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 |
|---|---|---|---|---|---|
jkarnows/scikit-learn | sklearn/grid_search.py | 103 | 36232 | """
The :mod:`sklearn.grid_search` includes utilities to fine-tune the parameters
of an estimator.
"""
from __future__ import print_function
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>,
# Gael Varoquaux <gael.varoquaux@normalesup.org>
# Andreas Mueller <amueller@ais.uni-bonn.de>
# ... | bsd-3-clause |
pulinagrawal/nupic | examples/opf/clients/hotgym/anomaly/one_gym/nupic_anomaly_output.py | 49 | 9450 | # ----------------------------------------------------------------------
# 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 |
georgid/sms-tools | lectures/5-Sinusoidal-model/plots-code/synthesis-window-2.py | 2 | 2042 | import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import hamming, triang, blackmanharris
import sys, os, functools, time
from scipy.fftpack import fft, ifft, fftshift
sys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)), '../../../software/models/'))
import dftModel as DFT
import ... | agpl-3.0 |
ychfan/tensorflow | tensorflow/contrib/learn/python/learn/estimators/dnn_linear_combined_test.py | 52 | 69800 | # 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 |
kkozarev/mwacme | src/fit_powerlaw_spectra_normalized.py | 2 | 4350 | import numpy as np
import os,sys
from scipy import optimize
import matplotlib.pyplot as plt
import matplotlib.dates as pltdates
from astropy.io import ascii
from datetime import datetime
#This script will fit a power law to the moving source synchrotron spectrum
#The new data location
#if sys.platform == 'darwin': B... | gpl-2.0 |
evgchz/scikit-learn | examples/mixture/plot_gmm_selection.py | 248 | 3223 | """
=================================
Gaussian Mixture Model Selection
=================================
This example shows that model selection can be performed with
Gaussian Mixture Models using information-theoretic criteria (BIC).
Model selection concerns both the covariance type
and the number of components in th... | bsd-3-clause |
chris-ch/omarket | python-lab/src/cointeg.py | 1 | 9096 | import numpy
from scipy.signal import detrend
from statsmodels.tsa import tsatools
from numpy import linalg
from statsmodels.tsa.stattools import adfuller
__author__ = 'Christophe'
def is_not_stationary(v, significance='5%', max_d=6, reg='nc', autolag='AIC'):
""" Augmented Dickey Fuller test for a unit root in a... | apache-2.0 |
lthurlow/Network-Grapher | proj/external/matplotlib-1.2.1/examples/mplot3d/mixed_subplots_demo.py | 12 | 1032 | """
Demonstrate the mixing of 2d and 3d subplots
"""
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
def f(t):
s1 = np.cos(2*np.pi*t)
e1 = np.exp(-t)
return np.multiply(s1,e1)
################
# First subplot
################
t1 = np.arange(0.0, 5.0, 0.1)
t2 = n... | mit |
ewels/genomics-status | status/sequencing.py | 2 | 8779 | """ Handlers related to data sequencing statistics.
"""
from collections import defaultdict
import cStringIO
from datetime import datetime
import json
from dateutil import parser
import matplotlib.pyplot as plt
from matplotlib.backends.backend_agg import FigureCanvasAgg
import numpy as np
import tornado.web
from stat... | mit |
jhmadhav/pynopticon | src/em/info.py | 4 | 2971 | """
Routines for Gaussian Mixture Models and learning with Expectation Maximization
===============================================================================
This module contains classes and function to compute multivariate Gaussian
densities (diagonal and full covariance matrices), Gaussian mixtures, Gaussian
... | gpl-3.0 |
d-chambers/animations | simplex/simplex.py | 1 | 13205 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Jun 2 13:12:55 2017
@author: isti_ew
"""
import os
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.patches import Polygon
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.collections import PatchCollection
# import seaborn as... | mit |
nafitzgerald/allennlp | allennlp/training/metrics/conll_coref_scores.py | 1 | 8684 | from typing import Dict, List, Tuple
from collections import Counter
import numpy as np
from sklearn.utils.linear_assignment_ import linear_assignment
from overrides import overrides
from allennlp.training.metrics.metric import Metric
@Metric.register("conll_coref_scores")
class ConllCorefScores(Metric):
def __i... | apache-2.0 |
3WiseMen/python | 21. Showfreq.VISUAL/VisualShowfreq.v1.py | 1 | 1944 | #Refer to http://blog.rcnelson.com/building-a-matplotlib-gui-with-qt-designer-part-2/l
from PyQt4.uic import loadUiType
from matplotlib.figure import Figure
from matplotlib.backends.backend_qt4agg import (FigureCanvasQTAgg as FigureCanvas, NavigationToolbar2QT as NavigationToolbar)
import sys
from PyQt4 import QtGui
im... | mit |
tomlof/scikit-learn | sklearn/neural_network/rbm.py | 46 | 12291 | """Restricted Boltzmann Machine
"""
# Authors: Yann N. Dauphin <dauphiya@iro.umontreal.ca>
# Vlad Niculae
# Gabriel Synnaeve
# Lars Buitinck
# License: BSD 3 clause
import time
import numpy as np
import scipy.sparse as sp
from ..base import BaseEstimator
from ..base import TransformerMixi... | bsd-3-clause |
acarmel/dreampie | dreampielib/subprocess/__init__.py | 2 | 37126 | # Copyright 2010 Noam Yorav-Raphael
#
# This file is part of DreamPie.
#
# DreamPie 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 |
mwv/scikit-learn | sklearn/tests/test_common.py | 127 | 7665 | """
General tests for all estimators in sklearn.
"""
# Authors: Andreas Mueller <amueller@ais.uni-bonn.de>
# Gael Varoquaux gael.varoquaux@normalesup.org
# License: BSD 3 clause
from __future__ import print_function
import os
import warnings
import sys
import pkgutil
from sklearn.externals.six import PY3
fr... | bsd-3-clause |
bkuczenski/lca-tools | antelope_reports/charts/vertical.py | 1 | 6321 | import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
from .base import standard_labels, label_vbar, prefab_colors, net_color, wrap
def spread_bars(ax, data, color_gen, hi=None, lo=None, y_lim=None, barwidth=0.65, x_offset=0, labels=True, **kwargs):
"""
:param ax:
:param data:
:param... | gpl-2.0 |
andrewcmyers/tensorflow | tensorflow/contrib/learn/python/learn/estimators/kmeans.py | 34 | 10130 | # 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 |
shssoichiro/servo | tests/heartbeats/process_logs.py | 139 | 16143 | #!/usr/bin/env python
# This Source Code Form is subject to the terms of the Mozilla Public
# License, v. 2.0. If a copy of the MPL was not distributed with this
# file, You can obtain one at http://mozilla.org/MPL/2.0/.
import argparse
import matplotlib.pyplot as plt
import numpy as np
import os
from os import path
... | mpl-2.0 |
maxwell-lv/MyQuant | ssd.py | 1 | 7030 | from sqlalchemy.sql import select
from sqlalchemy.orm import sessionmaker
from sqlalchemy import create_engine, Column, Integer, String, Float, Date, MetaData
from sqlalchemy.ext.declarative import declarative_base
Base = declarative_base()
import sqlite3
from xlrd import open_workbook
import re
import click
from datet... | gpl-3.0 |
jpinedaf/pyspeckit | pyspeckit/spectrum/models/modelgrid.py | 5 | 2036 | """
==========
Model Grid
==========
Fit a line based on parameters output from a grid of models
Module API
^^^^^^^^^^
"""
import numpy as np
from pyspeckit.mpfit import mpfit
import matplotlib.cbook as mpcb
import copy
try:
import scipy.interpolate
import scipy.ndimage
scipyOK = True
except ImportError:
... | mit |
hlin117/scikit-learn | examples/linear_model/plot_theilsen.py | 100 | 3846 | """
====================
Theil-Sen Regression
====================
Computes a Theil-Sen Regression on a synthetic dataset.
See :ref:`theil_sen_regression` for more information on the regressor.
Compared to the OLS (ordinary least squares) estimator, the Theil-Sen
estimator is robust against outliers. It has a breakd... | bsd-3-clause |
ZENGXH/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 |
SaganBolliger/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/backends/backend_svg.py | 69 | 23593 | from __future__ import division
import os, codecs, base64, tempfile, urllib, gzip, cStringIO
try:
from hashlib import md5
except ImportError:
from md5 import md5 #Deprecated in 2.5
from matplotlib import verbose, __version__, rcParams
from matplotlib.backend_bases import RendererBase, GraphicsContextBase,\
... | agpl-3.0 |
msultan/msmbuilder | msmbuilder/tests/test_ghmm.py | 3 | 6219 | from __future__ import print_function, division
import warnings
from itertools import permutations
import hmmlearn.hmm
import numpy as np
import pickle
import tempfile
from sklearn.pipeline import Pipeline
from msmbuilder.example_datasets import AlanineDipeptide
from msmbuilder.featurizer import SuperposeFeaturizer... | lgpl-2.1 |
nkhuyu/office-nfl-pool | transform.py | 6 | 4239 | """
transform
~~~~~~~~~
Helper functions for data manipulation using Pandas.
"""
import numpy as np
import pandas as pd
def from_byteam_to_bygame(df, augment=True, dont_mirror=[]):
"""Tranform data with one row per team to one row per game.
In the 'byteam' format, there is one row per team -- one for the
... | mit |
ammarkhann/FinalSeniorCode | lib/python2.7/site-packages/pandas/core/tools/datetimes.py | 7 | 30773 | from datetime import datetime, timedelta, time
import numpy as np
from collections import MutableMapping
from pandas._libs import lib, tslib
from pandas.core.dtypes.common import (
_ensure_object,
is_datetime64_ns_dtype,
is_datetime64_dtype,
is_datetime64tz_dtype,
is_integer_dtype,
is_integer,... | mit |
jay3sh/vispy | vispy/testing/__init__.py | 21 | 2415 | # -*- coding: utf-8 -*-
# Copyright (c) 2015, Vispy Development Team.
# Distributed under the (new) BSD License. See LICENSE.txt for more info.
"""
Testing
=======
This module provides functions useful for running tests in vispy.
Tests can be run in a few ways:
* From Python, you can import ``vispy`` and do ``vis... | bsd-3-clause |
akionakamura/scikit-learn | sklearn/utils/multiclass.py | 92 | 13986 | # Author: Arnaud Joly, Joel Nothman, Hamzeh Alsalhi
#
# License: BSD 3 clause
"""
Multi-class / multi-label utility function
==========================================
"""
from __future__ import division
from collections import Sequence
from itertools import chain
import warnings
from scipy.sparse import issparse
fro... | bsd-3-clause |
rcrowder/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/backends/backend_gtkcairo.py | 69 | 2207 | """
GTK+ Matplotlib interface using cairo (not GDK) drawing operations.
Author: Steve Chaplin
"""
import gtk
if gtk.pygtk_version < (2,7,0):
import cairo.gtk
from matplotlib.backends import backend_cairo
from matplotlib.backends.backend_gtk import *
backend_version = 'PyGTK(%d.%d.%d) ' % gtk.pygtk_version + \
... | agpl-3.0 |
ldirer/scikit-learn | examples/ensemble/plot_adaboost_hastie_10_2.py | 355 | 3576 | """
=============================
Discrete versus Real AdaBoost
=============================
This example is based on Figure 10.2 from Hastie et al 2009 [1] and illustrates
the difference in performance between the discrete SAMME [2] boosting
algorithm and real SAMME.R boosting algorithm. Both algorithms are evaluate... | bsd-3-clause |
andrewnc/scikit-learn | examples/ensemble/plot_feature_transformation.py | 67 | 4285 | """
===============================================
Feature transformations with ensembles of trees
===============================================
Transform your features into a higher dimensional, sparse space. Then
train a linear model on these features.
First fit an ensemble of trees (totally random trees, a rand... | bsd-3-clause |
mne-tools/mne-python | examples/simulation/simulate_raw_data.py | 19 | 2830 | """
===========================
Generate simulated raw data
===========================
This example generates raw data by repeating a desired source activation
multiple times.
"""
# Authors: Yousra Bekhti <yousra.bekhti@gmail.com>
# Mark Wronkiewicz <wronk.mark@gmail.com>
# Eric Larson <larson.eric.... | bsd-3-clause |
guschmue/tensorflow | tensorflow/contrib/learn/python/learn/estimators/estimators_test.py | 21 | 6697 | # 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 |
sebp/scikit-survival | sksurv/nonparametric.py | 1 | 13820 | # 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.
#
# This program is distributed in the hope that it will be useful,
# bu... | gpl-3.0 |
TK-TarunW/ecosystem | spark-2.0.2-bin-hadoop2.7/python/pyspark/sql/session.py | 3 | 24896 | #
# 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 |
ryandougherty/mwa-capstone | MWA_Tools/build/matplotlib/examples/axes_grid/demo_axes_divider.py | 8 | 3104 | import matplotlib.pyplot as plt
def get_demo_image():
import numpy as np
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
return z, (-3,4,-4,3)
def demo_simple_image(ax):
Z, ext... | gpl-2.0 |
hvanwyk/drifter | src/grid/mesh.py | 1 | 15658 | from grid.cell import Cell
from grid.vertex import Vertex
from grid.triangle import Triangle
import numpy
import matplotlib.pyplot as plt
class Mesh(object):
'''
Description: (Quad) Mesh object
Attributes:
bounding_box: [xmin, xmax, ymin, ymax]
children: Cell, list of cel... | mit |
kjung/scikit-learn | examples/gaussian_process/plot_gpr_noisy_targets.py | 45 | 3680 | """
=========================================================
Gaussian Processes regression: basic introductory example
=========================================================
A simple one-dimensional regression example computed in two different ways:
1. A noise-free case
2. A noisy case with known noise-level per ... | bsd-3-clause |
CSyllabus/webapp | backend/apps/csyllabusapi/helper/generate_fixtures_from_polimi_dump.py | 1 | 6681 | import pandas as pd
import requests
from requests.adapters import HTTPAdapter
from requests.packages.urllib3.util.retry import Retry
from lxml import html
import json
polimi_fixtures_json = open("../fixtures/polimi_fixtures_json.json", "w")
# reading file polimi_courses_nodescription and extracting course description ... | mit |
tonysyu/mpltools | mpltools/widgets/slider.py | 2 | 4289 | import matplotlib.widgets as mwidgets
class Slider(mwidgets.Slider):
"""Slider widget to select a value from a floating point range.
Parameters
----------
ax : :class:`~matplotlib.axes.Axes` instance
The parent axes for the widget
value_range : (float, float)
(min, max) value allo... | bsd-3-clause |
aarchiba/scipy | scipy/interpolate/ndgriddata.py | 4 | 7600 | """
Convenience interface to N-D interpolation
.. versionadded:: 0.9
"""
from __future__ import division, print_function, absolute_import
import numpy as np
from .interpnd import LinearNDInterpolator, NDInterpolatorBase, \
CloughTocher2DInterpolator, _ndim_coords_from_arrays
from scipy.spatial import cKDTree
_... | bsd-3-clause |
janscience/thunderfish | thunderfish/fishshapes.py | 1 | 42376 | """
Manipulate and plot fish outlines.
## Fish shapes
All fish shapes of this module are accessible via these dictionaries:
- `fish_shapes`: dictionary holding all electric fish shapes.
- `fish_top_shapes`: dictionary holding electric fish shapes viewed from top.
- `fish_side_shapes`: dictionary holding electric fis... | gpl-3.0 |
jhonatancasale/ML-T3 | utils/dev/parse.csv.into.pandas/parse.csv.into.pandas.py | 1 | 3609 | #!env python3
# -*- coding: utf-8 -*-
import click
import logging
import sys
import requests
import os.path
import glob
import re
#logging.basicConfig(filename='history.log', level=logging.DEBUG,
logging.basicConfig(level=logging.DEBUG,
format='%(asctime)s:%(levelname)s:%(message)s'
... | apache-2.0 |
andrewv587/pycharm-project | static-spark-na-sa.py | 1 | 8935 | #!/usr/bin/python
# -*- coding:utf-8 -*-
# Filename:na-sa.py
# Function:
# Author:Huang Weihang
# Email:huangweihang14@mails.ucas.ac.cn
# Data:2016-12-28
import os
from pyspark import SparkConf
os.environ["SPARK_HOME"] = "/usr/local/spark"
import time
from numpy import *
from pyspark import SparkContext
import p... | apache-2.0 |
redreamality/tushare | tushare/util/dateu.py | 27 | 2184 | # -*- coding:utf-8 -*-
import datetime
import pandas as pd
def year_qua(date):
mon = date[5:7]
mon = int(mon)
return[date[0:4], _quar(mon)]
def _quar(mon):
if mon in [1, 2, 3]:
return '1'
elif mon in [4, 5, 6]:
return '2'
elif mon in [7, 8, 9]:
... | bsd-3-clause |
svebk/qpr-winter-2017 | code/CP1_eval_script_v2.py | 1 | 4171 | #!/usr/bin/env python
import matplotlib.pyplot as plt
from sklearn.metrics import roc_curve, roc_auc_score
import sys
import json
# how to use: python CP1_eval_script.py ground_truth_sample_CP1.json submission_sample_CP1.json output_sample_CP1.pdf output_cg_chart.pdf
################################################
... | mit |
jontyjashan/PiNN_Caffe2 | dc_iv_api.py | 1 | 16120 | import caffe2_paths
import os
import pickle
from caffe2.python import (
workspace, layer_model_helper, schema, optimizer, net_drawer
)
import caffe2.python.layer_model_instantiator as instantiator
import numpy as np
from pinn.pinn_lib import build_pinn, init_model_with_schemas
import pinn.data_reader as data_reader
im... | mit |
Sklearn-HMM/scikit-learn-HMM | sklean-hmm/utils/tests/test_utils.py | 12 | 4539 | import warnings
import numpy as np
import scipy.sparse as sp
from scipy.linalg import pinv2
from sklearn.utils.testing import (assert_equal, assert_raises, assert_true,
assert_almost_equal, assert_array_equal)
from sklearn.utils import check_random_state
from sklearn.utils import d... | bsd-3-clause |
pandeylab/pyquant | pyquant/command_line.py | 1 | 52961 | from __future__ import division, unicode_literals, print_function
import base64
import copy
import gzip
import os
import operator
import traceback
import random
import signal
import sys
from collections import defaultdict, OrderedDict
from functools import partial
from multiprocessing import Queue, Manager
from string ... | mit |
VladiMihaylenko/omim | search/search_quality/scoring_model.py | 2 | 10118 | #!/usr/bin/env python3
from math import exp, log
from scipy.stats import pearsonr, t
from sklearn import svm
from sklearn.model_selection import GridSearchCV, KFold
from sklearn.utils import resample
import argparse
import collections
import itertools
import numpy as np
import pandas as pd
import random
import sys
M... | apache-2.0 |
marqh/iris | lib/iris/symbols.py | 16 | 7823 | # (C) British Crown Copyright 2010 - 2015, Met Office
#
# This file is part of Iris.
#
# Iris is free software: you can redistribute it and/or modify it under
# the terms of the GNU Lesser General Public License as published by the
# Free Software Foundation, either version 3 of the License, or
# (at your option) any l... | lgpl-3.0 |
h2educ/scikit-learn | sklearn/decomposition/__init__.py | 147 | 1421 | """
The :mod:`sklearn.decomposition` module includes matrix decomposition
algorithms, including among others PCA, NMF or ICA. Most of the algorithms of
this module can be regarded as dimensionality reduction techniques.
"""
from .nmf import NMF, ProjectedGradientNMF
from .pca import PCA, RandomizedPCA
from .incrementa... | bsd-3-clause |
dhruvparamhans/zipline | 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 |
mila-udem/blocks-extras | blocks_extras/scripts/plot.py | 5 | 3705 | from __future__ import division, print_function
import fnmatch
from six import iteritems
from collections import OrderedDict
from functools import reduce
from blocks.config import config
from blocks.utils import change_recursion_limit
from blocks.log import TrainingLog
from blocks.main_loop import MainLoop
from bloc... | mit |
varun-rajan/python-modules | Obsolete/mdutilities_crack3d.py | 1 | 4822 | import numpy as np
import mdutilities_io as mduio
import myio as Mio
import mymath as Mmath
import Ccircumradii14 as C
import networkx as nx
import scipy.spatial as spsp
import matplotlib as mpl
import matplotlib.tri as mtri
import matplotlib.pyplot as plt
def parseCrackData(crackdata,cR,option,r0=2**(1/6),timeincreme... | gpl-2.0 |
AlexandreMoulti/bachelier | bachelier.py | 1 | 10663 | # -*- coding: utf-8 -*-
import numpy as np
from math import *
import pandas as pd
import matplotlib.pyplot as plt
import statsmodels.api as sm
import scipy as sc
class DiscretisationGrid(object):
""" Discretisation to be used for the Monte-Carlo simulations
Time grid, discretisation of the time... | mit |
cuilishen/cuilishenMissionPlanner | Lib/site-packages/numpy/core/code_generators/ufunc_docstrings.py | 57 | 85797 | # Docstrings for generated ufuncs
docdict = {}
def get(name):
return docdict.get(name)
def add_newdoc(place, name, doc):
docdict['.'.join((place, name))] = doc
add_newdoc('numpy.core.umath', 'absolute',
"""
Calculate the absolute value element-wise.
Parameters
----------
x : array_like... | gpl-3.0 |
DouglasLeeTucker/DECam_PGCM | bin/rawdata_se_objects_exp_combine.py | 1 | 5148 | #!/usr/bin/env python
"""
rawdata_se_objects_exp_combine.py
Example:
rawdata_se_objects_exp_combine.py --help
rawdata_se_objects_exp_combine.py --inputSEObjFile seobjfile.csv
--inputExpFile expfile.csv
--outputFile output... | gpl-3.0 |
mfjb/scikit-learn | examples/applications/plot_stock_market.py | 227 | 8284 | """
=======================================
Visualizing the stock market structure
=======================================
This example employs several unsupervised learning techniques to extract
the stock market structure from variations in historical quotes.
The quantity that we use is the daily variation in quote ... | bsd-3-clause |
nelango/ViralityAnalysis | model/lib/sklearn/feature_selection/__init__.py | 33 | 1159 | """
The :mod:`sklearn.feature_selection` module implements feature selection
algorithms. It currently includes univariate filter selection methods and the
recursive feature elimination algorithm.
"""
from .univariate_selection import chi2
from .univariate_selection import f_classif
from .univariate_selection import f_... | mit |
AlexRobson/scikit-learn | sklearn/cluster/tests/test_mean_shift.py | 121 | 3429 | """
Testing for mean shift clustering methods
"""
import numpy as np
import warnings
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_false
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import asser... | bsd-3-clause |
wangming28/syzygy | third_party/numpy/files/numpy/core/function_base.py | 82 | 5474 | __all__ = ['logspace', 'linspace']
import numeric as _nx
from numeric import array
def linspace(start, stop, num=50, endpoint=True, retstep=False):
"""
Return evenly spaced numbers over a specified interval.
Returns `num` evenly spaced samples, calculated over the
interval [`start`, `stop` ].
Th... | apache-2.0 |
ofgulban/scikit-image | doc/ext/plot2rst.py | 21 | 20507 | """
Example generation from python files.
Generate the rst files for the examples by iterating over the python
example files. Files that generate images should start with 'plot'.
To generate your own examples, add this extension to the list of
``extensions``in your Sphinx configuration file. In addition, make sure th... | bsd-3-clause |
annoviko/pyclustering | pyclustering/cluster/tests/unit/ut_ttsas.py | 1 | 3807 | """!
@brief Unit-tests for TTSAS algorithm.
@authors Andrei Novikov (pyclustering@yandex.ru)
@date 2014-2020
@copyright BSD-3-Clause
"""
import unittest;
import matplotlib;
matplotlib.use('Agg');
from pyclustering.cluster.tests.ttsas_template import ttsas_test;
from pyclustering.utils.metric impor... | gpl-3.0 |
mrshu/scikit-learn | sklearn/tree/tests/test_tree.py | 1 | 15609 | """
Testing for the tree module (sklearn.tree).
"""
import numpy as np
from numpy.testing import assert_array_equal
from numpy.testing import assert_array_almost_equal
from numpy.testing import assert_almost_equal
from numpy.testing import assert_equal
from nose.tools import assert_raises
from nose.tools import assert... | bsd-3-clause |
ajdawson/iris | lib/iris/tests/unit/plot/test_contourf.py | 11 | 3169 | # (C) British Crown Copyright 2014 - 2016, Met Office
#
# This file is part of Iris.
#
# Iris is free software: you can redistribute it and/or modify it under
# the terms of the GNU Lesser General Public License as published by the
# Free Software Foundation, either version 3 of the License, or
# (at your option) any l... | gpl-3.0 |
samleegithub/RestaurantRecs | src/data_counts.py | 1 | 6364 | from scrape_yelp_reviews import load_restaurant_ids
import pyspark as ps
import matplotlib.pyplot as plt
plt.style.use('ggplot')
def load_data(spark):
restaurants_df = spark.read.parquet('../data/restaurants')
ratings_df = spark.read.parquet('../data/ratings')
return restaurants_df, ratings_df
def get_f... | gpl-3.0 |
musically-ut/statsmodels | statsmodels/stats/tests/test_weightstats.py | 30 | 21864 | '''tests for weightstats, compares with replication
no failures but needs cleanup
update 2012-09-09:
added test after fixing bug in covariance
TODOs:
- I don't remember what all the commented out code is doing
- should be refactored to use generator or inherited tests
- still gaps in test coverage... | bsd-3-clause |
aroooshi/CloudFinalProject | application.py | 1 | 8188 | import os
from flask import Flask, render_template, request, redirect, url_for, send_from_directory, json, jsonify, session
import omdb
import math
app = Flask(__name__)
import math
import pandas as pd
import re
import pickle
from sklearn.externals import joblib
clf2 = joblib.load('model/tree.pkl')
df110 = pd.read_p... | apache-2.0 |
exord/bayev | test.py | 1 | 5761 | import pickle
import time
import bayev.pastislib as pl
import bayev.chib as chib
import bayev.perrakis as perr
import bayev.lib
import numpy as n
import matplotlib.pylab as plt
from math import e, log10
__author__ = 'Rodrigo F. Diaz'
def test_pastis_logprior(nsamples=300):
# Read test data
f = open('/Users... | mit |
johnowhitaker/bobibabber | mlp_example_origional.py | 1 | 1087 | from sklearn.datasets import load_digits
from multilayer_perceptron import MultilayerPerceptronClassifier, MultilayerPerceptronRegressor
import numpy as np
from matplotlib import pyplot as plt
# contrive the "exclusive or" problem
X = np.array([[0.0,0.1], [0.9,0], [0,0.85], [0.92,0.87]])
y = np.array([0, 1, 1, 0])
#... | mit |
stevertaylor/NX01 | NX01_processResults.py | 1 | 11770 | #!/usr/bin/env python
"""
Created by stevertaylor
Copyright (c) 2014 Stephen R. Taylor
Code contributions by Rutger van Haasteren (piccard) and Justin Ellis (PAL/PAL2).
"""
from __future__ import division
import numpy as np
from numpy import *
import os, optparse, corner, json
import h5py as h5
import matplotlib
m... | mit |
tacaswell/bokeh | bokeh/crossfilter/models.py | 40 | 30635 | from __future__ import absolute_import
import logging
import six
import pandas as pd
import numpy as np
from ..plotting import curdoc
from ..models import ColumnDataSource, GridPlot, Panel, Tabs, Range
from ..models.widgets import Select, MultiSelect, InputWidget
# crossfilter plotting utilities
from .plotting impo... | bsd-3-clause |
lgarren/spack | var/spack/repos/builtin/packages/py-pymatgen/package.py | 3 | 2608 | ##############################################################################
# Copyright (c) 2013-2017, Lawrence Livermore National Security, LLC.
# Produced at the Lawrence Livermore National Laboratory.
#
# This file is part of Spack.
# Created by Todd Gamblin, tgamblin@llnl.gov, All rights reserved.
# LLNL-CODE-64... | lgpl-2.1 |
brennmat/ruediPy | python/classes/rgams_SRS.py | 1 | 77748 | # Code for the SRS RGA mass spec class
#
# DISCLAIMER:
# This file is part of ruediPy, a toolbox for operation of RUEDI mass spectrometer systems.
#
# ruediPy 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, ... | gpl-3.0 |
morganics/bayesianpy | examples/iris_clustering_visualisation.py | 1 | 4326 | import pandas as pd
import bayesianpy
from bayesianpy.network import Builder as builder
import logging
import os
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Ellipse
# Using the latent variable to cluster data points. Based upon the Iris dataset which has 3 distinct clusters
# (... | apache-2.0 |
michigraber/scikit-learn | examples/plot_isotonic_regression.py | 303 | 1767 | """
===================
Isotonic Regression
===================
An illustration of the isotonic regression on generated data. The
isotonic regression finds a non-decreasing approximation of a function
while minimizing the mean squared error on the training data. The benefit
of such a model is that it does not assume a... | bsd-3-clause |
e-koch/BaSiCs | Examples/THINGS/catalog_comparison.py | 1 | 6301 |
import numpy as np
from astropy.table import Table
from astropy.modeling.models import Ellipse2D
from astropy.coordinates import SkyCoord
from astropy.io import fits
import astropy.units as u
from spectral_cube import SpectralCube
from basics import Bubble2D, Bubble3D
import glob
import matplotlib.pyplot as p
'''
Com... | mit |
numenta/htmresearch | htmresearch/frameworks/layers/physical_objects.py | 10 | 25225 | # ----------------------------------------------------------------------
# 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 |
mmottahedi/neuralnilm_prototype | scripts/e147.py | 2 | 5179 | from __future__ import print_function, division
import matplotlib
matplotlib.use('Agg') # Must be before importing matplotlib.pyplot or pylab!
from neuralnilm import Net, RealApplianceSource, BLSTMLayer, DimshuffleLayer
from lasagne.nonlinearities import sigmoid, rectify
from lasagne.objectives import crossentropy, mse... | mit |
paladin74/neural-network-animation | matplotlib/hatch.py | 10 | 7132 | """
Contains a classes for generating hatch patterns.
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from six.moves import xrange
import numpy as np
from matplotlib.path import Path
class HatchPatternBase:
"""
The base class for a... | mit |
mmottahedi/neuralnilm_prototype | scripts/e429.py | 2 | 7308 | from __future__ import print_function, division
import matplotlib
import logging
from sys import stdout
matplotlib.use('Agg') # Must be before importing matplotlib.pyplot or pylab!
from neuralnilm import (Net, RealApplianceSource,
BLSTMLayer, DimshuffleLayer,
Bidirectio... | mit |
lixt/lily2-gem5 | util/stats/barchart.py | 90 | 12472 | # Copyright (c) 2005-2006 The Regents of The University of Michigan
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met: redistributions of source code must retain the above copyright
# notice, this ... | bsd-3-clause |
imaculate/scikit-learn | sklearn/linear_model/tests/test_perceptron.py | 378 | 1815 | import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_raises
from sklearn.utils import check_random_state
from sklearn.datasets import load_iris
from sklearn.linear_model import Pe... | bsd-3-clause |
kelle/astropy | astropy/visualization/scripts/tests/test_fits2bitmap.py | 2 | 1749 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
import pytest
import numpy as np
from ....io import fits
try:
import matplotlib # pylint: disable=W0611
HAS_MATPLOTLIB = True
from ..fits2bitmap import fits2bitmap, main
except ImportError:
HAS_MATPLOTLIB = False
@pytest.mark.skipif('... | bsd-3-clause |
likelyzhao/mxnet | example/rcnn/rcnn/pycocotools/coco.py | 1 | 14869 | from __future__ import print_function
__version__ = '1.0.1'
__author__ = 'tylin'
# Interface for accessing the Microsoft COCO dataset.
# Microsoft COCO is a large image dataset designed for object detection,
# segmentation, and caption generation. pycocotools is a Python API that
# assists in loading, parsing and visu... | apache-2.0 |
TAMU-CPT/galaxy-tools | tools/genome_viz/dna_features_viewer/BiopythonTranslator/BiopythonTranslatorBase.py | 1 | 4482 | from ..biotools import load_record
from ..GraphicRecord import GraphicRecord
from ..CircularGraphicRecord import CircularGraphicRecord
from ..GraphicFeature import GraphicFeature
class BiopythonTranslatorBase:
"""Base class for all BiopythonTranslators.
This class needs to be complemented with methods comput... | gpl-3.0 |
MayukhSobo/EnronFraud | poi_id.py | 1 | 24774 | from feature_engineering import feature_importance
from feature_engineering import feature_loader
from feature_engineering import feature_misc
from sklearn.decomposition import PCA
from sklearn.feature_selection import SelectKBest
from sklearn.model_selection import GridSearchCV
from sklearn.model_selection import Stra... | mit |
JeanKossaifi/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 |
seemethere/nba_py | nba_py/__init__.py | 1 | 4486 | from datetime import datetime, timedelta
import os
from requests import get
from nba_py.constants import League
HAS_PANDAS = True
try:
from pandas import DataFrame
except ImportError:
HAS_PANDAS = False
HAS_REQUESTS_CACHE = True
CACHE_EXPIRE_MINUTES = int(os.getenv('NBA_PY_CACHE_EXPIRE_MINUTES', 10))
try:
... | bsd-3-clause |
APMonitor/arduino | 5_Moving_Horizon_Estimation/1st_order_linear/Python/main_mhe.py | 1 | 3157 | import tclab
import numpy as np
import time
from APMonitor.apm import *
import matplotlib.pyplot as plt
# Connect to Arduino
a = tclab.TCLab()
# Run time in minutes
run_time = 10.0
# Number of cycles (1 cycle per 2 seconds)
loops = int(30.0*run_time)
# Temperature (K)
T1 = np.ones(loops) * a.T1 # measured T
T1mhe =... | apache-2.0 |
mkraemer67/plugml | plugml/feature.py | 1 | 3221 | import numpy as np
from nltk.corpus import stopwords
from nltk.stem.lancaster import LancasterStemmer
from nltk.tokenize import RegexpTokenizer
from sklearn.feature_extraction import DictVectorizer
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.preprocessing import Imputer, StandardScale... | apache-2.0 |
sergpolly/Thermal_adapt_scripts | ArchNew/EDITING_composition_analysis_Thermo.py | 1 | 15908 | import pandas as pd
import os
import subprocess as sub
import re
import sys
from Bio import SeqUtils
import matplotlib.pyplot as plt
import numpy as np
from scipy import stats
path = "."
# ['DbxRefs','Description','FeaturesNum','GenomicID','GenomicLen','GenomicName','Keywords','NucsPresent','Organism_des',
# 'Source... | mit |
cccfran/sympy | examples/intermediate/mplot3d.py | 14 | 1261 | #!/usr/bin/env python
"""Matplotlib 3D plotting example
Demonstrates plotting with matplotlib.
"""
import sys
from sample import sample
from sympy import sin, Symbol
from sympy.external import import_module
def mplot3d(f, var1, var2, show=True):
"""
Plot a 3d function using matplotlib/Tk.
"""
im... | bsd-3-clause |
vigilv/scikit-learn | examples/ensemble/plot_gradient_boosting_regression.py | 227 | 2520 | """
============================
Gradient Boosting regression
============================
Demonstrate Gradient Boosting on the Boston housing dataset.
This example fits a Gradient Boosting model with least squares loss and
500 regression trees of depth 4.
"""
print(__doc__)
# Author: Peter Prettenhofer <peter.prett... | bsd-3-clause |
santosjorge/cufflinks | cufflinks/pandastools.py | 1 | 2712 | import pandas as pd
import re
def _screen(self,include=True,**kwargs):
"""
Filters a DataFrame for columns that contain the given strings.
Parameters:
-----------
include : bool
If False then it will exclude items that match
the given filters.
This is the same as passing a regex ^keyword
kwargs : ... | mit |
lukebarnard1/bokeh | bokeh/cli/utils.py | 42 | 8119 | from __future__ import absolute_import, print_function
from collections import OrderedDict
from six.moves.urllib import request as urllib2
import io
import pandas as pd
from .. import charts
from . import help_messages as hm
def keep_source_input_sync(filepath, callback, start=0):
""" Monitor file at filepath ch... | bsd-3-clause |
benslice/ggplot | ggplot/tests/test_element_text.py | 12 | 1362 | from nose.tools import assert_equal, assert_true
from ggplot.tests import image_comparison, cleanup
from ggplot import *
from numpy import linspace
from pandas import DataFrame
df = DataFrame({"blahblahblah": linspace(999, 1111, 9),
"yadayadayada": linspace(999, 1111, 9)})
simple_gg = ggplot(aes(x="b... | bsd-2-clause |
MikeDT/CNN_2_BBN | CNN_2_BBN_Optimiser.py | 1 | 5940 | from __future__ import print_function
from hyperopt import Trials, STATUS_OK, tpe
from keras.datasets import mnist
from keras.layers.core import Dense, Dropout, Activation,Flatten
from keras.models import Sequential
from keras.utils import np_utils
from Synthetic_Data_Creator import Synthetic_Data_Creator
from hyperas... | apache-2.0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.