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 |
|---|---|---|---|---|---|
hugobowne/scikit-learn | examples/decomposition/plot_image_denoising.py | 70 | 6249 | """
=========================================
Image denoising using dictionary learning
=========================================
An example comparing the effect of reconstructing noisy fragments
of a raccoon face image using firstly online :ref:`DictionaryLearning` and
various transform methods.
The dictionary is fi... | bsd-3-clause |
ssaeger/scikit-learn | benchmarks/bench_glm.py | 297 | 1493 | """
A comparison of different methods in GLM
Data comes from a random square matrix.
"""
from datetime import datetime
import numpy as np
from sklearn import linear_model
from sklearn.utils.bench import total_seconds
if __name__ == '__main__':
import pylab as pl
n_iter = 40
time_ridge = np.empty(n_it... | bsd-3-clause |
rhyolight/nupic | examples/opf/clients/cpu/cpu.py | 10 | 3122 | # ----------------------------------------------------------------------
# Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2013, Numenta, Inc. Unless you have an agreement
# with Numenta, Inc., for a separate license for this software code, the
# following terms and conditions apply:
#
# This progra... | agpl-3.0 |
466152112/scikit-learn | examples/svm/plot_svm_regression.py | 249 | 1451 | """
===================================================================
Support Vector Regression (SVR) using linear and non-linear kernels
===================================================================
Toy example of 1D regression using linear, polynomial and RBF kernels.
"""
print(__doc__)
import numpy as np
... | bsd-3-clause |
yushiangfu/jusa | src/fetch-test.py | 1 | 12741 | import filecmp
import fetch
import os
from datetime import datetime, date, timedelta
from urllib import request
import time
import pandas
def need_update_stock_table_test(expect):
""" test module for need_update_stock_table() """
res = fetch.need_update_stock_table()
if res == expect:
print('pass'... | gpl-2.0 |
kevinthesun/mxnet | example/autoencoder/data.py | 27 | 1272 | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | apache-2.0 |
JeffreyFish/DocWebTool | Rename.py | 2 | 5793 | #!/usr/bin/env python
# -*- Coding: UTF-8 -*-
#------------------------------------
#--Author: Jeffrey Yu
#--CreationDate: 2017/10/24 14:00
#--RevisedDate:
#------------------------------------
import os
import pandas as pd
import datetime
import common
def rename(x, type='umbrella'):
if type == 'umbrell... | gpl-3.0 |
mabevillar/rmtk | tests/vulnerability/tests_TO_BE_CHANGED/NSP/fragility_process/test_spo2ida_method.py | 4 | 2144 | # -*- coding: utf-8 -*-
# <nbformat>3.0</nbformat>
# <codecell>
"""
Created on Thu May 29 11:29:32 2014
@author: chiaracasotto
"""
# Clear existing variables
def clearall():
all = [var for var in globals() if var[0] != "_"]
for var in all:
del globals()[var]
clearall()
import pandas as pd
import nump... | agpl-3.0 |
tobiasgehring/qudi | core/__init__.py | 6 | 1673 | # -*- coding: utf-8 -*-
"""
This file contains the Qudi Manager class.
Qudi is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Qudi is distrib... | gpl-3.0 |
anve8004/trading-with-python | nautilus/nautilus.py | 77 | 5403 | '''
Created on 26 dec. 2011
Copyright: Jev Kuznetsov
License: BSD
'''
from PyQt4.QtCore import *
from PyQt4.QtGui import *
from ib.ext.Contract import Contract
from ib.opt import ibConnection
from ib.ext.Order import Order
import tradingWithPython.lib.logger as logger
from tradingWithPython.lib.eve... | bsd-3-clause |
Achuth17/scikit-learn | sklearn/utils/tests/test_multiclass.py | 72 | 15350 | from __future__ import division
import numpy as np
import scipy.sparse as sp
from itertools import product
from functools import partial
from sklearn.externals.six.moves import xrange
from sklearn.externals.six import iteritems
from scipy.sparse import issparse
from scipy.sparse import csc_matrix
from scipy.sparse im... | bsd-3-clause |
zhenv5/scikit-learn | sklearn/metrics/tests/test_pairwise.py | 71 | 25104 | 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 |
glemaitre/UnbalancedDataset | examples/under-sampling/plot_illustration_tomek_links.py | 2 | 3511 | """
==============================================
Illustration of the definition of a Tomek link
==============================================
This example illustrates what is a Tomek link.
"""
import matplotlib.pyplot as plt
import numpy as np
from imblearn.under_sampling import TomekLinks
print(__doc__)
rng =... | mit |
pnedunuri/scikit-learn | sklearn/cluster/tests/test_k_means.py | 63 | 26190 | """Testing for K-means"""
import sys
import numpy as np
from scipy import sparse as sp
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import SkipTest
from sklearn.utils.testing i... | bsd-3-clause |
edouardpoitras/NowTrade | nowtrade/figures.py | 1 | 8093 | """
This module provides an abstraction layer over matplotlib's plotting
functionality. It focuses on easily plotting charts of your strategy's
performance and technical indicators.
"""
import matplotlib.pyplot as plt
from matplotlib.finance import candlestick_ochl
from matplotlib.dates import date2num
import pandas a... | mit |
DavidTingley/ephys-processing-pipeline | installation/klustaviewa-0.3.0/klustaviewa/views/tests/test_logview.py | 2 | 1038 | """Unit tests for log view."""
# -----------------------------------------------------------------------------
# Imports
# -----------------------------------------------------------------------------
import os
import sys
import time
import numpy as np
import numpy.random as rnd
import pandas as pd
from... | gpl-3.0 |
metaml/nupic | src/nupic/research/monitor_mixin/monitor_mixin_base.py | 27 | 5512 | # ----------------------------------------------------------------------
# Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2014, Numenta, Inc. Unless you have an agreement
# with Numenta, Inc., for a separate license for this software code, the
# following terms and conditions apply:
#
# This progra... | agpl-3.0 |
AlexanderFabisch/scikit-learn | examples/svm/plot_svm_regression.py | 120 | 1520 | """
===================================================================
Support Vector Regression (SVR) using linear and non-linear kernels
===================================================================
Toy example of 1D regression using linear, polynomial and RBF kernels.
"""
print(__doc__)
import numpy as np
... | bsd-3-clause |
andyraib/data-storage | python_scripts/env/lib/python3.6/site-packages/mpl_toolkits/axes_grid1/axes_divider.py | 10 | 31231 | """
The axes_divider module provides helper classes to adjust the positions of
multiple axes at drawing time.
Divider: this is the class that is used to calculate the axes
position. It divides the given rectangular area into several sub
rectangles. You initialize the divider by setting the horizontal
and ... | apache-2.0 |
kashif/scikit-learn | sklearn/tests/test_multiclass.py | 18 | 24010 | import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_false
from sklearn.utils.testing ... | bsd-3-clause |
ChanderG/scipy | scipy/stats/kde.py | 27 | 17303 | #-------------------------------------------------------------------------------
#
# Define classes for (uni/multi)-variate kernel density estimation.
#
# Currently, only Gaussian kernels are implemented.
#
# Written by: Robert Kern
#
# Date: 2004-08-09
#
# Modified: 2005-02-10 by Robert Kern.
# Contr... | bsd-3-clause |
mehdidc/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 |
Nathx/subs_check | code/feature_blending.py | 2 | 5969 | from main import set_spark_context
from spark_model import SparkModel
from datetime import datetime
from pyspark.ml import Pipeline
import numpy as np
import pandas as pd
from boto.s3.connection import S3Connection
from pyspark import SparkConf, SparkContext, SQLContext
from pyspark.ml.feature import StringIndexer, St... | mit |
edent/Fronius-DataManager-Solar-Logger | fronius-strings.py | 1 | 4754 | ## With thanks to https://github.com/grann0s/_pushPVStringData.php
## And https://forum.pvoutput.org/t/fronius-mppt-1-and-2-voltages-and-details/1259/
## This code MIT
import datetime
from datetime import timedelta
import pytz
import os
import os.path
import requests
import json
import matplotlib as mpl
mpl.use('Agg')... | mit |
kezilu/pextant | pextant/explorers.py | 2 | 11816 | import logging
import numpy as np
from pextant.lib.geoshapely import GeoPolygon
import pandas as pd
logger = logging.getLogger()
class TraversePath:
def __init__(self, geopolygon, z, x,y,em=None, derived=None):
self.geopolygon = geopolygon
self.z = z
self.x = x
self.y = y
s... | mit |
YinongLong/scikit-learn | sklearn/linear_model/least_angle.py | 15 | 57254 | """
Least Angle Regression algorithm. See the documentation on the
Generalized Linear Model for a complete discussion.
"""
from __future__ import print_function
# Author: Fabian Pedregosa <fabian.pedregosa@inria.fr>
# Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Gael Varoquaux
#
# License: BSD 3 ... | bsd-3-clause |
rkmaddox/mne-python | tutorials/epochs/10_epochs_overview.py | 7 | 19956 | # -*- coding: utf-8 -*-
"""
.. _tut-epochs-class:
The Epochs data structure: discontinuous data
=============================================
This tutorial covers the basics of creating and working with :term:`epoched
<epochs>` data. It introduces the :class:`~mne.Epochs` data structure in
detail, including how to lo... | bsd-3-clause |
bakfu/bakfu | bakfu/process/vectorize/tests/test_vec_sklearn.py | 2 | 1503 | # -*- coding: utf-8 -*-
import pytest
from bakfu.core import Chain
from bakfu.process.vectorize import vec_sklearn
@pytest.fixture
def fixture():
'''
Creates a processor chain with test data.
'''
data=((0,'data test 1'),
(1,'Data test 2'),
(2,'other data test 3.')
)
... | bsd-3-clause |
valexandersaulys/prudential_insurance_kaggle | venv/lib/python2.7/site-packages/sklearn/feature_extraction/text.py | 50 | 50249 | # -*- coding: utf-8 -*-
# Authors: Olivier Grisel <olivier.grisel@ensta.org>
# Mathieu Blondel <mathieu@mblondel.org>
# Lars Buitinck <L.J.Buitinck@uva.nl>
# Robert Layton <robertlayton@gmail.com>
# Jochen Wersdörfer <jochen@wersdoerfer.de>
# Roman Sinayev <roman.sinayev@gma... | gpl-2.0 |
Caoimhinmg/PmagPy | programs/remanence_anisotropy_magic.py | 3 | 27367 | #!/usr/bin/env python
#import matplotlib
from __future__ import division
from __future__ import print_function
from builtins import range
from past.utils import old_div
import sys
import pylab
from pylab import *
import scipy
import os
import pmagpy.pmag as pmag
def main():
"""
NAME
remanence_aniso_m... | bsd-3-clause |
jackbrucesimpson/DBee | src/beehaviour/csv_utils.py | 1 | 8679 | #!/usr/bin/env python
import os
import datetime
from beehaviour import DB
from .experiment import Experiment
CAMERA_FRAMES_PER_SEC = 25
FRAMES_IN_AN_HOUR = CAMERA_FRAMES_PER_SEC * 60 * 60
def get_next_bee_id():
db = DB()
query_statement = db.query_string(table='bees', cols=['MAX(BeeID)'])
query_result =... | mit |
edouardpoitras/NowTrade | nowtrade/strategy.py | 1 | 7470 | """
Strategy module iterates through all trading data, coordinates all criteria
groups with actions, and feeds information to the report object for metrics.
"""
import pandas as pd
from nowtrade import logger
from nowtrade.action import LONG, SHORT, NO_ACTION, LONG_EXIT, SHORT_EXIT, ACTIONS_MAP
from nowtrade import rep... | mit |
mehdidc/scikit-learn | examples/svm/plot_svm_scale_c.py | 223 | 5375 | """
==============================================
Scaling the regularization parameter for SVCs
==============================================
The following example illustrates the effect of scaling the
regularization parameter when using :ref:`svm` for
:ref:`classification <svm_classification>`.
For SVC classificati... | bsd-3-clause |
nelango/ViralityAnalysis | model/lib/pandas/tests/test_categorical.py | 9 | 162878 | # -*- coding: utf-8 -*-
# pylint: disable=E1101,E1103,W0232
from datetime import datetime
from pandas.compat import range, lrange, u, PY3
import os
import pickle
import re
from distutils.version import LooseVersion
import numpy as np
import pandas as pd
from pandas import Categorical, Index, Series, DataFrame, Perio... | mit |
CovingtonResearchGroup/olm | olm/loggers/TruBluToolkit.py | 1 | 1515 | #Tools for reading and analysis of data from TruBlu data loggers
from pandas import read_csv
from pandas import concat
from pandas import DataFrame
import os
"""
Functions to read TruBlu logger files.
"""
#read in the CSV file from a TruBlu logger and return a pandas DataFrame
def readTruBlu(csvfile):
"""
R... | mit |
ryfeus/lambda-packs | Tensorflow_Pandas_Numpy/source3.6/keras_preprocessing/image.py | 1 | 94844 | """Utilities for real-time data augmentation on image data.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import re
from six.moves import range
import os
import threading
import warnings
import multiprocessing.pool
from keras_preproc... | mit |
davidam/python-examples | scikit/scikit-plot-unveil-tree-sctructure.py | 47 | 4852 | """
=========================================
Understanding the decision tree structure
=========================================
The decision tree structure can be analysed to gain further insight on the
relation between the features and the target to predict. In this example, we
show how to retrieve:
- the binary t... | gpl-3.0 |
ryanpepper/oommf-python | joommf/vectorfield.py | 2 | 3858 | import numpy as np
import matplotlib.pyplot as plt
class VectorField(object):
def __init__(self, filename):
f = open(filename, 'r')
lines = f.readlines()
for line in lines:
if line.startswith('# xmin'):
self.xmin = float(line[7:])
if line.startswith... | bsd-2-clause |
ngoix/OCRF | sklearn/datasets/__init__.py | 1 | 4316 | """
The :mod:`sklearn.datasets` module includes utilities to load datasets,
including methods to load and fetch popular reference datasets. It also
features some artificial data generators.
"""
from .base import load_diabetes
from .base import load_digits
from .base import load_files
from .base import load_iris
from .... | bsd-3-clause |
fumitoh/modelx | modelx/tests/core/space/test_new_cells_from_csv.py | 1 | 2163 | import pytest
from modelx import *
from modelx.tests.testdata import (
CSV_SINGLE_PARAM,
CSV_MULTI_PARAMS,
CSV_SINGLE_PARAM_SINGLE_COL,
CSV_IRIS)
@pytest.fixture(scope="session")
def testmodel():
return new_model()
@pytest.mark.parametrize(
"param, index_col, usecols", [[None, 0, None],
... | gpl-3.0 |
christobal54/aei-grad-school | bin/old/plot_image_histograms.py | 1 | 4630 | #####
# plots histograms of raster data
#####
import os as os
import aei as aei
import numpy as np
import gdal as gdal
import matplotlib.pyplot as plt
import matplotlib.mlab as mlab
infiles = ['/home/cba/cba/costa_rica/Costa_Rica_Biomass_Baccini.tif',
'/home/cba/cba/costa_rica/Costa_Rica_insol_total_winter.... | mit |
Edu-Glez/Bank_sentiment_analysis | env/lib/python3.6/site-packages/jupyter_core/tests/dotipython_empty/profile_default/ipython_notebook_config.py | 13 | 19986 | # Configuration file for ipython-notebook.
c = get_config()
#------------------------------------------------------------------------------
# NotebookApp configuration
#------------------------------------------------------------------------------
# NotebookApp will inherit config from: BaseIPythonApplication, Appli... | apache-2.0 |
466152112/scikit-learn | examples/linear_model/plot_robust_fit.py | 238 | 2414 | """
Robust linear estimator fitting
===============================
Here a sine function is fit with a polynomial of order 3, for values
close to zero.
Robust fitting is demoed in different situations:
- No measurement errors, only modelling errors (fitting a sine with a
polynomial)
- Measurement errors in X
- M... | bsd-3-clause |
divyanshgaba/Summer-Training-Project | Practice/ConvolutionLayerMNISTwithPrettyTensor.py | 1 | 4402 | import matplotlib.pyplot as plt
import tensorflow as tf
import numpy as np
import time
from datetime import timedelta
import math
import prettytensor as pt
from tensorflow.examples.tutorials.mnist import input_data
data = input_data.read_data_sets('data/MNIST/',one_hot=True)
data.test.cls = np.argmax(data.test.labels... | apache-2.0 |
dboyliao/ibis | ibis/impala/tests/test_client.py | 2 | 7689 | # Copyright 2014 Cloudera 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 writing, so... | apache-2.0 |
CUFCTL/face-recognition | scripts/parse_gtex.py | 4 | 2441 | #/usr/bin/python
import numpy as np
import cmapPy as cmap
import os
# dictionary for each sample type
tissues = {
"Adipose-Subcutaneous" : 350,
"Adipose-Visceral" : 227,
"Adrenal-Gland" : 145,
"Artery-Aorta" : 224,
"Artery-Coronary" : 133,
"Artery-Tibial" : 332,
"Bladder" : 11,
"Brain-Amygdala" : 72,
"Bra... | mit |
abhishekgahlot/scikit-learn | examples/cluster/plot_dict_face_patches.py | 11 | 2747 | """
Online learning of a dictionary of parts of faces
==================================================
This example uses a large dataset of faces to learn a set of 20 x 20
images patches that constitute faces.
From the programming standpoint, it is interesting because it shows how
to use the online API of the sciki... | bsd-3-clause |
wilsonkichoi/zipline | zipline/data/treasuries.py | 9 | 3406 | #
# 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 |
sebp/scikit-survival | tests/test_datasets.py | 1 | 18366 | from io import StringIO
import os
import tempfile
import numpy
from numpy.testing import assert_array_almost_equal, assert_array_equal
import pandas
import pandas.util.testing as tm
import pytest
import sksurv.datasets as sdata
from sksurv.io import writearff
ARFF_CATEGORICAL_INDEX_1 = """@relation arff_categorical_... | gpl-3.0 |
DSLituiev/scikit-learn | examples/datasets/plot_iris_dataset.py | 283 | 1928 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
The Iris Dataset
=========================================================
This data sets consists of 3 different types of irises'
(Setosa, Versicolour, and Virginica) petal and sepal
length, stored in a 150x4 numpy... | bsd-3-clause |
Monika319/EWEF-1 | Sprawko 4/Bode/BodePlotMultifile.py | 1 | 1525 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals, division
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import rc
import scipy.optimize
import os
from matplotlib.ticker import MultipleLocator, FormatStrFormatter, FixedLocator
from numpy import pi
rc('font', family='Consolas')
from ... | gpl-2.0 |
kubeflow/examples | github_issue_summarization/workflow/workspace/src/recommend.py | 2 | 1448 | import argparse
import keras
import pandas as pd
from seq2seq_utils import load_text_processor
from seq2seq_utils import Seq2Seq_Inference
# Parsing flags.
parser = argparse.ArgumentParser()
parser.add_argument("--input_csv")
parser.add_argument("--input_model_h5")
parser.add_argument("--input_body_preprocessor_dpkl")... | apache-2.0 |
wateraccounting/wa | General/data_conversions.py | 1 | 16172 | # -*- coding: utf-8 -*-
"""
Created on Sun Dec 18 13:07:32 2016
@author: tih
"""
import gzip
import zipfile
import gdal
import osr
import os
import pandas as pd
import numpy as np
import netCDF4
import time
def Convert_nc_to_tiff(input_nc, output_folder):
"""
This function converts the nc file into tiff files... | apache-2.0 |
scikit-garden/scikit-garden | skgarden/mondrian/tree/tests/test_mondrian_partial_fit.py | 1 | 11034 | """
Tests specific to incremental building of trees.
"""
import numpy as np
from sklearn.datasets import make_classification
from sklearn.datasets import make_regression
from sklearn.datasets import load_digits
from numpy.testing import assert_almost_equal
from numpy.testing import assert_equal
from numpy.testing impo... | bsd-3-clause |
michaelbramwell/sms-tools | lectures/06-Harmonic-model/plots-code/spectral-peaks.py | 22 | 1161 | import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import hamming, triang, blackmanharris
import math
import sys, os, functools, time
sys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)), '../../../software/models/'))
import dftModel as DFT
import utilFunctions as UF
(fs, x) = UF... | agpl-3.0 |
DemocracyClub/yournextrepresentative | ynr/apps/sopn_parsing/models.py | 1 | 1043 | import json
from django.db import models
from model_utils.models import TimeStampedModel
class ParsedSOPN(TimeStampedModel):
"""
A model for storing the parsed data out of a PDF
"""
sopn = models.OneToOneField(
"official_documents.OfficialDocument", on_delete=models.CASCADE
)
raw_da... | agpl-3.0 |
tojojames/MVCP-Orange3 | cp/tests.py | 2 | 27714 | """Unittests for conformal prediction."""
from unittest import TestCase
import os
import numpy as np
import sklearn.svm as skl_svm
from sklearn.ensemble import RandomForestRegressor
from Orange.classification import NaiveBayesLearner, LogisticRegressionLearner, SVMLearner, KNNLearner
from Orange.data impor... | lgpl-3.0 |
LohithBlaze/scikit-learn | examples/linear_model/plot_sgd_loss_functions.py | 249 | 1095 | """
==========================
SGD: convex loss functions
==========================
A plot that compares the various convex loss functions supported by
:class:`sklearn.linear_model.SGDClassifier` .
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
def modified_huber_loss(y_true, y_pred):
z ... | bsd-3-clause |
soulmachine/scikit-learn | sklearn/neighbors/tests/test_neighbors.py | 2 | 31748 | from itertools import product
import numpy as np
from scipy.sparse import (bsr_matrix, coo_matrix, csc_matrix, csr_matrix,
dok_matrix, lil_matrix)
from sklearn.cross_validation import train_test_split
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing impo... | bsd-3-clause |
VUIIS/dax | bin/supplemental_tools/Xnatreport_assessor.py | 1 | 1468 | #!/usr/bin/env python
import json
import sys
import pandas
import pyxnat
from dax import XnatUtils
from dax import utilities
if len(sys.argv)!=4 :
print('Usage:')
print('python Xnatreport_assessor.py <project> <proctype> <output_csvfile>')
sys.exit()
project = sys.argv[1]
proctype = sys.argv[2]
outfile ... | mit |
CDNoyes/EDL-Py | EntryGuidance/EntryEquations.py | 1 | 21185 | import numpy as np
import sys
sys.path.append("./")
from EntryGuidance.EntryVehicle import EntryVehicle
from EntryGuidance.Planet import Planet
class Entry(object):
""" Basic equations of motion for unpowered and powered flight through an atmosphere. """
def __init__(self, PlanetModel=Planet('Mars... | gpl-3.0 |
serl/hls-bba-testbed | pylibs/plot.py | 1 | 41021 | import log
import numpy as np
import cPickle as pickle
from zipfile import PyZipFile
from tempfile import NamedTemporaryFile
from generic import is_percentage
def show(plt, session, fig, export, size=None):
if export:
if size is None:
size = (22,12)
if isinstance(export, basestring):
export = [export]
for... | mit |
KAsante95/osf.io | scripts/annotate_rsvps.py | 60 | 2256 | """Utilities for annotating workshop RSVP data.
Example ::
import pandas as pd
from scripts import annotate_rsvps
frame = pd.read_csv('workshop.csv')
annotated = annotate_rsvps.process(frame)
annotated.to_csv('workshop-annotated.csv')
"""
import re
import logging
from dateutil.parser import par... | apache-2.0 |
aparafita/news-similarity | newsparser/scripts/retry_download.py | 1 | 1061 | # -*- coding: utf-8-*-
# Author: Álvaro Parafita (parafita.alvaro@gmail.com)
import pandas as pd
from newsparser.updater import retry_download
from newsparser.data import load_feeds
folder = '/Users/alvaro_parafita/Desktop/TFG/data'
feeds = load_feeds(folder)
# Update local files
try:
for feed in feeds:
... | gpl-3.0 |
tbs1980/otkpp | pyotk/pyotk/plot2d.py | 1 | 5735 | """Implements tools for drawing 2d plots.
This module implements tools for drawing contour plots
of objective functions and iterates on top of contour
lines.
"""
import math
import numpy
from native import *
from plotutils import *
from testproblems import *
from matplotlib.pyplot import *
from numpy import arange,... | gpl-3.0 |
jrderuiter/im-fusion | src/imfusion/merge.py | 2 | 3739 | # -*- coding: utf-8 -*-
"""Implements functions for merging datasets from multiple samples."""
# pylint: disable=wildcard-import,redefined-builtin,unused-wildcard-import
from __future__ import absolute_import, division, print_function
from builtins import *
# pylint: enable=wildcard-import,redefined-builtin,unused-wil... | mit |
cainesap/mapMakeR | languagesOfTheWorld/archive/glottolog_ipython.py | 1 | 6932 | ## Exploring Glottolog with Python
## from: http://nbviewer.ipython.org/gist/xflr6/9050337/glottolog.ipynb
## via: Robert Forkel <robert_forkel@eva.mpg.de>
import urllib
## Download the RDF export file with Pythons built-in urllib module (docs).
URL = 'http://glottolog.org/static/download/glottolog-language.n3.gz'
fil... | mit |
avmarchenko/exa | exa/core/numerical.py | 2 | 15937 | # -*- coding: utf-8 -*-
# Copyright (c) 2015-2018, Exa Analytics Development Team
# Distributed under the terms of the Apache License 2.0
"""
Data Objects
###################################
Data objects are used to store typed data coming from an external source (for
example a file on disk). There are three primary da... | apache-2.0 |
liam2/liam2 | liam2/charts.py | 1 | 11591 | # encoding: utf-8
from __future__ import absolute_import, division, print_function
import os
import math
import sys
import numpy as np
import larray as la
from liam2.compat import basestring, PY2
from liam2 import config
from liam2.expr import FunctionExpr
from liam2.utils import aslabeledarray, ExceptionOnGetAttr, ... | gpl-3.0 |
dssg/givinggraph | givinggraph/companycause/company_cause_svm.py | 3 | 2950 | #!/usr/bin/env python
#
# Description: This runs a support vector machine (SVM) on the
# labelled dataset (company summary, donation cause).
#
import pickle
import string
import re
import numpy as np
from nltk.corpus import stopwords
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn import cros... | mit |
johnboyington/homework | me777/hw5/hw5_p5.py | 1 | 1579 | import numpy as np
from numpy.random import rand
import matplotlib.pyplot as plt
def q(x):
return 3
def walk_on_lines(r, n, bounds, bound_temp, tol):
s = 0
for z in range(n):
x = r
qs = 0
found = False
while not found:
L, R = abs(bounds[0] - x), abs(bounds[1] ... | gpl-3.0 |
prheenan/Research | Personal/EventDetection/Docs/paper/Figures/FigureRupture/main_figure_rupture.py | 1 | 7687 | # force floating point division. Can still use integer with //
from __future__ import division
# This file is used for importing the common utilities classes.
import numpy as np
import matplotlib.pyplot as plt
import sys
sys.path.append("../../../../../../../")
from GeneralUtil.python import PlotUtilities
from Researc... | gpl-3.0 |
bavardage/statsmodels | statsmodels/sandbox/nonparametric/dgp_examples.py | 37 | 6008 | # -*- coding: utf-8 -*-
"""Examples of non-linear functions for non-parametric regression
Created on Sat Jan 05 20:21:22 2013
Author: Josef Perktold
"""
import numpy as np
## Functions
def fg1(x):
'''Fan and Gijbels example function 1
'''
return x + 2 * np.exp(-16 * x**2)
def fg1eu(x):
'''Eubank ... | bsd-3-clause |
thomasgibson/tabula-rasa | HDG_CG_comp/table_cg_hdg_breakdown.py | 1 | 5273 | import os
import pandas as pd
hdg_params = [(64, 1), (64, 2), (64, 3)]
hdg_data = ["results/HDG_data_N%d_deg%d.csv" % param
for param in hdg_params]
cg_params = [(64, 2), (64, 3), (64, 4)]
cg_data = ["results/CG_data_N%d_deg%d.csv" % param
for param in cg_params]
for d in hdg_data + cg_data:
... | mit |
guillochon/FriendlyFit | mosfit/plotting.py | 5 | 4917 | """Functions for assisting with plotting, inherited from AstroCats."""
from collections import OrderedDict
from random import seed, shuffle
import seaborn as sns
from matplotlib.colors import rgb2hex
from palettable import colorbrewer, cubehelix, wesanderson
__all__ = [
'bandrepf', 'bandcolorf', 'radiocolorf', '... | mit |
Adai0808/scikit-learn | sklearn/linear_model/tests/test_sgd.py | 129 | 43401 | 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 |
mlperf/training_results_v0.5 | v0.5.0/google/cloud_v2.512/resnet-tpuv2-512/code/resnet/model/models/official/boosted_trees/data_download.py | 4 | 3383 | # Copyright 2018 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 |
imaculate/scikit-learn | sklearn/linear_model/ransac.py | 17 | 17164 | # coding: utf-8
# Author: Johannes Schönberger
#
# License: BSD 3 clause
import numpy as np
import warnings
from ..base import BaseEstimator, MetaEstimatorMixin, RegressorMixin, clone
from ..utils import check_random_state, check_array, check_consistent_length
from ..utils.random import sample_without_replacement
fr... | bsd-3-clause |
caseyclements/bokeh | bokeh/charts/builder/tests/test_heatmap_builder.py | 33 | 4145 | """ This is the Bokeh charts testing interface.
"""
#-----------------------------------------------------------------------------
# Copyright (c) 2012 - 2014, Continuum Analytics, Inc. All rights reserved.
#
# Powered by the Bokeh Development Team.
#
# The full license is in the file LICENSE.txt, distributed with thi... | bsd-3-clause |
droundy/deft | papers/polyhedra/figs/plot-pressure.py | 1 | 1724 | #!/usr/bin/python2
from __future__ import division
import matplotlib, sys, os, argparse
import common
parser = argparse.ArgumentParser(description='Plot pressure of polyhedra.')
parser.add_argument('ff', metavar='ff', type=float, help='filling fraction')
parser.add_argument('-N', metavar='N', type=int, default=0,
... | gpl-2.0 |
dpinney/omf | omf/scratch/Neural_Net_Experimentation/deleted models/forecastStorageDeferral.py | 1 | 8680 | ''' Apply PNNL VirtualBatteries (VBAT) load model to day ahead forecast.'''
import pandas as pd
import numpy as np
from sklearn import linear_model
import pulp
from os.path import isdir, join as pJoin
import __neoMetaModel__
from __neoMetaModel__ import *
from omf import forecast as fc
# Model metadata:
modelName, tem... | gpl-2.0 |
RPGOne/Skynet | scikit-learn-c604ac39ad0e5b066d964df3e8f31ba7ebda1e0e/examples/manifold/plot_swissroll.py | 330 | 1446 | """
===================================
Swiss Roll reduction with LLE
===================================
An illustration of Swiss Roll reduction
with locally linear embedding
"""
# Author: Fabian Pedregosa -- <fabian.pedregosa@inria.fr>
# License: BSD 3 clause (C) INRIA 2011
print(__doc__)
import matplotlib.pyplot... | bsd-3-clause |
bsipocz/scikit-image | skimage/viewer/qt.py | 48 | 1281 | _qt_version = None
has_qt = True
try:
from matplotlib.backends.qt_compat import QtGui, QtCore, QtWidgets, QT_RC_MAJOR_VERSION as _qt_version
except ImportError:
try:
from matplotlib.backends.qt4_compat import QtGui, QtCore
QtWidgets = QtGui
_qt_version = 4
except ImportError:
... | bsd-3-clause |
Sentient07/scikit-learn | examples/decomposition/plot_pca_3d.py | 354 | 2432 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
Principal components analysis (PCA)
=========================================================
These figures aid in illustrating how a point cloud
can be very flat in one direction--which is where PCA
comes in to ch... | bsd-3-clause |
thegooglecodearchive/mpmath | mpmath/visualization.py | 6 | 9486 | """
Plotting (requires matplotlib)
"""
from colorsys import hsv_to_rgb, hls_to_rgb
from .libmp import NoConvergence
from .libmp.backend import xrange
class VisualizationMethods(object):
plot_ignore = (ValueError, ArithmeticError, ZeroDivisionError, NoConvergence)
def plot(ctx, f, xlim=[-5,5], ylim=Non... | bsd-3-clause |
rodekruis/priorityindex | learn_v1p0.py | 1 | 29671 | # Script developed by Marco Velliscig (marco.velliscig AT gmail.com)
# for the NL Red Cross
# released under GNU GENERAL PUBLIC LICENSE Version 3 for the NL Red Cross
# This script is for illustrative reasons only.
# If you are interested in using the script please contact the 510.global team
#
# notes of this vers... | lgpl-3.0 |
Bleyddyn/malpi | exp/check_state.py | 1 | 1373 | import numpy as np
import pickle
import os
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
from scipy import stats
with open('one_experience.pickle', 'rb') as pf:
exp = pickle.load(pf)
states, actions, rewards, batch_done, new_states = exp
print states.shape
print actions
print rewards
print bat... | mit |
kjung/scikit-learn | sklearn/linear_model/tests/test_bayes.py | 299 | 1770 | # Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Fabian Pedregosa <fabian.pedregosa@inria.fr>
#
# License: BSD 3 clause
import numpy as np
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import SkipTest
from sklearn.linear_model.bayes import BayesianRidge, ARDRegres... | bsd-3-clause |
drewm1980/multi_view_stereo_benchmark | benchmark.py | 1 | 5019 | #!/usr/bin/env python3
# Code for running the benchmark
import pathlib
from pathlib import Path
import numpy
import datetime
import pandas
from multi_view_stereo_benchmark.compare_clouds import compare_clouds
from multi_view_stereo_benchmark.load_ply import load_ply
def to_datetime(scanID):
''' Convert my strin... | mit |
shenzebang/scikit-learn | examples/text/document_clustering.py | 230 | 8356 | """
=======================================
Clustering text documents using k-means
=======================================
This is an example showing how the scikit-learn can be used to cluster
documents by topics using a bag-of-words approach. This example uses
a scipy.sparse matrix to store the features instead of ... | bsd-3-clause |
hazelnusse/robot.bicycle | plots/plot_data.py | 1 | 7624 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""Class used for plotting data of a Message_np object.
Examples
========
p = PlotData('sample_pb2', 'Sample', 'samples.dat')
p.print_fields()
p.plot('system_time', 'mpu6050', norm=True)
p.plot('system_time', 'mpu6050.accelerometer_x')
p.plot(... | bsd-2-clause |
cancan101/tensorflow | tensorflow/contrib/learn/python/learn/dataframe/dataframe.py | 85 | 4704 | # 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 |
blancha/abcngspipelines | utils/ensemblbedgraphtoucscbedgraph_batch_stranded.py | 1 | 4683 | #!/usr/bin/env python3
# Version 1.1
# Author Alexis Blanchet-Cohen
# Date: ../2014
import argparse
import glob
import os
import pandas
import subprocess
import util
parser = argparse.ArgumentParser(description='Generate scripts to convert bedgraph files from Ensembl to UCSC format.')
parser.add_argument("-s", "--sc... | gpl-3.0 |
muneebalam/scrapenhl2 | scrapenhl2/scrape/parse_toi.py | 1 | 24833 | """
This module contains methods for parsing TOI.
"""
import os.path
import re
import pandas as pd
import scrapenhl2.scrape.general_helpers as helpers
import scrapenhl2.scrape.organization as organization
import scrapenhl2.scrape.players as players
import scrapenhl2.scrape.schedules as schedules
import scrapenhl2.sc... | mit |
tyarkoni/pliers | pliers/tests/test_stims.py | 1 | 12234 | import tempfile
import os
import base64
from os.path import join, exists
from pathlib import Path
import numpy as np
import pandas as pd
import pytest
from .utils import get_test_data_path
from pliers.stimuli import (VideoStim, VideoFrameStim, ComplexTextStim,
AudioStim, ImageStim, Compoun... | bsd-3-clause |
sjdv1982/seamless | tests/highlevel/highlink-cpp.py | 1 | 1715 | from seamless.highlevel import Context, Cell, Transformer
ctx = Context()
def calc_arr(period, npoints):
import numpy as np
points = np.arange(npoints)
phase = points/period*np.pi*2
return np.sin(phase)
ctx.period = 200
ctx.npoints = 1100
ctx.calc_arr = calc_arr
ctx.calc_arr.period = ctx.period
ctx.ca... | mit |
sumspr/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 |
voxlol/scikit-learn | sklearn/decomposition/tests/test_pca.py | 199 | 10949 | import numpy as np
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_greater
from sklearn.utils.testing import assert_rai... | bsd-3-clause |
macks22/scikit-learn | examples/ensemble/plot_voting_probas.py | 316 | 2824 | """
===========================================================
Plot class probabilities calculated by the VotingClassifier
===========================================================
Plot the class probabilities of the first sample in a toy dataset
predicted by three different classifiers and averaged by the
`VotingC... | bsd-3-clause |
OshynSong/scikit-learn | sklearn/neural_network/rbm.py | 206 | 12292 | """Restricted Boltzmann Machine
"""
# Authors: Yann N. Dauphin <dauphiya@iro.umontreal.ca>
# Vlad Niculae
# Gabriel Synnaeve
# Lars Buitinck
# License: BSD 3 clause
import time
import numpy as np
import scipy.sparse as sp
from ..base import BaseEstimator
from ..base import TransformerMixi... | bsd-3-clause |
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