Added a nojekyll file to display documentation on github pages

.github/workflows/documentation.yaml

@@ -0,0 +1,20 @@
+name: documentation
+
+on:
+  push:
+
+jobs:
+  docs:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: write
+    concurrency:
+      group: ${{ github.workflow }}-${{ github.ref }}
+    steps:
+      - uses: actions/checkout@v3
+      - name: Deploy
+        uses: peaceiris/actions-gh-pages@v3
+        if: github.ref == 'refs/heads/main'
+        with:
+          github_token: ${{ secrets.GITHUB_TOKEN }}
+          publish_dir: ./public

docs/source/conf.py

@@ -17,7 +17,8 @@
     "myst_nb",
     "autoapi.extension",
     "sphinx.ext.napoleon",
-    "sphinx.ext.viewcode"
+    "sphinx.ext.viewcode",
+    "sphinx.ext.githubpages"
 ]
 
 autoapi_dirs = ["../../zarrdataset"]

jupyter_execute/examples/advanced_example_pytorch.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "9c447ef0",
+   "id": "f3a9f6b1",
    "metadata": {},
    "source": [
     "# Integration of ZarrDataset with PyTorch's DataLoader (Advanced)"
@@ -11,7 +11,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "3819451a",
+   "id": "3f7e048c",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -24,7 +24,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "5f56235d",
+   "id": "6086aa43",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -45,7 +45,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "ee28ea66",
+   "id": "df5fa55c",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -60,15 +60,15 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0c9ef47a",
+   "id": "904ba888",
    "metadata": {},
    "source": [
     "### Extracting patches of size 128x128x32 voxels from a three-dimensional image"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "590e9773",
+   "id": "422d652a",
    "metadata": {},
    "source": [
     "Sample the image randomly"
@@ -77,7 +77,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "5c7b24b3",
+   "id": "e02745e0",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -87,7 +87,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ebcad6e2",
+   "id": "bb6e137d",
    "metadata": {},
    "source": [
     "Transform the input data from uint16 to float16 with a torchvision pre-processing pipeline"
@@ -96,7 +96,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "b743b256",
+   "id": "a3769ba3",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -109,7 +109,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ed360d3c",
+   "id": "6d5081f2",
    "metadata": {},
    "source": [
     "Pass the pre-processing function to ZarrDataset to be used when generating the samples.\n",
@@ -120,7 +120,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "f41a29dd",
+   "id": "f916a7e7",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -145,7 +145,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3b108376",
+   "id": "c085f4a6",
    "metadata": {},
    "source": [
     "### Create a ChainDataset from a set of ZarrDatasets that can be put together a single large dataset"
@@ -154,7 +154,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "d860fb62",
+   "id": "0ac8b9d9",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -163,7 +163,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1163e1e3",
+   "id": "46886013",
    "metadata": {},
    "source": [
     "Make sure the chained_zarrdataset_worker_init_fn function is passed to the DataLoader, so the workers can initialize the dataset correctly"
@@ -172,7 +172,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "290966fb",
+   "id": "3afa42ee",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -186,7 +186,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "45bf7f87",
+   "id": "29aee72f",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -211,7 +211,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ae453ed7",
+   "id": "c4c774a8",
    "metadata": {},
    "source": [
     "### Generate a grid with the sampled patches using `torchvision` utilities"
@@ -220,7 +220,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "73546b6b",
+   "id": "e8b997be",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -230,7 +230,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "caa41605",
+   "id": "5de13983",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -243,7 +243,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "f499043b",
+   "id": "4915d39d",
    "metadata": {},
    "outputs": [],
    "source": [