.. _iris.experimental.regrid: ======================== iris.experimental.regrid ======================== .. currentmodule:: iris .. automodule:: iris.experimental.regrid In this module: * :py:obj:`regrid_area_weighted_rectilinear_src_and_grid` * :py:obj:`regrid_weighted_curvilinear_to_rectilinear` * :py:obj:`PointInCell` * :py:obj:`ProjectedUnstructuredLinear` * :py:obj:`ProjectedUnstructuredNearest` .. autofunction:: iris.experimental.regrid.regrid_area_weighted_rectilinear_src_and_grid .. raw:: html
.. autofunction:: iris.experimental.regrid.regrid_weighted_curvilinear_to_rectilinear .. raw:: html This class describes the point-in-cell regridding scheme for use typically with :meth:`iris.cube.Cube.regrid()`. .. warning:: This class is now **disabled**. The functionality has been moved to :class:`iris.analysis.PointInCell`. .. .. autoclass:: iris.experimental.regrid.PointInCell :members: :undoc-members: :inherited-members: .. raw:: html This class describes the linear regridding scheme which uses the scipy.interpolate.griddata to regrid unstructured data on to a grid. The source cube and the target cube will be projected into a common projection for the scipy calculation to be performed. .. .. autoclass:: iris.experimental.regrid.ProjectedUnstructuredLinear :members: :undoc-members: :inherited-members: .. raw:: html This class describes the nearest regridding scheme which uses the scipy.interpolate.griddata to regrid unstructured data on to a grid. The source cube and the target cube will be projected into a common projection for the scipy calculation to be performed. .. Note:: The :class:`iris.analysis.UnstructuredNearest` scheme performs essentially the same job. That calculation is more rigorously correct and may be applied to larger data regions (including global). This one however, where applicable, is substantially faster. .. .. autoclass:: iris.experimental.regrid.ProjectedUnstructuredNearest :members: :undoc-members: :inherited-members: