{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "0",
   "metadata": {},
   "source": [
    "# Visualizing pre-processing results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1",
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import holoviews as hv\n",
    "\n",
    "from hv_anndata import A, register\n",
    "from hv_anndata import scanpy as hv_sc\n",
    "from hv_anndata.plotting import utils as hv_sc_utils\n",
    "\n",
    "register()\n",
    "\n",
    "hv.extension(\"bokeh\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3",
   "metadata": {},
   "outputs": [],
   "source": [
    "import scanpy as sc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4",
   "metadata": {},
   "outputs": [],
   "source": [
    "adata = sc.datasets.pbmc68k_reduced()\n",
    "adata.layers[\"counts\"] = adata.raw.X\n",
    "del adata.raw\n",
    "adata"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5",
   "metadata": {},
   "source": [
    "{func}`scanpy.pl.highest_expr_genes`\n",
    "\n",
    "tool to get the data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6",
   "metadata": {},
   "outputs": [],
   "source": [
    "hv.HeatMap(\n",
    "    hv_sc_utils.highest_expr_genes(adata), [A.obs.index, A.var.index], A.X[:, :]\n",
    ").opts(responsive=True, height=400, xrotation=30)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7",
   "metadata": {},
   "source": [
    "plotting function using above data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8",
   "metadata": {},
   "outputs": [],
   "source": [
    "hv_sc.highest_expr_genes(adata, layer=\"counts\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9",
   "metadata": {},
   "source": [
    "{func}`scanpy.pl.highly_variable_genes`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "10",
   "metadata": {},
   "outputs": [],
   "source": [
    "sc.pp.highly_variable_genes(adata)\n",
    "# sc.pl.highly_variable_genes(adata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "11",
   "metadata": {},
   "outputs": [],
   "source": [
    "hv_sc.highly_variable_genes(adata)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12",
   "metadata": {},
   "source": [
    "{func}`scanpy.pl.scrublet_score_distribution`\n",
    "\n",
    "TODO:\n",
    "- batches\n",
    "\n",
    "missing:\n",
    "- where are the y ticks on the y axis?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "13",
   "metadata": {},
   "outputs": [],
   "source": [
    "adata_sim = sc.pp.scrublet_simulate_doublets(adata)\n",
    "sc.pp.scrublet(adata, adata_sim)\n",
    "# sc.pl.scrublet_score_distribution(adata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "14",
   "metadata": {},
   "outputs": [],
   "source": [
    "hv_sc.scrublet_score_distribution(adata)"
   ]
  }
 ],
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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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