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 |
|---|---|---|---|---|---|
Tong-Chen/scikit-learn | examples/linear_model/plot_sgd_comparison.py | 8 | 1639 | """
==================================
Comparing various online solvers
==================================
An example showing how different online solvers perform
on the hand-written digits dataset.
"""
# Author: Rob Zinkov <rob at zinkov dot com>
# License: BSD 3 clause
import numpy as np
import pylab as pl
from sk... | bsd-3-clause |
newville/scikit-image | doc/examples/plot_shapes.py | 22 | 1913 | """
======
Shapes
======
This example shows how to draw several different shapes:
- line
- Bezier curve
- polygon
- circle
- ellipse
Anti-aliased drawing for:
- line
- circle
"""
import math
import numpy as np
import matplotlib.pyplot as plt
from skimage.draw import (line, polygon, circle,
... | bsd-3-clause |
JohnCEarls/DataDirac | datadirac/aggregator/resultset.py | 1 | 13038 | import boto.sqs
import logging
import time
import boto
import json
import numpy as np
import tempfile
import hashlib
from collections import defaultdict
from boto.sqs.message import Message
from boto.s3.key import Key
import base64
import datetime
from boto.dynamodb2.exceptions import ConditionalCheckFailedException
im... | gpl-3.0 |
zooniverse/aggregation | experimental/condor/retireBlank.py | 2 | 2893 | #!/usr/bin/env python
__author__ = 'greghines'
import numpy as np
import matplotlib.pyplot as plt
import csv
import sys
import os
import pymongo
import matplotlib.cbook as cbook
import cPickle as pickle
sys.path.append("/home/greg/github/pyIBCC/python")
import ibcc
client = pymongo.MongoClient()
db = client['condor... | apache-2.0 |
linebp/pandas | pandas/io/pytables.py | 1 | 161539 | """
High level interface to PyTables for reading and writing pandas data structures
to disk
"""
# pylint: disable-msg=E1101,W0613,W0603
from datetime import datetime, date
import time
import re
import copy
import itertools
import warnings
import os
from pandas.core.dtypes.common import (
is_list_like,
is_cate... | bsd-3-clause |
florianbeyer/Extract_Landsat_Data | ExtractLandsat.py | 1 | 2172 | '''
#### Florian Beyers script to extract Landsat-Data vom *.tar.gz in a folder
### with Python 2.7
## 2017-05-24
# mail@flobeyer.de
Copyright 2015 Florian Beyer
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You ... | gpl-3.0 |
ryanjmccall/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/colors.py | 69 | 31676 | """
A module for converting numbers or color arguments to *RGB* or *RGBA*
*RGB* and *RGBA* are sequences of, respectively, 3 or 4 floats in the
range 0-1.
This module includes functions and classes for color specification
conversions, and for mapping numbers to colors in a 1-D array of
colors called a colormap. Color... | gpl-3.0 |
aabadie/scikit-learn | benchmarks/bench_plot_randomized_svd.py | 57 | 17557 | """
Benchmarks on the power iterations phase in randomized SVD.
We test on various synthetic and real datasets the effect of increasing
the number of power iterations in terms of quality of approximation
and running time. A number greater than 0 should help with noisy matrices,
which are characterized by a slow spectr... | bsd-3-clause |
eclee25/flu-SDI-simulations-age | age_perc_vaxcov.py | 1 | 8484 | #!/usr/bin/python
##############################################
###Python template
###Author: Elizabeth Lee
###Date: 8/8/13
###Function:
##### 1) odds ratio by vax coverage
###Import data: urban_edges_Sarah.csv, urban_ages_Sarah.csv
###Command Line: python age_perc_vaxcov.py
########################################... | mit |
andaag/scikit-learn | sklearn/lda.py | 72 | 17751 | """
Linear Discriminant Analysis (LDA)
"""
# Authors: Clemens Brunner
# Martin Billinger
# Matthieu Perrot
# Mathieu Blondel
# License: BSD 3-Clause
from __future__ import print_function
import warnings
import numpy as np
from scipy import linalg
from .externals.six import string_types
f... | bsd-3-clause |
rishikksh20/scikit-learn | examples/decomposition/plot_sparse_coding.py | 60 | 4016 | """
===========================================
Sparse coding with a precomputed dictionary
===========================================
Transform a signal as a sparse combination of Ricker wavelets. This example
visually compares different sparse coding methods using the
:class:`sklearn.decomposition.SparseCoder` esti... | bsd-3-clause |
harshaneelhg/scikit-learn | examples/mixture/plot_gmm_selection.py | 248 | 3223 | """
=================================
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 th... | bsd-3-clause |
chrsrds/scikit-learn | examples/cluster/plot_affinity_propagation.py | 46 | 2307 | """
=================================================
Demo of affinity propagation clustering algorithm
=================================================
Reference:
Brendan J. Frey and Delbert Dueck, "Clustering by Passing Messages
Between Data Points", Science Feb. 2007
"""
print(__doc__)
from sklearn.cluster impor... | bsd-3-clause |
wasade/qiita | qiita_db/metadata_template.py | 1 | 82170 | r"""
Metadata template objects (:mod: `qiita_db.metadata_template)
=============================================================
..currentmodule:: qiita_db.metadata_template
This module provides the MetadataTemplate base class and the subclasses
SampleTemplate and PrepTemplate.
Classes
-------
..autosummary::
:... | bsd-3-clause |
tudo-astroparticlephysics/starry_night | tests/test_skycam.py | 1 | 2454 | from starry_night import skycam
from nose.tools import eq_
import numpy as np
import pandas as pd
def test_findLocalMaxPos():
img = np.zeros((480,640))
img[10,30] = 1
# find max value if we are on top of it
pos = skycam.findLocalMaxPos(img, 30,10,1)
eq_((pos.maxX,pos.maxY), (30,10), 'Right on Maxi... | mit |
tapomayukh/projects_in_python | sandbox_tapo/src/skin_related/BMED_8813_HAP/Features/multiple_features/best_kNN_PC/cross_validate_categories_kNN_PC_BMED_8813_HAP_scaled_method_II_area_shape.py | 1 | 4445 |
# Principal Component Analysis Code :
from numpy import mean,cov,double,cumsum,dot,linalg,array,rank,size,flipud
from pylab import *
import numpy as np
import matplotlib.pyplot as pp
#from enthought.mayavi import mlab
import scipy.ndimage as ni
import roslib; roslib.load_manifest('sandbox_tapo_darpa_m3')
import ro... | mit |
HarrisonKramer/optiland | wavefront.py | 1 | 4234 | # -*- coding: utf-8 -*-
"""
Created on Mon Jun 12 22:18:00 2017
@author: kramer
"""
from trace import trace
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
class wavefront(object):
def __init__(self, lens, distribution, Hx=0, Hy=0, wave=0):
self.lens = lens... | gpl-3.0 |
soulmachine/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 |
kenshay/ImageScripter | ProgramData/SystemFiles/Python/Lib/site-packages/numpy/lib/polynomial.py | 32 | 37972 | """
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.... | gpl-3.0 |
tesera/pygypsy | tests/test_disagg.py | 1 | 1260 | #pylint: disable=missing-docstring, no-member
import os
import pandas as pd
import numpy as np
from pygypsy.disaggregate import (
sp_prop_total,
disaggregate_simulation
)
from conftest import DATA_DIR
def test_sp_prop_total():
perc_sp = [
('Aw', 50), ('Sw', 30),
('Pb', 20), ('', 0),
... | mit |
bert9bert/statsmodels | statsmodels/tsa/descriptivestats.py | 33 | 2304 | # -*- coding: utf-8 -*-
"""Descriptive Statistics for Time Series
Created on Sat Oct 30 14:24:08 2010
Author: josef-pktd
License: BSD(3clause)
"""
import numpy as np
from . import stattools as stt
#todo: check subclassing for descriptive stats classes
class TsaDescriptive(object):
'''collection of descriptive ... | bsd-3-clause |
ycaihua/scikit-learn | sklearn/tests/test_cross_validation.py | 1 | 45051 | """Test the cross_validation module"""
from __future__ import division
import warnings
import numpy as np
from scipy.sparse import coo_matrix
from scipy import stats
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_false
from sklearn.utils.testing import assert_equal
from sklearn... | bsd-3-clause |
sinmaniphel/py_isear_dataset | main.py | 1 | 1317 | #!/usr/bin/env python
import sys
import os
from py_isear.isear_loader import IsearLoader
import itertools
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
from sklearn.pipeline import Pipeline
from sklearn.linear_model import SGDClassifier
import... | gpl-3.0 |
bsipocz/statsmodels | statsmodels/examples/l1_demo/short_demo.py | 33 | 3737 | """
You can fit your LikelihoodModel using l1 regularization by changing
the method argument and adding an argument alpha. See code for
details.
The Story
---------
The maximum likelihood (ML) solution works well when the number of data
points is large and the noise is small. When the ML solution starts
"bre... | bsd-3-clause |
almarklein/bokeh | sphinx/source/tutorial/solutions/boxplot.py | 1 | 3003 | import numpy as np
import pandas as pd
from bokeh.plotting import figure, output_file, show
# Generate some synthetic time series for six different categories
cats = list("abcdef")
score = np.random.randn(2000)
g = np.random.choice(cats, 2000)
for i, l in enumerate(cats):
score[g == l] += i // 2
df = pd.DataFrame... | bsd-3-clause |
jayflo/scikit-learn | sklearn/neighbors/approximate.py | 128 | 22351 | """Approximate nearest neighbor search"""
# Author: Maheshakya Wijewardena <maheshakya.10@cse.mrt.ac.lk>
# Joel Nothman <joel.nothman@gmail.com>
import numpy as np
import warnings
from scipy import sparse
from .base import KNeighborsMixin, RadiusNeighborsMixin
from ..base import BaseEstimator
from ..utils.va... | bsd-3-clause |
prheenan/Research | Perkins/Projects/Primers/Demos/2016_4_21_Order_Linear_Primers/LinearMp13_1607F_3520R_Order.py | 1 | 1317 | # force floating point division. Can still use integer with //
from __future__ import division
# This file is used for importing the common utilities classes.
import numpy as np
import matplotlib.pyplot as plt
import sys
baseDir = "../../"
sys.path.append(baseDir)
import networkx
import PrimerDesign.OverHangingPrime... | gpl-3.0 |
edux300/research | data/cbisv2.py | 1 | 3667 | # -*- coding: utf-8 -*-
"""
Created on Mon Oct 9 19:22:38 2017
cbisv2
@author: eduardo
"""
import sys
sys.path.append("/home/eduardo/research/research/")
import os
import glob
import pickle as pkl
import auxiliary_funcs as auxilf
import funcs.xml_reader as xmlr
from matplotlib import pyplot as plt
src_folder = "/med... | apache-2.0 |
imaculate/scikit-learn | examples/semi_supervised/plot_label_propagation_versus_svm_iris.py | 50 | 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 |
tomchor/pymicra | pymicra/tests.py | 1 | 13840 | """
This module contains functions that test certain conditions on pandas.dataframes to
be used with the qcontrol().
They all return True for the columns that pass the test and False for the columns
that fail the test.
"""
from __future__ import absolute_import, print_function, division
from . import algs
def check_r... | gpl-3.0 |
iliavolyova/evo-clustering | src/core.py | 1 | 20837 | from __future__ import division
from matplotlib.pyplot import colormaps
import textwrap
import random
import math
import os
import numpy as np
from scipy import spatial
from sklearn.cluster import *
import time
import log
from sklearn import metrics
from sklearn import preprocessing
from dataset import *
class Con... | mit |
jreback/pandas | pandas/tests/indexes/multi/test_names.py | 1 | 4966 | import pytest
import pandas as pd
from pandas import MultiIndex
import pandas._testing as tm
def check_level_names(index, names):
assert [level.name for level in index.levels] == list(names)
def test_slice_keep_name():
x = MultiIndex.from_tuples([("a", "b"), (1, 2), ("c", "d")], names=["x", "y"])
asser... | bsd-3-clause |
anirudhjayaraman/scikit-learn | examples/decomposition/plot_ica_vs_pca.py | 306 | 3329 | """
==========================
FastICA on 2D point clouds
==========================
This example illustrates visually in the feature space a comparison by
results using two different component analysis techniques.
:ref:`ICA` vs :ref:`PCA`.
Representing ICA in the feature space gives the view of 'geometric ICA':
ICA... | bsd-3-clause |
pligor/predicting-future-product-prices | 00_skroutz_import/advanced_one_hot_encoder.py | 1 | 2817 | from sklearn.preprocessing import LabelEncoder, OneHotEncoder
import numpy as np
import pandas as pd
class AdvancedOneHotEncoder(object):
def encodePandasColAndMerge(self, data_frame, col_name, check_to_null=lambda vv: False):
"""check_to_null provided robustness against invalid values, simply filter thos... | agpl-3.0 |
wattlebird/pystruct | examples/plot_potts_model.py | 5 | 1709 | """
=================================================
Comparing inference times on a simple Potts model
=================================================
Simple comparison of inference times on a Potts model (smoothing)
on a 2d grid of random noise of 5 classes.
The plots show the label results together with energies... | bsd-2-clause |
Shaswat27/sympy | sympy/plotting/tests/test_plot.py | 43 | 8577 | from sympy import (pi, sin, cos, Symbol, Integral, summation, sqrt, log,
oo, LambertW, I, meijerg, exp_polar, Max, Piecewise)
from sympy.plotting import (plot, plot_parametric, plot3d_parametric_line,
plot3d, plot3d_parametric_surface)
from sympy.plotting.plot import unset... | bsd-3-clause |
kshedstrom/pyroms | examples/NWGOA3/Fetch_Pacific/get_pacific_grid.py | 1 | 4241 | #import matplotlib
#matplotlib.use('Agg')
#import numpy as np
import netCDF4
from datetime import datetime
#import pyroms
#import pyroms_toolbox
#import sys
# get HYCOM Northeast Pacific data from 2007 to 2011
invarname = 'angle'
outvarname = 'angle'
#read grid and variable attributes from the first file
url='htt... | bsd-3-clause |
htwangtw/Patterns-of-Thought | src/visualise.py | 1 | 4634 |
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from mpl_toolkits.axes_grid1 import make_axes_locatable
from src.utils import unflatten
def rank_labels(pd_ser):
'''
rank behaviour variables and ignore labels of sparsed variables.
return label and a flatten array ... | mit |
wegamekinglc/alpha-mind | alphamind/tests/portfolio/test_riskmodel.py | 1 | 2187 | # -*- coding: utf-8 -*-
"""
Created on 2018-5-29
@author: cheng.li
"""
import unittest
import numpy as np
import pandas as pd
from alphamind.portfolio.riskmodel import FactorRiskModel
from alphamind.portfolio.riskmodel import FullRiskModel
class TestRiskModel(unittest.TestCase):
def setUp(self):
self... | mit |
Gorbagzog/StageIAP | HorizonPhotometric.py | 1 | 7778 | #!/usr/bin/env python3
# -*-coding:Utf-8 -*
"""H-AGN LightCone photometric Catalog.
Load catalog and make a match with the true lightcone catalog.
"""
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import pyfits
from scipy.spatial import cKDTree
from timeit import default_timer as timer
star... | gpl-3.0 |
wavelets/ThinkStats2 | code/chap12ex_soln.py | 68 | 4459 | """This file contains code for use with "Think Stats",
by Allen B. Downey, available from greenteapress.com
Copyright 2014 Allen B. Downey
License: GNU GPLv3 http://www.gnu.org/licenses/gpl.html
"""
from __future__ import print_function
import pandas
import numpy as np
import statsmodels.formula.api as smf
import t... | gpl-3.0 |
madjelan/Data-Science-45min-Intros | choosing-k-in-kmeans/3d-example.py | 25 | 2925 | #!/usr/bin/env python
# -*- coding: UTF-8 -*-
__author__="Josh Montague"
__license__="MIT License"
"""
This script is designed to run inline (%run 3d-example.py) in
the corresponding IPython notebook. It generates a 3d scatter
plot using scikit-learn data generation and with a number of
samples and clusters determi... | unlicense |
bzero/statsmodels | examples/python/robust_models_0.py | 33 | 2992 |
## Robust Linear Models
from __future__ import print_function
import numpy as np
import statsmodels.api as sm
import matplotlib.pyplot as plt
from statsmodels.sandbox.regression.predstd import wls_prediction_std
# ## Estimation
#
# Load data:
data = sm.datasets.stackloss.load()
data.exog = sm.add_constant(data.ex... | bsd-3-clause |
efce/voltPy | manager/helpers/genetic_algorithm/best_result.py | 1 | 1254 | import numpy as np
from scipy.interpolate import CubicSpline
from scipy.interpolate import InterpolatedUnivariateSpline
# import matplotlib.pyplot as plt
def bestResult(bestChrom,signals,Pmax):
[m,n] = signals.shape
# dodanie pierwszego i ostatniego punktu
bestChrom[0] = 1
bestChrom[n-1... | gpl-3.0 |
RomainBrault/scikit-learn | examples/cluster/plot_kmeans_silhouette_analysis.py | 83 | 5888 | """
===============================================================================
Selecting the number of clusters with silhouette analysis on KMeans clustering
===============================================================================
Silhouette analysis can be used to study the separation distance between the... | bsd-3-clause |
jjx02230808/project0223 | sklearn/datasets/__init__.py | 72 | 3807 | """
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 |
dgies/incubator-airflow | airflow/hooks/base_hook.py | 5 | 2571 | # -*- 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 |
Habasari/sms-tools | software/transformations_interface/stochasticTransformations_function.py | 23 | 2689 | # function call to the transformation function of relevance to the stochasticModel
import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import get_window
import sys, os
sys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)), '../models/'))
sys.path.append(os.path.join(os.path.dirname(... | agpl-3.0 |
pythonvietnam/scikit-learn | sklearn/datasets/tests/test_base.py | 205 | 5878 | import os
import shutil
import tempfile
import warnings
import nose
import numpy
from pickle import loads
from pickle import dumps
from sklearn.datasets import get_data_home
from sklearn.datasets import clear_data_home
from sklearn.datasets import load_files
from sklearn.datasets import load_sample_images
from sklearn... | bsd-3-clause |
macsharma/FORKS | arabidopsis_python/FORKS_crossval.py | 1 | 24696 |
# -*- coding: utf-8 -*-
"""
Created on Fri Nov 04 16:04:25 2016
@author: mayank
"""
#%%
import os
print (os.getcwd())
path1="D:\\Dropbox\\phd\\pseudotemporal\\arabidopsis_python"
os.chdir(path1)
print (os.getcwd())
#%%
from forks_fcns import *
#%%
#import seaborn as sns
#sns.set_style("darkgrid")
... | gpl-3.0 |
ekadhanda/bin | python/katRiseSet.py | 1 | 5735 | #! /usr/bin/env python
# IMPORTANT: All times are in UTC.
#
# katRiseSet.py is based on Lindsay's
# "Scheduling_catalogue_tester.ipynb" to compute source rise, transit
# and set times. The input "source_catalogue.csv" is of the format in
# katsdpcatalogue files.
#
# If no date and time is given, current UTC time is us... | mit |
procoder317/scikit-learn | sklearn/covariance/tests/test_covariance.py | 69 | 11116 | # 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 |
tdhopper/scikit-learn | sklearn/datasets/species_distributions.py | 198 | 7923 | """
=============================
Species distribution dataset
=============================
This dataset represents the geographic distribution of species.
The dataset is provided by Phillips et. al. (2006).
The two species are:
- `"Bradypus variegatus"
<http://www.iucnredlist.org/apps/redlist/details/3038/0>`_... | bsd-3-clause |
myselfHimanshu/UdacityDSWork | Intro-To-Data-Science/Lesson2/PS2_3.py | 2 | 1702 | import pandas
import pandasql
def avg_weekend_temperature(filename):
'''
This function should run a SQL query on a dataframe of
weather data. The SQL query should return one column and
one row - the average meantempi on days that are a Saturday
or Sunday (i.e., the the average mean temperature on ... | gpl-2.0 |
Akshay0724/scikit-learn | examples/covariance/plot_lw_vs_oas.py | 159 | 2951 | """
=============================
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 |
IBT-FMI/COSgen | irf/design.py | 1 | 3879 | # -*- coding: utf-8 -*-
import numpy as np
from scipy import stats, signal
import matplotlib.pyplot as plt
def get_irf(
a=2,
b=10,
resolution=1,
):
my_x = np.linspace(0,100,100*resolution)
my_y = stats.beta.pdf(my_x/100, a, b)
my_z = np.linspace(0,0,100*resolution)
my_z[:20*resolution]=1
irf = signal.deconv... | lgpl-3.0 |
lukeiwanski/tensorflow | tensorflow/contrib/factorization/python/ops/gmm_test.py | 41 | 8716 | # 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 |
eickenberg/scikit-learn | sklearn/mixture/tests/test_dpgmm.py | 34 | 2573 | import unittest
import nose
import numpy as np
from sklearn.mixture import DPGMM, VBGMM
from sklearn.mixture.dpgmm import log_normalize
from sklearn.datasets import make_blobs
from sklearn.utils.testing import assert_array_less
from .test_gmm import GMMTester
np.seterr(all='warn')
def test_class_weights():
# ... | bsd-3-clause |
napjon/moocs_solution | ml-udacity/pca/eigenfaces.py | 1 | 5184 |
"""
===================================================
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 (... | mit |
Saurabh7/shogun | applications/easysvm/tutpaper/svm_params.py | 26 | 12935 |
#from matplotlib import rc
#rc('text', usetex=True)
fontsize = 16
contourFontsize = 12
showColorbar = False
xmin = -1
xmax = 1
ymin = -1.05
ymax = 1
import sys,os
import numpy
import shogun
from shogun.Kernel import GaussianKernel, LinearKernel, PolyKernel
from shogun.Features import RealFeatures, BinaryLabels
from... | mit |
kenshay/ImageScript | ProgramData/SystemFiles/Python/Lib/site-packages/matplotlib/axes/_subplots.py | 10 | 8310 | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from six.moves import map
from matplotlib.gridspec import GridSpec, SubplotSpec
from matplotlib import docstring
import matplotlib.artist as martist
from matplotlib.axes._axes import Axes
import wa... | gpl-3.0 |
Split-Screen/android_kernel_nvidia_shieldtablet | scripts/tracing/dma-api/plotting.py | 96 | 4043 | """Ugly graph drawing tools"""
import matplotlib.pyplot as plt
import matplotlib.cm as cmap
#import numpy as np
from matplotlib import cbook
# http://stackoverflow.com/questions/4652439/is-there-a-matplotlib-equivalent-of-matlabs-datacursormode
class DataCursor(object):
"""A simple data cursor widget that displays... | gpl-2.0 |
YihaoLu/pyfolio | pyfolio/plotting.py | 1 | 41802 | #
# 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 wr... | apache-2.0 |
pratapvardhan/scikit-learn | sklearn/utils/tests/test_shortest_path.py | 303 | 2841 | from collections import defaultdict
import numpy as np
from numpy.testing import assert_array_almost_equal
from sklearn.utils.graph import (graph_shortest_path,
single_source_shortest_path_length)
def floyd_warshall_slow(graph, directed=False):
N = graph.shape[0]
#set nonzer... | bsd-3-clause |
steffengraber/nest-simulator | pynest/examples/lin_rate_ipn_network.py | 8 | 5702 | # -*- coding: utf-8 -*-
#
# lin_rate_ipn_network.py
#
# This file is part of NEST.
#
# Copyright (C) 2004 The NEST Initiative
#
# NEST 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 2 of the Li... | gpl-2.0 |
sumsuddinshojib/openface | evaluation/lfw.py | 1 | 9377 | #!/usr/bin/env python3
#
# Copyright 2015 Carnegie Mellon University
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | apache-2.0 |
Toxad/TWDM-PON-Sim | run_plot_partially_done.py | 1 | 1378 | import sim
import matplotlib.pyplot as plt
sim.DEBUG = True
# seed
sim.random.seed(13)
# default values
sim.tg_default_size = lambda x: 250
sim.DBA_IPACT_default_bandwidth = 5000
max_onus = 3
# seed
sim.random.seed(13)
# for f in range(1,max_onus):
# # override suffix writer
# sim.packet_w = sim.Writer("#... | mit |
jhamman/xarray | xarray/core/ops.py | 1 | 11133 | """Define core operations for xarray objects.
TODO(shoyer): rewrite this module, making use of xarray.core.computation,
NumPy's __array_ufunc__ and mixin classes instead of the unintuitive "inject"
functions.
"""
import operator
import numpy as np
from . import dtypes, duck_array_ops
from .nputils import array_eq, ... | apache-2.0 |
mdrumond/tensorflow | tensorflow/contrib/training/python/training/feeding_queue_runner_test.py | 76 | 5052 | # 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 |
neilhan/tensorflow | tensorflow/examples/skflow/iris_custom_model.py | 12 | 2592 | # 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 |
Clyde-fare/scikit-learn | sklearn/metrics/cluster/tests/test_supervised.py | 206 | 7643 | import numpy as np
from sklearn.metrics.cluster import adjusted_rand_score
from sklearn.metrics.cluster import homogeneity_score
from sklearn.metrics.cluster import completeness_score
from sklearn.metrics.cluster import v_measure_score
from sklearn.metrics.cluster import homogeneity_completeness_v_measure
from sklearn... | bsd-3-clause |
Scapogo/zipline | tests/utils/test_cache.py | 6 | 1936 | from unittest import TestCase
from pandas import Timestamp, Timedelta
from zipline.utils.cache import CachedObject, Expired, ExpiringCache
class CachedObjectTestCase(TestCase):
def test_cached_object(self):
expiry = Timestamp('2014')
before = expiry - Timedelta('1 minute')
after = expir... | apache-2.0 |
google-research/google-research | neural_guided_symbolic_regression/utils/expression_generalization_metrics_test.py | 1 | 7963 | # coding=utf-8
# Copyright 2021 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... | apache-2.0 |
evgchz/scikit-learn | sklearn/cluster/__init__.py | 19 | 1215 | """
The :mod:`sklearn.cluster` module gathers popular unsupervised clustering
algorithms.
"""
from .spectral import spectral_clustering, SpectralClustering
from .mean_shift_ import mean_shift, MeanShift, estimate_bandwidth, \
get_bin_seeds
from .affinity_propagation_ import affinity_propagation, AffinityPropagatio... | bsd-3-clause |
zachcp/qiime | tests/test_stats.py | 15 | 101464 | #!/usr/bin/env python
from __future__ import division
__author__ = "Michael Dwan"
__copyright__ = "Copyright 2012, The QIIME project"
__credits__ = ["Jai Ram Rideout", "Michael Dwan", "Logan Knecht",
"Damien Coy", "Levi McCracken", "Andrew Cochran",
"Will Van Treuren"]
__license__ = "GPL"... | gpl-2.0 |
dolejarz/engsci_capstone_transport | python/DDM/ARPM_utils.py | 1 | 5598 | from collections import namedtuple
import numpy as np
from datetime import datetime, timedelta
from matplotlib.pyplot import savefig
from numpy import meshgrid, pi, power as pow, isnan, diag
from numpy.linalg import svd, inv, det
from scipy.interpolate import LinearNDInterpolator, interp2d
from scipy.special import gam... | mit |
rnowling/asaph | setup.py | 2 | 1136 | """
Copyright 2020 Ronald J. Nowling
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, softw... | apache-2.0 |
richlewis42/scikit-chem | skchem/core/atom.py | 1 | 19470 | #! /usr/bin/env python
#
# Copyright (C) 2015-2016 Rich Lewis <rl403@cam.ac.uk>
# License: 3-clause BSD
"""
## skchem.core.atom
Defining atoms in scikit-chem.
"""
import numpy as np
import pandas as pd
from rdkit import Chem
from rdkit.Chem.rdchem import GetPeriodicTable
from rdkit.Chem.AtomPairs.Utils import NumP... | bsd-3-clause |
techaddict/spark | python/pyspark/sql/tests/test_pandas_udf_window.py | 21 | 12850 | #
# 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 |
luoyetx/mxnet | example/multivariate_time_series/src/lstnet.py | 17 | 11583 | # !/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
# "... | apache-2.0 |
jmcorgan/gnuradio | gr-filter/examples/fft_filter_ccc.py | 47 | 4363 | #!/usr/bin/env python
#
# Copyright 2013 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 |
lthurlow/Network-Grapher | proj/external/matplotlib-1.2.1/lib/mpl_examples/pylab_examples/fill_betweenx_demo.py | 12 | 1576 | import matplotlib.mlab as mlab
from matplotlib.pyplot import figure, show
import numpy as np
## Copy of fill_between.py but using fill_betweenx() instead.
x = np.arange(0.0, 2, 0.01)
y1 = np.sin(2*np.pi*x)
y2 = 1.2*np.sin(4*np.pi*x)
fig = figure()
ax1 = fig.add_subplot(311)
ax2 = fig.add_subplot(312, sharex=ax1)
ax3... | mit |
spinellic/Mission-Planner | Lib/site-packages/numpy/lib/polynomial.py | 58 | 35930 | """
Functions to operate on polynomials.
"""
__all__ = ['poly', 'roots', 'polyint', 'polyder', 'polyadd',
'polysub', 'polymul', 'polydiv', 'polyval', 'poly1d',
'polyfit', 'RankWarning']
import re
import warnings
import numpy.core.numeric as NX
from numpy.core import isscalar, abs, finfo, atleas... | gpl-3.0 |
OXPHOS/shogun | examples/undocumented/python/graphical/so_multiclass_BMRM.py | 11 | 2823 | #!/usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
from shogun import RealFeatures
from shogun import MulticlassModel, MulticlassSOLabels, RealNumber, DualLibQPBMSOSVM
from shogun import BMRM, PPBMRM, P3BMRM
from shogun import StructuredAccuracy
def fill_data(cnt, minv, maxv):
x1 = np.linspace... | gpl-3.0 |
sunil07t/e-mission-server | emission/analysis/result/metrics/time_grouping.py | 1 | 9767 | from __future__ import unicode_literals
from __future__ import print_function
from __future__ import division
from __future__ import absolute_import
from future import standard_library
standard_library.install_aliases()
from builtins import range
from builtins import *
import enum
import pandas as pd
import arrow as ar... | bsd-3-clause |
akhilari7/pa-dude | lib/python2.7/site-packages/nltk/sentiment/util.py | 3 | 30992 | # coding: utf-8
#
# Natural Language Toolkit: Sentiment Analyzer
#
# Copyright (C) 2001-2015 NLTK Project
# Author: Pierpaolo Pantone <24alsecondo@gmail.com>
# URL: <http://nltk.org/>
# For license information, see LICENSE.TXT
"""
Utility methods for Sentiment Analysis.
"""
from copy import deepcopy
import codecs
imp... | mit |
eWaterCycle/ewatercycle | tests/observation/test_grdc.py | 1 | 4364 | from datetime import datetime
import pandas as pd
import pytest
import numpy as np
from pandas.testing import assert_frame_equal
from ewatercycle import CFG
from ewatercycle.observation.grdc import get_grdc_data
@pytest.fixture
def sample_grdc_file(tmp_path):
fn = tmp_path / '42424242_Q_Day.Cmd.txt'
# Sampl... | apache-2.0 |
Akshen/workshop_booking | statistics_app/views.py | 1 | 22195 | from workshop_app.forms import (
UserRegistrationForm, UserLoginForm,
ProfileForm, CreateWorkshop,
ProposeWorkshopDateForm
)
from workshop_app.models import (
Profile, User,
has_profile, Workshop,
WorkshopType, RequestedWorkshop,
BookedWorkshop, ProposeWorkshopDate,
Testimonial
)
from dj... | gpl-3.0 |
TariqAHassan/BioVida | biovida/support_tools/printing.py | 1 | 12309 | # coding: utf-8
"""
Printing Tools
~~~~~~~~~~~~~~
"""
import pandas as pd
# General Support Tools
from biovida.support_tools.support_tools import cln, pstr, items_null, remove_line_breaks
# Suppress Pandas' SettingWithCopyWarning
pd.options.mode.chained_assignment = None
# -------------------------------... | bsd-3-clause |
fredhusser/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 |
KSchoenleber/urbs | urbs/input.py | 1 | 25369 | import pandas as pd
import os
import glob
from xlrd import XLRDError
import pyomo.core as pyomo
from .features.modelhelper import *
from .identify import *
def read_input(input_files, year):
"""Read Excel input file and prepare URBS input dict.
Reads the Excel spreadsheets that adheres to the structure shown... | gpl-3.0 |
benhoff/vexbot | vexbot/entity_extraction.py | 2 | 3561 | import sklearn_crfsuite
import spacy
class EntityExtraction:
def __init__(self, language_model=None):
values = {'algorithm': 'lbfgs',
# coefficient for L1 penalty
'c1': 1,
# coefficient for L2 penalty
'c2': 1e-3,
'ma... | gpl-3.0 |
openfisca/openfisca-france-indirect-taxation | openfisca_france_indirect_taxation/examples/all_indirect_taxes/plot_regressivite.py | 4 | 3282 | # -*- coding: utf-8 -*-
"""
Created on Thu Feb 04 11:28:12 2016
@author: thomas.douenne
"""
# Import de modules généraux
from __future__ import division
import pandas
import seaborn
# Import de modules spécifiques à Openfisca
from openfisca_france_indirect_taxation.examples.utils_example import graph_builder_bar
fr... | agpl-3.0 |
zorroblue/scikit-learn | sklearn/kernel_approximation.py | 29 | 19022 | """
The :mod:`sklearn.kernel_approximation` module implements several
approximate kernel feature maps base on Fourier transforms.
"""
# Author: Andreas Mueller <amueller@ais.uni-bonn.de>
#
# License: BSD 3 clause
import warnings
import numpy as np
import scipy.sparse as sp
from scipy.linalg import svd
from .base im... | bsd-3-clause |
tosolveit/scikit-learn | benchmarks/bench_plot_ward.py | 290 | 1260 | """
Benchmark scikit-learn's Ward implement compared to SciPy's
"""
import time
import numpy as np
from scipy.cluster import hierarchy
import pylab as pl
from sklearn.cluster import AgglomerativeClustering
ward = AgglomerativeClustering(n_clusters=3, linkage='ward')
n_samples = np.logspace(.5, 3, 9)
n_features = n... | bsd-3-clause |
obreitwi/nest-simulator | testsuite/manualtests/stdp_check.py | 4 | 4615 | # -*- coding: utf-8 -*-
#
# stdp_check.py
#
# This file is part of NEST.
#
# Copyright (C) 2004 The NEST Initiative
#
# NEST 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 2 of the License, or
... | gpl-2.0 |
stefanosbou/trading-with-python | lib/backtest.py | 74 | 7381 | #-------------------------------------------------------------------------------
# Name: backtest
# Purpose: perform routine backtesting tasks.
# This module should be useable as a stand-alone library outide of the TWP package.
#
# Author: Jev Kuznetsov
#
# Created: 03/07/2014
... | bsd-3-clause |
smartscheduling/scikit-learn-categorical-tree | sklearn/linear_model/ransac.py | 22 | 14007 | # 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 |
airanmehr/bio | Scripts/TimeSeriesPaper/RealData/GeneAnalysis.py | 1 | 20033 | '''
Copyleft Jun 16, 2016 Arya Iranmehr, PhD Student, Bafna Lab, UC San Diego, Email: airanmehr@gmail.com
'''
import numpy as np;
import pylab as plt
np.set_printoptions(linewidth=200, precision=5, suppress=True)
import pandas as pd;
import seaborn as sns
sns.set_style("whitegrid", {"grid.color": "1", 'axes.linewid... | mit |
darshanthaker/nupic | external/linux32/lib/python2.6/site-packages/matplotlib/projections/geo.py | 69 | 19738 | import math
import numpy as np
import numpy.ma as ma
import matplotlib
rcParams = matplotlib.rcParams
from matplotlib.artist import kwdocd
from matplotlib.axes import Axes
from matplotlib import cbook
from matplotlib.patches import Circle
from matplotlib.path import Path
from matplotlib.ticker import Formatter, Locat... | agpl-3.0 |
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