais da imagem,... |
<reponame>vsomnath/holoprot
"""
Functions to compute features for a patch on the protein surface.
Taken from https://github.com/LPDI-EPFL/masif
"""
import numpy as np
from Bio.PDB import Selection
from Bio.PDB.Residue import Residue
from subprocess import PIPE, Popen
import os
from scipy.spatial import KDTree
from typ... |
<gh_stars>0
import networkx as nx
import numpy as np
from scipy.spatial import KDTree
def getInputNeighbors(q, tree, knn, rnn):
d, i = tree.query(q, k=knn, eps=0.0, p=2.0, distance_upper_bound=rnn)
d = list(d)
i = list(i)
nn = 0
if d.count(float('inf')) > 0:
infIndex = d.index(float('inf'... |
<gh_stars>0
# -*- coding: utf-8 -*-
from __future__ import print_function, division, absolute_import
import math
import cmath
import unittest
from flypy import jit
from flypy.runtime import mathlib
import numpy as np
# ______________________________________________________________________
class TestMathLib(unittes... |
<gh_stars>1-10
from pathlib import Path
import argparse
import scipy.misc
import numpy as np
import imageio
from utils import load_case
# Constants
DEFAULT_KIDNEY_COLOR = [255, 0, 0]
DEFAULT_TUMOR_COLOR = [0, 0, 255]
DEFAULT_HU_MAX = 512
DEFAULT_HU_MIN = -512
DEFAULT_OVERLAY_ALPHA = 0.3
DEFAULT_PLANE = "axial"
de... |
<filename>mner/model.py
import numpy as np
import theano.tensor as T
import theano
from scipy.linalg import svd
""" model.py (module)
This module contains the basic model classes, their objective
functions, gradients, constraints, and Hessians. For now, the only
model is the 'MNEr' model for the low-rank ... |
<filename>training-data/converge-diverge/preProcess.py<gh_stars>10-100
"""
A simple pre-processing file for converting raw OpenFOAM data to
PyTorch tensors. This makes reading the data by the neural network
signifcantly faster. Additionally, depending on the flow, spacial
averages can be taken to increase smoothness o... |
# -*- coding: utf-8 -*-
###################################################################################
# MIT License
# Copyright (c) 2015-2017 <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... |
#!/usr/bin/env python
############################################################################
#
# This file contains different functions used for the processing of Geodesy
# data.
#
# written by <NAME> and <NAME>
#
# 16 July 2020
#
# note that all *csv files have to be unique!
#
# requires - pandas versio... |
<gh_stars>1-10
import numpy as np
import scipy
import scipy.io as sio
import sys
import pandas as pd
import os
import datetime
import time
import copy
import estimator
from tqdm import tqdm
from timeit import default_timer as timer
from initialize import initialize
from Adaptive_SEIR import SEIR
from multiprocessing... |
<reponame>grlee77/dask-summit-2021-life-sciences
# adapted from cuCIM, see ../LICENSE-3rdparty.txt
import os
import pickle
import cupy
import cupy as cp
import cupyx.scipy.ndimage
import dask.array as da
import dask_image
import dask_image.ndfilters
import numpy as np
import pandas as pd
import scipy
from _image_ben... |
<filename>Newton-Raphson-Method.py
import sympy as sp
x, y, z = sp.symbols('x y z')
sp.init_printing()
# Here we simply give the input needed as The Following:
# ( Xi ) is The Initial Point
# ( Fx ) is the equation of the function
# ( n ) is the number of Iterations needed
Xi = 0
Fx = x**3 -0.2589*x**2+0.2262*x -... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Licensed under the GNU LGPL v2.1 - http://www.gnu.org/licenses/lgpl.html
from gensim.summarization.textcleaner import tokenize_by_word as _tokenize_by_word
from gensim.utils import to_unicode
import numpy
import scipy
def mz_keywords(text, blocksize=1024, scores=Fal... |
<filename>smt/applications/moe.py
"""
Author: <NAME> <<EMAIL>>
This package is distributed under New BSD license.
Mixture of Experts
"""
# TODO : support for best number of clusters
# TODO : implement verbosity 'print_global'
# TODO : documentation
import numpy as np
import warnings
OLD_SKLEARN = False
try: # scik... |
from ctypes import CDLL, c_int, c_double, POINTER
import numpy as np
from config import get_library_path
library = CDLL(get_library_path("eigen"))
c_int_p = POINTER(c_int)
c_double_p = POINTER(c_double)
_solve_eigen_icholt_coo = library.solve_eigen_icholt_coo
_solve_eigen_icholt_coo.restype = c_int
_solve_eigen_icho... |
<filename>eureka/S4_generate_lightcurves/s4_genLC.py
#! /usr/bin/env python
# Generic Stage 4 light curve generation pipeline
# Proposed Steps
# -------- -----
# 1. Read in Stage 3 data products
# 2. Replace NaNs with zero
# 3. Determine wavelength bins
# 4. Increase resolution of spectra (optional)
# 5. Smooth... |
import abc
import numpy as np
import pandas as pd
import scipy.cluster.hierarchy as sch
from fipie.common import ReprMixin
class ClusterAlgo(ReprMixin, metaclass=abc.ABCMeta):
def __init__(self, max_clusters):
self.max_clusters = max_clusters
def pre_process(self, data: pd.DataFrame) -> pd.DataFra... |
<reponame>impressive8/Practice
# =============================================================
# This file contains helper functions and classes
#
# <NAME>, 2017
#
# Report bugs/suggestions:
# <EMAIL>
# =============================================================
import png
import numpy as np
import scipy.misc
impo... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Author: <NAME> <<EMAIL>>
# Copyright (C) 2017 <NAME> <<EMAIL>>
# Licensed under the GNU LGPL v2.1 - http://www.gnu.org/licenses/lgpl.html
"""Scikit learn interface for :class:`gensim.models.lsimodel.LsiModel`.
Follows scikit-learn API conventions to facilitate using g... |
<filename>af_primitives/afSKMLPRegressor.py
from typing import Any, Callable, List, Dict, Union, Optional, Sequence, Tuple
from numpy import ndarray
from collections import OrderedDict
from scipy import sparse
import os
import sklearn
import numpy
import typing
import pandas
# Custom import commands if any
from af_mul... |
from sympy import S, Rational
from sympy import re, im, conjugate, sign
from sympy import sqrt, sin, cos, acos, exp, ln
from sympy import trigsimp
from sympy import integrate
from sympy import Matrix
from sympy import sympify
from sympy.core.evalf import prec_to_dps
from sympy.core.expr import Expr
class Quaternion(E... |
<gh_stars>1-10
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plot
import matplotlib.cm as cm # cm.rainbow
import sys, pprint, math, numpy, sympy, simpy, getopt
from math import factorial
from numpy import linalg
from patch import *
from commonly_used import *
'''
# ------------------------------... |
<filename>spimcube/spimclass.py
import re
import copy
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.widgets import (AxesWidget, Slider, Button, RadioButtons, CheckButtons, Cursor, MultiCursor, RectangleSelector, Lasso)
from matplotlib import path
from matplotlib.collections import RegularPol... |
# -*- coding: utf-8 -*-
"""
Define functions useful for conversion between different NFW conventions
This module contains the functions used to move between NFW conventions and
to transform NFW parameters into lenstronomy inputs.
"""
import numpy as np
from ..Utils import cosmology_utils
import numba
from scipy.interp... |
import numpy as np
from scipy.stats import norm, truncnorm
def _em_step_body_(args):
"""
Does a step of the EM algorithm, needed to dereference args to support parallelism
"""
return _em_step_body(*args)
def _em_step_body(Z, r_lower, r_upper, sigma, num_ord_updates=1):
"""
Iterate the rows ove... |
<reponame>Abeilles14/motion_planning<filename>python_src/rrts/3D/main.py
# STATE MACHINE FOR 3D PICK AND PLACE SIMULATION
import numpy as np
from numpy.linalg import norm
from math import *
from matplotlib import pyplot as plt
from matplotlib.patches import Polygon
from random import random
from scipy.spatial import Co... |
<filename>VIV_data_on_velocities.py
import tensorflow.compat.v1 as tf
import numpy as np
import matplotlib.pyplot as plt
import scipy.io
from scipy.interpolate import griddata
import time
from plotting import newfig, savefig
import matplotlib.gridspec as gridspec
from mpl_toolkits.axes_grid1 import make_axes_locatable
... |
<reponame>kastnerkyle/tfbldr
import matplotlib
matplotlib.use("Agg")
import os
import argparse
import tensorflow as tf
import numpy as np
from tfbldr.datasets import fetch_fruitspeech
from tfbldr.datasets.audio import soundsc
from tfbldr.datasets.audio import overlap
from tfbldr.plot import specgram
from tfbldr.plot i... |
<reponame>liningtonlab/npmrd_curator
"""Takes data blocks and converts to ACS style guide string.
"""
from typing import Dict
from statistics import mean
def write_all(data: Dict) -> str:
n = data.get("name", "")
# optr = optical_rotation(data.get("optical_rotation"))
# uv = uv_spectroscopy(data.get("uv_s... |
<filename>stanford/sms-tools/lectures/04-STFT/plots-code/hamming.py
import matplotlib.pyplot as plt
import numpy as np
from scipy.fftpack import fft
M = 64
N = 512
hN = N//2
hM = M//2
fftbuffer = np.zeros(N)
mX1 = np.zeros(N)
plt.figure(1, figsize=(7.5, 4))
fftbuffer[hN-hM:hN+hM]=np.hamming(M)
plt.subplot(2,1,1)... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
# CODE NAME HERE
# CODE DESCRIPTION HERE
Created on 2019-08-21 at 12:28
@author: cook
"""
from astropy.table import Table
from astropy import constants as cc
from astropy import units as uu
import numpy as np
import os
from scipy.optimize import curve_fit
import warn... |
import os
import numpy as np
import scipy.io as sio
import torch
ISING_GRID_H = 4
ISING_GRID_W = 4
ISING_N_EDGES = 24
CONTAMINATION_N_STAGES = 25
AEROSTRUCTURAL_N_COUPLINGS = 21
def sample_init_points(n_vertices, n_points, random_seed=None):
"""
:param n_vertices: 1D array
:param n_points:
:para... |
<reponame>catalystneuro/tank-lab-to-nwb
"""Authors: <NAME>, <NAME>."""
import os
import sys
from pathlib import Path
from shutil import which
import numpy as np
from datetime import datetime
from scipy.io import loadmat, matlab
from collections import Iterable
try:
from typing import ArrayLike
except ImportError... |
<reponame>prateek-rtk/jun
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import sys
import scipy as sp
import numpy as np
import matplotlib as mpl
import pandas as pd
import sklearn as skl
import operator as opt
import pyodbc as pyodbc
from io import StringIO
from dateutil.parser import parse
mpl.use('Agg')
opers = {'<... |
# -*- coding: utf-8 -*-
"""
Created on Thu Jan 15, 2015
@author: <NAME>
"""
from __future__ import print_function
from .filter import \
_lowpass_ba, _highpass_ba, _bandpass_ba, \
_lowpass_ba_lanczos, _highpass_ba_lanczos
import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import freqz
# -... |
#coding: utf-8
import wave
import pyaudio
import matplotlib.pyplot as plt
import numpy as np
import time
import wave
from scipy.fftpack import fft, ifft
from scipy import signal
def printWaveInfo(wf):
"""WAVEファイルの情報を取得"""
print( "chn:", wf.getnchannels())
print( "width:", wf.getsampwidth())
print( "sam... |
<filename>pisa/stages/osc/pi_nusquids.py
'''
Oscillation stage using nuSQuIDS
'''
# TODO Check if can speed up by linking containers in certain modes (see `pi_prob3`)
# TODO Update descriptions/docs
from __future__ import absolute_import, print_function, division
# TODO Clean these up, including numba
import math
i... |
# Copyright 1999-2020 Alibaba Group Holding Ltd.
#
# 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 a... |
<filename>test_IRC10420_IR.py<gh_stars>0
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Jan 3 16:27:40 2022
@author: nbadolo
"""
"""
Code simplifié
"""
import numpy as np
from astropy.io import fits
from scipy import optimize
import cv2 # pour ameliorer la résolution de l'image
from astropy.ndda... |
<filename>filters.py
# 2014.04.29
# S.Rodney
# HST Filter transmission curves: plotting and such
import numpy as np
from matplotlib import pylab as pl
import os
topdir = os.path.abspath( '.' )
try :
sndataroot = os.environ['SNDATA_ROOT']
os.chdir( sndataroot+'/filters/HST_CANDELS')
w435, f435 = np.loadt... |
<gh_stars>10-100
from sklearn import metrics
import numpy as np
import time
from scipy import stats
from mlxtend.evaluate import permutation_test
class DataSanitization():
def __init__(self, data):
self.data = data
def is_complete(self, column):
return self.data[column].isnull().sum()... |
<filename>dmtreduce/utils.py
import os
import pathlib as path
from matplotlib import pyplot as plt
from astropy.visualization import ZScaleInterval
from scipy.signal import savgol_filter
def quickplot_spectra(data, contrast=1, make_figure=True, show=True, outfile=None, colorbar=False):
""" Quickly plot an easi... |
import statistics
from collections import deque
from ParadoxTrading.Indicator.IndicatorAbstract import IndicatorAbstract
from ParadoxTrading.Utils import DataStruct
class KDJ(IndicatorAbstract):
def __init__(
self,
_k_period: int = 20,
_d_period: int = 3,
_j_period... |
__all__ = ['SimplicialComplex','simplicial_complex']
from warnings import warn
import numpy
import scipy
from numpy import array, dot, inner, ones, cross, copysign
from scipy import sparse, zeros, asarray, mat, hstack
import pydec
from pydec.mesh.simplex import simplex, simplicial_mesh
from pydec.math import (circum... |
from scipy.interpolate import LinearNDInterpolator, NearestNDInterpolator, interp1d
from scipy.spatial import ConvexHull
import numpy as np
class DTL_Classifier():
def __init__(self):
self.dtl = None
self.nnl = None
self.hull = None
self.max1d = None
self.min1d =... |
import pickle
import sympy as sp
import numpy as np
from racing import offboard
from utils import base, racing_env
from utils.constants import *
def racing(args):
track_layout = args["track_layout"]
track_spec = np.genfromtxt("data/track_layout/" + track_layout + ".csv", delimiter=",")
if args["simulation... |
<filename>nerual_style/main.py<gh_stars>1-10
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# File: main.py
# Author: <NAME> <<EMAIL>>
import os
import argparse
import numpy as np
from scipy import misc
import tensorflow as tf
from utils import load_image
from neural_style import NerualStyle
VGG_PATH = '/home/qge2/w... |
"""Most of these tests come from the examples in Bronstein's book."""
from sympy.integrals.risch import DifferentialExtension, derivation
from sympy.integrals.prde import (prde_normal_denom, prde_special_denom,
prde_linear_constraints, constant_system, prde_spde, prde_no_cancel_b_large,
prde_no_cancel_b_small, ... |
#!/usr/bin/env python
"""Script that parses CATME peer evaluation data and plots summary plots and
statistics.
The CATME Peer evaluation results are provided in a CSV file which contains
more than one table and mixed in metadata. The data are separated by double
line returns and are as follows:
1. Extraneous metadat... |
from graph_data import graph_data
import numpy as np
from scipy.linalg import block_diag
from typing import Final
from networkx.generators.random_graphs import watts_strogatz_graph, barabasi_albert_graph, fast_gnp_random_graph
from networkx.linalg.graphmatrix import adjacency_matrix
class Gnp_overfit:
def __init__... |
import requests
import json
import sys
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
from scipy.optimize import curve_fit
from matplotlib.ticker import PercentFormatter
# get all
# url = 'http://localhost:5000/gasstat'
headers = {'content-type': 'application/json'}
response = requests.get(u... |
<gh_stars>10-100
import os
import sys
import re
import ast
from heapq import nlargest
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.lines import Line2D
from matplotlib.patches import Rectangle, Circle, PathPatch, Path
import numpy as np
import scipy.interpolate
import tkinter as tk
import cv2
import... |
<filename>graph.py<gh_stars>10-100
import matplotlib.pyplot as plt
import seaborn as sns
sns.set(style = "whitegrid", palette = "muted")
import numpy as np
import matplotlib.gridspec as gridspec
import csv
import pandas as pd
from scipy import misc
def generategraph(x, accuracy, lost):
fig = plt.figure(figsiz... |
<reponame>Lituchy/nrpyunittesting<gh_stars>0
import NRPy_param_funcs as par
import re
from SIMD import expr_convert_to_SIMD_intrins
from collections import namedtuple
lhrh = namedtuple('lhrh', 'lhs rhs')
outCparams = namedtuple('outCparams', 'preindent includebraces declareoutputvars outCfileaccess outCverbose CSE_ena... |
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