{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## How to use ciso on structured grids"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-09-29T15:02:47.061039Z",
     "iopub.status.busy": "2026-09-29T15:02:47.060791Z",
     "iopub.status.idle": "2026-09-29T15:02:48.875283Z",
     "shell.execute_reply": "2026-09-29T15:02:48.874275Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading data from 'https://github.com/ioos/ciso/releases/download/v0.2.2.post0/Averages_Best_Excluding_Day1.nc' to file '/home/runner/.cache/pooch/7fda05e350e2b6024d65024f525963ce-Averages_Best_Excluding_Day1.nc'.\n"
     ]
    }
   ],
   "source": [
    "import warnings\n",
    "\n",
    "import iris\n",
    "import pooch\n",
    "\n",
    "fname = \"Averages_Best_Excluding_Day1.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:b5446c930003b91b3c35204e39d7beb89da8c16c1f3c2b343a5563a65ecd9265\",\n",
    ")\n",
    "\n",
    "\n",
    "with warnings.catch_warnings():\n",
    "    warnings.simplefilter(\"ignore\")\n",
    "    cubes = iris.load_raw(fname)\n",
    "\n",
    "# Last time step.\n",
    "salt = cubes.extract_cube(\"sea_water_salinity\")[-1, ...]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-09-29T15:02:48.877140Z",
     "iopub.status.busy": "2026-09-29T15:02:48.876857Z",
     "iopub.status.idle": "2026-09-29T15:02:48.884727Z",
     "shell.execute_reply": "2026-09-29T15:02:48.883917Z"
    }
   },
   "outputs": [],
   "source": [
    "from netCDF4 import Dataset\n",
    "\n",
    "with Dataset(fname) as nc:\n",
    "    lon = nc[\"lon_rho\"][:]\n",
    "    lat = nc[\"lat_rho\"][:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-09-29T15:02:48.886398Z",
     "iopub.status.busy": "2026-09-29T15:02:48.886235Z",
     "iopub.status.idle": "2026-09-29T15:02:48.935635Z",
     "shell.execute_reply": "2026-09-29T15:02:48.934683Z"
    }
   },
   "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": "2026-09-29T15:02:48.937342Z",
     "iopub.status.busy": "2026-09-29T15:02:48.937163Z",
     "iopub.status.idle": "2026-09-29T15:02:48.950438Z",
     "shell.execute_reply": "2026-09-29T15:02:48.949445Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "from ciso import zslice\n",
    "\n",
    "p0 = -250\n",
    "\n",
    "isoslice = zslice(q.astype(np.float64), p, p0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-09-29T15:02:48.952601Z",
     "iopub.status.busy": "2026-09-29T15:02:48.952282Z",
     "iopub.status.idle": "2026-09-29T15:02:49.236258Z",
     "shell.execute_reply": "2026-09-29T15:02:49.235433Z"
    }
   },
   "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",
    "extent = [lon.min(), lon.max(), lat.min(), lat.max()]\n",
    "\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.set_extent(extent)\n",
    "    ax.coastlines(\"50m\")\n",
    "    return fig, ax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-09-29T15:02:49.238525Z",
     "iopub.status.busy": "2026-09-29T15:02:49.238250Z",
     "iopub.status.idle": "2026-09-29T15:02:49.629247Z",
     "shell.execute_reply": "2026-09-29T15:02:49.628345Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x1300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from numpy import ma\n",
    "\n",
    "fig, ax = make_map()\n",
    "\n",
    "cs = ax.pcolormesh(lon, lat, ma.masked_invalid(isoslice))\n",
    "\n",
    "kw = {\"shrink\": 0.5, \"orientation\": \"vertical\", \"extend\": \"both\"}\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": 1
}