repo_name stringlengths 6 67 | path stringlengths 5 185 | copies stringlengths 1 3 | size stringlengths 4 6 | content stringlengths 1.02k 962k | license stringclasses 15
values |
|---|---|---|---|---|---|
fabianp/scikit-learn | sklearn/neighbors/unsupervised.py | 106 | 4461 | """Unsupervised nearest neighbors learner"""
from .base import NeighborsBase
from .base import KNeighborsMixin
from .base import RadiusNeighborsMixin
from .base import UnsupervisedMixin
class NearestNeighbors(NeighborsBase, KNeighborsMixin,
RadiusNeighborsMixin, UnsupervisedMixin):
"""Unsu... | bsd-3-clause |
vishnumani2009/OpenSource-Open-Ended-Statistical-toolkit | FRONTEND/pyroc.py | 2 | 12161 | #!/usr/bin/env python
# encoding: utf-8
"""
PyRoc.py
Created by Marcel Caraciolo on 2009-11-16.
Copyright (c) 2009 Federal University of Pernambuco. All rights reserved.
IMPORTANT:
Based on the original code by Eithon Cadag (http://www.eithoncadag.com/files/pyroc.txt)
Python Module for calculating the area under the... | gpl-3.0 |
dpsfotocestou/SkyDrop | skydrop/utils/serial_chart/chart_3D.py | 5 | 2332 | import serial
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
def add_line(name, x, index):
item = {}
item["name"] = name
item["data"] = np.zeros(len(x))
item["index"] = index
item["axis"] = False
return item
time = np.arange(2)
y = []
y.append(a... | gpl-2.0 |
dominiktomicevic/pedestrian | classifier/extractor.py | 1 | 6723 | from itertools import product, repeat, chain, ifilter, imap
from multiprocessing import Pool, cpu_count
from sklearn.preprocessing import binarize
from utils.profiling import profile
from numpy.random import randint
from functools import partial
from random import sample
import numpy as np
import logging
logger = logg... | mit |
shyamalschandra/scikit-learn | sklearn/model_selection/_split.py | 8 | 55300 | """
The :mod:`sklearn.model_selection._split` module includes classes and
functions to split the data based on a preset strategy.
"""
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>,
# Gael Varoquaux <gael.varoquaux@normalesup.org>,
# Olivier Girsel <olivier.grisel@ensta.org>
# Ragha... | bsd-3-clause |
StingraySoftware/stingray | stingray/deadtime/model.py | 1 | 4595 | from stingray.utils import njit, prange
import numpy as np
import matplotlib.pyplot as plt
from astropy import log
try:
from scipy.special import factorial
except ImportError:
from scipy.misc import factorial
__FACTORIALS = factorial(np.arange(160))
def r_in(td, r_0):
"""Calculate incident countrate g... | mit |
bsipocz/statsmodels | statsmodels/examples/ex_multivar_kde.py | 34 | 1504 |
from __future__ import print_function
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
from mpl_toolkits.mplot3d import axes3d
import statsmodels.api as sm
"""
This example illustrates the nonparametric estimation of a
bivariate bi-modal distribution that is a mixture of two normal
distri... | bsd-3-clause |
waddell/urbansim | urbansim/models/regression.py | 5 | 33858 | """
Use the ``RegressionModel`` class to fit a model using statsmodels'
OLS capability and then do subsequent prediction.
"""
from __future__ import print_function
import logging
import numpy as np
import pandas as pd
import statsmodels.formula.api as smf
from patsy import dmatrix
from prettytable import PrettyTable... | bsd-3-clause |
poojavade/Genomics_Docker | Dockerfiles/gedlab-khmer-filter-abund/pymodules/python2.7/lib/python/statsmodels-0.5.0-py2.7-linux-x86_64.egg/statsmodels/tools/tests/test_tools.py | 3 | 17257 | """
Test functions for models.tools
"""
import numpy as np
from numpy.random import standard_normal
from numpy.testing import (assert_equal, assert_array_equal,
assert_almost_equal, assert_string_equal, TestCase)
from nose.tools import (assert_true, assert_false, assert_raises)
from statsmo... | apache-2.0 |
HHammond/PrettyPandas | test/test_pretty_pandas.py | 1 | 2421 | import copy
import pytest
import numpy as np
import pandas as pd
from prettypandas import PrettyPandas
@pytest.fixture()
def dataframe():
np.random.seed(24)
df = pd.DataFrame({'A': np.linspace(1, 10, 10)})
df = pd.concat([df, pd.DataFrame(np.random.randn(10, 4),
colu... | mit |
VladimirTyrin/urbansim | urbansim/models/util.py | 5 | 9254 | """
Utilities used within the ``urbansim.models`` package.
"""
import collections
import logging
import numbers
from StringIO import StringIO
from tokenize import generate_tokens, NAME
import numpy as np
import pandas as pd
import patsy
from zbox import toolz as tz
from ..utils.logutil import log_start_finish
logge... | bsd-3-clause |
andrebrener/crypto_predictor | backtest.py | 1 | 2740 | # =============================================================================
# File: backtest.py
# Author: Andre Brener
# Created: 12 Jun 2017
# Last Modified: 14 Jun 2017
# Description: description
# =============================================================================
from datetime ... | mit |
suiyuan2009/tensorflow | tensorflow/python/estimator/inputs/queues/feeding_queue_runner_test.py | 116 | 5164 | # Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | apache-2.0 |
kernc/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 |
pyspace/pyspace | pySPACE/run/launch.py | 2 | 16052 | #!/usr/bin/env python
""" Main program to run pySPACE
For further instructions take a look at the pySPACE documentation and the tutorials
in there!
.. note::
Due to errors in configuration files, data or the software, the software may
crash. Because of internal parallelization and threading, it is currently
... | bsd-3-clause |
airbnb/superset | tests/model_tests.py | 1 | 14095 | # 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 u... | apache-2.0 |
duerrp/pyexperiment | docs/conf.py | 4 | 12427 | # -*- coding: utf-8 -*-
#
# pyexperiment documentation build configuration file, created by
# sphinx-quickstart on Sat Apr 25 13:55:57 2015.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
... | mit |
tranlyvu/kaggle | Digit Recognizer/main/second_attempt.py | 1 | 2058 | """
The script generate submission file for the kaggle contest "Digit recognizer",An
image recognition contest whose challenge was to classify handwritten single digits
dimensionality reduction with PCA+randomforest selection
Predictive model: svm
"""
import pandas as pd
import numpy as np
from sklearn.svm impor... | apache-2.0 |
kjung/scikit-learn | examples/neural_networks/plot_mnist_filters.py | 57 | 2195 | """
=====================================
Visualization of MLP weights on MNIST
=====================================
Sometimes looking at the learned coefficients of a neural network can provide
insight into the learning behavior. For example if weights look unstructured,
maybe some were not used at all, or if very l... | bsd-3-clause |
Alexoner/mooc | cs231n/assignment2/cs231n/activation_statistics.py | 1 | 1817 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import numpy as np
import matplotlib.pyplot as plt
def activation_statistics(init_func=lambda fan_in, fan_out: np.random.randn(fan_in, fan_out) * 0.001, nonlinearity='tanh'):
"""TODO: Docstring for activation_statistics.
Demonstrate activation statistics with diff... | apache-2.0 |
Carralex/landlab | landlab/ca/examples/turbulent_suspension_with_settling_and_bleaching.py | 4 | 16830 | #!/usr/env/python
"""
isotropic_turbulent_suspension_with_settling_and_bleaching.py
Example of a continuous-time, stochastic, pair-based cellular automaton model,
which simulates the diffusion of suspended particles in a turbulent fluid.
Particles start with an accumulated luminescence signal L = 1, and are bleached
... | mit |
patrick-winter-knime/deep-learning-on-molecules | autoencoder_features/util/random_forest.py | 2 | 1688 | from sklearn.ensemble import RandomForestClassifier
from sklearn.externals import joblib
import numpy
from progressbar import ProgressBar
def train(train_data_input, train_data_output, model_path, nr_trees=1000):
train_data_input = numerical_to_features(train_data_input)
random_forest = RandomForestClassifier... | gpl-3.0 |
alexmojaki/odo | odo/backends/tests/test_sparksql.py | 2 | 6058 | from __future__ import print_function, absolute_import, division
import pytest
pyspark = pytest.importorskip('pyspark')
py4j = pytest.importorskip('py4j')
import os
import shutil
import json
import tempfile
from contextlib import contextmanager
import toolz
from toolz.compatibility import map
from pyspark.sql impo... | bsd-3-clause |
petrbel/PscKonvertor | psc_konvertor/__init__.py | 2 | 1828 | # -*- coding: utf-8 -*-
import os
import pandas
__author__ = 'Petr Belohlavek <me@petrbel.cz>'
print()
class PscKonvertor:
"""Konvertuje postovni smerovaci cisla na prislusne okresy a kraje.
Vyhledavani je pro maximalni rychlost indexovane."""
_MODULE_PATH = os.path.dirname(os.path.abspath(__file__... | mit |
devanshdalal/scikit-learn | examples/applications/plot_out_of_core_classification.py | 51 | 13651 | """
======================================================
Out-of-core classification of text documents
======================================================
This is an example showing how scikit-learn can be used for classification
using an out-of-core approach: learning from data that doesn't fit into main
memory. ... | bsd-3-clause |
plotly/plotly.py | packages/python/plotly/plotly/tests/test_optional/test_px/test_px_input.py | 1 | 19349 | import plotly.express as px
import plotly.graph_objects as go
import numpy as np
import pandas as pd
import pytest
from plotly.express._core import build_dataframe
from pandas.testing import assert_frame_equal
def test_numpy():
fig = px.scatter(x=[1, 2, 3], y=[2, 3, 4], color=[1, 3, 9])
assert np.all(fig.data... | mit |
BoltzmannBrain/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/backends/__init__.py | 72 | 2225 |
import matplotlib
import inspect
import warnings
# ipython relies on interactive_bk being defined here
from matplotlib.rcsetup import interactive_bk
__all__ = ['backend','show','draw_if_interactive',
'new_figure_manager', 'backend_version']
backend = matplotlib.get_backend() # validates, to match all_bac... | agpl-3.0 |
466152112/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 |
karstenw/nodebox-pyobjc | examples/Extended Application/matplotlib/examples/misc/pythonic_matplotlib.py | 1 | 3300 | """
===================
Pythonic Matplotlib
===================
Some people prefer to write more pythonic, object-oriented code
rather than use the pyplot interface to matplotlib. This example shows
you how.
Unless you are an application developer, I recommend using part of the
pyplot interface, particularly the fig... | mit |
rs2/pandas | pandas/tests/indexes/ranges/test_range.py | 1 | 16923 | import numpy as np
import pytest
from pandas.core.dtypes.common import ensure_platform_int
import pandas as pd
from pandas import Float64Index, Index, Int64Index, RangeIndex
import pandas._testing as tm
from ..test_numeric import Numeric
# aliases to make some tests easier to read
RI = RangeIndex
I64 = Int64Index
F... | bsd-3-clause |
michelle192837/test-infra | hack/analyze-memory-profiles.py | 9 | 6137 | #!/usr/bin/env python3
# Copyright 2021 The Kubernetes Authors.
#
# 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 |
kjung/scikit-learn | sklearn/datasets/tests/test_kddcup99.py | 59 | 1336 | """Test kddcup99 loader. Only 'percent10' mode is tested, as the full data
is too big to use in unit-testing.
The test is skipped if the data wasn't previously fetched and saved to
scikit-learn data folder.
"""
import errno
from sklearn.datasets import fetch_kddcup99
from sklearn.utils.testing import assert_equal, S... | bsd-3-clause |
jmschrei/scikit-learn | examples/svm/plot_iris.py | 225 | 3252 | """
==================================================
Plot different SVM classifiers in the iris dataset
==================================================
Comparison of different linear SVM classifiers on a 2D projection of the iris
dataset. We only consider the first 2 features of this dataset:
- Sepal length
- Se... | bsd-3-clause |
valexandersaulys/airbnb_kaggle_contest | venv/lib/python3.4/site-packages/pandas/io/tests/test_sql.py | 9 | 102928 | """SQL io tests
The SQL tests are broken down in different classes:
- `PandasSQLTest`: base class with common methods for all test classes
- Tests for the public API (only tests with sqlite3)
- `_TestSQLApi` base class
- `TestSQLApi`: test the public API with sqlalchemy engine
- `TestSQLiteFallbackApi`: t... | gpl-2.0 |
xxd3vin/spp-sdk | opt/Python27/Lib/site-packages/numpy/lib/recfunctions.py | 23 | 34483 | """
Collection of utilities to manipulate structured arrays.
Most of these functions were initially implemented by John Hunter for matplotlib.
They have been rewritten and extended for convenience.
"""
import sys
import itertools
import numpy as np
import numpy.ma as ma
from numpy import ndarray, recarray
from nump... | mit |
harisbal/pandas | pandas/tests/series/test_duplicates.py | 2 | 4227 | # coding=utf-8
import numpy as np
import pytest
from pandas import Categorical, Series
import pandas.util.testing as tm
def test_value_counts_nunique():
# basics.rst doc example
series = Series(np.random.randn(500))
series[20:500] = np.nan
series[10:20] = 5000
result = series.nunique()
asser... | bsd-3-clause |
poldrack/myconnectome | myconnectome/rnaseq/predict_svm_behav_rnaseq.py | 2 | 2055 | """
use SVM to predict outcome variables based on connectivity
"""
import numpy
import sklearn.preprocessing
import sklearn.linear_model
import scipy.stats
from run_classification import run_classification
from load_myconnectome_data import *
xvar_names=['panas.positive','panas.negative','panas.fatigue','afterscan.A... | mit |
kdebrab/pandas | pandas/tests/indexes/multi/test_copy.py | 2 | 4111 | # -*- coding: utf-8 -*-
from copy import copy, deepcopy
import pandas.util.testing as tm
from pandas import (CategoricalIndex, IntervalIndex, MultiIndex, PeriodIndex,
RangeIndex, Series, compat)
def assert_multiindex_copied(copy, original):
# Levels should be (at least, shallow copied)
t... | bsd-3-clause |
yyjiang/scikit-learn | sklearn/feature_extraction/tests/test_text.py | 75 | 34122 | from __future__ import unicode_literals
import warnings
from sklearn.feature_extraction.text import strip_tags
from sklearn.feature_extraction.text import strip_accents_unicode
from sklearn.feature_extraction.text import strip_accents_ascii
from sklearn.feature_extraction.text import HashingVectorizer
from sklearn.fe... | bsd-3-clause |
nouiz/pylearn2 | pylearn2/models/svm.py | 21 | 3386 | """Wrappers for SVM models."""
__authors__ = "Ian Goodfellow"
__copyright__ = "Copyright 2010-2012, Universite de Montreal"
__credits__ = ["Ian Goodfellow"]
__license__ = "3-clause BSD"
__maintainer__ = "LISA Lab"
__email__ = "pylearn-dev@googlegroups"
import numpy as np
import warnings
try:
from sklearn.multicla... | bsd-3-clause |
sdvillal/manysources | manysources/analyses/better_or_worse_coocc.py | 1 | 6541 | '''
For each experiment: are the resulting losses (or AUC) better or worse than average?
'''
from manysources.analyses.losses import read_losses
from collections import defaultdict
import pandas as pd
import numpy as np
def average_loss(dset, feats, model, lso, calibration):
"""
At each expid, we get 1 loss p... | bsd-3-clause |
NelisVerhoef/scikit-learn | sklearn/tree/export.py | 78 | 15814 | """
This module defines export functions for decision trees.
"""
# Authors: Gilles Louppe <g.louppe@gmail.com>
# Peter Prettenhofer <peter.prettenhofer@gmail.com>
# Brian Holt <bdholt1@gmail.com>
# Noel Dawe <noel@dawe.me>
# Satrajit Gosh <satrajit.ghosh@gmail.com>
# Trevor... | bsd-3-clause |
datapythonista/pandas | pandas/core/internals/base.py | 1 | 4002 | """
Base class for the internal managers. Both BlockManager and ArrayManager
inherit from this class.
"""
from typing import (
List,
Optional,
TypeVar,
)
from pandas._typing import (
DtypeObj,
Shape,
final,
)
from pandas.errors import AbstractMethodError
from pandas.core.dtypes.cast import fin... | bsd-3-clause |
LohithBlaze/scikit-learn | examples/mixture/plot_gmm_classifier.py | 250 | 3918 | """
==================
GMM classification
==================
Demonstration of Gaussian mixture models for classification.
See :ref:`gmm` for more information on the estimator.
Plots predicted labels on both training and held out test data using a
variety of GMM classifiers on the iris dataset.
Compares GMMs with sp... | bsd-3-clause |
tbekolay/neurotools | neurotools/visualization/__init__.py | 1 | 6758 | import sys, os.path
import numpy
import tempfile, shutil
import logging
from neurotools import check_dependency
from neurotools.plotting import progress_bar
if check_dependency('matplotlib'):
from matplotlib.figure import Figure
from matplotlib.lines import Line2D
from matplotlib.backends.backend_agg impor... | gpl-2.0 |
mbayon/TFG-MachineLearning | vbig/lib/python2.7/site-packages/sklearn/cluster/tests/test_k_means.py | 7 | 32602 | """Testing for K-means"""
import sys
import numpy as np
from scipy import sparse as sp
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import SkipTest
from sklearn.utils.testing i... | mit |
benoitsteiner/tensorflow-opencl | tensorflow/python/estimator/inputs/pandas_io_test.py | 89 | 8340 | # Copyright 2015 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 |
uwescience/pulse2percept | examples/models/plot_horsager2009.py | 1 | 9470 | # -*- coding: utf-8 -*-
"""
===============================================================================
Horsager et al. (2009): Predicting temporal sensitivity
===============================================================================
This example shows how to use the
:py:class:`~pulse2percept.models.Horsager... | bsd-3-clause |
dssg/wikienergy | disaggregator/build/pandas/pandas/tests/test_msgpack/test_seq.py | 6 | 1439 | #!/usr/bin/env python
# coding: utf-8
from pandas import compat
from pandas.compat import u
import pandas.msgpack as msgpack
binarydata = [chr(i) for i in range(256)]
binarydata = "".join(binarydata)
if compat.PY3:
binarydata = binarydata.encode('utf-8')
def gen_binary_data(idx):
data = binarydata[:idx % 300... | mit |
toobaz/pandas | asv_bench/benchmarks/stat_ops.py | 1 | 4452 | import numpy as np
import pandas as pd
ops = ["mean", "sum", "median", "std", "skew", "kurt", "mad", "prod", "sem", "var"]
class FrameOps:
params = [ops, ["float", "int"], [0, 1], [True, False]]
param_names = ["op", "dtype", "axis", "use_bottleneck"]
def setup(self, op, dtype, axis, use_bottleneck):
... | bsd-3-clause |
ericfourrier/decam | decam/feature_importance.py | 1 | 5164 | # -*- coding: utf-8 -*-
"""
@author: kevin olivier
"""
import pandas as pd
import numpy as np
from sklearn.feature_selection import SelectKBest, f_classif
from sklearn.ensemble import RandomForestClassifier, GradientBoostingClassifier
class FeatureImportance:
def __init__(self, df, resp):
self.dataframe = df... | mit |
terkkila/scikit-learn | sklearn/pipeline.py | 162 | 21103 | """
The :mod:`sklearn.pipeline` module implements utilities to build a composite
estimator, as a chain of transforms and estimators.
"""
# Author: Edouard Duchesnay
# Gael Varoquaux
# Virgile Fritsch
# Alexandre Gramfort
# Lars Buitinck
# Licence: BSD
from collections import defaultdict... | bsd-3-clause |
BuddyVolly/OpenSARKit | lib/python/ost_regressor.py | 2 | 6757 | #! /usr/bin/python
# thanks to the great tutorial of Carlos de la Torre
# http://www.machinalis.com/blog/python-for-geospatial-data-processing/
import numpy as np
import os
from osgeo import gdal, ogr, osr
from sklearn import metrics
from sklearn.ensemble import RandomForestRegressor
# Tell GDAL to throw Python exce... | mit |
MatthieuBizien/scikit-learn | examples/cross_decomposition/plot_compare_cross_decomposition.py | 55 | 4761 | """
===================================
Compare cross decomposition methods
===================================
Simple usage of various cross decomposition algorithms:
- PLSCanonical
- PLSRegression, with multivariate response, a.k.a. PLS2
- PLSRegression, with univariate response, a.k.a. PLS1
- CCA
Given 2 multivari... | bsd-3-clause |
darioizzo/optimal_landing | indirect_method/falcon_landing.py | 1 | 16719 | """
Implements an indirect method to solve the optimal control
problem of a varying mass spacecraft controlled by one
thruster capable of vectoring.
Dario Izzo 2016
"""
from PyGMO.problem._base import base
from numpy.linalg import norm
from math import sqrt, sin, cos, atan2, pi
from scipy.integrate import odeint
f... | lgpl-3.0 |
Denisolt/Tensorflow_Chat_Bot | local/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/_sklearn.py | 153 | 6723 | # 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... | gpl-3.0 |
shikhardb/scikit-learn | sklearn/decomposition/pca.py | 24 | 22932 | """ Principal Component Analysis
"""
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Olivier Grisel <olivier.grisel@ensta.org>
# Mathieu Blondel <mathieu@mblondel.org>
# Denis A. Engemann <d.engemann@fz-juelich.de>
# Michael Eickenberg <michael.eickenberg@inria.fr>
#
# Lice... | bsd-3-clause |
karstenw/nodebox-pyobjc | examples/Extended Application/sklearn/examples/ensemble/plot_voting_decision_regions.py | 1 | 3238 | """
==================================================
Plot the decision boundaries of a VotingClassifier
==================================================
Plot the decision boundaries of a `VotingClassifier` for
two features of the Iris dataset.
Plot the class probabilities of the first sample in a toy dataset
pred... | mit |
DGrady/pandas | pandas/tests/io/msgpack/test_format.py | 25 | 2882 | # coding: utf-8
from pandas.io.msgpack import unpackb
def check(src, should, use_list=0):
assert unpackb(src, use_list=use_list) == should
def testSimpleValue():
check(b"\x93\xc0\xc2\xc3", (None, False, True, ))
def testFixnum():
check(b"\x92\x93\x00\x40\x7f\x93\xe0\xf0\xff", ((0,
... | bsd-3-clause |
RayMick/scikit-learn | sklearn/externals/joblib/parallel.py | 79 | 35628 | """
Helpers for embarrassingly parallel code.
"""
# Author: Gael Varoquaux < gael dot varoquaux at normalesup dot org >
# Copyright: 2010, Gael Varoquaux
# License: BSD 3 clause
from __future__ import division
import os
import sys
import gc
import warnings
from math import sqrt
import functools
import time
import thr... | bsd-3-clause |
akionakamura/scikit-learn | examples/cluster/plot_agglomerative_clustering.py | 343 | 2931 | """
Agglomerative clustering with and without structure
===================================================
This example shows the effect of imposing a connectivity graph to capture
local structure in the data. The graph is simply the graph of 20 nearest
neighbors.
Two consequences of imposing a connectivity can be s... | bsd-3-clause |
eg-zhang/h2o-2 | py/testdir_single_jvm/test_GLM2_score_same.py | 9 | 4631 |
## Dataset created from this:
#
# from sklearn.datasets import make_hastie_10_2
# import numpy as np
# i = 1000000
# f = 10
# (X,y) = make_hastie_10_2(n_samples=i,random_state=None)
# y.shape = (i,1)
# Y = np.hstack((X,y))
# np.savetxt('./1mx' + str(f) + '_hastie_10_2.data', Y, delimiter=',', fmt='%.2f');
import unit... | apache-2.0 |
PedroTrujilloV/nest-simulator | pynest/nest/voltage_trace.py | 12 | 6711 | # -*- coding: utf-8 -*-
#
# voltage_trace.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, ... | gpl-2.0 |
irisyuichan/news_topic_mining | news_topic_clustering.py | 1 | 8205 | """
=======================================
Clustering text documents using k-means
=======================================
This is an example showing how the scikit-learn can be used to cluster
documents by topics using a bag-of-words approach. This example uses
a scipy.sparse matrix to store the features instead of ... | mit |
iarroyof/distributionalSemanticStabilityThesis | mkl_regressor.py | 2 | 9784 | from modshogun import *
from numpy import *
from sklearn.metrics import r2_score
from scipy.stats import randint
from scipy import stats
from scipy.stats import randint as sp_randint
from scipy.stats import expon
import sys, os
import Gnuplot, Gnuplot.funcutils
class mkl_regressor():
def __init__(self, widths = N... | gpl-2.0 |
H3rsh3/odm-py-templating | example/templp.py | 2 | 3594 | import pandas as pd
import numpy as np
import shutil
import fileinput
import sys
import time
import subprocess
class Import_conf():
def __init__(self,i_data,i_base):
self.i_data = i_data
self.i_base = i_base
def generate_ic(self):
#--import config_data file
config_data = pd.read_csv("{0}".format(self.i_da... | gpl-3.0 |
badbytes/pymeg | meg/get.py | 1 | 1332 | """Return sensors and headshape positions"""
from msiread import getposted
from numpy import *
pdf=getposted.read()
hs=pdf.head_shape.hs_points
m=pdf.GetSignalMEGDevices()
x=[]; y=[]; z=[];
class headshape():
"""hs=pos.headshape.hsm"""
hsa=array(hs)
hsm=zeros((size(hsa),3))
for i in range(len(hsa)):
... | gpl-3.0 |
dpshelio/sunpy | sunpy/map/sources/trace.py | 2 | 3151 | """TRACE Map subclass definitions"""
#pylint: disable=W0221,W0222,E1101,E1121
__author__ = "Jack Ireland"
__email__ = "jack.ireland@nasa.gov"
import matplotlib.pyplot as plt
from astropy.visualization import LogStretch
from astropy.visualization.mpl_normalize import ImageNormalize
from sunpy.map import GenericMap
fr... | bsd-2-clause |
awalls-cx18/gnuradio | gr-filter/examples/reconstruction.py | 7 | 5011 | #!/usr/bin/env python
#
# Copyright 2010,2012,2013 Free Software Foundation, Inc.
#
# This file is part of GNU Radio
#
# GNU Radio is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3, or (at your ... | gpl-3.0 |
RBDA-F17/crime | code_drop_2/filter_clean_crime.py | 2 | 1179 | import os
import sys
import pandas as pd
from pyspark.sql.types import *
from pyspark.sql import Row, Column
from pyspark.sql.functions import *
from datetime import datetime
from pyspark import SparkConf, SparkContext
from pyspark.sql import SQLContext
from pyspark.sql.functions import udf
user = os. environ['USER']
... | gpl-3.0 |
robin-lai/scikit-learn | examples/linear_model/plot_sgd_comparison.py | 77 | 1820 | """
==================================
Comparing various online solvers
==================================
An example showing how different online solvers perform
on the hand-written digits dataset.
"""
# Author: Rob Zinkov <rob at zinkov dot com>
# License: BSD 3 clause
import numpy as np
import matplotlib.pyplot a... | bsd-3-clause |
metaml/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 |
alexsavio/scikit-learn | examples/model_selection/plot_underfitting_overfitting.py | 41 | 2672 | """
============================
Underfitting vs. Overfitting
============================
This example demonstrates the problems of underfitting and overfitting and
how we can use linear regression with polynomial features to approximate
nonlinear functions. The plot shows the function that we want to approximate,
wh... | bsd-3-clause |
hlin117/statsmodels | statsmodels/stats/power.py | 31 | 47523 | # -*- coding: utf-8 -*-
#pylint: disable-msg=W0142
"""Statistical power, solving for nobs, ... - trial version
Created on Sat Jan 12 21:48:06 2013
Author: Josef Perktold
Example
roundtrip - root with respect to all variables
calculated, desired
nobs 33.367204205 33.367204205
effect 0.5 0.5
alpha 0.05 0.05... | bsd-3-clause |
gibiansky/tensorflow | tensorflow/contrib/learn/python/learn/estimators/estimator_test.py | 3 | 38410 | # 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 |
maxplanck-ie/HiCExplorer | hicexplorer/hicCorrectMatrix.py | 1 | 31877 | import warnings
import sys
warnings.simplefilter(action="ignore", category=RuntimeWarning)
warnings.simplefilter(action="ignore", category=PendingDeprecationWarning)
import argparse
from past.builtins import zip
from scipy.sparse import lil_matrix
from hicexplorer.iterativeCorrection import iterativeCorrection
from hi... | gpl-2.0 |
marrcio/relate-kanji | resources/util/toolbox/graphictools.py | 1 | 1873 | import matplotlib.pyplot as plt
from collections import Counter
plt.ion()
def visualize_bars(iterable, width=0.5, color='b', counter_feed=False, high_dpi=True, transformation=lambda x:x):
if counter_feed:
c = iterable
else:
c = Counter(iterable)
if high_dpi:
plt.figure(dpi=200)
... | mit |
kou/arrow | python/pyarrow/tests/test_flight.py | 3 | 68243 | # 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 u... | apache-2.0 |
schets/LILAC | src/scripts/python/learn-grad.py | 2 | 3221 | import numpy as np
from sklearn import manifold, svm, preprocessing
import pylab as pl
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.ticker import NullFormatter
Axes3D
def read_data(gradname, scorename):
#could use numpy.loadtxt, but that blindly accepts nan values
slist = open(scorename, 'r').readlin... | bsd-3-clause |
brockk/clintrials | clintrials/dosefinding/efftox.py | 1 | 45709 | __author__ = 'Kristian Brock'
__contact__ = 'kristian.brock@gmail.com'
""" An implementation of Thall & Cook's EffTox design for dose-finding in clinical trials.
See:
Thall, P.F. and Cook, J.D. (2004). Dose-Finding Based on Efficacy-Toxicity Trade-Offs, Biometrics, 60: 684-693.
Cook, J.D. Efficacy-Toxicity trade-offs... | gpl-3.0 |
idontgetoutmuch/ParkingWestminster | load_SJWHS.py | 1 | 2784 | import pandas as pd
from pandas import DataFrame, Series
import numpy as np
import os
import csv
names = ["amount paid", "paid duration mins", "start date", "start day", "end date", "end day", "start time", "end time", "DesignationType", "Hours of Control", "Tariff", "Max Stay", "Spaces", "Street", "x coordinate... | apache-2.0 |
NMGRL/pychron | pychron/mv/locator.py | 2 | 28476 | # Copyright 2012 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/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, soft... | apache-2.0 |
e-koch/VLA_Lband | ancillary_data/HST/HI_properties_near_feedback.py | 1 | 17038 |
'''
Pull out HI properties (and/or others) from a set of point sources.
Create a distance map as a function of distance from the nearest source.
'''
import astropy.coordinates as coord
from astropy.table import Table, Column
import astropy.units as u
import astropy.constants as const
import numpy as np
from galaxies... | mit |
jrbadiabo/Coursera-Stanford-ML-Class | Python_Version/Ex1.Linear_Regresion_with_one_variable/ex1_multi.py | 1 | 3757 | from matplotlib import use
use('TkAgg')
import numpy as np
import matplotlib.pyplot as plt
from gradientDescentMulti import gradientDescentMulti
from normalEqn import normalEqn
from featureNormalize import featureNormalize
from show import show
# ================ Part 1: Feature Normalization ================
print '... | mit |
ndingwall/scikit-learn | examples/ensemble/plot_gradient_boosting_regression.py | 11 | 5041 | """
============================
Gradient Boosting regression
============================
This example demonstrates Gradient Boosting to produce a predictive
model from an ensemble of weak predictive models. Gradient boosting can be used
for regression and classification problems. Here, we will train a model to
tackl... | bsd-3-clause |
ycaihua/scikit-learn | sklearn/datasets/svmlight_format.py | 39 | 15319 | """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 |
sem-geologist/hyperspy | hyperspy/tests/mva/test_bss.py | 2 | 13019 | import pytest
import numpy as np
import numpy.testing as nt
from hyperspy._signals.signal1d import Signal1D
from hyperspy._signals.signal2d import Signal2D
from hyperspy.misc.machine_learning.import_sklearn import sklearn_installed
from hyperspy.datasets import artificial_data
def are_bss_components_equivalent(c1_li... | gpl-3.0 |
PabloPiaggi/plumed2 | user-doc/tutorials/others/ves-lugano2017-kinetics/TRAJECTORIES-1700K/cdf-analysis.py | 6 | 1134 | #!/usr/bin/env python
import numpy as np
from scipy.stats import ks_2samp
from scipy.optimize import curve_fit
from statsmodels.distributions.empirical_distribution import ECDF
import matplotlib.pyplot as plt
f=open('fpt.dat','r')
# define theoretical CDF
def func(x,tau):
return 1-np.exp(-x/tau)
x = []
count=0
... | lgpl-3.0 |
jmargeta/scikit-learn | sklearn/tests/test_multiclass.py | 3 | 12251 | import numpy as np
import warnings
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_false
from sklearn.utils.testing import ass... | bsd-3-clause |
HyukjinKwon/spark | python/pyspark/sql/dataframe.py | 9 | 102339 | #
# 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 |
white-lab/pyproteome | pyproteome/pathways/photon_ptm.py | 1 | 5508 |
from collections import OrderedDict
import io
import logging
import requests
import os
import tarfile
import uuid
import pyproteome as pyp
import brainrnaseq as brs
import pandas as pd
import numpy as np
LOGGER = logging.getLogger('pathways.photon_ptm')
try:
from genemap.mappers import EnsemblMapper
except Impo... | bsd-2-clause |
SteVwonder/MusiGraph | musigraph.py | 1 | 6030 | import requests
import json
import argparse
from hashlib import md5
import networkx as nx
import pygraphviz as pgv
import matplotlib.pyplot as plt
API_ROOT = "http://ws.audioscrobbler.com/2.0/"
class ConfigException(Exception):
pass
class APIException(Exception):
pass
def parse_config(config_path):
with... | apache-2.0 |
Srisai85/scikit-learn | sklearn/calibration.py | 137 | 18876 | """Calibration of predicted probabilities."""
# Author: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Balazs Kegl <balazs.kegl@gmail.com>
# Jan Hendrik Metzen <jhm@informatik.uni-bremen.de>
# Mathieu Blondel <mathieu@mblondel.org>
#
# License: BSD 3 clause
from __future__ impo... | bsd-3-clause |
bittremieux/ANN-SoLo | src/setup.py | 1 | 3715 | import codecs
import os
import setuptools
import numpy as np
try:
import Cython.Distutils
except ImportError:
use_cython = False
else:
use_cython = True
def read(rel_path):
here = os.path.abspath(os.path.dirname(__file__))
# Intentionally *not* adding an encoding option to open, See:
# htt... | apache-2.0 |
kevin-intel/scikit-learn | examples/miscellaneous/plot_display_object_visualization.py | 17 | 3676 | """
===================================
Visualizations with Display Objects
===================================
.. currentmodule:: sklearn.metrics
In this example, we will construct display objects,
:class:`ConfusionMatrixDisplay`, :class:`RocCurveDisplay`, and
:class:`PrecisionRecallDisplay` directly from their resp... | bsd-3-clause |
Deepomatic/DIGITS | digits/dataset/generic/views.py | 3 | 7099 | # Copyright (c) 2016-2017, NVIDIA CORPORATION. All rights reserved.
from __future__ import absolute_import
import os
# Find the best implementation available
try:
from cStringIO import StringIO
except ImportError:
from StringIO import StringIO
import caffe_pb2
import flask
import matplotlib as mpl
import mat... | bsd-3-clause |
russel1237/scikit-learn | examples/missing_values.py | 233 | 3056 | """
======================================================
Imputing missing values before building an estimator
======================================================
This example shows that imputing the missing values can give better results
than discarding the samples containing any missing value.
Imputing does not ... | bsd-3-clause |
herilalaina/scikit-learn | examples/linear_model/plot_sgd_comparison.py | 29 | 1873 | """
==================================
Comparing various online solvers
==================================
An example showing how different online solvers perform
on the hand-written digits dataset.
"""
# Author: Rob Zinkov <rob at zinkov dot com>
# License: BSD 3 clause
import numpy as np
import matplotlib.pyplot a... | bsd-3-clause |
nchammas/spark | python/pyspark/sql/pandas/utils.py | 6 | 2633 | #
# 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 |
dmitriz/zipline | tests/pipeline/test_engine.py | 3 | 26134 | """
Tests for SimplePipelineEngine
"""
from __future__ import division
from collections import OrderedDict
from unittest import TestCase
from itertools import product
from numpy import (
array,
full,
nan,
tile,
zeros,
float32,
concatenate,
)
from pandas import (
DataFrame,
date_rang... | apache-2.0 |
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