repo_name stringlengths 7 92 | path stringlengths 5 149 | copies stringlengths 1 3 | size stringlengths 4 6 | content stringlengths 911 693k | license stringclasses 15
values |
|---|---|---|---|---|---|
Minhua722/NMF | egs/ar/local/ar_extract_nmf_feats.py | 1 | 3850 | #!/usr/bin/env python
import cv2
import numpy as np
import argparse
import math
import pickle
from sklearn.decomposition import PCA
from nmf_support import *
import sys, os
if __name__ == '__main__':
#------------------------------------------------------
# Args parser
#--------------------------------------... | apache-2.0 |
qPCR4vir/orange | Orange/projection/mds.py | 6 | 14713 | """
.. index:: multidimensional scaling (mds)
.. index::
single: projection; multidimensional scaling (mds)
**********************************
Multidimensional scaling (``mds``)
**********************************
The functionality to perform multidimensional scaling
(http://en.wikipedia.org/wiki/Multidimensional_... | gpl-3.0 |
maryklayne/Funcao | examples/intermediate/mplot3d.py | 14 | 1261 | #!/usr/bin/env python
"""Matplotlib 3D plotting example
Demonstrates plotting with matplotlib.
"""
import sys
from sample import sample
from sympy import sin, Symbol
from sympy.external import import_module
def mplot3d(f, var1, var2, show=True):
"""
Plot a 3d function using matplotlib/Tk.
"""
im... | bsd-3-clause |
rkmaddox/mne-python | examples/visualization/topo_compare_conditions.py | 20 | 1828 | """
=================================================
Compare evoked responses for different conditions
=================================================
In this example, an Epochs object for visual and auditory responses is created.
Both conditions are then accessed by their respective names to create a sensor
layout... | bsd-3-clause |
esatel/ADCPy | doc/source/conf.py | 1 | 8929 | # -*- coding: utf-8 -*-
#
# ADCpy documentation build configuration file, created by
# sphinx-quickstart on Tue Oct 07 11:54:34 2014.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# All... | mit |
vdt/SimpleCV | SimpleCV/examples/util/ColorCube.py | 13 | 1901 | from SimpleCV import Image, Camera, Display, Color
import pygame as pg
import numpy as np
from pylab import *
from mpl_toolkits.mplot3d import axes3d
from matplotlib.backends.backend_agg import FigureCanvasAgg
import cv2
bins = 8
#precompute
idxs = []
colors = []
offset = bins/2
skip = 255/bins
for x in range(0,bins):... | bsd-3-clause |
lancezlin/ml_template_py | lib/python2.7/site-packages/mpl_toolkits/mplot3d/axis3d.py | 7 | 17489 | #!/usr/bin/python
# axis3d.py, original mplot3d version by John Porter
# Created: 23 Sep 2005
# Parts rewritten by Reinier Heeres <reinier@heeres.eu>
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from matplotlib.externals import six
import math
import co... | mit |
scottpurdy/NAB | tests/integration/corpus_test.py | 10 | 4895 | # ----------------------------------------------------------------------
# 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 |
NSLS-II-SRX/ipython_ophyd | profile_xf05id1-noX11/startup/85-bs_callbacks.py | 1 | 3670 | # -*- coding: utf-8 -*-
"""
Created on Wed Feb 24 12:30:06 2016
@author: xf05id1
"""
from bluesky.callbacks import CallbackBase,LivePlot
#import os
#import time as ttime
#from databroker import DataBroker as db, get_events
#from databroker.databroker import fill_event
import filestore.api as fsapi
#from metadatasto... | bsd-2-clause |
leon-adams/datascience | algorithms/hobfield.py | 1 | 5247 | #
# Leon Adams
#
# Python Module for running a hopfield network to relocate the memory from a perturbed image.
# The raw data set is represented in png image format. This code takes the three color channels (rgb)
# Converts to a single channel gray scaled image and then transforms the output to a [-1,1] vector
# for u... | mpl-2.0 |
lxsmnv/spark | examples/src/main/python/sql/arrow.py | 13 | 3997 | #
# 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 |
dancingdan/tensorflow | tensorflow/examples/tutorials/input_fn/boston.py | 76 | 2920 | # 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 appl... | apache-2.0 |
karvenka/sp17-i524 | project/S17-IR-P014/code/delay.py | 15 | 5276 | import sys
import csv
import sip
#import org.apache.log4j.{Level, Logger}
import matplotlib
#matplotlib.user('agg')
import matplotlib.pyplot as plt
plt.switch_backend('agg')
from matplotlib import rcParams
rcParams.update({'figure.autolayout': True})
from pyspark import SparkContext, SparkConf
from datetime import date... | apache-2.0 |
Carnon/nlp | TextClassify/textclassify/textdata.py | 1 | 2565 | import os
import codecs
import re
import jieba
import numpy as np
from tqdm import tqdm
from tensorflow.contrib import learn
from sklearn.preprocessing import OneHotEncoder
from sklearn.preprocessing import LabelEncoder
class TextData(object):
def __init__(self,args):
self.args = args
corpus_dir =... | apache-2.0 |
yarikoptic/NiPy-OLD | examples/neurospin/demo_dmtx.py | 1 | 2005 | """ test code to make a design matrix
"""
import numpy as np
from nipy.neurospin.utils.design_matrix import dmtx_light
tr = 1.0
frametimes = np.linspace(0,127*tr,128)
conditions = [0,0,0,1,1,1,3,3,3]
onsets=[30,70,100,10,30,90,30,40,60]
hrf_model = 'Canonical'
motion = np.cumsum(np.random.randn(128,6),0)
add_reg_name... | bsd-3-clause |
sarathid/Learning | Intro_to_ML/pca/eigenfaces.py | 9 | 4989 | """
===================================================
Faces recognition example using eigenfaces and SVMs
===================================================
The dataset used in this example is a preprocessed excerpt of the
"Labeled Faces in the Wild", aka LFW_:
http://vis-www.cs.umass.edu/lfw/lfw-funneled.tgz (2... | gpl-3.0 |
lancezlin/ml_template_py | lib/python2.7/site-packages/pandas/tools/tests/test_util.py | 7 | 16721 | import os
import locale
import codecs
import nose
import numpy as np
from numpy import iinfo
import pandas as pd
from pandas import (date_range, Index, _np_version_under1p9)
import pandas.util.testing as tm
from pandas.tools.util import cartesian_product, to_numeric
CURRENT_LOCALE = locale.getlocale()
LOCALE_OVERRID... | mit |
rboyes/KerasScripts | CSVTrainer.py | 1 | 5321 | import os
import datetime
import sys
import time
import string
import random
import pandas as pd
import numpy as np
import gc
if(len(sys.argv) < 2):
print('Usage: CSVTrainer.py train.csv validation.csv model.h5 log.txt')
sys.exit(1)
trainingName = sys.argv[1]
validationName = sys.argv[2]
modelName = sys.... | apache-2.0 |
DonBeo/statsmodels | statsmodels/graphics/tests/test_gofplots.py | 27 | 6814 | import numpy as np
from numpy.testing import dec
import statsmodels.api as sm
from statsmodels.graphics.gofplots import qqplot, qqline, ProbPlot
from scipy import stats
try:
import matplotlib.pyplot as plt
import matplotlib
have_matplotlib = True
except ImportError:
have_matplotlib = False
class Ba... | bsd-3-clause |
jolove/monmale | machineLearningLibrary.py | 1 | 14267 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from sklearn.cross_validation import train_test_split
from sklearn import linear_model
from sklearn import mixture
from sklearn import metrics
import logging
import sys, traceback, os
import uuid
import psutil
import getpass
import usefulLibraryFiles # Libreria pr... | apache-2.0 |
jimsrc/seatos | mixed/figs/sheaths.paper/src/together4.py | 1 | 11024 | #!/usr/bin/env ipython
from pylab import *
import numpy as np
import console_colors as ccl
from scipy.io.netcdf import netcdf_file
import os, sys
import matplotlib.patches as patches
import matplotlib.transforms as transforms
from numpy import array
from matplotlib.gridspec import GridSpec
import matplotlib.pyplot as p... | mit |
CleverChuk/ices | Python/multijob_module.py | 1 | 3479 | """
Author: Chukwubuikem Ume-Ugwa
Email: chubiyke@gmail.com
MIT License
Copyright (c) 2017 CleverChuk
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limit... | mit |
ZenDevelopmentSystems/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 |
TheGhostHuCodes/spy_dir | spy_dir.py | 1 | 2182 | #!/usr/bin/env python
import os
import os.path as pt
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
import argparse
#TODO: take decimal places as parameter for printing.
def sizeof_pp(num):
for unit in ['B', 'KiB', 'MiB', 'GiB', 'TiB', 'PiB', 'EiB', 'ZiB']:
if abs(num) < 1024.... | apache-2.0 |
deepesch/scikit-learn | sklearn/datasets/lfw.py | 141 | 19372 | """Loader for the Labeled Faces in the Wild (LFW) dataset
This dataset is a collection of JPEG pictures of famous people collected
over the internet, all details are available on the official website:
http://vis-www.cs.umass.edu/lfw/
Each picture is centered on a single face. The typical task is called
Face Veri... | bsd-3-clause |
HolgerPeters/scikit-learn | sklearn/ensemble/gradient_boosting.py | 5 | 73159 | """Gradient Boosted Regression Trees
This module contains methods for fitting gradient boosted regression trees for
both classification and regression.
The module structure is the following:
- The ``BaseGradientBoosting`` base class implements a common ``fit`` method
for all the estimators in the module. Regressio... | bsd-3-clause |
0x0all/scikit-learn | examples/covariance/plot_covariance_estimation.py | 250 | 5070 | """
=======================================================================
Shrinkage covariance estimation: LedoitWolf vs OAS and max-likelihood
=======================================================================
When working with covariance estimation, the usual approach is to use
a maximum likelihood estimator,... | bsd-3-clause |
abimannans/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 |
dcastro9/patternrec_ps2 | code/alcohol_script.py | 1 | 5623 | from Dataset import Dataset
from WTA_Hasher import WTAHasher
from kNN_Classifier import kNNClassifier
import numpy as np
import matplotlib.pyplot as plt
import copy
ds_train_dir = "../datasets/alcohol/alcoholism_training.csv"
ds_test_dir = "../datasets/alcohol/alcoholism_test.csv"
results_dir = "../final_results/alcoh... | mit |
dhruv13J/scikit-learn | sklearn/tests/test_naive_bayes.py | 142 | 17496 | import pickle
from io import BytesIO
import numpy as np
import scipy.sparse
from sklearn.datasets import load_digits, load_iris
from sklearn.cross_validation import cross_val_score, train_test_split
from sklearn.externals.six.moves import zip
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.te... | bsd-3-clause |
hagabbar/pycbc_copy | examples/distributions/spin_spatial_distr_example.py | 14 | 1973 | import numpy
import matplotlib.pyplot as plt
import pycbc.coordinates as co
from mpl_toolkits.mplot3d import Axes3D
from pycbc import distributions
# We can choose any bounds between 0 and pi for this distribution but in units
# of pi so we use between 0 and 1.
theta_low = 0.
theta_high = 1.
# Units of pi for the bou... | gpl-3.0 |
zaxliu/deepnap | experiments/kdd-exps/experiment_DynaQNN_130_Feb10_2317.py | 1 | 5180 | # System built-in modules
import time
from datetime import datetime
import sys
import os
from multiprocessing import Pool
# Project dependency modules
import pandas as pd
pd.set_option('mode.chained_assignment', None) # block warnings due to DataFrame value assignment
import lasagne
# Project modules
sys.path.append('... | bsd-3-clause |
kedz/sumpy | sumpy/io.py | 1 | 4037 | import os
import re
import pandas as pd
def load_duc_docset(input_source):
docs = DucSgmlReader().read(input_source)
return docs
def load_duc_abstractive_summaries(input_source):
models = DucAbstractSgmlReader().read(input_source)
return models
class FileInput(object):
def gather_paths(self, sou... | apache-2.0 |
zzcclp/spark | python/pyspark/pandas/tests/test_groupby.py | 14 | 118068 | #
# 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 |
AndrewBMartin/pygurobi | pygurobi/pygurobi.py | 1 | 31972 | """
Functions to support rapid interactive modification of Gurobi models.
For reference on Gurobi objects such as Models, Variables, and Constraints, see
http://www.gurobi.com/documentation/7.0/refman/py_python_api_overview.html.
"""
import csv
import json
try:
import gurobipy as gp
except ImportError:
raise ... | mit |
gtoonstra/airflow | airflow/hooks/base_hook.py | 14 | 3184 | # -*- coding: utf-8 -*-
#
# 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
#... | apache-2.0 |
bootphon/crossitlearn | simple_dnn.py | 1 | 32993 | """
A deep neural network with or w/o dropout in one file.
"""
import numpy
import theano
import sys
import math
from theano import tensor as T
from theano import shared
from theano.tensor.shared_randomstreams import RandomStreams
from collections import OrderedDict
BATCH_SIZE = 100
STACKSIZE = 69
def relu_f(vec):
... | mit |
parthea/pydatalab | datalab/data/_csv.py | 6 | 7063 | # Copyright 2016 Google Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except
# in compliance with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed ... | apache-2.0 |
vene/marseille | experiments/exp_rnn.py | 1 | 5162 | import os
import dill
import numpy as np
from sklearn.model_selection import KFold
from marseille.custom_logging import logging
from marseille.datasets import get_dataset_loader, load_embeds
from marseille.io import cache_fname
from marseille.argrnn import ArgumentLSTM
def argrnn_cv_score(dataset, dynet_weight_deca... | bsd-3-clause |
soft-matter/mr | mr/tests/test_feature_saving.py | 1 | 1721 | import unittest
import nose
from numpy.testing import assert_almost_equal, assert_allclose
from numpy.testing.decorators import slow
from pandas.util.testing import (assert_series_equal, assert_frame_equal)
import os
from tempfile import NamedTemporaryFile
import pandas as pd
from pandas import DataFrame, Series
imp... | gpl-3.0 |
eyadsibai/rep | tests/test_pybrain.py | 3 | 3872 | # Copyright 2014-2015 Yandex LLC and contributors <https://yandex.com/>
#
# 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... | apache-2.0 |
ybalgir/Quantop | Lec7.py | 1 | 1822 | import numpy as np
import pandas as pd
from statsmodels import regression
import statsmodels.api as sm
import matplotlib.pyplot as plt
import math
import pandas_datareader.data as web
from datetime import datetime
def Starter_Lec7():
start = datetime(2014, 1, 1)
end = datetime(2015, 1, 1)
asset = web.Da... | gpl-3.0 |
studywolf/pydmps | pydmps/dmp_rhythmic.py | 1 | 5004 | """
Copyright (C) 2013 Travis DeWolf
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope t... | gpl-3.0 |
fracturica/shardlib | shardlib/comp_analysis/SIMCompAnalysis.py | 1 | 23592 | import dataProcessing as dp
import plotFuncs as pf
import numpy as np
from matplotlib.ticker import MultipleLocator, FormatStrFormatter
from mpl_toolkits.axes_grid1 import host_subplot
import mpl_toolkits.axisartist as AA
from matplotlib.path import Path
from mpl_toolkits.mplot3d import Axes3D
import matplotlib as mp... | mit |
slarosa/QGIS | python/plugins/sextante/algs/MeanAndStdDevPlot.py | 3 | 3304 | # -*- coding: utf-8 -*-
"""
***************************************************************************
MeanAndStdDevPlot.py
---------------------
Date : January 2013
Copyright : (C) 2013 by Victor Olaya
Email : volayaf at gmail dot com
********************... | gpl-2.0 |
mne-tools/mne-tools.github.io | 0.14/_downloads/plot_topo_compare_conditions.py | 3 | 2175 | """
=================================================
Compare evoked responses for different conditions
=================================================
In this example, an Epochs object for visual and
auditory responses is created. Both conditions
are then accessed by their respective names to
create a sensor layout... | bsd-3-clause |
rupakc/Kaggle-Compendium | Santas Stolen Sleigh/SantaUtil.py | 1 | 6924 | # -*- coding: utf-8 -*-
"""
Created on Wed Jan 13 23:21:29 2016
Defines a set of utility functions to be used for prediction
@author: Rupak Chakraborty
"""
import math
from trip import Trip
from gift import Gift
import random
import time
import pandas as pd
import operator
RADIUS_EARTH = 6773
NORTH_POLE_LAT = 90
NOR... | mit |
nesterione/scikit-learn | examples/cluster/plot_agglomerative_clustering.py | 343 | 2931 | """
Agglomerative clustering with and without structure
===================================================
This example shows the effect of imposing a connectivity graph to capture
local structure in the data. The graph is simply the graph of 20 nearest
neighbors.
Two consequences of imposing a connectivity can be s... | bsd-3-clause |
shuangshuangwang/spark | python/pyspark/sql/tests/test_pandas_udf.py | 1 | 10216 | #
# 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 |
kkouer/PcGcs | Lib/site-packages/numpy/core/code_generators/ufunc_docstrings.py | 57 | 85797 | # Docstrings for generated ufuncs
docdict = {}
def get(name):
return docdict.get(name)
def add_newdoc(place, name, doc):
docdict['.'.join((place, name))] = doc
add_newdoc('numpy.core.umath', 'absolute',
"""
Calculate the absolute value element-wise.
Parameters
----------
x : array_like... | gpl-3.0 |
bdestombe/flopy-1 | flopy/utils/mflistfile.py | 1 | 25207 | """
This is a set of classes for reading budget information out of MODFLOW-style
listing files. Cumulative and incremental budgets are returned as numpy
recarrays, which can then be easily plotted.
"""
import collections
import os
import re
import sys
from datetime import timedelta
import numpy as np
from ..utils.u... | bsd-3-clause |
vermouthmjl/scikit-learn | examples/gaussian_process/plot_gpr_co2.py | 131 | 5705 | """
========================================================
Gaussian process regression (GPR) on Mauna Loa CO2 data.
========================================================
This example is based on Section 5.4.3 of "Gaussian Processes for Machine
Learning" [RW2006]. It illustrates an example of complex kernel engine... | bsd-3-clause |
preprocessed-connectomes-project/quality-assessment-protocol | scripts/qap_check_output_csv.py | 1 | 1302 | #!/usr/bin/env python
def main():
import os
import argparse
from qap.script_utils import check_csv_missing_subs, csv_to_pandas_df, \
write_inputs_dict_to_yaml_file, read_yml_file
from qap.qap_utils import raise_smart_exception
parser = argparse.ArgumentParser()
parser.add_argument("o... | bsd-3-clause |
Ttl/scikit-rf | skrf/io/general.py | 3 | 22567 |
'''
.. module:: skrf.io.general
========================================
general (:mod:`skrf.io.general`)
========================================
General io functions for reading and writing skrf objects
.. autosummary::
:toctree: generated/
read
read_all
read_all_networks
write
write_all
... | bsd-3-clause |
a113n/bcbio-nextgen | bcbio/rnaseq/sailfish.py | 4 | 8177 | import os
from collections import namedtuple
import pandas as pd
from bcbio import utils
import bcbio.pipeline.datadict as dd
import bcbio.rnaseq.gtf as gtf
from bcbio.distributed.transaction import file_transaction
from bcbio.provenance import do
from bcbio.utils import (file_exists, safe_makedir, is_gzipped,
... | mit |
daleloogn/all-in-one | evaluation.py | 2 | 2290 | import argparse
import numpy as np
from sklearn.metrics import precision_score, recall_score, f1_score
_ALL_ = ["random", "decision_trees", "linear_svm", "gaussian_naive_bayes"]
def precision_recall_f1score(GT, Y_pred):
precisions, recalls, f1scores = [], [], []
for i in range(GT.shape[0]):
precisions.append(prec... | gpl-2.0 |
arahuja/scikit-learn | examples/calibration/plot_calibration_multiclass.py | 272 | 6972 | """
==================================================
Probability Calibration for 3-class classification
==================================================
This example illustrates how sigmoid calibration changes predicted
probabilities for a 3-class classification problem. Illustrated is the
standard 2-simplex, wher... | bsd-3-clause |
vshtanko/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 |
xzh86/scikit-learn | examples/ensemble/plot_bias_variance.py | 357 | 7324 | """
============================================================
Single estimator versus bagging: bias-variance decomposition
============================================================
This example illustrates and compares the bias-variance decomposition of the
expected mean squared error of a single estimator again... | bsd-3-clause |
google-research/google-research | learn_to_infer/run_ring.py | 1 | 10211 | # coding=utf-8
# Copyright 2021 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... | apache-2.0 |
kelseyoo14/Wander | venv_2_7/lib/python2.7/site-packages/numpy/lib/twodim_base.py | 83 | 26903 | """ Basic functions for manipulating 2d arrays
"""
from __future__ import division, absolute_import, print_function
from numpy.core.numeric import (
asanyarray, arange, zeros, greater_equal, multiply, ones, asarray,
where, int8, int16, int32, int64, empty, promote_types, diagonal,
)
from numpy.core import... | artistic-2.0 |
edonyM/emthesis | code/3point2plane.py | 1 | 3545 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
r"""
# .---. .-----------
# / \ __ / ------
# / / \( )/ ----- (`-') _ _(`-') <-. (`-')_
# ////// '\/ ` --- ( OO).-/( (OO ).-> .-> \( OO) ) .->
# //// / // : : --- (,------... | mit |
lgeiger/ide-python | lib/debugger/VendorLib/vs-py-debugger/pythonFiles/experimental/ptvsd/ptvsd/_vendored/pydevd/pydev_ipython/matplotlibtools.py | 8 | 5428 |
import sys
backends = {'tk': 'TkAgg',
'gtk': 'GTKAgg',
'wx': 'WXAgg',
'qt': 'Qt4Agg', # qt3 not supported
'qt4': 'Qt4Agg',
'qt5': 'Qt5Agg',
'osx': 'MacOSX'}
# We also need a reverse backends2guis mapping that will properly choose which
# GUI sup... | mit |
zorojean/scikit-learn | sklearn/ensemble/tests/test_gradient_boosting_loss_functions.py | 221 | 5517 | """
Testing for the gradient boosting loss functions and initial estimators.
"""
import numpy as np
from numpy.testing import assert_array_equal
from numpy.testing import assert_almost_equal
from numpy.testing import assert_equal
from nose.tools import assert_raises
from sklearn.utils import check_random_state
from ... | bsd-3-clause |
HyperloopTeam/FullOpenMDAO | lib/python2.7/site-packages/mpl_toolkits/axisartist/grid_helper_curvelinear.py | 18 | 26105 | """
An experimental support for curvilinear grid.
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from six.moves import zip
from itertools import chain
from .grid_finder import GridFinder
from .axislines import AxisArtistHelper, GridHelperB... | gpl-2.0 |
michaelhuang/QuantSoftwareToolkit | Examples/Basic/tutorial3.py | 4 | 3612 | '''
(c) 2011, 2012 Georgia Tech Research Corporation
This source code is released under the New BSD license. Please see
http://wiki.quantsoftware.org/index.php?title=QSTK_License
for license details.
Created on January, 24, 2013
@author: Sourabh Bajaj
@contact: sourabhbajaj@gatech.edu
@summary: Example tut... | bsd-3-clause |
maxlikely/scikit-learn | sklearn/manifold/tests/test_spectral_embedding.py | 6 | 8149 | import warnings
from nose.tools import assert_true
from nose.tools import assert_equal
from scipy.sparse import csr_matrix
from scipy.sparse import csc_matrix
import numpy as np
from numpy.testing import assert_array_almost_equal
from nose.tools import assert_raises
from nose.plugins.skip import SkipTest
from sklea... | bsd-3-clause |
LeSam/avoplot | src/avoplot/gui/analysis_tools.py | 3 | 4491 | #Copyright (C) Nial Peters 2013
#
#This file is part of AvoPlot.
#
#AvoPlot 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.
#
#AvoPlot is ... | gpl-3.0 |
stylianos-kampakis/scikit-learn | sklearn/mixture/gmm.py | 68 | 31091 | """
Gaussian Mixture Models.
This implementation corresponds to frequentist (non-Bayesian) formulation
of Gaussian Mixture Models.
"""
# Author: Ron Weiss <ronweiss@gmail.com>
# Fabian Pedregosa <fabian.pedregosa@inria.fr>
# Bertrand Thirion <bertrand.thirion@inria.fr>
import warnings
import numpy as... | bsd-3-clause |
davidgbe/scikit-learn | sklearn/ensemble/voting_classifier.py | 178 | 8006 | """
Soft Voting/Majority Rule classifier.
This module contains a Soft Voting/Majority Rule classifier for
classification estimators.
"""
# Authors: Sebastian Raschka <se.raschka@gmail.com>,
# Gilles Louppe <g.louppe@gmail.com>
#
# Licence: BSD 3 clause
import numpy as np
from ..base import BaseEstimator
f... | bsd-3-clause |
OTAkeys/RIOT | tests/pkg_utensor/generate_digit.py | 19 | 1149 | #!/usr/bin/env python3
"""Generate a binary file from a sample image of the MNIST dataset.
Pixel of the sample are stored as float32, images have size 28x28.
"""
import os
import argparse
import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf
SCRIPT_DIR = os.path.dirname(os.path.realpath(__fil... | lgpl-2.1 |
abyssxsy/gnuradio | gr-utils/python/utils/plot_fft_base.py | 53 | 10449 | #!/usr/bin/env python
#
# Copyright 2007,2008,2011 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 |
rfriesen/DR1_analysis | property_histograms.py | 2 | 7527 | from astropy.io import fits
import aplpy
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import astropy.units as u
import astropy.constants as c
import warnings
import numpy as np
from astropy.visualization import hist
from config import plottingDictionary
"""
Make histogram plots of NH3-derived prop... | mit |
bsipocz/statsmodels | statsmodels/graphics/plot_grids.py | 33 | 5711 | '''create scatterplot with confidence ellipsis
Author: Josef Perktold
License: BSD-3
TODO: update script to use sharex, sharey, and visible=False
see http://www.scipy.org/Cookbook/Matplotlib/Multiple_Subplots_with_One_Axis_Label
for sharex I need to have the ax of the last_row when editing the earlier
row... | bsd-3-clause |
jereze/scikit-learn | benchmarks/bench_rcv1_logreg_convergence.py | 149 | 7173 | # Authors: Tom Dupre la Tour <tom.dupre-la-tour@m4x.org>
# Olivier Grisel <olivier.grisel@ensta.org>
#
# License: BSD 3 clause
import matplotlib.pyplot as plt
import numpy as np
import gc
import time
from sklearn.externals.joblib import Memory
from sklearn.linear_model import (LogisticRegression, SGDClassifi... | bsd-3-clause |
nhmc/LAE | cloudy/find_par.py | 1 | 13374 | from __future__ import division
from math import log, sqrt, pi
from barak.utilities import adict
from barak.absorb import split_trans_name
from barak.io import parse_config, loadobj
from barak.interp import AkimaSpline, MapCoord_Interpolator
from cloudy.utils import read_observed
import numpy as np
import os
from glob... | mit |
cloudera/ibis | ibis/backends/pandas/tests/conftest.py | 1 | 1158 | from pathlib import Path
import pandas as pd
import ibis
import ibis.expr.operations as ops
from ibis.backends.tests.base import BackendTest, RoundHalfToEven
class TestConf(BackendTest, RoundHalfToEven):
check_names = False
additional_skipped_operations = frozenset({ops.StringSQLLike})
supported_to_time... | apache-2.0 |
seckcoder/lang-learn | python/sklearn/examples/covariance/plot_lw_vs_oas.py | 4 | 2864 | """
=============================
Ledoit-Wolf vs OAS estimation
=============================
The usual covariance maximum likelihood estimate can be regularized
using shrinkage. Ledoit and Wolf proposed a close formula to compute
the asymptotical optimal shrinkage parameter (minimizing a MSE
criterion), yielding the ... | unlicense |
jswanljung/iris | docs/iris/example_code/General/inset_plot.py | 7 | 2357 | """
Test Data Showing Inset Plots
=============================
This example demonstrates the use of a single 3D data cube with time, latitude
and longitude dimensions to plot a temperature series for a single latitude
coordinate, with an inset plot of the data region.
"""
import matplotlib.pyplot as plt
import nump... | lgpl-3.0 |
gviejo/ThalamusPhysio | python/main_make_MAPinfo.py | 1 | 14284 | #!/usr/bin/env python
'''
File name: main_make_movie.py
Author: Guillaume Viejo
Date created: 09/10/2017
Python Version: 3.5.2
To make shank mapping
'''
import numpy as np
import pandas as pd
# from matplotlib.pyplot import plot,show,draw
import scipy.io
from functions import *
from pylab import *
from skle... | gpl-3.0 |
piyush0609/scipy | scipy/spatial/tests/test__plotutils.py | 71 | 1463 | from __future__ import division, print_function, absolute_import
from numpy.testing import dec, assert_, assert_array_equal
try:
import matplotlib
matplotlib.rcParams['backend'] = 'Agg'
import matplotlib.pyplot as plt
has_matplotlib = True
except:
has_matplotlib = False
from scipy.spatial import ... | bsd-3-clause |
sgenoud/scikit-learn | sklearn/tests/test_base.py | 4 | 3825 |
# Author: Gael Varoquaux
# License: BSD
import numpy as np
import scipy.sparse as sp
from numpy.testing import assert_array_equal
from nose.tools import assert_true
from nose.tools import assert_false
from nose.tools import assert_equal
from nose.tools import assert_raises
from sklearn.base import BaseEstimator, clo... | bsd-3-clause |
PatrickOReilly/scikit-learn | sklearn/tests/test_metaestimators.py | 57 | 4958 | """Common tests for metaestimators"""
import functools
import numpy as np
from sklearn.base import BaseEstimator
from sklearn.externals.six import iterkeys
from sklearn.datasets import make_classification
from sklearn.utils.testing import assert_true, assert_false, assert_raises
from sklearn.pipeline import Pipeline... | bsd-3-clause |
AlexanderFabisch/scikit-learn | examples/missing_values.py | 71 | 3055 | """
======================================================
Imputing missing values before building an estimator
======================================================
This example shows that imputing the missing values can give better results
than discarding the samples containing any missing value.
Imputing does not ... | bsd-3-clause |
russel1237/scikit-learn | sklearn/utils/tests/test_sparsefuncs.py | 157 | 13799 | import numpy as np
import scipy.sparse as sp
from scipy import linalg
from numpy.testing import assert_array_almost_equal, assert_array_equal
from sklearn.datasets import make_classification
from sklearn.utils.sparsefuncs import (mean_variance_axis,
inplace_column_scale,
... | bsd-3-clause |
yongfuyang/vnpy | vn.how/tick2trade/vn.trader_t2t/ctaAlgo/tools/multiTimeFrame/strategyBreakOut.py | 22 | 11811 | # encoding: UTF-8
"""
This file tweaks ctaTemplate Module to suit multi-TimeFrame strategies.
"""
from ctaBase import *
from ctaTemplate import CtaTemplate
import numpy as np
########################################################################
class BreakOut(CtaTemplate):
"""
"infoArray" 字典是用来储存辅助品种信息的, ... | mit |
hchim/stockanalyzer | simulator/TradeSimulator.py | 1 | 4978 | import pandas as pd
import numpy as np
from utils.webdata import get_close_of_symbols
class TradeSimulator(object):
def __init__(self, start_val=1000000, leverage=2.0, allow_short=True):
"""
Parameters
----------
start_val: float
start value of the portfolio
l... | mit |
aflaxman/scikit-learn | sklearn/tests/test_learning_curve.py | 33 | 12840 | # Author: Alexander Fabisch <afabisch@informatik.uni-bremen.de>
#
# License: BSD 3 clause
import sys
from sklearn.externals.six.moves import cStringIO as StringIO
import numpy as np
import warnings
from sklearn.base import BaseEstimator
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing import ... | bsd-3-clause |
WillBrennan/DigitClassifier | DeepConv.py | 1 | 8479 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
__author__ = 'Will Brennan'
# Built-in Module
import os
import time
import logging
import warnings
import cPickle as pickle
from datetime import datetime
# Standard Modules
import numpy
import sklearn
import theano
import theano.tensor as T
# Custom Modules
import Scripts... | bsd-2-clause |
breeezzz/local-bitcoins-api | LocalBitcoins/market_depth.py | 1 | 6253 | '''
Created on 7 Jun 2013
@author: Jamie
'''
import urllib2
import math
import re
import itertools
import argparse
from bs4 import BeautifulSoup
import matplotlib.pyplot as plt
markets = {'UK': {'url': 'gb/united%20kingdom/', 'curr': 'GBP'},
'USA': {'url': 'us/united%20states/', 'curr': 'USD'},
... | mit |
planetarymike/IDL-Colorbars | IDL_py_test/027_Eos_B.py | 1 | 5942 | from matplotlib.colors import LinearSegmentedColormap
from numpy import nan, inf
cm_data = [[1., 1., 1.],
[1., 1., 1.],
[0.498039, 0.498039, 0.498039],
[0., 0., 0.513725],
[0., 0., 0.533333],
[0., 0., 0.54902],
[0., 0., 0.564706],
[0., 0., 0.580392],
[0., 0., 0.6],
[0., 0., 0.615686],
[0., 0., 0.568627],
[0., 0., 0.584... | gpl-2.0 |
williamleif/histwords | statutils/plothelper.py | 2 | 5401 | import matplotlib.pyplot as plt
import numpy as np
import scipy as sp
def trendline(xd, yd, order=1, c='r', alpha=1, plot_r=False, text_pos=None):
"""Make a line of best fit"""
#Calculate trendline
coeffs = np.polyfit(xd, yd, order)
intercept = coeffs[-1]
slope = coeffs[-2]
if order == 2: pow... | apache-2.0 |
c-PRIMED/puq | test/UniformPDF_test.py | 1 | 4485 | #! /usr/bin/env python
'''
Testsuite for the UniformPDF class
'''
from __future__ import absolute_import, division, print_function
import numpy as np
from puq import *
import scipy.stats as stats
def _hisplot(y, nbins):
n, bins = np.histogram(y, nbins, normed=True)
mids = bins[:-1] + np.diff(bins) / 2.0
... | mit |
aolindahl/streaking | process_hdf5.py | 1 | 46151 | # -*- coding: utf-8 -*-
"""
Created on Mon Jun 8 15:37:51 2015
@author: Anton O Lindahl
"""
import h5py
import argparse
import matplotlib.pyplot as plt
import numpy as np
import time
import os
import sys
import lmfit
import warnings
from aolPyModules import wiener, wavelet_filter
import time_to_energy_conversion as ... | gpl-2.0 |
TiKunze/CanMics | src/python/01_SingleChannel/3pop/EIN/HeHiVariation/RUM_Detektor_HeHi_2ndversion_cluster.py | 1 | 5917 | # -*- coding: utf-8 -*-
"""
Created on Mon Jun 22 17:15:03 2015
@author: Tim Kunze
Copyright (C) 2015, Tim Kunze. All rights reserved.
This script is a modified version of the RUM Detector:
instead of sweeping over He and Hi in every diagram, we sweep over lenge and intensity of the impulse (as in the actiation p... | gpl-3.0 |
GitYiheng/reinforcement_learning_test | test00_previous_files/mountaincar_q_learning.py | 1 | 4304 | import gym
import os
import sys
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from gym import wrappers
from datetime import datetime
from sklearn.pipeline import FeatureUnion
from sklearn.preprocessing import StandardScaler
from sklearn.kernel_approximation... | mit |
aemerick/galaxy_analysis | particle_analysis/sn_rate.py | 1 | 9054 | #import yt.mods as yt
import yt
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import glob
__all__ = ['future_snr', 'snr']
_core_collapse_labels = ["SNII", "II", "2", "SN_II", "TypeII", "Type 2",
"Type II", "type II", "typeII", 'core collapse']
_... | mit |
CallaJun/hackprince | indico/matplotlib/tests/test_style.py | 10 | 1977 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import os
import shutil
import tempfile
from contextlib import contextmanager
import matplotlib as mpl
from matplotlib import style
from matplotlib.style.core import USER_LIBRARY_PATHS, STYLE_EXTENSION
import... | lgpl-3.0 |
rhattersley/cartopy | lib/cartopy/tests/mpl/test_ticker.py | 3 | 8574 | # (C) British Crown Copyright 2014 - 2017, Met Office
#
# This file is part of cartopy.
#
# cartopy is free software: you can redistribute it and/or modify it under
# the terms of the GNU Lesser General Public License as published by the
# Free Software Foundation, either version 3 of the License, or
# (at your option)... | lgpl-3.0 |
gibiansky/tensorflow | tensorflow/contrib/learn/python/learn/preprocessing/tests/categorical_test.py | 30 | 2249 | # encoding: utf-8
# 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 r... | apache-2.0 |
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