NEDAS.assim_tools.transforms package

Submodules

NEDAS.assim_tools.transforms.identity module

class NEDAS.assim_tools.transforms.identity.Identity(c: Context, **kwargs)

Bases: Transform

Subclass for the identity transform.

forward_state(c: Context, rec: FieldRecord, field: ndarray) → ndarray

Forward transform for the model state variables.

Parameters:

• c (Context) – the runtime context.

• rec (FieldRecord) – State information record for the variable.

• field (np.ndarray) – The state variable.

Returns:

The transformed state variable.

Return type:

np.ndarray

backward_state(c: Context, rec: FieldRecord, field: ndarray) → ndarray

Backward (inverse) transform for the model state variables.

Parameters:

• c (Context) – the runtime context.

• rec (FieldRecord) – State information record for the variable.

• field (np.ndarray) – The transformed state variable.

Returns:

The state variable transformed back to the original space.

Return type:

np.ndarray

forward_obs(c: Context, obs_rec: ObsRecord, obs_seq: dict[str, ndarray]) → dict[str, ndarray]

Forward transform for the observation sequence.

Parameters:

• c (Context) – the runtime context.

• obs_rec (ObsRecord) – Observation information record.

• obs_seq (dict[str, np.ndarray]) – The observation sequence. With keys 'obs' the observation; 'x', 'y', 'z', 't' the space/time coordinates; and 'err_std' the observation errors.

Returns:

The transformed observation sequence.

Return type:

dict[str, np.ndarray]

backward_obs(c: Context, obs_rec: ObsRecord, obs_seq: dict[str, ndarray]) → dict[str, ndarray]

Backward (inverse) transform for the observation sequence.

Parameters:

• c (Context) – the runtime context.

• obs_rFieldRecord)ict) – Observation information record.

• obs_seq (dict) – The transformed observation sequence. With keys 'obs' the observation; 'x', 'y', 'z', 't' the space/time coordinates; and 'err_std' the observation errors.

Returns:

The observation sequence transformed back to the original space.

Return type:

dict

NEDAS.assim_tools.transforms.scale_bandpass module

class NEDAS.assim_tools.transforms.scale_bandpass.ScaleBandpass(c, decompose_obs=True, **kwargs)

Bases: Transform

Subclass for scale bandpass filter to get a scale component.

decompose_obs: bool

nscale: int

forward_state(c, rec, field)

Forward transform for the model state variables.

Parameters:

• c (Context) – the runtime context.

• rec (FieldRecord) – State information record for the variable.

• field (np.ndarray) – The state variable.

Returns:

The transformed state variable.

Return type:

np.ndarray

backward_state(c, rec, field)

Backward (inverse) transform for the model state variables.

Parameters:

• c (Context) – the runtime context.

• rec (FieldRecord) – State information record for the variable.

• field (np.ndarray) – The transformed state variable.

Returns:

The state variable transformed back to the original space.

Return type:

np.ndarray

forward_obs(c, obs_rec, obs_seq)

Forward transform for the observation sequence.

Parameters:

• c (Context) – the runtime context.

• obs_rec (ObsRecord) – Observation information record.

• obs_seq (dict[str, np.ndarray]) – The observation sequence. With keys 'obs' the observation; 'x', 'y', 'z', 't' the space/time coordinates; and 'err_std' the observation errors.

Returns:

The transformed observation sequence.

Return type:

dict[str, np.ndarray]

backward_obs(c, obs_rec, obs_seq)

Backward (inverse) transform for the observation sequence.

Parameters:

• c (Context) – the runtime context.

• obs_rFieldRecord)ict) – Observation information record.

• obs_seq (dict) – The transformed observation sequence. With keys 'obs' the observation; 'x', 'y', 'z', 't' the space/time coordinates; and 'err_std' the observation errors.

Returns:

The observation sequence transformed back to the original space.

Return type:

dict

Module contents

NEDAS.assim_tools.transforms.get_transform_funcs(c: Context) → list[Transform]