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The first 'iteration' of the Python redesign is starting to converge - see #237. In a rough order of chronology and/or complexity, the next steps to be tackled in future PRs are as follows:
To Do - Functionality
Implement correlate_tensors:
defcorrelate_tensors(
tensor_1: TensorMap,
tensor_2: TensorMap,
angular_cutoff: Optional[int] =None,
selected_keys: Optional[Labels] =None,
) ->TensorMap:
""" Performs the Clebsch Gordan tensor product of two TensorMaps that correspond to densities or density correlations. Returns a new TensorMap corresponding to a higher correlation-order descriptor. The two input tensors can be single- or multi-center, and of arbitrary (and different) correlation order, but must contain the same samples. """
Ensure torch dispatch works and make the CG code torchscript-able (with @Luthaf)
Speed up wrapper code (i.e. everything that isn't the tensor product operation). Line profiling shows that the pre-calculation (and caching for subsequent but separate calculations) of the components and properties might be a good place to start (with @frostedoyster)
Run systematic benchmarking on sparse vs dense vs sparse w/ Mops. Define when in general it is best to use one over the others, and dynamically change the default based on the input system (with @frostedoyster)
Metadata such as "order_nu" should be associated with the TensorMap and not in the keys - awaiting functionality in metatensor
Later down the line: customizable and arbitrary (non)linear transformations at each iteration (with @agoscinski, thesis dependent)
To Do - Documentation
Include concise but complete explanations of sign conventions (i.e. Sph Harms, Condon Shortley, etc) both in reference to the CG cache implemented (i.e. using wigners) and compared to other rascaline Calculators --> i.e. PowerSpectrum updated to include (-1)^l factor
function that compute metadata should not need to allocate memory for the data arrays. We should have a new EmptyArray class in Python's metatensor API that just track the size of the array but is not allocating memory.
The first 'iteration' of the Python redesign is starting to converge - see #237. In a rough order of chronology and/or complexity, the next steps to be tackled in future PRs are as follows:
To Do - Functionality
correlate_tensors
:To Do - Documentation
wigners
) and compared to other rascaline Calculators --> i.e. PowerSpectrum updated to include (-1)^l factorThe text was updated successfully, but these errors were encountered: