text string |
|---|
<reponame>bigfooted/sympy
from sympy.core.numbers import Rational
from sympy.ntheory.egyptian_fraction import egyptian_fraction
from sympy.core.add import Add
from sympy.testing.pytest import raises
from sympy.testing.randtest import random_complex_number
def test_egyptian_fraction():
def test_equality(r, alg="Gr... |
<filename>report/code/sympy.py
from sympy import lambdify, diff, hessian, jacobi, cos, sin, pprint
from sympy.matrices import Matrix
from sympy.abc import x,y,w,z
from Error import *
from Log import * |
from __future__ import print_function, division
from sympy.core import Mul, sympify, Pow
from sympy.strategies import unpack, flatten, condition, exhaust, do_one
from sympy.matrices.expressions.matexpr import MatrixExpr, ShapeError
def hadamard_product(*matrices):
"""
Return the elementwise (aka Hadamard) pr... |
<filename>src/tests/unit/test_fraction_sum.py
import unittest
from models import sum
from fractions import Fraction
"""
(base) ➜ src git:(master) ✗ python -m unittest discover -s tests/unit/ -v
test_bad_type (test_sum.TestSum) ... ok
test_list_fraction (test_sum.TestSum) ... ok
test_list_int (test_sum.TestSum) ... o... |
#!/usr/bin/python3
# final_project.py
import logging
import os
import sys
from itertools import product
from functools import reduce
from imutils.video import VideoStream
from imutils.video import FPS
import imutils
import colorlog
from PIL import Image
import numpy as np
from scipy import signal
import cv2 as cv
l... |
import numpy as np
import statsmodels.api as sm
import matplotlib.pyplot as plt
from scipy.fftpack import rfft
from scipy.fftpack import fftshift
data_loader = sm.datasets.sunspots.load_pandas()
sunspots = data_loader.data["SUNACTIVITY"].values
t = np.linspace(-2 * np.pi, 2 * np.pi, len(sunspots))
mid = np.ptp(sunspo... |
<filename>gpt/element.py
import numpy as np
import os
import math, cmath
from matplotlib import pyplot as plt
from numpy.linalg import norm
import copy
#from gpt.maps import Map1D_E, Map1D_B, Map1D_TM, Map2D_E, Map2D_B, Map25D_TM
from gpt.tools import rotation_matrix
from gpt.tools import cvector
from gpt.tools impo... |
<reponame>cwardell97/learn-hippo-1
import os
import numpy as np
from utils.constants import TZ_COND_DICT
from analysis import compute_stats, remove_none
from scipy.stats import pearsonr, sem, ttest_ind
from collections import defaultdict
import matplotlib.pyplot as plt
import seaborn as sns
sns.set(style='white', palet... |
''' Utility module with functions that perform operations on (one or multiple) onset functions.'''
import numpy as np
from scipy.interpolate import interp1d
def select_top_k(arr, k):
idx = np.argpartition(arr, -k)[-k:]
idx = idx[np.argsort(arr[idx])][::-1]
return arr[idx], idx
def hwr(x, N=16):
de... |
"""
Image Data Analysis Using Numpy & OpenCV
author: <NAME>
email: <EMAIL>
website: https://iphton.github.io/iphton.github.io/
Please feel free to use and modify this, but keep the above information. Thanks!
"""
# importing necessary packages
from skimage import color
from skimage import exposure
impor... |
<filename>pyDHM/utilities.py
# -*- coding: utf-8 -*-
"""
Title--> Utility script
Author--> <NAME>, <NAME>, <NAME>,
Date--> 03/03/2019
Last modified--> 16/04/2022
University of Memphis
Optical Imaging Research lab (OIRL)
EAFI... |
<gh_stars>1-10
## label propagation routines
## label propagation algorithms:
import networkx as nx
import pandas as pd
from sklearn.model_selection import ShuffleSplit
from ..general.benchmark_classification import *
import numpy as np
import scipy.sparse as sp
import time
import multiprocessing as mp ## initialize t... |
#!/usr/bin/env python
from scipy.ndimage import imread
import pickle
import numpy
import glob
import os
from joblib import Parallel, delayed
import sys
from datasets.DAVIS.DAVIS_iterative import get_bounding_box
imgs_path = "/work/mahadevan/data/DAVIS/JPEGImages/480p/"
annots_path = "/work/mahadevan/data/DAVIS/Annot... |
#!/usr/bin/env python
# Copyright 2014-2020 The PySCF Developers. 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/LICENSE-2.0
#
# U... |
#!/usr/bin/env python
import matplotlib
matplotlib.use('pdf')
import scrublet as scr
import scipy.io
import numpy
import numpy.ma
from PIL import Image, ImageDraw, ImageFont
import os
import argparse
if __name__ == '__main__':
parser = argparse.ArgumentParser('Check sample sheet')
parser.add_argument('--key',... |
###
# pySuStaIn: a Python implementation of the Subtype and Stage Inference (SuStaIn) algorithm
#
# If you use pySuStaIn, please cite the following core papers:
# 1. The original SuStaIn paper: https://doi.org/10.1038/s41467-018-05892-0
# 2. The pySuStaIn software paper: https://doi.org/10.1016/j.softx.2021.100811
... |
<reponame>neurodata/j1c-experiments
# Copyright 2020 NeuroData (http://neurodata.io)
#
# 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
#
# Unl... |
"""
functions that convert predicted labels to file types used by different programs,
e.g., evsonganaly (GUI for labeling song), Sound Analysis Pro, etc.
"""
import os
import numpy as np
import scipy.io
def to_notmat(songfile_name, pred_labels, clf_file, samp_freq, segment_params,
onsets_s, offsets_s, ... |
# coding: utf-8
# # Hierarchical Clustering
# **Hierarchical clustering** refers to a class of clustering methods that seek to build a **hierarchy** of clusters, in which some clusters contain others. In this assignment, we will explore a top-down approach, recursively bipartitioning the data using k-means.
# **Not... |
import numpy as np
import matplotlib.pyplot as plt
from scipy.integrate import odeint
from scipy.optimize import minimize
from scipy.interpolate import interp1d
import warnings
# Import data file
# Column 1 = time (t)
# Column 2 = input (u)
# Column 3 = output (yp)
data = np.loadtxt('data_step_test.csv',del... |
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.widgets import Slider
import matplotlib
from scipy.sparse import csr_matrix, identity, kron
from scipy.sparse.linalg import eigs, eigsh
import itertools
from scipy.linalg import block_diag, eig, expm, eigh
import yaml
import copy
from scipy.special impo... |
<gh_stars>1-10
# -*- coding: utf-8 -*-
"""Written by <NAME>
Email: danaukes<at>gmail.com
Please see LICENSE for full license."""
#class FrameVector(object):
# def __init__(self,frame,coords):
# self.frame = frame
# self.coords = sympy.Matrix(coords)
# def __str__(self):
# return str(self.f... |
<reponame>dfki-asr/morphablegraphs<filename>morphablegraphs/construction/dtw.py
#!/usr/bin/env python
#
# Copyright 2019 DFKI GmbH.
#
# 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 r... |
from fractions import Fraction
from unittest import TestCase
from musurgia.fractaltree.fractalmusic import FractalMusic
def get_infos(fm):
return [fm.tempo, fm.quarter_duration, fm.duration]
def print_infos(fm):
print('tempo={}; quarter_duration={}; duration={};'.format(
*get_infos(fm)))
class Te... |
# --------------
# Importing header files
import numpy as np
import pandas as pd
from scipy.stats import mode
import warnings
warnings.filterwarnings('ignore')
#Reading file
bank_data = pd.read_csv(path)
#Code starts here
categorical_var=bank_data.select_dtypes(include='object')
print(categorical_var)
... |
<filename>inversion.py
import argparse
import h5sparse as h5py
from h5py import SoftLink
import os
import numpy as np
import blockmodel
from math import sqrt
from read_matrix import body_matrix, surface_matrix, revert_h_weighting, revert_c_weighting
from scipy.sparse import csr_matrix, diags, vstack
from scipy.sparse.l... |
"""Copyright (c) 2021 <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 rights
to use, copy, modify, merge, publish, distribute, sublicen... |
<gh_stars>1-10
"""
Simulate geomorphic scenarios along with CN production.
"""
from __future__ import division, print_function, unicode_literals
import numpy as np
import scipy.integrate
from cosmogenic import production
def nexpose(n, z, ti, tf=0, p=None, tol=1e-4, thickness=None):
"""
Calculate concentrat... |
import ast
import itertools
import os
import numpy as np
from scipy.stats import gamma
import mapel.elections.models.mallows as mallows
from mapel.elections._glossary import *
from mapel.elections.models.group_separable import get_gs_caterpillar_vectors
from mapel.elections.models.mallows import get_mallows_vectors
f... |
#!/usr/bin/python
import numpy as np
from scipy.integrate import ode
from scipy.stats import norm
from hybmc.models.StochasticProcess import StochasticProcess
# We implement three different approaches to evolve a sqrt-process.
# Details follow Andersen/Piterbarg 2010, sec. 9.5
# Andersen/Piterbarg 2010, Corollary ... |
<reponame>simo955/RecSys_2018<filename>Utils/data/IncrementalSparseMatrix.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on 09/09/2018
"""
import scipy.sparse as sps
class IncrementalSparseMatrix(object):
def __init__(self, auto_create_col_mapper = False, auto_create_row_mapper = False, n_rows ... |
# -*-coding:Utf-8 -*
# Copyright (c) 2013 <NAME>
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# * Redistributions of source code must retain the above copyright notice, this
# list of cond... |
import logging
import argparse
import ast
from collections import OrderedDict
import torch
import os
import scipy
from datetime import datetime
import time
import math
import random
import numpy as np
import sys
import cv2
irange = range
def mylogger(logpath='./param.log'):
logger = logging.getLogger('mylogger')
... |
<filename>mining/try_scipy.py
'''
Created on 2018/04/08
@author: syuu
'''
import numpy as np
from scipy.cluster.hierarchy import linkage, dendrogram
from matplotlib import pyplot
x=np.array([[1,2],[2,1],[3,4],[4,3]])
z=linkage(x,'ward')
dendrogram(z)
pyplot.show() |
<reponame>paulhtremblay/big-data
from bokeh.plotting import figure, show
from bokeh.models import Legend
import numpy as np
from scipy.signal import savgol_filter
def line_historgram():
#positive skew
percent_skew = 50
size = 1000
amount_skew = 4
start = size - int(round(size * percent_skew/100))... |
<gh_stars>10-100
# (c) Copyright IBM Corporation 2020.
# LICENSE: Apache License 2.0 (Apache-2.0)
# http://www.apache.org/licenses/LICENSE-2.0
from statistics import mean
from sklearn.neighbors import NearestNeighbors
from lrtc_lib.active_learning.batch_measure_api import BatchScorerApi
class DiversityCalculator(B... |
# -*- coding: utf-8 -*-
def main():
from math import pi
from cmath import rect
import sys
input = sys.stdin.readline
n = int(input())
x0, y0 = map(int, input().split())
xn2, yn2 = map(int, input().split())
p0 = complex(x0, y0)
pn2 = complex(xn2, yn2)
o = (p0 + pn2) / 2
r... |
from scipy.optimize import fmin_bfgs
from sklearn.base import BaseEstimator, ClassifierMixin, TransformerMixin
from svm_kernels import linear_kernel, polynomial_kernel, rbf_kernel, gaussian_kernel
import numpy as np
import cvxpy as cp
class PlattScaler(TransformerMixin):
'''
Perform Platt Scaling.
Based o... |
<filename>testmanagementserver/lib/dwt_parse.py
#! /usr/bin/env python3
"""
Copyright (c) 2020, ETH Zurich, Computer Engineering Group
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions ... |
"""
Detects Cars in an image using KittiSeg.
Input: Image
Output: Image (with Cars plotted in Green)
Utilizes: Trained KittiSeg weights. If no logdir is given,
pretrained weights will be downloaded and used.
Usage:
python demo.py --input_image data/demo.png [--output_image output_image]
[--logdir /pa... |
# -*- coding: utf-8 -*-
"""
Created on Thu Apr 16 20:52:06 2020
@author: Nicolai
"""
from ITestbenchBase import ITestbenchBase
import numpy as np
import scipy.integrate as integrate
import time
import psutil
import gc
class CiPdeBase(ITestbenchBase):
"""
Abstract class that implements the ITestbenchBase inte... |
<reponame>tychon/physics
# This module gives easy access to fitting functions and supports
# the quantities module.
import inspect
import numpy as np
import numpy.random as random
import quantities as pq
import scipy.optimize as opt
import scipy.odr as odr
import scipy.stats as stats
from physics.fmt import fmtquan... |
<reponame>nameforjoy/Synchronisation
"""
NetworkClasses
@author: JoyClimaco
"""
import numpy as np
from scipy.integrate import odeint
from odeintw import odeintw
class StuartLandau(object):
""" Class defining a Stuart-Landau network object.
Holds the most important network properties of a network fo... |
# Computation of normalized anomalies using JRA-55
# <NAME>, <NAME>
# Klimamodelle SS19
# version: 2019-07-23
#
# data:
# /home/srvx11/lehre/users/a1127897/JRA-55/mslp_daily rh_daily spfh_daily
#
# execute:
# python3 01-NormalizedAnomalies.py
# python3 01-NormalizedAnomalies.py --ifile1 "mslp_daily/anl_surf125.002... |
import matplotlib.pyplot as plt
import matplotlib as mpl
import numpy as np
import h5py
import os
from glob import glob
import argparse
from scipy import ndimage
plt.close('all')
mpl.rcParams['pdf.fonttype'] = 42
mpl.rcParams['font.size'] = 12
mpl.rcParams['axes.linewidth'] = 2
mpl.rcParams['xtick.major.width'] = 2
mp... |
<reponame>mwhchen/quantecon<gh_stars>10-100
# -*- coding: utf-8 -*-
"""
Created on Sun Feb 22 10:47:42 2015
@author: dgevans
"""
import numpy as np
from scipy.interpolate import UnivariateSpline
class interpolate_wrapper(object):
'''
Wrapper to interpolate vector function
'''
def __init__(self,F):
... |
<reponame>bhaney/graph_embeddings<filename>gembed/embedding_models/rgcn_node_classification.py
# Based primarily on https://github.com/tkipf/relational-gcn/blob/master/rgcn/train.py
# From <NAME>'s relational-gcn repo
from __future__ import print_function
import pickle, os, random
import numpy as np
import scipy as sp... |
from copy import copy
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
from scipy import linalg as LA
from scipy.sparse import linalg as las
from scipy.signal import lti
from scipy.signal import lsim
from opentorsion.disk_element import Disk
from opentorsion.shaft_element import Shaft
from opentors... |
<reponame>mad-lab-fau/SMARTurinalysis<filename>color_analysis.py<gh_stars>0
import math
import os
import cv2
import numpy as np
import scipy.signal
from matplotlib import cm
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from numpyencoder import NumpyEncoder
from helper import color_calc... |
<reponame>aerial-defence/pytak<gh_stars>0
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Python Team Awareness Kit (PyTAK) Module Tests."""
import asyncio
from cmath import isnan
import enum
import inspect
import urllib
from unittest import mock
import pytest
import pytak
__author__ = '<NAME> W2GMD <<EMAIL>>'... |
<reponame>EliotDucky/AC2XFLR<filename>AC2XFLR.py
from scipy.integrate import quad
import xml.etree.ElementTree as el
from matplotlib import pyplot as plt
import numpy as np
import os.path as os_p
from os import makedirs
import math
def createSimpleKVP(key, txt, parent):
elem = el.Element(key)
elem.text = txt
parent... |
<filename>Scripts/best_March2012six.py
"""
*Script Reads and Plots Leaf,Bloom,Freeze Data from 1880-2013*
"""
from netCDF4 import Dataset
import numpy as np
from scipy.stats import nanmean
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
import matplotlib.colors as c
plt.rc('text',usetex=True)
... |
"""
Authors: <NAME>, <NAME>
These are the functions for creation of encodings for TADs and chromosomes
"""
#Dependencies
import itertools
import numpy as np
from scipy.spatial.distance import pdist
def flatten(list_):
### flattens one layer of a list. For example, [[0,1],[2,3],[4,[5,6]]] will become [0,1,2,3,4,[5... |
<filename>bmm/src/inference/parameters.py
########################################################################################################################
# Module: inference/parameters.py
# Description: Expectation maximisation to infer maximum likelihood hyperparameters.
#
# Web: https://github.com/SamDuffiel... |
<reponame>lixiaoyu0575/physionet_challenge2020_pytorch
import sys
import pandas as pd
import numpy as np
import scipy.io as scio
import os
import wfdb
from scipy import signal
import csv
import pywt
def WTfilt_1d(sig):
coeffs = pywt.wavedec(data=sig, wavelet='db5', level=9)
cA9, cD9, cD8, cD7, cD6, cD5, cD4, cD... |
<filename>Without_DL_framework/opti_adam.py
import numpy as np
import matplotlib.pyplot as plt
import h5py
import scipy.io
import math
import sklearn
import sklearn.datasets
def init_adam(parameters) :
L = len(parameters) // 2 # number of layers
v = {} # the exponentially weighted average of the gradient
... |
<filename>exps/thermo_final_exp.py<gh_stars>0
import sys
sys.path.append("..")
import json
import numpy as np
import math
from typing import Dict, List, Tuple
import copy
from itertools import combinations
from collections import Counter
from statistics import median
import logging
from datetime import timedelta
fro... |
import os
import numpy as np
import sklearn.metrics as METRICS ;
from collections import OrderedDict
try:
import cPickle as pickle
except:
import pickle
import TEESDocumentHelper;
import ProjectRunner;
import FeatureGeneration as FeGen
import GeneralFunctions as GF
import SharedFunctions as SF
class TS... |
import pandas as pd
import matplotlib.pyplot as plt
import scipy.stats
def draw_plot():
# Read data from file
# df=pd.read_csv("epa-sea-level.csv")
currDir = ""
for aa in __file__.split("/")[:-1]:
currDir = currDir + aa + "/"
try:
print("Reading file ", currDir + "epa-sea-level.csv")... |
""" Core S4 convolution kernel implementing the 'normal plus low-rank' algorithm.
The main module is SSKernelNPLR, which stores parameters A, B, C, dt, and calling it creates the SSM convolution kernel bar{K}.
A much simpler version SSKernelSlow is included for illustration purposes: it has the same output, but uses ... |
import os, re
import basic_file_ops
#from numpy import array, zeros, ones
class txt_file(object):
def readfile(self, pathin, strip=False, rstrip=True):
return basic_file_ops.readfile(pathin, strip=strip, rstrip=rstrip)
def writefile(self, pathin, listin=None, append=False):
if listin is None... |
<gh_stars>1-10
"""Some basic routines for working with the force sensors."""
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import linregress
from scipy.interpolate import CubicSpline
import sys
from calibrations import force_sensors as FORCE_SENSORS
def plot_force_sensor(sensor_id):
"""Gene... |
<gh_stars>10-100
import math
import logging
from random import random, randint, choices, seed
import itertools
import numpy as np
from scipy.spatial import cKDTree
from skimage.transform import integral_image, integrate
from gunpowder.batch_request import BatchRequest
from gunpowder.coordinate import Coordinate
from g... |
<filename>Chapter04/EMOTION_CNN/Python 2.7/EmotionDetectorUtils.py
import pandas as pd
import numpy as np
import os, sys, inspect
from six.moves import cPickle as pickle
import scipy.misc as misc
IMAGE_SIZE = 48
NUM_LABELS = 7
VALIDATION_PERCENT = 0.1 # use 10 percent of training images for validation
IMAGE_LOCATION... |
#!/usr/bin/env python
#
# (c) 2015-2018, ETH Zurich, Institut fuer Theoretische Physik
# Author: <NAME> <<EMAIL>>
"""
Helper module wrapping scipy.sparse matrix types to make them
convertible directly to numpy arrays by implementing the __array__
method.
"""
import scipy.sparse as sp
class ArrayConvertible:
"""
... |
import argparse
import glob
import itertools
import os
import random
import numpy as np
import pandas as pd
from scipy.stats import ttest_ind, kendalltau
def parse_argument() -> argparse.Namespace:
"""
Parse input arguments.
"""
parser = argparse.ArgumentParser()
parser.add_argument(
'--... |
<filename>magpylib/_src/obj_classes/class_BaseTransform.py
"""BaseTransform class code
DOCSTRING v4 READY
"""
# pylint: disable=protected-access
import numbers
import numpy as np
from scipy.spatial.transform import Rotation as R
from magpylib._src.input_checks import check_degree_type
from magpylib._src.input_checks ... |
<gh_stars>1-10
import unittest
from typing import Callable, Optional, Tuple
import numpy as np
import tensorflow as tf
from scipy.stats import random_correlation, multivariate_normal
from pilco.controllers import squash_sin, squash_cum_normal
class TestSquash(unittest.TestCase):
def test_sin_squash(self):
... |
import regex as re
import operator
import numpy as np
from scipy import sparse
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.base import BaseEstimator, ClassifierMixin
from sklearn.utils.validation import check_X_y, check_is_fitted
from sklearn.linear_model import LogisticRegression
from skle... |
import numbers
from collections import Iterable
import warnings
from .lti import LinearTimeInvariant, _pickup_dt
from .exception import *
import numpy as np
import sympy as sym
# TODO: trans function of MIMO
__all__ = ["TransferFunction", "tf", "zpk"]
class TransferFunction(LinearTimeInvariant):
"""
a clas... |
<reponame>SimonCqk/mars
# Copyright 1999-2020 Alibaba Group Holding Ltd.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... |
<filename>src/data_visualization/visualize_price_distribution_of_airbnb_rentals_kdeplot.py
# -*- coding: utf-8 -*-
"""
------ What is this file? ------
This script targets one file:
- istanbul_airbnb_processed.csv
The script produces histograms for the distribution of Airbnb
prices in the city of Istanbul.
... |
# -*- coding: utf-8 -*-
import pandas as pd
import numpy as np
from scipy.integrate import simps
def transfer_fuction(xplane2dec,control_DATA,flight_data_for_integrate):
Phi_sp = control_DATA[1]*180
Theta_sp = control_DATA[0]*180
Psi_sp = control_DATA[2]*180
h_sp = 300
sp_array = np.asarray([Phi_s... |
from Statistics.Mean import mean
from Calculator.Subtraction import subtraction
import scipy.stats as st
import numpy as np
def ConfidenceInterval(Data, ConfidenceLevel):
# Uses T distribution for under 30
if len(Data) < 30:
DegreesOfFreedom = subtraction(len(Data), 1)
DataMean = mean(Data)
... |
<gh_stars>0
#!/usr/bin/python
'''
mjtsai1974@20180606, v1.0, MLE for https://mjtsai1974.github.io/DevBlog/2018/06/06/bayesian-ml-beyes-to-practice/
http://www.astroml.org/book_figures/chapter3/fig_gaussian_distribution.html
dist = scipy.stats.norm(...)
Where ... should be filled in with the desired distribution par... |
#!/usr/bin/env python3
# Author: <NAME>
from __future__ import division
from __future__ import absolute_import
import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import fsolve, brentq
# dummies function for testing
def function_f(x, *args):
return np.sin(x + 1.)
def function_g(x):
re... |
<reponame>tp5uiuc/kinematic_snake
import numpy as np
from numpy.testing import assert_allclose
from scipy.integrate import trapz
import pytest
from kinematic_snake.kinematic_snake import zero_mean_integral, project, KinematicSnake
class TestZeroMeanIntegral:
@pytest.fixture(scope="class", params=[101, np.random.... |
# This file is part of libigl, a simple c++ geometry processing library.
#
# Copyright (C) 2017 <NAME> <<EMAIL>> and <NAME> <<EMAIL>>
#
# This Source Code Form is subject to the terms of the Mozilla Public License
# v. 2.0. If a copy of the MPL was not distributed with this file, You can
# obtain one at http://mozilla.... |
<reponame>cleverhans-lab/capc-iclr
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import getpass
import argparse
import numpy as np
import os
import pickle
import random
import scipy.stats
import sys
import torch
import torch.nn as nn
import torch.nn.funct... |
<reponame>tskisner/redmonster
# Use chi2 surfaces from zfinder.py to choose and classify objects on each fiber. Each zfind
# argument is the ENTIRE object created by ZFinder for a single template, and each zfit argument
# is the ENTIRE object created by ZFitter for a single template. Zfiti must correspond with
# zfind... |
<filename>tests/test_buildings.py
from unittest.case import expectedFailure
import numpy as np
import sys
from fractions import Fraction
sys.path.append("..")
from SimFactoryPy.simulation.Logistics import ConveyorBelt
from SimFactoryPy.simulation.Buildings import Miner, Constructor
from SimFactoryPy.simulation.entities... |
<reponame>paulmorio/adventofcode
"""
Solution for Day 6 Part 1
"""
from collections import defaultdict
from scipy.spatial.distance import cityblock
import numpy as np
data_fp = "data.txt"
coordinates = []
max_x = 500
max_y = 500
with open(data_fp, "r") as df:
lines = df.readlines()
for line in lines:
x, y = line.... |
<gh_stars>0
from sympy import *
from prettytable import PrettyTable, ALL
circle = PrettyTable(["Degree", "Radian", "sin()", "cos()"])
circle.hrules = ALL
for deg in [0,30,45,60,90,120,135,150,180,210,225,240,300,315,330]:
rad = Rational(deg, 180) * pi
circle.add_row([deg, pretty(rad), pretty(sin(rad)), pretty... |
import os
import itertools
import numpy as np
from PIL import Image
import torch
from torch.utils.data import Dataset
from glob import glob
import random
import scipy.misc
class ref_dataset(Dataset):
def __init__(self,
root,
transform=None,
target_transform=None,... |
"""
********************************************************************************
Attitude Estimation with an IMU - Example
********************************************************************************
Goal of this script:
- applying the UKF for estimating 3D attitude from an IMU.
*We assume the reader is alrea... |
"""
Module: LMR_psms.py
Purpose: Module containing methods for various Proxy System Models (PSMs)
Adapted from LMR_proxy and LMR_calibrate using OOP by <NAME>
Originator: <NAME>, U. of Washington
Revisions:
- Use of new more efficient "get_distance" function to calculate the
distance ... |
<gh_stars>10-100
# -*- coding: utf-8 -*-
# Copyright 2019 <NAME>
#
# 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... |
#!/usr/bin/env python
"""
author: <NAME>
revised by: <NAME> (<EMAIL>)
"""
import sys
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import cv2
import numpy as np
from keras import backend as K
from scipy.stats import truncnorm, norm
from basics import *
from FeatureExtraction import *
import colle... |
#!/usr/bin/env python3
# awkwardly need to use python3 for this single file because of the package statsmodels!
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import os
import sys
import warnings
import scipy
import statsmodels.api as sm
from statsmodels.nonparametric import _smoothers_lowess a... |
from __future__ import division
import numpy as np
import math
import random
from scipy.spatial import Delaunay
from copy import copy
def randommap(rows, cols):
'''terribly coded random-height-map generator, takes # of rows and cols as input as well as the minimum and maximum height for starting the randomization... |
import random
import numpy as np
import scipy.sparse as sp
import torch
import torch.nn.functional as F
import grb.utils as utils
from grb.attack.base import InjectionAttack
from grb.evaluator import metric
class FGSM(InjectionAttack):
def __init__(self,
epsilon,
n_epoch,
... |
# -*- coding: utf-8 -*-
"""
Created on Wed Jul 24 10:27:06 2019
This code creates a class DBR that represents a reflection experiment on a porous DBR.
The reflection is modelled using the transfer matrix model given structural information about the DBR.
The model is capable of simulating graded interfaces between the ... |
"""
Authors: <NAME>, <NAME> and <NAME>
All rights reserved, 2017.
"""
__all__ = ['solid_harmonic_filter_bank']
import numpy as np
from scipy.special import sph_harm, factorial
from .utils import get_3d_angles, double_factorial, sqrt
def solid_harmonic_filter_bank(M, N, O, J, L, sigma_0, fourier=True):
"""
... |
<reponame>dhroth/count_quasars<filename>getMags.py
from __future__ import print_function, division
import os
import sys
from matplotlib import pyplot as plt
import lsst.sims.photUtils.Bandpass as Bandpass
import lsst.sims.photUtils.Sed as Sed
import scipy.integrate as integrate
import numpy as np
import config
def g... |
<gh_stars>0
# Copyright 2019 The Cirq Developers
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... |
# The particle filter, prediciton and correction.
# In addition to the filtered particles, the density is estimated. In this
# simple case, the mean position and heading is computed from all particles.
#
# slam_08_c_density_estimation.
# <NAME>, 04.01.2013
from lego_robot import *
from slam_e_library import get_... |
<reponame>krematas/scannerapps
import soccer.calibration.utils as utils
import numpy as np
from os.path import join
import cv2
import matplotlib.pyplot as plt
data_path = '/home/krematas/Mountpoints/grail/data/Singleview/Soccer/'
path_to_field3d = join(data_path, 'field.ply')
vertex_data, _, _, _ = utils.read_ply(pa... |
<filename>lib/priors.py
'''A module that contains a prior class that can be used with emcee
(it has to be pickleable)'''
import numpy as np
from scipy.special import gamma as Gamma
import os
class Uninformative:
'''Uninformative prior. Trivial.'''
def __call__(self, value):
return 0.0
class STAN:
'''A... |
# -*- coding:utf-8 -*-
#
# Copyright (C) 2019-2021, Saarland University
# Copyright (C) 2019-2021, <NAME> <<EMAIL>>
from __future__ import annotations
import dataclasses as d
import typing as t
import abc
import decimal
import enum
import fractions
import math
import warnings
from . import errors, operators, types
... |
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
# bisher: Berechnung der Schallgeschwindigkeit über unsere Messung mit v_0 und bestimmten lambda
# zudem: Import der ganzen daten mitte... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.