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<filename>interp.py<gh_stars>0 #!/usr/bin/python3 """Read .interp files from ORCA NEB calculations and create graphs.""" import argparse import matplotlib.pyplot as plt import numpy as np from scipy.constants import calorie from scipy.constants import kilo from scipy.constants import N_A from scipy.constants import ...
<reponame>DenisSch/svca<filename>svca_limix/limix/test/gp/test_gplvm.py """GP testing code""" import unittest import scipy as SP import numpy as np import limix.deprecated as dlimix import scipy.linalg as linalg def PCA(Y, components): """run PCA, retrieving the first (components) principle components return ...
# Copyright (c) 2017 Sony Corporation. 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 # # Unless required by applicabl...
"""Curves in n-dimensional Euclidean space Contains ======== Curve """ import numpy as np from sympy import integrate, sqrt from sympy.abc import * from sympy.core.basic import Basic from sympy.core import sympify, diff class Curve(Basic): """A curve in space n-dimensional space A curve is constructed by ...
import numpy as np import pytest from scipy.stats import beta from ..unlikely.misc import find_closest, hpdi def test_hpdi(): size = 10_000 # Skewed to the right array = np.random.beta(2, 1, size=size) credible_interval_width = 0.95 lower, upper = hpdi(proba=credible_interval_width, array=array) ...
<reponame>GTJuniorDesign0100-2020/anti-malarial-MCMC-bayesian-algorithm from collections import namedtuple import os import sys import numpy as np import pandas as pd import pytest import scipy.stats as sp_stats # Add parent directory to search path, so we can import those files sys.path.append(os.path.dirname(os.pat...
<reponame>ramellose/anuran<filename>tests/test_sets.py<gh_stars>1-10 """ This file contains a testing function + resources for testing whether the correct sets are returned with set.py. """ __author__ = '<NAME>' __maintainer__ = '<NAME>' __email__ = '<EMAIL>' __status__ = 'Development' __license__ = 'Apache 2.0' impo...
from __future__ import print_function, division, unicode_literals, absolute_import import os import numpy as np import re from GCR import GCRQuery from scipy import interpolate from scipy.stats import binned_statistic try: from itertools import zip_longest except ImportError: from itertools import izip_longest ...
import numpy as np import h5py import itertools import joblib from sklearn.preprocessing import StandardScaler import sys import scipy.signal as scisig from scipy import interpolate import librosa color_iter = itertools.cycle(['navy', 'c', 'cornflowerblue', 'gold', 'darkorange', 'm', 'g',...
<filename>statsmodels/regression/rolling.py """ Rolling OLS and WLS Implements an efficient rolling estimator that avoids repeated matrix multiplication. Copyright (c) 2019 <NAME> License: 3-clause BSD """ from statsmodels.compat.numpy import lstsq from collections import namedtuple import numpy as np from pandas i...
<reponame>PeterZs/take_an_emotion_walk import matplotlib.pyplot as plt import numpy as np import scipy.optimize as opt import torch from mpl_toolkits.mplot3d import Axes3D from sklearn.decomposition import PCA from torch.autograd import Variable from utils.Quaternions import Quaternions def fleiss_kappa(M): """ ...
<reponame>sudojarvis/arviz """Matplotib Bayesian p-value Posterior predictive plot.""" import matplotlib.pyplot as plt import numpy as np from scipy import stats from ....stats.density_utils import kde from ....stats.stats_utils import smooth_data from ...kdeplot import plot_kde from ...plot_utils import ( _scale_...
<reponame>haoyang-insitro/ABC-Enhancer-Gene-Prediction import glob import sys import traceback from os.path import basename, join import numpy as np import pandas from hic import * from redun import Dir, task from scipy import stats from insitro_core.utils.cloud.bucket_utils import * from insitro_core.utils.storage i...
<filename>blendz/model/model_base.py from builtins import * #Python 2 & 3 compatibility for abstract base classes, from #https://stackoverflow.com/questions/35673474/ import sys import warnings import abc from future.utils import with_metaclass import numpy as np from scipy.integrate import quad from scipy.special impo...
import os import random from itertools import product from unittest import mock import arff import pytest import numpy as np import pandas as pd import scipy.sparse from oslo_concurrency import lockutils import openml from openml import OpenMLDataset from openml.exceptions import OpenMLCacheException, OpenMLHashExce...
# Copyright 2020 The Trieste Contributors # # 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 agreed to...
import sys import numpy as np import pytest from pathlib import Path from stardist.models import Config2D, StarDist2D from stardist.matching import matching from stardist.utils import export_imagej_rois from stardist.plot import render_label, render_label_pred from csbdeep.utils import normalize from utils import circl...
#### Declaration Section ###### import streamlit as st import awesome_streamlit as ast import src.pages.page2 import src.pages.page3 from sklearn.feature_extraction.text import CountVectorizer from PIL import Image import requests from io import BytesIO import matplotlib.pyplot as plt import numpy as np import pandas a...
import sys; sys.path.append('/home/shao/simple_spn/simple_spn/src') from spn.data.datasets import get_binary_data, get_nips_data, get_mnist from os.path import dirname; path = dirname(__file__) import numpy as np; np.random.seed(42) from spn.algorithms.LearningWrappers import learn_conditional, learn_structure, lea...
#!/usr/bin/python """ Plot evolution of the resolution with redshift in both the single dish and interferometer cases. """ import numpy as np import pylab as P from rfwrapper import rf import matplotlib.patches import matplotlib.cm import matplotlib.ticker import scipy.integrate from radiofisher.units import * from mp...
<reponame>AdvancedPhotonSource/cdi # ######################################################################### # Copyright (c) , UChicago Argonne, LLC. All rights reserved. # # # # See LICENSE file. ...
import json import numpy as np from scipy.spatial.distance import cdist import os try: import cPickle as pickle except ImportError: import pickle import torch import torch.nn.functional as F import cv2 import argparse name2id = {} results = [] def morpho(mask, iter, bigger=True): # return mask mask ...
<filename>DeepAR/preprocess_elect.py from __future__ import absolute_import from __future__ import division from __future__ import print_function import os from datetime import datetime, timedelta import pandas as pd import math import numpy as np import random from tqdm import trange from io import BytesIO from urll...
<filename>realworld-testbed/benchmarks.py<gh_stars>0 from statistics import mean from loguru import logger from abc import ABC, abstractmethod import docker import json import time import re from pymongo import MongoClient import pymongo from datetime import datetime import os from dotenv import load_dotenv load_doten...
from fe_approx1D import approximate from sympy import Symbol, sin, tanh, pi x = Symbol('x') def approx(functionclass='intro'): """ Exemplify approximating various functions by various choices of finite element functions """ import os if functionclass == 'intro': # Note: no plot if symb...
from __future__ import division from math import pi import numpy as np import random import os import scipy.io.wavfile as wav class SineOsc: def __init__(self): self.sample_rate = 44100 / 2 self.sound_data = self.mp3_to_np('./NickyAudio2.mp3') def wave(self, frequency, length, rate): ...
<gh_stars>0 from elasticsearch import Elasticsearch import psycopg2 import pandas as pd from statistics import mean import time import random import pickle from scipy import stats import db_config as conf ''' Run query speed tests from local machines between PostgreSQL and Elasticsearch ''' # Open the list of tags wit...
from __future__ import unicode_literals import frappe from frappe import _ import json from frappe.utils import flt, cint def get_list(self,method): for i in self.items: a=[] a.append(i.against_sales_order) b=i.batch_no count=frappe.db.sql("""select distinct count(qci.name) as count...
from __future__ import division from __future__ import print_function from __future__ import absolute_import from __future__ import unicode_literals import matplotlib matplotlib.use('agg') import numpy as np import pandas as pd import tensorflow as tf from scipy.stats import pearsonr from load_mnist import load_m...
<filename>2021/10/main.py #!/bin/python from dataclasses import dataclass from typing import Dict, List, Set import statistics score_table: Dict[str, int] = { ')': 3, ']': 57, '}': 1197, '>': 25137 } def part_one(lines: List[str]) -> int: score: int = 0 for line in lines: character...
from enum import Enum import numpy as np from typing import Dict, List, Optional, Tuple, Final, Iterable from numpy.typing import NDArray from scipy.sparse import csr_matrix, spmatrix from .utils import * import numba # Type Aliases # For shorthand, we refer to the floating point type used to represent # scalar value...
from itertools import product import numpy as np import scipy.sparse as sp from cops.optimization_wrappers import Constraint def constraint_static_master(problem, master): # Constructing A_iq and b_iq for equality (59) as sp.coo matrix A_iq_row = [] A_iq_col = [] A_iq_data = [] b_iq = [] co...
import numpy as np import os.path as op from numpy.testing import assert_array_almost_equal, assert_allclose from scipy.signal import welch import pytest from mne import pick_types, Epochs, read_events from mne.io import RawArray, read_raw_fif from mne.utils import catch_logging from mne.time_frequency import (psd_wel...
<filename>nipype/pipeline/plugins/base.py<gh_stars>100-1000 # -*- coding: utf-8 -*- # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*- # vi: set ft=python sts=4 ts=4 sw=4 et: """Common graph operations for execution.""" import sys from copy import deepcopy from glob import glob import os import s...
<reponame>laols574/ngram<filename>classify.py<gh_stars>0 """ Project: n-grams classify Class: CSC 439 Instructor: Bethard Author: <NAME> Description: This program has one function and three classes. The function "read_smsspam" reads in a spam file and creates an array of tuples where the first part of the tuple is a ...
import sys from argparse import ArgumentParser from sympy import diff, dsolve, integrate, solve, var # TODO: fix it sys.path.append("./") from calculus_of_variations.abstract_problem import AbstractSolver from calculus_of_variations.utils import sympy_eval, t, x, x_diff, x_t0, x_t1 class BoltzSolver(AbstractSolver)...
<reponame>yfe404/nutripy from .nutripy import Nutripy, Goal, Gender, Activity from .config import * import numpy as np from enum import Enum from scipy.ndimage.filters import uniform_filter1d def is_close(a, b, close=150): if abs(a - b) < close: return True return False class Phase(Enum): LOSS...
#!/usr/bin/env python3 # -*- coding: utf-8 -* #/// DEPENDENCIES import os, tensorflow, dbl, scipy, cv2 import discord #python3.7 -m pip install -U discord.py import logging import numpy as np #python3.7 -m pip install -U numpy import numexpr as ne #python3.7 -m pip instal...
<filename>pybinding/solver.py """Eigensolvers with a few extra computation methods The :class:`.Solver` class is the main interface for dealing with eigenvalue problems. It is made to work specifically with pybinding's :class:`.Model` objects, but it may use any eigensolver algorithm under the hood. A few different a...
<reponame>Linjackffy/toppra from .solverwrapper import SolverWrapper from ..constraint import ConstraintType from ..constants import INFTY, ECOS_MAXX, ECOS_INFTY import logging import numpy as np import scipy.sparse logger = logging.getLogger(__name__) try: import ecos IMPORT_ECOS = True except ImportError ...
from scipy.stats import qmc from gmpe_analytic import get_analytic import numpy as np import matplotlib.pyplot as plt plt.rcParams['font.size'] = 13 # Bounds for depth, strike, length, dip, width l_bound = [0, 0, 15, 0, 15] u_bound = [60, 360, 45, 90, 45] nsamples = 300 fig, axes = plt.subplots(nrows=1, ncols=2, fig...
<reponame>ali493/pybotics<filename>pybotics/robot.py """Robot module.""" from typing import Any, Optional, Sequence, Sized, Union import attr import numpy as np # type: ignore import scipy.optimize # type: ignore from pybotics.errors import PyboticsError from pybotics.json_encoder import JSONEncoder from pybotics.k...
# -*- coding: utf-8 -*- """ Created on Tue Apr 20 11:41:36 2021 @author: Koustav """ import os import glob import matplotlib.pyplot as plt import seaborn as sea import numpy as np import pandas as pan import math import matplotlib.ticker as mtick from scipy.optimize import curve_fit def expo(x, a, b, c): return ...
<reponame>Thibaut-Kovaltchouk/MultiPyzo<filename>miniconda3-win/pyzo-4.10.2/source/pyzo/yoton/tests/_test_inExternalCode.py import numpy as np import scipy as sp # import scipy.linalg import time t0 = time.time() a = np.random.normal(size=(1600, 1600)) sp.linalg.svd(a) print(time.time() - t0) # For chan...
#!/usr/bin/env python3 """Coefficient for noise sensitivity evaluation.""" import argparse import math import os import sys import numpy as np from scipy.stats import linregress def load_file(path): with open(path) as f: return np.array([float(line.strip()) for line in f]) def main(): parser = ar...
from TextRank import Textrank import pickle from keras.preprocessing.text import Tokenizer from gensim.models import word2vec import numpy as np from scipy import spatial import re import nltk nltk.download('stopwords') def cleanTex(descrlist): REGEX_URL = r"(http(s)?:\/\/.)?(www\.)?[-a-zA-Z0-9@:%._\+~#=]{2,256}\....
<reponame>LoganAMorrison/Hazma<gh_stars>1-10 from typing import Generator, Optional, Union import numpy as np import numpy.typing as npt from scipy.special import gamma # type:ignore # Pion mass in GeV MPI_GEV = 0.13957018 # Neutral Kaon mass in GeV MK0_GEV = 0.497611 # Charged Kaon mass in GeV MKP_GEV = 0.493677 # ...
from statistics import mean class CalibrationPoint: def __init__(self, samples, vdd_volts, temperature_celsius, clock_frequency_hz): if samples is None: raise TypeError('samples') if vdd_volts is None: raise TypeError('vdd_volts') if temperature_celsius is None: raise TypeError('temperature_celsius')...
<reponame>PozzettiAndrea/Armageddon-ODE-Solver import numpy as np import pandas as pd import armageddon from scipy.optimize import fsolve def f(k, p): r""" Airblast empirical function. k is substituted in the place of the parethesis: .. math:: k := \begin{equation} \frac{r^2+z^2}...
<filename>src/app/actions/peptable/psmtopeptable.py from statistics import median from app.dataformats import mzidtsv as mzidtsvdata from app.dataformats import peptable as peptabledata from app.readers import tsv as reader from app.actions.peptable.base import evaluate_peptide from app.actions.headers.peptable import...
<filename>modules/ClimateDataPortal/MapPlugin.py # -*- coding: utf-8 -*- import datetime import hashlib from math import log10, floor, isnan try: import json # try stdlib (Python 2.6) except ImportError: try: import simplejson as json # try external module except: import gluon.contrib.simp...
<reponame>pablonavarrob/analysis-of-stellar-spectra<gh_stars>0 import pandas as pd import numpy as np import matplotlib.pyplot as plt import matplotlib from functools import reduce from astropy.io import fits from scipy.optimize import curve_fit from scipy.special import wofz from lmfit.models import GaussianModel, Voi...
''' webrt_vad.py Prerequisite: + Install webrtcvad $ pip install webrtcvad + Install other packages such as numpy, matplotlib, and scipy $ pip install package_name fs sampling rate py-webrtcvad, https://github.com/wiseman/py-webrtcvad/ Voice activity detection example, https://www.kaggle.com/holzner/voice-acti...
import numpy as np import json import os from PIL import Image from scipy.io import loadmat def index_data(track_data): final_data = {} final_data['data'] = track_data final_data['data_index'] = {} cnt = 0 for vid_id in track_data.keys(): #import pdb; pdb.set_trace() fo...
import pytest from solo import hashsolo from anndata import AnnData import numpy as np def test_cell_demultiplexing(): from scipy import stats import random random.seed(52) signal = stats.poisson.rvs(1000, 1, 990) doublet_signal = stats.poisson.rvs(1000, 1, 10) x = np.reshape(stats.poisson....
<gh_stars>0 import numpy import scipy import scipy.special from typing import NoReturn from cryspy.A_functions_base.function_1_tof import tof_Jorgensen, \ tof_Jorgensen_VonDreele, calc_hpv_eta, calc_sigma_gamma from cryspy.B_parent_classes.cl_1_item import ItemN from cryspy.B_parent_classes.cl_2_loop import LoopN...
<reponame>alsgkals2/SRResCGAN import os import random import numpy as np import scipy.misc as misc import imageio from tqdm import tqdm from utils import utils_image import torch IMG_EXTENSIONS = ['.jpg', '.JPG', '.jpeg', '.JPEG', '.png', '.PNG', '.ppm', '.PPM', '.bmp', '.BMP'] BINARY_EXTENSIONS = ['.npy'] ...
import sys import os sys.path.append(os.getcwd() + "/src") from logistic_regression import LogisticRegression from datagen import DataGenerator import matplotlib.pyplot as plt from scipy.io import loadmat from logistic_regression import LogisticRegression from tools import plot_loss from tools import preprocess, plot...
# ====================================================================== # Imports # ====================================================================== import os import copy import numpy as np from scipy import sparse from scipy.sparse import linalg from pyspline import Volume from pyspline.utils import ope...
<reponame>julesberman/chunkflow<filename>chunkflow/plugins/median_filter.py import numpy as np from scipy.ndimage import median_filter def execute(chunk: np.ndarray, size: tuple=(3,1,1), mode: str='reflect'): print('median filtering of chunk...') chunk = median_filter(chunk, size=size, mode=mode) return [...
<filename>scalability/experiments/run_system_baseline_experiment.py #!/usr/bin/env python """ P0 Experiment 1: System baseline overhead under load. Purpose: Measure system overhead using a canister that does essentially nothing for typical application subnetworks. Do so for a canister in Rust and Motoko. For request ...
<filename>CompareAccuracy.py from sqlalchemy import create_engine, func, inspect from sqlalchemy.ext.declarative import declarative_base from sqlalchemy.schema import Table,MetaData from sqlalchemy import Column, Integer, Float, ForeignKey from geoalchemy2 import Geometry from geoalchemy2.functions import GenericFuncti...
import sys import os import random import math import bpy import numpy as np from os import getenv from os import remove from os.path import join, dirname, realpath, exists from mathutils import Matrix, Vector, Quaternion, Euler from glob import glob from random import choice from pickle import load from b...
import numpy as np from scipy.ndimage import label from skimage.color import rgb2gray def image2position(img, thres=0.5): grayscale_img = rgb2gray(img) x, y = get_brightest_point(grayscale_img) thresholded = threshold_image(grayscale_img, thres) connected_clusters, _ = label(thresholded) centroid ...
<gh_stars>10-100 import os from define_model import define_model from constants import * os.environ["CUDA_DEVICE_ORDER"]="PCI_BUS_ID" os.environ["CUDA_VISIBLE_DEVICES"]=CUDA_VISIBLE_DEVICES from keras.models import load_model from keras.utils import np_utils from keras.callbacks import EarlyStopping, ModelCheckpoint,...
<gh_stars>0 """ Written by <NAME> Edited by <NAME> to work with macOS/Unix-based systems Purpose: Extract animalNotes from .mat files and format into DataFrame Export as csv file Inputs: animalNotes.mat files Outputs: .csv files Last Revised: March 6th, 2019 """ from scipy.io import loadmat import pandas a...
<reponame>mwang87/minstrel import biom import pandas as pd import numpy as np import tensorflow as tf from skbio import OrdinationResults from skbio.stats.composition import clr, clr_inv from qiime2.plugin import Metadata from rhapsody.multimodal import MMvec from rhapsody.util import split_tables from scipy.sparse imp...
<gh_stars>10-100 # Copyright 2018 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 # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law...
<reponame>vanessagraber/bilby from __future__ import division, print_function, absolute_import import os import sys import matplotlib.pyplot as plt import numpy as np from scipy.signal.windows import tukey from scipy.interpolate import interp1d import deepdish as dd from . import utils as gwutils from ..core import ...
# This script computes the MFCC features for automatic speech recognition # # You need to complete the part indicated by #### so that the code can produce # sensible results. # # <NAME> (<EMAIL>) # import numpy as np import scipy.io.wavfile as wav from scipy.linalg import toeplitz from scipy.fftpack import dct, fft, ...
from __future__ import division, print_function from pyscf.nao.m_ao_matelem import build_3dgrid from pyscf.nao.m_dens_libnao import dens_libnao from pyscf.nao.m_ao_eval_libnao import ao_eval_libnao as ao_eval import scipy.linalg.blas as blas from pyscf.dft import libxc # # # def xc_scalar_ni(me, sp1,R1, sp2,R2, xc_cod...
<gh_stars>0 import argparse import os import sys import cv2 import numpy as np import torch from tqdm import tqdm from scipy.ndimage import gaussian_filter from PIL import Image import pickle import pytorch_lightning as pl from torchvision import transforms import pdb sys.path.append('/mnt/lustre/wanghao3/projects/Pa...
import os import sys import subprocess import cv2 import numpy as np module_path = os.path.abspath(os.path.join( os.path.dirname(__file__), '../3rdparty/Objectron')) if module_path not in sys.path: sys.path.append(module_path) #pylint: disable = wrong-import-position from objectron.schema import annotation_d...
<filename>pybamm/solvers/algebraic_solver.py # # Algebraic solver class # import pybamm import numpy as np from scipy import optimize class AlgebraicSolver(object): """Solve a discretised model which contains only (time independent) algebraic equations using a root finding algorithm. Note: this solver cou...
<gh_stars>1-10 # General import snap import numpy as np import scipy.sparse as sp import json import os import multiprocessing # Our methods from . import config_prepare_dataset as config """ Use this script to precompute information about the underlying base graph. """ def get_shortest_path(node_id): NIdToDis...
<filename>KNN/Python/knn-implementation.py # Importing the dependancies import numpy as np import pandas as pd import matplotlib.pyplot as plt from scipy.stats import mode # Loading the data in numerical format X = pd.read_csv("KNN/Python/xdata.csv").values y = pd.read_csv("KNN/Python/ydata.csv").values X = X[:, 1:] ...
import rclpy # Import the ROS client library for Python from rclpy.node import Node # Enables the use of rclpy's Node class from std_msgs.msg import Float64MultiArray # Enable use of the std_msgs/Float64MultiArray message type from lgsvl_msgs.msg import CanBusData from lgsvl_msgs.msg import Detection3DArray import nump...
# constrained double pendulum # import all we need for solving the problem from pytrajectory import TransitionProblem import numpy as np import sympy as sp from sympy import cos, sin, Matrix from numpy import pi # to define a callable function that returns the vectorfield # we first solve the motion equations of for...
import numba import numpy as np from scipy import sparse from . import utils from .BE import BE from .CPAlgorithm import CPAlgorithm class Divisive(CPAlgorithm): """Divisive algorithm. This algorithm partitions a network into communities using the Louvain algorithm. Then, it partitions each community in...
<filename>CCP_with_Dash/main.py import dash import dash_core_components as dcc import dash_html_components as html import numpy as np from scipy.spatial import distance as dist import pandas as pd from dash.dependencies import Input, Output import plotly.express as px from datasets import load_data from tsom import TSO...
from scipy.stats import kurtosis from scipy.signal import find_peaks from numpy.fft import fft import numpy as np pca_comps = 9 # preprocessing def normalize(col): mean_col = col.mean() max_col = col.max() min_col = col.min() col = (col - mean_col) / (max_col - min_col) return col def normalize_...
from . import matcher import matplotlib.pyplot as plt import matplotlib.colors as clrs from scipy import stats import numpy as np import umap import seaborn as sns import matplotlib.patches as mpatches def pearsonMatrix(dataset_filtered, patterns_filtered, cellTypeColumnName, num_cell_types, projectionName, plotName,...
<filename>script/fsrcnn/convert.py from os import listdir, makedirs from os.path import isfile, join, exists import argparse parser = argparse.ArgumentParser() parser.add_argument("input_dir", help="Data input directory") parser.add_argument("output_dir", help="Data output directory") parser.add_argument("-scale", ty...
<gh_stars>1-10 # Post processing tools for PyRFQ bunch data # <NAME> July 2019 import numpy as np from scipy import constants as const from scipy import stats import h5py import matplotlib.pyplot as plt from temp_particles import IonSpecies from dans_pymodules import FileDialog, ParticleDistribution from bunch_particl...
# Copyright 2019 Xanadu Quantum Technologies Inc. # 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 agre...
import time import sympy from sympy.ntheory import factorint from scipy.special import comb import copy from collections import OrderedDict from itertools import combinations import random import numpy as np import os from fractions import Fraction import math import networkx from networkx.algorithms.appro...
import librosa import librosa.filters import numpy as np from scipy import signal from espnet2.VC_SRC import hparams_for_preprocessing as hparams def load_wav(path): return librosa.core.load(path, sr=hparams.target_sample_rate)[0] def save_wav(wav, path): wav *= 32767 / max(0.01, np.max(np.abs(wav))) librosa...
# from proxmin import nmf import numpy as np import proxmin from proxmin.utils import Traceback from scipy.optimize import linear_sum_assignment import matplotlib.pyplot as plt import time, sys from functools import partial # initialize and run NMF import logging logging.basicConfig() logger = logging.ge...
from copy import deepcopy import logging import numpy as np import pandas as pd from scipy.stats import norm from sklearn.model_selection import cross_val_predict, KFold from tqdm import tqdm from xgboost import XGBRegressor from causalml.inference.meta.base import BaseLearner from causalml.inference.meta.explainer im...
#!/usr/bin/env python #11915010 <NAME> #11915043 <NAME> #11915001 <NAME> #11915052 <NAME> import pickle import warnings warnings.filterwarnings("ignore") import pandas as pd import numpy as np from sklearn.metrics.pairwise import cosine_similarity from scipy import sparse with open('models/covid_tf_idf_vect.pkl', 'r...
<gh_stars>100-1000 from __future__ import print_function, division import sys,os quspin_path = os.path.join(os.getcwd(),"../") sys.path.insert(0,quspin_path) from quspin.operators import hamiltonian from quspin.basis import spin_basis_general, boson_basis_general, spinless_fermion_basis_general, spinful_fermion_basis...
import pandas as pd import math import numpy as np from scipy import stats from parameter_cal import cf from dtw import dtw from scipy.misc import * from sdtw.config import sub_len, nBlocks from sdtw.utils import norm, cal_refer_query_descriptor from parameter_cal.utils import get_fact_align, get_reverse_dict,...
<reponame>lucinezhong/controllers_ode_COVID<filename>Code/input_library.py<gh_stars>0 import pandas import os import networkx as nx import numpy import numpy as np from collections import defaultdict,Counter import datetime import json import math import pickle from numpy import linspace, zeros, abs import sympy as sp ...
<reponame>manulera/simulationsLeraRamirez2021 from random import random from math import log, exp import numpy as np from scipy.stats import beta class Parameters: """ A class to store the parameters of the simulation. All the magnitudes are in minutes and micrometers """ def __init__(self): ...
<filename>solveSystem.py import copy import matplotlib.pyplot as plt import networkx as nx import numpy as np import pandas as pd import sympy as sy from scipy.linalg import null_space from tqdm import tqdm import basicDeltaOperations as op def perturbStandard(standardData, theory = True): ''' Takes a diction...
<gh_stars>1-10 """ Caching facility for SymPy """ # TODO: refactor CACHE & friends into class? # global cache registry: CACHE = [] # [] of # (item, {} or tuple of {}) from sympy.core.decorators import wraps def print_cache(): """print cache content""" for item, cache in CACHE: item ...
<reponame>dcslagel/MarinePlasticTools import os, sys, datetime import numpy as np import matplotlib.pyplot as plt import matplotlib.dates as mdates from scipy.signal import butter, filtfilt import matplotlib.ticker as ticker import matplotlib.patheffects as pe def butter_lowpass(cutoff, fs, order=5): nyq = 0.5 * f...
# Copyright 2016-2019 The <NAME> at the California Institute of # Technology (Caltech), with support from the Paul Allen Family Foundation, # Google, & National Institutes of Health (NIH) under Grant U24CA224309-01. # All rights reserved. # # Licensed under a modified Apache License, Version 2.0 (the "License"); # you ...
# -*- coding: utf-8 -*- """ Created on Sun Mar 14 20:12:15 2021 @author: Ryan """ import numpy as np import scipy.special as sc import scipy.constants as const import scipy.integrate as integrate import matplotlib.pyplot as plt from matplotlib.colors import Normalize # Get first five values of x for wh...
import numpy as np import scipy.sparse.linalg as sp_linalg from six import string_types def recursive_nmu(array, r=None, max_iter=5e2, tol=1e-3, downdate='minus', init='svd'): if r is None: r = min(array.shape) array = array.copy() factors = [] for k in range(r): u, ...