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   "source": [
    "# Tutorial 7: Angular scans\n",
    "\n",
    "As a package dedicated to GID data, `pygid` supports measurements with a varying angle of incidence (`ai`).\n",
    "\n",
    "The angle of incidence `ai` can be provided in several ways:\n",
    "\n",
    "- **Single value**\n",
    "  ```python\n",
    "  ai = 0.01\n",
    "  ```\n",
    "- **List of values**\n",
    "  ```python\n",
    "  ai = [0.0, 0.01, 0.02]\n",
    "  ```\n",
    "- **Automatically parsed from a scan command** (start, stop, number-1).\n",
    "```python\n",
    "scan = \"ascan om 0.0400 0.1000 12\"\n",
    "```\n",
    "or\n",
    "```python\n",
    "scan = \"0.0400 0.1000 12\"\n",
    "```\n",
    "\n",
    "NOTE: For angular scans, the number of angles (ai) in ExpParams should match the number of loaded images."
   ],
   "id": "617f6418251cf81"
  },
  {
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     "end_time": "2026-02-09T17:53:59.946930Z",
     "start_time": "2026-02-09T17:53:59.942287Z"
    }
   },
   "cell_type": "code",
   "source": [
    "from pygid.datasets import get_dataset\n",
    "\n",
    "# Download example dataset from Zenodo\n",
    "try:\n",
    "    files = get_dataset(\"tutorial_07\")\n",
    "    poni_path = files[\"poni\"]\n",
    "    mask_path = files[\"mask\"]\n",
    "    # several files for batch processing\n",
    "    data_path = files[\"data\"]\n",
    "except:\n",
    "    print(\"Dataset download skipped on Read the Docs.\")"
   ],
   "id": "25b1340933d39802",
   "outputs": [],
   "execution_count": 2
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "#### Single image for a single angle of incidence",
   "id": "8e5c87abc0054bed"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-02-09T17:57:49.852862Z",
     "start_time": "2026-02-09T17:57:49.761101Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import pygid\n",
    "\n",
    "params = pygid.ExpParams(\n",
    "    poni_path=poni_path,\n",
    "    mask_path=mask_path,\n",
    "    ai=0.004,                       # angle of incidence (degrees)\n",
    "    fliplr=True,\n",
    "    flipud=True\n",
    ")\n",
    "\n",
    "matrix = pygid.CoordMaps(\n",
    "    params,  # pygid.ExpParams\n",
    "    vert_positive=True,\n",
    "    hor_positive=True,\n",
    ")\n",
    "\n",
    "analysis = pygid.Conversion(\n",
    "    matrix=matrix,\n",
    "    path=data_path,\n",
    "    dataset='/entry_0000/ESRF-ID10/eiger4m/data',\n",
    "    frame_num = 0,                  # corresponding image\n",
    ")\n",
    "print(f\"ai: {params.ai}, number of images: {len(analysis.img_raw)}\")"
   ],
   "id": "82ab191f9e6a5d19",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ai: 0.004, number of images: 1\n"
     ]
    }
   ],
   "execution_count": 9
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "#### List of images, list of angles",
   "id": "a71456aeb9961d6a"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-02-09T17:57:43.165100Z",
     "start_time": "2026-02-09T17:57:42.949957Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import pygid\n",
    "\n",
    "params = pygid.ExpParams(\n",
    "    poni_path=poni_path,\n",
    "    mask_path=mask_path,\n",
    "    ai=[0.065, 0.07, 0.075],       # angles of incidence (degrees)\n",
    "    fliplr=True,\n",
    "    flipud=True\n",
    ")\n",
    "\n",
    "matrix = pygid.CoordMaps(\n",
    "    params,  # pygid.ExpParams\n",
    "    vert_positive=True,\n",
    "    hor_positive=True,\n",
    ")\n",
    "\n",
    "analysis = pygid.Conversion(\n",
    "    matrix=matrix,\n",
    "    path=data_path,\n",
    "    dataset='/entry_0000/ESRF-ID10/eiger4m/data',\n",
    "    frame_num = [6,7,8],           # corresponding images\n",
    ")\n",
    "\n",
    "print(f\"ai: {params.ai}, number of images: {len(analysis.img_raw)}\")"
   ],
   "id": "3aa8df31b1362eaa",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ai: [0.065, 0.07, 0.075], number of images: 3\n"
     ]
    }
   ],
   "execution_count": 8
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "#### List of images, scan command",
   "id": "d2aa4465d0c6099a"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-02-09T17:58:13.619747Z",
     "start_time": "2026-02-09T17:58:13.144072Z"
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   "cell_type": "code",
   "source": [
    "params = pygid.ExpParams(\n",
    "    poni_path=poni_path,          # path to the PONI file\n",
    "    mask_path=mask_path,\n",
    "    scan = \"ascan om 0.0400 0.1000 12\",                       # angle of incidence (degrees)\n",
    "    fliplr=True,\n",
    "    flipud=True\n",
    ")\n",
    "\n",
    "matrix = pygid.CoordMaps(\n",
    "    params,  # pygid.ExpParams\n",
    "    vert_positive=True,\n",
    "    hor_positive=True,\n",
    ")\n",
    "\n",
    "analysis = pygid.Conversion(\n",
    "    matrix=matrix,\n",
    "    path=data_path,\n",
    "    dataset='/entry_0000/ESRF-ID10/eiger4m/data',\n",
    "    frame_num = None,           # all images\n",
    ")\n",
    "\n",
    "\n",
    "print(f\"ai: {params.ai}, number of images: {len(analysis.img_raw)}\")"
   ],
   "id": "264a1da28b48ba2a",
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO - ai list calculated: [0.04, 0.045, 0.05, 0.055, 0.06, 0.065, 0.07, 0.075, 0.08, 0.085, 0.09, 0.095, 0.1]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ai: [0.04, 0.045, 0.05, 0.055, 0.06, 0.065, 0.07, 0.075, 0.08, 0.085, 0.09, 0.095, 0.1], number of images: 13\n"
     ]
    }
   ],
   "execution_count": 11
  },
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   "metadata": {},
   "cell_type": "code",
   "outputs": [],
   "execution_count": null,
   "source": "",
   "id": "11a7b36ca13e2b1e"
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