def test_filter_table(self):
# prior to filtering there are observations with count less than 10
self.assertTrue(np.array([e.sum() < 10
for e in self.table3.iter_data(axis='observation')]).any())
filtered_table = filter_table(self.table3, min_count=10,
taxonomy_level=0)
# after filtering there are no observations with count less than 10
self.assertFalse(np.array([e.sum() < 10
for e in filtered_table.iter_data(axis='observation')]).any())
# but some observations are still present
self.assertTrue(filtered_table.shape[0] > 0)
self.assertTrue(np.array([e.sum() < 100
for e in self.table3.iter_data(axis='observation')]).any())
filtered_table = filter_table(self.table3, min_count=100,
taxonomy_level=0)
self.assertFalse(np.array([e.sum() < 100
for e in filtered_table.iter_data(axis='observation')]).any())
# but some observations are still present
self.assertTrue(filtered_table.shape[0] > 0)
# prior to filtering, there are taxonomies with fewer than 4 levels
md_levels = [len(md['taxonomy']) < 4
for _, _, md in self.table3.iter(axis='observation')]
self.assertTrue(np.array(md_levels).any())
filtered_table = filter_table(self.table3, min_count=0,
taxonomy_level=4)
# after filtering, there are no taxonomies with fewer than 4 levels
md_levels = [len(md['taxonomy']) < 4
for _, _, md in filtered_table.iter(axis='observation')]
self.assertFalse(np.array(md_levels).any())
# but some observations are still present
self.assertTrue(filtered_table.shape[0] > 0)
md_levels = [len(md['taxonomy']) < 5
for _, _, md in self.table3.iter(axis='observation')]
self.assertTrue(np.array(md_levels).any())
filtered_table = filter_table(self.table3, min_count=0,
taxonomy_level=5)
md_levels = [len(md['taxonomy']) < 5
for _, _, md in filtered_table.iter(axis='observation')]
self.assertFalse(np.array(md_levels).any())
# but some observations are still present
self.assertTrue(filtered_table.shape[0] > 0)
md_levels = [len(md['taxonomy']) < 6
for _, _, md in self.table3.iter(axis='observation')]
self.assertTrue(np.array(md_levels).any())
filtered_table = filter_table(self.table3, min_count=0,
taxonomy_level=6)
md_levels = [len(md['taxonomy']) < 6
for _, _, md in filtered_table.iter(axis='observation')]
self.assertFalse(np.array(md_levels).any())
# but some observations are still present
self.assertTrue(filtered_table.shape[0] > 0)
def test_filter_table_taxa(self):
""" taxa-based filtering works as expected """
taxa_to_keep= ["k__Bacteria", "p__Firmicutes", "c__Bacilli"]
filtered_table = filter_table(self.table3, taxa_to_keep=taxa_to_keep)
# expected value determined with grep -c c__Bacilli
self.assertEqual(filtered_table.shape[0], 53)
taxa_to_keep= ["k__Bacteria", "p__Firmicutes", "c__Bacilli",
"o__Bacillales", "f__Staphylococcaceae",
"g__Staphylococcus"]
filtered_table = filter_table(self.table3, taxa_to_keep=taxa_to_keep)
# expected value determined with grep -c g__Staphylococcus
self.assertEqual(filtered_table.shape[0], 8)
taxa_to_keep= ["k__Bacteria"]
filtered_table = filter_table(self.table3, taxa_to_keep=taxa_to_keep)
# all observations are retained
self.assertEqual(filtered_table.shape[0], self.table3.shape[0])
taxa_to_keep= ["k__Archaea"]
filtered_table = filter_table(self.table3, taxa_to_keep=taxa_to_keep)
# no observations are retained
self.assertEqual(filtered_table.shape[0], 0)
