text string |
|---|
import numpy as np
from scipy.fftpack import fft, fftshift
import math
"""
A3-Part-3: Symmetry properties of the DFT
Write a function to check if the input signal is real and even using the symmetry properties of its
DFT. The function will return the result of this test, the zerophase windowed version of the input
s... |
"""Callback functions for CPF
"""
from numpy import c_, r_, amax, argmax, array
from scipy.sparse import issparse
import sys
import os
def cpf_default_callback(k, V_c, lam_c, V_p, lam_p, cb_data, cb_state, cb_args, results=None, is_final=False):
"""Default callback function for CPF
"""
# initialize plo... |
<gh_stars>0
import numpy as np
import scipy as scipy
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns
from matplotlib import rc
# plotting settings
rc('text', usetex=True)
rc('text.latex', preamble=r'\usepackage{cmbright}')
rc('font', **{'family': 'sans-serif', 'sans-serif': ['Helvetica']... |
import scipy.ndimage as ndimage
import pylab as plt
import moments
#import indexTricks as iT
import numpy
class RingFinder():
def __init__(self,B,R,sB,sR,pB,pR,pixelsize=0.265,zerofluxB=1e12,zerofluxR=1e12,visualize=False,psfmode="worst"):
self.pixelsize=pixelsize
self.zerofluxB=zerofluxB
... |
<reponame>xrick/Lcj-DSP-in-Python<gh_stars>0
from scipy.io.wavfile import read
import matplotlib.pyplot as plt
filename = input( "Please enter file name: " )
sampling_rate, x = read( filename )
plt.plot( x )
plt.xlabel( 'n' )
plt.ylabel( 'Amplitude' )
plt.show( ) |
import pickle as pkl
import numpy as np
from scipy import special as spec
import higrid.Microphone as mc
def shd_nm(channels, n, m):
"""
Calculate the n-the order, m-th degree SHD coefficients for the given Eigenmike em32 channels
:param channels: 32 channels of audio from Eigenmike em32
:param n: S... |
<reponame>akutkin/apipeline<gh_stars>0
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Clustering based on presence of artifacts around sources
Created on Tue Dec 10 20:48:31 2019
@author: kutkin
"""
import os
import sys
import astropy.io.fits as fits
from astropy.wcs import WCS
from astropy.coordinates import Sk... |
"""Back-calculating TrainingPeaks Normalized Graded Pace"""
import os
import pandas as pd
from scipy.interpolate import interp1d
from . import util
def factor(grade, source='strava'):
"""Speed-independent factor for adjusting pace based on grade.
TrainingPeaks: decimal grade is constrained to (-0.25, 0.3), be... |
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Tue Apr 18 16:59:56 2017
@author: m.irvine
"""
import numpy as np
import matplotlib.pyplot as plt
from scipy.ndimage.filters import convolve
def shortenKernel(l,N):
k = np.floor(np.sqrt(2*np.log(1/0.025))*l**2)+1; #this selects the size of the kernel s... |
import logging
from collections import defaultdict
import itertools
import time
import scipy as sp
import scipy.stats as stats
import numpy as np
import pandas as pd
import plotly.express as px
from tqdm import tqdm
from xps import get_methods_from_results
# ███████╗██╗ ██╗███████╗ ██████╗██╗ ██╗█... |
<filename>training_and_testing/make_life_assay_pilot_background_subtraction_comparison.py
# The MIT License (MIT)
#
# Copyright (c) 2014 WUSTL ZPLAB
#
# 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 S... |
<filename>rapidhrv/preprocessing.py
import dataclasses
from typing import Literal, Optional
import numpy as np
import scipy.interpolate
import scipy.signal
from .data import Signal
def cubic_spline_interpolation(signal: Signal, resample_rate: int) -> Signal:
if resample_rate % signal.sample_rate != 0:
r... |
#!/usr/bin/python3
# This is an initial, hacky implementation of the extended LQR paper. It's just
# a proof of concept, so don't trust it too much.
import numpy
import scipy.optimize
from matplotlib import pylab
import sys
from frc971.control_loops.python import controls
class ArmDynamics(object):
def __init__(s... |
<gh_stars>0
#!/usr/bin/env python
# coding: utf-8
import sys
import scipy.sparse as sp
import numpy as np
from scipy.io import loadmat, savemat
import os
from sklearn.metrics import confusion_matrix
import matplotlib.pyplot as plt
from matplotlib import rcParams
def replace_list_element(l, before, after):
"""Help... |
import h5py
import itertools
import marshal
import multiprocessing as mp
import numpy as np
import pandas as pd
import pathlib
import pickle
import scipy.signal
import sklearn.model_selection
import sklearn.svm
import tqdm.notebook as tqdm
import types
def _init_pdist(fastmap, _X1, _X2, _W1, _W2):
global self, X1... |
<gh_stars>0
# -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4
#
# Copyright (C) 2012-2016 GEM Foundation
#
# OpenQuake is free software: you can redistribute it and/or modify it
# under the terms of the GNU Affero General Public License as published
# by the Free Software Foundation, either version 3 ... |
<filename>TESTDPP.py
import argparse
import baselineUtils
import torch
import torch.utils.data
import torch.nn as nn
import torch.nn.functional as F
import os
import time
from transformer.batch import subsequent_mask
from torch.optim import Adam,SGD,RMSprop,Adagrad
from transformer.noam_opt import NoamOpt
import numpy ... |
<filename>startup/43-ESM_utilities.py
import IPython
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy.interpolate import interp1d
import scipy.optimize as opt
import os
from bluesky.plans import scan, adaptive_scan, spiral_fermat, spiral,scan_nd
from bluesky.plan_stubs import abs_set, m... |
<reponame>scalabel/scalabel
"""Functions for KITTI."""
import os
from typing import Dict, List, Tuple
import numpy as np
from scipy.spatial.transform import Rotation as R
from ..common.io import open_read_text
from ..common.typing import NDArrayF64
try:
import utm
except ImportError:
utm = None
# Functions... |
<reponame>grawies/stable-poly
#!/home/sam/shared-space/linux-system/anaconda3/bin/python
import math
import sympy as sp
from bistochastic import generate_matrix
import fpiter
from polynomials import product_polynomial
from functionals import elementary_symmetric_differential_operator
import numpy.random
SEED = 1
nump... |
import matplotlib.pyplot as plt
import numpy as np
from scipy.spatial import HalfspaceIntersection
from kaa.lputil import minLinProg, maxLinProg
from kaa.timer import Timer
from kaa.settings import PlotSettings
plt.rcParams.update({'font.size': PlotSettings.plot_font})
"""
Object encapsulating flowpipe data.
"""
cl... |
<gh_stars>0
import numpy as np
from numpy import pi, sin, cos
import math
import matplotlib.pyplot as plt
import sympy as sp
from sympy.interactive.printing import init_printing
init_printing(use_unicode=False, wrap_line=False)
from sympy.matrices import Matrix, eye, zeros, ones, diag, GramSchmidt
from sympy im... |
import csv
import ray
import logging
import numpy as np
import pandas as pd
#import torch
from scipy.stats.mstats import gmean
# from .lw.lw_nn import LWNN
# from .lw.lw_tree import LWTree
from .estimator import Estimator
from ..constants import NUM_THREADS, RESULT_ROOT
from ..workload.workload import load_queryset,... |
import os
import torch
from torch import nn
import pytorch_lightning as pl
from argparse import ArgumentParser
import KohnShamSpin
from tqdm import tqdm
from scipy import optimize
import sys
import numpy as np
class XC_Model(pl.LightningModule):
def __init__(self, **hparams):
"""
Pass in parsed HyperOptArg... |
<reponame>ozanarkancan/path-planning<filename>potential_field.py<gh_stars>1-10
import numpy as np
from scipy.ndimage.filters import gaussian_filter
class PotentialField:
def __init__(self, start, goal, cspace):
self.start = start
self.goal = goal
self.cspace = cspace
def get_attractive... |
<reponame>sfarrens/lenspack
# -*- coding: utf-8 -*-
import numpy as np
from scipy.ndimage import convolve
from scipy.signal import fftconvolve
from lenspack.utils import radius2d, round_up_to_odd
FILTER_OPTIONS = {'s98', 'vw98', 'jbj04', 'starlet', 'gauss'}
METHOD_OPTIONS = {'direct', 'fourier', 'brute'}
BORDER_OPT... |
# 通用类
import cmath
import wave
import librosa
import librosa.display
import matplotlib.pyplot as plt
import numpy as np
import pyaudio
class Speech:
def audiorecorder(self, path, len=2, formater=pyaudio.paInt16, rate=16000, frames_per_buffer=1024, channels=2):
p = pyaudio.PyAudio()
stream = p.o... |
from scipy.constants import hbar, pi
import numpy as np
DeltaS = 1.764*1.38064852e-23*1.1
e = 1.60217662e-19
GHz = 1e9
MHz = 1e6
kHz = 1e3
Hz = 1
bare_cavity_freq = 7.35*GHz
dressed_cavity_freq_ground = 7.24426*GHz
dressed_cavity_freq_exited = 7.21762*GHz #None
f01 = 6.63387*GHz
f12 = 5.79571*GHz
Ec = ... |
<filename>python/create_climatology.py
#
# Copyright (c) 2017, UT-BATTELLE, LLC
# All rights reserved.
#
# This software is released under the BSD license detailed
# in the LICENSE file in the top level a-prime directory
#
# Compute the climatology for a case
# Uses MPI
import numpy
from scipy.io import netcdf
from ... |
import argparse
import glob, os
import random
import re
import sys
import time
from os.path import join
import cv2
import numpy as np
import tensorflow as tf
from utils.metrics_utils import *
random.seed(1024)
np.random.seed(1024)
tf.set_random_seed(1024)
from utils.icp_zou import icp
from tqdm import tqdm
import ... |
<filename>env_dev/lib/python3.6/site-packages/sparsegrad/tests/test_dot.py
# -*- coding: utf-8; -*-
#
# sparsegrad - automatic calculation of sparse gradient
# Copyright (C) 2016-2018 <NAME> (<EMAIL>)
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General... |
<filename>tests/test_reduction.py
#!/usr/bin/env python
"""Tests for reduction methods of CRN class.
References
==========
[1] <NAME>. "Fundamentals of enzyme kinetics". Elsevier, 2014.
[2] <NAME>. "Mathematical Modelling in Systems Biology: An Introduction.", 2013.
[3] SBMLsqueezer documentation, http://www.cogsys.cs... |
import numpy as np
from reader import read_cifar10
from scipy.io import loadmat
class load_data(object):
def __init__(self, name=None, bs=64):
if name == 'svhn':
data = loadmat('./dataset/svhn/svhn.mat')
self.images = data['X'].transpose(3,0,1,2)/127.5 - 1.0
self.nums_images = self.... |
<reponame>TChis/Musketeer
import os
import tkinter as tk
import tkinter.ttk as ttk
import tkinter.filedialog as fd
import packaging.version
import numpy as np
import tksheet
from scipy.interpolate import interp1d
from cycler import cycler
from ttkbootstrap.widgets import InteractiveNotebook
import tkinter.messagebox a... |
<filename>diagnostics/thomson/Thomson/thomson_theory.py
# -*- coding: utf-8 -*-
"""
Created on Wed Aug 8 08:19:21 2018
@author: James
"""
import matplotlib.pyplot as plt
import numpy as np
from scipy import signal
from scipy.optimize import leastsq
def laser_photons(E_pulse, laser_wavelength):
h = 6.626*... |
<filename>Croise_SCAT/croise_scatt.py
from pylab import *
import matplotlib
import time
from scipy.interpolate import interp1d
from scipy.io.wavfile import read
matplotlib.rc('xtick', labelsize=35)
matplotlib.rc('ytick', labelsize=30)
class sparse_filter:
def __init__(self,coeffs,support,mu):
self.mu = m... |
<reponame>enjoyneer87/SciDataTool
from numpy import (
array,
stack,
linspace,
argmin,
take,
isclose,
isin,
all,
abs as np_abs,
where,
zeros,
unique,
)
from scipy.interpolate import interp1d
def get_common_base(values1, values2, is_extrap=False, is_downsample=False):
... |
<filename>MEG eyes open vs closed.py
# -*- coding: utf-8 -*-
"""
Created on Thu Aug 22 17:53:14 2019
@author: Localadmin_fesieben
"""
projects_directory = 'K:\\palva\\'
#source_directory = 'D:\\felix\\OL2015\source\\'
source_directory = 'E:\\HY-data\\FESIEBEN\\OL2000\\OL2015\\source\\'
import... |
'''
AUTHORS: <NAME> and <NAME>
DATE: March 22, 2019
COPYRIGHT MARCH 22, 2019 <NAME> AND <NAME>
'''
from __future__ import print_function
'''
This module should be organized as follows:
Main function:
chi_estimate() = returns chi_n, chi_b
- calls:
wealth.get_wealth_data() - returns data moments on wealth... |
<reponame>xiaxin2000/OpenCDA-Documents<filename>opencda/core/sensing/perception/o3d_lidar_libs.py
# -*- coding: utf-8 -*-
"""
Utility functions for 3d lidar visualization and processing by utilizing open3d.
"""
# Author: <NAME>, <NAME> <<EMAIL>>
# License: MIT
import time
import open3d as o3d
import numpy as np
fro... |
import pandas as pd
import numpy as np
import hickle, pickle
import set_up
import scipy.sparse as sp
from sklearn.externals import joblib
import os
import logging
import imp
imp.reload(logging)
logging.basicConfig(format = '[%(asctime)s] %(message)s', level = logging.INFO)
logging.info('[Script for 1st st... |
<reponame>pengyonghui/invRCA
# -*- coding: utf-8 -*-
"""
Created on Sun Sep 13 13:54:59 2019
@author: yonghui
Control func that fits NMR data multiexponentially using non-negative least squares(NNLS)
with tikhonov regularization for nmr data analysis
- first written by <NAME> in Sep. 2006
- Keating and Falzone rev... |
#!/usr/bin/env python
'''
things that make affine_transform easier
'''
import numpy
import quietscipy
import scipy.ndimage
import scipy.linalg
def affine_transform_offset(inputshape, outputshape, affine_matrix, offset=(0,0)):
'''
calculation of affine transform offset
for now we assume center of image
'''
outcen... |
import numpy as np
from scipy import constants, optimize, math
from sympy.physics import units as U
from sympy.physics.units import convert_to
from pde.domain import Domain, DomainVar
from property_set.property_set import PropertySet
from utils.functional import cached_property
class InputError(Exception):
pass... |
import numpy as np
import itertools
import scipy
from scipy import sparse
from tqdm.notebook import tqdm
from itertools import chain, combinations, product
from scipy.special import comb
"""
This is a Python implementation of the minimum epistasis interpolation method for sequence-fitness prediction by Zhou & McCandl... |
import os
import sys
import datetime
import numpy as np
import scipy.signal
import pandas as pd
import yfinance as yf
from contextlib import contextmanager
from src.utils_date import add_days
from src.utils_date import prev_weekday
#from pandas_datareader.nasdaq_trader import get_nasdaq_symbols
ERROR_NO_MINUTE_DATA_YT... |
# AUTOGENERATED! DO NOT EDIT! File to edit: 03_visualize.ipynb (unless otherwise specified).
__all__ = ['plot_poses', 'plot_delaunay', 'fig2img', 'excerpt_pose', 'overlay_poses', 'overlay_video', 'draw_figure',
'viz_dist_matrices', 'GC_INTERVAL', 'MIN_MOVE', 'MAX_MOVE']
# Cell
import openpifpaf
import num... |
<reponame>chapman-phys227-2016s/hw-2-C0deMonkee
#! /usr/bin/env python
"""
File: Lagrange_poly2b.py
Copyright (c) 2016 <NAME>
License: MIT
Course: PHYS227
Assignment: 5.25
Date: Feb 11, 2016
Email: <EMAIL>
Name: <NAME>
Description: Behaivor of Lagrange interpolating polynomials
"""
import Lagrange_poly2 as L2
import ... |
"""
PTM_BTRACE
Magnetic field tracing and analysis for magnetic field data on scattered grids. This module is intended
to supercede the PTM_FIELDS_TRACING module.
This module defines a "GRIDDED_MAGNETIC_FIELD" object that reads in gridded magnetic field data
and allows for the fields to be arbitrarily evaluated, allo... |
"""Film Mode Matching Mode Solver
Implementation of the Film Mode Matching (FMM) algorithm, as described in:
- Sudbo, "Film mode matching a versatile numerical method for vector mode field calculations in dielectric waveguides", Pure App. Optics, 2 (1993), 211-233
- Sudbo, "Improved formulation of the film mode mat... |
import scipy.signal as signal
from concurrent.futures import ProcessPoolExecutor
import torch
import torch.nn as nn
import numpy as np
import torch.nn.functional as F
from torch.distributions import Categorical
import cy_heuristics as cy_heu
import sched
INPUT_SIZE = 10
N_WORKERS = 8
executor = ProcessPoolExecutor(ma... |
<filename>pcmc/pcmc-orig-synthetic.py<gh_stars>1-10
# (c) 2020 alherit
# This code is licensed under MIT license (see LICENSE.txt for details)
# python 2
# requires pcmc-nips\\lib from https://github.com/sragain/pcmc-nips in PYTHONPATH
import numpy as np
import pickle
import os
import pandas as pd
f... |
# -*- coding: utf-8 -*-
"""
Created on Fri Aug 31 14:18:58 2018
"""
import geopandas as gpd
import pandas as pd
from scipy.stats import linregress
from functools import reduce
import matplotlib.pyplot as plt
from math import sqrt
import numpy as np
from numpy.polynomial.polynomial import polyfit
#---------------------... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright (C) 2010 <NAME> <<EMAIL>>
# Licensed under the GNU LGPL v2.1 - http://www.gnu.org/licenses/lgpl.html
"""
Automated tests for checking transformation algorithms (the models package).
"""
import logging
import unittest
import os
import os.path
import tempfile... |
#!/usr/bin/env python
'''
A solution to a ROSALIND bioinformatics problem.
Problem Title: Independent Alleles
Rosalind ID: LIA
Rosalind #: 015
URL: http://rosalind.info/problems/lia/
'''
from scipy.misc import comb
with open('data/rosalind_lia.txt') as input_data:
k, N = map(int, input_data.read().split())
prob = ... |
# This code is licensed under the MIT License (see LICENSE file for details)
import pathlib
import os
import pkg_resources
import subprocess
import tempfile
import numpy
from scipy import ndimage
from sklearn import mixture
import freeimage
import zplib.image.mask as zpl_mask
from . import load_data
from . import w... |
<gh_stars>0
"""A collection of classes to that build regularisation matrices for a least
squares inversion.
The regularisation matrices are created to be used as part of Tikhonov
regularisation [1]. I think this is also referred to as damping or damped
least squares. In the simplest case the Tikhonov matrix (Γ) is jus... |
<gh_stars>1-10
#============================================================
# THIS IS FOR COLLECTING ALL OBSERVATION DATA FOR FOLLOW-UP OBSERVATION TO S190425z
# 2019.06.08 MADE BY <NAME>
#============================================================
import os, glob
import numpy as np
from astropy.io import ascii
from ... |
<reponame>Timonzimm/CS-401<filename>project/api/api.py<gh_stars>0
import sqlite3
from scipy.stats import gaussian_kde
from flask import Flask, g, jsonify
from flask_cors import CORS
app = Flask(__name__)
CORS(app)
DATABASE = 'data/database.sqlite'
def get_db():
db = getattr(g, '_database', None)
if db is None... |
'''
Created on 28 Mar 2021
@author: thomasgumbricht
'''
import os
from sys import exit
import numpy as np
import gc
#from numpy import pi, log, tan, empty, float32, arctan, rad2deg, gradient
from scipy.ndimage import gaussian_gradient_magnitude
from math import sqrt
from geoimagine.gis import RasterOpenGetFirs... |
# -*- coding: utf-8 -*-
"""
Muse LSL Example Auxiliary Tools
These functions perform the lower-level operations involved in buffering,
epoching, and transforming EEG data into frequency bands
@author: Cassani
"""
import numpy as np
from scipy.signal import butter, lfilter, lfilter_zi
NOTCH_B, NOTCH_A = butter(4, np.a... |
import numpy as np
from math import log,e
import hankelmatrixcreator
import sppy
from sppy import linalg
import sys
import time
import iohelpers
import math
from scipy import sparse
import copy
VERBOSE = True
class SparseSpectralWFA:
def __init__(self, n_symbols, prefixdict, suffixdict, basis_length, maxDim=80):... |
<reponame>b7500af1/orbcomm_decoder
##############################################################################
#
# Author: <NAME>
# Date: 17 April 2019
# Name: timing_detection_demo.py
# Description:
# This is a demo of transmitting and receiving qpsk samples. It uses a RRC
# pulse shaping filter and matched filte... |
<filename>tests/pyposmat/engines/PyposmatMonteCarloSampler/test__PyposmatMonteCarloSampler__eam_Ni/dev__PyposmatMonteCarloSampler__eam_Ni.py<gh_stars>1-10
import copy,yaml
from collections import OrderedDict
from pypospack.pyposmat import PyposmatMonteCarloSampler
from pypospack.pyposmat import PyposmatDataFile
from py... |
<gh_stars>0
import numpy as np
import matplotlib.pyplot as plt
import os
from scipy.interpolate import make_interp_spline, BSpline
def comparison_plots(shape="medium", bkgd="1.0e+02", label="medium"):
# PAPER PLOT- Medium case, 5% signal uncertainty and 0% uncertainty
fig = plt.figure()
fig.patch.set_facec... |
<reponame>European-XFEL/euxfel-python
"""AGIPD & LPD geometry handling."""
from cfelpyutils.crystfel_utils import load_crystfel_geometry
from copy import copy
import h5py
from itertools import product
import numpy as np
from scipy.ndimage import affine_transform
import warnings
from .crystfel_fmt import write_crystfel... |
<filename>tde1.py
#coding:utf-8
# (概要）
# チャイム音(chime_wav)をマイクでステレオ録音しとき、L channelとR channelの音の時間差を推定するもの。
#
# (方法）
# 調波構造の majorな部分を抜きとって、再合成して ２つの信号を比較し、時間差を求める。
#
# Check version
# Python 3.6.4, 64bit on Win32 (Windows 10)
# numpy 1.18.4
# scipy 1.4.1
# matplotlib 3.3.1
import sys
import os
... |
import numpy as np
import ctypes
from scipy.optimize import minimize, check_grad, approx_fprime
from scipy.sparse import coo_matrix, csr_matrix, csc_matrix
import test_math
m = int(1e1)
n = int(2e1)
p = int(3e1)
q = int(1e2)
nzX = int(.25*m*n)
nzU = int(.25*m*p)
nzI = int(.25*n*q)
lam = 6e-1
w_user = 0.1234
w_item = ... |
from taylorDiagram import plot_Taylor_graph
import matplotlib.pyplot as plt
from PyEMD import EEMD
from hht import hht
from hht import plot_imfs
from hht import plot_frequency
import waipy
from scipy.stats import norm
import numpy as np
# from matplotlib.ticker import FuncFormatter
def millions(x, pos):
'The two a... |
<gh_stars>1-10
import numpy as np
from numpy import sin, cos, pi
import matplotlib.pyplot as plt
from scipy.spatial import Delaunay
import scipy
import fem
import scipy as sp
import pygmsh
import time
from scipy.spatial import ConvexHull, convex_hull_plot_2d
import random
import torch as T
import torch_geom... |
# -*- coding: utf-8 -*-
"""Main Controller"""
from tg import expose, flash, require, url, lurl
from tg import request, redirect, tmpl_context
from tg.i18n import ugettext as _, lazy_ugettext as l_
from tg.exceptions import HTTPFound
from icrar.model import DBSession
from icrar.config.parameters import TELESCOPES, DEF... |
<gh_stars>1-10
import torch
from torch.utils.data import Dataset, DataLoader
from pathlib import Path
from scipy.io import loadmat
import copy
import mri_utils
from fft_utils import numpy_2_complex
import numpy as np
DEFAULT_OPTS = {'root_dir':'data/knee',
'name':'coronal_pd',
'patients':[1,2,3,4,5,6... |
<gh_stars>0
import statistics
from communication.comm import LoxComm
from api import sync_api_list, discover_api_fns
from firmware_analyzer import unpacker, binary_analyzer
from config_analyzer.loxcc_parser import uncompress_loxcc # , decompress_loxcc
import argparse
import pathlib
async def echo(websocket, path):
... |
import cv2
import os
import numpy as np
#import scipy as scp
import scipy.misc
import triangle_detection as triang
import psycopg2
maindir = "E:\\Pesquisa\\codigos\\KittiSeg_shivam\\KittiSeg\\RUNS\\retrain_SVM_balanced_novo_2\\results\\"
#or_imgs_dir = "C... |
from __future__ import division
import matplotlib
from __builtin__ import dict
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import os
import logging
import numpy as np
from sklearn.metrics import roc_curve, auc, f1_score, confusion_matrix, classification_report
import datetime
from scipy import integrate
impor... |
<gh_stars>0
import sys, getopt, os
from scipy.stats import poisson
usage = """
Usage:
This script takes in the paired-end table containing the stats from the EpitopeID pipeine and calculates
the Poisson p-value threshold given a minimum 2-fold enrichment over the expected tags based on the bin size.
Example: python2 ... |
<reponame>anton-petrov/centerline<filename>src/centerline/geometry.py
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
import os
import pickle
from numpy import array
from scipy.spatial import Voronoi
from shapely.geometry import LineString, MultiLineString, MultiPolygon, Polygon
from shapely.ops impor... |
<reponame>QNZhang/LC-KSVD
# -*- coding: utf-8 -*-
""" main """
import numpy as np
from scipy.io import loadmat
from sklearn.metrics import accuracy_score
from lcksvd.dksvd import DKSVD
def main():
###########################################################################
# ... |
<gh_stars>0
import pandas as pd
import numpy as np
import csv
import os
from PIL import Image
import imagehash
import matplotlib.pyplot as plot
import librosa
from pydub import AudioSegment
from tempfile import mktemp
import librosa.display
import numpy as np
import os
import pylab
import pandas as pd
import numpy as ... |
<filename>limix_cl/tests/test_limix_lmm.py
# -*- coding: utf-8 -*-
import sys
import os
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__),
'..')))
import limix_lmm
import numpy as np
import scipy as sp
import pandas as pd
import unittest
class BasicTestSuite(unittest.TestCase):
"""Te... |
from __future__ import division
import os
import numpy as np
#from scipy.ndimage import imread
from imageio import imread
import scipy.io as sio
import torch
import torch.utils.data as data
from datasets import pms_transforms
from . import util
np.random.seed(0)
class MyDataset(data.Dataset):
def __init__(self, a... |
<reponame>cgodine/RadTraQ<filename>radtraq/plotting/corner_reflector.py
import numpy as np
import matplotlib.pyplot as plt
from scipy.interpolate import griddata
import pandas as pd
def plot_cr_raster(obj, field='reflectivity', target_range=None, ax=None, fig=None,
delta_x=None, delta_y=None, az_li... |
<filename>aced_hmm/visualize_forecasts.py
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import json
import scipy
from scipy import stats
import seaborn as sns
import argparse
sns.set_style("whitegrid")
def plot_stat(stats_filepath, stat, last_N_not_nan=None):
stats = pd.read_csv(stats_fil... |
<reponame>zhampel/gaussGAN
from __future__ import print_function
try:
import argparse
import os
import numpy as np
import matplotlib
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib import cm as cm
from scipy import stats
import pickle
import torch
... |
<filename>resource_provisioning/calc.py
import numpy as np
from config import *
import gurobipy
from scipy.optimize import minimize, LinearConstraint
from util import *
from torch.optim import SGD
from torch.autograd import Variable
import gurobipy as gp
from gurobipy import GRB
import torch.nn as nn
import cvxpy as cp... |
# Use the OpenMDAO framework for OUU for optimizing a Rosenbrock function
from __future__ import division, print_function
import os
import sys
import errno
sys.path.insert(0, '../../src')
# pyStatReduce specific imports
import numpy as np
import chaospy as cp
from stochastic_collocation import StochasticCollocation
fr... |
<filename>PrescribedAreaDrawing.py
#Best you use Anaconda. If you do not have quadprog, you have to
#install it.. in anaconda you can use this '-c omnia quadprog '
import numpy as np
import random
#import quadprog
from sympy.geometry import *
from PIL import Image, ImageDraw
import matplotlib.pyplot as plt
import matpl... |
import matplotlib.pyplot as plt
import numpy as np
from scipy.ndimage import gaussian_filter
import scipy.stats as st
def whist(x, smooth=True, kde_n=512, kde_range=None, bins='auto', plot=None,
kde_kwargs=None, hist_kwargs=None, **kwargs):
"""
Turn an array of samples, x, into an estimate of pro... |
<filename>phase4_analysis/metrics.py
# <NAME> (<EMAIL>)
import numpy as np
import scipy.stats as ss
#from diagnostics import MIN_ESS
MIN_ESS_PER_CHAIN = 1.0 # TODO limit dupes
def stack_first(X):
assert(X.ndim == 3)
# Equivalent to:
# Y = np.concatenate([X[ii, :, :] for ii in xrange(X.shape[0])], axis=0... |
<filename>Assignment1/1.2/plot.py<gh_stars>1-10
import os
import matplotlib.pyplot as plt
import numpy as np
import statistics
with open('data.txt') as f:
lines = f.readlines()
z = [line.split()[0] for line in lines]
rows, cols = (24, 5)
data_set = [[0 for i in range(cols)] for j in range(rows)]
for i in ra... |
<filename>examples/applications/intent_recognition.py
"""
This is a simple application for sentence embeddings: semantic search
We have a corpus with various sentences. Then, for a given query sentence,
we want to find the most similar sentence in this corpus.
This script outputs for various queries the top 5 most si... |
import pandas as pd
import numpy as np
import scipy.stats as stats
def compute_indep_ci(df, loc=0.95):
mean_list, std_list, ci_list = [], [], []
for col_name in df:
col_values = df[col_name].values
sample_size = len(col_values)
degrees_freedom = sample_size - 1
sample_mean = np... |
# first version of two way lattice for getting more densities
import numpy as np
import numpy.random as rd
import random as random
import scipy
import matplotlib as mpl
import matplotlib.pyplot as plt
from os import path
from datetime import datetime
now = datetime.now()
#parameters
N = 100 # number of sites
a1 = ... |
<gh_stars>10-100
# -*- coding: utf-8 -*-
"""
Created on Thu Aug 20 08:22:45 2020
This class fits multivariate ARMA-GARCH type models
@author: iankh
"""
import pandas as pd
import numpy as np
from .errors import InputError, HessianError
import datetime
import scipy
import shutil
class multiModel(object):
def __i... |
import scipy as sc
import more_itertools as mit
length = 4 # Длина теплообменника [м]
time = 300 # Время работы теплообменника [с]
rball = 0.01 # Радиус однгого шара засыпки [м]
rbckfill = 2 # Радиус засыпки [м]
f... |
import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
import pandas as pd
from scipy.stats.distributions import t
# Import PySwarms
import pyswarms as ps
from pyswarms.utils.functions import single_obj as fx
def exp_func(x, a, b, c):
return c + a * np.exp(b * x)
... |
"""Multiple MC to show how it can be bad."""
from scipy.stats import qmc
from scipy.stats._qmc import check_random_state
import numpy as np
import matplotlib.pyplot as plt
rng = np.random.default_rng(12345)
n_sample = 256
dim = 2
sample = {}
# MC
sample['MC 1'] = rng.random((n_sample, dim))
sample["MC 2"] = rng.r... |
<gh_stars>1-10
import tensorflow as tf
import numpy as np
import scipy.io.wavfile
import scipy.io
import scoping
BATCH_AXIS = 0 # B
LENGTH_AXIS = 1 # L
DEPTH_AXIS = 2 # D
CHANNELS_AXIS = -1 # C
def sliding_window(inp, frame_length, frame_shift, max_number_frames=None, padding="VALID", name=None):
'''
... |
<gh_stars>10-100
from scipy.io import loadmat
import matplotlib.pyplot as plt
from hsi_toolkit.signature_detectors import *
from hsi_toolkit.util import get_RGB
"""
Demo script that runs all signature detectors in hsi_toolkit_py
Inputs:
hsi_sub - n_row x n_col x n_band hyperspectral image
tgt_spectra - n_band x 1 t... |
# -*- coding:utf-8 -*-
"""File I/O related operations, such as list files, import/export or remove files/folder."""
__author__ = "<NAME>"
import os
import shutil
import json
import pickle
import zipfile
import urllib
import wget
DependencyFlag = False #Check if dependencies are satisfied. If not, some... |
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