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<reponame>rvbcldud/sympy """ Finite Discrete Random Variables - Prebuilt variable types Contains ======== FiniteRV DiscreteUniform Die Bernoulli Coin Binomial BetaBinomial Hypergeometric Rademacher IdealSoliton RobustSoliton """ from sympy.core.cache import cacheit from sympy.core.function import Lambda from sympy.c...
<gh_stars>1-10 #!/usr/bin/env python2 # -*- coding: utf-8 -*- from tqdm import tqdm import datetime import argparse import matplotlib.pyplot as plt import math import scipy import torch from torch.autograd import Variable import sys import os import torch from utils.utils import * import torch.optim as optim import tor...
<reponame>tesslerc/H-DRLN<filename>graying_the_box/smdp.py import numpy as np import scipy.linalg def divide_tt(X, tt_ratio): N = X.shape[0] X_train = X[:int(tt_ratio*N)] X_test = X[int(tt_ratio*N):] return X_train, X_test class SMDP(object): def __init__(self, labels, termination, rewards, value...
<filename>uncertify/evaluation/statistics.py from collections import defaultdict import logging from scipy.stats.kde import gaussian_kde import torch from torch import nn from torch.utils.data import DataLoader import numpy as np import pandas as pd from uncertify.evaluation.entropy import get_entropy from uncertify....
import ctypes from numba.extending import get_cython_function_address import numba import binom import numpy as np from common import Models from scipy import LowLevelCallable import util # TODO: Can I just replace this with `util.lbeta`? Would it be faster / less bullshit? def _make_betainc(): addr = get_cython_fun...
"""Header here.""" import numpy as np import scipy.stats as sps from base.utilities import postsampler import copy """ ############################################################################## ############################################################################## ###################### THIS BEGINS THE RE...
import numpy as np import matplotlib.pyplot as plt from scipy.optimize import minimize, leastsq def linear_fit(args, x, y, num): m, b = args fit = m*x+b#b * x**m return np.nansum((y-fit)**2/num**2) def linear(args, x): m, b = args fit = m*x+b#b * x**m return fit def power_law(args, x): ...
<filename>chi_sq.py #!/usr/bin/env python # classification in presence of imbalance and overlap # matching the variable names as in the corresponding R code import os, sys, pickle import numpy as np from sklearn.decomposition import PCA from scipy.stats import gamma from scipy.special import beta def main(): if ...
# -*- coding: utf-8 -*- """ Tests for abagen.correct module """ import itertools import numpy as np import pandas as pd import pytest import scipy.stats as sstats from abagen import allen, correct, io from abagen.utils import flatten_dict @pytest.fixture(scope='module') def donor_expression(testfiles, atlas): ...
# MIT License # # Copyright (c) 2017 <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, publi...
import math from scipy.special import logsumexp def logsumexp_list(lst): while len(lst)>1: a = lst.pop(0) b = lst.pop(0) c = b + math.log10(math.exp(a - b) + 1) lst.insert(0,c) return lst[0] def forward(X): K = 2 F0_1 = [] F0_2 = [] E = [[1/6,1/6,1/6,1/6,1/6,1/6...
<reponame>Mirwaisse/pytorch_geometric import torch import scipy.sparse import networkx as nx import torch_geometric.data from .num_nodes import maybe_num_nodes def to_scipy_sparse_matrix(edge_index, edge_attr=None, num_nodes=None): r"""Converts a graph given by edge indices and edge attributes to a scipy spa...
<filename>hedp/tests/test_plasma_physics.py #!/usr/bin/python # -*- coding: utf-8 -*- # Copyright CNRS 2012 # <NAME> (LULI) # This software is governed by the CeCILL-B license under French law and # abiding by the rules of distribution of free software. import numpy as np from numpy.testing import assert_allclose impo...
import numpy as np import matplotlib.pyplot as plt from scipy import stats # Folsom annual inflow data # summary statistics, histogram, QQ plot annQ = np.loadtxt('data/folsom-annual-flow.csv', delimiter=',', skiprows=1, usecols=[1]) N = len(annQ) m = np.mean(annQ) s = np.std(annQ) g = stats.skew(annQ) # print('Mean...
<reponame>yuankailiu/isce2 #!/usr/bin/env python3 #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # Copyright 2014 California Institute of Technology. ALL RIGHTS RESERVED. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compli...
#!/usr/bin/env python3 # -*- coding: utf-8 -*- import numpy as np import scipy.stats as st import seaborn as sns import matplotlib.pyplot as plt from arpym.statistics.meancov_sp import meancov_sp from arpym.tools.plot_ellipse import plot_ellipse from arpym.tools.histogram_sp import histogram_sp def invariance_test_...
<filename>sympy/core/decorators.py """ SymPy core decorators. The purpose of this module is to expose decorators without any other dependencies, so that they can be easily imported anywhere in sympy/core. """ from __future__ import print_function, division from functools import wraps from .sympify import SympifyErro...
<reponame>tarment10/CoolProp import numpy as np import matplotlib.pyplot as plt import CoolProp, scipy.optimize class CurveTracer(object): def __init__(self, backend, fluid, p0, T0): """ p0 : Initial pressure [Pa] T0 : Initial temperatrure [K] """ self.P = [p0] sel...
from ..algorithms.base import Algorithm from ..algorithms.action_selection import MaxActionSelector, SoftmaxActionSelector from .dynamic_programming import ValueIteration, solve_value_iteration from .mcts import MCTS_next_node, get_actions_states from ..mdp import MDP import numpy as np from numba import njit from fast...
<reponame>bpinsard/nipy # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*- # vi: set ft=python sts=4 ts=4 sw=4 et: """ Utilities for extracting masks from EPI images and applying them to time series. """ from __future__ import absolute_import import math # Major scientific libraries imports imp...
#!/usr/local/bin/python3 ###!/Users/zhiyang/anaconda3/bin/python3 """ This Python script is written by <NAME> to perform miscellaneous tasks in analyzing data. Synopsis: Perform miscellaneous tasks in data analysis. To-Do List: + Add information for statistics regarding: - accuracy - precision Revisi...
# # DCP product code # # (C) Copyright 2015-2016 Dataculture Analytics Company # All right reserved. # # This file is confidential and NOT open source. Do not distribute. # """ A collection of miscellaneous utility functions. """ import pandas as pd def colnames(filename, **kwargs): """ Read the column na...
import torch from torch.utils import data import json import os import numpy as np import soundfile as sf import scipy.io.wavfile EPS = 1e-8 DATASET = 'WHAM' # WHAM tasks enh_single = {'mixture': 'mix_single', 'sources': ['s1'], 'infos': ['noise'], 'default_nsrc': 1} enh_both ...
##################################################### # # 20 October 2009 # <NAME> # University of California, San Diego # <EMAIL> # # This script performs symbolic Hermite-Simpson # integration on a vector field given in the text file # equations.txt, takes the Jacobian and Hessian of the # vector field, and s...
<filename>SNDATA_ADDONS/snsedextend.py #! /usr/bin/env python #S.rodney # 2011.05.04 """ Extrapolate the Hsiao SED down to 300 angstroms to allow the W filter to reach out to z=2.5 smoothly in the k-correction tables """ import os from numpy import * from pylab import * sndataroot = os.environ['SNDATA_ROOT'] MINWAV...
<gh_stars>1-10 from emlp.reps import V,T,Rep from emlp.groups import Z,S,SO,Group from scipy.spatial.transform import Rotation import jax.numpy as jnp import numpy as np class PseudoScalar(Rep): is_regular=False def __init__(self,G=None): self.G=G self.concrete = (self.G is not None) def __...
import os os.chdir('MERFISH_Moffit/') import numpy as np import pandas as pd import pickle import matplotlib matplotlib.use('qt5agg') matplotlib.rcParams['pdf.fonttype'] = 42 matplotlib.rcParams['ps.fonttype'] = 42 import matplotlib.pyplot as plt import scipy.stats as st with open ('data/SpaGE_pkl/MERFIS...
<gh_stars>10-100 # https://github.com/keithito/tacotron/blob/master/util/audio.py # https://github.com/carpedm20/multi-speaker-tacotron-tensorflow/blob/master/audio/__init__.py # I only changed the hparams to usual parameters from oroginal code. import numpy as np from scipy import signal import librosa.filters import...
from rdkit import Chem import pandas as pd import matplotlib.pyplot as plt from tqdm import tqdm import os import numpy as np from scipy import stats import pickle import random from multiprocessing import Pool import time """ Create a list of mol representations (from rdkit) from a list of smarts strings Note: al...
import numpy as np from scipy.linalg import expm, eigvals import matplotlib.pyplot as plt from numpy.random import normal from math import sin, pi, cos, sqrt try: from dynamic_graph.sot.torque_control.utils.plot_utils import * except: print "Failed to load plot-utils" class Robot: def __init__(self, omega,...
<gh_stars>0 import sys import time import os import gc import numpy as np import matplotlib.pyplot as plt import matplotlib.cm as cm from scipy.signal import argrelextrema import majoranaJJ.modules.SNRG as SNRG import majoranaJJ.modules.finders as finders import majoranaJJ.modules.checkers as check import majoranaJJ.m...
<gh_stars>0 """Define distributions from which to get random numbers.""" import numpy as np import math from scipy.stats import truncnorm import frbpoppy.precalc as pc from scipy.integrate import odeint def schechter(low, high, power, shape=1): """ Return random variables distributed according to Schechter lu...
import itertools import copy from enum import Enum import numpy as np import scipy.misc as spmisc from matplotlib.colors import BoundaryNorm import matplotlib.cm as cm from matplotlib.patches import Rectangle __all__ = ['Bunch', 'ChannelMap', 'get_electrode_map'] NonSignalChannels = Enum('NonSignalChannels', ['grou...
<reponame>timgates42/imbalanced-learn<filename>imblearn/under_sampling/_prototype_selection/_edited_nearest_neighbours.py<gh_stars>1-10 """Class to perform under-sampling based on the edited nearest neighbour method.""" # Authors: <NAME> <<EMAIL>> # <NAME> # <NAME> # License: MIT from collections im...
import numpy as np from scipy import signal from gpitch import windowed def frame(y, window_size, overlap, fs): x_b, y_b = windowed.balance_data_size(y, window_size, overlap, fs) new_n = x_b.shape xout = [] yout = [] n = x_b.size l = (window_size - overlap) nw = (n - overlap) / l for i...
<gh_stars>1-10 import re import pandas as pd from collections import defaultdict from scipy.spatial.distance import cosine def group_by_scale(labels): """ Utility that groups attribute labels by time scale """ groups = defaultdict(list) # Extract scales from labels (assumes that the scale is given by the l...
<gh_stars>0 """ The MIT License (MIT) Copyright (c) 2016 <NAME> (Stanford University) 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 ...
<filename>modules/delay_spectrum.py from __future__ import division import numpy as NP import multiprocessing as MP import itertools as IT import statsmodels.robust.scale as stats import progressbar as PGB import writer_module as WM import aipy as AP import astropy from astropy.io import fits import astropy.cosmology ...
# -*- coding: utf-8 -*- """ Created on 2021/12/14 21:10:08 @File -> mutual_info.py @Author: luolei @Email: <EMAIL> @Describe: 互信息和条件互信息计算 """ from scipy.special import psi import pandas as pd import numpy as np from . import DTYPES from . import preprocess_values, deter_k, build_tree, query_neighbors_dist from .e...
<filename>cube-builder-aws/cube_builder_aws/utils/builder.py import numpy import datetime import rasterio from datetime import timedelta from dateutil.relativedelta import relativedelta from numpngw import write_png from scipy import ndimage as ndi ############################# def get_date(str_date): return date...
<filename>src/voice_synthesis/inference/inference.py ## 기본 라이브러리 Import import sys import numpy as np import torch import os import argparse ## WaveGlow 프로젝트 위치 설정 sys.path.append('waveglow/') ## Tacontron2 프로젝트 위치 설정 sys.path.append('tacotron2/') ## 프로젝트 라이브러리 Import from hparams import defaults from model import Ta...
# metal_binding_classifier import os #os.environ['CUDA_VISIBLE_DEVICES'] = '0' #import the tools import torch import torch.nn as nn import torch.nn.functional as F import torch.optim as optim from torch.optim import lr_scheduler from torch.utils.data.dataset import Dataset from torch.utils.data import DataLoader, Wei...
import random import logging import numpy as np import scipy import scipy.ndimage import scipy.interpolate import torch # A sparse tensor consists of coordinates and associated features. # You must apply augmentation to both. # In 2D, flip, shear, scale, and rotation of images are coordinate transformation # color j...
from warnings import warn import autograd.numpy as np import autograd.numpy.random as npr from autograd.scipy.special import logsumexp from autograd.scipy.linalg import block_diag from autograd import grad from scipy.optimize import linear_sum_assignment, minimize from scipy.special import gammaln, digamma, polygamma...
<filename>code_experiments/select_valid_range.py from scipy import misc import os import fnmatch import numpy as np import matplotlib.pyplot as plt from scipy import ndimage from scipy import signal from tqdm import tqdm import pickle # %matplotlib inline ##############################################################...
<reponame>webclinic017/qf-lib<filename>qf_lib/common/utils/returns/beta_and_alpha.py # Copyright 2016-present CERN – European Organization for Nuclear Research # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may...
<filename>bayesian_privacy_accountant.py #!/usr/bin/env python3 # Author: <NAME> # Date: 12 August 2020 import itertools import numpy as np import scipy as sp import torch import warnings from scipy.stats import t, binom from scipy.special import logsumexp from scaled_renyi import scaled_renyi_gaussian class...
<reponame>GirZ0n/Methods-of-Computation from enum import Enum from sympy.parsing.sympy_parser import ( convert_xor, function_exponentiation, implicit_application, implicit_multiplication, split_symbols, standard_transformations, ) TRANSFORMATIONS = standard_transformations + ( split_symbol...
<reponame>jessestewart1/nrn-rrn import calendar import geopandas as gpd import logging import networkx as nx import numpy as np import pandas as pd import pyproj import shapely.ops import string import sys from collections import Counter, defaultdict from datetime import datetime from itertools import chain, combinatio...
<reponame>zisluiz/FCN.tensorflow<filename>evaluation.py import tensorflow as tf import numpy as np import scipy.misc as misc import os def _transform(filename, __channels): image_options = {'resize': True, 'resize_size': 224} image = misc.imread(filename, flatten=False if __channels else True, mode='RGB' if __...
<gh_stars>0 # -*- coding: utf-8 -*- """ Spyder Editor This is a temporary script file. """ import pandas as pd import numpy as np from scipy import stats import csv import matplotlib.pyplot as plt import matplotlib.path as path import seaborn as sns import tkinter as tk from tkinter import ttk from sklearn.model_sele...
#!/usr/bin/env python2 # -*- coding: utf-8 -*- """Main module.""" import xarray as xr import numpy as np from scipy import signal from functools import partial # Wrap it into a simple function def season_mean(ds, calendar='standard'): # Make a DataArray of season/year groups year_season = xr.DataArray(ds.time...
<gh_stars>10-100 import osqp import numpy as np import scipy as sp import scipy.sparse as sparse import time # Discrete time model of the system (mass point with input force and friction) # Constants # Ts = 0.2 # sampling time (s) M = 2 # mass (Kg) b = 0.3 # friction coefficient (N*s/m) Ad = sparse.csc_matrix([ ...
from functools import wraps from pathlib import Path from typing import Union import numpy as np from spikeextractors.extraction_tools import cast_start_end_frame from tqdm import tqdm try: import h5py HAVE_H5 = True except ImportError: HAVE_H5 = False try: import scipy.io as spio HAVE_Scipy = ...
""" thouless_anderson_palmer.py --------------------- Reconstruction of graphs using a Thouless-Anderson-Palmer mean field approximation author: <NAME> email: <EMAIL> submitted as part of the 2019 NetSI Collabathon """ from .base import BaseReconstructor import numpy as np import networkx as nx import scipy as sp from...
# Mostly based on the code written by <NAME>: # https://github.com/mrharicot/monodepth/blob/master/utils/evaluation_utils.py import numpy as np import torch.utils.data as data from path import Path from scipy.misc import imresize, imread from tqdm import tqdm import random class pose_framework_KITTI(data.Data...
<filename>HW1/gibbs_sampling/gibbs_samplers.py import numpy as np import scipy.stats as st import matplotlib.pyplot as plt from gibbs_sampling.sampling_functions import * from gibbs_sampling.initialization import * def log_joint(data, theta_s, z_s, beta_mean_s, beta_sigma_s, theta_p, beta_mean_p, beta_sigma_p): t...
"""Based on: https://github.com/mbinkowski/MMD-GAN/blob/678bb5e2d5f7b0bb8dd5c3591d7759e1bb3f8018/gan/compute_scores.py BSD 3-Clause License Copyright (c) 2016, <NAME> All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following condit...
""" =========================================================================== Modelize the static and dynamic behaviour ok an orienteering compass in the Earth magnetic field Every parameters are in international system units, angles in radians =========================================================================...
''' A set of classes that implement analytical responses to simple systems (mainly used in testing the discrete cases). ''' from __future__ import division, unicode_literals, print_function, absolute_import from future import standard_library standard_library.install_aliases() from builtins import object import warnin...
from __future__ import print_function import nltk import random #from nltk.corpus import movie_reviews from nltk.classify.scikitlearn import SklearnClassifier import pickle from sklearn.naive_bayes import MultinomialNB, BernoulliNB from sklearn.linear_model import LogisticRegression, SGDClassifier from sklearn.svm impo...
# -*- coding: utf-8 -*- """'Current Source Density analysis (CSD) is a class of methods of analysis of extracellular electric potentials recorded at multiple sites leading to estimates of current sources generating the measured potentials. It is usually applied to low-frequency part of the potential (called the Local F...
<gh_stars>0 import scipy.stats as ss def compute_ranking_correlation(pseudotime1, pseudotime2): kt = ss.kendalltau(pseudotime1, pseudotime2) weighted_kt = ss.weightedtau(pseudotime1, pseudotime2) sr = ss.spearmanr(pseudotime1, pseudotime2) return {"kendall": kt, "weighted_kendall": weighted_kt, "spear...
<reponame>CHuanSite/Dutl import numpy as np from scipy.spatial import distance_matrix def probDistance(x, sigma_est = True): ''' Embed data into probabilistic distance matrix ''' x = np.array(x) if sigma_est == True: sigma = np.mean(np.std(x, 0)) else: sigma = 1 dist = dis...
<filename>app.py # app.py import json import joblib import os import numpy as np import pandas as pd from flask import Flask, request, send_file from pathlib import Path from scipy.spatial import distance from sklearn.tree import export_text app = Flask(__name__) with open(os.path.join('models', 'ansible', 'metadata...
from __future__ import print_function, division, absolute_import import numpy as np from scipy import optimize as sciopt from Bio import Phylo from treetime import config as ttconf from treetime import MissingDataError,UnknownMethodError,NotReadyError from .utils import tree_layout from .clock_tree import ClockTree re...
import pandas as pd import numpy as np from scipy.stats import chisquare class QuestionDependence: """ Checks if there is any association between single/multiple choice questions in a survey. Uses chi square test for independence. Parameters ---------- path : str Path to a csv file co...
<filename>pymc3_hmm/utils.py<gh_stars>0 from typing import Any, Callable, Dict, List, Optional, Sequence, Text, Tuple, Union import matplotlib.pyplot as plt import numpy as np import pandas as pd import theano.tensor as tt from matplotlib import cm from matplotlib.axes import Axes from matplotlib.colors import Colorma...
##Here we plot distributrions of how many individuals were correct for each states. import seaborn as sns import matplotlib.pyplot as plt import numpy as np from scipy.stats import gaussian_kde pal = sns.diverging_palette(10, 220, sep=80, n=5,l=40,center='light') pal2 = sns.diverging_palette(10, 220, sep=80, n=5,l=40,...
<reponame>Childhoo/Chen_Matcher import numpy as np import matplotlib.pyplot as plt from copy import deepcopy from scipy.spatial.distance import cdist from numpy.linalg import inv from scipy.linalg import schur, sqrtm import torch from torch.autograd import Variable ##########numpy def invSqrt(a,b,c): eps = 1e...
from termcolor import colored as color import statistics import math from scipy import stats import matplotlib.pyplot as plt import pylab def getStats (samble_means): variance = statistics.variance(samble_means) mean = statistics.mean(samble_means) stdev = statistics.stdev(samble_means) confidence = ...
<gh_stars>10-100 import numpy as np import scipy as scp from numpy import pi def calculate_exvolume_redfactor(): """ Calculates DEER background reduction factor alpha(d) See Kattnig et al J.Phys. Chem. B, 117, 16542 (2013) https://doi.org/10.1021/jp408338q The background reduct...
######################################################################## # Required packages ######################################################################## import argparse import sys import os import pandas as pd import numpy as np from tqdm.auto import tqdm import tomotopy as tp from pyteomics import mgf, au...
<filename>eye_blink_detector_dlib4.py<gh_stars>0 import os,sys import cv2 import dlib from imutils import face_utils from scipy.spatial import distance cap = cv2.VideoCapture(0) face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_alt2.xml') face_parts_detector = dlib.shape_predictor('shape_predictor_...
<reponame>sn6uv/sympy from basic import S from expr import Expr from evalf import EvalfMixin from sympify import _sympify from sympy.logic.boolalg import Boolean __all__ = ( 'Rel', 'Eq', 'Ne', 'Lt', 'Le', 'Gt', 'Ge', 'Relational', 'Equality', 'Unequality', 'StrictLessThan', 'LessThan', 'StrictGreaterThan', 'Greate...
<gh_stars>0 import os import pickle import numpy as np from sklearn.preprocessing import StandardScaler from sklearn.decomposition import PCA import tqdm from tqdm import tqdm from scipy.spatial import distance #self sim def get_self_sim(word, data): dat = [x[1] for x in data if x[0][1] == word] count = 0 ...
<reponame>watsonjj/CHECLabPySB<filename>sstcam_sandbox/d191118_pedestal_temperature/extract_residuals_interp.py from sstcam_sandbox import get_data, get_checs from CHECLabPy.core.io import HDF5Writer from TargetCalibSB.pedestal import PedestalTargetCalib from TargetCalibSB.stats import OnlineStats, OnlineHist from CHEC...
#!/usr/bin/env python from __future__ import division import numpy as np import scipy.special as scsp import argparse import asetk.format.cp2k as cp2k import asetk.format.cube as cube import asetk.atomistic.constants as constants import asetk.util.progressbar as progressbar import os.path # Define command line parser ...
<filename>quantecon/lss.py """ Filename: lss.py Reference: https://lectures.quantecon.org/py/linear_models.html Computes quantities associated with the Gaussian linear state space model. """ from textwrap import dedent import numpy as np from numpy.random import multivariate_normal from scipy.linalg import solve from...
from cc3d.core.PySteppables import * from cc3d import CompuCellSetup from cc3d.core.SteeringParam import SteeringParam import scipy.integrate import numpy class VolumeSteeringSteppable(SteppableBasePy): def __init__(self, frequency=10): SteppableBasePy.__init__(self, frequency) def add_steering_panel...
<reponame>hebatallah/LCILP import argparse import os import numpy as np from scipy.stats import rankdata def get_ranks(scores): ''' Given scores of head/tail substituted triplets, return ranks of each triplet. Assumes a fixed number of negative samples (50) ''' ranks = [] for i in range(len(s...
################################################################################ # Copyright (C) 2014 <NAME> # # This file is licensed under the MIT License. ################################################################################ """ Module for the multinomial distribution node. """ import numpy as np from ...
import argparse import numpy as np from scipy.optimize import minimize from OCBO.cstrats.profile_cts import ContinuousMultiTaskTS, CMTSPM, ProfileEI from OCBO.cstrats import copts from dragonfly.utils.option_handler import load_options from OCBO.util.misc_util import uniform_draw def black_box_function_1(vec): ...
<reponame>SK-tklab/RandomFourierFeatures<filename>RFM.py import numpy as np import matplotlib.pyplot as plt from scipy.linalg import cholesky, cho_solve import seaborn as sns sns.set_style('darkgrid') class GP: def __init__(self, x_train: np.ndarray, y_train: np.ndarray, noise_var: float = 1., lscale: float = 1....
<reponame>Sujit-O/gemben<gh_stars>1-10 #!/usr/bin/env python # -*- coding: utf-8 -*- from __future__ import absolute_import from __future__ import division from __future__ import print_function import matplotlib.pyplot as plt import networkx as nx import numpy as np import scipy.io as sio import scipy.sparse...
import glob, h5py, os, subprocess import numpy as np from scipy.ndimage import imread from hangul_analysis.utils import resize from hangul_analysis.label_mapping import int2imf from hangul_analysis.fontslist import fonts_with_imf from hangul_analysis.cropping import load_crops500 def txt2png(base_path, font_file, f...
from fractions import Fraction as frac def subtract_matricies(m, n): """ 1 2 1 0 0 2 3 4 - 1 2 = 2 2 5 6 4 2 1 4 """ row_count = len(m) return [[m[row][col] - n[row][col] for col in range(row_count)] for row in range(row_count)] def multiply_matricies(m, n)...
<gh_stars>0 import numpy as np import pandas as pd from scipy.interpolate import interp1d def detect_timestep(data): """ Get the time steps present in the loaded data """ same_trace = data.shift(-1).trace_id == data.trace_id dts = data.shift(-1).time - data.time dts[~same_trace] = np.nan ...
<reponame>IRPIhydrology/sm2rain """Module to compute and calibrate sm2rain.""" import numpy as np from scipy.optimize import minimize np.seterr(invalid='ignore') # handle the case when numba is not available try: from numba import jit _numba_available = True except ImportError: _numba_available = False t...
import numpy as np import scipy.signal as sps def filter_sigma_clip(x, y, nsigma=3, window_length=49, polyorder=3): """ Sigma clip a light curve using a Savitzky-Golay filter. Args: x (array): The x-data array. y (array): The y-data array. nsigma (Optional[float]): The number of sigma...
# -*- coding: utf-8 -*- """ Created on Thu Jul 30 18:05:41 2020 @author: badat """ import torch import torchvision import torch.nn as nn import torch.optim as optim from torchvision import transforms from torch.utils.data import Dataset, DataLoader import torchvision.models.resnet as models from PIL import Image impo...
__author__ = '<NAME>' from unittest import TestCase import os from nose.tools import raises import numpy as np from scipy.integrate import odeint import numba from ..symbolic import make_jit_model from test_utils import simple_model from test_utils.jittable_model import model as unjitted_model from test_utils.sens_j...
import os import numpy as np from scipy.spatial.transform import Rotation as R def read_kitti_calibration_file(file_path): calib = dict() with open(file_path, 'r') as f: for line in f: if len(line) < 5: continue key, val = line.rstrip().split(': ') ...
<reponame>stewartadam/netl3d<gh_stars>1-10 #!/usr/bin/env python # -*- coding: utf-8 -*- """ Takes system microphone input (no parameters) or an audio file (with parameter) and performs frequency analysis on the samples read. """ import audiotools import numpy import pyaudio import pygame import scipy import spectra im...
"""Test RESS.""" import matplotlib.pyplot as plt import numpy as np import pytest import scipy.signal as ss from scipy.linalg import pinv from meegkit import ress from meegkit.utils import fold, matmul3d, rms, snr_spectrum, unfold def create_data(n_times, n_chans=10, n_trials=20, freq=12, sfreq=250, n...
<filename>sd/plotlib.py #!/usr/bin/env python """plot_lib.py: module is dedicated to plot and create the movies.""" __author__ = "<NAME>." __copyright__ = "Copyright 2020, SuperDARN@VT" __credits__ = [] __license__ = "MIT" __version__ = "1.0." __maintainer__ = "<NAME>." __email__ = "<EMAIL>" __status__ = "Research" ...
<filename>examples/matlab_data.py # See also http://www.scipy.org/Cookbook/Reading_mat_files import numpy as np import scipy.io # For old-style Matlab (up to 7.1) files you can use scipy.io R = np.random.rand(100) data = { 'R': R, 'test': 123, } scipy.io.savemat('test.mat', data) data = scipy.io.loadmat('te...
<filename>dm_control/locomotion/arenas/bowl.py # Copyright 2020 The dm_control Authors. # # 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...
<gh_stars>0 # -*- coding: utf-8 -*- """ 2017-9-7 <Statistical Analysis with Missing Data> Problems 1.6 Page 23 """ import numpy as np import matplotlib.pyplot as plt from scipy import stats N = 100 np.random.seed(0) z = np.random.randn(N,4) #(1) a = 0 # 0 , 2 , 0 b = 2 # 0 , 0 , 2 y = np.zeros((N,...
<filename>postprocessing/partner_annotations/luigi_pipeline_spec_dir/find_partners_luigi_generators.py<gh_stars>0 from __future__ import print_function import luigi import z5py import os import numpy as np import numpy.ma as ma import scipy.ndimage import itertools import cremi from cc_luigi import ConnectedComponents ...