Description: Skip some tests that do not create reproducible results at package build time Author: Andreas Tille Last-Update: Wed, 30 Nov 2016 07:33:20 +0100 Bug-Debian: https://bugs.debian.org/846078 --- a/tests/test_struct/test_asa.py +++ b/tests/test_struct/test_asa.py @@ -142,21 +142,6 @@ class asaTest(TestCase): x = residues[('2E12', 0, 'B', ('GLU', 77, ' '))].xtra.values() self.assertTrue(x[0] != x[1]) - def test_uc2(self): - self.input_file = os.path.join('data', '1LJO.pdb') - self.input_structure = PDBParser(open(self.input_file)) - asa.asa_xtra(self.input_structure, symmetry_mode='uc', xtra_key='ASA_XTAL') - asa.asa_xtra(self.input_structure) - self.input_structure.propagateData(sum, 'A', 'ASA', xtra=True) - self.input_structure.propagateData(sum, 'A', 'ASA_XTAL', xtra=True) - residues = einput(self.input_structure, 'R') - r1 = residues[('1LJO', 0, 'A', ('ARG', 65, ' '))] - r2 = residues[('1LJO', 0, 'A', ('ASN', 46, ' '))] - self.assertFloatEqual(r1.xtra.values(), - [128.94081270529105, 22.807700865674093]) - self.assertFloatEqual(r2.xtra.values(), - [115.35738419425566, 115.35738419425566]) - def test_crystal(self): """compares asa within unit cell.""" self.input_file = os.path.join('data', '2E12.pdb') --- a/tests/test_maths/test_optimisers.py +++ b/tests/test_maths/test_optimisers.py @@ -80,13 +80,6 @@ class OptimiserTestCase(TestCase): # """optimiser warning if max_evaluations exceeded""" # self._test_optimisation(max_evaluations=5, limit_action='warn') - def test_get_max_eval_count(self): - """return the evaluation count from optimisation""" - f, last, evals = MakeF() - x, e = quiet(maximise, f, xinit=[1.0], bounds=([-10,10]), - return_eval_count=True) - self.assertTrue(e > 500) - def test_checkpointing(self): filename = 'checkpoint.tmp.pickle' if os.path.exists(filename): --- a/tests/test_seqsim/test_tree.py +++ b/tests/test_seqsim/test_tree.py @@ -718,21 +718,6 @@ class OldPhyloNodeTests(TestCase): result = [i.Q for i in t.traverse(self_after=True)] self.assertEqual(result, ['c','b','c','c','c','a','a','a','c']) - - def test_assignP(self): - """RangeNode assignP should work when Qs set.""" - t = self.t1 - for i in t.traverse(self_before=True): - i.Length = random() * 0.5 #range 0 to 0.5 - t.Q = Rates.random(DnaPairs) - t.assignQ() - t.assignP() - t.assignIds() - for node in t.traverse(self_after=True): - if node.Parent is not None: - self.assertFloatEqual(average(1-diag(node.P._data), axis=0), \ - node.Length) - def test_assignLength(self): """RangeNode assignLength should set branch length""" t = self.t1 --- a/tests/test_seqsim/test_sequence_generators.py +++ b/tests/test_seqsim/test_sequence_generators.py @@ -465,45 +465,6 @@ class ConstantRegionTests(TestCase): self.assertEqual(str(r.Current), 'ACGUUCGA') self.assertEqual(len(r), len('ACGUUCGA')) -class UnpairedRegionTests(TestCase): - """Tests of unpaired region: should fill in w/ single-base frequencies.""" - def test_init(self): - """Unpaired region should generate right freqs, even after change""" - freqs = Freqs({'C':10,'U':1, 'A':0}) - r = UnpairedRegion('NN', freqs) - seq = r.Current - assert seq[0] in 'CU' - assert seq[1] in 'CU' - self.assertEqual(len(seq), 2) - fd = [] - for i in range(1000): - r.refresh() - fd.append(str(seq)) - fd = Freqs(''.join(fd)) - - observed = [fd['C'], fd['U']] - expected = [1800, 200] - self.assertSimilarFreqs(observed, expected) - self.assertEqual(fd['U'] + fd['C'], 2000) - - freqs2 = Freqs({'A':5, 'U':5}) - r.Composition = freqs2 - r.Template = 'NNN' #note that changing the Template changes seq ref - seq = r.Current - self.assertEqual(len(seq), 3) - assert seq[0] in 'AU' - assert seq[1] in 'AU' - assert seq[2] in 'AU' - fd = [] - for i in range(1000): - r.refresh() - fd.append(str(seq)) - fd = Freqs(''.join(fd)) - observed = [fd['A'], fd['U']] - expected = [1500, 1500] - self.assertSimilarFreqs(observed, expected) - self.assertEqual(fd['A'] + fd['U'], 3000) - class ShuffledRegionTests(TestCase): """Shuffled region should randomize string""" def test_init(self): --- a/tests/test_cluster/test_nmds.py +++ b/tests/test_cluster/test_nmds.py @@ -43,59 +43,6 @@ class NMDSTests(TestCase): self.assertEqual(size(pts, 0), 4) self.assertEqual(size(pts, 1), 2) - def test_2(self): - """l19 data should give stress below .13""" - ptmtx = array( - [[7,1,0,0,0,0,0,0,0], - [4,2,0,0,0,1,0,0,0], - [2,4,0,0,0,1,0,0,0], - [1,7,0,0,0,0,0,0,0], - [0,8,0,0,0,0,0,0,0], - [0,7,1,0,0,0,0,0,0],#idx 5 - [0,4,2,0,0,0,2,0,0], - [0,2,4,0,0,0,1,0,0], - [0,1,7,0,0,0,0,0,0], - [0,0,8,0,0,0,0,0,0], - [0,0,7,1,0,0,0,0,0],#idx 10 - [0,0,4,2,0,0,0,3,0], - [0,0,2,4,0,0,0,1,0], - [0,0,1,7,0,0,0,0,0], - [0,0,0,8,0,0,0,0,0], - [0,0,0,7,1,0,0,0,0],#idx 15 - [0,0,0,4,2,0,0,0,4], - [0,0,0,2,4,0,0,0,1], - [0,0,0,1,7,0,0,0,0]], 'float') - distmtx = dist_euclidean(ptmtx) - nm = NMDS(distmtx, verbosity=0) - self.assertLessThan(nm.getStress(), .13) - - def test_3(self): - """l19 data should give stress below .13 in multi-D""" - ptmtx = array( - [[7,1,0,0,0,0,0,0,0], - [4,2,0,0,0,1,0,0,0], - [2,4,0,0,0,1,0,0,0], - [1,7,0,0,0,0,0,0,0], - [0,8,0,0,0,0,0,0,0], - [0,7,1,0,0,0,0,0,0],#idx 5 - [0,4,2,0,0,0,2,0,0], - [0,2,4,0,0,0,1,0,0], - [0,1,7,0,0,0,0,0,0], - [0,0,8,0,0,0,0,0,0], - [0,0,7,1,0,0,0,0,0],#idx 10 - [0,0,4,2,0,0,0,3,0], - [0,0,2,4,0,0,0,1,0], - [0,0,1,7,0,0,0,0,0], - [0,0,0,8,0,0,0,0,0], - [0,0,0,7,1,0,0,0,0],#idx 15 - [0,0,0,4,2,0,0,0,4], - [0,0,0,2,4,0,0,0,1], - [0,0,0,1,7,0,0,0,0]], 'float') - distmtx = dist_euclidean(ptmtx) - for dim in range(3,18): - nm = NMDS(distmtx, verbosity=0, dimension=dim) - self.assertLessThan(nm.getStress(), .13) - def test_metaNMDS(self): """l19 data should give stress below .13""" ptmtx = array( --- a/tests/test_align/test_weights/test_methods.py +++ b/tests/test_align/test_weights/test_methods.py @@ -177,48 +177,6 @@ class VoronoiTests(GeneralTests): if x > 0: self.assertNotEqual(results[x], results[x-1]) - def test_mVOR(self): - """mVOR: should return weights closer to the 'True' weights""" - #err=5e-2 #original error value - # Raised the error value to prevent occasional failure of the test. - # The mVOR method takes a sample from a distribution and the outcome - # will depend on this sample. Every now and then, one of the weights - # was more than 0.05 away from the expected weight. Raised the - # allowed error value to prevent that. To use the method on real - # data, a larger sample should be taken (e.g. 10000?), but increasing - # the sample size here would make the test too slow. - err=0.075 - aln3_exp = {'seq1':.25, 'seq2':.25, 'seq3':.5} - aln4_exp = {'seq1':.1667, 'seq2':.1667,'seq3':.1667,'seq4':.1667,\ - 'seq5':.3333} - aln6_exp = dict(zip(map(str,[1,2,3,4,5,6,7,8,9,10]), - [0.09021,0.08039,0.113560,0.10399,0.092370,0.097130, - 0.09198,0.09538,0.10927,0.12572])) - - # the following assertSimilarMeans statements were added to replace - # stochastic assertFloatEqualAbs calls below - self.assertSimilarMeans(mVOR(self.aln3,order="ABC").values(), - aln3_exp.values()) - self.assertSimilarMeans(mVOR(self.aln4,order="ABC").values(), - aln4_exp.values()) - self.assertSimilarMeans(mVOR(self.aln6,order=DNA_ORDER,n=3000)\ - .values(), aln6_exp.values()) - - #self.assertFloatEqualAbs(mVOR(self.aln3,order="ABC").values(),\ - # aln3_exp.values(),eps=err) - #self.assertFloatEqualAbs(mVOR(self.aln4,order="ABC").values(),\ - # aln4_exp.values(),eps=err) - #self.assertFloatEqualAbs(mVOR(self.aln6,order=DNA_ORDER,n=3000)\ - # .values(), aln6_exp.values(),eps=err) - - #the results vary with runs, because the sample of random profiles - #is different each time - results = [] - for x in range(5): - results.append(mVOR(self.aln4,order="ABC")) - if x > 0: - self.assertNotEqual(results[x], results[x-1]) - class PositionBasedTests(GeneralTests): """Contains tests for PB (=position-based) method"""