text string |
|---|
'''
Module defining the growth factor `Component`.
The primary class, :class:`GrowthFactor`, executes a full
numerical calculation in standard flat LambdaCDM. Simplifications
which may be more efficient, or extensions to alternate cosmologies,
may be implemented.
'''
import numpy as np
from scipy import integrate as ... |
<filename>tensorqtl/core.py
import torch
import numpy as np
import pandas as pd
import scipy.stats as stats
import scipy.optimize
from scipy.special import loggamma
import sys
output_dtype_dict = {
'num_var':np.int32,
'beta_shape1':np.float32,
'beta_shape2':np.float32,
'true_df':np.float32,
'pval_... |
<gh_stars>0
import numpy as np
import random
from scipy.spatial.distance import cdist, cosine
CORPUS_BASELINE = 0.5022927110761003 # this is the baseline for df_covid_with_text
def get_average_pairwise_distance(df, n=1000):
"""Get average pairwise distance for a group of embeddings. Smaller number means closer to... |
<reponame>jilljenn/TF-recomm
from config import *
from scipy.sparse import lil_matrix, save_npz, load_npz
from sklearn.metrics import roc_auc_score, mean_squared_error
import pandas as pd
import numpy as np
import dataio
import pickle
import pywFM
os.environ['LIBFM_PATH'] = '/Users/jin/code/libfm/bin/'
df_train, df_v... |
<reponame>uber/orb<filename>orbit/template/lgt.py<gh_stars>1000+
import numpy as np
import pandas as pd
from scipy.stats import nct
from copy import deepcopy
import torch
from enum import Enum
import warnings
from ..constants.constants import (
DEFAULT_REGRESSOR_SIGN,
DEFAULT_REGRESSOR_BETA,
DEFAULT_REGRES... |
import numpy as np
import math
import scipy.special
import matplotlib.pyplot as plt
import time
import scipy.ndimage as ndimage
import scipy.ndimage.filters as filters
import array
from scipy.sparse import issparse, spdiags, coo_matrix, csc_matrix
#from mpl_toolkits.mplot3d import Axes3D
import matplotlib.gridspec as ... |
"""
This module contains methods used our implementation of the Asynchronously
Parallel Optimization Solver for finding Multiple Minima (APOSMM) method
described in detail in the paper
`https://doi.org/10.1007/s12532-017-0131-4 <https://doi.org/10.1007/s12532-017-0131-4>`_
"""
from __future__ import division
from __fut... |
import string
import numpy as np
import math
from sympy import Matrix #inverse key
#-------------------------
def letterToNumber(letter):
return string.ascii_lowercase.index(letter)
def numberToLetter(number):
return chr(int(number) + 97)
#-------------------------
module = 26 #english alphabet
#ra... |
import numpy as np
import scipy
from sklearn.linear_model import LinearRegression
import matplotlib.pyplot as plt
from hydroDL import utils
n = 10000
np.random.seed(28041990)
a = np.random.normal(20, 0.1, size=n)
scipy.stats.kstest(a/np.std(a), 'norm')
scipy.stats.anderson(a, dist='norm')
scipy.stats.chisquare(a)
scip... |
# -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
import numpy as np
import scipy.interpolate
from ..signal import signal_distort
def ppg_simulate(
duration=120,
sampling_rate=1000,
heart_rate=70,
frequency_modulation=0.2,
ibi_randomness=0.1,
drift=0,
motion_amplitude=0.1,
powe... |
'''
Dimerization model:
A + A <> AA
'''
from pysb import Model, Parameter, Monomer, Rule, Observable, Initial
from scipy.stats import norm
import numpy as np
from gleipnir.pysb_utilities import NestIt
nest_it = NestIt()
Model()
#######
V = 100.
#######
nest_it(Parameter('kf', 0.001))
nest_it(Parameter('kr', 1.),... |
# -*- coding: utf-8 -*-
from __future__ import (absolute_import, division, print_function)
from ..util.testing import requires
try:
import numpy as np
except ImportError:
np, NumSysLin, NumSysLog = [None]*3
else:
from scipy.optimize import fsolve
from .._equilibrium import equilibrium_residual, solve_equ... |
<filename>src/base/cicflow_dataset.py<gh_stars>0
from pathlib import Path
from torch.utils.data import Dataset
from scipy.io import loadmat
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler, MinMaxScaler
from torchvision.datasets.utils import download_url
import panda... |
from collections import namedtuple
import datetime
import io
import matplotlib
matplotlib.use('Agg') # noqa: E402
import matplotlib.patches as patches
import matplotlib.pyplot as plt
import numpy as np
import scipy as sp
import scipy.stats
import time
from tensorboardX import SummaryWriter
import pyro
import pyro.di... |
<filename>Python Scripts/lesson_209_timeitchallenge.py
# In the section on Functions, we looked at 2 different ways to calculate the factorial
# of a number. We used an iterative approach, and also used a recursive function.
#
# This challenge is to use the timeit module to see which performs better.
#
# The two funct... |
#!/usr/bin/python
# To kick off the script, run the following from the python directory:
# PYTHONPATH=`pwd` python DriveDaemon.py start
#
#standard python libs
import logging
import time
import datetime
import socket
import threading
import os
import io
import atexit
#from cStringIO import StringIO
import scipy.mis... |
#!/usr/bin/python3
from __future__ import print_function
from __future__ import division
'''
This code implements elm controller
'''
# Basic
import numpy as np
from matplotlib import pyplot as plt
from scipy.linalg import pinv2
from tqdm import tqdm
import pandas as pd
import itertools
from argparse import Argument... |
<filename>steady_websocket_server_EEG.py
import time
import random
import json
import datetime
from tornado import websocket, web, ioloop
from datetime import timedelta
from random import randint
import csv
import pandas as pd
import os
import numpy as np
from scipy.stats import pearsonr
paymentTypes = ["cash", "tab",... |
<gh_stars>1-10
import numpy as np
import matplotlib.pyplot as plt
from scipy.misc import toimage
import tensorflow as tf
from keras.datasets import cifar10
from keras.layers import Dense, Activation, Flatten, Lambda, Convolution2D, AveragePooling2D, BatchNormalization, Dropout
from keras.engine import Input, Model
fro... |
#!/usr/bin/python
import math
import sys
import os
import re
import subprocess
import numpy as np
import pandas as pd
import argparse
import operator
import mxnet as mx
import struct
import cv2
from collections import namedtuple
import scipy.io
import matplotlib.pyplot as plt
import matplotlib as mpl
import pylab
impo... |
# -*- coding: utf-8 -*-
""" Mixture model for selecting read count cutoff """
import os
import numpy as np
from sklearn.mixture import GaussianMixture
from sklearn.preprocessing import PowerTransformer
import matplotlib.pyplot as plt
import scipy.stats as stats
# TODO: Include a gamma mixture model function, perhaps... |
<filename>stlearn/plotting/classes.py
"""
Title: SpatialBasePlot for all spatial coordinates and image plot
Author: <NAME>
Date: 20 Feb 2021
"""
from typing import Optional, Union, Mapping # Special
from typing import Sequence, Iterable # ABCs
from typing import Tuple # Classes
import numpy as np
import pandas as ... |
"""helper functions for symbolic manipulation of equations"""
import sympy
def eval_expr(expr, functionals={}, params={}, state={}):
"""Evaluate a symbolic expression based provided information.
Parameters
----------
expr : sympy.Expr
Expression to evaluate.
functionals: Dict[sympy.Symbo... |
import sys
import numpy as np
from scipy.optimize import curve_fit
# Get data to fit
data = np.loadtxt(sys.argv[1])
time = data[:,0]
flux = data[:,1]
sig = data[:,2]
guess_per = np.float(sys.argv[2])
guess_epo = np.float(sys.argv[3])
guess_dep = np.float(sys.argv[4])
guess_dur = np.float(sys.argv[5])
g1 = np.float(sys... |
import numpy as np
import numpy.random as npr
import scipy as sc
from scipy import linalg
class MatrixNormalWithPrecision:
def __init__(self, column_dim, row_dim,
M=None, V=None, K=None):
self.column_dim = column_dim
self.row_dim = row_dim
self.M = M
self._V = ... |
<gh_stars>10-100
#!/user/bin/env python
'''interaction_extractor.py
This class creates dataset of ligand - macromolecule and macromolecule -
macromolecule interaction information. Criteria to select interactions are
specified by the InteractionFilter.
'''
__author__ = "<NAME>"
__version__ = "0.3.0"
__status__ = "expe... |
#!/usr/bin/env python
"""
Various utility functions for working with spectra from DEIMOS on Keck II
"""
import os
import numpy as np
from astropy import units as u
from astropy import constants as cnst
from astropy.io import fits
from astropy.coordinates import SkyCoord
DEIMOS_pixscale = .1185 * u.arcsec/u.pixel
DE... |
################################################################################
# MIT License
#
# Copyright (c) 2020 <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 restrict... |
# PyTorch StudioGAN: https://github.com/POSTECH-CVLab/PyTorch-StudioGAN
# The MIT License (MIT)
# See license file or visit https://github.com/POSTECH-CVLab/PyTorch-StudioGAN for details
# src/metrics/Accuracy.py
import numpy as np
import math
from scipy import linalg
from tqdm import tqdm
from utils.sample import ... |
import numpy as np
import pandas as pd
import pickle
import os
from math import ceil
import matplotlib
import matplotlib.gridspec as gridspec
import matplotlib.pyplot as plt
import seaborn as sns
import warnings
import copy
from scipy.stats import entropy
from matplotlib.ticker import FormatStrFormatter
import statsmod... |
<gh_stars>0
import numpy as np
from scipy.stats import chi2
from statsmodels.stats.diagnostic import acorr_ljungbox
# Helper Functions
def auto_covariance(series, h):
n = len(series)
x_bar = np.mean(series)
series_centered = series - x_bar
return np.dot(series_centered[:(n - h)], series_centered[h:]) ... |
<filename>Benchmark_functions/C4/benchmark_tests_c4.py
import numpy as np
import tensorflow as tf
from keras.layers import Dense, Input
from keras.models import Model
from keras.optimizers import Adam
from scipy.stats import norm
from keras.layers.advanced_activations import LeakyReLU
def cost(X,dim):
C=1+1/4000*... |
import numpy as np
import scipy.io as scio
import torch
def load_ft(data_dir, feature_name='GVCNN'):
data = scio.loadmat(data_dir)
lbls = data['Y'].astype(np.long)
if lbls.min() == 1:
lbls = lbls - 1
idx = data['indices'].item()
if feature_name == 'MVCNN':
fts = data['X'][0].item(... |
from scipy.integrate import solve_ivp
import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import OptimizeResult
# todo 1. change plot color
# todo 2. extension: contact rate "b" -> "b(t)"
# todo 3. extension: vaccination related model modification
# todo 4. phase plot need to be updated
class covi... |
<filename>python/pysvso/localization/pnp.py
import cv2
import numpy as np
# used to evaluated pose graph optimization inside PnP Solver
class Measurement:
def __init__(self, pt3d, frame1, px2d1, frame2, px2d2):
self.pt3d = pt3d
#
self.frame1 = frame1
self.px2d1 = px2d1
self... |
import os
import sys
import re
import json
import math
from difflib import SequenceMatcher
import plotly.graph_objects as go
import requests
import networkx as nx
import pandas as pd
import numpy as np
import scipy
import matplotlib
import matplotlib.pyplot as plt
from ipywidgets import interactive, HBox, VBox
import i... |
import numpy as np
import matplotlib.pyplot as plt
import numpy as np
from skimage import io
from skimage import img_as_uint
import scipy
from scipy.ndimage.morphology import generate_binary_structure
import os
from argparse import ArgumentParser
import warnings
warnings.filterwarnings("ignore", category=UserWarning)
... |
import math
from scipy.spatial import distance
from .semantic_similarity import SemanticSimilarity, _find_interesting_segments
from .util import nlp
class SemanticDistance(SemanticSimilarity):
"""
The output of this metric is reported in the paper.
"""
def __init__(self, embedding_method='elmo', sepa... |
<gh_stars>0
"""This file contains tests for deprecated functions.
This includes correct behaviour as well as throwing warnings.
"""
import h5py
import numpy as np
import pytest
from scipy import sparse
import anndata as ad
from anndata import AnnData
from anndata.tests.helpers import assert_equal
@pytest.fixture
d... |
<reponame>talkncloud/tyhac-aws-hackster<gh_stars>0
import numpy as np
import librosa
from scipy import signal
from scipy.io import wavfile
from scipy.signal import butter,filtfilt
from scipy.signal import cwt
from scipy.signal import hilbert
from scipy.signal import resample
from scipy.signal import decimate
from scipy... |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from __future__ import division
from __future__ import absolute_import
from __future__ import print_function
import logging
log = logging.getLogger(__name__)
import pandas as pd
import numpy as np
from scipy import integrate
from skimage.filters imp... |
import numpy as np
from pyflann import *
import matplotlib.pyplot as plt
from skimage.io import imread
## Some function definitions that we need in this exercise
# pyflann - https://www.cs.ubc.ca/research/flann/uploads/FLANN/flann_manual-1.8.4.pdf
def findNeighbours(descrs1, descrs2, numNeighbors=1):
flann = FLAN... |
from tempfile import mkdtemp, mktemp
import os
import io
import shutil
import textwrap
import numpy as np
from numpy import array, transpose, pi
from numpy.testing import (assert_equal, assert_allclose,
assert_array_equal, assert_array_almost_equal)
import pytest
from pytest import raises as... |
# Copyright 2017 <NAME>. 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 applicable law or agree... |
"""
Commonly used utils:
evaluation metrics e.g. similarity, AUC, AP@k, MAP@k
graph related operation
testing data generator
file I/O
visualization
etc...
"""
import time
import numpy as np
from scipy import sparse
import pickle
import networkx as nx
# ----------------------------------------------------------------... |
#!/usr/bin/env python
"""Limits Example
Demonstrates limits.
"""
from sympy import exp, log, Symbol, Rational, sin, limit, sqrt, oo
def sqrt3(x):
return x**Rational(1, 3)
def show(computed, correct):
print("computed:", computed, "correct:", correct)
def main():
x = Symbol("x")
a = Symbol("a")
... |
<reponame>sorinbiriescu/apt_search_analytics
import streamlit as st
from pg8000.exceptions import DatabaseError
from pg8000.native import Connection
import datetime as DT
import pandas as pd
import logging
import sklearn.cluster as cluster
from sklearn.preprocessing import OrdinalEncoder, StandardScaler
import altair ... |
# -*- coding: utf-8 -*-
"""
Created on Mon Jul 20 09:58:28 2020
@author: TheBeast
"""
# =============================================================================
# Clear Variables
# =============================================================================
# Clear variables before runn... |
<filename>wilcoxon.py
# -*- coding: utf-8 -*-
"""
Created on Tue Sep 15 12:16:21 2015
"""
import scipy.stats as st
import math
import random
wilcoxon_table = {5e-2: {6: 0, 7: 2, 8: 4, 9: 6, 10: 8, 11: 11, 12: 14},
1e-2: {7: 0, 8: 2, 9: 3}}
def wilcoxon_test(a, b, alpha = .05):
"""
Performs ... |
<reponame>bvitos/bandcamp_library_classifier<filename>bandcamp_librarian/flask/clusterer.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Estimates clusters among tracks of Bandcamp labels,
based on features extracted with pyAudioAnalysis and Essentia
The classification model is based on the Electronic Music F... |
<reponame>AyushGit123/sympy
from __future__ import print_function, division
from collections import defaultdict
from sympy.core.compatibility import as_int
from sympy.utilities.iterables import multiset, is_palindromic as _palindromic
def digits(n, b=10):
"""
Return a list of the digits of ``n`` in base ``b... |
<filename>sym.py
from sympy import *
from sympy.abc import *
def equa():
a = input("enter the expression")
pprint(a)
print(diff(a,x))
print(integrate(a,x))
b = input("enter expression for summation")
pprint(summation(b,(i,1,10)))
pprint(solve(a,x))
pprint(series(sin(x),x))
expr =a
expr.subs(x,y)
pprint(exp... |
import os
import copy
import logging
import json
import glob
from collections import defaultdict
import tqdm
import numpy as np
import torch
from scipy.cluster.hierarchy import linkage, fcluster
from scipy.spatial.distance import squareform
from utils.transforms import project_pose, back_project_pose
logger = loggi... |
#!/usr/bin/env python
import argparse
import numpy as np
import sys
from converter_base import BeamConverter
import glob
from scipy.interpolate import interp1d
try:
import lusee
have_lusee = True
except:
have_lusee = False
class CST2LBeam(BeamConverter):
def __init__ (self, root, thetamax = 90, m... |
<gh_stars>1-10
import matplotlib.pyplot as plt
import numpy as np
import scipy.stats as stats
from scipy.optimize import minimize
import math
n = 1000;
mu, variance = 0, 0.25
sigma = math.sqrt(variance)
s = np.random.normal(mu, sigma, n)
x = np.linspace(0, 1, n)
y = x + stats.norm.pdf(x, mu, sigma)
#x = np.linspace... |
"""Empirical Bayes Negative Binomial Means
"""
import numpy as np
import scipy.special as sp
import scipy.stats as st
import scmodes.em
def _check_args(x, s):
n, p = x.shape
s = np.array(s)
if s.shape != () and s.shape != (n, 1):
raise ValueError
if s.shape == ():
s = np.ones(n) * s
return x, s
def... |
import numpy as np
from tools.utils import Helper, INFO, ERROR, NOTE
import matplotlib.pyplot as plt
from scipy.spatial.distance import cdist
import sys
import argparse
import tensorflow as tf
def tf_fake_iou(X: tf.Tensor, centroids: tf.Tensor) -> tf.Tensor:
""" calc the fake iou between x and centroids
Para... |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# vim:fenc=utf-8
#
# Copyright © 2018 <NAME> <<EMAIL>>
#
# Distributed under terms of the BSD license.
"""
"""
from collections import Counter
import numpy as np
import random
import scipy.stats as ss
import matplotlib.pyplot as plt
def distance(p1,p2):
'''Find dis... |
from __future__ import division
from __future__ import print_function
import time
import tensorflow as tf
from utils import *
from models import DSSGCN
from tensorflow import set_random_seed
import matplotlib.pyplot as plt
import scipy.io as sio
import scipy
from scipy.sparse import csr_matrix, lil_matrix
import os
... |
<filename>image-processing/1.augmented.py
import numpy as np
import pandas as pd
from os.path import join
import os
from scipy.misc import imread
from scipy.misc import imresize
from scipy.misc import imsave
from keras.preprocessing import image
input_size = 256
# folder location
data_dir = 'negative'
image_list = os.... |
<reponame>ruizhang-ai/EA_for_KG
import argparse
import pickle
import numpy as np
import scipy
from scipy.spatial import distance
def get_vocab(filename):
fo = open(filename,"r")
list_id = list()
id2ent=dict()
ent2id=dict()
counter = 0
for line in fo:
line_split = line.split()
the_id = counter
the_ent = lin... |
<reponame>ubc-vision/image-matching-benchmark
# Copyright 2020 Google LLC, University of Victoria, Czech Technical University
#
# 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://w... |
import cv2
import math
import numpy as np
import random
import torch
from scipy import special
from scipy.stats import multivariate_normal
from torchvision.transforms.functional_tensor import rgb_to_grayscale
# -------------------------------------------------------------------- #
# --------------------------- blur ke... |
<filename>misc/legacy/fermions/yaferp/vqe/vqe.py<gh_stars>1-10
#import pyquil
import numpy
from yaferp.circuits import circuit
from yaferp.interfaces import fermilibInterface
import openfermion
from yaferp.general import optDict
import copy
import scipy
def pauliStringBasisChangeToPyquil(pauliString, pyQuilCircuit,pyQ... |
#!/usr/bin/env python
"""
Single sideband modulation and demodulation
Refer to Lathi's communications text or another reputable source
"""
from pathlib import Path
from numpy import linspace, cos, pi, arange, int16, log10
from numpy.fft import fft, fftshift
from scipy.signal import butter, lfilter, resample
from matplo... |
<filename>buglocalizer/evaluation.py
import json
import operator
import pickle
import numpy as np
from scipy import optimize
from datasets import DATASET
def combine_rank_scores(coeffs, *rank_scores):
"""Combining the rank score of different algorithms"""
final_score = []
for scores in zip(*rank_scores... |
import scipy as sp
import matplotlib.pyplot as plt
from scipy.integrate import odeint
import numpy as np
####
# Define constants
###
### all parameters taken from cerevisiae
#Transcription:
# <NAME>., <NAME>., & <NAME>. (2010). A complete set of nascent transcription rates for yeast genes. PloS one, 5(11), e15442.... |
# Copyright 2019-2021 ETH Zurich and the DaCe authors. All rights reserved.
""" Various AST parsing utilities for DaCe. """
import ast
import astunparse
from collections import OrderedDict
import inspect
import numbers
import sympy
from typing import Any, Dict, List, Set, Tuple
from dace import dtypes, symbolic
def ... |
import numpy as np
from scipy.special import expi, gammainc
from .ssp_basis import SSPBasis
__all__ = ["CSPBasis", "StepSFHBasis", "CompositeSFH", "LinearSFHBasis"]
# change base
from .constants import loge
class CSPBasis(object):
"""
A class for composite stellar populations, which can be composed from
... |
<gh_stars>10-100
# import functions
from numpy import linspace
from scipy.integrate import odeint
#import pylab as pyl
import matplotlib.pyplot as plt
# define constants
init_cond = [0.3, -0.1]
t_init = 0.0
t_final = 10.0
time_step = 0.005
num_data =int((t_final-t_init)/time_step)
k_spring = 0.1
c_damper = 0.5
... |
import numpy as np
import scipy.sparse as sp
import keras.backend as K
def adjacency_matrix(n):
S = np.zeros((n,n))
for i in range(len(S)):
if i==0:
S[0][1] =1
S[0][n-1] = 1
elif i==(n-1):
S[n-1][n-2] = 1
S[n-1][0] = 1
else:
S[... |
# coding = utf-8
import numpy as np
import sys
import sympy
from fractions import Fraction
import fieldmath
import pypuf.simulation, pypuf.io
import pypuf.attack
import pypuf.metrics
from boolean_function import *
# Note: Put fieldmath.py together in the same repository
# Description: Learning a LBF(Linear Boolea... |
<gh_stars>1-10
import operator
import warnings
import numpy
try:
import scipy.sparse
_scipy_available = True
except ImportError:
_scipy_available = False
from cupy_backends.cuda.api import driver
import cupy
from cupy._core import _accelerator
from cupy.cuda import cub
from cupy import cusparse
from cupy... |
# -*- coding: utf-8 -*-
#Created on Oct 4, 2016
#@author: <NAME>
from __future__ import division
import numpy as np
import time
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from functools import partial
from scipy.integrate import quad, odeint, simps
from scipy.misc import derivative
fr... |
<gh_stars>0
################################################################################
##### Python module for creating simulated time-of-flight mass spectra with
##### Gaussian and hyper-exponentially-modified Gaussian lines shapes
##### Author: <NAME>
import numpy as np
import pandas as pd
from scipy.st... |
<reponame>intelligentEarth/surrogateBayeslands
##~#~#~#~#~#~#~#~#~#~#~#~#~#~#~#~#~#~#~#~#~#~#~#~#~#~#~#~#~#~#~#~#~#~#~#~#~#~#~#~#~#~##
## ##
## This file forms part of the Badlands surface processes modelling application. ##
## ... |
"""
Authors: <NAME>, <NAME>
Licensed under the CC BY-NC 4.0 license (https://creativecommons.org/licenses/by-nc/4.0/)
"""
import numpy as np
import torch
import torch.nn.functional as F
from utils.common_config import get_feature_dimensions_backbone
from utils.utils import AverageMeter, confusion_matrix
from sklearn im... |
<reponame>alzaia/improving_neural_nets_python<filename>utils/opt_utils.py<gh_stars>0
import numpy as np
import matplotlib.pyplot as plt
import h5py
import scipy.io
import sklearn
import sklearn.datasets
def sigmoid(x):
s = 1/(1+np.exp(-x))
return s
def relu(x):
s = np.maximum(0,x)
return s
def load_... |
# Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... |
<gh_stars>1-10
from sympy.core.numbers import (I, Rational, oo)
from sympy.core.singleton import S
from sympy.core.symbol import Symbol
from sympy.functions.elementary.exponential import (exp, log)
from sympy.functions.elementary.miscellaneous import sqrt
from sympy.calculus.singularities import (
singularities,
... |
<filename>pgmult/lda.py
"""
Latent Dirichlet Allocation models, including vanilla LDA as well as correlated
and dynamic topic models (CTMs and DTMs) employing the Polya-Gamma augmentation.
"""
import abc
import copy
import numpy as np
from scipy.misc import logsumexp
from scipy.linalg import solve_triangular as _solve... |
# -*- coding: utf-8 -*-
"""
Created on Tue Jan 21 11:31:50 2020
@author: Dell
"""
import numpy as np
import pandas as pd
import yfinance as yf
import os
import scipy as sp
#function for downloading indicators
def downloadTickerData(tickers,startDate,endDate):
data=yf.download((tickers),start=start... |
<reponame>hywel1994/SARosPerceptionKitti<filename>segmentation_2d/scripts/segmentation_ros.py<gh_stars>0
#!/usr/bin/env python
# for ros
import rospy
from std_msgs.msg import String
from std_msgs.msg import Header
from sensor_msgs.msg import Image
from cv_bridge import CvBridge, CvBridgeError
from copy import deepcop... |
<gh_stars>1-10
#!/usr/bin/env python3
#
# Copyright 2019-2021 <NAME>, <NAME>
#
#
# This file is part of WarpX.
#
# License: BSD-3-Clause-LBNL
"""
This script tests the expansion of a uniformly charged sphere of electrons.
An input file inputs_3d or inputs_rz is used: it defines a sphere of charge with
given initial c... |
import numpy as np
import matplotlib.pyplot as plt
import copy
from scipy.io import loadmat
from sklearn.decomposition import PCA
from matplotlib.gridspec import GridSpec
from matplotlib.collections import LineCollection
from matplotlib import colors as mcolors
import matplotlib.patheffects as pe
def preprocess(dat... |
<reponame>ziliHarvey/Lucas-Kanade-tracking-and-Correlation-Filters
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors as colors
from matplotlib import animation
import matplotlib.patches as patches
from scipy.ndimage import correlate, convolve
from mpl_toolkits.mplot3d import Axes3D
img = np.l... |
<reponame>petarmaric/beam_integrals<gh_stars>0
from itertools import chain
from math import ceil, floor
from nose.plugins.skip import SkipTest
from nose_extra_tools import assert_almost_equal, assert_equal, assert_less_equal, assert_is, assert_raises #@UnresolvedImport
import shutil
from sympy import Abs
import t... |
<filename>evaluation_segmentation.py
# -*- coding: utf-8 -*-
"""
Created on Tue Apr 7 15:51:05 2020
@author: <NAME>
Evaluation for segmentation at ADAM challenge at MICCAI 2020
"""
from difflib import SequenceMatcher
import numpy as np
import os
import SimpleITK as sitk
from scipy import ndimage
impor... |
# import math
import h5py
import scipy.io as sio
import numpy as np
import scipy.linalg as sla
import mcmc.util as util
import numba as nb
import time
import math
FASTMATH=True
PARALLEL = True
CACHE=True
# from numba import complex64, complex128, float32, float64, int32, jit, njit, prange
SQRT2 = np.sqrt(2)
njitSerial ... |
<gh_stars>0
from sympy import Symbol, Limit
t = Symbol( 't' )
St = 5*t**2 + 2*t + 8
t1 = Symbol( 't1' )
delta_t = Symbol( 'delta_t' )
St1 = St.subs( { t: t1 } )
St1_delta = St.subs( { t: t1 + delta_t } )
Limit( ( St1_delta - St1 ) / delta_t, delta_t, 0 ).doit() |
from coarseAlignFeatMatch import CoarseAlign
import sys
sys.path.append('../../model')
sys.path.append('../../utils')
import outil
import model as model
import PIL.Image as Image
import os
import numpy as np
import torch
from torchvision import transforms
from tqdm import tqdm
import argparse
import warnings
imp... |
<gh_stars>100-1000
# MIT License
#
# Copyright (c) 2016 <NAME>
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, m... |
<filename>tests/unit_tests/test_svwf_orthogonality.py<gh_stars>0
# -*- coding: utf-8 -*-
"""Test the orthogonality relations of the SVWFs."""
import unittest
import smuthi.fields.vector_wave_functions as vwf
import smuthi.utility.math as sf
import smuthi.fields.expansions as fldex
import numpy as np
import scipy.inte... |
# Copyright 2016 Google Inc.
#
# This program 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 2 of the License, or
# (at your option) any later version.
#
# This program is distributed in the ho... |
import numpy as np
import rx
import scipy
import scipy.io
import sounddevice as sd
PERIOD_SEC_LEN = 1
SAMPLE_RATE = 8000
BLOCK_SIZE = PERIOD_SEC_LEN * SAMPLE_RATE
def add_channels(signals):
return np.array(np.vstack(signals)).T
def append(*signals):
return np.array(np.hstack(signals))
def wav_read(file... |
<gh_stars>1-10
import scipy.spatial.distance as distance
import numpy as np
import cPickle as pkl
import os
import sys
import pdb
root_dir = 'home_directory/VIC/track3/new'
filtered_dis_dir = os.path.join(root_dir, 'filtered_mot_final_distance/diss')
# concat all filtered cache
all_split_num = 50
all_res = []
for i... |
<filename>examples/Kane1985/Chapter4/Ex8.2.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Exercise 8.2 from Kane 1985."""
from __future__ import division
from sympy import diff, factor, solve, simplify, symbols
from sympy.physics.mechanics import ReferenceFrame, Point
from sympy.physics.mechanics import dot
from ... |
<reponame>AlexanderFengler/hddm<gh_stars>0
import numpy as np
from numpy.random import rand
import time
import pymc as pm
import matplotlib.pyplot as plt
import pandas as pd
import hddm
import hddm.diag
from scipy.integrate import *
from scipy.stats import kstest
from scipy.optimize import fmin_powell
np.random.seed... |
<filename>train_jpeg.py<gh_stars>1-10
from tqdm import tqdm
import math, sys, os, random
import numpy as np
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from argparse import ArgumentParser
import torch
from torch.optim import Adam
from torch.nn.functional import binary_cross_entropy, relu... |
<reponame>AlexS12/poliastro<filename>src/poliastro/twobody/propagation.py
"""Propagation algorithms
"""
import numpy as np
import functools
from scipy.integrate import solve_ivp
from poliastro.integrators import DOP835
from astropy import units as u
from poliastro.twobody.rv import rv2coe
from poliastro.twobody.clas... |
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