repo_name stringlengths 6 67 | path stringlengths 5 185 | copies stringlengths 1 3 | size stringlengths 4 6 | content stringlengths 1.02k 962k | license stringclasses 15
values |
|---|---|---|---|---|---|
dialounke/pylayers | pylayers/mobility/transit/Person.py | 2 | 20819 | """
.. currentmodule:: pylayers.mobility.transit.Person
Utility Functions
=================
.. autosummary;;
:toctree: generated/
scale
copy
Person Class
=================
.. autosummary;;
:toctree: generated/
Person.__init__
Person.__repr__
Person.move
Person.delete
"""
from Sim... | mit |
mxjl620/scikit-learn | examples/mixture/plot_gmm_pdf.py | 284 | 1528 | """
=============================================
Density Estimation for a mixture of Gaussians
=============================================
Plot the density estimation of a mixture of two Gaussians. Data is
generated from two Gaussians with different centers and covariance
matrices.
"""
import numpy as np
import ma... | bsd-3-clause |
kelseyoo14/Wander | venv_2_7/lib/python2.7/site-packages/pandas/sparse/list.py | 16 | 3695 | import numpy as np
from pandas.core.base import PandasObject
from pandas.core.common import pprint_thing
from pandas.sparse.array import SparseArray
import pandas._sparse as splib
class SparseList(PandasObject):
"""
Data structure for accumulating data to be converted into a
SparseArray. Has similar API... | artistic-2.0 |
jakobworldpeace/scikit-learn | examples/cluster/plot_mean_shift.py | 351 | 1793 | """
=============================================
A demo of the mean-shift clustering algorithm
=============================================
Reference:
Dorin Comaniciu and Peter Meer, "Mean Shift: A robust approach toward
feature space analysis". IEEE Transactions on Pattern Analysis and
Machine Intelligence. 2002. ... | bsd-3-clause |
monitor1379/sammale | examples/e1_LinearPrimaryFunctionMode_for_regressionl.py | 1 | 1822 | # encoding: utf-8
"""
@author: monitor1379
@contact: yy4f5da2@hotmail.com
@site: www.monitor1379.com
@version: 1.0
@license: GNU General Public License(Version 3)
@file: e1_LinearPrimaryFunctionModel.py
@time: 2016/12/18 23:56
"""
from __future__ import print_function
import matplotlib.pyplot as plt
import numpy ... | gpl-3.0 |
BBN-Q/PyQLab | analysis/SSRO.py | 4 | 6234 | import numpy as np
from scipy.signal import butter, lfilter
from scipy.io import loadmat
from sklearn import decomposition, preprocessing, cross_validation
from sklearn import svm, grid_search
import pywt
import h5py
import matplotlib.pyplot as plt
def create_fake_data(SNR, dt, maxTime, numShots, T1=1.0):
"""
Hel... | apache-2.0 |
Jessime/Excision | src/play_levels.py | 1 | 7834 | import os
import sys
import json
import markdown
import subprocess as sp
import numpy as np
import pandas as pd
from flask import Markup
from pickle import load
from importlib import import_module, reload
from shutil import copyfile
from traceback import format_exc
from level_markdown import parse, change_log
class ... | mit |
sanuj/shogun | examples/undocumented/python_modular/graphical/interactive_gp_demo.py | 10 | 14176 | #
# This program 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 License, or
# (at your option) any later version.
#
# Written (C) 2012 Heiko Strathmann, based on interactive_svm_demo by ... | gpl-3.0 |
devanshdalal/scikit-learn | examples/covariance/plot_outlier_detection.py | 36 | 5023 | """
==========================================
Outlier detection with several methods.
==========================================
When the amount of contamination is known, this example illustrates three
different ways of performing :ref:`outlier_detection`:
- based on a robust estimator of covariance, which is assum... | bsd-3-clause |
kelseyoo14/Wander | venv_2_7/lib/python2.7/site-packages/pandas/io/tests/test_pytables.py | 9 | 194218 | import nose
import sys
import os
import warnings
import tempfile
from contextlib import contextmanager
import datetime
import numpy as np
import pandas
import pandas as pd
from pandas import (Series, DataFrame, Panel, MultiIndex, Categorical, bdate_range,
date_range, timedelta_range, Index, Dateti... | artistic-2.0 |
rtrwalker/geotecha | geotecha/consolidation/smear_zones.py | 1 | 127140 | # geotecha - A software suite for geotechncial engineering
# Copyright (C) 2018 Rohan T. Walker (rtrwalker@gmail.com)
#
# This program 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... | gpl-3.0 |
yaroslavvb/tensorflow | tensorflow/examples/learn/iris_custom_decay_dnn.py | 56 | 1959 | # Copyright 2016 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 appl... | apache-2.0 |
moosekaka/sweepython | tubule_het/psd_rand_carbon.py | 1 | 4161 | # -*- coding: utf-8 -*-
"""
Calculates and plots POWER SPEC DENSITY (psd) of Δψ for real and random dists.
@author: sweel
"""
import os
import os.path as op
import cPickle as pickle
from collections import defaultdict
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import wr... | mit |
twschum/mix-mind | mixmind_cli.py | 1 | 15109 | #!/usr/bin/env python
"""
Turn recipes json into a readable menu
"""
import argparse
import pickle as pickle
from collections import Counter, defaultdict
import json
import jsonschema
import pandas as pd
import mixmind.recipe as drink_recipe
from mixmind.barstock import Barstock
import mixmind.formatted_menu as form... | apache-2.0 |
deepesch/scikit-learn | examples/svm/plot_iris.py | 225 | 3252 | """
==================================================
Plot different SVM classifiers in the iris dataset
==================================================
Comparison of different linear SVM classifiers on a 2D projection of the iris
dataset. We only consider the first 2 features of this dataset:
- Sepal length
- Se... | bsd-3-clause |
terkkila/scikit-learn | sklearn/decomposition/tests/test_fastica.py | 272 | 7798 | """
Test the fastica algorithm.
"""
import itertools
import warnings
import numpy as np
from scipy import stats
from nose.tools import assert_raises
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_true
from skl... | bsd-3-clause |
redreamality/daft | examples/exoplanets.py | 7 | 1616 | """
The Fergus model of exoplanet detection
=======================================
Besides being generally awesome, this example also demonstrates how you can
color the nodes and add arbitrary labels to the figure.
"""
from matplotlib import rc
rc("font", family="serif", size=12)
rc("text", usetex=True)
import daf... | mit |
daniaki/Enrich2 | plugins/ratios_scorer.py | 1 | 4679 | # Copyright 2016-2017 Alan F Rubin
#
# This file is part of Enrich2.
#
# Enrich2 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 License, or
# (at your option) any later version.
... | gpl-3.0 |
lordkman/burnman | misc/benchmarks/debye.py | 4 | 1721 | from __future__ import absolute_import
from __future__ import print_function
import os.path
import sys
sys.path.insert(1, os.path.abspath('../..'))
import numpy as np
import matplotlib.pyplot as plt
import burnman
import scipy.integrate
import time
def old_thermal(T, debye_T, n):
if T == 0:
return 0
... | gpl-2.0 |
akionakamura/scikit-learn | examples/semi_supervised/plot_label_propagation_digits_active_learning.py | 294 | 3417 | """
========================================
Label Propagation digits active learning
========================================
Demonstrates an active learning technique to learn handwritten digits
using label propagation.
We start by training a label propagation model with only 10 labeled points,
then we select the t... | bsd-3-clause |
dsullivan7/scikit-learn | examples/cluster/plot_kmeans_stability_low_dim_dense.py | 338 | 4324 | """
============================================================
Empirical evaluation of the impact of k-means initialization
============================================================
Evaluate the ability of k-means initializations strategies to make
the algorithm convergence robust as measured by the relative stan... | bsd-3-clause |
FilipDominec/python-meep-utils | colormaps.py | 28 | 50518 | # New matplotlib colormaps by Nathaniel J. Smith, Stefan van der Walt,
# and (in the case of viridis) Eric Firing.
#
# This file and the colormaps in it are released under the CC0 license /
# public domain dedication. We would appreciate credit if you use or
# redistribute these colormaps, but do not impose any legal r... | gpl-2.0 |
tseaver/gcloud-python | bigquery/google/cloud/bigquery/table.py | 1 | 46359 | # Copyright 2015 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, s... | apache-2.0 |
simon-pepin/scikit-learn | examples/mixture/plot_gmm_pdf.py | 284 | 1528 | """
=============================================
Density Estimation for a mixture of Gaussians
=============================================
Plot the density estimation of a mixture of two Gaussians. Data is
generated from two Gaussians with different centers and covariance
matrices.
"""
import numpy as np
import ma... | bsd-3-clause |
zooniverse/aggregation | active_weather/text_detection.py | 1 | 4656 | #!/usr/bin/env python
import glob
import active_weather
import matplotlib.pyplot as plt
import cv2
import numpy as np
import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets("MNIST_data/", one_hot=True)
height = 40#int(np.median(heights))
width = 30#int(np.... | apache-2.0 |
btabibian/scikit-learn | benchmarks/bench_multilabel_metrics.py | 276 | 7138 | #!/usr/bin/env python
"""
A comparison of multilabel target formats and metrics over them
"""
from __future__ import division
from __future__ import print_function
from timeit import timeit
from functools import partial
import itertools
import argparse
import sys
import matplotlib.pyplot as plt
import scipy.sparse as... | bsd-3-clause |
tcchenbtx/project-zeta-J | code/correlation_analysis_scripts_sub5.py | 3 | 23223 | import numpy as np
import os
import matplotlib.pyplot as plt
from matplotlib import colors
import copy
# maximally responded area, percentile setting:
percent = 80
# object_list
object_list = ["bottle", "cat", "chair", "face", "house", "scissors", "scrambledpix", "shoe"]
# important path:
base_path = os.path.abspath... | bsd-3-clause |
arjoly/scikit-learn | sklearn/linear_model/tests/test_logistic.py | 3 | 37569 | import numpy as np
import scipy.sparse as sp
from scipy import linalg, optimize, sparse
import scipy
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_equal
from... | bsd-3-clause |
chetan51/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/widgets.py | 69 | 40833 | """
GUI Neutral widgets
All of these widgets require you to predefine an Axes instance and
pass that as the first arg. matplotlib doesn't try to be too smart in
layout -- you have to figure out how wide and tall you want your Axes
to be to accommodate your widget.
"""
import numpy as np
from mlab import dist
from p... | gpl-3.0 |
cython-testbed/pandas | pandas/tests/scalar/timestamp/test_arithmetic.py | 5 | 2572 | # -*- coding: utf-8 -*-
from datetime import datetime, timedelta
import pytest
import numpy as np
from pandas.compat import long
from pandas.tseries import offsets
from pandas import Timestamp, Timedelta
class TestTimestampArithmetic(object):
def test_overflow_offset(self):
# xref https://github.com/sta... | bsd-3-clause |
ryandougherty/mwa-capstone | MWA_Tools/build/matplotlib/doc/mpl_examples/user_interfaces/embedding_in_gtk3.py | 4 | 1137 | #!/usr/bin/env python
"""
demonstrate adding a FigureCanvasGTK/GTKAgg widget to a gtk.ScrolledWindow
"""
import gtk
from matplotlib.figure import Figure
from numpy import arange, sin, pi
# uncomment to select /GTK/GTKAgg/GTKCairo
#from matplotlib.backends.backend_gtk import FigureCanvasGTK as FigureCanvas
from matpl... | gpl-2.0 |
kaichogami/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 |
rs2/pandas | pandas/tests/window/test_numba.py | 1 | 2942 | import numpy as np
import pytest
import pandas.util._test_decorators as td
from pandas import Series, option_context
import pandas._testing as tm
from pandas.core.util.numba_ import NUMBA_FUNC_CACHE
@td.skip_if_no("numba", "0.46.0")
@pytest.mark.filterwarnings("ignore:\\nThe keyword argument")
# Filter warnings whe... | bsd-3-clause |
napsternxg/pytorch-practice | chunking_bilstm_crf_char_concat.py | 1 | 7939 |
# coding: utf-8
# In[1]:
import matplotlib
matplotlib.use("Agg")
import torch
from torch.autograd import Variable
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
torch.manual_seed(1)
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from pytorch_utils impo... | apache-2.0 |
miloharper/neural-network-animation | matplotlib/axes/_axes.py | 10 | 260820 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from six.moves import reduce, xrange, zip, zip_longest
import math
import warnings
import numpy as np
from numpy import ma
import matplotlib
rcParams = matplotlib.rcParams
import matplotlib.cbook... | mit |
rainest/dance-partner-matching | networkx/readwrite/tests/test_gml.py | 1 | 2734 | #!/usr/bin/env python
import io
from nose.tools import *
from nose import SkipTest
import networkx
class TestGraph(object):
@classmethod
def setupClass(cls):
global pyparsing
try:
import pyparsing
except ImportError:
try:
import matplotlib.pyparsi... | bsd-2-clause |
kirel/political-affiliation-prediction | topicmodel.py | 2 | 3883 | # -*- coding: utf-8 -*-
from sklearn.cluster import KMeans
import classifier
from scipy import zeros,double
import datetime
import json
import cPickle
class Topicmodel():
'''
Wrapper class for different topic models
'''
def __init__(self,folder='model',modeltype='kmeans',topics=100,topwords=10):
... | mit |
darwinex/DarwinexLabs | tools/Python/MetaTrader_Helpers/Report_Conversion/MT_TO_PYTHON/DWX_MT_TO_PYTHON_v2_RC4.py | 1 | 9361 | # -*- coding: utf-8 -*-
"""
Created on Mon Feb 04 12:01:07 2019
@author: Darwinex Labs (www.darwinex.com)
DWX_MT_TO_PYTHON_v2_RC4.py
Purpose:
This script enables traders knowledgable in Python to import
their Account History and Strategy Tester reports directly into
pandas dataframes.... | bsd-3-clause |
AnasGhrab/scikit-learn | sklearn/linear_model/stochastic_gradient.py | 130 | 50966 | # Authors: Peter Prettenhofer <peter.prettenhofer@gmail.com> (main author)
# Mathieu Blondel (partial_fit support)
#
# License: BSD 3 clause
"""Classification and regression using Stochastic Gradient Descent (SGD)."""
import numpy as np
import scipy.sparse as sp
from abc import ABCMeta, abstractmethod
from ... | bsd-3-clause |
Arn-O/kadenze-deep-creative-apps | final-project/libs/utils.py | 1 | 2157 | """
Utility for image manipulation, directly copied (and slightly modified) from:
https://github.com/pkmital/CADL
"""
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import numpy as np
def img_crop(img, pos):
"""Crop to square from a position.
Parameters
----------
img : np.n... | apache-2.0 |
akrherz/dep | scripts/plots/scenario_soil.py | 2 | 2595 | """Plot soil stuff."""
import os
import glob
import sys
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from pyiem.dep import read_slp
from pyiem.util import utc
def read_data():
"""Do intensive stuff"""
scenarios = []
kr = []
for huc12 in [
"070600060701",
"070... | mit |
JT5D/scikit-learn | sklearn/tests/test_base.py | 9 | 5815 |
# Author: Gael Varoquaux
# License: BSD 3 clause
import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_false
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing imp... | bsd-3-clause |
aydevosotros/tradingMachine | DataManager.py | 1 | 1627 | #
# Copyright (c) 2015 by Antonio Molina García-Retamero. All Rights Reserved.
#
import requests
import datetime
import csv
import numpy as np
import matplotlib.pyplot as plt
class DataManager(object):
"""docstring for DataManager"""
def __init__(self, arg):
super(DataManager, self).__init__()
... | gpl-2.0 |
shusenl/scikit-learn | sklearn/linear_model/tests/test_bayes.py | 299 | 1770 | # Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Fabian Pedregosa <fabian.pedregosa@inria.fr>
#
# License: BSD 3 clause
import numpy as np
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import SkipTest
from sklearn.linear_model.bayes import BayesianRidge, ARDRegres... | bsd-3-clause |
adamrvfisher/TechnicalAnalysisLibrary | CSVtoDFDiv.py | 1 | 1762 | # -*- coding: utf-8 -*-
"""
Created on Sun May 21 11:47:12 2017
@author: AmatVictoriaCuramIII
"""
from pandas import read_csv
import pandas as pd
import os
CSVfiles = os.listdir('F:\\Users\\AmatVictoriaCuram\\TemporaryCSV')
ranger = range(0,len(CSVfiles))
for i in ranger:
try:
temp = read_cs... | apache-2.0 |
chengsoonong/digbeta | dchen/music/src/tools/evaluate.py | 2 | 10972 | import numpy as np
# from sklearn.metrics import f1_score
from sklearn.metrics import precision_recall_fscore_support, roc_auc_score
from joblib import Parallel, delayed
def calc_metrics(y_true, y_pred, tops=[]):
assert y_true.ndim == y_pred.ndim == 1
assert len(y_true) == len(y_pred)
npos = y_true.sum()
... | gpl-3.0 |
alexxyjiang/docker-images | jupyterlab/scala2.11/jupyter_notebook_config.py | 2 | 23448 | # Configuration file for jupyter-notebook.
#------------------------------------------------------------------------------
# Application(SingletonConfigurable) configuration
#------------------------------------------------------------------------------
## This is an application.
## The date format used by logging f... | mit |
Achuth17/scikit-learn | examples/cluster/plot_kmeans_silhouette_analysis.py | 242 | 5885 | """
===============================================================================
Selecting the number of clusters with silhouette analysis on KMeans clustering
===============================================================================
Silhouette analysis can be used to study the separation distance between the... | bsd-3-clause |
buckiracer/data-science-from-scratch | RefMaterials/code-python3/introduction.py | 6 | 8194 | # at this stage in the book we haven't actually installed matplotlib,
# comment this out if you need to
from matplotlib import pyplot as plt
##########################
# #
# FINDING KEY CONNECTORS #
# #
##########################
users = [
{ "id": 0, "name": "Hero" },... | unlicense |
knutfrode/opendrift | opendrift/__init__.py | 1 | 7342 | import logging
import unittest
import importlib
import numpy as np
import time
from datetime import timedelta
from .version import __version__
# For automated access to available drift classes, e.g. for GUI
# Hardcoded for now
_available_models = \
['leeway.Leeway',
'openoil.OpenOil',
'shipdrift.ShipDrif... | gpl-2.0 |
JPFrancoia/scikit-learn | examples/tree/plot_tree_regression.py | 95 | 1516 | """
===================================================================
Decision Tree Regression
===================================================================
A 1D regression with decision tree.
The :ref:`decision trees <tree>` is
used to fit a sine curve with addition noisy observation. As a result, it
learns ... | bsd-3-clause |
zorroblue/scikit-learn | benchmarks/bench_sparsify.py | 50 | 3410 | """
Benchmark SGD prediction time with dense/sparse coefficients.
Invoke with
-----------
$ kernprof.py -l sparsity_benchmark.py
$ python -m line_profiler sparsity_benchmark.py.lprof
Typical output
--------------
input data sparsity: 0.050000
true coef sparsity: 0.000100
test data sparsity: 0.027400
model sparsity:... | bsd-3-clause |
xubenben/scikit-learn | examples/cluster/plot_lena_ward_segmentation.py | 271 | 1998 | """
===============================================================
A demo of structured Ward hierarchical clustering on Lena image
===============================================================
Compute the segmentation of a 2D image with Ward hierarchical
clustering. The clustering is spatially constrained in order
... | bsd-3-clause |
benoitsteiner/tensorflow-opencl | tensorflow/contrib/learn/python/learn/learn_io/io_test.py | 137 | 5063 | # Copyright 2016 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 |
MartinThoma/algorithms | Python/string-concat/main.py | 1 | 2095 | import operator
import random
import string
import timeit
from io import StringIO
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
def main():
str_list = [create_random_string(255) for i in range(1000)]
functions = [
(plus_concat, "plus_concat"),
(join_concat, "join_co... | mit |
roxyboy/scikit-learn | sklearn/utils/tests/test_extmath.py | 130 | 16270 | # Authors: Olivier Grisel <olivier.grisel@ensta.org>
# Mathieu Blondel <mathieu@mblondel.org>
# Denis Engemann <d.engemann@fz-juelich.de>
#
# License: BSD 3 clause
import numpy as np
from scipy import sparse
from scipy import linalg
from scipy import stats
from sklearn.utils.testing import assert_eq... | bsd-3-clause |
yavalvas/yav_com | build/matplotlib/lib/mpl_examples/pylab_examples/contour_demo.py | 14 | 3478 | #!/usr/bin/env python
"""
Illustrate simple contour plotting, contours on an image with
a colorbar for the contours, and labelled contours.
See also contour_image.py.
"""
import matplotlib
import numpy as np
import matplotlib.cm as cm
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
matplotlib.rcParams[... | mit |
qifeigit/scikit-learn | sklearn/tests/test_qda.py | 155 | 3481 | import numpy as np
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_greater
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing import ignore_war... | bsd-3-clause |
jmmease/pandas | pandas/errors/__init__.py | 6 | 1697 | # flake8: noqa
"""
Expose public exceptions & warnings
"""
from pandas._libs.tslib import OutOfBoundsDatetime
class PerformanceWarning(Warning):
"""
Warning raised when there is a possible
performance impact.
"""
class UnsupportedFunctionCall(ValueError):
"""
Exception raised when attemptin... | bsd-3-clause |
cxhernandez/msmbuilder | msmbuilder/utils/nearest.py | 12 | 6505 | # Author: Matthew Harrigan <matthew.p.harrigan@gmail.com>
# Contributors:
# Copyright (c) 2015, Stanford University and the Authors
# All rights reserved.
from __future__ import absolute_import, print_function, division
from scipy.spatial import KDTree as sp_KDTree
import numpy as np
from . import check_iter_of_seque... | lgpl-2.1 |
pepo27/PatternRecognition | Python/SegundoParcial/mx/pepo/pattern/perceptron.py | 2 | 3439 | __author__ = 'alberto'
from random import choice
#import matplotlib.pyplot as plt
from numpy import array, dot, random
import numpy as np
import matplotlib.pyplot as plt
def perceptronOR():
unit_step = lambda x: 0 if x < 0 else 1
training_data = [
(array([0,0,1]), 0),
(array([0,1,1]), 1),
(array([1,0,1]), 1... | gpl-2.0 |
teonlamont/mne-python | mne/decoding/tests/test_ems.py | 2 | 3389 | # Author: Denis A. Engemann <d.engemann@gmail.com>
#
# License: BSD (3-clause)
import os.path as op
import numpy as np
from numpy.testing import assert_array_almost_equal, assert_equal
import pytest
from mne import io, Epochs, read_events, pick_types
from mne.utils import requires_version, check_version, run_tests_if... | bsd-3-clause |
jmetzen/scikit-learn | examples/linear_model/plot_logistic.py | 312 | 1426 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Logit function
=========================================================
Show in the plot is how the logistic regression would, in this
synthetic dataset, classify values as either 0 or 1,
i.e. class one or two, u... | bsd-3-clause |
biocyberman/bcbio-nextgen | bcbio/structural/prioritize.py | 1 | 10138 | """Prioritize structural variants based on biological information.
Provides high level summaries of structural variants in regions of interest,
as defined by the input configuration. Tries to narrow structural variant calls
based on potential biological targets.
"""
import os
import pandas as pd
import toolz as tz
fr... | mit |
mbayon/TFG-MachineLearning | vbig/lib/python2.7/site-packages/sklearn/neighbors/tests/test_ball_tree.py | 26 | 10379 | import pickle
import numpy as np
from numpy.testing import assert_array_almost_equal
from sklearn.neighbors.ball_tree import (BallTree, NeighborsHeap,
simultaneous_sort, kernel_norm,
nodeheap_sort, DTYPE, ITYPE)
from sklearn.neighbors.dis... | mit |
jmikko/fairnessML | zafar_methods/disparate_mistreatment/synthetic_data_demo/fairness_acc_tradeoff.py | 1 | 11588 | import os, sys
import numpy as np
from generate_synthetic_data import *
sys.path.insert(0, '../../fair_classification/') # the code for fair classification is in this directory
import utils as ut
import funcs_disp_mist as fdm
import loss_funcs as lf # loss funcs that can be optimized subject to various constraints
i... | gpl-3.0 |
LiaoPan/scikit-learn | examples/plot_johnson_lindenstrauss_bound.py | 134 | 7452 | """
=====================================================================
The Johnson-Lindenstrauss bound for embedding with random projections
=====================================================================
The `Johnson-Lindenstrauss lemma`_ states that any high dimensional
dataset can be randomly projected in... | bsd-3-clause |
ChanderG/scikit-learn | benchmarks/bench_plot_incremental_pca.py | 374 | 6430 | """
========================
IncrementalPCA benchmark
========================
Benchmarks for IncrementalPCA
"""
import numpy as np
import gc
from time import time
from collections import defaultdict
import matplotlib.pyplot as plt
from sklearn.datasets import fetch_lfw_people
from sklearn.decomposition import Incre... | bsd-3-clause |
pianomania/scikit-learn | benchmarks/bench_multilabel_metrics.py | 276 | 7138 | #!/usr/bin/env python
"""
A comparison of multilabel target formats and metrics over them
"""
from __future__ import division
from __future__ import print_function
from timeit import timeit
from functools import partial
import itertools
import argparse
import sys
import matplotlib.pyplot as plt
import scipy.sparse as... | bsd-3-clause |
kenshay/ImageScript | ProgramData/SystemFiles/Python/Lib/site-packages/spyderlib/plugins/externalconsole.py | 2 | 64194 | # -*- coding: utf-8 -*-
#
# Copyright © 2009-2010 Pierre Raybaut
# Licensed under the terms of the MIT License
# (see spyderlib/__init__.py for details)
"""External Console plugin"""
# pylint: disable=C0103
# pylint: disable=R0903
# pylint: disable=R0911
# pylint: disable=R0201
# Qt imports
from spyderlib.qt.QtGui i... | gpl-3.0 |
mdeff/ntds_2017 | projects/reports/speech_recognition/main_pipeline.py | 1 | 13366 |
import os
from os.path import isdir, join
from pathlib import Path
import pandas as pd
from tqdm import tqdm
# Math
import numpy as np
import scipy.stats
from scipy.fftpack import fft
from scipy import signal
from scipy.io import wavfile
import librosa
import librosa.display
from scipy import sparse, stats, spatial
i... | mit |
xavierwu/scikit-learn | sklearn/utils/random.py | 234 | 10510 | # Author: Hamzeh Alsalhi <ha258@cornell.edu>
#
# License: BSD 3 clause
from __future__ import division
import numpy as np
import scipy.sparse as sp
import operator
import array
from sklearn.utils import check_random_state
from sklearn.utils.fixes import astype
from ._random import sample_without_replacement
__all__ =... | bsd-3-clause |
mjescobar/RF_Estimation | Clustering/helpers/processClusters/processClustersBin2.py | 2 | 4923 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# processClustersBin2.py
#
# Copyright 2015 Monica Otero <monicaot2011@gmail.com>
#
# This program 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; eithe... | gpl-2.0 |
kaichogami/sympy | sympy/interactive/printing.py | 19 | 16124 | """Tools for setting up printing in interactive sessions. """
from __future__ import print_function, division
import sys
from distutils.version import LooseVersion as V
from io import BytesIO
from sympy import latex as default_latex
from sympy import preview
from sympy.core.compatibility import integer_types
from sy... | bsd-3-clause |
PythonCharmers/bokeh | bokeh/charts/builder/tests/test_heatmap_builder.py | 33 | 4145 | """ This is the Bokeh charts testing interface.
"""
#-----------------------------------------------------------------------------
# Copyright (c) 2012 - 2014, Continuum Analytics, Inc. All rights reserved.
#
# Powered by the Bokeh Development Team.
#
# The full license is in the file LICENSE.txt, distributed with thi... | bsd-3-clause |
alexis-jacq/Mutual_Modelling | tools/teacher_learner_noise.py | 1 | 3735 | #!/usr/bin/env python
# coding: utf-8
import numpy as np
import random
from mutualModelling import model,agent0
import matplotlib.pyplot as plt
import copy
def create_teacher(name,all_names):
percepts = ["a","b","c"]
actions = ["a","b","c","reward","punish"]
#rewards = [["success",1.,1.],["fail",1.,-1.]]
... | isc |
luo66/scikit-learn | examples/cluster/plot_lena_ward_segmentation.py | 271 | 1998 | """
===============================================================
A demo of structured Ward hierarchical clustering on Lena image
===============================================================
Compute the segmentation of a 2D image with Ward hierarchical
clustering. The clustering is spatially constrained in order
... | bsd-3-clause |
FelixPM/Learning-Machine-Learning | sentdex/best_fit_slope.py | 1 | 2180 | """Linear Regression code
Find slope and intercept
"""
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import style
import random
style.use('fivethirtyeight')
def create_dataset(how_many_points, variance, step=2, correlation='pos'):
val = 1
ys = []
for i in range(how_many_points):
... | mit |
bavardage/statsmodels | statsmodels/sandbox/multilinear.py | 3 | 14059 | """Analyze a set of multiple variables with a linear models
multiOLS:
take a model and test it on a series of variables defined over a
pandas dataset, returning a summary for each variable
multigroup:
take a boolean vector and the definition of several groups of variables
and test if the group has a f... | bsd-3-clause |
JosmanPS/scikit-learn | sklearn/linear_model/coordinate_descent.py | 43 | 75144 | # Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Fabian Pedregosa <fabian.pedregosa@inria.fr>
# Olivier Grisel <olivier.grisel@ensta.org>
# Gael Varoquaux <gael.varoquaux@inria.fr>
#
# License: BSD 3 clause
import sys
import warnings
from abc import ABCMeta, abstractmethod
import n... | bsd-3-clause |
bucricket/projectMASpreprocess | preparepydisalexi/processLandsatLAI.py | 1 | 14392 | #!/usr/bin/env python2
#!/Applications/anaconda/envs/root3 python
# -*- coding: utf-8 -*-
"""
Created on Thu Dec 1 13:50:04 2016
@author: mschull
"""
#python
from .search import Search
import os
import subprocess
import glob
import shutil
import pandas as pd
import datetime
import argparse
import getpass
import keyr... | bsd-3-clause |
ml-ensemble/ml-ensemble.github.io | info/source/tutorials_source/parallel.py | 2 | 8200 | # -*- coding: utf-8 -*-
"""
.. _parallel_tutorial:
.. currentmodule: mlens.parallel
Parallel Mechanics
==================
ML-Ensemble is designed to provide an easy user interface. But it is also designed
to be extremely flexible, all the wile providing maximum concurrency at minimal
memory consumption. The lower-... | mit |
psav/cfme_tests | cfme/utils/smem_memory_monitor.py | 1 | 67380 | """Monitor Memory on a CFME/Miq appliance and builds report&graphs displaying usage per process."""
import json
import time
import traceback
from collections import OrderedDict
from datetime import datetime
from threading import Thread
import os
import six
import yaml
from cycler import cycler
from yaycl import AttrDi... | gpl-2.0 |
astocko/statsmodels | statsmodels/sandbox/survival2.py | 35 | 17924 | #Kaplan-Meier Estimator
import numpy as np
import numpy.linalg as la
import matplotlib.pyplot as plt
from scipy import stats
from statsmodels.iolib.table import SimpleTable
class KaplanMeier(object):
"""
KaplanMeier(...)
KaplanMeier(data, endog, exog=None, censoring=None)
Create an object of... | bsd-3-clause |
ccauet/scikit-optimize | skopt/space/transformers.py | 1 | 4631 | import numpy as np
from sklearn.preprocessing import LabelBinarizer
# Base class for all 1-D transformers.
class Transformer(object):
def fit(self, X):
return self
def transform(self, X):
raise NotImplementedError
def inverse_transform(self, X):
raise NotImplementedError
class ... | bsd-3-clause |
natasasdj/OpenWPM | analysis/15_images_zero.py | 1 | 9003 | import os
import sqlite3
import pandas as pd
import numpy as np
from matplotlib.colors import LogNorm
import matplotlib.pyplot as plt
from matplotlib.ticker import FuncFormatter
from statsmodels.distributions.empirical_distribution import ECDF
def thousands(x, pos):
if x>=1e9:
return '%dB' % (x*1e-9)
e... | gpl-3.0 |
carolFrohlich/nipype | doc/sphinxext/numpy_ext/docscrape_sphinx.py | 10 | 7922 | # -*- coding: utf-8 -*-
from __future__ import absolute_import, unicode_literals
from builtins import str, bytes
import re
import inspect
import textwrap
import pydoc
import sphinx
from .docscrape import NumpyDocString, FunctionDoc, ClassDoc
class SphinxDocString(NumpyDocString):
def __init__(self, docstring, con... | bsd-3-clause |
AlexRBaker/ScaffoldM | pwd/lib/python2.7/site-packages/scaffoldm/templateClass.py | 2 | 4971 | #!/usr/bin/env python
###############################################################################
# #
# scaffoldm.py #
# ... | gpl-3.0 |
datacommonsorg/data | scripts/biomedical/pharmgkb/drug_gene_relations/pharm.py | 1 | 23854 | # Copyright 2020 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... | apache-2.0 |
JosmanPS/scikit-learn | examples/plot_multioutput_face_completion.py | 330 | 3019 | """
==============================================
Face completion with a multi-output estimators
==============================================
This example shows the use of multi-output estimator to complete images.
The goal is to predict the lower half of a face given its upper half.
The first column of images sho... | bsd-3-clause |
ishank08/scikit-learn | examples/cluster/plot_agglomerative_clustering.py | 343 | 2931 | """
Agglomerative clustering with and without structure
===================================================
This example shows the effect of imposing a connectivity graph to capture
local structure in the data. The graph is simply the graph of 20 nearest
neighbors.
Two consequences of imposing a connectivity can be s... | bsd-3-clause |
pgdr/ert | python/python/ert_gui/plottery/plots/observations.py | 3 | 2027 | import math
def plotObservations(plot_context, axes):
ert = plot_context.ert()
key = plot_context.key()
config = plot_context.plotConfig()
case_list = plot_context.cases()
data_gatherer = plot_context.dataGatherer()
if config.isObservationsEnabled() and data_gatherer.hasObservationGatherFuncti... | gpl-3.0 |
brchiu/tensorflow | tensorflow/contrib/distributions/python/ops/mixture.py | 22 | 21121 | # Copyright 2016 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 |
thomasspiesser/MYpop | MYpop_plots.py | 1 | 13621 | #!/usr/bin/python
# -*- coding: iso-8859-1 -*-
import pylab as p
from numpy import *
from scipy import stats,polyval
import sys
import re
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import rc,cm
import mpl_toolkits.mplot3d.art3d as art3d
from matplotlib.patches import PathPatch
################ plot per... | mit |
uglyboxer/linear_neuron | net-p3/lib/python3.5/site-packages/matplotlib/tests/test_backend_pgf.py | 9 | 6311 | # -*- encoding: utf-8 -*-
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import os
import shutil
import numpy as np
import nose
from nose.plugins.skip import SkipTest
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.com... | mit |
breznak/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/mathtext.py | 69 | 101723 | r"""
:mod:`~matplotlib.mathtext` is a module for parsing a subset of the
TeX math syntax and drawing them to a matplotlib backend.
For a tutorial of its usage see :ref:`mathtext-tutorial`. This
document is primarily concerned with implementation details.
The module uses pyparsing_ to parse the TeX expression.
.. _p... | agpl-3.0 |
andaag/scikit-learn | sklearn/cluster/setup.py | 263 | 1449 | # Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# License: BSD 3 clause
import os
from os.path import join
import numpy
from sklearn._build_utils import get_blas_info
def configuration(parent_package='', top_path=None):
from numpy.distutils.misc_util import Configuration
cblas_libs, blas_info = ... | bsd-3-clause |
tdhopper/scikit-learn | sklearn/tests/test_base.py | 216 | 7045 | # Author: Gael Varoquaux
# License: BSD 3 clause
import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_false
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing impo... | bsd-3-clause |
ryandougherty/mwa-capstone | MWA_Tools/build/matplotlib/examples/pylab_examples/finance_demo.py | 6 | 1134 | #!/usr/bin/env python
from pylab import *
from matplotlib.dates import DateFormatter, WeekdayLocator, HourLocator, \
DayLocator, MONDAY
from matplotlib.finance import quotes_historical_yahoo, candlestick,\
plot_day_summary, candlestick2
# (Year, month, day) tuples suffice as args for quotes_historical_yahoo... | gpl-2.0 |
sarahgrogan/scikit-learn | sklearn/cluster/bicluster.py | 211 | 19443 | """Spectral biclustering algorithms.
Authors : Kemal Eren
License: BSD 3 clause
"""
from abc import ABCMeta, abstractmethod
import numpy as np
from scipy.sparse import dia_matrix
from scipy.sparse import issparse
from . import KMeans, MiniBatchKMeans
from ..base import BaseEstimator, BiclusterMixin
from ..external... | bsd-3-clause |
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