Update phonors requirement from <0.5 to <0.7

[dependabot]

Updates the requirements on phonors to permit the latest version.

Changelog

Sourced from phonors's changelog.

[0.6.0] - 2026-10-02

Added

• pp_collision, collision_at_grid_point, and collision_at_grid_points_batched accept a new argument degenerate_ids. It is an integer array of the shape of frequencies, and for each band it gives the index of the first band of the degenerate set that the band belongs to. When degenerate_ids is given, the tetrahedron-method integration weights of each triplet are averaged over the degenerate bands at q' and over those at q''. The tetrahedron method makes the weight of each band from its frequencies at the neighbouring grid points, where the degeneracy is lifted, so bands that are degenerate at q' or q'' have different weights. After the averaging, they have equal weights. A pair of bands at q' and q'' is treated as having zero weight only when every pair in its degenerate block has zero weight. The default None leaves the weights unchanged.

[0.5.0] - 2026-09-26

Changed

• grid_index_from_address, which took a single address, is replaced by grid_indices_from_addresses, which takes addresses of shape (n, 3) and returns their GR grid-point indices.

Fixed

• The tetrahedron-method integration weight at a frequency point exactly equal to a vertex frequency was zero. It is now the limit from above, so the weight is continuous there. This changes, e.g., isotope scattering rates, whose frequency points are the frequencies of the grid point itself.

[0.4.0] - 2026-09-25

Changed

• integration_weights_at_grid_points, triplets_integration_weights, pp_collision, collision_at_grid_point, and collision_at_grid_points_batched now accept relative_grid_address of shape (24 * n, 4, 3), i.e., n concatenated sets of 24 tetrahedra, and average the tetrahedron-method weights over the sets. The previous (24, 4, 3) input is the n = 1 case and behaves as before.

[0.3.0] - 2026-06-27

Added

• eigvalsh_batch kernel for diagonalizing a batch of Hermitian dynamical matrices. Each matrix is solved single-threaded while the batch is parallelized across cores, giving a large speedup over numpy.linalg.eigh for dense meshes of small matrices. Numerically a drop-in for numpy.linalg.eigh: eigenvalues are returned in ascending order, eigenvectors as columns, and the input matrices are left unmodified.
• eigvalsh_values_batch kernel: same as eigvalsh_batch but computes only the eigenvalues, skipping the eigenvectors and their output buffer. A

... (truncated)

Commits

• f520bbf Merge pull request #36 from phonopy/release/v0.6.0
• b596dd7 Release v0.6.0
• 5b41205 Merge pull request #35 from phonopy/degenerate-weights-zero-flags
• 81e11e6 Average weights and reduce iw_zero by AND over each degenerate block
• 30d1f68 Merge pull request #34 from phonopy/degenerate-tetrahedron-weights
• 322b2df Average tetrahedron weights over degenerate bands in pp_collision when degene...
• 5ea0ba3 Merge pull request #33 from phonopy/release/v0.5.0
• 455f472 Release v0.5.0
• e5b916e Merge pull request #32 from phonopy/tetrahedron-vertex-ties
• 2b96c29 Give the tetrahedron-method weight at a frequency equal to a vertex its limit...
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