{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "b73c76ce-38ac-4282-a1f1-802d61cd9c92",
   "metadata": {},
   "source": [
    "# Figure 6. Maps of time mean precipitation rate\n",
    "[Skip code and jump to the figure](#Show-the-figure)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d241d0d0-c777-4ab4-bffd-5b231b8621b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "from dataclasses import dataclass, field\n",
    "from functools import partial\n",
    "from typing import Optional\n",
    "\n",
    "import cmcrameri\n",
    "import cmocean\n",
    "import iris\n",
    "import matplotlib.colors as mcol\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from aeolus.calc import calc_derived_cubes, precip_sum, zonal_mean\n",
    "from aeolus.coord import ensure_bounds\n",
    "from aeolus.io import load_data\n",
    "from aeolus.model import lfric\n",
    "from aeolus.plot import (\n",
    "    add_custom_legend,\n",
    "    all_sim_file_label,\n",
    "    capitalise,\n",
    "    cube_minmeanmax_str,\n",
    "    figsave,\n",
    "    linspace_pm1,\n",
    "    subplot_label_generator,\n",
    "    tex2cf_units,\n",
    ")\n",
    "from matplotlib.offsetbox import AnchoredText"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "62c1ac4a-3a92-42c2-9e3f-891fb94b647b",
   "metadata": {},
   "source": [
    "Local modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5958b357-763b-4031-9614-3259e62eadde",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import paths\n",
    "from common import CONST, DAYSIDE, DC, KW_ZERO_LINE, N_RES, NIGHTSIDE, SIMULATIONS"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eac28614-ff47-4023-89e7-7d7d4f5f8a09",
   "metadata": {},
   "source": [
    "Show all simulations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "041de538-d851-4312-bb83-9d7a2ffa7451",
   "metadata": {},
   "outputs": [],
   "source": [
    "show_sim = [*SIMULATIONS.keys()]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "438fdcdc-8125-4e76-ae6f-148feb120c98",
   "metadata": {},
   "source": [
    "## Load regridded time-mean data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6868ba1e-72ac-4eba-aa5c-355d3e34be98",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Combine two datasets into one cube list\n",
    "dset = {}\n",
    "for sim_label in show_sim:\n",
    "    dset_averages = dset[sim_label] = load_data(\n",
    "        paths.data_proc\n",
    "        / SIMULATIONS[sim_label].work_name\n",
    "        / f\"{SIMULATIONS[sim_label].work_name}_averages_*_time_mean_and_regr_{N_RES}.nc\".lower()\n",
    "    )\n",
    "    dset_inst_diag = load_data(\n",
    "        paths.data_proc\n",
    "        / SIMULATIONS[sim_label].work_name\n",
    "        / f\"{SIMULATIONS[sim_label].work_name}_inst_diag_*_time_mean_and_regr_{N_RES}.nc\".lower()\n",
    "    )\n",
    "    dset_averages = iris.cube.CubeList(\n",
    "        cube\n",
    "        for cube in dset_averages\n",
    "        if cube.var_name\n",
    "        not in [\n",
    "            \"tot_col_w_kinetic_energy\",\n",
    "            \"tot_col_uv_kinetic_energy\",\n",
    "            \"cell_area\",\n",
    "        ]\n",
    "    )\n",
    "    dset[sim_label] = dset_averages + dset_inst_diag"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2870653-9a9b-428c-a6fc-5949359b0811",
   "metadata": {},
   "source": [
    "## Make plots"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf772847-6de1-4842-bb49-59e50c018740",
   "metadata": {},
   "source": [
    "Define coordinate points and labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d11d3a5b-d792-4b38-958e-cfccc4f8620f",
   "metadata": {},
   "outputs": [],
   "source": [
    "lons = dset[sim_label].extract(DC.relax.x)[0].coord(lfric.x).points\n",
    "lats = dset[sim_label].extract(DC.relax.y)[0].coord(lfric.y).points\n",
    "heights = dset[sim_label].extract(DC.relax.z)[0].coord(lfric.z).points\n",
    "\n",
    "coord_mappings = {\n",
    "    \"longitude\": dict(ticks=np.arange(-180, 181, 60), units=\"degrees\"),\n",
    "    \"latitude\": dict(ticks=np.arange(-90, 91, 30), units=\"degrees\"),\n",
    "    \"level_height\": dict(ticks=np.arange(0, 41, 5), units=\"km\"),\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87586b6b-b080-4d13-be71-3095335b08d8",
   "metadata": {},
   "source": [
    "Define diagnostics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "b924b436-c121-41d2-bcbc-c21cb708e648",
   "metadata": {},
   "outputs": [],
   "source": [
    "@dataclass\n",
    "class Diag:\n",
    "    recipe: callable\n",
    "    title: str\n",
    "    units: str\n",
    "    fmt: str\n",
    "    kw_plt: dict = field(default_factory=dict)\n",
    "    method: str = \"contourf\"\n",
    "\n",
    "\n",
    "prec_levels = [0.1, 0.25, 0.5, 1, 2, 4, 8, 16, 32, 64]\n",
    "prec_colors = cmocean.cm.rain(np.linspace(0, 1, len(prec_levels) - 1))\n",
    "prec_cmap, prec_norm = mcol.from_levels_and_colors(prec_levels, prec_colors)\n",
    "\n",
    "\n",
    "DIAGS = {\n",
    "    \"t_sfc\": Diag(\n",
    "        recipe=lambda cl: cl.extract_cube(lfric.t_sfc),\n",
    "        title=\"Surface Temperature\",\n",
    "        units=\"$K$\",\n",
    "        method=\"pcolormesh\",\n",
    "        kw_plt=dict(\n",
    "            cmap=cmocean.cm.thermal,\n",
    "            vmin=180,\n",
    "            vmax=290,\n",
    "            rasterized=True,\n",
    "        ),\n",
    "        fmt=\"auto\",\n",
    "    ),\n",
    "    \"toa_olr\": Diag(\n",
    "        recipe=lambda cl: cl.extract_cube(lfric.toa_olr),\n",
    "        title=\"TOA Outgoing Longwave Radiation\",\n",
    "        units=\"$W$ $m^{-2}$\",\n",
    "        method=\"pcolormesh\",\n",
    "        kw_plt=dict(\n",
    "            cmap=cmocean.cm.gray,\n",
    "            # levels=np.arange(180, 291, 10),\n",
    "            vmin=90,\n",
    "            vmax=240,\n",
    "            # extend=\"both\",\n",
    "            rasterized=True,\n",
    "        ),\n",
    "        fmt=\"auto\",\n",
    "    ),\n",
    "    \"caf\": Diag(\n",
    "        recipe=lambda cl: cl.extract_cube(lfric.caf),\n",
    "        title=\"Cloud Fraction\",\n",
    "        units=\"%\",\n",
    "        method=\"contourf\",\n",
    "        kw_plt=dict(cmap=cmocean.cm.gray, levels=np.arange(0, 101, 10)),\n",
    "        fmt=\"auto\",\n",
    "    ),\n",
    "    \"caf_vl\": Diag(\n",
    "        recipe=lambda cl: cl.extract_cube(\"very_low_type_cloud_amount\"),\n",
    "        title=\"Very Low Cloud Fraction\",\n",
    "        units=\"%\",\n",
    "        method=\"contourf\",\n",
    "        kw_plt=dict(cmap=cmcrameri.cm.batlowK, levels=np.arange(0, 101, 10)),\n",
    "        fmt=\"auto\",\n",
    "    ),\n",
    "    \"caf_l\": Diag(\n",
    "        recipe=lambda cl: cl.extract_cube(\"low_type_cloud_amount\"),\n",
    "        title=\"Low Cloud Fraction\",\n",
    "        units=\"%\",\n",
    "        method=\"contourf\",\n",
    "        kw_plt=dict(cmap=cmcrameri.cm.batlowK, levels=np.arange(0, 101, 10)),\n",
    "        fmt=\"auto\",\n",
    "    ),\n",
    "    \"caf_m\": Diag(\n",
    "        recipe=lambda cl: cl.extract_cube(\"medium_type_cloud_amount\"),\n",
    "        title=\"Medium Cloud Fraction\",\n",
    "        units=\"%\",\n",
    "        method=\"contourf\",\n",
    "        kw_plt=dict(cmap=cmcrameri.cm.batlowK, levels=np.arange(0, 101, 10)),\n",
    "        fmt=\"auto\",\n",
    "    ),\n",
    "    \"caf_h\": Diag(\n",
    "        recipe=lambda cl: cl.extract_cube(\"high_type_cloud_amount\"),\n",
    "        title=\"High Cloud Fraction\",\n",
    "        units=\"%\",\n",
    "        method=\"contourf\",\n",
    "        kw_plt=dict(cmap=cmcrameri.cm.batlowK, levels=np.arange(0, 101, 10)),\n",
    "        fmt=\"auto\",\n",
    "    ),\n",
    "    \"caf_vh\": Diag(\n",
    "        recipe=lambda cl: cl.extract_cube(\"very_high_type_cloud_amount\"),\n",
    "        title=\"Very High Cloud Fraction\",\n",
    "        units=\"%\",\n",
    "        method=\"contourf\",\n",
    "        kw_plt=dict(cmap=cmcrameri.cm.batlowK, levels=np.arange(0, 101, 10)),\n",
    "        fmt=\"auto\",\n",
    "    ),\n",
    "    \"u_zm\": Diag(\n",
    "        recipe=lambda cl: zonal_mean(cl.extract_cube(lfric.u)),\n",
    "        title=\"Eastward Wind\",\n",
    "        units=\"$m$ $s^{-1}$\",\n",
    "        method=\"contourf\",\n",
    "        kw_plt=dict(\n",
    "            # cmap=swiftascmaps.nineteen_eighty_nine_tv_r,\n",
    "            # levels=np.arange(-50, 51, 10),\n",
    "            # extend=\"both\",\n",
    "            norm=mcol.CenteredNorm(0, halfrange=50),\n",
    "            cmap=plt.cm.PuOr_r,\n",
    "            extend=\"max\",\n",
    "        ),\n",
    "        fmt=\"auto\",\n",
    "    ),\n",
    "    \"w_zm_day\": Diag(\n",
    "        recipe=lambda cl: zonal_mean(\n",
    "            cl.extract_cube(lfric.w).extract(DAYSIDE.constraint)\n",
    "        ),\n",
    "        title=\"Upward Wind, Day Side\",\n",
    "        units=\"$cm$ $s^{-1}$\",\n",
    "        method=\"contourf\",\n",
    "        kw_plt=dict(\n",
    "            # cmap=swiftascmaps.nineteen_eighty_nine_tv_r,\n",
    "            # levels=linspace_pm1(4) * 2,\n",
    "            # extend=\"both\",\n",
    "            levels=linspace_pm1(4) * 2,\n",
    "            cmap=plt.cm.seismic,\n",
    "        ),\n",
    "        fmt=\"auto\",\n",
    "    ),\n",
    "    \"temp_zm\": Diag(\n",
    "        recipe=lambda cl: zonal_mean(\n",
    "            cl.extract_cube(lfric.thta) * cl.extract_cube(lfric.exner)\n",
    "        ),\n",
    "        title=\"Temperature\",\n",
    "        units=\"$K$\",\n",
    "        method=\"contourf\",\n",
    "        kw_plt=dict(\n",
    "            cmap=cmocean.cm.thermal,\n",
    "            levels=np.arange(170, 271, 10),\n",
    "            extend=\"both\",\n",
    "        ),\n",
    "        fmt=\"auto\",\n",
    "    ),\n",
    "    \"tot_col_m_v\": Diag(\n",
    "        recipe=lambda cl: cl.extract_cube(\"tot_col_m_v\"),\n",
    "        title=\"Total Column Water Vapour\",\n",
    "        units=\"$kg$ $m^{-2}$\",\n",
    "        method=\"contourf\",\n",
    "        kw_plt=dict(\n",
    "            cmap=cmocean.cm.dense,\n",
    "            levels=np.arange(0, 40, 5),\n",
    "            # norm=mcol.LogNorm(vmin=1e-1, vmax=1e2),\n",
    "            # rasterized=True,\n",
    "        ),\n",
    "        fmt=\"pretty\",\n",
    "    ),\n",
    "    \"tot_col_m_cl\": Diag(\n",
    "        recipe=lambda cl: cl.extract_cube(\"tot_col_m_cl\"),\n",
    "        title=\"Total Column Cloud Liquid\",\n",
    "        units=\"$kg$ $m^{-2}$\",\n",
    "        method=\"contourf\",\n",
    "        kw_plt=dict(\n",
    "            cmap=cmocean.cm.tempo,\n",
    "            levels=np.arange(0, 0.30, 0.05),\n",
    "            # norm=mcol.LogNorm(vmin=1e-4, vmax=1e0),\n",
    "            # rasterized=True,\n",
    "        ),\n",
    "        fmt=\"pretty\",\n",
    "    ),\n",
    "    \"tot_col_m_ci\": Diag(\n",
    "        recipe=lambda cl: cl.extract_cube(\"tot_col_m_ci\"),\n",
    "        title=\"Total Column Cloud Ice\",\n",
    "        units=\"$kg$ $m^{-2}$\",\n",
    "        method=\"contourf\",\n",
    "        kw_plt=dict(\n",
    "            cmap=cmocean.cm.ice_r,\n",
    "            levels=np.arange(0, 1.1, 0.2),\n",
    "            # norm=mcol.LogNorm(vmin=1e-4, vmax=1e0),\n",
    "            # rasterized=True,\n",
    "        ),\n",
    "        fmt=\"pretty\",\n",
    "    ),\n",
    "    # \"tot_col_uv_kinetic_energy\": Diag(\n",
    "    #     recipe=lambda cl: cl.extract_cube(\"tot_col_uv_kinetic_energy\"),\n",
    "    #     title=\"Total Column Horizontal Kinetic Energy\",\n",
    "    #     units=\"$10^6$ $J$ $m^{-2}$\",\n",
    "    #     method=\"pcolormesh\",\n",
    "    #     kw_plt=dict(cmap=cmocean.cm.amp, vmin=0.0, vmax=20, rasterized=True),\n",
    "    # ),\n",
    "    # \"tot_col_w_kinetic_energy\": Diag(\n",
    "    #     recipe=lambda cl: cl.extract_cube(\"tot_col_w_kinetic_energy\"),\n",
    "    #     title=\"Total Column Vertical Kinetic Energy\",\n",
    "    #     units=\"$J$ $m^{-2}$\",\n",
    "    #     method=\"pcolormesh\",\n",
    "    #     kw_plt=dict(\n",
    "    #         cmap=cmocean.cm.amp,\n",
    "    #         norm=mcol.LogNorm(vmin=1e-2, vmax=1e3),\n",
    "    #         rasterized=True,\n",
    "    #     ),\n",
    "    # ),\n",
    "    \"m_v_zm\": Diag(\n",
    "        recipe=lambda cl: zonal_mean(cl.extract_cube(\"m_v\")),\n",
    "        title=\"Water Vapour\",\n",
    "        units=\"$kg$ $kg^{-1}$\",\n",
    "        method=\"pcolormesh\",\n",
    "        kw_plt=dict(\n",
    "            cmap=cmocean.cm.dense,\n",
    "            norm=mcol.LogNorm(vmin=1e-7, vmax=1e-2),\n",
    "            rasterized=True,\n",
    "        ),\n",
    "        fmt=\"pretty\",\n",
    "    ),\n",
    "    \"m_cl_zm\": Diag(\n",
    "        recipe=lambda cl: zonal_mean(cl.extract_cube(\"m_cl\")),\n",
    "        title=\"Cloud Liquid\",\n",
    "        units=\"$kg$ $kg^{-1}$\",\n",
    "        method=\"pcolormesh\",\n",
    "        kw_plt=dict(\n",
    "            cmap=cmocean.cm.tempo,\n",
    "            norm=mcol.LogNorm(vmin=1e-8, vmax=1e-4),\n",
    "            rasterized=True,\n",
    "        ),\n",
    "        fmt=\"pretty\",\n",
    "    ),\n",
    "    \"m_ci_zm\": Diag(\n",
    "        recipe=lambda cl: zonal_mean(cl.extract_cube(\"m_ci\")),\n",
    "        title=\"Cloud Ice\",\n",
    "        units=\"$kg$ $kg^{-1}$\",\n",
    "        method=\"pcolormesh\",\n",
    "        kw_plt=dict(\n",
    "            cmap=cmocean.cm.ice_r,\n",
    "            norm=mcol.LogNorm(vmin=1e-8, vmax=1e-4),\n",
    "            rasterized=True,\n",
    "        ),\n",
    "        fmt=\"pretty\",\n",
    "    ),\n",
    "    \"rhw_zm\": Diag(\n",
    "        recipe=lambda cl: zonal_mean(cl.extract_cube(\"rh_water\")),\n",
    "        title=\"RH w.r.t. Liquid\",\n",
    "        units=\"1\",\n",
    "        method=\"contourf\",\n",
    "        kw_plt=dict(\n",
    "            cmap=cmocean.cm.haline_r,\n",
    "            levels=np.arange(0, 101, 10),\n",
    "        ),\n",
    "        fmt=\"auto\",\n",
    "    ),\n",
    "    \"bulk_fraction\": Diag(\n",
    "        recipe=lambda cl: zonal_mean(cl.extract_cube(\"bulk_fraction\")),\n",
    "        title=\"Bulk Cloud Fraction\",\n",
    "        units=\"1\",\n",
    "        method=\"contourf\",\n",
    "        kw_plt=dict(\n",
    "            cmap=cmocean.cm.haline_r,\n",
    "            levels=np.arange(0, 1.1, 0.1),\n",
    "        ),\n",
    "        fmt=\"auto\",\n",
    "    ),\n",
    "    \"tot_prec\": Diag(\n",
    "        recipe=partial(precip_sum, const=CONST, model=lfric),\n",
    "        title=\"Total Precipitation\",\n",
    "        units=\"$mm$ $day^{-1}$\",\n",
    "        method=\"pcolormesh\",\n",
    "        kw_plt=dict(\n",
    "            cmap=prec_cmap,\n",
    "            norm=prec_norm,\n",
    "            # cmap=cmocean.cm.rain,\n",
    "            # levels=np.arange(0, 31, 5),\n",
    "            # levels=[0.1, 0.25, 0.5, 1, 2, 4, 8, 16, 32],\n",
    "            # extend=\"max\",\n",
    "            # norm=mcol.LogNorm(vmin=5e-3, vmax=2e1),\n",
    "            rasterized=True,\n",
    "        ),\n",
    "        fmt=\"pretty\",\n",
    "    ),\n",
    "    \"ls_prec\": Diag(\n",
    "        recipe=lambda cl: cl.extract_cube(lfric.ls_rain) / CONST.condensible_density,\n",
    "        title=\"Grid-scale Precipitation\",\n",
    "        units=\"$mm$ $day^{-1}$\",\n",
    "        method=\"pcolormesh\",\n",
    "        kw_plt=dict(\n",
    "            cmap=prec_cmap,\n",
    "            norm=prec_norm,\n",
    "            # cmap=cmocean.cm.rain,\n",
    "            # levels=np.arange(0, 31, 5),\n",
    "            # levels=[0.1, 0.25, 0.5, 1, 2, 4, 8, 16, 32],\n",
    "            # extend=\"max\",\n",
    "            # norm=mcol.LogNorm(vmin=5e-3, vmax=2e1),\n",
    "            rasterized=True,\n",
    "        ),\n",
    "        fmt=\"pretty\",\n",
    "    ),\n",
    "    \"conv_prec\": Diag(\n",
    "        recipe=lambda cl: cl.extract_cube(lfric.cv_rain) / CONST.condensible_density,\n",
    "        title=\"Convective Precipitation\",\n",
    "        units=\"$mm$ $day^{-1}$\",\n",
    "        method=\"pcolormesh\",\n",
    "        kw_plt=dict(\n",
    "            cmap=prec_cmap,\n",
    "            norm=prec_norm,\n",
    "            # cmap=cmocean.cm.rain,\n",
    "            # levels=np.arange(0, 31, 5),\n",
    "            # levels=[0.1, 0.25, 0.5, 1, 2, 4, 8, 16, 32],\n",
    "            # extend=\"max\",\n",
    "            # norm=mcol.LogNorm(vmin=5e-3, vmax=2e1),\n",
    "            rasterized=True,\n",
    "        ),\n",
    "        fmt=\"pretty\",\n",
    "    ),\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "33be8e1d-dfec-45fb-83c3-f5a97d3157df",
   "metadata": {},
   "source": [
    "Assemble the figure using selected diagnostics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "3423788c-da41-491c-9dc5-f994683f8f35",
   "metadata": {},
   "outputs": [],
   "source": [
    "# diag_keys = [\"tot_col_m_v\", \"tot_col_m_cl\", \"tot_col_m_ci\", \"caf\"]\n",
    "# diag_keys = [\"t_sfc\", \"toa_olr\", \"u_zm\"]\n",
    "diag_keys = [\"tot_prec\", \"ls_prec\", \"conv_prec\"]\n",
    "# diag_keys = [\"caf\", \"caf_vl\", \"caf_l\", \"caf_m\", \"caf_h\", \"caf_vh\"]\n",
    "# diag_keys = [\"u_zm\", \"w_zm_day\", \"temp_zm\"]\n",
    "# diag_keys = [\"m_v_zm\", \"m_cl_zm\", \"m_ci_zm\"]\n",
    "# diag_keys = [\"rhw_zm\", \"bulk_fraction\"]\n",
    "\n",
    "\n",
    "savefig = True\n",
    "plot_winds = [\"t_sfc\"]\n",
    "height_constraint = iris.Constraint(**{lfric.z: 8000})\n",
    "plot_w_zm_day = [\"u_zm\"]\n",
    "\n",
    "fig = plt.figure(figsize=(8, 1.5 * len(diag_keys)), layout=\"constrained\")\n",
    "subfigs = fig.subfigures(nrows=len(diag_keys), ncols=1, squeeze=False)[:, 0]\n",
    "mosaic = [show_sim + [\"cax\"]]\n",
    "\n",
    "iletters = subplot_label_generator()\n",
    "for diag_key, subfig in zip(diag_keys, subfigs):\n",
    "    axd = subfig.subplot_mosaic(\n",
    "        mosaic,\n",
    "        width_ratios=[1] * len(show_sim) + [0.05],\n",
    "        gridspec_kw={},\n",
    "    )\n",
    "    for sim_label in show_sim:\n",
    "        ax = axd[sim_label]\n",
    "\n",
    "        ax.set_title(\n",
    "            f\"({next(iletters)})\",\n",
    "            loc=\"left\",\n",
    "            fontdict={\"weight\": \"bold\"},\n",
    "            pad=3,\n",
    "        )\n",
    "        ax.set_title(\n",
    "            SIMULATIONS[sim_label].title,\n",
    "            loc=\"center\",\n",
    "            fontdict={\"weight\": \"bold\"},\n",
    "            pad=3,\n",
    "            color=SIMULATIONS[sim_label].kw_plt[\"color\"],\n",
    "        )\n",
    "        if diag_key == \"conv_prec\" and sim_label == \"hab1_mod_c192s10e\":\n",
    "            [ax.spines[spine].set_visible(False) for spine in ax.spines]\n",
    "            ax.tick_params(colors=plt.rcParams[\"figure.facecolor\"])\n",
    "            # ax.\n",
    "            continue\n",
    "        cube = DIAGS[diag_key].recipe(dset[sim_label])\n",
    "        cube.convert_units(tex2cf_units(DIAGS[diag_key].units))\n",
    "        y, x = cube.dim_coords\n",
    "        if coord_mapping := coord_mappings.get(x.name()):\n",
    "            x.convert_units(coord_mapping[\"units\"])\n",
    "            ax.set_xticks(coord_mapping[\"ticks\"])\n",
    "            ax.set_xlim(coord_mapping[\"ticks\"][0], coord_mapping[\"ticks\"][-1])\n",
    "        if coord_mapping := coord_mappings.get(y.name()):\n",
    "            y.convert_units(coord_mapping[\"units\"])\n",
    "            ax.set_yticks(coord_mapping[\"ticks\"])\n",
    "            ax.set_ylim(coord_mapping[\"ticks\"][0], coord_mapping[\"ticks\"][-1])\n",
    "        if ax.get_subplotspec().is_first_col():\n",
    "            ax.set_ylabel(\n",
    "                f\"{capitalise(y.name())} [{y.units}]\", size=\"small\", labelpad=1\n",
    "            )\n",
    "        elif not ax.get_subplotspec().is_last_col():\n",
    "            ax.set_yticklabels([])\n",
    "        if ax.get_subplotspec().is_last_row():\n",
    "            ax.set_xlabel(\n",
    "                f\"{capitalise(x.name())} [{x.units}]\", size=\"small\", labelpad=1\n",
    "            )\n",
    "        ax.tick_params(labelsize=\"small\")\n",
    "        h = getattr(ax, DIAGS[diag_key].method)(\n",
    "            x.points, y.points, cube.data, **DIAGS[diag_key].kw_plt\n",
    "        )\n",
    "        if (\n",
    "            iris.util.guess_coord_axis(x) == \"X\"\n",
    "            and iris.util.guess_coord_axis(y) == \"Y\"\n",
    "        ):\n",
    "            at = AnchoredText(\n",
    "                cube_minmeanmax_str(\n",
    "                    cube,\n",
    "                    fmt=DIAGS[diag_key].fmt,\n",
    "                    precision=1,\n",
    "                    sep=\"\\n\",\n",
    "                    eq_sign=\": \",\n",
    "                ),\n",
    "                loc=\"lower left\",\n",
    "                frameon=True,\n",
    "                prop={\n",
    "                    \"size\": \"xx-small\",\n",
    "                    \"weight\": \"bold\",\n",
    "                    \"color\": SIMULATIONS[sim_label].kw_plt[\"color\"],\n",
    "                },\n",
    "            )\n",
    "            at.patch.set_facecolor(mcol.to_rgba(\"w\", alpha=0.75))\n",
    "            at.patch.set_edgecolor(\"none\")\n",
    "            ax.add_artist(at)\n",
    "        if diag_key in plot_winds:\n",
    "            u = dset[sim_label].extract_cube(lfric.u)\n",
    "            v = dset[sim_label].extract_cube(lfric.v)\n",
    "            for cube in [u, v]:\n",
    "                ensure_bounds(cube, coords=(\"z\"), model=lfric)\n",
    "            u = u.extract(height_constraint)\n",
    "            v = v.extract(height_constraint)\n",
    "            rounded_height = round(u.coord(lfric.z).points[0])\n",
    "\n",
    "            wspd = (u**2 + v**2) ** 0.5\n",
    "            ax.streamplot(\n",
    "                x.points,\n",
    "                y.points,\n",
    "                u.data,\n",
    "                v.data,\n",
    "                density=0.75,\n",
    "                color=SIMULATIONS[sim_label].kw_plt[\"color\"],\n",
    "                linewidth=wspd.data / wspd.data.max(),\n",
    "                arrowstyle=\"Fancy, head_length=0.5, head_width=0.2, tail_width=0.1\",\n",
    "                # broken_streamlines=False\n",
    "            )\n",
    "        if diag_key in plot_w_zm_day:\n",
    "            cube = DIAGS[\"w_zm_day\"].recipe(dset[sim_label])\n",
    "            cube.convert_units(tex2cf_units(DIAGS[\"w_zm_day\"].units))\n",
    "            _ = ax.contourf(\n",
    "                x.points, y.points, cube.data, **DIAGS[\"w_zm_day\"].kw_plt, alpha=0.25\n",
    "            )\n",
    "            cntr = ax.contour(x.points, y.points, cube.data, **DIAGS[\"w_zm_day\"].kw_plt)\n",
    "            ax.clabel(cntr, fmt=\"%.1f\")\n",
    "    ttl = f\"{DIAGS[diag_key].title} [{DIAGS[diag_key].units}]\"\n",
    "    if diag_key in plot_winds:\n",
    "        ttl += f\" and Wind Streamlines at {rounded_height} m\"\n",
    "        extra_label = f\"__wind_{rounded_height:05d}m\"\n",
    "    elif diag_key in plot_w_zm_day:\n",
    "        ttl += f\" and {DIAGS['w_zm_day'].title} [{DIAGS['w_zm_day'].units}]\"\n",
    "        extra_label = \"__w_zm_day\"\n",
    "    else:\n",
    "        extra_label = \"\"\n",
    "    subfig.suptitle(ttl, fontweight=\"bold\")\n",
    "    cbar = subfig.colorbar(h, cax=axd[\"cax\"])\n",
    "    if diag_key in [\"tot_prec\", \"ls_prec\", \"conv_prec\"]:\n",
    "        cbar.ax.set_yticks(prec_levels)\n",
    "        cbar.ax.set_yticklabels([str(i) for i in prec_levels])\n",
    "plt.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fec062f8-97f4-45b7-ad01-1c9b3974a365",
   "metadata": {},
   "source": [
    "# Show the figure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "33c2d22a-6b68-4a84-afc8-5fd485eecdf7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1600x900 with 15 Axes>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "78e0c8f7-02b6-4906-8803-ad42b99d2e36",
   "metadata": {},
   "source": [
    "- **Maps of time mean precipitation rate in $mm$ $day^{-1}$, from top to bottom: total, grid-scale, convective.**\n",
    "- **Note that there is no convective precipitation in the StretchExplicit simulation, because the convection parameterization is switched off.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a0231d28-797b-4369-8b78-c856e739f1cc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saved to ../figures/regr__hab1_mod_c192_s10e_s10r_s10p_p__tot_prec_ls_prec_conv_prec__tm_map.pdf\n",
      "Size: 64.0 KB\n"
     ]
    }
   ],
   "source": [
    "# and save it\n",
    "figsave(\n",
    "    fig,\n",
    "    paths.figures\n",
    "    / f\"regr__{all_sim_file_label(show_sim)}__{'_'.join(diag_keys)}{extra_label}__tm_map\",\n",
    ")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:stretched_mesh_env]",
   "language": "python",
   "name": "conda-env-stretched_mesh_env-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
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