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Upgraded Documenter compat
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jagot committed Feb 23, 2024
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2 changes: 1 addition & 1 deletion docs/Project.toml
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Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"

[compat]
Documenter = "0.25"
Documenter = "1"
3 changes: 2 additions & 1 deletion docs/make.jl
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Expand Up @@ -14,10 +14,11 @@ makedocs(;
"Newton polynomials" => "newton_polynomials.md",
"φₖ functions" => "phi_functions.md",
],
repo="https://github.com/jagot/MatrixPolynomials.jl/blob/{commit}{path}#L{line}",
repo=Remotes.GitHub("jagot", "MatrixPolynomials.jl"),
sitename="MatrixPolynomials.jl",
authors="Stefanos Carlström <[email protected]>",
doctest=false,
checkdocs=:exports
)

deploydocs(;
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8 changes: 1 addition & 7 deletions docs/src/divided_differences.md
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Expand Up @@ -56,7 +56,7 @@ i.e. the first row of the function ``f`` applied to the matrix
&&&&\zeta_j}.
\end{equation}
```
The right-eigenvectors are given by [Opitz]
The right-eigenvectors are given by [^Opitz]
```math
\begin{equation}
\label{eqn:div-diff-mat-right-eigen}
Expand Down Expand Up @@ -268,12 +268,6 @@ MatrixPolynomials.propagate_div_diff_sin_cos
propagators. Computing, 80(2), 189–201. [DOI:
10.1007/s00607-007-0227-1](http://dx.doi.org/10.1007/s00607-007-0227-1)

[^Kandolf]: Kandolf, P., Ostermann, A., & Rainer, S. (2014). A
residual based error estimate for Leja interpolation of matrix
functions. Linear Algebra and its Applications, 456(nil),
157–173. [DOI:
10.1016/j.laa.2014.04.023](http://dx.doi.org/10.1016/j.laa.2014.04.023)

[^McCurdy]: McCurdy, A. C., Ng, K. C., & Parlett,
B. N. (1984). Accurate computation of divided differences of the
exponential function. Mathematics of Computation, 43(168),
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1 change: 1 addition & 0 deletions docs/src/funcv.md
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Expand Up @@ -10,6 +10,7 @@ LinearAlgebra.mul!(w, funcv::MatrixPolynomials.FuncV, v)

```@docs
MatrixPolynomials.spectral_range
MatrixPolynomials.hermitian_spectral_range
```

### Shapes
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12 changes: 6 additions & 6 deletions docs/src/leja.md
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Expand Up @@ -34,12 +34,12 @@ interpolation points.

MatrixPolynomials.jl provides two methods for generating the Leja
points, [`MatrixPolynomials.Leja`](@ref) and
[`MatrixPolynomials.FastLeja`](@ref). The figure below illustrates the
distribution of Leja points using both methods, on the line
``[-2,2]``, for the [`MatrixPolynomials.Leja`](@ref), an underlying
discretization of 1000 points was employed, and 10 Leja points were
generated. The lower part of the plot shows the estimation of the
[capacity](https://en.wikipedia.org/wiki/Capacity_of_a_set),
[`MatrixPolynomials.FastLeja`](@ref)[^Baglama]. The figure below
illustrates the distribution of Leja points using both methods, on the
line ``[-2,2]``, for the [`MatrixPolynomials.Leja`](@ref), an
underlying discretization of 1000 points was employed, and 10 Leja
points were generated. The lower part of the plot shows the estimation
of the [capacity](https://en.wikipedia.org/wiki/Capacity_of_a_set),
calculated as
```math
C(\{\zeta_{1:m}\}) \approx
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8 changes: 8 additions & 0 deletions docs/src/newton_polynomials.md
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@@ -1,4 +1,5 @@
# Newton polynomials
[^Kandolf]

```@docs
MatrixPolynomials.NewtonPolynomial
Expand All @@ -13,3 +14,10 @@ LinearAlgebra.mul!(w, nmp::MatrixPolynomials.NewtonMatrixPolynomial, A, v)
MatrixPolynomials.NewtonMatrixPolynomialDerivative
MatrixPolynomials.φₖResidualEstimator
```
## Bibliography

[^Kandolf]: Kandolf, P., Ostermann, A., & Rainer, S. (2014). A
residual based error estimate for Leja interpolation of matrix
functions. Linear Algebra and its Applications, 456(nil),
157–173. [DOI:
10.1016/j.laa.2014.04.023](http://dx.doi.org/10.1016/j.laa.2014.04.023)

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