{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "0",
   "metadata": {},
   "source": [
    "# Violin"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1",
   "metadata": {},
   "outputs": [],
   "source": [
    "import holoviews as hv\n",
    "\n",
    "from hv_anndata.interface import register\n",
    "\n",
    "register()\n",
    "\n",
    "hv.extension(\"bokeh\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import anndata as ad\n",
    "import pooch\n",
    "import scanpy as sc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3",
   "metadata": {},
   "outputs": [],
   "source": [
    "EXAMPLE_DATA = pooch.create(\n",
    "    path=pooch.os_cache(\"scverse_tutorials\"),\n",
    "    base_url=\"doi:10.6084/m9.figshare.22716739.v1/\",\n",
    ")\n",
    "EXAMPLE_DATA.load_registry_from_doi()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4",
   "metadata": {},
   "outputs": [],
   "source": [
    "samples = {\n",
    "    \"s1d1\": \"s1d1_filtered_feature_bc_matrix.h5\",\n",
    "    \"s1d3\": \"s1d3_filtered_feature_bc_matrix.h5\",\n",
    "}\n",
    "adatas = {}\n",
    "\n",
    "for sample_id, filename in samples.items():\n",
    "    path = EXAMPLE_DATA.fetch(filename)\n",
    "    sample_adata = sc.read_10x_h5(path)\n",
    "    sample_adata.var_names_make_unique()\n",
    "    adatas[sample_id] = sample_adata\n",
    "\n",
    "adata = ad.concat(adatas, label=\"sample\")\n",
    "adata.obs_names_make_unique()\n",
    "print(adata.obs[\"sample\"].value_counts())\n",
    "adata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5",
   "metadata": {},
   "outputs": [],
   "source": [
    "adata.var[\"mt\"] = adata.var_names.str.startswith(\"MT-\")\n",
    "adata.var[\"ribo\"] = adata.var_names.str.startswith((\"RPS\", \"RPL\"))\n",
    "adata.var[\"hb\"] = adata.var_names.str.contains(\"^HB[^(P)]\")\n",
    "\n",
    "sc.pp.calculate_qc_metrics(\n",
    "    adata, qc_vars=[\"mt\", \"ribo\", \"hb\"], inplace=True, log1p=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6",
   "metadata": {},
   "outputs": [],
   "source": [
    "sc.pl.violin(\n",
    "    adata,\n",
    "    [\"n_genes_by_counts\", \"total_counts\", \"pct_counts_mt\"],\n",
    "    jitter=0.4,\n",
    "    multi_panel=True,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7",
   "metadata": {},
   "outputs": [],
   "source": [
    "violins = [\n",
    "    hv.Violin(adata, vdims=i).opts(\n",
    "        ylabel=\"Value\",\n",
    "        title=i.split(\".\")[-1],  # drop the 'obs.'\n",
    "        show_grid=True,\n",
    "        ylim=(0, None),\n",
    "    )\n",
    "    for i in [\"obs.n_genes_by_counts\", \"obs.total_counts\", \"obs.pct_counts_mt\"]\n",
    "]\n",
    "hv.Layout(violins).opts(axiswise=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
   "display_name": "hv-anndata",
   "language": "python",
   "name": "hv-anndata"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.7"
  }
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 "nbformat": 4,
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