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 |
|---|---|---|---|---|---|
dr-leo/pandaSDMX | pandasdmx/util.py | 1 | 9243 | import collections
import logging
import typing
from enum import Enum
from typing import TYPE_CHECKING, Any, List, Type, TypeVar, Union, no_type_check
import pydantic
from pydantic import DictError, Extra, ValidationError, validator # noqa: F401
from pydantic.class_validators import make_generic_validator
KT = TypeV... | apache-2.0 |
andim/scipydirect | doc/sphinxext/inheritance_diagram.py | 98 | 13648 | """
Defines a docutils directive for inserting inheritance diagrams.
Provide the directive with one or more classes or modules (separated
by whitespace). For modules, all of the classes in that module will
be used.
Example::
Given the following classes:
class A: pass
class B(A): pass
class C(A): pass
... | mit |
adykstra/mne-python | tutorials/discussions/plot_background_filtering.py | 1 | 49893 | # -*- coding: utf-8 -*-
r"""
.. _disc-filtering:
===================================
Background information on filtering
===================================
Here we give some background information on filtering in general,
and how it is done in MNE-Python in particular.
Recommended reading for practical applications ... | bsd-3-clause |
andrewcmyers/tensorflow | tensorflow/contrib/timeseries/examples/predict_test.py | 80 | 2487 | # Copyright 2017 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 |
shyamalschandra/scikit-learn | examples/semi_supervised/plot_label_propagation_versus_svm_iris.py | 286 | 2378 | """
=====================================================================
Decision boundary of label propagation versus SVM on the Iris dataset
=====================================================================
Comparison for decision boundary generated on iris dataset
between Label Propagation and SVM.
This demon... | bsd-3-clause |
YJango/tensorflow | Py_version/FNNs_Demo/demoLV3.py | 1 | 12562 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time : 2018/6/19 11:10
# @Author : zzy824
# @File : demoLV3.py
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
tf.set_random_seed(55)
np.random.seed(55)
""" add some branched based on demoLV2，X.npy and Y.npy are files including data fo... | gpl-3.0 |
anntzer/scikit-learn | sklearn/decomposition/_fastica.py | 7 | 21041 | """
Python implementation of the fast ICA algorithms.
Reference: Tables 8.3 and 8.4 page 196 in the book:
Independent Component Analysis, by Hyvarinen et al.
"""
# Authors: Pierre Lafaye de Micheaux, Stefan van der Walt, Gael Varoquaux,
# Bertrand Thirion, Alexandre Gramfort, Denis A. Engemann
# License: BS... | bsd-3-clause |
inpefess/kaggle_competitions | cats_vs_dogs/predict.py | 1 | 1193 | import argparse
import pandas as pd
from keras.models import load_model
from cats_vs_dogs.config import data_dir
from cats_vs_dogs.data_generators import DataGenerators
def save_predictions(
model_file: str,
submission_filename: str = "submission.csv"
):
batch_size = 20
model = load_model(mo... | mit |
IshankGulati/scikit-learn | sklearn/datasets/tests/test_svmlight_format.py | 53 | 13398 | from bz2 import BZ2File
import gzip
from io import BytesIO
import numpy as np
import scipy.sparse as sp
import os
import shutil
from tempfile import NamedTemporaryFile
from sklearn.externals.six import b
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.u... | bsd-3-clause |
Karel-van-de-Plassche/QLKNN-develop | qlknn/misc/random_access_benchmark.py | 1 | 3875 | import xarray as xr
from IPython import embed
import numpy as np
from itertools import product
import pandas as pd
#import dask.dataframe as df
import time
#import dask.array as da
import numpy as np
def cartesian(arrays, out=None):
"""
Generate a cartesian product of input arrays.
Parameters
--------... | mit |
bmcfee/ismir2017_chords | code/train_model.py | 1 | 19274 | #!/usr/bin/env python
'''Model construction and training script'''
import argparse
import os
import sys
from collections import defaultdict
from glob import glob
import six
import pickle
import numpy as np
import pandas as pd
import keras as K
from tqdm import tqdm
from sklearn.model_selection import ShuffleSplit
... | bsd-2-clause |
aliciawyy/CompInvest | portfolio_frontier.py | 1 | 4645 | """
This file will store the function which will determine
the efficient frontier
@author: Alicia Wang
@date: 4 Oct 2014
"""
# QSTK Imports
import QSTK.qstkutil.tsutil as tsu
# Third Party import
import datetime as dt
import numpy as np
import matplotlib.pyplot as plt
from load.load_ticker import load_valid_cac40_na... | mit |
thilbern/scikit-learn | examples/linear_model/plot_omp.py | 385 | 2263 | """
===========================
Orthogonal Matching Pursuit
===========================
Using orthogonal matching pursuit for recovering a sparse signal from a noisy
measurement encoded with a dictionary
"""
print(__doc__)
import matplotlib.pyplot as plt
import numpy as np
from sklearn.linear_model import OrthogonalM... | bsd-3-clause |
Anmol-Singh-Jaggi/Recommend | without-DB/python/uu.py | 1 | 3767 | import scipy as sp
import time
import pickle
import numpy as np
import os
import sys
import matplotlib.pyplot as plt
import math
from collections import defaultdict
f = open("/home/goel/rec/data/u1.base",'r')
user_train = {}
user_mean = {}
user_ratings = {}
simy = {}
n_all = {}
def init_user_train():
for line... | gpl-2.0 |
yyjiang/scikit-learn | sklearn/utils/arpack.py | 265 | 64837 | """
This contains a copy of the future version of
scipy.sparse.linalg.eigen.arpack.eigsh
It's an upgraded wrapper of the ARPACK library which
allows the use of shift-invert mode for symmetric matrices.
Find a few eigenvectors and eigenvalues of a matrix.
Uses ARPACK: http://www.caam.rice.edu/software/ARPACK/
"""
#... | bsd-3-clause |
akionakamura/scikit-learn | sklearn/datasets/tests/test_rcv1.py | 322 | 2414 | """Test the rcv1 loader.
Skipped if rcv1 is not already downloaded to data_home.
"""
import errno
import scipy.sparse as sp
import numpy as np
from sklearn.datasets import fetch_rcv1
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing i... | bsd-3-clause |
trashkalmar/omim | search/search_quality/scoring_model.py | 4 | 9667 | #!/usr/bin/env python3
from math import exp, log
from scipy.stats import pearsonr, t
from sklearn import svm
from sklearn.model_selection import GridSearchCV, KFold
from sklearn.utils import resample
import argparse
import collections
import itertools
import numpy as np
import pandas as pd
import random
import sys
M... | apache-2.0 |
vigilv/scikit-learn | examples/gaussian_process/plot_gp_regression.py | 253 | 4054 | #!/usr/bin/python
# -*- coding: utf-8 -*-
r"""
=========================================================
Gaussian Processes regression: basic introductory example
=========================================================
A simple one-dimensional regression exercise computed in two different ways:
1. A noise-free cas... | bsd-3-clause |
kenshay/ImageScript | ProgramData/SystemFiles/Python/Lib/site-packages/matplotlib/tight_bbox.py | 22 | 2601 | """
This module is to support *bbox_inches* option in savefig command.
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import warnings
from matplotlib.transforms import Bbox, TransformedBbox, Affine2D
def adjust_bbox(fig, bbox_inches, fixe... | gpl-3.0 |
atanna/benchpy | benchpy/magic.py | 1 | 5170 | # -*- coding: utf-8 -*-
from __future__ import absolute_import
from functools import partial
from matplotlib import pyplot as plt
def magic_benchpy(line='', cell=None):
"""
Run benchpy.run
%benchpy [[-i] [-g] [-n <N>] [-m <M>] [-p] [-r <R>] [-t <T>] -s<S>] statement
where statement is Bench or Grou... | mit |
jakdot/pyactr | tutorials/forbook/code/ch7_lexical_decision_pyactr_no_imaginal.py | 1 | 10801 | """
A model of lexical decision: Bayes+ACT-R, no imaginal buffer
"""
import warnings
import sys
import matplotlib as mpl
mpl.use("pgf")
pgf_with_pdflatex = {"text.usetex": True, "pgf.texsystem": "pdflatex",
"pgf.preamble": [r"\usepackage{mathpazo}",
r"\usepac... | gpl-3.0 |
rpbarnes/nmrglue | doc/_build/html/examples/el/interactive/2d_interactive/2d_interactive.py | 10 | 1209 | #! /usr/bin/env python
# Create contour plots of a 2D NMRPipe spectrum
import nmrglue as ng
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm
# plot parameters
cmap = matplotlib.cm.Blues_r # contour map (colors to use for contours)
contour_start = 30000 # contour level start value
conto... | bsd-3-clause |
lail3344/sms-tools | lectures/09-Sound-description/plots-code/mfcc.py | 25 | 1103 | import numpy as np
import matplotlib.pyplot as plt
import essentia.standard as ess
M = 1024
N = 1024
H = 512
fs = 44100
spectrum = ess.Spectrum(size=N)
window = ess.Windowing(size=M, type='hann')
mfcc = ess.MFCC(numberCoefficients = 12)
x = ess.MonoLoader(filename = '../../../sounds/speech-male.wav', sampleRate = fs)(... | agpl-3.0 |
liangz0707/scikit-learn | examples/plot_digits_pipe.py | 250 | 1809 | #!/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 |
aberdah/Stockvider | stockvider/stockviderApp/sourceDA/rawData/referenceRawDataDA.py | 1 | 13837 | # -*- coding: utf-8 -*-
'''
Todo :
- vérifier que quand on fait le réindex, les dates ajoutées à un DF ont
bien des values à NaN (sinon ça fausse le vote).
'''
import pandas as pd
import numpy as np
class ReferenceRawDataDA(object):
'''
Base class handling **raw data aggregation to reference dat... | mit |
DonBeo/scikit-learn | sklearn/tests/test_qda.py | 155 | 3481 | import numpy as np
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_greater
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing import ignore_war... | bsd-3-clause |
abimannans/scikit-learn | examples/ensemble/plot_gradient_boosting_quantile.py | 392 | 2114 | """
=====================================================
Prediction Intervals for Gradient Boosting Regression
=====================================================
This example shows how quantile regression can be used
to create prediction intervals.
"""
import numpy as np
import matplotlib.pyplot as plt
from skle... | bsd-3-clause |
eg-zhang/scikit-learn | sklearn/tree/export.py | 78 | 15814 | """
This module defines export functions for decision trees.
"""
# Authors: Gilles Louppe <g.louppe@gmail.com>
# Peter Prettenhofer <peter.prettenhofer@gmail.com>
# Brian Holt <bdholt1@gmail.com>
# Noel Dawe <noel@dawe.me>
# Satrajit Gosh <satrajit.ghosh@gmail.com>
# Trevor... | bsd-3-clause |
ChanChiChoi/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 |
gilt/incubator-airflow | airflow/contrib/operators/hive_to_dynamodb.py | 15 | 3701 | # -*- coding: utf-8 -*-
#
# 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, software
... | apache-2.0 |
h2oai/h2o-3 | h2o-hadoop-3/tests/python/pyunit_s3_import_export.py | 2 | 2041 | #! /usr/env/python
import sys, os
sys.path.insert(1, os.path.join("..","..",".."))
from tests import pyunit_utils
from datetime import datetime
import h2o
import uuid
from pandas.util.testing import assert_frame_equal
import boto3
def s3_import_export():
local_frame = h2o.import_file(path=pyunit_utils.locate("sma... | apache-2.0 |
choldgraf/download | examples/plot_download_providers.py | 1 | 1876 | """
Download from Dropbox, Google Drive, and Github
-----------------------------------------------
It's also possible to download files from Github, Google Drive, and Dropbox.
While you can go through a little extra effort to get a direct download link,
``download`` will try to make things a little bit easier for you... | mit |
tianrui/521dev | svhn/cnn_train.py | 1 | 8823 | # Copyright 2015 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... | gpl-3.0 |
kaichogami/scikit-learn | sklearn/__init__.py | 29 | 3071 | """
Machine learning module for Python
==================================
sklearn is a Python module integrating classical machine
learning algorithms in the tightly-knit world of scientific Python
packages (numpy, scipy, matplotlib).
It aims to provide simple and efficient solutions to learning problems
that are acc... | bsd-3-clause |
neuro-lyon/multiglom-model | src/plotting.py | 1 | 6438 | # -*- coding:utf-8 -*-
from matplotlib import pyplot as plt, cm as cmap
from numpy import where
from brian.stdunits import *
from brian.units import *
from matplotlib.mlab import psd
from pylab import detrend_mean
def raster_plot(spikes_i, spikes_t, connection_matrix):
"""Raster plot with focus on interconnecti... | mit |
pv/scikit-learn | examples/svm/plot_rbf_parameters.py | 57 | 8096 | '''
==================
RBF SVM parameters
==================
This example illustrates the effect of the parameters ``gamma`` and ``C`` of
the Radius Basis Function (RBF) kernel SVM.
Intuitively, the ``gamma`` parameter defines how far the influence of a single
training example reaches, with low values meaning 'far' a... | bsd-3-clause |
lifei96/Medium-crawler-with-data-analyzer | User_Crawler/medium_users_data_reader.py | 2 | 1748 | # -*- coding: utf-8 -*-
import pandas as pd
import json
import datetime
import os
def read_users():
users = list()
file_in = open('./username_list.txt', 'r')
username_list = str(file_in.read()).split(' ')
file_in.close()
num = 0
for username in username_list:
if not username:
... | mit |
mjirik/larVolumeToObj | larVolumeToObj/computation/old/step_calcchains_tobinary.py | 2 | 8706 | # -*- 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, sys
import traceback
#
import matplotlib.pyplot as plt
# ------------------------------------------------------------
# Logg... | mit |
kenshay/ImageScript | ProgramData/SystemFiles/Python/Lib/site-packages/dask/dataframe/io/demo.py | 4 | 8227 | from __future__ import absolute_import, division, print_function
import pandas as pd
import numpy as np
from ..core import tokenize, DataFrame
from .io import from_delayed
from ...delayed import delayed
from ...utils import random_state_data
__all__ = ['make_timeseries']
def make_float(n, rstate):
return rstat... | gpl-3.0 |
Jiangshangmin/mpld3 | examples/heart_path.py | 19 | 3958 | """
Patches and Paths
=================
This is a demo adapted from a `matplotlib gallery example
<http://matplotlib.org/examples/shapes_and_collections/path_patch_demo.html>`_
This example adds a custom D3 plugin allowing the user to drag the path
control-points and see the effect on the path.
Use the toolbar button... | bsd-3-clause |
thientu/scikit-learn | sklearn/__check_build/__init__.py | 345 | 1671 | """ Module to give helpful messages to the user that did not
compile the scikit properly.
"""
import os
INPLACE_MSG = """
It appears that you are importing a local scikit-learn source tree. For
this, you need to have an inplace install. Maybe you are in the source
directory and you need to try from another location.""... | bsd-3-clause |
MartinSavc/scikit-learn | sklearn/gaussian_process/gaussian_process.py | 83 | 34544 | # -*- coding: utf-8 -*-
# Author: Vincent Dubourg <vincent.dubourg@gmail.com>
# (mostly translation, see implementation details)
# Licence: BSD 3 clause
from __future__ import print_function
import numpy as np
from scipy import linalg, optimize
from ..base import BaseEstimator, RegressorMixin
from ..metrics... | bsd-3-clause |
waterponey/scikit-learn | sklearn/ensemble/tests/test_gradient_boosting_loss_functions.py | 13 | 5539 | """
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 sklearn.utils import check_random_state
from sklearn.utils.testing import assert_ra... | bsd-3-clause |
DuCorey/bokeh | examples/models/file/anscombe.py | 12 | 3015 | from __future__ import print_function
import numpy as np
import pandas as pd
from bokeh.util.browser import view
from bokeh.document import Document
from bokeh.embed import file_html
from bokeh.layouts import gridplot
from bokeh.models.glyphs import Circle, Line
from bokeh.models import ColumnDataSource, Grid, Linear... | bsd-3-clause |
energyPATHWAYS/energyPATHWAYS | energyPATHWAYS/shape.py | 1 | 25285 | # -*- coding: utf-8 -*-
"""
Created on Mon Oct 05 14:45:48 2015
@author: ryan
"""
import config as cfg
import datamapfunctions as dmf
import util
import pandas as pd
import pytz
import datetime as DT
# PyCharm complains about dateutil not being listed in the project requirements, but my understanding is that
# it is ... | mit |
cerebis/meta-sweeper | bin/readthru_parser.py | 1 | 16212 | #!/usr/bin/env python
"""
meta-sweeper - for performing parametric sweeps of simulated
metagenomic sequencing experiments.
Copyright (C) 2016 "Matthew Z DeMaere"
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 F... | gpl-3.0 |
ilo10/scikit-learn | sklearn/datasets/lfw.py | 50 | 19048 | """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 |
meerkat-code/meerkat_api | meerkat_api/resources/indicators.py | 1 | 6821 | import pandas as pd
import numpy as np
from dateutil.relativedelta import relativedelta
from flask_restful import Resource
from flask import request
from sqlalchemy import or_, Float
from meerkat_api.extensions import db, api
from meerkat_api.util import series_to_json_dict
from meerkat_analysis.indicators import count... | mit |
monkeypants/MAVProxy | setup.py | 1 | 3872 | from setuptools import setup
import os, platform
version = "1.8.2"
def package_files(directory):
paths = []
for (path, directories, filenames) in os.walk(directory):
for filename in filenames:
paths.append(os.path.join('..', path, filename))
return paths
package_data = ['modules/mavpr... | gpl-3.0 |
seckcoder/lang-learn | python/sklearn/sklearn/decomposition/__init__.py | 2 | 1166 | """
The :mod:`sklearn.decomposition` module includes matrix decomposition
algorithms, including among others PCA, NMF or ICA. Most of the algorithms of
this module can be regarded as dimensionality reduction techniques.
"""
from .nmf import NMF, ProjectedGradientNMF
from .pca import PCA, RandomizedPCA, ProbabilisticPC... | unlicense |
kyleabeauchamp/FitEnsemble | fitensemble/nmr_tools/chemical_shift_readers.py | 1 | 2854 | import pandas as pd
import string
import numpy as np
""" TO DO: implement shiftx2 parser."""
def read_sparta_tab(filename, skiprows):
names = string.split("RESID RESNAME ATOMNAME SS_SHIFT SHIFT RC_SHIFT HM_SHIFT EF_SHIFT SIGMA")
x = pd.io.parsers.read_table(filename, skiprows=skiprows, header=None, names=nam... | gpl-3.0 |
ch3ll0v3k/scikit-learn | sklearn/metrics/ranking.py | 75 | 25426 | """Metrics to assess performance on classification task given scores
Functions named as ``*_score`` return a scalar value to maximize: the higher
the better
Function named as ``*_error`` or ``*_loss`` return a scalar value to minimize:
the lower the better
"""
# Authors: Alexandre Gramfort <alexandre.gramfort@inria.... | bsd-3-clause |
code-sauce/tensorflow | tensorflow/contrib/learn/python/learn/dataframe/queues/feeding_functions.py | 18 | 12209 | # 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 |
etkirsch/scikit-learn | examples/linear_model/plot_polynomial_interpolation.py | 251 | 1895 | #!/usr/bin/env python
"""
========================
Polynomial interpolation
========================
This example demonstrates how to approximate a function with a polynomial of
degree n_degree by using ridge regression. Concretely, from n_samples 1d
points, it suffices to build the Vandermonde matrix, which is n_samp... | bsd-3-clause |
ABcDexter/python-weka-wrapper | setup.py | 2 | 3655 | # 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 that it will be useful,
# b... | gpl-3.0 |
rethore/FUSED-Wake | setup.py | 1 | 2873 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# try:
# from setuptools import setup
# except ImportError:
# from distutils.core import setup
#from setuptools import setup
#from setuptools import Extension
from numpy.distutils.core import setup
from numpy.distutils.extension import Extension
import os
impo... | agpl-3.0 |
ThomasMiconi/nupic.research | htmresearch/frameworks/layers/l2456_model.py | 2 | 22876 | # ----------------------------------------------------------------------
# Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2016, Numenta, Inc. Unless you have an agreement
# with Numenta, Inc., for a separate license for this software code, the
# following terms and conditions apply:
#
# This progra... | agpl-3.0 |
rosinality/knotter | knotter/mapper/lense.py | 1 | 1316 | import numpy as np
import scipy as sp
import scipy.linalg as la
import scipy.spatial.distance as dist
from sklearn import manifold
def pca(X, n_components=2):
centered = X - X.mean(axis=0)
U, s, Vt = la.svd(centered, full_matrices = False)
s2 = s ** 2
U = U[:, :n_components]
s = s[:n_compone... | mit |
wangyum/spark | python/pyspark/ml/clustering.py | 5 | 62508 | #
# 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 |
Shaswat27/scipy | scipy/signal/windows.py | 11 | 53970 | """The suite of window functions."""
from __future__ import division, print_function, absolute_import
import warnings
import numpy as np
from scipy import fftpack, linalg, special
from scipy._lib.six import string_types
__all__ = ['boxcar', 'triang', 'parzen', 'bohman', 'blackman', 'nuttall',
'blackmanhar... | bsd-3-clause |
monarch-initiative/dipper | setup.py | 2 | 1401 | #!/usr/bin/env python3
from setuptools import setup, find_packages
import os
import subprocess
directory = os.path.dirname(os.path.abspath(__file__))
# long_description
readme_path = os.path.join(directory, 'README.md')
with open(readme_path) as read_file:
long_description = read_file.read()
setup(
name='... | bsd-3-clause |
peterwilletts24/Python-Scripts | plot_scripts/EMBRACE/rad_flux/plot_from_pp_2201_diff_8km.py | 2 | 5598 | """
Load pp, plot and save
"""
import os, sys
import matplotlib
matplotlib.use('Agg') # Must be before importing matplotlib.pyplot or pylab!
from matplotlib import rc
from matplotlib.font_manager import FontProperties
from matplotlib import rcParams
from mpl_toolkits.basemap import Basemap
rc('font', family = '... | mit |
hypergravity/bopy | bopy/spec/dataset.py | 1 | 17097 | # -*- coding: utf-8 -*-
"""
migrated from TheCannon package
"""
from __future__ import (absolute_import, division, print_function)
import numpy as np
import sys
from corner import corner
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
from matplotlib import rc
# from astropy.table import Table
f... | bsd-3-clause |
caisq/tensorflow | tensorflow/contrib/losses/python/metric_learning/metric_loss_ops_test.py | 41 | 20535 | # Copyright 2017 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 |
rstoneback/pysat | pysat/tests/test_ssnl_plot.py | 2 | 3184 | """
tests the pysat averaging code
"""
import matplotlib as mpl
import matplotlib.pyplot as plt
import warnings
import pysat
from pysat.ssnl import plot
class TestBasics():
def setup(self):
"""Runs before every method to create a clean testing setup."""
self.testInst = pysat.Instrument('pysat', '... | bsd-3-clause |
droundy/deft | papers/histogram/figs/ising-N128-lndos-comparison.py | 1 | 1853 | from __future__ import division, print_function
import sys, os, matplotlib
import numpy as np
matplotlib.rcParams['text.usetex'] = True
matplotlib.rc('font', family='serif')
if 'noshow' in sys.argv:
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import colors
import readnew
plt.figure(figsize=(5, 4))
... | gpl-2.0 |
Akshay0724/scikit-learn | sklearn/covariance/tests/test_covariance.py | 79 | 12193 | # Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Gael Varoquaux <gael.varoquaux@normalesup.org>
# Virgile Fritsch <virgile.fritsch@inria.fr>
#
# License: BSD 3 clause
import numpy as np
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_alm... | bsd-3-clause |
torypages/luigi | examples/pyspark_wc.py | 56 | 3361 | # -*- coding: utf-8 -*-
#
# Copyright 2012-2015 Spotify AB
#
# 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... | apache-2.0 |
jmmease/pandas | pandas/tests/indexing/test_callable.py | 14 | 8721 | # -*- coding: utf-8 -*-
# pylint: disable-msg=W0612,E1101
import numpy as np
import pandas as pd
import pandas.util.testing as tm
class TestIndexingCallable(object):
def test_frame_loc_ix_callable(self):
# GH 11485
df = pd.DataFrame({'A': [1, 2, 3, 4], 'B': list('aabb'),
... | bsd-3-clause |
benoitsteiner/tensorflow-xsmm | tensorflow/examples/learn/hdf5_classification.py | 75 | 2899 | # 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 |
silky/sms-tools | lectures/09-Sound-description/plots-code/mfcc.py | 25 | 1103 | import numpy as np
import matplotlib.pyplot as plt
import essentia.standard as ess
M = 1024
N = 1024
H = 512
fs = 44100
spectrum = ess.Spectrum(size=N)
window = ess.Windowing(size=M, type='hann')
mfcc = ess.MFCC(numberCoefficients = 12)
x = ess.MonoLoader(filename = '../../../sounds/speech-male.wav', sampleRate = fs)(... | agpl-3.0 |
quchunguang/test | testpy/testmatplotlib.py | 1 | 1277 | import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import norm
def f(t):
return np.exp(-t) * np.cos(2*np.pi*t)
def simple_plot1():
plt.plot([1, 2, 3, 4])
plt.ylabel('some numbers')
plt.show()
def simple_plot2():
plt.plot([1, 2, 3, 4], [1, 4, 9, 16], 'ro')
plt.axis([0, 6, 0... | mit |
petebachant/TurbineDAQ-project-template | Modules/processing.py | 1 | 30074 | # -*- coding: utf-8 -*-
"""
This module contains classes and functions for processing data.
"""
from __future__ import division, print_function
import numpy as np
from pxl import timeseries as ts
from pxl.timeseries import loadhdf
import matplotlib.pyplot as plt
import multiprocessing as mp
import scipy.stats
from sci... | mit |
habi/GlobalDiagnostiX | readAptinaRAW.py | 1 | 1313 | # -*- coding: utf-8 -*-
"""
This script reads the RAW files from the Aptina cameras as numpy arrays,
ready for display or further use.
Made to help Valerie Duay get up to speed :)
"""
import os
import numpy
import matplotlib.pyplot as plt
Directory = '/scratch/tmp/DevWareX/MT9M001/DSL949A-NIR/'
Folder = '1394629994_M... | unlicense |
daniel20162016/my-first | read_xml_all/good_version_read_xml_1/read_wav_xml_good_1.py | 2 | 2673 | # -*- coding: utf-8 -*-
"""
Created on Mon Oct 31 15:45:22 2016
@author: wang
"""
from matplotlib import pylab as plt
from numpy import fft, fromstring, int16, linspace
import wave
from good_read_xml_1 import*
# open a wave file
#filename = 'francois_filon_pure_1.wav'
#filename_1 ='francois_filon_pure_1.xml'
#word ='... | mit |
tum-camp/survival-support-vector-machine | survival/svm/naive_survival_svm.py | 1 | 6322 | # 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 that it will be useful,
# bu... | gpl-3.0 |
eranchetz/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/units.py | 70 | 4810 | """
The classes here provide support for using custom classes with
matplotlib, eg those that do not expose the array interface but know
how to converter themselves to arrays. It also supoprts classes with
units and units conversion. Use cases include converters for custom
objects, eg a list of datetime objects, as we... | agpl-3.0 |
bsipocz/statsmodels | statsmodels/examples/ex_lowess.py | 34 | 2827 | # -*- coding: utf-8 -*-
"""
Created on Mon Oct 31 15:26:06 2011
Author: Chris Jordan Squire
extracted from test suite by josef-pktd
"""
from __future__ import print_function
import numpy as np
import matplotlib.pyplot as plt
import statsmodels.api as sm
lowess = sm.nonparametric.lowess
# this is just to check dire... | bsd-3-clause |
verdverm/pypge | experiments/post_process/scripts/timing_stats_05.py | 1 | 1221 | import pandas as pd
import sys
pgefile=sys.argv[1]
df = pd.read_csv(pgefile, delim_whitespace=True)
df2 = df[sys.argv[2:]]
pge = df2.groupby("problem")
for name, grp in pge:
# print(name)
# print(grp)
ac_t = grp["elapsed_seconds"].iloc[2]/grp["elapsed_seconds"].iloc[0]
ac_m = grp["evald_models"].iloc[2]/grp... | mit |
jmetzen/scikit-learn | benchmarks/bench_covertype.py | 120 | 7381 | """
===========================
Covertype dataset benchmark
===========================
Benchmark stochastic gradient descent (SGD), Liblinear, and Naive Bayes, CART
(decision tree), RandomForest and Extra-Trees on the forest covertype dataset
of Blackard, Jock, and Dean [1]. The dataset comprises 581,012 samples. It ... | bsd-3-clause |
jblackburne/scikit-learn | sklearn/tests/test_multioutput.py | 39 | 6609 | import numpy as np
import scipy.sparse as sp
from sklearn.utils import shuffle
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing import assert_raises_regex
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing impor... | bsd-3-clause |
JeremyRubin/Graffiti-codes | Graffiti-server/Processor.py | 1 | 3841 | from App import *
import ast
import numpy
import matplotlib.pyplot as plt
import datetime
import scipy
from scipy import signal, integrate
from numpy import trapz
class Processor(object):
""" This class processes the data from the Phone"""
def __init__(self, data):
data = ast.literal_eval(data)
... | mit |
dsquareindia/scikit-learn | sklearn/feature_extraction/dict_vectorizer.py | 41 | 12562 | # Authors: Lars Buitinck
# Dan Blanchard <dblanchard@ets.org>
# License: BSD 3 clause
from array import array
from collections import Mapping
from operator import itemgetter
import numpy as np
import scipy.sparse as sp
from ..base import BaseEstimator, TransformerMixin
from ..externals import six
from ..ext... | bsd-3-clause |
tvaroska/autopandas | autopandas/transformers.py | 1 | 3679 | """
Collection of transformers for autopandas
"""
import numpy as np
from sklearn.base import TransformerMixin
from sklearn.preprocessing import LabelEncoder
from sklearn.linear_model import LinearRegression
class DataFrameImputer(TransformerMixin):
"""
Credits http://stackoverflow.com/a/25562948/1575066
... | mit |
Jimmy-Morzaria/scikit-learn | benchmarks/bench_multilabel_metrics.py | 86 | 7286 | #!/usr/bin/env python
"""
A comparison of multilabel target formats and metrics over them
"""
from __future__ import division
from __future__ import print_function
from timeit import timeit
from functools import partial
import itertools
import argparse
import sys
import matplotlib.pyplot as plt
import scipy.sparse as... | bsd-3-clause |
equialgo/scikit-learn | examples/ensemble/plot_forest_iris.py | 335 | 6271 | """
====================================================================
Plot the decision surfaces of ensembles of trees on the iris dataset
====================================================================
Plot the decision surfaces of forests of randomized trees trained on pairs of
features of the iris dataset.
... | bsd-3-clause |
francisco-dlp/hyperspy | hyperspy/_signals/signal1d.py | 1 | 58255 | # -*- coding: utf-8 -*-
# Copyright 2007-2016 The HyperSpy developers
#
# This file is part of HyperSpy.
#
# HyperSpy 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... | gpl-3.0 |
nesterione/scikit-learn | sklearn/cluster/tests/test_spectral.py | 262 | 7954 | """Testing for Spectral Clustering methods"""
from sklearn.externals.six.moves import cPickle
dumps, loads = cPickle.dumps, cPickle.loads
import numpy as np
from scipy import sparse
from sklearn.utils import check_random_state
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_a... | bsd-3-clause |
greysAcademicCode/batch-iv-analysis | batch_iv_analysis/gui.py | 1 | 54573 | from batch_iv_analysis.batch_iv_analysis_UI import Ui_batch_iv_analysis
# needed for file watching
import time
# for performance tuning
#import cProfile, pstats, io
#pr = cProfile.Profile()
import math
#TODO: make area editable
from collections import OrderedDict
from itertools import zip_longest
import os, sys,... | mit |
twankim/weaksemi | main_local.py | 1 | 8601 | # -*- coding: utf-8 -*-
# @Author: twankim
# @Date: 2017-02-24 17:46:51
# @Last Modified by: twankim
# @Last Modified time: 2018-03-09 22:14:15
import numpy as np
import time
import sys
import os
import argparse
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from ssac import weakSSAC
from... | mit |
denis-gordeev/CNN-aggression-RU | train_tensorflow.py | 1 | 10126 | # -*- coding: UTF-8 -*-
import numpy as np
import pandas as pd
import itertools
import csv
import gensim
import re
import nltk.data
import tensorflow
from nltk.tokenize import WordPunctTokenizer
from collections import Counter
from keras.models import Sequential, Graph
from keras.layers.core import Dense, Dropout, Acti... | mit |
AlmightyMegadeth00/kernel_tegra | scripts/tracing/dma-api/trace.py | 96 | 12420 | """Main program and stuff"""
#from pprint import pprint
from sys import stdin
import os.path
import re
from argparse import ArgumentParser
import cPickle as pickle
from collections import namedtuple
from plotting import plotseries, disp_pic
import smmu
class TracelineParser(object):
"""Parse the needed informatio... | gpl-2.0 |
edublancas/python-ds-tools | src/dstools/util.py | 2 | 6039 | import pickle
from pathlib import Path
import yaml
from pydoc import locate
import re
import collections
from functools import wraps
from inspect import signature, _empty, getargspec
from copy import copy
def isiterable(obj):
try:
iter(obj)
except TypeError:
return False
else:
ret... | mit |
mojoboss/scikit-learn | examples/ensemble/plot_adaboost_regression.py | 311 | 1529 | """
======================================
Decision Tree Regression with AdaBoost
======================================
A decision tree is boosted using the AdaBoost.R2 [1] algorithm on a 1D
sinusoidal dataset with a small amount of Gaussian noise.
299 boosts (300 decision trees) is compared with a single decision tr... | bsd-3-clause |
kenshay/ImageScript | ProgramData/SystemFiles/Python/Lib/site-packages/androidviewclient-13.4.0-py2.7.egg/com/dtmilano/android/plot.py | 2 | 6871 | # -*- coding: utf-8 -*-
"""
Copyright (C) 2012-2017 Diego Torres Milano
Created on mar 11, 2017
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
U... | gpl-3.0 |
nmartensen/pandas | pandas/tests/indexes/datetimes/test_tools.py | 1 | 65488 | """ test to_datetime """
import sys
import pytz
import pytest
import locale
import calendar
import dateutil
import numpy as np
from dateutil.parser import parse
from datetime import datetime, date, time
from distutils.version import LooseVersion
import pandas as pd
from pandas._libs import tslib, lib
from pandas.core... | bsd-3-clause |
vellamike/optimizer | optimizer/graphic.py | 1 | 97405 | import wx
import sys
from traceHandler import sizeError
try:
import matplotlib
matplotlib.use('WXAgg')
from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg as FigureCanvas
from matplotlib.figure import Figure
except RuntimeError as re:
print re
sys.exit()
#from inspyred.ec import anal... | lgpl-2.1 |
RayMick/scikit-learn | examples/covariance/plot_lw_vs_oas.py | 248 | 2903 | """
=============================
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 asymptotically optimal shrinkage parameter (minimizing a MSE
criterion), yielding th... | bsd-3-clause |
nrhine1/scikit-learn | examples/mixture/plot_gmm_pdf.py | 284 | 1528 | """
=============================================
Density Estimation for a mixture of Gaussians
=============================================
Plot the density estimation of a mixture of two Gaussians. Data is
generated from two Gaussians with different centers and covariance
matrices.
"""
import numpy as np
import ma... | bsd-3-clause |
LiaoPan/scikit-learn | sklearn/metrics/pairwise.py | 104 | 42995 | # -*- coding: utf-8 -*-
# Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Mathieu Blondel <mathieu@mblondel.org>
# Robert Layton <robertlayton@gmail.com>
# Andreas Mueller <amueller@ais.uni-bonn.de>
# Philippe Gervais <philippe.gervais@inria.fr>
# Lars Buitinck ... | bsd-3-clause |
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