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 |
|---|---|---|---|---|---|
zachcp/qiime | qiime/make_otu_heatmap.py | 15 | 7171 | from __future__ import division
__author__ = "Dan Knights"
__copyright__ = "Copyright 2011, The QIIME project"
__credits__ = ["Dan Knights", "Greg Caporaso", "Jai Ram Rideout"]
__license__ = "GPL"
__version__ = "1.9.1-dev"
__maintainer__ = "Dan Knights"
__email__ = "daniel.knights@colorado.edu"
import numpy as np
imp... | gpl-2.0 |
mne-tools/mne-python | mne/annotations.py | 1 | 51935 | # Authors: Jaakko Leppakangas <jaeilepp@student.jyu.fi>
# Robert Luke <mail@robertluke.net>
#
# License: BSD (3-clause)
from collections import OrderedDict
from datetime import datetime, timedelta, timezone
import os.path as op
import re
from copy import deepcopy
from itertools import takewhile
import json
fr... | bsd-3-clause |
jinified/selam | examples/preprocess_data.py | 1 | 2719 | #!/usr/bin/env python
""" Explore different preprocessing transformation on data before training """
import cv2
import numpy as np
from selam.utils import img
from sklearn import pipeline
from sklearn.preprocessing import MinMaxScaler, StandardScaler, scale
def incrementalPreprocesser(data, method, batch_size=3):
... | mit |
TNT-Samuel/Coding-Projects | DNS Server/Source/Lib/site-packages/dask/dataframe/tests/test_multi.py | 2 | 50298 | import dask.dataframe as dd
import numpy as np
import pandas as pd
import pandas.util.testing as tm
from dask.base import compute_as_if_collection
from dask.dataframe.core import _Frame
from dask.dataframe.methods import concat
from dask.dataframe.multi import (align_partitions, merge_indexed_dataframes,
... | gpl-3.0 |
ashwinpathak20/ashwinpathak20.github.io | markdown_generator/publications.py | 197 | 3887 |
# coding: utf-8
# # Publications markdown generator for academicpages
#
# Takes a TSV of publications with metadata and converts them for use with [academicpages.github.io](academicpages.github.io). This is an interactive Jupyter notebook, with the core python code in publications.py. Run either from the `markdown_g... | mit |
meee1/ardupilot | Tools/FilterTestTool/FilterTest.py | 30 | 22307 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
""" ArduPilot IMU Filter Test Class
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
versi... | gpl-3.0 |
erikness/AlephOne | zipline/examples/pairtrade.py | 11 | 4925 | #!/usr/bin/env python
#
# 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 ... | apache-2.0 |
jakobworldpeace/scikit-learn | sklearn/linear_model/tests/test_sgd.py | 34 | 47824 | import pickle
import unittest
import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_greater
from sklearn.utils.testing ... | bsd-3-clause |
paulscherrerinstitute/pshell | src/main/assembly/help/Tutorial_py/5_Utils/57_EmbedingCPython.py | 1 | 2502 | ###################################################################################################
# Embedding CPython with JEP: USe of numpy, pandas and matpplotlib in the same process.
# Requires cpython.py to be put in the scripts folder, or else in the python path.
################################################... | gpl-3.0 |
bpsmith/tia | tia/analysis/plots.py | 1 | 3032 | import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
from tia.analysis.perf import returns_cumulative, max_drawdown, guess_freq
from tia.util.mplot import AxesFormat
from tia.util.fmt import new_float_formatter
def plot_return_on_dollar(rets, title='Return on $1', show_maxdd=0, figsize=None, ax=None... | bsd-3-clause |
rs2/pandas | pandas/tests/frame/indexing/test_insert.py | 2 | 2291 | """
test_insert is specifically for the DataFrame.insert method; not to be
confused with tests with "insert" in their names that are really testing
__setitem__.
"""
import numpy as np
import pytest
from pandas import DataFrame, Index
import pandas._testing as tm
class TestDataFrameInsert:
def test_insert(self):
... | bsd-3-clause |
bbfrederick/rapidtide | rapidtide/tests/test_fullrunrapidtide_v4.py | 1 | 1733 | #!/usr/bin/env python
# -*- coding: latin-1 -*-
#
# Copyright 2016-2021 Blaise Frederick
#
# 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/LICEN... | apache-2.0 |
plotly/plotly.py | packages/python/plotly/plotly/graph_objs/table/_cells.py | 1 | 17840 | from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Cells(_BaseTraceHierarchyType):
# class properties
# --------------------
_parent_path_str = "table"
_path_str = "table.cells"
_valid_props = {
"align",
"alignsrc",
... | mit |
ZxlAaron/mypros | python/pyspark/sql/dataframe.py | 10 | 64367 | #
# 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 |
AlertaDengue/InfoDenguePredict | infodenguepredict/models/rgf_model.py | 2 | 5373 | import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import os
from rgf.sklearn import RGFRegressor
from sklearn.model_selection import train_test_split
from sklearn.metrics import *
from infodenguepredict.data.infodengue import get_cluster_data, get_city_names, build_multicity_dataset, get_alerta_t... | gpl-3.0 |
apeyser/nest-simulator | examples/neuronview/neuronview.py | 13 | 10676 | # -*- coding: utf-8 -*-
#
# neuronview.py
#
# This file is part of NEST.
#
# Copyright (C) 2004 The NEST Initiative
#
# NEST 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 2 of the License, or
... | gpl-2.0 |
wangmiao1981/spark | python/pyspark/sql/group.py | 23 | 10681 | #
# 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 |
rbalda/neural_ocr | env/lib/python2.7/site-packages/scipy/cluster/tests/test_hierarchy.py | 3 | 37641 | #! /usr/bin/env python
#
# Author: Damian Eads
# Date: April 17, 2008
#
# Copyright (C) 2008 Damian Eads
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
#
# 1. Redistributions of source code must retain the above copy... | mit |
mohitganguly/IRBlock_Vanderbilt | 4/mHH/make_fig.py | 1 | 1150 | from __future__ import division
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
temp = [25,26,27,28,29,29.5]
pas = [17575,17575,17575,17575,17575,17575]
na_only = [7275,7250,7225,7200,7175,7150]
k_only = [1070,980,930,910,900,875]
norm = [1300,1100,1030,950,925,900]
plt.plot(temp, pas, '-o', ... | gpl-3.0 |
PyRsw/PyRsw | src/Plot_tools/update_save_2D.py | 1 | 3510 | # Update plot objects if saving
import numpy as np
from smart_time import smart_time
import matplotlib.pyplot as plt
def update_save_2D(sim):
Nx, Ny = sim.Nx, sim.Ny
for var_cnt in range(len(sim.plot_vars)):
var = sim.plot_vars[var_cnt]
for L in range(sim.Nz):
if var == 'u':
... | mit |
imaculate/scikit-learn | examples/manifold/plot_swissroll.py | 330 | 1446 | """
===================================
Swiss Roll reduction with LLE
===================================
An illustration of Swiss Roll reduction
with locally linear embedding
"""
# Author: Fabian Pedregosa -- <fabian.pedregosa@inria.fr>
# License: BSD 3 clause (C) INRIA 2011
print(__doc__)
import matplotlib.pyplot... | bsd-3-clause |
CforED/Machine-Learning | sklearn/cross_decomposition/cca_.py | 151 | 3192 | from .pls_ import _PLS
__all__ = ['CCA']
class CCA(_PLS):
"""CCA Canonical Correlation Analysis.
CCA inherits from PLS with mode="B" and deflation_mode="canonical".
Read more in the :ref:`User Guide <cross_decomposition>`.
Parameters
----------
n_components : int, (default 2).
numb... | bsd-3-clause |
bibsian/database-development | poplerGUI/ui_logic_main.py | 1 | 8237 | from PyQt4 import QtGui, QtCore
from pandas import read_sql
from collections import OrderedDict, namedtuple
from Views import ui_dialog_main as dmainw
from poplerGUI import ui_logic_preview as tprev
from poplerGUI import class_inputhandler as ini
from poplerGUI import class_modelviewpandas as view
from poplerGUI.logicl... | mit |
yavalvas/yav_com | build/matplotlib/doc/mpl_examples/axes_grid/inset_locator_demo2.py | 8 | 1239 | import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1.inset_locator import zoomed_inset_axes
from mpl_toolkits.axes_grid1.inset_locator import mark_inset
import numpy as np
def get_demo_image():
from matplotlib.cbook import get_sample_data
import numpy as np
f = get_sample_data("axes_grid/bivariat... | mit |
dimkal/mne-python | mne/decoding/tests/test_ems.py | 19 | 1969 | # Author: Denis A. Engemann <d.engemann@gmail.com>
#
# License: BSD (3-clause)
import os.path as op
from nose.tools import assert_equal, assert_raises
from mne import io, Epochs, read_events, pick_types
from mne.utils import requires_sklearn
from mne.decoding import compute_ems
data_dir = op.join(op.dirname(__file_... | bsd-3-clause |
hainm/scikit-learn | sklearn/tests/test_isotonic.py | 230 | 11087 | import numpy as np
import pickle
from sklearn.isotonic import (check_increasing, isotonic_regression,
IsotonicRegression)
from sklearn.utils.testing import (assert_raises, assert_array_equal,
assert_true, assert_false, assert_equal,
... | bsd-3-clause |
farmlab/AgronoPy | agronopy/simulator/aqyield.py | 1 | 24456 | """File
File: aqyield.py
Author: Jerome Dury
Email: jerome.dury@flyingheep.fr
Github: https://github.com/farmlab
Description:
http://maelia-platform.inra.fr/modeles/processus-agricoles/dynamique-sol-culture-2/dynamique-sol-culture/
Reference: Constantin, J. , Willaume, M., Murgue, C., Lacroix, B., Therond, O.
(2015). ... | mit |
door2door-io/gtfs-merger | tests/test_gtfsmerger.py | 1 | 2658 | from gtfsmerger import GTFSMerger
import pandas as pd
from pandas.util import testing as tm
import numpy as np
import pytest
def test_gtfs_merger(gtfs_merger):
assert gtfs_merger.merged['stops'].iloc[:5]['stop_id'].tolist() == [
u'0-n1502-1',
u'0-n62046-1',
u'0-n1520-1',
u'0-n1522-... | mit |
farthir/msc-project | data_processing.py | 1 | 12356 | """Module containing classes and methods for data processing"""
import copy
import numpy as np
import pandas as pd
class ProcessingError(Exception):
"""Base class for exceptions in this module."""
pass
class VariableTypeError(ProcessingError):
"""Raise error if type of variable not handled."""
pass
c... | mit |
UManPychron/pychron | pychron/mv/zoom/zoom.py | 2 | 6536 | # ===============================================================================
# Copyright 2016 Jake Ross
#
# 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... | apache-2.0 |
simon-pepin/scikit-learn | examples/semi_supervised/plot_label_propagation_versus_svm_iris.py | 286 | 2378 | """
=====================================================================
Decision boundary of label propagation versus SVM on the Iris dataset
=====================================================================
Comparison for decision boundary generated on iris dataset
between Label Propagation and SVM.
This demon... | bsd-3-clause |
mcflugen/bmi-tutorial | examples/heat_2.py | 1 | 1879 | #! /usr/bin/env python
import sys
import numpy as np
import matplotlib.pyplot as plt
from heat_utils import solve_2d_heat_eqn, read_params_from_file
class Heat(object):
"""Basic Model Interface for heat component"""
def __init__(self):
self._spacing = (1., 1.)
self._alpha = 1.
self.... | mit |
akhilpm/Masters-Project | UMKL/classifiers.py | 1 | 1851 | import numpy as np
import scipy.io
from scipy.io import loadmat
from sklearn.cross_validation import train_test_split
from sklearn.metrics import accuracy_score
from sklearn.metrics import confusion_matrix
import warnings
import time
from sklearn.neighbors import KNeighborsClassifier
from sklearn.tree import DecisionT... | mit |
jnarhan/Breast_Cancer | src/helper_modules/jn_bc_helper.py | 1 | 13754 | # coding: utf-8
# A package of helper functions for Neural Net processing in breast cancer detection/diagnosis
# Author: Jay Narhan
# Date: April-2017
import os
import gc
import csv
import sys
import time
import shutil
import itertools
import collections
import numpy as np
from scipy import misc
import keras.call... | mit |
Reagankm/KnockKnock | venv/lib/python3.4/site-packages/mpl_toolkits/tests/test_axes_grid1.py | 7 | 1871 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import matplotlib.pyplot as plt
from matplotlib.testing.decorators import image_comparison
from mpl_toolkits.axes_grid1 import make_axes_locatable
import numpy as np
@image_comparison(baseline_ima... | gpl-2.0 |
DonBeo/statsmodels | statsmodels/examples/ex_lowess.py | 34 | 2827 | # -*- coding: utf-8 -*-
"""
Created on Mon Oct 31 15:26:06 2011
Author: Chris Jordan Squire
extracted from test suite by josef-pktd
"""
from __future__ import print_function
import numpy as np
import matplotlib.pyplot as plt
import statsmodels.api as sm
lowess = sm.nonparametric.lowess
# this is just to check dire... | bsd-3-clause |
lstout/GendERC | CVs.py | 1 | 7608 | from __future__ import division, print_function
import cPickle
import os
import re
import time
from collections import defaultdict
from functools import partial
from os import listdir
import pandas as pd
import requests
from SPARQLWrapper import JSON, SPARQLWrapper
import reader
from spotlight import SpotlightExcept... | mit |
pv/scikit-learn | examples/applications/plot_outlier_detection_housing.py | 243 | 5577 | """
====================================
Outlier detection on a real data set
====================================
This example illustrates the need for robust covariance estimation
on a real data set. It is useful both for outlier detection and for
a better understanding of the data structure.
We selected two sets o... | bsd-3-clause |
pythonvietnam/scikit-learn | sklearn/linear_model/tests/test_passive_aggressive.py | 169 | 8809 | import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_less
from sklearn.utils.testing import assert_greater
from sklearn.utils.testing import assert_array_almost_equal, assert_array_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_rais... | bsd-3-clause |
huanzhang12/LightGBM | tests/python_package_test/test_plotting.py | 5 | 4569 | # coding: utf-8
# pylint: skip-file
import unittest
import lightgbm as lgb
from sklearn.datasets import load_breast_cancer
from sklearn.model_selection import train_test_split
try:
import matplotlib
matplotlib.use('Agg')
matplotlib_installed = True
except ImportError:
matplotlib_installed = False
cl... | mit |
tobbad/pydwf | digilent_samples/AnalogOutIn.py | 1 | 1665 | """
DWF Python Example translated to swig bindings
Author: Tobias Badertscher based on work by Digilent, Inc.
Revision: 12/31/2013
"""
import sys
sys.path.append('..')
from pydwf import dwf
import time
import matplotlib.pyplot as plt
import numpy as np
def AnalogOutIn():
version = dwf.GetVersion()
... | lgpl-3.0 |
smsolivier/VEF | tex/ictt/src/mms.py | 1 | 3266 | #!/usr/bin/env python3
import numpy as np
import matplotlib.pyplot as plt
import sys
sys.path.append('../../code')
import ld as LD
import dd as DD
from scipy.interpolate import interp1d
from hidespines import *
from R2 import *
import texTools as tex
''' Test order of accuracy for LD options '''
if (len(... | mit |
amerc/TCP3 | chips2/examples/example_5.py | 3 | 3116 | #!/usr/bin/env python
import subprocess
import atexit
from math import pi
try:
import scipy as s
except ImportError:
print "You need scipy to run this script!"
exit(0)
try:
import numpy as n
except ImportError:
print "You need numpy to run this script!"
exit(0)
try:
from matplotlib impor... | mit |
jreback/pandas | pandas/tests/series/methods/test_nlargest.py | 5 | 7121 | """
Note: for naming purposes, most tests are title with as e.g. "test_nlargest_foo"
but are implicitly also testing nsmallest_foo.
"""
from itertools import product
import numpy as np
import pytest
import pandas as pd
from pandas import Series
import pandas._testing as tm
main_dtypes = [
"datetime",
"dateti... | bsd-3-clause |
chetan51/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/projections/polar.py | 69 | 20981 | import math
import numpy as npy
import matplotlib
rcParams = matplotlib.rcParams
from matplotlib.artist import kwdocd
from matplotlib.axes import Axes
from matplotlib import cbook
from matplotlib.patches import Circle
from matplotlib.path import Path
from matplotlib.ticker import Formatter, Locator
from matplotlib.tr... | gpl-3.0 |
abhishekgahlot/scikit-learn | examples/cluster/plot_feature_agglomeration_vs_univariate_selection.py | 30 | 3909 | """
==============================================
Feature agglomeration vs. univariate selection
==============================================
This example compares 2 dimensionality reduction strategies:
- univariate feature selection with Anova
- feature agglomeration with Ward hierarchical clustering
Both metho... | bsd-3-clause |
ngoix/OCRF | examples/svm/plot_svm_anova.py | 85 | 2024 | """
=================================================
SVM-Anova: SVM with univariate feature selection
=================================================
This example shows how to perform univariate feature selection before running a
SVC (support vector classifier) to improve the classification scores.
"""
print(__doc_... | bsd-3-clause |
mlyundin/scikit-learn | examples/model_selection/plot_train_error_vs_test_error.py | 349 | 2577 | """
=========================
Train error vs Test error
=========================
Illustration of how the performance of an estimator on unseen data (test data)
is not the same as the performance on training data. As the regularization
increases the performance on train decreases while the performance on test
is optim... | bsd-3-clause |
ch3ll0v3k/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 |
MSeifert04/astropy | astropy/visualization/wcsaxes/tests/test_frame.py | 11 | 5290 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
import pytest
import numpy as np
import matplotlib.pyplot as plt
from astropy.wcs import WCS
from astropy.visualization.wcsaxes import WCSAxes
from astropy.visualization.wcsaxes.frame import BaseFrame
from astropy.tests.image_tests import IMAGE_REFEREN... | bsd-3-clause |
kostajaitachi/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 |
xyguo/scikit-learn | sklearn/linear_model/tests/test_sparse_coordinate_descent.py | 34 | 9987 | import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_less
from sklearn.utils.testing import assert_true
from sklearn.utils.t... | 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 |
mbayon/TFG-MachineLearning | vbig/lib/python2.7/site-packages/scipy/ndimage/io.py | 9 | 1248 | from __future__ import division, print_function, absolute_import
import numpy as np
_have_pil = True
try:
from scipy.misc.pilutil import imread as _imread
except ImportError:
_have_pil = False
__all__ = ['imread']
# Use the implementation of `imread` in `scipy.misc.pilutil.imread`.
# If it weren't for th... | mit |
rjosest/WTC | Scripts/QueryingOrthanc.py | 1 | 2915 | #from urllib2 import Request, urlopen, URLError
#import json
#
#
#remote='http://54.208.95.22/'
#
#query='patients'
#
#request = Request(remote+query)
#
#try:
# response = urlopen(request)
# return json.loads(response.read())
#
#except URLError, e:
# print 'No patient', e
import requests
import pandas as pd
... | bsd-3-clause |
nelson-liu/scikit-learn | examples/model_selection/plot_roc_crossval.py | 21 | 3477 | """
=============================================================
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 |
herilalaina/scikit-learn | sklearn/cluster/spectral.py | 7 | 19261 | # -*- coding: utf-8 -*-
"""Algorithms for spectral clustering"""
# Author: Gael Varoquaux gael.varoquaux@normalesup.org
# Brian Cheung
# Wei LI <kuantkid@gmail.com>
# License: BSD 3 clause
import warnings
import numpy as np
from ..base import BaseEstimator, ClusterMixin
from ..utils import check_rand... | bsd-3-clause |
Batch21/pywr | tests/test_agg_constraints.py | 1 | 7631 | from pywr.core import Model, Input, Output, Link, Storage, AggregatedNode, PiecewiseLink, MultiSplitLink
from pywr.parameters import ConstantParameter
import pytest
from numpy.testing import assert_allclose
import pandas
from pandas import Timestamp
from helpers import load_model
@pytest.fixture
def model(solver):
... | gpl-3.0 |
ryandougherty/mwa-capstone | MWA_Tools/build/matplotlib/lib/mpl_examples/axes_grid/demo_axes_rgb.py | 8 | 1876 | import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1.axes_rgb import make_rgb_axes, RGBAxes
def get_demo_image():
from matplotlib.cbook import get_sample_data
f = get_sample_data("axes_grid/bivariate_normal.npy", asfileobj=False)
z = np.load(f)
# z is a numpy array of 15x15
... | gpl-2.0 |
cngo-github/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/offsetbox.py | 69 | 17728 | """
The OffsetBox is a simple container artist. The child artist are meant
to be drawn at a relative position to its parent. The [VH]Packer,
DrawingArea and TextArea are derived from the OffsetBox.
The [VH]Packer automatically adjust the relative postisions of their
children, which should be instances of the OffsetBo... | agpl-3.0 |
iamkingmaker/trading-with-python | cookbook/getDataFromYahooFinance.py | 77 | 1391 | # -*- coding: utf-8 -*-
"""
Created on Sun Oct 16 18:37:23 2011
@author: jev
"""
from urllib import urlretrieve
from urllib2 import urlopen
from pandas import Index, DataFrame
from datetime import datetime
import matplotlib.pyplot as plt
sDate = (2005,1,1)
eDate = (2011,10,1)
symbol = 'SPY'
fNa... | bsd-3-clause |
google/timesketch | timesketch/api/v1/resources/event.py | 1 | 29673 | # Copyright 2020 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 a... | apache-2.0 |
rseubert/scikit-learn | sklearn/feature_extraction/text.py | 6 | 49520 | # -*- coding: utf-8 -*-
# Authors: Olivier Grisel <olivier.grisel@ensta.org>
# Mathieu Blondel <mathieu@mblondel.org>
# Lars Buitinck <L.J.Buitinck@uva.nl>
# Robert Layton <robertlayton@gmail.com>
# Jochen Wersdörfer <jochen@wersdoerfer.de>
# Roman Sinayev <roman.sinayev@gma... | bsd-3-clause |
ruthfranklin/hande | tools/dmqmc/plot_excit_dist.py | 2 | 2290 | #!/usr/bin/env python
'''Plot excitation distribution from dmqmc output.'''
import os
import pkgutil
import sys
import matplotlib.pyplot as pl
import argparse
if not pkgutil.find_loader('pyhande'):
_script_dir = os.path.dirname(os.path.abspath(__file__))
sys.path.append(os.path.join(_script_dir, '../pyhande')... | lgpl-2.1 |
homeslike/OpticalTweezer | scripts/p0.3_at0.05/vCOMhistogramMass.py | 27 | 3006 | import math
import sys
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.mlab as mlab
from subprocess import call
from scipy.stats import norm
# proc = call("ls *.dat",shell=True)
# datetime = "170123_2033_"
datetime = sys.argv[1]+"_"
gasTempDataIn = np.genfromtxt(datetime+"gasTempData.dat",usecols... | mit |
cwu2011/scikit-learn | sklearn/ensemble/tests/test_gradient_boosting_loss_functions.py | 221 | 5517 | """
Testing for the gradient boosting loss functions and initial estimators.
"""
import numpy as np
from numpy.testing import assert_array_equal
from numpy.testing import assert_almost_equal
from numpy.testing import assert_equal
from nose.tools import assert_raises
from sklearn.utils import check_random_state
from ... | bsd-3-clause |
scr4t/rep | rep/plotting.py | 3 | 45902 | """
There are different plotting backends supported:
* *matplotlib* (default, de-facto standard plotting library),
* *plotly* (proprietary package with interactive plots, information is kept on the server),
* *ROOT* (the library used by CERN people),
* *bokeh* (open-source package with interactive plot... | apache-2.0 |
Bismarrck/pymatgen | pymatgen/analysis/transition_state.py | 3 | 16550 | # coding: utf-8
# Copyright (c) Pymatgen Development Team.
# Distributed under the terms of the MIT License.
from __future__ import division, unicode_literals
import os
import glob
import numpy as np
from monty.json import jsanitize
from monty.json import MSONable
scipy_old_piecewisepolynomial = True
try:
from s... | mit |
Split-Screen/android_kernel_htc_flounder | scripts/tracing/dma-api/trace.py | 96 | 12420 | """Main program and stuff"""
#from pprint import pprint
from sys import stdin
import os.path
import re
from argparse import ArgumentParser
import cPickle as pickle
from collections import namedtuple
from plotting import plotseries, disp_pic
import smmu
class TracelineParser(object):
"""Parse the needed informatio... | gpl-2.0 |
olinguyen/shogun | examples/undocumented/python/graphical/regression_lars.py | 11 | 3318 | #!/usr/bin/python
import numpy as np
import matplotlib.pyplot as plt
from shogun import RegressionLabels, RealFeatures
from shogun import LeastAngleRegression, LinearRidgeRegression, LeastSquaresRegression
from shogun import MeanSquaredError
# we compare LASSO with ordinary least-squares (OLE)
# in the ideal case, t... | gpl-3.0 |
jungla/ICOM-fluidity-toolbox | Detectors/offline_advection/plot_dispersion_23D.py | 1 | 17046 | #!~/python
import fluidity_tools
import matplotlib as mpl
mpl.use('ps')
import matplotlib.pyplot as plt
import myfun
import numpy as np
from scipy import optimize
import os
import scipy.stats as sp
import scipy
import lagrangian_stats
import advect_functions
from scipy.interpolate import interp1d
import csv
def RD_t(... | gpl-2.0 |
ESSS/numpy | numpy/core/tests/test_multiarray.py | 4 | 238197 | from __future__ import division, absolute_import, print_function
import collections
import tempfile
import sys
import shutil
import warnings
import operator
import io
import itertools
import ctypes
import os
if sys.version_info[0] >= 3:
import builtins
else:
import __builtin__ as builtins
from decimal import D... | bsd-3-clause |
holsety/tushare | tushare/datayes/macro.py | 17 | 191349 | # -*- coding:utf-8 -*-
"""
通联数据
Created on 2015/08/24
@author: Jimmy Liu
@group : waditu
@contact: jimmysoa@sina.cn
"""
from pandas.compat import StringIO
import pandas as pd
from tushare.util import vars as vs
from tushare.util.common import Client
from tushare.util import upass as up
class Macro():
def __... | bsd-3-clause |
ismailakbudak/election-algorithm-on-graph | graph.py | 1 | 24608 | # -*- coding: utf-8 -*-
# Node and graph implementation
# Developer
# Ismail AKBUDAK
# ismailakbudak.com
from matplotlib import pyplot as plt
import networkx as nx
import random
from collections import OrderedDict
import pprint
pp = pprint.PrettyPrinter(indent=4)
# Node objects for graph structure
class Node(object)... | mit |
richardotis/scipy | scipy/signal/signaltools.py | 6 | 87532 | # Author: Travis Oliphant
# 1999 -- 2002
from __future__ import division, print_function, absolute_import
import warnings
import threading
from . import sigtools
from scipy._lib.six import callable
from scipy._lib._version import NumpyVersion
from scipy import linalg
from scipy.fftpack import (fft, ifft, ifftshift, ... | bsd-3-clause |
meduz/scikit-learn | sklearn/feature_selection/rfe.py | 33 | 16667 | # Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Vincent Michel <vincent.michel@inria.fr>
# Gilles Louppe <g.louppe@gmail.com>
#
# License: BSD 3 clause
"""Recursive feature elimination for feature ranking"""
import numpy as np
from ..utils import check_X_y, safe_sqr
from ..utils.metaes... | bsd-3-clause |
scholer/nascent | nascent/utils/simple_system.py | 2 | 8427 | # -*- coding: utf-8 -*-
## Copyright 2015 Rasmus Scholer Sorensen, rasmusscholer@gmail.com
##
## This file is part of Nascent.
##
## Nascent is free software: you can redistribute it and/or modify
## it under the terms of the GNU Affero General Public License as
## published by the Free Software Foundati... | agpl-3.0 |
yonglehou/scikit-learn | examples/gaussian_process/plot_gp_regression.py | 253 | 4054 | #!/usr/bin/python
# -*- coding: utf-8 -*-
r"""
=========================================================
Gaussian Processes regression: basic introductory example
=========================================================
A simple one-dimensional regression exercise computed in two different ways:
1. A noise-free cas... | bsd-3-clause |
dsullivan7/scikit-learn | sklearn/__check_build/__init__.py | 345 | 1671 | """ Module to give helpful messages to the user that did not
compile the scikit properly.
"""
import os
INPLACE_MSG = """
It appears that you are importing a local scikit-learn source tree. For
this, you need to have an inplace install. Maybe you are in the source
directory and you need to try from another location.""... | bsd-3-clause |
silburt/rebound2 | examples/planetesimals2/Removed_plot.py | 1 | 3024 | #This macro plots the distribution of ejections/collisions for a given run(s). Can also compare identical runs from Swifter and my Hybrid integrator. Takes *_removed.txt as input, or the corresponding file for swifter.
import sys
import matplotlib.pyplot as plt
import numpy as np
import pylab as pl
import re
swifter_... | gpl-3.0 |
n3011/deeprl | train_cartpole.py | 1 | 2378 | import gym
from tqdm import tqdm
import matplotlib.pyplot as plt
from core.solver_pg import VanillaPolicyGradient, tf
import core.logger as log
def main():
gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=0.8)
DISPLAY = True
DISPLAY_REWARD_THRESHOLD = 400
with tf.Session(config=tf.ConfigPro... | mit |
wilsonqin/pandas-mint-taxes | review_transactions.py | 1 | 1774 | ### DISCLAIMER:
### THIS DEMO IS DISTRIBUTED FOR EDUCATIONAL PURPOSES ONLY. IT IS NOT TAX-RELATED ADVICE OR FILING SOFTWARE.
### FOR ALL TAX-RELATED QUESTIONS AND CONCERNS PLEASE ASK A CERTIFIED ACCOUNTANT
import pandas as pd
# TODO: move your MINT.com transactions.csv into this project directory
# / the directory wh... | mit |
frank-tancf/scikit-learn | sklearn/neighbors/approximate.py | 40 | 22369 | """Approximate nearest neighbor search"""
# Author: Maheshakya Wijewardena <maheshakya.10@cse.mrt.ac.lk>
# Joel Nothman <joel.nothman@gmail.com>
import numpy as np
import warnings
from scipy import sparse
from .base import KNeighborsMixin, RadiusNeighborsMixin
from ..base import BaseEstimator
from ..utils.va... | bsd-3-clause |
sgenoud/scikit-learn | sklearn/neighbors/tests/test_ball_tree.py | 8 | 3174 | import numpy as np
from numpy.testing import assert_array_almost_equal
from scipy.spatial import cKDTree
from sklearn import neighbors
# Note: simple tests of BallTree.query() and BallTree.query_radius()
# are contained within the tests of test_neighbors.py
rng = np.random.RandomState(0)
def test_warning_flag(n_s... | bsd-3-clause |
seakers/daphne_brain | AT/analysis/detectMultivariateAnomalies.py | 1 | 3177 | from rest_framework.views import APIView
from rest_framework.response import Response
import pandas as pd
import numpy as np
import json
class DetectMultivariateAnomaliesThreshold (APIView):
def post(self, request, format=None):
method = request.data['selectedMultiVarAlgorithm']
anomalyScore =... | mit |
louisLouL/pair_trading | capstone_env/lib/python3.6/site-packages/pandas/core/indexes/range.py | 6 | 21868 | from sys import getsizeof
import operator
import numpy as np
from pandas._libs import index as libindex
from pandas.core.dtypes.common import (
is_integer,
is_scalar,
is_int64_dtype)
from pandas import compat
from pandas.compat import lrange, range
from pandas.compat.numpy import function as nv
from pand... | mit |
jangorecki/h2o-3 | h2o-py/tests/testdir_algos/gbm/pyunit_bernoulli_gbm.py | 6 | 2766 | from builtins import range
import sys, os
sys.path.insert(1, os.path.join("..","..",".."))
import h2o
from tests import pyunit_utils
import numpy as np
from sklearn import ensemble
from sklearn.metrics import roc_auc_score
from h2o.estimators.gbm import H2OGradientBoostingEstimator
def bernoulli_gbm():
#Log.info("I... | apache-2.0 |
ThomasMiconi/htmresearch | projects/poolingCapacity/layer2_capacity.py | 3 | 16286 | # ----------------------------------------------------------------------
# Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2016, 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 |
florentchandelier/zipline | zipline/utils/calendars/exchange_calendar_cme.py | 7 | 3143 | #
# Copyright 2016 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 |
dwhswenson/openpathsampling | openpathsampling/tests/test_shooting_point_analysis.py | 2 | 12078 | from __future__ import division
from __future__ import absolute_import
from builtins import zip
from builtins import range
from past.utils import old_div
from builtins import object
from nose.tools import (assert_equal, raises,
assert_almost_equal, assert_true, assert_in)
from numpy.testing impo... | mit |
jinzishuai/learn2deeplearn | deeplearning.ai/C1.NN_DL/week3/week3.py | 1 | 30275 | #!/usr/bin/python3
# coding: utf-8
# # Planar data classification with one hidden layer
#
# Welcome to your week 3 programming assignment. It's time to build your first neural network, which will have a hidden layer. You will see a big difference between this model and the one you implemented using logistic regressio... | gpl-3.0 |
rseubert/scikit-learn | sklearn/feature_selection/tests/test_feature_select.py | 3 | 22744 | """
Todo: cross-check the F-value with stats model
"""
import itertools
import numpy as np
from scipy import stats, sparse
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing import assert_true
... | bsd-3-clause |
barentsen/dave | susanplay/thrusterMatchup.py | 1 | 3128 | # -*- coding: utf-8 -*-
"""
Created on Mon Mar 7 09:36:25 2016
@author: smullall
"""
import dave.susanplay.mainSusan as mS
import dave.pipeline.pipeline as pipe
import dave.pipeline.main as main
import numpy as np
#import dave.pipeline.plotting as pp
import matplotlib.pyplot as plt
import dave.susanplay.sueplotting ... | mit |
zhuango/python | machine-learning-algorithms/mlalg/EM/twoDimGaussian3D.py | 2 | 1095 | import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
def multivariateDensity(x, mu, sigma):
d = mu.shape[0]
density = 1.0 / ((2.0*np.pi) ** (d / 2.0))
density *= 1 / (np.linalg.det(sigma) ** 0.5)
dur = x - mu
density *= np.exp(-0.5 * np.dot(np.dot(du... | gpl-2.0 |
perpetua1/django-pandas | runtests.py | 3 | 1374 | #!/usr/bin/env python
import os
import sys
import django
from django.conf import settings
if not settings.configured:
settings_dict = dict(
INSTALLED_APPS=(
'django.contrib.contenttypes',
'django_pandas',
'django_pandas.tests',
),
DATABASES={
... | bsd-3-clause |
dcprojects/CoolProp | wrappers/Python/CoolProp/Plots/SimpleCycles.py | 3 | 26676 | # -*- coding: utf-8 -*-
from __future__ import print_function, division, absolute_import
import matplotlib, warnings
import numpy as np
import CoolProp
from CoolProp.CoolProp import PropsSI
from CoolProp.Plots.Common import BasePlot, PropertyDict, SIunits
def SimpleCycle(Ref,Te,Tc,DTsh,DTsc,eta_a,Ts_Ph='Ph',**kw... | mit |
kaichogami/scikit-learn | sklearn/decomposition/tests/test_dict_learning.py | 67 | 9084 | import numpy as np
from sklearn.utils import check_array
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_less
from sklea... | bsd-3-clause |
surgebiswas/poker | PokerBots_2017/Johnny/scipy/optimize/_lsq/least_squares.py | 22 | 36536 | """Generic interface for least-square minimization."""
from __future__ import division, print_function, absolute_import
from warnings import warn
import numpy as np
from numpy.linalg import norm
from scipy.sparse import issparse, csr_matrix
from scipy.sparse.linalg import LinearOperator
from scipy.optimize import _m... | mit |
TiKeil/Master-thesis-LOD | python_files/generate_figures/7.1_Refinement.py | 1 | 2195 | # This file is part of the master thesis "Variational crimes in the Localized orthogonal decomposition method":
# https://github.com/TiKeil/Masterthesis-LOD.git
# Copyright holder: Tim Keil
# License: BSD 2-Clause License (http://opensource.org/licenses/BSD-2-Clause)
import numpy as np
import matplotlib.pyplot as ... | apache-2.0 |
dsquareindia/scikit-learn | sklearn/ensemble/tests/test_forest.py | 19 | 41737 | """
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 |
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