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 |
|---|---|---|---|---|---|
imaculate/scikit-learn | sklearn/datasets/tests/test_mldata.py | 384 | 5221 | """Test functionality of mldata fetching utilities."""
import os
import shutil
import tempfile
import scipy as sp
from sklearn import datasets
from sklearn.datasets import mldata_filename, fetch_mldata
from sklearn.utils.testing import assert_in
from sklearn.utils.testing import assert_not_in
from sklearn.utils.test... | bsd-3-clause |
bzero/statsmodels | docs/source/plots/graphics_gofplots_qqplot.py | 38 | 1911 | # -*- coding: utf-8 -*-
"""
Created on Sun May 06 05:32:15 2012
Author: Josef Perktold
editted by: Paul Hobson (2012-08-19)
"""
from scipy import stats
from matplotlib import pyplot as plt
import statsmodels.api as sm
#example from docstring
data = sm.datasets.longley.load()
data.exog = sm.add_constant(data.exog, pre... | bsd-3-clause |
cauchycui/scikit-learn | sklearn/linear_model/bayes.py | 220 | 15248 | """
Various bayesian regression
"""
from __future__ import print_function
# Authors: V. Michel, F. Pedregosa, A. Gramfort
# License: BSD 3 clause
from math import log
import numpy as np
from scipy import linalg
from .base import LinearModel
from ..base import RegressorMixin
from ..utils.extmath import fast_logdet, p... | bsd-3-clause |
Diego-debian/FREE_POPS_1.0 | free_pops/bin/g_Estadi.py | 1 | 3586 | #!/usr/bin/python
# *-* coding:utf-8 *-*
# Este script es sofware libre. Puede redistribuirlo y/o modificarlo bajo
# los terminos de la licencia pública general de GNU, según es publicada
# por la free software fundation bien la versión 3 de la misma licencia
# o de cualquier versión posterior. (según su elección ).... | gpl-3.0 |
kevinlee9/cnn-text-classification-tf | text_cnn.py | 1 | 4784 | import tensorflow as tf
import numpy as np
from gensim.models.keyedvectors import KeyedVectors
import sklearn as sk
class TextCNN(object):
"""
A CNN for text classification.
Uses an embedding layer, followed by a convolutional, max-pooling and softmax layer.
"""
def __init__(
self, sequence_l... | apache-2.0 |
mwaskom/seaborn | examples/kde_ridgeplot.py | 2 | 1279 | """
Overlapping densities ('ridge plot')
====================================
"""
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
sns.set_theme(style="white", rc={"axes.facecolor": (0, 0, 0, 0)})
# Create the data
rs = np.random.RandomState(1979)
x = rs.randn(500)
g = np.... | bsd-3-clause |
cauchycui/scikit-learn | examples/cluster/plot_lena_compress.py | 271 | 2229 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Vector Quantization Example
=========================================================
The classic image processing example, Lena, an 8-bit grayscale
bit-depth, 512 x 512 sized image, is used here to illustrate
how ... | bsd-3-clause |
ConeyLiu/spark | python/pyspark/sql/pandas/typehints.py | 8 | 6323 | #
# 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 |
gregcaporaso/qiime | setup.py | 6 | 15094 | #!/usr/bin/env python
# File created on 17 Feb 2010
from __future__ import division
import re
import sys
from setuptools import setup
from stat import S_IEXEC
from os import (chdir, getcwd, listdir, chmod, walk, rename, remove, chmod,
stat, devnull, environ)
from os.path import join, abspath
from subpr... | gpl-2.0 |
neurodroid/stimfit | src/stimfit/py/embedded_mpl.py | 4 | 4111 | #===========================================================================
# embedded_mpl.py
# 2011.02.05
# Don't modify this file unless you know what you are doing!!!
#===========================================================================
"""
embedded_mpl.py
starting code to embed a matplotlib wx figure into ... | gpl-2.0 |
MohammedWasim/scikit-learn | sklearn/decomposition/tests/test_factor_analysis.py | 222 | 3055 | # Author: Christian Osendorfer <osendorf@gmail.com>
# Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Licence: BSD3
import numpy as np
from sklearn.utils.testing import assert_warns
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_greater
from sklearn.utils.testing im... | bsd-3-clause |
shikhardb/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 |
kevin-intel/scikit-learn | examples/linear_model/plot_ols_ridge_variance.py | 39 | 1968 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Ordinary Least Squares and Ridge Regression Variance
=========================================================
Due to the few points in each dimension and the straight
line that linear regression uses to follow thes... | bsd-3-clause |
cedadev/jasmin_cis | cis/plotting/formatter.py | 3 | 1607 | from matplotlib.ticker import LogFormatter, is_close_to_int, nearest_long
from matplotlib import rcParams
import math
class LogFormatterMathtextSpecial(LogFormatter):
"""
Special formatter for color log axis, using notation such as 2.3 x 10 ^ 4.
This is a modified version of LogFormatterMathtext supplied ... | gpl-3.0 |
lukeiwanski/tensorflow | tensorflow/contrib/learn/python/learn/learn_io/__init__.py | 42 | 2656 | # 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 |
nesterione/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 |
xavierwu/scikit-learn | examples/linear_model/plot_ols_ridge_variance.py | 387 | 2060 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Ordinary Least Squares and Ridge Regression Variance
=========================================================
Due to the few points in each dimension and the straight
line that linear regression uses to follow thes... | bsd-3-clause |
tongwang01/tensorflow | tensorflow/contrib/learn/python/learn/estimators/dnn_linear_combined_test.py | 2 | 45785 | # 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 |
project-asap/IReS-Platform | asap-platform/asap-server/asapLibrary/operators/lr_classify_spark/imr_tools.py | 5 | 5668 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
tools for imr datasets
@author: Chris Mantas
@contact: the1pro@gmail.com
@since: Created on 2016-02-12
@todo: custom formats, break up big lines
@license: http://www.apache.org/licenses/LICENSE-2.0 Apache License
"""
from ast import literal_eval
from collections impor... | apache-2.0 |
JesseLivezey/sklearn-theano | examples/plot_overfeat_layer1_filters.py | 9 | 1724 | """
====================================
Visualization of first layer filters
====================================
The first layers of convolutional neural networks often have very "human
interpretable" values, as seen in these example plots. Visually, these filters
are similar to other filters used in computer vision... | bsd-3-clause |
tawsifkhan/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 |
xguse/ggplot | ggplot/stats/stat_function.py | 12 | 4439 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import numpy as np
import pandas as pd
from ggplot.utils import make_iterable_ntimes
from ggplot.utils.exceptions import GgplotError
from .stat import stat
class stat_function(stat):
"""
Superimpose a... | bsd-2-clause |
tongwang01/tensorflow | tensorflow/contrib/learn/python/learn/estimators/multioutput_test.py | 15 | 1675 | # 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 |
youprofit/scikit-image | doc/examples/plot_seam_carving.py | 13 | 2351 | """
============
Seam Carving
============
This example demonstrates how images can be resized using seam carving [1]_.
Resizing to a new aspect ratio distorts image contents. Seam carving attempts
to resize *without* distortion, by removing regions of an image which are less
important. In this example we are using th... | bsd-3-clause |
ddemidov/vexcl | docs/conf.py | 1 | 9667 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# VexCL documentation build configuration file, created by
# sphinx-quickstart on Fri Mar 11 13:53:31 2016.
#
# 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
# auto... | mit |
joshbohde/scikit-learn | sklearn/externals/joblib/__init__.py | 2 | 4050 | """ Joblib is a set of tools to provide **lightweight pipelining in
Python**. In particular, joblib offers:
1. transparent disk-caching of the output values and lazy re-evaluation
(memoize pattern)
2. easy simple parallel computing
3. logging and tracing of the execution
Joblib is optimized to be **fast*... | bsd-3-clause |
yanlend/scikit-learn | examples/ensemble/plot_adaboost_multiclass.py | 354 | 4124 | """
=====================================
Multi-class AdaBoosted Decision Trees
=====================================
This example reproduces Figure 1 of Zhu et al [1] and shows how boosting can
improve prediction accuracy on a multi-class problem. The classification
dataset is constructed by taking a ten-dimensional ... | bsd-3-clause |
mikaem/spectralDNS | tests/OrrSommerfeldr.py | 4 | 8316 | """Orr-Sommerfeld"""
import warnings
from numpy import real, pi, exp, zeros, imag, sqrt, log10
from spectralDNS import config, get_solver, solve
from spectralDNS.utilities import dx
#from spectralDNS.utilities import reset_profile
from OrrSommerfeld_shen import OrrSommerfeld
try:
import matplotlib.pyplot as plt
... | gpl-3.0 |
rlowrance/mlpack | delessandro_utilities.py | 1 | 5720 | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import sklearn
import math
from sklearn.metrics import roc_curve, auc
import pickle
def evenSplit(dat,fld):
'''
Evenly splits the data on a given binary field, returns a shuffled dataframe
'''
pos=dat[(dat[fld]==1)]
neg=dat[(dat... | mit |
voxlol/scikit-learn | sklearn/ensemble/__init__.py | 217 | 1307 | """
The :mod:`sklearn.ensemble` module includes ensemble-based methods for
classification and regression.
"""
from .base import BaseEnsemble
from .forest import RandomForestClassifier
from .forest import RandomForestRegressor
from .forest import RandomTreesEmbedding
from .forest import ExtraTreesClassifier
from .fores... | bsd-3-clause |
JT5D/scikit-learn | sklearn/manifold/tests/test_locally_linear.py | 4 | 4824 | from itertools import product
import numpy as np
from nose.tools import assert_true
from numpy.testing import assert_almost_equal, assert_array_almost_equal
from sklearn import neighbors, manifold
from sklearn.manifold.locally_linear import barycenter_kneighbors_graph
from sklearn.utils.testing import assert_less
from... | bsd-3-clause |
SummaLabs/DLS | app/backend/core/datasets/dbbuilder.py | 1 | 9245 | #!/usr/bin/python
# -*- coding: utf-8 -*-
__author__ = 'ar'
import os
import sys
import glob
import fnmatch
import numpy as np
import json
import lmdb
import matplotlib.pyplot as plt
from datetime import datetime
import copy
import shutil
import skimage.io as skio
from dbhelpers import DBImageImportReader, DBImage... | mit |
subhacom/moose-core | python/moose/genesis/writeKkit.py | 1 | 29153 | """ Chemical Signalling model loaded into moose can be save into Genesis-Kkit format """
__author__ = "Harsha Rani"
__copyright__ = "Copyright 2017, Harsha Rani and NCBS Bangalore"
__credits__ = ["NCBS Bangalore"]
__license__ = "GNU GPL"
__version__ = "1.0.0"
__maintainer__ ... | gpl-3.0 |
zorroblue/scikit-learn | examples/ensemble/plot_ensemble_oob.py | 29 | 3266 | """
=============================
OOB Errors for Random Forests
=============================
The ``RandomForestClassifier`` is trained using *bootstrap aggregation*, where
each new tree is fit from a bootstrap sample of the training observations
:math:`z_i = (x_i, y_i)`. The *out-of-bag* (OOB) error is the average er... | bsd-3-clause |
Tong-Chen/scikit-learn | sklearn/feature_extraction/dict_vectorizer.py | 7 | 10162 | # Author: Lars Buitinck <L.J.Buitinck@uva.nl>
# License: BSD 3 clause
from array import array
from collections import Mapping
from operator import itemgetter
import numpy as np
import scipy.sparse as sp
from ..base import BaseEstimator, TransformerMixin
from ..externals import six
from ..externals.six.moves import x... | bsd-3-clause |
PROSIC/prosic-evaluation | scripts/plot-allelefreq-estimation.py | 1 | 2979 | from itertools import product
import math
import matplotlib
matplotlib.use("agg")
from matplotlib import pyplot as plt
import seaborn as sns
import pandas as pd
import common
import numpy as np
MIN_CALLS = 10
vartype = snakemake.wildcards.vartype
colors = common.get_colors(snakemake.config)
truth = common.load_vari... | mit |
rsignell-usgs/notebook | UGRID/NECOFS_wave_levels.py | 1 | 4737 |
# coding: utf-8
# # Extract NECOFS data using NetCDF4-Python and analyze/visualize with Pandas
# In[1]:
# Plot forecast water levels from NECOFS model from list of lon,lat locations
# (uses the nearest point, no interpolation)
import netCDF4
import datetime as dt
import pandas as pd
import numpy as np
import matplo... | mit |
jniediek/mne-python | tutorials/plot_stats_cluster_methods.py | 6 | 8607 | # doc:slow-example
"""
.. _tut_stats_cluster_methods:
======================================================
Permutation t-test on toy data with spatial clustering
======================================================
Following the illustrative example of Ridgway et al. 2012,
this demonstrates some basic ideas behin... | bsd-3-clause |
cpcloud/dask | dask/dataframe/hashing.py | 1 | 6179 | from __future__ import absolute_import, division, print_function
import numpy as np
import pandas as pd
from pandas.types.common import (is_categorical_dtype, is_numeric_dtype,
is_datetime64_dtype, is_timedelta64_dtype)
from pandas.lib import is_bool_array
from .utils import PANDAS_V... | bsd-3-clause |
potash/scikit-learn | sklearn/cross_decomposition/pls_.py | 35 | 30767 | """
The :mod:`sklearn.pls` module implements Partial Least Squares (PLS).
"""
# Author: Edouard Duchesnay <edouard.duchesnay@cea.fr>
# License: BSD 3 clause
from distutils.version import LooseVersion
from sklearn.utils.extmath import svd_flip
from ..base import BaseEstimator, RegressorMixin, TransformerMixin
from ..u... | bsd-3-clause |
jreback/pandas | pandas/tests/series/methods/test_fillna.py | 1 | 27814 | from datetime import datetime, timedelta
import numpy as np
import pytest
import pytz
from pandas import (
Categorical,
DataFrame,
DatetimeIndex,
NaT,
Period,
Series,
Timedelta,
Timestamp,
isna,
)
import pandas._testing as tm
class TestSeriesFillNA:
def test_fillna_nat(self):... | bsd-3-clause |
AndreiBarsan/visualqa | visualqa/evaluateMLP.py | 1 | 5309 | """
Evaluates a model trained by `trainMLP`.
TODO(andrei): Integrate with training script for convenience.
"""
try:
# Keep this import on top!
from spacy.en import English
except:
# Shit, son.
raise
import click
from os.path import join as pjoin
import argparse
from keras.models import model_from_json... | apache-2.0 |
DougBurke/astropy | astropy/visualization/wcsaxes/transforms.py | 2 | 9202 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
# Note: This file incldues code dervived from pywcsgrid2
#
# This file contains Matplotlib transformation objects (e.g. from pixel to world
# coordinates, but also world-to-world).
import abc
import numpy as np
from matplotlib.path import Path
from ma... | bsd-3-clause |
ThomasMiconi/htmresearch | projects/l2_pooling/multi_column_synapse_sampling.py | 2 | 18276 | # 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 program is free software: you can redistribute it and/or modify
# it under the ... | agpl-3.0 |
GuessWhoSamFoo/pandas | pandas/tests/scalar/timestamp/test_arithmetic.py | 2 | 4035 | # -*- coding: utf-8 -*-
from datetime import datetime, timedelta
import numpy as np
import pytest
from pandas.compat import long
from pandas import Timedelta, Timestamp
import pandas.util.testing as tm
from pandas.tseries import offsets
from pandas.tseries.frequencies import to_offset
class TestTimestampArithmeti... | bsd-3-clause |
scottstanie/scottstanie.github.io | scripts/paths.py | 1 | 5798 | import numpy as np
from queue import PriorityQueue
from collections import defaultdict
import matplotlib.pyplot as plt
import matplotlib.animation
def dijkstra(graph, src, dest):
"""Find shortest path from src to dest
graph:
dict[list[(int, int)]]: {node: [adj_node1, adj_node2,...]}
src (int)... | mit |
liberatorqjw/scikit-learn | sklearn/decomposition/__init__.py | 99 | 1331 | """
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 |
tony810430/flink | flink-python/pyflink/fn_execution/coder_impl_slow.py | 6 | 25554 | ################################################################################
# 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... | apache-2.0 |
cauchycui/scikit-learn | sklearn/linear_model/tests/test_ransac.py | 216 | 13290 | import numpy as np
from numpy.testing import assert_equal, assert_raises
from numpy.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_raises_regexp
from scipy import sparse
from sklearn.utils.testing import assert_less
from sklearn.linear_model import LinearRegression, RANSACRegressor
f... | bsd-3-clause |
kjung/scikit-learn | sklearn/linear_model/setup.py | 146 | 1713 | 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
config = Configuration('linear_model', parent_package, top_path)
cblas_libs, blas_info = get_blas_info... | bsd-3-clause |
eranroz/dnase | src/data_provider/SeqLoader.py | 1 | 18864 | """
General utility class for accessing pickle data files and for simple transformations
Generally data is stored as dict of arrays, as dumped and compressed file.
using pytables is probably the best approach but we may have problems with portability
(or easy installation in different environments)
so here we use simp... | mit |
ilayn/scipy | scipy/integrate/_bvp.py | 16 | 41051 | """Boundary value problem solver."""
from warnings import warn
import numpy as np
from numpy.linalg import pinv
from scipy.sparse import coo_matrix, csc_matrix
from scipy.sparse.linalg import splu
from scipy.optimize import OptimizeResult
EPS = np.finfo(float).eps
def estimate_fun_jac(fun, x, y, p, f0=None):
... | bsd-3-clause |
cedar10b/travelapp | airports.py | 1 | 10650 | # -*- coding: utf-8 -*-
import urllib2
import numpy as np
import pandas as pd
from bs4 import BeautifulSoup
from sql_functions import *
df = read_table('cities')
# collect airport codes
# first, find the closest airport to each city
# also check: http://www.closestairportto.com/cities/
airports = pd.DataFrame([], co... | mit |
epitron/youtube-dl | youtube_dl/extractor/wsj.py | 30 | 4694 | # coding: utf-8
from __future__ import unicode_literals
from .common import InfoExtractor
from ..utils import (
int_or_none,
float_or_none,
unified_strdate,
)
class WSJIE(InfoExtractor):
_VALID_URL = r'''(?x)
(?:
https?://video-api\.wsj\.com/api-vid... | unlicense |
adamgreenhall/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 |
mugizico/scikit-learn | examples/ensemble/plot_adaboost_regression.py | 311 | 1529 | """
======================================
Decision Tree Regression with AdaBoost
======================================
A decision tree is boosted using the AdaBoost.R2 [1] algorithm on a 1D
sinusoidal dataset with a small amount of Gaussian noise.
299 boosts (300 decision trees) is compared with a single decision tr... | bsd-3-clause |
dreuven/SampleSparse | SampleSparse/scripts/PersonalPlotting.py | 3 | 9713 | import matplotlib.pyplot as plt
import numpy as np
import matplotlib.cm as cm
class PPlotting:
root_directory = None
def __init__(self, directory):
# try:
# str(directory)
# except:
# print("Cannot convert input to string. Put in a name!")
self.root_directory = st... | gpl-3.0 |
zguangyu/rts2 | scripts/u_point/u_select.py | 1 | 7976 | #!/usr/bin/env python3
# (C) 2016, Markus Wildi, wildi.markus@bluewin.ch
#
# 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 2, or (at your option)
# any later version.
#
# ... | gpl-2.0 |
djgagne/scikit-learn | examples/ensemble/plot_gradient_boosting_oob.py | 230 | 4762 | """
======================================
Gradient Boosting Out-of-Bag estimates
======================================
Out-of-bag (OOB) estimates can be a useful heuristic to estimate
the "optimal" number of boosting iterations.
OOB estimates are almost identical to cross-validation estimates but
they can be compute... | bsd-3-clause |
sepehr125/pybrain | pybrain/tools/plotting/multiline.py | 25 | 7884 | # $Id$
__author__ = 'Martin Felder and Frank Sehnke'
import math, imp
from matplotlib.lines import Line2D
from pylab import clf, plot, axes, show, xlabel, ylabel, savefig, ioff, draw_if_interactive
class MultilinePlotter:
""" Basic plotting class build on pylab
Implementing by instancing the class with the nu... | bsd-3-clause |
kayarre/Tools | hist/process_case.py | 1 | 8337 | # import pickle
# import pyvips
import os
import pandas as pd
# import numpy as np
import SimpleITK as sitk
import networkx as nx
import pickle
import copy
# import itk
import matplotlib.pyplot as plt
# from ipywidgets import interact, fixed
# from IPython.display import clear_output
import logging
logging.basicCo... | bsd-2-clause |
vagonbar/GNUnetwork | gwn/blocks/libio/gnuradio/new/.grc_gnuradio/read_files_plot.py | 1 | 3351 | # -*- coding: utf-8 -*-
"""
Created on Sun Nov 23 08:54:25 2014
@author: belza
"""
import scipy
from gnuradio import gr
from gnuradio import blocks
import matplotlib.pyplot as plt
def frombitstohex(bits):
vbytes = []
for b in range(len(bits) / 8):
byte = bits[b*8:(b+1)*8]
i=0
res=0
... | gpl-3.0 |
onyxfish/fever | agatecharts/table.py | 2 | 5012 | #!/usr/bin/env python
from matplotlib import pyplot
from agatecharts.charts import Bars, Columns, Lines, Scatter
from agatecharts.utils import round_limits
#: Default rendered chart size in inches
DEFAULT_SIZE = (8, 8)
#: Default rendered chart dpi
DEFAULT_DPI = 72
class TableCharts(object):
def bar_chart(self... | mit |
btel/svg_utils | docs/source/tutorials/scripts/anscombe.py | 1 | 1998 | #!/usr/bin/env python3
"""
Edward Tufte uses this example from Anscombe to show 4 datasets of x
and y that have the same mean, standard deviation, and regression
line, but which are qualitatively different.
matplotlib fun for a rainy day
Downloaded from: http://matplotlib.sourceforge.net/examples/pylab_examples/ansc... | mit |
devanshdalal/scikit-learn | sklearn/neighbors/tests/test_kd_tree.py | 26 | 7800 | import numpy as np
from numpy.testing import assert_array_almost_equal
from sklearn.neighbors.kd_tree import (KDTree, NeighborsHeap,
simultaneous_sort, kernel_norm,
nodeheap_sort, DTYPE, ITYPE)
from sklearn.neighbors.dist_metrics import Dista... | bsd-3-clause |
etkirsch/scikit-learn | sklearn/manifold/isomap.py | 229 | 7169 | """Isomap for manifold learning"""
# Author: Jake Vanderplas -- <vanderplas@astro.washington.edu>
# License: BSD 3 clause (C) 2011
import numpy as np
from ..base import BaseEstimator, TransformerMixin
from ..neighbors import NearestNeighbors, kneighbors_graph
from ..utils import check_array
from ..utils.graph import... | bsd-3-clause |
alphaBenj/zipline | tests/test_fetcher.py | 5 | 20667 | #
# Copyright 2015 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 |
tcheehow/MissionPlanner | Lib/site-packages/numpy/lib/polynomial.py | 58 | 35930 | """
Functions to operate on polynomials.
"""
__all__ = ['poly', 'roots', 'polyint', 'polyder', 'polyadd',
'polysub', 'polymul', 'polydiv', 'polyval', 'poly1d',
'polyfit', 'RankWarning']
import re
import warnings
import numpy.core.numeric as NX
from numpy.core import isscalar, abs, finfo, atleas... | gpl-3.0 |
Mistobaan/tensorflow | tensorflow/contrib/learn/python/learn/learn_io/pandas_io.py | 92 | 4535 | # 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 |
bjodah/fastinverse | examples/invnewton_main.py | 1 | 2866 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import print_function, division, absolute_import, unicode_literals
import logging
import os
import time
import sys
import argh
import numpy as np
import sympy
from sympy.parsing.sympy_parser import (
parse_expr, standard_transformations,
implicit_... | bsd-2-clause |
pypot/scikit-learn | examples/text/mlcomp_sparse_document_classification.py | 292 | 4498 | """
========================================================
Classification of text documents: using a MLComp dataset
========================================================
This is an example showing how the scikit-learn can be used to classify
documents by topics using a bag-of-words approach. This example uses
a s... | bsd-3-clause |
chongyangma/python-machine-learning-book | code/optional-py-scripts/ch03.py | 4 | 12944 | # Sebastian Raschka, 2015 (http://sebastianraschka.com)
# Python Machine Learning - Code Examples
#
# Chapter 3 - A Tour of Machine Learning Classifiers Using Scikit-Learn
#
# S. Raschka. Python Machine Learning. Packt Publishing Ltd., 2015.
# GitHub Repo: https://github.com/rasbt/python-machine-learning-book
#
# Licen... | mit |
raymak/contextualfeaturerecommender | phase2/analysis/cross_user_analysis.py | 1 | 17225 | #!/usr/bin/env python
"""
Recursively searches through the jsonl files in the given root directory (or the current directory by default)
and extracts variables of interest for each user. It then generates, prints, and saves cross-user data reports and data frames.
input:
[implicit] current working directory... | mpl-2.0 |
alexcpsec/coursera-compinvesting1-hw | HW4/analyse.py | 2 | 1966 | ## Computational Investing I
## HW 3 - analyse.py
##
## Author: alexcpsec
import pandas as pd
import pandas.io.parsers as pd_par
import numpy as np
import math
import copy
import QSTK.qstkutil.qsdateutil as du
import datetime as dt
import QSTK.qstkutil.DataAccess as da
import QSTK.qstkutil.tsutil as tsu
NUM_TRADING_D... | mit |
CrazyGuo/bokeh | bokeh/session.py | 42 | 20253 | ''' The session module provides the Session class, which encapsulates a
connection to a Document that resides on a Bokeh server.
The Session class provides methods for creating, loading and storing
documents and objects, as well as methods for user-authentication. These
are useful when the server is run in multi-user ... | bsd-3-clause |
mcm326/programingworkshop | Python/pandas_and_parallel/meso_surface.py | 8 | 2237 | import pandas as pd
import os
import datetime as dt
import numpy as np
import mesonet_calculations
from plotting import sfc_plot
''' For reading in and creating surface plots of mesonet data in a given time
interval saved in folders in the current working directory for each variable
plotted
'''
variables = {'temp... | mit |
jhamman/xarray | xarray/tests/test_sparse.py | 1 | 27235 | import pickle
from textwrap import dedent
import numpy as np
import pandas as pd
import pytest
import xarray as xr
import xarray.ufuncs as xu
from xarray import DataArray, Variable
from xarray.core.npcompat import IS_NEP18_ACTIVE
from xarray.core.pycompat import sparse_array_type
from . import assert_equal, assert_i... | apache-2.0 |
vipul1409/zeppelin | interpreter/lib/python/backend_zinline.py | 61 | 11831 | # 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 use ... | apache-2.0 |
craigcitro/pydatalab | solutionbox/image_classification/mltoolbox/image/classification/_util.py | 6 | 9918 | # Copyright 2017 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | apache-2.0 |
Basil-M/AMGEN-Summer-Project-2017 | python/code/Random walker/test_niifti.py | 1 | 2531 | import numpy as np
import niipy as nii
import matplotlib.pyplot as plt
from skimage.segmentation import random_walker
from skimage.data import binary_blobs
from skimage.exposure import rescale_intensity
import skimage
FOLDER_PATH= "/scratch/python/datasets/ACDC/ACDC_challenge_20170617/"
patient = 1
frame = 1
debug = 0... | mit |
mjgrav2001/scikit-learn | examples/linear_model/plot_lasso_model_selection.py | 311 | 5431 | """
===================================================
Lasso model selection: Cross-Validation / AIC / BIC
===================================================
Use the Akaike information criterion (AIC), the Bayes Information
criterion (BIC) and cross-validation to select an optimal value
of the regularization paramet... | bsd-3-clause |
unsiloai/syntaxnet-ops-hack | tensorflow/contrib/learn/python/learn/learn_io/data_feeder_test.py | 71 | 12923 | # 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 |
cbertinato/pandas | pandas/tseries/holiday.py | 1 | 16245 | from datetime import datetime, timedelta
from typing import List
import warnings
from dateutil.relativedelta import FR, MO, SA, SU, TH, TU, WE # noqa
import numpy as np
from pandas.errors import PerformanceWarning
from pandas import DateOffset, Series, Timestamp, date_range
from pandas.tseries.offsets import Day, ... | bsd-3-clause |
pratapvardhan/pandas | pandas/io/sas/sasreader.py | 14 | 2558 | """
Read SAS sas7bdat or xport files.
"""
from pandas import compat
from pandas.io.common import _stringify_path
def read_sas(filepath_or_buffer, format=None, index=None, encoding=None,
chunksize=None, iterator=False):
"""
Read SAS files stored as either XPORT or SAS7BDAT format files.
Param... | bsd-3-clause |
umuzungu/zipline | zipline/assets/assets.py | 3 | 36849 | # Copyright 2015 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 writ... | apache-2.0 |
numenta/nupic.research | projects/visual_recognition_grid_cells/SDR_decoder.py | 3 | 7700 | # Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2020, 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 program is free software: you can redistribute it and/or modify
# it unde... | agpl-3.0 |
nomadcube/scikit-learn | examples/plot_multioutput_face_completion.py | 330 | 3019 | """
==============================================
Face completion with a multi-output estimators
==============================================
This example shows the use of multi-output estimator to complete images.
The goal is to predict the lower half of a face given its upper half.
The first column of images sho... | bsd-3-clause |
yunfeilu/scikit-learn | sklearn/manifold/setup.py | 99 | 1243 | import os
from os.path import join
import numpy
from numpy.distutils.misc_util import Configuration
from sklearn._build_utils import get_blas_info
def configuration(parent_package="", top_path=None):
config = Configuration("manifold", parent_package, top_path)
libraries = []
if os.name == 'posix':
... | bsd-3-clause |
tansey/vsmrfs | vsmrfs/run_node_learning.py | 2 | 13217 | import matplotlib
matplotlib.use('Agg')
from matplotlib import cm, colors
import matplotlib.pyplot as plt
import numpy as np
import scipy.sparse as sps
import argparse
import csv
import sys
from node_learning import *
from exponential_families import *
from utils import *
FIG_FONTSIZE = 18
FIG_TITLE_FONTSIZE = 28
FIG... | mit |
BigDataforYou/movie_recommendation_workshop_1 | big_data_4_you_demo_1/venv/lib/python2.7/site-packages/pandas/computation/scope.py | 24 | 9002 | """Module for scope operations
"""
import sys
import struct
import inspect
import datetime
import itertools
import pprint
import numpy as np
import pandas as pd
from pandas.compat import DeepChainMap, map, StringIO
from pandas.core.base import StringMixin
import pandas.computation as compu
def _ensure_scope(level,... | mit |
rbiswas4/simlib | tests/test_summarize.py | 1 | 6310 | """ Tests for the code in `opsimsummary/opsim_out.py`
"""
from __future__ import print_function, division, absolute_import
import os
import pytest
import numpy as np
import pandas as pd
import opsimsummary as oss
from opsimsummary import (OpSimOutput, SynOpSim, PointingTree)
import healpy as hp
from numpy.testing impor... | mit |
shamidreza/Festival-features | festival_features.py | 1 | 5694 | import os
import logging
import numpy as np
import struct
from matplotlib import pyplot as pp
festival_path = '/Users/hamid/Code/festival/festival/'
class Festival_features():
def __init__(self, lname, feats_file=None):
self._read_list(lname)
if feats_file:
self._read_list_header(hnam... | gpl-2.0 |
e-koch/FilFinder | fil_finder/length.py | 1 | 28484 | # Licensed under an MIT open source license - see LICENSE
from .utilities import *
from .pixel_ident import *
import numpy as np
import scipy.ndimage as nd
import networkx as nx
import operator
import string
import copy
# Create 4 to 8-connected elements to use with binary hit-or-miss
struct1 = np.array([[1, 0, 0],... | mit |
Weihonghao/ECM | Vpy34/lib/python3.5/site-packages/numpy/lib/function_base.py | 19 | 164441 | from __future__ import division, absolute_import, print_function
import collections
import operator
import re
import sys
import warnings
import numpy as np
import numpy.core.numeric as _nx
from numpy.core import linspace, atleast_1d, atleast_2d, transpose
from numpy.core.numeric import (
ones, zeros, arange, conc... | agpl-3.0 |
stscieisenhamer/glue | glue/viewers/scatter/qt/tests/test_data_viewer.py | 1 | 17632 | # pylint: disable=I0011,W0613,W0201,W0212,E1101,E1103
from __future__ import absolute_import, division, print_function
import os
from collections import Counter
import pytest
from numpy.testing import assert_allclose
from glue.config import colormaps
from glue.core.message import SubsetUpdateMessage
from glue.core... | bsd-3-clause |
OSSHealth/ghdata | tests/test_metrics/test_pull_request_metrics.py | 1 | 1388 | #SPDX-License-Identifier: MIT
import pytest
import pandas as pd
def test_pull_requests_merge_contributor_new(metrics):
# repo id
assert metrics.pull_requests_merge_contributor_new(10, repo_id=25430, period='year').isin(
[pd.Timestamp('2019-01-01 00:00:00', tz='UTC')]).any().any()
# repo_group_id
... | mit |
seismology-RUB/ASKI | py/plot_ASKI_data_spectrum.py | 1 | 3433 | #!/usr/bin/env python
#
#----------------------------------------------------------------------------
# Copyright 2016 Florian Schumacher (Ruhr-Universitaet Bochum, Germany)
#
# This file is part of ASKI version 1.2.
#
# ASKI version 1.2 is free software: you can redistribute it and/or modify
# it under the ter... | gpl-2.0 |
talbrecht/pism_pik07 | test/vnreport.py | 1 | 8840 | #!/usr/bin/env python
from pylab import close, figure, clf, hold, plot, xlabel, ylabel, xticks, yticks, axis, legend, title, grid, show, savefig
from numpy import array, polyfit, polyval, log10, floor, ceil, unique
import sys
try:
from netCDF4 import Dataset as NC
except:
print "netCDF4 is not installed!"
... | gpl-3.0 |
theoryno3/scikit-learn | sklearn/ensemble/tests/test_weight_boosting.py | 14 | 15763 | """Testing for the boost module (sklearn.ensemble.boost)."""
import numpy as np
from sklearn.utils.testing import assert_array_equal, assert_array_less
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_raises, assert_rais... | bsd-3-clause |
GoogleCloudPlatform/datacatalog-connectors | google-datacatalog-connectors-commons-test/src/google/datacatalog_connectors/commons_test/utils/utils.py | 1 | 12637 | #!/usr/bin/python
#
# Copyright 2020 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ag... | apache-2.0 |
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