{
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   "cell_type": "markdown",
   "id": "adb3e352-ec0d-44b4-8d5e-b7ab84d9dbce",
   "metadata": {},
   "source": [
    "# `CircularExclusion` Overview"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4ae898fc-477a-419c-8325-2768e658e973",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "46416d10-4fd6-4454-a1c1-f3b9f1826ad6",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import sys\n",
    "import xarray as xr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ad5a56bf-7182-49f0-9e80-d0c8fa3ca33a",
   "metadata": {},
   "outputs": [],
   "source": [
    "try:\n",
    "    from bapsf_motion.motion_builder.exclusions import CircularExclusion\n",
    "except ModuleNotFoundError:\n",
    "    from pathlib import Path\n",
    "\n",
    "    HERE = Path().cwd()\n",
    "    BAPSF_MOTION = (HERE / \"..\" / \"..\" / \"..\" ).resolve()\n",
    "    sys.path.append(str(BAPSF_MOTION))\n",
    "    \n",
    "    from bapsf_motion.motion_builder.exclusions import CircularExclusion\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3a465d6d-ecb1-4bae-94a1-5b562e9bff17",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams.update(\n",
    "    {\n",
    "        # \"figure.figsize\": [12, 0.56 * 12],\n",
    "        \"figure.figsize\": [10, 0.8 * 10],\n",
    "        \"font.size\": 16,\n",
    "    }\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "54f5a53e-ecf0-4778-a753-cc697a7effa6",
   "metadata": {},
   "source": [
    "## LaPD Exclusion in XY\n",
    "\n",
    "Create the seeding boolean mask.  In the boolean mask a `True` value indicates a point allowed for a motion list and a `False` value indicaes an exclusion zone."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f6055f59-3083-4dd6-b817-5469873df2e2",
   "metadata": {},
   "outputs": [],
   "source": [
    "size = 100\n",
    "side = np.linspace(-35, 35, num=size)\n",
    "ds = xr.Dataset(\n",
    "    {\"mask\": ((\"x\", \"y\"), np.ones((size, size), dtype=bool))},\n",
    "    coords={\n",
    "        \"x\": side,\n",
    "        \"y\": side,\n",
    "    },\n",
    ")\n",
    "\n",
    "ds.mask.plot(x=\"x\", y=\"y\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f7dc2dee-6d06-4be8-b65d-4d60c7ef0f16",
   "metadata": {},
   "source": [
    "Add a circular XY exclusion that simulates the LaPD inner diameter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "65a510f8-7617-4604-9ea6-f92565f78032",
   "metadata": {},
   "outputs": [],
   "source": [
    "ex1 = CircularExclusion(ds, radius=30)\n",
    "ds[\"mask\"].plot(x=\"x\", y=\"y\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2468421-47df-45c8-a74c-04ade3cc3a0c",
   "metadata": {},
   "source": [
    "The exclusion configuration is avaibled as a dictionary via the `config` attribute."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7a05b8d8-5f07-4a94-9c9c-3b5eef371ef6",
   "metadata": {},
   "outputs": [],
   "source": [
    "ex1.config"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3cacbe19-9aab-4018-ba13-09e8f8541809",
   "metadata": {},
   "source": [
    "Note that `CircularExclusion` updates the overall mask and stores it's exclusion later into the `xarray.Dataset` as `mask_ex1`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "63a77890-6806-4d17-8c0a-b37a0a549b92",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "441b0c15-a5a1-42b3-b15a-4ee9a51ae020",
   "metadata": {},
   "source": [
    "We can check if a specific point is considered excluded or not."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "efe3a512-1c92-4987-b75d-abfb1be5f3aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "(\n",
    "    ex1.is_excluded((0, 0)),\n",
    "    ex1.is_excluded((-30, 30)),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5cabc0f5-9293-4822-8aee-f0656bf7c4bf",
   "metadata": {},
   "source": [
    "## Let's add a 2nd Circular Exclusion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cf48b209-3027-49da-b716-a19dd6b84702",
   "metadata": {},
   "outputs": [],
   "source": [
    "ex2 = CircularExclusion(ds, radius=20, center=(10.0, 10.0), exclude=\"inside\")\n",
    "ds[\"mask\"].plot(x=\"x\", y=\"y\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9bc16cb2-9aeb-4952-9cac-7d1072846272",
   "metadata": {},
   "source": [
    "Now both exclusion layers are stored in the `Dataset`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1edbd49d-3636-4c92-aadc-9838936ce2dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7bf3ca57-9e40-4660-94d8-5718214c3d92",
   "metadata": {},
   "source": "Note that the `is_exclusion()` function only checks for exclusion from the class instance the point is being checked to.  The exclusion evaluation is done by the overall `MotionBuilder` class.  Please refer to the `MotionBuilder` notebook for further details."
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a421f304-0c41-43b2-a4e9-19c1751d3220",
   "metadata": {},
   "outputs": [],
   "source": [
    "(\n",
    "    ex1.is_excluded((0, 0)),\n",
    "    ex2.is_excluded((0, 0)),\n",
    ")"
   ]
  }
 ],
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