text string |
|---|
import numpy as np
import pickle
import multiprocessing as mp
from multiprocessing import Pool
import matplotlib
# matplotlib.rcParams.update({'font.size': 18})
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import itertools
from collections import defaultdict
from joblib import Parallel, delayed
from scipy.sta... |
"""
Implementation of <NAME>'s BLUP-based shrink (Mefford, PhD thesis 2018).
"""
import sys
import time
import scipy as sp
from scipy import stats
import h5py
from ldpred import LDpred_inf
from ldpred import util
from ldpred import ld
from ldpred import reporting
from ldpred import coord_genotypes
def get_LDpr... |
<filename>loader/dataset.py
import os
import pandas as pd
import torch
import torch.utils.data as data
import mrcfile as mrc
import numpy as np
import scipy.ndimage as nd
from tqdm.notebook import tqdm
import pandas as pd
class Dataset_subtomo(data.Dataset):
def __init__(self, dir_csv,task='classification',test=F... |
<reponame>rowland-208/colorsort
"""The colorsort python library provides algorithms for sorting colors.
You can use colorsort to:
* Convert an image into a color vector
* Reduce the number of colors in a color vector while maintaining the overall pallete
* Sort the colors in a color vector
For an interactive demo che... |
import time
from functools import wraps
import numpy as np
import pybullet as p
import pybullet_data as pd
from scipy.spatial.transform import Rotation as R
from utils.text import TextFlag, log
from world.action.primitives import PushAction
from world.environment.objects import RandomObjectsGenerator
GRAVITY = -9.80... |
from sparse_als_soft_impute import SparseSoftImputeALS
import numpy as np
import graphlab
import pandas as pd
from sklearn.base import TransformerMixin
from scipy.sparse import csr_matrix, csc_matrix, coo_matrix, issparse
from sklearn.pipeline import Pipeline
from sklearn.grid_search import GridSearchCV
from sklearn.me... |
<gh_stars>0
""" TFR predictions on test set from log folder """
import os
import glob
import pickle
import numpy as np
import pandas as pd
from scipy.stats import spearmanr
from scipy.stats import pearsonr
pd.set_option('display.max_rows', 500)
pd.set_option('display.max_columns', 50)
pd.set_option('display.width', 10... |
<filename>match_filtering/verify_snr.py
from __future__ import division
import cPickle
import numpy as np
from scipy import integrate, interpolate
from scipy.misc import imsave
import matplotlib
matplotlib.use('agg')
import matplotlib.pyplot as plt
import lal
import lalsimulation
from pylal import antenna, co... |
from collections import defaultdict, Counter
import json
import string
from pathlib import Path
import os
from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords
import pandas as pd
import numpy as np
from nltk.sentiment.vader import SentimentIntensityAnalyzer
import statistics
import csv
#Fetching ... |
import numpy as np
import pandas as pd
import pickle
import math
from sklearn.decomposition import PCA
from sklearn import preprocessing
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
from sklearn.preprocessing import StandardScaler
from scipy.spatial.distance import pdist, cdist, squareform
from... |
<gh_stars>1-10
"""
Module for feature processing. Includes feature selection and feature
engineering algorithms
"""
import typing as t
import numpy as np
import pandas as pd
import warnings
from pyoneer import guards, metrics
from pyoneer.base import CorrBasedSelectorMixin
from pyoneer import warn_messages as w
from s... |
<filename>example.py<gh_stars>10-100
import config
import sys
sys.path.insert(0,config.caffe_path)
import os
import argparse
import pickle
import scipy.ndimage as ndimage
import numpy as np
import calc_horizon
parser = argparse.ArgumentParser(description='')
parser.add_argument('--gpu', default=0, type=int, help='GPU ... |
<filename>src/camera_helper.py
from fractions import Fraction
def get_settings(camera):
"""Returns a dictionary of settings of the camera
Input:
camera: PiCamera camera object
Output:
settings: Dictionary, the settings of the camera
"""
settings = {}
settings['iso'] = camera.iso... |
"""
-----------------------------------------------------------------------
Harmoni: a Novel Method for Eliminating Spurious Neuronal Interactions due to the Harmonic Components in Neuronal Data
<NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>
https://doi.org/10.1101/2021.10.06.463319
----------------------------... |
<reponame>JordiManyer/bddc<filename>src/main1D.py
###############################################################################
##### MAIN PROGRAM #####
###############################################################################
import sys
sys.path.append(".... |
"""
This package is used to generate the values of the
1) derivative of function
2) Taylor series
3) Fourier series
4) Legendre approximation
5) Larange approximation
6) Series converenge viewing
7) Limit of a given sequence
"""
import numpy as np
import seaborn as sn... |
import numpy as np
from scipy.sparse import csr_matrix, lil_matrix
from scipy.sparse.linalg import spsolve
from numpy.linalg import solve, norm
from scipy.spatial import KDTree
from math import *
from numpy import newaxis
import matplotlib.pyplot as plt
# constants
elem_c = 1.6e-19
eps0 = 8.85e-12
m_elec = 9.11e-31
m_... |
<filename>Project_02/Given_Data_and_Code_Skeleton/nnScript.py
import numpy as np
from scipy.optimize import minimize
from scipy.io import loadmat
from math import sqrt
def initializeWeights(n_in, n_out):
"""
# initializeWeights return the random weights for Neural Network given the
# number of node in the... |
import sys,csv,time,calendar
from math import log,sqrt
import numpy as np
from scipy.optimize import minimize
from scipy.special import gammaln
def datetoday(x):
t=time.strptime(x+'UTC','%Y-%m-%d%Z')
return calendar.timegm(t)//86400
def daytodate(r):
t=time.gmtime(r*86400)
return time.strftime('%Y-%m-%d',t)
... |
<filename>codigos/fft_audio.py
import pyaudio
import scipy.io.wavfile as wavfile
import matplotlib.pylab as plt
import numpy as np
import wave
from scipy.fft import fft, fftfreq
from playsound import playsound
## Reproducir audio
playsound('/home/angie/Git/python_dsp/alejandro.wav')
## trear, extraer y gráficar los ... |
# coding=utf-8
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
import json
import sys
import kws_streaming.train.test as test
import numpy as np
import tensorflow.compat.v1 as tf1
import tensorflow as tf
import scipy as scipy
import scipy.io.wavfile as wav
import scipy.signal
from kws_streaming.models import models... |
<reponame>yotamyaniv/kaczmarz-algorithms
"""
Dummy conftest.py for clapsolver.
If you don't know what this is for, just leave it empty.
Read more about conftest.py under:
https://pytest.org/latest/plugins.html
https://stackoverflow.com/questions/34466027/in-pytest-what-is-the-use-of-conftest-py-files
"""
import nump... |
<filename>scripts/genereate_celeba_syn.py
from glob import glob
import os
import random
import scipy.misc as misc
import numpy as np
import random
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--syn_type", type=str, choices=["inward", "outward"])
parser.add_argument("--data_dir", type=str)
ar... |
#-*-coding: utf-8 -*-
import numpy as np
from scipy.misc import derivative
import matplotlib.pyplot as pt
#Definicje funkcji
def f(x):
'''Zwraca wartość dla funkcji eksponencjalnej'''
return np.exp(x)
def g(x):
'''Zwraca wartość dla funkcji exp(-(x**2))'''
return np.exp((x**2)*(-1))
def j(x):
'... |
"""
apply SVD on a PPMI matrix to get low-dimensional word embeddings
"""
import heapq
import logging
import numpy as np
from gensim.models.lsimodel import stochastic_svd
from scipy.sparse import linalg
logger = logging.getLogger(__name__)
try:
from sparsesvd import sparsesvd
except ImportError:
logger.inf... |
import numpy as np
import matplotlib.pyplot as plt
from scipy.interpolate import make_interp_spline, BSpline
font = {'family' : 'normal',
'size' : 16}
plt.rc('font', **font)
# Load data sources
data = np.load('results/keep/delay/a.npy')
times1 = np.load('results/keep/delay/a_td3.npy')
# times1 = np.load(... |
<reponame>frhrdr/MMD-GAN
import numpy as np
import lhsmdu
import tensorflow as tf
import tensorflow_probability as tfp
from sklearn.mixture import GaussianMixture
from sklearn.exceptions import ConvergenceWarning
import warnings
from dp_funcs.net_picker import NetPicker
from scipy.stats import multivariate_normal
impor... |
"""
Class for calculation of likelihood of a pixel expectation, given the pixel amplitude,
the level of noise in the pixel and the photoelectron resolution. This calculation is
taken from:
de Naurois & Rolland, Astroparticle Physics, Volume 32, Issue 5, p. 231-252 (2009)
https://arxiv.org/abs/0907.2610
The likelihood ... |
<reponame>dmilios/dirichletGPC
#!/usr/bin/python3
# Copyright 2018 <NAME>, <NAME>,
# <NAME>,<NAME>, <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.apa... |
# TWO CONNECTED NEURONS
from sklearn.svm import LinearSVC
from scipy.special import erf
import nest
import pylab
# Create two neurons
# Create neurons
neuron1 = nest.Create("iaf_psc_alpha")
nest.SetStatus(neuron1 , {"I_e": 376.})
neuron2 = nest.Create("iaf_psc_alpha")
# Create data gatherer
multimeter = nest.Cr... |
import numpy as np
import pytest
import scipy.special as sp
import scipy.stats as st
import scqtl.simple
@pytest.fixture
def simulate_pois():
np.random.seed(1)
x = np.random.poisson(lam=100, size=1000)
return x
@pytest.fixture
def simulate_nb():
np.random.seed(1)
x = st.nbinom(n=3, p=1e-3).rvs(size=1000)
... |
import os
import time
from collections import Counter
from functools import partial
import numpy as np
import scipy.optimize as so
from matplotlib.backends.backend_pdf import PdfPages
from matplotlib.figure import Figure
from matplotlib.animation import FuncAnimation
from matplotlib.collections import LineCollection
... |
# encoding: utf-8
"""
compare.py -- Functions for comparing double-rotation session responses
Exoported namespace: mismatch_response_tally, mismatch_rotation,
cluster_mismatch_rotation, population_spatial_correlation,
correlation_matrix, correlation_diagonals, common_units
Created by <NAME> on 2010-02-11.
... |
import torch
import LoaderFish
import os
import sys
import numpy as np
import matplotlib.pylab as plt
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import torch.optim as optim
import torch.backends.cudnn as cudnn
import geotnf.point_tnf
##########################... |
import cv2
import numpy as np
import pywt
from scipy.fft import dct, idct
from .detection_nonsonoprompt import texture_areas, ALPHA, MARK_SIZE, BLOCK_SIZE
def embed_into_subband(wav_subband, mark_elements, alpha):
mark_end = len(mark_elements)
mark_index = 0
modified_subband = np.zeros(np.shape(wav_subba... |
<filename>code/pyseg/psd/cleft_batch.py
"""
Script for extracting an analyzing a GraphMCF with a cleft
(v3) 24.03.16 - Modification for not to compute filaments
Input: - Density map tomogram
- Segmentation tomogram
Output: - GraphMCF
"""
__author__ = '<NAME>'
# ################ Packag... |
# -*- coding: utf-8 -*-
from __future__ import print_function
from itertools import combinations, permutations
import logging
import time
import math
import numpy as np
import networkx as nx
from scipy.integrate import quad
from indep_test import bincondKendall, discondKendall, wrapped_ci_test_bin, wrapped_ci_test_d... |
<reponame>oasys-kit/wofryimpl<filename>wofryimpl/propagator/test/propagators2D_test.py
import unittest
import numpy
#
# Note that the tests for the Fraunhofer phase do not make any assert, because a good matching has not yet been found.
#
from syned.beamline.shape import Rectangle, Ellipse
from syned.beamline.eleme... |
#!/usr/bin/env python3
"""Functions to generate completions of operators with explicit SU(2) structure."""
from neutrinomass.tensormethod.core import (
Index,
Field,
IndexedField,
eps,
delta,
is_invariant_symbol,
Operator,
get_dynkin,
D,
)
from neutrinomass.tensormethod.contract im... |
<filename>FASTQ_Preprocess.py
"""
@author: <NAME>
University of North Carolina at Chapel Hill
Chapel Hill, NC 27599
@copyright: 2019
"""
import datetime
import os
import collections
import subprocess
import argparse
import sys
import time
from distutils.util import strtobool
from scipy.stats import ... |
<reponame>irenetrampoline/clustering-interval-censored
import logging
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
# torch.manual_seed(0)
# torch.backends.cudnn.deterministic = True
# torch.backends.cudnn.benchmark = False
from pyro.distributions import MultivariateNormal, No... |
<gh_stars>0
# -*- coding: utf-8 -*-
"""
Created on Tue Aug 18 07:47:32 2020
@author: Sujit
Time Series Analysis
"""
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
plt.style.use('fivethirtyeight')
df = pd.read_csv('international-airli... |
#!/usr/bin/env python
# coding: utf-8
# In[1]:
def TestData(data):
print(type(data))
print(data)
castdata=list(data)
print(type(castdata))
print(castdata)
return False
# In[ ]:
def AutoSBTest( inputs_train,outputs_train):
# firstmodel
from sklearn.neural_network import MLPReg... |
<gh_stars>0
from django.shortcuts import render, redirect
from django.http import HttpResponse
from django.contrib.auth import authenticate, login, logout
from django.contrib.auth.models import User
from django.contrib import messages
from crypto.models import crypto
from ssim.models import ssim
from sympy import *
d... |
import numpy as np
import sys
sys.path.append('../')
from Pipeline import DPA
import hdbscan
import sklearn.cluster as cluster
import matplotlib.pyplot as plt
import scipy as sp
from sklearn import manifold
from scipy import cluster
from matplotlib.collections import LineCollection
from math import sqrt
from sklearn.me... |
<filename>model.py<gh_stars>0
""" Model implementation """
import numpy as np # Numerical computing
from scipy.integrate import odeint # ODE system numerical integrator
from scipy.optimize import curve_fit
ABSERR = 1.0e-8
RELERR = 1.0e-6
DAYS = 7
NUMPOINTS = DAYS
def call_solver(func, p, w0, t):
"""
Intern... |
<filename>examples/paper_examples/nnls_reg.py
"""
Copyright 2019 <NAME>, <NAME>
This file is part of A2DR.
A2DR is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option... |
<reponame>wangleon/stella
#!/usr/bin/env python3
import math
import numpy as np
from scipy.integrate import odeint
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from astropy.coordinates import SkyCoord
from stella.catalog import HIP2
from stella.kinetics import potential
from stella.kinetics ... |
# -*- coding: utf-8 -*-
# @Author: <NAME>
# @Date: 2016-11-22 20:41:39
# @Last Modified by: <NAME>
# @Last Modified time: 2016-12-14 22:09:28
from __future__ import division
import numpy as np
from numpy import linalg as LA
from scipy.stats import gamma
from itertools import permutations, combinations
from sklearn.... |
# -*- coding: utf-8 -*-
# Copyright 2018 the HERA Project
# Licensed under the MIT License
from hera_cal import io
from hera_cal import smooth_cal
from hera_cal.datacontainer import DataContainer
import numpy as np
import unittest
from copy import deepcopy
from pyuvdata.utils import check_histories
from pyuvdata impor... |
<gh_stars>10-100
"""Utilities for strongly connected components"""
from typing import Dict, List, Tuple
import numpy
from scipy.sparse import csr_matrix
from scipy.sparse.csgraph import connected_components
from .graph import Node, Nodes, Graph
NodeIndexes = Dict[Node, int]
def get_graph_csr_matrix(graph: Graph, nod... |
# Copyright 2018 <NAME> & <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 applicable law or agreed to i... |
<reponame>wtysos11/k8sPredictor
# Birch论文 A BIRCH-Based Clustering Method for Large Time Series Databases
# 固定读取部分
import time
foreignTime = time.time()
import os
fileName = 'result.txt'
dataPath = "E:\\code\\myPaper\\k8sPredictor"
#返回一个词典，词典的key为第二项，value为一个列表，所有列表都应该等长
def ReadDataFromFile():
LocalPath = os.path.... |
import numpy as np
from scipy.io import wavfile
from scipy.signal import butter, lfilter
class Signal:
def __init__(self, path):
self._path = path
self._rate, self._data = self._load()
def _load(self):
return wavfile.read(self._path)
@property
def data(self):
return ... |
<gh_stars>0
__description__ = \
"""
ordered_ternary_association.py
Model for a ternary association, where a pair of the components
are assumed to be at identical total concentrations.
"""
__author__ = "<NAME>"
__date__ = "20th Aug 2019"
import numpy as np
from scipy.optimize import root as solve_mass_bala... |
import numpy as np
import pydart2 as pydart
import math
import IKsolve_double_stance
import copy
from scipy import interpolate
from fltk import *
from PyCommon.modules.GUI import hpSimpleViewer as hsv
from PyCommon.modules.Renderer import ysRenderer as yr
render_vector = []
render_vector_origin = []
push_force = []
pu... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
:mod:`decision_stump`
==================
.. module:: decision_stump
:platform: Unix, Windows
:synopsis:
.. moduleauthor:: hbldh <<EMAIL>>
Created on 2014-08-31, 01:52
"""
from __future__ import division
from __future__ import print_function
from __future__ im... |
# -*- coding: utf-8 -*-
import random
import sys
import datetime
import csv
import itertools
from scipy.stats import poisson
import networkx as nx
class AbstractSimulation:
""" Functions for the simulation of interactions between proteins that are
needed independently from the consideration of protein p... |
<reponame>maria-kuruvilla/temp_collective_code<filename>annd_batch.py
# -*- coding: utf-8 -*-
"""
Created on Sun May 10 2020
@author: <NAME>
Goal - Code to analyse all the tracked videos and calculate annd and save it as pickled file.
"""
import sys, os
import pathlib
from pprint import pprint
import numpy as np
f... |
<gh_stars>0
#!/usr/bin/env python
import argparse
import subprocess
import re
import sys
from scipy import special
import numpy
parser = argparse.ArgumentParser(description='for building pages from combos, input trans:hgvs;trans:hgvs;trans:hgvs\tlabelID')
parser.add_argument("--mut", help="Batch output",required=True)... |
<gh_stars>0
import skimage.io as io
import numpy as np
import tensorflow as tf
import scipy.misc
import openslide
from resnet import Resnet
def readTif (name : str):
X = openslide.OpenSlide (name)
X = X.read_region ((0,0),0,(X.dimensions[0],X.dimensions[1]))
X = np.array (X, dtype='uint8')
return X
def ratioW... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Feb 7 08:46:25 2022
This script calculates the 90th percentile threshold of climatological daily
maximum temperatures, centred on a 31 d window, for the base period 1981–2010.
This threshold is used in the calculation of heatwave magnitude index.
The ... |
import os
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from DataStat import Handeler
from pathlib import Path
from sklearn.preprocessing import LabelEncoder
from scipy import stats
from scipy.stats import norm, skew
def make_dir(file_path):
if not os.path.exists(fil... |
import open3d as o3d
from scipy.spatial import ConvexHull
import numpy as np
from tqdm import tqdm
import matplotlib.pyplot as plt
import scipy.stats as stats
from scipy.spatial.distance import euclidean
def bins_stat(x, y, number_of_bins):
xmin, xmax = x.min(), x.max()
ymin, ymax = y.min(), y.max()
binx ... |
import numpy as np
from scipy.interpolate import LinearNDInterpolator, griddata
import time
global precision
precision = 0.1
def func(x, y):
return x*(1-x)*np.cos(4*np.pi*x) * np.sin(4*np.pi*y**2)**2
def my_interp(points, vals):
numpoints = len(vals)
A = np.empty(shape = (numpoints,4))
for idx, point in enumer... |
# -*- coding: utf-8 -*-
"""
Created on Sun Dec 1 01:06:06 2019
@author: YQ
"""
from model import MusicVAE
from scipy.io import wavfile
import pretty_midi
import numpy as np
import tensorflow as tf
import argparse
tf.reset_default_graph()
ap = argparse.ArgumentParser()
ap.add_argument("--ckpt_path", default="vae_m... |
<reponame>alexsavio/aizkolari
#!/usr/bin/python
#-------------------------------------------------------------------------------
#License GPL v3.0
#Author: <NAME> <<EMAIL>>
#Grupo de Inteligencia Computational <www.ehu.es/ccwintco>
#Universidad del Pais Vasco UPV/EHU
#Use this at your own risk!
#2012-01-31
#----------... |
"""
=================================
Travelling Salesman Problem (TSP)
=================================
Implementation of approximate algorithms
for solving and approximating the TSP problem.
Categories of algorithms which are implemented:
- Christofides (provides a 3/2-approximation of TSP)
- Greedy
- Simulated A... |
<filename>simulation-data/kuramoto.py<gh_stars>1-10
# -*- coding: utf-8 -*-
from NNetwork import NNetwork
""" Fun Colors"""
fun_colors = ['Accent', 'Accent_r', 'Blues', 'Blues_r', 'BrBG', 'BrBG_r', 'BuGn', 'BuGn_r',
'BuPu', 'BuPu_r', 'CMRmap', 'CMRmap_r', 'Dark2', 'Dark2_r', 'GnBu', 'GnBu_r',
'Greens', 'Greens_r', '... |
try:
# import version included with old SymPy
from sympy.mpmath import mp
except ImportError:
# import newer version
from mpmath import mp
print("how many digits of pi do you want? I can give you that many digits up to 1000")
#with imported library we can set precision of pi with mp.dps
mp.dps = input... |
<gh_stars>1-10
import pandas as pd
from scipy.stats import chi2_contingency, ttest_ind
from .plots import plot_categorical, plot_numerical
def split_classes(X, Y, label):
""" Returns the splited value of the dataset using the requested label
Args:
X (pd.DataFrame): Main dataset with the variables
... |
import sys
import pickle
import numpy as np
import scipy
from opengl_viewer.opengl_viewer import OpenGlViewer
from ntu_rgb import NTU
from sysu_dataset import SYSU
def record_multiple_voxel_flow():
# dataset = NTU()
dataset = SYSU()
all_voxels = []
for vid in range(int(sys.argv[1]) - 12, int(sys.argv[... |
from itertools import accumulate as _accumulate
from operator import add as _add
import numpy as _np
from scipy import signal as _signal
from scipy.stats import norm as _norm
def reshape(u_seq):
if (ndim:=u_seq.ndim) == 1:
u_seq = u_seq.reshape(len(u_seq), 1)
elif ndim >= 3:
raise NotImplement... |
r"""@package motsfinder.numutils
Miscellaneous numerical utilities and helpers.
@b Examples
```
>>> binomial(5, 3)
10
```
"""
from contextlib import contextmanager
import warnings
from scipy.linalg import LinAlgWarning
from scipy.integrate import fixed_quad, IntegrationWarning
from scipy.interpolate impor... |
import sys
import random
import pickle
from tqdm import tqdm
try :
import numpy as np
except ModuleNotFoundError as error:
numpy = None
print("numpy module not found")
try :
import scipy.spatial.transform
except ModuleNotFoundError as error:
scipy = None
print("scipy module not found")
try :
... |
<filename>BAMnet/src/core/build_data/utils.py
'''
Created on Sep, 2017
@author: hugo
'''
import os
import datetime
import shutil
from collections import defaultdict
import numpy as np
from scipy.sparse import *
RESERVED_TOKENS = {'PAD': 0, 'UNK': 1}
def built(path, version_string=None):
"""Checks if '.built' f... |
import os
import torch
import numpy as np
import math
import scipy
from htvlearn.lattice import Lattice
from htvlearn.delaunay import Delaunay
from htvlearn.grid import Grid
class Hex():
"""Hexagonal lattice vectors"""
v1 = Lattice.hexagonal_matrix[:, 0].numpy()
v2 = Lattice.hexagonal_matrix[:, 1].numpy... |
<reponame>xinranzhu/GPTune-1<filename>examples/GCN/gcn_MB.py
#! /usr/bin/env python
# GPTune Copyright (c) 2019, The Regents of the University of California,
# through Lawrence Berkeley National Laboratory (subject to receipt of any
# required approvals from the U.S.Dept. of Energy) and the University of
# California,... |
from django.http import HttpResponse, JsonResponse
import boto3
import json
import io
import base64
from django.conf import settings
from PIL import Image
import math
import numpy
import os
from scipy.optimize import linear_sum_assignment
from scipy.spatial.distance import euclidean, cosine
def infer(image0, boxes0, ... |
# -*- coding: utf-8 -*-
import numpy
import scipy
from .redfieldtensor import RedfieldRelaxationTensor
from ...core.time import TimeDependent
class TDRedfieldRelaxationTensor(RedfieldRelaxationTensor, TimeDependent):
def _implementation(self, ham, sbi):
""" Reference implementation, complet... |
<filename>examples/bicycle/inertial_param_convert.py<gh_stars>1-10
from pydy import *
from sympy import *
from bicycle_lib_hand import mj_params as mj_p
# Reference frames
N = NewtonianReferenceFrame('N')
(q,), (qd,) = N.declare_coords('q', 1)
lmbda=q
var('rr rrt rf rft xb zb xh zh mc md me mf mr mb mh w c')
var('xr... |
<filename>mGST/additional_fns.py<gh_stars>1-10
import random
import warnings
import numpy as np
import numpy.linalg as la
from scipy.linalg import expm
from scipy.linalg import qr
from scipy.optimize import root_scalar
from low_level_jit import local_basis,contract,MVE_lower,Mp_norm_lower
def transp(dim1,dim2):
... |
<gh_stars>0
'''
Initially written by <NAME> in MATLAB
Rewritten in Python by <NAME> (<EMAIL>), 2021
'''
import numpy as np
import scipy.linalg
from scipy.sparse import csr_matrix
from scipy.sparse.linalg import spsolve
import argparse
import matplotlib.pyplot as plt
from solvers import *
from utils... |
# coding=utf-8
import numpy as np
import scipy.sparse as sparse
from hyperg.hyperg import HyperG
def test_hyperg():
edge_idx = np.array([0, 0, 1, 1, 2, 2, 2])
node_idx = np.array([0, 1, 2, 3, 0, 1, 4])
val = np.array([0.1, 0.3, 0.2, 0.5, 0.6, 0.1, 0.3])
H = sparse.coo_matrix((val, (node_idx, edge_i... |
import logging
from msnlp.config import TaskName
from msnlp.config import WORD_SIMILARITY_PATH
from msnlp.config import WORD_SIMILARITY_PARAMS
import torch
from transformers import AutoModel, AutoConfig, AutoTokenizer, AlbertForMaskedLM, BertTokenizer, BertModel
from scipy.spatial.distance import cosine
import numpy a... |
import pathlib
import reprlib
from typing import Optional, Union
import numpy as np
import scipy.io
from .. import validators
SPECT_FILE_LOADING_FUNCTIONS = {
'mat': scipy.io.loadmat,
'npz': np.load,
}
VALID_SPECT_FILE_FORMATS = tuple(SPECT_FILE_LOADING_FUNCTIONS.keys())
VALID_KEYS = ('s', 'f', 't', 'audi... |
import numpy as np
import cv2
import glob
from scipy.misc import imread, imresize, imsave
import matplotlib.pyplot as plt
# %matplotlib qt
# prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)
objp = np.zeros((6*9,3), np.float32)
# print("objp")
# print(objp)
objp[:,:2] = np.mgrid[0:9,0:6].T.reshape(-1,... |
<filename>bihgpy/posterior.py
import numpy as np
from scipy.special import comb
from scipy.special import beta
from scipy.special import gamma
import tqdm
from .check import initial_checks
binom_coef_exact = True
def K_posterior_value(N,n,K,k,a=1,b=1):
return comb(a+K,a+k,exact=binom_coef_exact)*comb(b+N-K,b+n-k... |
'''Predict OCR images using keras model.
'''
import os
import itertools
import numpy as np
from tensorflow.python import keras
from tensorflow.python.keras.preprocessing import image
from scipy import ndimage
from PIL import Image, ImageDraw, ImageFont
# digit classes
# alphabet = u'0123456789 '
# English characters... |
import os
import h5py
import argparse
import pandas as pd
import numpy as np
import json
import seaborn as sns
import matplotlib.pyplot as plt
from scipy.spatial import distance
parser = argparse.ArgumentParser()
parser.add_argument(
"--partition_file",
type=str,
default="data/partition_fil... |
<filename>utils.py
import numpy as np
import math
from sklearn import preprocessing
from sklearn.model_selection import train_test_split
import pickle as pkl
import geopandas as gpd
from geopandas import GeoSeries
from shapely.geometry import LineString,MultiLineString
import scipy.sparse as sp
import pandas as pd
im... |
<gh_stars>100-1000
import gpflowopt
import numpy as np
import pytest
import gpflow
import six
import sys
import os
import warnings
from contextlib import contextmanager
from scipy.optimize import OptimizeResult
from ..utility import vlmop2, create_parabola_model, create_vlmop2_model, GPflowOptTestCase
def parabola2d(... |
<gh_stars>0
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
from sys import argv
import h5py
import pickle
import numpy as np
from scipy.misc import imread
from scipy.misc import imresize
# TODO Change parameters to different file, or take them a... |
<gh_stars>0
from scipy.io import loadmat
import numpy as np
'''
test_mat_file = '../GazeFollowData/test2_annotations.mat'
prediction_file = 'multi_scale_concat_prediction.npz'
anns = loadmat(test_mat_file)
gazes = anns['test_gaze']
eyes = anns['test_eyes']
N = anns['test_path'].shape[0]
prediction = np.load(predicti... |
<gh_stars>10-100
import os
import sys
import tempfile
import yaml
import zlib
import numpy as np
import simplejson as js
import subprocess as sb
from time import time,sleep
from os import path
from scipy.stats.mstats import mquantiles
try:
from sklearn.lda import LDA
from sklearn.svm import SVC
from sklear... |
import json
import pickle
import matlab
import scipy
import numpy as np
import os
import yaml
from EDL.dialogue.MatEngine_object import eng1
from EDL.dialogue.func_helpers import CalculateFuncs, ScorecardDataFrameFuncs, get_variable_info, correlation_multiprocessing
from EDL.models import EDLContextScorecards
from d... |
import unittest
import numpy as np
import sympy as sp
from graphik.robots.robot_base import RobotSpherical
from graphik.solvers.local_solver import LocalSolver
from graphik.graphs.graph_base import RobotSphericalGraph
from graphik.utils.utils import list_to_variable_dict, list_to_variable_dict_spherical
from liegroup... |
<reponame>philipperemy/keras-mode-normalization<gh_stars>1-10
# https://github.com/aditya9211/SVHN-CNN
import numpy as np
import scipy.io as sio
def load_data():
"""Loads the SVHN dataset.
# Returns
Tuple of Numpy arrays: `(x_train, y_train), (x_test, y_test)`.
"""
train = sio.loadmat('svhn/t... |
import os
from styx_msgs.msg import TrafficLight
import tensorflow as tf
import numpy as np
from PIL import Image
from PIL import ImageDraw
from scipy.stats import norm
import scipy
import scipy.misc
import time
import cv2
SSD_GRAPH_FILE = '../../frozen_models/ssd_inception_v2_coco_2017_11_17/frozen_inference_graph.pb... |
<gh_stars>1-10
import distcan as dc
import numpy as np
from numpy.testing import assert_allclose
import scipy as sp
import scipy.stats as st
# Get some random places to check pdf
np.random.seed(1234)
x = np.random.rand(10)
# Create chi distributions
chi_dc = dc.univariate.Chi(5)
chi_sp = st.chi(5)
# Check chi cdfs/... |
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