94 lines
3.0 KiB
Python
94 lines
3.0 KiB
Python
"""Testing utilities."""
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# Copyright (c) 2011 Pietro Berkes
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# License: Simplified BSD
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from .fixes import savemat
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import urllib2
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from StringIO import StringIO
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import scipy as sp
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def assert_in(obj, in_=None, out_=None):
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"""Checks that all names in `in_` as in `obj`, but no name
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in `out_` is."""
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if in_ is not None:
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for name in in_:
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assert name in obj
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if out_ is not None:
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for name in out_:
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assert name not in obj
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def fake_mldata_cache(columns_dict, dataname, matfile, ordering=None):
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"""Create a fake mldata data set in the cache_path.
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Parameters
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----------
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columns_dict: contains data as
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columns_dict[column_name] = array of data
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dataname: name of data set
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matfile: file-like object or file name
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ordering: list of column_names, determines the ordering in the data set
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Note: this function transposes all arrays, while fetch_mldata only
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transposes 'data', keep that into account in the tests.
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"""
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datasets = dict(columns_dict)
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# transpose all variables
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for name in datasets:
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datasets[name] = datasets[name].T
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if ordering is None:
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ordering = sorted(list(datasets.keys()))
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# NOTE: setting up this array is tricky, because of the way Matlab
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# re-packages 1D arrays
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datasets['mldata_descr_ordering'] = sp.empty((1, len(ordering)),
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dtype='object')
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for i, name in enumerate(ordering):
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datasets['mldata_descr_ordering'][0, i] = name
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savemat(matfile, datasets, oned_as='column')
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class mock_urllib2(object):
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def __init__(self, mock_datasets):
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"""Object that mocks the urllib2 module to fake requests to mldata.
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`mock_datasets` is a dictionary of {dataset_name: data_dict}, or
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{dataset_name: (data_dict, ordering).
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`data_dict` itself is a dictionary of {column_name: data_array},
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and `ordering` is a list of column_names to determine the ordering
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in the data set (see `fake_mldata_cache` for details).
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When requesting a dataset with a name that is in mock_datasets,
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this object creates a fake dataset in a StringIO object and
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returns it. Otherwise, it raises an URLError.
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"""
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self.mock_datasets = mock_datasets
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class HTTPError(urllib2.URLError):
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code = 404
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def urlopen(self, urlname):
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dataset_name = urlname.split('/')[-1]
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if dataset_name in self.mock_datasets:
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resource_name = '_' + dataset_name
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matfile = StringIO()
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dataset = self.mock_datasets[dataset_name]
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ordering = None
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if isinstance(dataset, tuple):
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dataset, ordering = dataset
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fake_mldata_cache(dataset, resource_name, matfile, ordering)
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matfile.seek(0)
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return matfile
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else:
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raise mock_urllib2.HTTPError('%s not found.' % urlname)
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def quote(self, string, safe='/'):
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return urllib2.quote(string, safe)
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