text string |
|---|
<reponame>hmajid2301/EmotionCommotion<gh_stars>0
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Nov 11 14:18:26 2016
@author: <NAME>
"""
# In[1]
import scipy.io.wavfile as wav # Reads wav file
import pandas as pd
import numpy as np
import os
import glob
import sys
sys.path.append('../')
from data... |
<reponame>brunojacobs/ulsdpb
# External modules
import numpy as np
from scipy.special import gammaln, digamma
#
# Parameter mappings
#
def dim_from_concatenated_vector(v):
"""Returns the value of K for a (2K)-vector."""
return np.int(v.shape[0] / 2)
def split_concatenated_vector(v):
"""Split a (2K,)-ve... |
from scipy import spatial
import torch.nn as nn
import torch
from lib.config import cfg
from lib.networks.rdopt.util import rot_vec_to_mat
class NetworkWrapper(nn.Module):
def __init__(self, net):
super(NetworkWrapper, self).__init__()
self.net = net
def forward(self, batch):
output ... |
#!/usr/bin/env python
import sys
import os
import math
import numpy
from rdkit import Chem, DataStructs
from rdkit.Chem import rdMolDescriptors as rdmd
from sklearn.cluster import MiniBatchKMeans
import pandas as pd
from tqdm import tqdm
import time
import numpy as np
from scipy.spatial.distance import cdist
from... |
import os
import numpy as np
from scipy import stats
import matplotlib.pyplot as plt
import os
def getRewardsSingle(rewards, window=1000):
moving_avg = []
i = window
while i-window < len(rewards):
moving_avg.append(np.average(rewards[i-window:i]))
i += window
moving_avg = np.array(movi... |
"""Import data from the EIT-systems built at the Research Center Jülich (FZJ).
As there is an increasing number of slightly different file formats in use,
this module acts as an selector for the appropriate import functions.
"""
import functools
import os
import numpy as np
import pandas as pd
import scipy.io as sio
... |
<reponame>Brian-Tomasik/leveraged_investing<gh_stars>1-10
import util
import numpy
import math
import Market
import Investor
import TaxRates
import BrokerageAccount
import plots
from scipy.optimize import fsolve
import os
from os import path
import copy
import write_results
import margin_leverage
from random import Ra... |
<reponame>Millitesla/Retina_Python_Tools
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Mar 29 18:28:07 2017
Stratification Analyzer
@author: ruff
"""
import pandas as pd
import numpy as np
import matplotlib as mpl
import seaborn as sns
import glob
import math
import matplotlib.pyplot as plt
import... |
<reponame>poornasairoyal/Laser-Simulation<filename>laser/misc.py
import numpy as np
from scipy.interpolate import interp1d, interp2d
from scipy.optimize import curve_fit
import matplotlib.image as mpimg
def get_moments(image):
"""
Compute image centroid and statistical waist from the intensity distribution.
... |
# Distributed under the MIT License.
# See LICENSE.txt for details.
import numpy as np
from scipy.optimize import newton
def compute_alpha(density, radius):
def f(a):
return density * radius**2 - 3. / (2. * np.pi) * a**10 / (1. + a**2)**6
def fprime(a):
return 3. * a**9 * (a**2 - 5.) / (1. +... |
import numpy as np
import matplotlib.pyplot as plt
import scipy.integrate as sp
colours = [[0, 150 / 255, 100 / 255], [225 / 255, 149 / 255, 0], [207 / 255, 0, 48 / 255], 'C3', 'C4', 'C9', 'C6', 'C7',
'C8', 'C5']
blue = [23 / 255, 114 / 255, 183 / 255, 0.75]
orange = [255 / 255, 119 / 255, 15 / 255, 0.75]
g... |
# -*- coding: utf-8 -*-
from __future__ import absolute_import
from .common_scroll_geo import *
from .symm_scroll_geo import *
from math import pi
# If scipy is available, use its interpolation and optimization functions, otherwise,
# use our implementation (for packaging purposes mostly)
try:
from scipy.optimi... |
import math
from scipy.stats import pearsonr, linregress
from statsmodels.stats.power import TTestIndPower
def is_valid_alt_hypothesis(alt_hypothesis):
"""
:param alt_hypothesis: str
:return: boolean
"""
# check for valid alt_hypothesis
if alt_hypothesis not in ('!=', '>', '<'):
raise ... |
# -*- coding: utf-8 -*-
# Copyright 2020 The PsiZ Authors. 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 r... |
<filename>python/packages/isce3/signal/doppler_est_func.py
"""
Collection of functions for doppler centroid estimation.
"""
import functools
import numbers
import collections as cl
import numpy as np
from scipy import fft
def corr_doppler_est(echo, prf, lag=1, axis=None):
"""Estimate Doppler centroid based on com... |
<reponame>jensv/relative_canonical_helicity_tools
# -*- coding: utf-8 -*-
"""
Created on Tue Dec 1 13:48:25 2015
@author: <NAME>
"""
import numpy as np
from pyvisfile.vtk import (write_structured_grid,
UnstructuredGrid,
DataArray,
Appen... |
# -*- coding: utf-8 -*-
# Paul's Extreme Sound Stretch (Paulstretch) - Python version
# Batch processing adapted from https://github.com/paulnasca/paulstretch_python/blob/master/paulstretch_stereo.py
#
import contextlib
from numpy import *
import scipy.io.wavfile
import sys
import wave
def load_wav(filename):
tr... |
<filename>tests/reprsimil/test_gbrsa.py
# Copyright 2016 <NAME>, Princeton Neuroscience Instititute,
# Princeton 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... |
import tensorflow as tf
from scipy import misc
import numpy as np
import random
class ImageData:
def __init__(self, load_size, channels, augment_flag):
self.load_size = load_size
self.channels = channels
self.augment_flag = augment_flag
def image_processing(self, filename):
x ... |
<gh_stars>10-100
# MELO: Margin-dependent Elo ratings and predictions
# Copyright 2019 <NAME>
# MIT License
import numpy as np
from scipy.special import erf, erfc, erfcinv, expit
class normal:
"""
Normal probability distribution function
"""
@staticmethod
def cdf(x, loc=0, scale=1):
"""
... |
# 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... |
<filename>srtm_path.py
import numpy as np
from pathlib import Path
from scipy.interpolate import RectBivariateSpline
from tkinter.messagebox import showerror, showwarning
# folder name where hgt files are located:
hgtfolder = 'hgt'
hgtpath = Path.joinpath(Path.cwd(), hgtfolder)
x = np.linspace(0, 1, 3601, dtyp... |
<reponame>adagj/ECS_SOconvection
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Oct 7 17:08:18 2020
@author: adag
"""
import sys
sys.path.insert(1, '/scratch/adagj/CMIP6/CLIMSENS/CMIP6_UTILS')
import CMIP6_ATMOS_UTILS as atmos
import glob
import numpy as np
import warnings
warnings.simplefilter('ig... |
import scipy.io as scio
from models import PF_GCN, VM_GCN
from utils import cal_DAD, gen_batches
from genSamples import LoadMatSamples, loadADJ
import numpy as np
import os
import torch
import torch.nn as nn
import torch.optim as optim
# This script is for SR in the base case (chapter 4.1)
# This script... |
"""
===============================================================================
DelaunayCubic: Generate semi-random networks based on Delaunay Tessellations and
perturbed cubic lattices
===============================================================================
"""
import OpenPNM
import scipy as sp
import sys
... |
"""Script used to generate evoked spike test data
Usage: python -i import_spike_detection.py expt_id cell_id
This will load all spikes evoked in the specified cell one at a time.
For each one you can select whether to write the data out to a new test file.
Note that files are saved without results; to generate thes... |
<filename>python/irispy/mosek_ellipsoid/matlab_wrapper.py
import sys
from scipy.io import loadmat, savemat
from irispy.mosek_ellipsoid.lownerjohn_ellipsoid import lownerjohn_inner
"""
MATLAB wrapper to the python lownerjohn_inner function (the MATLAB interface to Mosek Fusion fails after any call to 'clear java', so ... |
<filename>lorenz.py
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
from scipy.integrate import odeint
import matplotlib.pyplot as plt
def lorenz96(x, t, N=5, F=8):
"""
This is the Lorenz 96 model with constant forcing.
Code snippet adapted from a Wikipedia example.
Here the differential eq... |
"""Linear models based on Torch library."""
from copy import deepcopy
from typing import Sequence, Callable, Optional, Union
import numpy as np
import torch
from log_calls import record_history
from scipy import sparse
from torch import nn
from torch import optim
from ...tasks.losses import TorchLossWrapper
from ...... |
import numpy as np
import matplotlib.pyplot as plt
import scipy.special as sci
import math
import random
from astropy.io.fits import getdata
### CONSTANTS ###
G = 6.67408E-11 # Gravitational constant [m^3/(kg*s^2)]
M = 1.989E30 ... |
<reponame>WenlinG28/Encryption-Image
from PIL import Image
from scipy.misc import imread,imsave
import matplotlib.pyplot as plt
import numpy as np
background = Image.open("import2.jpg")
img = Image.open("import1.jpg")
width, height = img.size
backg_width = 2120
backg_height = 1414
# crop the center part of... |
<gh_stars>0
import streamlit as st
import pandas as pd
from streamlit_lottie import st_lottie
import requests
import matplotlib.pyplot as plt
import seaborn
import statistics
def load_lottieurl(url: str):
r = requests.get(url)
if r.status_code != 200:
return None
return r.json()
lottie_book = load... |
<reponame>barbayrak/PicnicHackathon
#!/usr/bin/env python
# coding: utf-8
# In[1]:
import math
import numpy as np
import pandas as pd
import h5py
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import PIL
import tensorflow as tf
from tensorflow.python.framework import ops
import scipy
from scipy imp... |
<filename>models/network.py
import torch
import torch.nn as nn
from .transformer import *
import scipy.io as sio
# To handle a bug
class Idn(nn.Module):
def __init__(self,net):
super(Idn, self).__init__()
self.module = net
def forward(self, inputs):
return self.module(inputs)
def init_... |
import os
import numpy as np
import matplotlib.pyplot as plt
from scipy import stats
def element_wise_difference_matrix(list1,list2):
'''
difference bound matrix (DBM)
https://en.wikipedia.org/wiki/Difference_bound_matrix#DBMs
:param list1:
:param list2:
:return:
'''
# using list comp... |
from sympy import Wild
import itertools
from .Math import isZero, expand
from .Symbols import mMul
from .Trace import trace, sortYukTrace
class TensorDic(dict):
def __new__(self, *args, **kwargs):
return dict.__new__(self)
def __init__(self, *args, **kwargs):
self.args = args
self.k... |
from coopr.pyomo import *
from math import sin, cos, sqrt, atan2, radians
import matplotlib.pyplot as plt
from random import uniform
import gspread
from oauth2client.service_account import ServiceAccountCredentials
import ast
import pprint
from numpy import ones, vstack, arange
from numpy.linalg import lstsq
from stati... |
# -*- encoding: utf-8 -*-
"""
@File Name : __init__.py
@Create Time : 2021/9/25 8:45
@Description :
@Version :
@License :
@Author : diklios
@Contact Email : <EMAIL>
@Github : https://github.com/diklios5768
@Blog :
@Motto : All our ... |
<reponame>ccarballolozano/transhipment-problem-solver
import numpy as np
from scipy.optimize import linprog
import os
import pandas as pd
def build_and_solve(o_to_d, o_to_t, t_to_t, t_to_d, o_prod, t_prod, d_dem, t_dem, o_to_d_cap, o_to_t_cap, t_to_d_cap, t_to_t_cap):
n_o = o_to_d.shape[0]
n_d = o_to_d.shape[... |
# get_ipython().magic('matplotlib inline')
import matplotlib
import numpy as np
import matplotlib.pyplot as plt
from sklearn import linear_model
import functools
from scipy.stats import poisson
# Generate training data for sales probability regression
def generate_train_data(B=100):
def rank(a, p):
return... |
'''
Portfolio Analysis : Skewness
'''
# %% set system path
import sys,os
sys.path.append(os.path.abspath(".."))
# %% import data
import pandas as pd
month_return = pd.read_hdf('.\\data\\month_return.h5', key='month_return')
company_data = pd.read_hdf('.\\data\\last_filter_pe.h5', key='data')
trade_data = pd.read_hd... |
<filename>data/scripts/dmd_jov.py
"""
Derived module from dmdbase.py for classic dmd.
"""
import numpy as np
import scipy as sp
from pydmd import DMDBase
class DMD_jov(DMDBase):
"""
Dynamic Mode Decomposition
:param svd_rank: the rank for the truncation; If 0, the method computes the
optimal rank... |
<gh_stars>0
# -*- coding: utf-8 -*-
"""
Created on Tue Dec 10 14:38:13 2019
@author: Nathan
"""
import random
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import animation
from scipy.spatial import distance
from collections.abc import Iterator
from itertools import islice
import argparse
from it... |
#
# Author: <NAME> <<EMAIL>>
#
import unittest
import numpy
import scipy.linalg
import tempfile
from pyscf import gto
from pyscf import scf
from pyscf import dft
class KnowValues(unittest.TestCase):
def test_nr_rhf(self):
mol = gto.M(
verbose = 5,
output = '/dev/null',
... |
import pandas as pd
import scanpy as sc
from pathlib import Path
from scipy.stats import zscore
import json
#---------------------------------------------------------
fd_rss='./out/a01_gl-meni_01_rss'
fd_ada='./out/a00_pp_00_load'
fd_out='./out/a01_gl-meni_02_hm-pp'
#--------------------------------------------------... |
# Authors: <NAME> <<EMAIL>>
# <NAME> <<EMAIL>>
# License: BSD (3-clause)
from __future__ import division
from os import path as op
import numpy as np
from scipy.linalg import pinv
from math import factorial
from .. import pick_types, pick_info
from ..io.constants import FIFF
from ..forward._compute_forward... |
<reponame>takacsistvan01010101/OCR_API
"""Filename: server.py
"""
import os
import pandas as pd
from sklearn.externals import joblib
from flask import Flask, jsonify, request
app = Flask(__name__)
@app.route('/predict', methods=['POST'])
def apicall():
"""API Call
Pandas dataframe (sent as a payload) from A... |
# Licensed under a 3-clause BSD style license - see LICENSE.rst
# -*- coding: utf-8 -*-
"""
==================
prospect.utilities
==================
Utility functions for prospect.
"""
import os, glob
from pkg_resources import resource_string, resource_listdir
import numpy as np
import astropy.io.fits
from astropy.t... |
<gh_stars>0
from glue.config import data_factory
from glue.core import Data
from pathlib import Path
import stl
from stl import mesh
import numpy as np
from scipy import interpolate
__all__ = ['is_3dgnome', 'read_3dgnome']
def is_3dgnome(filename, **kwargs):
return filename.endswith('.stl')
def fix_file(filenam... |
<reponame>yihui-he/Estimated-Depth-Map-Helps-Image-Classification<gh_stars>10-100
#! /usr/bin/python
# file: import-caffe.py
# brief: Caffe importer
# author: <NAME> and <NAME>
# Requires Google Protobuf for Python and SciPy
import sys
import os
import argparse
import code
import re
import numpy as np
from math impor... |
import math
import cmath
energy = [0]*28
#[s] read energy
for Sz in range(1,28,2):
#[s] read file
f_name = 'Sz%d/output/zvo_energy.dat' % Sz
f = open(f_name)
tmp = f.read()
f.close
#[e] read file
line = tmp.split("\n")
for name in line:
x = name.split()
if x[0] == "Energy":
tmp_energy =... |
<filename>phasepy/sgt/path_hk.py<gh_stars>10-100
from __future__ import division, print_function, absolute_import
import numpy as np
from scipy.optimize import fsolve
from scipy.integrate import cumtrapz
from .cijmix_cy import cmix_cy
from .tensionresult import TensionResult
def fobj_beta0(dro, ro1, dh2, s, temp_aux,... |
#!/usr/bin/env python
import matplotlib.pyplot as plt
from scipy.stats import truncnorm
from time import sleep
def generate_group_membership_probabilities(num_hosts, mean, std_dev, avg_group_size = 0):
a , b = a, b = (0 - mean) / std_dev, (1 - mean) / std_dev
midpoint_ab = (b + a) / 2
scale = 1 / (b - a)
... |
import logging
import socket
import pickle
from select import select
from gen import generate_code_str
import time
import os
import numpy
import scipy
from net import *
if __name__ == '__main__':
logging.basicConfig(level=logging.INFO)
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.settimeout(15)... |
<gh_stars>0
from setuptools import setup, find_packages
import os
# Taken from setup.py in seaborn.
# temporarily redirect config directory to prevent matplotlib importing
# testing that for writeable directory which results in sandbox error in
# certain easy_install versions
os.environ["MPLCONFIGDIR"]="."
# Modified ... |
import numpy as np
import xarray as xr
from scipy.spatial import Voronoi
from scipy.spatial import Delaunay
from ..graph import Graph
from ...core.utils import as_id_array
from ..ugrid import (MESH_ATTRS, update_node_coords, update_nodes_at_link,
update_links_at_patch)
def remove_bad_patches(m... |
import argparse
import numpy as np
import numpy.random as npr
import scipy
import os
import seaborn as sns
import matplotlib.pyplot as plt
import time
import random
from load_data import DSprites, Cars3D, MPI3D, SmallNORB
import pandas as pd
from utils import uniformize, IRS_score, betatc_compute_total_correlation, D... |
<reponame>neuromusic/waver
import numpy as np
import scipy.ndimage as ndi
from tqdm import tqdm
# from napari.qt import progress as tqdm
from ._detector import Detector
from ._grid import Grid
from ._source import Source
from ._time import Time
from ._wave import WaveEquation
class Simulation:
"""Simulation of w... |
<reponame>certik/sympy-oldcore
"""examples for print_gtk. It prints in gtkmathview using mathml"""
import sys
sys.path.append("..")
from sympy import *
from sympy.printing import print_gtk
x = Symbol('x')
#l1 = limit(sin(x)/x, x, 0, evaluate=False)
#print_gtk(l1)
l2 = integrate(exp(x), (x,0,1), evaluate=False)
pri... |
"""
Testing data augmentation composed of rotations and reflections.
"""
import matplotlib.pyplot as plt
import numpy as np
import scipy.ndimage
import tensorflow.keras as keras
def with_numbers():
"""
Test with a simple numbered array.
Note that this uses scipy.ndimage.rotate for rotations, but I later... |
<gh_stars>1-10
#!/usr/bin/env python
"""
tree_edit.py
Tool that reads data from analyzed leaf networks and allows for
graphcial selection of certain subtrees, followed by
averaging over the associated tree asymmetries.
Also exports all of the leaf metrics.
<NAME> 2013
"""
import os.path
import os
import sys
import... |
# Author: <NAME>
# Demo: Compute largest inscribed spheres in (approximately) centroidal Laguerre diagram
import numpy as np
from scipy.optimize import linprog
import vorostereology as vs
from math import pi
# NOTE: plotting requires packages not part of the dependencies.
# Install via:
# pip install vtk
# pip install... |
import numpy as np
import pandas as pd
from scipy import stats
def get_common_timestep(data, units='m', string_output=True):
"""
Get the most commonly occuring timestep of data as frequency string.
Parameters
----------
data : Series or DataFrame
Data with a DateTimeIndex.
units : str... |
<filename>interactive_grid_transformation.py
import sys
import os
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from matplotlib.figure import Figure
import matplotlib.image as mpimg
import pandas as pd
from scipy.spatial import cKDTree
from PyQt4.QtCore import *
import PyQt4.QtGui as QtGui
... |
import scipy.io
import numpy as np
from util import save, read
from channelPrune import takeOnlyCertainChannels
from downsample import downSample
files = {
'01': ['1', '2', '3', '4'],
'02': ['1', '2', '3'],
'03': ['1', '2', '3', '4'],
'04': ['1', '2', '3', '4']
}
directories = ['S01', 'S02', 'S03', 'S... |
from collections import OrderedDict
import numpy as np
import cgen as c
from mpmath.libmp import prec_to_dps, to_str
from sympy import Function
from sympy.printing.ccode import C99CodePrinter
class Allocator(object):
"""
Generate C strings to declare pointers, allocate and free memory.
"""
def __i... |
<filename>deadtrees/loss/losses.py
# source: https://github.com/LIVIAETS/boundary-loss
# paper: https://doi.org/10.1016/j.media.2020.101851
# license: unspecified as of 2021-12-06
# only selected code from repo
import logging
from functools import partial
from typing import Any, Callable, cast, Iterable, List, Set, Tu... |
<gh_stars>0
import argparse
import os
os.environ["CUDA_DEVICE_ORDER"]="PCI_BUS_ID" # see issue #152
os.environ["CUDA_VISIBLE_DEVICES"]="5"
import time
import shutil
import torch
import torch.nn.parallel
import torch.backends.cudnn as cudnn
import torch.optim
import torch.utils.data
import torchvision.transforms as ... |
<filename>cosine_transform/test/tests.py
from __future__ import print_function, absolute_import, unicode_literals
import unittest
import cosine_transform as ct
import numpy
from scipy.spatial.distance import cosine
__author__ = 'calvin'
class VariableVTransformTestCase(unittest.TestCase):
def setUp(self):
... |
from __future__ import print_function
from time import time
import torch.nn.functional as F
from torch.autograd import Variable
from tqdm import tqdm
from torchvision import transforms
import lmdb, six
from torch.utils import data
from PIL import Image
import os
import sys
import numpy as np
import tensorflow as tf
im... |
<reponame>xiaozai/openISP
from matplotlib import pyplot as plt
import numpy as np
import csv
from PIL import Image
from skimage.metrics import structural_similarity as ssim
from skimage.metrics import mean_squared_error
from scipy.optimize import minimize, rosen, rosen_der
import cv2
visualize = True
def vis_img(im... |
<reponame>emiliogozo/qmap
import numpy as np
from scipy.stats import gamma, rv_histogram
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from qm import do_qmap
# sns.set_context('talk')
sns.set_context('paper')
sns.set_style('ticks')
plt_args = {
'obs': {
'name': 'Obs',
... |
<reponame>RWTH-EBC/Deep-learning-supervised-topology-detection<gh_stars>0
import numpy as np
import sklearn
import os
from scipy.signal import savgol_filter
from scipy.signal import butter
from scipy.signal import wiener
from scipy.signal import medfilt
DATASET_NAMES = ["case_1_real", "case_1_real_sim", "case_1_sim",
... |
#!/usr/bin/env python
import numpy as np
import pandas as pd
import time
import dask
import dask.dataframe as dd
import multiprocessing
import os
import logging
import scipy.stats as stats
import bisect
from wistl.config import unit_vector_by_bearing, angle_between_unit_vectors
class Tower(object):
"""
class... |
<filename>cool_MPC/mpc_solver.py
import torch
from torch.autograd.functional import jacobian
import numpy as np
from scipy.optimize import minimize
from cool_linear_solver import Variable, Constrained_least_squares
from matplotlib import pyplot as plt
from .tictoctimer import Tictoctimer
class MPC_solver(object):
... |
# -*- coding: utf-8 -*-
"""
Created on 30/10/2017
@Author: <NAME>
Produces color image for Eta Carinae using HST images.
"""
from __future__ import division, print_function
import os
import numpy as np
from astropy.io import fits
import matplotlib.pyplot as plt
from astropy.wcs import WCS
from astropy.coordinates... |
# %%
import numpy as np
import pandas as pd
import scipy as sp
import scipy.optimize
from scipy.optimize import leastsq
import git
# Find home directory for repo
repo = git.Repo("./", search_parent_directories=True)
homedir = repo.working_dir
# Import plotting features
import matplotlib.pyplot as plt
import matplot... |
"""
A model of thermal preference with clusters.
Authors:
<NAME>
<NAME>
Date:
01/05/2017
"""
import numpy as np
import math
import pymc as pm
import pysmc as ps
from scipy.misc import logsumexp
import os
__all__ = ['DATA_FILE',
'load_training_data',
'pmv_functio... |
<filename>moldyn/processing/data_proc.py
# -*-encoding: utf-8 -*-
import os
from functools import wraps
from pprint import pprint
import numpy as np
import numexpr as ne
from matplotlib.tri import TriAnalyzer, Triangulation, UniformTriRefiner
from scipy.spatial import Voronoi, ConvexHull
import moderngl
from moldyn.... |
<reponame>JRF-2018/simbd<gh_stars>0
#!/usr/bin/python3
__version__ = '0.0.1' # Time-stamp: <2021-01-15T17:44:23Z>
## Language: Japanese/UTF-8
"""「大バクチ」の正規分布+マイナスのレヴィ分布のためのパラメータを計算しておく。"""
##
## License:
##
## Public Domain
## (Since this small code is close to be mathematically trivial.)
##
## Author:... |
<reponame>deviantfero/leastfun
from gi import require_version
require_version( 'Gtk', '3.0' )
from gi.repository import Gtk
import re as regexp
import os
import sys
from ..proc.eparser import *
from ..proc.least import *
from ..proc.pdfactory import *
from sympy import *
WIDTH = 10
class MainGrid(Gtk.Grid):
def... |
<gh_stars>0
from __future__ import absolute_import, print_function, unicode_literals
from builtins import dict, str
import logging
import requests
from sympy.physics import units
from indra.databases import chebi_client, uniprot_client
from indra.statements import Inhibition, Agent, Evidence
from collections import def... |
import math
import random
import scipy.fftpack as fftp
import numpy as np
import cmath
import sys
import re
def gaussianRnd(sig2=1.0): #function that get gaussian random number
x1=0.0
x2=0.0
while(x1==0.0)and(x2==0.0):
x1=random.random()
x2=random.random()
y1=math.sqrt(-2*sig2*math.log(x... |
from scipy.spatial.transform import Rotation as R
from tinkerforge.ip_connection import IPConnection
from tinkerforge.bricklet_gps_v2 import BrickletGPSV2
from tinkerforge.brick_imu_v2 import BrickIMUV2 as IMU
import astropy.units as u
from astropy.time import Time
from astropy.coordinates import SkyCoord, EarthLocati... |
import json
import glob
import pickle as pkl
import numpy as np
import matplotlib.pyplot as plt
import scipy.io
from sklearn import svm, tree
from sklearn.metrics import precision_recall_fscore_support
from sklearn.preprocessing import normalize, scale
from scipy.cluster.vq import whiten
from sklearn.manifold import TS... |
""" This module tests functions in the patient demographics module including
the importation, preprocessing and selection of features.
"""
import sys
import os
import pandas as pd
from icu_mortality import DATA_DIR
"""import datetime as datetime
import numpy as np
from dateutil.relativedelta import relativedelta
f... |
#!/usr/bin/env python
#########################################################################################
# Spinal Cord Registration module
#
# ---------------------------------------------------------------------------------------
# Copyright (c) 2020 NeuroPoly, Polytechnique Montreal <www.neuro.polymtl.ca>
#
# ... |
import os
import matplotlib.pyplot as plt
import numpy as np
import scipy.integrate
from scipy.fftpack import fft
import SBCcode
from SBCcode.Tools import SBCtools
class SiPMTrigger(object):
def __init__(self, trig=0):
self.trig=trig
class SiPMPlotter(object):
def __init__(self, pmt_data, left=None... |
<filename>svgp/load_uci_data.py
import torch
from scipy.io import loadmat
from sklearn.impute import SimpleImputer
from math import floor
import numpy as np
import pandas as pd
def set_seed(seed):
torch.manual_seed(seed)
if torch.cuda.is_available():
torch.cuda.manual_seed_all(seed)
def load_airline... |
<filename>metrics/fid.py<gh_stars>10-100
"""
Created on Thu Dec 07 21:24:14 2019
@author: <NAME>
A stand-alone program to calculate the the Frechet Inception Distance (FID) between two datasets distributions as
described here : https://arxiv.org/abs/1706.08500.
Usually used to evaluate GANs. Unlike the original paper,... |
<reponame>OddballSports-tv/obies-eyes<gh_stars>0
# import packages
import os
import cv2
import imutils
import argparse
import numpy as np
import time
from pyimagesearch.descriptors.histogram import Histogram
from sklearn.cluster import KMeans
from scipy.spatial import distance as dist
# construct the argument parser ... |
import os
import numpy as np
import cv2
import math
from scipy import io
from skimage import feature
from scipy import ndimage
from tqdm import tqdm
def canny_edge(depth, th_low=0.15, th_high=0.3):
# normalize est depth map from 0 to 1
depth_normalized = depth.copy().astype('f')
depth_normalized[depth_no... |
import argparse
import logging
import matplotlib.pyplot as plt
import numpy as np
import os
import pickle
from PySide2 import QtWidgets
from skimage.transform import resize
import scipy.io as sio
import sys
import tensorflow as tf
import trimesh
import tqdm
import yaml
from pathlib import Path
from collections import n... |
<reponame>BriyanKleijn/DockerTest
# imports
import requests
from math import sin, cos, sqrt, atan2, radians
import pandas as pd
import scipy.optimize
import io
import numpy as np
import datetime
# workaround for importing classes
import sys
sys.path.append('./weather_predictions/')
import knmi
class weather_estimate... |
<reponame>julianschumann/ae-opt
import numpy as np
import scipy.sparse as sp
from scipy.sparse.linalg import spsolve
#from scikit.sparse.cholmod import cholesky
def make_Conn_matrix(nelx,nely):
#returns the pair with all nonzero entries in stiffness matrix
nEl = nelx * nely #number of elements
nodeNrs... |
import warnings
import numpy as np
from scipy.spatial.distance import pdist, squareform
from .wmean import wmean
def knnimpute(x, k=3):
"""kNN missing value imputation using Euclidean distance.
Parameters
----------
x: array-like
An array-like object that contains the data with NaNs.
k: ... |
<filename>agents/policy_approximators.py
import numpy as np
from scipy.stats import binom_test
from agents.stew.choice_set_data import ChoiceSetData
from agents.stew.mlogit import StewMultinomialLogit
import warnings
class PolicyApproximator:
"""
Parent/base class from which other policy approximators inher... |
import numpy as np
import matplotlib.pyplot as plt
from optimization.optimizn import *
from scipy.stats import expon
from scipy.optimize import minimize
class Exponential():
def __init__(self, ts, xs=None):
if xs is not None:
denominator = sum(ts)+sum(xs)
self.lmb = len(ts)/denomina... |
<filename>opt/utils/kernels.py
import numpy as np
import numexpr as ne
from scipy.linalg.blas import dgemm, sgemm
def polynomial_kernel_matrix(P, Q, c, degree):
"""
Calculate kernel matrix using polynomial kernel.
k(p,q) = (p^{T}q + c)^d
Parameters:
-----------
P : `numpy.ndarray`
... |
import numpy as np
from skimage import io
from skimage.color import rgb2gray
from scipy.spatial import distance
import matplotlib.pyplot as plt
# Configurar matplotlib
plt.gray()
# Cargar imagen
image = io.imread('edificio_china.jpg')
M, N = image.shape[:2]
# Calcular DFT-2D
fft = np.fft.fft2(rgb2gray(image))
# Con... |
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