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 |
|---|---|---|---|---|---|
mkukielka/oddt | oddt/spatial.py | 2 | 9648 | """Spatial functions included in ODDT
Mainly used by other modules, but can be accessed directly.
"""
from math import sin, cos
import numpy as np
from scipy.spatial.distance import cdist
# for Hungarian algorithm, in future use scipy.optimize.linear_sum_assignment (in scipy 0.17+)
try:
from scipy.optimize import... | bsd-3-clause |
rs2/pandas | pandas/tests/arithmetic/test_timedelta64.py | 1 | 78590 | # Arithmetic tests for DataFrame/Series/Index/Array classes that should
# behave identically.
from datetime import datetime, timedelta
import numpy as np
import pytest
from pandas.errors import OutOfBoundsDatetime, PerformanceWarning
import pandas as pd
from pandas import (
DataFrame,
DatetimeIndex,
NaT,... | bsd-3-clause |
RayMick/scikit-learn | examples/ensemble/plot_forest_iris.py | 335 | 6271 | """
====================================================================
Plot the decision surfaces of ensembles of trees on the iris dataset
====================================================================
Plot the decision surfaces of forests of randomized trees trained on pairs of
features of the iris dataset.
... | bsd-3-clause |
chenyyx/scikit-learn-doc-zh | examples/zh/preprocessing/plot_function_transformer.py | 158 | 1993 | """
=========================================================
Using FunctionTransformer to select columns
=========================================================
Shows how to use a function transformer in a pipeline. If you know your
dataset's first principle component is irrelevant for a classification task,
you ca... | gpl-3.0 |
pyoceans/pocean-core | pocean/utils.py | 1 | 14316 | #!python
# coding=utf-8
import six
import uuid
import decimal
import operator
import itertools
import simplejson as json
from datetime import datetime, date, time
from collections import namedtuple, Mapping, Counter
try:
# PY2 support
from urlparse import urlparse as uparse
except ImportError:
from urllib.... | mit |
PFCM/facebook_data_collection | test_mergetools.py | 1 | 5340 | """
Tests for the mergetools.py script.
"""
import tempfile
import random
from contextlib import contextmanager
import string
import datetime
import csv
import os
import pandas as pd
import mergetools
from scraper import CSV_HEADERS, write_data
def random_str(length, chars=string.ascii_lowercase):
return ''.join... | bsd-2-clause |
dsm054/pandas | pandas/plotting/_timeseries.py | 4 | 11279 | # TODO: Use the fact that axis can have units to simplify the process
import functools
import numpy as np
from matplotlib import pylab
from pandas._libs.tslibs.period import Period
from pandas.core.dtypes.generic import (
ABCPeriodIndex, ABCDatetimeIndex, ABCTimedeltaIndex)
from pandas.tseries.offsets import D... | bsd-3-clause |
gsathya/metrics-tasks | task-2718/detectorv2.py | 2 | 17462 | ## Copyright (c) 2011 George Danezis <gdane@microsoft.com>
##
## All rights reserved.
##
## Redistribution and use in source and binary forms, with or without
## modification, are permitted (subject to the limitations in the
## disclaimer below) provided that the following conditions are met:
##
## * Red... | bsd-3-clause |
mrcouts/Bootstrap-Paradox | Experimental/Aquisicoes/SMCx_triangulo/aquisicoes.py | 1 | 8595 | # -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
import numpy as np
from math import pi as Pi
from txt2py import *
from matplotlib.ticker import MultipleLocator
A = txt2py("aquisicao_triangulo_SMCx_lambda60_phi6_k103_0_2.txt")
#aquisicao_circulo_PIDSMCx_lambda70_phi6_k70_0_3: e_quad = 0.912252649215 | tau_quad... | gpl-3.0 |
alexpearce/thesis | scripts/background_categories.py | 1 | 3206 | from __future__ import absolute_import, division, print_function
import os
import matplotlib.pyplot as plt
import ROOT
import root_pandas
from histograms import histogram
from root_converters import roocurve, tgraphasymerrors
from plotting_utilities import (
COLOURS as colours,
set_axis_labels
)
PREFIX = 'ro... | mit |
Caranarq/01_Dmine | Scripts/PCCS_variables/PCCS_variables.py | 1 | 2306 | # -*- coding: utf-8 -*-
"""
Created on Tue Aug 29 10:45:27 2017
@author: carlos.arana
"""
'''
Descripcion:
Script para revisar variables existentes en un dataset.
El script revisa, a partir de una lista, si las variables se encuentran previamente identificadas
en el proyecto de la PCCS (En el archivo PCCS_variables.c... | gpl-3.0 |
GuessWhoSamFoo/pandas | pandas/core/reshape/reshape.py | 1 | 36545 | # pylint: disable=E1101,E1103
# pylint: disable=W0703,W0622,W0613,W0201
from functools import partial
import itertools
import numpy as np
from pandas._libs import algos as _algos, reshape as _reshape
from pandas._libs.sparse import IntIndex
from pandas.compat import PY2, range, text_type, u, zip
from pandas.core.dty... | bsd-3-clause |
rdo-management/cardiff | cardiff/check.py | 2 | 25187 | import re
import numpy
from pandas import *
from cardiff import compare_sets
from cardiff import perf_cpu_tables
from cardiff import utils
def search_item(systems, unique_id, item, regexp, exclude_list=[], include_list=[], override_list=[]):
sets = {}
for system in systems:
sets[system[unique_id]] =... | apache-2.0 |
leggitta/mne-python | examples/stats/plot_fdr_stats_evoked.py | 19 | 2743 | """
=======================================
FDR correction on T-test on sensor data
=======================================
One tests if the evoked response significantly deviates from 0.
Multiple comparison problem is addressed with
False Discovery Rate (FDR) correction.
"""
# Authors: Alexandre Gramfort <alexandre.... | bsd-3-clause |
herilalaina/scikit-learn | sklearn/ensemble/tests/test_iforest.py | 27 | 8377 | """
Testing for Isolation Forest algorithm (sklearn.ensemble.iforest).
"""
# Authors: Nicolas Goix <nicolas.goix@telecom-paristech.fr>
# Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# License: BSD 3 clause
import numpy as np
from sklearn.utils.fixes import euler_gamma
from sklearn.utils.test... | bsd-3-clause |
StevenBlack/pandashells | pandashells/bin/p_format.py | 7 | 1691 | #! /usr/bin/env python
import argparse
import sys
import textwrap
from pandashells.lib import arg_lib, io_lib
class OutStream(object): # pragma no cover
"""
This class exisist for easing testing of sys.stdout and doesn't
need to be tested itself
"""
def __init__(self, template):
self.te... | bsd-2-clause |
hmendozap/auto-sklearn | autosklearn/ensembles/ensemble_selection.py | 1 | 8074 | from collections import Counter
import random
import numpy as np
import six
from autosklearn.constants import *
from autosklearn.ensembles.abstract_ensemble import AbstractEnsemble
from autosklearn.evaluation.util import calculate_score
class EnsembleSelection(AbstractEnsemble):
def __init__(self, ensemble_size... | bsd-3-clause |
lthurlow/Network-Grapher | proj/external/matplotlib-1.2.1/lib/mpl_examples/units/bar_demo2.py | 9 | 1062 | """
plot using a variety of cm vs inches conversions. The example shows
how default unit instrospection works (ax1), how various keywords can
be used to set the x and y units to override the defaults (ax2, ax3,
ax4) and how one can set the xlimits using scalars (ax3, current units
assumed) or units (conversions applie... | mit |
xzh86/scikit-learn | sklearn/utils/testing.py | 84 | 24860 | """Testing utilities."""
# Copyright (c) 2011, 2012
# Authors: Pietro Berkes,
# Andreas Muller
# Mathieu Blondel
# Olivier Grisel
# Arnaud Joly
# Denis Engemann
# License: BSD 3 clause
import os
import inspect
import pkgutil
import warnings
import sys
import re
import platf... | bsd-3-clause |
benkirk/libmesh | doc/statistics/libmesh_mailinglists.py | 1 | 9729 | #!/usr/bin/env python
import matplotlib.pyplot as plt
import numpy as np
from operator import add
# Import stuff for working with dates
from datetime import datetime
from matplotlib.dates import date2num, num2date
# Number of messages to libmesh-devel and libmesh-users over the life
# of the project. I cut and paste... | lgpl-2.1 |
eg-zhang/scikit-learn | sklearn/tests/test_kernel_ridge.py | 342 | 3027 | import numpy as np
import scipy.sparse as sp
from sklearn.datasets import make_regression
from sklearn.linear_model import Ridge
from sklearn.kernel_ridge import KernelRidge
from sklearn.metrics.pairwise import pairwise_kernels
from sklearn.utils.testing import ignore_warnings
from sklearn.utils.testing import assert... | bsd-3-clause |
alphaBenj/zipline | tests/test_api_shim.py | 5 | 19179 | import warnings
from mock import patch
import numpy as np
import pandas as pd
from pandas.core.common import PerformanceWarning
from zipline import TradingAlgorithm
from zipline.finance.trading import SimulationParameters
from zipline.testing import (
MockDailyBarReader,
create_daily_df_for_asset,
create_... | apache-2.0 |
remenska/rootpy | rootpy/plotting/style/__init__.py | 5 | 2962 | # Copyright 2012 the rootpy developers
# distributed under the terms of the GNU General Public License
from __future__ import absolute_import
import ROOT
from ... import log; log = log[__name__]
from ... import asrootpy, QROOT
from ...base import Object
from ...extern.six import string_types
__all__ = [
'get_sty... | gpl-3.0 |
andrewnc/scikit-learn | examples/linear_model/plot_ols_3d.py | 350 | 2040 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Sparsity Example: Fitting only features 1 and 2
=========================================================
Features 1 and 2 of the diabetes-dataset are fitted and
plotted below. It illustrates that although feature... | bsd-3-clause |
jeffery-do/Vizdoombot | doom/lib/python3.5/site-packages/dask/dataframe/tests/test_rolling.py | 1 | 9749 | import pandas as pd
import pytest
import numpy as np
import dask.dataframe as dd
from dask.dataframe.utils import assert_eq
from dask.utils import ignoring
def mad(x):
return np.fabs(x - x.mean()).mean()
def rolling_functions_tests(p, d):
# Old-fashioned rolling API
assert_eq(pd.rolling_count(p, 3), dd... | mit |
lthurlow/Network-Grapher | proj/external/matplotlib-1.2.1/lib/mpl_examples/mplot3d/lorenz_attractor.py | 3 | 1242 | # Plot of the Lorenz Attractor based on Edward Lorenz's 1963 "Deterministic
# Nonperiodic Flow" publication.
# http://journals.ametsoc.org/doi/abs/10.1175/1520-0469%281963%29020%3C0130%3ADNF%3E2.0.CO%3B2
#
# Note: Because this is a simple non-linear ODE, it would be more easily
# done using SciPy's ode solver, bu... | mit |
x75/actinf | active_inference_basic.py | 1 | 80206 |
import argparse, cPickle, os, sys
from collections import OrderedDict
from functools import partial # mhm :)
import numpy as np
import pylab as pl
import matplotlib.gridspec as gridspec
import pandas as pd
import explauto
from explauto import Environment
from explauto.environment import environments
from explauto.... | mit |
trungnt13/scikit-learn | examples/tree/plot_tree_regression_multioutput.py | 206 | 1800 | """
===================================================================
Multi-output Decision Tree Regression
===================================================================
An example to illustrate multi-output regression with decision tree.
The :ref:`decision trees <tree>`
is used to predict simultaneously the ... | bsd-3-clause |
wasit7/cs402 | randomForest_tutorials/_src_ncore_ntree/scdataset_spiral.py | 1 | 3124 | """
Created on Tue Oct 14 18:52:01 2014
@author: Wasit
"""
import numpy as np
class dataset:
def __init__(self):
self.clmax=5
self.spc=100
self.dim_theta=2
self.size=self.clmax*self.spc
#list of np.array
self.I=np.zeros((2,self.size))
#samples first row is th... | mit |
mspkvp/MiningOpinionTweets | src/lda_without_tf_idf_politics.py | 1 | 3990 | from __future__ import print_function
from time import time
import csv
import sys
import os
from sklearn.feature_extraction.text import CountVectorizer
import numpy as np
import lda
import logging
logging.basicConfig(filename='lda_analyser.log', level=logging.DEBUG)
entities = ['passos_coelho',
'jose_so... | mit |
eramirem/astroML | book_figures/chapter10/fig_LINEAR_SVM.py | 3 | 6143 | """
SVM classification of LINEAR data
---------------------------------
Figure 10.23
Supervised classification of periodic variable stars from the LINEAR data set
using a support vector machines method. The training sample includes five
input classes. The top row shows clusters derived using two attributes
(g - i and ... | bsd-2-clause |
lcharleux/compmod | doc/sandbox/awa/opti_compart_awa.py | 1 | 7585 | """
Compartimented optimization
LC 13/05/2015
"""
import numpy as np
import matplotlib.pyplot as plt
import compmod, abapy, platform
from scipy import optimize, interpolate
#-------------------------------------------------------------------------------
# FUNCTIONS AND CLASSES
def Saint_Venant(X):
sy_mean = X[0]
... | gpl-2.0 |
nhejazi/scikit-learn | sklearn/mixture/dpgmm.py | 5 | 35901 | """Bayesian Gaussian Mixture Models and
Dirichlet Process Gaussian Mixture Models"""
from __future__ import print_function
# Author: Alexandre Passos (alexandre.tp@gmail.com)
# Bertrand Thirion <bertrand.thirion@inria.fr>
#
# Based on mixture.py by:
# Ron Weiss <ronweiss@gmail.com>
# Fabian Ped... | bsd-3-clause |
mjaquier/NestModelSimplification | modelfit.py | 1 | 4674 |
import loading
import numpy as np
import cPickle as pickle
from Experiment import *
from GIF import *
from AEC_Badel import *
from AEC_Dummy import *
from Filter_Rect_LinSpaced import *
from Filter_Rect_LogSpaced import *
from Filter_Exps import *
from GIF_HT import *
import seaborn
class Fit():
def __init__(s... | mit |
ryfeus/lambda-packs | Tensorflow_Pandas_Numpy/source3.6/pandas/io/packers.py | 2 | 29027 | """
Msgpack serializer support for reading and writing pandas data structures
to disk
portions of msgpack_numpy package, by Lev Givon were incorporated
into this module (and tests_packers.py)
License
=======
Copyright (c) 2013, Lev Givon.
All rights reserved.
Redistribution and use in source and binary forms, with ... | mit |
vigilv/scikit-learn | sklearn/neighbors/graph.py | 208 | 7031 | """Nearest Neighbors graph functions"""
# Author: Jake Vanderplas <vanderplas@astro.washington.edu>
#
# License: BSD 3 clause (C) INRIA, University of Amsterdam
import warnings
from .base import KNeighborsMixin, RadiusNeighborsMixin
from .unsupervised import NearestNeighbors
def _check_params(X, metric, p, metric_... | bsd-3-clause |
jerryjiahaha/rts2 | scripts/shiftfoc.py | 3 | 3802 | #!/usr/bin/python
#
# Autofocosing routines using shift-store.
#
# You will need: scipy matplotlib sextractor
# This should work on Debian/ubuntu:
# sudo apt-get install python-matplotlib python-scipy python-pyfits sextractor
#
# If you would like to see sextractor results, get DS9 and pyds9:
#
# http://hea-www.harvard... | lgpl-3.0 |
robin-lai/scikit-learn | examples/covariance/plot_mahalanobis_distances.py | 348 | 6232 | r"""
================================================================
Robust covariance estimation and Mahalanobis distances relevance
================================================================
An example to show covariance estimation with the Mahalanobis
distances on Gaussian distributed data.
For Gaussian dis... | bsd-3-clause |
mlyundin/scikit-learn | sklearn/metrics/cluster/bicluster.py | 359 | 2797 | from __future__ import division
import numpy as np
from sklearn.utils.linear_assignment_ import linear_assignment
from sklearn.utils.validation import check_consistent_length, check_array
__all__ = ["consensus_score"]
def _check_rows_and_columns(a, b):
"""Unpacks the row and column arrays and checks their shap... | bsd-3-clause |
Universal-Model-Converter/UMC3.0a | data/Python/x86/Lib/site-packages/numpy/lib/function_base.py | 3 | 115310 | __docformat__ = "restructuredtext en"
__all__ = ['select', 'piecewise', 'trim_zeros', 'copy', 'iterable',
'percentile', 'diff', 'gradient', 'angle', 'unwrap', 'sort_complex',
'disp', 'extract', 'place', 'nansum', 'nanmax', 'nanargmax',
'nanargmin', 'nanmin', 'vectorize', 'asarray_chkfin... | mit |
JosmanPS/scikit-learn | sklearn/linear_model/logistic.py | 105 | 56686 | """
Logistic Regression
"""
# Author: Gael Varoquaux <gael.varoquaux@normalesup.org>
# Fabian Pedregosa <f@bianp.net>
# Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Manoj Kumar <manojkumarsivaraj334@gmail.com>
# Lars Buitinck
# Simon Wu <s8wu@uwaterloo.ca>
imp... | bsd-3-clause |
rajul/mne-python | mne/tests/test_source_space.py | 9 | 23354 | from __future__ import print_function
import os
import os.path as op
from nose.tools import assert_true, assert_raises
from nose.plugins.skip import SkipTest
import numpy as np
from numpy.testing import assert_array_equal, assert_allclose, assert_equal
import warnings
from mne.datasets import testing
from mne import ... | bsd-3-clause |
Phil9l/cosmos | code/quantum_algorithms/grover's_algorithm/P1_grover_plot.py | 2 | 2177 | ### Imports required for this solution
import matplotlib.pyplot as plot
import numpy as NP
import hashlib
from math import sqrt, pi
from collections import OrderedDict
from statistics import mean
###############
### PlotGraph(n, amplitude): Plots the graph for target value with the highest amplitude.
def PlotGraph(... | gpl-3.0 |
zrhans/pythonanywhere | .virtualenvs/django19/lib/python3.4/site-packages/pandas/tseries/tests/test_daterange.py | 9 | 26349 | from datetime import datetime
from pandas.compat import range
import nose
import numpy as np
from pandas.core.index import Index
from pandas.tseries.index import DatetimeIndex
from pandas import Timestamp
from pandas.tseries.offsets import generate_range
from pandas.tseries.index import cdate_range, bdate_range, date... | apache-2.0 |
girish946/plot-cat | setup.py | 1 | 1808 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
from setuptools import setup
description = '''
plot-cat is the python library for plotting live serial input. plotcat works on
python 2.7 and later. plotcat comes handy when you want to plot live data that
is coming form different sensors over the serial port, ... | gpl-3.0 |
cyrusmaher/mosaic | mosaic_example.py | 1 | 7009 | import sys
import re
import os
import mosaic
from Bio import AlignIO
import pandas as pd
def specfunc(name):
specieslist_ca = [
['(CCDS|hg19|Homo_sapiens)', 'Hom'],
['(ENSPTR|Pan|Pan_troglodytes)', 'Pan'],
['(ENSGGO|Gor|Gorilla_gorilla)', 'Gor'],
['(ENSPPY|Pon|Pongo_abelii)', 'Pon'... | mit |
mikekestemont/tag | tag/tagger.py | 1 | 35876 | from __future__ import print_function
import os
import shutil
import ConfigParser
from operator import itemgetter
import cPickle as pickle
from sklearn.preprocessing import LabelEncoder
import matplotlib
matplotlib.use('Agg') # Must be before importing matplotlib.pyplot or pylab!
import matplotlib.pyplot as plt
import... | mit |
Adai0808/scikit-learn | examples/hetero_feature_union.py | 288 | 6236 | """
=============================================
Feature Union with Heterogeneous Data Sources
=============================================
Datasets can often contain components of that require different feature
extraction and processing pipelines. This scenario might occur when:
1. Your dataset consists of hetero... | bsd-3-clause |
JeffreyFish/DocWebTool | DocTracking.py | 2 | 9018 | #!/usr/bin/env python
# -*- Coding: UTF-8 -*-
#------------------------------------
#--Author: Lychee Li
#--CreationDate: 2017/10/18
#--RevisedDate: 2017/10/27
#--RevisedDate: 2018/03/12
#------------------------------------
import datetime
import pyodbc
import common
import pandas as pd
# 读取SQL代码
with... | gpl-3.0 |
lucval/dmm-ns-3.17 | src/flow-monitor/examples/wifi-olsr-flowmon.py | 108 | 7439 | # -*- Mode: Python; -*-
# Copyright (c) 2009 INESC Porto
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License version 2 as
# published by the Free Software Foundation;
#
# This program is distributed in the hope that it will be useful,
#... | gpl-2.0 |
feilchenfeldt/pypopgen | modules/genotypemat.py | 1 | 1245 | import gc
import numpy as np
import pandas as pd
def pairwise_diff_numpy(gen_arr):
"""Squared pairwise distances between all
columns of 0,1,2 genotype array arr.
This matrix based function is at least 10
times faster than iterating over columns.
"""
gen_arr = gen_arr.astype(np.float64)-1
... | mit |
echanna/EdxNotAFork | docs/en_us/developers/source/conf.py | 10 | 6880 | # -*- coding: utf-8 -*-
# pylint: disable=C0103
# pylint: disable=W0622
# pylint: disable=W0212
# pylint: disable=W0613
import sys, os
from path import path
on_rtd = os.environ.get('READTHEDOCS', None) == 'True'
sys.path.append('../../../../')
from docs.shared.conf import *
# Add any paths that contain template... | agpl-3.0 |
schmidtc/pysal | pysal/spreg/opt.py | 8 | 2370 | import copy
def simport(modname):
"""
Safely import a module without raising an error.
Parameters
-----------
modname : str
module name needed to import
Returns
--------
tuple of (True, Module) or (False, None) depending on whether the import
succeeded.
Not... | bsd-3-clause |
idealabasu/code_pynamics | python/pynamics_examples/springy_pendulum.py | 1 | 2902 | # -*- coding: utf-8 -*-
"""
Written by Daniel M. Aukes
Email: danaukes<at>gmail.com
Please see LICENSE for full license.
"""
import pynamics
pynamics.script_mode = False
from pynamics.frame import Frame
from pynamics.variable_types import Differentiable,Constant
from pynamics.system import System
from pynamics.body i... | mit |
MJuddBooth/pandas | pandas/tests/frame/test_api.py | 1 | 18686 | # -*- coding: utf-8 -*-
from __future__ import print_function
# pylint: disable-msg=W0612,E1101
from copy import deepcopy
import pydoc
import numpy as np
import pytest
from pandas.compat import PY2, long, lrange, range
import pandas as pd
from pandas import (
Categorical, DataFrame, Series, SparseDataFrame, co... | bsd-3-clause |
lifuhuang/critic | hotels/tf_demo.py | 1 | 3255 | # -*- coding: utf-8 -*-
"""
Created on Sat May 7 09:51:35 2016
@author: lifu
"""
import numpy as np
import tensorflow as tf
batch_size=50
X_train = np.random.randn(50, 200)
y_train = np.random.randint(0, 3, 50)
W = tf.Variable(tf.random_normal([200, 3]), name='weight')
b = tf.Variable(tf.zeros([1, 3]), name='bias'... | gpl-3.0 |
SaganBolliger/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/table.py | 69 | 16757 | """
Place a table below the x-axis at location loc.
The table consists of a grid of cells.
The grid need not be rectangular and can have holes.
Cells are added by specifying their row and column.
For the purposes of positioning the cell at (0, 0) is
assumed to be at the top left and the cell at (max_row, max_col)
i... | agpl-3.0 |
patelrajnath/rnn4nlp | metrics/pos_eval.py | 1 | 1915 | from __future__ import division
import codecs
from sklearn.metrics import f1_score
import logging, sys
def read_tag_file(filename):
with codecs.open(filename) as tagfile:
tags_by_line = [l.strip().split() for l in tagfile]
return tags_by_line
def weighted_fmeasure(y_true, y_pred):
return f1_score... | gpl-3.0 |
ueshin/apache-spark | python/pyspark/pandas/tests/test_series.py | 9 | 118972 | #
# 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 |
theoryno3/scikit-learn | examples/applications/plot_tomography_l1_reconstruction.py | 204 | 5442 | """
======================================================================
Compressive sensing: tomography reconstruction with L1 prior (Lasso)
======================================================================
This example shows the reconstruction of an image from a set of parallel
projections, acquired along dif... | bsd-3-clause |
bnaul/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 |
espiritocz/giSAR | remot_watch.py | 1 | 23679 | # -*- coding: utf-8 -*-
"""
/***************************************************************************
Remotwatch
A QGIS plugin
This plugin is for visualize and manipulate points from Stamps and SAR PROZ Processing
-------------------
beg... | gpl-3.0 |
slundberg/shap | tests/explainers/test_sampling.py | 1 | 1484 | """ Unit tests for the Sampling explainer.
"""
# pylint: disable=missing-function-docstring
import numpy as np
import pytest
import shap
def test_null_model_small():
explainer = shap.SamplingExplainer(lambda x: np.zeros(x.shape[0]), np.ones((2, 4)), nsamples=100)
shap_values = explainer.shap_values(np.ones(... | mit |
abonaca/gary | docs/_code/examples.py | 1 | 1060 | import astropy.units as u
import matplotlib.pyplot as plt
from matplotlib import cm
import numpy as np
import gary.potential as sp
import gary.integrate as si
from gary.units import galactic
# integrate & potential example
v_c = (200*u.km/u.s).decompose(galactic).value
potential = sp.SphericalNFWPotential(v_c=v_c, r_s... | mit |
sergio2pi/NeuroDB | test/test5.py | 1 | 2324 | '''
Created on Oct 21, 2014
@author: sergio
'''
import numpy as np
import ctypes
import numpy.ctypeslib as npct
import matplotlib.pyplot as plt
#cfsfd = ctypes.cdll.LoadLibrary('/home/sergio/iibm/sandbox/t.so')
#cfsfd.get_dc.restype = ctypes.c_float
#dc = cfsfd.get_dc("dbname=demo host=192.168.2.2 user=postgres pass... | gpl-2.0 |
alvarofierroclavero/scikit-learn | sklearn/datasets/species_distributions.py | 198 | 7923 | """
=============================
Species distribution dataset
=============================
This dataset represents the geographic distribution of species.
The dataset is provided by Phillips et. al. (2006).
The two species are:
- `"Bradypus variegatus"
<http://www.iucnredlist.org/apps/redlist/details/3038/0>`_... | bsd-3-clause |
mbayon/TFG-MachineLearning | venv/lib/python3.6/site-packages/pandas/tests/io/parser/header.py | 6 | 9126 | # -*- coding: utf-8 -*-
"""
Tests that the file header is properly handled or inferred
during parsing for all of the parsers defined in parsers.py
"""
import pytest
import numpy as np
import pandas.util.testing as tm
from pandas import DataFrame, Index, MultiIndex
from pandas.compat import StringIO, lrange, u
cla... | mit |
sniemi/SamPy | sandbox/src1/examples/tex_demo.py | 1 | 1036 | #!/usr/bin/env python
"""
You can use TeX to render all of your matplotlib text if the rc
parameter text.usetex is set. This works currently on the agg and ps
backends, and requires that you have tex and the other dependencies
described at http://matplotlib.sf.net/matplotlib.texmanager.html
properly installed on your ... | bsd-2-clause |
roxyboy/scikit-learn | examples/hetero_feature_union.py | 288 | 6236 | """
=============================================
Feature Union with Heterogeneous Data Sources
=============================================
Datasets can often contain components of that require different feature
extraction and processing pipelines. This scenario might occur when:
1. Your dataset consists of hetero... | bsd-3-clause |
hyperion-rt/paper-galaxy-rt-model | scripts/groups.py | 1 | 1230 | from matplotlib.colors import ColorConverter
def group(spectral_type):
if 'AGB' in spectral_type:
return 2
elif 'III' in spectral_type:
return 3
elif 'V' in spectral_type:
return 4
elif 'YOUNG OB' in spectral_type:
return 4
elif 'TAURI' in spectral_type:
re... | bsd-2-clause |
fbagirov/scikit-learn | examples/neighbors/plot_classification.py | 287 | 1790 | """
================================
Nearest Neighbors Classification
================================
Sample usage of Nearest Neighbors classification.
It will plot the decision boundaries for each class.
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColorm... | bsd-3-clause |
mitdrc/pronto | motion_estimate/scripts/republish_multisense_state.py | 2 | 1128 | #!/usr/bin/python
# MIT uses hokuyo_joint
# other teams use motor_joint, rename here
import os,sys
import lcm
import time
from lcm import LCM
from math import *
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.mlab as mlab
from threading import Thread
import threading
home_dir =os.getenv("HOME")... | lgpl-2.1 |
brian-team/brian2cuda | dev/benchmarks/results_2017_11_30_cuba_stdp/cuba_stdp/run_speed_test_script.py | 1 | 18566 | import os
import shutil
import glob
import subprocess
import sys
import socket
# run tests without X-server
import matplotlib
matplotlib.use('Agg')
# pretty plots
import seaborn
import time
import datetime
import cPickle as pickle
from brian2 import *
from brian2.tests.features import *
from brian2.tests.features.b... | gpl-2.0 |
earlew/earlew.github.io | markdown_generator/publications.py | 197 | 3887 |
# coding: utf-8
# # Publications markdown generator for academicpages
#
# Takes a TSV of publications with metadata and converts them for use with [academicpages.github.io](academicpages.github.io). This is an interactive Jupyter notebook, with the core python code in publications.py. Run either from the `markdown_g... | mit |
spallavolu/scikit-learn | examples/linear_model/plot_sgd_separating_hyperplane.py | 260 | 1219 | """
=========================================
SGD: Maximum margin separating hyperplane
=========================================
Plot the maximum margin separating hyperplane within a two-class
separable dataset using a linear Support Vector Machines classifier
trained using SGD.
"""
print(__doc__)
import numpy as n... | bsd-3-clause |
JackKelly/neuralnilm_prototype | scripts/e241.py | 2 | 5806 | 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 |
abhishekgahlot/scikit-learn | sklearn/manifold/isomap.py | 36 | 7119 | """Isomap for manifold learning"""
# Author: Jake Vanderplas -- <vanderplas@astro.washington.edu>
# License: BSD 3 clause (C) 2011
import numpy as np
from ..base import BaseEstimator, TransformerMixin
from ..neighbors import NearestNeighbors, kneighbors_graph
from ..utils import check_array
from ..utils.graph import... | bsd-3-clause |
jbest/digitization_tools | productivity/productivity.py | 1 | 6643 | """
Imaging productivity stats
Jason Best - jbest@brit.org
Generates a productivity report based on the creation timestamps of image files.
Details of the imaging session are extracted from the folder name containing the images.
Assumed folder name format is: YYYY-MM-DD_ImagerID_OtherInfo
Usage:
python productivity.p... | mit |
clemkoa/scikit-learn | examples/plot_johnson_lindenstrauss_bound.py | 39 | 7489 | r"""
=====================================================================
The Johnson-Lindenstrauss bound for embedding with random projections
=====================================================================
The `Johnson-Lindenstrauss lemma`_ states that any high dimensional
dataset can be randomly projected i... | bsd-3-clause |
openeemeter/eemeter | tests/test_io.py | 1 | 10485 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Copyright 2014-2019 OpenEEmeter contributors
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/LIC... | apache-2.0 |
Obus/scikit-learn | examples/text/document_classification_20newsgroups.py | 222 | 10500 | """
======================================================
Classification of text documents using sparse features
======================================================
This is an example showing how scikit-learn can be used to classify documents
by topics using a bag-of-words approach. This example uses a scipy.spars... | bsd-3-clause |
ethen8181/machine-learning | ga/tsp_solver/tspga.py | 1 | 8343 | import random
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from collections import namedtuple
from itertools import combinations
class TSPGA(object):
"""
Travel Salesman Problem using Genetic Algorithm
Parameters
----------
generation : int
number of iteration to train the algorithm
... | mit |
PatrickChrist/scikit-learn | examples/svm/plot_custom_kernel.py | 171 | 1546 | """
======================
SVM with custom kernel
======================
Simple usage of Support Vector Machines to classify a sample. It will
plot the decision surface and the support vectors.
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
from sklearn import svm, datasets
# import some data... | bsd-3-clause |
tomasreimers/tensorflow-emscripten | tensorflow/contrib/learn/python/learn/learn_io/__init__.py | 37 | 2375 | # 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 |
tioover/naprock | run.py | 1 | 1993 | import os
import matplotlib.image as mpimg
from lib import split_and_save, is_windows, remove
from mark import marker
from config import player_id, server, raw_problem_filename
def main(problem_id):
print("Get Problem...")
problem_id = input("Input Problem ID (default %s): " % problem_id) or problem_id
... | gpl-2.0 |
toobaz/pandas | pandas/tests/tslibs/test_fields.py | 1 | 1144 | import numpy as np
from pandas._libs.tslibs import fields
import pandas.util.testing as tm
def test_fields_readonly():
# https://github.com/vaexio/vaex/issues/357
# fields functions should't raise when we pass read-only data
dtindex = np.arange(5, dtype=np.int64) * 10 ** 9 * 3600 * 24 * 32
dtindex.... | bsd-3-clause |
sampathweb/bayes_hack | bayes-hack-app/app/blueprints/pred_model.py | 1 | 8726 | from flask import g
import sklearn.ensemble
import sklearn as skl
import numpy as np
import pandas as pd
import pylab as pl
import cPickle
def project_data(db_engine, fn='opendata_projects.csv'):
return pd.read_csv(fn,
parse_dates=['date_expiration','date_thank_you_packet_mailed',
... | mit |
fedspendingtransparency/data-act-broker-backend | dataactvalidator/scripts/load_tas.py | 1 | 12283 | from collections import defaultdict
import os
import logging
import argparse
from datetime import datetime, timezone
import json
import pandas as pd
import boto3
from dataactcore.config import CONFIG_BROKER
from dataactcore.interfaces.db import GlobalDB
from dataactcore.logging import configure_logging
from dataactco... | cc0-1.0 |
Unidata/MetPy | v0.6/_downloads/Hodograph_Inset.py | 1 | 2534 | # Copyright (c) 2016 MetPy Developers.
# Distributed under the terms of the BSD 3-Clause License.
# SPDX-License-Identifier: BSD-3-Clause
"""
Hodograph Inset
===============
Layout a Skew-T plot with a hodograph inset into the plot.
"""
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1.inset_locator import... | bsd-3-clause |
moosekaka/sweepython | tubule_het/plt_lineseries/Dist_DY_OneEdgeCell.py | 1 | 4023 | # -*- coding: utf-8 -*-
"""
Created on Sun Jul 05 22:14:07 2015
plot ONE EDGE of ONE CELL, run the commented lines below main block to
generate the distributions first
@author: sweel
"""
# pylint: disable=C0103
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import cPickle as pickle
sns.set_con... | mit |
Naereen/notebooks | simus/Des_dates_qui_font_des_nombres_premiers.py | 1 | 13116 |
# coding: utf-8
# # Des dates qui font des nombres premiers ?
#
# Ce petit [notebook Jupyter](https://www.jupyter.org/), écrit en [Python](https://www.python.org/), a pour but de résoudre la question suivante :
#
# > *"En 2017, combien de jours ont leur date qui est un nombre premier ?"*
#
# Par exemple, en 2017, ... | mit |
anntzer/scikit-learn | examples/linear_model/plot_lasso_lars.py | 23 | 1048 | #!/usr/bin/env python
"""
=====================
Lasso path using LARS
=====================
Computes Lasso Path along the regularization parameter using the LARS
algorithm on the diabetes dataset. Each color represents a different
feature of the coefficient vector, and this is displayed as a function
of the regulariza... | bsd-3-clause |
CSB-IG/non-coding-NGS | paired_linguistic_group_jaccard_indexes.py | 1 | 1567 | import matplotlib
matplotlib.use('svg')
matplotlib.rcParams.update({'font.size': 8})
from matplotlib import pyplot as plt
import numpy as np
from matplotlib_venn import venn2
from sample_code_file_maps import *
from itertools import combinations
# computes jacard index for two or mor sets
def jaccard_index(first, *o... | gpl-3.0 |
lancezlin/ml_template_py | lib/python2.7/site-packages/sklearn/preprocessing/tests/test_label.py | 40 | 18519 | import numpy as np
from scipy.sparse import issparse
from scipy.sparse import coo_matrix
from scipy.sparse import csc_matrix
from scipy.sparse import csr_matrix
from scipy.sparse import dok_matrix
from scipy.sparse import lil_matrix
from sklearn.utils.multiclass import type_of_target
from sklearn.utils.testing impor... | mit |
sinhrks/scikit-learn | sklearn/linear_model/tests/test_sgd.py | 8 | 44274 | import pickle
import unittest
import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_greater
from sklearn.utils.testing ... | bsd-3-clause |
beiko-lab/gengis | bin/Lib/site-packages/mpl_toolkits/mplot3d/axis3d.py | 6 | 16960 | #!/usr/bin/python
# axis3d.py, original mplot3d version by John Porter
# Created: 23 Sep 2005
# Parts rewritten by Reinier Heeres <reinier@heeres.eu>
import math
import copy
from matplotlib import lines as mlines, axis as maxis, \
patches as mpatches
import art3d
import proj3d
import numpy as np
def get_fli... | gpl-3.0 |
ilo10/scikit-learn | examples/decomposition/plot_pca_iris.py | 253 | 1801 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
PCA example with Iris Data-set
=========================================================
Principal Component Analysis applied to the Iris dataset.
See `here <http://en.wikipedia.org/wiki/Iris_flower_data_set>`_ fo... | bsd-3-clause |
saketkc/statsmodels | statsmodels/sandbox/tsa/garch.py | 25 | 52178 | '''general non-linear MLE for time series analysis
idea for general version
------------------------
subclass defines geterrors(parameters) besides loglike,...
and covariance matrix of parameter estimates (e.g. from hessian
or outerproduct of jacobian)
update: I don't really need geterrors directly, but get_h the con... | bsd-3-clause |
droundy/deft | talks/colloquium/figs/sphere-energy.py | 1 | 1500 | #!/usr/bin/python
# We need the following two lines in order for matplotlib to work
# without access to an X server.
from __future__ import division
import matplotlib
matplotlib.use('Agg')
import pylab, numpy, sys
mNpermeter = 6.4230498e-07 # in atomic units
nm = 18.8972613 # in atomic units
angstrom = 0.1*nm
spced... | gpl-2.0 |
andersgs/kraken-trawl | kraken_trawl/kraken_trawl.py | 1 | 19736 | from __future__ import print_function
'''
Expects a environmental variable called ASPERA_KEY
'''
import click
import os
import subprocess
import pandas as pd
import re
import shlex
import gzip
from Bio import SeqIO
from Bio import Entrez
import tempfile
import sys
import pkg_resources
### SOME CONSTANTS #############... | gpl-3.0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.