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 |
|---|---|---|---|---|---|
morganics/bayesianpy | bayesianpy/reader.py | 1 | 7533 | from bayesianpy.jni import bayesServer
from bayesianpy.jni import jp
import pandas as pd
import dask.dataframe as dd
import numpy as np
from typing import List
import asyncio
import logging
class Creatable:
def create(self):
pass
class CreatableWithDf:
def create(self, df:pd.DataFrame):
pass
... | apache-2.0 |
TuKo/brainiak | brainiak/fcma/mvpa_voxelselector.py | 2 | 4407 | # Copyright 2016 Intel Corporation
#
# 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... | apache-2.0 |
mugizico/scikit-learn | sklearn/cluster/tests/test_hierarchical.py | 230 | 19795 | """
Several basic tests for hierarchical clustering procedures
"""
# Authors: Vincent Michel, 2010, Gael Varoquaux 2012,
# Matteo Visconti di Oleggio Castello 2014
# License: BSD 3 clause
from tempfile import mkdtemp
import shutil
from functools import partial
import numpy as np
from scipy import sparse
from... | bsd-3-clause |
JT5D/scikit-learn | examples/ensemble/plot_adaboost_multiclass.py | 7 | 3621 | """
=====================================
Multi-class AdaBoosted Decision Trees
=====================================
This example reproduces Figure 1 of Zhu et al [1] and shows how boosting can
improve prediction accuracy on a multi-class problem. The classification
dataset is constructed by taking a ten-dimensional ... | bsd-3-clause |
mbayon/TFG-MachineLearning | venv/lib/python3.6/site-packages/pandas/core/computation/ops.py | 15 | 15900 | """Operator classes for eval.
"""
import operator as op
from functools import partial
from datetime import datetime
import numpy as np
from pandas.core.dtypes.common import is_list_like, is_scalar
import pandas as pd
from pandas.compat import PY3, string_types, text_type
import pandas.core.common as com
from pandas.... | mit |
tverbrug/openWEC | Run/openWEC_WS.py | 1 | 76610 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'openWECv2.ui'
#
# Created: Wed May 06 10:39:04 2015
# by: PyQt4 UI code generator 4.9.6
#
# WARNING! All changes made in this file will be lost!
from PyQt4 import QtCore, QtGui
from matplotlib.backends import qt_compat
from matplotlib... | gpl-3.0 |
AnasGhrab/scikit-learn | sklearn/ensemble/partial_dependence.py | 251 | 15097 | """Partial dependence plots for tree ensembles. """
# Authors: Peter Prettenhofer
# License: BSD 3 clause
from itertools import count
import numbers
import numpy as np
from scipy.stats.mstats import mquantiles
from ..utils.extmath import cartesian
from ..externals.joblib import Parallel, delayed
from ..externals im... | bsd-3-clause |
paris-saclay-cds/ramp-workflow | rampwf/utils/scoring.py | 1 | 5037 | # coding: utf-8
"""
Scoring utilities
"""
import numpy as np
import pandas as pd
from .pretty_print import IS_COLOR_TERM
from .pretty_print import print_warning
def reorder_df_scores(df_scores, score_types):
"""Reorder scores according to the order in score_types.
Parameters
----------
df_scores : p... | bsd-3-clause |
taotaocoule/stock | spider/data/stock_flow.py | 1 | 3578 | # 个股净流入:http://nufm.dfcfw.com/EM_Finance2014NumericApplication/JS.aspx/JS.aspx?type=ct&st=(FFRank)&sr=1&p=1&ps=10000&js=[(x)]&token=894050c76af8597a853f5b408b759f5d&cmd=C._AB&sty=DCFFITAM&rt=50602335
# 板块净流入
import urllib.request
import pandas as pd
import json
class Stock_Flow(object):
"""docstring for Stoc... | mit |
IntelPNI/brainiak | brainiak/factoranalysis/tfa.py | 7 | 30560 | # Copyright 2016 Intel Corporation
#
# 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... | apache-2.0 |
aewhatley/scikit-learn | examples/linear_model/plot_logistic_path.py | 349 | 1195 | #!/usr/bin/env python
"""
=================================
Path with L1- Logistic Regression
=================================
Computes path on IRIS dataset.
"""
print(__doc__)
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# License: BSD 3 clause
from datetime import datetime
import numpy as np
import... | bsd-3-clause |
karstenw/nodebox-pyobjc | examples/Extended Application/matplotlib/examples/statistics/boxplot_demo.py | 1 | 8516 | """
========
Boxplots
========
Visualizing boxplots with matplotlib.
The following examples show off how to visualize boxplots with
Matplotlib. There are many options to control their appearance and
the statistics that they use to summarize the data.
"""
import matplotlib.pyplot as plt
import numpy as np
from matplo... | mit |
hadim/spindle_tracker | spindle_tracker/tracker/cost_function/brownian.py | 2 | 4804 |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from __future__ import division
from __future__ import absolute_import
from __future__ import print_function
import numpy as np
import pandas as pd
from scipy.spatial.distance import cdist
from . import AbstractCostFunction
from .gap_close import Abs... | bsd-3-clause |
phenopolis/phenopolis | views/__init__.py | 3 | 59475 | #flask import
from flask import Flask
from flask import session
from flask.ext.session import Session
from flask import Response
from flask import stream_with_context
from flask import request
from flask import make_response
from flask import request
from flask import send_file
from flask import g
from flask import red... | mit |
ywcui1990/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/delaunay/testfuncs.py | 72 | 20890 | """Some test functions for bivariate interpolation.
Most of these have been yoinked from ACM TOMS 792.
http://netlib.org/toms/792
"""
import numpy as np
from triangulate import Triangulation
class TestData(dict):
def __init__(self, *args, **kwds):
dict.__init__(self, *args, **kwds)
self.__dict__ ... | agpl-3.0 |
skuschel/postpic | examples/kspace-test-2d.py | 1 | 9839 | #!/usr/bin/env python
# coding: utf-8
# In[1]:
import sys
def download(url, file):
import urllib3
import shutil
import os
if os.path.isfile(file):
return True
try:
urllib3.disable_warnings()
http = urllib3.PoolManager()
print('downloading {:} ...'.format(file))
... | gpl-3.0 |
LiuVII/Machine_learning_and_AI | Sentiment_Analysis/cnn.py | 1 | 7322 | # Code based on source: https://github.com/dennybritz/cnn-text-classification-tf
from __future__ import print_function
import tensorflow as tf
from tensorflow.contrib import learn
import pandas as pd
import numpy as np
import math
import time
import os
import datetime
import data_helpers
from sklearn.metrics import a... | mit |
mjirik/imtools | imtools/uiThreshold.py | 1 | 29690 | # -*- coding: utf-8 -*-
"""
Purpose: (CZE-ZCU-FAV-KKY) Liver medical project
Author: Pavel Volkovinsky, Miroslav Jirik
Email: volkovinsky.pavel@gmail.com
Created: 2012/11/08
Copyright: (c) Pavel Volkovinsky
"""
import sys
sys.path.append("../src/")
sys.path.append("../extern/")
import loggin... | mit |
googledatalab/pydatalab | tests/ml/summary_tests.py | 2 | 3980 | # Copyright 2017 Google Inc. 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 applicable law or agreed ... | apache-2.0 |
metatier/kaggle-titanic | KaggleAux/predict.py | 6 | 3114 | import numpy as np
from pandas import DataFrame
from patsy import dmatrices
def get_dataframe_intersection(df, comparator1, comparator2):
"""
Return a dataframe with only the columns found in a comparative dataframe.
Parameters
----------
comparator1: DataFrame
DataFrame to preform compar... | apache-2.0 |
robintw/scikit-image | doc/examples/plot_line_hough_transform.py | 14 | 4465 | r"""
=============================
Straight line Hough transform
=============================
The Hough transform in its simplest form is a `method to detect straight lines
<http://en.wikipedia.org/wiki/Hough_transform>`__.
In the following example, we construct an image with a line intersection. We
then use the Ho... | bsd-3-clause |
mbayon/TFG-MachineLearning | venv/lib/python3.6/site-packages/sklearn/mixture/tests/test_gmm.py | 44 | 20880 | # Important note for the deprecation cleaning of 0.20 :
# All the functions and classes of this file have been deprecated in 0.18.
# When you remove this file please remove the related files
# - 'sklearn/mixture/dpgmm.py'
# - 'sklearn/mixture/gmm.py'
# - 'sklearn/mixture/test_dpgmm.py'
import unittest
import copy
impor... | mit |
sebotic/WikidataIntegrator | wikidataintegrator/wdi_core.py | 1 | 157222 | import copy
import datetime
import json
import logging
import os
import re
import time
import warnings
from collections import defaultdict
from typing import List
import pandas as pd
import requests
from pyshex import ShExEvaluator
from rdflib import Graph
from shexer.shaper import Shaper
from wikidataintegrator.wdi_... | agpl-3.0 |
wilsonkichoi/zipline | zipline/protocol.py | 3 | 4172 | #
# Copyright 2013 Quantopian, Inc.
#
# 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 wr... | apache-2.0 |
cybernet14/scikit-learn | examples/svm/plot_svm_kernels.py | 329 | 1971 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
SVM-Kernels
=========================================================
Three different types of SVM-Kernels are displayed below.
The polynomial and RBF are especially useful when the
data-points are not linearly sep... | bsd-3-clause |
Reagankm/KnockKnock | venv/lib/python3.4/site-packages/mpl_toolkits/mplot3d/art3d.py | 8 | 23462 | #!/usr/bin/python
# art3d.py, original mplot3d version by John Porter
# Parts rewritten by Reinier Heeres <reinier@heeres.eu>
# Minor additions by Ben Axelrod <baxelrod@coroware.com>
'''
Module containing 3D artist code and functions to convert 2D
artists into 3D versions which can be added to an Axes3D.
'''
from __fu... | gpl-2.0 |
pianomania/scikit-learn | sklearn/utils/tests/test_murmurhash.py | 79 | 2849 | # Author: Olivier Grisel <olivier.grisel@ensta.org>
#
# License: BSD 3 clause
import numpy as np
from sklearn.externals.six import b, u
from sklearn.utils.murmurhash import murmurhash3_32
from numpy.testing import assert_array_almost_equal
from numpy.testing import assert_array_equal
from sklearn.utils.testing import ... | bsd-3-clause |
inclement/vispy | examples/basics/plotting/mpl_plot.py | 14 | 1579 | # -*- coding: utf-8 -*-
# vispy: testskip
# -----------------------------------------------------------------------------
# Copyright (c) 2015, Vispy Development Team.
# Distributed under the (new) BSD License. See LICENSE.txt for more info.
# ----------------------------------------------------------------------------... | bsd-3-clause |
GuessWhoSamFoo/pandas | pandas/tests/groupby/test_function.py | 1 | 38953 | from string import ascii_lowercase
import numpy as np
import pytest
from pandas.compat import product as cart_product
from pandas.errors import UnsupportedFunctionCall
import pandas as pd
from pandas import (
DataFrame, Index, MultiIndex, Series, Timestamp, compat, date_range, isna)
import pandas.core.nanops as ... | bsd-3-clause |
ii0/pybrain | pybrain/tools/neuralnets.py | 26 | 13763 | # Neural network data analysis tool collection. Makes heavy use of the logging module.
# Can generate training curves during the run (from properly setup IPython and/or with
# TkAgg backend and interactive mode - see matplotlib documentation).
__author__ = "Martin Felder"
__version__ = "$Id$"
from pylab import ion, fi... | bsd-3-clause |
arokem/scipy | scipy/signal/_arraytools.py | 2 | 7555 | """
Functions for acting on a axis of an array.
"""
from __future__ import division, print_function, absolute_import
import numpy as np
def axis_slice(a, start=None, stop=None, step=None, axis=-1):
"""Take a slice along axis 'axis' from 'a'.
Parameters
----------
a : numpy.ndarray
The array ... | bsd-3-clause |
zingale/pyro2 | examples/multigrid/mg_test_vc_constant.py | 1 | 3887 | #!/usr/bin/env python3
"""
Test the variable coefficient MG solver with a CONSTANT coefficient
problem -- the same one from the multigrid class test. This ensures
we didn't screw up the base functionality here.
We solve::
u_xx + u_yy = -2[(1-6x**2)y**2(1-y**2) + (1-6y**2)x**2(1-x**2)]
u = 0 on the boundary
... | bsd-3-clause |
18padx08/PPTex | PPTexEnv_x86_64/lib/python2.7/site-packages/matplotlib/testing/jpl_units/StrConverter.py | 23 | 5293 | #===========================================================================
#
# StrConverter
#
#===========================================================================
"""StrConverter module containing class StrConverter."""
#===========================================================================
# Place al... | mit |
russel1237/scikit-learn | sklearn/neighbors/tests/test_ball_tree.py | 159 | 10196 | 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... | bsd-3-clause |
chibbargroup/CentralRepository | FLOURescence/Source/Plotter.py | 2 | 4165 | import pandas as pd
import numpy as np
from os import listdir, mkdir
from os.path import isfile, join, isdir, split, dirname
import matplotlib.pyplot as plt
#Rename the headers for all the files
def Rename_Spectra_Labels (spectra_dir, header_file):
print("Working...one moment please")
header = pd.read_csv(header_fil... | mit |
DmitryOdinoky/sms-tools | lectures/07-Sinusoidal-plus-residual-model/plots-code/LPC.py | 24 | 1191 | import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import hamming, hanning, triang, blackmanharris, resample
import math
import sys, os, time
from scipy.fftpack import fft, ifft
import essentia.standard as ess
sys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)), '../../../softwar... | agpl-3.0 |
ecatkins/data | us-weather-history/visualize_weather.py | 36 | 4799 | import matplotlib.pyplot as plt
import pandas as pd
from datetime import datetime
'''
This is an example to generate the Philadelphia, PA weather chart.
If you want to make the chart for another city, you will have to modify
this code slightly to read that city's data in, change the title, and
likely change the y-axi... | mit |
michelrobijns/vortexpanelmethod | vpm.py | 1 | 5903 | #!/usr/bin/python3
""" vpm.py
Created: 12/28/2014
Author: Michel Robijns
This file is part of vortexpanelmethod which is released under the MIT license.
See the file LICENSE or go to http://opensource.org/licenses/MIT for full
license details.
TODO: Add description
"""
from math import *
import numpy as np
import ... | mit |
stylianos-kampakis/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 |
jonyroda97/redbot-amigosprovaveis | lib/matplotlib/axis.py | 2 | 85455 | """
Classes for the ticks and x and y axis
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from matplotlib import rcParams
import matplotlib.artist as artist
from matplotlib.artist import allow_rasterization
import matplotlib.cbook as cbook
f... | gpl-3.0 |
rseubert/scikit-learn | sklearn/manifold/isomap.py | 36 | 7119 | """Isomap for manifold learning"""
# Author: Jake Vanderplas -- <vanderplas@astro.washington.edu>
# License: BSD 3 clause (C) 2011
import numpy as np
from ..base import BaseEstimator, TransformerMixin
from ..neighbors import NearestNeighbors, kneighbors_graph
from ..utils import check_array
from ..utils.graph import... | bsd-3-clause |
akshayparopkari/phylotoast | bin/core_overlap_plot.py | 2 | 11734 | #!/usr/bin/env python
# coding: utf-8
"""
Given a set of core microbiome files, create a matching set of ovelapping
barplots that visualize which species belong to each core microbiome.
"""
from __future__ import absolute_import, division, print_function
import ast
import argparse
from collections import Counter, Orde... | mit |
pochoi/SHTOOLS | examples/python/ClassInterface/WindowExample.py | 2 | 1379 | #!/usr/bin/env python
"""
This script tests the python class interface
"""
from __future__ import division
from __future__ import print_function
# standard imports:
import os
import sys
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
# import shtools:
sys.path.append(os.path.join(os.path.... | bsd-3-clause |
devs1991/test_edx_docmode | venv/lib/python2.7/site-packages/sklearn/preprocessing.py | 2 | 29089 | # Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Mathieu Blondel <mathieu@mblondel.org>
# Olivier Grisel <olivier.grisel@ensta.org>
# License: BSD
from collections import Sequence
import numpy as np
import scipy.sparse as sp
from .utils import check_arrays, array2d
from .utils import wa... | agpl-3.0 |
fyffyt/scikit-learn | examples/linear_model/plot_ols.py | 220 | 1940 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Linear Regression Example
=========================================================
This example uses the only the first feature of the `diabetes` dataset, in
order to illustrate a two-dimensional plot of this regre... | bsd-3-clause |
thouska/spotpy | spotpy/examples/dds/__init__.py | 10 | 1478 | # -*- coding: utf-8 -*-
'''
Copyright (c) 2015 by Tobias Houska
This file is part of Statistical Parameter Estimation Tool (SPOTPY).
:author: Tobias Houska
:paper: Houska, T., Kraft, P., Chamorro-Chavez, A. and Breuer, L.:
SPOTting Model Parameters Using a Ready-Made Python Package,
PLoS ONE, 10(12), e0145180, doi:... | mit |
tkerola/chainer | examples/glance/glance.py | 8 | 2876 | # Note for contributors:
# This example code is referred to from "Chainer at a Glance" tutorial.
# If this file is to be modified, please also update the line numbers in
# `docs/source/glance.rst` accordingly.
import chainer as ch
from chainer import datasets
import chainer.functions as F
import chainer.links as L
fro... | mit |
ibm-cds-labs/pixiedust | pixiedust/display/app/pixieapp.py | 1 | 22966 | # -------------------------------------------------------------------------------
# Copyright IBM Corp. 2017
#
# 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/licens... | apache-2.0 |
0x0all/nupic | examples/opf/tools/sp_plotter.py | 8 | 15763 | #! /usr/bin/env python
# ----------------------------------------------------------------------
# Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2013, Numenta, Inc. Unless you have an agreement
# with Numenta, Inc., for a separate license for this software code, the
# following terms and conditions... | gpl-3.0 |
BanditCat/tfstocks | emnist.py | 1 | 10133 | #antialias graph
import getsdata
DIM = getsdata.DIM
TRAIN_DIR = "/home/banditcat/tfmuse/train/"
TRAIN_FILE = "t"
STOCK_DIR = getsdata.STOCK_DIR
PATCH_SIZE = 5
L1_FEATURES = 32
L2_FEATURES = 64
DENSE_FEATURES = 1024
BATCH_SIZE = 50
STEPS = 15
NUM_STOCKS = 3
GOOD_TICKER_THRESHHOLD = 0
BAD_TICKER_THRESHHOLD = -1
POINT... | apache-2.0 |
bnaul/scikit-learn | examples/linear_model/plot_sgd_separating_hyperplane.py | 23 | 1223 | """
=========================================
SGD: Maximum margin separating hyperplane
=========================================
Plot the maximum margin separating hyperplane within a two-class
separable dataset using a linear Support Vector Machines classifier
trained using SGD.
"""
print(__doc__)
import numpy as n... | bsd-3-clause |
benoitsteiner/tensorflow-opencl | tensorflow/examples/learn/text_classification.py | 8 | 6685 | # 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 |
lbishal/scikit-learn | sklearn/metrics/tests/test_regression.py | 272 | 6066 | from __future__ import division, print_function
import numpy as np
from itertools import product
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.... | bsd-3-clause |
daniestevez/jupyter_notebooks | dslwp/demtrack.py | 1 | 7938 | #!/usr/bin/env python3
import numpy as np
import matplotlib.pyplot as plt
import xarray
from astropy.time import Time
import astropy.io
import pymap3d
import datetime
from pandas.plotting import register_matplotlib_converters
register_matplotlib_converters()
# Digital elevation model (DEM) available at http://pds-ge... | gpl-3.0 |
blink1073/scikit-image | doc/examples/edges/plot_contours.py | 30 | 1247 | """
===============
Contour finding
===============
``skimage.measure.find_contours`` uses a marching squares method to find
constant valued contours in an image. Array values are linearly interpolated
to provide better precision of the output contours. Contours which intersect
the image edge are open; all others ar... | bsd-3-clause |
Horta/limix | limix/stats/_pca.py | 1 | 1401 | # TODO: normalise this documentation
def pca(X, ncomp):
r"""Principal component analysis.
Parameters
----------
X : array_like
Data.
ncomp : int
Number of components.
Returns
-------
dict
- **components** (*array_like*):
first components ordered by exp... | apache-2.0 |
swharden/SWHLab | doc/uses/EPSCs-and-IPSCs/smooth histogram method/10.py | 1 | 3441 | """
MOST OF THIS CODE IS NOT USED
ITS COPY/PASTED AND LEFT HERE FOR CONVENIENCE
"""
import os
import sys
# in case our module isn't installed (running from this folder)
if not os.path.abspath('../../../') in sys.path:
sys.path.append('../../../') # helps spyder get docs
import swhlab
import swhlab.common as cm
i... | mit |
dlebauer/plantcv | lib/plantcv/fluor_fvfm.py | 1 | 6264 | ### Fluorescence Analysis
import os
import cv2
import numpy as np
import matplotlib
#if not os.getenv('DISPLAY'):
# matplotlib.use('Agg')
from matplotlib import pyplot as plt
from matplotlib import cm as cm
from matplotlib import colors as colors
from matplotlib import colorbar as colorbar
import pylab as pl
from . i... | gpl-2.0 |
alexanian/uwaterloo-igem-2015 | models/targeting/genome_simulation.py | 4 | 8108 | import datetime
import matplotlib.pyplot as plt
import os
import random
import make_video
from genome_csv import results_to_csv, csv_to_dict, map_genome_events, map_target_events
from genome_plot import genome_plot_polar, plot_states
from init_genome_camv import init_genome_camv, init_targets_all_domains, init_targets... | mit |
idlead/scikit-learn | examples/ensemble/plot_gradient_boosting_quantile.py | 392 | 2114 | """
=====================================================
Prediction Intervals for Gradient Boosting Regression
=====================================================
This example shows how quantile regression can be used
to create prediction intervals.
"""
import numpy as np
import matplotlib.pyplot as plt
from skle... | bsd-3-clause |
arabenjamin/scikit-learn | sklearn/semi_supervised/label_propagation.py | 128 | 15312 | # coding=utf8
"""
Label propagation in the context of this module refers to a set of
semisupervised classification algorithms. In the high level, these algorithms
work by forming a fully-connected graph between all points given and solving
for the steady-state distribution of labels at each point.
These algorithms per... | bsd-3-clause |
olologin/scikit-learn | benchmarks/bench_mnist.py | 44 | 6801 | """
=======================
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 |
gfyoung/pandas | pandas/core/dtypes/base.py | 1 | 13214 | """
Extend pandas with custom array types.
"""
from __future__ import annotations
from typing import TYPE_CHECKING, Any, List, Optional, Tuple, Type, Union
import numpy as np
from pandas._typing import DtypeObj
from pandas.errors import AbstractMethodError
from pandas.core.dtypes.generic import ABCDataFrame, ABCIn... | bsd-3-clause |
gfyoung/pandas | pandas/tests/tseries/offsets/test_business_day.py | 1 | 14564 | """
Tests for offsets.BDay
"""
from datetime import date, datetime, timedelta
import numpy as np
import pytest
from pandas._libs.tslibs.offsets import ApplyTypeError, BDay, BMonthEnd, CDay
from pandas.compat import np_datetime64_compat
from pandas import DatetimeIndex, _testing as tm, read_pickle
from pandas.tests.t... | bsd-3-clause |
mikebenfield/scikit-learn | sklearn/ensemble/tests/test_forest.py | 9 | 43013 | """
Testing for the forest module (sklearn.ensemble.forest).
"""
# Authors: Gilles Louppe,
# Brian Holt,
# Andreas Mueller,
# Arnaud Joly
# License: BSD 3 clause
import pickle
from collections import defaultdict
from itertools import combinations
from itertools import product
import numpy ... | bsd-3-clause |
leppa/home-assistant | homeassistant/components/smappee/__init__.py | 3 | 12173 | """Support for Smappee energy monitor."""
from datetime import datetime, timedelta
import logging
import re
from requests.exceptions import RequestException
import smappy
import voluptuous as vol
from homeassistant.const import CONF_HOST, CONF_PASSWORD, CONF_USERNAME
import homeassistant.helpers.config_validation as ... | apache-2.0 |
edmunoz/aed | proyecto_aed_fb/create_graph.py | 1 | 3757 | import MySQLdb as mdb
import networkx as nx
import matplotlib.pyplot as plt
import community
def connect_db():
connection = mdb.connect('108.167.133.34', 'connie_usr_aed', 'SK5CTTs8zXV9', 'connie_facebook')
return connection
def get_cursor(connect):
cursor = connect.cursor()
return cursor
def get_... | apache-2.0 |
laurent-george/bokeh | bokeh/compat/bokeh_renderer.py | 6 | 16979 | "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 |
kdebrab/pandas | pandas/tests/frame/test_repr_info.py | 6 | 17679 | # -*- coding: utf-8 -*-
from __future__ import print_function
from datetime import datetime, timedelta
import re
import sys
import textwrap
from numpy import nan
import numpy as np
import pytest
from pandas import (DataFrame, Series, compat, option_context,
date_range, period_range, Categorical)... | bsd-3-clause |
DonBeo/statsmodels | statsmodels/examples/ex_generic_mle.py | 32 | 16462 |
from __future__ import print_function
import numpy as np
from scipy import stats
import statsmodels.api as sm
from statsmodels.base.model import GenericLikelihoodModel
data = sm.datasets.spector.load()
data.exog = sm.add_constant(data.exog, prepend=False)
# in this dir
probit_mod = sm.Probit(data.endog, data.exog)
... | bsd-3-clause |
lhilt/scipy | scipy/fft/_basic.py | 2 | 54035 | from scipy._lib.uarray import generate_multimethod, Dispatchable
import numpy as np
def _x_replacer(args, kwargs, dispatchables):
"""
uarray argument replacer to replace the transform input array (``x``)
"""
if len(args) > 0:
return (dispatchables[0],) + args[1:], kwargs
kw = kwargs.copy()... | bsd-3-clause |
binghongcha08/pyQMD | QMC/MC_exchange/permute4d/dissipation/5.0/en.py | 15 | 1291 | import numpy as np
import pylab as plt
import matplotlib.pyplot as plt
import matplotlib as mpl
#data = np.genfromtxt(fname='/home/bing/dissipation/energy.dat')
data = np.genfromtxt(fname='energy.dat')
fig, (ax1,ax2) = plt.subplots(ncols=1, nrows=2, sharex=True)
#font = {'family' : 'ubuntu',
# 'weight' : ... | gpl-3.0 |
ephes/scikit-learn | sklearn/utils/metaestimators.py | 283 | 2353 | """Utilities for meta-estimators"""
# Author: Joel Nothman
# Andreas Mueller
# Licence: BSD
from operator import attrgetter
from functools import update_wrapper
__all__ = ['if_delegate_has_method']
class _IffHasAttrDescriptor(object):
"""Implements a conditional property using the descriptor protocol.
... | bsd-3-clause |
zehpunktbarron/iOSMAnalyzer | scripts/c5_tag_completeness_accom.py | 1 | 12548 | # -*- coding: utf-8 -*-
#!/usr/bin/python2.7
#description :This file creates a plot: Calculates the development of the tag-completeness [%] of all "accomodation & gastronomy" POIs
#author :Christopher Barron @ http://giscience.uni-hd.de/
#date :19.01.2013
#version :0.1
#usage ... | gpl-3.0 |
argentumproject/electrum-arg | plugins/plot/qt.py | 1 | 3557 | from PyQt4.QtGui import *
from electrum_arg.plugins import BasePlugin, hook
from electrum_arg.i18n import _
import datetime
from electrum_arg.util import format_satoshis
from electrum_arg.bitcoin import COIN
try:
import matplotlib.pyplot as plt
import matplotlib.dates as md
from matplotlib.patches import... | mit |
billy-inn/scikit-learn | sklearn/utils/tests/test_murmurhash.py | 261 | 2836 | # Author: Olivier Grisel <olivier.grisel@ensta.org>
#
# License: BSD 3 clause
import numpy as np
from sklearn.externals.six import b, u
from sklearn.utils.murmurhash import murmurhash3_32
from numpy.testing import assert_array_almost_equal
from numpy.testing import assert_array_equal
from nose.tools import assert_equa... | bsd-3-clause |
huobaowangxi/scikit-learn | sklearn/datasets/svmlight_format.py | 114 | 15826 | """This module implements a loader and dumper for the svmlight format
This format is a text-based format, with one sample per line. It does
not store zero valued features hence is suitable for sparse dataset.
The first element of each line can be used to store a target variable to
predict.
This format is used as the... | bsd-3-clause |
antgonza/qiime | qiime/make_2d_plots.py | 6 | 23462 | #!/usr/bin/env python
# File created on 09 Feb 2010
# file make_2d_plots.py
__author__ = "Jesse Stombaugh and Micah Hamady"
__copyright__ = "Copyright 2011, The QIIME Project"
# remember to add yourself
__credits__ = ["Jesse Stombaugh", "Jose Antonio Navas Molina"]
__license__ = "GPL"
__version__ = "1.9.1-dev"
__maint... | gpl-2.0 |
antoinecarme/pyaf | tests/bugs/issue_106/insurance_exog.py | 1 | 1208 | import numpy as np
import pandas as pd
import pyaf.ForecastEngine as autof
# example from https://otexts.org/fpp2/lagged-predictors.html
df = pd.read_csv("https://raw.githubusercontent.com/antoinecarme/TimeSeriesData/master/fpp2/insurance.csv")
df.info()
(lTimeVar , lSigVar , lExogVar) = ("Index", "Quotes" , "TV.adv... | bsd-3-clause |
alexchao56/sklearn-theano | sklearn_theano/datasets/asirra.py | 8 | 2952 | """Dataset loading utilities for asirra dataset."""
# Authors: Kyle Kastner
# License: BSD 3 Clause
import os
import numpy as np
from PIL import Image
import tarfile
from glob import glob
from sklearn.externals.joblib import Memory
from sklearn.datasets.base import Bunch
from .base import download, get_dataset_dir
... | bsd-3-clause |
donlnz/nonconformist | setup.py | 1 | 1178 | #!/usr/bin/env python
from distutils.core import setup
import nonconformist
setup(
name = 'nonconformist',
packages = ['nonconformist'],
version = nonconformist.__version__,
description = 'Python implementation of the conformal prediction framework.',
author = 'Henrik Linusson',
author_email = 'henrik.linusson@... | mit |
maropu/spark | python/pyspark/sql/tests/test_dataframe.py | 4 | 41251 | #
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not us... | apache-2.0 |
alisidd/tensorflow | tensorflow/examples/learn/text_classification_character_cnn.py | 30 | 4292 | # 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 |
IssamLaradji/scikit-learn | sklearn/linear_model/tests/test_logistic.py | 19 | 22876 | import numpy as np
import scipy.sparse as sp
from scipy import linalg, optimize, sparse
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 sklearn.util... | bsd-3-clause |
paladin74/neural-network-animation | matplotlib/_cm.py | 15 | 94005 | """
Nothing here but dictionaries for generating LinearSegmentedColormaps,
and a dictionary of these dictionaries.
Documentation for each is in pyplot.colormaps()
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import numpy as np
_binary_data = {
... | mit |
ishay2b/tensorflow | tensorflow/contrib/learn/python/learn/estimators/__init__.py | 34 | 12484 | # 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 |
ZENGXH/scikit-learn | examples/exercises/plot_cv_digits.py | 232 | 1206 | """
=============================================
Cross-validation on Digits Dataset Exercise
=============================================
A tutorial exercise using Cross-validation with an SVM on the Digits dataset.
This exercise is used in the :ref:`cv_generators_tut` part of the
:ref:`model_selection_tut` section... | bsd-3-clause |
bnaul/scikit-learn | sklearn/datasets/_species_distributions.py | 11 | 8726 | """
=============================
Species distribution dataset
=============================
This dataset represents the geographic distribution of species.
The dataset is provided by Phillips et. al. (2006).
The two species are:
- `"Bradypus variegatus"
<http://www.iucnredlist.org/details/3038/0>`_ ,
the Bro... | bsd-3-clause |
darshanthaker/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/backends/backend_gtk.py | 69 | 43991 | from __future__ import division
import os, sys
def fn_name(): return sys._getframe(1).f_code.co_name
try:
import gobject
import gtk; gdk = gtk.gdk
import pango
except ImportError:
raise ImportError("Gtk* backend requires pygtk to be installed.")
pygtk_version_required = (2,2,0)
if gtk.pygtk_version <... | agpl-3.0 |
yavalvas/yav_com | build/matplotlib/lib/mpl_examples/pylab_examples/demo_text_path.py | 9 | 4470 |
# -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
from matplotlib.image import BboxImage
import numpy as np
from matplotlib.transforms import IdentityTransform
import matplotlib.patches as mpatches
from matplotlib.offsetbox import AnnotationBbox,\
AnchoredOffsetbox, AuxTransformBox
from matplotlib.cbook... | mit |
arokem/scipy | scipy/integrate/quadrature.py | 1 | 31441 | from __future__ import division, print_function, absolute_import
import functools
import numpy as np
import math
import types
import warnings
# trapz is a public function for scipy.integrate,
# even though it's actually a NumPy function.
from numpy import trapz
from scipy.special import roots_legendre
from scipy.spec... | bsd-3-clause |
ben-hopps/nupic | examples/opf/clients/hotgym/prediction/one_gym/nupic_output.py | 32 | 6059 | # ----------------------------------------------------------------------
# Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2013, 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 |
fengzhyuan/scikit-learn | examples/model_selection/plot_roc_crossval.py | 247 | 3253 | """
=============================================================
Receiver Operating Characteristic (ROC) with cross validation
=============================================================
Example of Receiver Operating Characteristic (ROC) metric to evaluate
classifier output quality using cross-validation.
ROC curv... | bsd-3-clause |
mlhhu2017/identifyDigit | r.weishaupt/mnist_utils.py | 1 | 4405 | # Import required packages
import numpy as np;
import idx2numpy as idx;
import matplotlib.pyplot as plt;
def loadset(data, labels):
""" Loads data and labels from given paths.
Arguments:
data [string] -- Path to data file
labels [string] -- Path to labels file
Return:
[2-tuple:np.... | mit |
saiwing-yeung/scikit-learn | examples/ensemble/plot_voting_probas.py | 316 | 2824 | """
===========================================================
Plot class probabilities calculated by the VotingClassifier
===========================================================
Plot the class probabilities of the first sample in a toy dataset
predicted by three different classifiers and averaged by the
`VotingC... | bsd-3-clause |
mkery/CS349-roads | tripmatching/rdp_trip.py | 1 | 4074 | import numpy as np
import sys
import matplotlib.pyplot as pyplot
"""
edited 4/25 to fit trip default numpy format
If you import a trip and then add a 3rd column to the trip that is time,
when this runs the time field is kept... a bit hacky but works.
"""
def distance(x0, y0, x1, y1):
return ((x1-x0)**2 + (y1-y0)*... | mit |
iismd17/scikit-learn | benchmarks/bench_20newsgroups.py | 377 | 3555 | from __future__ import print_function, division
from time import time
import argparse
import numpy as np
from sklearn.dummy import DummyClassifier
from sklearn.datasets import fetch_20newsgroups_vectorized
from sklearn.metrics import accuracy_score
from sklearn.utils.validation import check_array
from sklearn.ensemb... | bsd-3-clause |
joplen/svgplotlib | svgplotlib/TEX/Model.py | 2 | 29467 | #!/usr/bin/python
# -*- coding: utf-8 -*-
# TeX-LIKE BOX MODEL
# The following is based directly on the document 'woven' from the
# TeX82 source code. This information is also available in printed
# form:
#
# Knuth, Donald E.. 1986. Computers and Typesetting, Volume B:
# TeX: The Program. Addison-Wesley Profes... | bsd-3-clause |
LangmuirSim/langmuir | LangmuirPython/analyze/gather.py | 2 | 2521 | # -*- coding: utf-8 -*-
"""
gather.py
=========
.. argparse::
:module: gather
:func: create_parser
:prog: gather.py
.. moduleauthor:: Adam Gagorik <adam.gagorik@gmail.com>
"""
import langmuir as lm
import pandas as pd
import itertools
import argparse
import os
desc = """
Gather the output of a series of ... | gpl-2.0 |
ActiveState/code | recipes/Python/578242_Artificial_Neuroglial_Network_ANGN_/recipe-578242.py | 1 | 29104 | from operator import itemgetter, attrgetter
import math
from math import copysign
from random import *
import timeit
from timeit import Timer as t
from matplotlib.pyplot import *
from numpy import *
def sigmoid (x):
return math.tanh(x)
class NN:
# ni,nh,no = n of input (i), hidden (h) and output (o) nodes
# ai,... | mit |
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