@pytest.mark.parametrize('bodies', body_list)
@pytest.mark.parametrize('multihyps', multi_list)
def test_init(bodies, multihyps, all_mgp, all_gp):
    '\n    test the init function\n    '
    clean()
    gp_model = all_gp[f'{bodies}{multihyps}']
    grid_params = {}
    if ('2' in bodies):
        grid_params['twobody'] = {'grid_num': [160], 'lower_bound': [0.02]}
    if ('3' in bodies):
        grid_params['threebody'] = {'grid_num': [31, 32, 33], 'lower_bound': ([0.02] * 3)}
    lammps_location = f'{bodies}{multihyps}'
    data = gp_model.training_statistics
    try:
        mgp_model = MappedGaussianProcess(grid_params=grid_params, unique_species=data['species'], n_cpus=1, lmp_file_name=lammps_location, var_map='simple')
    except:
        mgp_model = MappedGaussianProcess(grid_params=grid_params, unique_species=data['species'], n_cpus=1, lmp_file_name=lammps_location, var_map=None)
    all_mgp[f'{bodies}{multihyps}'] = mgp_model
test the init function
@pytest.mark.parametrize('bodies', body_list)
@pytest.mark.parametrize('multihyps', multi_list)
def test_init(bodies, multihyps, all_mgp, all_gp):
    '\n    \n    '
    clean()
    gp_model = all_gp[f'{bodies}{multihyps}']
    grid_params = {}
    if ('2' in bodies):
        grid_params['twobody'] = {'grid_num': [160], 'lower_bound': [0.02]}
    if ('3' in bodies):
        grid_params['threebody'] = {'grid_num': [31, 32, 33], 'lower_bound': ([0.02] * 3)}
    lammps_location = f'{bodies}{multihyps}'
    data = gp_model.training_statistics
    try:
        mgp_model = MappedGaussianProcess(grid_params=grid_params, unique_species=data['species'], n_cpus=1, lmp_file_name=lammps_location, var_map='simple')
    except:
        mgp_model = MappedGaussianProcess(grid_params=grid_params, unique_species=data['species'], n_cpus=1, lmp_file_name=lammps_location, var_map=None)
    all_mgp[f'{bodies}{multihyps}'] = mgp_model