sequence.sequence module

Sequence’s main API for constructing sequence-stratigraphic models.

class sequence.sequence.Sequence(*args, **kwds)

Bases: Component

Landlab component interface to the Sequence model.

__init__(grid: SequenceModelGrid, time_step: float = 100.0, components: Iterable | None = None)

Create a Sequence model.

Parameters:

• grid (SequenceModelGrid) – A model grid.

• time_step (float, optional) – The time step at which the model will run each of its components.

• components (iterable, optional) – A list of components to run every time step.

add_layer(dz_at_cell: ndarray[Any, dtype[floating]]) → None

Add a new layer to each cell.

Properties

dz_at_cellarray-like

Thickness of the new layers for each cell along the profile.

layer_properties() → dict[str, _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | bool | int | float | complex | str | bytes | _NestedSequence[bool | int | float | complex | str | bytes]]

Return the properties being tracked at each layer.

Returns:

properties – A dictionary of the tracked properties where the keys are the names of properties and the values are the property values at each column.

Return type:

dict

layer_reducers() → dict[str, Any]

Return layer-reducers for each property.

Returns:

reducers – A dictionary of reducers where keys are property names and values are functions that act as layer reducers for those quantities.

Return type:

dict

plot() → None

Plot the grid.

run(until: float | None = None, dt: float | None = None, progress_bar: bool = True) → None

Run the model to a given time.

Parameters:

• until (float, optional) – The time (in years) to run the model to. If not provided, run for a single time step.

• dt (float, optional) – Run using a time step other than what the component was initialized with.

• progress_bar (bool, optional) – If True display a progress bar while the model is running.

property time: float

Return the current model time (in years).

update(dt: float | None = None) → None

Update the model of a given time step.

Parameters:

dt (float, optional) – The length of time to run the model for. If not given, update the model a single time step.