Ejemplo n.º 1
0
args = parser.parse_args()
dataset = args.dataset

name = os.path.splitext(os.path.basename(dataset.name))[0]
dataset_file_name = name + '.npz'

dataset_exists = os.path.isfile(dataset_file_name)
if dataset_exists and args.overwrite:
    print ui.info_str('[INFO]') + ' Overwriting existing dataset file.'
if not dataset_exists or args.overwrite:
    print 'Writing dataset to \'%s\'...' % dataset_file_name
else:
    sys.exit(
        ui.fail_str('[FAIL]') +
        ' Dataset \'%s\' already exists.' % dataset_file_name)

R, z, E, F = read_concat_ext_xyz(dataset)

# Base variables contained in every model file.
base_vars = {'type':   'd',\
    'R':    R,\
    'z':    z,\
    'E':    E[:,None],\
    'F':    F,\
    'name':   name,\
    'theory':   'unknown'}
base_vars['md5'] = io.dataset_md5(base_vars)

np.savez_compressed(dataset_file_name, **base_vars)
print ui.pass_str('DONE')
Ejemplo n.º 2
0
        ui.warn_str('[WARN]') +
        ' Incomplete output detected: Final dataset was pruned to %d points.' %
        n_mols)
R = R[:n_mols, :, :]
F = F[:n_mols, :, :]
E = E[:n_mols]

# Base variables contained in every model file.
base_vars = {
    'type': 'd',
    'R': R,
    'z': z,
    'E': E[:, None],
    'F': F,
    'e_unit': 'kcal/mol',
    'r_unit': 'Ang',
    'name': name,
    'theory': 'unknown',
}

base_vars['F_min'], base_vars['F_max'] = np.min(F.ravel()), np.max(F.ravel())
base_vars['F_mean'], base_vars['F_var'] = np.mean(F.ravel()), np.var(F.ravel())

base_vars['E_min'], base_vars['E_max'] = np.min(E), np.max(E)
base_vars['E_mean'], base_vars['E_var'] = np.mean(E), np.var(E)

base_vars['md5'] = io.dataset_md5(base_vars)

np.savez_compressed(dataset_file_name, **base_vars)
print(ui.pass_str('DONE'))
Ejemplo n.º 3
0
if not xyz_exists or args.overwrite:
    print('Writing dataset to \'%s\'...' % dataset_file_name)
else:
    sys.exit(
        ui.fail_str('[FAIL]') + ' Dataset \'%s\' already exists.' % dataset_file_name
    )

z = dataset['z']
R = dataset['R']
F = dataset['F']
E = dataset['E']
n = R.shape[0]

try:
    with open(dataset_file_name, 'w') as f:
        for i, r in enumerate(R):

            f.write(str(len(r)) + '\n' + str(np.squeeze(E[i])))
            for j, atom in enumerate(r):
                f.write('\n' + io._z_to_z_str_dict[z[j]] + '\t')
                f.write('\t'.join(str(x) for x in atom) + '\t')
                f.write('\t'.join(str(x) for x in F[i][j]))
            f.write('\n')

            progr = float(i) / (n - 1)
            ui.progr_bar(i, n - 1, disp_str='Exporting %d data points...' % n)
except IOError:
    sys.exit("ERROR: Writing xyz file failed.")

print('\n' + ui.pass_str('DONE'))