def test_assign_taxonomy_file_output(self):
""" assign_taxonomy wrapper writes correct file output when requested
This function tests for sucessful completion of assign_taxonomy
when writing to file, that the lines in the file roughly look
correct by verifying how many are written (by zipping with
expected), and that each line starts with the correct seq id.
Actual testing of taxonomy data is performed elsewhere.
"""
output_fp = get_tmp_filename(\
prefix='RDPAssignTaxonomyTests',suffix='.txt')
# convert the expected dict to a list of lines to match
# file output
expected_file_headers = self.expected_assignments1.keys()
expected_file_headers.sort()
actual_return_value = assign_taxonomy(\
self.test_input1,min_confidence=0.95,output_fp=output_fp)
actual_file_output = list(open(output_fp))
actual_file_output.sort()
# remove the output_fp before running the tests, so if they
# fail the output file is still cleaned-up
remove(output_fp)
# None return value on write to file
self.assertEqual(actual_return_value, None)
# check that each line starts with the correct seq_id -- not
# checking the taxonomies or confidences here as these are variable and
# tested elsewhere
for a, e in zip(actual_file_output, expected_file_headers):
self.assertTrue(a.startswith(e))
def test_assign_taxonomy_file_output(self):
""" assign_taxonomy wrapper writes correct file output when requested
This function tests for sucessful completion of assign_taxonomy
when writing to file, that the lines in the file roughly look
correct by verifying how many are written (by zipping with
expected), and that each line starts with the correct seq id.
Actual testing of taxonomy data is performed elsewhere.
"""
output_fp = get_tmp_filename(\
prefix='RDPAssignTaxonomyTests',suffix='.txt')
# convert the expected dict to a list of lines to match
# file output
expected_file_headers = self.expected_assignments1.keys()
expected_file_headers.sort()
actual_return_value = assign_taxonomy(\
self.test_input1,min_confidence=0.95,output_fp=output_fp)
actual_file_output = list(open(output_fp))
actual_file_output.sort()
# remove the output_fp before running the tests, so if they
# fail the output file is still cleaned-up
remove(output_fp)
# None return value on write to file
self.assertEqual(actual_return_value,None)
# check that each line starts with the correct seq_id -- not
# checking the taxonomies or confidences here as these are variable and
# tested elsewhere
for a,e in zip(actual_file_output,expected_file_headers):
self.assertTrue(a.startswith(e))
def test_assign_taxonomy_short_sequence(self):
"""assign_taxonomy should return Unclassifiable if sequence is too short
"""
assignments = assign_taxonomy([
'>MySeq 1',
'TTCCGGTTGATCCTGCCGGACCCGACTGCTATCCGGA',
])
self.assertEqual(assignments, {'MySeq 1': ('Unassignable', 1.0)})
def test_assign_taxonomy_short_sequence(self):
"""assign_taxonomy should return Unclassifiable if sequence is too short
"""
assignments = assign_taxonomy([
'>MySeq 1',
'TTCCGGTTGATCCTGCCGGACCCGACTGCTATCCGGA',
])
self.assertEqual(assignments, {'MySeq 1': ('Unassignable', 1.0)})
def test_assign_taxonomy(self):
"""assign_taxonomy wrapper functions as expected
This test may fail periodicially, but failure should be rare.
"""
# convert the expected dict to a list, so it's easier to
# handle the order
expected_assignments = \
[(k,v[0],v[1]) for k,v in self.expected_assignments1.items()]
expected_assignments.sort()
# Because there is some variation in the taxon assignments,
# I run the test several times (which can be quite slow) and
# each sequence was classified the same as expected at least once
taxon_assignment_results = [False] * len(expected_assignments)
all_assigned_correctly = False
for i in range(10):
actual_assignments = assign_taxonomy(self.test_input1)
# covert actual_assignments to a list so it's easier to handle
# the order
actual_assignments = \
[(k,v[0],v[1]) for k,v in actual_assignments.items()]
actual_assignments.sort()
for j in range(len(expected_assignments)):
a = actual_assignments[j]
e = expected_assignments[j]
# same description fields
self.assertEqual(a[0], e[0])
# same taxonomic assignment
r = a[1] == e[1]
if r and not taxon_assignment_results[j]:
taxon_assignment_results[j] = True
# confidence >= 0.80
self.assertTrue(a[2] >= 0.80)
if False not in taxon_assignment_results:
# all sequences have been correctly assigned at
# least once -- bail out
all_assigned_correctly = True
break
# make sure all taxonomic results were correct at least once
self.assertTrue(all_assigned_correctly)
def test_assign_taxonomy(self):
"""assign_taxonomy wrapper functions as expected
This test may fail periodicially, but failure should be rare.
"""
# convert the expected dict to a list, so it's easier to
# handle the order
expected_assignments = \
[(k,v[0],v[1]) for k,v in self.expected_assignments1.items()]
expected_assignments.sort()
# Because there is some variation in the taxon assignments,
# I run the test several times (which can be quite slow) and
# each sequence was classified the same as expected at least once
taxon_assignment_results = [False] * len(expected_assignments)
all_assigned_correctly = False
for i in range(10):
actual_assignments = assign_taxonomy(self.test_input1)
# covert actual_assignments to a list so it's easier to handle
# the order
actual_assignments = \
[(k,v[0],v[1]) for k,v in actual_assignments.items()]
actual_assignments.sort()
for j in range(len(expected_assignments)):
a = actual_assignments[j]
e = expected_assignments[j]
# same description fields
self.assertEqual(a[0],e[0])
# same taxonomic assignment
r = a[1] == e[1]
if r and not taxon_assignment_results[j]:
taxon_assignment_results[j] = True
# confidence >= 0.80
self.assertTrue(a[2]>=0.80)
if False not in taxon_assignment_results:
# all sequences have been correctly assigned at
# least once -- bail out
all_assigned_correctly = True
break
# make sure all taxonomic results were correct at least once
self.assertTrue(all_assigned_correctly)
def test_assign_taxonomy_alt_confidence(self):
"""assign_taxonomy wrapper functions as expected with alt confidence
"""
actual_assignments = \
assign_taxonomy(self.test_input1,min_confidence=0.95)
# covert actual_assignments to a list so it's easier to handle
# the order
actual_assignments = \
[(k,v[0],v[1]) for k,v in actual_assignments.items()]
actual_assignments.sort()
# convert the expected dict to a list, so it's easier to
# handle the order
expected_assignments = \
[(k,v[0],v[1]) for k,v in self.expected_assignments1.items()]
expected_assignments.sort()
for a, e in zip(actual_assignments, expected_assignments):
# same description fields
self.assertEqual(a[0], e[0])
# confidence >= 0.95
self.assertTrue(a[2] >= 0.95)
def test_assign_taxonomy_alt_confidence(self):
"""assign_taxonomy wrapper functions as expected with alt confidence
"""
actual_assignments = \
assign_taxonomy(self.test_input1,min_confidence=0.95)
# covert actual_assignments to a list so it's easier to handle
# the order
actual_assignments = \
[(k,v[0],v[1]) for k,v in actual_assignments.items()]
actual_assignments.sort()
# convert the expected dict to a list, so it's easier to
# handle the order
expected_assignments = \
[(k,v[0],v[1]) for k,v in self.expected_assignments1.items()]
expected_assignments.sort()
for a,e in zip(actual_assignments,expected_assignments):
# same description fields
self.assertEqual(a[0],e[0])
# confidence >= 0.95
self.assertTrue(a[2]>=0.95)