repo_name stringlengths 7 90 | path stringlengths 5 191 | copies stringlengths 1 3 | size stringlengths 4 6 | content stringlengths 976 581k | license stringclasses 15
values |
|---|---|---|---|---|---|
aquadrop/solr_py | client/sc_belief_clf_fasttext.py | 1 | 9680 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import print_function
import traceback
import requests
import json
import os
import sys
import argparse
import time
from sklearn.pipeline import Pipeline
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.svm import LinearSVC
from skl... | gpl-3.0 |
mne-tools/mne-tools.github.io | 0.12/_downloads/plot_cluster_1samp_test_time_frequency.py | 16 | 4759 | """
.. _tut_stats_cluster_sensor_1samp_tfr:
===============================================================
Non-parametric 1 sample cluster statistic on single trial power
===============================================================
This script shows how to estimate significant clusters
in time-frequency power est... | bsd-3-clause |
probml/pyprobml | scripts/gibbs_potts_demo_jax.py | 1 | 3170 | # -*- coding: utf-8 -*-
"""
Author: Ang Ming Liang
For further explanations refer to the following gist https://gist.github.com/Neoanarika/a339224d24affd7840a30a1064fc16ff
"""
import jax
import jax.numpy as jnp
from jax import lax
from jax import vmap
from jax import random
from jax import jit
import matplotlib.pyplo... | mit |
vybstat/scikit-learn | sklearn/manifold/tests/test_spectral_embedding.py | 216 | 8091 | from nose.tools import assert_true
from nose.tools import assert_equal
from scipy.sparse import csr_matrix
from scipy.sparse import csc_matrix
import numpy as np
from numpy.testing import assert_array_almost_equal, assert_array_equal
from nose.tools import assert_raises
from nose.plugins.skip import SkipTest
from sk... | bsd-3-clause |
landmanbester/Copernicus | SimLTB.py | 1 | 6581 | # -*- coding: utf-8 -*-
"""
Created on Thu Aug 21 09:33:52 2014
@author: landman
This program simulates data for an LTB model
"""
import numpy as np
from scipy.integrate import quad
from scipy.interpolate import UnivariateSpline as uvs
import matplotlib.pyplot as plt
import matplotlib as mpl
from Copernicus.fortran_... | gpl-3.0 |
xavialex/Deep-Learning-Templates | Volume 1 - Supervised Deep Learning/Part 1 - Artificial Neural Networks (ANN)/Section 4 - Building an ANN/ann_homework_solution.py | 6 | 2749 | # Artificial Neural Network
# Installing Theano
# pip install --upgrade --no-deps git+git://github.com/Theano/Theano.git
# Installing Tensorflow
# pip install tensorflow
# Installing Keras
# pip install --upgrade keras
# Part 1 - Data Preprocessing
# Importing the libraries
import numpy as np
import matplotlib.pyp... | mit |
h2oai/h2o-3 | h2o-py/h2o/estimators/svd.py | 2 | 17854 | #!/usr/bin/env python
# -*- encoding: utf-8 -*-
#
# This file is auto-generated by h2o-3/h2o-bindings/bin/gen_python.py
# Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
#
from __future__ import absolute_import, division, print_function, unicode_literals
from h2o.estimators.estimator_base ... | apache-2.0 |
nearai/program_synthesis | program_synthesis/karel/scripts/eval_io_trace_code.py | 1 | 6445 | import sys
import os
import collections
import glob
import json
import re
import math
import random
import copy
import numpy as np
import pandas as pd
from program_synthesis.common.tools import saver
from program_synthesis.karel import arguments
from program_synthesis.karel import dataset
from program_synthesis.kare... | apache-2.0 |
jmeline/wifi_signal_analysis | src/sampleAnalyizer.py | 1 | 3984 | # sampleAnalyzer.py
import pandas as pd
import numpy as np
import pprint
class Vividict(dict):
def __missing__(self, key):
value = self[key] = type(self)()
return value
class SampleAnalyizer():
def __init__(self):
self.tests = Vividict()
def printVariables(self):
print ("c... | mit |
ishay2b/tensorflow | tensorflow/python/estimator/canned/dnn_test.py | 20 | 16058 | # Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | apache-2.0 |
wathen/PhD | MHD/FEniCS/Orignal/test.py | 1 | 7894 | #!/usr/bin/python
import petsc4py
import slepc4py
import sys
petsc4py.init(sys.argv)
slepc4py.init(sys.argv)
from petsc4py import PETSc
from slepc4py import SLEPc
Print = PETSc.Sys.Print
# from MatrixOperations import *
from dolfin import *
import numpy as np
import matplotlib.pylab as plt
import scipy.sparse as sps
... | mit |
JonatanAntoni/CMSIS_5 | CMSIS/DSP/Testing/summaryBench.py | 2 | 4189 | # Process the test results
# Test status (like passed, or failed with error code)
import argparse
import re
import TestScripts.NewParser as parse
import TestScripts.CodeGen
from collections import deque
import os.path
import numpy as np
import pandas as pd
import statsmodels.api as sm
import statsmodels.formula.api a... | apache-2.0 |
andyraib/data-storage | python_scripts/env/lib/python3.6/site-packages/pandas/util/clipboard/__init__.py | 7 | 3420 | """
Pyperclip
A cross-platform clipboard module for Python. (only handles plain text for now)
By Al Sweigart al@inventwithpython.com
BSD License
Usage:
import pyperclip
pyperclip.copy('The text to be copied to the clipboard.')
spam = pyperclip.paste()
if not pyperclip.copy:
print("Copy functionality unav... | apache-2.0 |
blaze/dask | dask/dataframe/categorical.py | 1 | 9117 | from collections import defaultdict
import pandas as pd
from tlz import partition_all
from numbers import Integral
from ..base import tokenize, compute_as_if_collection
from .accessor import Accessor
from .utils import (
has_known_categories,
clear_known_categories,
is_scalar,
is_categorical_dtype,
)
f... | bsd-3-clause |
tosolveit/scikit-learn | examples/linear_model/plot_ransac.py | 250 | 1673 | """
===========================================
Robust linear model estimation using RANSAC
===========================================
In this example we see how to robustly fit a linear model to faulty data using
the RANSAC algorithm.
"""
import numpy as np
from matplotlib import pyplot as plt
from sklearn import ... | bsd-3-clause |
mfiers/hagfish | hagfishUtils.py | 1 | 16813 | import os
import sys
import math
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.path as mpath
import matplotlib.colors as mcol
import matplotlib.patches as mpatches
import matplotlib as mpl
import logging
import optparse
from hagfish_file_util import *
##########################################... | gpl-3.0 |
etkirsch/scikit-learn | sklearn/utils/graph.py | 289 | 6239 | """
Graph utilities and algorithms
Graphs are represented with their adjacency matrices, preferably using
sparse matrices.
"""
# Authors: Aric Hagberg <hagberg@lanl.gov>
# Gael Varoquaux <gael.varoquaux@normalesup.org>
# Jake Vanderplas <vanderplas@astro.washington.edu>
# License: BSD 3 clause
impo... | bsd-3-clause |
tlhr/plumology | tests/test_calc.py | 1 | 10237 | import pytest
import numpy as np
import pandas as pd
from plumology import calc, util
arr = [[1.0, 10.5, 0.2], [-0.3, 0.5, 0.4], [-0.2, 0.5, 0.4]]
data = pd.DataFrame(data=arr, columns=['a', 'b', 'c'])
expdata = data.rename(columns={'c': 'exp_a'}).drop('b', axis=1)
class Test_population:
def test_1(self):
... | mit |
tkoziara/parmec | tests/spherical_joint.py | 1 | 3544 | # PARMEC test --> spherical joint made of SPRING and TORSION_SPRING
# bulk material
matnum = MATERIAL (1E3, 1E9, 0.25)
# two particles
nodes1 = [0, 0, 0,
1, 0, 0,
1, 1, 0,
0, 1, 0,
0, 0, 1,
1, 0, 1,
1, 1, 1,
0, 1, 1]
nodes2 = [0.25, 0.25, 1,
0.75, 0.25, 1,
0.75, 0.75, 1,
0.... | mit |
loretoparisi/nupic | nupic/research/monitor_mixin/monitor_mixin_base.py | 27 | 5512 | # ----------------------------------------------------------------------
# Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2014, Numenta, Inc. Unless you have an agreement
# with Numenta, Inc., for a separate license for this software code, the
# following terms and conditions apply:
#
# This progra... | agpl-3.0 |
ssaeger/scikit-learn | examples/svm/plot_separating_hyperplane_unbalanced.py | 329 | 1850 | """
=================================================
SVM: Separating hyperplane for unbalanced classes
=================================================
Find the optimal separating hyperplane using an SVC for classes that
are unbalanced.
We first find the separating plane with a plain SVC and then plot
(dashed) the ... | bsd-3-clause |
themrmax/scikit-learn | sklearn/cluster/tests/test_spectral.py | 72 | 7950 | """Testing for Spectral Clustering methods"""
from sklearn.externals.six.moves import cPickle
dumps, loads = cPickle.dumps, cPickle.loads
import numpy as np
from scipy import sparse
from sklearn.utils import check_random_state
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_a... | bsd-3-clause |
micmn/shogun | examples/undocumented/python/graphical/inverse_covariance_estimation_demo.py | 11 | 2514 | #!/usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
from pylab import show, imshow
def simulate_data (n,p):
from shogun import SparseInverseCovariance
import numpy as np
#create a random pxp covariance matrix
cov = np.random.normal(size=(p,p))
#generate data set with multivariate Gaussian ... | gpl-3.0 |
kms6bn/FDA_Recalls | fdaStackPlot.py | 1 | 3506 | # -*- coding: utf-8 -*-
"""
Create stackplot for FDA food recall database using csv file created from
PythonProject file.
Katherine Schinkel, Hope McIntyre, Shannon Mitchell
kms6bn, hm7zg, som3dq
install seaborn (in your terminal, type pip install seaborn)
August 12, 2015
"""
import pandas as pd
import numpy as np
im... | mit |
jobovy/apogee-maps | py/plot_mapflare_highalpha.py | 1 | 5694 | ###############################################################################
# plot_mapflare_highalpha.py: make of plot of the flaring of MAPs
###############################################################################
import os, os.path
import sys
import csv
import pickle
import numpy
import matplotlib
matplotl... | bsd-3-clause |
funbaker/astropy | astropy/visualization/wcsaxes/ticks.py | 2 | 6187 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
import numpy as np
from matplotlib.lines import Path, Line2D
from matplotlib.transforms import Affine2D
from matplotlib import rcParams
class Ticks(Line2D):
"""
Ticks are derived from Line2D, and note that ticks themselves
are markers. Thu... | bsd-3-clause |
tkaitchuck/nupic | external/linux64/lib/python2.6/site-packages/matplotlib/bezier.py | 70 | 14387 | """
A module providing some utility functions regarding bezier path manipulation.
"""
import numpy as np
from math import sqrt
from matplotlib.path import Path
from operator import xor
# some functions
def get_intersection(cx1, cy1, cos_t1, sin_t1,
cx2, cy2, cos_t2, sin_t2):
""" return a... | gpl-3.0 |
civisanalytics/muffnn | muffnn/autoencoder/autoencoder.py | 1 | 33037 | """
Autoencoder in scikit-learn style with TensorFlow
"""
import logging
import re
import warnings
import numpy as np
import tensorflow as tf
import scipy.sparse as sp
from sklearn.base import TransformerMixin, BaseEstimator
from sklearn.utils import check_array, check_random_state
from sklearn.exceptions import Not... | bsd-3-clause |
janmedlock/HIV-95-vaccine | plots/differences.py | 1 | 5922 | #!/usr/bin/python3
'''
Plot differences for samples from uncertainty analysis.
'''
import operator
import os.path
import sys
from matplotlib import colorbar
from matplotlib import colors
from matplotlib import gridspec
from matplotlib import pyplot
from matplotlib import ticker
from matplotlib.backends import backend... | agpl-3.0 |
roxyboy/scikit-learn | sklearn/linear_model/least_angle.py | 57 | 49338 | """
Least Angle Regression algorithm. See the documentation on the
Generalized Linear Model for a complete discussion.
"""
from __future__ import print_function
# Author: Fabian Pedregosa <fabian.pedregosa@inria.fr>
# Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Gael Varoquaux
#
# License: BSD 3 ... | bsd-3-clause |
keflavich/APEX_CMZ_H2CO | analysis/backstream_pv.py | 2 | 8401 | import os
import numpy as np
import pvextractor
import spectral_cube
import aplpy
import pylab as pl
import matplotlib
import pyregion
import copy
from paths import mpath,apath,fpath,molpath,hpath,rpath,h2copath
from astropy import units as u
from astropy import coordinates
from astropy.io import ascii
from astropy imp... | bsd-3-clause |
JonathanAlvarado/bioclimatica | nom020/nom/ajax.py | 1 | 13035 | from dajaxice.decorators import dajaxice_register
from dajax.core import Dajax
from nom.models import estados, ciudades, soluciones, soluciones_detalles, ciudades_k, ciudades_fg, ciudades_temp, resultados
import simplejson as json
#from django.db.models import Q
'''@dajaxice_register
def multiply( request, a, b ):
da... | mit |
jlegendary/scikit-learn | sklearn/externals/joblib/parallel.py | 36 | 34375 | """
Helpers for embarrassingly parallel code.
"""
# Author: Gael Varoquaux < gael dot varoquaux at normalesup dot org >
# Copyright: 2010, Gael Varoquaux
# License: BSD 3 clause
from __future__ import division
import os
import sys
import gc
import warnings
from math import sqrt
import functools
import time
import thr... | bsd-3-clause |
gumm/luds | adc/plottest.py | 1 | 2681 | # Simple demo of reading each analog input from the ADS1x15 and printing it to
# the screen.
# Author: Tony DiCola
# License: Public Domain
import time
import argparse
import matplotlib.pyplot as plt
# Import the ADS1x15 module.
import Adafruit_ADS1x15
plt.ion()
# Create an ADS1115 ADC (16-bit) instance.
adc = Ada... | gpl-3.0 |
pgmpy/pgmpy | pgmpy/tests/test_factors/test_continuous/test_Linear_Gaussain_CPD.py | 2 | 3451 | import unittest
import numpy.testing as np_test
import pandas as pd
import numpy as np
from pgmpy.factors.continuous import LinearGaussianCPD
class TestLGCPD(unittest.TestCase):
# @unittest.skip("TODO")
def test_class_init(self):
mu = np.array([7, 13])
sigma = np.array([[4, 3], [3, 6]])
... | mit |
xapple/plumbing | setup.py | 1 | 1238 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Written by Lucas Sinclair.
MIT Licensed.
Contact at www.sinclair.bio
"""
# Imports #
from setuptools import setup, find_namespace_packages
from os import path
# Load the contents of the README file #
this_dir = path.abspath(path.dirname(__file__))
readme_path = path... | mit |
PmagPy/PmagPy | pmagpy_tests/test_contribution_builder.py | 1 | 33035 | #!/usr/bin/env python
import unittest
import os
import sys
import numpy as np
import pandas as pd
from pmagpy import pmag
from pmagpy import ipmag
from pmagpy import contribution_builder as cb
from pmagpy import data_model3 as data_model
from pmagpy import controlled_vocabularies3 as cv
# set constants
WD = pmag.get... | bsd-3-clause |
mugwort-rc/idata | idata/config/csv.py | 1 | 1387 | import csv
from .base import TableSourceConfig
from ..source.table import TableSource, StackedTableSource
class CSVTableSourceConfig(TableSourceConfig):
def load(self, path, encoding="utf-8"):
if hasattr(path, "read"):
return self._load(path)
with open(path, "r", encoding=encoding) as... | gpl-3.0 |
yuanagain/seniorthesis | venv/lib/python2.7/site-packages/matplotlib/textpath.py | 7 | 16677 | # -*- coding: utf-8 -*-
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from matplotlib.externals import six
from matplotlib.externals.six.moves import zip
import warnings
import numpy as np
from matplotlib.path import Path
from matplotlib import rcParam... | mit |
C2SM-RCM/serialbox | python/serialbox/Visualizer.py | 1 | 4181 | # This file is released under terms of BSD license`
# See LICENSE.txt for more information
"""Visualizer module used for visualization of serialized data."""
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.widgets import Slider, CheckButtons
from matplotlib.colors import LogNorm, SymLogNorm, N... | bsd-2-clause |
andreyzhd/VideoMEG | examples/sync_test.py | 1 | 4276 | # -*- coding: utf-8 -*-
"""An example: code for assessing video/audio/MEG synchronization.
This script takes a triplet (fiff, audio, and video) of files and generates
a bunch of pictures. Each picture describes a short piece of the
recordings. The upper pane shows 3 consecutive video frames. The lower ... | gpl-3.0 |
Erotemic/local | misc/code/physics.py | 1 | 3177 | #http://stackoverflow.com/questions/11874767/real-time-plotting-in-while-loop-with-matplotlib
from __future__ import division
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import time
G = 1 # Strength of gravity
HEIGHT = 255
WIDTH = 255
DEPTH = 0
def calculate_gravity(p1, p2):
global G
... | gpl-3.0 |
rcurtin/shogun | examples/undocumented/python_modular/graphical/preprocessor_kpca_graphical.py | 26 | 1893 | from numpy import *
import matplotlib.pyplot as p
import os, sys, inspect
path = os.path.abspath(os.path.join(os.path.dirname(__file__), '../tools'))
if not path in sys.path:
sys.path.insert(1, path)
del path
from generate_circle_data import circle_data
cir=circle_data()
number_of_points_for_circle1=42
number_of_p... | gpl-3.0 |
bzero/statsmodels | statsmodels/examples/ex_misc_tarma.py | 34 | 1875 | # -*- coding: utf-8 -*-
"""
Created on Wed Jul 03 23:01:44 2013
Author: Josef Perktold
"""
from __future__ import print_function
import numpy as np
from statsmodels.tsa.arima_process import arma_generate_sample, ArmaProcess
from statsmodels.miscmodels.tmodel import TArma
from statsmodels.tsa.arima_model import ARMA... | bsd-3-clause |
sablet/algo_trade | src/nn_model.py | 1 | 3740 | from __future__ import print_function
import os
from keras.layers import LSTM, Conv1D
from keras.layers.core import Dense
from keras.models import Sequential, load_model
from keras.optimizers import SGD
from src.model_template import ModelTemplate
from src.utility import get_out_path, np3to2
import pytest
import pandas... | mit |
rsheftel/pandas_market_calendars | pandas_market_calendars/exchange_calendar_jpx.py | 1 | 3219 | from datetime import time
from itertools import chain
from pandas.tseries.holiday import AbstractHolidayCalendar
from pytz import timezone
from pandas_market_calendars.holidays_jp import *
from pandas_market_calendars.holidays_us import USNewYearsDay
from .market_calendar import MarketCalendar
# TODO:
# From 1949 t... | mit |
ephes/scikit-learn | examples/plot_isotonic_regression.py | 303 | 1767 | """
===================
Isotonic Regression
===================
An illustration of the isotonic regression on generated data. The
isotonic regression finds a non-decreasing approximation of a function
while minimizing the mean squared error on the training data. The benefit
of such a model is that it does not assume a... | bsd-3-clause |
istb-mia/MIALab | exercise/exercise_rf.py | 1 | 5635 | """A decision forest toy example.
Trains and evaluates a decision forest classifier on a 2-D point cloud.
"""
import argparse
import datetime
import os
import sys
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap
import sklearn.ensemble as sk_ensemble
from sklearn.datase... | apache-2.0 |
Z2PackDev/Z2Pack | z2pack/plot.py | 1 | 7739 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""This submodule contains all functions for plotting Z2Pack results."""
import colorsys
import decorator
import numpy as np
from fsc.export import export
from ._utils import _pol_step
def _plot(proj_3d=False):
"""Decorator that sets up the figure axes and handles ... | gpl-3.0 |
wuxue/altanalyze | GO_Elite.py | 1 | 155516 | ###GO-Elite
#Copyright 2005-2008 J. David Gladstone Institutes, San Francisco California
#Author Nathan Salomonis - nsalomonis@gmail.com
#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 withou... | apache-2.0 |
nirdizati/nirdizati-runtime | PredictiveMethods/CaseOutcome/test_all_cases.py | 1 | 3309 | """
Copyright (c) 2016-2017 The Nirdizati Project.
This file is part of "Nirdizati".
"Nirdizati" is free software; you can redistribute it and/or modify
it under the terms of the GNU Lesser General Public License as
published by the Free Software Foundation; either version 3 of the
License, or (at your option) any lat... | lgpl-3.0 |
toobaz/pandas | pandas/tests/resample/test_time_grouper.py | 2 | 8802 | from datetime import datetime
from operator import methodcaller
import numpy as np
import pytest
import pandas as pd
from pandas import DataFrame, Series
from pandas.core.groupby.grouper import Grouper
from pandas.core.indexes.datetimes import date_range
import pandas.util.testing as tm
from pandas.util.testing impor... | bsd-3-clause |
kdebrab/pandas | pandas/core/nanops.py | 1 | 25582 | import itertools
import functools
import operator
import warnings
from distutils.version import LooseVersion
import numpy as np
from pandas import compat
from pandas._libs import tslibs, lib
from pandas.core.dtypes.common import (
_get_dtype,
is_float, is_scalar,
is_integer, is_complex, is_float_dtype,
... | bsd-3-clause |
herilalaina/scikit-learn | examples/decomposition/plot_sparse_coding.py | 60 | 4016 | """
===========================================
Sparse coding with a precomputed dictionary
===========================================
Transform a signal as a sparse combination of Ricker wavelets. This example
visually compares different sparse coding methods using the
:class:`sklearn.decomposition.SparseCoder` esti... | bsd-3-clause |
mbayon/TFG-MachineLearning | vbig/lib/python2.7/site-packages/pandas/io/sas/sas_xport.py | 14 | 14805 | """
Read a SAS XPort format file into a Pandas DataFrame.
Based on code from Jack Cushman (github.com/jcushman/xport).
The file format is defined here:
https://support.sas.com/techsup/technote/ts140.pdf
"""
from datetime import datetime
import pandas as pd
from pandas.io.common import get_filepath_or_buffer, BaseIt... | mit |
Thru-Echoes/BirdShader | database_prep/database_populate.py | 2 | 1999 | import os.path
import osgeo.ogr
import numpy as np
import psycopg2 as psy
import pandas as pd
print('Creating database for temperature...')
database_create = 'createdb temperature -T template_postgis'
os.system(database_create )
connection = psy.connect('dbname = temperature host = localhost')
cursor = connectio... | bsd-3-clause |
klusta-team/kwiklib | kwiklib/dataio/experiment.py | 1 | 29510 | """Object-oriented interface to an experiment's data."""
# -----------------------------------------------------------------------------
# Imports
# -----------------------------------------------------------------------------
import os
import os.path as op
import re
from itertools import chain
from collections import... | bsd-3-clause |
fengzhe29888/gnuradio-old | gr-filter/examples/synth_to_chan.py | 40 | 3854 | #!/usr/bin/env python
#
# Copyright 2010,2012,2013 Free Software Foundation, Inc.
#
# This file is part of GNU Radio
#
# GNU Radio 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, or (at your ... | gpl-3.0 |
pianomania/scikit-learn | examples/applications/plot_prediction_latency.py | 85 | 11395 | """
==================
Prediction Latency
==================
This is an example showing the prediction latency of various scikit-learn
estimators.
The goal is to measure the latency one can expect when doing predictions
either in bulk or atomic (i.e. one by one) mode.
The plots represent the distribution of the pred... | bsd-3-clause |
mrshu/scikit-learn | sklearn/tests/test_dummy.py | 2 | 2326 | import numpy as np
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_raises
from sklearn.dummy import DummyClassifier
from sklearn.dummy import DummyRegressor
def _check_p... | bsd-3-clause |
juggernautone/trading-with-python | lib/vixFutures.py | 79 | 4157 | # -*- coding: utf-8 -*-
"""
set of tools for working with VIX futures
@author: Jev Kuznetsov
Licence: GPL v2
"""
import datetime as dt
from pandas import *
import os
import urllib2
#from csvDatabase import HistDataCsv
m_codes = dict(zip(range(1,13),['F','G','H','J','K','M','N','Q','U','V','X','Z'])) #m... | bsd-3-clause |
jkarnows/scikit-learn | sklearn/externals/joblib/__init__.py | 36 | 4795 | """ Joblib is a set of tools to provide **lightweight pipelining in
Python**. In particular, joblib offers:
1. transparent disk-caching of the output values and lazy re-evaluation
(memoize pattern)
2. easy simple parallel computing
3. logging and tracing of the execution
Joblib is optimized to be **fast*... | bsd-3-clause |
Evfro/polara | polara/datasets/yahoo.py | 1 | 1594 | import tarfile
import pandas as pd
def get_yahoo_music_data(path=None, fileid=0, include_test=True, read_attributes=False, read_genres=False):
res = []
if path:
data_folder = 'ydata-ymusic-user-song-ratings-meta-v1_0'
col_names = ['userid', 'songid', 'rating']
with tarfile.open(path, 'r... | mit |
arabenjamin/scikit-learn | sklearn/utils/tests/test_sparsefuncs.py | 157 | 13799 | import numpy as np
import scipy.sparse as sp
from scipy import linalg
from numpy.testing import assert_array_almost_equal, assert_array_equal
from sklearn.datasets import make_classification
from sklearn.utils.sparsefuncs import (mean_variance_axis,
inplace_column_scale,
... | bsd-3-clause |
DSLituiev/scikit-learn | sklearn/utils/tests/test_fixes.py | 281 | 1829 | # Authors: Gael Varoquaux <gael.varoquaux@normalesup.org>
# Justin Vincent
# Lars Buitinck
# License: BSD 3 clause
import numpy as np
from nose.tools import assert_equal
from nose.tools import assert_false
from nose.tools import assert_true
from numpy.testing import (assert_almost_equal,
... | bsd-3-clause |
dhaase-de/dh-python-dh | dh/thirdparty/tqdm/_tqdm_pandas.py | 28 | 1608 | import sys
__author__ = "github.com/casperdcl"
__all__ = ['tqdm_pandas']
def tqdm_pandas(tclass, *targs, **tkwargs):
"""
Registers the given `tqdm` instance with
`pandas.core.groupby.DataFrameGroupBy.progress_apply`.
It will even close() the `tqdm` instance upon completion.
Parameters
------... | mit |
shenzebang/scikit-learn | sklearn/neighbors/tests/test_kde.py | 208 | 5556 | import numpy as np
from sklearn.utils.testing import (assert_allclose, assert_raises,
assert_equal)
from sklearn.neighbors import KernelDensity, KDTree, NearestNeighbors
from sklearn.neighbors.ball_tree import kernel_norm
from sklearn.pipeline import make_pipeline
from sklearn.dataset... | bsd-3-clause |
dcprojects/CoolProp | dev/scripts/fit_shape_factor.py | 5 | 8075 | from CoolProp import CoolProp as CP
from PDSim.misc.datatypes import Collector
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from scipy.odr import *
import textwrap
fluid_REF = 'Propane'
Tcrit_REF = CP.Props(fluid_REF,'Tcrit')
omega_REF = CP.Props(fluid_REF,"accentric")
mol... | mit |
jonahe1/vwm_behaviorTask | data_analysis/dataMethods.py | 1 | 8534 | # This file performs the first step of data analysis, performing calculations
# on a .csv data file output by the psychopy package. Pashler's K, d prime,
# hit rates, RTs and more are returned in a dictionary by extractPerformance to
# be utilized by pandas or another python data analysis library.
# imports
from __fut... | mit |
alander/StarCluster | utils/scimage_12_04.py | 20 | 17216 | #!/usr/bin/env python
"""
This script is meant to be run inside of a ubuntu cloud image available at
uec-images.ubuntu.com::
$ EC2_UBUNTU_IMG_URL=http://uec-images.ubuntu.com/precise/current
$ wget $EC2_UBUNTU_IMG_URL/precise-server-cloudimg-amd64.tar.gz
or::
$ wget $EC2_UBUNTU_IMG_URL/precise-server-clo... | gpl-3.0 |
DiamondLightSource/auto_tomo_calibration-experimental | old_code_scripts/simulate_data/lmfit-py/lmfit/ui/basefitter.py | 7 | 12312 | import warnings
import numpy as np
from ..model import Model
from ..models import ExponentialModel # arbitrary default
from ..asteval import Interpreter
from ..astutils import NameFinder
from ..parameter import check_ast_errors
_COMMON_DOC = """
This an interactive container for fitting models to particular dat... | apache-2.0 |
belltailjp/scikit-learn | benchmarks/bench_mnist.py | 154 | 6006 | """
=======================
MNIST dataset benchmark
=======================
Benchmark on the MNIST dataset. The dataset comprises 70,000 samples
and 784 features. Here, we consider the task of predicting
10 classes - digits from 0 to 9 from their raw images. By contrast to the
covertype dataset, the feature space is... | bsd-3-clause |
CINPLA/expipe-dev | exana/exana/tests/test_salt.py | 2 | 4650 | import pytest
import elephant
import neo
import quantities as pq
import numpy as np
def _test_salt_inh():
from exana.stimulus import salt, generate_salt_trials
from exana.misc import concatenate_spiketrains
from elephant.spike_train_generation import homogeneous_poisson_process as hpp
np.random.seed(1... | gpl-3.0 |
grlee77/scipy | doc/source/tutorial/stats/plots/mgc_plot2.py | 12 | 1282 | import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import multiscale_graphcorr
def mgc_plot(x, y, mgc_dict):
"""Plot sim and MGC-plot"""
plt.figure(figsize=(8, 8))
ax = plt.gca()
# local correlation map
mgc_map = mgc_dict["mgc_map"]
# draw heatmap
ax.set_title("Local Cor... | bsd-3-clause |
mmmatthew/raycast | code/s13__ortho_cluster.py | 1 | 1550 | '''
This function turns the image coordinates to geographic coordinates
'''
import os
import pandas as pd
from s10__cluster_3d import cluster_dbscan
def ortho_cluster(config, debug, settings):
# Where to save clusters
save_to_directory = os.path.join(config['iteration_directory'],
... | apache-2.0 |
yousrabk/mne-python | mne/tests/test_cov.py | 6 | 18217 | # Author: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Denis Engemann <denis.engemann@gmail.com>
#
# License: BSD (3-clause)
import os.path as op
from nose.tools import assert_true, assert_equal
from numpy.testing import assert_array_almost_equal, assert_array_equal
from nose.tools import as... | bsd-3-clause |
mayblue9/bokeh | examples/glyphs/colors.py | 19 | 8922 | from __future__ import print_function
from math import pi
import pandas as pd
from bokeh.models import Plot, ColumnDataSource, FactorRange, CategoricalAxis, TapTool, HoverTool, OpenURL
from bokeh.models.glyphs import Rect
from bokeh.document import Document
from bokeh.embed import file_html
from bokeh.resources impor... | bsd-3-clause |
MesserLab/SLiM | SLiMgui/Recipes/Recipe 17.5 - Mapping admixture (analyzing ancestry in Python) II.py | 2 | 1037 | # Keywords: Python, tree-sequence recording, tree sequence recording
# This is a Python recipe; note that it runs the SLiM model internally, below
import subprocess, msprime, pyslim
import matplotlib.pyplot as plt
import numpy as np
# Run the SLiM model and load the resulting .trees file
subprocess.check_output(["sl... | gpl-3.0 |
foreversand/QSTK | Examples/Basic/tutorial6.py | 1 | 3275 | '''
(c) 2011, 2012 Georgia Tech Research Corporation
This source code is released under the New BSD license. Please see
http://wiki.quantsoftware.org/index.php?title=QSTK_License
for license details.
Created on June 1, 2011
@author: John Cornwell
@contact: JohnWCornwellV@gmail.com
@summary: Demonstrates the retrieva... | bsd-3-clause |
xiaoxiamii/scikit-learn | examples/exercises/plot_iris_exercise.py | 323 | 1602 | """
================================
SVM Exercise
================================
A tutorial exercise for using different SVM kernels.
This exercise is used in the :ref:`using_kernels_tut` part of the
:ref:`supervised_learning_tut` section of the :ref:`stat_learn_tut_index`.
"""
print(__doc__)
import numpy as np
i... | bsd-3-clause |
eljost/td | td/mix_spectra.py | 1 | 2711 | #!/usr/bin/env python3
"""This script plots two gradually mixed spectra. It can be used
to visualize the spectra changes over the course of a chemical reaction,
e.g. a photoreaction."""
import argparse
import sys
import matplotlib as mpl
import matplotlib.animation as animation
import matplotlib.pyplot as plt
import... | gpl-3.0 |
gereon/trading-with-python | historicDataDownloader/historicDataDownloader.py | 77 | 4526 | '''
Created on 4 aug. 2012
Copyright: Jev Kuznetsov
License: BSD
a module for downloading historic data from IB
'''
import ib
import pandas
from ib.ext.Contract import Contract
from ib.opt import ibConnection, message
from time import sleep
import tradingWithPython.lib.logger as logger
from pandas impor... | bsd-3-clause |
kagayakidan/scikit-learn | examples/cross_decomposition/plot_compare_cross_decomposition.py | 128 | 4761 | """
===================================
Compare cross decomposition methods
===================================
Simple usage of various cross decomposition algorithms:
- PLSCanonical
- PLSRegression, with multivariate response, a.k.a. PLS2
- PLSRegression, with univariate response, a.k.a. PLS1
- CCA
Given 2 multivari... | bsd-3-clause |
hitrace/RDATKit | _deprecated_/likelihood/optimize.py | 1 | 16052 | import pickle
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.pylab import *
import random
import pdb
from numpy import *
import numpy as np
"""
from cvxmod import *
from cvxmod.atoms import *
from cvxmod.sets import *
"""
from rdatkit import secondary_structure
from rdatkit import settings
from rdatkit import ... | bsd-3-clause |
eclee25/flu-SDI-exploratory-age | scripts/create_fluseverity_figs_v5/FR_incid_time_v5.py | 1 | 2436 | #!/usr/bin/python
##############################################
###Python template
###Author: Elizabeth Lee
###Date: 1/19/15
###Function: (France data) Total estimated incidence per 100,000 vs. week number normalized by the first 'gp_normweeks' of the season.
###Import data: Documents/FRANCE_ILI_DATA_2014/inc2_inc-... | mit |
ColdSauce/solvinga858 | solve.py | 1 | 1526 | import csv
import numpy as np
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
def is_number(c):
try:
int(c)
return True
except ValueError:
return False
def get_amount_chars_together(st):
total = 0
previous_was_char = False
for c in st:
if not is_numbe... | mit |
FRBs/DM | frb/galaxies/eazy.py | 2 | 20922 | """ Module to faciliate scripting of EAZY analysis"""
import os
import warnings
from pkg_resources import resource_filename
from distutils import spawn
import subprocess
import numpy as np
import pandas
from astropy.table import Table
from astropy.cosmology import Planck15
from frb.surveys import catalog_utils
fro... | bsd-3-clause |
ghackebeil/sbb_project | problems.py | 1 | 11801 | import json
from collections import OrderedDict
import pyomo.kernel as pmo
import numpy
import relaxations
registered_problems = {}
class Problem(object):
def create_model(self):
raise NotImplementedError
def transform_to_convex(self, model):
raise NotImplementedError
def restore_from_... | mit |
bzero/statsmodels | statsmodels/iolib/tests/test_foreign.py | 25 | 7274 | """
Tests for iolib/foreign.py
"""
import os
import warnings
from datetime import datetime
from numpy.testing import *
import numpy as np
from pandas import DataFrame, isnull
import pandas.util.testing as ptesting
from statsmodels.compat.python import BytesIO, asbytes
import statsmodels.api as sm
from statsmodels.iol... | bsd-3-clause |
almarklein/bokeh | bokeh/mpl.py | 1 | 18876 | "Supporting objects and functions to convert Matplotlib objects into Bokeh."
#-----------------------------------------------------------------------------
# Copyright (c) 2012 - 2014, Continuum Analytics, Inc. All rights reserved.
#
# Powered by the Bokeh Development Team.
#
# The full license is in the file LICENSE.t... | bsd-3-clause |
ghost9023/DeepLearningPythonStudy | DeepLearning/DeepLearning/09_Deep_SongJW/book/ch04/train_neuralnet.py | 1 | 1942 | # coding: utf-8
import sys, os
sys.path.append(os.pardir) # 부모 디렉터리의 파일을 가져올 수 있도록 설정
import numpy as np
import matplotlib.pyplot as plt
from dataset.mnist import load_mnist
from book.ch04.two_layer_net import TwoLayerNet
# 데이터 읽기
(x_train, t_train), (x_test, t_test) = load_mnist(normalize=True, one_hot_label=True)
... | mit |
musoke/dotfiles | .ipython/profile_default/ipython_config.py | 1 | 20580 | # Configuration file for ipython.
c = get_config()
#------------------------------------------------------------------------------
# InteractiveShellApp configuration
#------------------------------------------------------------------------------
# A Mixin for applications that start InteractiveShell instances.
#
#... | mit |
felipecustodio/algorithms | digital_image_processing/steganography/demo.py | 2 | 3941 | import numpy as np
import imageio
import seaborn as sns
from matplotlib import pyplot as plt
from matplotlib import animation
from subprocess import call
# load images
print("Loading images...")
original = np.asarray(imageio.imread("images/forest.png", as_gray=False, pilmode="RGB"))
secret = np.asarray(ima... | mit |
clemkoa/scikit-learn | sklearn/metrics/cluster/supervised.py | 13 | 31406 | """Utilities to evaluate the clustering performance of models.
Functions named as *_score return a scalar value to maximize: the higher the
better.
"""
# Authors: Olivier Grisel <olivier.grisel@ensta.org>
# Wei LI <kuantkid@gmail.com>
# Diego Molla <dmolla-aliod@gmail.com>
# Arnaud Fouchet ... | bsd-3-clause |
bundgus/python-playground | matplotlib-playground/examples/tests/backend_driver.py | 1 | 15265 | #!/usr/bin/env python
from __future__ import print_function, division
"""
This is used to drive many of the examples across the backends, for
regression testing, and comparing backend efficiency.
You can specify the backends to be tested either via the --backends
switch, which takes a comma-separated list, or as sepa... | mit |
BhallaLab/moose | moose-examples/traub_2005/py/display_morphology.py | 1 | 5878 | # display_morphology.py ---
#
# Filename: display_morphology.py
# Description:
# Author:
# Maintainer:
# Created: Fri Mar 8 11:26:13 2013 (+0530)
# Version:
# Last-Updated: Sun Jun 25 15:09:55 2017 (-0400)
# By: subha
# Update #: 390
# URL:
# Keywords:
# Compatibility:
#
#
# Commentary:
#
#... | gpl-3.0 |
frapa/Schr | windows/schr.py | 2 | 8864 | # -*- encoding:utf-8 -*-
#!/usr/bin/python
from multiprocessing import Process, Queue
import time
import locale, gettext
import os
from gi.repository import Gtk
from gi.repository import GLib
import numpy as np # stupid!!!
from numpy import *
import matplotlib.pyplot as plt
import compy as cp
APP = "schr"
TRANSLATI... | gpl-3.0 |
UNR-AERIAL/scikit-learn | sklearn/linear_model/ransac.py | 191 | 14261 | # coding: utf-8
# Author: Johannes Schönberger
#
# License: BSD 3 clause
import numpy as np
from ..base import BaseEstimator, MetaEstimatorMixin, RegressorMixin, clone
from ..utils import check_random_state, check_array, check_consistent_length
from ..utils.random import sample_without_replacement
from ..utils.valid... | bsd-3-clause |
CrazyGuo/bokeh | examples/plotting/server/burtin.py | 42 | 4826 | # The plot server must be running
# Go to http://localhost:5006/bokeh to view this plot
from collections import OrderedDict
from math import log, sqrt
import numpy as np
import pandas as pd
from six.moves import cStringIO as StringIO
from bokeh.plotting import figure, show, output_server
antibiotics = """
bacteria,... | bsd-3-clause |
abramovd/Newster | newster/algorithms/KMeans.py | 1 | 3895 | #!/usr/bin/env python
# -*- coding: utf-8
# Dmitry Abramov
# Python v. 2.7.9
from __future__ import print_function
import os.path, sys
sys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)), os.pardir))
import numpy as np
from preprocessing.tokenize_and_stem import tokenize_and_stem
from Scraper i... | mit |
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