text string |
|---|
<gh_stars>0
#!/usr/bin/env python3
'''apogeeTharTest.py test #2 line fitting, plot optional (EM)
EM, 09/23/2013 - program for the testing of fitting compare reference.
The reference are "/data/apogee/quickred/56531/ap1D-a-09690003.fits.fz" (A)
"ap1D-a-09690005.fits... |
from email.utils import localtime
from scipy import interpolate
import time
from stepper import Stepper
az_motor = Stepper()
el_motor = Stepper()
def interpolate_pos_data(orig_arr):
return interpolate.interp1d(orig_arr)
def main(): #put in tracking data download logic when topocentric data is bug fixed.
positi... |
<reponame>Tarheel-Formal-Methods/kaa-optimize
import numpy as np
from scipy.spatial import ConvexHull
from settings import KaaSettings
"""
Wrapper around list for representing arbitrary trajectories of a system.
"""
class Traj:
def __init__(self, model, initial_point, steps=0, label=None, traj_mat=None):
... |
<filename>expo.py
#!/usr/bin/python3
import h5py
import click
from matplotlib import pyplot as plt
from cycler import cycler
import re
import statistics
import math
import numpy as np
from itertools import islice
import scipy.stats as stats
TEXT_ENCODING = 'utf-8'
def get_gene(id, radix):
gene = []
for x ... |
import numpy as np
from numpy.linalg import det
from scipy.optimize import fsolve
from scipy.stats import norm
import itertools
from .constants import *
def check_condition(state, condition):
# Define a success condition for each state, e.g., mutual exclusivity.
if condition==EXCLUSIVITY:
if sum(stat... |
"""Use the pyDOE2 library to generate latin hypercube samples."""
import numpy as np
import warnings
try:
from pyDOE2 import lhs as lhs_pydoe
HAS_PYDOE2 = True
except ImportError:
HAS_PYDOE2 = False
try:
from scipy.stats.qmc import LatinHypercube as lhs_scipy
HAS_SCIPY_QMC = True
except ImportEr... |
<reponame>prakass1/Rank_Based_Detection_Algorithm
##########################################################################################
#
# Synthetic simulation, to test the constructed algorithm approach against various scenarios
# Uncomment to work with synthethic data analysis using - https://pyod.readthedocs.i... |
import numpy as np
import torch
from scipy import linalg
from torch.nn.functional import adaptive_avg_pool2d
from tqdm import tqdm
from utils.fid.inception import InceptionV3
class FID:
def __init__(self, dims=2048):
'''
64: first max pooling features
192: second max pooling features
... |
<reponame>super-resolution/Locan
"""
Regions as support for localization data.
This module provides classes to define geometric regions for localization data.
All region classes inherit from the abstract base class `Region`.
"""
# todo: fix docstrings
import itertools as it
from abc import ABC, abstractmethod
impo... |
import numpy as np
from MachineLearning.Distances import DistancesMatrix
import scipy as sp
#Need to add the possibility to mix kenerls together like K1+K2, K1*K2 etc
def KernelCalc(X,Xt,Nl,Nt,var=None,typeK='Poly',typeD=None,T=False,xinterval=None):
##################################################################... |
import numpy as np
import pandas as pd
from sklearn.datasets import load_digits
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
from sklearn.svm import SVC
from sklearn.cluster import KMeans
from sklearn.metrics import accuracy_score, confusion_matrix
from sklear... |
import math
import h5py
import nibabel as nib
import numpy as np
import SimpleITK as sitk
import torch
import torch.nn.functional as F
from medpy import metric
from tqdm import tqdm
from scipy.ndimage import interpolation
def test_single_case(net, image, stride, patch_size, num_classes=1):
w, h, d = image.shape
... |
import itertools
import logging
import statistics
import struct
from math import isclose
from typing import NamedTuple, Optional, List, Tuple
from numpy.random import default_rng
from .name_gen import NameGenerator
from .genome import Genome, GenomeMaker, make_identity_genome
class BranchLenStats(NamedTuple):
ave... |
<reponame>danielabler/glimslib
"""Provides helper functions for visualisation module.
"""
import os
import time
import matplotlib.pylab as plt
import numpy as np
from matplotlib import pyplot as plt, colors as colors
from mpl_toolkits.axes_grid1 import make_axes_locatable
from scipy.interpolate import griddata
from u... |
<filename>pynrm/nirc2.py
"""NIRC2 specific methods and variables for an AOInstrument.
"""
from __future__ import division, print_function
import astropy.io.fits as pyfits
import numpy as np
import scipy.ndimage as nd
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import time
import glob
import pdb
import ti... |
<gh_stars>0
from ast import Mod
import numpy as np
import scipy
from multiprocessing import Pool
from enum import Enum
class Direction(Enum):
N = 0
NE = 1
E = 2
SE = 3
S = 4
SW = 5
W = 6
NW = 7
transform = {
'N': (-1,0),
'NE': (-1,1),
'E': (0,1),
'SE': (1,1),
'S': ... |
<gh_stars>0
# -*- coding: utf-8 -*-
'''
Semiparametric Support Vector Machine model under POM3.
'''
__author__ = "<NAME>"
__date__ = "January 2021"
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import accuracy_score
from MMLL.models.POM3.CommonML.POM3_CommonML import ... |
<reponame>mathkann/understanding-random-forests<filename>scripts/ch4_bias_variance.py<gh_stars>100-1000
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import norm
blue = (0, 0, 1.0)
red = (1.0, 0, 0)
gray = (0.7, 0.7, 0.7)
x = np.arange(-10, 10, 0.0001)
p_y = norm.pdf(x, -3.0, 1)
p_y_hat = norm.p... |
import datetime, inspect, random, msgpack, os, sys, math, time, torch, pdb
import numpy as np
from pprint import pprint
from scipy.sparse.csgraph import floyd_warshall
currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
parentdir = os.path.dirname(currentdir)
sys.path.insert(0, pa... |
# coding: utf-8
# ## Heatmap with change-cell-size feature
#
# ### Motivation
# Heatmap is a great chart to catch information in matrix.
# However, I sometimes want to add more information in cases like this:
# * matrix is like [product A-F] x [area a-f]
# * want to see [profitability] and [sales volume] of each ... |
from logs import logDecorator as lD
import jsonref
import pprint
import statistics as stats
from psycopg2.sql import SQL, Identifier, Literal
from lib.databaseIO import pgIO
from collections import Counter
from tqdm import tqdm
from multiprocessing import Pool
from time import sleep
config = jsonref.load(open('../con... |
<filename>pk_predictors.py
import subprocess as sp
from arnie.utils import *
import glob
from os import getcwd, chdir, remove, mkdir, rmdir, path
from scipy.optimize import linear_sum_assignment
# TODO script all previous investigations
# TODO Debug modes to print output and err to help with install issues
# TODO pk_... |
# Author: <NAME> <<EMAIL>>
# Copyright (c) 2020 <NAME>
#
# This file is part of Monet.
import logging
from typing import Iterable
from math import floor, ceil
import pandas as pd
import numpy as np
from scipy.stats import binom, mannwhitneyu
import plotly.graph_objs as go
from ..core import ExpMatrix
from .. import ... |
<reponame>KongHag/emotion_project<filename>metrics.py
# -*- coding: utf-8 -*-
"""
Created on Sun Mar 29 15:32:25 2020
@author: lucas
"""
import torch
from scipy.stats import pearsonr
def get_metrics(model, testloader):
device = torch.device(
'cuda:0') if torch.cuda.is_available() else torch.device('c... |
<gh_stars>0
from sympy import *
import re
x = Symbol('x')
y = Symbol('y')
z = Symbol('z')
# if (tipo==1){ alert("numerador");}
# if (tipo==2){ alert("numerador raiz");}
# if (tipo==3){ alert("numerador e denominador");}
# if (tipo==4){ alert("numerador raiz e denominador");}
# if (tipo==5){ alert("numerador raiz e de... |
<filename>peakhood/hoodlib.py<gh_stars>1-10
#!/usr/bin/env python3
from distutils.spawn import find_executable
import matplotlib.pyplot as plt
# import plotly.express as px
import seaborn as sns
import pandas as pd
import numpy as np
import subprocess
import statistics
import random
import math
import gzip
import uuid... |
<reponame>aalto-ui/chi21adaptive
import csv
#For fasttext word embedding
# import fasttext
# import fasttext.util
#For word2vec embeddings
# from gensim.models import KeyedVectors
#To compute cosine similarity
from scipy import spatial
import math
# reads a log file and returns a frequency distribution as a dict
def l... |
import tkinter as tk
import tkinter.ttk as ttk
from tkinter import filedialog
from tkinter import font
import sys
import os
import numpy as np
import librosa
from sklearn.model_selection import train_test_split
import math
import scipy
import requests
import tarfile
import time
import matplotlib
from pylab import Max... |
from __future__ import print_function
from builtins import zip
from builtins import range
from builtins import object
from cosmosis.gaussian_likelihood import GaussianLikelihood
from cosmosis.datablock import names
from twopoint_cosmosis import theory_names, type_table
from astropy.io import fits
from scipy.interpolate... |
# -*- coding: utf-8 -*-
#
# Copyright © Spyder Project Contributors
# Licensed under the terms of the MIT License
# (see spyder/__init__.py for details)
"""
Scientific Python startup script
Requires NumPy, SciPy and Matplotlib
"""
# Need a temporary print function that is Python version agnostic.
import sys
import o... |
#!C:\\Python38\\python.exe
DIR = "C:\\wamp64\\www\\ProjetS4\\"
from sklearn.metrics.pairwise import cosine_similarity
from IPython.display import display
import matplotlib.pyplot as plt
import pandas as pd
import statistics
import operator
import subprocess
import php
import popen2
import simplejson as json
import li... |
import os
import sys
import glob
import numpy as np
import matplotlib.pyplot as plt
import scipy.stats as sps
from dlt import DLT
from collections import defaultdict
from calibration_point_selection import label_to_3Dcoord
from config import *
PATH = 'data_082421'
IMAGE_PATH = os.path.join(PATH, 'calibration')
CAL... |
<filename>Utils/io.py
import numpy as np
import pandas as pd
import torch
import torch.nn.functional as F
from scipy.sparse import coo_matrix
except_chr = {'hsa': {'X': 23, 23: 'X'}, 'mouse': {'X': 20, 20: 'X'}}
def readcoo2mat(cooFile, normFile, resolution):
"""
Function used for reading a coordinated tag f... |
<filename>src/dimsm/measurement.py<gh_stars>0
"""
Measurement
===========
Contains table of measurements and the (co)variance matrix.
"""
from typing import List, Union
from operator import attrgetter
from itertools import product
import numpy as np
import pandas as pd
from scipy.sparse import csr_matrix, diags
from ... |
<gh_stars>1-10
# -*- coding: utf-8 -*-
#------------------------------------------------------------------------------
# FEDERAL UNIVERSITY OF UBERLANDIA
# Faculty of Electrical Engineering
# Biomedical Engineering Lab
#------------------------------------------------------------------------------
# Author: <NAME>, MSc... |
# -*- coding: utf-8 -*-
"""
Created on Wed Feb 17 18:09:11 2021
@author: peter
"""
import numpy as np
from scipy.special import gammaln
from scipy.stats import t
import pandas as pd
def loglikelihood_normal(resid, sigma2):
"""
Negative Log-Likelihood function whereas the underlying distribution is Normal.
... |
from __future__ import absolute_import, division, print_function
# TensorFlow and tf.keras
import tensorflow as tf
import keras
from keras.utils import CustomObjectScope
from keras.initializers import glorot_uniform
from keras.preprocessing import image
from keras.models import Sequential, load_model, model_from_json
... |
<gh_stars>0
"""
dab-seq: single-cell dna genotyping and antibody sequencing
<NAME> 7.9.2019
functions required for the processing pipeline
two classes are defined:
* TapestriTube: variables and methods that operate on the level of a single Tapestri tube library
* SingleCell: variables and methods that operate on the... |
<reponame>EMSTrack/Algorithms
from typing import List
from geopy import Point
from scipy.spatial import KDTree
from ems.datasets.location.location_set import LocationSet
class KDTreeLocationSet(LocationSet):
def __init__(self,
latitudes: List[float],
longitudes: List[float]):
... |
import logging
import math
import numpy as np
from mdsea.constants import DTYPE
from scipy import special
from scipy.interpolate import interp1d
log = logging.getLogger(__name__)
MONTECARLO_SPEEDRANGE = np.arange(0, 50, 0.001)
# ======================================================================
# --- Speed Di... |
<reponame>open-pulse/OpenPulse
import numpy as np
from scipy.sparse import save_npz, load_npz
# import pytest
from pulse.utils import sparse_is_equal
from pulse.preprocessing.cross_section import CrossSection
from pulse.preprocessing.material import Material
from pulse.preprocessing.preprocessor import Preprocessor
... |
<filename>sys_simulator/channels/__init__.py
import numpy as np
import scipy
from scipy.stats import nakagami, rayleigh
from scipy import constants
class Channel:
def __init__(self, *kwargs):
pass
def large_scale(self, *kwargs):
pass
def pathloss(self, *kwargs):
pass
def sma... |
<filename>utils.py
import numpy as np
import torch
import matlab
import csv
import os
import shutil
import torch.nn as nn
from torch.autograd import Variable
import matplotlib.pyplot as plt
import matlab.engine
from numpy import random
import json
from skimage import img_as_float
from skimage.metrics import structural_... |
<filename>scripts/bayesian_LC.py
#!/usr/bin/env python
"""
The main module of kNe-inference that sets up the Bayesian formalism.
Classes:
Kilonova_Inference
Sampler
"""
__author__ = '<NAME>'
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import norm, truncnorm
from scipy.integrate impor... |
import numpy as np
from scipy.sparse import csr_matrix
from scipy.sparse.csgraph import minimum_spanning_tree
def main() -> None:
N, M = map(int, input().split())
large, small = [], []
for i in range(N):
x, y, c = map(int, input().split())
large.append((x, y, c))
for i in range(M):
... |
<reponame>Taiji-pipeline/Taiji-utils
import gzip
import scipy as sp
import numpy as np
from sklearn.linear_model import LinearRegression
class InputData:
def __init__(self, filename):
self.filename = filename
with gzip.open(self.filename, mode='rt') as f:
header = f.readline().strip()
... |
<reponame>akarshkumar0101/timm-mlp-shaker
import scipy
import scipy.stats
import numpy as np
import torch
import torchvision
from torch import nn
from torch.utils.data import Dataset
from torch.utils.data import DataLoader
from torchvision import transforms
import matplotlib.pyplot as plt
from tqdm.notebook import tqdm... |
<reponame>pzh1989/trikit<filename>trikit/__init__.py
"""
_
| |_ _ __(_)/| _(_) |
| __| '__| | |/ / | __|
| |_| | | | <| | |_
\__|_| |_|_|\_\_|\__|
A Pythonic Approach to Actuarial Reserving
Copyright 2018 <NAME>
"""
import collections
import datetime
from functools import partial
import os
import os.path
im... |
<reponame>LuizFritsch/analise_projeto_algoritmo<gh_stars>0
#!/usr/bin/python3
# -*- coding: utf-8 -*-
DEFAULT_OUT = "out_alg_naive_tsp.txt"
DEFAULT_SEED = None
DEFAULT_N_START = 1
DEFAULT_N_STOP = 10
DEFAULT_N_STEP = 1
DEFAULT_TRIALS = 3
from subprocess import Popen, PIPE
from time import sleep, time
from multiproce... |
<filename>src/features/preprocess.py
# region imports
import math
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from scipy.stats import norm
from sklearn.model_selection import train_test_split
from sklearn.metrics import mean_squared_log_error
from sklearn import preproce... |
<reponame>wathen/PhD
from dolfin import assemble, MixedFunctionSpace, tic,toc
import petsc4py
import sys
petsc4py.init(sys.argv)
from petsc4py import PETSc
import CheckPetsc4py as CP
import StokesPrecond
import NSprecond
import MaxwellPrecond as MP
import PETScIO as IO
import numpy as np
import P as PrecondMulti
impo... |
import numpy as np
import scipy.io as scio
'''
Efficient and flexible MATLAB implementation of 2D and 3D elastoplastic problems
https://github.com/matlabfem/matlab_fem_elastoplasticity
D:\FluidSim\FluidSim\FEMNEW\matlab_fem_elastoplasticity-master
'''
young = 206900
poisson = 0.29
shear = young / (2*(1 + poisson))
... |
<filename>polyML/TON_tools3.py
# -*- coding: utf-8 -*-
"""
This function takes a data file and removes correlations
Created on Fri Oct 14 18:53:40 2016
@author: pipolose
"""
import numpy as np
import scipy.io
import pandas as pd
from sklearn.base import BaseEstimator, TransformerMixin
import warnings
import logging
im... |
"""
Calibration
===========
This module contains routines for the blind calibration of a microphone
array with sources in the far field. The methods are:
* `joint_calibration_gd`: Straightforward gradient descent method
* `joint_calibration_sgd`: Straightforward stochastic gradient descent method
* `struc... |
# Copyright (c) 2020, 2021, NECSTLab, Politecnico di Milano. All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
# * Redistributions of source code must retain the above copyright
# notice, this li... |
<filename>arve/from_arve/Experiment.py<gh_stars>0
"""
Copyright 2016 <NAME>
This file is part of the COMTESSA project software.
This is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the L... |
"""
Runs a model on a single node across multiple gpus.
"""
import os
from pathlib import Path
import torch
import numpy as np
import torch.nn.functional as F
import scipy.io as sio
import matplotlib.pyplot as plt
import configargparse
from src.DeepRegression import Model
TOL = 1e-14
def main(hparams):
if hp... |
# code for fitting spectra, using the models in spectral_model.py
from __future__ import absolute_import, division, print_function # python2 compatibility
import math
import numpy as np
from scipy.optimize import curve_fit
from bisect import bisect
from numpy.polynomial.chebyshev import chebval
from scipy.ndimage impor... |
<filename>tests/test_statistics.py<gh_stars>0
import sys
import unittest
import random
import statistics
from mpyc.runtime import mpc
from mpyc.statistics import (mean, variance, stdev, pvariance, pstdev,
mode, median, median_low, median_high, quantiles,
covaria... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Oct 26 12:25:54 2018
@author: luoyuhao
"""
import base64
import cv2
import numpy as np
import imageio
from scipy import misc
import json
import time
import os
import sklearn
from vector_normalization import Vector
def base64_to_image(base64_code):
#... |
"""
Script used to test the adaptive interpolation and
the evaluation of said interpolant
"""
from __future__ import absolute_import
import ctypes
import ctypes.util
import os
import time
import numpy as np
import numpy.linalg as la
import scipy.special as spec
import matplotlib as mpl
from tempfile import TemporaryD... |
#!/usr/bin/env python
# The MIT License (MIT)
#
# Copyright (c) 2016 <NAME>, National Institutes of Health / NINDS
#
# 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, incl... |
<reponame>PoliHydra/hydra<filename>utils/npz2mat.py
from __future__ import print_function
import os
import argparse
from numpy import load
from scipy.io import savemat
def main():
parser = argparse.ArgumentParser(
description='convert numpy .npz to matlab .mat format')
parser.add_argument('npz', nargs... |
<filename>src/chapter_02/code/ch2_fig4.py
#%%
import os
import glob
import pickle
import re
import numpy as np
import pandas as pd
import sys
import phd.viz
import phd.stats
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib.gridspec as gridspec
import matplotlib.colors as plc
import altair as... |
<reponame>david-zwicker/cv-mouse-burrows
'''
Created on Oct 2, 2014
@author: <NAME> <<EMAIL>>
Module that contains the class responsible for the fourth pass of the algorithm
'''
from __future__ import division
import copy
import functools
import time
import cv2
import numpy as np
from scipy import cluster
from sha... |
<gh_stars>1-10
#!/usr/bin/python
'''
@author: <NAME>
@email: <EMAIL>
@title: FaekCast
@description: Cast audio out of linux box (including seperate applications) from Chromium browser extension using MPEG HTTP Stream
'''
import numpy
import jack
import time
import sys
import io
import struct
import warnings
im... |
"""SentimentInvestor Model"""
__docformat__ = "numpy"
import dataclasses
import datetime
import logging
import multiprocessing
import os
import statistics
import time
from typing import Any, List, Optional, Tuple, Union
import pandas as pd
from colorama import Fore, Style
from sentipy.sentipy import Sentipy
from gam... |
<filename>python/ex8_anomaly_recommender/ex8.py
# Machine Learning Online Class
# Exercise 8 | Anomaly Detection and Collaborative Filtering
#
# Instructions
# ------------
#
# This file contains code that helps you get started on the
# exercise. You will need to complete the following functions:
#
# estimateG... |
import requests
from typing import Dict, List, Optional
from datetime import date, timedelta
from scipy import stats # type: ignore
from .parser import Parser
HEADERS = {
'User-Agent': "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 "
"(KHTML, like Gecko) Chrome/79.0.3945.94 Safari/537.36"
... |
"""
Tests for functions used in Randomized Parcellation Based Inference.
"""
# Author: <NAME>, <<EMAIL>>, Feb. 2014
import numpy as np
from numpy.testing import (assert_equal, assert_array_equal,
assert_array_almost_equal, assert_raises)
from sklearn.utils import check_random_state
from nile... |
<reponame>IceCubeOpenSource/ic3-labels<gh_stars>1-10
"""nuVeto Atmospheric Self-Veto Models
This file implements a wrapper class around nuVeto
(https://github.com/tianluyuan/nuVeto) which builds splines in energy and
zenith.
These can then be used to calculate the self-veto effect for atmospheric
neutrinos. See also t... |
<gh_stars>1-10
#!/usr/bin/env python2
#
# wsi_bot_apply2
#
# Version 2 of Bag-Of_things:
#
# -uses OpenCV for faster operation - but different local descriptors than in the 1st version;
# -uses annotation files for defining the regions from where the descriptors are to be
# extracted
from __future__ import (absolute... |
<filename>angelinoNozzle_py/test_plug_code.py
from plug_nozzle_angelino import plug_nozzle
import matplotlib.pyplot as plt
import numpy as np
import aerospike_optimizer as ao
import gasdynamics as gd
from scipy import interpolate
r_e = 0.027
T_w = 600
alpha = 1
beta = 1
truncate_ratio_init = 0.2
design_alt_init = 9... |
import numpy as np
import numpy.typing as npt
import osqp
from scipy.sparse import csc_matrix
from optimization.__split_optimization_pu_classifier import SplitOptimizationPUClassifier
from optimization.functions import mm_q, add_bias, joint_risk
class MMClassifier(SplitOptimizationPUClassifier):
osqp_max_iter: i... |
<filename>pykomposter/behaviours.py
from asyncio import events
import fractions
import sys
import time
import matplotlib.pyplot as plt
import music21
import numpy as np
import pandas as pd
import tqdm
############################
# FOR FINITE STATE MACHINE #
############################
from transitions import Machin... |
<reponame>gqfiddler/Stylometer<gh_stars>1-10
'''
contains example calls for adding authors or generating new data tables
with authors / texts of your choice
'''
from scipy.spatial.distance import minkowski
import modules.dataGenerator as dataGenerator
import modules.metrics as metrics
import os
THIS_FOLDER = os.path.d... |
"""
Copyright © 2020. All rights reserved.
Author: <NAME> <<EMAIL>>
Licensed under the Apache License, Version 2.0
http://www.apache.org/licenses/LICENSE-2.0
"""
import numpy as np
import random
import copy
import math
import scipy.optimize as opt
from .func import *
class FormulaVertex:
"""
Класс вершины де... |
"""A wrapper for the LibFM recommender. See www.libfm.org for implementation details."""
import numpy as np
import scipy.sparse
import wpyfm
from . import recommender
class LibFM(recommender.PredictRecommender):
"""The libFM recommendation model which is a factorization machine.
Parameters
----------
... |
<filename>Lowess.py
# -*- coding: utf-8 -*-
"""
Created on Wed Mar 16 14:54:33 2022
@author: marco
"""
import os
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from datetime import date
import warnings # `do not disturbe` mode
import seaborn as sns... |
# <NAME> (<EMAIL>)
# Harvard-MIT Department of Health Sciences & Technology
# Athinoula A. Martinos Center for Biomedical Imaging
import numpy as np
from skimage import measure
import matplotlib.pylab as plt
from scipy.ndimage.morphology import binary_fill_holes
def Contours(mask, tissue_labels=[1,2,3]):
contou... |
# -*- coding: utf-8 -*-
# SPDX-License-Identifier: BSD-3-Clause
# SPDX-FileCopyrightText: © 2010 by California Institute of Technology.
#
# statefbk.py - tools for state feedback control
#
# Author: <NAME>, <NAME>
# Date: 31 May 2010
#
# This file contains routines for designing state space controllers
#
# Copyright (c... |
<gh_stars>1-10
import rebalancer
from sp500_data_loader import load_data
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from scipy.stats import binom
def plot_data(data1, data2, label1='asset1', label2='asset2'):
f, (p1, p2) = plt.subplots(2, 2)
p1[0].plot(data1, label=label1)
p1[0... |
<<<<<<< HEAD
import logging
import numpy as np
import pandas as pd
import torch
import torch.nn as nn
from scipy.stats import multivariate_normal
from torch.utils.data import DataLoader
from torch.utils.data.sampler import SubsetRandomSampler
from tqdm import trange
from .algorithm_utils import Algorithm, ... |
'''
## Test ##
# Test a trained DQN. This can be run alongside training by running 'run_every_new_ckpt.sh'.
@author: <NAME> (<EMAIL>)
'''
from datetime import datetime
import os
import sys
import argparse
import gym
import tensorflow as tf
import numpy as np
import scipy.stats as ss
import random
impor... |
import numpy as np
import pytest
from scipy.sparse import issparse
from scipy.sparse import coo_matrix
from scipy.sparse import csc_matrix
from scipy.sparse import csr_matrix
from scipy.sparse import dok_matrix
from scipy.sparse import lil_matrix
from sklearn.utils.multiclass import type_of_target
from sklearn.util... |
<reponame>AlbertMillan/THU--ACM_2019-2021<filename>THU--DDBS/HW1/bea.py
import numpy as np
import pylab
import scipy.cluster.hierarchy as sch
#Create matrices
n = 7
# AA = np.zeros([n,n])
# AA = np.array([[42,0,37,5],[0,82,7,75],[37,7,44,0],[5,75,0,8]])
AA = np.array([ [30,30,30,30,30,30,30],
... |
<gh_stars>10-100
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from PIL import Image
from typing import Any, Callable, Optional, Tuple
import numpy as np
import os
impor... |
<reponame>Lila14/multimds
import numpy as np
import data_tools as dt
import sys
import os
import linear_algebra as la
import array_tools as at
from scipy import signal as sg
from hmmlearn import hmm
import argparse
def call_peaks(data):
"""Calls peaks using Gaussian hidden markov model"""
reshaped_data = data.reshap... |
<reponame>marcovaas/uclametrics<gh_stars>0
# -*- coding: utf-8 -*-
"""
Created on Tue Apr 12 17:39:48 2022
@author: marco
"""
import pandas as pd
import numpy as np
import os
from scipy.linalg import pinv as pinv
from scipy.linalg import inv as inv
from sklearn.preprocessing import PolynomialFeatures
os.... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import print_function, unicode_literals, division, absolute_import
from builtins import (bytes, dict, int, list, object, range, str, # noqa
ascii, chr, hex, input, next, oct, open, pow, round, super, filter, map, zip)
from future import standard_library... |
<filename>redshift_paper/code/high_spin_halos.py
#!/usr/bin/env python
################################################################################
import sys
sys.path.append("../code")
from read_data import read_data
import matplotlib.cm as cm
import matplotlib.pyplot as plt
import numpy as np
from scipy import... |
<reponame>austinbrown34/shap<gh_stars>0
import numpy as np
import scipy as sp
import warnings
from .explainer import Explainer
class LinearExplainer(Explainer):
""" Computes SHAP values for a linear model, optionally accounting for inter-feature correlations.
This computes the SHAP values for a linear model a... |
<reponame>asceenl/lasp
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""!
Author: <NAME> - ASCEE
Description: FIR filter design for octave bands from 16Hz to 16 kHz for a
sampling frequency of 48 kHz, filter design for one-third octave bands.
Resulting filters are supposed to be standard compliant.
See test/octave_f... |
<filename>mcmc/util_cupy.py
# -*- coding: utf-8 -*-
"""
Created on Thu Dec 13 14:17:09 2018
@author: puat133
"""
# import math
import h5py
import scipy.io as sio
import numpy as np
import scipy.linalg as sla
import numba as nb
import cupy as cp
import time
import gc
import mcmc.image_cupy as im
import h5py
from skimag... |
# -*- coding: utf-8 -*-
# Authors: <NAME> <<EMAIL>>
# <NAME> <<EMAIL>>
# <NAME> <<EMAIL>>
# <NAME> <<EMAIL>>
# <NAME> <<EMAIL>>
# <NAME> <<EMAIL>>
#
# License: BSD 3 clause
"""
The :mod:`sklearn.feature_extraction.text` submodule gathers utilities to
build feature vectors fr... |
from os import listdir, path
import numpy as np
import scipy, cv2, os, sys, argparse, audio
import json, subprocess, random, string
from tqdm import tqdm
from glob import glob
import torch, face_detection
from models import Wav2Lip
parser = argparse.ArgumentParser(description='Inference code to lip-sync videos in the ... |
#!/usr/bin/env python3
# -*- coding: UTF-8 -*-
from __future__ import division, print_function
"""diffacto.diffacto: provides entry point main()."""
__version__ = "1.0.5"
import csv
import re
import warnings
from collections import defaultdict
from multiprocessing import Pool
from scipy import optimize, stats
impor... |
#!/usr/bin/python
# -*- coding: utf-8 -*-
## Add path to library (just for examples; you do not need this)
import sys, os
sys.path.append(os.path.join(os.path.dirname(__file__), '..', '..'))
from scipy import random
from PyQt4 import QtGui, QtCore
from pyqtgraph.PlotWidget import *
from pyqtgraph.graphicsItems import ... |
<reponame>CAVED123/reinvent-randomized
import random
import math
import numpy as np
import scipy.stats as sps
import torch
import torch.utils.data as tud
import torch.nn.utils as tnnu
import models.dataset as md
import models.vocabulary as mv
import utils.chem as uc
import utils.tensorboard as utb
class Action:
... |
from anndata import AnnData
from collections import Counter
import datetime
from dateutil.parser import parse as dparse
import errno
import math
import matplotlib.pyplot as plt
import numpy as np
import os
import pandas as pd
import random
import scanpy as sc
from scipy.sparse import csr_matrix, dok_matrix
import scipy... |
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