def main():
client, db = mongo.connect()
parser = argparse.ArgumentParser(description='TEST SET MANAGEMENT')
parser.add_argument('dataset', help='the name of the test set', nargs='?')
parser.add_argument('-d', '--delete', help='Removes the spectrum from the lists of spectra in the database')
parser.set_defaults(which='main')
subparser = parser.add_subparsers(help='TEST SET COMMANDS')
delete = subparser.add_parser('delete', help="Removes the spectrum from the lists of spectra in the database")
delete.set_defaults(which='del')
insert = subparser.add_parser('insert', help="Inserts processed spectra into the database")
insert.set_defaults(which='insert')
cp = subparser.add_parser('cp', help='COPY')
cp.add_argument('name', help='The new testset name')
cp.add_argument('-f', '--full', action='store_true', help='Copy all files in dir')
cp.add_argument('-s', '--success', action='store_true', help='Copy only successfully optimised molecules')
cp.set_defaults(which='cp')
nw = subparser.add_parser('nw', help='NEW')
nw.set_defaults(which='nw')
rb = subparser.add_parser('rebuild', help='REBUILD')
rb.set_defaults(which='rebuild')
minimise = subparser.add_parser('mini', help='MINIMISATION OPERATIONS')
minimise.add_argument('-c', '--conformers', type=int, help='Set the number of conformers to try')
minimise.add_argument('-r', '--rdkit', action='store_true', help='Minimise with rdkit mmff')
minimise.set_defaults(which='minimise')
convert = subparser.add_parser('convert', help='CONVERSION OPERATIONS')
convert.add_argument('-a', '--arguments', nargs='+', default=[], help='Supply the conversion arguments')
convert.add_argument('-s', '--savecpm', help='Location to save the com file')
# convert.add_argument('convert', help='Convert to com file, default save as g_safename in same dir')
convert.set_defaults(which='convert')
molecules = subparser.add_parser('molecule', help='MOLECULE OPERATIONS')
molecules.add_argument('-a', '--add', metavar='<FILE>', type=argparse.FileType('r', 0), help='Add molecules from file to the test set')
molecules.add_argument('-r', '--remove', nargs='+', help='Remove named molecules, or all')
molecules.add_argument('-n', '--num', action='store_true', help='How many molecules in the dataset')
molecules.add_argument('-c', '--convert', action='store_true', help='Convert to com file')
molecules.add_argument('--molfiles', default=False, help='Dump to molfiles, with no hydrgens (for Chemdraw)')
molecules.set_defaults(which='molecules')
tensors = subparser.add_parser('tensor', help='TENSOR OPERATIONS')
tensors.add_argument('-p', '--process', action='store_true', help='Process the tensors from the dataset')
tensors.add_argument('-o', '--output', help='Writes a tensor analysis to csv')
tensors.set_defaults(which='tensors')
printer = subparser.add_parser('print', help='PRINT OPERATIONS')
printer.add_argument('pprint', metavar='<ATTRIBUTE>', help='Print a dataset attribute by name')
printer.set_defaults(which='printing')
args = parser.parse_args()
if args.dataset.endswith('/'):
print 'No trailing slash!'
sys.exit(1)
if not os.path.exists(args.dataset) and args.which != 'nw':
print "dataset directory does not exist"
sys.exit(1)
elif args.which == 'nw':
print 'Creating new dataset directory: ' + args.dataset
if os.path.isdir(args.dataset):
print 'Directory already exists!'
sys.exit(1)
else:
dataset = testset.TestSet(args.dataset)
print 'Serialising...'
dataset.save()
sys.exit(0)
elif os.path.exists(args.dataset):
try:
dataset = testset.TestSet.deserialise(args.dataset)
except IOError:
print 'This dataset has a filestructure but no serialised set found'
i = raw_input("Would you like to create one? y/n ")
if i == 'y':
dataset = testset.TestSet.build(db, args.dataset)
print 'Dataset {0} created with {1} molecules'.format(dataset.dataset, len(dataset.molecules))
else:
return
if args.which == 'del':
mongo.delete_spectrum(db, dataset.dataset)
elif args.which == 'printing':
if '.' in args.pprint:
args.pprint, attr2 = args.pprint.split('.')
if hasattr(dataset, args.pprint):
attr = getattr(dataset, args.pprint)
if isinstance(attr, list):
for item in attr:
if hasattr(item, attr2):
print getattr(item, attr2)
else:
print item
else:
print attr
else:
print 'No attribute with name "{0}" found'.format(args.pprint)
if args.which == 'molecules':
if args.add:
print 'Reading molecules from {0}'.format(args.add.name)
dataset.import_molecules(db, args.add)
dataset.save()
elif args.remove:
if args.remove == ['all']:
i = raw_input("""Are you sure you wish to remove all molecules from this dataset? All directories will be removed - y/n: """)
if i == 'y':
dataset.remove_molecules(dataset.molecules)
dataset.save()
else:
sys.exit(0)
else:
print 'Removing molecules: '+str(args.remove)
dataset.remove_molecules(args.remove)
elif args.num:
print '{0} molecules in the dataset'.format(len(dataset.molecules))
elif args.molfiles:
cwd = os.getcwd()
location = os.path.join(cwd, args.molfiles)
for m in dataset.molecules:
m.mol_to_molfile(dir=location, hydrogens=False)
elif args.which == 'convert':
if args.arguments:
params = {'cpus':args.arguments[0], 'memory':args.arguments[1], 'command':args.arguments[2]}
else:
params = molecule.input_gaussian_params()
dataset.prepare_com_files(**params)
elif args.which == 'tensors':
if args.process:
dataset.process_logs()
elif args.output:
"""Write the tensors to file"""
stream = tensor_analysis.TensorStream.build(db, args.dataset)
stream.scale_stream()
with open(args.output, 'w') as handle:
handle.write('Output from dataset {} on {}\n'.format(args.dataset, str(dt.now())))
handle.write('molecule, atomid, hybridisation, mulliken charge, exp, calc, scaled error\n')
for line in stream:
print line
handle.write('{}\n'.format(','.join(map(str,line))))
print 'Wrote output to {}'.format(args.output)
elif args.which == 'cp':
if os.path.exists(args.name):
print 'This dir exists, please choose another name'
sys.exit(1)
else:
print 'Duplicating {0} to {1}'.format(dataset.dataset, args.name)
dataset = dataset.duplicate_set(args.name, args.full, args.success)
dataset.save()
elif args.which == 'minimise':
if args.conformers:
print 'Scanning conformer space with {0} starting points'.format(args.conformers)
dataset.minimise_molecules(molecule.m_rdkit_conformers, confs=args.conformers)
dataset.save()
elif args.rdkit:
print 'Minimising with RDKIT'
dataset.minimise_molecules(molecule.m_rdkit)
dataset.save()
elif args.which == 'rebuild':
print 'Rebuilding dataset'
newset = dataset.build(db, dataset.dataset)
newset.save()
elif args.which == 'insert':
print 'Inserting tensors'
dataset.insert_tensors(db)
def main ():
client, db = mongo.connect()
parser = argparse.ArgumentParser(description='UTILITIES')
parser.add_argument('molecule', help='the name of the molecule/molecues', nargs='?')
parser.set_defaults(which='main')
subparser = parser.add_subparsers(help='TEST SET COMMANDS')
plotter = subparser.add_parser('plot', help='PLOTTING OPERATIONS')
plotter.add_argument('-d', '--dataset', required=True, help='Dataset to plot')
plotter.add_argument('-s', '--savefig', help='Location to save the figure')
plotter.set_defaults(which='plotting')
converter = subparser.add_parser('convert', help='CONVERSION OPERATIONS')
converter.add_argument('-s', '--save', help='Name the com file')
converter.set_defaults(which='convert')
spectra = subparser.add_parser('spectra', help='SPECTRA GRAB')
spectra.add_argument('-s', '--savefig', help='Location to save the figure')
spectra.add_argument('-d', '--dataset', help='dataset to examine, otherwise all', default=None)
spectra.set_defaults(which='spectra')
args = parser.parse_args()
mol = molecule.Molecule(os.getcwd()).pull_record(db, {'g_safename':args.molecule})
if args.which == 'plotting':
if args.savefig:
loc = args.savefig
else:
loc = None
main_title = mol.g_safename + ' ' + args.dataset
shift_sets = tensor_analysis.molecule_tensor_analysis(mol, args.dataset)
exp, calc, names = tensor_analysis.extract_data(shift_sets)
fig = plotting.Figure(dimensions=(12,5), cols=1, main_title=main_title)
plotting.plot_tensor_scatter(calc, exp, fig, loc, legend=False)
fig.show_figure()
# plotting.plot_tensors(tensors, title=args.dataset, loc=loc)
elif args.which == 'convert':
params = molecule.input_gaussian_params()
molecule.convert_to_com(mol, **params)
mol.cleanup()
if args.save:
if not args.save.endswith('.com'):
args.save += '.com'
old = os.path.join(os.getcwd(), mol.g_safename, mol.g_safename+'.com')
new = os.path.join(os.path.dirname(old), args.save)
os.rename(old, new)
elif args.which == 'spectra':
shift_list = []
for x in mol.get_spectra(nuclei='13C'):
if hasattr(x, 'dataset'):
name = "(C) " + x.dataset
else:
name = "(E) " + str(x.assignment_method)
shifts = sorted(x.shifts, key=lambda y: y[0])
shifts.insert(0, name)
shift_list.append(shifts)
print '\n'
for sl in sublist(shift_list, 5):
for line in zip(*sl):
# print shifts
print ''.join(['{:<30}'.format(x) for x in line])
print '\n'
exp_spectra = mol.get_spectra(computed=False, nuclei='13C')
if args.dataset:
comp_spectra = mol.get_spectra(computed=True, dataset=args.dataset, assignment_method='Computed')
else:
comp_spectra = mol.get_spectra(computed=True, assignment_method='Computed')
if comp_spectra:
print '{:<30}{:<25}{:<20}{:<20}{:<20}'.format('Experimental', 'Computed', 'slope', 'intercept', 'R')
for exp_spec in exp_spectra:
for comp_spec in comp_spectra:
stats = tensor_analysis.regres_stats(comp_spec, exp_spec)
print '{:<30}{:<25}{:<20}{:<20}{:<20}'.format(exp_spec.assignment_method, comp_spec.dataset, round(stats[0],4),
round(stats[1],4), round(stats[2],4))
if args.savefig:
print 'Saving figure to {0}'.format(saveto)
t = tensor_analysis.molecule_tensor_analysis(mol, comp_spec.dataset)
plotting.plot_tensors(t, title=mol.g_safename, loc=saveto)
