text string |
|---|
<filename>geomstats/_backend/pytorch/linalg.py<gh_stars>1-10
"""Pytorch based linear algebra backend."""
import numpy as np
import scipy.linalg
import torch
def _raise_not_implemented_error(*args, **kwargs):
raise NotImplementedError
eig = _raise_not_implemented_error
expm = torch.matrix_exp
logm = _raise_not_... |
import numpy as np
import pandas as pd
from scipy.io import mmread, mmwrite
from scipy.stats import entropy
from sklearn.mixture import GaussianMixture
from scipy.sparse import csr_matrix
from .utils import nd, read_str_list, write_list
def knee(mtx, sum_axis):
u = nd(mtx.sum(sum_axis)) # counts per barcode
... |
<filename>grsnp/hypergeom4.py<gh_stars>10-100
#!/usr/bin/env python2
from __future__ import division
import argparse
import collections
import math
import sys
import logging
from logging import FileHandler,StreamHandler
#from bx.intervals.intersection import IntervalTree
from scipy.stats import hypergeom
import numpy a... |
<reponame>smichr/sympy
from sympy import (symbols, MatrixSymbol, Symbol, MatPow, BlockMatrix,
Identity, ZeroMatrix, ImmutableMatrix, eye)
from sympy.utilities.pytest import raises
k, l, m, n = symbols('k l m n', integer=True)
i, j = symbols('i j', integer=True)
W = MatrixSymbol('W', k, l)
X = MatrixSymbol('X'... |
<filename>make_summary_table.py
from basic import *
import parse_tsv
import scipy
from amino_acids import HP, GES, KD, aa_charge, amino_acids
from operator import add
import html_colors
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import util
with Parser(locals()) as p:
... |
<gh_stars>1-10
import os
import math
import sys
import numpy as np
from matplotlib import pyplot as plt
from scipy.stats import norm, rv_histogram
from matrix_loader import load
from pathlib import Path
weak_percentile = 0.21450289100201259
strong_percentile = 0.0033595580728521786
def recommend(data, nbins=100, pl... |
from scipy import ndimage
def rotate_clockwise(img):
"""
Function to rotate image clockwise
"""
return ndimage.rotate(img, -90)
def rotate_anticlockwise(img):
"""
Function to rotate image anticlockwise
"""
return ndimage.rotate(img, 90)
def rotate_arbitrary(img, deg):
"""
... |
<gh_stars>1-10
import numpy as np
from scipy.spatial import procrustes
from scipy.stats.stats import pearsonr, kendalltau
import seaborn as sns
def random_ortho_transform(X):
# transform the input matrix by
# left multiplying some random orthogonal matrix
#
# assume x in n by m
n, _ = np.shape(X)
... |
"""Utils.py."""
from __future__ import division, print_function
import astropy.constants as const
import astropy.units as u
import scipy as sp
def energy(l):
"""Calculate the energy of a photon with wavelength l.
Parameters
----------
l : float
Photon's wavelength in meters.
Returns
... |
<gh_stars>1-10
import numbers
import os
from copy import copy
import numpy as np
from scipy.special import logsumexp
class MDP:
def __init__(self, S=50, A=4, T=None, R=None, gamma=0.95, temperature=0):
"""
Create a random MDP
:param S: the number of states
:param A: the number o... |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
import numpy as np
from numpy import linalg
import random
from sklearn.metrics.pairwise import cosine_similarity
from scipy.stats import uniform
import csv
import pandas as pd
import argparse
from sklearn.decomposition import PCA
import math
from numpy.... |
<reponame>oasys-kit/ShadowOui-Advanced-Tools
import sys, numpy, copy
from PyQt5.QtGui import QPalette, QColor, QFont
from PyQt5.QtWidgets import QMessageBox
from matplotlib import cm, rcParams
from scipy.interpolate import RectBivariateSpline, interp1d
from silx.gui.plot import Plot2D
from orangewidget import gui,... |
import math
from abc import ABCMeta, abstractmethod
import numpy.random as rand
import scipy.stats as stats
import inspect
KG_PER_LB = 0.453592
MJ_PER_MCAL = 4.184
class Cow:
__metaclass__ = ABCMeta
def __init__(self, day_of_lactation=None, day_of_gestation=None,
parity=None, weight=None):
... |
import pkg_resources
try:
pkg_resources.get_distribution('numpy')
except pkg_resources.DistributionNotFound:
numpyPresent = False
print("Error: Numpy package not available.")
else:
numpyPresent = True
import numpy as np
try:
pkg_resources.get_distribution('pandas')
except pkg_resources.Distri... |
<reponame>DragaDoncila/napari-clemreg<filename>napari_clemreg/widgets/data_preprocessing.py
#!/usr/bin/env python3
# coding: utf-8
import numpy as np
from magicgui import magic_factory, widgets
from scipy import ndimage
from napari.layers import Image
from napari.qt import thread_worker
import time
@magic_factory
def ... |
<reponame>linuxlizard/q60
#!/usr/bin/env python
# Find fiducials in Q60
#
# davep 30-oct-2013
import sys
import numpy as np
import logging
import pickle
import math
import itertools
import Image
import ImageDraw
from scipy.cluster.vq import kmeans,vq
import scipy.ndimage.filters
#import matplotlib.pyplot as plt
impo... |
<reponame>Lam3name/TKP4120<filename>tasks.py<gh_stars>0
import scipy.optimize
import numpy as np
import matplotlib.pyplot as plt
import WtFrac
import constants as con
import compression as comp
def taskPatrialPressureCO2():
alphalist = []
pressurelist = []
for i in range(0,50):
alphalist.append(i*0... |
import cProfile
import profile
import pstats
from statistics import stdev, mean
def calibrate():
pr = profile.Profile()
samples = []
for i in range(20):
samples.append(pr.calibrate(100000))
print("calculated {:02d}: {}".format(i + 1, samples[i]))
print("--------------------------------... |
<gh_stars>1-10
"""
MIT License
Copyright (C) <2019> <NAME> <<EMAIL>>
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, mo... |
<reponame>janvanroestel/roche.py<gh_stars>0
# -*- coding: utf-8 -*-
"""This module contains functions to calculate different Roche radii
Author: <NAME>
Date: 9-1-2017
Version: 0.1
This code is based on the paper "A calculator for Roche lobe properties" by
Leahy and Leahy DOI:10.1186/s40668-015-0008-8
The main functi... |
# %matplotlib inline
import os, time, pickle, argparse
import pandas as pd
import torch
import torch.nn as nn
import numpy as np
from scipy.stats import beta
torch.set_printoptions(threshold=10000)
np.set_printoptions(threshold=np.inf)
parser = argparse.ArgumentParser(description='RSAutoML')
parser.add_argument('--Tra... |
# python pascalvoc.py -gt ../gt_pred/ -det ../maskrcnn_pred/ -gtformat 'xyrb' -detformat 'xyrb'
import torch
import torch.nn as nn
import hyperparams as hyp
import numpy as np
import time
import detectron2
import ipdb
st = ipdb.set_trace
from detectron2 import model_zoo
from detectron2.engine import DefaultPredictor
f... |
import bayescraft.stats as bstats
import scipy.stats as stats
import numpy as np
from numpy.linalg import inv
import scipy as sp
def test_approaches_normal():
eps = 1e-6
df = 1e+9
dim = 5
n_points = 1000
t_distr = bstats.multivariate_student_t(mean=np.zeros(dim), scale=np.eye(dim), shape=df)
no... |
<gh_stars>0
import itertools as itt
from src.data import epochs as cep, cache as ccache, load, reconstitute_rec as crec
import matplotlib.pyplot as plt
import numpy as np
import scipy.signal as ssig
batch = 310
all_models = ['wc.2x2.c-stp.2-fir.2x15-lvl.1-stategain.S-dexp.1', 'wc.2x2.c-stp.2-fir.2x15-lvl.1-dexp.1',
... |
from scipy.interpolate import splprep, splev
from utils import get_logger
from preproc import Proc
import numpy as np
logger = get_logger(__name__)
class RoiBox:
@staticmethod
def curves2roi(image, curves) -> np.ndarray:
"""
:param curves: list of N x 2 matrices, (x, y)
:return: cont... |
<gh_stars>1-10
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# Copyright 2020-2021 by <NAME>. All rights reserved. This file is part
# of the Robot Operating System project, released under the MIT License. Please
# see the LICENSE file included as part of this package.
#
# author: <NAME>
# created: 2020-10-05
# m... |
<gh_stars>0
import scipy.io
import numpy
import matplotlib.pyplot as plt
from scipy import linalg as LA
mat = scipy.io.loadmat('/Users/shreyajain/Downloads/hw0data.mat')
m = mat["M"]
print m
m = numpy.matrix(m)
print numpy.shape(m)
s = m[[3],:]
print s
print m[:,[4]]
avg = m[:,4].mean()
print avg
hi = plt.hist(s)
plt... |
'''
TITLE:
TASK_TYPE:
PURPOSE:
LAST_UPDATED: 15 December 2020
STATUS:
TO_DO:
'''
#%% Import modules
# Import standard pacakges
import numpy as np
import pandas as pd
import scipy.stats as stats
import matplotlib.pyplot as plt
# Import LLGEO modules
import llgeo.quad4m.geometry as q4m_geom
import ... |
<filename>experiments/vtype/dataset/box_cars.py<gh_stars>0
import os
from typing import Any, List, Union
import xml.etree.ElementTree as et
from . import TypeDataset, Type
from scipy.io import loadmat
import pickle
import json
class BoxCars116kDataset(TypeDataset):
dataset_name = "BoxCars116k"
# datase... |
<filename>code/99-seizure_severity.py
# %%
import numpy as np
import pandas as pd
import json
from os.path import join as ospj
from scipy.stats import ttest_ind
import matplotlib.pyplot as plt
import sys, os
code_path = os.path.dirname(os.path.realpath(__file__))
sys.path.append(ospj(code_path, 'tools'))
from line_l... |
<reponame>utkarsh7236/SCILLA<filename>Designers/scipy_minimize_designer.py<gh_stars>10-100
#!/usr/bin/env python
#====================================================
import sys
import copy
import time
import uuid
import pickle
import threading
import numpy as np
from scipy.optimize import minimize as sp_minimize
... |
import types
import dataclasses
from scipy import stats
import jax
from jax import numpy as jnp, random, nn
from flax import struct
import q_learning
import deep_q_functions as q_functions
import utils
from environments import jax_specs
from experiment_logging import default_logger as logger
N_CANDIDATES = 32
TARG... |
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
import warnings
import time as t
from sklearn.linear_model import LogisticRegression
from sklearn.neighbors import KNeighborsClassifier
from sklearn.ensemble import RandomForestClassifier
from sklearn.svm import SVC
from sklear... |
<filename>QL_path.py<gh_stars>10-100
"""
Create path planner with Q-learning.
Precise description environment function, can be found in DQN_PATH.py
"""
import numpy as np
from scipy.spatial.distance import pdist, squareform
import matplotlib.pyplot as plt
import scipy.integrate as integrate
import matplotlib.animation ... |
<reponame>xishansnow/MLAPP
# coding: utf-8
# In[10]:
from scipy.stats import beta
import numpy as np
import matplotlib.pyplot as plt
plt.rcParams['figure.figsize']=(15,5)
# In[12]:
# 从beta(1,5)中采集样本
x1=beta.rvs(a=1,b=5,size=10000)
bins=np.linspace(0,1,100)
ax1 = plt.subplot(121)
result=ax1.hist(x1,bins,align='l... |
# coding: utf-8
# # 3 class discrimination of trialtype.
# ### Using sklean and skflow. Comparison to each of the 4 mice
# In[163]:
import tensorflow as tf
import tensorflow.contrib.learn as skflow
import numpy as np
import matplotlib.pyplot as plt
# get_ipython().magic('matplotlib inline')
import pandas as pd
impo... |
#!/usr/bin/python
# script to calculate autocorrelation profile of a window within in larger profile
# version 1 - 21-03-2013
# Usage autocorrelation_mapper.py <readmap> <window_up_coordinates> <window_down_coordinates> <output>
import sys
from scipy import stats
window_up_coor= int(sys.argv[2])
window_down_coor= int... |
#
# Utility functions for loading and creating and solving circuits defined by
# netlists
#
import numpy as np
import codecs
import pandas as pd
import liionpack as lp
import os
import pybamm
import scipy as sp
from lcapy import Circuit
def read_netlist(
filepath,
Ri=None,
Rc=None,
Rb=None,
Rt=N... |
<reponame>KVSlab/vascularManipulationToolkit<gh_stars>10-100
import math
from scipy.interpolate import splrep, splev
from morphman.common.common import get_distance
from morphman.common.vmtk_wrapper import *
from morphman.common.vtk_wrapper import *
### The following code is adapted from:
### https://github.com/vmt... |
<reponame>Asher-1/FaceKit
#!/usr/bin/python3
from ctypes import *
import cv2
import numpy as np
import sys
import os
from enum import IntEnum
import scipy.spatial.qhull ##whitchcraft
class Point(Structure):
_fields_ = [("x", c_int),
("y", c_int)]
FEAT_POINTS = 14
DESCRIPTORS = 128
class Window(Str... |
<gh_stars>0
### imports ###
import numpy as np
import pandas as pd
from typing import Tuple, Union
import random
from collections import defaultdict
from scipy.stats.stats import pearsonr
###
def look_around(point, parc):
around = []
[x, y, z] = point
for i in range(max(0, x - 1), min(np.shape(parc)[0], ... |
<gh_stars>10-100
import random as rnd
import queue
import statistics as stat
import bisect
# Define a dictionary to hold the simulation parameters
param = {'Timeout_Duration': 1,
'P' : 0.5, # Frame Error Rate (FER)
'Frame_Trans_Time': 1, # Frame transmission time
'Num_Frames': 1
}
#-------------- G... |
import logging, math, json, pickle, os
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.dates as mdates
from datetime import datetime
import matplotlib.patches as patches
from matplotlib.backends.backend_pdf import PdfPages
import matplotlib.gridspec as gridspec
import statistics
logger = logging.g... |
<filename>damagekorrektur.py
import matplotlib.pyplot as plt
import numpy as np
from scipy.optimize import curve_fit
#current related damage rate
a_I = 1.23 * 10**(-17) #A/cm
k_0I = 1.2 * 10**(13) #1/s
E_I = 1.11 * 1.6 * 10**(-19) #j
b = 3.07*10**(-18) #A/cm
t_0 = 1 #min
k_B = 1.38064852 * 10**(-23) #Boltzmann Kon... |
from pyqpanda.Hamiltonian import chem_client
#from pyqpanda.Hamiltonian.QubitOperator import *
from pyqpanda import *
#from pyqpanda.utils import *
from pyqpanda.Algorithm.hamiltonian_simulation import *
from pyqpanda.Algorithm.fragments import *
from scipy.optimize import minimize
from functools import partial
import... |
import gc
import os
import numpy as np
import pandas as pd
import scipy.stats
from tensorflow import keras as keras
from .autoencoder import custom_loss, train_network, activation_types_default, hidden_layers_default, \
encoding_dim_default, loss_function_default, training_method_default, activity_regularizer_def... |
# ======================================================================
# Copyright CERFACS (October 2018)
# Contributor: <NAME> (<EMAIL>)
#
# This software is governed by the CeCILL-B license under French law and
# abiding by the rules of distribution of free software. You can use,
# modify and/or redistribute ... |
<reponame>suswei/RLCT
from __future__ import print_function
# from plotly.subplots import make_subplots
# import plotly.graph_objects as go
import os
import argparse
import random
# from sklearn.manifold import TSNE
# import seaborn as sns
import pandas as pd
from random import randint
import scipy.stats as st
import ... |
import scipy.io
import numpy as np
import sys
input_name = "output_cpu.mat"
output_name = "output_cpu.raw"
# overwrite
input_name = sys.argv[1]
output_name = sys.argv[2]
print(f"[mat2raw] Converting {input_name} to {output_name}...")
mat = np.array(scipy.io.loadmat(input_name))
array = np.array(mat.item(0)['output_c... |
"""
Title:
anylogo.py
Creation Date:
2017-07-31
Author(s):
<NAME>
Purpose:
This file contains a variety of functions used to generate sequence logos.
License: MIT
Copyright (c) 2017 <NAME> group @ California Institute of Technology
Permission is hereby granted, free of charge, to any person ob... |
<gh_stars>0
from fractions import Fraction as Q
from math import floor
from quest.opcode import Opcode
from quest.register import Register
IR = Register.IR.value
DR = Register.DR.value
CR = Register.CR.value
def add(process, operand):
right = process.pop_data()
left = process.pop_data()
process.push_da... |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import matplotlib.cm as cm
import PIL.Image as Image
from scipy.misc import imresize
def create_jpeg(img, output_filename):
jet = cm.get_cmap('jet')
mn = np.min(img)
mx = np.ma... |
import os,re
import glob
import errno
import random
import urllib.request
import numpy as np
from scipy.io import loadmat
from sklearn.utils import shuffle
import sys
# Filtering values of three sensors
def keyfilter(dictionary_keys,sens):
keylist = []
#print(sens)
for key in dictionary_keys:
... |
<gh_stars>0
import os
import traceback
import scipy
import numpy as np
import json
import sys
import random
from keras.callbacks import EarlyStopping, ModelCheckpoint
from model import Multimodel
from mult_image_save_callback import ImageSaveCallback
from error_metrics import ErrorMetrics
class Experiment(object):
... |
"""Script to calculate and plot the sensitivity flux from the population of the different SNe types"""
import numpy as np
from astropy import units as u
from scipy.integrate import quad
from flarestack.shared import plot_output_dir
from flarestack.analyses.ccsn.necker_2019.ccsn_helpers import raw_output_dir, limit_sens... |
#!/usr/bin/python3
__version__ = '0.0.2' # Time-stamp: <2021-01-29T09:26:30Z>
## Language: Japanese/UTF-8
"""正規分布+マイナスのレヴィ分布の実験。「株式」「債券」「農地」「大バクチ」「死蔵」それぞれの分布の形を見てみる。"""
##
## License:
##
## Public Domain
## (Since this small code is close to be mathematically trivial.)
##
## Author:
##
## JRF
## ... |
import cvxpy as cp
import numpy as np
import geopandas as gpd
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection
from shapely.geometry import box, Point, LineString, Polygon, MultiPolygon
import shapely.geometry
from shapely.affinity import scale
from shapely.prepared import prep
from sci... |
<filename>ipde/solvers/single_boundary/interior/stokes.py
import numpy as np
import scipy as sp
import scipy.linalg
import pybie2d
from qfs.two_d_qfs import QFS_Evaluator
from ....annular.stokes import AnnularStokesSolver
from ....annular.annular import ApproximateAnnularGeometry, RealAnnularGeometry
from ....derivativ... |
# # # # # # # # # # # # # # # # # # # # # # # #
# #
# Module to compute optimal decisions #
# By: <NAME> #
# 20-05-2021 #
# Version Aplha-0. 1 #
# ... |
#Standard python libraries
import os
import warnings
import copy
import time
import itertools
import functools
#Dependencies - numpy, scipy, matplotlib, pyfftw
import numpy as np
import matplotlib.pyplot as plt
import pyfftw
from pyfftw.interfaces.numpy_fft import fft, fftshift, ifft, ifftshift, fftfreq
from scipy.int... |
import numpy as np
import scipy
import matplotlib.pyplot as plt
from astropy.io import fits
from .lightcurve import KeplerLightCurve, LightCurve
from .utils import KeplerQualityFlags, plot_image
__all__ = ['KeplerTargetPixelFile']
class TargetPixelFile(object):
"""
TargetPixelFile class
"""
def to_l... |
<filename>src/slim_bpr.py
#!/usr/bin/env python3
import numpy as np
import scipy.sparse as sps
from scipy.special import expit
from tqdm import trange
from basic_recommenders import TopPopRecommender
from helper import TailBoost
from Base.Recommender_utils import similarityMatrixTopK
from run_utils import build_all_ma... |
<reponame>mpi-sws-rse/antevents-python<filename>examples/event_library_comparison/asyncawait.py<gh_stars>1-10
"""This version uses the async and await calls.
"""
from statistics import median
import json
import asyncio
import random
import time
import hbmqtt.client
from antevents.base import SensorEvent
URL = "mqtt:/... |
<reponame>callat-qcd/project_fkfpi
#!/usr/bin/env python3
import matplotlib.pyplot as plt
import numpy as np
from scipy.optimize import minimize_scalar
import os, copy
import gvar as gv
# import chipt lib for fit functions
import chipt
class ExtrapolationPlots:
def __init__(self, model, model_list, fitEnv, fit_r... |
<filename>CASutils/blocking_utils.py
###Subroutines for calculating the 2D blocking statistics of Masato et al (2013) Winter and Summer Northern Hemisphere Blocking in CMIP6 Models, J. Clim.
import importlib
import pandas as pd
import xarray as xr
import numpy as np
from numpy import nan
import sys
import warnings
imp... |
"""
This file contains the methods used for estimating aberration prevalence in a
two-echelon supply chain. See descriptions for particular inputs.
"""
######### NEED TO ADD CAPACITY TO HANDLE DIFFERENT DIAGNOSTIC DEVICES @ DIFFERENT DATA POINTS
import numpy as np
import scipy.optimize as spo
import scipy.stats as sp... |
<reponame>shadiakiki1986/garage
import os
import matplotlib
try:
matplotlib.pyplot.figure()
matplotlib.pyplot.close()
except Exception:
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
from scipy.signal import convolve2d
from scipy.stats import multivariate_normal
from garage.envs.... |
#!/usr/bin/env python
import numpy as np
from scipy.special import expit as sigmoid
# this example shows how to load y from a test file in VW format
# and predictions too - VW doesn't output probabilities hence the sigmoid
# we want y like np.array([ 0, 1, 0, 1 ])
# and p like np.array([ 0.3, 0.98, 0.2, 0.75435832345... |
from numpy import save, load
from glob import glob
from os import listdir
from scipy.spatial import distance
from dlib import shape_predictor
from dlib import face_recognition_model_v1
from dlib import get_frontal_face_detector, load_rgb_image
detector = get_frontal_face_detector()
shape_predictor = shape_predictor(... |
<reponame>gautelinga/Surfaise<filename>surfaise/common/mesh_refinement.py
import scipy.integrate as integrate
import matplotlib.pyplot as plt
import numpy as np
from pynverse import inversefunc
import dolfin as df
from scipy.interpolate import RectBivariateSpline, InterpolatedUnivariateSpline
import mpi4py.MPI as MPI
c... |
<filename>workflow/plot_all_cartels.py
import numpy as np
import pandas as pd
import utils
from scipy import sparse
import matplotlib.pyplot as plt
import seaborn as sns
import sys
import matplotlib.colors as colors
from matplotlib import cm
import os
sys.path.append(os.path.abspath(os.path.join("libs/cidre")))
from ci... |
# Authors:
# <NAME> <<EMAIL>>
# <NAME> <<EMAIL>>
#
# License: BSD 3 clause
"""
Example of a double D1Q2 for shallow water
"""
import sympy as sp
import pylbm
# parameters
h, q, X, LA, g = sp.symbols('h, q, X, LA, g')
la = 2. # velocity of the scheme
s_h, s_q = 1.7, 1.5 # relaxation parameters
... |
from PyBambooHR.PyBambooHR import PyBambooHR
import csv
import os
import pandas as pd
import smtplib
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
import random
import statistics
import sys
import jinja2
import itertools
import configparser
def load_df():
EMPLOYEES_CSV = conf... |
from typing import Optional, Tuple
import numpy as np
from astropy.convolution import Gaussian1DKernel, convolve
from gacf import GACF
from matplotlib.axes import Axes
from scipy.stats import median_abs_deviation
from roto.methods.fft import FFTPeriodFinder
from roto.methods.periodfinder import PeriodFinder, PeriodRe... |
from numpy import array, mat, shape, transpose
from scipy import cov, linalg
from pylab import load, arange
data2 = mat(array(load('raw3.dat', delimiter='\t',usecols=arange(0,13,1), unpack=True)))
time_series = mat(cov(data2, rowvar=1))
print 'covariance matrix : ', shape(time_series)
eval, evec = linalg.eig(mat(time_... |
<filename>bhc/bayesian_hierarchical_clustering.py
"""
Bayesian Hierarchical Clustering
Author: <NAME>
July 2020
bayesian_hierarchical_clustering.py
Class `BHC`. This is the primary object for user interface in the bhc library.
"""
import numpy as np
from bhc.cluster import Cluster
import scipy.linalg as la
from scip... |
<gh_stars>1-10
# -*- coding: utf-8 -*-
"""Classes for calcs e wfls analysis. hybrid AiiDA and not_AiiDA...hopefully"""
from __future__ import absolute_import
import numpy as np
from scipy.optimize import curve_fit
from matplotlib import pyplot as plt, style
import pandas as pd
import copy
import cmath
try:
from ai... |
import numpy as np
from openfermion.chem import MolecularData
from openfermionpyscf import run_pyscf
from openfermion.chem.pubchem import geometry_from_pubchem
from openfermion.linalg import get_sparse_operator
from scipy.sparse.linalg import eigs
class Hamiltonian_PySCF():
"""
The UCC_Terms object calcula... |
# -*- coding: utf-8 -*-
import os
import numpy as np
import statsmodels.api as sm # recommended import according to the docs
import matplotlib.pyplot as plt
import pandas as pd
import scipy.stats.mstats as mstats
from common import globals as glob
import seaborn as sns
sns.set(color_codes=True)
from scipy import stats... |
<reponame>PaulPan00/donkey_wrapper
#%%
from IPython.display import Audio
from scipy.io import wavfile
import numpy as np
#%%
file_name = 'C:\\Users\\pyjpa\\Desktop\\aac.wav'
# %%
# Audio(file_name)
# %%
data = wavfile.read(file_name)
framerate = data[0]
sounddata = data[1]
time = np.arange(0,len(sounddata))/framerate
... |
import pandas as pd
import json
import os
import json
import pandas as pd
import time
from PIL import Image
import requests
from io import BytesIO
import numpy as np
from datetime import datetime
import dateutil.relativedelta
from dateutil.parser import parse
from scipy import stats
import ast
import sys
import google... |
<reponame>isadrtdinov/StarGAN
import torch
import numpy as np
from scipy import linalg
from torch import nn
import torch.nn.functional as F
import torchvision.transforms as T
from torchvision.models import inception_v3
from utils import permute_labels
class FrechetInceptionDistance(object):
"""
Calculates Fre... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
""" Plot ranks of top 100 users in the cyberbullying dataset
Usage: python plot_fig4_top_entities.py
Input data files: ../data/[app_name]_out/complete_user_[app_name].txt, ../data/[app_name]_out/user_[app_name]_all.txt
Time: ~8M
"""
import sys, os, platform
from collecti... |
#!/usr/bin/env python
from scipy.version import version as SciPyVersion
if tuple(int(x) for x in SciPyVersion.split('.')) < (0, 9, 0):
from Scientific.IO.NetCDF import NetCDFFile as netcdf_file
else:
from scipy.io.netcdf import netcdf_file
from numpy import arange, zeros
import height
f = netcdf_file('heigh... |
<filename>data/lsun.py
from torchvision.datasets import VisionDataset
from PIL import Image
import torch
import os
import os.path
import io
import sys
import string
from collections.abc import Iterable
import pickle
import numpy as np
from scipy import ndimage
from typing import Any, Callable, cast, List, Optional, Tup... |
<reponame>gechiru/RNPRF-RNDFF-RNPMF<gh_stars>1-10
#Write by <NAME>, contact: <EMAIL>
# stack (HSI+HSI_EPLBP+LiDAR_EPLBP) ++ Resnet
# 3 deep feature fusion
### use CPU only
#import os
#import sys
#os.environ["CUDA_DEVICE_ORDER"]="PCA_BUS_ID"
#os.environ["CUDA_VISIBLE_DEVICES"]="-1"
## use GPU
import os
import tenso... |
# -*- coding: utf-8 -*-
"""
Created on Wed Sep 11 14:29:48 2019
@author: s166895
"""
import numpy as np
from sklearn.datasets import load_diabetes, load_breast_cancer
import operator
<<<<<<< HEAD
from scipy.special import expit
def distance(X_train, X_test):
return np.sqrt(np.sum(np.power(X_train-X_test, 2))) ... |
import networkx as nx
import sympy as sym
import numpy as np
from netodesys import Dynamical, TermwiseDynamical
__all__ = []
__all__.extend([
'NodewiseSISNet',
'VarwiseSISNet',
'TermwiseSISNet'
])
class NodewiseSISNet(Dynamical, nx.Graph, vars=['S', 'I'],
node_params=['a', 'b']):
... |
import json
import random
import imageio
import os
import argparse
import time
import numpy as np
import tensorflow as tf
from scipy import misc
import utils
from ops import *
import sys
from generate_gif import *
BOOL_LABEL=3
def load_dataset(dataset_file, min_group_size, max_jpgs=-1):
with open(dataset_file) as ... |
import logging
import os
import numpy as np
from astropy import units
from astropy.io import fits
from astropy.table import Table
from astropy.time import Time
from scipy import ndimage
def get_filename(basename, extension='ast', exists=False):
cnt = 0
answer = None
while True:
cnt += 1
f... |
from datetime import timedelta, date
import random
import statistics
from django.conf import settings
from django.contrib import messages
from django.contrib.auth.decorators import login_required
from django.db.models import Sum
from django.http import HttpResponseBadRequest, HttpResponse
from django.shortcuts import ... |
<gh_stars>1-10
"""
This module exposes the RegressionDiagnostic class, which helps the user understand whether or not the required assumptions for their model to work are met.
The theoretical foundation for some of the tests (particularly those based on classical linear regression) can be found in [<NAME>'s regression... |
<gh_stars>1-10
##########################################
# File: util.py #
# Copyright <NAME> 2014. #
# Distributed under the MIT License. #
# (See accompany file LICENSE or copy at #
# http://opensource.org/licenses/MIT) #
##########################################
# Imports
imp... |
"""
Trying to implement the oscillating cap in a
rigid sphere described in Chp. 12 of Beranek and Mello 2012
TODO:
* Implement the special case of alpha = pi/2, described by equations
12.60
"""
from gmpy2 import *
from symengine import *
import mpmath
#mpmath.mp.dps = 15
from sympy import expand,symbols,... |
<filename>pyhrp/marcos.py<gh_stars>1-10
# the original implementation by <NAME> is using recursive bisection
# on a ranked list of columns of the covariance matrix
# To get to this list <NAME> is using what he calls the matrix quasi-diagonlization
# but it's induced by the order (from left to right) of the dendrogram.
... |
# -*- coding: utf-8 -*-
"""
Created on Fri Jan 16 11:42:57 2015
@author: jmilli
"""
import sys
from sympy import Symbol, nsolve
import math
import numpy as np
import matplotlib.pyplot as plt
#from scipy import ndimage
sys.path.append('/Users/jmilli/Dropbox/lib_py/image_utilities')
import rotation_images as rot
fro... |
<reponame>Lioscro/bebi103-9-2
import scipy
import skimage
def subtract_background(im, sigma=50):
"""Subtract background of the given image with a Gaussian blur.
Additional arguments are passed directly on to the skimage.filters.gaussian
function.
:param im: input image to filter
:type im: array-l... |
import numpy as np
from math import cos, sin
import cv2
from scipy.spatial import distance as dist
def eye_aspect_ratio(eye):
# compute the euclidean distances between the two sets of
# vertical eye landmarks (x, y)-coordinates
A = dist.euclidean(eye[1], eye[5])
B = dist.euclidean(eye[2], eye[4])
... |
<filename>dkr-py310/docker-student-portal-310/course_files/experimental/py_precision.py<gh_stars>0
#py_precision.py
"""A brief foray into the precision available with different numeric
data types and some Python libraries you can use to wrangle them."""
#floats controlled by hardware; accurate to nearest binary va... |
##############################################################################
#
# Copyright (c) 2003-2018 by The University of Queensland
# http://www.uq.edu.au
#
# Primary Business: Queensland, Australia
# Licensed under the Apache License, version 2.0
# http://www.apache.org/licenses/LICENSE-2.0
#
# Development unt... |
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