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Changelog.md

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Changelog

Versioning

v0.7.5

  • New normalization mode support for DISCO convolutions
  • More efficient computation of Morlet filter basis
  • Changed default for Morlet filter basis to a Hann window function

v0.7.4

  • New filter basis normalization in DISCO convolutions
  • More robust pre-computation of DISCO convolution tensor
  • Reworked DISCO filter basis datastructure
  • Support for new filter basis types
  • Added Zernike polynomial basis on a disk
  • Added Morlet wavelet basis functions on a spherical disk
  • Cleaning up the SFNO example and adding new Local Spherical Neural Operator model
  • Updated resampling module to extend input signal to the poles if needed
  • Added slerp interpolation to the resampling module
  • Added distributed resampling module

v0.7.3

  • Changing default grid in all SHT routines to equiangular
  • Hotfix to the numpy version requirements

v0.7.2

  • Added resampling modules for convenience
  • Changing behavior of distributed SHT to use dim=-3 as channel dimension
  • Fixing SHT unittests to test SHT and ISHT individually, rather than the roundtrip
  • Changing the way custom CUDA extensions are handled

v0.7.1

  • Hotfix to AMP in SFNO example

v0.7.0

  • CUDA-accelerated DISCO convolutions
  • Updated DISCO convolutions to support even number of collocation points across the diameter
  • Distributed DISCO convolutions
  • Fused quadrature into multiplication with the Psi tensor to lower memory footprint
  • Removed DISCO convolution in the plane to focus on the sphere
  • Updated unit tests which now include tests for the distributed convolutions

v0.6.5

  • Discrete-continuous (DISCO) convolutions on the sphere and in two dimensions
  • DISCO supports isotropic and anisotropic kernel functions parameterized as hat functions
  • Supports regular and transpose convolutions
  • Accelerated spherical DISCO convolutions on GPU via Triton implementation
  • Unittests for DISCO convolutions in tests/test_convolution.py

v0.6.4

  • Reworking distributed to allow for uneven split tensors, effectively removing the necessity of padding the transformed tensors
  • Distributed SHT tests are now using unittest. Test extended to vector SHT versions
  • Tests are defined in torch_harmonics/distributed/distributed_tests.py
  • Base pytorch container version bumped up to 23.11 in Dockerfile

v0.6.3

  • Adding gradient check in unit tests
  • Temporary work-around for NCCL contiguous issues with distributed SHT
  • Refactored examples and documentation
  • Updated SFNO example

v0.6.2

  • Adding github CI
  • Changed SHT modules to convert dtype dynamically when computing the SHT/ISHT
  • Bugfixes to fix importing examples

v0.6.1

  • Minor bugfixes to export SFNO code
  • Readme should now render correctly in PyPI

v0.6.0

  • Added SFNO example
  • Added Shallow Water Equations Dataset for SFNO training
  • Cleanup of the repository and added PyPI
  • Updated Readme

v0.5.0

  • Reworked distributed SHT
  • Module for sampling Gaussian Random Fields on the sphere

v0.4.0

  • Computation of associated Legendre polynomials
    • changed algorithm to compute the associated Legendre polynomials for improved stability
  • Improved Readme

v0.3.0

  • Vector Spherical Harmonic Transforms
    • projects vector-valued fields onto the vector Spherical Harmonics
    • supports computation of div and curl on the sphere
  • New quadrature rules
    • Clenshaw-Curtis quadrature rule
    • Fejér quadrature rule
    • Legendre-Gauss-Lobatto quadrature
  • New notebooks
    • complete with differentiable Shallow Water Solver
    • notebook on quadrature and interpolation
  • Unit tests
  • Refactor of the API

v0.2.0

  • Renaming from torch_sht to torch_harmonics
  • Adding distributed SHT support
  • New logo

v0.1.0

  • Single GPU forward and backward transform
  • Minimal code example and notebook