def test_save_metadata_no_grids(self, tmp_path):
p = utilities.yaml_from_dict(tmp_path, 'input.yaml', {
'save_dt': 1,
'save_metadata': True
})
_delta = DeltaModel(input_file=p)
# mock the log_info
_delta.log_info = mock.MagicMock()
# mock the actual output routines
_delta.make_figure = mock.MagicMock()
_delta.save_figure = mock.MagicMock()
_delta.save_grids = mock.MagicMock()
exp_path_nc = os.path.join(tmp_path / 'out_dir',
'pyDeltaRCM_output.nc')
assert os.path.isfile(exp_path_nc)
for _t in range(0, 3):
_delta.save_grids_and_figs()
_delta._save_iter += 1
# close the file and connect
_delta.output_netcdf.close()
ds = netCDF4.Dataset(exp_path_nc, "r", format="NETCDF4")
# assertions
assert not ('eta' in ds.variables)
assert ds['meta']['H_SL'].shape[0] == 4 # init + 3
assert ds['meta']['L0'][:] == 3
def test_save_one_fig_one_grid(self, tmp_path):
p = utilities.yaml_from_dict(tmp_path, 'input.yaml', {
'save_dt': 1,
'save_eta_grids': True,
'save_discharge_figs': True
})
_delta = DeltaModel(input_file=p)
# mock the log_info
_delta.log_info = mock.MagicMock()
# mock the actual output routines
_delta.make_figure = mock.MagicMock()
_delta.save_figure = mock.MagicMock()
_delta.save_grids = mock.MagicMock()
assert (_delta._save_eta_grids is True)
assert (_delta._save_metadata is True)
# check for the netcdf file
exp_path_nc = os.path.join(tmp_path / 'out_dir',
'pyDeltaRCM_output.nc')
assert os.path.isfile(exp_path_nc)
nc_size_before = os.path.getsize(exp_path_nc)
assert nc_size_before > 0 # saved once already / inited
# update a couple times, should increase on each save
for _t in range(0, 5):
_delta.save_grids_and_figs()
_delta._save_iter += 1
_delta.make_figure.call_count == 5
_delta.save_figure.call_count == 5
_delta.save_grids.call_count == 5
def test_save_one_fig_no_grids(self, tmp_path):
p = utilities.yaml_from_dict(tmp_path, 'input.yaml', {
'save_dt': 1,
'save_eta_figs': True
})
_delta = DeltaModel(input_file=p)
# mock the log_info
_delta.log_info = mock.MagicMock()
# mock the actual output routines
_delta.make_figure = mock.MagicMock()
_delta.save_figure = mock.MagicMock()
_delta.save_grids = mock.MagicMock()
# check nothing created at the start
_delta.make_figure.call_count == 0
_delta.save_figure.call_count == 0
_delta.save_grids.call_count == 0
assert (len(_delta._save_fig_list) > 0)
assert (_delta._save_eta_figs is True)
# update the delta a few times
for _t in range(0, 5):
_delta.save_grids_and_figs()
_delta._save_iter += 1
_delta.make_figure.call_count == 5
_delta.save_figure.call_count == 5
_delta.save_grids.call_count == 0
def test_save_no_figs_no_grids(self, tmp_path):
p = utilities.yaml_from_dict(tmp_path, 'input.yaml', {'save_dt': 1})
_delta = DeltaModel(input_file=p)
# mock the log_info
_delta.log_info = mock.MagicMock()
# mock the actual output routines
_delta.make_figure = mock.MagicMock()
_delta.save_figure = mock.MagicMock()
_delta.save_grids = mock.MagicMock()
# check nothing created at the start
_delta.make_figure.call_count == 0
_delta.save_figure.call_count == 0
_delta.save_grids.call_count == 0
# update the delta a few times
for _t in range(0, 4):
_delta._time = (_t * _delta._dt)
_delta.save_grids_and_figs()
# check nothing after a number of iterations, greater than dt
assert _delta._time > _delta.save_dt
_delta.make_figure.call_count == 0
_delta.save_figure.call_count == 0
_delta.save_grids.call_count == 0
def test_save_all_figures_no_grids(self, tmp_path):
p = utilities.yaml_from_dict(
tmp_path, 'input.yaml', {
'save_dt': 1,
'save_eta_figs': True,
'save_discharge_figs': True,
'save_velocity_figs': True,
'save_stage_figs': True,
'save_depth_figs': True,
'save_sedflux_figs': True
})
_delta = DeltaModel(input_file=p)
# mock the log_info
_delta.log_info = mock.MagicMock()
# mock the actual output routines
_delta.make_figure = mock.MagicMock()
_delta.save_figure = mock.MagicMock()
_delta.save_grids = mock.MagicMock()
exp_path_nc = os.path.join(tmp_path / 'out_dir',
'pyDeltaRCM_output.nc')
assert not os.path.isfile(exp_path_nc)
for _t in range(0, 5):
_delta.save_grids_and_figs()
_delta._save_iter += 1
_delta._time += _delta._dt
# assertions
_delta.make_figure.assert_any_call('eta', 0)
_delta.make_figure.assert_any_call('stage', 0)
_delta.make_figure.assert_any_call('depth', 0)
_delta.make_figure.assert_any_call('qw', 0)
_delta.make_figure.assert_any_call('uw', 0)
_delta.make_figure.assert_any_call('qs', 0)
for _i in range(1, 5):
_delta.make_figure.assert_any_call('eta', _delta._dt * _i)
_delta.make_figure.call_count == 5 * 6
_delta.save_figure.call_count == 5 * 6
_delta.save_grids.call_count == 0
def test_save_one_grid_metadata_by_default(self, tmp_path):
p = utilities.yaml_from_dict(
tmp_path, 'input.yaml', {
'save_dt': 1,
'save_metadata': False,
'save_eta_grids': True,
'C0_percent': 0.2
})
_delta = DeltaModel(input_file=p)
# mock the log_info
_delta.log_info = mock.MagicMock()
# mock the actual output routines
_delta.make_figure = mock.MagicMock()
_delta.save_figure = mock.MagicMock()
_delta.save_grids = mock.MagicMock()
exp_path_nc = os.path.join(tmp_path / 'out_dir',
'pyDeltaRCM_output.nc')
assert os.path.isfile(exp_path_nc)
for _t in range(0, 6):
_delta.save_grids_and_figs()
_delta._save_iter += 1
# close the file and connect
_delta.output_netcdf.close()
ds = netCDF4.Dataset(exp_path_nc, "r", format="NETCDF4")
# assertions
_arr = ds.variables['eta']
assert _arr.shape[1] == _delta.eta.shape[0]
assert _arr.shape[2] == _delta.eta.shape[1]
assert ('meta' in ds.groups) # if any grids, save meta too
assert ds.groups['meta']['H_SL'].shape[0] == _arr.shape[0]
assert np.all(ds.groups['meta']['C0_percent'][:] == 0.2)
assert np.all(ds.groups['meta']['f_bedload'][:] == 0.5)
