def test_gesamt_radius(self):
# Test we can reproduce the original thresholds
gesamt_exe = ample_util.find_exe("gesamt" + ample_util.EXE_EXT)
clusterer = subcluster.GesamtClusterer(executable=gesamt_exe)
pdb_list = glob.glob(
os.path.join(self.testfiles_dir, "models", '*.pdb'))
radius = 4
clusterer.generate_distance_matrix(pdb_list, purge=True)
cluster_files1 = set(
[os.path.basename(x) for x in clusterer.cluster_by_radius(radius)])
ref = set([
'1_S_00000002.pdb',
'1_S_00000004.pdb',
'1_S_00000005.pdb',
'2_S_00000001.pdb',
'2_S_00000005.pdb',
'3_S_00000003.pdb',
'3_S_00000004.pdb',
'3_S_00000006.pdb',
'4_S_00000002.pdb',
'4_S_00000005.pdb',
'5_S_00000004.pdb',
'5_S_00000005.pdb',
])
# clusterer.dump_pdb_matrix('foo')
self.assertEqual(0, len(ref - cluster_files1))
return
def subclusterer_factory(self, subcluster_program):
"""Return an instantiated subclusterer based on the given program"""
if subcluster_program == 'gesamt':
clusterer = subcluster.GesamtClusterer(self.gesamt_exe, nproc=self.nproc)
elif subcluster_program == 'lsqkab':
clusterer = subcluster.LsqkabClusterer(self.lsqkab_exe)
else:
raise RuntimeError("Unrecognised subcluster_program: {0}".format(subcluster_program))
return clusterer
def test_gesamt_matrix_generic(self):
# Test we can reproduce the original thresholds
gesamt_exe = ample_util.find_exe("gesamt" + ample_util.EXE_EXT)
clusterer = subcluster.GesamtClusterer(executable=gesamt_exe)
pdb_list = sorted(
glob.glob(os.path.join(self.testfiles_dir, "models", '*.pdb')))
clusterer._generate_distance_matrix_generic(pdb_list, purge_all=True)
# Test two files manually
index1 = 2
index2 = 25
f1 = pdb_list[index1]
f2 = pdb_list[index2]
# Run gesamt to get the score between the two
logfile = 'gesamt.log'
ample_util.run_command([gesamt_exe, f1, f2], logfile=logfile)
qscore = None
with open(logfile) as f:
for l in f.readlines():
if l.startswith(' Q-score'):
qscore = float(l.split()[2])
self.assertIsNotNone(qscore, "No q-score found")
# read score matrix
matrix = []
with open(subcluster.SCORE_MATRIX_NAME) as f:
for l in f.readlines():
if not l.strip():
continue
fields = l.split()
matrix.append(
(int(fields[0]), int(fields[1]), float(fields[2])))
# Make sure the score matches
for l in matrix:
if l[0] == index1 and l[1] == index2:
# Gesamt log and out file formats have different precisions
self.assertAlmostEqual(
l[2], qscore, 3,
"Q-scores differ: {0} - {1}".format(l[2], qscore))
os.unlink(logfile)
os.unlink(subcluster.SCORE_MATRIX_NAME)
os.unlink(subcluster.FILE_LIST_NAME)
return