def testLoadPDB(self):
""" Check that we can load a pdb and convert it to a dict. """
# Setup path to pdb file.
pdb_path = generateTestFilePath("2nip.pdb")
self.__paths_to_remove.append('obsolete')
# Attempt to load it.
return_dict = IOUtilities.loadPDB(pdb_path)
# Check items on dict.
self.assertIsInstance( return_dict['Z'], numpy.ndarray )
self.assertIsInstance( return_dict['r'], numpy.ndarray )
self.assertIsInstance( return_dict['selZ'], dict )
self.assertIsInstance( return_dict['N'], int )
self.assertEqual( return_dict['Z'].shape, (4728,) )
self.assertEqual( return_dict['r'].shape, (4728,3) )
# Check that return type is a dict.
self.assertIsInstance( return_dict, dict )
# Check exception on wrong input type.
self.assertRaises( IOError, IOUtilities.loadPDB, [1,2] )
# Check exception on wrong file type.
self.assertRaises( IOError, IOUtilities.loadPDB, generateTestFilePath("sample.h5") )
def testLoadPDB(self):
""" Check that we can load a pdb and convert it to a dict. """
# Setup path to pdb file.
pdb_path = generateTestFilePath("2nip.pdb")
self.__paths_to_remove.append('obsolete')
# Attempt to load it.
return_dict = IOUtilities.loadPDB(pdb_path)
# Check items on dict.
self.assertIsInstance( return_dict['Z'], numpy.ndarray )
self.assertIsInstance( return_dict['r'], numpy.ndarray )
self.assertIsInstance( return_dict['selZ'], dict )
self.assertIsInstance( return_dict['N'], int )
self.assertEqual( return_dict['Z'].shape, (4728,) )
self.assertEqual( return_dict['r'].shape, (4728,3) )
# Check that return type is a dict.
self.assertIsInstance( return_dict, dict )
# Check exception on corrupt file.
# does not raise due to highly tolerant default acceptance levels in Bio.PDB.
#self.assertRaises( IOError, IOUtilities.loadPDB, generateTestFilePath("2nip_corrupt.pdb" ) )
# Check exception on wrong input type.
self.assertRaises( IOError, IOUtilities.loadPDB, [1,2] )
# Check exception on wrong file type.
self.assertRaises( IOError, IOUtilities.loadPDB, generateTestFilePath("sample.h5") )
def notestQueryPDB(self):
""" Check that we can query a non-existing pdb from pdb.org and convert it to a dict. """
# Setup path to pdb file.
pdb_path = '2nip.pdb'
self.__files_to_remove.append(pdb_path)
self.__paths_to_remove.append('obsolete')
# Attempt to load it.
return_dict = IOUtilities.loadPDB(pdb_path)
# Check items on dict.
self.assertIsInstance( return_dict['Z'], numpy.ndarray )
self.assertIsInstance( return_dict['r'], numpy.ndarray )
self.assertIsInstance( return_dict['selZ'], dict )
self.assertIsInstance( return_dict['N'], int )
self.assertEqual( return_dict['Z'].shape, (4728,) )
self.assertEqual( return_dict['r'].shape, (4728,3) )
# Check that return type is a dict.
self.assertIsInstance( return_dict, dict )
# Check exception on wrong input type.
self.assertRaises( IOError, IOUtilities.loadPDB, 'xyz.pdb' )
def testQueryPDBDirectory(self):
""" Check that if the pdb does not exist in the local database, it is queried from pdb.org, save in a dir, and convert it to a dict. """
# Setup path to pdb file.
pdb_path = 'pdb/2nip.pdb'
self.__files_to_remove.append(pdb_path)
self.__paths_to_remove.append('obsolete')
self.__paths_to_remove.append('pdb')
os.mkdir('pdb')
# Attempt to load it.
return_dict = IOUtilities.loadPDB(pdb_path)
# Check items on dict.
self.assertIsInstance( return_dict['Z'], numpy.ndarray )
self.assertIsInstance( return_dict['r'], numpy.ndarray )
self.assertIsInstance( return_dict['selZ'], dict )
self.assertIsInstance( return_dict['N'], int )
self.assertEqual( return_dict['Z'].shape, (4728,) )
self.assertEqual( return_dict['r'].shape, (4728,3) )
# Check that return type is a dict.
self.assertIsInstance( return_dict, dict )
def backengine(self):
""" This method drives the backengine code."""
status = 0
input_files = []
if os.path.isfile(self.input_path):
input_files = [self.input_path]
elif os.path.isdir(self.input_path):
input_files = [ os.path.join( self.input_path, f) for f in os.listdir( self.input_path ) if f.split('.')[-1] == 'h5' and f.split('.')[-2] != 'opmd' ]
input_files.sort()
else:
raise IOError("Input file %s does not exist or cannot be read." % (self.input_path) )
# Create output directory if not existing yet.
if not os.path.isdir( self.output_path ):
os.mkdir( self.output_path )
elif os.path.isfile( self.output_path ):
raise IOError( "Output file %s already exists, cowardly refusing to overwrite." % (self.output_path) )
# Generate formatted output files (i.e. attach history to output file).
for i,input_file in enumerate(input_files):
tail = input_file.split( 'prop' )[-1]
output_file = os.path.join( self.output_path , 'pmi_out_%07d.h5' % (i+1) )
pmi_script.f_h5_out2in( input_file, output_file)
# Get the backengine calculator.
pmi_demo = PMIDemo()
# Transfer some parameters.
pmi_demo.g_s2e['prj'] = ''
pmi_demo.g_s2e['id'] = tail.split('_')[-1].split('.')[0]
pmi_demo.g_s2e['prop_out'] = input_file
pmi_demo.g_s2e['setup'] = dict()
pmi_demo.g_s2e['sys'] = dict()
pmi_demo.g_s2e['setup']['num_digits'] = 7
if 'number_of_steps' in self.parameters.keys():
pmi_demo.g_s2e['steps'] = self.parameters['number_of_steps']
else:
pmi_demo.g_s2e['steps'] = 100
pmi_demo.g_s2e['maxZ'] = 100
pmi_demo.g_s2e['setup']['pmi_out'] = output_file
# Setup the database.
pmi_demo.f_dbase_setup()
# Go through the pmi workflow.
pmi_demo.f_init_random()
pmi_demo.f_save_info()
pmi_demo.f_load_pulse( pmi_demo.g_s2e['prop_out'] )
# Check if sample is a h5 file. Horrible hack.
try:
h5 = h5py.File(self.__sample_path)
h5.close()
pmi_demo.f_load_sample(self.__sample_path)
except:
# Assume it's a pdb file. Will raise if not.
atoms_dict = IOUtilities.loadPDB(self.__sample_path)
pmi_demo.g_s2e['sample'] = atoms_dict
pmi_demo.f_rotate_sample()
pmi_demo.f_system_setup()
# Perform the trajectories for this pulse and orientation.
for traj in range( self.parameters['number_of_trajectories'] ):
pmi_demo.f_time_evolution()
return status
