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github-actions[bot]CompatHelper Juliajagot
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CompatHelper: bump compat for ArnoldiMethod to 0.4, (keep existing compat) (#7)
* CompatHelper: bump compat for ArnoldiMethod to 0.4, (keep existing compat) * Updated CompatHelper workflow * Add new compat entry for Statistics * Updated TagBot workflow * Bump version * Imports of targets from ArnoldiMethod.jl * Transitioned documentation plot to Python{Call,Plot} * Upgraded Documenter compat * Fix test --------- Co-authored-by: CompatHelper Julia <compathelper_noreply@julialang.org> Co-authored-by: Stefanos Carlström <stefanos.carlstrom@gmail.com>
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‎.github/workflows/CI.yml

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- run: |
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julia --project=docs -e '
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using Pkg
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pkg"add PyCall PyPlot https://github.com/jagot/Jagot.jl.git https://github.com/jagot/PyPlotRecipes.jl.git Colors SpecialFunctions LinearAlgebra"
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pkg"add PythonCall PythonPlot https://github.com/jagot/Jagot.jl.git Colors SpecialFunctions LinearAlgebra"
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Pkg.develop(PackageSpec(path=pwd()))
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Pkg.instantiate()'
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env:

‎.github/workflows/CompatHelper.yml

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schedule:
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- cron: 0 0 * * *
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workflow_dispatch:
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permissions:
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contents: write
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pull-requests: write
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jobs:
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CompatHelper:
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runs-on: ubuntu-latest
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steps:
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- name: Pkg.add("CompatHelper")
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run: julia -e 'using Pkg; Pkg.add("CompatHelper")'
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- name: CompatHelper.main()
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- name: Check if Julia is already available in the PATH
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id: julia_in_path
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run: which julia
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continue-on-error: true
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- name: Install Julia, but only if it is not already available in the PATH
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uses: julia-actions/setup-julia@v1
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with:
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version: '1'
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arch: ${{ runner.arch }}
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if: steps.julia_in_path.outcome != 'success'
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- name: "Add the General registry via Git"
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run: |
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import Pkg
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ENV["JULIA_PKG_SERVER"] = ""
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Pkg.Registry.add("General")
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shell: julia --color=yes {0}
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- name: "Install CompatHelper"
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run: |
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import Pkg
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name = "CompatHelper"
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uuid = "aa819f21-2bde-4658-8897-bab36330d9b7"
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version = "3"
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Pkg.add(; name, uuid, version)
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shell: julia --color=yes {0}
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- name: "Run CompatHelper"
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run: |
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import CompatHelper
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CompatHelper.main()
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shell: julia --color=yes {0}
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env:
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GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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COMPATHELPER_PRIV: ${{ secrets.DOCUMENTER_KEY }}
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run: julia -e 'using CompatHelper; CompatHelper.main()'
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# COMPATHELPER_PRIV: ${{ secrets.COMPATHELPER_PRIV }}

‎.github/workflows/TagBot.yml

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types:
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- created
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workflow_dispatch:
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inputs:
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lookback:
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default: 3
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permissions:
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actions: read
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checks: read
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contents: write
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deployments: read
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issues: read
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discussions: read
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packages: read
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pages: read
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pull-requests: read
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repository-projects: read
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security-events: read
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statuses: read
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jobs:
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TagBot:
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if: github.event_name == 'workflow_dispatch' || github.actor == 'JuliaTagBot'
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- uses: JuliaRegistries/TagBot@v1
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with:
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token: ${{ secrets.GITHUB_TOKEN }}
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# Edit the following line to reflect the actual name of the GitHub Secret containing your private key
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ssh: ${{ secrets.DOCUMENTER_KEY }}
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# ssh: ${{ secrets.NAME_OF_MY_SSH_PRIVATE_KEY_SECRET }}

‎.gitignore

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/docs/build/
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/docs/site/
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/docs/src/figures/
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/docs/Manifest.toml
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.CondaPkg/

‎Project.toml

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name = "MatrixPolynomials"
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uuid = "bd52c179-449c-4965-a404-68b29a447f4b"
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authors = ["Stefanos Carlström <stefanos.carlstrom@gmail.com>"]
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version = "0.1.2"
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version = "0.1.3"
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[deps]
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ArnoldiMethod = "ec485272-7323-5ecc-a04f-4719b315124d"
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UnicodeFun = "1cfade01-22cf-5700-b092-accc4b62d6e1"
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[compat]
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ArnoldiMethod = "0.2.0"
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ArnoldiMethod = "0.2.0, 0.4"
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Compat = "3.26.0, 4"
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Formatting = "0.4"
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Parameters = "0.12"
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SpecialFunctions = "1.3, 2"
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Statistics = "1"
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UnicodeFun = "0.4"
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julia = "1.3"
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‎docs/Project.toml

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Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
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[compat]
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Documenter = "0.25"
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Documenter = "1"

‎docs/make.jl

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"Newton polynomials" => "newton_polynomials.md",
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"φₖ functions" => "phi_functions.md",
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],
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repo="https://github.com/jagot/MatrixPolynomials.jl/blob/{commit}{path}#L{line}",
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repo=Remotes.GitHub("jagot", "MatrixPolynomials.jl"),
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sitename="MatrixPolynomials.jl",
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authors="Stefanos Carlström <stefanos.carlstrom@gmail.com>",
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doctest=false,
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checkdocs=:exports
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)
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deploydocs(;

‎docs/plots.jl

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using PyPlot
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using PythonPlot
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using Jagot.plotting
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plot_style("ggplot")
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‎docs/src/divided_differences.md

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&&&&\zeta_j}.
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\end{equation}
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```
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The right-eigenvectors are given by [Opitz]
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The right-eigenvectors are given by [^Opitz]
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```math
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\begin{equation}
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\label{eqn:div-diff-mat-right-eigen}
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propagators. Computing, 80(2), 189–201. [DOI:
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10.1007/s00607-007-0227-1](http://dx.doi.org/10.1007/s00607-007-0227-1)
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[^Kandolf]: Kandolf, P., Ostermann, A., & Rainer, S. (2014). A
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residual based error estimate for Leja interpolation of matrix
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functions. Linear Algebra and its Applications, 456(nil),
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157–173. [DOI:
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10.1016/j.laa.2014.04.023](http://dx.doi.org/10.1016/j.laa.2014.04.023)
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[^McCurdy]: McCurdy, A. C., Ng, K. C., & Parlett,
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B. N. (1984). Accurate computation of divided differences of the
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exponential function. Mathematics of Computation, 43(168),

‎docs/src/funcv.md

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```@docs
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MatrixPolynomials.spectral_range
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MatrixPolynomials.hermitian_spectral_range
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```
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### Shapes

‎docs/src/leja.md

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

‎docs/src/newton_polynomials.md

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

‎src/MatrixPolynomials.jl

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using Parameters
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using LinearAlgebra
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using ArnoldiMethod
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using ArnoldiMethod: SR, SI, LR, LI
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using SpecialFunctions
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const Γ = gamma
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const lnΓ = loggamma

‎test/newton.jl

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@testset "Matrix polynomials" begin
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@testset "Inhomogeneous coupled ODEs, $kind" for (kind,m,tol) in [(:real,43,1e-12), (:complex,60,1e-12)]
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n = 10 # Number of ODEs
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Y₀ = 1.0*ones(n)
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Y₀ = 1.0*ones(kind == :real ? Float64 : ComplexF64, n)
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G = -3*ones(n) # Inhomogeneous terms
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n_discr = 1000 # Number of points spanning eigenspectrum interval

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