{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "from pathlib import Path\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import collections\n",
    "\n",
    "ld2dap_path = Path('../')\n",
    "sys.path.append(str(ld2dap_path.resolve()))\n",
    "import ld2dap\n",
    "from ld2dap.core import Filter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "layers_files = [\n",
    "    '../Data/phase1_rasters/DEM+B_C123/UH17_GEM051_TR.tif',\n",
    "    '../Data/phase1_rasters/DEM_C123_3msr/UH17_GEG051_TR.tif',\n",
    "    '../Data/phase1_rasters/DEM_C123_TLI/UH17_GEG05_TR.tif',\n",
    "    '../Data/phase1_rasters/DSM_C12/UH17c_GEF051_TR.tif',\n",
    "    '../Data/phase1_rasters/Intensity_C1/UH17_GI1F051_TR.tif',\n",
    "    '../Data/phase1_rasters/Intensity_C2/UH17_GI2F051_TR.tif',\n",
    "    '../Data/phase1_rasters/Intensity_C3/UH17_GI3F051_TR.tif'\n",
    "]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Node Streaming Local FeaturesAttribute Profiles\n",
    "\n",
    "We made some custom LFAPs in Python, but now Triskele comes with its owns in C++! Let's try it out then create a streaming node.\n",
    "\n",
    "## Triskele LFAPs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "sys.path.append('../triskele/python/')\n",
    "import triskele"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "raster = triskele.read(layers_files[0])\n",
    "raster.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "lfaps = triskele.Triskele(raster)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "results = lfaps.filter(area=[100, 1e4], feature='SD')\n",
    "results.shape, lfaps.process"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Streamin Node"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import logging\n",
    "logger = logging.getLogger()\n",
    "logger.setLevel(logging.DEBUG)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "l = ld2dap.LoadTIFF(layers_files)\n",
    "t = ld2dap.Treshold(1e4)\n",
    "a = ld2dap.LocalFeatures([np.var, np.std, ])#, sd=[.4,.6,.8], moi=[.5,.9])\n",
    "d = ld2dap.ShowFig(stack_id='all', symb=False)\n",
    "o = ld2dap.RawOutput()\n",
    "\n",
    "o.input = a\n",
    "d.input = a\n",
    "a.input = t\n",
    "t.input = l\n",
    "\n",
    "d.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(o.metadata[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "file_extension": ".py",
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