def setUp(self):
"""Create MetadataMap objects that will be used in the tests."""
# Create a map using the overview tutorial mapping file.
self.overview_map_str = [
"#SampleID\tBarcodeSequence\tTreatment\tDOB\tDescription",
"PC.354\tAGCACGAGCCTA\tControl\t20061218\t354",
"PC.355\tAACTCGTCGATG\tControl\t20061218\t355",
"PC.356\tACAGACCACTCA\tControl\t20061126\t356",
"PC.481\tACCAGCGACTAG\tControl\t20070314\t481",
"PC.593\tAGCAGCACTTGT\tControl\t20071210\t593",
"PC.607\tAACTGTGCGTAC\tFast\t20071112\t607",
"PC.634\tACAGAGTCGGCT\tFast\t20080116\t634",
"PC.635\tACCGCAGAGTCA\tFast\t20080116\t635",
"PC.636\tACGGTGAGTGTC\tFast\t20080116\t636"]
self.overview_map = MetadataMap(
*parse_mapping_file_to_dict(self.overview_map_str))
# Create the same overview tutorial map, but this time with some
# comments.
self.comment = "# Some comments about this mapping file"
self.map_with_comments_str = self.overview_map_str[:]
self.map_with_comments_str.insert(1, self.comment)
self.map_with_comments = MetadataMap(*parse_mapping_file_to_dict(
self.map_with_comments_str))
# Create a MetadataMap object that has no metadata (i.e. no sample IDs,
# so no metadata about samples).
self.empty_map = MetadataMap({}, [])
# Create a MetadataMap object that has samples (i.e. sample IDs) but
# not associated metadata (i.e. no columns other than SampleID).
self.no_metadata_str = ["#SampleID",
"PC.354",
"PC.355",
"PC.356",
"PC.481",
"PC.593",
"PC.607",
"PC.634",
"PC.635",
"PC.636"]
self.no_metadata = MetadataMap(*parse_mapping_file_to_dict(
self.no_metadata_str))
# Create a MetadataMap object that has a category with only one value
# throughout the entire column.
self.single_value_str = ["#SampleID\tFoo",
"PC.354\tfoo",
"PC.355\tfoo",
"PC.356\tfoo",
"PC.481\tfoo",
"PC.593\tfoo",
"PC.607\tfoo",
"PC.634\tfoo",
"PC.635\tfoo",
"PC.636\tfoo"]
self.single_value = MetadataMap(*parse_mapping_file_to_dict(
self.single_value_str))
def setUp(self):
"""Create MetadataMap objects that will be used in the tests."""
# Create a map using the overview tutorial mapping file.
self.overview_map_str = [
"#SampleID\tBarcodeSequence\tTreatment\tDOB\tDescription",
"PC.354\tAGCACGAGCCTA\tControl\t20061218\t354",
"PC.355\tAACTCGTCGATG\tControl\t20061218\t355",
"PC.356\tACAGACCACTCA\tControl\t20061126\t356",
"PC.481\tACCAGCGACTAG\tControl\t20070314\t481",
"PC.593\tAGCAGCACTTGT\tControl\t20071210\t593",
"PC.607\tAACTGTGCGTAC\tFast\t20071112\t607",
"PC.634\tACAGAGTCGGCT\tFast\t20080116\t634",
"PC.635\tACCGCAGAGTCA\tFast\t20080116\t635",
"PC.636\tACGGTGAGTGTC\tFast\t20080116\t636"
]
self.overview_map = MetadataMap(
*parse_mapping_file_to_dict(self.overview_map_str))
# Create the same overview tutorial map, but this time with some
# comments.
self.comment = "# Some comments about this mapping file"
self.map_with_comments_str = self.overview_map_str[:]
self.map_with_comments_str.insert(1, self.comment)
self.map_with_comments = MetadataMap(
*parse_mapping_file_to_dict(self.map_with_comments_str))
# Create a MetadataMap object that has no metadata (i.e. no sample IDs,
# so no metadata about samples).
self.empty_map = MetadataMap({}, [])
# Create a MetadataMap object that has samples (i.e. sample IDs) but
# not associated metadata (i.e. no columns other than SampleID).
self.no_metadata_str = [
"#SampleID", "PC.354", "PC.355", "PC.356", "PC.481", "PC.593",
"PC.607", "PC.634", "PC.635", "PC.636"
]
self.no_metadata = MetadataMap(
*parse_mapping_file_to_dict(self.no_metadata_str))
# Create a MetadataMap object that has a category with only one value
# throughout the entire column.
self.single_value_str = [
"#SampleID\tFoo", "PC.354\tfoo", "PC.355\tfoo", "PC.356\tfoo",
"PC.481\tfoo", "PC.593\tfoo", "PC.607\tfoo", "PC.634\tfoo",
"PC.635\tfoo", "PC.636\tfoo"
]
self.single_value = MetadataMap(
*parse_mapping_file_to_dict(self.single_value_str))
def test_parse_mapping_file_to_dict(self):
"""parse_mapping_file functions as expected"""
s1 = ["#sample\ta\tb", "#comment line to skip", "x \t y \t z ", " ", "#more skip", "i\tj\tk"]
exp = ([["x", "y", "z"], ["i", "j", "k"]], ["sample", "a", "b"], ["comment line to skip", "more skip"])
mapdict, comments = parse_mapping_file_to_dict(s1)
expdict = {"x": {"a": "y", "b": "z"}, "i": {"a": "j", "b": "k"}}
self.assertEqual(mapdict, expdict)
self.assertEqual(comments, ["comment line to skip", "more skip"])
def test_parse_mapping_file_to_dict(self):
"""parse_mapping_file functions as expected"""
s1 = ['#sample\ta\tb', '#comment line to skip',\
'x \t y \t z ', ' ', '#more skip', 'i\tj\tk']
exp = ([['x','y','z'],['i','j','k']],\
['sample','a','b'],\
['comment line to skip','more skip'])
mapdict, comments = parse_mapping_file_to_dict(s1)
expdict = {'x': {'a': 'y', 'b': 'z'}, 'i': {'a': 'j', 'b': 'k'}}
self.assertEqual(mapdict, expdict)
self.assertEqual(comments, ['comment line to skip', 'more skip'])
def parseMetadataMap(lines):
"""Parses a QIIME metadata mapping file into a MetadataMap object.
This static method is basically a factory that reads in the given
metadata mapping file contents and returns a MetadataMap instance. This
method is provided for convenience.
Arguments:
lines - a list of strings representing the file contents of a QIIME
metadata mapping file
"""
return MetadataMap(*parse_mapping_file_to_dict(lines))
def parseMetadataMap(lines):
"""Parses a QIIME metadata mapping file into a MetadataMap object.
This static method is basically a factory that reads in the given
metadata mapping file contents and returns a MetadataMap instance. This
method is provided for convenience.
Arguments:
lines - a list of strings representing the file contents of a QIIME
metadata mapping file
"""
return MetadataMap(*parse_mapping_file_to_dict(lines))
