def test_load_checkpoint_with_netcdf(self, tmp_path):
"""Test that a run can be resumed when there are outputs.
"""
# define a yaml with outputs (defaults will output strata)
p = utilities.yaml_from_dict(tmp_path, 'input.yaml',
{'save_checkpoint': True,
'save_eta_grids': True})
_delta = DeltaModel(input_file=p)
# replace eta with a random field for checkpointing success check
_rand_field = np.random.uniform(0, 1, size=_delta.eta.shape)
_delta.eta = _rand_field
_delta._save_time_since_checkpoint = float("inf")
_delta.output_checkpoint() # force another checkpoint
_delta.finalize()
# paths exists
assert os.path.isfile(os.path.join(
_delta.prefix, 'pyDeltaRCM_output.nc'))
assert os.path.isfile(os.path.join(
_delta.prefix, 'checkpoint.npz'))
_delta = [] # clear
# can be resumed
p = utilities.yaml_from_dict(tmp_path, 'input.yaml',
{'save_checkpoint': True,
'resume_checkpoint': True})
_delta = DeltaModel(input_file=p)
# check that fields match
assert np.all(_delta.eta == _rand_field)
def test_create_checkpoint_without_netcdf(self, tmp_path):
"""Test that a checkpoint can be created when there are no outputs
"""
# define a yaml with NO outputs, but checkpoint
p = utilities.yaml_from_dict(tmp_path, 'input.yaml',
{'save_checkpoint': True})
_delta = DeltaModel(input_file=p)
# replace eta with a random field for checkpointing success check
_rand_field = np.random.uniform(0, 1, size=_delta.eta.shape)
_delta.eta = _rand_field
_delta._save_time_since_checkpoint = float("inf")
_delta.output_checkpoint() # force another checkpoint
_delta.finalize()
# should be no file
assert not os.path.isfile(os.path.join(
_delta.prefix, 'pyDeltaRCM_output.nc'))
# can be resumed
p = utilities.yaml_from_dict(tmp_path, 'input.yaml',
{'save_checkpoint': True,
'resume_checkpoint': True})
_delta = DeltaModel(input_file=p)
# check that fields match
assert np.all(_delta.eta == _rand_field)
def test_load_checkpoint_with_open_netcdf_win(self, tmp_path):
"""Test what happens if output netCDF file is actually open.
This is not the same as when the netCDF file is open in another
process. That situation raises an error for all OS.
"""
# define a yaml with outputs (defaults will output strata)
p = utilities.yaml_from_dict(tmp_path, 'input.yaml', {
'save_checkpoint': True,
'save_eta_grids': True
})
_delta = DeltaModel(input_file=p)
# replace eta with a random field for checkpointing success check
_rand_field = np.random.uniform(0, 1, size=_delta.eta.shape)
_delta.eta = _rand_field
_delta._save_time_since_checkpoint = float("inf")
_delta.output_checkpoint() # force another checkpoint
_delta.finalize()
# paths exists
assert os.path.isfile(
os.path.join(_delta.prefix, 'pyDeltaRCM_output.nc'))
assert os.path.isfile(os.path.join(_delta.prefix, 'checkpoint.npz'))
_prefix = _delta.prefix
_delta = [] # clear
# open the netCDF file
_opened = Dataset(os.path.join(_prefix, 'pyDeltaRCM_output.nc'),
'r+',
format='NETCDF4')
assert type(_opened) == Dataset
assert 'eta' in _opened.variables.keys()
# saved grid is the initial one, before random field was assigned
assert np.all(_opened.variables['eta'][:].data != _rand_field)
# can be resumed
p = utilities.yaml_from_dict(
tmp_path, 'input.yaml', {
'save_checkpoint': True,
'resume_checkpoint': True,
'save_eta_grids': True
})
# raises a permissions error on Windows
with pytest.raises(PermissionError):
_ = DeltaModel(input_file=p)
def test_load_checkpoint_without_netcdf(self, tmp_path):
"""Test that a run can be resumed when there are outputs.
"""
# define a yaml with NO outputs, but checkpoint
p = utilities.yaml_from_dict(tmp_path, 'input.yaml',
{'save_checkpoint': True})
_delta = DeltaModel(input_file=p)
# replace eta with a random field for checkpointing success check
_rand_field = np.random.uniform(0, 1, size=_delta.eta.shape)
_delta.eta = _rand_field
_delta._save_time_since_checkpoint = float("inf")
_delta.output_checkpoint() # force another checkpoint
_delta.finalize()
# should be no nc file but should be a checkpoint file
assert not os.path.isfile(os.path.join(
_delta.prefix, 'pyDeltaRCM_output.nc'))
assert os.path.isfile(os.path.join(
_delta.prefix, 'checkpoint.npz'))
# now try to resume, will WARN on not finding netcdf
p = utilities.yaml_from_dict(tmp_path, 'input.yaml',
{'save_checkpoint': True,
'save_eta_grids': True,
'resume_checkpoint': True})
with pytest.warns(UserWarning, match=r'NetCDF4 output *.'):
_delta = DeltaModel(input_file=p)
# assert that a new output file exists file exists
assert os.path.isfile(os.path.join(
_delta.prefix, 'pyDeltaRCM_output.nc'))
assert os.path.isfile(os.path.join(
_delta.prefix, 'checkpoint.npz'))
# check that fields match
assert np.all(_delta.eta == _rand_field)
def test_load_checkpoint_with_open_netcdf(self, tmp_path):
"""Test what happens if output netCDF file is actually open.
This is not the same as when the netCDF file is open in another
process. That situation raises an error for all OS.
"""
# define a yaml with outputs (defaults will output strata)
p = utilities.yaml_from_dict(tmp_path, 'input.yaml',
{'save_checkpoint': True,
'save_eta_grids': True})
_delta = DeltaModel(input_file=p)
# replace eta with a random field for checkpointing success check
_rand_field = np.random.uniform(0, 1, size=_delta.eta.shape)
_delta.eta = _rand_field
_delta._save_time_since_checkpoint = float("inf")
_delta.output_checkpoint() # force another checkpoint
_delta.finalize()
# paths exists
assert os.path.isfile(os.path.join(
_delta.prefix, 'pyDeltaRCM_output.nc'))
assert os.path.isfile(os.path.join(
_delta.prefix, 'checkpoint.npz'))
_prefix = _delta.prefix
_delta = [] # clear
# open the netCDF file
_opened = Dataset(os.path.join(_prefix, 'pyDeltaRCM_output.nc'),
'r+', format='NETCDF4')
assert type(_opened) == Dataset
assert 'eta' in _opened.variables.keys()
# saved grid is the initial one, before random field was assigned
assert np.all(_opened.variables['eta'][:].data != _rand_field)
# can be resumed
p = utilities.yaml_from_dict(tmp_path, 'input.yaml',
{'save_checkpoint': True,
'resume_checkpoint': True,
'save_eta_grids': True})
_delta = DeltaModel(input_file=p)
# force save grids/figs
_delta.save_grids_and_figs()
# check that fields match
assert np.all(_delta.eta == _rand_field)
# assert that old netCDF object is still around and hasn't changed
assert type(_opened) == Dataset
assert 'eta' in _opened.variables.keys()
# grid from old netCDF is initial one, before random field was assigned
assert np.all(_opened.variables['eta'][:].data != _rand_field)
# clear delta
_delta = []
# open the new netCDF file
_new = Dataset(os.path.join(_prefix, 'pyDeltaRCM_output.nc'),
'r+', format='NETCDF4')
# first grid should be the OG one
assert np.all(_opened['eta'][:].data == _new['eta'][0, :, :].data)
# random field should be saved in the new netCDF file
# some rounding/truncation happens in the netCDF so we use approx
assert pytest.approx(_rand_field) == _new['eta'][1, :, :].data