New HAG KDE

new-hag-kde.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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37+7U/dfuPOrUOEEAtKoAhKkDEaqu+1TQUHUAQjWBdfM0gdCGBECpFBr9Qbf8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\n6BMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f081c76fd90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import pdal\n",
    "import seaborn as sns\n",
    "json = u'''\n",
    "{\n",
    "  \"pipeline\":[\n",
    "    \"./data/isprs/samp11-utm.laz\",\n",
    "    {\n",
    "      \"type\":\"filters.smrf\"\n",
    "    },\n",
    "    {\n",
    "      \"type\":\"filters.hag\"\n",
    "    }\n",
    "  ]\n",
    "}'''\n",
    "p = pdal.Pipeline(json)\n",
    "p.execute()\n",
    "df = pd.DataFrame(p.arrays[0])\n",
    "sns.kdeplot(df['HeightAboveGround'], cut=0, shade=True, vertical=True);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "00.00-Preface.ipynb\r\n",
      "00.00-Preface.rst\r\n",
      "01.00-Getting-Started.ipynb\r\n",
      "01.01-FOSS4G.ipynb\r\n",
      "01.02-Take-Two.ipynb\r\n",
      "02.01-Height-Above-Ground.ipynb\r\n",
      "02.02-Sampling.ipynb\r\n",
      "03.01-Analysis-Removing-Noise.ipynb\r\n",
      "03.01-Analysis-Removing-Noise.rst\r\n",
      "\u001b[0m\u001b[01;34m03.01-Analysis-Removing-Noise_files\u001b[0m/\r\n",
      "03.02-Georeferencing.ipynb\r\n",
      "03.xx-Basic-Information.ipynb\r\n",
      "03.xx-Boundary.ipynb\r\n",
      "03.xx-Eigenvalues.ipynb\r\n",
      "03.xx-Grid-Free-Denoising.ipynb\r\n",
      "03.xx-Inter-Quartile-Range.ipynb\r\n",
      "03.xx-Local-Outlier-Factor.ipynb\r\n",
      "03.xx-Reprojection.ipynb\r\n",
      "AccumulatedPipeline.ipynb\r\n",
      "Basic-HAG-KDE.ipynb\r\n",
      "Creating-a-Pipeline.ipynb\r\n",
      "CropDocs.ipynb\r\n",
      "Import-PDAL.ipynb\r\n",
      "Index.ipynb\r\n",
      "Numpy-ndarrays.ipynb\r\n",
      "Reader-Only-Pipeline.ipynb\r\n",
      "Replot-KDE-Z.ipynb\r\n",
      "S1C1_csd_004.laz\r\n",
      "Seaborn-KDEPlot.ipynb\r\n",
      "Searching-Near-Point.ipynb\r\n",
      "Untitled.ipynb\r\n",
      "Untitled1.slides.html\r\n",
      "Using-Pandas.ipynb\r\n",
      "Validating-and-Executing-the-Pipeline.ipynb\r\n",
      "address.txt\r\n",
      "address2.txt\r\n",
      "bar.laz\r\n",
      "baz.laz\r\n",
      "clean.laz\r\n",
      "\u001b[01;34mdata\u001b[0m/\r\n",
      "decimation.laz\r\n",
      "\u001b[01;34mfigures\u001b[0m/\r\n",
      "foo.json\r\n",
      "foo.laz\r\n",
      "gh.slides.html\r\n",
      "pclblock.json\r\n",
      "point_cloud_filters_and_pipelines_foss4g-2017.ipynb\r\n",
      "point_cloud_filters_and_pipelines_foss4g-2017.md\r\n",
      "point_cloud_filters_and_pipelines_foss4g-2017.slides.html\r\n",
      "\u001b[01;34mpoint_cloud_filters_and_pipelines_foss4g-2017_files\u001b[0m/\r\n",
      "poisson.laz\r\n",
      "range.laz\r\n",
      "\u001b[01;34msample-input\u001b[0m/\r\n",
      "\u001b[01;34msample-output\u001b[0m/\r\n",
      "voxelgrid.laz\r\n",
      "xx.xx-Gary-Noble-Difference.ipynb\r\n"
     ]
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