nixify notebook

This commit is contained in:
Laureηt 2024-09-07 13:44:56 +02:00
parent 456f1234a2
commit 3c21d9a900
Signed by: Laurent
SSH key fingerprint: SHA256:pb5NrYg80So5z9hmqQFPmp//sgr+DFeJkKhmGyU2NLk
6 changed files with 136 additions and 60 deletions

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@ -1,30 +1,32 @@
{
"nodes": {
"flake-utils": {
"flake-parts": {
"inputs": {
"systems": "systems"
"nixpkgs-lib": [
"nixpkgs"
]
},
"locked": {
"lastModified": 1687709756,
"narHash": "sha256-Y5wKlQSkgEK2weWdOu4J3riRd+kV/VCgHsqLNTTWQ/0=",
"owner": "numtide",
"repo": "flake-utils",
"rev": "dbabf0ca0c0c4bce6ea5eaf65af5cb694d2082c7",
"lastModified": 1725234343,
"narHash": "sha256-+ebgonl3NbiKD2UD0x4BszCZQ6sTfL4xioaM49o5B3Y=",
"owner": "hercules-ci",
"repo": "flake-parts",
"rev": "567b938d64d4b4112ee253b9274472dc3a346eb6",
"type": "github"
},
"original": {
"owner": "numtide",
"repo": "flake-utils",
"owner": "hercules-ci",
"repo": "flake-parts",
"type": "github"
}
},
"nixpkgs": {
"locked": {
"lastModified": 1687898314,
"narHash": "sha256-B4BHon3uMXQw8ZdbwxRK1BmxVOGBV4viipKpGaIlGwk=",
"lastModified": 1725432240,
"narHash": "sha256-+yj+xgsfZaErbfYM3T+QvEE2hU7UuE+Jf0fJCJ8uPS0=",
"owner": "NixOS",
"repo": "nixpkgs",
"rev": "e18dc963075ed115afb3e312b64643bf8fd4b474",
"rev": "ad416d066ca1222956472ab7d0555a6946746a80",
"type": "github"
},
"original": {
@ -36,8 +38,9 @@
},
"root": {
"inputs": {
"flake-utils": "flake-utils",
"nixpkgs": "nixpkgs"
"flake-parts": "flake-parts",
"nixpkgs": "nixpkgs",
"systems": "systems"
}
},
"systems": {

64
flake.nix Normal file
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@ -0,0 +1,64 @@
{
inputs = {
nixpkgs.url = "github:NixOS/nixpkgs/nixos-unstable";
flake-parts = {
url = "github:hercules-ci/flake-parts";
inputs.nixpkgs-lib.follows = "nixpkgs";
};
systems.url = "github:nix-systems/default";
};
outputs = {flake-parts, ...} @ inputs:
flake-parts.lib.mkFlake {inherit inputs;} {
systems = import inputs.systems;
perSystem = {
pkgs,
system,
...
}: rec {
devShells.default = pkgs.mkShell {
packages = packages.notebooks.buildInputs;
};
packages.notebooks = pkgs.stdenvNoCC.mkDerivation {
name = "notebooks";
src = ./julia;
dontUnpack = true;
buildInputs = [
(pkgs.julia.withPackages [
"Pluto"
"Plots"
"Statistics"
"PlutoUI"
"LinearAlgebra"
"StatsPlots"
"Distributions"
"MAT"
"DSP"
])
];
buildPhase = ''
# copy the notebooks, Pluto needs write permission
cp $src/notebook.jl index.jl
cp $src/donnees.mat donnees.mat
chmod +w index.jl
# julia needs permission to create .julia directory
export HOME=$TMPDIR
# run and export the notebooks
julia $src/export_html.jl index.jl
'';
installPhase = ''
mkdir -p $out
cp index.html $out
cp -r $src/content $out
'';
};
};
};
}

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@ -1,13 +0,0 @@
{
"editor.formatOnSave": true,
"files.insertFinalNewline": true,
"editor.trimAutoWhitespace": true,
"files.trimTrailingWhitespace": true,
"terminal.integrated.env.linux": {
"JULIA_PROJECT": "@."
},
"[julia]": {
"editor.tabSize": 2,
"editor.insertSpaces": true
}
}

42
julia/export_html.jl Normal file
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@ -0,0 +1,42 @@
using Pluto
function export_html(notebook_path, html_path)
# load notebook
notebook = Pluto.load_notebook(Pluto.tamepath(notebook_path));
topology = Pluto.updated_topology(notebook.topology, notebook, notebook.cells)
# create offline workspace
workspace = Pluto.WorkspaceManager.make_workspace(
(
Pluto.ServerSession(),
notebook,
),
is_offline_renderer=true,
)
# run all the cells of the notebook
for cell in notebook.cells
Pluto.run_single!(
workspace,
cell,
topology.nodes[cell],
topology.codes[cell],
)
end
# convert notebook outputs to html
html_contents = Pluto.generate_html(notebook);
# write to html file
open(html_path, "w") do html_file
write(html_file, html_contents);
end
end
# get cli args
for arg in ARGS
filename, _ = splitext(arg)
html_path = filename * ".html"
println("Exporting $arg to $html_path")
export_html(arg, filename * ".html")
end

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@ -1,19 +0,0 @@
{
inputs = {
nixpkgs.url = "github:NixOS/nixpkgs/nixos-unstable";
flake-utils.url = "github:numtide/flake-utils";
};
outputs = { self, nixpkgs, flake-utils }:
flake-utils.lib.eachDefaultSystem (system:
let pkgs = nixpkgs.legacyPackages.${system};
in {
devShell = pkgs.mkShell {
buildInputs = with pkgs; [
julia
ffmpeg-full # https://github.com/JuliaIO/FFMPEG.jl/issues/48#issuecomment-898340527
patchelf
];
};
});
}

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@ -435,7 +435,7 @@ On peut montrer que le vecteur de paramètres estimé en moindres carrés est di
$$\beta \hookrightarrow \mathcal{N} ( \beta^*, \sigma^2 ( A^\intercal A )^{-1})$$
On trace alors sur la figure suivante, avec un tracé continu la distribution théorique des $\beta$, et via un histogramme la distribution que l'on obtient par estimation aux moindres carrés (sur un grand nombre de points, n=$(n))
On trace alors sur la figure suivante, avec un tracé continu la distribution théorique des $\beta$, et via un histogramme la distribution que l'on obtient par estimation aux moindres carrés (sur un grand nombre de points, n=1000)
"""
# ╔═╡ a8843a99-cd5d-47fa-810b-68b56e405af9
@ -452,7 +452,6 @@ begin
λ: $(λ_slider)
On observe que via les moindres carrés classiques, notre régression a souvent tendance à [overfitter](https://fr.wikipedia.org/wiki/Surapprentissage) les points d'apprentissage. Pour remédier à ce problème, nous pouvons introduire un hyperparamètre $\lambda$ qui nous permettra de pénaliser l'overfitting (par régularisation).
"""
end
@ -3953,27 +3952,30 @@ version = "1.4.1+0"
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