text string |
|---|
<reponame>camcl/genotypooler
import os, sys
import pysam
import pandas as pd
import numpy as np
from scipy.stats import *
rootdir = os.path.dirname(os.path.dirname(os.getcwd()))
sys.path.insert(0, rootdir)
from genotypooler.poolSNPs import chunkvcf as chkvcf
from genotypooler.persotools.files import *
"""
Building p... |
<filename>PythonNetwork/venv/Lib/site-packages/scipy/special/__init__.py
"""
========================================
Special functions (:mod:`scipy.special`)
========================================
.. module:: scipy.special
Nearly all of the functions below are universal functions and follow
broadcasting and automa... |
<filename>sympy/printing/ccode.py
"""
C code printer
The C89CodePrinter & C99CodePrinter converts single sympy expressions into
single C expressions, using the functions defined in math.h where possible.
A complete code generator, which uses ccode extensively, can be found in
sympy.utilities.codegen. The codegen modu... |
import cmath
a=complex(input().strip())
print(cmath.polar(a)[0])
print(cmath.polar(a)[1])
|
import numpy as np
from scipy import interpolate
from .enums import ControlType
class Data:
class Phase:
def __init__(self, time, phase):
"""
Initializes phases with user provided information.
:param time: Duration of the movement optimized. (float)
:param p... |
<filename>code/traditional/BDA/BDA.py
# encoding=utf-8
"""
Created on 9:52 2018/11/14
@author: <NAME>
"""
import numpy as np
import scipy.io
import scipy.linalg
import sklearn.metrics
import sklearn.neighbors
from sklearn import metrics
from sklearn import svm
def kernel(ker, X1, X2, gamma):
K = None
... |
<filename>roots/core.py
import numpy as np
import math
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import random
from scipy.interpolate import interp1d
import scipy
import time
from roots.graphmethods import GraphMethods
from roots.kmd import KMDD
#import seaborn as sns
#plt.style.use('seabo... |
<filename>gmi_invert_old.py
import gmi_misc
#**************** PRINT HEADER ***************************#
gmi_misc.print_header()
print("Script no. 4: Inversion")
#**************** ------------ ***************************#
#**************** GET WORKING DIRECTORY ******************#
import os
old_cwd = os.getcwd()
gmi_m... |
<reponame>arfon/starry_process
from ..base_op import BaseOp
from ...compat import Op, Apply, theano, tt, floatX
import numpy as np
from functools import partial
from six.moves import xrange
import scipy.linalg
__all__ = ["EighOp"]
def _numpy_eigh(x, neig):
try:
eigvals, eigvecs = np.linalg.eigh(x)
ex... |
<reponame>jaws/JustifiedAWS<gh_stars>10-100
from datetime import datetime
import os
import requests
import numpy as np
import scipy.interpolate
import xarray as xr
try:
from jaws import common
except ImportError:
import common
def deg_to_rad(list_deg):
"""Convert degrees to radians"""
list_rad = [np... |
import os
import sys
import csv
import pprint as pprint
import re
import statistics
import fiolib.supporting as supporting
from pathlib import Path
def list_fio_log_files(directory):
"""Lists all .log files in a directory. Exits with an error if no files are found.
"""
absolute_dir = os.path.abspath(direc... |
# -*- coding: utf-8 -*-
"""
Created on Sun Dec 3 18:52:20 2017
@author: ybarancan
"""
import scipy.io as sio
import os
import glob
import h5py
import random
import tensorflow as tf
import numpy as np
FLAGS = tf.app.flags.FLAGS
def valid_preprocess(path):
mat_file = sio.loadmat(path)
... |
# testing p = 1 case 2 with FEM
# running code for p = 1 with increasing number of elements for 2**1
import numpy as np
import matplotlib.pyplot as plt
from scipy import integrate
from scipy import stats
"""
#returns sample points and weights for gaussian quadrature
deg = 2
print("sample points:")
print(np.polynomia... |
<reponame>psaks/auto-sklearn<gh_stars>1000+
import hashlib
import json
import os
import pathlib
import pickle
from typing import Any, Dict, List, Optional, Union
import dask.distributed
import scipy.sparse
from ConfigSpace import Configuration
import numpy as np
import pandas as pd
import sklearn
import autosklearn
... |
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from args import get_parser
from pycocotools.cocoeval import COCOeval
from pycocotools.coco import COCO
import pycocotools.mask
from utils.utils import batch_to_var, make_dir, outs_perms_to_cpu, load_checkpoint, check_parallel
from scipy.ndimage.me... |
# -*- coding: utf-8 -*-
"""
Created on Wed Feb 17 14:32:14 2021
@author: <NAME>
"""
import numpy as np
from numpy import sin, cos, sqrt
from scipy.constants import mu_0 as μ0, pi as π
from scipy.integrate import quad
from scipy.special import ellipk as ellK, ellipe as ellE
from scipy.special import ellipkinc as ellK_i... |
<reponame>JinLi711/quantum_circuits
from sympy import *
import numpy as np
import utils
class Measure(object):
def __init__(self, qubit_index, bit_index):
self.template = 'measure q[{}] -> c[{}]'.format(qubit_index, bit_index)
def measure(qubits, basis='z'):
"""Perform a measurement on the q... |
<gh_stars>1-10
# ---
# jupyter:
# kernelspec:
# display_name: Python 3
# name: python3
# ---
# %% [markdown]
# # Hyperparameter tuning
#
# In the previous section, we did not discuss the parameters of random forest
# and gradient-boosting. However, there are a couple of things to keep in mind
# when setting ... |
<gh_stars>0
import glob
import os
import audioBasicIO
import sys
import csv
import scipy.io.wavfile as wavfile
def annotation2files(wavFile, csvFile):
'''
Break an audio stream to segments of interest,
defined by a csv file
- wavFile: path to input wavfile
... |
<filename>competitive/AtCoder/ABC212/B.py
import bisect
from copy import deepcopy
from fractions import Fraction
from functools import reduce
import heapq as hq
import io
from itertools import combinations, permutations
import math
from math import factorial
import re
import sys
sys.setrecursionlimit(10000)
#from numb... |
<filename>sureal/subjective_model.py
import copy
from abc import ABCMeta, abstractmethod
import sys
import time
import numpy as np
from scipy import linalg
from scipy import stats
import pandas as pd
from scipy.stats import chi2, norm
from sureal.core.mixin import TypeVersionEnabled
from sureal.tools.misc import impo... |
import cv2
import csv
import datetime
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
from scipy.misc import imread, imresize
from sklearn.utils import shuffle
from os import listdir
from os.path import join
from keras.preprocessing.image import img_to_array, load_img
from keras.... |
from otolto import *
import scipy.optimize as spop
import cma
import multiprocessing
if __name__ == '__main__':
print('My name is __main__!')
multiprocessing.freeze_support()
multiprocessing.freeze_support()
desiredEccentricity=0.0
desiredInclination=0.0
desiredSemiMajor=7e6
eccTol=0.002
smaTol=1.0
... |
# coding=utf-8
# Copyright 2021 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 statsmodels.api as sm
import numpy as np
import matplotlib.pyplot as plt
from date_functions import *
import time
from get_WMAE import *
import pywt
from scipy.optimize import basinhopping
def remove_mean(window_size,first_day_index,lprices,lloads):
window_size_h = window_size*24
first_hour_i... |
'''
Module: jelephant.analysis.rate_estimation
Contains utility functions for instantaneous rate estimation of SpikeTrains.
'''
import quantities as pq
import numpy as np
import numpy
import scipy.signal
import neo
#def make_kernel(form, sigma, resolution, direction=1):
#
#
# """Creates kernel functions for convo... |
<reponame>rickdr/Data-analysis-DNN-testing
import sys
import torch
import numpy as np
# import cupy as cp
from tqdm import tqdm
from scipy import stats
from sklearn import metrics
import matplotlib.pyplot as plt
import concurrent
from concurrent.futures.thread import ThreadPoolExecutor
sys.path.insert(0, '../')
from ... |
import numpy as np
import scipy.integrate as integrate
from numpy import cosh, cos, log, sqrt
'''
1D Transverse Field Ising Model(1D TFIM)
H = \sum_i -J*\sigma_{i}\sigma_{i+1} - h*\sigma_{i}
'''
# beta = 1/kT
# Jordan–Wigner transformation
def lnZ(beta, J, h):
lam = J / h
w = lambda x: (1 + 2 * lam * cos(x... |
from typing import Union
from typing import Tuple
from typing import Any
from typing import List
import numpy as np
import onnxruntime
from scipy.special import log_softmax
from espnet_onnx.asr.scorer.interface import BatchScorerInterface
from espnet_onnx.utils.function import subsequent_mask
class TransformerLM(Ba... |
<reponame>nrupatunga/circulant_matrix_tracker
# !/usr/bin/env python
# -*- coding: utf-8 -*-
"""
This is a python reimplementation of the open source tracker in
http://www2.isr.uc.pt/~henriques/circulant/index.html
Found http://wiki.scipy.org/NumPy_for_Matlab_Users very useful
Based on the work of <NAME>, 2012
http:... |
<reponame>charles-stan/learn_python_Stanier
"""
Example 13a_ode_single_ver_a
Solving a single ODE for a level tank
<NAME>
<EMAIL>
Oct 2, 2019
simple version - everything hard coded,
derivative function and driver in same file
constants hard-coded into derivative file
note: I am using solve_ivp (solve in... |
## LSDMap_KnickpointPlotting.py
##=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
## These functions are tools for analysing and plotting knickpoint data
##=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
## FJC
## 05/06/2017
##=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=... |
"""
Hierarchical clustering (:mod:`scipy.cluster.hierarchy`)
========================================================
.. currentmodule:: scipy.cluster.hierarchy
These functions cut hierarchical clusterings into flat clusterings
or find the roots of the forest formed by a cut by providing the flat
cluster ids of each ... |
<reponame>dnidever/chronos
#!/usr/bin/env python
"""CHRONOS.PY - Automatic isochrone fitting to photometric data
"""
__authors__ = '<NAME> <<EMAIL>?'
__version__ = '20210919' # yyyymmdd
import os
import time
import numpy as np
from glob import glob
from astropy.wcs import WCS
from astropy.io import fits
from astro... |
import scipy.interpolate as interp
import numpy as np
from pyevtk.hl import gridToVTK
def interpSurface(pointfile,outfile,nxgrid=100,nygrid=100,method='spline',delimiter='\t',kx=1,ky=1):
'''
Creates a surface interpolating the provided three dimensional points.
INPUT:
pointfile ASCII text file w... |
<filename>test_script.py
import sys
import numpy as np
import time
import cv2
import os
from os import listdir
from os.path import isfile, join, isdir
import random
from sklearn.tree import DecisionTreeClassifier
from UCSDped1 import TestVideoFile
from sklearn.neighbors import KNeighborsClassifier
import time
from skle... |
'''
Contains Field class and field related routines.
Note: g2g functionality was moved to gridtile.py due to dependence on f2py.
pca method is moved to pca.py module due to dependence on f2py.
'''
import scipy as sp
from scipy import interpolate
import matplotlib.pyplot as pl
from matplotlib import dates, mlab
... |
from scipy import linalg
import numpy as np
from ..utils.simple_functions import choose
CLOSED_THRESHOLD = 0.001
def bezier(points):
n = len(points) - 1
return lambda t: sum([
((1 - t)**(n - k)) * (t**k) * choose(n, k) * point
for k, point in enumerate(points)
])
def partial_bezier_poi... |
__author__ = '<NAME>'
import os
import numpy as np
import scipy.stats as st
import matplotlib.pyplot as plt
def check_inf(string):
# bug no python 2.3
if string == '1.#INF\n':
result = 99999
else:
result = float(string)
result = max(0, result)
#result = min(20.0, result)
return result
if __name__ == '_... |
import numpy as np
from loader import *
from scipy import sparse
import math
import os, sys
utils_path = os.path.dirname(os.path.abspath(__file__)) + os.path.sep + "/../utils"
sys.path.append(utils_path)
import sparse_matrix
def loadAllCutSongci(path):
f = open(path, "r")
lines = f.readlines()
cs = "".jo... |
<filename>librosa/util/utils.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Utility functions"""
import warnings
import scipy.ndimage
import scipy.sparse
import numpy as np
import numba
from numpy.lib.stride_tricks import as_strided
from .._cache import cache
from .exceptions import ParameterError
# Constrain ... |
'''
Forward algorithm for Hidden Markov Models.
Includes:
* skeleton of run_forward_algorithm requiring edits
* a __main__ method with example input
* doctests showing expected behavior
Usage
-----
To see forward messages on simple example printed to stdout, do
$ python forward_alg.py
To verify if the script passes ... |
#!/usr/bin/env python
# Copyright 2019 Calico LLC
# 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 agr... |
<reponame>filecoin-project/consensus
import numpy as np
import time
from math import floor
import multiprocessing as mp
import scipy.special
#Initialize parameters
Num_of_sim_per_proc = 10
height = 11 #height of the attack
start_time = time.time()
e = 5.
alpha = 0.33
ntot = 1000
na = int(ntot*alpha)
nh = ntot - na
p... |
<reponame>dhjpolymath/pytorch-minimize<gh_stars>10-100
"""
TODO: this module is not yet complete. It is not ready for use.
"""
import numpy as np
from scipy.linalg import eigh_tridiagonal, get_lapack_funcs
import torch
from .base import _minimize_trust_region, BaseQuadraticSubproblem
def _minimize_trust_krylov(fun, ... |
from matplotlib import pyplot as plt
from scipy import stats as st
import numpy as np
marks = ("H3K27ac", "H3K4me1", "H3K4me3", "H3K9ac", "H3K36me3", "H2AZ", "H3K79me2", "H3K27me3", "EZH2", "enhancer", "transcription", "polycomb")
datasets = []
for celltype in ("GM12878", "K562"):
for mark in marks:
datasets.append... |
#!/usr/bin/env python
"""Minimum Variance Analysis and boundary normal crd tools"""
from __future__ import print_function, division
import os
import numpy as np
import viscid
__all__ = ["paraboloid", "paraboloid_normal", "fit_paraboloid",
"get_mp_info", "find_mp_edges"]
_dtf = 'f8'
_paraboloid_dt = np.d... |
<gh_stars>0
import scipy.signal
import numpy as np
def find_peaks(x, max_num = -1, height = None, distance = None):
''' Find peaks positions and their heights in 1-d array of real data. (Based on `scipy.signal.find_peaks`)
:param x: 1-d array of real data
:param max_num: `optional` defines maximum num... |
import measure as ms
from measure import pi, sqrt, sin, tan, cos, arcsin, arccos, exp, ln
from measure import npfarray as npf
import numpy as np
import scipy.constants as cs
ms.plt.rc('text', usetex=True)
ms.plt.rc('font', family='serif')
titles = [
r'Bestimmung des Grenzwinkels $\beta_G$ durch Extrapolation' '\n' ... |
#!/usr/bin/env python
# coding: utf-8
# # Regularization
#
# Welcome to the second assignment of this week. Deep Learning models have so much flexibility and capacity that **overfitting can be a serious problem**, if the training dataset is not big enough. Sure it does well on the training set, but the learned networ... |
# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this so... |
import numpy as np
from scipy import io
import os
g_nr_of_clusters = 17
def numpy_to_uint8(the_image, verbal=False):
original_image_type = the_image.dtype
original_image_info = np.iinfo(original_image_type)
converted_image = the_image.astype(np.float32) / original_image_info.max
converted_im... |
<reponame>simpeg-research/casingSimulations<gh_stars>1-10
import unittest
import numpy as np
import discretize
import os
import pytest
from discretize import utils
from scipy.constants import mu_0
import casingSimulations as casingSim
class ModelTests(unittest.TestCase):
def setUp(self):
self.mesh = dis... |
<reponame>jensv/relative_canonical_helicity_tools<filename>centroid_fitting/gyration_path.py
r""""
Created on Apr 17 2017
@author: <NAME>
Plot field line null gyration of RSX magnetic flux tube.
"""
import numpy as np
from scipy.optimize import leastsq
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_s... |
<filename>exoabc/completeness.py<gh_stars>0
# -*- coding: utf-8 -*-
from __future__ import division, print_function
import logging
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy.optimize import leastsq
from .sim import DR24CompletenessModel
from .data import get_q1_q17_dr24_injecti... |
<reponame>sampritipanda/audio_captcha_solver<filename>rasta.py
import librosa
import librosa.filters
import scipy
import scipy.fftpack as fft
from scipy import signal
import numpy as np
import matplotlib.pyplot as plt
import spectrum
def rastaplp(x, fs = 16000, win_time = 0.040, hop_time = 0.020, dorasta = True, model... |
<reponame>iyaja/efficientnet
from fastai2.vision.all import *
from fastai2.callback.wandb import *
import pandas as pd
import scipy.io as sio
import wandb
import geffnet
from fastai2.distributed import *
hyperparameter_defaults = dict(
efficientnet_b = 3,
)
run = wandb.init(config=hyperparameter_defaults, pr... |
"""
This module contains the algorithm for optimizing the costs of energy systems.
"""
from datetime import datetime
from scipy.optimize import fmin_l_bfgs_b
import calendar
import cProfile
import copy
from collections import namedtuple
import numpy as np
from numpy import array
from server.devices.base import BaseEn... |
"""Test the 20news downloader, if the data is available."""
import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import SkipTest
from sklearn import datasets
def test_20news():
try:
data = dat... |
<gh_stars>0
# aclock.py Test/demo program for Adafruit ssd1351-based OLED displays
# Adafruit 1.5" 128*128 OLED display: https://www.adafruit.com/product/1431
# Adafruit 1.27" 128*96 display https://www.adafruit.com/product/1673
# Released under the MIT License (MIT). See LICENSE.
# Copyright (c) 2018-2020 <NAME>
# I... |
# with Gaze ------------------
import bpy
import numpy as np
from itertools import repeat
import random
import os
import sys
from sympy.geometry import Point
from numpy import cos, sin
from math import radians
import mathutils
from bpy import context
"""
Render the images, Depth and capture the metadata
Sce... |
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from scipy.stats import multivariate_normal
from scipy.spatial.distance import cdist
from matplotlib.colors import rgb2hex
class GaussianProcesses:
var_error = -1
kernel = 'rbf'
kernel_params = 1.
mu = -1
K = -1
X = -1
y = -1
bound... |
<gh_stars>100-1000
#!/usr/bin/env python
from __future__ import print_function
from sympy import symbols, sin, cos, simplify
from sympy.galgebra.ga import MV
from sympy.galgebra.printing import enhance_print
def main():
enhance_print()
(ex, ey, ez) = MV.setup('e*x|y|z', metric='[1,1,1]')
u = MV('u', 'v... |
import os,sys,random,pickle,copy,re,operator
import pandas as pd
import numpy as np
import scipy as sp
from scipy.special import softmax
from plot_utils import *
import ast
from sklearn.metrics import confusion_matrix
from deap import algorithms
from deap import base
from deap import benchmarks
from deap.benchmarks.... |
<gh_stars>10-100
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Data augmentation routines.
Author: <NAME>
"""
import sys
import os
import subprocess
import numpy as np
import scipy.ndimage
def grab_random_excerpts(spects, labels, batchsize, frames):
"""
Exctracts random excerpts of `frames` frames fro... |
import numpy as np
import scipy.interpolate as interpolate # B-Spline
def bspline(x, y, sections, degree=3):
idx = np.linspace(0, len(x) - 1, sections + 1, endpoint=True).round(0).astype("int")
x = x[idx]
y = y[idx]
t, c, k = interpolate.splrep(x, y, s=0, k=degree)
spline = interpolate.BSpline(t... |
<reponame>Andrej1A/ml_with_django<gh_stars>1-10
# -*- coding: utf-8 -*-
__author__ = '<NAME>'
import os
import datetime
import dill
import numpy as np
import tensorflow as tf
import matplotlib
matplotlib.use('Agg')
from matplotlib import pyplot as plt
from keras.models import load_model
from keras.preprocessing.image ... |
<reponame>FleischerResearchLab/wvlib
#!/usr/bin/env python
"""DBSCAN clustering for word vectors.
Requires scikit-learn."""
import sys
import math
import logging
import numpy
import scipy.cluster
import wvlib
import sklearn.cluster
if float(sklearn.__version__) < 0.14:
# old scikit-learn fails to realize the p... |
<gh_stars>1-10
"""
Module for skill model evaluation
@author <NAME> <<EMAIL>>
"""
from __future__ import division
import logging
import random
import time
import math
import copy
from matplotlib import pyplot as plt
from sklearn import cross_validation, metrics
from scipy import stats
import numpy as np
from . imp... |
"""This module implements tools for integrating rational functions. """
from sympy.core.function import Lambda
from sympy.core.numbers import I
from sympy.core.singleton import S
from sympy.core.symbol import (Dummy, Symbol, symbols)
from sympy.functions.elementary.exponential import log
from sympy.functions.elementar... |
<filename>dask_image/ndfilters/_smooth.py
# -*- coding: utf-8 -*-
import scipy.ndimage.filters
from . import _utils
from ._gaussian import gaussian_filter
gaussian_filter = gaussian_filter
@_utils._update_wrapper(scipy.ndimage.filters.uniform_filter)
def uniform_filter(image,
size=3,
... |
# --------------------------------------------------------
# Factory file for LRP-HAI
# Licensed under The MIT License [see LICENSE for details]
# Written by <NAME>
# Written by <NAME>
# Faster R-CNN code by <NAME>, <NAME>, based on code
# from <NAME>
# --------------------------------------------------------
import cv... |
<gh_stars>1-10
from sympy.core.numbers import igcd
from primetest import isprime
def totient_(n):
"""returns the number of integers less than n
and relatively prime to n"""
if n < 1:
raise ValueError("n must be a positive integer")
tot=0
for x in xrange(1,n):
if igcd(x,n)==1:
... |
<filename>great_expectations/dataset/sparkdf_dataset.py
from __future__ import division
import inspect
import re
import logging
from six import PY3, string_types
from functools import wraps
from datetime import datetime
from dateutil.parser import parse
from .dataset import Dataset
from great_expectations.data_asset.... |
#!/usr/bin/env python
# Load required modules
import sys, os, argparse, numpy as np, pandas as pd
from scipy.stats import multivariate_normal, poisson
if __name__ == '__main__':
# Parse command-line arguments
parser = argparse.ArgumentParser()
parser.add_argument('-at', '--active_topics', type=int, requir... |
<gh_stars>0
"""
Copyright 2013 <NAME>, 2017 <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 copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in ... |
<gh_stars>10-100
from sympy import (sympify, S, pi, sqrt, exp, Lambda, Indexed, Gt,
IndexedBase)
from sympy.matrices import ImmutableMatrix
from sympy.matrices.expressions.determinant import det
from sympy.stats.joint_rv import (JointDistribution, JointPSpace,
JointDistributionHandmade, MarginalDistribution)
fr... |
import numpy as np
from scipy.spatial import Voronoi, voronoi_plot_2d
import matplotlib.pyplot as plt
points = np.random.rand(30, 2)
vor = Voronoi(points)
fig = plt.figure()
ax = fig.add_subplot(111, aspect='equal')
ax.tick_params(labelbottom="off", labelleft="off")
voronoi_plot_2d(vor, ax=ax)
plt.show()
|
# 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>shuuji3/Cirq
# 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 applicab... |
'''
Extract physical features of airfoils or wing sections.
'''
import copy
import os
import numpy as np
from scipy.interpolate import interp1d
class PhysicalSec():
'''
Extracting flow features of a section (features on/near the wall)
'''
_i = 0 # index of the mesh point
_X = 0.0 # locati... |
<filename>pyamg/relaxation/smoothing.py
"""Method to create pre and post-smoothers on the levels of a MultilevelSolver.
The setup_smoother_name functions are helper functions for
parsing user input and assigning each level the appropriate smoother for
the functions in 'change_smoothers'.
The standard interface is
Pa... |
'''
<NAME>
15863
Exercise 16
'''
import matplotlib.pyplot as plt
import pandas as pd
import scipy.constants as sc
millikan = pd.read_csv("millikan.txt", sep=' ', header=None)
x = []
y = []
sumx = 0
sumy = 0
sumxx = 0
sumxy = 0
for i in range(0, 6):
x.append(millikan[0][i])
y.append(millikan[1][i])
for xi in ... |
# -*- coding: utf-8 -*-
import numpy as np
from .utils import fast_OLS, fast_optimize, bootstrap_sampler, eval_expression, bias_corrected_ci, z_score, \
percentile_ci
import scipy.stats as stats
from numpy.linalg import inv, LinAlgError
from numpy import dot
from itertools import product, combinations
import pandas... |
'''
**************** PLEASE READ ***************
Script that reads in spam and ham messages and converts each training example
into a feature vector
Code intended for UC Berkeley course CS 189/289A: Machine Learning
Requirements:
-scipy ('pip install scipy')
To add your own features, create a function that takes in... |
from statsmodels.compat.python import iterkeys
from statsmodels.regression.linear_model import GLS
import numpy as np
from statsmodels.base.model import LikelihoodModelResults
from scipy import sparse
# http://www.irisa.fr/aladin/wg-statlin/WORKSHOPS/RENNES02/SLIDES/Foschi.pdf
__all__ = ['SUR', 'Sem2SLS']
#probably... |
<gh_stars>0
from CSIKit.reader import IWLBeamformReader
from CSIKit.util import csitools
import numpy as np
import errno
import glob
import os
import scipy.io
class InconsistentOutputError(RuntimeError):
def __init__(self, arg):
self.args = arg
def test_intel_matlab_consistency():
example_dir = os... |
# 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 ... |
<filename>clusterpy/core/toolboxes/rimaps/__init__.py<gh_stars>0
"""Spatial statistics library (sstats)
"""
__author__ = "<NAME>, <NAME>"
__credits__ = "Copyright (c) 2009-11 <NAME>"
__license__ = "GPL"
__version__ = "1.0.0"
__maintainer__ = "RiSE Group"
__email__ = "<EMAIL>"
from statistics import topoStatistics, noF... |
"""Entropy functions"""
import numpy as np
from numba import jit
from math import factorial, log
from sklearn.neighbors import KDTree
from scipy.signal import periodogram, welch
from .utils import _embed
all = ['perm_entropy', 'spectral_entropy', 'svd_entropy', 'app_entropy',
'sample_entropy', 'lziv_complexity... |
<filename>RealTimeProcessing.py<gh_stars>0
# -*- coding: utf-8 -*-
"""
Created on Fri Jun 4 11:29:48 2021
@author: <NAME>
"""
y2=['a']
import pyaudio
import numpy as np
CHUNK = 512
WIDTH = 2
CHANNELS = 1
RATE = 8192
FORMAT = pyaudio.paInt16
data2=np.linspace(0,1,2)
import scipy.io
from scipy import ... |
<reponame>LIDeB/iRaPCA-v1.0
#!/usr/bin/env python
# coding: utf-8 -*-
"""
@author: LIDeB UNLP
"""
# iRaPCA Clustering is a clustering strategy based on an iterative combination
# of the random subspace approach (feature bagging), dimensionality reduction
# through Principal Component Analysis (PCA) and the k-m... |
#
# Copyright (c) <NAME>. All rights reserved.
# Licensed under the MIT license. See LICENSE file in the project root for details.
#
import os
import numpy as np
import scipy.constants
import scipy.special
# whether to show animations of simulated constellations
ANIMATE = False
# whether to print debug information
D... |
<gh_stars>0
import numpy as np
import matplotlib.pyplot as plt
import numpy as np
import os
from scipy.stats import norm
import pickle
from keras.datasets import mnist, fashion_mnist
#from utils.loaders import load_mnist, load_model
from sklearn.metrics import classification_report
from sklearn.metrics import confusi... |
import calendar
import datetime
import os
import shutil
import gdal
import gdalnumeric
import netCDF4
import numpy
import osr
import statistics
import pandas
from .app import LdasCentral as App
from .model import app_configuration
def pointchart(data):
"""
Description: generates a timeseries for a given poi... |
import json
import os
import pprint
from os import listdir
from os.path import isfile, join
import cv2 as cv
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import scipy
import seaborn as sns
import torch
import torch.backends.cudnn as cudnn
import torch.nn as nn
import torch.n... |
<filename>Make_Timelist.py<gh_stars>0
from netCDF4 import Dataset
import glob,os.path
import numpy as np
from scipy.interpolate import UnivariateSpline
import matplotlib
import matplotlib.pyplot as plt
import site
site.addsitedir('/tera/phil/nchaparr/python')
from nchap_fun import *
"""
Get list of strings represen... |
#!/usr/bin/env python3
from statistics import mean
import multiprocessing
from multiprocessing import Process
import sys
import time
import argparse
import traceback
import math
import numpy as np
from trabalho_final.logger import Logger, TagTypes
from trabalho_final.caches.static_cache import StaticCache
from trabalh... |
<reponame>Sharath302/popmon
# Copyright (c) 2021 ING Wholesale Banking Advanced Analytics
#
# 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 t... |
#!/usr/bin/env python
"""
IDT: Individualized Discounting Task (out-of-scanner version)
Copyright 2017 <NAME>.
Licensed under the Educational Community 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.osedu.o... |
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