Retain internal mask

retain-internal-mask.ipynb

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   "source": [
    "# Restore internal mask\n",
    "\n",
    "## Current situation\n",
    "\n",
    "* Generating warped mask band is not supported by GDAL: [#689](https://github.com/OSGeo/gdal/issues/689)\n",
    "* Example of warping .msk sidecar file: [#754](https://github.com/OSGeo/gdal/issues/754)\n",
    "* rasterio.warp.reproject supports alpha band: [#984](https://github.com/mapbox/rasterio/issues/984)\n",
    "\n",
    "## Potentially possible ways to retain masks\n",
    "\n",
    "* Create `*.msk` from original `*.tif`, reproject it and then merge them together\n",
    "* Convert internal mask to alpha band, reproject `*.tif` and then translate alpha to internal mask\n",
    "* Use rasterio `write_mask`, code example [here](https://github.com/drnextgis/telluric/commit/014886e348004883425671bb8cf255293c4b90e9). In this case we call `read_masks(1)` which creates numpy array internally"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from telluric import GeoRaster2\n",
    "from rasterio.enums import Resampling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
      "100   663  100   663    0     0    710      0 --:--:-- --:--:-- --:--:--   710\n"
     ]
    }
   ],
   "source": [
    "!curl -O https://transfer.sh/47mmP/normalized.tif"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "masked_array(\n",
       "  data=[[[0, 1, 2],\n",
       "         [3, 4, --]]],\n",
       "  mask=[[[False, False, False],\n",
       "         [False, False,  True]]],\n",
       "  fill_value=999999,\n",
       "  dtype=uint8)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "src = GeoRaster2.open('normalized.tif')\n",
    "src.image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "src = GeoRaster2.open('normalized.tif')\n",
    "dst = src.reproject(dimensions=(6, 4), resampling=Resampling.nearest)\n",
    "dst._image # non-in-memory raster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "masked_array(\n",
       "  data=[[[0, 0, 1, 1, 2, 2],\n",
       "         [0, 0, 1, 1, 2, 2],\n",
       "         [3, 3, 4, 4, --, --],\n",
       "         [3, 3, 4, 4, --, --]]],\n",
       "  mask=[[[False, False, False, False, False, False],\n",
       "         [False, False, False, False, False, False],\n",
       "         [False, False, False, False,  True,  True],\n",
       "         [False, False, False, False,  True,  True]]],\n",
       "  fill_value=999999,\n",
       "  dtype=uint8)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dst.image"
   ]
  }
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