Dataset dimension/axis label renaming #322
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This commit adds support for dimension renaming with net.imagej.Dataset objects. The _rename_dataset_dims() function matches the _rename_xarray_dims() function in that it *only* renames the dimensions of the input data. It does not transpose the data array or modify the coordinates/calibration. Users should use transpose and permute with their respective xarray and dataset objects. The _rename_dataset_dims() function gets the axis type from new dim order sequencs and creates a new axis with the old scale and origin values, preserving the axis coordinates. This implementation only supports DefaultLinearAxis.
Instead of creating new DefaultLinearAxis or EnumeratedAxis, simply set the axis type on the existing axes. Both DefaultLinearAxis and EnumeratedAxis both inherit net.imagej.TypedAxis.
This commit makes updates the dataset to dataset conversion tests with new and expected dimension label outcomes.
This commit adds a new section to the Working-with-Images notebook demonstrating how to rename the dimension labels on both Python and Java images. Note that I added this section as 6.11 and incremented all following heading numbers by 1.
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This PR address issue #304 by adding support for dimension label renaming on
net.imagej.Datasetobjects via theto_dataset()method (with dim order hints). Below is a list of what this PR brings:net.imagej.DatasetDefaultLinearAxisandEnumeratedAxistype.Datasetconversion tests to test dim renaming.06-Working-with-images, 6.11, demonstrating how to use the renaming features.