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 |
|---|---|---|---|---|---|
AlphaDeeX/LSTM-Python | lstm_execution.py | 1 | 2828 | import numpy as np
#import pandas as pd
import matplotlib.pyplot as plt
from lstm_class_object import LSTMPopulation
import sys
def normalise(signal):
mu = np.mean(signal)
variance = np.mean((signal - mu)**2)
signal_normalised = (signal - mu)/(np.sqrt(variance + 1e-8))
return signal_normalise... | mit |
jungla/ICOM-fluidity-toolbox | Detectors/offline_advection/advect_particles_C_3Dv.py | 1 | 4066 | import os, sys
import myfun
import numpy as np
import lagrangian_stats
import scipy.interpolate as interpolate
import csv
import matplotlib.pyplot as plt
import advect_functions
import fio
from intergrid import Intergrid
## READ archive (too many points... somehow)
# args: name, dayi, dayf, days
#label = 'm_25_2_512'... | gpl-2.0 |
adamtiger/tensorflow | tensorflow/python/estimator/inputs/pandas_io_test.py | 89 | 8340 | # 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 applica... | apache-2.0 |
axbaretto/beam | sdks/python/apache_beam/dataframe/expressions.py | 1 | 15120 | #
# 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 |
ryfeus/lambda-packs | Spacy/source2.7/numpy/lib/polynomial.py | 18 | 38572 | """
Functions to operate on polynomials.
"""
from __future__ import division, absolute_import, print_function
__all__ = ['poly', 'roots', 'polyint', 'polyder', 'polyadd',
'polysub', 'polymul', 'polydiv', 'polyval', 'poly1d',
'polyfit', 'RankWarning']
import re
import warnings
import numpy.core.... | mit |
EnergieID/ediel | setup.py | 1 | 2771 | # -*- coding: utf-8 -*-
"""
A setuptools based setup module for smappy.
Adapted from
https://packaging.python.org/en/latest/distributing.html
https://github.com/pypa/sampleproject
"""
# Always prefer setuptools over distutils
from setuptools import setup, find_packages
# To use a consistent encoding
from codecs impo... | mit |
xaibeing/cn-deep-learning | face-generation/dlnd_face_generation.py | 1 | 22781 |
# coding: utf-8
# # 人脸生成（Face Generation）
# 在该项目中，你将使用生成式对抗网络（Generative Adversarial Nets）来生成新的人脸图像。
# ### 获取数据
# 该项目将使用以下数据集：
# - MNIST
# - CelebA
#
# 由于 CelebA 数据集比较复杂，而且这是你第一次使用 GANs。我们想让你先在 MNIST 数据集上测试你的 GANs 模型，以让你更快的评估所建立模型的性能。
#
# 如果你在使用 [FloydHub](https://www.floydhub.com/), 请将 `data_dir` 设置为 "/input" 并使用 ... | mit |
IEOR242-16S-Group6/IEOR242 | src/Feb17_IEOR242_Harry_Python.py | 1 | 1658 | #!/usr/bin/env python
# Some exploratory tests
# Harry Sun
# Feb 17 2016
import pandas as pd
# Get the files and import to DataFrames
!wget -c http://funglab.berkeley.edu/pub/tic_company_gics
gics_df = pd.read_table("tic_company_gics")
!wget -c funglab.berkeley.edu/pub/sec.list.txt -o sec_list.txt
sec_list_df = pd.re... | bsd-3-clause |
daniaki/Enrich2 | enrich2/base/dataframe.py | 1 | 11023 | # Copyright 2016-2017 Alan F Rubin, Daniel Esposito
#
# This file is part of Enrich2.
#
# Enrich2 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) an... | gpl-3.0 |
sinhrks/pandas-ml | pandas_ml/skaccessors/covariance.py | 3 | 1575 | #!/usr/bin/env python
from pandas_ml.core.accessor import _AccessorMethods
class CovarianceMethods(_AccessorMethods):
"""
Accessor to ``sklearn.covariance``.
"""
_module_name = 'sklearn.covariance'
def empirical_covariance(self, *args, **kwargs):
"""
Call ``sklearn... | bsd-3-clause |
platinhom/ManualHom | Coding/Python/scipy-html-0.16.1/generated/scipy-stats-genpareto-1.py | 1 | 1100 | from scipy.stats import genpareto
import matplotlib.pyplot as plt
fig, ax = plt.subplots(1, 1)
# Calculate a few first moments:
c = 0.1
mean, var, skew, kurt = genpareto.stats(c, moments='mvsk')
# Display the probability density function (``pdf``):
x = np.linspace(genpareto.ppf(0.01, c),
genpareto.p... | gpl-2.0 |
sunshineatnoon/sunshineatnoon.github.io | markdown_generator/talks.py | 199 | 4000 |
# coding: utf-8
# # Talks markdown generator for academicpages
#
# Takes a TSV of talks with metadata and converts them for use with [academicpages.github.io](academicpages.github.io). This is an interactive Jupyter notebook ([see more info here](http://jupyter-notebook-beginner-guide.readthedocs.io/en/latest/what_i... | mit |
flennerhag/mlens | mlens/estimators/tests/test_transformer.py | 1 | 3620 | """ML-ENSEMBLE
Test classes.
"""
import numpy as np
from mlens.index import FullIndex, FoldIndex
from mlens.utils.dummy import OLS, Scale
from mlens.utils.exceptions import ParameterChangeWarning
from mlens.testing import Data
from mlens.estimators import LearnerEstimator, TransformerEstimator, LayerEnsemble
from mlen... | mit |
jschueller/numpy | numpy/core/code_generators/ufunc_docstrings.py | 51 | 90047 | """
Docstrings for generated ufuncs
The syntax is designed to look like the function add_newdoc is being
called from numpy.lib, but in this file add_newdoc puts the docstrings
in a dictionary. This dictionary is used in
numpy/core/code_generators/generate_umath.py to generate the docstrings
for the ufuncs in numpy.co... | bsd-3-clause |
kjung/scikit-learn | examples/cluster/plot_mini_batch_kmeans.py | 86 | 4092 | """
====================================================================
Comparison of the K-Means and MiniBatchKMeans clustering algorithms
====================================================================
We want to compare the performance of the MiniBatchKMeans and KMeans:
the MiniBatchKMeans is faster, but give... | bsd-3-clause |
kylerbrown/scikit-learn | examples/cluster/plot_birch_vs_minibatchkmeans.py | 333 | 3694 | """
=================================
Compare BIRCH and MiniBatchKMeans
=================================
This example compares the timing of Birch (with and without the global
clustering step) and MiniBatchKMeans on a synthetic dataset having
100,000 samples and 2 features generated using make_blobs.
If ``n_clusters... | bsd-3-clause |
lscheinkman/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/backends/backend_qt4.py | 69 | 20664 | from __future__ import division
import math
import os
import sys
import matplotlib
from matplotlib import verbose
from matplotlib.cbook import is_string_like, onetrue
from matplotlib.backend_bases import RendererBase, GraphicsContextBase, \
FigureManagerBase, FigureCanvasBase, NavigationToolbar2, IdleEvent, curso... | agpl-3.0 |
greytip/data-science-utils | datascienceutils/sklearnUtils.py | 1 | 7274 | import copy
import fnmatch
import numpy as np
import os
import pandas as pd
import json
from collections import defaultdict
from sklearn.externals import joblib
from sklearn.preprocessing import LabelEncoder, MultiLabelBinarizer, LabelBinarizer
from . import settings
def feature_scale_or_normalize(dataframe, col_na... | gpl-3.0 |
ryanfobel/dmf_control_board | pavement.py | 3 | 6155 | import os
import re
import subprocess as sp
import sys
from paver.easy import task, needs, path, sh
from paver.setuputils import setup
import conda_helpers as ch
import path_helpers as ph
import platformio_helpers as pioh
import versioneer
DEFAULT_ARDUINO_BOARDS = ['mega2560']
setup(name='dmf-control-board-firmwar... | gpl-3.0 |
SpaceKatt/CSPLN | apps/scaffolding/mac/web2py/web2py.app/Contents/Resources/lib/python2.7/matplotlib/projections/geo.py | 3 | 21839 | import math
import numpy as np
import numpy.ma as ma
import matplotlib
rcParams = matplotlib.rcParams
from matplotlib.axes import Axes
from matplotlib import cbook
from matplotlib.patches import Circle
from matplotlib.path import Path
import matplotlib.spines as mspines
import matplotlib.axis as maxis
from matplotlib... | gpl-3.0 |
AWNystrom/SparseInteraction | old/random_matrix_compare.py | 1 | 4171 | from time import time
from scipy.sparse import rand
from sparse_interaction import SparsePolynomialFeatures
import matplotlib.pyplot as plt
from sklearn.preprocessing import PolynomialFeatures
from code import interact
from numpy import arange, median
from memory_profiler import profile
import StringIO
N = 1000
iters=... | apache-2.0 |
febert/DeepRL | easy21/sarsa_lambda_fa.py | 1 | 5922 | import cPickle
import matplotlib.pyplot as plt
from sklearn.metrics import mean_squared_error
from math import sqrt
from mpl_toolkits.mplot3d import axes3d
import os
os.environ["FONTCONFIG_PATH"]="/etc/fonts"
#
# import time
#
# def procedure():
# time.sleep(2.5)
#
# # measure process time
# t0 = time.clock()
#... | gpl-3.0 |
runawayhorse001/LearningApacheSpark | doc/code/mcmc.py | 1 | 2389 |
# coding: utf-8
# In[1]:
import numpy as np
# In[2]:
from scipy.stats import norm
def rnorm(n,mean,sd):
"""
same functions as rnorm in r
r: rnorm(n, mean=0, sd=1)
py: rvs(loc=0, scale=1, size=1, random_state=None)
"""
return norm.rvs(loc=mean,scale=sd,size=n)
def dnorm(x,mean,sd, log=Fal... | mit |
wubr2000/zipline | zipline/data/ffc/loaders/us_equity_pricing.py | 16 | 21283 | # Copyright 2015 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 writ... | apache-2.0 |
cloud-fan/spark | python/pyspark/pandas/typedef/string_typehints.py | 15 | 1599 | #
# 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 |
lorenzo-desantis/mne-python | examples/inverse/plot_compute_mne_inverse_raw_in_label.py | 19 | 1614 | """
=============================================
Compute sLORETA inverse solution on raw data
=============================================
Compute sLORETA inverse solution on raw dataset restricted
to a brain label and stores the solution in stc files for
visualisation.
"""
# Author: Alexandre Gramfort <alexandre.g... | bsd-3-clause |
LunarLanding/Pythics | pythics/libcontrol.py | 1 | 4477 | # -*- coding: utf-8 -*-
#
# Copyright 2008 - 2013 Brian R. D'Urso
#
# This file is part of Python Instrument Control System, also known as Pythics.
#
# Pythics 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, e... | gpl-3.0 |
appapantula/scikit-learn | sklearn/linear_model/tests/test_passive_aggressive.py | 121 | 6117 | import numpy as np
import scipy.sparse as sp
from sklearn.utils.testing import assert_less
from sklearn.utils.testing import assert_greater
from sklearn.utils.testing import assert_array_almost_equal, assert_array_equal
from sklearn.utils.testing import assert_raises
from sklearn.base import ClassifierMixin
from skle... | bsd-3-clause |
lamastex/scalable-data-science | db/studentProjects/07_MatthewHendtlass/054_Yuki_Katoh_GSW_Passing_Analysis.py | 2 | 12223 | # Databricks notebook source exported at Tue, 28 Jun 2016 11:17:28 UTC
# MAGIC %md
# MAGIC # Analyzing Golden State Warriors' passing network using GraphFrames
# MAGIC
# MAGIC ** This notebook is created by [Yuki Katoh](https://de.linkedin.com/in/yukiegosapporo) and is a modified version of the article originally post... | unlicense |
jluttine/bayespy | doc/source/conf.py | 1 | 11116 | # -*- coding: utf-8 -*-
#
# BayesPy documentation build configuration file, created by
# sphinx-quickstart on Mon Aug 27 12:22:11 2012.
#
# 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 |
jakirkham/bokeh | bokeh/core/json_encoder.py | 3 | 9053 | #-----------------------------------------------------------------------------
# Copyright (c) 2012 - 2018, Anaconda, Inc. All rights reserved.
#
# Powered by the Bokeh Development Team.
#
# The full license is in the file LICENSE.txt, distributed with this software.
#---------------------------------------------------... | bsd-3-clause |
shyamalschandra/copperhead | samples/mandelbrot.py | 5 | 1382 | from copperhead import *
@cu
def z_square(z):
real, imag = z
return real * real - imag * imag, 2 * real * imag
@cu
def z_magnitude(z):
real, imag = z
return sqrt(real * real + imag * imag)
@cu
def z_add((z0r, z0i), (z1r, z1i)):
return z0r + z1r, z0i + z1i
@cu
def mandelbrot_iteration(z0, z, i, m... | apache-2.0 |
varun-invent/Autism-Connectome-Analysis | postProcessingFcVolMatchedModularDynamicPipeline.py | 1 | 38729 |
# coding: utf-8
# ## Post processing:
# * Global Signal Regression using orthogonalization
# * Band Pass filtering 0.1 - 0.01 Hz
# * Motion regression using GLM
#
#
# In[460]:
from nipype.interfaces.fsl import (BET, ExtractROI, FAST, FLIRT, ImageMaths,
MCFLIRT, SliceTimer, Thres... | apache-2.0 |
adaptive-learning/flocs | analysis/taskInstance/flow_on_time.py | 3 | 1278 | import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
# TODO: Create infrastructure for analysis and desribe it on our wiki.
def show_flow_on_time_plot(name, show, store):
data = pd.read_csv('data/{name}.csv'.format(name=name))
plot_practice_session(data)
if store:
plt.savefig('p... | gpl-2.0 |
xuleiboy1234/autoTitle | tensorflow/tensorflow/examples/learn/boston.py | 75 | 2549 | # 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... | mit |
magic2du/contact_matrix | Contact_maps/DeepLearning/DeepLearningTool/DL_contact_matrix_load2-new10fold_12_01_2014_server2.py | 1 | 41830 |
# coding: utf-8
# In[3]:
import sys, os
sys.path.append('../../../libs/')
import os.path
import IO_class
from IO_class import FileOperator
from sklearn import cross_validation
import sklearn
import numpy as np
import csv
from dateutil import parser
from datetime import timedelta
from sklearn import svm
import numpy ... | gpl-2.0 |
louisLouL/pair_trading | capstone_env/lib/python3.6/site-packages/matplotlib/spines.py | 2 | 21267 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import matplotlib
import matplotlib.artist as martist
from matplotlib.artist import allow_rasterization
from matplotlib import docstring
import matplotlib.transforms as mtransforms
import matplotli... | mit |
andaag/scikit-learn | sklearn/datasets/__init__.py | 176 | 3671 | """
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 |
neohanju/GarbageDumping | EventEncoder/legacy/test_.py | 1 | 3267 | ########################################
# import requirement libraries #
########################################
from keras.models import Sequential
from keras.layers import Dense, Activation
from keras.layers import Flatten
from keras.layers.normalization import BatchNormalization
from keras.layers im... | bsd-2-clause |
lbishal/scikit-learn | examples/applications/face_recognition.py | 48 | 5691 | """
===================================================
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... | bsd-3-clause |
jmontoyam/mne-python | mne/decoding/tests/test_time_gen.py | 3 | 19294 | # Authors: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Jean-Remi King <jeanremi.king@gmail.com>
#
# License: BSD (3-clause)
import warnings
import copy
import os.path as op
from nose.tools import assert_equal, assert_true, assert_raises
import numpy as np
from numpy.testing import assert_ar... | bsd-3-clause |
lmallin/coverage_test | python_venv/lib/python2.7/site-packages/pandas/tests/scalar/test_period.py | 6 | 50302 | import pytest
import numpy as np
from datetime import datetime, date, timedelta
import pandas as pd
import pandas.util.testing as tm
import pandas.core.indexes.period as period
from pandas.compat import text_type, iteritems
from pandas.compat.numpy import np_datetime64_compat
from pandas._libs import tslib, period a... | mit |
likelyzhao/mxnet | docs/conf.py | 11 | 6195 | # -*- coding: utf-8 -*-
import sys, os, re, subprocess
import mock
from recommonmark import parser
curr_path = os.path.dirname(os.path.abspath(os.path.expanduser(__file__)))
libpath = os.path.join(curr_path, '../python/')
sys.path.insert(0, libpath)
sys.path.insert(0, curr_path)
# -- mock out modules
MOCK_MODULES = [... | apache-2.0 |
udrg/rpg_svo | svo_analysis/src/svo_analysis/analyse_trajectory.py | 17 | 8764 | #!/usr/bin/python
import os
import yaml
import argparse
import numpy as np
import matplotlib.pyplot as plt
import svo_analysis.tum_benchmark_tools.associate as associate
import vikit_py.transformations as transformations
import vikit_py.align_trajectory as align_trajectory
from matplotlib import rc
rc('font',**{'famil... | gpl-3.0 |
jmargeta/scikit-learn | doc/datasets/mldata_fixture.py | 3 | 1205 | """Fixture module to skip the datasets loading when offline
Mock urllib2 access to mldata.org
"""
from os import makedirs
from os.path import join
import numpy as np
import tempfile
import shutil
from sklearn import datasets
from sklearn.utils.testing import mock_mldata_urlopen
def globs(globs):
# setup mock u... | bsd-3-clause |
asarnow/pyem | pyem/metadata.py | 1 | 20458 | # Copyright (C) 2017 Daniel Asarnow
# University of California, San Francisco
#
# I/O routines in pyem.
# See README file for more information.
#
# 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, ... | gpl-3.0 |
dfm/kpsf | test2.py | 1 | 4612 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import division, print_function
__all__ = []
import kplr
import numpy as np
from simplexy import simplexy
import matplotlib.pyplot as pl
from kpsf import TimeSeries, PSF
client = kplr.API()
tpf = client.k2_star(202137899).get_target_pixel_files()[0]
da... | mit |
vigilv/scikit-learn | examples/bicluster/bicluster_newsgroups.py | 142 | 7183 | """
================================================================
Biclustering documents with the Spectral Co-clustering algorithm
================================================================
This example demonstrates the Spectral Co-clustering algorithm on the
twenty newsgroups dataset. The 'comp.os.ms-windows... | bsd-3-clause |
ssh0/growing-string | constant_length_model/constant_length.py | 1 | 2571 | #!/usr/bin/env python
# -*- coding:utf-8 -*-
""" Numerical simulation of growing strings
成長する線素群のシミュレーションを行う。
以前のモデルのように自然長が時間と共に大きくなっていくようなモデルとは異なり，
自然長，バネ定数Kを一定に保ったまま，ある時間でランダムに点を1つずつ追加して
いくことによって線素群の成長を記述することにする。
また，自己回避的な挙動を示すようにするために，各点ごとにポテンシャルを設けて，
この範囲内に入った他の結節点に対して，斥力が働くようにする。
オイラー法または4次のルンゲクッタ法でこれを解き、matplo... | mit |
paulrbrenner/GOS | examples/migration/migration.py | 2 | 6675 | import numpy as np
import pandas as pd
import data as data
from constants import POPULATION_SCALE, MIGRATION_THRESHOLD, PROCESSES, SPLITS, BRAIN_DRAIN_THRESHOLD
from gos import Globe
import sys
# The attributes for each agent.
world_columns = ["Country", "Income", "High Income", "Employed", "Attachment",
... | apache-2.0 |
victorbergelin/scikit-learn | sklearn/decomposition/nmf.py | 30 | 19208 | """ Non-negative matrix factorization
"""
# Author: Vlad Niculae
# Lars Buitinck <L.J.Buitinck@uva.nl>
# Author: Chih-Jen Lin, National Taiwan University (original projected gradient
# NMF implementation)
# Author: Anthony Di Franco (original Python and NumPy port)
# License: BSD 3 clause
from __future__ ... | bsd-3-clause |
mlperf/training_results_v0.5 | v0.5.0/google/cloud_v3.8/resnet-tpuv3-8/code/resnet/model/staging/models/rough/nmt/nmt.py | 2 | 28086 | # Copyright 2017 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 a... | apache-2.0 |
LamaHamadeh/Microsoft-DAT210x | Parallel_Coordinates.py | 1 | 2124 | # -*- coding: utf-8 -*-
"""
Spyder Editor
Authot: Lama Hamadeh 28/11/2016
This file is to create a 6-D parallel coordinate chart for x=[0, 2pi] and the relations with its sin, cos, tan, exp, sqrt and sqruare values.
*Still working on it!*
"""
import pandas as pd
import math
import numpy as np
import m... | mit |
imsparsh/librosa | librosa/feature/spectral.py | 2 | 38170 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Spectral feature extraction"""
import numpy as np
from .. import util
from .. import filters
from ..util.exceptions import ParameterError
from ..core.time_frequency import fft_frequencies
from ..core.audio import zero_crossings
from ..core.spectrum import logamplitude... | isc |
schen496/auditory-hallucinations | model_tester/CNN_LSTM_scratch_Tester.py | 1 | 3493 | from __future__ import print_function
import os
import numpy as np
from keras.models import load_model
import h5py
import math
from sklearn.preprocessing import MinMaxScaler
from sklearn.metrics import mean_squared_error
import matplotlib.pyplot as plt
import math
from tqdm import tqdm
## This code tests the model trai... | apache-2.0 |
MachineLearningProject/flight-delay-prediction | app/predict.py | 1 | 10539 | from collections import defaultdict
import thread
import numpy as np
from datetime import datetime, timedelta
from dateutil.parser import parse
from sklearn import preprocessing
from sklearn import linear_model
from sklearn import cross_validation
from sklearn.ensemble import RandomForestClassifier
from sklearn import... | mit |
supriyagarg/pydatalab | google/datalab/contrib/mlworkbench/commands/_ml.py | 2 | 33262 | # Copyright 2017 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 agre... | apache-2.0 |
evanbiederstedt/RRBSfun | epiphen/total_chr12.py | 2 | 32998 | import glob
import pandas as pd
import numpy as np
pd.set_option('display.max_columns', 50) # print all rows
import os
os.chdir("/gpfs/commons/home/biederstedte-934/evan_projects/correct_phylo_files")
normalB = glob.glob("binary_position_RRBS_normal_B_cell*")
mcell = glob.glob("binary_position_RRBS_NormalBCD19pCD27... | mit |
draperjames/bokeh | bokeh/util/serialization.py | 2 | 8701 | """
Functions for helping with serialization and deserialization of
Bokeh objects.
Certain NunPy array dtypes can be serialized to a binary format for
performance and efficiency. The list of supported dtypes is:
%s
"""
from __future__ import absolute_import
import base64
from six import iterkeys
from .dependencie... | bsd-3-clause |
great-expectations/great_expectations | great_expectations/expectations/metrics/column_map_metrics/column_values_non_null.py | 1 | 2633 | from typing import Optional
from great_expectations.core import ExpectationConfiguration
from great_expectations.execution_engine import (
ExecutionEngine,
PandasExecutionEngine,
SparkDFExecutionEngine,
)
from great_expectations.execution_engine.sqlalchemy_execution_engine import (
SqlAlchemyExecutionE... | apache-2.0 |
scienceopen/python-matlab-examples | PlotContour/contour_demo.py | 1 | 3495 | #!/usr/bin/env python
"""
Illustrate simple contour plotting, contours on an image with
a colorbar for the contours, and labelled contours.
See also contour_image.py.
"""
import matplotlib
import numpy as np
import matplotlib.cm as cm
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
matplotlib.rcParams[... | mit |
arahuja/scikit-learn | examples/svm/plot_svm_margin.py | 318 | 2328 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
=========================================================
SVM Margins Example
=========================================================
The plots below illustrate the effect the parameter `C` has
on the separation line. A large value of `C` basically tells
our model that w... | bsd-3-clause |
muku42/seaborn | seaborn/utils.py | 19 | 15509 | """Small plotting-related utility functions."""
from __future__ import print_function, division
import colorsys
import warnings
import os
import numpy as np
from scipy import stats
import pandas as pd
import matplotlib.colors as mplcol
import matplotlib.pyplot as plt
from distutils.version import LooseVersion
pandas_... | bsd-3-clause |
simon-r/dr14_t.meter | dr14tmeter/lev_histogram.py | 1 | 1499 | # dr14_t.meter: compute the DR14 value of the given audiofiles
# Copyright (C) 2011 - 2012 Simone Riva
#
# 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
# (a... | gpl-3.0 |
IndraVikas/scikit-learn | examples/cluster/plot_adjusted_for_chance_measures.py | 286 | 4353 | """
==========================================================
Adjustment for chance in clustering performance evaluation
==========================================================
The following plots demonstrate the impact of the number of clusters and
number of samples on various clustering performance evaluation me... | bsd-3-clause |
bhargav/scikit-learn | sklearn/metrics/base.py | 46 | 4627 | """
Common code for all metrics
"""
# Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Mathieu Blondel <mathieu@mblondel.org>
# Olivier Grisel <olivier.grisel@ensta.org>
# Arnaud Joly <a.joly@ulg.ac.be>
# Jochen Wersdorfer <jochen@wersdoerfer.de>
# Lars Buitinck
... | bsd-3-clause |
vfine/webplatform | pmModules/taskBuffer.py | 1 | 5868 | """ Invoke the PanDA Server TaskBuffer API """
# $Id: taskBuffer.py 15860 2013-06-12 22:13:47Z fine $
# Display DB status and stats
from pmUtils.pmState import pmstate
from pmCore.pmModule import pmRoles
from pmTaskBuffer.pmTaskBuffer import pmtaskbuffer as pmt
try:
from pmTaskBuffer.pmTaskBuffer import pmgrislias... | lgpl-3.0 |
boland1992/SeisSuite | build/lib.linux-x86_64-2.7/seissuite/ant/stack.py | 8 | 12789 | # -*- coding: utf-8 -*-
"""
Created on Tue Aug 11 12:17:56 2015
@author: boland
The following script is being used in order to explore and develop
python methods for phase-stacking, and phase-weighted stacking between
two seismic waveforms. Input uses one file per station waveform. Needs
a minimum of two channels to... | gpl-3.0 |
neurospin/pylearn-epac | epac/tests/test_warm_start_methods.py | 1 | 2149 | # -*- coding: utf-8 -*-
"""
Created on Mon Oct 7 11:44:30 2013
@author: jinpeng.li@cea.fr
"""
import unittest
import numpy as np
from sklearn import datasets
from epac import Methods
from epac.workflow.splitters import WarmStartMethods
from epac.tests.utils import comp_2wf_reduce_res
from epac.tests.utils import com... | bsd-3-clause |
laurensdeprez/RMPCDMD | scripts/h5md_plot.py | 1 | 2375 | #!/usr/bin/env python
from __future__ import print_function, division
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('file', type=str, help='H5MD datafile')
parser.add_argument('--obs', type=str,
help='Observables to plot, e.g. \'temperature\'',
nargs='+... | bsd-3-clause |
tobegit3hub/deep_cnn | java_predict_client/src/main/proto/tensorflow/contrib/learn/python/learn/estimators/estimator.py | 3 | 47786 | # 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 |
zhenv5/scikit-learn | sklearn/externals/joblib/__init__.py | 72 | 4795 | """ Joblib is a set of tools to provide **lightweight pipelining in
Python**. In particular, joblib offers:
1. transparent disk-caching of the output values and lazy re-evaluation
(memoize pattern)
2. easy simple parallel computing
3. logging and tracing of the execution
Joblib is optimized to be **fast*... | bsd-3-clause |
XiaopeiZhang/user-timeline-tools | twitterWordCloud.py | 1 | 1984 | from os import path
import matplotlib.pyplot as plt
from scipy.misc import imread
from wordcloud import WordCloud, STOPWORDS
from np_extractor import NPExtractor
import json
from ConfigParser import SafeConfigParser
from getUserTimeline import get_users
# load config file
config = SafeConfigParser()
script_dir = path.... | mit |
cg31/tensorflow | tensorflow/contrib/learn/python/learn/tests/dataframe/feeding_queue_runner_test.py | 30 | 4727 | # 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 applica... | apache-2.0 |
MashiMaroLjc/ML-and-DM-in-action | DouBanMovie/datas.py | 1 | 14113 | #coding:utf-8
# 分析脚本
import json
import glob
import matplotlib.pyplot as plt
import matplotlib.font_manager
ZH = matplotlib.font_manager.FontProperties(fname='C:\Windows\Fonts\simsun.ttc')
from queue import PriorityQueue
#
PATH = "data/"
#载入json数据
def load_json(path:str):
file_list = glob.glob(path + "*.txt")
prin... | apache-2.0 |
YuepengGuo/backtrader | backtrader/plot/utils.py | 4 | 2915 | #!/usr/bin/env python
# -*- coding: utf-8; py-indent-offset:4 -*-
###############################################################################
#
# Copyright (C) 2015 Daniel Rodriguez
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as pub... | gpl-3.0 |
fyffyt/scikit-learn | benchmarks/bench_sample_without_replacement.py | 397 | 8008 | """
Benchmarks for sampling without replacement of integer.
"""
from __future__ import division
from __future__ import print_function
import gc
import sys
import optparse
from datetime import datetime
import operator
import matplotlib.pyplot as plt
import numpy as np
import random
from sklearn.externals.six.moves i... | bsd-3-clause |
RapidApplicationDevelopment/tensorflow | tensorflow/contrib/learn/python/learn/estimators/linear_test.py | 3 | 60352 | # 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 |
JonasWallin/BayesFlow | setup_KJ.py | 1 | 2810 | # -*- coding: utf-8 -*-
from distutils.core import setup
from distutils.extension import Extension
#from Cython.Distutils import build_ext
from Cython.Build import cythonize
from numpy import get_include
setup(name='BayesFlow',
version='0.1',
author='Jonas Wallin',
url='',
author_email='jonas.w... | gpl-2.0 |
ZacBlanco/ChefBoyRD | chefboyrd/controllers/model_controller.py | 1 | 5128 | '''ModelController
This is a preprocessor for the prediction_controller. Given data in the form of our local models,
it converts it into numbers usable by the prediction controller.
'''
from peewee import Model
import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
from date... | gpl-3.0 |
cainiaocome/scikit-learn | sklearn/linear_model/__init__.py | 270 | 3096 | """
The :mod:`sklearn.linear_model` module implements generalized linear models. It
includes Ridge regression, Bayesian Regression, Lasso and Elastic Net
estimators computed with Least Angle Regression and coordinate descent. It also
implements Stochastic Gradient Descent related algorithms.
"""
# See http://scikit-le... | bsd-3-clause |
nmmarquez/pymc | pymc3/glm/glm.py | 2 | 6438 | import numpy as np
from pymc import *
import patsy
import theano
import pandas as pd
from collections import defaultdict
from statsmodels.formula.api import glm as glm_sm
import statsmodels.api as sm
from pandas.tools.plotting import scatter_matrix
from . import links
from . import families
def linear_component(formu... | apache-2.0 |
r-mart/scikit-learn | sklearn/semi_supervised/tests/test_label_propagation.py | 307 | 1974 | """ test the label propagation module """
import nose
import numpy as np
from sklearn.semi_supervised import label_propagation
from numpy.testing import assert_array_almost_equal
from numpy.testing import assert_array_equal
ESTIMATORS = [
(label_propagation.LabelPropagation, {'kernel': 'rbf'}),
(label_propa... | bsd-3-clause |
Dapid/GPy | GPy/plotting/matplot_dep/kernel_plots.py | 8 | 6216 | # Copyright (c) 2012, GPy authors (see AUTHORS.txt).
# Licensed under the BSD 3-clause license (see LICENSE.txt)
import numpy as np
from matplotlib import pyplot as pb
import Tango
from matplotlib.textpath import TextPath
from matplotlib.transforms import offset_copy
from .base_plots import ax_default
def add_bar_l... | bsd-3-clause |
HyperloopTeam/FullOpenMDAO | lib/python2.7/site-packages/mpl_toolkits/axisartist/grid_finder.py | 8 | 11969 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import numpy as np
import matplotlib.cbook as mcbook
from matplotlib.transforms import Bbox
from . import clip_path
clip_line_to_rect = clip_path.clip_line_to_rect
import matplotlib.ticker as mtick... | gpl-2.0 |
cxysteven/Paddle | python/paddle/v2/dataset/uci_housing.py | 2 | 3303 | # Copyright (c) 2016 PaddlePaddle 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 applic... | apache-2.0 |
bhargavasana/activitysim | activitysim/defaults/models/mode.py | 1 | 3907 | import os
import yaml
import orca
import pandas as pd
import yaml
from activitysim import activitysim as asim
from activitysim import skim as askim
from .util.mode import _mode_choice_spec
"""
Mode choice is run for all tours to determine the transportation mode that
will be used for the tour
"""
@orca.injectable(... | agpl-3.0 |
keflavich/pyspeckit-obsolete | pyspeckit/spectrum/models/hcn.py | 1 | 5464 | """
====================
HCN Hyperfine Fitter
====================
This is an HCN fitter...
ref for line params: http://www.strw.leidenuniv.nl/~moldata/datafiles/hcn@hfs.dat
"""
import numpy as np
from .. import units
from . import fitter,model,modelgrid
import matplotlib.cbook as mpcb
import copy
try: # for model grid... | mit |
zrhans/pythonanywhere | .virtualenvs/django19/lib/python3.4/site-packages/pandas/stats/ols.py | 9 | 40004 | """
Ordinary least squares regression
"""
# pylint: disable-msg=W0201
from pandas.compat import zip, range, StringIO
from itertools import starmap
from pandas import compat
import numpy as np
from pandas.core.api import DataFrame, Series, isnull
from pandas.core.base import StringMixin
from pandas.core.common import... | apache-2.0 |
cuiwei0322/cost_analysis | tall_building_zero_attack_angle_cost_analysis/Result/plot_cost_stem.py | 1 | 1229 | from pylab import *
import scipy.io
from matplotlib.font_manager import FontProperties
from scipy.interpolate import interp1d
from matplotlib import rc
import matplotlib.pyplot as plt
rc('font',**{'family':'serif','serif':['Times New Roman'],'size':7})
mat_contents = scipy.io.loadmat('cost.mat')
n_50 = mat_contents[... | apache-2.0 |
kiyoto/statsmodels | statsmodels/datasets/china_smoking/data.py | 3 | 1336 | """Smoking and lung cancer in eight cities in China."""
__docformat__ = 'restructuredtext'
COPYRIGHT = """Intern. J. Epidemiol. (1992)"""
TITLE = __doc__
SOURCE = """
Transcribed from Z. Liu, Smoking and Lung Cancer Incidence in China,
Intern. J. Epidemiol., 21:197-201, (1992).
"""
DESCRSHORT = """Co-o... | bsd-3-clause |
bibsian/database-development | test/manual_test_dialogsession.py | 1 | 5780 | #!/usr/bin/env python
import pytest
import pytestqt
from pandas import to_numeric
from PyQt4 import QtCore, QtGui, QtWebKit
import sys,os
from Views import ui_mainrefactor as mw
from Views import ui_dialog_session as dsess
from poplerGUI import class_inputhandler as ini
from poplerGUI.logiclayer import class_userfacade... | mit |
aflaxman/scikit-learn | sklearn/cluster/affinity_propagation_.py | 15 | 13973 | """Affinity Propagation clustering algorithm."""
# Author: Alexandre Gramfort alexandre.gramfort@inria.fr
# Gael Varoquaux gael.varoquaux@normalesup.org
# License: BSD 3 clause
import numpy as np
import warnings
from sklearn.exceptions import ConvergenceWarning
from ..base import BaseEstimator, ClusterMixin
... | bsd-3-clause |
ndingwall/scikit-learn | sklearn/preprocessing/_encoders.py | 6 | 32932 | # Authors: Andreas Mueller <amueller@ais.uni-bonn.de>
# Joris Van den Bossche <jorisvandenbossche@gmail.com>
# License: BSD 3 clause
import numpy as np
from scipy import sparse
import numbers
from ..base import BaseEstimator, TransformerMixin
from ..utils import check_array, is_scalar_nan
from ..utils.valida... | bsd-3-clause |
AIML/scikit-learn | benchmarks/bench_random_projections.py | 397 | 8900 | """
===========================
Random projection benchmark
===========================
Benchmarks for random projections.
"""
from __future__ import division
from __future__ import print_function
import gc
import sys
import optparse
from datetime import datetime
import collections
import numpy as np
import scipy.s... | bsd-3-clause |
caseyclements/bokeh | examples/plotting/server/boxplot.py | 42 | 2372 | # The plot server must be running
# Go to http://localhost:5006/bokeh to view this plot
import numpy as np
import pandas as pd
from bokeh.plotting import figure, show, output_server
# Generate some synthetic time series for six different categories
cats = list("abcdef")
data = np.random.randn(2000)
g = np.random.cho... | bsd-3-clause |
aburgasser/splat | splat/empirical.py | 1 | 100089 | # -*- coding: utf-8 -*-
from __future__ import print_function, division
"""
.. note::
These are the empirical relations functions for SPLAT
"""
# imports: internal
import copy
import sys
# imports - external
import numpy
from astropy import units as u # standard units
#from astropy import const... | mit |
lancezlin/ml_template_py | lib/python2.7/site-packages/matplotlib/pylab.py | 8 | 11110 | """
This is a procedural interface to the matplotlib object-oriented
plotting library.
The following plotting commands are provided; the majority have
MATLAB |reg| [*]_ analogs and similar arguments.
.. |reg| unicode:: 0xAE
_Plotting commands
acorr - plot the autocorrelation function
annotate - annotate som... | mit |
polyaxon/polyaxon | examples/in_cluster/sklearn/iris/model.py | 1 | 1100 | import joblib
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier
from sklearn import metrics
from sklearn.datasets import load_iris
def train_and_eval(
n_neighbors=3,
leaf_size=30,
metric='minkowski',
p=2,
weights='uniform',
test_size=0.3,
... | apache-2.0 |
tjhei/burnman-original | example_averaging.py | 2 | 6557 | # BurnMan - a lower mantle toolkit
# Copyright (C) 2012, 2013, Heister, T., Unterborn, C., Rose, I. and Cottaar, S.
# Released under GPL v2 or later.
"""
This example shows the effect of different averaging schemes. Currently four
averaging schemes are available:
1. Voight-Reuss-Hill
2. Voight averaging
3. Reuss avera... | gpl-2.0 |
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