{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## How to use ciso on unstructured grids"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-09-29T15:02:35.593589Z",
     "iopub.status.busy": "2026-09-29T15:02:35.593421Z",
     "iopub.status.idle": "2026-09-29T15:02:38.612786Z",
     "shell.execute_reply": "2026-09-29T15:02:38.611690Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading data from 'https://github.com/ioos/ciso/releases/download/v0.2.2.post0/NECOFS_GOM3_FORECAST.nc' to file '/home/runner/.cache/pooch/9c4b68fb11876bd3d409003c22c81edb-NECOFS_GOM3_FORECAST.nc'.\n"
     ]
    }
   ],
   "source": [
    "import warnings\n",
    "\n",
    "import iris\n",
    "import pooch\n",
    "\n",
    "fname = \"NECOFS_GOM3_FORECAST.nc\"\n",
    "version = \"v0.2.2.post0\"\n",
    "url = f\"https://github.com/ioos/ciso/releases/download/{version}/{fname}\"\n",
    "\n",
    "fname = pooch.retrieve(\n",
    "    url,\n",
    "    known_hash=\"sha256:05589ca949e112f60b6a8ca1ac0eb1f1c6239659b4443151731a177135fe58d0\",\n",
    ")\n",
    "\n",
    "\n",
    "with warnings.catch_warnings():\n",
    "    warnings.simplefilter(\"ignore\")\n",
    "    cubes = iris.load_raw(fname)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-09-29T15:02:38.614537Z",
     "iopub.status.busy": "2026-09-29T15:02:38.614295Z",
     "iopub.status.idle": "2026-09-29T15:02:38.634033Z",
     "shell.execute_reply": "2026-09-29T15:02:38.633144Z"
    }
   },
   "outputs": [],
   "source": [
    "salt = cubes.extract_cube(\"sea_water_salinity\")[-1, ...]\n",
    "\n",
    "lon = salt.coord(axis=\"X\").points\n",
    "lat = salt.coord(axis=\"Y\").points"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-09-29T15:02:38.635840Z",
     "iopub.status.busy": "2026-09-29T15:02:38.635656Z",
     "iopub.status.idle": "2026-09-29T15:02:38.675808Z",
     "shell.execute_reply": "2026-09-29T15:02:38.674839Z"
    }
   },
   "outputs": [],
   "source": [
    "p = salt.coord(\"sea_surface_height_above_reference_ellipsoid\").points\n",
    "q = salt.data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-09-29T15:02:38.677576Z",
     "iopub.status.busy": "2026-09-29T15:02:38.677409Z",
     "iopub.status.idle": "2026-09-29T15:02:38.692240Z",
     "shell.execute_reply": "2026-09-29T15:02:38.691318Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "from ciso import zslice\n",
    "\n",
    "p0 = -25\n",
    "isoslice = zslice(q, p, -50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-09-29T15:02:38.694239Z",
     "iopub.status.busy": "2026-09-29T15:02:38.693918Z",
     "iopub.status.idle": "2026-09-29T15:02:38.698059Z",
     "shell.execute_reply": "2026-09-29T15:02:38.697309Z"
    }
   },
   "outputs": [],
   "source": [
    "from numpy import ma\n",
    "\n",
    "# Cannot tricontourf with NaNs.\n",
    "isoslice = ma.masked_invalid(isoslice)\n",
    "vmin, vmax = isoslice.min(), isoslice.max()\n",
    "isoslice = isoslice.filled(fill_value=-999)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-09-29T15:02:38.699610Z",
     "iopub.status.busy": "2026-09-29T15:02:38.699451Z",
     "iopub.status.idle": "2026-09-29T15:02:39.784436Z",
     "shell.execute_reply": "2026-09-29T15:02:39.783565Z"
    }
   },
   "outputs": [],
   "source": [
    "import cartopy.crs as ccrs\n",
    "import matplotlib.pyplot as plt\n",
    "from cartopy.mpl.gridliner import LATITUDE_FORMATTER, LONGITUDE_FORMATTER\n",
    "\n",
    "_plate_carree = ccrs.PlateCarree()\n",
    "\n",
    "\n",
    "def make_map(projection=_plate_carree):\n",
    "    fig, ax = plt.subplots(\n",
    "        figsize=(9, 13),\n",
    "        subplot_kw={\"projection\": projection},\n",
    "    )\n",
    "    gl = ax.gridlines(draw_labels=True)\n",
    "    gl.right_labels = gl.top_labels = False\n",
    "    gl.xformatter = LONGITUDE_FORMATTER\n",
    "    gl.yformatter = LATITUDE_FORMATTER\n",
    "    ax.coastlines(\"50m\")\n",
    "    return fig, ax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-09-29T15:02:39.786429Z",
     "iopub.status.busy": "2026-09-29T15:02:39.785995Z",
     "iopub.status.idle": "2026-09-29T15:02:42.235214Z",
     "shell.execute_reply": "2026-09-29T15:02:42.234323Z"
    }
   },
   "outputs": [],
   "source": [
    "import gridgeo\n",
    "\n",
    "grid = gridgeo.GridGeo(fname, standard_name=\"sea_water_salinity\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-09-29T15:02:42.237064Z",
     "iopub.status.busy": "2026-09-29T15:02:42.236854Z",
     "iopub.status.idle": "2026-09-29T15:02:43.489339Z",
     "shell.execute_reply": "2026-09-29T15:02:43.488499Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/runner/work/ciso/ciso/.pixi/envs/py314/lib/python3.14/site-packages/cartopy/io/__init__.py:241: DownloadWarning: Downloading: https://naturalearth.s3.amazonaws.com/50m_physical/ne_50m_coastline.zip\n",
      "  warnings.warn(f'Downloading: {url}', DownloadWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x1300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = make_map()\n",
    "extent = [lon.min(), lon.max(), lat.min(), lat.max()]\n",
    "ax.set_extent(extent)\n",
    "\n",
    "levels = np.linspace(vmin, vmax, 20)\n",
    "\n",
    "kw = {\"alpha\": 0.9, \"levels\": levels}\n",
    "cs = ax.tricontourf(grid.triang, isoslice, **kw)\n",
    "\n",
    "kw = {\"shrink\": 0.5, \"orientation\": \"vertical\"}\n",
    "cbar = fig.colorbar(cs, **kw)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.14.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}