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Source code for iris.experimental.stratify

# Copyright Iris contributors
# This file is part of Iris and is released under the LGPL license.
# See COPYING and COPYING.LESSER in the root of the repository for full
# licensing details.
Routines for putting data on new strata (aka. isosurfaces), often in the
Z direction.


from functools import partial

import numpy as np
import stratify

from iris.coords import AuxCoord, Coord, DimCoord
from iris.cube import Cube

def _copy_coords_without_z_dim(src, tgt, z_dim):
    Helper function to copy across non z-dimenson coordinates between cubes.

    src : :class:`~iris.cube.Cube`
        Incoming cube containing the coordinates to be copied from.

    tgt : :class:`~iris.cube.Cube`
        Outgoing cube for the coordinates to be copied to.

    z_dim : int
        Dimension within the `src` cube that is the z-dimension.
        This dimension will not be copied. For example, the incoming
        z-dimension cube has model level_height, whilst the outgoing
        z-dimension cube has pressure.

    # Copy across non z-dimension coordinates.
    for coord in src.dim_coords:
        [dim] = src.coord_dims(coord)
        if dim != z_dim:
            tgt.add_dim_coord(coord.copy(), dim)

    for coord in src.aux_coords:
        dims = src.coord_dims(coord)
        if z_dim not in dims:
            tgt.add_aux_coord(coord.copy(), dims)

    for coord in src.derived_coords:
        dims = src.coord_dims(coord)
        if z_dim not in dims:
            tgt.add_aux_coord(coord.copy(), dims)

[docs]def relevel(cube, src_levels, tgt_levels, axis=None, interpolator=None): """ Interpolate the cube onto the specified target levels, given the source levels of the cube. For example, suppose we have two datasets `P(i,j,k)` and `H(i,j,k)` and we want `P(i,j,H)`. We call :func:`relevel` with `cube=P`, `src_levels=H` and `tgt_levels` being an array of the values of `H` we would like. This routine is especially useful for computing isosurfaces of phenomenon that are generally monotonic in the direction of interpolation, such as height/pressure or salinity/depth. Args: cube : :class:`~iris.cube.Cube` The phenomenon data to be re-levelled. src_levels : :class:`~iris.cube.Cube`, :class:`~iris.coord.Coord` or string Describes the source levels of the `cube` that will be interpolated over. The `src_levels` must be in the same system as the `tgt_levels`. The dimensions of `src_levels` must be broadcastable to the dimensions of the `cube`. Note that, the coordinate name containing the source levels in the `cube` may be provided. tgt_levels : array-like Describes the target levels of the `cube` to be interpolated to. The `tgt_levels` must be in the same system as the `src_levels`. The dimensions of the `tgt_levels` must be broadcastable to the dimensions of the `cube`, except in the nominated axis of interpolation. axis : int, :class:`~iris.coords.Coord` or string The axis of interpolation. Defaults to the first dimension of the `cube`, which is typically the z-dimension. Note that, the coordinate name specifying the z-dimension of the `cube` may be provided. interpolator : callable or None The interpolator to use when computing the interpolation. The function will be passed the following positional arguments:: (tgt-data, src-data, cube-data, axis-of-interpolation) If the interpolator is None, :func:`stratify.interpolate` will be used with linear interpolation and NaN extrapolation. An example of constructing an alternative interpolation scheme:: from functools import partial interpolator = partial(stratify.interpolate, interpolation=stratify.INTERPOLATE_NEAREST, extrapolation=stratify.EXTRAPOLATE_LINEAR) """ # Identify the z-coordinate within the phenomenon cube. if axis is None: axis = 0 if isinstance(axis, (str, Coord)): [axis] = cube.coord_dims(axis) # Get the source level data. if isinstance(src_levels, str): src_data = cube.coord(src_levels).points elif isinstance(src_levels, Coord): src_data = src_levels.points else: src_data = # The dimensions of cube and src_data must be broadcastable. try: cube_data, src_data = np.broadcast_arrays(, src_data) except ValueError: emsg = ( "Cannot broadcast the cube and src_levels with " "shapes {} and {}." ) raise ValueError(emsg.format(cube.shape, src_data.shape)) tgt_levels = np.asarray(tgt_levels) tgt_aux_dims = axis if tgt_levels.ndim != 1: # The dimensions of tgt_levels must be broadcastable to cube # in everything but the interpolation axis - otherwise raise # an exception. dim_delta = cube_data.ndim - tgt_levels.ndim # The axis is relative to the cube. Calculate the axis of # interplation relative to the tgt_levels. tgt_axis = axis - dim_delta # Calculate the cube shape without the axis of interpolation. data_shape = list(cube_data.shape) data_shape.pop(axis) # Calculate the tgt_levels shape without the axis of interpolation. target_shape = list(tgt_levels.shape) target_shape.pop(tgt_axis) # Now ensure that the shapes are broadcastable. try: np.broadcast_arrays(np.empty(data_shape), np.empty(target_shape)) except ValueError: emsg = ( "Cannot broadcast the cube and tgt_levels with " "shapes {} and {}, whilst ignoring axis of interpolation." ) raise ValueError(emsg.format(cube_data.shape, tgt_levels.shape)) # Calculate the dimensions over the cube that the tgt_levels span. tgt_aux_dims = list(range(cube_data.ndim))[dim_delta:] if interpolator is None: # Use the default stratify interpolator. interpolator = partial( stratify.interpolate, interpolation="linear", extrapolation="nan" ) # Now perform the interpolation. new_data = interpolator(tgt_levels, src_data, cube_data, axis=axis) # Create a result cube with the correct shape and metadata. result = Cube(new_data, **cube.copy().metadata._asdict()) # Copy across non z-dimension coordinates from the source cube # to the result cube. _copy_coords_without_z_dim(cube, result, axis) kwargs = dict( standard_name=src_levels.standard_name, long_name=src_levels.long_name, var_name=src_levels.var_name, units=src_levels.units, attributes=src_levels.attributes, ) # Add our new interpolated coordinate to the result cube. try: coord = DimCoord(tgt_levels, **kwargs) result.add_dim_coord(coord, axis) except ValueError: # Attach the data to the trailing dimensions. coord = AuxCoord(tgt_levels, **kwargs) result.add_aux_coord(coord, tgt_aux_dims) return result