text string |
|---|
from __future__ import print_function
import argparse
import os
import torch
import torch.nn as nn
import torch.optim as optim
from torch.autograd import Variable
from torch.utils.data import DataLoader
from rbpn import Net as RBPN
from data import get_test_set
from functools import reduce
import numpy as np
# from s... |
from sklearn.model_selection import train_test_split
from sklearn.metrics import classification_report
import matplotlib.pyplot as plt
from matplotlib.patches import Patch
import matplotlib.gridspec as gridspec
import scipy.io as scio
import numpy as np
from minisom import MiniSom
import math
import torch
fro... |
<reponame>jajool/pipepy
import os
import json
import numpy as np
from scipy import interpolate
class CompFactorInterpolator:
address = os.path.join(
os.path.dirname(__file__), os.pardir, 'databases', "z.json")
def __init__(self):
with open(self.address) as fp:
points = np.array(js... |
import numpy as np
import scipy.signal
import matplotlib.pyplot as plt
import gym
from numpy.random import choice
import random
import time
N_POS = 150
N_VEL = 120
VALUE_STEP_SIZE = 1e-2 # faster than policy
POLICY_STEP_SIZE = 1e-3
NUM_EPISODES = 1000
GAMMA = 0.999
TEMPERATURE = 1000
EPSILON = 1
ACTIONS = [-1, 0,... |
#!/usr/bin/env python
# --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by <NAME>
# --------------------------------------------------------
"""Train a Fast R-CNN network on a region of interest d... |
import cmath
import math
from tkinter import W
polos = 8
freq = 60
t1 = 380
t2 = 220
r1 = 0.19
r2L = 0.11
x1 = 0.45
x2L = 0.21
rp = 130
xm = 22
perdastotais = 1735
rpm = 400
ns = 120*freq/polos
print("ns = ", ns)
s = (ns - rpm)/ns
print("s = ", s)
aux1=[x1+x2L]
Zs = complex(r1+r2L/s,sum(list(aux1)))
print("Zs = ",... |
import numpy as np
import tensorflow as tf
import tensorflow.keras.backend as K
from scipy.ndimage.interpolation import zoom
from tensorflow.python.keras.layers.convolutional import Conv
from tf_keras_vis import ModelVisualization
from tf_keras_vis.utils import find_layer
class Gradcam(ModelVisualization):
def _... |
<reponame>Jahidul007/Python-Bootcamp
import nltk
import random
from nltk.corpus import movie_reviews
from nltk.classify.scikitlearn import SklearnClassifier
from sklearn.linear_model import LogisticRegression,SGDClassifier
from sklearn.svm import SVC, LinearSVC, NuSVC
import pickle
from sklearn.naive_bayes import Multi... |
from __future__ import print_function, division
__all__ = ['Particle']
from sympy import sympify
from sympy.physics.vector import Point
class Particle(object):
"""A particle.
Particles have a non-zero mass and lack spatial extension; they take up no
space.
Values need to be supplied on initializat... |
<filename>ompclib/ompclib_numpy.py
# This file is a part of OMPC (http://ompc.juricap.com/)
#
# for testing:
# import ompclib_numpy; reload(ompclib_numpy); from ompclib_numpy import *
# TODO
# - remove all references to array, use "ompc_base._init_data" instead
import sys, os; sys.path.append(os.path.absp... |
# ---
# jupyter:
# jupytext:
# text_representation:
# extension: .py
# format_name: light
# format_version: '1.5'
# jupytext_version: 1.11.3
# kernelspec:
# display_name: Python 3
# name: python3
# ---
# + [markdown] id="view-in-github" colab_type="text"
# <a href="https://colab... |
# Copyright 2018 The Cirq Developers
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in ... |
<reponame>jonathanishhorowicz/RATE_python_package
import numpy as np
import pandas as pd
import tensorflow as tf
from sklearn.preprocessing import OneHotEncoder
from sklearn.metrics import roc_curve, auc
import matplotlib.pyplot as plt
import seaborn as sns
from scipy.stats import rankdata
import time
import logging
l... |
<reponame>NunoEdgarGFlowHub/cvxpy
"""
Copyright 2013 <NAME>
This file is part of CVXPY.
CVXPY is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later versio... |
## Source : https://github.com/naokishibuya/car-behavioral-cloning/blob/master/utils.py
import os
import cv2
import sklearn
import math
import csv
import numpy as np
from scipy.ndimage import rotate
from scipy.stats import bernoulli
IMAGE_HEIGHT, IMAGE_WIDTH, IMAGE_CHANNELS = 66, 200, 3
INPUT_SHAPE = (IMAGE_HEIGHT,... |
<reponame>DanAmador/BeamNGpy
import sys
from time import sleep
import numpy as np
from scipy import interpolate
from beamngpy import BeamNGpy, Scenario, Road, Vehicle, setup_logging
SIZE = 1024
def main():
setup_logging()
beamng = BeamNGpy('localhost', 64256)
bng = beamng.open(launch=True)
sce... |
<filename>top_pop_rec.py<gh_stars>1-10
import numpy as np
import pandas as pd
from tqdm import tqdm
from definitions import ROOT_DIR
from scipy import sparse as sps
class TopPopRecommender(object):
"""
An unpersonalized top popular recommender. It recommends the top 500 tracks for each playlist.
"""
... |
"""
Numerical tools
"""
from functools import partial
import numpy as np
from scipy.interpolate import splrep, splev
import astropy.units as u
__all__ = ['vectorize_where', 'vectorize_where_sum', 'burgess_tully_descale']
def vectorize_where(x_1, x_2):
"""
Find indices of one array in another
Parameters
... |
<reponame>bridgejio/2019_nCov_predcition<gh_stars>1-10
#!/usr/bin/env python
# coding: utf-8
# ## Class Encapsulation for SEIR Model
# In[1]:
import pandas as pd
import numpy as np
import warnings
import matplotlib.pyplot as plt
warnings.filterwarnings('ignore')
# ### hyperopt for seir model parameters optimizat... |
<filename>examples/000_sphere/000_sphere_xfields3D.py
import time
import numpy as np
from numpy.random import rand
from scipy.constants import epsilon_0
from numpy import pi
from xobjects import ContextCpu, ContextCupy, ContextPyopencl
from xfields import TriLinearInterpolatedFieldMap
context = ContextCpu()
context ... |
<reponame>Pandinosaurus/lapjv<gh_stars>100-1000
import unittest
from numpy import array, dstack, float32, float64, linspace, meshgrid, random, sqrt
from scipy.spatial.distance import cdist
from lapjv import lapjv
class LapjvTests(unittest.TestCase):
def _test_random_100(self, dtype):
random.seed(777)
... |
<reponame>fmi-basel/gzenke-nonlinear-transient-amplification<filename>src/Fig_7_Spiking_neuron_networks_EE_STP_random_patterns.py
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from sympy.solvers import solve
from sympy import Symbol
from matplotlib import patches
import matplotlib.patches as ... |
<reponame>ivandebono/montepython_public_3.2dev_Python3
"""
.. module:: mcmc
:synopsis: Monte Carlo procedure
.. moduleauthor:: <NAME> <<EMAIL>>
This module defines one key function, :func:`chain`, that handles the Markov
chain. So far, the code uses only one chain, as no parallelization is done.
The following rout... |
# Kernel PCA toy example for k(x,y)=exp(-||x-y||^2/rbf_var)
# Author: <NAME>
import superimport
import numpy as np
import matplotlib.pyplot as plt
import scipy.linalg as la
from scipy.spatial.distance import pdist, cdist, squareform
rbf_var = 0.1
xnum = 4
ynum = 2
max_ev = xnum*ynum
x_test_num = 15
y_test_num = 15
c... |
import sys
import numpy as np
import pandas as pd
import scipy.stats
from sktime.transformers.series_as_features.base import \
BaseSeriesAsFeaturesTransformer
from sktime.transformers.series_as_features.dictionary_based import PAA
from sktime.utils.data_container import tabularize
# TO DO: verify this returned ... |
<filename>liesym/algebras/_classic.py<gh_stars>1-10
from sympy.core.sympify import _sympify
from sympy import Matrix, flatten
from ._base import LieAlgebra, NumericSymbol
def _euclidean_root(i, n):
root = [0]*n
root[i] = 1
try:
root[i+1] = -1
except IndexError:
pass # catches B last ... |
<reponame>changhoonhahn/feasiBGS
'''
validating the sky model
'''
import os
import pickle
import numpy as np
from scipy.interpolate import interp1d
from speclite import filters
# -- astropy --
import astropy.time
import astropy.coordinates
from astropy.io import fits
from astropy import units as u
from astropy.tabl... |
<filename>malsynth/base.py
import dataclasses
import numbers
import numpy as np
from scipy import signal
class PitchToHz:
def __init__(self):
self.two_pi = 2 * np.pi
self._data = {}
def __call__(self, pitch):
"""Technically doesn't return hz but instead hz * 2 * pi.
Args:
... |
<filename>ClusteringRelatedPosts/solution.py
import scipy as sp
from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer
import nltk.stem
stemmer = nltk.stem.SnowballStemmer('english')
class StemmedCountVectorizer(CountVectorizer):
def build_analyzer(self):
analyzer = super(CountVect... |
<filename>cylinder.py<gh_stars>0
import numpy as np
import matplotlib.pyplot as plt
import scipy.optimize
import pdb
import utilities.imaging.man as man
import utilities.imaging.fitting as fit
import scipy.ndimage as nd
from utilities.plotting import scatter3d
import utilities.plotting
from utilities.imaging.analysis i... |
import csv
import pylab
import numpy as np
import uuid
from numpy import vstack,array
from scipy.cluster.vq import *
from flask import Flask,render_template,request
app = Flask(__name__,template_folder="static")
coloumn_names = ["pclass","survived","name","sex","age","sibsp","parch","ticket","fare","cabin","embarked",... |
import numbers
import dolfin as fem
import munch
import numpy as np
import sympy as sym
from scipy import interpolate as intp
import domain2
import mtnlion.comsol as comsol
import mtnlion.engine as engine
import utilities
def prepare_comsol_buildup():
# cmn = Common(time)
cmn = Common()
domain = cmn.dom... |
'''
Generate a time series incorporating the motion of the screen across the source.
This script may take a long time to run. I suggest you read through it first and
adjust the num_samples variable to check out its performance.
'''
import numpy as np
from scipy.ndimage import imread
import time
import matplotlib.pyplot... |
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""A miscellaneous collection of basic functions."""
import sys
import copy
import os
import warnings
from collections.abc import Iterable
from pathlib import Path
import tempfile
from scipy.interpolate import interp1d
from scipy.stats import ncx2
import... |
<filename>utils/misc.py
import cPickle as pickle
import numpy as np
import networkx as nx
import operator
import sys
import itertools
from scipy.stats import pearsonr
def run_it_uconn(wdir, script_txt, n, m, k, missing=None):
# write it.
script_file = '%s/script.sh' % wdir
with open(script_file, "wb") as ... |
<reponame>BystrickyK/SINDy<gh_stars>1-10
import pandas as pd
import matplotlib.pyplot as plt
from src.utils.identification.PI_Identifier import PI_Identifier
from src.utils.solution_processing import *
from differentiation.spectral_derivative import compute_spectral_derivative
from filtering.SpectralFilter import Spect... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
""" CPU time comparison of resampling implementations.
See Python corner of Chapter 9 (importance resampling) for more
explanations.
Notes:
1. this works only if numba is installed, see install notes.
2. Takes approx 1h 10min
3. If run on Pyth... |
<filename>pyigm/continuum/quasar.py<gh_stars>10-100
""" Module for quasar continuum code
"""
from __future__ import print_function, absolute_import, division, unicode_literals
import numpy as np
import os
import pdb
from pkg_resources import resource_filename
from scipy.interpolate import interp1d
from astropy impo... |
<gh_stars>0
# %% [markdown]
# ## 0 | Import packages and load data
# %%
# Import packages
import os
import tkinter
from tkinter.filedialog import askopenfilename, askopenfilenames, askdirectory
import h5py
from collections import defaultdict
from nptdms import TdmsFile
import numpy as np
import pandas as pd
import sea... |
import numpy as n
import scipy as s
import matplotlib as m
import sklearn as sk
import pandas as p
import tensorflow as t
result = t.__version__ >= '1.3.1' and m.__version__ >= '2.0.2' and sk.__version__ >= '0.18.2' and p.__version__[1:] >= '0.20.3' and s.__version__ >= '0.19.1' and n.version.version >= '1.13.1'
resu... |
<gh_stars>10-100
import numpy as np
import scipy.io as sio
import matplotlib.pyplot as plt
import time
import skimage.io as io
from skimage.segmentation import slic,mark_boundaries
class SegmentMap(object):
def __init__(self,datasetname:np.array):
if datasetname=='indian_':
... |
<filename>pysptools/spectro/hull_removal.py
#
#------------------------------------------------------------------------------
# Copyright (c) 2013-2014, <NAME>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a... |
<reponame>simonsobs/ps_py<filename>project/old/analyse_sims/sim_spectra_model.py<gh_stars>10-100
"""
This script is used for the modeling the theoretical spectra that goes into the covariance computation.
At the moment, we simply used interpolation and extrapolation of the signal only spectra, we hope to change this to... |
<reponame>AkashKumarSingh11032001/Google-KickStart
from sympy.core.cache import cacheit
from sympy import binomial
print(binomial(500, 2))
def fac(b):
if b==1:
return 1
else:
return b * fac(b-1)
def combinations(n,k):
result = (fac(n)) / (fac(k) * fac(n-k))
return result
print(50... |
<filename>networkExperiments.py
#!/usr/bin/env python
# coding: utf-8
import numpy as np
import numpy.linalg as lin
import networkx as nx
import scipy
import matplotlib.pyplot as plt
from scipy.stats import chi2_contingency
# # Spectral norm from degree sequences
# In this notebook we demonstrate experimently that ... |
from time import sleep
import numpy as np
from scipy.fft import fft
from scipy.integrate import simps
NUM_SAMPLES = 1024
SAMPLING_RATE = 44100.
MAX_FREQ = SAMPLING_RATE / 2
FREQ_SAMPLES = NUM_SAMPLES / 8
TIMESLICE = 100 # ms
NUM_BINS = 16
data = {'values': None}
try:
import pyaudio
def update_audio_data()... |
<reponame>yamsam/G2Net-GoGoGo<gh_stars>1-10
import torch
from torch import nn
from scipy import signal
import torch.nn.functional as F
class GeM(nn.Module):
'''
Code modified from the 2d code in
https://amaarora.github.io/2020/08/30/gempool.html
'''
def __init__(self, kernel_size=8, p=3, eps=1e-6... |
# -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import numpy as np
from numpy import testing as npt
from ...tests.helper import pytest, assert_quantity_allclose as assert... |
import sympy.physics.mechanics as me
import sympy as sm
import math as m
import numpy as np
x1, x2 = me.dynamicsymbols('x1 x2')
f1 = x1*x2+3*x1**2
f2 = x1*me.dynamicsymbols._t+x2*me.dynamicsymbols._t**2
x, y = me.dynamicsymbols('x y')
xd, yd = me.dynamicsymbols('x y', 1)
yd2 = me.dynamicsymbols('y', 2)
q1, q2, q3, u1,... |
import numpy as np
import scipy.sparse as sp
import numba
from numba import njit
from ..base_transforms import SparseTransform
from ..transform import Transform
from ..sparse import add_selfloops, eliminate_selfloops
@Transform.register()
class NeighborSampler(SparseTransform):
def __init__(self, max_degree: in... |
# Copyright (c) 2019-2020, NVIDIA CORPORATION.
# 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... |
<reponame>Bmete7/bark
# Copyright (c) 2020 fortiss GmbH
#
# Authors: <NAME>, <NAME>, <NAME> and
# <NAME>
#
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
import unittest
import numpy as np
from scipy.special import fresnel
from bark.core.world.open... |
<reponame>dice-group/NETL-Automatic-Topic-Labelling-
"""
Author: <NAME>
Date: October 2016
File: supervised_labels.py
Updated by: <NAME>
Date: January 7, 2019
Fix: Updated to work with Python 3.6.5
This python code gives the top supervised labels for that topic. The paramt... |
"""
Tools for DESI spectroperfectionism extractions implemented for a CPU
"""
import sys
import numpy as np
from numpy.polynomial.legendre import legvander, legval
from numpy.polynomial import hermite_e as He
import scipy.special
import numba
#-------------------------------------------------------------------------
... |
<filename>torch_geometric_signed_directed/utils/signed/unhappy_ratio.py
import torch
import scipy.sparse as sp
from ..general.scipy_sparse_to_torch_sparse import scipy_sparse_to_torch_sparse
class Unhappy_Ratio(torch.nn.Module):
r"""A calculation of the ratio of unhappy edges among all edges from the
`SSSNET:... |
<reponame>Corentin-LF/pyGPs<filename>pyGPs/GraphExtensions/graphKernels.py
from __future__ import division
from builtins import str
from builtins import range
from past.utils import old_div
#================================================================================
# <NAME> [marion dot neumann at uni-bonn dot ... |
'''
Run this script to train the NN. Loads the problem and configuration
according to examples/choose_problem.py.
'''
import numpy as np
import tensorflow as tf
import scipy.io
import time
from utilities.other import int_input, load_NN
from examples.choose_problem import system, problem, config, time_dependent
if ti... |
<reponame>dliu5812/PDAM
import numexpr as ne
from sklearn.metrics import f1_score
import os
import numpy as np
from scipy.optimize import linear_sum_assignment
# fast version of Aggregated Jaccrd Index
def agg_jc_index(gt_ins, pred):
from tqdm import tqdm_notebook
"""Calculate aggregated jaccard index for p... |
import itertools
import numpy as np
import scipy
import scipy.signal as signal
__all__ = ['gaussian_kernel', 'blur_image', 'resample_array']
def gaussian_kernel(size, sigma, mesh_deltas=None):
""" Returns a normalized gauss kernel array for convolutions.
Parameters
----------
size : iterable
... |
import logging
import math
import hashlib
from functools import partial
from inspect import getmembers
from itertools import repeat
import numpy as np
import datajoint as dj
import scipy.stats as sc_stats
from . import lab
from . import experiment
from . import ephys
[lab, experiment, ephys] # NOQA
from . import ... |
from ddapp.consoleapp import ConsoleApp
from ddapp import robotsystem
from ddapp import robotstate
from ddapp import planplayback
from ddapp import lcmUtils
from ddapp import drcargs
from ddapp import roboturdf
from ddapp import simpletimer
from ddapp.timercallback import TimerCallback
from ddapp.fieldcontainer import ... |
"""
This code tests features in development.
"""
import mfanalysis as mf
import os
import numpy as np
from scipy.io import loadmat
#-------------------------------------------------------------------------------
# Function to load data
#-------------------------------------------------------------------------------
... |
<reponame>aragilar/astroML
"""
Example of a Fourier Transform
------------------------------
Figure E.1
An example of approximating the continuous Fourier transform of a function
using the fast Fourier transform.
"""
# Author: <NAME>
# License: BSD
# The figure produced by this code is published in the textbook
# ... |
<reponame>lev1khachatryan/ASDS_DSP
# sampling rate = 16000 , points per second
# 1) compute power of this wav
# 2) create function which plots previously defined segment of data
# 3) study signal data (print various segments of signal)
# 4) write new wav with 2 times greater volume
import numpy as np
import scipy.io.w... |
<filename>projects/dataprep/bg_ols_multiprocessing.py
"""
author: <NAME> 2019 - 07 - 29
Determine background overlaps using means and covariances for both
background and stars.
Covariance matrices for the background are Identity*bandwidth.
Parameters
----------
background_means: [nstars,6] float array_like
Phase-... |
import decimal
import math
import numpy as np
import pywt
from scipy.io import wavfile
def units_to_sample(x, unit, sr):
unit = unit.lower()
if unit == "ms":
return ms_to_sample(x, sr)
if unit == "s":
in_ms = float(x) * 1000
return ms_to_sample(in_ms, sr)
if unit == "sample":... |
###############################################################################
# Copyright (c) 2007-2018, National Research Foundation (Square Kilometre Array)
#
# Licensed under the BSD 3-Clause License (the "License"); you may not use
# this file except in compliance with the License. You may obtain a copy
# of the ... |
import speechbrain as sb
import os
import torch
import logging
import numpy as np
import speechbrain as sb
from tqdm.contrib import tqdm
from torch.utils.data import DataLoader
from denoiser.losses import task1_metric
import speechbrain.nnet.schedulers as schedulers
from scipy.io import wavfile
from pesq import pesq
... |
<filename>scipy/linalg/_matfuncs_inv_ssq.py
"""
Matrix functions that use Pade approximation with inverse scaling and squaring.
"""
from __future__ import division, print_function, absolute_import
import warnings
import numpy as np
from scipy.linalg._matfuncs_sqrtm import SqrtmError, _sqrtm_triu
from scipy.linalg.d... |
<gh_stars>0
import importlib
from hydroDL.master import basins
from hydroDL.app import waterQuality, wqLinear, wqRela
from hydroDL import kPath
from hydroDL.model import trainTS
from hydroDL.data import gageII, usgs, gridMET, transform
from hydroDL.post import axplot, figplot
import torch
import time
import numpy as n... |
<reponame>crocaos/OpenCV-4-with-Python-Blueprints-Second-Edition
import cv2
import numpy as np
from scipy.interpolate import UnivariateSpline
def display_img(img):
# Display image
cv2.imshow('image', img)
cv2.waitKey(0)
cv2.destroyAllWindows()
def resized(img_rgb, scale):
scale_percent = scale
... |
<filename>pycompvis/compvis/feature/detectors.py
"""
Feature detection (Szeliski 4.1.1)
"""
import numpy as np
import scipy.signal as sig
import scipy.ndimage as ndi
from compvis.utils import get_patch
def sum_sq_diff(img_0, img_1, u, x, y, x_len, y_len):
"""
Returns the summed square difference between two im... |
<filename>discovery/pair_discovery.py
# coding: utf-8
import outils
import sys
sys.path.append("..")
from model.model import Model
import torch
import os
from torchvision import datasets, transforms,models
import numpy as np
from tqdm import tqdm
import ujson
import cv2
import argparse
import warnings
import PIL.I... |
<reponame>samuelcolvin/notbook
from notbook import show_plot
from bokeh.plotting import figure
import numpy as np
import scipy.optimize as opt
"""md
_This is an example of a better way to work on and display numerical python code._
[Here's](https://github.com/samuelcolvin/notbook/blob/master/demo-script.py) the input... |
<reponame>kidrabit/Data-Visualization-Lab-RND
import sys
import os
import csv
import math
import json
import random
from datetime import datetime
import numpy as np
import pandas as pd
import cv2
from scipy.spatial.distance import euclidean
from fastdtw import fastdtw
from collections import OrderedDict... |
<gh_stars>1-10
import pandas as pd
import numpy as np
from scipy import stats
from transformers import AutoModelWithLMHead, AutoTokenizer, AutoModelForMaskedLM, AutoModelForCausalLM, AutoModelWithLMAndDebiasHead
import time
import seaborn as sns
import matplotlib.pyplot as plt
import logging
import argparse
import torc... |
"""
## Reference from: Multi-Stage Progressive Image Restoration
## Syed <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, and <NAME>
## https://arxiv.org/abs/2102.02808
"""
import numpy as np
import os
import argparse
from tqdm import tqdm
import torch
import utils
from model_arch.SRMNet_SWFF import SRM... |
# Assignment 1 for ME4233
# Author: <NAME>
# Prof: <NAME>
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits import mplot3d
from itertools import product
from scipy.sparse import dia_matrix, csr_matrix, csc_matrix, lil_matrix, identity, tril, triu
# Main functions used
def assemble_algebr... |
# A manufacturer purchases a part for use at both of its plantsdashone at Roseville, California, the other at Akron, Ohio.
# The part is available in limited quantities from two suppliers.
# Each supplier has 85 units available.
# The Roseville plant needs 50 units, and the Akron plant requires 85 units.
# Th... |
<filename>build/lib/mageck/mleem.py
'''
Defining the core EM MLE approach
'''
import re
import sys
import scipy
from scipy.stats import nbinom
from scipy.stats import norm
import random
import math
import numpy as np
import numpy.linalg as linalg
import copy
from mageck.mleclassdef import *
from mageck.mledesignmat... |
<reponame>verypluming/SyGNS
# -*- coding: utf-8 -*-
import pandas as pd
from statistics import stdev
import argparse
import glob
parser = argparse.ArgumentParser(
formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument("--outdir", nargs='?', type=str, help="output dir")
parser.add_argument("-... |
<gh_stars>0
import math
import os
from adjustText import adjust_text
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import ImageGrid
import numpy as np
from scipy.stats import linregress
from process import DicomProcess
case = 2
site = None # None for all except 1
dir_loc = './data/to_process/'
test_... |
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
import scipy
from scipy.spatial.distance import cdist
from .anchor_head_template import AnchorHeadTemplate
class Self_Attn(nn.Module):
""" Self attention Layer"""
def __init__(self,in_dim,activation):
super(Self_Attn... |
#!/usr/bin/ python
# -*- coding: utf-8 -*-
"""
Created on Sun Oct 2 18:33:10 2016
Modified from https://stackoverflow.com/questions/38076682/how-to-add-colors-to-each-individual-face-of-a-cylinder-using-matplotlib
to add "end caps" and to undo fancy coloring.
@author: astrokeat
"""
import numpy as np
from matplotli... |
<gh_stars>0
#!/usr/bin/env python
"""
LPU output visualization.
"""
import collections
from collections import OrderedDict
import itertools
import os
import h5py
from future.utils import itervalues, iteritems
import matplotlib
from matplotlib import cm
from matplotlib.colors import Normalize
import matplotlib.pyplot... |
# Authors: <NAME> (<EMAIL>), <NAME> (<EMAIL>), <NAME> (<EMAIL>)
import os
import yaml
import logging
import time
import psutil
import argparse
import pandas as pd
import numpy as np
import multiprocessing as mp
from scipy.integrate import solve_ivp
from scipy.optimize import minimize
from datetime import datetime, time... |
<gh_stars>0
import numpy as np
import scipy
import GPyOpt
import GPy
from multi_objective import MultiObjective
from multi_outputGP import multi_outputGP
from maEI import maEI
from parameter_distribution import ParameterDistribution
from utility import Utility
import cbo
# --- Function to optimize
m = 5 # Number of ... |
<reponame>swederik/structurefunction<gh_stars>1-10
import os
import os.path as op
import nipype.interfaces.io as nio # Data i/o
import nipype.interfaces.utility as util # utility
import nipype.pipeline.engine as pe # pypeline engine
import nipype.interfaces.fsl as fsl
import nipype.interfaces.fre... |
<filename>cryomem/cmtools/lib/sfs.py
# -*- coding: utf-8 -*-
"""
SFS JJ data fitting etc.
@author: burm
"""
#import pylab as pl
import numpy as np
from scipy.optimize import curve_fit, root
from scipy.special import sici
from scipy.integrate import quad
e = 1.60217657e-19
hbar = 1.05457173e-34
kb = 1.3806488e-23
... |
# -*- coding: utf-8 -*-
"""
=======================================================
Math helper functions (:mod:`sknano.core._extras`)
=======================================================
.. currentmodule:: sknano.core._extras
"""
from __future__ import absolute_import, division, print_function
from __future__ imp... |
<filename>gptf/core/models.py
# -*- encoding: utf-8 -*-
"""Provides base classes for models of all kinds."""
from builtins import super, range
from future.utils import with_metaclass
from abc import ABCMeta, abstractmethod
import numpy as np
import tensorflow as tf
from tensorflow.contrib.opt import ScipyOptimizerInte... |
import pandas as pd
from scipy.io import loadmat
import os
from python_speech_features import logfbank
import matplotlib.pyplot as plt
import numpy as np
import librosa
import librosa.display
import pickle
import math
import glob
import regex as rgx
from pathlib import Path
n_time_frames = 41
n_frequency_bands = 40
... |
def Halo_Plot(Data):
##### HALO ORBITS PLOTTING TOOL #####
#
# Importing required functions
#
import numpy as np
from scipy import linalg
from scipy.integrate import solve_ivp
from .intFun import ThreeBodyProp, DiffCorrection
import matplotlib.pyplot as plt
from mpl_toolkits.mplo... |
from __future__ import print_function
import numpy as np
np.random.seed(1337) # for reproducibility
import os
import sys
import multiprocessing
from scipy import misc
from keras.utils import np_utils
from keras import backend as K
from keras.preprocessing.image import ImageDataGenerator
from skimage.filter import thre... |
<reponame>TangYucopper/GCC
import argparse
import copy
import random
import warnings
from collections import defaultdict
import networkx as nx
import numpy as np
import scipy.sparse as sp
import torch
import torch.nn.functional as F
from scipy import sparse as sp
from sklearn.linear_model import LogisticRegression
fro... |
"""
There are N workers. The i-th worker has a quality[i] and a minimum wage expectation wage[i].
Now we want to hire exactly K workers to form a paid group. When hiring a group of K workers, we must pay them according to the following rules:
Every worker in the paid group should be paid in the ratio of their quali... |
# -*- coding: utf-8 -*-
u"""Integrate an ion and a magnetized electron forward in time,
using the original phase space coordinates.
The fast Larmor oscillations of the electron must be resolved.
:copyright: Copyright (c) 2017 RadiaSoft LLC. All Rights Reserved.
:license: http://www.apache.org/licenses/LICENSE-... |
<gh_stars>10-100
from itertools import combinations
import numpy as np
import torch
import torch.nn.functional as F
from sklearn.metrics import roc_curve
from scipy.interpolate import interp1d
from scipy.optimize import brentq
def eer(y_true, y_pred):
fpr, tpr, thres = roc_curve(y_true, y_pred, pos_label = 1)
... |
<filename>tensorbay/opendataset/Flower/loader.py
#!/usr/bin/env python3
#
# Copyright 2021 Graviti. Licensed under MIT License.
#
# pylint: disable=invalid-name
# pylint: disable=missing-module-docstring
import os
from tensorbay.dataset import Data, Dataset
from tensorbay.exception import ModuleImportError
from tenso... |
# -*- coding: utf-8 -*-
import numpy as np
import multiprocessing as mp
from functools import partial
from statistics import mode, StatisticsError
from math import radians, sin, cos, sqrt, tan, atan2, floor, pi, degrees
__all__ = ["make_point_cloud", "rel2abs", "project_point_cloud", "rotation_matrix", "point_cloud2... |
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