{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Convert profiles vertical coordinate from Hybrid-Pressure to altitude"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-01-13T11:35:08.041895Z",
     "iopub.status.busy": "2025-01-13T11:35:08.040613Z",
     "iopub.status.idle": "2025-01-13T11:35:08.560516Z",
     "shell.execute_reply": "2025-01-13T11:35:08.560108Z"
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "# for figures in notebook\n",
    "\n",
    "# import & initialize epygram\n",
    "import epygram\n",
    "epygram.init_env()\n",
    "\n",
    "import os\n",
    "INPUTS_DIR = os.path.join('..', 'inputs')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-01-13T11:35:08.562714Z",
     "iopub.status.busy": "2025-01-13T11:35:08.562501Z",
     "iopub.status.idle": "2025-01-13T11:35:08.697593Z",
     "shell.execute_reply": "2025-01-13T11:35:08.696937Z"
    }
   },
   "outputs": [],
   "source": [
    "r = epygram.resources.meta_resource(os.path.join(INPUTS_DIR, 'ICMSHAROM+0022'), 'r', 'CL')  # CL = CombineLevels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-01-13T11:35:08.700009Z",
     "iopub.status.busy": "2025-01-13T11:35:08.699731Z",
     "iopub.status.idle": "2025-01-13T11:35:08.702855Z",
     "shell.execute_reply": "2025-01-13T11:35:08.702513Z"
    }
   },
   "outputs": [],
   "source": [
    "# in a \"CL\" meta-resource, fields are to be grabbed through a GRIB2 nomenclature\n",
    "t_as_grib2 = dict(discipline=0, parameterCategory=0, parameterNumber=0,  # this is temperature\n",
    "                  typeOfFirstFixedSurface=119)  # hybrid-pressure levels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-01-13T11:35:08.704231Z",
     "iopub.status.busy": "2025-01-13T11:35:08.704104Z",
     "iopub.status.idle": "2025-01-13T11:35:11.171718Z",
     "shell.execute_reply": "2025-01-13T11:35:11.171221Z"
    }
   },
   "outputs": [],
   "source": [
    "t3d = r.readfield(t_as_grib2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-01-13T11:35:11.173889Z",
     "iopub.status.busy": "2025-01-13T11:35:11.173664Z",
     "iopub.status.idle": "2025-01-13T11:35:11.292838Z",
     "shell.execute_reply": "2025-01-13T11:35:11.292379Z"
    }
   },
   "outputs": [],
   "source": [
    "t3d.sp2gp()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-01-13T11:35:11.294586Z",
     "iopub.status.busy": "2025-01-13T11:35:11.294433Z",
     "iopub.status.idle": "2025-01-13T11:35:11.306275Z",
     "shell.execute_reply": "2025-01-13T11:35:11.305851Z"
    }
   },
   "outputs": [],
   "source": [
    "# extract profiles\n",
    "profiles = []\n",
    "for position in [(6.1,46.2), (6.8,45.8), (6,46.5)]:\n",
    "    profgeo = t3d.geometry.make_profile_geometry(*position)  # make a V1D geometry at that position\n",
    "    profiles.append(t3d.extract_subdomain(profgeo))  # extract subdomain corresponding to the geometry of the profile"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-01-13T11:35:11.307901Z",
     "iopub.status.busy": "2025-01-13T11:35:11.307693Z",
     "iopub.status.idle": "2025-01-13T11:35:11.690934Z",
     "shell.execute_reply": "2025-01-13T11:35:11.690320Z"
    }
   },
   "outputs": [],
   "source": [
    "fig = ax = None\n",
    "for p in profiles:\n",
    "    fig, ax = p.plotfield(labels='Temperature @ ({}, {})'.format(p.geometry.grid['longitudes'][0],\n",
    "                                                                 p.geometry.grid['latitudes'][0]),\n",
    "                          over=(fig, ax))  # superpose profiles"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## and now on an Altitude z-axis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-01-13T11:35:11.692744Z",
     "iopub.status.busy": "2025-01-13T11:35:11.692612Z",
     "iopub.status.idle": "2025-01-13T11:35:12.054592Z",
     "shell.execute_reply": "2025-01-13T11:35:12.054042Z"
    }
   },
   "outputs": [],
   "source": [
    "# for the conversions, we need R and T profiles, so (at least) q and T\n",
    "q_as_grib2 = dict(discipline=0, parameterCategory=1, parameterNumber=0,  # this is specific humidity\n",
    "                  typeOfFirstFixedSurface=119)  # on hybrid-pressure levels\n",
    "q3d = r.readfield(q_as_grib2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-01-13T11:35:12.056671Z",
     "iopub.status.busy": "2025-01-13T11:35:12.056483Z",
     "iopub.status.idle": "2025-01-13T11:35:12.392355Z",
     "shell.execute_reply": "2025-01-13T11:35:12.391596Z"
    }
   },
   "outputs": [],
   "source": [
    "# but also Surface pressure and geopotential\n",
    "ps = epygram.open(r.resource.container.abspath, 'r').readfield('SURFPRESSION')\n",
    "zs = epygram.open(r.resource.container.abspath, 'r').readfield('SPECSURFGEOPOTEN')\n",
    "# Ps is spectral and ln(Ps)\n",
    "ps.sp2gp()\n",
    "ps.operation('exp')\n",
    "zs.sp2gp()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-01-13T11:35:12.394349Z",
     "iopub.status.busy": "2025-01-13T11:35:12.394217Z",
     "iopub.status.idle": "2025-01-13T11:35:12.415325Z",
     "shell.execute_reply": "2025-01-13T11:35:12.414894Z"
    }
   },
   "outputs": [],
   "source": [
    "from epygram.geometries.VGeometry import hybridP2altitude\n",
    "from bronx.meteo.conversion import q2R\n",
    "\n",
    "for p in profiles:\n",
    "    q_profile = q3d.extract_subdomain(p.geometry).data  # profile of q at the same place\n",
    "    # specific humidity (and optionally hydrometeors) to moist air specific constant R\n",
    "    R_profile = q2R(q_profile)\n",
    "    t_profile = p.data\n",
    "    ps_local = ps.getvalue_ll(p.geometry.grid['longitudes'][0],\n",
    "                              p.geometry.grid['latitudes'][0])\n",
    "    zs_local = zs.getvalue_ll(p.geometry.grid['longitudes'][0],\n",
    "                              p.geometry.grid['latitudes'][0])\n",
    "    # create the Z vertical coordinate\n",
    "    p.geometry.vcoordinate = hybridP2altitude(p.geometry.vcoordinate,\n",
    "                                              R_profile,\n",
    "                                              t_profile,\n",
    "                                              ps_local,\n",
    "                                              vertical_mean='geometric',\n",
    "                                              Phi_surf=zs_local,\n",
    "                                              Pdep=None)  # we could also provide a (NH) Pressure-departure profile for more accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-01-13T11:35:12.416848Z",
     "iopub.status.busy": "2025-01-13T11:35:12.416651Z",
     "iopub.status.idle": "2025-01-13T11:35:12.572542Z",
     "shell.execute_reply": "2025-01-13T11:35:12.572064Z"
    }
   },
   "outputs": [],
   "source": [
    "fig = ax = None\n",
    "for p in profiles:\n",
    "    fig, ax = p.plotfield(labels='Temperature @ ({}, {})'.format(p.geometry.grid['longitudes'][0],\n",
    "                                                                 p.geometry.grid['latitudes'][0]),\n",
    "                          over=(fig, ax))  # superpose profiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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