{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "nbsphinx": "hidden"
   },
   "source": [
    "# Vitessce Widget Tutorial"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualization of 3k PBMC reference"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Import dependencies\n",
    "\n",
    "We need to import the classes and functions that we will be using from the corresponding packages."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from os.path import join, isfile, isdir\n",
    "from urllib.request import urlretrieve\n",
    "from anndata import read_h5ad\n",
    "import scanpy as sc\n",
    "\n",
    "from vitessce import (\n",
    "    VitessceConfig,\n",
    "    Component as cm,\n",
    "    CoordinationType as ct,\n",
    "    AnnDataWrapper,\n",
    ")\n",
    "from vitessce.data_utils import (\n",
    "    optimize_adata,\n",
    "    VAR_CHUNK_SIZE,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Download the dataset\n",
    "\n",
    "Download `pbmc3k_final.h5ad` from https://seurat.nygenome.org/pbmc3k_final.h5ad"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "adata_filepath = join(\"data\", \"pbmc3k_final.h5ad\")\n",
    "if not isfile(adata_filepath):\n",
    "    os.makedirs(\"data\", exist_ok=True)\n",
    "    urlretrieve('https://seurat.nygenome.org/pbmc3k_final.h5ad', adata_filepath)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Load the dataset\n",
    "\n",
    "Load the dataset using AnnData's `read_h5ad` function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "adata = read_h5ad(adata_filepath)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.1 Save the AnnData object to Zarr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "zarr_filepath = join(\"data\", \"pbmc3k_final.zarr\")\n",
    "if not isdir(zarr_filepath):\n",
    "    adata = optimize_adata(\n",
    "        adata,\n",
    "        obs_cols=[\"leiden\"],\n",
    "        obsm_keys=[\"X_umap\", \"X_pca\"],\n",
    "        optimize_X=True,\n",
    "    )\n",
    "    adata.write_zarr(zarr_filepath, chunks=[adata.shape[0], VAR_CHUNK_SIZE])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Create a Vitessce view config\n",
    "\n",
    "Define the data and views you would like to include in the widget."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "vc = VitessceConfig(schema_version=\"1.0.15\", name='PBMC Reference')\n",
    "dataset = vc.add_dataset(name='PBMC 3k').add_object(AnnDataWrapper(\n",
    "    adata_path=zarr_filepath,\n",
    "    obs_set_paths=[\"obs/leiden\"],\n",
    "    obs_set_names=[\"Leiden\"],\n",
    "    obs_embedding_paths=[\"obsm/X_umap\", \"obsm/X_pca\"],\n",
    "    obs_embedding_names=[\"UMAP\", \"PCA\"],\n",
    "    obs_feature_matrix_path=\"X\"\n",
    "))\n",
    "\n",
    "umap = vc.add_view(cm.SCATTERPLOT, dataset=dataset, mapping=\"UMAP\")\n",
    "pca = vc.add_view(cm.SCATTERPLOT, dataset=dataset, mapping=\"PCA\")\n",
    "cell_sets = vc.add_view(cm.OBS_SETS, dataset=dataset)\n",
    "genes = vc.add_view(cm.FEATURE_LIST, dataset=dataset)\n",
    "heatmap = vc.add_view(cm.HEATMAP, dataset=dataset)\n",
    "\n",
    "vc.layout((umap / pca) | ((cell_sets | genes) / heatmap));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. Create the Vitessce widget"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A widget can be created with the `.widget()` method on the config instance. Here, the `proxy=True` parameter allows this widget to be used in a cloud notebook environment, such as Binder."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "vw = vc.widget()\n",
    "vw"
   ]
  }
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