text string |
|---|
<reponame>hrichstein/phys_50733<filename>rh_hw6/richstein_hw6_prob1b.py
"""
Student Name: <NAME>
Professor Name: Dr. Frinchaboy
Class: PHYS 50733
HW 6: Nonlinear Pendulum - Leapfrog Method
Last edited: 24 April 2017
Overview:
---------
Input:
------
Output:
-------
"""
# Importing Needed Modules
import numpy a... |
<filename>active_semi_clustering/active/pairwise_constraints/min_max.py<gh_stars>1-10
import numpy as np
from scipy.spatial.distance import cdist, pdist
from .example_oracle import MaximumQueriesExceeded
from .explore_consolidate import ExploreConsolidate
class MinMax(ExploreConsolidate):
'''
More intellige... |
<gh_stars>0
import torch, os
from statistics import mean
from itertools import takewhile
from _train import jieba_train
from _train import bert_train
from _train import print_data
USE_CUDA = torch.cuda.is_available()
device = torch.device("cuda" if USE_CUDA else "cpu")
def train_evaluation(data_mode, data_... |
<filename>draw.py<gh_stars>1-10
import os
import numpy as np
def process(filename):
'读取文件，并且输出数据位置，与处理好的横纵坐标数据'
data = []
with open (filename,encoding = 'UTF-8', errors = 'ignore') as lines:
for line in lines:
line = line.split()#按制位符将数据分割
data.append(line)#读取的文件付给dat... |
#<EMAIL> 02/20/2018
import numpy as np
from scipy.optimize import bisect
class PyCFD:
def __init__(self, params):
self.sample_interval = params['sample_interval']
self.delay = int(params['delay']/self.sample_interval)
self.fraction = params['fraction']
self.threshold = params['t... |
<reponame>PacktPublishing/Building-Practical-Recommendation-Engines-Part-2
# -*- coding: utf-8 -*-
"""
Created on Wed Nov 30 22:36:10 2016
@author: Suresh
"""
import pandas as pd
import numpy as np
import scipy
import sklearn
path = "C:/RND/RecoEngine/anonymous-msweb.test.txt"
raw_data = pd.read_csv(path,header=None... |
<gh_stars>1-10
from sympy import symbols
from homogeneous import *
def main():
a, b, c, d, e, f, g, h, k, m, n, p, q = symbols('a, b, c, d, e, f, g, h, k, m, n, p, q')
A, C, E, B, D = (a, 0, b), (c, 0, d), (e, 0, f), (0, g, h), (k, m, n)
# The dual theorem is also proved when lines ACE are parallel.
# ... |
import csv
import statistics
from collections import defaultdict as dd
def parse_data(filename):
#initialize list of valid years and months to use for checking
valid_years = ["2010", "2011", "2012", "2013", "2014"]
valid_months = ["JAN", "FEB", "MAR", "APR", "MAY", "JUN",
"JUL", "... |
#!/usr/bin/env python3
# Project : From geodynamic to Seismic observations in the Earth's inner core
# Author : <NAME>
# Seismic properties of material as function of ka (adimensional frequency): P and S wave velocity and attenuation.
# Please refer to Calvet and Margerin 2008 (figures 3 and 4)
from __future__ import... |
<reponame>ed-ortizm/autoencoders-outlier-detection
import numpy as np
from scipy.stats import norm, gamma, uniform, expon, entropy
###############################################################################
class KLD:
"""
Compute Kullback-Leibler Divergence (KLD) between samples of a
distribution and a... |
import pickle
import numpy as np
from util.editdistance import lcsdistance
from scipy.cluster.hierarchy import linkage, dendrogram
from scipy.spatial.distance import squareform
import matplotlib.pyplot as plt
from scipy.cluster.hierarchy import fcluster
import random
# Borg pattern for EZ singletons https://python-3-p... |
<filename>datafactory/preprocessing/outlier_detecting.py
import pandas as pd
from scipy.stats import iqr
from sklearn.ensemble import IsolationForest
from sklearn.neighbors import LocalOutlierFactor
import sys
sys.path.append('../util')
from ..util.constants import logger
def outlier_detection_dataframe(df: pd.DataFr... |
<filename>Bio-StrongHold/src/The_Wright_Fisher_Model_of_Genetic_Drift.py
from scipy.misc import comb
with open('data/data.dat') as input_data:
N,m,g,k = [int(num) for num in input_data.read().strip().split()]
# Determine the probabiliy of a given of recessive allels in the first generation.
# Use a binomial random v... |
<filename>project.py
# <NAME>, 20-April-2018
# Analysis of the Iris Flower Data Set
# Adapted from http://archive.ics.uci.edu/ml/machine-learning-databases/iris/
print("Petal Length", "Petal Width", "Sepal Length", "Sepal Width") # Column headings
with open ("Data/iris.csv") as f: # Link the csv file
for line i... |
#encoding: utf-8
import math
import numpy as np
from sympy import *
Nm=8
def get_Amount_of_Motif():
array=open('./data2/CountMotif.csv').readlines()
matrix=[]
for line in array:
line=line.strip('\r\n').split(',')
line=[int(x) for x in line]
matrix.append(line)
matrix=np.array... |
<filename>CalculateError.py
# Name: <NAME>
# NUSP: 10276675
# SCC0251 - Image Processing
# Project: Segmentation of Cell Cycles Images
# 2021/1
import ImagePreprocessing
from scipy import stats
import numpy as np
import os
import imageio
import cv2
def convertLuminance(img):
"""
Convert to Grayscale using Lu... |
"""
Diagnostics for MCMC methods
==================================
This notebook illustrates the use of a few diagnostics for :class:`.MCMC`. The example consists in learning the
parameters of a regression model via Bayesian inference.
"""
# %% md
#
# Import the necessary libraries.
# %%
from UQpy.sampling import... |
<gh_stars>0
#Algoritm of Gamp
from autograd.differential_operators import jacobian
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from scipy.optimize import minimize
from autograd import elementwise_grad as egrad
from autograd import grad
# This function open window for search loca... |
import csv
import json
import logging
import multiprocessing as mp
import os
import sys
import scipy
import pandas as pd
import daisy
import numpy as np
from lsd import local_segmentation
from pymongo import MongoClient
from scipy.spatial import KDTree
import pymaid
from . import database, synapse, evaluation
logger... |
from unittest import TestCase
import numpy as np
from scipy.stats import truncnorm
from copulas.univariate import GaussianKDE, GaussianUnivariate, TruncatedGaussian
from copulas.univariate.selection import select_univariate
class TestSelectUnivariate(TestCase):
def setUp(self):
size = 1000
np.r... |
from numpy import (abs, array, eye, rint)
# from scipy.linalg import lu, svd
from sympy import acos, cos, pi, sin, sqrt, Rational
def round_if_safe(val, atol):
ival = rint(val)
if abs(ival - val) < atol:
return int(ival)
else:
return val
def rotx(theta):
c = cos(theta)
s = sin(t... |
# -*- coding: utf-8 -*-
# ------------------------------------------------------------------
# Filename: <filename>
# Purpose: <purpose>
# Author: <author>
# Email: <email>
#
# Copyright (C) <copyright>
# --------------------------------------------------------------------
"""
:copyright:
<copyright>
:licen... |
<reponame>suchyta1/BalrogReconstruction
#!/usr/bin/env python
import numpy as np
from numpy import recarray
from scipy import linalg as slin
import sys
import esutil
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator, FormatStrFormatter
def generateTr... |
<filename>widget_creation.py
import numpy as np
import pandas as pd
from scipy import stats
idx = pd.IndexSlice
from os import getcwd,listdir
import matplotlib.pyplot as plt
from random import shuffle, sample, seed
import seaborn as sns
from random import seed, sample, shuffle
from matplotlib.lines import Line2D
import... |
<reponame>emdodds/DictLearner
# -*- coding: utf-8 -*-
"""
Created on Fri Dec 11 22:33:12 2015
@author: Eric
"""
import scipy.io as io
import LCALearner
import numpy as np
import sys
import pca.pca
sys.modules['pca'] = pca.pca
import matplotlib.pyplot as plt
plt.ioff()
overcompleteness = 0.5
numinp... |
<reponame>n-yoshikawa/automatic-differentiation-SCF<gh_stars>1-10
import time
import numpy
import matplotlib.pyplot as plt
from pyscf import gto, scf, ao2mo
import scipy
from scipy.optimize import minimize
import jax.numpy as jnp
from jax import grad, jit, random
from jax.config import config
config.update("jax_enab... |
<filename>startup/41-ESM_motion.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, mv
... |
<gh_stars>1-10
# -*- coding: utf-8 -*-
"""
Created on Wed Jul 06 12:33:31 2016
@author: <NAME>
"""
import math
import numpy as np
from scipy import polyfit, polyval
import matplotlib.pyplot as plt
from xfoil_module import output_reader
# Wire properties
rho = 3.55041728247e-06
A = math.pi*(0.000381/2.)**2
L = math.s... |
<reponame>bmorris3/catastropy
from copy import copy
from itertools import zip_longest
from concurrent import futures as cf
import numpy as np
from scipy.stats import gamma, nbinom
from numba import njit
__all__ = ['abc', 'compute', 'simulate_outbreak']
@njit
def sample_nbinom(n, p, size):
nb = np.zeros(size)
... |
<reponame>VDelv/Emotion-EEG<filename>Utils_Bashivan.py
'''
Created by <NAME>
This code has been created by p. bashivan source : https://github.com/pbashivan/EEGLearn
'''
__author__ = '<NAME>'
import numpy as np
np.random.seed(123)
import scipy.io
from scipy.interpolate import griddata
from sklearn.pr... |
#!/usr/bin/env python3
import sys
import os
import argparse
import matplotlib.pyplot as plt
import pandas as pd
import math
import numpy as np
import scipy.stats
import h5py
import json
# import seaborn as sns
# from matplotlib import cm
# from matplotlib.colors import ListedColormap, LinearSegmentedColormap
colors =... |
"""Defines N-1 dimensional surfaces in N-dimensional space.
All surfaces are represented by a Mesh with points and connections (i.e. line segments or triangles) between those points.
"""
import numpy as np
from scipy import sparse, linalg
from nibabel import freesurfer, spatialimages, gifti
import nibabel as nib
from ... |
<filename>client/read_data.py
import numpy
import pandas as pd
import pickle
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import normalize, StandardScaler, LabelEncoder
import keras
import sys
import numpy as np
import scipy
import scipy.io
from keras.utils import to_categorical
impor... |
from __future__ import annotations
from typing import List, Optional
from typing import final
import numpy as np
import scipy.linalg
import pyccl
import sacc
from ..likelihood import Likelihood
from ...updatable import UpdatableCollection
from .statistic.statistic import Statistic
from ...parameters import ParamsMap,... |
<gh_stars>1-10
# import some modules
import filter_env
from ddpg import *
import gc
gc.enable()
#import math and ros modules
import roslib
import rospy
import rostopic
import random
import time
import math
import csv
from std_srvs.srv import Empty
from gazebo_msgs.srv import SetModelConfiguration
#import some msgs ty... |
# -- coding: utf-8 --
# Copyright 2018 <NAME> <<EMAIL>>
"""
Helper functions to handle spectras.
"""
def get_substance_peaks(substance, negative=True):
import os
import sqlite3
DB_PATH = os.path.join(os.path.abspath(os.path.join(__file__,"../..")),"data", "elements.db")
conn = sqlite3.connect(DB_PATH... |
<filename>jetset/template_2Dmodel.py
__author__ = "<NAME>"
from scipy import interpolate
import numpy as np
from astropy.units import Unit as u
from astropy.units import spectral
from astropy.table import Table
import os
from .plot_sedfit import PlotSED,PlotSpectralMultipl
from .model_parameters import ModelP... |
<gh_stars>0
#!/usr/bin/env python
import os
import glob
import sys
import shutil
import re
from argparse import ArgumentParser
import pandas as pd
import numpy as np
import math
import matplotlib.pyplot as plt
sys.path.insert(0,'..')
import ESM_xsec_setup_inputs
import ESM_utils as esm
from scipy.optimize import ... |
#!/usr/bin/env python
# Run using python3 N50_Calculator <Input Path> <GenomeSize (Optional)>
import sys
import os
import scipy
def file_parser(file_path):
# Parses a txt file to consolidate all the contig lengths into a list
# txt file must contain contigs on seperate lines for this parsing func to work
o... |
from __future__ import division
import os.path as op
from itertools import product
import numpy as np
import pandas as pd
import nibabel as nib
from scipy.signal import periodogram
import pytest
from pytest import approx
from .. import glm
def assert_highly_correlated(a, b, thresh=.999):
corr = np.corrcoef(a.f... |
# Copyright (c) <NAME>.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory.
import ray
import os
import sys
import math
import random
import time
import ctypes as ct
import multiprocessing as mp
from multiprocessing import Process
from numpy.random import Generato... |
<gh_stars>0
#!/usr/bin/python
# -*- coding: utf-8 -*-
'''
Created on Dec 4, 2014
@author: jwe
'''
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
from numpy import array
from scipy import interpolate
wifsipqe = array([[300, 0.675],
[320, 0.725],
[340, 0.66],
[350, 0.62],
[36... |
import numpy as np
import scipy.misc
from du.preprocessing.image2d import affine_transform
from du._test_utils import (numpy_almost_equal,
equal,
numpy_allclose,
numpy_not_allclose,
numpy_not_almost_equal)
... |
<reponame>masterdesky/ELTE_Digit_Lab_2018
from numpy import convolve, mean, sin, pi
from pylab import find
def radar_korkep(fn, dphi = .015, s_chirp = 9.5, n_chirp = 3, noise_percentile = .99, trig_thresh = .8, cut_sample = .75):
"""
param fn: filename (*.wav)
param dphi: egy lepes
param trig_thresh: simitott trig... |
<filename>lib/linalg.py
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# written by <NAME> (<EMAIL>) while at Facebook.
from __future__ import print_function
import scipy.sparse.linalg as l... |
<reponame>19katz/matching
from scipy.spatial import distance
from collections import Counter
from typing import Dict, List, Tuple
import numpy as np
import pandas as pd
import random
import copy
# random.seed(42)
np.set_printoptions(suppress=True)
# import itertools
def mini_sheet(matchesFile: str, n_suiteds: int, m_... |
import unittest
from functools import partial
import numpy as np
from scipy import stats
from pyapprox.arbitrary_polynomial_chaos import \
compute_moment_matrix_from_samples, APC, FPC, \
compute_moment_matrix_using_tensor_product_quadrature, \
compute_grammian_matrix_using_combination_sparse_grid, \
c... |
<gh_stars>1-10
import os
import csv
import numpy as np
from Bio.motifs import transfac
from scipy.stats import pearsonr, spearmanr
def motif_compare(args):
"""Compare PSSMs of filter motifs."""
# create output directory
if not os.path.exists(args.out_dir):
os.makedirs(args.out_dir)
# load tra... |
<filename>smarts/core/smarts.py
# Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved.
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including witho... |
<filename>fibonacci.py
import sys
try:
import math
import sympy as sym
from sympy import sin,cos,tan,N
except:
print("Packages not installed. Please install 'sympy' package")
sys.exit()
print("Fibonacci search method")
x = sym.Symbol('x')
def substitute(k):
return (f.subs(x,k))
... |
#!/usr/bin/env python3
import numpy as np
import random
import math
from scipy import signal
import imageio
from skimage import segmentation as seg
import matplotlib.pyplot as plt
from PIL import Image
from skimage import transform
from collections import Counter
from scipy import signal, ndimage
from skimage import mo... |
<filename>tests/test_repet.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import unittest
import nussl
import numpy as np
import scipy.io
import os
class TestRepet(unittest.TestCase):
@staticmethod
def _load_final_matlab_results():
back_path = os.path.join('repet_reference', 'repet_matlab_results', ... |
<gh_stars>1-10
from numpy import min, max, asarray, percentile, zeros, exp, unravel_index,\
ones, dot, where, round, reshape, r_, ix_, arange, nan_to_num, argmax,\
prod, mean, sqrt, repeat, allclose, any, outer, unique, hstack, isnan
from numpy.linalg import norm
from numpy.random import randint
from scipy.sign... |
import numpy as np
from scipy.linalg import expm
import pymctdh.units as units
from .optools import matel
from .cy.wftools import norm,inner
def lanczos(A, nel, nmodes, nspfs, npbfs, ham, uopips, copips, spfovs, nvecs=5,
return_evecs=True):
"""
"""
# thing to store A tensors
V = np.zeros(n... |
<filename>XRDXRFutils/spectra.py
from numpy import loadtxt,arctan,pi,arange,array, asarray, linspace, zeros
from matplotlib.pyplot import plot
from .utils import snip,convolve
import xml.etree.ElementTree as et
from scipy.interpolate import interp1d
from .calibration import Calibration
class Spectra():
def __init... |
# coding: utf-8
from __future__ import print_function
import os
from functools import partial
import numpy as np
from scipy.interpolate import interp1d
def get_filepath(base_path, driver, period, post_amp, tube_r, exp_fac):
if exp_fac is not None:
data_dir = os.path.join(base_path, '%s/%s_%s_%s_%s/'%(dr... |
# -*- coding: utf-8 -*-
# (c) 2017-2018, ETH Zurich, Institut fuer Theoretische Physik
# Author: <NAME> <<EMAIL>>
"""
Defines constants which are useful for creating orbitals.
"""
from fractions import Fraction
from ._orbitals import Spin
__all__ = ['WANNIER_ORBITALS', 'SPIN_UP', 'SPIN_DOWN', 'NO_SPIN']
WANNIER_OR... |
#!/usr/bin/python3
## dependencies
from pylab import *
import matplotlib as mplt
import numpy as np
import matplotlib.pyplot as plt
import os
import math
import argparse
from module_getarg import getarg
from argparse import RawTextHelpFormatter
# this is to ignore warnings
import warnings
warnings.filterwarnings("ig... |
# Test script for comparing GMM integrator to existing mcsampler integrator in
# RIFT. A simple n-dimensional integrand consisting of a highly-correlated
# Gaussian is used.
from __future__ import print_function
import numpy as np
from scipy.stats import multivariate_normal
from scipy.stats import truncnorm
import mat... |
<gh_stars>0
import matplotlib
# reset defaults
matplotlib.rcParams.update(matplotlib.rcParamsDefault)
# matplotlib.rcParams['font.sans-serif'] = "Arial"
# matplotlib.rcParams['font.family'] = "sans-serif"
#matplotlib.rcParams['axes.linewidth'] = 0.3
matplotlib.rcParams["axes.labelcolor"] = "black"
matplotlib.rcParam... |
import numpy as np
import scipy.integrate as integrate
import control
import matplotlib.pyplot as plt
import controlinverilog as civ
def ise(time, error):
return integrate.trapz(error*error, time)
def ramp_tracking_optimization_tuning_example():
s = control.TransferFunction.s
ratio = 0.1
wn = 2*np.pi*... |
#!/usr/bin/env python
import sys, pdb
import sqlalchemy as sa
from sqlalchemy.orm import Session
from sqlalchemy.ext.declarative import declarative_base
#from pisces.io.trace import read_waveform
from obspy.core import UTCDateTime
from obspy.core import trace
from obspy.core import Stream
from obspy.core.util import ... |
import argparse
import gc
import json
import logging
from pathlib import Path
import feather
import numpy as np
import lightgbm as lgb
import pandas as pd
from scipy import sparse as sp
from tqdm import tqdm
import config as cfg
from predictors import GBMFeatures, GBMPredictor
from utils import (
ProductEncoder,
... |
######## IMPORTS ########
# General purpose imports
import numpy as np
import os
import scipy
from lumopt import CONFIG
# Optimization specific imports
from lumopt.utilities.load_lumerical_scripts import load_from_lsf
from lumopt.geometries.polygon import function_defined_Polygon
from lumopt.figures_of_merit.modematc... |
import math
import logging
import torch
import torch.nn as nn
from torch.nn import functional as F
from scipy.ndimage import gaussian_filter as G
from scipy.signal import argrelextrema
import numpy as np
# logger = logging.getLogger(__name__)
def calc_db(keypoints_seqs):
# keypoints_seqs = keypoints_seqs.data.c... |
<filename>scripts/esrm20_total-repl-cost_vulnerability_postprocess.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sat Jul 17 19:04:01 2021
@author: helencrowley
"""
import glob
import os
import pandas as pd
import numpy as np
from scipy import stats
#%% read list of typologies from capacity curves
... |
<reponame>Morrighan89/Python-In-The-Lab_Project
# coding: utf-8
# # Python-in-the-lab: function and data fitting
# In[42]:
import os
import numpy as np
import scipy.integrate as integrate
import matplotlib.pylab as plt
from scipy.optimize import curve_fit
parameters3p = ["gamma", "A1", "A2"]
def fitShape3p(x, gamm... |
# Python 2-to-3 compatibility code
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
from collections import namedtuple
try:
import qutip as qu
except ImportError:
qu = None
import numpy as np
import scipy.const... |
<reponame>mshobair/invitro_cheminformatics
import pandas as pd
import scipy.stats as stats
## this only works for toxprints chemotypes can change this to work with any set of fingerprints
##create and fill final_table
def generate_final_table(my_enrichment_table,full_table):
column_names = ['Fingerprint_ID','TP... |
# -*- coding: utf-8 -*-
"""
FHWwallDesignSCR
This script finds the value of the force required to mantain stability of a
slope (Preqd), maximizing the failure surface's angle (alpha) and the d/H
relation (xi). Additionally, calculates the safety factor of the sliding
wedge that was found by the FHWA's simplified meth... |
from asist.utility import power_spectrum
from datetime import datetime, timedelta
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from scipy.signal import detrend
from scipy.stats import beta
from sustain_drag_2020.irgason import read_irgason_from_toa5, rotate
from sustain_drag_2020.udm import re... |
import pdb
import numpy as np
import scipy as sp
import scipy.optimize as op
import util
import matplotlib.pyplot as plt
import time
# Laplace Inference -----------------------------------------------------------
def negLogPosteriorUnNorm(xbar, ybar, C_big, d_big, K_bigInv, xdim, ydim):
xbar = np.ndarray.flatten... |
<reponame>PacktPublishing/Practical-Machine-Learning
# Practical Machine learning
# Clustering based Analysis - K-Means Clustering example
# Chapter 8
import pandas as pd
from sklearn.cross_validation import train_test_split
data = pd.read_csv('household_power_consumption.txt', delimiter=';')
power_consumption = dat... |
<filename>pandas_help/pandas_module.py<gh_stars>0
import pandas as pd
#%%
'''
if you want to read a txt or any other files as pandas use below code:
data = pd.read_csv(file, sep='\t', comment='#', na_values=['Nothing'])
'''
#%%
'''
pickle is used for saving python objects with the concept of serializing and des... |
import numpy as np
from scipy.signal import convolve
def parse_data():
with open('2020/17/input.txt') as f:
data = f.read()
return np.array(
[[int(value == '#') for value in line] for line in data.splitlines()]
)
def conway_cubes(data, dimensions):
kernel = np.ones((3,) * dimensions... |
#------------------
#Contour Size extractor
#<NAME>
#
#writes contours to pickle files given a mojo folder
#7/30/13
#------------------
import sys
import h5py
import numpy as np
import glob
import os
import pickle
import math
import time
import cv2
import threading
from Queue import Queue
import Polygon
import scip... |
<reponame>PyCubed-Mini/GNC
# -*- coding: utf-8 -*-
"""
Created on Wed Oct 9 11:53:17 2019
@author: <NAME>
@description: example script for calling and testing dynamics/kinematics functions
"""
from euler import quat2DCM, get_attitude_derivative, get_q_dot, get_w_dot
import matplotlib.pyplot as plt
from mpl_toolkits... |
<reponame>novoalab/mpileup2stats<gh_stars>0
#!/usr/bin/env python
import sys
import numpy as np
from scipy.stats import mannwhitneyu
def mann_whitney_test (list1,list2):
ary1 = np.array(list1)
ary2 = np.array(list2)
return mannwhitneyu(ary1,ary2)
def cal_man_whitney_z_score (samp1, samp2):
s1_len = sa... |
from abc import ABCMeta
from abc import abstractmethod
import numpy as np
import scipy as sp
import scipy.sparse
import random
from scipy.sparse.linalg import eigs
from scipy.sparse import coo_matrix
class UndirectedGraph(metaclass=ABCMeta):
"""
Use a doubly stochastic mixing matrix to represent an undirected... |
<reponame>bondgeodima/first<filename>sas_planet_cache.py<gh_stars>0
from maptiler import GlobalMercator
import os
import sqlite3
from sqlite3 import Error
import io
from PIL import Image
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import numpy as np
import skimage.io
import sys
import mrcnn.mod... |
from statistics import NormalDist
import dataclasses
from typing import Iterable
import numpy as np
class OrderUpToNormal:
def fit(self, demand: Iterable):
self.normal_distribution = NormalDist.from_samples(demand)
return self
def predict(
self,
current_inventory: int,
... |
<reponame>ecaruyer/qspace<filename>qspace/sampling/multishell.py
from __future__ import division
from scipy import optimize as scopt
import numpy as np
def equality_constraints(vects, *args):
"""
Spherical equality constraint. Returns 0 if vects lies on the unit
sphere.
Parameters
----------... |
<gh_stars>0
import matplotlib.pyplot as plt
import matplotlib.ticker as mtick
import numpy as np
from scipy.stats import norm
# Create an array of points to use as the x-coordinates for plotting the normal distribution
x_min = norm.ppf(0.00005) # we will plot 99.99 % of the normal curve.
x_max = norm.ppf(0.99995)
x =... |
<filename>craftroom/twod.py
'''tools for dealing with 2D arrays (images), or 3D arrays of images.'''
import numpy as np
import scipy.ndimage
import matplotlib.pyplot as plt
try:
from .displays.ds9 import ds9
except ImportError:
def ds9():
raise NameError("This is a kludge, because ds9 couldn't be import... |
<gh_stars>1-10
import sys
import json
import numpy as np
from scipy import signal
import time
def butter_highpass_filter(data, cutoff, fs, order=5):
nyq = 0.5 * fs
normal_cutoff = cutoff / nyq
b, a = signal.butter(order, normal_cutoff, btype='high', analog=False)
filt_data = signal.filtfilt(b, a, data)... |
"""Print an input number into a series."""
from sympy import Symbol, pprint, init_printing
def print_series(n, x_value):
"""Print the series.
x + x**2 + X**3 +... + x**n
_ _ _
2 3 n
"""
init_printing(order='rev-lex')
x = Symbol('x')
series = x
... |
<filename>moirai/webapi/api.py
# -*- coding: utf-8; -*-
#
# Copyright (c) 2016 <NAME>
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the r... |
<gh_stars>0
import os
import time
import numpy as np
from tqdm import tqdm
import scipy.stats
import pandas as pd
import matplotlib
# Force matplotlib to not use any Xwindows backend.
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import argparse
import tensorflow as tf
from tensorflow import keras
import mode... |
<filename>jp.atcoder/code-festival-2014-morning-easy/code_festival_morning_easy_c/31219820.py
import sys
import numpy as np
import scipy.sparse
def main() -> None:
n, m, s, t, *latter = map(int, sys.stdin.read().split())
x, y, d = np.array(latter).reshape(m, 3).T
csgraph = scipy.sparse.csr_matrix(... |
import concurrent
import contextlib
import itertools
import logging
import os
import pickle
import statistics
import time
from abc import ABC, abstractmethod
from functools import wraps
import math
import numpy as np
import scipy.fft as fft
import torch
from pyinsect.collector.NGramGraphCollector import (
ArrayGra... |
<filename>tests/atom_expr_test.py
from .context import assert_equal
import pytest
from sympy import Symbol, Integer, Pow
# label, text, symbol_text
symbols = [
('letter', 'x', 'x'),
('greek letter', '\\lambda', 'lambda'),
('greek letter w/ space', '\\alpha ', 'alpha'),
('accented letter', '\\overline{x... |
<filename>tests/test_propagation.py<gh_stars>0
"""Tests for propagation sub-module."""
import matplotlib.pyplot as plt
import numpy as np
import pytest
import scipy.constants as sc
import skrf as rf
from pytest import approx
import waveguide as wg
# Test against examples in Pozar -------------------------... |
<filename>kmeans_from_scratch.py
import pandas as pd
#Loading the required modules
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.datasets import load_digits
from sklearn.decomposition import PCA
import matplotlib.pyplot as plt
K = 10
N_iter = 10
cluster = {}
data = load_digits().data
dat... |
<gh_stars>10-100
import torch
import argparse
import torch.nn.functional as F
import statistics
import utils
from loaders.mms_dataloader_meta_split_test import get_meta_split_data_loaders
import models
from metrics.dice_loss import dice_coeff
from metrics.hausdorff import hausdorff_distance
# python inference.py -bs 1... |
import pytest
from hypothesis import given, assume
from hypothesis.strategies import sampled_from, decimals, floats, fractions, integers
from fractions import Fraction as Frac
import omk_core as omk
denominators = [2**n for n in range(1, 10)]
@given(integers(1,100), sampled_from(denominators))
def test_str(n, d):
... |
<filename>nasws/cnn/policy/cnn_general_search_policies.py<gh_stars>1-10
# ========================================================
# CONFIDENTIAL - Under development
# ========================================================
# Author: <NAME> with email <EMAIL>
# All Rights Reserved.
# Last modified: 2019/11/27 下午... |
<filename>code/Sparse_Dense matrix.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sat Dec 7 15:05:31 2019
@author: quert
"""
import numpy as np
from numpy import array
# Dense matrix -> Sparse matrix
from scipy.sparse import csr_matrix
# Create dense matrix
A = array([[1, 0, 0, 1, 0, 0], [0, 0, 2... |
#TO-DO
#WORKING ON THIES
import pandas as pd
import numpy as np
from pandas import DataFrame
from sklearn.cross_validation import train_test_split
import sklearn.cross_validation
from scipy.spatial.distance import pdist, squareform
from tpot import TPOTClassifier
from tpot import TPOTRegressor
df = pd.read_csv('sourc... |
<reponame>Suveksha/labelflow
from datetime import datetime
import scipy.misc as sm
from collections import OrderedDict
import glob
import numpy as np
import socket
# PyTorch includes
import torch
import torch.optim as optim
from torchvision import transforms
from torch.utils.data import DataLoader
# Custom includes
f... |
from ContinuousGridworld import *
import helpersContinuous
from scipy.optimize import linprog
import numpy as np
import argparse
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--iteration', type=int, default=1, help='number irl iterations')
parser.add_argument('--disc... |
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