def testDrawMiniAlignmentMarkUp(self):
self.alignment, self.names = readMSA("./tests/test_files/example1.fasta")
self.dest = "./tests/test_files/test_mini_markup.png"
self.legend = "./tests/test_files/test_mini_markup_legend.png"
expected = image.imread('./tests/test_files/expected_mini_ali_markup.png')
markup_dict = {'remove_divergent': {'Seq1'},
'remove_gaponly': {89, 90, 91, 92, 93, 94, 95},
'remove_insertions': {22, 23, 24, 25, 26, 27},
'crop_ends': {'Seq5': ((np.array([]), np.array([92, 93, 94, 95])))},
'remove_short': {'Seq6'}}
logger = logging.getLogger('path.to.module.under.test')
with mock.patch.object(logger, 'debug') as mock_debug:
miniAlignments.drawMiniAlignment(self.alignment, self.names,
logger, self.dest,
'nt', 300, None, 5, 3,
True, markup_dict, False)
mini_alignment = image.imread(self.dest)
# added a bit of leeway to allow for images created on different
# machines - they are visually identical but have minor differences
# in rendering - look for 95% structural similarity
simi = skimage.metrics.structural_similarity(expected,
mini_alignment,
multichannel=True)
self.assertTrue(simi > 0.9)
def testRemoveShort(self, min_length, expected):
exp_array, names = readMSA(expected)
logger = logging.getLogger('path.to.module.under.test')
with mock.patch.object(logger, 'debug') as mock_debug:
result_ali, r = parsingFunctions.removeTooShort(self.in_array, self.nams, self.rm_file, mock_debug, min_length)
self.assertTrue((result_ali == exp_array).all())
self.assertGreaterEqual(len(self.in_array), len(result_ali))
def testRemoveGapOnly(self):
expected = "./tests/test_files/remove_gaponly_cleaned.fasta"
exp_array, names = readMSA(expected)
logger = logging.getLogger('path.to.module.under.test')
with mock.patch.object(logger, 'debug') as mock_debug:
result_ali, r, self.relativePositions = parsingFunctions.removeGapOnly(self.in_array, self.relativePositions, self.rm_file, mock_debug)
self.assertTrue((result_ali == exp_array).all())
self.assertEqual(len(self.in_array), len(result_ali))
def testCropEnds(self, mingap, redefine_perc, expected):
exp_array, names = readMSA(expected)
logger = logging.getLogger('path.to.module.under.test')
with mock.patch.object(logger, 'debug') as mock_debug:
result_ali, names = parsingFunctions.cropEnds(self.in_array, self.nams, self.relativePositions, self.rm_file, mock_debug, mingap, redefine_perc)
self.assertEqual(result_ali[0,:].size, exp_array[0,:].size)
self.assertEqual(len(self.in_array), len(result_ali))
self.assertTrue((result_ali == exp_array).all())
def testRemoveInsertions(self, min_size, max_size, min_flank, expected):
exp_array, names = readMSA(expected)
logger = logging.getLogger('path.to.module.under.test')
with mock.patch.object(logger, 'debug') as mock_debug:
result_ali, r, self.relativePositions = parsingFunctions.removeInsertions(self.in_array, self.relativePositions, self.rm_file, mock_debug, min_size, max_size, min_flank)
# check if dimensions are equal first
self.assertEqual(result_ali[0,:].size, exp_array[0,:].size)
self.assertEqual(len(self.in_array), len(result_ali))
self.assertTrue((result_ali == exp_array).all())
def testFindConsensus(self, MSA, type, expected_consensus,
expected_coverage):
alignment, names = readMSA(MSA)
logger = logging.getLogger('path.to.module.under.test')
with mock.patch.object(logger, 'debug') as mock_debug:
consensus, coverage = consensusSeq.findConsensus(
alignment, logger, type)
coverage_rounded = [round(num, 2) for num in coverage]
self.assertEqual(consensus, expected_consensus)
self.assertEqual(coverage_rounded, expected_coverage)
def testRemoveDivergent(self, percidentity, expected):
exp_array, names = readMSA(expected)
logger = logging.getLogger('path.to.module.under.test')
with mock.patch.object(logger, 'debug') as mock_debug:
result_ali, r = parsingFunctions.removeDivergent(self.in_array, self.nams, self.rm_file, mock_debug, percidentity)
self.assertEqual(result_ali[0,:].size, exp_array[0,:].size)
self.assertEqual(result_ali[:,0].size, exp_array[:,0].size)
self.assertGreaterEqual(len(self.in_array), len(result_ali))
self.assertTrue((result_ali == exp_array).all())
def testArrNumeric(self):
alignment, names = readMSA("./tests/test_files/consensus_example_nt.fasta")
arr_expected = [[1, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 0, 4, 2, 4, 3],
[1, 1, 1, 3, 3, 3, 3, 3, 3, 4, 4, 0, 4, 2, 4, 2],
[1, 1, 1, 3, 3, 3, 3, 3, 3, 4, 4, 0, 0, 1, 2, 4],
[1, 1, 1, 2, 4, 2, 4, 4, 0, 4, 4, 0, 4, 2, 4, 2],
[4, 2, 1, 3, 3, 3, 3, 3, 3, 4, 4, 0, 4, 2, 4, 2],
[2, 4, 0, 3, 3, 3, 3, 3, 3, 4, 2, 1, 2, 4, 0, 2],]
arr_int, colour_map = miniAlignments.arrNumeric(alignment,'nt')
self.assertTrue((arr_int == arr_expected).all())
def setUp(self):
self.dest = "./tests/test_files/test_mini.png"
self.alignment, self.names = readMSA("./tests/test_files/example1.fasta")
self.ali_width = len(self.alignment[0])
self.ali_height = len(self.alignment)
self.markup_dict = {'remove_divergent': {'Seq1'},
'remove_gaponly': {89, 90, 91, 92, 93, 94, 95},
'remove_insertions': {22, 23, 24, 25, 26, 27},
'crop_ends': {'Seq5': ((np.array([]), np.array([92, 93, 94, 95])))},
'remove_short': {'Seq6'}}
logger = logging.getLogger('path.to.module.under.test')
with mock.patch.object(logger, 'debug') as mock_debug:
# make mini plot without markup
self.mini_plot = miniAlignments.drawMiniAlignment(self.alignment, self.names, logger, self.dest,
'nt', 300, None, 5, 3,
False, None, True)
# make mini plot with markup
self.mini_plot_expected = miniAlignments.drawMiniAlignment(self.alignment, self.names, logger, self.dest,
'nt', 300, None, 5, 3,
True, self.markup_dict, True)
def testDrawMiniAlignment(self, input, expected, type):
self.alignment, self.names = readMSA(input)
self.dest = "./tests/test_files/test_mini.png"
self.legend = ""
expected = image.imread(expected)
logger = logging.getLogger('path.to.module.under.test')
with mock.patch.object(logger, 'debug') as mock_debug:
miniAlignments.drawMiniAlignment(self.alignment, self.names, logger, self.dest,
type, 300, None, 5, 3,
False, None, False)
mini_alignment = image.imread(self.dest)
# added a bit of leeway to allow for images created on different
# machines - they are visually identical but have minor differences
# in rendering - look for 95% structural similarity
simi = skimage.metrics.structural_similarity(expected,
mini_alignment,
multichannel=True)
self.assertTrue(simi > 0.9)
def testMakeCoveragePlot(self):
alignment, names = readMSA(
"./tests/test_files/consensus_example_aa.fasta")
consensusSeq.sequence_bar_logo(alignment, self.dest, 'aa')
self.assertTrue(os.path.isfile(self.dest))
def setUp(self):
self.in_array, self.nams = readMSA("./tests/test_files/example1.fasta")
self.relativePositions = list(range(0, len(self.in_array[0])))
self.rm_file = 'mock_rmfile.txt'
def testSeqType(self, input, expected):
in_array, names = readMSA(input)
type = utilityFunctions.seqType(in_array)
self.assertEqual(type, expected)
def setUp(self):
self.input = "./tests/test_files/example1.fasta"
self.in_array, self.nams = readMSA(self.input)
self.removed = set()
self.outfile = "writeOutfile_test.txt"
def setUp(self):
self.input = "./tests/test_files/example1.fasta"
self.in_array, self.nams = readMSA(self.input)
def setUp(self):
self.in_array, self.nams = readMSA(
"./tests/test_files/remove_gaponly_cleaned.fasta")