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Remove redundant _laplacian_1neg_spectra(spec::SSpectra) method #38

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Merged
merged 1 commit into from
Aug 5, 2025
Merged

Remove redundant _laplacian_1neg_spectra(spec::SSpectra) method #38

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1 change: 1 addition & 0 deletions CHANGELOG.md
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Expand Up @@ -8,6 +8,7 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),

### Changed

- Remove the unnecessary and redundant `_laplacian_1neg_spectra(spec::SSpectra)` method from `src/laplacian_s_spectra.jl` (this method literally did nothing whatsoever; I left it in from a previous design approach) (#38).
- Changed `check_spectrum_integrality` to compute the real integer eigenvalues lazily (comparison was already lazy, but taking the real part and rounding was not) (#37).

## [0.1.0] - 2025-08-01
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83 changes: 0 additions & 83 deletions src/laplacian_s_spectra.jl
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Expand Up @@ -159,96 +159,13 @@ end

"""
_laplacian_1neg_spectra(L) -> SSpectra
_laplacian_1neg_spectra(spec) -> SSpectra

[TODO: Write here]
"""
function _laplacian_1neg_spectra(L::AbstractMatrix{<:Integer})
return _classified_laplacian_1neg_spectra(classify_laplacian(L))
end

function _laplacian_1neg_spectra(spec::SSpectra)
if spec.S != (-1, 0, 1)
throw(
ArgumentError(
"Expected `{-1, 0, 1}`-spectra` to compute `{-1, 1}`-spectra, got $(spec.S)-spectra",
),
)
end

L = copy(spec.matrix)
n = size(L, 1)
S = (-1, 1)
multiplicities = copy(spec.multiplicities)

eigenspaces_01neg = spec.s_eigenspaces

#= If `n > 1` is odd, then all non-kernel eigenvectors must be orthogonal to the
all-ones vector and thus are precluded from having all entries from {-1, 1}. If `n = 1`,
then the kernel is the only eigenspace, so we need not handle that case separately. =#
if iseven(n)
s_eigenspaces = OrderedDict{Int,Matrix{Int}}()
s_eigenbases = OrderedDict{Int,Union{Nothing,Matrix{Int}}}()

for eigval in keys(multiplicities)
multi = multiplicities[eigval]
eigvecs = Iterators.filter(
col -> !any(iszero, col), eachcol(eigenspaces_01neg[eigval])
)

if isempty(eigvecs)
eigenspace = Matrix{Int}(undef, n, 0)
eigenbasis = nothing
else
eigenspace = stack(eigvecs)
pot_eigenbasis = _extract_independent_cols(eigenspace)

if size(pot_eigenbasis, 2) < multi
eigenbasis = nothing
else
eigenbasis = pot_eigenbasis
end
end

s_eigenspaces[eigval] = eigenspace
s_eigenbases[eigval] = eigenbasis
end
else
dim_kernel = multiplicities[0]
kernel_vecs = Iterators.filter(
col -> !any(iszero, col), eachcol(eigenspaces_01neg[0])
)

if isempty(kernel_vecs)
kernel = Matrix{Int}(undef, n, 0)
null_basis = nothing
else
kernel = stack(kernel_vecs)
pot_null_basis = _extract_independent_cols(kernel)

if size(pot_null_basis, 2) < dim_kernel
null_basis = nothing
else
null_basis = pot_null_basis
end
end

s_eigenspaces = OrderedDict(
eigval => Matrix{Int}(undef, n, 0) for eigval in keys(multiplicities)
)
s_eigenspaces[0] = kernel

s_eigenbases = OrderedDict{Int,Union{Nothing,Matrix{Int}}}(
eigval => nothing for eigval in keys(multiplicities)
)
s_eigenbases[0] = null_basis
end

s_diagonalizable = all(!isnothing, values(s_eigenbases))

return SSpectra(L, S, multiplicities, s_eigenspaces, s_eigenbases, s_diagonalizable)
end

"""
_classified_laplacian_01neg_spectra(CL) -> SSpectra

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