text string |
|---|
<gh_stars>0
#!/usr/bin/env python
# coding: utf-8
# In[1]:
import os, sys
import pandas as pd
import numpy as np
import numpy.matlib
import scipy as sp
import geopandas as gpd
# Plotting
import matplotlib.pyplot as plt
import seaborn as sns
# In[2]:
from IPython.display import clear_output
# In[3]:
def upd... |
<reponame>coganlab/IEEG_preprocessing<filename>Python/audio_stitch.py
from bids import BIDSLayout
from scipy.io import wavfile
import os
def get_audio(my_layout: BIDSLayout, sub_id, run) -> list:
events = my_layout.get(subject=sub_id, run=run, suffix="events",
extension=".tsv")[0].get_d... |
import numpy as np
import os
from vtk import vtkImageData, vtkXMLImageDataReader, vtkXMLImageDataWriter
from vtk.util import numpy_support as vn
from scipy.spatial.transform import Rotation as R
from scipy.interpolate import interpn
from warnings import simplefilter
simplefilter(action='ignore', category=Fut... |
# Import Usefull libraries
import sys
import re
import numpy as np
import torch
import argparse
from os import path, system, chdir
from load_csv import load_csv
from text import text_to_sequence
from text.symbols import symbols
from model import Tacotron2, to_gpu
code_PAR=text_to_sequence('§',['basic_cleaners'])[0] #... |
<gh_stars>1-10
#http://scikit-learn.org/0.11/auto_examples/cluster/plot_dbscan.html
print __doc__
import numpy as np
from scipy.spatial import distance
from sklearn.cluster import DBSCAN
from sklearn import metrics
from sklearn.datasets.samples_generator import make_blobs
############################################... |
<gh_stars>1-10
import os
import argparse
import numpy as np
import pathlib
from track import Track
import pickle
from scipy.misc import imread
def sample_tracks(dets_, tracks, sample_interval, track_idx_offset):
"""Sample tracks at specific interval"""
# build a track_id to track_idx dict
id2idx = {t.id:i+... |
<gh_stars>10-100
#!/usr/bin/env python
import os
import sys
import re
import csv
import argparse
import math
from collections import Counter
#-------------------------------------------------------------------------------
# complex imports
#----------------------------------------------------------------------------... |
<reponame>labolas89/koheron-sdk
import visa
import os
import numpy as np
import time
import matplotlib.pyplot as plt
from scipy import stats
from fft import FFT, Window
from koheron import connect
# Both the Koheron Alpha and the Keysight 33600A must be
# disciplined on the Tektronix MCA3027 OCXO 10 MHz output.
clas... |
# coding: utf-8
# created by deng on 7/30/2018
import numpy as np
import scipy as sp
import term_weighting_model.calc_weightings as cw
from utils.data_util import load_to_df
from utils.path_util import from_project_root
from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer
from sklearn.externa... |
<filename>src/feature/demographics_content.py
import numpy as np
import scipy.sparse as sps
import pandas as pd
from src.data_management.data_getter import get_warmer_UCM
from src.feature.clustering_utils import cluster_data
def get_sub_class_content(ICM_subclass, original_feature_to_id_mapper, binned=True):
"""... |
"""
EXAMPLE FOR CAT 9, maximizing ndcg with norm_max_row, :
python generic_bayesian.py 8 ndcg l1 quni
"""
import sys
import time
import json, os
from skopt import gp_minimize
from skopt.space import Real
from utils.post_processing import eurm_to_recommendation_list,eurm_remove_seed
from utils.pre_processing import... |
<filename>lttnganalyses/cli/io.py
# The MIT License (MIT)
#
# Copyright (C) 2015 - <NAME> <<EMAIL>>
# 2015 - <NAME> <<EMAIL>>
# 2015 - <NAME> <<EMAIL>>
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the ... |
<filename>kaggle-lung-cancer-approach1/modules/lungprepare.py
import numpy as np
from modules.utils import Timer
from modules.logging import logger
import modules.utils as utils
import os
import dicom
import scipy.ndimage
import matplotlib.pyplot as plt
import matplotlib.patches as patches
import scipy.ndimage as ndima... |
<reponame>Thamik/lossy-stern-sig
'''
Created on Jan 24, 2018
@author: <NAME>, Technische Universiteit Eindhoven, <EMAIL>
'''
# imports
from math import log, floor, ceil
from scipy.optimize import minimize
import numpy as np
# binomial coefficient (source: wikipedia)
def binom(n, k):
if k < 0 or k > n:
... |
# -*- coding: utf-8 -*-
"""Extract the soi from low field measurements.
The density and mobility are extracted at the same time.
"""
# =============================================================================
# --- Parameters --------------------------------------------------------------
# ======================... |
<filename>model_raisim/Dribble_Control/DRMpc_Arm/ForTra_Verify.py
import numpy as np
import matplotlib.pyplot as plt
from scipy.integrate import odeint, solve_bvp, solve_ivp
from scipy import optimize
x_ref = -0.1
x_reb = -0.47
# f1 = 25
# f2 = 150
# k_vir = 560
k_con = 100000
g = 10
m = 0.5
class DefFun(object):
... |
import argparse
import os
import matplotlib.pyplot as plt
from matplotlib.pyplot import imshow
import scipy.io
import scipy.misc
import numpy as np
import pandas as pd
import PIL
import tensorflow.compat.v1 as tf
tf.disable_v2_behavior()
from keras import backend as K
from keras.layers import Input, Lambda, Conv2D
from... |
import numpy as np
import scipy as sp
import scipy.constants
import cPickle
import radarmodel
msl = np.array([-1, -1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, 1, -1, -1, -1, 1, 1, -1, -1, 1, -1, -1, -1, 1, -1, -1, 1, -1, 1, -1, 1, -1, -1, 1, -1, -1, 1, -1, -1, 1, -1, 1, 1]).astype(np.float_)
m = 128... |
<reponame>databyjp/asset_correlation_analysis<gh_stars>1-10
# ========== (c) <NAME> 16/3/21 ==========
import logging
import pandas as pd
import numpy as np
import requests
import json
import os
import utils
import plotly.express as px
import scipy.stats
logger = logging.getLogger(__name__)
desired_width = 320
pd.s... |
import numpy as np
import matplotlib.pyplot as plt
import scipy
n = 365*5
t = np.linspace(0, n, n)
x = 3 * np.sin(2*t*2*np.pi/365)
# x = np.array([1, 1, 1, 1])
n = len(x)
# w = np.exp(complex(0, -2*np.pi/n))
# # f = 2*np.pi/np.linspace(1/n, 1, n)
# M = np.ndarray([n, n], dtype=complex)
# for j in range(n):
# for ... |
from rdkit import DataStructs
from scipy.spatial.distance import *
import rdkit.Chem as Chem
import numpy as np
from .normalize import *
from tqdm import tqdm
def prior_unc(fps_train,
fps_test,
fp_fun=None,
dis_fun=lambda x, y: euclidean(x, y),
sc_fun=lambda dis... |
# -------------------------------------------------------------------------------------
# Library
import logging
import numpy as np
from scipy.interpolate import griddata
# -------------------------------------------------------------------------------------
# ---------------------------------------------------------... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Written by <NAME> and CBIG under MIT license:
https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
"""
import os
import sys
import glob
import random
import shutil
import numpy as np
import pandas as pd
import scipy.io as sio
sys.path.append("..")
sys.path.app... |
import numpy as np
def spectral(im: np.ndarray, fm: int):
from scipy import fftpack
#Spectral Filter
axis = len(np.shape(im))
dim = np.shape(im)[0]
form = np.shape(im)
half = np.zeros(len(form))
im_fft = fftpack.fftn(im)
im_fft = np.fft.fftshift(im_fft)
half[0] = int... |
<gh_stars>0
#Ce fichier contient toute les fonctions nécéssaire pour la caméra
from cmath import inf
import cv2 as cv
import numpy as np
import RPi.GPIO as GPIO
import time
LED = 11
# Une classe qui permet de stocker les informations des zones souillées.
class Zone :
# Une méthode utilisée pour créer ... |
<reponame>marc-h-lambert/L-RVGA<filename>KalmanMachine/KUtils.py<gh_stars>0
###################################################################################
# THE KALMAN MACHINE LIBRARY #
# Code supported by <NAME> ... |
import classifier
import features
import sound
import numpy as np
import pylab as pl
import scipy.signal
class TimeSpan(object):
def __init__(self, start_time=None, end_time=None, duration=None):
if start_time==None:
raise ValueError("start_time must be provided")
self.start_time=flo... |
<filename>volumetricspy/volumetrics.py
import numpy as np
import matplotlib.pyplot as plt
import pyvista as pv
import pandas as pd
from skimage import measure
from scipy.integrate import simps
from scipy.interpolate import griddata
import geopandas as gpd
from shapely.geometry import MultiPolygon, Polygon
from zmapio i... |
<filename>contact/contact.py
import os
import sys
import pickle
import numpy as np
from scipy.spatial.distance import pdist, squareform
from typing import List, Tuple
import torch
from sklearn.linear_model import Lasso, ElasticNet, LogisticRegression
import logging
import argparse
from joblib import Parallel, delayed
... |
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D, proj3d
from scipy.stats import multivariate_normal
from matplotlib.patches import FancyArrowPatch
class Arrow3D(FancyArrowPatch):
def __init__(self, xs, ys, zs, *args, **kwargs):
FancyArrowPatch.__init__(self, (0,0... |
# https://stackoverflow.com/questions/49306092/parsing-a-symbolic-expression-that-includes-user-defined-functions-in-sympy
"""
The logical flow of the class follows the paper by Wilson 2020.
-produce heterogeneous terms for g for arbirary dx
-substitute dx with g=g0 + psi*g1 + psi^2*g2+...
-produce het. terms for irc
... |
import glob
import cv2
import matplotlib.image as mpimg
import matplotlib.pyplot as plt
import numpy as np
import pickle
from skimage.feature import hog
from scipy.ndimage.measurements import label
from collections import deque
from moviepy.editor import VideoFileClip
def get_hog_features(img, orient, pix_per_cell, c... |
<gh_stars>1-10
from statistics import median
from typing import Any, Callable, Dict, Optional
import pandas as pd
import plotly.graph_objects as go
from hyperstyle.src.python.review.inspectors.issue import IssueType
from analysis.src.python.evaluation.inspectors.common.statistics import IssuesStatistics, PenaltyInflue... |
<reponame>roinaveiro/poisoning_hmms<filename>attackers/decoding_attacker.py
import numpy as np
from hmm_utils import HMM
from params import *
from itertools import product
from scipy.special import softmax
class dec_attacker():
def __init__(self, prior_m, transition_m, emission_m, rho_probs,
X, w1, w2, ... |
<filename>PropensityScoreMatching/__init__.py
# -*- coding: utf-8 -*-
"""
Created on Mon May 18 15:09:03 2015
@author: Alexander
"""
from statsmodels.api import families
from statsmodels.api import GLM
from statsmodels.tools.tools import add_constant
from statsmodels.stats.weightstats import ttest_ind
import pandas a... |
<filename>sympy/mpmath/tests/elliptic_torture_tests.py
#!/usr/bin/env python
"""
Tests of the elliptic functions module. If all unittests are run
at 100 digit precision, it takes ~ 12 m on a Athlon 64 X2 3800+.
Author: <NAME>
References:
[1] Abramowitz & Stegun. 'Handbook of Mathematical Functio... |
# <NAME>
import argparse, sys, os
import numpy as np
import pylab as plt
from glob import glob
from spectral.io import envi
from scipy.stats import norm
from scipy.linalg import solve, inv
from astropy import modeling
from numba import jit
def find_header(infile):
if os.path.exists(infile+'.hdr'):
return infile... |
"""Gauss-Jordan assistant
Enabling user-driven live demonstration of the Gauss-Jordan algorithm
in a terminal/console.
Source: https://github.com/aroberge/gauss-jordan-assistant
Requires Python 3.8+ and Rich (https://github.com/willmcgugan/rich)
All the content is in this single file, for those that do not want
to ... |
<reponame>porya-gohary/real-time-task-generators<filename>lib/generator_WATERS_fixedsum.py
#!/usr/bin/env python3
"""Task set generation with WATERS benchmark.
From the paper: 'Real world automotive benchmark for free' (WATERS 2015).
some part adapted from https://github.com/tu-dortmund-ls12-rt/end-to-end
"""
from scip... |
"""
Synth800K for Text Detection
"""
import os
import cv2
import json
import torch
import random
import numpy as np
from PIL import Image
from scipy.io import loadmat
from torch.utils.data import Dataset
from torchvision.transforms import transforms
from datasets.utils import normalize_image, get_im_scale
CLASSES = ... |
<filename>archived/columbia_aerialplot-example.py
# Columbia retreat 1957-2007, viewed from above, contour plot by colour
# Jun/Nov 2016 EHU
#from numpy import *
from netCDF4 import Dataset
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
from mpl_toolkits.axes_grid1 import make_axes_locat... |
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you m... |
from __future__ import print_function
import matplotlib.pyplot as plt
import numpy as np
from scipy import interpolate
x_raw = np.linspace(0, 2*np.pi, 10)
y_raw = np.sin(x_raw**(2/3))
linear = interpolate.interp1d(x_raw, y_raw) # linear interpolation
cubic = interpolate.interp1d(x_raw, y_raw, kind='cubic') # cubic ... |
__author__ = 'DGriffith'
# Functions related to interpolation of xarray.DataArray and other utilities
# Some sort of global data dictionary (CF compliant ?), including short names and synonyms
# Could import some or all CF definitions from XML file.
import numpy as np
import xarray
from scipy.interpolate import Regu... |
"""
Some methods which are useful but didn't quite fit into the graph classes.
"""
import logging
import numpy
import scipy.sparse
class GraphUtils(object):
def __init__(self):
pass
@staticmethod
def vertexLabelPairs(graph, edgeArray):
"""
Create an array of pairs of vertex la... |
import argparse
import numpy as np
from multiprocessing import Queue, JoinableQueue, Process
from PIL import Image
from scipy.spatial.transform import Rotation as R
from tetrominoes import *
import os as os
import h5py as h5py
def init_episode_dict():
return {
'obs': [],
'action_matrix': [],
... |
<filename>NC_rBC_UHSAS_binned_data_to_txt_file-daily_averages.py
import sys
import os
import numpy as np
from pprint import pprint
from datetime import datetime
from datetime import timedelta
import mysql.connector
import math
import matplotlib.pyplot as plt
import matplotlib.colors
from matplotlib import dates
from mp... |
<filename>eventsearch/utils.py
import numpy as np
from scipy.stats import gaussian_kde
import scipy.signal as sig
from scipy.spatial import distance
from scipy.optimize import linear_sum_assignment
def kernel_helper(window_len=11, window='hann', **kwargs):
"""
Helper function to call kernel from st... |
"""
Make a movie out of a shotgun VAE projection and an audio file.
Reduce speed by 50%:
::
ffmpeg -i out.mp4 -filter_complex "[0:v]setpts=PTS/0.5[v];[0:a]atempo=0.5[a]" -map "[v]" -map "[a]" -strict -2 out.mp4
TO DO
-----
* Check whether ffmpeg is installed.
"""
__date__ = "November 2019 - November 2020"
import... |
import pickle
import math
import os
from scipy.io.wavfile import write
with open('music_genres_dataset.pkl', 'rb') as f:
data = pickle.load(f)
for idx, segment in enumerate(data['data']):
track = int(math.floor(idx/15))
part = idx % 15
if not os.path.exists('tracks/{}'.format(track)):
... |
<gh_stars>0
import numpy as np
import matplotlib.pyplot as plt
import scipy.optimize
# volume_list_low = [4.0, 3.5, 3.0, 2.5, 2.0, 1.9, 1.8, 1.7, 1.6, 1.5, 1.4, 1.3, 1.2, 1.1, 1.0, 0.9, 0.8, 0.7, 0.6]
# volume_list = [4.0, 3.5, 3.0, 2.5, 2.0, 1.9, 1.8, 1.7, 1.6, 1.5, 1.4, 1.3, 1.2, 1.1, 1.0, 0.9, 0.8, 0.7]
# 21 degre... |
<gh_stars>0
#important URLs:
#http://192.168.1.113:8000/stream.mjpg
#http://192.168.1.113:8000/prev_view.html
#http://192.168.1.113:8000/next_view.html
#http://192.168.1.113:8000/brighter.html
#http://192.168.1.113:8000/dimmer.html
# in virtual env, python qr.py
# on browser, http://192.168.1.100:8000
# Overview
# Re... |
import numpy as np
import math
from scipy.spatial.distance import cityblock
import matplotlib.pyplot as plt
from re import split
# sample finishing time based on statistics
def sample_FT(f_t_model, fast_m, fast_s, medium_m, medium_s, slow_m, slow_s):
sample_ft=np.zeros(len(f_t_model))
for i, model in enumerat... |
<gh_stars>0
"""
<NAME> & <NAME>
2022-01-10, v1.0
! Make sure to cite the paper below if you use "ApThermo" in your research:
Li and Costa (2020, GCA) https://doi.org/10.1016/j.gca.2019.10.035
"""
import scipy.optimize
import math, numpy as np, pandas as pd
MassCl = 35.45 # Molar mass of Cl
MassF = 18.998 ... |
"""
one_mode is an example file which seeks to verify the new Hamiltonian algorithm and update sequence
as derived by Dan and Stephen. It will ignore much of the class structure applied to OLIVE in an
attempt to provide a simple example of the algorithm. Once verified, it will be implemented within
OLIVE using the ap... |
<gh_stars>1-10
"""Tracks PV modules over subsequent video frames.
This module performs multiple-object tracking of segmentation masks of PV
modules in subsequent IR video frames. The aim is to identify the same physical
PC module in subsequent frames and assign a unique tracking ID to it. This
allows to group ima... |
import os
import math
import random
import operator
from functools import reduce
import numpy as np
from sklearn.metrics import f1_score
from tqdm import tqdm
from nltk.util import everygrams
from scipy.stats import pearsonr
import torch
import torch.nn as nn
import torch.nn.functional as F
from pytorch_pretrained_be... |
<reponame>dpopadic/arpmRes
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# ---
# jupyter:
# jupytext:
# text_representation:
# extension: .py
# format_name: light
# format_version: '1.4'
# jupytext_version: 1.1.4
# kernelspec:
# display_name: Python 3
# language: python
# na... |
<reponame>tmaiwald/OSIM
import numpy as np
from numba import jit
from scipy.sparse.linalg import spsolve
import scipy as np
import numpy
from OSIM.Modeling.CircuitSystemEquations import CircuitSystemEquations
from OSIM.Modeling.Components.Port import Port
from OSIM.Modeling.Components.VoltageSource import VoltageSource... |
import os
import sys
import time
import datetime
import argparse
import re
from pathlib import Path
from tqdm import tqdm
from copy import deepcopy, copy
import traceback
import json
import warnings
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib_venn import venn2
from mpl_toolk... |
import scipy.io as io
import numpy as np
import scipy.ndimage as nd
import os,random
import tensorflow as tf
import sys
import argparse,sys
def shuffle(names,max_epoch): # 我自己加的，因为后续程序会使每张图片的出现次数不一样！！！
Names = names
retu = []
for i in range(max_epoch):
random.shuffle(Names)
retu += Names
... |
#!/usr/bin/env python
### Written by <NAME> @ AG Klebe Marburg University
### Please contact via <EMAIL>
### Numerical libraries
import numpy as np
from scipy import spatial as spatial_scipy
### Use field classes abd grid_water
from io_operations import load_dx, write_files
### Other
import sys
import time
if len(... |
<reponame>LBJ-Wade/GALLUMI_public
import numpy as np
from matplotlib import pyplot as plt
import glob
from matplotlib import patches as mpatches
import scipy.ndimage
plt.style.use("../template.mplstyle")
# purple - green - darkgoldenrod - blue - red
colors = ['purple', '#306B37', 'darkgoldenrod', '#3F7BB6', '#BF4145']... |
"""
*Calculates plots for SIx from historical LENS*
"""
import numpy as np
from netCDF4 import Dataset
import matplotlib.pyplot as plt
import scipy.stats as sts
from mpl_toolkits.basemap import Basemap
directory = '/volumes/eas-shared/ault/ecrl/spring-indices/data/'
def SIxHistorical():
"""
Reads in historic... |
import pdb
import os
import pandas as pd
import dymos as dm
import numpy as np
import datetime as dt
from typing import Union
import openmdao.api as om
from pyNA.src.settings import Settings
from pyNA.src.aircraft import Aircraft
from pyNA.src.trajectory_src.atmosphere import Atmosphere
from pyNA.src.engine import Engi... |
#!/usr/bin/env python
"""Generate Input files
Author: {0} ({1})
This module is part of CADEE, the framework for
Computer-Aided Directed Evolution of Enzymes.
"""
from __future__ import print_function
from random import randint
from fractions import gcd
import logging
import os
import sys
from tools import get_... |
<gh_stars>1-10
import numpy as np
# from numba import jit
import progressbar as pb
import scipy as sp
import sys
# bayesian matting ------------------------------------------------------------
# @jit
def bayesian(im, tm, dvar=.4, lws=60, overlap=1.0/3, npmin=400):
# This uses a maximum-likelihood (Bayesian) approa... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# author: Yizhong
# created_at: 10/26/2016 下午8:36
import argparse
import gzip
import pickle
import scipy
from data_helper import DataHelper
from eval.evaluation import Evaluator
from models.classifiers import ActionClassifier, RelationClassifier
from models.parser import ... |
<reponame>amirhertz/shadowpix<gh_stars>1-10
from PIL import Image
import cv2
import numpy as np
import matplotlib.pyplot as plt
from scipy.ndimage.filters import convolve
import os
GRADIENT_KERNEL = np.array([[-1, -1, -1],
[-1, 8, -1],
[-1, -1, -1]])
x = cv2.getG... |
# -*- coding: utf-8 -*-
"""
Generates primary figures for HCP results
"""
from pathlib import Path
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from scipy import ndimage
import seaborn as sns
from parspin.partitions import NET_OPTIONS, YEO_CODES
from parspin.plotting import savefig
from par... |
""" This module
"""
import numpy, math
from numpy import log10 as log10
from numpy import pi as pi
from scipy.interpolate import UnivariateSpline as interpolate
from scipy.optimize import curve_fit as cf
from s... |
<filename>k210_code/gen_ary.py
import numpy as np
from scipy.special import expit
with open('/home/zqh/Documents/kendryte-standalone-sdk/src/k210_face/act_ary.h', 'w') as f:
f.write('#ifndef _ACTARY_H_ \n\
# define _ACTARY_H_ \n\
# include <stdint.h> \n\
float sigmoid[] = {')
for i in range(256):
f.wr... |
""" Module for calculating pseudoinverses. """
from sympy import *
class Calculator:
@staticmethod
def load_matrix(m, n):
"""
Returns the matrix which user gives as input or None if the input is incorrect.
"""
matrix = []
for i in range(m):
matrix.append(in... |
<gh_stars>0
import sys
import os
import gc
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import ticker
import scipy.sparse.linalg as spLA
import majoranaJJ.modules.plots as plots #plotting functions
import majoranaJJ.modules.finders as fndrs
import majoranaJJ.modules.SNRG as SNRG
import majoranaJ... |
<reponame>svz71195/XRBs
import numpy as np
from scipy.special import gammaincc, gamma
from numba import njit
class Integrate:
@staticmethod
def Riemann(func: np.ufunc, lim_l: float, lim_u: float, n: int, *arg: tuple) -> float:
eval = np.linspace(lim_l,lim_u,n+1)
delta = np.diff(eval)
... |
<filename>data/data_util.py
import scipy.fftpack as fftpack
import librosa
import pyworld as pw
import numpy as np
import os
import soundfile as sf
import fnmatch
import matplotlib.pyplot as plt
import pysptk
from librosa.display import specshow
import copy
gamma = 0
mcepInput = 3 # 0 for dB, 3 for magnitude
alpha =... |
<reponame>ajeddeloh/ray-optics
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright © 2016 <NAME>
""" converting a spectrum to a colour
code from the web blog:
https://scipython.com/blog/converting-a-spectrum-to-a-colour/
@author: <NAME>
"""
import numpy as np
from scipy.constants import h, c, k
from rayop... |
<reponame>Jael24/TB_ElasticStack<filename>images/python_analysis/src/venv/lib/python3.7/site-packages/mlxtend/classifier/stacking_classification.py
# Stacking classifier
# <NAME> 2014-2020
# mlxtend Machine Learning Library Extensions
#
# An ensemble-learning meta-classifier for stacking
# Author: <NAME> <<EMAIL>>
#
#... |
#!/usr/bin/env python
import os
import multiprocessing as mp
import sys
import numpy as np
from scipy import linalg
from saf.action.solve import solve
from saf.euler1d.linear.config import Config
from saf.euler1d.linear.asciireader import ASCIIReader
E_ACT = 50.0
T_FINAL = 20
def _run_solver(args):
q, n12 = ... |
<reponame>v1259397/cosmic-gnuradio
#!/usr/bin/env python
#
# Copyright 2011-2013 Free Software Foundation, Inc.
#
# This file is part of GNU Radio
#
# GNU Radio is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; ... |
<reponame>MilesCranmer/bnn_chaos_model
"""This file takes a model at its minima, and models the Gaussian at the posterior mode"""
import sys
import seaborn as sns
sns.set_style('darkgrid')
from matplotlib import pyplot as plt
import spock_reg_model
spock_reg_model.HACK_MODEL = True
from pytorch_lightning import Trainer... |
"""
Ledalab analysis functions (original folder: Ledalab/analyze)
"""
from __future__ import division
import numpy as np
from numpy import array as npa
import math
from scipy import stats
from scipy.signal import convolve
from scipy import interpolate
from scipy.linalg import norm
from . import leda2
from . import util... |
<reponame>PascalSavage/procedural-cell-generation<filename>preprocess.py
import numpy as np
import cv2
import czifile
import pickle
import matplotlib.pyplot as plt
import scipy.misc
import os
SLICE_COUNT = 15
def extract_channel(channel_number, czi_image, file_name):
with open(file_name, 'wb+') as f:
pick... |
"""
"""
from .base_statistics import BaseStatistics
from ..base import Base, CLUSTER_NAME_COLUMN_LABEL, CLUSTERED_FILENAME_POSFIX
from ..plots.base_plot import BasePlot
import numpy as np
import os
import sys
import pandas as pd
import matplotlib.pyplot as plt
import scipy.cluster.hierarchy as shc
from sklearn.clust... |
<reponame>JoseChulani/PyFDTD
import numpy as np
import math
import scipy.constants
import time
import matplotlib.pyplot as plt
import matplotlib.animation as animation
# ==== Preamble ===============================================================
c0 = scipy.constants.speed_of_light
mu0 = scipy.constants.mu_0
eps0 ... |
# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
from co... |
<reponame>johnmgregoire/JCAPdatavis
import time, copy
import os, os.path
import sys
import numpy
from PyQt4.QtCore import *
from PyQt4.QtGui import *
from scipy import optimize
from echem_plate_ui import *
from echem_plate_math import *
import pickle
#p='C:/Users/Gregoire/Documents/CaltechWork/echemdrop/20120728NiFeCo... |
<reponame>rocksat/jsis3d
import os
import json
import h5py
import argparse
import numpy as np
import plyfile as ply
import scipy.stats as stats
from utils import block_merge
parser = argparse.ArgumentParser()
parser.add_argument('--logdir', help='path to the logging directory')
parser.add_argument('--visualize', act... |
import numpy as np
import nn_closed_loop.constraints as constraints
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.patches import Rectangle
from copy import deepcopy
import os
from nn_closed_loop.utils.utils import Hausdorff_dist_two_convex_hulls
from nn_closed_loop.utils.utils import is_hul... |
<reponame>e-pet/e-pet.github.io<filename>snippets/2018-04-04-interpolation.py
from scipy import interpolate
import numpy as np
import matplotlib.pyplot as plt
# Example 1: Impulse
x1 = np.arange(0, 7)
x1_dense = np.linspace(start=0, stop=6, num=1000)
y1 = np.array([0, 0, 0, 1, 0, 0, 0])
f_cubic_splines = interpolate.i... |
#!/usr/bin/env python
import argparse as ap
import cooler
import gc
import h5py
import numpy as np
import multiprocessing as mp
from krbalancing import *
from scipy.sparse import csr_matrix, triu, tril
from cooler import ice
from cooler.util import parse_cooler_uri
import logging
def cooler2csr(cooleruri):
'''
... |
import mne
import pandas as pd
import numpy as np
from scipy.signal import spectrogram
from sklearn.svm import LinearSVC, SVC
import matplotlib.pyplot as plt
import matplotlib
class ssvep:
def __init__(self, set_fontsize=True, fontsize=22):
"""
Parameters
----------
set_fontsize : b... |
<gh_stars>1-10
#!/usr/bin/env python
"""
Spherical Brain Mapping of 3D Brain Images.
3D brain imaging, such as MRI or PET produces a huge amount of data that is
currently analysed using uni or multivariate approaches.
The main aim of SBM is to provide a new framework that allows the mapping
of a 3D brain image to ... |
"""
-----------------------------------------------------------------------
Harmoni: a Novel Method for Eliminating Spurious Neuronal Interactions due to the Harmonic Components in Neuronal Data
<NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>
https://doi.org/10.1101/2021.10.06.463319
----------------------------... |
#☆𝒐𝒎𝒂𝒋𝒊𝒏𝒂𝒊☆#
import sys
import math
import cmath
import itertools
from functools import lru_cache
from collections import deque
sys.setrecursionlimit(10000000)
input=lambda : sys.stdin.readline().rstrip()
'''''✂'''''''''''''''''''''''''''''''''''''''''''''''''''''''''
n=int(input())
d=[]
for i in range(n):
... |
<gh_stars>10-100
'''
This package contains code for submodular maximization and
structured learning using stochastic gradient decent.
It allows to learn an objective function as a linear combination of simpler functions f, i.e.
.. math:: o(\mathbf{x_\mathcal{V}},\mathbf{y})=\mathbf{w^\mathrm{T}}\mathbf{f}(\mathbf{x_\m... |
<filename>compare_J_from_mat_file.py<gh_stars>0
import numpy as np
from scipy.stats import linregress
import matplotlib.pyplot as plt
import scipy.io as sio
import seaborn
import click
import sys
from sklearn.linear_model import Lasso
@click.command()
@click.option('--show_plot', type=click.BOOL,
defaul... |
"""Utilities for noise estimation."""
import numpy as np
from scipy.special import gammainc
def mmse_henriks(sigpspec, noise=None, alpha=.98, beta=.8, rule='wiener'):
"""Implement the MMSE method by Henriks et al for noise PSD estimation.
Hendriks, <NAME>., <NAME>, and <NAME>.
"MMSE based noise PSD track... |
"""
Simple shift-only and linear time-warping functions.
This is an alternative to `affinewarp` time warping.
Warning
-------
* `ava.preprocessing.warping` is experimental and may change in a future version
of AVA!
"""
__date__ = "September 2020 - November 2020"
import numpy as np
from scipy.interpolate import in... |
<filename>escriptcore/py_src/start.py<gh_stars>0
##############################################################################
#
# Copyright (c) 2003-2018 by The University of Queensland
# http://www.uq.edu.au
#
# Primary Business: Queensland, Australia
# Licensed under the Apache License, version 2.0
# http://www.ap... |
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