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 |
|---|---|---|---|---|---|
PTDreamer/dRonin | python/ins/cins.py | 11 | 3838 |
from sympy import symbols, lambdify, sqrt
from sympy import MatrixSymbol, Matrix
from numpy import cos, sin, power
from sympy.matrices import *
from quaternions import *
import numpy
import ins
# this is the set of (currently) recommend INS settings. modified from
# https://raw.githubusercontent.com/wiki/TauLabs/TauL... | gpl-3.0 |
q1ang/scikit-learn | examples/decomposition/plot_pca_vs_fa_model_selection.py | 142 | 4467 | """
===============================================================
Model selection with Probabilistic PCA and Factor Analysis (FA)
===============================================================
Probabilistic PCA and Factor Analysis are probabilistic models.
The consequence is that the likelihood of new data can be u... | bsd-3-clause |
Zhang-O/small | tensor__cpu/http/spyser_liyou.py | 1 | 5473 | import urllib.request
from bs4 import BeautifulSoup
import re
import urllib.parse
import xlsxwriter
import pandas as pd
import numpy as np
from urllib import request, parse
from urllib.error import URLError
import json
import multiprocessing
import time
# 详情页面的 地址 存放在这里面
urls_of_detail = []
total_pages = 0
# 要爬取的内容 ... | mit |
harisbal/pandas | pandas/tests/test_panel.py | 1 | 95658 | # -*- coding: utf-8 -*-
# pylint: disable=W0612,E1101
from warnings import catch_warnings, simplefilter
from datetime import datetime
import operator
import pytest
import numpy as np
from pandas.core.dtypes.common import is_float_dtype
from pandas import (Series, DataFrame, Index, date_range, isna, notna,
... | bsd-3-clause |
RomainBrault/scikit-learn | examples/linear_model/plot_sgd_weighted_samples.py | 344 | 1458 | """
=====================
SGD: Weighted samples
=====================
Plot decision function of a weighted dataset, where the size of points
is proportional to its weight.
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
from sklearn import linear_model
# we create 20 points
np.random.seed(0)
X ... | bsd-3-clause |
pratapvardhan/pandas | pandas/tests/io/json/test_normalize.py | 6 | 16358 | import pytest
import numpy as np
import json
import pandas.util.testing as tm
from pandas import compat, Index, DataFrame
from pandas.io.json import json_normalize
from pandas.io.json.normalize import nested_to_record
@pytest.fixture
def deep_nested():
# deeply nested data
return [{'country': 'USA',
... | bsd-3-clause |
chanceraine/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/legend.py | 69 | 30705 | """
Place a legend on the axes at location loc. Labels are a
sequence of strings and loc can be a string or an integer
specifying the legend location
The location codes are
'best' : 0, (only implemented for axis legends)
'upper right' : 1,
'upper left' : 2,
'lower left' : 3,
'lower right' : 4... | agpl-3.0 |
UKPLab/semeval2017-scienceie | code/convNet.py | 1 | 7292 | #!/usr/bin/python
# -*- coding: UTF-8 -*-
from extras import VSM, read_and_map
from representation import VeryStupidCBOWMapper, CharMapper
import sys, numpy as np,os
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import confusion_matrix
from sklearn.metrics import precision_recall_fscore_sup... | apache-2.0 |
ran5515/DeepDecision | 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 |
mbayon/TFG-MachineLearning | vbig/lib/python2.7/site-packages/pandas/util/testing.py | 3 | 92623 | from __future__ import division
# pylint: disable-msg=W0402
import re
import string
import sys
import tempfile
import warnings
import inspect
import os
import subprocess
import locale
import traceback
from datetime import datetime
from functools import wraps, partial
from contextlib import contextmanager
from distuti... | mit |
jaidevd/scikit-learn | sklearn/cluster/bicluster.py | 26 | 19870 | """Spectral biclustering algorithms.
Authors : Kemal Eren
License: BSD 3 clause
"""
from abc import ABCMeta, abstractmethod
import numpy as np
from scipy.sparse import dia_matrix
from scipy.sparse import issparse
from . import KMeans, MiniBatchKMeans
from ..base import BaseEstimator, BiclusterMixin
from ..external... | bsd-3-clause |
ephes/scikit-learn | sklearn/__init__.py | 154 | 3014 | """
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 |
zhoulingjun/zipline | zipline/assets/assets.py | 8 | 34670 | # 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 |
vivekmishra1991/scikit-learn | sklearn/linear_model/randomized_l1.py | 68 | 23405 | """
Randomized Lasso/Logistic: feature selection based on Lasso and
sparse Logistic Regression
"""
# Author: Gael Varoquaux, Alexandre Gramfort
#
# License: BSD 3 clause
import itertools
from abc import ABCMeta, abstractmethod
import warnings
import numpy as np
from scipy.sparse import issparse
from scipy import spar... | bsd-3-clause |
faroit/loudness | python/tests/test_OME.py | 1 | 2084 | import numpy as np
import matplotlib.pyplot as plt
import loudness as ln
def plotResponse(freqPoints, dataPoints,
freqsInterp, responseInterp,
ylim=(-40, 10), title = ""):
if np.any(dataPoints):
plt.semilogx(freqPoints, dataPoints, 'o')
plt.semilogx(freqsInterp, resp... | gpl-3.0 |
jrshust/spark | python/setup.py | 25 | 9659 | #!/usr/bin/env python
#
# 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 "Li... | apache-2.0 |
xyguo/scikit-learn | examples/cross_decomposition/plot_compare_cross_decomposition.py | 55 | 4761 | """
===================================
Compare cross decomposition methods
===================================
Simple usage of various cross decomposition algorithms:
- PLSCanonical
- PLSRegression, with multivariate response, a.k.a. PLS2
- PLSRegression, with univariate response, a.k.a. PLS1
- CCA
Given 2 multivari... | bsd-3-clause |
FernanOrtega/DAT210x | Module2/assignment3.py | 1 | 1065 | import pandas as pd
# TODO: Load up the dataset
# Ensuring you set the appropriate header column names
#
df = pd.read_csv('Datasets/servo.data', names=['motor', 'screw', 'pgain', 'vgain', 'class'])
print df.head()
# TODO: Create a slice that contains all entries
# having a vgain equal to 5. Then print the
# length ... | mit |
DeepVisionTeam/TensorFlowBook | Titanic/data_processing.py | 2 | 4807 | import os
import re
import pandas as pd
import tensorflow as tf
pjoin = os.path.join
DATA_DIR = pjoin(os.path.dirname(__file__), 'data')
train_data = pd.read_csv(pjoin(DATA_DIR, 'train.csv'))
test_data = pd.read_csv(pjoin(DATA_DIR, 'test.csv'))
# Translation:
# Don: an honorific title used in Spain, Portugal, Ital... | apache-2.0 |
tomzw11/Pydrone | route.py | 1 | 2000 | import matplotlib.pyplot as plt
import matplotlib.patches as patches
def route(root):
root_height = root[2]
coordinates = [\
[0.42*root_height+root[0],0.42*root_height+root[1],root_height/2],\
[-0.42*root_height+root[0],0.42*root_height+root[1],root_height/2],\
[-0.42*root_height+root[0],-0.15*root_height+root[1]... | mit |
moutai/scikit-learn | sklearn/cluster/tests/test_dbscan.py | 176 | 12155 | """
Tests for DBSCAN clustering algorithm
"""
import pickle
import numpy as np
from scipy.spatial import distance
from scipy import sparse
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_raises
from sklearn.utils.testing im... | bsd-3-clause |
MysterionRise/fantazy-predictor | enriching_data.py | 1 | 10896 | #!/usr/local/bin/python
# -*- coding: utf-8 -*-
import calendar
import os
import pandas as pd
# Правила подсчета очков:
#
# за участие в матче – 2 очка, если сыграно 10 минут и больше; 1 очко, если сыграно меньше 10 минут
#
# за победу – 3 очка (в гостях); 2 очка (дома)
#
# за поражение – минус 3 очка (дома); минуc... | mit |
bmazin/SDR | Projects/ChannelizerSim/legacy/bin_width_1st_stage.py | 1 | 1524 |
import matplotlib.pyplot as plt
import scipy.signal
import numpy as np
import math
import random
from matplotlib.backends.backend_pdf import PdfPages
samples = 51200
L = samples/512
fs = 512e6
dt = 1/fs
time = [i*dt for i in range(samples)]
def pfb_fir(x):
N = len(x)
T = 4
L = 512
bin_width_scale = 2.5
dx = T*... | gpl-2.0 |
nistats/nistats | examples/03_second_level_models/plot_oasis.py | 1 | 6030 | """Voxel-Based Morphometry on Oasis dataset
========================================
This example uses Voxel-Based Morphometry (VBM) to study the relationship
between aging, sex and gray matter density.
The data come from the `OASIS <http://www.oasis-brains.org/>`_ project.
If you use it, you need to agree with the d... | bsd-3-clause |
MPIBGC-TEE/CompartmentalSystems | notebooks/ELM_dask.py | 1 | 1730 | #from dask.distributed import Client
import xarray as xr
import numpy as np
import pandas as pd
import importlib
import ELMlib
importlib.reload(ELMlib)
#client = Client(n_workers=2, threads_per_worker=2, memory_limit='1GB')
#client
#ds = xr.open_dataset('../Data/14C_spinup_holger_fire.2x2_small.nc')
from netCDF4 imp... | mit |
ky822/scikit-learn | sklearn/utils/metaestimators.py | 283 | 2353 | """Utilities for meta-estimators"""
# Author: Joel Nothman
# Andreas Mueller
# Licence: BSD
from operator import attrgetter
from functools import update_wrapper
__all__ = ['if_delegate_has_method']
class _IffHasAttrDescriptor(object):
"""Implements a conditional property using the descriptor protocol.
... | bsd-3-clause |
cpcloud/ibis | ibis/pandas/execution/tests/test_structs.py | 1 | 2175 | from collections import OrderedDict
import pandas as pd
import pandas.util.testing as tm
import pytest
import ibis
import ibis.expr.datatypes as dt
@pytest.fixture(scope="module")
def value():
return OrderedDict([("fruit", "pear"), ("weight", 0)])
@pytest.fixture(scope="module")
def struct_client(value):
... | apache-2.0 |
mobarski/sandbox | rsm/v4.py | 2 | 5658 | from common2 import *
# NAME IDEA -> pooling/random/sparse/distributed hebbian/horde/crowd/fragment/sample memory
# FEATURES:
# + boost -- neurons with empty mem slots learn faster
# + noise --
# + dropout -- temporal disabling of neurons
# + decay -- remove from mem
# + negatives -- learning to avoid detecting some... | mit |
c11/yatsm | yatsm/classification/__init__.py | 3 | 2042 | """ Module storing classifiers for YATSM
Contains utilities and helper classes for classifying timeseries generated
using YATSM change detection.
"""
import logging
from sklearn.ensemble import RandomForestClassifier
import yaml
from ..errors import AlgorithmNotFoundException
logger = logging.getLogger('yatsm')
_a... | mit |
SKIRT/PTS | magic/plot/imagegrid.py | 1 | 106384 | # -*- coding: utf8 -*-
# *****************************************************************
# ** PTS -- Python Toolkit for working with SKIRT **
# ** © Astronomical Observatory, Ghent University **
# *****************************************************************
## \package pts.magic.pl... | agpl-3.0 |
glamp/coffe2py | main.py | 1 | 1282 | import sys
from IPython.core.interactiveshell import InteractiveShell
import pandasjson as json
import StringIO
if __name__=="__main__":
mode = "ipython"
line = sys.stdin.readline()
shell = InteractiveShell()
while line:
# explicitly write to stdout
sys.stdout.write(line)
sys.st... | bsd-2-clause |
capntransit/carfree-council | cfcensus2010.py | 1 | 1828 | import sys, os, json, time
import pandas as pd
BOROCODE = {'61' : '1', '05' : '2', '47': '3', '81' : '4', '85': '5'}
if (len(sys.argv) < 2):
print ("Usage: cfcensus.py census.csv districts.json")
exit()
censusfile = sys.argv[1]
councilfile = sys.argv[2]
TRACTCOL = 'BoroCT' # rename this for 2000 census
... | gpl-3.0 |
Omegaphora/external_chromium_org | chrome/test/nacl_test_injection/buildbot_chrome_nacl_stage.py | 35 | 11261 | #!/usr/bin/python
# Copyright (c) 2012 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
"""Do all the steps required to build and test against nacl."""
import optparse
import os.path
import re
import shutil
import subproc... | bsd-3-clause |
CartoDB/cartoframes | cartoframes/io/managers/context_manager.py | 1 | 22518 | import time
import pandas as pd
from warnings import warn
from carto.auth import APIKeyAuthClient
from carto.datasets import DatasetManager
from carto.exceptions import CartoException, CartoRateLimitException
from carto.sql import SQLClient, BatchSQLClient, CopySQLClient
from pyrestcli.exceptions import NotFoundExce... | bsd-3-clause |
hsuantien/scikit-learn | examples/covariance/plot_sparse_cov.py | 300 | 5078 | """
======================================
Sparse inverse covariance estimation
======================================
Using the GraphLasso estimator to learn a covariance and sparse precision
from a small number of samples.
To estimate a probabilistic model (e.g. a Gaussian model), estimating the
precision matrix, t... | bsd-3-clause |
louisLouL/pair_trading | capstone_env/lib/python3.6/site-packages/matplotlib/tests/test_collections.py | 2 | 21231 | """
Tests specific to the collections module.
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import io
import numpy as np
from numpy.testing import (
assert_array_equal, assert_array_almost_equal, assert_equal)
import pytest
import matplotlib.pypl... | mit |
sthyme/ZFSchizophrenia | BehaviorAnalysis/Alternative_Analyses/Correlation_between_genes/correlations_DISTANCE_betweengenes.py | 1 | 5605 | import matplotlib
matplotlib.use('Agg')
import matplotlib.pylab as plt
import matplotlib.colors as mat_col
from matplotlib.colors import LinearSegmentedColormap
import scipy
import scipy.cluster.hierarchy as sch
from scipy.cluster.hierarchy import set_link_color_palette
import numpy as np
import pandas as pd
import glo... | mit |
sillvan/hyperspy | hyperspy/drawing/_markers/horizontal_line_segment.py | 1 | 3320 | # -*- coding: utf-8 -*-
# Copyright 2007-2011 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 |
giacomov/lclike | lclike/duration_computation.py | 1 | 12141 | __author__ = 'giacomov'
# !/usr/bin/env python
# add |^| to the top line to run the script without needing 'python' to run it at cmd
# importing modules1
import numpy as np
# cant use 'show' inside the farm
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
from matplotlib import gridspec
imp... | bsd-3-clause |
numenta/nupic.vision | src/nupic/vision/data/OCR/characters/parseJPG.py | 3 | 7772 | #!/usr/bin/python2
'''
This script parses JPEG images of text documents to isolate and save images
of individual characters. The size of these output images in pixels is
specified by the parameters desired_height and desired_width.
The JPEG images are converted to grey scale using a parameter called
luminance_thre... | agpl-3.0 |
google-research/social_cascades | news/graph_processing.py | 1 | 1943 | # Copyright 2020 Google LLC
#
# 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, ... | apache-2.0 |
equialgo/scikit-learn | sklearn/utils/tests/test_random.py | 85 | 7349 | from __future__ import division
import numpy as np
import scipy.sparse as sp
from scipy.misc import comb as combinations
from numpy.testing import assert_array_almost_equal
from sklearn.utils.random import sample_without_replacement
from sklearn.utils.random import random_choice_csc
from sklearn.utils.testing import ... | bsd-3-clause |
gfyoung/pandas | pandas/io/formats/printing.py | 3 | 17290 | """
Printing tools.
"""
import sys
from typing import (
Any,
Callable,
Dict,
Iterable,
List,
Mapping,
Optional,
Sequence,
Sized,
Tuple,
TypeVar,
Union,
)
from pandas._config import get_option
from pandas.core.dtypes.inference import is_sequence
EscapeChars = Union[Map... | bsd-3-clause |
jaeilepp/eggie | mne/viz/_3d.py | 1 | 24122 | """Functions to make 3D plots with M/EEG data
"""
from __future__ import print_function
# Authors: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Denis Engemann <denis.engemann@gmail.com>
# Martin Luessi <mluessi@nmr.mgh.harvard.edu>
# Eric Larson <larson.eric.d@gmail.com>
# ... | bsd-2-clause |
GbalsaC/bitnamiP | venv/lib/python2.7/site-packages/nltk/probability.py | 12 | 81647 | # -*- coding: utf-8 -*-
# Natural Language Toolkit: Probability and Statistics
#
# Copyright (C) 2001-2012 NLTK Project
# Author: Edward Loper <edloper@gradient.cis.upenn.edu>
# Steven Bird <sb@csse.unimelb.edu.au> (additions)
# Trevor Cohn <tacohn@cs.mu.oz.au> (additions)
# Peter Ljunglöf <pete... | agpl-3.0 |
phobson/pygridtools | pygridtools/tests/test_core.py | 2 | 24947 | import os
import warnings
from pkg_resources import resource_filename
import tempfile
import numpy
from numpy import nan
import pandas
from shapely.geometry import Polygon
import geopandas
import pytest
import numpy.testing as nptest
import pandas.util.testing as pdtest
from pygridtools import core
from pygridgen.te... | bsd-3-clause |
nvoron23/statsmodels | statsmodels/graphics/mosaicplot.py | 6 | 26886 | """Create a mosaic plot from a contingency table.
It allows to visualize multivariate categorical data in a rigorous
and informative way.
see the docstring of the mosaic function for more informations.
"""
# Author: Enrico Giampieri - 21 Jan 2013
from __future__ import division
from statsmodels.compat.python import ... | bsd-3-clause |
thomas-bottesch/fcl | python/utils/create_pca_vectors_from_dataset.py | 1 | 2284 | from __future__ import print_function
import fcl
import os
import time
from os.path import abspath, join, dirname, isfile
from fcl import kmeans
from fcl.datasets import load_sector_dataset, load_usps_dataset
from fcl.matrix.csr_matrix import get_csr_matrix_from_object, csr_matrix_to_libsvm_string
from sklearn.decompos... | mit |
kjung/scikit-learn | sklearn/pipeline.py | 12 | 21283 | """
The :mod:`sklearn.pipeline` module implements utilities to build a composite
estimator, as a chain of transforms and estimators.
"""
# Author: Edouard Duchesnay
# Gael Varoquaux
# Virgile Fritsch
# Alexandre Gramfort
# Lars Buitinck
# Licence: BSD
from collections import defaultdict... | bsd-3-clause |
LAIRLAB/qr_trees | src/python/run_ilqr_diffdrive.py | 1 | 2328 | #!/usr/bin/env python
#
# Arun Venkatraman (arunvenk@cs.cmu.edu)
# December 2016
#
# If we are not running from the build directory, then add lib to path from
# build assuming we are running from the python folder
import os
full_path = os.path.realpath(__file__)
if full_path.count("src/python") > 0:
import sys
... | bsd-3-clause |
mcvidomi/poim2motif | run_svm_real.py | 1 | 1483 | '''
Created on 08.06.2015
@author: marinavidovic
'''
import os
import pdb
import utils_svm
import pickle
import numpy as np
import copy
import genQ
import makePOIM
import view
import matplotlib
matplotlib.use('Agg')
if __name__ == '__main__':
read_data = 1
datapath = "/home/mvidovic/POIM... | mit |
phev8/dataset_tools | experiment_handler/time_synchronisation.py | 1 | 1444 | import os
import pandas as pd
def read_synchronisation_file(experiment_root):
filepath = os.path.join(experiment_root, "labels", "synchronisation.csv")
return pd.read_csv(filepath)
def convert_timestamps(experiment_root, timestamps, from_reference, to_reference):
"""
Convert numeric timestamps (seco... | mit |
xfaxca/pygaero | example/tmax_peakfind_example.py | 1 | 4986 | # tmax_peakfind_example.py
"""
Demonstration of some of the primary functions in pygaero, including Tmax finding and elemental analysis.
"""
# Module import
from pygaero import pio
from pygaero import therm
from pygaero import gen_chem
import os
import matplotlib.pyplot as plt
def example1():
# -----------------... | gpl-3.0 |
FrankWang33/cuda-convnet2 | shownet.py | 180 | 18206 | # Copyright 2014 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... | apache-2.0 |
aabadie/scikit-learn | examples/mixture/plot_gmm_selection.py | 95 | 3310 | """
================================
Gaussian Mixture Model Selection
================================
This example shows that model selection can be performed with
Gaussian Mixture Models using information-theoretic criteria (BIC).
Model selection concerns both the covariance type
and the number of components in the ... | bsd-3-clause |
equialgo/scikit-learn | examples/cluster/plot_color_quantization.py | 61 | 3444 | # -*- coding: utf-8 -*-
"""
==================================
Color Quantization using K-Means
==================================
Performs a pixel-wise Vector Quantization (VQ) of an image of the summer palace
(China), reducing the number of colors required to show the image from 96,615
unique colors to 64, while pre... | bsd-3-clause |
gsmaxwell/phase_offset_rx | gnuradio-core/src/examples/pfb/fmtest.py | 17 | 7785 | #!/usr/bin/env python
#
# Copyright 2009 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 option)
# ... | gpl-3.0 |
smblance/ggplot | ggplot/tests/__init__.py | 8 | 10135 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import matplotlib as mpl
import matplotlib.pyplot as plt
from nose.tools import with_setup, make_decorator, assert_true
import warnings
figsize_orig = mpl.rcParams["figure.figsize"]
def setup_package():
m... | bsd-2-clause |
seanli9jan/tensorflow | tensorflow/contrib/learn/python/learn/learn_io/pandas_io_test.py | 25 | 7883 | # 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 |
will-iam/Variant | script/process/ergodicity_scaling.py | 1 | 4083 | #!/usr/bin/python3
# -*- coding:utf-8 -*-
import __future__
import parser
import sys
import matplotlib.pyplot as plt
#plt.style.use('ggplot')
import numpy as np
import operator
from collections import *
caseSize = (8192, 8192)
if parser.args.res:
maxAvailableNode = parser.args.res
else:
maxAvailableNode = 8
... | mit |
sgenoud/scikit-learn | sklearn/datasets/lfw.py | 6 | 16362 | """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 |
pv/scikit-learn | examples/neighbors/plot_nearest_centroid.py | 264 | 1804 | """
===============================
Nearest Centroid Classification
===============================
Sample usage of Nearest Centroid classification.
It will plot the decision boundaries for each class.
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap
f... | bsd-3-clause |
xavierwu/scikit-learn | examples/linear_model/plot_ransac.py | 250 | 1673 | """
===========================================
Robust linear model estimation using RANSAC
===========================================
In this example we see how to robustly fit a linear model to faulty data using
the RANSAC algorithm.
"""
import numpy as np
from matplotlib import pyplot as plt
from sklearn import ... | bsd-3-clause |
giorgiop/scikit-learn | examples/ensemble/plot_adaboost_twoclass.py | 347 | 3268 | """
==================
Two-class AdaBoost
==================
This example fits an AdaBoosted decision stump on a non-linearly separable
classification dataset composed of two "Gaussian quantiles" clusters
(see :func:`sklearn.datasets.make_gaussian_quantiles`) and plots the decision
boundary and decision scores. The di... | bsd-3-clause |
anhaidgroup/py_entitymatching | py_entitymatching/dask/dask_extract_features.py | 1 | 9597 | import logging
import os
import pandas as pd
import multiprocessing
import numpy as np
import dask
from dask.diagnostics import ProgressBar
from dask import delayed
from cloudpickle import cloudpickle
import tempfile
import py_entitymatching.catalog.catalog_manager as cm
import py_entitymatching.utils.catalog_helpe... | bsd-3-clause |
sinkpoint/dipy | scratch/very_scratch/simulation_comparisons_modified.py | 20 | 13117 | import nibabel
import os
import numpy as np
import dipy as dp
import dipy.core.generalized_q_sampling as dgqs
import dipy.io.pickles as pkl
import scipy as sp
from matplotlib.mlab import find
import dipy.core.sphere_plots as splots
import dipy.core.sphere_stats as sphats
import dipy.core.geometry as geometry
import get... | bsd-3-clause |
NunoEdgarGub1/scikit-learn | examples/classification/plot_digits_classification.py | 289 | 2397 | """
================================
Recognizing hand-written digits
================================
An example showing how the scikit-learn can be used to recognize images of
hand-written digits.
This example is commented in the
:ref:`tutorial section of the user manual <introduction>`.
"""
print(__doc__)
# Autho... | bsd-3-clause |
abalckin/cwavenet | examples/WNvsPWN/show_snr.py | 2 | 2454 | #! /usr/bin/python3
import pylab as plb
import numpy as np
from matplotlib import rc
rc('text', usetex=True)
rc('text.latex', unicode=True)
rc('text.latex', preamble=r'\usepackage[russian]{babel}')
#rc('font',**{'family':'serif'})
rc('font',**{'size':'19'})
res = np.loadtxt('result.txt', delimiter=', ')[0:7]
#import p... | gpl-2.0 |
linsalrob/EdwardsLab | phage_protein_blast_genera/tax_violin_plots.py | 1 | 2239 | """
"""
import os
import sys
import argparse
import matplotlib
#matplotlib.use('Agg')
import matplotlib.pyplot as plt
if __name__ == '__main__':
parser = argparse.ArgumentParser(description="")
parser.add_argument('-f', help='Genome average output file (from genera_per_phage_protein.py', default='/home/redw... | mit |
bmazin/ARCONS-pipeline | fluxcal/fluxCal.py | 1 | 29931 | #!/bin/python
'''
fluxCal.py
Created by Seth Meeker on 11-21-2012
Modified on 02-16-2015 to perform absolute fluxCal with point sources
Opens ARCONS observation of a spectrophotometric standard star and
associated wavelength cal file, reads in all photons and converts to energies.
Bins photons to generate a spectru... | gpl-2.0 |
nomadcube/scikit-learn | examples/neighbors/plot_nearest_centroid.py | 264 | 1804 | """
===============================
Nearest Centroid Classification
===============================
Sample usage of Nearest Centroid classification.
It will plot the decision boundaries for each class.
"""
print(__doc__)
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap
f... | bsd-3-clause |
shikhar413/openmc | tests/regression_tests/diff_tally/test.py | 10 | 4122 | import glob
import os
import pandas as pd
import openmc
import pytest
from tests.testing_harness import PyAPITestHarness
class DiffTallyTestHarness(PyAPITestHarness):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
# Set settings explicitly
self._model.settings.ba... | mit |
cgheller/splotch | labeltool/splotchColormap.py | 4 | 5402 | #!/usr/bin/env python
# Generate overlay images in PNG format with transparancy which can be
# used to label Splotch frames. This script can be called as a
# standalone program, see below for details. To label an entire
# directory of Splotch frames, use the driver script <splotchLabelFrames.sh>.
#
# ... | gpl-2.0 |
APMonitor/arduino | 2_Regression/2nd_order_MIMO/GEKKO/tclab_2nd_order_linear.py | 1 | 3283 | import numpy as np
import time
import matplotlib.pyplot as plt
import random
# get gekko package with:
# pip install gekko
from gekko import GEKKO
import pandas as pd
# import data
data = pd.read_csv('data.txt')
tm = data['Time (sec)'].values
Q1s = data[' Heater 1'].values
Q2s = data[' Heater 2'].values... | apache-2.0 |
DistrictDataLabs/yellowbrick | yellowbrick/contrib/scatter.py | 1 | 11862 | # yellowbrick.contrib.scatter
# Implements a 2d scatter plot for feature analysis.
#
# Author: Nathan Danielsen
# Created: Fri Feb 26 19:40:00 2017 -0400
#
# Copyright (C) 2017 The scikit-yb developers
# For license information, see LICENSE.txt
#
# ID: scatter.py [a89633e] benjamin@bengfort.com $
"""
Implements a 2D... | apache-2.0 |
santiago-salas-v/walas | node_images.py | 1 | 1746 | import matplotlib
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111)
patch1 = matplotlib.patches.Circle(
[0.5,0.5],0.05
)
patch2 = matplotlib.patches.Rectangle(
[0.3,0.3],0.4, 0.4, alpha=0.5,
fill=False, edgecolor='black',
linestyle = '--'
)
arrow1 = matplotlib.patches.Arrow(
... | mit |
TNT-Samuel/Coding-Projects | DNS Server/Source/Lib/site-packages/dask/dataframe/io/tests/test_parquet.py | 2 | 45993 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import os
from distutils.version import LooseVersion
import numpy as np
import pandas as pd
import pandas.util.testing as tm
import pytest
import dask
import dask.multiprocessing
import dask.dataframe as dd
f... | gpl-3.0 |
hbldh/skboost | skboost/stumps/decision_stump.py | 1 | 17561 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
:mod:`decision_stump`
==================
.. module:: decision_stump
:platform: Unix, Windows
:synopsis:
.. moduleauthor:: hbldh <henrik.blidh@nedomkull.com>
Created on 2014-08-31, 01:52
"""
from __future__ import division
from __future__ import print_function... | mit |
eric-haibin-lin/mxnet | python/mxnet/ndarray/numpy/_op.py | 2 | 252233 | # pylint: disable=C0302
# 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 |
arahuja/scikit-learn | sklearn/feature_extraction/tests/test_dict_vectorizer.py | 276 | 3790 | # Authors: Lars Buitinck <L.J.Buitinck@uva.nl>
# Dan Blanchard <dblanchard@ets.org>
# License: BSD 3 clause
from random import Random
import numpy as np
import scipy.sparse as sp
from numpy.testing import assert_array_equal
from sklearn.utils.testing import (assert_equal, assert_in,
... | bsd-3-clause |
ChanChiChoi/scikit-learn | sklearn/linear_model/ransac.py | 191 | 14261 | # coding: utf-8
# Author: Johannes Schönberger
#
# License: BSD 3 clause
import numpy as np
from ..base import BaseEstimator, MetaEstimatorMixin, RegressorMixin, clone
from ..utils import check_random_state, check_array, check_consistent_length
from ..utils.random import sample_without_replacement
from ..utils.valid... | bsd-3-clause |
ptitjano/bokeh | examples/compat/mpl_contour.py | 7 | 1028 | # demo inspired by: http://matplotlib.org/examples/pylab_examples/contour_demo.html
from bokeh import mpl
from bokeh.plotting import output_file, show
import matplotlib
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
import numpy as np
matplotlib.rcParams['xtick.direction'] = 'out'
matplotlib.rcParams... | bsd-3-clause |
bd-j/magellanic | magellanic/sfhs/prediction_scripts/predicted_total.py | 1 | 5894 | import sys, pickle, copy
import numpy as np
import matplotlib.pyplot as pl
import astropy.io.fits as pyfits
import magellanic.regionsed as rsed
import magellanic.mcutils as utils
from magellanic.lfutils import *
try:
import fsps
from sedpy import observate
except ImportError:
#you wont be able to predict... | gpl-2.0 |
sunshinelover/chanlun | vn.trader/ctaAlgo/uiChanlunWidget.py | 1 | 68647 | # encoding: UTF-8
"""
缠论模块相关的GUI控制组件
"""
from vtGateway import VtSubscribeReq
from uiBasicWidget import QtGui, QtCore, BasicCell,BasicMonitor,TradingWidget
from eventEngine import *
from ctaBase import *
import pyqtgraph as pg
import numpy as np
import pymongo
from pymongo.errors import *
from datetime import datetime... | mit |
bgris/ODL_bgris | lib/python3.5/site-packages/odl/util/graphics.py | 1 | 15419 | # Copyright 2014-2016 The ODL development group
#
# This file is part of ODL.
#
# ODL 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.
#... | gpl-3.0 |
emoronayuso/beeton | asterisk-bee/asteriskbee/api_status/scripts_graficas/recoge_marcas_graficas.py | 1 | 2307 | #!/usr/bin/python
import matplotlib.pyplot as plt
import numpy as np
#import calendar
from datetime import datetime
from django.conf import settings
settings.configure()
import os
#para conexion con la bases de datos de beeton (asteriskbee)
import sqlite3 as dbapi
##Directorio de la aplicaion
### STATIC_ROOT = '/va... | gpl-3.0 |
crichardson17/starburst_atlas | Low_resolution_sims/Dusty_LowRes/Padova_inst/padova_inst_0/fullgrid/UV1.py | 31 | 9315 | import csv
import matplotlib.pyplot as plt
from numpy import *
import scipy.interpolate
import math
from pylab import *
from matplotlib.ticker import MultipleLocator, FormatStrFormatter
import matplotlib.patches as patches
from matplotlib.path import Path
import os
# --------------------------------------------------... | gpl-2.0 |
CTSRD-SOAAP/chromium-42.0.2311.135 | native_client/buildbot/buildbot_selector.py | 1 | 18629 | #!/usr/bin/python
# Copyright (c) 2012 The Native Client Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
import json
import os
import subprocess
import sys
sys.path.append(os.path.join(os.path.dirname(__file__), '..'))
import pynacl.p... | bsd-3-clause |
googleinterns/cabby | cabby/model/datasets.py | 1 | 4391 | # coding=utf-8
# Copyright 2020 Google LLC
# 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 ... | apache-2.0 |
ywcui1990/nupic | examples/opf/clients/hotgym/prediction/one_gym/nupic_output.py | 17 | 6193 | # ----------------------------------------------------------------------
# Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2013, Numenta, Inc. Unless you have an agreement
# with Numenta, Inc., for a separate license for this software code, the
# following terms and conditions apply:
#
# This progra... | agpl-3.0 |
deeplook/bokeh | bokeh/charts/builder/timeseries_builder.py | 26 | 6252 | """This is the Bokeh charts interface. It gives you a high level API to build
complex plot is a simple way.
This is the TimeSeries class which lets you build your TimeSeries charts just
passing the arguments to the Chart class and calling the proper functions.
"""
#-----------------------------------------------------... | bsd-3-clause |
jonyroda97/redbot-amigosprovaveis | lib/matplotlib/backends/backend_nbagg.py | 2 | 9384 | """Interactive figures in the IPython notebook"""
# Note: There is a notebook in
# lib/matplotlib/backends/web_backend/nbagg_uat.ipynb to help verify
# that changes made maintain expected behaviour.
import datetime
from base64 import b64encode
import json
import io
import os
import six
from uuid import uuid4 as uuid
... | gpl-3.0 |
tuanvu216/udacity-course | intro_to_machine_learning/lesson/lesson_14_evaluation_metrics/evaluate_poi_identifier.py | 1 | 2588 | #!/usr/bin/python
"""
starter code for the evaluation mini-project
start by copying your trained/tested POI identifier from
that you built in the validation mini-project
the second step toward building your POI identifier!
start by loading/formatting the data
"""
import pickle
import sys
sys.p... | mit |
Garrett-R/scikit-learn | sklearn/linear_model/randomized_l1.py | 11 | 23088 | """
Randomized Lasso/Logistic: feature selection based on Lasso and
sparse Logistic Regression
"""
# Author: Gael Varoquaux, Alexandre Gramfort
#
# License: BSD 3 clause
import itertools
from abc import ABCMeta, abstractmethod
import warnings
import numpy as np
from scipy.sparse import issparse
from scipy import spar... | bsd-3-clause |
matplotlib/cmocean | cmocean/rgb/dense.py | 2 | 13693 |
from matplotlib.colors import ListedColormap
from numpy import nan, inf
# Used to reconstruct the colormap in pycam02ucs.cm.viscm
parameters = {'xp': [16.121891585344997, 33.901145962549492, 5.5873058066040926, -14.703203914141397, -17.875928056390336, -5.3288735306278738],
'yp': [-2.5423728813559308, -... | mit |
ctozlm/Dato-Core | src/unity/python/graphlab/data_structures/sframe.py | 13 | 196438 | """
This module defines the SFrame class which provides the
ability to create, access and manipulate a remote scalable dataframe object.
SFrame acts similarly to pandas.DataFrame, but the data is completely immutable
and is stored column wise on the GraphLab Server side.
"""
'''
Copyright (C) 2015 Dato, Inc.
All righ... | agpl-3.0 |
kmkolasinski/Quantulaba | plots/plot_lattice.py | 2 | 1492 | #!/usr/bin/python
import numpy as np
import matplotlib.pyplot as plt
import csv
from matplotlib.collections import LineCollection
file = "lattice.dat"
#ax = plt.gca(projection='3d')
pscale=1.0
lscale=10.0
fig, ax = plt. subplots()
ax.set_aspect('equal')
desired=[1,2]
with open(file, 'r') as fin:
reader=csv.reade... | mit |
thorwhalen/ut | ml/stream/sequences.py | 1 | 6137 |
from sklearn.base import BaseEstimator
from collections import Counter
import pandas as pd
from numpy import sum, nan, isnan
from ut.util.uiter import window
class NextElementPredictor(BaseEstimator):
def predict(self, seqs):
preds = self.predict_proba(seqs)
return [max(pred, key=lambda key: pr... | mit |
jmschrei/scikit-learn | sklearn/linear_model/tests/test_passive_aggressive.py | 169 | 8809 | 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_almost_equal
from sklearn.utils.testing import assert_rais... | bsd-3-clause |
lovexiaov/SandwichApp | venv/lib/python2.7/site-packages/py2app/build_app.py | 9 | 77527 | """
Mac OS X .app build command for distutils
Originally (loosely) based on code from py2exe's build_exe.py by Thomas Heller.
"""
from __future__ import print_function
import imp
import sys
import os
import zipfile
import plistlib
import shlex
import shutil
import textwrap
import pkg_resources
import collections
from... | apache-2.0 |
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