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#!/usr/bin/env python
"""Tests public and private functions in the group module."""
__author__ = "Jai Rideout"
__copyright__ = "Copyright 2011, The QIIME project"
__credits__ = ["Jai Rideout", "Jeremy Widmann"]
__license__ = "GPL"
__version__ = "1.4.0"
__maintainer__ = "Jai Rideout"
__email__ = "jr378@nau.edu"
__status__ = "Release"
from cogent.util.unit_test import TestCase, main
from qiime.parse import parse_mapping_file, parse_distmat, group_by_field
from qiime.group import get_grouped_distances, get_all_grouped_distances,\
get_field_state_comparisons, _get_indices, _get_groupings, _validate_input
class GroupTests(TestCase):
"""Tests of the group module."""
def setUp(self):
"""Create some data to be used in the tests."""
# Create the mapping file/distance matrix combo from the overview
# tutorial.
self.dist_matrix_string = ["\tPC.354\tPC.355\tPC.356\tPC.481\tPC.593\
\tPC.607\tPC.634\tPC.635\tPC.636",
"PC.354\t0.0\t0.625\t0.623\t0.61\t0.577\
\t0.729\t0.8\t0.721\t0.765",
"PC.355\t0.625\t0.0\t0.615\t0.642\t0.673\
\t0.776\t0.744\t0.749\t0.677",
"PC.356\t0.623\t0.615\t0.0\t0.682\t0.737\
\t0.734\t0.777\t0.733\t0.724",
"PC.481\t0.61\t0.642\t0.682\t0.0\t0.704\
\t0.696\t0.675\t0.654\t0.696",
"PC.593\t0.577\t0.673\t0.737\t0.704\t0.0\
\t0.731\t0.758\t0.738\t0.737",
"PC.607\t0.729\t0.776\t0.734\t0.696\t0.731\
\t0.0\t0.718\t0.666\t0.727",
"PC.634\t0.8\t0.744\t0.777\t0.675\t0.758\
\t0.718\t0.0\t0.6\t0.578",
"PC.635\t0.721\t0.749\t0.733\t0.654\t0.738\
\t0.666\t0.6\t0.0\t0.623",
"PC.636\t0.765\t0.677\t0.724\t0.696\t0.737\
\t0.727\t0.578\t0.623\t0.0"]
self.mapping_string = ["#SampleID\tBarcodeSequence\tTreatment\tDOB",
"PC.354\tAGCACGAGCCTA\tControl\t20061218",
"PC.355\tAACTCGTCGATG\tControl\t20061218",
"PC.356\tACAGACCACTCA\tControl\t20061126",
"PC.481\tACCAGCGACTAG\tControl\t20070314",
"PC.593\tAGCAGCACTTGT\tControl\t20071210",
"PC.607\tAACTGTGCGTAC\tFast\t20071112",
"PC.634\tACAGAGTCGGCT\tFast\t20080116",
"PC.635\tACCGCAGAGTCA\tFast\t20080116",
"PC.636\tACGGTGAGTGTC\tFast\t20080116"]
# Field to test on. Field values are either "Control" or "Fast".
self.field = 'Treatment'
# Create a tiny distancy matrix/mapping file with a single sample for
# additional testing.
self.tiny_dist_matrix_string = ["\tSamp.1", "Samp.1\t0"]
self.tiny_mapping_string = ["#SampleID\tBarcodeSequence\tSampleField",
"Samp.1\tAGCACGAGCCTA\tSampleFieldState1"]
self.tiny_field = 'SampleField'
self.small_dist_matrix_string = ["\tSamp.1\tSamp.2", "Samp.1\t0\t0.5",
"Samp.2\t0.5\t0"]
self.small_mapping_string = ["#SampleID\tBarcodeSequence\tSampleField",
"Samp.1\tAGCACGAGCCTA\tSampleFieldState1",
"Samp.2\tAGCACGAGCCTG\tSampleFieldState2"]
self.small_field = 'SampleField'
# Parse mapping "files" (faked here).
self.mapping, self.mapping_header, self.comments = parse_mapping_file(
self.mapping_string)
mapping_data = [self.mapping_header]
mapping_data.extend(self.mapping)
self.groups = group_by_field(mapping_data, self.field)
self.tiny_mapping, self.tiny_mapping_header, self.tiny_comments = \
parse_mapping_file(self.tiny_mapping_string)
tiny_mapping_data = [self.tiny_mapping_header]
tiny_mapping_data.extend(self.tiny_mapping)
self.tiny_groups = group_by_field(tiny_mapping_data, self.tiny_field)
self.small_mapping, self.small_mapping_header, self.small_comments = \
parse_mapping_file(self.small_mapping_string)
small_mapping_data = [self.small_mapping_header]
small_mapping_data.extend(self.small_mapping)
self.small_groups = group_by_field(small_mapping_data,
self.small_field)
# Parse distance matrix "files" (faked here).
self.dist_matrix_header, self.dist_matrix = parse_distmat(
self.dist_matrix_string)
self.tiny_dist_matrix_header, self.tiny_dist_matrix = parse_distmat(
self.tiny_dist_matrix_string)
self.small_dist_matrix_header, self.small_dist_matrix = parse_distmat(
self.small_dist_matrix_string)
def test_get_grouped_distances_within(self):
"""get_grouped_distances() should return a list of within distance
groupings."""
groupings = get_grouped_distances(self.dist_matrix_header,
self.dist_matrix, self.mapping_header, self.mapping,
self.field, within=True)
expected = [
('Control', 'Control', [0.625, 0.623, 0.60999999999999999, \
0.57699999999999996, 0.61499999999999999, \
0.64200000000000002, 0.67300000000000004, \
0.68200000000000005, 0.73699999999999999, \
0.70399999999999996]),
('Fast', 'Fast', [0.71799999999999997, 0.66600000000000004, \
0.72699999999999998, 0.59999999999999998, \
0.57799999999999996, 0.623])]
self.assertEqual(groupings, expected)
def test_get_grouped_distances_between(self):
"""get_grouped_distances() should return a list of between distance
groupings."""
groupings = get_grouped_distances(self.dist_matrix_header,
self.dist_matrix, self.mapping_header, self.mapping,
self.field, within=False)
expected = [
('Control', 'Fast', [0.72899999999999998, 0.80000000000000004, \
0.72099999999999997, 0.76500000000000001, \
0.77600000000000002, 0.74399999999999999, \
0.749, 0.67700000000000005, \
0.73399999999999999, 0.77700000000000002, \
0.73299999999999998, 0.72399999999999998, \
0.69599999999999995, 0.67500000000000004, \
0.65400000000000003, 0.69599999999999995, \
0.73099999999999998, 0.75800000000000001, \
0.73799999999999999, 0.73699999999999999])]
self.assertEqual(groupings, expected)
def test_get_all_grouped_distances_within(self):
"""get_all_grouped_distances() should return a list of distances for
all samples with the same field value."""
groupings = get_all_grouped_distances(self.dist_matrix_header,
self.dist_matrix, self.mapping_header, self.mapping,
self.field, within=True)
expected = [0.625, 0.623, 0.60999999999999999, 0.57699999999999996,
0.61499999999999999, 0.64200000000000002,
0.67300000000000004, 0.68200000000000005,
0.73699999999999999, 0.70399999999999996,
0.71799999999999997, 0.66600000000000004,
0.72699999999999998, 0.59999999999999998,
0.57799999999999996, 0.623]
self.assertEqual(groupings, expected)
def test_get_all_grouped_distances_between(self):
"""get_all_grouped_distances() should return a list of distances
between samples of all different field values."""
groupings = get_all_grouped_distances(self.dist_matrix_header,
self.dist_matrix, self.mapping_header, self.mapping,
self.field, within=False)
expected = [0.72899999999999998, 0.80000000000000004,
0.72099999999999997, 0.76500000000000001,
0.77600000000000002, 0.74399999999999999, 0.749,
0.67700000000000005, 0.73399999999999999,
0.77700000000000002, 0.73299999999999998,
0.72399999999999998, 0.69599999999999995,
0.67500000000000004, 0.65400000000000003,
0.69599999999999995, 0.73099999999999998,
0.75800000000000001, 0.73799999999999999,
0.73699999999999999]
self.assertEqual(groupings, expected)
def test_get_field_state_comparisons(self):
"""get_field_state_comparisons() should return a 2D dictionary of
distances between a field state and its comparison field states."""
comparison_groupings = get_field_state_comparisons(
self.dist_matrix_header, self.dist_matrix, self.mapping_header,
self.mapping, self.field, ['Control'])
expected = {'Fast': {'Control': [0.72899999999999998,
0.80000000000000004, 0.72099999999999997, 0.76500000000000001,
0.77600000000000002, 0.74399999999999999, 0.749,
0.67700000000000005, 0.73399999999999999, 0.77700000000000002,
0.73299999999999998, 0.72399999999999998, 0.69599999999999995,
0.67500000000000004, 0.65400000000000003, 0.69599999999999995,
0.73099999999999998, 0.75800000000000001, 0.73799999999999999,
0.73699999999999999]}}
self.assertFloatEqual(comparison_groupings, expected)
comparison_groupings = get_field_state_comparisons(
self.dist_matrix_header, self.dist_matrix, self.mapping_header,
self.mapping, self.field, ['Fast'])
expected = {'Control': {'Fast': [0.72899999999999998,
0.80000000000000004, 0.72099999999999997, 0.76500000000000001,
0.77600000000000002, 0.74399999999999999, 0.749,
0.67700000000000005, 0.73399999999999999, 0.77700000000000002,
0.73299999999999998, 0.72399999999999998, 0.69599999999999995,
0.67500000000000004, 0.65400000000000003, 0.69599999999999995,
0.73099999999999998, 0.75800000000000001, 0.73799999999999999,
0.73699999999999999]}}
self.assertFloatEqual(comparison_groupings, expected)
def test_get_field_state_comparisons_small(self):
"""get_field_state_comparisons() should return a 2D dictionary of
distances between a field state and its comparison field states."""
comparison_groupings = get_field_state_comparisons(
self.small_dist_matrix_header, self.small_dist_matrix,
self.small_mapping_header, self.small_mapping,
self.small_field, ['SampleFieldState1'])
expected = {'SampleFieldState2': {'SampleFieldState1': [0.5]}}
self.assertFloatEqual(comparison_groupings, expected)
def test_get_field_state_comparisons_tiny(self):
"""get_field_state_comparisons() should return an empty dictionary."""
comparison_groupings = get_field_state_comparisons(
self.tiny_dist_matrix_header, self.tiny_dist_matrix,
self.tiny_mapping_header, self.tiny_mapping, self.tiny_field,
['SampleFieldState1'])
self.assertEqual(comparison_groupings, {})
def test_get_field_state_comparisons_no_comp_states(self):
"""get_field_state_comparisons() should raise a ValueError if no
comparison field states are provided."""
self.assertRaises(ValueError, get_field_state_comparisons,
self.dist_matrix_header, self.dist_matrix,
self.mapping_header, self.mapping, self.field,
[])
def test_get_field_state_comparisons_bad_comp_state(self):
"""get_field_state_comparisons() should raise a ValueError if a
non-existent comparison field state is provided."""
self.assertRaises(ValueError, get_field_state_comparisons,
self.dist_matrix_header, self.dist_matrix,
self.mapping_header, self.mapping, self.field,
['T0', 'Fast'])
self.assertRaises(ValueError, get_field_state_comparisons,
self.dist_matrix_header, self.dist_matrix,
self.mapping_header, self.mapping, self.field,
['Fast', 'T0'])
def test_validate_input_bad_input(self):
"""_validate_input() should raise ValueErrors on bad input."""
self.assertRaises(ValueError, _validate_input,
None, None, None, None, None)
self.assertRaises(ValueError, _validate_input,
self.dist_matrix_header, self.dist_matrix,
self.mapping_header, self.mapping, None)
self.assertRaises(ValueError, _validate_input,
self.dist_matrix_header, 12,
self.mapping_header, self.mapping, None)
self.assertRaises(ValueError, _validate_input,
self.dist_matrix_header, self.dist_matrix,
self.mapping_header, self.mapping, 42)
self.assertRaises(ValueError, _validate_input,
self.dist_matrix_header, self.dist_matrix,
self.mapping_header, self.mapping, "aeiou")
def test_validate_input_good_input(self):
"""_validate_input() should not raise any errors on good input."""
_validate_input(self.dist_matrix_header, self.dist_matrix,
self.mapping_header, self.mapping, "Treatment")
def test_get_indices_several_existing_items(self):
"""_get_indices() should return a list of valid indices for several
existing items."""
control_ids = ['PC.354', 'PC.355', 'PC.356', 'PC.481', 'PC.593']
exp_control_indices = [0,1,2,3,4]
fast_ids = ['PC.607', 'PC.634', 'PC.635', 'PC.636']
exp_fast_indices = [5,6,7,8]
obs_control = _get_indices(self.dist_matrix_header, control_ids)
self.assertEqual(obs_control, exp_control_indices)
obs_fast = _get_indices(self.dist_matrix_header, fast_ids)
self.assertEqual(obs_fast, exp_fast_indices)
def test_get_indices_one_existing_item_list(self):
"""_get_indices() should return a list of size 1 for a single item in a
list that exists in the search list."""
item_to_find = ['PC.355']
self.assertEqual(_get_indices(self.dist_matrix_header, item_to_find),
[1])
def test_get_indices_one_existing_item_scalar(self):
"""_get_indices() should return a list of size 1 for a single item that
exists in the search list."""
item_to_find = 'PC.355'
self.assertEqual(_get_indices(self.dist_matrix_header, item_to_find),
[1])
def test_get_indices_no_existing_item(self):
"""_get_indices() should return an empty list if no items exist in the
search list."""
item_to_find = 'PC.4242'
self.assertEqual(_get_indices(self.dist_matrix_header, item_to_find),
[])
item_to_find = 42
self.assertEqual(_get_indices(self.dist_matrix_header, item_to_find),
[])
item_to_find = ['PC.4242', 'CP.2424']
self.assertEqual(_get_indices(self.dist_matrix_header, item_to_find),
[])
item_to_find = ['PC.4242', 'CP.2424', 56]
self.assertEqual(_get_indices(self.dist_matrix_header, item_to_find),
[])
def test_get_indices_no_items_to_search(self):
"""_get_indices() should return an empty list if no search items are
given."""
item_to_find = []
self.assertEqual(_get_indices(self.dist_matrix_header, item_to_find),
[])
item_to_find = ''
self.assertEqual(_get_indices(self.dist_matrix_header, item_to_find),
[])
item_to_find = None
self.assertEqual(_get_indices(self.dist_matrix_header, item_to_find),
[])
def test_get_indices_null_or_empty_search_list(self):
"""_get_indices() should throw an error if the search list is None, and
return an empty list if the search list is empty."""
search_list = None
self.assertRaises(ValueError, _get_indices, search_list, 'item')
search_list = []
self.assertEqual(_get_indices(search_list, 'item'), [])
search_list = ''
self.assertEqual(_get_indices(search_list, 'item'), [])
def test_get_groupings_no_field_states(self):
"""_get_groupings() should return an empty list if there are no field
states in the groupings dictionary."""
self.assertEqual(_get_groupings(self.dist_matrix_header,
self.dist_matrix, {}, within=True), [])
self.assertEqual(_get_groupings(self.dist_matrix_header,
self.dist_matrix, {}, within=False), [])
def test_get_groupings_within_tiny_dataset(self):
"""_get_groupings() should return an empty list for a single-sample
dataset as the diagonal is omitted for within distances."""
self.assertEqual(_get_groupings(self.tiny_dist_matrix_header,
self.tiny_dist_matrix, self.tiny_groups, within=True), [])
def test_get_groupings_between_tiny_dataset(self):
"""_get_groupings() should return an empty list for a single-sample
dataset as there is only one field state, so no between distances can
be computed."""
self.assertEqual(_get_groupings(self.tiny_dist_matrix_header,
self.tiny_dist_matrix, self.tiny_groups, within=False), [])
if __name__ == '__main__':
main()
|
