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Docs: fix build, highlight non-square options #363

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Jun 5, 2024
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Docs: fix build, highlight non-square options #363

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02be357
Highlight non-square options
timholy Jun 3, 2024
991a955
Fix doc builds
timholy Jun 3, 2024
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3 changes: 2 additions & 1 deletion docs/Project.toml
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Original file line number Diff line number Diff line change
@@ -1,5 +1,6 @@
[deps]
Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
IterativeSolvers = "42fd0dbc-a981-5370-80f2-aaf504508153"

[compat]
Documenter = "~0.26, 0.27, 1.0, 1.1"
Documenter = "1"
1 change: 1 addition & 0 deletions docs/make.jl
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Expand Up @@ -10,6 +10,7 @@ makedocs(
),
doctest = false,
clean = true,
checkdocs = :none, # consider changing to :exports, but, e.g., `?IterativeSolvers` itself seems silly to include in the docs
sitename = "IterativeSolvers.jl",
pages = [
"Home" => "index.md",
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7 changes: 6 additions & 1 deletion docs/src/index.md
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Expand Up @@ -8,6 +8,8 @@ For more information on future methods have a look at the package [roadmap](http

## What method should I use for linear systems?

### Square linear systems

When solving linear systems $Ax = b$ for a square matrix $A$ there are quite some options. The typical choices are listed below:

| Method | When to use it |
Expand All @@ -22,7 +24,10 @@ We also offer [Chebyshev iteration](@ref Chebyshev) as an alternative to Conjuga

Stationary methods like [Jacobi](@ref), [Gauss-Seidel](@ref), [SOR](@ref) and [SSOR](@ref) can be used as smoothers to reduce high-frequency components in the error in just a few iterations.

When solving **least-squares** problems we currently offer just [LSMR](@ref LSMR) and [LSQR](@ref LSQR).
### Non-square systems: least squares

When solving **least-squares** problems we currently offer [LSMR](@ref LSMR) and [LSQR](@ref LSQR).
LSMR generally converges more quickly than LSQR.

## Eigenproblems and SVD

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