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from flask import send_from_directory, abort, Flask, jsonify, abort, request, render_template
import os
#importing classes
import pandas as pd
import numpy as np
#import matplotlib.pyplot as plt
from sklearn import linear_model
from sklearn.model_selection import cross_val_score
from sklearn.model_selection imp... |
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Sat Jan 7 23:37:04 2017
@author: LinZhang
"""
from __future__ import print_function
import matplotlib.pyplot as plt
import numpy as np
import os
import sys
import tarfile
from IPython.display import display, Image
from scipy import ndimage
from sklearn.lin... |
#!/usr/bin/env python3
# Copyright (c) 2020 NVIDIA Corporation. All rights reserved.
# This work is licensed under the NVIDIA Source Code License - Non-commercial. Full
# text can be found in LICENSE.md
import _init_paths
import argparse
import os, sys
import subprocess
from transforms3d.quaternions import mat2quat, ... |
<filename>ethologger/features/spatio_temporal.py
import math
import itertools
import numpy as np
import pandas as pd
from scipy.ndimage.filters import uniform_filter1d, median_filter
import ethologger.utils.auxiliary as aux
import ethologger.utils.preprocessing as prep
np.seterr(all="ignore")
class SpatioTemporal:... |
<reponame>DASdaNen4f/microsoftw<gh_stars>10-100
import json
from itertools import islice
from urllib.request import urlopen
import numpy as np
import tensorflow as tf
import tensorflow_hub as hub
import PIL.Image as Image
import requests
from moviepy.editor import *
from scipy.stats import truncnorm
from io import Byte... |
import re
import requests
import warnings
import pandas as pd
import numpy as np
import statsmodels.api as sm
import statsmodels.stats.api as sms
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
from statsmodels.compat import lzip
from statsmodels.stats.stattools import durbin_watson
from statsmodels.t... |
<filename>probability-distributions/continous.py
from scipy.stats import norm, beta, chi2, expon, gamma, laplace, t
from bokeh.models import Slider
from bokeh.plotting import curdoc
from distributions import BokehContDist
normal = BokehContDist(
norm.rvs,
norm.pdf,
norm.cdf,
name="Normal Distrib... |
<gh_stars>10-100
# AUTOGENERATED! DO NOT EDIT! File to edit: nbs/06_conjugates.ipynb (unless otherwise specified).
__all__ = ['beta_approx', 'gamma_approx', 'gamma_alpha_approx', 'pois_alpha_param', 'gamma_solver', 'beta_solver',
'conj_params', 'bern_conjugate_params', 'pois_conjugate_params', 'bin_conjugat... |
<reponame>chenhaoxing/ASL<filename>torchmeta/datasets/semantic.py
'''
CUB original website: http://www.vision.caltech.edu/visipedia/CUB-200-2011.html
auxiliary modality data can be obtained from the repository of Learning Deep Representations of Fine-grained Visual Descriptions：https://github.com/reedscot/cvpr2016
SUN... |
import pandas as pd
import numpy as np
import itertools
import scipy.stats as stats
from .trend_components import *
# from . import trend_components
# import *
## set all list at bottom
class Binary_Accuracy_Trend(BinClassStats,PredictionClass,Trend):
my_stat = 'acc'
name = 'binary_acc'
display_name = '... |
<reponame>l1va/controlsym<gh_stars>1-10
from sympy import (symbols, zeros, latex, ShapeError)
from sympy.printing import sstr
class StateSpaceModel:
def __init__(self, A, B, C=None, D=None, x=None, u=None):
if not (A.shape[0] == A.shape[1]):
raise ShapeError("Shapes of A must be nxn")
... |
import plots
from sympy import *
x = Symbol('x')
myPlot = plots.MyStandardPlot()
myPlot.ygraph(1-x/2,(x,0,1))
myPlot.disk(0,1,0.02)
myPlot.disk(1,0.5,0.02)
myPlot.xticks([0,1])
myPlot.yticks([0,1])
myPlot.yaxis("left")
myPlot.canvas.text(0.5,0.70,r'slope = $f(0,1)$',rotation=-26.575,ha='center',fontsize=12)
#myPl... |
from __future__ import annotations
import os
import time
from abc import ABC, abstractmethod
from collections import Counter
from logging import Logger, getLogger
from typing import Any, Optional
import imblearn
import joblib
import lightgbm as lgb
import MeCab
import numpy as np
import pandas as pd
import tensorflow... |
#!python
# spark-submit --master local[7] --deploy-mode client CondPerfTest.py
import gc
import scipy.stats, numpy
import time
from LinearRegression import linear_regression
from pyspark.sql import SparkSession
spark = None
sc = None
log = None
def createSparkContext():
global spark
spark = SparkSession \
... |
import scipy.optimize
import numpy as np
import pyautogui
import os, time
pyautogui.FAILSAFE = False
def write_dat_file(file_name, params):
file = open(file_name, "w")
file.write("& Version=4.20\n")
file.write("SI=yes\n")
file.write("\n")
file.write("\n")
file.write("\n")
file.write("\n"... |
import skimage
import skimage.io
import numpy as np
from scipy.ndimage import zoom
from skimage.transform import resize
import matplotlib.pylab as plt
import keras_image_preprocessing
# The following two function are borrowed from Caffe
# https://github.com/BVLC/caffe/blob/32dc03f14c36d1df46f37a7d13ad528e52c6f786/pyth... |
<filename>submit/vec_feat_xgb_test/feature_extract/word2vec.py
# -*- coding:utf8 -*-
# ==============================================================================
# Copyright 2018 Hisense, Inc. All Rights Reserved
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except ... |
import numpy as np
import scipy
import itertools
import time
from math import factorial
import copy as cp
import sys
from fermicluster import *
from pyscf_helper import *
import pyscf
ttt = time.time()
np.set_printoptions(suppress=True, precision=4, linewidth=1500)
pyscf.lib.num_threads(1) #with degenerate states a... |
<filename>PWEM_examples/verification_with_fdfd_TM.py
import os
## check how well pwem and fdfd match
import scipy.io
import numpy as np
import sys
sys.path.append("D:\\RCWA\\")
import matplotlib.pyplot as plt
from convolution_matrices import convmat2D as cm
from PWEM_functions import K_matrix as km
from PWEM_function... |
import numpy as np
from scipy import linalg
import pathlib, sys, os
file_path = pathlib.Path(__file__).parent.absolute()
from pressio4py import logger as logger
from pressio4py import rom as rom
from pressio4py import solvers as solvers
from pressio4py.apps.burgers1d import Burgers1d
np.set_printoptions(linewidth=24... |
<filename>thequickmath/stats.py
import functools
from typing import Sequence, Union
import numpy as np
import scipy.stats
class ScipyDistribution:
"""
Class ScipyDistribution is a handy wrap-up around scipy.stats.rv_continuous. It has the same interface as
scipy.stats.rv_continuous, but without distribut... |
"""
<NAME>
Code based on Intro and data section od the Machine learning series by Sentdex
https://www.youtube.com/channel/UCfzlCWGWYyIQ0aLC5w48gBQ
Description: regression on randomly generated data
"""
from statistics import mean
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import style
import ra... |
<gh_stars>0
"""Main module with most functionality.
The contents of this submodule are loaded when importing the package.
"""
from typing import Any, Callable, Dict, List, Tuple, Union
from abc import abstractmethod
import math
from scipy.sparse import csr_matrix, dia_matrix, diags, identity
from scipy.sparse.linalg ... |
#!/usr/bin/env python3
from netcdfTools import *
import sys
import argparse
import numpy as np
import matplotlib.pyplot as plt
from scipy.fftpack import rfft, irfft, fftfreq
from utilities import filesFromList, writeLog
'''
Description:
Author: <NAME>
<EMAIL>
University of Helsinki &
Finnish... |
import solvers as sol
from AS1_class import Asym_slab
import numpy as np
import matplotlib.pyplot as plt
import pickle
from scipy.interpolate import interp1d
def save():
with open('pickles/threshold_density_sym_c0={}_K={}_M_A={}.p'.format(
slab.c0, slab.K, slab.M_A), 'wb') as f:
pickle... |
import logging
import re
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import scanpy as sc
from captum.attr import IntegratedGradients
from pandas import read_excel
from scipy.stats import mannwhitneyu
from sklearn.metrics import precision_recall_curve, roc_curve
import scanpypip.utils as ut
... |
<reponame>fabiobaccarin/allstate-loss
"""
Cost-effectiveness analysis of transforming y for better prediction
Options:
A. Log
B. Yeo-Johnson
C. QuantileTransformer
"""
import time
import typing as t
import pandas as pd
import numpy as np
from sklearn.preprocessing import power_transform, quantile_transfor... |
from sympy import Symbol, integrate, oo, simplify
import math
t = Symbol('t')
ex = integrate(t * 0.01 * math.e**(-0.01*t), (t, 0, oo))
ex.doit()
import scipy.integrate as si
import numpy as np
si.quad(lambda t: t * 0.01 * np.exp(-0.01*t), 0, np.inf)
# https://www.derivative-calculator.net/
# https://www.integral-ca... |
<reponame>PeterJaq/optical_film_toolbox<gh_stars>1-10
from os.path import abspath, dirname, join
import numpy as np
import scipy.sparse as sp
FILE_DIR = dirname(abspath(__file__))
DATA_DIR = join(FILE_DIR, "data")
MACOSKO_COLORS = {
"Amacrine cells": "#A5C93D",
"Astrocytes": "#8B006B",
"Bipolar cells": "... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Denoise effect: RDM between denised and original data.
@author: <NAME>
"""
import os
import numpy as np
import pandas as pd
import nibabel as nib
from seaborn import heatmap
import matplotlib.pyplot as plt
from scipy.spatial.distance import cdist
# path and input
be... |
<gh_stars>0
r"""
===============================================================================
pore_diameter
===============================================================================
"""
from OpenPNM.Base import logging
from . import misc as _misc
import scipy as _sp
_logger = logging.getLogger()
def weibull... |
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from scipy.spatial.distance import cdist
pd.options.mode.chained_assignment = None
def plot_outliers(outliers, inliers, center, df):
plt.scatter(inliers['Quantity'] , inliers['Price'], label='Inliers')
plt.scatter(outliers['Quantity'] , out... |
<reponame>jjuch/simupy
import sympy as sp
from sympy.physics.mechanics import dynamicsymbols
from sympy.physics.mechanics.functions import find_dynamicsymbols
from simupy.utils.symbolic import (lambdify_with_vector_args, grad,
DEFAULT_LAMBDIFY_MODULES)
from simupy.array import Array
from simupy.systems import Dyn... |
<reponame>Piers14/sde_mc
import numpy as np
import torch
from scipy.integrate import quad
from scipy.stats import norm, lognorm
from abc import ABC, abstractmethod
def bs_binary_aon(spot, strike, expiry, r, sigma):
"""Computes the true value of a binary asset-or-nothing option under Black-Scholes assumptions
... |
<filename>wav2raw.py<gh_stars>0
from scipy.io import wavfile
import os
import h5py
# custom imports
import librispect as lspct
# trainroot = ['train-clean-100-wav/', 'train-clean-360-wav/', 'train-other-500-wav/']
# devroot = ['dev-clean/', 'dev-other/']
# testroot = ['test-clean/']
dev_clean = lspct.paths.DEV_C... |
<reponame>nouiz/pydy
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Exercise 9.13 from Kane 1985."""
from __future__ import division
from sympy import expand, symbols
from sympy.physics.mechanics import ReferenceFrame, Point
from sympy.physics.mechanics import dynamicsymbols
from util import msprint, partial_velocit... |
"""Galaxy morphology module.
This module provides facilities to sample the sizes and ellipticities of
galaxies.
"""
__all__ = [
'angular_size',
'beta_ellipticity',
'early_type_lognormal_size',
'late_type_lognormal_size',
'linear_lognormal_size',
'ryden04_ellipticity',
]
import numpy as np
fr... |
#!/usr/bin/env python
'''
########################################################################################################
# A Program to read the NIST website, extract isothermal or isobaric data and reformat into a rho-E table
# Written: April 2013
# Author: jph
# Version: 0.23
###########################... |
<filename>Backend/src/FunctionML.py
import pandas as pd
import numpy as np
from sklearn import ensemble
from sklearn import metrics
from statistics import mean
##Etude variation
def etudeRelationAbsolue(df_knockouts,df_wildtype):
m = len(df_knockouts.values)
mat = np.zeros((m,m))
mat2= np.zeros((m,m))
... |
<gh_stars>1-10
import os
import random
import pickle
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.pyplot import imshow
import keras
from keras.preprocessing import image
from keras.applications.imagenet_utils import decode_predictions, preprocess_input
from keras.datasets import mnist, fashion_mni... |
# coding: utf-8
"""
===================================
Enhanced chroma and chroma variants
===================================
This notebook demonstrates a variety of techniques for enhancing chroma features and
also, introduces chroma variants implemented in librosa.
"""
##########################################... |
#!/usr/bin/env python
"""File: pointpatterns.py
Module to facilitate point pattern analysis in arbitrarily shaped 2D windows.
"""
# Copyright 2015 <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 th... |
#!/usr/bin/python
# -*-coding: utf-8 -*-
# Author: <NAME>
# Email : <EMAIL>
from __future__ import division
def plot(data, idx, x=None, y=None, ci=95, n_boot=5000, random_seed=12345,
color_col=None,
paired=False,
effect_size="mean_diff",
raw_marker_size=6,
es_marker_size=9,
... |
<reponame>HunterLC/FARSystem
import random
import pandas as pd
import numpy as np
from sklearn.preprocessing import Normalizer, MinMaxScaler
from scipy.linalg import norm
from math import sqrt
class Recommend:
def __init__(self, data_path=r'E:\PythonCode\FARSystem\static\data\actor_similarity_data.csv', current_a... |
__all__ = ['CollectorManager']
import concurrent.futures
from datetime import datetime, timedelta
from statistics import mean
from spaceone.core.error import ERROR_NOT_IMPLEMENTED
from spaceone.core.manager import BaseManager
from spaceone.inventory.error.custom import *
from spaceone.inventory.model.server import *
... |
import pandas as pd
import numpy as np
from sklearn.model_selection import StratifiedKFold
from statistics import mean
from sklearn.metrics import precision_recall_curve, auc
from sklearn.svm import SVC
def pr_linear_SVC(X_train, X_test, y_train, y_test):
clf = SVC(kernel="linear", random_state=0, tol=1e-5, clas... |
import os
import statistics as s
from copy import deepcopy
import matplotlib.pyplot as plt
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.distributions.categorical import Categorical
from torch.utils.tensorboard import SummaryWriter
from tqdm import tqdm
from KD_Lib.KD.common.utils impo... |
import pandas as pd
import math, os, sys
"""
Usage: ./cd_spectra_mpl.py <file_or_folder>
Plots either a single CD spectrum or a folder of spectra.
"""
def parse_ascii(filename):
start = 0
xunits = None
yunits = None
y2units = None
enzyme_conc = None
with open(filename, 'r') as f:
pri... |
<reponame>hu-minghao/Anji-data
# python3 extractor.py
import os
import cv2
import numpy as np
from scipy import stats
from pathlib import Path
def main():
num_imgs = 50000
# The output dir for storing the extracted imgs
output_dir = "extracted"
os.makedirs(output_dir, exist_ok=True)
# The locatio... |
# -*- coding: utf-8 -*-
import json
import os
import sys
from glob import glob
from os.path import dirname, exists, join, realpath
import numpy as np
import pandas as pd
from astropy import units as u
from astropy.coordinates import AltAz, EarthLocation
from astropy.io import fits
from astropy.time import Time
from ca... |
#!/usr/bin/env python
# coding: utf-8
# In[1]:
get_ipython().system('pip install -U scipy')
# In[2]:
get_ipython().system('pip install -U statsmodels')
# In[3]:
import scipy
import statsmodels
# In[4]:
scipy.__version__
# In[5]:
statsmodels.__version__
# In[6]:
import numpy as np
import pandas a... |
import numpy as np
import itertools
import math
from tqdm import tqdm
import scipy
from sympy import simplify
from sympy.solvers.diophantine.diophantine import diop_solve
from sympy.solvers.diophantine.diophantine import diop_ternary_quadratic
import random
from sympy.solvers.diophantine.diophantine import diop_qua... |
from sklearn.neighbors import kneighbors_graph
from sklearn.neighbors import NearestNeighbors
from scipy.sparse.linalg import eigsh
from scipy import sparse
import numpy as np
class Laplacian():
def __init__(self, n_neighbours =50, n_component = 2, gamma= None, method ='kneighbour'):
self.n_neighbour = ... |
<reponame>cassiePython/cddfm3d<filename>Deep3DFaceReconstruction-pytorch/lib_py/chj_pic.py
# -*- coding:utf-8 -*
import re
import numpy
import numpy as np
import scipy.io as scio
import cv2 as cv
import cv2
from PIL import Image
from numpy import random
import scipy
import matplotlib.pyplot as plt
def ps(dt): print... |
<filename>src/dbsocp/cli/mergedups.py<gh_stars>0
"""
Find barcodes and merge originating from the same droplet/compartment.
"""
from collections import OrderedDict, defaultdict, Counter
import logging
from typing import Dict, Set, Tuple
import dataclasses
from xopen import xopen
import numpy as np
import scipy
impor... |
<reponame>jorgemauricio/proyectoCaborca
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Jul 17 16:17:25 2017
@author: jorgemauricio
"""
# librerías
import os
import urllib.request
import time
from time import gmtime, strftime
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
f... |
<filename>containers/anndata-to-ui/context/main.py
import argparse
from glob import glob
from pathlib import Path
from os import mkdir, environ
import json
import zarr
from scipy import sparse
from anndata import read_h5ad
NUM_MARKER_GENES_TO_VISUALIZE = 5
VAR_CHUNK_SIZE = 10
SECONDARY_ANALYSIS = "secondary_analysis.... |
<filename>scoreprobability/score_predict.py
"""
@Project : ScoreProbability
@Module : score_predict.py
@Author : HjwGivenLyy [<EMAIL>]
@Created : 12/18/18 10:22 AM
@Desc : predict the outcome by score probability calculation model
"""
import logging
import os
import typing
import loguru
import numpy as... |
# Functions for initializing and integrating the deletion frequency
# spectrum forward in time.
from . import util
from scipy.sparse.linalg import factorized
from scipy.sparse import identity
from scipy.special import gammaln
from scipy.sparse.linalg import csc_matrix, csr_matrix
from scipy.sparse.linalg import spsol... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# ---
# jupyter:
# jupytext:
# text_representation:
# extension: .py
# format_name: light
# format_version: '1.4'
# jupytext_version: 1.1.4
# kernelspec:
# display_name: Python 3
# language: python
# name: python3
# ---
# # s_co... |
# Classes and functions to make it easy to do a dscan with realtime fitting to
# a custom function.
import glob
from bluesky.callbacks import CallbackBase
class SavingCallback(CallbackBase):
''' This call back saves data in a data element.
Access each element by calling
scallback.data[key] etc...
'''
def __i... |
# -*- coding: utf-8 -*-
"""
SYS-611 Continuous Time Models.
@author: <NAME>, <EMAIL>
"""
# import the python3 behavior for importing, division, and printing in python2
from __future__ import absolute_import, division, print_function
# import the numpy package and refer to it as `np`
# see http://docs.scipy.org/doc/n... |
# -*- coding: utf-8 -*-
"""
@author: <NAME>
"""
import numpy as np
import matplotlib.pyplot as plt
from math import exp, log, ceil
from scipy.optimize import fsolve
from utility import u, k
from typeFunction import h, type_function
from distribution import G, invG
from parameters import lumbda, c
'''... |
from PyQt4 import QtGui
from PyQt4.QtCore import *
from PyQt4.QtGui import *
import os, sys
import csv
import pandas as pd
import numpy as np
from scipy.interpolate import spline
from scipy.optimize import curve_fit
from scipy.interpolate import interp1d
from sklearn.decomposition import FastICA
from scipy.interpolate ... |
<reponame>lnies/lEval
# -*- coding: utf-8 -*-
"""
Created on Thurs 16 Feb 2017
@author: mamougeo
"""
###################
# Global variables
###################
###################
from time import sleep
import win32com.client
import pydim as dim
import csdatalib as cs
import numpy as np
import scipy.optimize as scop
... |
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
from scipy.optimize import curve_fit
# Set fontsize larger for plots
matplotlib.rcParams.update({"font.size": 20})
a_x, a_y = np.genfromtxt("output/output_a.txt", unpack=True)
b_x, b_y = np.genfromtxt("output/output_b.txt", unpack=True)
c_x, c_y = n... |
<filename>m2/runAudioExperiment/trial_data.py
import os
import random
import logging
import time
import sounddevice
import pandas as pd
from scipy.io import wavfile
from m2.runAudioExperiment import audio
TRIAL_SETTINGS_FILENAME = 'trial_settings.csv'
TRIAL_DURATIONS_FILENAME = 'trial_durations.csv'
logger = logging.... |
<reponame>samarpan-rai/clumper<gh_stars>0
import json
import csv
import pathlib
import itertools as it
import urllib.request
from functools import reduce
from statistics import mean, variance, stdev, median
from clumper.decorators import (
return_value_if_empty,
grouped,
dict_collection_only,
multifil... |
<reponame>gionanide/Speech-Signal-Processing-and-Classification
#!usr/bin/python
import numpy
import numpy.matlib
import scipy
from scipy.fftpack.realtransforms import dct
from sidekit.frontend.vad import pre_emphasis
from sidekit.frontend.io import *
from sidekit.frontend.normfeat import *
from sidekit.frontend.featu... |
<reponame>universvm/sequence-recovery-benchmark<filename>benchmark/visualization.py
"""Functions for visualizing metrics and comparing different models"""
import pandas as pd
from benchmark import config
import ampal
from benchmark import get_cath
import gzip
from pathlib import Path
import numpy as np
import... |
<reponame>MrCull/Kamodo<filename>kamodo/readers/swmf_ie.py
from kamodo import Kamodo, kamodofy
#, gridify
from netCDF4 import Dataset
import numpy as np
import os
import scipy
from scipy import interpolate
from scipy.interpolate import RegularGridInterpolator
import math
import scipy.constants as constants
from plotly... |
import os
import pickle
import numpy as np
import soundfile as sf
from scipy import signal
from scipy.signal import get_window
from librosa.filters import mel
import librosa
from numpy.random import RandomState
from sklearn.preprocessing import RobustScaler
class Spect(object):
def __init__(self, config):
... |
<reponame>LaudateCorpus1/RosettaCodeData
from itertools import islice, tee
from fractions import Fraction
try:
from itertools import izip as zip # for 2.6
except:
pass
def pluspower(*powergenerators):
for elements in zip(*powergenerators):
yield sum(elements)
def minuspower(*powergenerators):
f... |
import numpy as np
from scipy.interpolate import griddata
import matplotlib.pyplot as plt
from numpy.random import uniform, seed
import pandas as pd
T_star = 470 #K 404.2
T_exit = 218.4014869888476
boundaries=np.linspace(T_exit, T_star , 11, endpoint=True)
mach = pd.read_csv("point_folder/tempcontour25.csv", de... |
<reponame>harshmathur1990/PoreAnalysis
import os
import sys
import datetime
import pywt
from datetime import timedelta
from ast import literal_eval as make_tuple
from pathlib import Path
from collections import defaultdict
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import segmentation_pyx as seg
... |
'''Module for additional computations required by the model'''
from numpy import (arange, array, atleast_2d, concatenate, copy, cumprod, diag,
int64, ix_, ones, prod, where, zeros)
from numpy import sum as nsum
from scipy.sparse import csc_matrix as sparse
from scipy.special import binom
def within_household_s... |
<reponame>kian1377/falco-python
# Copyright 2018-2020 by the California Institute of Technology. ALL RIGHTS
# RESERVED. United States Government Sponsorship acknowledged. Any
# commercial use must be negotiated with the Office of Technology Transfer
# at the California Institute of Technology.
# -----------------------... |
"""Some basic routines for working with microphones."""
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import linregress
from scipy.interpolate import CubicSpline
import sys
from calibrations import microphones as MICROPHONES
def plot_microphone_transfer_function(microphone_id):
try:
... |
<gh_stars>0
# -*- coding: utf-8 -*-
import glob
import base64
import scipy.misc
from StringIO import StringIO
import os
import numpy as np
import json
import copy
class DataProcessor:
def __init__(self, config):
self.config = config
self.num_channels = config.num_channels
self.row = config.... |
<filename>ros/src/tl_detector/light_classification/tl_classifier.py<gh_stars>0
#!/usr/bin/env python2
import os.path
import numpy as np
import scipy.misc
import tensorflow as tf
import cv2
import rospy
from styx_msgs.msg import TrafficLight
class TLClassifier(object):
# In Initialization, a boolean argument "is_s... |
<reponame>sohailsameer1994/EDS_COVID_-19-20-<filename>src/models/train_model.py<gh_stars>0
import pandas as pd
import numpy as np
from datetime import datetime
import pandas as pd
from scipy import optimize
from scipy import integrate
%matplotlib inline
import matplotlib as mpl
import matplotlib.pyplot as plt
impor... |
<filename>pyObjective/__init__.py<gh_stars>0
from scipy.optimize import dual_annealing
from prettytable import PrettyTable
class Variable:
def __init__(self, name, value, bounds, description=None):
""" Create a variable
Parameters
----------
name: str
name for the var... |
<filename>spirou/sandbox/ccf_tools/ccf2rv.py
import os
from shutil import copy
import sys
import warnings
import glob
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
from scipy.interpolate import InterpolatedUnivariateSpline as ius
from astropy.table import T... |
# -*- coding: utf-8 -*-
#
# Copyright © Simphony Project Contributors
# Licensed under the terms of the MIT License
# (see simphony/__init__.py for details)
"""
simphony.tools
==============
This package contains handy functions useful across simphony submodules
and to the average user.
"""
import re
from scipy.con... |
"""
Implementation of the base Fitter, Source, Model and Parameter classes
.. moduleauthor:: <NAME> <<EMAIL>>
"""
import numpy as np
import scipy.optimize as optimize
import lmfit as lm
import emcee
import copy
from .overwrite import SATLASSampler, SATLASHDFBackend, minimize, SATLASMinimizer
__all__ = ['Fitter', 'So... |
import argparse
import multiprocessing
import scipy.io as sio
import os
from Tree.WU_UCT import WU_UCT
from Tree.UCT import UCT
from Utils.NetworkDistillation.Distillation import train_distillation
def main():
parser = argparse.ArgumentParser(description = "P-MCTS")
parser.add_argument("--model", type = str... |
<reponame>vedantja/spark-sklearn<filename>python/spark_sklearn/test_utils.py<gh_stars>0
"""
Some test utilities to create the spark context.
"""
import sys
if sys.version_info[:2] <= (2, 6):
try:
import unittest2 as unittest
except ImportError:
sys.stderr.write('Please install unittest2 to test ... |
# Copyright 2019-, <NAME> and contributors
# Copyright 2016-2018, Rigetti Computing
#
# This source code is licensed under the Apache License, Version 2.0 found in
# the LICENSE.txt file in the root directory of this source tree.
"""
.. contents:: :local:
.. currentmodule:: quantumflow
QuantumFlow supports several ... |
<filename>mabs/bb/blackboard_optimization.py
import mabs.bb.blackboard as blackboard
import mabs.utils.utilities as utils
import mabs.utils.benchmark_utils as bu
import mabs.utils.performance_measure as pm
import matplotlib.pyplot as plt
import osbrain
from osbrain import proxy
from osbrain import run_agent
import tim... |
# coding: UTF-8
from __future__ import division
import numpy as np
import scipy as sp
from dml.ADAB import ADABC
from dml.ADAB.weakclassify import WEAKC
'''
Example 0:
this example is from the <统计学习方法>
'''
'''
X = np.array([0,1,2,3,4,5,6,7,8,9]).reshape(1,-1)
y = np.array([1,1,1,-1,-1,-1,1,1,1,-1]).transpose()
a= ... |
<filename>PRNet/helper/spatial_representation.py<gh_stars>0
import torch
import math
import scipy.spatial as sci_spatial
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
def get_2d_neighborhood_pairs_from_cache(cache_file_path):
'''
Gets all 2d point-pairs from the cache
'''
wit... |
from __future__ import print_function
import sys
#sys.path.insert(0, '../')#use this to have a reference to ripser_plusplus_python module (module is in parent directory)
# Importing from a previous directory if not installed
import ripserplusplus as rpp_py
import numpy as np
import scipy.sparse as sps
import os
mtx =... |
<gh_stars>0
#!/usr/bin/env python3
"""Evaluate APH for LCNN
Usage:
eval-APH.py <src> <dst>
eval-APH.py (-h | --help )
Examples:
python eval-APH.py logs/*
Arguments:
<src> Source directory that stores preprocessed npz
<dst> Temporary output directory
Options:
-h --... |
from scipy import interp
import numpy as np
from itertools import cycle
from sklearn.metrics import roc_curve, auc
from sklearn.metrics import precision_recall_curve
from sklearn.metrics import average_precision_score
from itertools import cycle
import matplotlib.pyplot as plt
def plot_roc_pr(
y_pred : np.ndar... |
import numpy as np
import warnings
from collections import defaultdict
from scipy.spatial.distance import cdist as sp_cdist
from typing import Callable
from .base_viewer import BaseViewer
from ..cooking_machine import BaseDataset
# If change, also modify docstring for view()
METRICS_NAMES = [
'jensenshannon', '... |
<gh_stars>1-10
#!/Library/Frameworks/Python.framework/Versions/2.6/bin/python
"""
Copyright (c) 2011, <NAME>
Permission is hereby granted, free of charge, to any person obtaining a
copy of this software and associated documentation files (the
"Software"), to deal in the Software without restriction, including
without... |
import numpy as np
from nse_opinf_poddmd.load_data import get_matrices, load_snapshots
from nse_opinf_poddmd.plotting_tools import plotting_SVD_decay, plotting_obv_vel, plotting_abs_error
from nse_opinf_poddmd.optinf_tools import deriv_approx_data, optinf_quad_svd, pod_model
import nse_opinf_poddmd.optinf_tools as oit
... |
import argparse
import sys
sys.path.insert(1, '../tsdate')
import tsdate
from tsdate.date import (SpansBySamples,
ConditionalCoalescentTimes, fill_prior, Likelihoods,
InOutAlgorithms, NodeGridValues, posterior_mean_var,
constrain_ages_topo,
... |
# MIT License
#
# Copyright (c) 2019 <NAME>
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge,... |
<filename>src/pyisotopomer/automate_gk_solver.py
"""
File: automate_gk_solver.py
---------------------------
Created on Weds April 14th, 2021
Functions to solve for IRMS scrambling coefficients to be used in
isotopomer calculations.
@author: <NAME> (<EMAIL>).
"""
import pandas as pd
import numpy as np
from scipy.op... |
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