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"""Test functionality of mldata fetching utilities."""
from sklearn import datasets
from sklearn.datasets import mldata_filename, fetch_mldata
from sklearn.utils.testing import assert_in, assert_not_in, mock_urllib2
from nose.tools import assert_equal, assert_raises
from nose import with_setup
from numpy.testing import assert_array_equal
import os
import shutil
import tempfile
import scipy as sp
tmpdir = None
def setup_tmpdata():
# create temporary dir
global tmpdir
tmpdir = tempfile.mkdtemp()
os.makedirs(os.path.join(tmpdir, 'mldata'))
def teardown_tmpdata():
# remove temporary dir
if tmpdir is not None:
shutil.rmtree(tmpdir)
def test_mldata_filename():
cases = [('datasets-UCI iris', 'datasets-uci-iris'),
('news20.binary', 'news20binary'),
('book-crossing-ratings-1.0', 'book-crossing-ratings-10'),
('Nile Water Level', 'nile-water-level'),
('MNIST (original)', 'mnist-original')]
for name, desired in cases:
assert_equal(mldata_filename(name), desired)
@with_setup(setup_tmpdata, teardown_tmpdata)
def test_download():
"""Test that fetch_mldata is able to download and cache a data set."""
_urllib2_ref = datasets.mldata.urllib2
datasets.mldata.urllib2 = mock_urllib2({'mock':
{'label': sp.ones((150,)),
'data': sp.ones((150, 4))}})
try:
mock = fetch_mldata('mock', data_home=tmpdir)
for n in ["COL_NAMES", "DESCR", "target", "data"]:
assert_in(n, mock)
assert_equal(mock.target.shape, (150,))
assert_equal(mock.data.shape, (150, 4))
assert_raises(datasets.mldata.urllib2.HTTPError,
fetch_mldata, 'not_existing_name')
finally:
datasets.mldata.urllib2 = _urllib2_ref
@with_setup(setup_tmpdata, teardown_tmpdata)
def test_fetch_one_column():
_urllib2_ref = datasets.mldata.urllib2
try:
dataname = 'onecol'
# create fake data set in cache
x = sp.arange(6).reshape(2, 3)
datasets.mldata.urllib2 = mock_urllib2({dataname: {'x': x}})
dset = fetch_mldata(dataname, data_home=tmpdir)
for n in ["COL_NAMES", "DESCR", "data"]:
assert_in(n, dset)
assert_not_in("target", dset)
assert_equal(dset.data.shape, (2, 3))
assert_array_equal(dset.data, x)
# transposing the data array
dset = fetch_mldata(dataname, transpose_data=False, data_home=tmpdir)
assert_equal(dset.data.shape, (3, 2))
finally:
datasets.mldata.urllib2 = _urllib2_ref
@with_setup(setup_tmpdata, teardown_tmpdata)
def test_fetch_multiple_column():
_urllib2_ref = datasets.mldata.urllib2
try:
# create fake data set in cache
x = sp.arange(6).reshape(2, 3)
y = sp.array([1, -1])
z = sp.arange(12).reshape(4, 3)
# by default
dataname = 'threecol-default'
datasets.mldata.urllib2 = mock_urllib2({dataname:
({'label': y,
'data': x,
'z': z},
['z', 'data', 'label'])})
dset = fetch_mldata(dataname, data_home=tmpdir)
for n in ["COL_NAMES", "DESCR", "target", "data", "z"]:
assert_in(n, dset)
assert_not_in("x", dset)
assert_not_in("y", dset)
assert_array_equal(dset.data, x)
assert_array_equal(dset.target, y)
assert_array_equal(dset.z, z.T)
# by order
dataname = 'threecol-order'
datasets.mldata.urllib2 = mock_urllib2({dataname:
({'y': y,
'x': x,
'z': z},
['y', 'x', 'z'])})
dset = fetch_mldata(dataname, data_home=tmpdir)
for n in ["COL_NAMES", "DESCR", "target", "data", "z"]:
assert_in(n, dset)
assert_not_in("x", dset)
assert_not_in("y", dset)
assert_array_equal(dset.data, x)
assert_array_equal(dset.target, y)
assert_array_equal(dset.z, z.T)
# by number
dataname = 'threecol-number'
datasets.mldata.urllib2 = mock_urllib2({dataname:
({'y': y,
'x': x,
'z': z},
['z', 'x', 'y'])})
dset = fetch_mldata(dataname, target_name=2, data_name=0,
data_home=tmpdir)
for n in ["COL_NAMES", "DESCR", "target", "data", "x"]:
assert_in(n, dset)
assert_not_in("y", dset)
assert_not_in("z", dset)
assert_array_equal(dset.data, z)
assert_array_equal(dset.target, y)
# by name
dset = fetch_mldata(dataname, target_name='y', data_name='z',
data_home=tmpdir)
for n in ["COL_NAMES", "DESCR", "target", "data", "x"]:
assert_in(n, dset)
assert_not_in("y", dset)
assert_not_in("z", dset)
finally:
datasets.mldata.urllib2 = _urllib2_ref
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