Example #1
0
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)