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 |
|---|---|---|---|---|---|
schets/scikit-learn | examples/linear_model/plot_sgd_penalties.py | 249 | 1563 | """
==============
SGD: Penalties
==============
Plot the contours of the three penalties.
All of the above are supported by
:class:`sklearn.linear_model.stochastic_gradient`.
"""
from __future__ import division
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
def l1(xs):
return np.array([np.... | bsd-3-clause |
kevinhikali/ml_kevin | bottom/logistic_regression.py | 1 | 1151 | # -*- coding: utf-8 -*-
"""
@author: kevinhikali
@email: hmingwei@gmail.com
"""
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from math import exp
# global variable
SampleTh = np.array([[2],
[5]])
# function
def h(th, x):
global SampleTh
retur... | gpl-3.0 |
brentp/vcfanno | scripts/paper/parallelization-figure.py | 2 | 2106 | import toolshed as ts
lookup = {'ALL.wgs.phase3_shapeit2_mvncall_integrated_v5a.20130502.sites': '1000G',
'ExAC.r0.3.sites.vep': 'ExAC'}
data = {'1000G': [], 'ExAC': []}
"""
method procs time query
var 20 888.29 seconds ALL.wgs.phase3_shapeit2_mvncall_integrated_v5a.20130502.sites
var 19 897.02 seconds ALL... | mit |
icfaust/TRIPPy | TRIPPy/plot/pyplot.py | 1 | 5770 | import scipy
import scipy.special
import matplotlib.pyplot as plt
def plotTokamak(tokamak, pltobj=None, axis=True, pargs=None, **kwargs):
if pltobj is None:
pltobj = plt
if pargs is None:
pltobj.plot(tokamak.sagi.s, tokamak.norm.s, **kwargs)
else:
pltobj.plot(tokamak.sagi.s, t... | mit |
stupid-coder/lwan | tools/benchmark.py | 6 | 4379 | #!/usr/bin/python
import sys
import json
import commands
import time
try:
import matplotlib.pyplot as plt
except ImportError:
plt = None
def clearstderrline():
sys.stderr.write('\033[2K')
def weighttp(url, n_threads, n_connections, n_requests, keep_alive):
keep_alive = '-k' if keep_alive else ''
command... | gpl-2.0 |
jjbrin/trading-with-python | lib/functions.py | 76 | 11627 | # -*- coding: utf-8 -*-
"""
twp support functions
@author: Jev Kuznetsov
Licence: GPL v2
"""
from scipy import polyfit, polyval
import datetime as dt
#from datetime import datetime, date
from pandas import DataFrame, Index, Series
import csv
import matplotlib.pyplot as plt
import numpy as np
import p... | bsd-3-clause |
DonBeo/scikit-learn | sklearn/metrics/__init__.py | 10 | 3328 | """
The :mod:`sklearn.metrics` module includes score functions, performance metrics
and pairwise metrics and distance computations.
"""
from .ranking import auc
from .ranking import average_precision_score
from .ranking import coverage_error
from .ranking import label_ranking_average_precision_score
from .ranking imp... | bsd-3-clause |
yask123/scikit-learn | sklearn/tests/test_dummy.py | 186 | 17778 | from __future__ import division
import numpy as np
import scipy.sparse as sp
from sklearn.base import clone
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_almost_eq... | bsd-3-clause |
galtys/galtys-addons | html_reports/controllers/reports.py | 1 | 1044 | import openerp.addons.web.http as oeweb
import werkzeug.utils
import werkzeug.wrappers
import openerp
from openerp import pooler
from openerp import SUPERUSER_ID
from werkzeug.wrappers import Response
from mako.template import Template
from mako.runtime import Context
from StringIO import StringIO
from openerp.module... | agpl-3.0 |
klusta-team/klustaviewa | klustaviewa/views/tests/test_correlogramsview.py | 2 | 1678 | """Unit tests for correlograms view."""
# -----------------------------------------------------------------------------
# Imports
# -----------------------------------------------------------------------------
import os
import numpy as np
import numpy.random as rnd
import pandas as pd
from klustaviewa.views.tests.mo... | bsd-3-clause |
mquezada/tweets-summarizer | src/doc2vec.py | 1 | 1688 | import gensim
import numpy as np
from collections import namedtuple
from load_data import expanded_urls, df
from process_text import process, replace_map_url
from model_documents import docs
from sklearn.manifold import TSNE
import matplotlib.pyplot as plt
from matplotlib.ticker import NullFormatter
from sklearn.clust... | gpl-3.0 |
evgchz/scikit-learn | examples/classification/plot_classification_probability.py | 242 | 2624 | """
===============================
Plot classification probability
===============================
Plot the classification probability for different classifiers. We use a 3
class dataset, and we classify it with a Support Vector classifier, L1
and L2 penalized logistic regression with either a One-Vs-Rest or multinom... | bsd-3-clause |
DerPhysikeR/pywbm | pywbm.py | 1 | 1782 | #!/usr/bin/env python
"""
2017-05-13 21:05:35
@author: Paul Reiter
"""
import numpy as np
import matplotlib.pyplot as plt
from scipy.special import hankel2
from pywbm import Subdomain
def vn(x, y, z, k):
# incident velocity on left side
# return (x == 0).astype(complex)*1j/(k*z)
# incident velocity on le... | gpl-3.0 |
abimannans/scikit-learn | examples/svm/plot_svm_nonlinear.py | 268 | 1091 | """
==============
Non-linear SVM
==============
Perform binary classification using non-linear SVC
with RBF kernel. The target to predict is a XOR of the
inputs.
The color map illustrates the decision function learned by the SVC.
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
from sklearn imp... | bsd-3-clause |
bdh1011/wau | venv/lib/python2.7/site-packages/pandas/io/clipboard.py | 14 | 2947 | """ io on the clipboard """
from pandas import compat, get_option, option_context, DataFrame
from pandas.compat import StringIO
def read_clipboard(**kwargs): # pragma: no cover
"""
Read text from clipboard and pass to read_table. See read_table for the
full argument list
If unspecified, `sep` defaul... | mit |
anhaidgroup/py_stringsimjoin | py_stringsimjoin/tests/test_suffix_filter.py | 1 | 25219 | import unittest
from nose.tools import assert_equal, assert_list_equal, nottest, raises
from py_stringmatching.tokenizer.delimiter_tokenizer import DelimiterTokenizer
from py_stringmatching.tokenizer.qgram_tokenizer import QgramTokenizer
import numpy as np
import pandas as pd
from py_stringsimjoin.filter.suffix_filte... | bsd-3-clause |
murali-munna/scikit-learn | examples/model_selection/plot_roc.py | 146 | 3697 | """
=======================================
Receiver Operating Characteristic (ROC)
=======================================
Example of Receiver Operating Characteristic (ROC) metric to evaluate
classifier output quality.
ROC curves typically feature true positive rate on the Y axis, and false
positive rate on the X a... | bsd-3-clause |
etkirsch/scikit-learn | sklearn/semi_supervised/label_propagation.py | 71 | 15342 | # coding=utf8
"""
Label propagation in the context of this module refers to a set of
semisupervised classification algorithms. In the high level, these algorithms
work by forming a fully-connected graph between all points given and solving
for the steady-state distribution of labels at each point.
These algorithms per... | bsd-3-clause |
pratapvardhan/scikit-learn | examples/plot_digits_pipe.py | 70 | 1813 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Pipelining: chaining a PCA and a logistic regression
=========================================================
The PCA does an unsupervised dimensionality reduction, while the logistic
regression does the predictio... | bsd-3-clause |
mavarick/jieba | test/extract_topic.py | 65 | 1463 | import sys
sys.path.append("../")
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
from sklearn import decomposition
import jieba
import time
import glob
import sys
import os
import random
if len(sys.argv)<2:
print("usage: extract_topic.py di... | mit |
nicproulx/mne-python | examples/inverse/plot_label_from_stc.py | 31 | 3963 | """
=================================================
Generate a functional label from source estimates
=================================================
Threshold source estimates and produce a functional label. The label
is typically the region of interest that contains high values.
Here we compare the average time ... | bsd-3-clause |
DmitryYurov/BornAgain | Examples/Demos/simul_demo_lattice2.py | 2 | 2472 | '''
Simulation demo: Cylinder form factor without interference
'''
import numpy
import matplotlib
import math
from bornagain import *
M_PI = numpy.pi
# ----------------------------------
# describe sample and run simulation
# ----------------------------------
def RunSimulation():
# defining materials
mAmbie... | gpl-3.0 |
fdeheeger/mpld3 | mpld3/tests/test_elements.py | 16 | 5658 | """
Test creation of basic plot elements
"""
import numpy as np
import matplotlib.pyplot as plt
from .. import fig_to_dict, fig_to_html
from numpy.testing import assert_equal
def test_line():
fig, ax = plt.subplots()
ax.plot(np.arange(10), np.random.random(10),
'--k', alpha=0.3, zorder=10, lw=2)
... | bsd-3-clause |
Myasuka/scikit-learn | sklearn/mixture/tests/test_gmm.py | 200 | 17427 | import unittest
import copy
import sys
from nose.tools import assert_true
import numpy as np
from numpy.testing import (assert_array_equal, assert_array_almost_equal,
assert_raises)
from scipy import stats
from sklearn import mixture
from sklearn.datasets.samples_generator import make_spd_ma... | bsd-3-clause |
mickypaganini/SSI2016-jet-clustering | hdb.py | 1 | 6413 | print(__doc__)
from sklearn import metrics
import numpy as np
from read_data import read_data
from sklearn.preprocessing import StandardScaler
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm
from itertools import cycle
import os
from sklearn.neighbors import DistanceMetric
def hdb(txtfile, even... | mit |
vbalderdash/LMAsimulation | simulation_ellipse.py | 1 | 12093 | import numpy as np
from scipy.linalg import lstsq
from scipy.optimize import leastsq
from coordinateSystems import GeographicSystem
from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
from matplotlib.patches import Ellipse
def travel_time(X, X_ctr, c, t0=0.0, get_r=False):
""" Units are meter... | mit |
grundgruen/zipline | zipline/utils/data_source_tables_gen.py | 40 | 7380 | #
# Copyright 2014 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 |
allthroughthenight/aces | python/drivers/ext_Hs_analysis.py | 1 | 22155 | import sys
import math
import numpy as np
import matplotlib.pyplot as plt
sys.path.append('../functions')
from base_driver import BaseDriver
from helper_objects import BaseField
import USER_INPUT
from ERRSTP import ERRSTP
from ERRWAVBRK1 import ERRWAVBRK1
from WAVELEN import WAVELEN
from EXPORTER import EXPORTER
## ... | gpl-3.0 |
hugobowne/scikit-learn | sklearn/metrics/tests/test_pairwise.py | 22 | 25505 | import numpy as np
from numpy import linalg
from scipy.sparse import dok_matrix, csr_matrix, issparse
from scipy.spatial.distance import cosine, cityblock, minkowski, wminkowski
from sklearn.utils.testing import assert_greater
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing impo... | bsd-3-clause |
HFO-detect/HFO-detect-python | pyhfo_detect/core/cs_detector.py | 1 | 18781 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Oct 20 14:27:15 2017
Ing.,Mgr. (MSc.) Jan Cimbálník, PhD.
Biomedical engineering
International Clinical Research Center
St. Anne's University Hospital in Brno
Czech Republic
&
Mayo systems electrophysiology lab
Mayo Clinic
200 1st St SW
Rochester, MN
Un... | bsd-3-clause |
ercius/openNCEM | setup.py | 1 | 4143 | """A setuptools based setup module.
See https://packaging.python.org/en/latest/distributing.html
Addapted from https://github.com/pypa/sampleproject
"""
# Always prefer setuptools over distutils
from codecs import open
from os import path
from setuptools import setup , find_packages
# To use a consistent encoding
h... | gpl-3.0 |
mesnardo/PetIBM | examples/decoupledibpm/cylinder2dRe550_GPU/scripts/plotVorticity.py | 3 | 1384 | """
Computes, plots, and saves the 2D vorticity field from a PetIBM simulation
after 1200 time steps (3 non-dimensional time-units).
"""
import pathlib
import h5py
import numpy
from matplotlib import pyplot
simu_dir = pathlib.Path(__file__).absolute().parents[1]
# Read vorticity field and its grid from files.
name ... | bsd-3-clause |
niamoto/niamoto-core | niamoto/data_providers/plantnote_provider/plantnote_occurrence_provider.py | 1 | 4162 | # coding: utf-8
from sqlalchemy import *
import pandas as pd
from niamoto.data_providers.base_occurrence_provider import \
BaseOccurrenceProvider
class PlantnoteOccurrenceProvider(BaseOccurrenceProvider):
"""
Pl@ntnote Occurrence Provider.
Provide occurrences from a Pl@ntnote database. The Pl@ntnote... | gpl-3.0 |
balazsdukai/GEO1005-StormManager | SpatialDecision/external/networkx/convert_matrix.py | 7 | 33333 | """Functions to convert NetworkX graphs to and from numpy/scipy matrices.
The preferred way of converting data to a NetworkX graph is through the
graph constuctor. The constructor calls the to_networkx_graph() function
which attempts to guess the input type and convert it automatically.
Examples
--------
Create a 10... | gpl-2.0 |
gilyclem/larVolumeToObj | larVolumeToObjG/computation/step_calcchains_serial_tobinary_filter_proc_lisa.py | 2 | 18114 | # -*- coding: utf-8 -*-
from lar import *
from scipy import *
import json
# import scipy
import numpy as np
# import time as tm
# import gc
# from pngstack2array3d import *
import struct
import getopt
import traceback
#
import matplotlib.pyplot as plt
# threading
import multiprocessing
from multiprocessing import Proc... | mit |
zorroblue/scikit-learn | examples/calibration/plot_calibration.py | 41 | 4826 | """
======================================
Probability calibration of classifiers
======================================
When performing classification you often want to predict not only
the class label, but also the associated probability. This probability
gives you some kind of confidence on the prediction. However,... | bsd-3-clause |
abhishekraok/LayeredNeuralNetwork | layeredneuralnetwork/layered_neural_network.py | 1 | 5785 | import numpy as np
from layeredneuralnetwork import node_manager
from layeredneuralnetwork import node
from sklearn import svm, metrics
from layeredneuralnetwork import transform_function
from layeredneuralnetwork.classifier_interface import ClassifierInterface
from layeredneuralnetwork import utilities
retrain_thresh... | mit |
CJ-Jewell/ThinkStats2 | code/hypothesis.py | 75 | 10162 | """This file contains code used in "Think Stats",
by Allen B. Downey, available from greenteapress.com
Copyright 2010 Allen B. Downey
License: GNU GPLv3 http://www.gnu.org/licenses/gpl.html
"""
from __future__ import print_function, division
import nsfg
import nsfg2
import first
import thinkstats2
import thinkplot
... | gpl-3.0 |
njcuk9999/neil_superwasp_periodogram | fastDFT.py | 1 | 19103 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on 08/03/17 at 12:41 PM
@author: neil
Program description here
Version 0.0.0
"""
import numpy as np
from astropy.io import fits
from numexpr import evaluate as ne
# =============================================================================
# Define vari... | mit |
satriaphd/bgc-learn | core/utils.py | 1 | 8964 | import sys
import os
import subprocess
import json
import straight.plugin
from tempfile import TemporaryFile
from os import path
from core import log
import warnings
with warnings.catch_warnings():
warnings.simplefilter("ignore")
from Bio import SearchIO
try:
from cStringIO import StringIO
except ImportErro... | gpl-3.0 |
qiime2/q2-types | q2_types/feature_data/_transformer.py | 1 | 20226 | # ----------------------------------------------------------------------------
# Copyright (c) 2016-2021, QIIME 2 development team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE, distributed with this software.
# ------------------------------------------------... | bsd-3-clause |
ntamas/yard | yard/curve.py | 1 | 32746 | """
Curve classes used in YARD.
This package contains implementations for all the curves YARD can plot.
At the time of writing, this includes:
- ROC curves (`ROCCurve`)
- CROC curves (`CROCCurve`)
- Precision-recall curves (`PrecisionRecallCurve`)
- Sensitivity-specificity plots (`SensitivitySpecifici... | mit |
FreeSchoolHackers/data_hacking | dga_detection/dga_model_gen.py | 6 | 13951 |
''' Build models to detect Algorithmically Generated Domain Names (DGA).
We're trying to classify domains as being 'legit' or having a high probability
of being generated by a DGA (Dynamic Generation Algorithm). We have 'legit' in
quotes as we're using the domains in Alexa as the 'legit' set.
'''
import o... | mit |
VipinRathor/zeppelin | spark/interpreter/src/main/resources/python/zeppelin_pyspark.py | 5 | 2768 | #
# 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 |
hmendozap/auto-sklearn | test/test_pipeline/components/feature_preprocessing/test_nystroem_sampler.py | 1 | 4484 | import unittest
import numpy as np
import sklearn.preprocessing
from autosklearn.pipeline.components.feature_preprocessing.nystroem_sampler import \
Nystroem
from autosklearn.pipeline.util import _test_preprocessing, get_dataset
class NystroemComponentTest(unittest.TestCase):
def test_default_configuration(... | bsd-3-clause |
akionakamura/scikit-learn | examples/svm/plot_custom_kernel.py | 115 | 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 |
Solid-Mechanics/matplotlib-4-abaqus | matplotlib/animation.py | 4 | 41616 | # TODO:
# * Loop Delay is broken on GTKAgg. This is because source_remove() is not
# working as we want. PyGTK bug?
# * Documentation -- this will need a new section of the User's Guide.
# Both for Animations and just timers.
# - Also need to update http://www.scipy.org/Cookbook/Matplotlib/Animations
# * Blit
... | mit |
glouppe/scikit-learn | doc/tutorial/text_analytics/skeletons/exercise_02_sentiment.py | 157 | 2409 | """Build a sentiment analysis / polarity model
Sentiment analysis can be casted as a binary text classification problem,
that is fitting a linear classifier on features extracted from the text
of the user messages so as to guess wether the opinion of the author is
positive or negative.
In this examples we will use a ... | bsd-3-clause |
SunPower/Carousel | examples/PVPower/pvpower/formulas/irradiance.py | 1 | 3682 | # -*- coding: utf-8 -*-
"""
This module contains formulas for calculating PV power.
"""
import pvlib
import pandas as pd
def f_linketurbidity(times, latitude, longitude):
times = pd.DatetimeIndex(times)
# latitude and longitude must be scalar or else linke turbidity lookup fails
latitude, longitude = la... | bsd-3-clause |
ville-k/tensorflow | tensorflow/contrib/learn/python/learn/estimators/estimators_test.py | 23 | 5276 | # 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 |
ZENGXH/scikit-learn | examples/decomposition/plot_sparse_coding.py | 247 | 3846 | """
===========================================
Sparse coding with a precomputed dictionary
===========================================
Transform a signal as a sparse combination of Ricker wavelets. This example
visually compares different sparse coding methods using the
:class:`sklearn.decomposition.SparseCoder` esti... | bsd-3-clause |
jakobj/nest-simulator | pynest/examples/one_neuron.py | 14 | 3680 | # -*- coding: utf-8 -*-
#
# one_neuron.py
#
# This file is part of NEST.
#
# Copyright (C) 2004 The NEST Initiative
#
# NEST is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 2 of the License, or
... | gpl-2.0 |
LiuVII/Self-driving-RC-car | script_multi.py | 1 | 5002 | import os, time
import argparse
import re
import pandas as pd
from datetime import datetime
import shutil
import csv
from collections import deque
def check_parameters():
if not os.path.exists(data_set_dir+args.record_set+"_log.csv"):
print "Corresponding log.csv file for %s does not exists" % \
... | mit |
moutai/scikit-learn | sklearn/decomposition/tests/test_dict_learning.py | 67 | 9084 | import numpy as np
from sklearn.utils import check_array
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_less
from sklea... | bsd-3-clause |
ClockworkOrigins/m2etis | configurator/quicktest/Reporting.py | 1 | 4530 | __author__ = 'amw'
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from configurator.persistence.PersistenceManager import PersistenceManager
import configurator.util.util as util
from scipy.interpolate import griddata
from configurator.util.util import sanitize_results
impor... | apache-2.0 |
yl565/statsmodels | statsmodels/datasets/nile/data.py | 5 | 1907 | """Nile River Flows."""
__docformat__ = 'restructuredtext'
COPYRIGHT = """This is public domain."""
TITLE = """Nile River flows at Ashwan 1871-1970"""
SOURCE = """
This data is first analyzed in:
Cobb, G. W. 1978. "The Problem of the Nile: Conditional Solution to a
Changepoint Problem." *Bio... | bsd-3-clause |
bsipocz/astropy | astropy/visualization/wcsaxes/tests/test_wcsapi.py | 1 | 6661 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
import pytest
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.transforms import Affine2D, IdentityTransform
from astropy import units as u
from astropy.wcs.wcsapi import BaseLowLevelWCS
from astropy.coordinates import SkyCoord
from as... | bsd-3-clause |
DEK11/Predicting-EOB-delay | withoutpayer.py | 1 | 2272 | import pandas as pd
import numpy as np
train = pd.read_csv('train.csv', header=0)
test = pd.read_csv('test.csv', header=0)
delcol = ['claim_file_arrival_year','claim_file_arrival_month','bill_print_year','bill_print_month','claim_min_service_year','claim_max_service_year','claim_frequency_type_code','claim_min_servic... | apache-2.0 |
blab/nextstrain-db | analysis/HIxFRA_plot.py | 2 | 2607 | import matplotlib.pyplot as plt
import seaborn as sns; sns.set(color_codes=True)
import numpy as np
import math
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('--infile', default=None, type=str, help="file to graph")
parser.add_argument('--rtype', default="linear", type=str, help="type of regr... | agpl-3.0 |
mehdidc/scikit-learn | doc/sphinxext/numpy_ext/docscrape_sphinx.py | 408 | 8061 | import re
import inspect
import textwrap
import pydoc
from .docscrape import NumpyDocString
from .docscrape import FunctionDoc
from .docscrape import ClassDoc
class SphinxDocString(NumpyDocString):
def __init__(self, docstring, config=None):
config = {} if config is None else config
self.use_plots... | bsd-3-clause |
alekz112/statsmodels | statsmodels/examples/ex_misc_tarma.py | 34 | 1875 | # -*- coding: utf-8 -*-
"""
Created on Wed Jul 03 23:01:44 2013
Author: Josef Perktold
"""
from __future__ import print_function
import numpy as np
from statsmodels.tsa.arima_process import arma_generate_sample, ArmaProcess
from statsmodels.miscmodels.tmodel import TArma
from statsmodels.tsa.arima_model import ARMA... | bsd-3-clause |
phdowling/scikit-learn | sklearn/utils/tests/test_random.py | 230 | 7344 | from __future__ import division
import numpy as np
import scipy.sparse as sp
from scipy.misc import comb as combinations
from numpy.testing import assert_array_almost_equal
from sklearn.utils.random import sample_without_replacement
from sklearn.utils.random import random_choice_csc
from sklearn.utils.testing import ... | bsd-3-clause |
huard/scipy-work | scipy/io/examples/read_array_demo1.py | 2 | 1440 | #=========================================================================
# NAME: read_array_demo1
#
# DESCRIPTION: Examples to read 2 columns from a multicolumn ascii text
# file, skipping the first line of header. First example reads into
# 2 separate arrays. Second example reads into a single array. Data are
# then... | bsd-3-clause |
mayblue9/scikit-learn | sklearn/decomposition/nmf.py | 35 | 39369 | """ Non-negative matrix factorization
"""
# Author: Vlad Niculae
# Lars Buitinck <L.J.Buitinck@uva.nl>
# Mathieu Blondel <mathieu@mblondel.org>
# Tom Dupre la Tour
# Author: Chih-Jen Lin, National Taiwan University (original projected gradient
# ... | bsd-3-clause |
ekansa/open-context-py | opencontext_py/apps/imports/kobotoolbox/dbupdate.py | 1 | 48497 | import copy
import csv
import uuid as GenUUID
import os, sys, shutil
import codecs
import numpy as np
import pandas as pd
from django.db import models
from django.db.models import Q
from django.conf import settings
from opencontext_py.apps.ocitems.manifest.models import Manifest
from opencontext_py.apps.ocitems.assert... | gpl-3.0 |
Mecanon/morphing_wing | dynamic_model/results/flexinol_SMA/config_A/max_deflection/power_usage_2.py | 3 | 11206 | # -*- coding: utf-8 -*-
"""
Analyze the heating, current and power usage of teh actuation
Created on Thu Apr 28 09:56:23 2016
@author: Pedro Leal
"""
import math
import numpy as np
import pickle
import matplotlib.pyplot as plt
#Time step
delta_t = 0.005
sigma_o = 100e6
r = 0.000381/2.
d = 2*r
alpha = 0. #... | mit |
leggitta/mne-python | examples/connectivity/plot_mne_inverse_connectivity_spectrum.py | 18 | 3465 | """
==============================================================
Compute full spectrum source space connectivity between labels
==============================================================
The connectivity is computed between 4 labels across the spectrum
between 5 and 40 Hz.
"""
# Authors: Alexandre Gramfort <alex... | bsd-3-clause |
Lawrence-Liu/scikit-learn | sklearn/datasets/tests/test_samples_generator.py | 181 | 15664 | from __future__ import division
from collections import defaultdict
from functools import partial
import numpy as np
import scipy.sparse as sp
from sklearn.externals.six.moves import zip
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing imp... | bsd-3-clause |
grundgruen/zipline | zipline/protocol.py | 1 | 17544 | #
# Copyright 2013 Quantopian, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in wr... | apache-2.0 |
davidgardenier/frbpoppy | frbpoppy/misc.py | 1 | 4119 | """Convenience functions."""
import inspect
import sys
import numpy as np
from scipy.integrate import quad
from scipy.stats import chi2, norm
def pprint(*s, output=True):
"""Hack to make for more informative print statements."""
f = inspect.stack()[1][1].split('/')[-1]
m = '{:13.13} |'.format(f)
if o... | mit |
emon10005/sympy | sympy/physics/quantum/state.py | 58 | 29186 | """Dirac notation for states."""
from __future__ import print_function, division
from sympy import (cacheit, conjugate, Expr, Function, integrate, oo, sqrt,
Tuple)
from sympy.core.compatibility import u, range
from sympy.printing.pretty.stringpict import stringPict
from sympy.physics.quantum.qexpr ... | bsd-3-clause |
SaikWolf/gnuradio | gr-filter/examples/synth_to_chan.py | 18 | 3875 | #!/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 |
gfyoung/pandas | pandas/tests/strings/test_string_array.py | 1 | 3130 | import numpy as np
import pytest
from pandas._libs import lib
import pandas as pd
from pandas import DataFrame, Series, _testing as tm
def test_string_array(any_string_method):
method_name, args, kwargs = any_string_method
if method_name == "decode":
pytest.skip("decode requires bytes.")
data =... | bsd-3-clause |
djgagne/scikit-learn | sklearn/decomposition/tests/test_kernel_pca.py | 155 | 8058 | import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import (assert_array_almost_equal, assert_less,
assert_equal, assert_not_equal,
assert_raises)
from sklearn.decomposition import PCA, KernelPCA
from sklearn.datasets import mak... | bsd-3-clause |
amolkahat/pandas | pandas/tests/extension/base/reduce.py | 2 | 1908 | import warnings
import pytest
import pandas.util.testing as tm
import pandas as pd
from .base import BaseExtensionTests
class BaseReduceTests(BaseExtensionTests):
"""
Reduction specific tests. Generally these only
make sense for numeric/boolean operations.
"""
def check_reduce(self, s, op_name, sk... | bsd-3-clause |
PG-TUe/tpot | tpot/config/classifier.py | 1 | 6159 | # -*- coding: utf-8 -*-
"""This file is part of the TPOT library.
TPOT was primarily developed at the University of Pennsylvania by:
- Randal S. Olson (rso@randalolson.com)
- Weixuan Fu (weixuanf@upenn.edu)
- Daniel Angell (dpa34@drexel.edu)
- and many more generous open source contributors
TPOT is f... | lgpl-3.0 |
Nyker510/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 |
Atzingen/controleForno-interface | imagens/bind.py | 1 | 1237 | # -*- coding: latin-1 -*-
import numpy as np
import cv2
from matplotlib import pyplot as plt
perfil = cv2.imread('temperatura.jpg')
forno = cv2.imread('forno-pre.jpg')
col_perfil, lin_perfil, _ = perfil.shape
col_forno, lin_forno, _ = forno.shape
print 'perfil antes:', lin_perfil, col_perfil, 'forno:', lin_forno, col... | mit |
RichHelle/data-science-from-scratch | scratch/visualization.py | 3 | 4696 | from matplotlib import pyplot as plt
years = [1950, 1960, 1970, 1980, 1990, 2000, 2010]
gdp = [300.2, 543.3, 1075.9, 2862.5, 5979.6, 10289.7, 14958.3]
# create a line chart, years on x-axis, gdp on y-axis
plt.plot(years, gdp, color='green', marker='o', linestyle='solid')
# add a title
plt.title("Nominal GDP")
# add... | unlicense |
Winand/pandas | pandas/tests/io/parser/na_values.py | 6 | 10530 | # -*- coding: utf-8 -*-
"""
Tests that NA values are properly handled during
parsing for all of the parsers defined in parsers.py
"""
import numpy as np
from numpy import nan
import pandas.io.common as com
import pandas.util.testing as tm
from pandas import DataFrame, Index, MultiIndex
from pandas.compat import Str... | bsd-3-clause |
hvasbath/beat | beat/heart.py | 1 | 115730 | """
Core module with functions to calculate Greens Functions and synthetics.
Also contains main classes for setup specific parameters.
"""
import os
import logging
import shutil
import copy
from time import time
from collections import OrderedDict
from beat import psgrn, pscmp, utility, qseis2d
from theano import co... | gpl-3.0 |
arabenjamin/scikit-learn | examples/linear_model/lasso_dense_vs_sparse_data.py | 348 | 1862 | """
==============================
Lasso on dense and sparse data
==============================
We show that linear_model.Lasso provides the same results for dense and sparse
data and that in the case of sparse data the speed is improved.
"""
print(__doc__)
from time import time
from scipy import sparse
from scipy ... | bsd-3-clause |
beiko-lab/gengis | bin/Lib/site-packages/mpl_toolkits/axes_grid1/axes_divider.py | 4 | 29599 | """
The axes_divider module provide helper classes to adjust the positions of
multiple axes at the drawing time.
Divider: this is the class that is used calculates the axes
position. It divides the given rectangular area into several sub
rectangles. You initialize the divider by setting the horizontal
and... | gpl-3.0 |
mantidproject/mantid | qt/python/mantidqt/widgets/samplelogs/test/test_samplelogs_presenter.py | 3 | 4246 | # Mantid Repository : https://github.com/mantidproject/mantid
#
# Copyright © 2018 ISIS Rutherford Appleton Laboratory UKRI,
# NScD Oak Ridge National Laboratory, European Spallation Source,
# Institut Laue - Langevin & CSNS, Institute of High Energy Physics, CAS
# SPDX - License - Identifier: GPL - 3.0 +
# T... | gpl-3.0 |
cuemacro/chartpy | chartpy/chartconstants.py | 1 | 11701 | __author__ = 'saeedamen' # Saeed Amen
#
# Copyright 2016 Cuemacro
#
# 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 l... | apache-2.0 |
pearpai/TensorFlow-action | action/demo5/captcha_image.py | 1 | 1686 | # coding=utf-8
from captcha.image import ImageCaptcha # pip install captcha
import numpy as np
import matplotlib.pyplot as plt
from PIL import Image
import random
# 验证码中的字符, 就不用汉字了
number = ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9']
# alphabet = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm'... | apache-2.0 |
carrillo/scikit-learn | examples/cluster/plot_kmeans_assumptions.py | 270 | 2040 | """
====================================
Demonstration of k-means assumptions
====================================
This example is meant to illustrate situations where k-means will produce
unintuitive and possibly unexpected clusters. In the first three plots, the
input data does not conform to some implicit assumptio... | bsd-3-clause |
zuku1985/scikit-learn | examples/cluster/plot_cluster_comparison.py | 58 | 4681 | """
=========================================================
Comparing different clustering algorithms on toy datasets
=========================================================
This example aims at showing characteristics of different
clustering algorithms on datasets that are "interesting"
but still in 2D. The last ... | bsd-3-clause |
robcarver17/pysystemtrade | systems/rawdata.py | 1 | 11935 | from copy import copy
import pandas as pd
from systems.stage import SystemStage
from syscore.objects import resolve_function
from systems.system_cache import input, diagnostic, output
from sysdata.sim.futures_sim_data import futuresSimData
from sysdata.config.configdata import Config
class RawData(SystemStage):
... | gpl-3.0 |
danielballan/vistools | vistools/qt_widgets.py | 1 | 3165 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import PySide.QtCore as QtCore
import PySide.QtGui as QtGui
from . import images
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas # noqa
from matplotlib.backends.b... | bsd-3-clause |
sao-eht/lmtscripts | 2017/loc.py | 1 | 9254 | # 1mm localization and total power in dreampy
# 2015, 2016 LLB
import numpy
import matplotlib
import shutil
# matplotlib.use('agg')
from matplotlib import pylab, mlab, pyplot
import os
np = numpy
plt = pyplot
# plt.ion()
from argparse import Namespace
from glob import glob
import scipy.io
from scipy.signal import butt... | mit |
dvida/UnknownPleasuresGenerator | UnknownPleasuresGenerator.py | 1 | 3075 | import matplotlib.pyplot as plt
import numpy as np
# Number of curves to plot
curves_no = 80
# Curve vertical spacing
curve_v_space = 3
# Maximum munber of peaks in the center
max_peaks = 9
# Maximum parabolic peak amplitude
max_parab_peak_amplitude = 0.05
# Maximum pointy peak amplitude
max_point_peak_amplitude = 0... | gpl-2.0 |
rosswhitfield/mantid | Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/SANS/SANSBeamCentreFinder.py | 3 | 19739 | # Mantid Repository : https://github.com/mantidproject/mantid
#
# Copyright © 2018 ISIS Rutherford Appleton Laboratory UKRI,
# NScD Oak Ridge National Laboratory, European Spallation Source,
# Institut Laue - Langevin & CSNS, Institute of High Energy Physics, CAS
# SPDX - License - Identifier: GPL - 3.0 +
# py... | gpl-3.0 |
francisleunggie/openface | demos/sphere.py | 7 | 8951 | #!/usr/bin/env python2
# projectS and projectC were written by Gabriele Farina.
import time
start = time.time()
import argparse
import cv2
import os
import dlib
import numpy as np
np.set_printoptions(precision=2)
import openface
from matplotlib import cm
fileDir = os.path.dirname(os.path.realpath(__file__))
model... | apache-2.0 |
gotomypc/scikit-learn | examples/decomposition/plot_sparse_coding.py | 247 | 3846 | """
===========================================
Sparse coding with a precomputed dictionary
===========================================
Transform a signal as a sparse combination of Ricker wavelets. This example
visually compares different sparse coding methods using the
:class:`sklearn.decomposition.SparseCoder` esti... | bsd-3-clause |
syl20bnr/nupic | examples/opf/tools/testDiagnostics.py | 11 | 1762 | import numpy as np
############################################################################
def printMatrix(inputs, spOutput):
''' (i,j)th cell of the diff matrix will have the number of inputs for which the input and output
pattern differ by i bits and the cells activated differ at j places.
Parameters:
-... | gpl-3.0 |
timtammittee/thorns | thorns/util/dumpdb.py | 1 | 3516 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""This module implements permanent store for data.
"""
from __future__ import division, print_function, absolute_import
from __future__ import unicode_literals
__author__ = "Marek Rudnicki"
import os
import datetime
import logging
from itertools import izip_longest
imp... | gpl-3.0 |
ajc158/beeworld | gigerommatidiamodelbeeworld.py | 1 | 4121 | import matplotlib.pyplot as plt
import math
import numpy
from mpl_toolkits.mplot3d import Axes3D
def vert(x):
return (0.000734*(x**2))-(0.1042253*x)+4.9
def horr(x):
if x>60:
return (0.00037*(x**2))-(0.04462*x)+3.438
else:
return (0.00069*(x**2))-(0.08333*x)+4.6
def radialDistortion(x,y):
camYaw=0.0/180.0*... | gpl-3.0 |
bitmonk/pgcli | pgcli/packages/tabulate.py | 28 | 38075 | # -*- coding: utf-8 -*-
"""Pretty-print tabular data."""
from __future__ import print_function
from __future__ import unicode_literals
from collections import namedtuple
from decimal import Decimal
from platform import python_version_tuple
from wcwidth import wcswidth
import re
if python_version_tuple()[0] < "3":
... | bsd-3-clause |
SeldonIO/seldon-server | docker/examples/tensorflow_deep_mnist/create_pipeline.py | 2 | 3690 | from tensorflow.examples.tutorials.mnist import input_data
#mnist = input_data.read_data_sets("MNIST_data/", one_hot = True)
import tensorflow as tf
from seldon.tensorflow_wrapper import TensorFlowWrapper
from sklearn.pipeline import Pipeline
import seldon.pipeline.util as sutl
import argparse
def weight_variable(shap... | apache-2.0 |
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