{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Extract a V2D+T section from a 4D field"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-01-13T11:33:24.931520Z",
     "iopub.status.busy": "2025-01-13T11:33:24.931018Z",
     "iopub.status.idle": "2025-01-13T11:33:25.458442Z",
     "shell.execute_reply": "2025-01-13T11:33:25.457919Z"
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "# for figures in notebook\n",
    "\n",
    "# import & initialize epygram\n",
    "import epygram\n",
    "epygram.init_env()\n",
    "\n",
    "# path to file\n",
    "import os\n",
    "INPUTS_DIR = os.path.join('..', 'inputs')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-01-13T11:33:25.460513Z",
     "iopub.status.busy": "2025-01-13T11:33:25.460282Z",
     "iopub.status.idle": "2025-01-13T11:33:25.790155Z",
     "shell.execute_reply": "2025-01-13T11:33:25.789690Z"
    }
   },
   "outputs": [],
   "source": [
    "paths = [os.path.join(INPUTS_DIR, 'grid.arome-forecast.guyane0025+00{:02}:00.grib'.format(i))\n",
    "         for i in (0, 12, 24)]\n",
    "r = epygram.resources.meta_resource(paths, 'r', 'CL+MV')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-01-13T11:33:25.792232Z",
     "iopub.status.busy": "2025-01-13T11:33:25.792065Z",
     "iopub.status.idle": "2025-01-13T11:33:51.420371Z",
     "shell.execute_reply": "2025-01-13T11:33:51.419887Z"
    }
   },
   "outputs": [],
   "source": [
    "f = r.readfield({'shortName':'t', 'typeOfFirstFixedSurface':100})  # temperature on pressure levels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-01-13T11:33:51.422391Z",
     "iopub.status.busy": "2025-01-13T11:33:51.422200Z",
     "iopub.status.idle": "2025-01-13T11:33:51.425066Z",
     "shell.execute_reply": "2025-01-13T11:33:51.424654Z"
    }
   },
   "outputs": [],
   "source": [
    "print(f.getdata(d4=True).shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-01-13T11:33:51.426913Z",
     "iopub.status.busy": "2025-01-13T11:33:51.426712Z",
     "iopub.status.idle": "2025-01-13T11:33:51.893232Z",
     "shell.execute_reply": "2025-01-13T11:33:51.892781Z"
    }
   },
   "outputs": [],
   "source": [
    "s = f.extractsection((-55,5), (-55,2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-01-13T11:33:51.895106Z",
     "iopub.status.busy": "2025-01-13T11:33:51.894955Z",
     "iopub.status.idle": "2025-01-13T11:33:51.897788Z",
     "shell.execute_reply": "2025-01-13T11:33:51.897335Z"
    }
   },
   "outputs": [],
   "source": [
    "print(type(s))\n",
    "print(s.getdata(d4=True).shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}