gplately.reconstruct_grid

gplately.reconstruct_grid(grid, partitioning_features, rotation_model, to_time, from_time=0.0, extent: tuple | str = 'global', origin=None, fill_value=None, threads=1, anchor_plate_id=None, x_dimension_name: str = '', y_dimension_name: str = '', data_variable_name: str = '')[source]

Reconstruct a gridded dataset to a given reconstruction time.

Note

Use Raster.reconstruct() whenever is possible. This reconstruct_grid() is better to be private.

Parameters:

  • grid (array_like, or str) – The grid to be reconstructed. If grid is a filename, it will be loaded using read_netcdf_grid().

  • partitioning_features (valid argument to pygplates.FeaturesFunctionArgument) – Features used to partition the grid by plate ID, usually a static polygons file. The partitioning_features may be a single pygplates.Feature object, a pygplates.FeatureCollection, a filename (str), or a (potentially nested) sequence of any combination of the above types.

  • rotation_model (valid argument to pygplates.RotationModel) – The rotation model used to reconstruct the grid. The rotation_model may be a pygplates.RotationModel object, a rotation pygplates.FeatureCollection, a rotation filename (str), a rotation pygplates.Feature, a sequence of rotation features, or a (potentially nested) sequence of any combination of the above types.

  • to_time (float) – Time to which grid will be reconstructed.

  • from_time (float, default=0.0) – Time from which to reconstruct the grid.

  • extent (tuple or str, default="global") – Extent of the grid. Valid arguments are a tuple of the form (xmin, xmax, ymin, ymax), or the string “global”, equivalent to (-180.0, 180.0, -90.0, 90.0).

  • origin ({"upper", "lower"}, optional) – Origin of the grid - either lower-left or upper-left. By default, determined from extent.

  • fill_value (float, int, or tuple, optional, default=None) – The value to be used for regions outside of partitioning_features at to_time. If not provided, this value will be determined based on the input.

  • threads (int, default=1) – Number of threads to use for certain computationally heavy routines.

  • anchor_plate_id (int, optional, default=None) – ID of the anchored plate. By default, use the default anchor plate ID of rotation_model if it’s a pygplates.RotationModel (otherwise zero).

  • x_dimension_name (str, optional, default="") – If the grid file uses comman names, such as “x”, “lon”, “lons” or “longitude”, you need not set this parameter. Otherwise, you need to tell us what the x dimension name is.

  • y_dimension_name (str, optional, default="") – If the grid file uses comman names, such as “y”, “lat”, “lats” or “latitude”, you need not set this parameter. Otherwise, you need to tell us what the y dimension name is.

  • data_variable_name (str, optional, default="") – The program will try its best to determine the data variable name. However, it would be better if you could tell us what the data variable name is. Otherwise, the program will guess. The result may/may not be correct.

Returns:

The reconstructed grid. Areas for which no plate ID could be determined from partitioning_features will be filled with fill_value.

Return type:

numpy.ndarray

Note

For two-dimensional grids, fill_value should be a single number. The default value will be np.nan for float or complex types, the minimum value for integer types, and the maximum value for unsigned types. For RGB image grids, fill_value should be a 3-tuple RGB colour code or a matplotlib colour name. The default value will be black (0.0, 0.0, 0.0). For RGBA image grids, fill_value should be a 4-tuple RGBA colour code or a matplotlib colour name. The default fill value will be transparent black (0.0, 0.0, 0.0, 0.0).