{
 "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",
    "\n",
    "triskele_path = Path('../triskele/python/')\n",
    "sys.path.append(str(triskele_path.resolve()))\n",
    "import triskele"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def DFC_filter(raster):\n",
    "    raster[raster > 1e4] = raster[raster < 1e4].max()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## One raster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "infile  = Path('../Data/phase1_rasters/DSM_C12/UH17c_GEF051_TR.tif')\n",
    "raster = triskele.read(infile)\n",
    "DFC_filter(raster)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "t = triskele.Triskele(raster, verbose=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "area = np.array([10, 100, 1e3, 1e4, 1e5])\n",
    "moi  = np.array([.0, .01, .1, .2, .3, .4, .5, .9, .99, 1.])\n",
    "\n",
    "filtered = t.filter(tree='tos-tree')\n",
    "filtered.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure(figsize=(16*1,5*1))\n",
    "plt.imshow(filtered[:,:].astype(np.float))\n",
    "plt.colorbar()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## More raster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "infile1  = Path('../Data/phase1_rasters/DSM_C12/UH17c_GEF051_TR.tif')\n",
    "infile2  = Path('../Data/phase1_rasters/Intensity_C1/UH17_GI1F051_TR.tif')\n",
    "raster1 = triskele.read(infile1)\n",
    "raster2 = triskele.read(infile2)\n",
    "DFC_filter(raster1)\n",
    "DFC_filter(raster2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure(figsize=(16*1,5*1))\n",
    "plt.imshow(raster1[:,:].astype(np.float))\n",
    "plt.colorbar()\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(16*1,5*1))\n",
    "plt.imshow(raster2[:,:].astype(np.float))\n",
    "plt.colorbar()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = np.stack((raster1, raster2), axis=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "t = triskele.Triskele(data, verbose=False)\n",
    "f = t.filter(tree='tos-tree', area=area)\n",
    "f.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(f.shape[2]):\n",
    "    plt.figure(figsize=(16*1,5*1))\n",
    "    plt.imshow(f[:,:,i].astype(np.float))\n",
    "    plt.colorbar()\n",
    "    plt.show()"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3"
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