text string |
|---|
# -*- coding: utf-8 -*-
""" Video Calibration functions, that wrap OpenCV functions mainly. """
# pylint:disable=too-many-lines
import logging
import copy
from typing import List
import numpy as np
import cv2
from scipy.optimize import least_squares
from scipy.optimize import minimize
import sksurgerycore.transforms... |
<reponame>ynakka/gPC_toolbox
#!/usr/bin/env python3
import numpy as np
from sympy import *
from scipy.special import comb
from itertools import combinations
def lambdify_gauss_hermite_pc(num_uncert,num_states,polynomial_degree):
xi_symbols = [symbols('xi'+str(i)) for i in range(1,num_uncert-num_states+1)]
xi ... |
<reponame>Lucasc-99/Meta-set
import os
import sys
sys.path.append(".")
from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter
import numpy as np
import torch
from scipy import linalg
from torchvision import transforms
from tqdm import trange
from FD.lenet import Net
from learn.utils import MNIST
try:
... |
#regression.py
import pandas as pd
from stats import *
import numpy as np
from scipy.stats import t, f
class Regression:
def __init__(self):
self.stats = Stats()
self.reg_history = {}
def OLS(self, reg_name, data, y_name, beta_names, min_val = 0,
max_val = None, constan... |
<filename>training_utils.py
import torch
import torch.nn as nn
import torch.nn.functional as F
import sys
import numpy as np
import scipy
import copy
import time
import pickle
import os
import math
import psutil
import itertools
import datetime
import shutil
from functions_utils import *
def train_initialization(... |
<reponame>carlosm3011/fing-montercarlo-2022<filename>cm2c/fing/mmc/integral.py
"""
Montecarlo para integrales.
(c) <NAME>, marzo-abril 2022
"""
import random
import math
import tabulate
import time
from scipy.stats import norm
import functools
from cm2c.fing.mmc.utils import sortearPuntoRN
from pathos.multiprocessing ... |
import binascii
from math import ceil, sqrt, floor
from skimage.measure import compare_psnr
import numpy as np
import cv2
import os
import math
from scipy.optimize import curve_fit
IMG_EXTENSIONS = ['.jpg', '.JPG', '.jpeg', '.JPEG',
'.png', '.PNG', '.ppm', '.PPM', '.bmp', '.BMP', '.bin', '.tiff'
... |
# -*- coding: utf-8 -*-
"""Optimal Interpolation of spatial data.
Interpolate spatial data using a modeled (analytical) covariance function.
Example:
python ointerp.py ~/data/ers1/floating/filt_scat_det/joined_pts_ad.h5_ross
-d 3 3 0.25 -r 15 -k 0.125 -e .2 -v t_year lon lat h_res None
-x... |
<reponame>DLarisa/FMI-Materials-BachelorDegree
# Lab1 -> 12.10
import numpy as np
import matplotlib.pyplot as plt
import metode_numerice_ecuatii_algebrice as mnea
import sympy as sym
"""
Lab#2.Ex2.b: Să se identifice intervalele pe care funcția f admite o sol unică.
f(x) = x^3 - 7*(x^2) + ... |
<reponame>PMBio/GNetLMM
from GNetLMM.pycore.mtSet.utils.utils import smartSum
from GNetLMM.pycore.mtSet.mean import mean
import GNetLMM.pycore.mtSet.covariance as covariance
import pdb
import numpy as NP
import scipy as SP
import scipy.linalg as LA
import sys
import time as TIME
from gp_base import GP
class gp3kronS... |
# Copyright 2017, <NAME>
import argparse
import os
import sys
import numpy as np
from scipy import ndimage
import gram
from gram import JoinMode
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Synthesize image from texture", formatter_class=argparse.ArgumentDefaultsHelpFormatter)
pars... |
<reponame>speppou/AFM_Nanobubble_Mapping<filename>SensitivityCalc.py<gh_stars>0
# -*- coding: utf-8 -*-
"""
Created on Thu Jan 24 09:50:36 2019
@author: <NAME>
"""
#Script to automatically calculate sensitivity from force curves on
#some incompressible substrate
#force curves must be in their own folder
... |
from typing import TypeVar, Optional, Dict, Any, List, Generic
from dataclasses import dataclass, field
import numpy as np
import scipy
from scipy.special import logsumexp
from estimatorduck import StateEstimator
from mixturedata import MixtureParameters
from gaussparams import GaussParams
ET = TypeVar("ET")
@datac... |
<reponame>WDot/G3DNet
from .AbstractPoolingPyramid import AbstractPoolingPyramid
import scipy.sparse
import pyamg
import numpy as np
#from graphcnn.util.modelnet.pointCloud2Graph import ply2graph
import tensorflow as tf
#import matlab.engine
import sys
import os
import os.path
#import matlab
import scipy.sparse
import ... |
<gh_stars>0
from fractions import Fraction
from pickle import dumps, loads
from typing import List, Union
import pytest
from conftest import BigIntSeq
import donuts
from donuts import Polynomial, RationalFunction, Variable
from donuts.poly import PolynomialLike
from donuts.rat import RationalFunctionLike
from donuts.... |
<reponame>jgalle29/deep_learning
import os
import tensorflow as tf
import matplotlib.pyplot as plt
import numpy as np
from scipy import stats
def load_mnist_images(binarize=True):
"""
:param binarize: Turn the images into binary vectors
:return: x_train, x_test Where
x_train is a (55000 x 784) ten... |
# coding: utf-8
# In[ ]:
import matplotlib.pyplot as plt
import numpy as np
import cv2
from scipy.ndimage import filters
def gaussian_smooth(size, sigma):
size = int(size) // 2
x, y = np.mgrid[-size:size+1, -size:size+1]
normal = 1 / (2.0 * np.pi * sigma**2)
img = np.exp(-((x**2 + y**2) / (2.0*si... |
from typing import Set, Dict, Any
from metagraph import ConcreteType, dtypes
from ..core.types import Matrix, EdgeSet, EdgeMap, Graph
from ..core.wrappers import EdgeSetWrapper, EdgeMapWrapper, GraphWrapper
from .. import has_scipy
import numpy as np
if has_scipy:
import scipy.sparse as ss
class ScipyEdgeSet... |
import unittest
import numpy as np
import scipy.stats as st
from ..analysis import Kruskal
from ..analysis.exc import MinimumSizeError, NoDataError
class MyTestCase(unittest.TestCase):
def test_500_Kruskal_matched(self):
"""Test the Kruskal Wallis class on matched data"""
np.random.seed(987654321... |
import numpy as np
import scipy as sci
import tensorflow as tf
import packing.packing_fea as packing_fea
from tensorflow.python.training import moving_averages
from packing.packing_env import PackingEnv
from gym import spaces
from stable_baselines.common.distributions import make_proba_dist_type
# Batch_norm adapted... |
<gh_stars>0
from tqdm import tqdm
from sympy import primefactors, prod, divisors
def findcycle(c):
for i in range(2, len(c)//2):
if c[len(c)-i : ] == c[len(c)-i*2 : len(c)-i]:
return c[len(c) - i:]
return []
for K in range(1, 2000):
terms = [1]
for i in range(60_001):
fo... |
import numpy as np
import matplotlib.pyplot as plt
from scipy import interpolate
def interpolated_intersection(x_1, y_1, x_2, y_2, acc=1000, spline='linear'):
x_1_dx_avg = (np.amax(x_1) - np.amin(x_1)) / len(x_1)
x_2_dx_avg = (np.amax(x_2) - np.amin(x_2)) / len(x_2)
dx = np.amin((x_1_dx_avg, x_2_dx_avg))
# interp... |
<gh_stars>1-10
"""
Makes group plots.
@author: bartulem
"""
import io
import os
import sys
import re
import json
import pickle
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from matplotlib.patches import FancyArrowPatch
from matplotlib import markers
from mpl_toolkits.mplot3d.proj3d import p... |
import seaborn as sns
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
def to_ndarray(data):
if isinstance(data, pd.DataFrame) or isinstance(data, pd.Series):
if data.shape[1] == 1:
return to_array(data)
return data.values
if isinstance(data, list):
ret... |
""" Tests of rna degradation submodel generation
:Author: <NAME> <<EMAIL>>
:Date: 2019-06-11
:Copyright: 2019, Karr Lab
:License: MIT
"""
from wc_model_gen.eukaryote import rna_degradation
from wc_onto import onto as wc_ontology
from wc_utils.util.units import unit_registry
import wc_model_gen.global_vars as gvar
impo... |
<filename>symbolic/van_genuchten.py
#!/usr/bin/env python
"""
Script that derives the expressions for the bundled Van Genuchten diffusivity
function
Used only in development. Running this script requires SymPy.
"""
from __future__ import division, absolute_import, print_function
import sympy
from generate import f... |
<filename>test/test_base_random_cell_transform.py
import pytest
import pandas as pd
import numpy as np
from scipy.stats import binom_test, chisquare
from keras_batchflow.base.batch_transformers import BaseRandomCellTransform, BatchFork
class LocalVersionTransform(BaseRandomCellTransform):
"""
BaseRandomCellTr... |
<filename>scripts/real_data_semi_supervised.py
import matplotlib as mpl
mpl.use('agg')
import os
import sys
import glob
import h5py
import argparse
import numpy as np
#import pylab as plt
import drama as drm
import scipy.io as sio
#from matplotlib import gridspec
import warnings
warnings.filterwarnings("ignore", messa... |
<reponame>pizilber/IMC<gh_stars>0
### Gradient descent algorithm for inductive matrix completion ###
### with option for balance regularization in the form of lambda * || U.T @ U - V.T @ V ||_F^2
### Written by <NAME> and <NAME>, 2022 ###
import numpy as np
from scipy import sparse
from scipy.sparse import linal... |
<filename>MetaLogo/connect.py
#!/usr/bin/env python
from numpy.core.fromnumeric import product
from scipy.stats import spearmanr,pearsonr
import numpy as np
from scipy.spatial import distance
import math
def dotproduct(v1, v2):
return sum((a*b) for a, b in zip(v1, v2))
def length(v):
return math.sqrt(dotproduc... |
<gh_stars>1-10
from __future__ import print_function
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.nn import init
from torch.utils.data import Dataset, DataLoader
import pickle
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from matp... |
<gh_stars>0
from sklearn.feature_extraction.text import CountVectorizer
import numpy as np
import pickle
import random
from scipy import sparse
import itertools
from scipy.io import savemat, loadmat
import os
import nltk
from nltk.corpus import stopwords
import re
import os
from utils import nearest_neighbors, get_to... |
#! /usr/bin/env python
# <NAME> 20.11.2015
# Dublin Institute for Advanced Studies
'''
L1551 IRS 5 field at 610 MHz
T Tau field
DG Tau field
'''
import numpy as np
import pandas as pd
import argparse
import matplotlib.pyplot as plt
import scipy.stats
myfontsize = 15
plt.rcParams.update({'font.size': myfontsize})
d... |
<gh_stars>0
import sys
sys.path.append('C:/Python37/Lib/site-packages')
from IPython.display import clear_output
import csv
import os
from pyqtgraph.Qt import QtGui, QtCore
import pyqtgraph as pg
import random
from pyOpenBCI import OpenBCICyton
import threading
import time
import numpy as np
from scipy import signal
fr... |
import numpy as np
from random import random
import sympy
import math
def calculation(alpha,beta,m):
a = np.zeros((m + 1,m + 1))
b = np.zeros((m + 1,m + 1))
i = j = 1
shift = True # shift 为 True 表明刚刚计算过 a
a[i,i] = beta[i]
# print('a',i,i,a[i,i])
while True:
if i == 1 and shift:
... |
import scipy.io
import numpy as np
import argparse
from scipy.stats import mode
from tqdm import tqdm
parser = argparse.ArgumentParser(description="hsi few-shot classification")
parser.add_argument("--data_folder", type=str, default='../data/')
parser.add_argument("--data_name", type=str, default='sar_train')
parser.a... |
import numpy as np
import pandas as pd
from functools import reduce
import seaborn as sns
from scipy.stats import multivariate_normal
import csv
def read_data(year,data_path):
path_name = data_path+'ENIGH'+year+'/'
hog = pd.read_csv(path_name+'hogares.csv', index_col = 'folioviv',
low_mem... |
import numpy as np
import theano
import theano.tensor as T
from treeano.sandbox.nodes import triplet_network as trip
fX = theano.config.floatX
def test_triplet_network_indices():
for y in [np.random.randint(0, 20, 300).astype(np.int32),
np.random.randint(0, 2, 256).astype(np.int32),
... |
<filename>davis/eval_custom_framewise.py
"""Per-frame version of proposed evaluation for video instance segmentation.
See fbms/eval_custom.py for a video-level evaluation that also works with
DAVIS."""
import argparse
import collections
import logging
import pickle
from pathlib import Path
import numpy as np
import ... |
<filename>untitled8.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Jul 31 22:35:45 2020
@author: nephilim
"""
import numpy as np
from matplotlib import pyplot,cm
import T_PowerGain
import skimage.transform
import scipy.io as scio
def CalculationSNR(Image,Noise):
frac_up=np.sum(Image**2)
... |
<reponame>bmoretz/Python-Playground<gh_stars>0
from sympy import Symbol, Derivative
t = Symbol( 't' )
St = 5*t**2 + 2*t + 8
d = Derivative( St, t )
d.doit()
d.doit().subs( { t : 1 } )
x = Symbol( 'x' )
f = ( x ** 3 + x ** 2 + x ) * ( x**2 + x )
Derivative( f, x ).doit() |
import numpy as np
import os
import six.moves.urllib as urllib
import sys
import tarfile
import tensorflow as tf
import zipfile
from collections import defaultdict
from io import StringIO
from matplotlib import pyplot as plt
from PIL import Image
from object_detection.utils import label_map_util
from object_detection... |
<filename>pyzx/hrules.py
# PyZX - Python library for quantum circuit rewriting
# and optimization using the ZX-calculus
# Copyright (C) 2018 - <NAME> and <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 ... |
from sklearn.ensemble import GradientBoostingClassifier
from scipy.stats import randint
from scipy.stats.distributions import uniform
seed = 0
model = GradientBoostingClassifier(random_state=seed)
param_dist = {
"loss": ['deviance', 'exponential'],
"learning_rate": [0.1, 0.03, 0.3],
"n_estimators": [50, 10... |
#Note: Please run seperately dont run this file
import textwrap
"""
Question 1: Given the names and grades for each student in a class of N students, store them in a nested list
and print the name(s) of any student(s) having the second lowest grade.
"""
python_students = [['Harry', 37.21], ['Berry', 37.21], ['Tina', 37... |
<reponame>hbredin/pyannote-db-plumcot<filename>scripts/image_features.py
#!/usr/bin/env python
# coding: utf-8
"""
Extracts features from images given IMDB-compliant JSON file,
described in `CONTRIBUTING.md` (scraped in `image_scraping`)
"""
# Dependencies
import os
from pathlib import Path
from shutil import co... |
import json
import hashlib
import numpy as np
from os import path
import seaborn as sns
from tqdm import tqdm
from scipy.stats import zscore
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
from sklearn.decomposition import PCA
from multiprocessing import Process, Manager, Pool
from Code import sam... |
import bempp.api
import numpy as np
from scipy import meshgrid
from matplotlib import pyplot as plt
grid = bempp.api.import_grid('TransitionCell_Assy.msh')
# grid1 = bempp.api.shapes.sphere(origin=(-2.0, 0.0, 0.0), h=0.5)
# grid2 = bempp.api.shapes.sphere(origin=(2.0, 0.0, 0.0), h=0.5)
#
# no_vert_grid1 = g... |
import glob
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec
import bezpy
from scipy.interpolate import interp1d
plt.style.use(['seaborn-paper', 'tex.mplstyle'])
mt_data_folder = '../data'
list_of_files = sorted(glob.glob(mt_data_folder + '*.xml'))
MT_sites = {site.name: s... |
import numpy as np
import copy
from itertools import combinations
from scipy.optimize import minimize, Bounds
from scipy.spatial.distance import cdist
from functools import partial
from scipy.linalg import solve_triangular
from scipy.special import kv, gamma
from sklearn.gaussian_process import GaussianProcessRegresso... |
#!/usr/bin/python2
#!encoding = utf-8
import sys
reload(sys)
sys.setdefaultencoding('utf-8')
try:
from sympy import *
x, y, z = symbols("x y z")
except:
print "[..?]\ncommand=echo yo\nicon=\nsubtext=install *sympy* for calculator!"
sys.exit(0)
cmd = ""
for i in range(1, len(sys.argv)):
cmd = cmd +... |
import pandas as pd
import scipy.stats as stats
import matplotlib.pyplot as plt
import seaborn as sns
df = pd.read_csv('C:\\...\\Data_Cortex_Nuclear.csv')
protein = df[['NR2A_N', 'class']].dropna()
sns.boxplot(x='class', y='NR2A_N', data = protein)
plt.show
|
"""
"""
import math
from qgis.core import *
try:
from scipy import interpolate
ScipyAvailable = True
except ImportError:
ScipyAvailable = False
# QGIS modules
from qgis.core import QgsRaster, QgsRectangle
def isin(value, array2d):
return bool([x for x in array2d if value in x])
class RasterInterp... |
<gh_stars>1-10
import unittest
import vrft
import scipy.signal as signal
import numpy as np
class TestVrft(unittest.TestCase):
def test_tf2ss(self):
G11 = signal.TransferFunction([1], [1, -0.9], dt=1)
G12 = 0
G21 = 0
G22 = signal.TransferFunction([1], [1, -0.9], dt=1)
G = ... |
<gh_stars>0
# -*- coding: utf-8 -*-
"""
Created on Feb 2018
@author: Chester (<NAME>)
"""
def warn(*args, **kwargs):
pass
import warnings
warnings.warn = warn
""""""""""""""""""""""""""""""
# import libraries
""""""""""""""""""""""""""""""
import os
import numpy as np
from sklearn.externals impo... |
import numpy as np
from scipy.optimize import least_squares
from . import math_tools as mt
import itertools
# import scipy.optimize as opt
def Peak_find_vectors(Peaks, atoll=0.087, toll=0.01):
""" Finds the first or 2 first smallest non colinear vectors
for each peak in an image
Input :
Peaks a... |
<reponame>loostrum/arts_gpu_python<filename>beamformer.py
#!/usr/bin/env python3
import math
import cmath
import numpy as np
from numba import jit, cuda, prange
from numba.cuda.cudadrv.error import CudaSupportError
import matplotlib.pyplot as plt
from tqdm import tqdm
from tools import timer
class BeamformerGPU(obj... |
"""
Experimental Functions - In Construction !!!
Author: <NAME>
Created: October 2017
Last Update: 02. August 2019
"""
from oap.__conf__ import MARKER, MONOSCALE_SHADOWLEVEL, SLICE_SIZE
from oap.utils import barycenter
import numpy as np
from copy import copy
from matplotlib import pyplot as plt
... |
# Copyright 2019 <NAME>.
#
# This file is part of Mi3-GPU.
#
# Mi3-GPU 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, version 3 of the License.
#
# Mi3-GPU is distributed in the hope that it will be useful,
#... |
from anndata import AnnData
import numpy as np
import os
from scanorama import *
import scanpy as sc
from scipy.sparse import vstack
from sklearn.preprocessing import normalize
from process import process, load_names, merge_datasets
from utils import *
NAMESPACE = 'zeng_develop_thymus'
DIMRED = 100
DR_METHOD = 'svd'
... |
#!/usr/bin/python
import sys
import numpy as np
import pandas as pd
from matplotlib import pyplot as pllt
from scipy.special import gamma
def main():
if len(sys.argv)>1:
file_name = str(sys.argv[1])
else:
file_name = 'wyniki.csv'
data = pd.read_csv(file_name,usecols=['graph_name','time','al... |
import pathlib
import csv
import json
import pickle
import statistics
import logging
from time import sleep
from datetime import datetime, timedelta
from gpiozero import DistanceSensor
from twilio.rest import Client
# Set up global logger
this_dir = pathlib.Path(__file__).parent.absolute()
logging_path = this_dir.joi... |
<filename>data_sources/tcga/__init__.py
from collections import defaultdict, UserList
from contextlib import contextmanager
from glob import glob
from statistics import StatisticsError
from tarfile import TarFile
from typing import Union
from warnings import warn
import numpy
from pandas import concat, read_table, Ser... |
<gh_stars>10-100
'''
Script demonstrating use of Aurora with explicit radial profiles of impurity neutral sources,
also allowing users to vary the ne,Te grids based on arbitrary heating, cooling or dilution
processes. This may be useful, for example, for pellet ablation or massive gas injection studies.
Run this in... |
from plotting.utils import arrow_style
from plotting.colors import SiteCategoryColors
from datetime import datetime
from collections import Counter, defaultdict
import operator
from statistics import mean
def prevalence(app):
pages_change = abs(round((app['history'][-2]['reach'] - app['history'][-1]['reach'] ) * ... |
<filename>modules/tests/sampling_numpy_metropolis.py
import pandas as ps
import numpy as np
import scipy
import os, sys
import json
import matplotlib.pyplot as plt
import pylab
plt.style.use('ggplot')
sys.path.append('../../modules/')
from sampling.libraries import Metropolis_Numpy_Random as Metropolis_Numpy
from sa... |
<gh_stars>0
#!/usr/bin/env python
# coding: utf-8
# In[1]:
import numpy as np
import matplotlib.pyplot as plt
from scipy import optimize
import math
# In[2]:
# this whole method is from https://blog.csdn.net/guduruyu/article/details/70313176
# some question need log functions to be fitted, I take log of inputs a... |
import matplotlib.pyplot as plt
import numpy as np
from joblib import Parallel, delayed
import seaborn as sns
from scipy.stats import gaussian_kde
class DoubleGaussian:
def __init__(self, mu=0.0, sigma=1.0):
self.mu = mu
self.sigma = sigma
def normal_dist(x):
return 1/(2*np.sqrt(2*np.pi)*sigma)*np.exp(-np.po... |
# Author: <NAME>
from pylab import *
import numpy as np
import scipy as sp
from scipy.io.wavfile import read
from scipy import signal
from scipy.signal import butter, lfilter
import matplotlib.pyplot as plt
import wave
import librosa
# Parameters
ENF_frequency = 50
sampling_freq = 1000
lowcut = ENF_f... |
<reponame>jfdur/durham-year2-archive<filename>ML/classifier.py
"""
Datasets must be stored in anonymisedData/ relative to this program's working directory.
If all of the imported modules are on your machine, running the classifiers should be as simple as executing the Python script directly.
The program will output som... |
#%% [markdown]
# # Comparing methods for SBM testing
#%%
from tkinter import N
from pkg.utils import set_warnings
set_warnings()
import csv
import datetime
import time
from pathlib import Path
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from giskard.plot import subun... |
#!/usr/bin/env python3
# To the extent possible under law, the libtcod maintainers have waived all
# copyright and related or neighboring rights for this example. This work is
# published from: United States.
# https://creativecommons.org/publicdomain/zero/1.0/
"""A system to control time since the original libtcod to... |
<gh_stars>1-10
# Includes a PEMD deflector with external shear, and Sersic sources. Includes
# a simple observational effect model that roughly matches HST effects for
# Wide Field Camera 3 (WFC3) IR channel with the F160W filter.
import numpy as np
from scipy.stats import norm, truncnorm, uniform
from paltas.MainDef... |
import os
import numpy as np
import matplotlib.pyplot as plt
import cv2
from scipy.ndimage import center_of_mass
PROJECT_PATH = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
def load(image_path):
image = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
return image
def resize(image):
image =... |
<filename>yb66/discussion/f0coeffs_fit.py
import numpy
from dabax_access_f0 import get_f0_coeffs_from_dabax_file, get_f0_from_f0coeff
from symbol_to_from_atomic_number import symbol_to_from_atomic_number
from scipy.optimize import curve_fit
"""
<NAME> <EMAIL>, <NAME>, <EMAIL>
Interpolation of f0 coefficients for a fra... |
import tensorflow as tf
import numpy as np
import matplotlib.image as mpimg
from scipy import misc
import matplotlib.pyplot as plt
import os.path
import math
# Plot images
def show_images(images):
plt.figure()
titles = ['Content Image', 'Style Image', 'Variable Image']
for i, img in enumerate(images,1):
... |
<gh_stars>0
# import modules
import pandas as pd
import glob
import numpy as np
import datetime
from fbprophet import Prophet
import matplotlib.pyplot as plt
import pickle
import os
from scipy import stats
from datetime import timedelta
from sklearn.metrics import r2_score
##############################################... |
# --------------
# Import packages
import numpy as np
import pandas as pd
from scipy.stats import mode
# code starts here
bank = pd.read_csv(path)
print(bank.head())
categorical_var = bank.select_dtypes(include='object')
print(categorical_var.head())
numerical_var = bank.select_dtypes(include = 'number')
print(... |
from manim import *
import math
from scipy.integrate import quad
class instagramPromo(GraphScene, MovingCameraScene):
def setup(self):
GraphScene.setup(self)
MovingCameraScene.setup(self)
def __init__(self, **kwargs):
GraphScene.__init__(
self,
x_min=0,
... |
#!/usr/bin/env python
# python 3 compatibility
from __future__ import print_function
import os.path
import sys
import shutil
import time
# stdlib imports
import abc
import textwrap
import glob
import os
import tempfile
# hack the path so that I can debug these functions if I need to
homedir = os.path.dirname(os.path... |
# ---
# jupyter:
# jupytext:
# text_representation:
# extension: .py
# format_name: percent
# format_version: '1.3'
# jupytext_version: 1.13.6
# kernelspec:
# display_name: Python 3 (ipykernel)
# language: python
# name: python3
# ---
# %% [markdown]
# ---
# # <center><font ... |
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
import seaborn as sns
import pickle
import pandas as pd
computation_vector = np.load("100_completion_times_13_robots.npy")
print(computation_vector)
print(np.median(computation_vector))
print(np.mean(computation_vector))
print(max(comput... |
<filename>_posts/PekerisCode/MatrixGeneratorGS_v1-02.py<gh_stars>1-10
import os
import cexprtk
import numpy as np
from numpy import genfromtxtimport multiprocessing
import parmap
import scipy
from scipy.linalg import eigvalsh, ordqz
import time
from sympy import Symbol, solve
np.seterr(divide='ignore')
# Specify numbe... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# #########################################################################
# Copyright (c) 2018, UChicago Argonne, LLC. All rights reserved. #
# #
# Copyright 2018. UChicago Argonne, LLC. This ... |
<reponame>kommunium/dip-lab<filename>lab2/bicubic_11912309.py
import numpy as np
import cv2 as cv
from scipy.interpolate import interp2d
from matplotlib import pyplot as plt
def bicubic_11912309(input_file: str, dim, output_file: str = 'bicubic_test.tif') -> np.ndarray:
"""
Use Python function “interp2” from ... |
from scipy import stats
from skimage import img_as_ubyte
from skimage.feature import local_binary_pattern
from skimage.io import imread
import glob
import keras_NN
import numpy as np
import os
import pandas as pd
import time
# Define the global variables related to the dataset
DATASET_PATH = "./input"
TRAINING_FOLDER_... |
<filename>examples/plot_physical_catalogs/plot_underlying.py
# To import required modules:
import numpy as np
import time
import os
import sys
import matplotlib
import matplotlib.cm as cm #for color maps
import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec #for specifying plot attributes
from matplo... |
<gh_stars>1-10
from collections import OrderedDict
import logging
from pathlib import Path, PureWindowsPath
import uuid
import matplotlib.pyplot as plt
import numpy as np
from pkg_resources import parse_version
from scipy import interpolate
import alf.io
from brainbox.core import Bunch
import ibllib.dsp as dsp
import... |
<reponame>fhoeb/py-mapping
import numpy as np
from scipy.special import gamma
def get_ohmic_coefficients(alpha, s, omega_c, nof_coefficients=100):
"""
Generates exact bsdo chain coefficients for a bosonic bath for ohmic spectral density with hard cutoff:
J(w) = alpha * omega_c * (w / omega_c) ** s... |
<reponame>norberto-schmidt/openmc
from collections.abc import Iterable, MutableSequence
import copy
from functools import partial, reduce
from itertools import product
from numbers import Integral, Real
import operator
from pathlib import Path
from xml.etree import ElementTree as ET
import h5py
import numpy as np
impo... |
"""
Collection of Numpy activation functions, wrapped to fit Ivy syntax and signature.
"""
from typing import Optional
# global
import numpy as np
try:
from scipy.special import erf as _erf
except (ImportError, ModuleNotFoundError):
_erf = None
def relu(x: np.ndarray, out: Optional[np.ndarray] = None) -> n... |
<reponame>Hroddric/cognionics-lsl-loop
# General imports
import numpy as np
import scipy as sp
import time
import glob
import os
import platform
if platform.architecture()[1][:7] == "Windows":
from win32api import GetSystemMetrics
from datetime import datetime
from scipy.io import loadmat
# Networking imports
from... |
<reponame>mathemacode/1D_DiffusionProcess
"""
Explicit, Implicit, Crank-Nicolson Methods
Solved via Linear Algebra for 1D Diffusion
"""
import numpy as np
from scipy import special
import matplotlib.pyplot as plt
def erf(x, t):
return special.erfc(x / (2 * np.sqrt(1 * t)))
def main():
# Constants
x_n =... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import argparse
import os
from collections import defaultdict
import numpy as np
from scipy.spatial import distance
from tqdm import tqdm
np.set_printoptions(threshold=np.inf, suppress=True)
def main(args):
num_batches = args.num_batches
bert_data = defaultdic... |
<filename>climvis/plots.py
"""
In this file all the functions for making the final plot in the interface are stored.
"""
import xarray as xr
from climvis.functions import clim, yearly_evol, path
from scipy import stats
import os
# path to data folder
file_dir = path()
long_name_to_short_name = {
"2m... |
from scipy import misc
import os, cv2, torch
import numpy as np
def load_test_data(image_path, size=256):
img = misc.imread(image_path, mode='RGB')
img = misc.imresize(img, [size, size])
img = np.expand_dims(img, axis=0)
img = preprocessing(img)
return img
def preprocessing(x):
x... |
from functools import partial
import logging
import json
from aws_xray_sdk.core import xray_recorder
from app.models.metrics.metrics_model import MetricsModel
from app.config import ROOT_DIR
from typing import List, Dict, Optional, Union
from operator import itemgetter
from scipy.stats import beta
from app.models.sl... |
<reponame>syanga/pycit
""" k-NN mutual information estimator for mixed continuous-discrete data """
import numpy as np
from scipy.special import digamma
from sklearn.neighbors import NearestNeighbors
def mixed_mi(x_data, y_data, k=5):
"""
KSG Mutual Information Estimator for continuous/discrete mixtures.
... |
<filename>Perspective Transformation/python_codes/deep/my_network_test.py
import sys
#sys.path.append('../')
import os
import torch
import torchvision.transforms as transforms
import torch.backends.cudnn as cudnn
import time
import numpy as np
import scipy.io as sio
import cv2
import argparse
from siamese import Br... |
#!/usr/bin/env python
import rospy
import math
import numpy as np
from geometry_msgs.msg import PoseStamped
from styx_msgs.msg import Lane, Waypoint
from scipy.spatial import KDTree
from std_msgs.msg import Int32
'''
This node will publish waypoints from the car's current position to some `x` distance ahead.
As ment... |
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