text string |
|---|
import random
import numpy as np
import tensorflow as tf
import scipy.sparse as sp
from graphgallery.sequence.base_sequence import Sequence
class MiniBatchSequence(Sequence):
def __init__(
self,
x,
y,
shuffle=False,
batch_size=1,
*args, **kwargs
):
sup... |
import os
import subprocess
import time
import signal
import random
import logging
import faulthandler
import threading
import functools
from multiprocessing import set_start_method
from droidlet import dashboard
from droidlet.dashboard.o3dviz import o3dviz
import numpy as np
from scipy.spatial import distance
import... |
import os
import time
import PIL
import numpy as np
import scipy.sparse
import cv2
from sklearn.cluster import DBSCAN
from collections import Counter
#from utils.cython_bbox import bbox_overlaps
#from utils.boxes_grid import get_boxes_grid
#import subprocess
#import cPickle
#from fast_rcnn.config import cfg
#import mat... |
<filename>third-party/osqp/tests/basic_qp/generate_problem.py
import numpy as np
import scipy.sparse as spa
import utils.codegen_utils as cu
P = spa.csc_matrix(np.array([[4., 1.], [1., 2.]]))
q = np.ones(2)
A = spa.csc_matrix(np.array([[1.0, 1.0], [1.0, 0.0], [0.0, 1.0], [0.0, 1.0]]))
l = np.array([1.0, 0.0, 0.0, -np... |
import pandas as pd
import scipy.stats
import random
def generate_wb_speed(n):
wb_speed_list = []
for i in range(0,n):
speed_temp = random.uniform(5,20)
wb_speed_list.append(speed_temp)
#print(randomlist)
return(wb_speed_list)
|
<gh_stars>0
from pathlib import Path
import sys
project_dir = Path("__file__").resolve().parents[1]
sys.path.insert(0, '{}/temporal_granularity/'.format(project_dir))
import pandas as pd
import numpy as np
from scipy import signal
import matplotlib.pyplot as plt
import seaborn as sns
import logging
from src.models.man... |
import pandas as pd
import numpy as np
from scipy import stats as sps
from scipy.interpolate import interp1d
from matplotlib import pyplot as plt
from matplotlib.dates import date2num, num2date
from matplotlib import dates as mdates
from matplotlib import ticker
from matplotlib.colors import ListedColormap
from matpl... |
<reponame>planplus/pysem<filename>pysem/model_effects.py<gh_stars>1-10
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""Random Effects SEM."""
import pandas as pd
import numpy as np
from .model_means import ModelMeans
from .utils import chol_inv, chol_inv2, cov, calc_zkz, delete_mx
from .univariate_blup import blup
fr... |
<gh_stars>1-10
import os
import json
import statistics
def calculate_average_grade(my_json_filepath):
with open(my_json_filepath, "r") as json_file:
file_contents = json_file.read()
gradebook = json.loads(file_contents)
grades = [s["finalGrade"] for s in gradebook["students"]] #> [86.7, 95.1, 60... |
import numpy as np
import scipy.stats as stats
import matplotlib.pyplot as plt
# noinspection PyTypeChecker
class DataToolkit:
def __init__(self, data):
self._data = np.asarray(data)
self._sorted_data = np.sort(self._data)
self._n = len(self._data)
self._mean = self._var... |
<reponame>c1-94/MPA
import numpy as np
from scipy.optimize import curve_fit
from scipy.special import gamma, factorial
import csv
file_kappa = "fitting_data_kappa_error_v_a_"
file_maxwell = "fitting_data_maxwell_error_v_a_"
list_a = ["0.0029", "0.0027", "0.0025", "0.0023", "0.0021", "0.0019", "0.0017", "0.0015", "0.0... |
from shutil import copyfileobj
from six.moves import urllib
from sklearn.datasets import get_data_home
from scipy.io import loadmat
import os
def load_mnist():
mnist_alternative_url = "https://github.com/amplab/datascience-sp14/raw/master/lab7/mldata/mnist-original.mat"
cwd = os.getcwd()
data_home = cwd
... |
### This file is a part of the Syncpy library.
### Copyright 2015, ISIR / Universite Pierre et <NAME> (UPMC)
### Main contributor(s): <NAME>, <NAME>,
### <EMAIL>
###
### This software is a computer program whose for investigating
### synchrony in a fast and exhaustive way.
###
### This software is governed by the Ce... |
# Bstar_corrections.py
# <NAME>, Jan 2018
#
# Generates and saves a .npy that contains apf corrections of three (five?) averaged b-star continua for deblazing
import numpy as np
import matplotlib.pyplot as plt
from astropy.io import fits
import seaborn as sb
import spectroseti.apf as apf
import spectroseti.utilities ... |
#!/usr/bin/env python3
import numpy as np
from numpy.linalg import inv
from scipy.spatial import distance
from math import sin
from math import cos
from numba import jit
import numpy as np
from kinematichs.support.matrixs import mdot,Tx,Tz,Ty
def r_jacobian(ax_previus, previus_point, final_point):
# cross per... |
from sklearn.metrics.pairwise import cosine_similarity
from scipy import sparse
import numpy as np
from umap import UMAP
def cosine_similarity_distance(activity):
A_sparse = sparse.csr_matrix(activity)
similarities = cosine_similarity(A_sparse)
similarities = np.triu(similarities, k=1)
ones = np.ones(... |
<filename>utils.py
import cv2
import numpy as np
import numexpr as ne
import pandas as pd
from scipy import spatial
import h5py
import matplotlib.pyplot as plt
def calc_dense_flow(prvs_img,next_img,farneback_param,swap_axes=False):
delta = cv2.calcOpticalFlowFarneback(prvs_img, next_img, None,
... |
from functools import wraps
import logging
import sys
import warnings
if sys.version_info[:2] >= (3, 8):
from functools import cached_property
else:
from backports.cached_property import cached_property
import numpy as np
import scipy.signal
import pandas as pd
from endaq.batch import quat
from endaq.batch.... |
<reponame>jjog22/interpret-community
# ---------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# ---------------------------------------------------------
import numpy as np
import pytest
from scipy.sparse import issparse, csr_matrix
from sklearn.compose im... |
<gh_stars>0
# Copyright (c) 2012, Bayesian Logic, Inc.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright
# notice, this l... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
A python class to read Kongsberg KMALL data format for swath mapping
bathymetric echosounders.
"""
import pandas as pd
import sys
import numpy as np
import struct
import datetime
import argparse
import os
import re
import bz2
import copy
from pyproj import Proj
from sc... |
<reponame>gyyang/olfaction_evolution
"""Model file."""
import os
import pickle
import numpy as np
import tensorflow as tf
from configs import FullConfig, SingleLayerConfig
import scipy.stats as st
class Model(object):
"""Abstract Model class."""
def __init__(self, save_path):
"""Make model.
... |
<filename>src/art_of_geom/geom/var.py
__all__ = \
'Variable', 'Var', \
'VARIABLE_AND_NUMERIC_TYPES', 'OptionalVariableOrNumericType'
from sympy.core.expr import Expr
from sympy.core.symbol import Symbol
from typing import Union
from .._util._tmp import TMP_NAME_FACTORY
from .._util._type import NUMERIC_TYPES... |
import h5py
import numpy as np
import json
import sys
from random import randint
import pylab
from util import sigmoid
import scipy
from attention import SelectiveAttentionModel
import math
import cPickle as pickle
from PIL import Image
import math
#np.random.seed(np.random.randint(1 << 30))
#rng = RandomStreams(seed=... |
# Copyright 2020 The Trieste Contributors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to... |
"""Generator base class"""
from abc import ABC
from collections import namedtuple
import numpy as np
import graphviz
from scipy.stats import bernoulli
from synmod.constants import NUMERIC
IN_WINDOW = "in-window"
OUT_WINDOW = "out-window"
SummaryStats = namedtuple("SummaryStats", ["mean", "sd"])
class TabularGener... |
<filename>src/network/mce_loss.py<gh_stars>0
"""Masked Cross Entropy Loss.
This custom loss function uses cross entropy loss as well as ground truth
data to calculate a loss specific to this use case scenario. It calculates a
regular cross entropy loss, but additionally heavily penalizes any curb
classification that i... |
<gh_stars>1-10
import pandas as pd
import numpy as np
import scipy
import os, sys
import matplotlib.pyplot as plt
import pylab
import matplotlib as mpl
sys.path.append("../utils/")
from utils import *
from stats import *
from parse import *
in_dir = '../../processed-simulations/'
subset = '1en01'
group_good_copy = ... |
# -*- coding: utf-8 -*-
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import numpy as np
from scipy.ndimage import map_coordinates
from scipy.ndimage.interpolation import shift
from scipy.optimize import curve_fit, ... |
<reponame>tza0035/RMG-Py<filename>arkane/encorr/ae.py
#!/usr/bin/env python3
###############################################################################
# #
# RMG - Reaction Mechanism Generator #
# ... |
"""
Copyright (c) 2019 NAVER Corp.
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, modify, merge, publish, distribute, su... |
# -*- coding: utf-8 -*-
"""
Created on Mon Mar 11 16:56:51 2019
@author: x
"""
import numpy as np
from collections import Counter
class MetricesConstants(object):
#qrs_cutoff_distance = 0.2
qrs_cutoff_distance = 0.120 #https://www.sciencedirect.com/science/article/abs/pii/S1746809417300216
def sample_to_tim... |
<filename>shaDow/utils.py
import os
import torch
import glob
import numpy as np
import scipy.sparse as sp
import yaml
from sklearn.preprocessing import StandardScaler
from shaDow.globals import git_rev, timestamp, Logger
from torch_scatter import scatter
from copy import deepcopy
from typing import List, Union
from... |
<reponame>jvrana/caldera<gh_stars>1-10
from typing import Optional
from typing import Type
import torch
from scipy.sparse import coo_matrix
from .indexing import SizeType
from .indexing import unroll_index
def torch_coo_to_scipy_coo(m: torch.sparse.FloatTensor) -> coo_matrix:
"""Convert torch :class:`torch.spar... |
<gh_stars>1-10
#real_time_ABRS
# Copyright (c) 2019 <NAME> UCSB
# Licensed under BSD 2-Clause [see LICENSE for details]
# Written by <NAME>
import numpy as np
import matplotlib.pyplot as plt
import cv2
import pickle
import msvcrt
from scipy import misc #pip install pillow
import scipy
from scipy impo... |
<gh_stars>1-10
# BIAS CORRECTION
import numpy as np
import pandas as pd
from scipy.stats import gamma
from scipy.stats import norm
from scipy.signal import detrend
'''
Scaled distribution mapping for climate data
This is a excerpt from pyCAT and the method after Switanek et al. (2017) containing the functions to perf... |
<reponame>Dee-chen/scGCN<gh_stars>10-100
import pickle as pkl
import scipy.sparse
import numpy as np
import pandas as pd
from scipy import sparse as sp
import networkx as nx
from data import *
from collections import defaultdict
from scipy.stats import uniform
import tensorflow as tf
#' -------- convert graph to speci... |
import keras
from keras.datasets import mnist
from keras.models import Sequential
from keras.layers import Dense, Dropout, Flatten
from keras.layers import Conv2D, MaxPooling2D
from gurobipy import *
import math
import numpy as np
import xlrd #excel
import sys
#quatratic
import datetime
from random import sample
fr... |
"""
Scorelator
"""
import os
from pathlib import Path
from typing import Tuple, Union
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import norm
from .model import CWModel
class Scorelator:
def __init__(self, model: CWModel,
draw_bounds: Tuple[float, float] = (0.05, 0.95),
... |
<reponame>achon22/cs231nLung<gh_stars>1-10
"""
Tutorial followed from https://www.kaggle.com/gzuidhof/full-preprocessing-tutorial
"""
import numpy as np # linear algebra
np.set_printoptions(threshold=np.inf)
import dicom
import os
import scipy.ndimage as ndimage
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d... |
"""
Provides routines for fitting stepwise Bayes regression model.
"""
# License: MIT
from __future__ import absolute_import, division
import collections
import warnings
import arviz as az
import numpy as np
import pandas as pd
import patsy
import scipy.linalg as sl
import scipy.special as sp
import scipy.stats as ... |
<filename>auxiliaries/data_simulators.py
# -*- coding: utf-8 -*-
"""
Created on Wed May 20 10:38:23 2020
@author: <NAME>
This file provides simple classes that allow one to specify both the 'pure'
(uncontaminated) DGP as well as the type of contamination.
Defining things this way is useful because it plays nice wit... |
import scipy as sp
import matplotlib.pylab as plt
import random
from scipy import linalg as la
def kmeans(data, f, N, K, var=1, normalize=False):
change = True
T = data.shape[0]
centroids = initialize(N, K, var, normalize)
old_clusters = computeDistances(data, centroids, f)
iters = 0
while chan... |
<gh_stars>0
import numpy as np
from scipy.signal import lfilter, butter
from scipy.integrate import simps, cumtrapz
from pylab import *
import matplotlib.pyplot as plt
from scipy.constants import g
file_in = "testDataHallwaySkateboardStationary.txt"
# open file with scan data
allData = open(file_in).read().sp... |
# -*- coding: utf-8 -*-
""" utils/utils """
from functools import wraps
from time import time
import numpy as np
import scipy.linalg as splin
def colnorms_squared_new(x):
"""
Calculate and returns the norms of the columns.
Note: Compute in blocks to conserve memory
Args:
x: numpy array
... |
<filename>tests/math/unary/test_scipy_mirror.py<gh_stars>100-1000
import hypothesis.extra.numpy as hnp
import hypothesis.strategies as st
import numpy as np
import pytest
from hypothesis import given, settings
from numpy.testing import assert_array_equal
from scipy import special
from mygrad.math._special import logsu... |
<filename>src/primitives/vonmises.py
# -*- coding: utf-8 -*-
# Copyright (c) 2015-2016 MIT Probabilistic Computing Project
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apa... |
<gh_stars>10-100
import numpy as np
import anndata
import ot
from sklearn.decomposition import NMF
from scipy.spatial import distance_matrix
import scipy
from numpy import linalg as LA
from .helper import kl_divergence, intersect, to_dense_array, extract_data_matrix
def pairwise_align(sliceA, sliceB, alpha = 0.1, diss... |
# coding=utf-8
# Copyright 2022 The Google Research Authors.
#
# 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 applicab... |
import numpy as np
import sympy
from nipy.modalities.fmri import formula, utils, hrf
import pylab
t = formula.Term('t')
def linBspline(t, knots):
""" Create a linear B spline that is zero outside [knots[0],
knots[-1]] (knots is assumed to be sorted).
"""
fns = []; symbols=[]
knots = np.array(knot... |
<filename>apportionment.py
""" Apportionment methods
<NAME>
https://github.com/martinlackner/apportionment/
"""
from __future__ import print_function, division
import string
import math
try:
from gmpy2 import mpq as Fraction
except ImportError:
# slower
from fractions import Fraction
METHODS = ["quota", ... |
<gh_stars>0
# -*- coding: utf-8 -*-
"""
Created on Fri Jul 23 08:59:01 2021
@author: alexa
"""
import numpy as np
import matplotlib.pyplot as plt
from scipy.integrate import solve_ivp
import time
import math
from numpy import pi as pi
from scipy import optimize
#par = [MASSA, MASSB, d_1, d_2, SADDLE_E]
def upo_ana... |
# Original source: https://www.kaggle.com/lopuhin/mercari-golf-0-3875-cv-in-75-loc-1900-s
# Data files can be found on Kaggle: https://www.kaggle.com/c/mercari-price-suggestion-challenge
# They must be stripped of non-ascii characters as Willump does not yet support arbitrary Unicode.
import argparse
import pickle
i... |
import numpy as np
import pylab
from scipy.io.wavfile import write
import os
class Soundcheck:
cnt = 0
cheatcnt = 0
def __init__(self):
self.cnt = 0
self.cheatcnt = 0
def soundanalysis(self, freq, signal_f, makefreq, makedb):
flag = -1
dbsum = 0
datacnt = 0
... |
"""
Author: <NAME>
"""
from statsmodels.compat.platform import PLATFORM_LINUX32, PLATFORM_WIN
from itertools import product
import json
import pathlib
import numpy as np
from numpy.testing import assert_allclose, assert_almost_equal
import pandas as pd
import pytest
import scipy.stats
from statsmodels.tsa.exponentia... |
import os
import scipy.sparse
import common.mongo
import common.utils
import common.settings
tweets = common.mongo.get_tweets(limit=1000)
users = common.mongo.get_users()
docs = common.mongo.get_docs()
annotations = common.mongo.get_annotations()
os.makedirs("data/sim/", exist_ok=True)
t2t_sim = common.settings.ne... |
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import plotly.express as px
import scipy.stats as stats
import statsmodels.api as sm
import statsmodels.stats.contingency_tables as ct
from statsmodels.graphics.gofplots import qqplot
from statsmodels.stats.weightstats import z... |
"""Provide the common bit-vector operators."""
import collections
import functools
import itertools
import math
from sympy.core import cache
from sympy.printing import precedence as sympy_precedence
from cascada.bitvector import context
from cascada.bitvector import core
zip = functools.partial(zip, strict=True)
... |
<filename>sherlockpipe/sherlock.py
import logging
import math
import multiprocessing
import shutil
import pandas
import wotan
import matplotlib.pyplot as plt
import transitleastsquares as tls
import lightkurve as lk
import numpy as np
import os
import sys
from scipy.ndimage import uniform_filter1d
from sherlockpipe.... |
<filename>aydin/it/classic_denoisers/spectral.py
import math
from functools import partial
from typing import Optional, Union, Tuple, Sequence
import numpy
from numba import jit, prange
from numpy.fft import fftshift, ifftshift
from scipy.fft import fftn, ifftn, dctn, idctn, dstn, idstn
from aydin.util.array.outer imp... |
from numpy import array, sqrt, max, zeros_like, int, argmin
from scipy.signal import convolve2d, gaussian
from numba import jit
from collections import deque
from sys import maxsize
from typing import List
import numpy
sobel_kernels = {
'x': array([
[-1, 0, 1],
[-2, 0, 2],
[-1, 0, 1]
])... |
<gh_stars>100-1000
import tensorflow as tf
import numpy as np
import os
import scipy.io
import sys
try:
import cPickle
except:
import _pickle as cPickle
def parse_devkit_meta(devkit_path):
meta_mat = scipy.io.loadmat(devkit_path+'/meta.mat')
labels_dic = dict((m[0][1][0], m[... |
#python分为可变结构与不可变结构，不可变结构基本等于复杂结构，包括list map等。复杂结构的赋值和传参都是传递的引用
# for it in list 中，it是只读的，修改它不会改变list值
import os
import datetime
import shutil
import configparser
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from scipy.interpolate import interp1d
import subprocess
import time
import ... |
<reponame>tjb900/devito
from cached_property import cached_property
from sympy import Basic, Eq
from devito.dimension import Dimension
from devito.symbolics import retrieve_indexed, q_affine
from devito.tools import as_tuple, is_integer, filter_sorted
from devito.types import Indexed
__all__ = ['Scope']
class Vect... |
from math import pi
import numpy as np
import scipy
from spatialmath import SE3
from spatialmath.base import isvector, getvector
def mkgrid(n, s, pose=None):
"""
Create grid of points
:param n: number of points
:type n: int or array_like(2)
:param s: side length of the whole grid
:type s: floa... |
"""
Copyright 2021 <NAME>, <NAME>, GlaxoSmithKline plc; <NAME>, University of Oxford; <NAME>, MIT
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
Unl... |
<reponame>SBRG/xplatform_ica_paper<filename>scripts/core.py
import pandas as pd
import numpy as np
from scipy import stats
import os
DATA_DIR = os.path.abspath(os.path.join(os.path.split(os.path.realpath(__file__))[0],'..','data'))
GENE_DIR = os.path.join(DATA_DIR,'annotation')
gene_info = pd.read_csv(os.path.join(GE... |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import torch.utils.data as data
import numpy as np
import torch
import json
import cv2
import os
from utils.image import flip, color_aug, random_contrast
from utils.image import get_affine_transform, affine_tra... |
# Copyright (c) 2020-2021 by <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, modify, merge, publish, dist... |
import logging
from time import time
from collections import deque
from matplotlib.figure import Figure
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
import numpy as np
from scipy import stats
import progressbar
from pybar.daq.readout_utils import get_col_row_array_from_data_... |
import numpy as np
import pickle as pkl
import networkx as nx
import scipy.sparse as sp
from scipy.sparse.linalg.eigen.arpack import eigsh
import sys
from scipy.sparse.linalg import norm as sparsenorm
from scipy.linalg import qr
# from sklearn.metrics import f1_score
def parse_index_file(filename):
"""Parse index... |
"""
Helpers image processing functions
==================================
"""
import math
import numpy as np
from scipy import ndimage as ndi
from skimage import feature, filters, measure, morphology
import warnings
from utils import setting
def assign_centroids(im_labeled, target_objects):
"""
Assigned objects ... |
<filename>code/aesmc/math.py
import numpy as np
import scipy.misc
import torch
def logsumexp(values, dim=0, keepdim=False):
"""Logsumexp of a Tensor/Variable.
See https://en.wikipedia.org/wiki/LogSumExp.
input:
values: Tensor/Variable [dim_1, ..., dim_N]
dim: n
output: result Tensor... |
<filename>predict_and_recompute/numerical_experiments/callbacks/lanczos_recurrence.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import numpy as np
import scipy as sp
from scipy import sparse
from scipy.sparse import linalg
def lanczos_recurrence(**kwargs):
"""
callback to compute quantities about the Lan... |
# -*- coding: utf-8 -*-
"""
pytests for TemporalStats
"""
from click.testing import CliRunner
import numpy as np
import os
import pandas as pd
import pytest
from scipy.stats import mode
import tempfile
import traceback
from rex.multi_year_resource import MultiYearWindResource
from rex.renewable_resource import WindRes... |
"""
This file is part of gempy.
Created on 21/02/2020
@author: <NAME>
"""
import numpy as np
import matplotlib.colors as mcolors
import pandas as pd
rexFileHeaderSize = 64
rexCoordSize = 22
file_header_size = 86
rexDataBlockHeaderSize = 16
file_header_and_data_header = 102
mesh_header_size = 128
all_header_size =... |
<reponame>sourav-majumder/qtlab
import qt
import time
from constants import *
from ZurichInstruments_UHFLI import ZurichInstruments_UHFLI
import timeout_decorator
from scipy.optimize import minimize
from noisyopt import minimizeCompass
def lo_power(dc):
uhf.set('sigouts/0/offset', float(dc[0]))
uhf.set('... |
<reponame>SzymonZos/Processing-of-digital-images<gh_stars>0
import os
import csv
from collections import defaultdict
import statistics
import re
import matplotlib.pyplot as plt
projectPath = os.path.dirname(os.path.abspath(__file__))
with open(projectPath + r'\logs.csv', 'r') as logFile:
logs = [log for log in csv... |
<reponame>ngunnar/learning-a-deformable-registration-pyramid
#!/usr/bin/env python3
from argparse import ArgumentParser
import nibabel as nib
import numpy as np
from scipy.ndimage.interpolation import zoom as zoom
from model import Model
from DataGenerators import Task1Generator, MergeDataGenerator
import re
import tim... |
# Library of Gaussian Mixture Models
# To-do: convert library into class
# Author: <NAME>
import superimport
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import multivariate_normal
def plot_mixtures(X, mu, pi, Sigma, r, step=0.01, cmap="viridis", ax=None):
ax = ax if ax is not None else p... |
<filename>split_wav.py
#!/usr/bin/env python
from scipy.io import wavfile
import os
import numpy as np
import argparse
from tqdm import tqdm
# Utility functions
def windows(signal, window_size, step_size):
if type(window_size) is not int:
raise AttributeError("Window size must be an integer.")
if typ... |
<reponame>shafferm/fast_sparCC
import pandas as pd
import numpy as np
from numpy.random.mtrand import dirichlet
from functools import partial
from scipy.spatial.distance import squareform
__author__ = 'shafferm'
def variation_mat(frame):
"""
***STOLEN FROM https://bitbucket.org/yonatanf/pysurvey/***
Retu... |
<filename>tests/test_consistency.py
from __future__ import print_function, absolute_import # Compatibility with python 2 and 3
import sys
import numpy, scipy.constants
import os
import logging
logger = logging.getLogger('condor')
logger.setLevel("WARNING")
import condor
SAVE_OUTPUT = False
TESTS_DIR = os.path.dirna... |
"""
Satellite Channels
------------------
A set of tools to determine the transmission channel of various satellites in 30 minute
observation by using rf data in conjunctin with chronological satellite ephemeris data.
"""
import concurrent.futures
import json
import re
from itertools import repeat
from pathlib impor... |
<filename>scattertext/termscoring/ScaledFScore.py
import numpy as np
from scipy.stats import norm, rankdata
from scattertext.Common import DEFAULT_SCALER_ALGO, DEFAULT_BETA
class InvalidScalerException(Exception):
pass
class ScoreBalancer(object):
@staticmethod
def balance_scores(cat_scores, not_cat_scores):
... |
import numpy as _np
import fractions as _fractions
# Available functions:
# ind2sub, gcd, my_chop2
def ind2sub(siz, idx):
'''
Translates full-format index into tt.vector one's.
----------
Parameters:
siz - tt.vector modes
idx - full-vector index
Note: not vectorized.
'''
n ... |
from __future__ import print_function
import pytest
import numpy as np
import random
from numpy.testing import assert_equal, assert_almost_equal
from choreo.interlock import compute_feasible_region_from_block_dir
from pybullet_planning import Euler, Pose, multiply, tform_point
from scipy.optimize import linear_sum_ass... |
<filename>molmap/utils/vismap.py
from scipy.cluster.hierarchy import dendrogram, linkage, to_tree
from scipy.spatial.distance import squareform
import seaborn as sns
from highcharts import Highchart
import pandas as pd
import numpy as np
import os
from molmap.utils.logtools import print_info
def plot_scatter(molmap... |
<filename>VCD/vc_dynamics.py
import os
import os.path as osp
import copy
import cv2
import json
import wandb
import numpy as np
import scipy
from tqdm import tqdm
from chester import logger
import torch
import torch_geometric
from softgym.utils.visualization import save_numpy_as_gif
from VCD.models import GNN
from V... |
<reponame>VariantEffect/Enrich2-py3
"""
Enrich2 selection module
========================
This module contains the class used by ``Enrich2`` to represent a selection
of sequencing libraries, which manages libraries.
"""
import logging
import numpy as np
import pandas as pd
import scipy.stats as stats
from ..base.co... |
import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
#自定义函数 e指数形式
def func(x, a, b,c):
return a*np.square(np.log(x))+b*np.log(x)+c
#定义x、y散点坐标
x = [20,30,40,50,60,70]
x = np.array(x)
num = [453,482,503,508,498,479]
y = np.array(num)
#非线性最小二乘法拟合
popt, pcov = curve_fit(func, x, y)
... |
<reponame>akmenon1996/akmenon1996-ReinforcementLearning-Temperature-Control
import PID
import time
import matplotlib.pyplot as plt
import numpy as np
#from scipy.interpolate import spline
from scipy.interpolate import BSpline, make_interp_spline # Switched to BSpline
def test_pid(P = 0.2, I = 0.0, D= 0.0, L=100):
... |
import os
import argparse
import scipy.io as sio
from PIL import Image
def get_yolo_bbox(bboxes, image_width, image_height):
yolo_bbox = []
for bbox in bboxes:
bbox = [e.squeeze().tolist() for e in bbox]
h, l, t, w, label = bbox
if label == 10:
label = 0
xc = (l+w... |
<reponame>yoelcortes/Bioindustrial-Complex<filename>BioSTEAM 2.x.x/biorefineries/TAL/system_TAL_adsorption_glucose.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Bioindustrial-Park: BioSTEAM's Premier Biorefinery Models and Results
# Copyright (C) 2022-2023, <NAME> <<EMAIL>> (this biorefinery)
#
# This module is ... |
from sklearn.neural_network import MLPClassifier
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score, classification_report
from sklearn.metrics import confusion_matrix
import pandas as pd
import numpy as np
from window_slider import Slider
from MLP.FirFilter import FirFilter... |
<reponame>jenskutilek/nibLib
import cmath
# a = 300
# b = 200
# phi = radians(45)
# alpha = 30
# nib_angle = 5
Variable([
dict(name="a", ui="Slider",
args=dict(
value=300,
minValue=0,
maxValue=500)),
dict(name="b", ui="Slider",
args=dict(
value... |
<filename>libfmp/c6/c6s1_peak_picking.py
"""
Module: libfmp.c6.c6s1_peak_picking
Author: <NAME>, <NAME>
License: The MIT license, https://opensource.org/licenses/MIT
This file is part of the FMP Notebooks (https://www.audiolabs-erlangen.de/FMP)
"""
import numpy as np
from scipy.ndimage import filters
def peak_picki... |
#!/usr/bin/env python
import rospy # ROS interface
import pymap3d as pm # coordinate conversion
# msgs
from formation.msg import RobotFormationState, FormationPositions
from std_msgs.msg import Empty, Int32
from geometry_msgs.msg import Point, PointStamped
from sensor_msgs.msg import NavSatFix
from mavros_msgs.msg im... |
<reponame>lanadescheemaeker/logistic_models<filename>neutral_covariance_test.py
# translation of the original Washburne code in R
import scipy.stats
from scipy.special import kolmogorov
import numpy as np
from statsmodels.stats.diagnostic import het_breuschpagan
import pandas as pd
import statsmodels.api as sm
import ... |
<gh_stars>0
from SCN import SCN
from Fractal_generator import koch, binary_frac
import torch
from torch.autograd import Variable
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
from mpl_toolkits.mplot3d import Axes3D
import pickle
from scipy.stats import multivariate_normal
X = np.arange(... |
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