{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "07f7dbb1-63c6-40e4-b0d9-6ec104aa0adc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# !pip install zarr\n",
    "\n",
    "import os\n",
    "import json\n",
    "from pathlib import Path\n",
    "import glob\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import scanpy as sc\n",
    "import pyvips\n",
    "import zarr\n",
    "import geopandas as gpd\n",
    "from shapely.geometry import Polygon\n",
    "from scipy.sparse import csc_matrix\n",
    "\n",
    "import tissuumaps.jupyter as tj\n",
    "from tissuumaps import read_h5ad\n",
    "\n",
    "\n",
    "# ----------------------------\n",
    "# Paths\n",
    "# ----------------------------\n",
    "sample = \"WTA_Preview_FFPE_Cervical_Cancer_outs\"\n",
    "# sample = \"Xenium_Prime_Human_Lymph_Node_Reactive_FFPE_outs\"\n",
    "# sample = \"Xenium_Prime_Ovarian_Cancer_FFPE_XRrun_outs\"\n",
    "# sample = \"Xenium_V1_humanLung_Cancer_FFPE_outs\"\n",
    "\n",
    "\n",
    "xenium_dir = os.path.abspath(f\"../data/instrument_data/{sample}\")\n",
    "basedir = os.path.abspath(f\"../data/processed_data/tissuumaps_h5ad/{sample}\")\n",
    "os.makedirs(basedir, exist_ok=True)\n",
    "\n",
    "out_h5ad_name = f\"{sample}_tmap.h5ad\"\n",
    "out_h5ad = os.path.join(basedir, out_h5ad_name)\n",
    "\n",
    "project_path = os.path.join(basedir, \"_project_h5ad.tmap\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a53c9e37-da32-4583-a74c-604d60df358b",
   "metadata": {},
   "outputs": [],
   "source": [
    "basedir = os.path.abspath(f\"../data/processed_data/tissuumaps_h5ad/{sample}\")\n",
    "# transcript_csv = f\"transcripts_image_space.csv\"\n",
    "transcript_h5ad = f\"transcripts_all_emptyX_tmap.h5ad\"\n",
    "\n",
    "print(basedir)\n",
    "\n",
    "region_files = []\n",
    "\n",
    "for geojson_path in glob.glob(os.path.join(basedir, \"*boundaries*.geojson\")):\n",
    "    geojson_name = os.path.basename(geojson_path)\n",
    "\n",
    "    region_files.append({\n",
    "        \"path\": geojson_name,          # relative path only\n",
    "        \"title\": geojson_name,\n",
    "        \"comment\": geojson_name,\n",
    "        \"autoLoad\": True,\n",
    "    })\n",
    "\n",
    "print(region_files)\n",
    "\n",
    "image_layers = []\n",
    "\n",
    "for tif_path in sorted(\n",
    "    glob.glob(os.path.join(basedir, \"morphology_focus_plane*_pyramid.tif\"))\n",
    "):\n",
    "    name = os.path.basename(tif_path)\n",
    "\n",
    "    image_layers.append({\n",
    "        \"name\": name.replace(\".tif\", \"\"),\n",
    "        \"tileSource\": name + \".dzi\",\n",
    "        \"x\": 0,\n",
    "        \"y\": 0,\n",
    "        \"scale\": 1,\n",
    "        \"rotation\": 0,\n",
    "        \"flip\": False,\n",
    "    })\n",
    "\n",
    "print(f\"Found {len(image_layers)} image layers\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bbcabbbd-3f76-48dd-b589-c80e47fc8cbc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ----------------------------\n",
    "# 5. Generate TissUUmaps project\n",
    "# ----------------------------\n",
    "project = read_h5ad.h5ad_to_tmap(basedir, out_h5ad_name)\n",
    "\n",
    "# Images: all stacked and visible\n",
    "project[\"layers\"] = image_layers\n",
    "\n",
    "project[\"collectionMode\"] = False\n",
    "project[\"compositeMode\"] = \"lighter\"\n",
    "project[\"backgroundColor\"] = \"#000000\"\n",
    "\n",
    "project[\"filters\"] = []\n",
    "project[\"layerFilters\"] = {}\n",
    "project[\"layerOpacities\"] = {str(i): 1 for i in range(len(image_layers))}\n",
    "project[\"layerVisibilities\"] = {str(i): True for i in range(len(image_layers))}\n",
    "\n",
    "# Polygons: autoload\n",
    "project[\"regionFiles\"] = []\n",
    "for rf in region_files:\n",
    "    rf = dict(rf)\n",
    "    rf[\"autoLoad\"] = True\n",
    "    project[\"regionFiles\"].append(rf)\n",
    "\n",
    "for i, mf in enumerate(project.get(\"markerFiles\", [])):\n",
    "    mf.setdefault(\"expectedHeader\", {})\n",
    "    mf[\"expectedHeader\"][\"shape_fixed\"] = \"disc\"\n",
    "    mf[\"expectedHeader\"][\"scale_factor\"] = 1\n",
    "    mf.setdefault(\"expectedRadios\", {})\n",
    "    mf[\"expectedRadios\"][\"shape_fixed\"] = True\n",
    "    mf[\"expectedRadios\"][\"shape_gr\"] = False\n",
    "    mf[\"expectedRadios\"][\"shape_gr_rand\"] = False\n",
    "    mf[\"expectedRadios\"][\"sortby_check\"] = False\n",
    "\n",
    "# Transcripts: autoload default marker layer\n",
    "# if transcript_csv is not None:\n",
    "#     project[\"markerFiles\"].insert(\n",
    "#         0,\n",
    "#         {\n",
    "#             \"path\": transcript_csv,\n",
    "#             \"title\": \"Load transcripts\",\n",
    "#             \"comment\": \"Transcript molecules\",\n",
    "#             \"name\": \"Transcripts\",\n",
    "#             \"uid\": \"transcripts\",\n",
    "#             \"autoLoad\": True,\n",
    "#             \"hideSettings\": True,\n",
    "#             \"expectedHeader\": {\n",
    "#                 \"X\": \"x\",\n",
    "#                 \"Y\": \"y\",\n",
    "#                 \"gb_col\": \"gene\",\n",
    "#                 \"gb_name\": \"\",\n",
    "#                 \"cb_col\": \"\",\n",
    "#                 \"cb_cmap\": \"\",\n",
    "#                 \"scale_factor\": 0.15,\n",
    "#                 \"shape_fixed\": \"disc\",\n",
    "#                 \"opacity\": 0.7,\n",
    "#             },\n",
    "#             \"expectedRadios\": {\n",
    "#                 \"cb_col\": False,\n",
    "#                 \"cb_gr\": True,\n",
    "#                 \"cb_gr_rand\": True,\n",
    "#                 \"cb_gr_dict\": False,\n",
    "#                 \"cb_gr_key\": False,\n",
    "#                 \"pie_check\": False,\n",
    "#                 \"scale_check\": False,\n",
    "#                 \"shape_col\": False,\n",
    "#                 \"shape_fixed\": True,\n",
    "#                 \"shape_gr\": False,\n",
    "#                 \"shape_gr_rand\": False,\n",
    "#                 \"shape_gr_dict\": False,\n",
    "#                 \"sortby_check\": False,\n",
    "#             },\n",
    "#         },\n",
    "#     )\n",
    "\n",
    "project[\"markerFiles\"].insert(\n",
    "    0,\n",
    "    {\n",
    "        \"path\": transcript_h5ad,\n",
    "        \"title\": \"Load transcript AnnData\",\n",
    "        \"comment\": \"All transcript molecules\",\n",
    "        \"name\": \"Transcript AnnData\",\n",
    "        \"uid\": \"transcript_h5ad\",\n",
    "        \"autoLoad\": True,\n",
    "        \"hideSettings\": True,\n",
    "        \"expectedHeader\": {\n",
    "            \"X\": \"/obsm/spatial;0\",\n",
    "            \"Y\": \"/obsm/spatial;1\",\n",
    "            \"gb_col\": \"/obs/gene\",\n",
    "            \"gb_name\": \"\",\n",
    "            \"cb_col\": \"\",\n",
    "            \"cb_cmap\": \"\",\n",
    "            \"scale_factor\": 0.15,\n",
    "            \"shape_fixed\": \"disc\",\n",
    "            \"opacity\": 0.7,\n",
    "        },\n",
    "        \"expectedRadios\": {\n",
    "            \"cb_col\": False,\n",
    "            \"cb_gr\": True,\n",
    "            \"cb_gr_rand\": True,\n",
    "            \"shape_fixed\": True,\n",
    "            \"shape_gr\": False,\n",
    "            \"scale_check\": False,\n",
    "            \"sortby_check\": False,\n",
    "        },\n",
    "    },\n",
    ")\n",
    "\n",
    "# Set autoLoad explicitly by name after insert\n",
    "for mf in project[\"markerFiles\"]:\n",
    "    if mf.get(\"name\") in (\"Transcript AnnData\", \"Categorical observations\"):\n",
    "        mf[\"autoLoad\"] = True\n",
    "    else:\n",
    "        mf[\"autoLoad\"] = False\n",
    "\n",
    "with open(project_path, \"w\") as f:\n",
    "    json.dump(project, f, indent=2)\n",
    "\n",
    "print(\"done\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1ee1ac2d-6de4-4fe2-b31a-90725d67669c",
   "metadata": {},
   "outputs": [],
   "source": [
    "viewer = tj.opentmap(project_path)\n",
    "viewer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "db4873e9-ba2e-4814-80a9-e32f92a5677a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7394d91a-54ad-49b1-834f-bda9f24f4944",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "68db233e-7105-4862-9635-c68875497962",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4c8a97c2-3285-4b9d-8a6c-7bdb6a89c4a8",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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