text string |
|---|
<reponame>forkunited/ltprg<gh_stars>10-100
#!/usr/bin/python
#
# Usage: plot.py [input_file] [xlabel] [ylabel] [x] [y] [where] [where_values] [groupby]
#
# input_file: Input tsv file where the first row contains column names
# xlabel: Label for plot horizontal axis
# ylabel: Label for plot vertical axis
# x: Name of co... |
<reponame>jfmalloy1/Patents
# import igraph as ig
# import numpy as np
import pickle
import pandas as pd
from tqdm import tqdm
import os
import heapq
import scipy.stats as stats
from random import sample
def build_cpd_df(fp):
""" Takes 29 separate compound data files and combines them into a single pandas datafra... |
<gh_stars>0
# -*- coding: utf-8 -*-
"""RED_linear_run1.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1-WN1MY9YYluGcnigLgrndqsxcOYldbB6
"""
#@title mount your Google Drive
#@markdown Your work will be stored in a folder called `cs285_f2021` by d... |
import numpy as np
from tqdm import tqdm
from scipy.sparse import csr_matrix, hstack, vstack
from sklearn.neighbors import NearestNeighbors
class MFKnn(object):
"""
Implementation of
"""
def __init__(self, metric, k):
self.k = k
self.metric = metric
def fit(self, X, y):
#
self.X_train = X
self.y_tr... |
<reponame>rezarajan/sdc-capstone
#!/usr/bin/env python
import rospy
import numpy as np
from scipy.spatial import KDTree
from std_msgs.msg import Int32
from geometry_msgs.msg import PoseStamped
from styx_msgs.msg import Lane, Waypoint
import math
'''
This node will publish waypoints from the car's current position to... |
#MNE tutorial
#Import modules
import os
import numpy as np
import mne
import re
import complexity_entropy as ce
#Import specific smodules for filtering
from numpy.fft import fft, fftfreq
from scipy import signal
from mne.time_frequency.tfr import morlet
from mne.viz import plot_filter, plot_ideal_filter
... |
import numpy as np
import scipy as sp
class MahalanobisClassifier():
def __init__(self, samples, labels):
self.clusters={}
for lbl in np.unique(labels):
self.clusters[lbl] = samples.loc[labels == lbl, :]
def mahalanobis(self, x, data, cov=None):
"""Compute the Mahalanobis D... |
<filename>figures/bothspectra.py<gh_stars>0
from astropy.io import fits
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_style('ticks')
sns.set_context('paper', font_scale=1.7)
from plot_fits import get_wavelength, dopplerShift
from scipy.interpolate import interp1d
plt.rcParams['xtick.d... |
import matplotlib.pyplot as plt
import numpy as np
from scipy.special import logit
import pandas as pd
from matplotlib.axes import Axes, Subplot
from matplotlib.collections import LineCollection
from matplotlib.colors import ListedColormap, BoundaryNorm
SMALL = 14
SIZE = 16
plt.rc('font', size=SIZE) # controls defaul... |
<filename>simulation/src/utils.py
#!/usr/bin/env python3
import numpy as np
import math
import random
import time
import scipy.misc
import scipy.signal
import multiprocessing
import json
import itertools
import os
import pprint
from collections import namedtuple
from fractions import gcd
from optimized import get_dist... |
from enum import Enum
from math import *
from scipy import integrate
import matplotlib.pyplot as plt
from libcellml import *
import lxml.etree as ET
__version__ = "0.1.0"
LIBCELLML_VERSION = "0.2.0"
STATE_COUNT = 1
VARIABLE_COUNT = 29
class VariableType(Enum):
CONSTANT = 1
COMPUTED_CONSTANT = 2
ALGEBRAI... |
<gh_stars>1-10
import numpy as np
import scipy as sp
import pandas as pd
import ast
import itertools
from itertools import product
from collections import Counter
import networkx as nx
import network_utils as nu
import hicode as hc
import matplotlib.pyplot as plt
import matplotlib.cm as cm
plt.style.use('classic')
... |
from typing import Any, Dict, Iterable, List, Optional, Tuple, Callable
from math import pi as π
from sympy import Matrix as Mat
from numpy import ndarray
from physical_education.links import Link3D, constrain_rel_angle
from physical_education.system import System3D
from physical_education.foot import add_foot, feet, ... |
import os
import pandas as pd
from plotnine import *
import plotnine
from matplotlib import pyplot as plt
import matplotlib
from scipy.spatial.distance import pdist, squareform
from skbio.stats.ordination import pcoa
from skbio.diversity import beta_diversity
from skbio.io import read
from skbio.tree import TreeNode
im... |
<gh_stars>0
import cv2
import sys
import numpy as np
from scipy.io import loadmat
def convert():
labels = loadmat('tmp/data/devkit/cars_meta.mat')
car_labels = []
for label in labels['class_names'][0]:
car_labels.append(label[0])
labels_file = open("tmp/data/devkit/car_labels.txt", "w")
l... |
<filename>tests/env/experiments_tools_2.py<gh_stars>1-10
import sys
sys.path.insert(0, '..')
import numpy as np
import pandas as pd
from itertools import combinations
from scipy.stats import binom
import scipy.special
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
from IPython.display import disp... |
<reponame>voreille/2d_bispectrum_cnn
from pathlib import Path
import numpy as np
from PIL import Image, ImageSequence
import matplotlib.pyplot as plt
import tensorflow as tf
import tensorflow_io as tfio
from scipy.ndimage import rotate
from src.data.monuseg import get_dataset, tf_random_rotate, tf_random_crop
ds = g... |
<gh_stars>0
import pybullet as p
import numpy as np
from icecream import ic
from scipy.spatial.transform import Rotation as R
from highlevel_planning_py.tools.util import (
homogenous_trafo,
invert_hom_trafo,
pos_and_orient_from_hom_trafo,
SkillExecutionError,
)
class SkillNavigate:
def __init__(s... |
import random, copy
import cv2 as cv
import numpy as np
from scipy import interpolate
from .augmenter import Augmenter
class WhiteBalancer(Augmenter):
'''
Augmenter that randomly changes the white balance of the SampleImages.
'''
def __init__(
self,
min_red_rand,
max_red_rand,
min_blue_rand,
... |
<filename>Graded/G3/slam/EKFSLAM.py
from typing import Tuple
import numpy as np
from numpy import ndarray
from dataclasses import dataclass, field
from scipy.linalg import block_diag
import scipy.linalg as la
from utils import rotmat2d
from JCBB import JCBB
import utils
import solution
@dataclass
class EKFSLAM:
Q... |
<reponame>ChunaraLab/medshifts
'''
Modifed from code by <NAME> https://github.com/steverab/failing-loudly
Plot test results across hospitals
Usage:
# region
python generate_hosp_plot.py --datset eicu --path orig --test_type multiv --num_hosp 4 --random_runs 100 --min_samples 5000 --sens_attr race --group --group_typ... |
import os
import time
import h5py
import json
from PIL import Image
import torch
from torch import nn
import torchvision
import torchvision.transforms as transforms
import torch.optim
import torch.nn.functional as F
from torch.utils.data.dataset import random_split
from torch.utils.data import Dataset
from torch.nn.... |
<filename>code/preprocess/consumption/sector/tn/tn_tx.py<gh_stars>1-10
#! usr/bin/python3
import pandas as pd
import re
import numpy as np
import os
import sys
from collections import OrderedDict, defaultdict
import matplotlib as mpl
import matplotlib.pyplot as plt
# import seaborn as sns
from scipy import stats, inte... |
<reponame>kanishk2509/TwitterBotDetection
######################
# Loading word2vec
######################
import os
from threading import Semaphore
import gensim
from gensim.models import KeyedVectors
pathToBinVectors = '/Users/kanishksinha/Downloads/GoogleNews-vectors-negative300.bin'
newFilePath = '/Users/kanishks... |
<reponame>yt7589/mgs
#
#import scipy
#from scipy import io as sio
import scipy.io.wavfile
from ext.spafe.utils import vis
from ext.spafe.features.bfcc import bfcc
class AfeBfcc:
@staticmethod
def extract_bfcc(wav_file):
print('获取BFCC特征')
num_ceps = 13
low_freq = 0
high_freq = 20... |
<gh_stars>10-100
from PyQt4.QtCore import *
from PyQt4.QtGui import *
import sys,os,time
from scipy.stats import gamma, norm, beta
import matplotlib.pyplot as plt
from datetime import date, timedelta
import numpy as np
import tkinter
from os import listdir
from os.path import isfile, join
def sorted_values(... |
<reponame>akerestely/nonlinearBestFit<filename>tools.py
import numpy as np
import pandas as pd
np.random.seed(421)
def hCG(x: np.ndarray, A: float, B: float, alpha: float):
return A * np.exp(-alpha * x) + B
def gen_rand_points(n: int, A: float = 1000, B: float = 3, alpha: float = 0.01, noise: float = 2, consecut... |
<filename>paul_analysis/Python/labird/fieldize.py
# -*- coding: utf-8 -*-
"""Methods for interpolating particle lists onto a grid. There are three classic methods:
ngp - Nearest grid point (point interpolation)
cic - Cloud in Cell (linear interpolation)
tsc - Triangular Shaped Cloud (quadratic interpolation... |
<filename>notebooks/working/_02_tb-Demo-visual-marginal-independence-tests.py
# ---
# jupyter:
# jupytext:
# formats: ipynb,py,md
# text_representation:
# extension: .py
# format_name: light
# format_version: '1.5'
# jupytext_version: 1.4.2
# kernelspec:
# display_name: Python 3
... |
# Copyright 2019 The Johns Hopkins University Applied Physics Laboratory
#
# 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 ... |
import numpy as np
import matplotlib.pyplot as plt
from sklearn.manifold import Isomap
from scipy.spatial.distance import pdist
from sklearn.neighbors import KNeighborsClassifier
from sklearn.model_selection import cross_val_score, LeaveOneOut
RANDOM_STATE = 42
def calculate_pairwise_distances(df_for_Box_Plot_featu... |
<gh_stars>0
import os
import io
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
from matplotlib.backends.backend_agg import FigureCanvasAgg
from matplotlib.figure import Figure
from keras.applications.imagenet_utils import preprocess_input
from keras.backend.tensorflow_backend import set_sessi... |
import numpy as np
from scipy import sparse as sp
from rlscore.utilities import multiclass
def load_newsgroups():
T = np.loadtxt("train.data")
#map indices from 1...n to 0...n-1
rows = T[:,0] -1
cols = T[:,1] -1
vals = T[:,2]
X_train = sp.coo_matrix((vals, (rows, cols)))
X_train = X_train.... |
<reponame>worldwise001/stylometry<filename>graph/__init__.py
import matplotlib
matplotlib.use('Agg')
import statsmodels.api as sm
import statsmodels.formula.api as smf
import numpy as np
from scipy.stats import linregress
import matplotlib.pyplot as plt
from sklearn.metrics import roc_curve, auc
def hist_prebin(filen... |
<reponame>haloship/rec-sys-dynamics<filename>code/src/algorithm/algo.py
"""Recommendation Algorithm Base Class
This module is a base class for algorithms using sparse matrices
The required packages can be found in requirements.txt
"""
import pandas as pd
import numpy as np
from lenskit import batch, topn, util
from ... |
import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
import scipy
import copy
def get_loss_from_z(model, z, t, reduction):
if model.name_loss == 'multi-class classification':
criterion = torch.nn.CrossEntropyLoss()
loss = criterion(z, t.type(torch.LongTensor).to(z... |
"""Sampling code for the parrot.
Loads the trained model and samples.
"""
import numpy
import os
import cPickle
import logging
from blocks.serialization import load_parameters
from blocks.model import Model
from datasets import parrot_stream
from model import Parrot
from utils import (
attention_plot, sample_pa... |
<filename>Visualizer.py
import numpy as np
import argparse
import scipy.linalg
from mpl_toolkits.mplot3d import Axes3D
from skimage.draw import polygon
import matplotlib.pyplot as plt
import glob
from sklearn import datasets, linear_model
import pdb
import time
parser = argparse.ArgumentParser()
parser.add_argument('-... |
<gh_stars>1-10
from clifford import g3c
import numpy as np
import scipy.optimize as opt
from pygacal.rotation.costfunction import restrictedImageCostFunction, restrictedMultiViewImageCostFunction
from pygacal.rotation import minimizeError
from pygacal.rotation.mapping import BivectorLineImageMapping, BivectorLineMapp... |
"""
Тесты для задания 2.4.
"""
from unittest import TestCase, main
from fractions import Fraction
from tasks import task_2_4
class TestFractionFromString(TestCase):
def test_fraction_from_string__CorrectArguments__ShouldReturnCorrectResult(self):
"""
Проверяет работу с корректными данными.
... |
<reponame>BrandonKates/open_spiel
# Copyright 2019 DeepMind Technologies Ltd. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICEN... |
<reponame>zmlabe/StratoVari
"""
Calculate PDFs for polar vortex response
Notes
-----
Author : <NAME>
Date : 25 June 2019
"""
### Import modules
import numpy as np
import matplotlib.pyplot as plt
import datetime
import read_MonthlyData as MO
import calc_Utilities as UT
import cmocean
import scipy.stats as st... |
import numpy as np
import pylab as plt
from scipy.integrate import simps
def grid_interpolate_samples(x, y, bins=1000, return_norm=False):
idx = np.argsort(x)
x, y = x[idx], y[idx]
x_grid = np.linspace(x[0], x[-1], bins)
y_grid = np.interp(x_grid, x, y)
norm = simps(y_grid, x_grid)
y_grid_norm... |
# -*- coding: utf-8 -*-
"""
Created on Thu Dec 11 11:37:39 2014
@author: sm1fg
Construct the magnetic network and generate the adjustments to the
non-magnetic atmosphere for mhs equilibrium.
"""
import os
import warnings
import numpy as np
import astropy.units as u
from scipy.interpolate import RectBivaria... |
<reponame>kenneth2001/Virus
import asyncio
import requests
from bs4 import BeautifulSoup
from datetime import date, datetime
import discord
import numpy as np
from urllib.error import HTTPError
import yt_dlp as youtube_dl
from discord.ext import commands
import os
from pytz import timezone
from yt_dlp.utils import Down... |
<gh_stars>0
########################################################################
# This script contains all the data analysis functions #
########################################################################
from __future__ import division
from pylab import *
import scipy, scipy.stats
import ta... |
# -*- coding: utf-8 -*-
"""Script which can be used to compare the features obtained of two different influenza models
Usage:
get_model_statistics.py <model> [--country=<country_name>] [--no-future] [--basedir=<directory>] [--start-year=<start_year>] [--end-year=<end_year>] [--save] [--no-graph]
<baseline> ... |
from scipy.sparse import vstack
from sklearn.metrics.pairwise import cosine_similarity
import numpy as np
from sisu.preprocessing.tokenizer import is_relevant_sentence, make_sentences, sanitize_text
from gismo.gismo import Gismo, covering_order
from gismo.common import auto_k
from gismo.parameters import Parameters
fr... |
<filename>Data_Science/Python-Estatistica/stats-ex8.py
import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
def cinematica(t,s0,v0,a):
s = s0 + v0*t +(a*t*t/2.0)
return s
t = np.linspace(0, 5, 500)
s0 = 0.5
v0 = 2.0
a = 1.5
s_noise = 0.5 * np.random.normal(size=t.size)
s = cin... |
"""
Twiss module.
Compute twiss parameters from amplitude & phase data.
Twiss filtering & processing.
"""
import numpy
import torch
import pandas
from scipy import odr
from .util import mod, generate_pairs, generate_other
from .statistics import weighted_mean, weighted_variance
from .statistics import median, biwei... |
import numpy as np
import scipy.linalg as la
from auxiliary import *
a = np.matrix([
[+0.35, +0.45, -0.14, -0.17],
[+0.09, +0.07, -0.54, +0.35],
[-0.44, -0.33, -0.03, +0.17],
[+0.25, -0.32, -0.13, +0.11],
], dtype=float)
w, vl, vr = la.eig(a, left=True, right=True)
vprintC('w', w)
print
for i in ran... |
<filename>MBC_ER_status/Ulz_pipeline/downloads/run_tf_analyses_from_bam.py
#!/usr/bin/env python
# coding: utf-8
#AL - the above code is new for the griffin paper version
#modified print commands for python3
# Analyze all possible things from BAM-file
import sys
import argparse
from subprocess import call
import num... |
<filename>scripts/plot_summary_stats.py<gh_stars>1-10
#!/usr/bin/env python
from pda.dataset import init_aggregate_and_appliance_dataset_figure
import matplotlib.pyplot as plt
from scipy.stats import *
import numpy as np
subplots, chan = init_aggregate_and_appliance_dataset_figure(
start_date='2013/6/4 10:00', en... |
<gh_stars>0
# PHS3350
# Week 2 - wave packet and RFAP -
# "what I cannot create I cannot understand" - <NAME>.
# <NAME>, 13/03/2021
import os
from pathlib import Path
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import physunits
from scipy.fft import fft, ifft
plt.rcParams['figure.dpi'] = 200
... |
<reponame>majkelx/astwro
#! /usr/bin/env python
# coding=utf-8
from __future__ import print_function, division
from scipy.stats import sigmaclip
from astwro.pydaophot import daophot
from astwro.pydaophot import fname
from astwro.pydaophot import allstar
from astwro.starlist import read_dao_file
from astwro.starlist ... |
import numpy as np
from scipy.integrate import simps
def get_wss_magnitude(wss_vector):
if (wss_vector.shape[-1] != 3):
return wss_vector
return np.sum(wss_vector ** 2, axis=-1) ** 0.5
def get_tawss(wss, dt):
x = np.arange(0, len(wss))
x = np.asarray(x) * dt
wss_int = simps(wss, x, axis=... |
"""
Calculate the translational entropy with EW, HSM and IGM models
"""
import numpy as np
import matplotlib.pyplot as plt
from scipy import integrate
plt.style.use("paper")
ha2kjmol = 627.5 * 4.184
class Constants:
hbar_au = 1.0
h_au = hbar_au * 2.0 * np.pi
kb_au = 3.1668114E-6 # hartrees K-1
h_... |
<reponame>JojoReikun/ClimbingLizardDLCAnalysis
def aep_pep_test(**kwargs):
"""
Calculates two different things:
1.) The x and y coordinates of the AEP and PEP, relative to the coxa of a respective leg
2.) The swing phases and the stance phases, identifying on a frame by frame basis
Return: results ... |
<reponame>gustxsr/learning-with-assemblies<filename>testing.py
import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import convolve
from matplotlib.gridspec import GridSpec
import matplotlib as mpl
rng = np.random.default_rng()
def k_cap(input, cap_size):
"""
Given a vector input it ... |
from collections import Counter, defaultdict
from datetime import datetime
from statistics import mean
from dateutil.parser import parse as parse_datetime
from dateutil import rrule
def num_comments_by_user(comments):
commenters = (comment['from']['name'] for comment in comments)
counter = Counter(commenters... |
<reponame>ZihaoChen0319/CMB-Segmentation
import torch.nn as nn
import os
import torch.optim as optim
from tqdm import tqdm
import numpy as np
import torch
import torch.nn.functional as nnf
import SimpleITK as sitk
import json
from scipy import ndimage
import medpy.io as mio
from Utils import find_binary_ob... |
#! /usr/bin/python3
# -*- coding: utf-8 -*-
import pickle
import pandas as pd
import xml.etree.ElementTree as ET
import math
import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np
import csv
import glob
import scikit_posthocs as sp
from scipy import stats
import os
from scipy import stats
import scik... |
<gh_stars>1-10
#!/usr/bin/env python3
# Copyright 2020 Google LLC
#
# 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 app... |
from cmath import nan
from sqlite3 import DatabaseError
import pandas as pd
import numpy as np
import json
def load_from_csv(path):
dt = pd.read_csv(path, sep=';', dtype={'matricule': object})
return dt.set_index('matricule')
def fix_matricule(matricule):
if matricule.startswith('195'):
return '19... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Software License Agreement (BSD License)
#
# Copyright (c) 2014, Ocean Systems Laboratory, Heriot-Watt University, UK.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the follow... |
import numpy as np
import time
import argparse
import pandas as pd
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
from scipy import special
from tqdm import tqdm
from scipy.optimize import curve_fit
from utils.build_hist import build_hist
class SS_Charge:
"""
read calibration data and ... |
# python /usr/bin/env/python
# /// The Exoplanet Pocketknife
# /// <NAME>, The Ohio State University 2015-2017
# /// All usage must include proper citation and a link to the Github repository
# /// https://github.com/ScottHull/Exoplanet-Pocketknife
import os, csv, time, sys, shutil, subprocess
from threading import ... |
#!usr/bin/env python3
#coding:utf8
import matplotlib.pyplot as plt
import numpy as np
from scipy.optimize import curve_fit
from astropy.io import ascii
from uncertainties import ufloat
import uncertainties.unumpy as unp
from modules.table import textable
import scipy.constants as const
import math as math
from modules.... |
<reponame>pierfra-ro/allesfitter<filename>allesfitter/basement.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Oct 5 00:17:06 2018
@author:
Dr. <NAME>
European Space Agency (ESA)
European Space Research and Technology Centre (ESTEC)
Keplerlaan 1, 2201 AZ Noordwijk, The Netherlands
Email: <EMAIL>
... |
import localmodule
import datetime
import h5py
import math
import music21 as m21
import numpy as np
import os
import scipy
import scipy.linalg
import sys
import time
# Parse arguments
args = sys.argv[1:]
composer_str = args[0]
track_str = args[1]
# Define constants.
J_tm = 8
N = 2**10
n_octaves = 8
midi_octave_off... |
<gh_stars>0
import math
import sys
from scipy.interpolate import interp2d
from scipy.ndimage import rotate, center_of_mass
from scipy.spatial import distance
from skimage.feature import canny
from skimage.filters import rank, gaussian
from skimage.measure import subdivide_polygon
from skimage.morphology import medial_... |
<filename>MISC/opt_omega_ip.py
#!/usr/bin/env python
import os
import sys
sys.path.append(os.getcwd())
import abinitio_driver as driver
from abinitio_driver import AUtoEV
import scipy.optimize as opt
from scipy.interpolate import interp1d
try:
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot a... |
<gh_stars>0
import os
import datetime
from collections import defaultdict
import numpy as np
from scipy import sparse
from episim.ontology import Ontology
from episim.plot.modeling import System, Accumulator
from .data import State
class EulerSimulator(object):
"""
Explicit Euler method
"""
def __i... |
<gh_stars>1-10
from functools import wraps
from typing import Iterable
import numpy as np
import scipy.stats as scist
import matplotlib.pyplot as plt
from rpy2.robjects.packages import importr
from rpy2.robjects.vectors import FloatVector
from phat.utils import argsetter
base = importr('base')
utils = importr('util... |
'''
Wrapper function to run PPO algorithm for training
'''
import numpy as np
import matplotlib.pyplot as plt
import time
import math
import logging
from scipy.optimize import minimize, LinearConstraint
# custom libraries
from training.PPO.run_helper import buyerPenaltiesCalculator, buyerUtilitiesCalculator, evaluati... |
# This code finds the Fourier Tranform of a signal and the Nyquist frequency
import matplotlib.pyplot as plt
import numpy as np
import librosa
import librosa as lr
from scipy import signal
from scipy.fft import fft, ifft
import math
import matplotlib.pyplot as plt
if __name__ == "__main__":
# Read the audio ... |
from numpy import *
from scipy.signal import correlate2d
from numpy.random import randint,choice,uniform
from matplotlib.pyplot import *
import matplotlib.pyplot as plt
from os import system
class KineticMonteCarlo(object) :
def __init__( self, Model ) :
# reference state
... |
<reponame>kaszperro/mapel
import numpy as np
def clustering_v1(experiment, num_clusters=20):
from scipy.cluster.hierarchy import dendrogram, linkage, fcluster
import scipy.spatial.distance as ssd
# skip the paths
SKIP = ['UNID', 'ANID', 'STID', 'ANUN', 'STUN', 'STAN',
'Mallows',
... |
#!/usr/bin/env python
# Copyright (C) 2017 Udacity Inc.
#
# This file is part of Robotic Arm: Pick and Place project for Udacity
# Robotics nano-degree program
#
# All Rights Reserved.
# Author: <NAME>
# import modules
import rospy
import tf
from kuka_arm.srv import *
from trajectory_msgs.msg import JointTrajectory,... |
# cppsimdata.py
# written by <NAME>
# with minor modifications by <NAME> to work with both Python 2.7 and Python 3.4
# available at www.cppsim.com as part of the CppSim package
# Copyright (c) 2013-2017 by <NAME>
# This file is disributed under the MIT license (see Copying file)
import ctypes as ct
import numpy as n... |
from tcga_encoder.utils.helpers import *
from tcga_encoder.data.data import *
#from tcga_encoder.data.pathway_data import Pathways
from tcga_encoder.data.hallmark_data import Pathways
from tcga_encoder.definitions.tcga import *
#from tcga_encoder.definitions.nn import *
from tcga_encoder.definitions.locations import *
... |
import warnings
import numpy as np
import pandas as pd
import xgboost as xgb
import scipy.stats as st
from sklearn.neighbors import BallTree
from xgbse._base import XGBSEBaseEstimator
from xgbse.converters import convert_data_to_xgb_format, convert_y
from xgbse.non_parametric import (
calculate_kaplan_vectorized,... |
<reponame>garrettdreyfus/HolteAndTalleyMLDPy<gh_stars>10-100
from scipy.io import loadmat
import pickle
mldinfo =loadmat('mldinfo.mat')["mldinfo"]
out={}
print(mldinfo)
for i in mldinfo:
line={}
line["floatNumber"] = i[0]
line["cycleNumber"] = i[26]
line["tempMLTFIT"] = i[27]
line["tempMLTFITIndex"]... |
# import libraries
import os, os.path
import numpy as np
import pandas as pd
# import geopandas as gpd
import sys
from IPython.display import Image
# from shapely.geometry import Point, Polygon
from math import factorial
import scipy
from statsmodels.sandbox.regression.predstd import wls_prediction_std
from sklearn.lin... |
#!/usr/bin/python
import os
import sys
import glob
import argparse
import tempfile
import numpy as np
from scipy.io import *
from scipy import stats
from subprocess import Popen, PIPE
from scai_utils import *
from get_qdec_info import get_qdec_info
from read_xml_labels import read_xml_labels
atlas_label_fn = \
"... |
<reponame>dimitra-maoutsa/DeterministicParticleFlowControl
# -*- coding: utf-8 -*-
"""
Created on Mon Jan 10 07:20:39 2022
@author: maout
"""
import numpy as np
from scipy.spatial.distance import cdist
import torch
#from score_function_estimators import my_cdist
from typing import Union
from torch.autograd import g... |
<reponame>BartSiwek/Neurotransmitter2D
import string
import scipy
import PslgIo, ElementAwarePslg
def loadEle(filename):
pslg = ElementAwarePslg.ElementAwarePslg()
file = open(filename, "r")
try:
PslgIo.readFromFile(file, pslg, filename)
finally:
file.close()
return pslg
def saveFe... |
from __future__ import division
from chempy.util.testing import requires
from ..integrated import pseudo_irrev, pseudo_rev, binary_irrev, binary_rev
import pytest
try:
import sympy
except ImportError:
sympy = None
else:
one = sympy.S(1)
t, kf, kb, prod, major, minor = sympy.symbols(
't kf kb... |
<reponame>amahoro12/anne<filename>setup.py<gh_stars>0
## This script set up classes for 4 bus and 2 bus environment
import pandapower as pp
import pandapower.networks as nw
import pandapower.plotting as plot
import enlopy as el
import numpy as np
import pandas as pd
import pickle
import copy
import math
import matplotl... |
<filename>datasets/kitti.py
# Basic libs
import os, time, glob, random, pickle, copy, torch
import numpy as np
import open3d
from scipy.spatial.transform import Rotation
# Dataset parent class
from torch.utils.data import Dataset
from lib.benchmark_utils import to_tsfm, to_o3d_pcd, get_correspondences
class KITTIDat... |
<reponame>blackyblack/symplyphysics
from sympy.functions import exp
from symplyphysics import (
symbols, Eq, pretty, solve, Quantity, units, S,
Probability, validate_input, expr_to_quantity, convert_to
)
# Description
## Ptnl (fast non-leakage factor) is the ratio of the number of fast neutrons that do not lea... |
<reponame>kirk86/kaggle
# import sys
# sys.path.appenval.'/usr/local/lib/python2.7/site-packages')
import dlib
import scipy
import skimage as io
import numpy as np
def dlib_selective_search(orig_img, img_scale, min_size, dedub_boxes=1./16):
rects = []
dlib.find_candidate_object_locations(orig_img, rects, min_... |
from skimage import img_as_int
import cv2
import numpy as np
from pylab import *
import scipy.ndimage.filters as filters
#img = cv2.imread('images/profile.jpg', 0)
img = cv2.imread('images/moon.jpg',0)
sobel_operator_v = np.array([
[-1, 0, 1],
[-2, 0 ,2],
[-1, 0, 1]
])
sobelX = cv2.Sobel(img, -1... |
<filename>LoanPandas/code.py<gh_stars>1-10
# --------------
# Import packages
import numpy as np
import pandas as pd
from scipy.stats import mode
# code starts here
bank = pd.read_csv(path)
categorical_var = bank.select_dtypes(include = 'object')
print(categorical_var)
numerical_var = bank.select_dtypes(include = 'n... |
"""Official merge script for PI-SQuAD v0.1"""
from __future__ import print_function
import os
import argparse
import json
import sys
import shutil
import scipy.sparse
import scipy.sparse.linalg
import numpy as np
import numpy.linalg
def get_q2c(dataset):
q2c = {}
for article in dataset:
for para_idx... |
<gh_stars>1-10
from imutils import face_utils
from scipy.spatial import distance
import cv2
import dlib
import imutils
import pygame
import time
# Initializing the alert sound
pygame.mixer.init()
alert_sound = pygame.mixer.Sound("alert_sound.wav")
default_volume = 0.2
# Eye-Aspect-Ratio data
EAR_threshhold = 0.17 # O... |
<reponame>daniel-schaefer/CompEcon-python
import numpy as np
from scipy.sparse import csc_matrix, diags, tril
from .basis import Basis
__author__ = 'Randall'
# TODO: complete this class
# todo: compare performance of csr_matrix and csc_matrix to deal with sparse interpolation operators
# fixme: interpolation is 25 slo... |
"""Class with high-level methods for processing NAPS and NAPS BE datasets."""
from config import DATA_NAPS_BE_ALL
from lib import partition_naps
from lib import plot
from lib import plot_clusters
from lib import plot_clusters_with_probability
from lib import plot_setup
from lib import read_naps
from lib import read_na... |
from __future__ import division
from builtins import str
from builtins import range
from astropy.utils.misc import isiterable
from past.utils import old_div
import copy
import collections
import numpy as np
import healpy as hp
import astropy.units as u
import matplotlib.pyplot as plt
import matplotlib as mpl
from sci... |
"""Model Definations for trpo."""
import gym
import numpy as np
import torch
import time
import scipy.optimize
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
from distributions import DiagonalGaussian
from helpers import get_flat_params, set_flat_params, get_flat_grads
#from ... |
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