templates/3e_stitch_images.ipynb

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   "source": [
    "# Stitch Images Notebook\n",
    "## This notebook is an example: create a copy before running it or you will get merge conflicts!\n",
    "\n",
    "This notebook will create a single stitched image for each channel in your panel across all of the FOVs in your run, allowing you to quickly inspect your data. \n",
    "\n",
    "**If you have not already extracted your images, please run notebook [3b_extract_images_from_bin](./3b_extract_images_from_bin.ipynb).**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "d09f9697",
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "sys.path.append('../')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "e13c18f8",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from toffy.image_stitching import stitch_images"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cba4089e-c167-4523-b359-1474f63b396e",
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   "source": [
    "## Required variables\n",
    "You will need to define the run name argument for this notebook, with two optional arguments.\n",
    " - `run_name` should contain the exact name of the MIBI run to stitch images for\n",
    " <br> <br>\n",
    " - `sub_dir` optional name of image sub-folder within each fov, if not applicable leave as None\n",
    " - `channel_list` optional channel list specifying which to stitch images for, when left as None will run on all extracted channels "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "83ffed12",
   "metadata": {},
   "outputs": [],
   "source": [
    "# the name of the run\n",
    "run_name = 'YYYY-MM-DD_run_name'\n",
    "\n",
    "sub_dir = None\n",
    "channel_list = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1780ae73-e967-4792-b5de-dcdd3632a0bb",
   "metadata": {},
   "outputs": [],
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    "# path to directory containing the run file,\n",
    "# can be set to None if there's no run file for the images you're stitching\n",
    "base_dir = os.path.join('D:\\\\Data', run_name) \n",
    "\n",
    "# path to directory containing extracted files\n",
    "extraction_dir = os.path.join('D:\\\\Extracted_Images', run_name)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "00c9a15f",
   "metadata": {},
   "source": [
    "## Stitch Images\n",
    "Stitched images are saved to the subdirectory `D:\\\\Extracted_Images\\\\run_name\\\\stitched_images`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "c71b389f",
   "metadata": {},
   "outputs": [],
   "source": [
    "stitch_images(extraction_dir, base_dir, channels=channel_list, img_sub_folder=sub_dir)"
   ]
  }
 ],
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