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<filename>pymir/Spectrum.py<gh_stars>100-1000
"""
Spectrum class
ndarray subclass for spectral data
Last updated: 17 December 2012
"""
from __future__ import division
import math
import numpy
from numpy import *
import scipy.stats
import scipy.stats.mstats
import matplotlib.pyplot as plt
import pymir
from pymir im... |
# coding: utf-8
# # Numerically solving differential equations with python
#
# *This is a brief description of what numerical integration is and a practical tutorial on how to do it in Python.*
# ## Software required
#
# *In order to run this notebook in your own computer, you need to install the following softwar... |
#!/usr/bin/env python
# coding: utf-8
import pandas as pd
import numpy as np
from scipy.stats import chisquare
from evidently.analyzers.base_analyzer import Analyzer
from .utils import proportions_diff_z_stat_ind, proportions_diff_z_test, process_columns
class CatTargetDriftAnalyzer(Analyzer):
def calculate(sel... |
__author__ = '<NAME>'
__email__ = '<EMAIL>'
__url__ = 'http://helderc.net'
"""
This is an improved implementation of SSIM, based on version of:
<NAME>, ISIT lab, <EMAIL>,
http://isit.u-clermont1.fr/~anvacava
References:
[1] <NAME>, <NAME>, <NAME> and <NAME>.
Image quality assessment: F... |
<reponame>anontruess/anonymous
from scipy.optimize import linear_sum_assignment
from sklearn.metrics import confusion_matrix
import matplotlib.pyplot as plt
import numpy as np
import os
import datetime
import shutil
import torch
def save_checkpoint(state, fdir, name='checkpoint.pth'):
filepath = os.path.join(fdir,... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Oct 23 21:11:01 2019
@author: nico
"""
from scipy.fftpack import fft
from scipy.signal import correlate
import scipy.signal as sg
import numpy as np
import sys
"""
brief: Esta funcio realiza el periodograma de una señal
argumentos
signal: es la seña... |
import abc
from typing import Dict, List, Tuple
import numpy
import torch
from scipy.spatial.qhull import Delaunay
from surrogates.drivers import Driver
from surrogates.likelihoods.likelihoods import Likelihood
from surrogates.utils.distributions import Distribution
from surrogates.utils.numpy import add_parameter_di... |
import numpy as np
from scipy.stats import laplace
import matplotlib.pyplot as plt
fig, ax = plt.subplots(1, 1)
mean, var, skew, kurt = laplace.stats(moments='mvsk')
x = np.linspace(laplace.ppf(0.01), laplace.ppf(0.99), 100)
ax.plot(x, laplace.pdf(x), 'r-', lw=5, alpha=0.6, label='laplace pdf'... |
<filename>src/util/comp_result_generator.py
from typing import List, Dict, Tuple
from statistics import mean
import sys
import os
from numpy.lib import math
sys.path.append(os.getcwd())
import locale
locale.setlocale(locale.LC_ALL, '')
import src.util.plot as alnsplot
import pandas as pd
def get_intermediate(exp... |
import numpy as np
from .util import pad, make_windows, weights_to_laplacian
import scipy.sparse
def closed_form_laplacian(image, epsilon):
h, w, depth = image.shape
n = h * w
indices = np.arange(n).reshape(h, w)
neighbor_indices = make_windows(pad(indices))
# shape: h w 3
means = make_windo... |
<reponame>dicai/stats_notebook
# coding: utf-8
# In[184]:
import numpy as np
import pylab
import scipy
import seaborn as sns
get_ipython().magic(u'matplotlib inline')
get_ipython().magic(u"config InlineBackend.figure_format = 'retina'")
# # Importance sampling
#
# We'll look at an example where we can compute the... |
<gh_stars>0
# ALCe by <NAME>
# Copyright (C) 2018 - Science and Technology Facility Council
# 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 ... |
<reponame>shwang/imitation-extern
"""Finite-horizon tabular Maximum Causal Entropy IRL.
Follows the description in chapters 9 and 10 of <NAME>'s `PhD thesis`_.
Uses NumPy-based optimizer Jax, so the code can be run without
PyTorch/TensorFlow, and some code for simple reward models.
.. _PhD thesis:
http://www.cs.... |
# coding: utf-8
"""
xgboost: eXtreme Gradient Boosting library
Version: 0.40
Authors: <NAME>, <NAME>
Early stopping by <NAME>
"""
from __future__ import absolute_import
import os
import sys
import re
import ctypes
import platform
import collections
import numpy as np
import scipy.sparse
try:
from sklearn.base ... |
#!/hosts/linuxhome/scarab/eva2/Programs/miniconda3/bin/python
#python3
import sys
from itertools import combinations
from euk_og_dict import *
from scipy.spatial import distance
################################################
#get inter orthology distances of profiles
################################################... |
<gh_stars>1-10
import numpy as np
from LVMvSSGP_model_SV2_IP import LVMvSSGP
import scipy.io as sio
from time import time
def extend(x, y, z = {}):
dictx=dict(x.items())
dicty=dict(y.items())
dictz=dict(z.items())
dictx.update(dicty)
dictx.update(dictz)
return dictx
pool, global_f, gl... |
<gh_stars>0
###############################################################################
# Potential.py: top-level class for a full potential
#
# Evaluate by calling the instance: Pot(R,z,phi)
#
# API for Potentials:
# function _evaluate(self,R,z,phi) returns Phi(R,z,phi)
# for orbit integration you ne... |
<gh_stars>1-10
from __future__ import unicode_literals, print_function, division, \
absolute_import
import numpy as np
from scipy.io import savemat
from datutils.utils import load_dat, create_dat, BUFFER_SIZE
BUF = BUFFER_SIZE
def dat2wave_clus(datfile, outfile):
data, params = load_dat(datfile)
sr = params["... |
#!/usr/bin/env python
from LLC_Membranes.analysis.markov_state_dependent_dynamics import States, Chain
from LLC_Membranes.timeseries.msd import Diffusivity
from LLC_Membranes.llclib import file_rw
from scipy.stats import levy_stable
import matplotlib.pyplot as plt
import numpy as np
import argparse
def initialize():
... |
<gh_stars>0
import funcs
from copy import copy
import os
from skimage import io, transform, color
from matplotlib import pyplot as plt
import pandas as pd
import numpy as np
from matplotlib_scalebar.scalebar import ScaleBar
from matplotlib import patches
import uncertainties
from uncertainties import unumpy as unp
impo... |
<filename>visu_images_all.py
# -*- coding: utf-8 -*-
"""
Created on Fri Jul 29 10:02:40 2016
@author: rflamary
"""
import sys
import numpy as np
import scipy as sp
import scipy.io as spio
import matplotlib.pylab as pl
import deconv
def get_fname(method,n,npsf,sigma,img):
return 'res/{}_{}x{}_PSF{}_sigma{:1.3f}... |
import sys
sys.path.insert(1,"/home1/07064/tg863631/anaconda3/envs/CbrainCustomLayer/lib/python3.6/site-packages") #work around for h5py
from cbrain.imports import *
from cbrain.cam_constants import *
from cbrain.utils import *
from cbrain.layers import *
from cbrain.data_generator import DataGenerator
import tensorflo... |
# -*- coding: utf-8 -*-
"""
This enables to parameterize the contributivity measurements to be performed.
"""
from __future__ import print_function
import bisect
import datetime
from itertools import combinations
from math import factorial
from timeit import default_timer as timer
import numpy as np
from loguru impo... |
<gh_stars>0
# -*- coding: utf-8 -*-
"""
Created on Sun Jan 3 13:21:37 2021
@author: mclea
"""
import numpy as np
import field as f
from scipy.interpolate import griddata
def jacobi_update(x, b, A, Rj, invD, nsteps=1, max_err=1e-3):
"""
Solves Ax=b
"""
# b_inner = b[1:-1, 1:-1].flatten()
n = x.x... |
import sympy as sp
from toy import Model
class Carbon(Model):
"""
A simple carbon model with 3 reservoirs: atmosphere, shallow oceans and
deep oceans.
Carbon simply flows between reservoirs and is conserved. In larger time
scales, we would expect net carbon sinks due to rock weathering, build up... |
<filename>run_script_pyg.py
import json
import pickle
import statistics
import time
import argparse
from os import listdir
import torch
import torch.nn.functional as F
from torch.nn import Linear, Sequential, ReLU
from torch_geometric.data import DataLoader
from torch_geometric.nn import GCNConv, avg_pool, global_mean... |
<reponame>mattzett/arcs_scen1
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Mar 5 06:02:51 2021
Load GEMINI output corresponding to synthetic Poynting flux, current density (parallel),
and electric field (perp.). Attempt to process the data into conductances
@author: zettergm
"""
# imports
im... |
import numpy as np
import scipy as sp
def emd(x, nIMF = 3, stoplim = .001):
"""Perform empirical mode decomposition to extract 'niMF' components out of the signal 'x'."""
r = x
t = np.arange(len(r))
imfs = np.zeros(nIMF,dtype=object)
for i in range(nIMF):
r_t = r
is_imf = False... |
import numpy as np
from scipy.special import expit
def mean_temperature(temperature, doy_series, start_doy, end_doy):
"""Mean temperature of a single time period.
ie. mean spring temperature.
Parameters
----------
temperature : Numpy array
array of daily temperature values
doy_series... |
#!/usr/bin/python3
"""
Perform Ordering-Dependency (OD) and Task-Consistency (TC) method.
Composed by <NAME> @THU_IVG
Last revision: <NAME> @THU_IVG @Oct 3rd, 2019 CST
"""
import argparse
import os.path
import pickle as pkl
import json
import scipy.io as sio
import numpy as np
import itertools
import concurrent.fut... |
import seaborn as sns
from matplotlib import pyplot as plt
import os
from scipy.io import loadmat
from seqnmf import seqnmf, plot
data = loadmat(os.path.join('data', 'MackeviciusData.mat'))
W, H, cost, loadings, power = seqnmf(data['NEURAL'])
h = plot(W, H)
h.show()
sns.heatmap(data['NEURAL'], cmap='gray_r')
plt.sho... |
<reponame>PetteriPulkkinen/SMPyBandits<filename>SMPyBandits/Arms/Poisson.py
# -*- coding: utf-8 -*-
""" Poisson distributed arm, possibly truncated.
Example of creating an arm:
>>> import random; import numpy as np
>>> random.seed(0); np.random.seed(0)
>>> Poisson5 = Poisson(5, trunc=10)
>>> Poisson5
P(5, 10)
>>> Poi... |
<gh_stars>0
from sympy import *
h = symbols('h',positive=true)
A = Matrix([[1 - h**2/2, -h/2*(2-h**2/2)],[h , 1-h**2/2]])
print("transition matrix")
print(A)
print("\n")
ATA = A.adjoint()*A
print("gram matrix")
print(simplify(ATA))
print("\n")
v1 = ATA.eigenvects()[0][2][0]
v2 = ATA.eigenvects()[1][2][0]
pri... |
"""Module containing the processing steps of the cwEPR package.
.. sidebar::
processing *vs.* analysis
For more details on the difference between processing and analysis,
see the `ASpecD documentation <https://docs.aspecd.de/>`_.
A processing step always operates on a dataset and usually modifies the
nu... |
import json
from collections import defaultdict
import random
import csv
from sklearn.svm import LinearSVC
from scipy import sparse
from joblib import dump, load
import numpy as np
from sklearn.feature_extraction import DictVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
from collections import... |
import warnings
import numpy as np
from scipy.integrate import quad
from scipy.interpolate import BSpline
from randomvars.options import config
# %% Array manipulations
def _as_1d_numpy(x, x_name, chkfinite=True, dtype="float64"):
"""Convert input to one-dimensional numpy array
Parameters
----------
... |
"""Comparing low vs. high dimensions/embeddings.
Description
-----------
import flameplot as flameplot
scores = flameplot.compare(data1, data2)
fig = flameplot.plot(scores)
X,y = flameplot.import_example()
fig = flameplot.scatterd(X[:,0],X[:,1],label=y)
Requirements
------------
os
numpy
tqdm
scipy
imagesc... |
<reponame>rinelson456/raven<gh_stars>100-1000
# Copyright 2017 Battelle Energy Alliance, 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
#
# http://www.apache.org/licenses/LICENSE-2.0
#
#... |
<reponame>delos/dm-pta-mc<gh_stars>0
"""
Handling custom density profile
"""
import numpy as np
from scipy.interpolate import interp1d
from scipy.integrate import cumtrapz
from scipy.special import hyp2f1
from src.input_parser import read_form
def prepare_form(form_path, verbose=False):
"""
Prepares in... |
<filename>basic_robotics/kinematics/arm_model.py
from ..general import tm, fmr, fsr
from ..plotting.Draw import DrawArm, DrawRectangle
from ..utilities.disp import disp
import numpy as np
import scipy as sci
import scipy.linalg as ling
import random
import xml.etree.ElementTree as ET
import os
import json
from os.path ... |
<reponame>rudimeier/BrainStat
import sys
sys.path.append("python")
from SurfStatPeakClus import *
from SurfStatEdg import *
import surfstat_wrap as sw
import numpy as np
import random
from scipy.io import loadmat
import pytest
def dummy_test(slm, mask, thresh, reselspvert=None, edg=None):
# Deal with edge offset.... |
# Computes the t-statistics on the whole experiment 1 dataset
import math
import csv
from scipy import stats
import numpy
def tstat(x1, x2, s1, s2, n):
'''
(float, float, float, float, int) => float
Computes the t-statistic for two datasets.
'''
t = (x1 - x2) / math.sqrt((s1**2 +s2**2)/n)
ret... |
"""Defines all the functions for plotting, allowing easier generation of results. Flexible, general functions remain a constant issue with plotting, so for more complex plots some tweaking may be needed.
Examples of these functions can be found in the :ref:`plotting_page` guide.
"""
from pathlib import Path
from iter... |
<gh_stars>1-10
from __future__ import print_function
from nltk.translate.bleu_score import sentence_bleu
from nltk.translate.bleu_score import SmoothingFunction
import sys
import re
import argparse
import torch
from util import read_corpus
import numpy as np
from scipy.misc import comb
from vocab import Vocab, VocabEnt... |
#!/usr/bin/env python3
import json
import numpy as np
import tkinter
import requests as req
from tkinter import *
from tkinter import ttk
from datetime import datetime
#from scipy import optimize
from scipy import signal
from matplotlib.backends.backend_tkagg import (
FigureCanvasTkAgg, NavigationToolbar2Tk)
# Im... |
<filename>graphics.py
# September 2020
#<EMAIL>
#graphings tools for plume rise analysis
import numpy as np
import matplotlib.pyplot as plt
import os.path
from matplotlib import ticker
from scipy.stats import linregress
from scipy.interpolate import interp1d
from mpl_toolkits.axes_grid1.inset_locator import inset_axes... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Jul 9 20:36:20 2020
@author: duttar
Description : Reads the daily temperature data from DS633 catalog
Calculates the Accumulated Degree Days of Thawing from the temperature data
"""
import numpy as np
from netCDF4 import Dataset # http://code.googl... |
<gh_stars>1-10
from importlib.util import find_spec
from scipy.sparse import coo_matrix, vstack
from numpy import matmul, isnan, clip
from numpy.linalg import norm
from math import ceil
if find_spec('joblib') is not None:
from joblib import Parallel, delayed, cpu_count
DEFAULT_CPUS = -1
else:
print('Could ... |
<reponame>bmoretz/Python-Playground<filename>src/Mathematics/Calculus/Differential/ch_03/3.1.py
import math
from sympy import Symbol, Limit, Derivative, sympify, S, simplify, pprint, init_printing
init_printing( order = 'rev-lex', use_unicode = True )
# 3.1.1
# h(t) = e^t + 2t^2
# simplify the expression:
# ( h( 5 ... |
<reponame>rsdefever/mosdef_slitpore
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy.ndimage.measurements import center_of_mass
from scipy import stats
import numpy as np
def compute_density(
traj,
area,
surface_normal_dim=2,
pore_center=0.0,
max_distance = 1.0,
... |
<reponame>dezeraecox/GEN_cell_culture
import os
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.ticker as tkr
import numpy as np
import pandas as pd
import scipy.stats as stats
import seaborn as sns
from loguru import logger
from matplotlib import rc
from pandas_profiling import ProfileRepo... |
<filename>vision/depth_camera/surface/bibspline_surface.py
import scipy.interpolate as si
import vision.depth_camera.surface._surface as sfc
import numpy as np
class BiBSpline(sfc.Surface):
def __init__(self,
xydata,
zdata,
degree_x=3,
degree_y=3... |
import subprocess
import matplotlib as mpl
import matplotlib
matplotlib.use('Qt5Agg')
import matplotlib.pyplot as plt
import numpy as np
import re
import math, cmath
from scipy.interpolate import griddata
import os
from femm import FEMM, FEMMfem, FEMMans
from PyQt5.QtWidgets import QApplication, QMainWindow, QMenu, ... |
#!/usr/bin/env python
import rospy
from std_msgs.msg import Int32
from geometry_msgs.msg import PoseStamped, Pose
from styx_msgs.msg import TrafficLightArray, TrafficLight
from styx_msgs.msg import Lane
from sensor_msgs.msg import Image
from cv_bridge import CvBridge
from light_classification.tl_classifier import TLCla... |
"""Various statistical helper functions"""
import warnings
import numpy as np
from scipy import stats
from scipy.special import ndtri
from .due import due
from . import references
def one_way(data, n):
""" One-way chi-square test of independence.
Takes a 1D array as input and compares activation at each vox... |
import os
import sys
import torch
import numpy as np
import scipy.misc as m
import matplotlib.pyplot as plt
import matplotlib.image as imgs
from PIL import Image
import random
import scipy.io as io
from tqdm import tqdm
from scipy import stats
from torch.utils import data
from .utils import recursive_glob
from augme... |
# This is the image processing module, which I used to preprocess my images, augment my dataset, and
# organize them into a structure suitable for input to a machine learning model
from __future__ import print_function
import matplotlib.pyplot as plt
import numpy as np
import os
import sys
import tarfile
import tensor... |
# License: BSD 3-clause
# Authors: <NAME>,
# <NAME>
import numpy as np
from numpy.lib.stride_tricks import as_strided
import scipy.signal as sg
from scipy import linalg, fftpack
from numpy.testing import assert_almost_equal
def rolling_mean(X, window_size):
"""
Calculate the rolling mean
Parame... |
import scipy
from SloppyCell.ReactionNetworks import *
import LeeNet
reload(LeeNet)
from LeeNet import net
# Network that is at unstimulated fixed point
net.set_var_ic('W', 0)
traj1 = Dynamics.integrate(net, [0, 1e5], rtol=1e-12)
unstimulated = net.copy('unstimulated')
for var in unstimulated.dynamicVars.keys():
... |
<reponame>zmlabe/predictGMSTrate
"""
Create plot to show scores vs. number of hiatuses it trained on
Author : <NAME>
Date : 27 September 2021
Version : 2 (mostly for testing)
"""
### Import packages
import sys
import matplotlib.pyplot as plt
import matplotlib.colors as c
import numpy as np
import scipy.s... |
<filename>src/test_mh_ggk.py<gh_stars>10-100
import unittest
import qnet
import qnetu
import numpy
import mytime
import netutils
import estimation
import yaml
import pwfun
import sampling
import arrivals
import qstats
import queues
import test_qnet
from scipy import integrate
from numpy import random
import gc
impor... |
from math import floor, ceil
from scipy.stats import uniform, randint, norm, truncnorm, bernoulli, geom, hypergeom, poisson, zipf, triang
from snake_eyes.distribution import add, mul
from snake_eyes.from_rv import rv_continuous_class, rv_discrete_class
from snake_eyes.support_space import DiscreteWholeSupportSpace
... |
<reponame>merenlab/meren.github.io
'''loop over a bam file and get the edit distance to the reference genome stored in the NM tag
scale by aligned read length. works for bowtie2, maybe others. Adopted from
https://gigabaseorgigabyte.wordpress.com/2017/04/14/getting-the-edit-distance-from-a-bam-alignment-a-journey/'''
... |
<filename>fastface/metric/ar.py
from pytorch_lightning.metrics import Metric
from typing import List
import torch
from ..utils.box import jaccard_vectorized
from scipy.optimize import linear_sum_assignment
class AverageRecall(Metric):
r"""pytorch_lightning.metrics.Metric instance to calculate average recall
.. math... |
<reponame>jm-begon/randconv
# -*- coding: utf-8 -*-
""" """
__author__ = "<NAME> <<EMAIL>>"
__copyright__ = "3-clause BSD License"
__date__ = "20 January 2015"
import numpy as np
import scipy.sparse as sps
from sklearn.metrics import confusion_matrix
from sklearn.ensemble import RandomTreesEmbedding
from progressmo... |
from pandas import Series,DataFrame
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn.cross_validation import train_test_split
from sklearn.cluster import KMeans
from sklearn import preprocessing
import os
from sklearn import datasets
import sklearn.metrics as sm
from sklearn.preproc... |
#
# Generates output .csv files from
#
import os
import numpy as np
import pandas as pd
import scipy.io
from typing import Dict
from birdspy.image_factory import ImageFactory
class OutputWriter:
"""Factory to generate ground truth images from a given annotation dataset.
Currently only stores the number of... |
<gh_stars>0
"""spectrum is an array of data which defines a physical spectrum
A Spectrum is a numpy array with an associated type which describes
the physical quantity (e.g. wavelength, energy, etc.) and a unit
for specifiying the SI unit of the spectrum (e.g. meter, electronVolt)
"""
import numpy as np
import scipy.c... |
<gh_stars>0
import warnings
import numpy as np
import pandas as pd
from scipy import stats
def _delta_mean(x, y):
"Implemented as function to allow calling from bootstrap."
return np.nanmean(x) - np.nanmean(y)
def make_delta(assume_normal=True, percentiles=[2.5, 97.5],
min_observations=20, n... |
<gh_stars>1-10
from __future__ import print_function
import sys
import os
from setuptools import setup, find_packages
from distutils.extension import Extension
from Cython.Build import cythonize
from Cython.Distutils import build_ext
with open('requirements.txt') as f:
INSTALL_REQUIRES = [l.strip() for l in f.re... |
import numpy as np
import os
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.colors as colors
from astropy.time import Time
import matplotlib.dates as mdates
from astropy.io import fits
import numpy.ma as ma
import matplotlib.cm as cm
from mpl_toolkits.axes_grid1 import make_axes_locatable
im... |
from initialise_parameters import params, control_data, categories, calculated_categories, change_in_categories
from math import exp, ceil, log, floor, sqrt
import numpy as np
from scipy.integrate import ode
from scipy.stats import norm, gamma
import pandas as pd
import statistics
import os
import pickle
from tqdm impo... |
<filename>machine-learning-ex2/owns/myex2++.py<gh_stars>0
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
#Scipy库中的optimiz可以实现matlab中fminunc的功能，来优化函数计算成本和梯度
import scipy.optimize as opt
#高级处理分类的一个信息report
from sklearn.metrics import classification_report as cr
#=================visualizing data... |
<gh_stars>1-10
import sys
sys.path.insert(0, '../prog')
from .psUtils import *
import numpy as np
import scipy.special
class ReconstructFromPyramid:
def __init__(self, pyr, indices, levels=-1, bands=-1, twidth=1):
self._pyr = pyr
if not isinstance(indices, np.ndarray):
self._pInd = np... |
<gh_stars>10-100
#!/usr/bin/env python
# Test example to generate 2D (embedded in 3D) and 3D Delaunay triangulations that output to VTK
import pyvtk
import numpy as np
from scipy.spatial import Delaunay
# Generate the random points
npoints = 1000
np.random.seed(1)
x = np.random.normal(size=npoints)*np.pi
y = np.rand... |
#!/usr/bin/env python
# coding: utf-8
# ### Level 4 - Normalized DMSO Profiles Cell painting data
#
#
# #### The goal here:
#
# -- is to determine the median score of each compound per dose based on taking the median of the correlation values between replicates of the same compound.
#
# - Level 4 data - are replic... |
from __future__ import print_function
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
'''
Copyright (c) 2016 <NAME>
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction... |
# -*- coding: utf-8 -*-
# import torch
# import torch.nn.functional as F
# from torch.autograd import Variable
# import numpy as np
# from math import exp
# import math
# def gaussian(window_size, sigma):
# gauss = torch.Tensor([exp(-(x - window_size//2)**2/float(2*sigma**2)) for x in range(window_size)])
# r... |
<filename>radmc-3d/version_0.41/python/radmc3dPy/miescat.py
"""This module contains functions for Mie-scattering and to write dust opacity files
"""
from __future__ import absolute_import
from __future__ import print_function
import traceback
try:
import numpy as np
except ImportError:
np = None
print(' Nu... |
<filename>samurai/main_fitlc_mcmc_EPOXI_NEW.py<gh_stars>1-10
import numpy as np
import healpy as hp
import emcee
from scipy.optimize import minimize
import sys
import datetime
import multiprocessing
import os
from pdb import set_trace as stop
import h5py
__all__ = ["run_lightcurve_mcmc"]
from fitlc_params import NUM_... |
# License: BSD 3 clause
import unittest
import numpy as np
from scipy.optimize import check_grad, fmin_bfgs
from scipy.linalg import norm
from scipy.sparse import csr_matrix
from tick.survival import SimuSCCS, ModelSCCS
from tick.preprocessing import LongitudinalFeaturesLagger
from tick.solver import SVRG
from tick.pr... |
# GPS L1Cp code construction
#
# Copyright 2018 <NAME>
import numpy as np
from sympy.ntheory import legendre_symbol
chip_rate = 1023000
code_length = 10230
l1cp_params = {
1: (5111,412), 2: (5109,161), 3: (5108,1), 4: (5106,303),
5: (5103,207), 6: (5101,4971), 7: (5100,4496), 8: (5098,5),
... |
import pandas
import numpy
import numpy.random
import typing
import itertools
import matplotlib.pyplot
import scipy.stats
DataFrame = typing.TypeVar('pandas.core.frame.DataFrame')
class Corpus(object):
def __init__(self, design_file_name: str, participant_file_name: str, genealogy_levels: list, weights: list) -... |
<filename>tests/zquantum/core/wip/circuits/_wavefunction_operations_test.py
import pytest
import sympy
from zquantum.core.wip.circuits import MultiPhaseOperation
import numpy as np
class TestMultiPhaseOperation:
@pytest.mark.parametrize(
"wavefunction",
[
np.array([1, 0, 0, 0]),
... |
<filename>notebooks/brunel-alpha-nest.py
#!/usr/env/bin python
# -*- coding: utf-8 -*-
#
# brunel_alpha_nest.py
#
# This file is part of NEST.
#
# Copyright (C) 2004 The NEST Initiative
#
# NEST is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published b... |
"""
The Abel habit model: contrasting stability tests
"""
from scipy.stats import norm
import numpy as np
class AbelModel:
"""
Represents the model.
"""
def __init__(self, β=0.99,
γ=2.5,
ρ=-0.14,
σ=0.002,
x... |
import numpy as np
import pandas as pd
from scipy import interpolate
from scipy.stats import norm
from scipy.optimize import curve_fit
from matplotlib import pyplot as plt
from scipy.stats import exponnorm
#import seaborn as sns
#from fitter import Fitter, get_common_distributions, get_distributions
def gauss_flat(xva... |
import numpy as np
from scipy.stats import kendalltau
import pandas as pd
def dividend_pricing(num_days, amount, completeness, position):
"""
Function is used to calculate "priced in" dividends in
daily historical prices. As no strict model is established
for dividend pricing, this is my own ... |
import string
import numpy as np
from scipy.constants import codata
from scipy.fftpack import fft, ifft
eV = codata.value("electron volt")
me = codata.value("electron mass") * 1e15 # convert to pico grams
hbar = codata.value("Planck constant over 2 pi") * 1e27 # convert to pico-compatible values
clas... |
"""
Prototyping some approaches for local orthogonalization
"""
from __future__ import print_function
import numpy as np
from stompy.grid import unstructured_grid
from stompy.utils import (mag, circumcenter, circular_pairs,signed_area, poly_circumcenter,
orient_intersection,array_append,wit... |
import numpy as np
import os
import h5py
import json
from .utils import asymptotic_error_quantile, bootstrap,\
dict_to_margins, margins_to_dict, matrix_to_list
from sklearn.utils import check_random_state
from scipy.stats import gaussian_kde, norm
from .vinecopula import Conversion
class ListDependenceResult(li... |
<gh_stars>0
"""An array context with profiling capabilities."""
__copyright__ = """
Copyright (C) 2020 University of Illinois Board of Trustees
"""
__license__ = """
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to de... |
<filename>pySPACE/missions/nodes/base_node.py
""" Skeleton for an elemental transformation of the signal
This includes some exception and metaclass handling, but the most important part
is the :class:`~pySPACE.missions.nodes.base_node.BaseNode`.
.. note::
This module includes a reimplementation of the MDP node cl... |
# Using convolutions in numpy
import numpy as np
from scipy.ndimage import convolve
from itertools import combinations
def read_file(test = True):
if test:
filename = '../tests/day20.txt'
else:
filename = '../input/day20.txt'
with open(filename) as file:
image = list()
for ... |
<gh_stars>1-10
################################################################################
# Github: https://github.com/MaxInGaussian/GomPlex
# Author: <NAME> (<EMAIL>)
################################################################################
import random
import numpy as np
import numpy.random as npr
fr... |
<gh_stars>0
import numpy as np
from scipy import stats
import random
import matplotlib.pyplot as plt
n = 10
arms = np.random.rand(n)
eps = 0.3
def reward(prob):
reward = 0;
for i in range(10):
if random.random() < prob:
reward += 1
return reward
#initialize memory array; has 1 row de... |
# -*- coding: utf-8 -*-
"""
Created on Tue Oct 5 17:56:11 2021
v0.8 28Oct21
@author: <NAME>
CHANGE POINT DETECTOR
This module takes a time series and returns the uunderlying linear trend and changpoints. It uses EVT as described in https://www.robots.ox.ac.uk/~sjrob/Pubs/LeeRoberts_EVT.pdf
INSTRUCTIONS:... |
# https://www.facebook.com/abhi.sensharma/posts/1241788872853419
# Subscribed by <NAME>
# Polar coordinates problem solution
# Enter your code here. Read input from STDIN. Print output to STDOUT
import cmath
# input is of type complex
c = complex(input())
# cmath.polar(x) returns a pair (abs(x), phase(x))
# * prefix... |
"""
Script calculates comparisons of T2M with SIT from LENS. Note the first
part regrids on 1x1 degree grid for comparison with LENS SIT
Notes
-----
Author : <NAME>
Date : 22 February 2017
"""
### Import modules
import numpy as np
import matplotlib.pyplot as plt
import datetime
import scipy.stats as sts
i... |
<reponame>rgautam95/seislib<filename>seislib/an/an_attenuation.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
@author: <NAME>
@email1: <EMAIL>
@email2: <EMAIL>
"""
import os
import itertools as it
from collections import defaultdict
from types import GeneratorType
import gc
import numpy as np
from numpy.fft im... |
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