Doc: add a tutorial on how to publish reconstructed volume to drac / icat

doc/tutorials/img/publish_to_drac.svg

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+               id="image23483"
+               x="0.71037143"
+               y="278.56134" />
+          </g>
+        </g>
+      </g>
+    </g>
+  </g>
+</svg>

doc/tutorials/index.rst

@@ -26,3 +26,8 @@ Tutorials
       :img-top: img/volumes.svg
 
       :doc:`volume`
+
+   .. grid-item-card::
+      :img-top: img/publish_to_drac.svg
+
+      :doc:`publish_processed_data_to_data_portal`

doc/tutorials/publish_processed_data_to_data_portal.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "287b637a-4a01-4c11-81b8-68404d4c0727",
+   "metadata": {},
+   "source": [
+    "# How to publish reconstructed volume to the data portal ?\n",
+    "\n",
+    "This tutorial explains how to publish a reconstructed volume (done by nabu) to the (esrf) data portal.\n",
+    "\n",
+    "Today the esrf data portal catalog is based on drac (sucessor of icat). At switching is fresh you should consider icat == drac as both name can be used."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "dae0f793-0a6b-440c-8bae-d6781b144bad",
+   "metadata": {},
+   "source": [
+    "## drac processed dataset\n",
+    "\n",
+    "At volume level we are only interested on the **drac processed dataset**. drac raw dataset exists but they are publish by bliss.\n",
+    "\n",
+    "A **drac processed dataset** is related to:\n",
+    "\n",
+    "* one or several raw datasets (usually one but it can be several in the case of a stiching for example) (*a*)\n",
+    "* a set of metadata keys (voxel size, phase retrievel options...) (*b*)\n",
+    "* one beamline (*c*)\n",
+    "* one proposal (*d*)\n",
+    "* one dataset (*e*)\n",
+    "* one folder (the folder containing the reconstructed volume) (*f*)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "868b2c98-0bb3-43de-b0ce-c14daa2fbbd2",
+   "metadata": {},
+   "source": [
+    "## retrieve all the data needed for icat\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a7254799-34f7-474e-9674-9a02874cd1ba",
+   "metadata": {},
+   "source": [
+    "### (*a*) `raw` parameter\n",
+    "\n",
+    "path to the raw datasets. source(s) of the processed dataset. It should be a tuple but it can be tuple of a single element.\n",
+    "\n",
+    "You can get the original dataset path from an instance of `TomoScanBaseInstance` then calling the `get_bliss_original_files()`.\n",
+    "\n",
+    "warning: this path can contain some '/mnt/multipath-shares' prefix that should be pass to icat/drac."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f0b764b9-93bd-46f5-bdda-ae93f1a3af40",
+   "metadata": {},
+   "source": [
+    "### (*b*) `metadata` parameter\n",
+    "\n",
+    "The metadata to be published to Icat can be obtained from an instance of a `VolumeBase` by calling the `build_drac_metadata` function.\n",
+    "\n",
+    "For example for an HDF5Volume you can have:\n",
+    "\n",
+    "```\n",
+    "volume = HDF5Volume(\n",
+    "    file_path=...,\n",
+    "    data_path=...,\n",
+    ")\n",
+    "\n",
+    "drac_metadata = volume.build_drac_metadata()\n",
+    "```\n",
+    "\n",
+    "note: there is a tutorial on volumes for more information.\n",
+    "\n",
+    "**warning**: at the moment the drac metadata will not contain the 'Sample_name' field which is mandatory (without there will be no processing done). So you will need to add it.\n",
+    "\n",
+    "```\n",
+    "drac_metadata[\"Sample_name\"] = ...\n",
+    "```\n",
+    "\n",
+    "It can be obtain from the `TomoScanBaseInstance` by calling `scan.sample_name`\n",
+    "\n",
+    "*note*: available drac keys are defined [here](https://gitlab.esrf.fr/icat/hdf5-master-config/-/blob/master/hdf5_cfg.xml?ref_type=heads) (see `Tomo` group, `reconstruction` section)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2c10b63a-b52e-4cff-8dea-e3b6f9105f74",
+   "metadata": {},
+   "source": [
+    "### (*c*) `beamline` parameter\n",
+    "\n",
+    "this is the name of the beamline like 'bm05', 'bm18'..."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c7ceb617-b64f-46c9-bfa4-8fa888f50b6b",
+   "metadata": {},
+   "source": [
+    "### (*d*) `proposal` parameter\n",
+    "\n",
+    "name of the proposal."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "45a211a4-e203-4517-8edb-1e7515beab01",
+   "metadata": {},
+   "source": [
+    "### (*e*) `dataset` parameter\n",
+    "\n",
+    "name of the dataset. This is the (processed) dataset in the drac context.\n",
+    "\n",
+    "This dataset will create a key with the folder path at drac level and it must be unique.\n",
+    "\n",
+    "The default value we propose is 'reconstructed_volumes'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0e6ce848-cc68-47bf-bb4f-65083bbf789c",
+   "metadata": {},
+   "source": [
+    "### (*f*) `path` parameter\n",
+    "\n",
+    "This is the path to the folder containing the reconstructed volume (by nabu).\n",
+    "\n",
+    "**warning**: all files contained in this folder will be published to icat. There is no mecanism to publish a single file or a set of file.\n",
+    "\n",
+    "Here is the recommanded structure if path == 'reconstructed_volumes' and for a HDF5 rconstruction:\n",
+    "\n",
+    "```\n",
+    "reconstructed_volumes\n",
+    "    |\n",
+    "    |------ nabu_rec.hdf5                                - nabu reconstructed volume master file  (1)\n",
+    "    |------ nabu_rec \n",
+    "    |         |---------- nabu_rec_0000_0256.hdf5        - nabu reconstructed volume sub file 1\n",
+    "    |------ gallery                                      - gallery related to the processed dataset (2) \n",
+    "    |         |------ screenshot_1.png\n",
+    "    |         |------ screenshot_2.png\n",
+    "    |------ nabu_cfg_files                               - folder containing nabu configuration files (3)\n",
+    "              |------ nabi_config.cfg\n",
+    "``` \n",
+    "(1) The nabu reconstructions. It can be replaced by a folder containing a volume with .tiff file for example\n",
+    "\n",
+    "(2) **optional**. A set of image (.png or .jpg) to be link to the reconstructed volume. Like 3 slices along each axis.\n",
+    "\n",
+    "(3) nabu_cfg_files: location of the configuration used to obtain the volume(s). In the future it should be used to reprocess a volume."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "28d6a1e3-2616-4112-a90d-736d6793ddd5",
+   "metadata": {},
+   "source": [
+    "## publication to drac / icat\n",
+    "\n",
+    "To publish a **processed dataset** to icat we can use [pyicat_plus](https://gitlab.esrf.fr/icat/pyicat-plus)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "eee28397-a05f-4aaa-a748-5bfa2d3e7944",
+   "metadata": {},
+   "source": [
+    "### Instantiate the `IcatClient`\n",
+    "\n",
+    "``` python\n",
+    "from pyicat_plus.client.main import IcatClient \n",
+    "icat_client = IcatClient(\n",
+    "    metadata_urls=(\"bcu-mq-01.esrf.fr:61613\", \"bcu-mq-02.esrf.fr:61613\")\n",
+    ")\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "047debaa-bac2-431a-8c99-d1411aa73c71",
+   "metadata": {},
+   "source": [
+    "### Publish to icat\n",
+    "\n",
+    "``` python\n",
+    " icat_client.store_processed_data(\n",
+    "    raw=raw,  # (a)\n",
+    "    metadata=metadata,  # (b)\n",
+    "    beamline=\"id16a\",  # (c)\n",
+    "    proposal=self.inputs.proposal, # (d)\n",
+    "    dataset=\"reconstructed_volumes\",\n",
+    "    path=path,\n",
+    ")\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1d4bee56-b109-4f38-9b34-66171c45b661",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}