{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "0",
   "metadata": {},
   "source": [
    "# CAMS EAC4 → EOPF HEALPix Converter\n",
    "\n",
    "Converts CAMS EAC4 aerosol reanalysis (regular 0.75°) to EOPF-compliant HEALPix zarr (level 6, ~100 km).\n",
    "\n",
    "**Pipeline**: download NetCDF via ADS REST API → resample to HEALPix → write zarr → inject STAC\n",
    "\n",
    "**Resampling** (`method=`, default `\"psf\"`): `PSFResampler` tuned for the regular grid (`threshold=0.01` → 0 NaN, `lam=5.0` → no Gibbs ringing / 0 negative AOD), with a final `clip(0, None)`. Pass `method=\"nn\"` for the nearest-neighbour binning alternative (exact, faster). Both give 0 NaN / 0 negative and correlate > 0.98."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1",
   "metadata": {},
   "outputs": [],
   "source": [
    "import logging\n",
    "from pathlib import Path\n",
    "\n",
    "from healpix_convert.converters.cams import CAMSConverter\n",
    "\n",
    "logging.basicConfig(level=logging.INFO, format=\"%(asctime)s %(levelname)s %(message)s\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2",
   "metadata": {},
   "source": [
    "## Configuration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3",
   "metadata": {},
   "outputs": [],
   "source": [
    "DATE = \"2025-01-01\"\n",
    "TIME = \"00:00\"\n",
    "LOCAL_DIR = Path(\".\")\n",
    "OUTPUT = LOCAL_DIR / f\"S00__ADF_CAMSA_{DATE.replace('-','')}.zarr\"\n",
    "\n",
    "converter = CAMSConverter(\n",
    "    date=DATE,\n",
    "    time=TIME,\n",
    "    local_dir=LOCAL_DIR,\n",
    "    method=\"psf\",  # default; use \"nn\" for nearest-neighbour binning\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4",
   "metadata": {},
   "source": [
    "## Step 1 — Prepare (download)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5",
   "metadata": {},
   "outputs": [],
   "source": [
    "result = converter.prepare(output_path=str(OUTPUT))\n",
    "print(f\"Chunks: {result.n_chunks} | Timesteps: {result.n_times}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6",
   "metadata": {},
   "source": [
    "## Step 2 — Convert (all spatial chunks)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7",
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(result.n_chunks):\n",
    "    converter.convert_group(i)\n",
    "    if (i + 1) % 20 == 0:\n",
    "        print(f\"  {i+1}/{result.n_chunks}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8",
   "metadata": {},
   "source": [
    "## Step 3 — Consolidate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9",
   "metadata": {},
   "outputs": [],
   "source": [
    "converter.consolidate()\n",
    "print(f\"Done: {OUTPUT}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10",
   "metadata": {},
   "source": [
    "## Validation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "11",
   "metadata": {},
   "outputs": [],
   "source": [
    "import healpy as hp\n",
    "import matplotlib.pyplot as plt\n",
    "import xarray as xr\n",
    "\n",
    "ds = xr.open_zarr(str(OUTPUT), consolidated=True)\n",
    "print(ds)\n",
    "\n",
    "data = ds[\"aod550\"].isel(time=0).values\n",
    "hp.mollview(\n",
    "    hp.reorder(data, n2r=True),\n",
    "    flip=\"geo\",\n",
    "    nest=False,\n",
    "    cmap=\"viridis\",\n",
    "    min=0,\n",
    "    max=1.5,\n",
    "    unit=\"AOD\",\n",
    "    title=\"CAMS AOD550 — HEALPix level 6\",\n",
    ")\n",
    "plt.show()"
   ]
  }
 ],
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