pygplates.ReconstructModel

class pygplates.ReconstructModel

Bases: instance

A history of reconstructed geometries over geological time.

A ReconstructModel can also be pickled.

Added in version 0.48.

__init__(reconstructable_features, rotation_model[, anchor_plate_id][, reconstruct_snapshot_cache_size])

Create from reconstructable features and a rotation model.

Parameters:

reconstructable_features (FeatureCollection, or string/os.PathLike, or Feature, or sequence of Feature, or sequence of any combination of those four types) – The features to reconstruct as a feature collection, or filename, or feature, or sequence of features, or a sequence (eg, list or tuple) of any combination of those four types.
rotation_model (RotationModel. Or FeatureCollection, or string/os.PathLike, or Feature, or sequence of Feature, or sequence of any combination of those four types) – A rotation model. Or a rotation feature collection, or a rotation filename, or a rotation feature, or a sequence of rotation features, or a sequence of any combination of those four types.
anchor_plate_id (int) – The anchored plate id used for reconstructions. Defaults to the default anchor plate of rotation_model (or zero if rotation_model is not a RotationModel).
reconstruct_snapshot_cache_size (int) – Number of reconstruct snapshots to cache internally. Defaults to unlimited.

Load a reconstruct model (and its associated rotation model):

rotation_model = pygplates.RotationModel('rotations.rot')
reconstruct_model = pygplates.ReconstructModel('reconstructable_features.gpml', rotation_model)

…or alternatively just:

reconstruct_model = pygplates.ReconstructModel('reconstructable_features.gpml', 'rotations.rot')

Note

All reconstructions use anchor_plate_id. So if you need to use a different anchor plate ID then you’ll need to create a new ReconstructModel. However this should only be done if necessary since each ReconstructModel created can consume a reasonable amount of CPU and memory (since it caches reconstructed geometries over geological time).

Note

The reconstruct_snapshot_cache_size parameter controls the size of an internal least-recently-used cache of reconstruct snapshots (evicts least recently requested reconstruct snapshot when a new reconstruction time is requested that does not currently exist in the cache). This enables reconstruct snapshots associated with different reconstruction times to be re-used instead of re-creating them, provided they have not been evicted from the cache.

Methods

`__init__`(reconstructable_features, ...)	Create from reconstructable features and a rotation model.
`get_anchor_plate_id`()	Return the anchor plate ID (see `constructor`).
`get_rotation_model`()	Return the rotation model used internally.
`reconstruct_snapshot`(reconstruction_time)	Returns a snapshot of reconstructed geometries at the requested reconstruction time.

get_anchor_plate_id()

Return the anchor plate ID (see constructor).

Return type:: int

Note

This is the same as the default anchor plate ID of get_rotation_model().

get_rotation_model()

Return the rotation model used internally.

Return type:: RotationModel

Note

The default anchor plate ID of the returned rotation model may be different to that of the rotation model passed into the constructor if an anchor plate ID was specified in the constructor.

Note

The reconstruction tree cache size of the returned rotation model is equal to the reconstruct_snapshot_cache_size argument specified in the constructor plus one (or unlimited if not specified).

reconstruct_snapshot(reconstruction_time)

Returns a snapshot of reconstructed geometries at the requested reconstruction time.

Parameters:: reconstruction_time (float or GeoTimeInstant) – the geological time of the snapshot
Return type:: ReconstructSnapshot
Raises:: ValueError if reconstruction_time is distant-past (float('inf')) or distant-future (float('-inf')).