chambbj/hag-nonground.ipynb

## hag-nonground.ipynb
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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mX/tYo0GHmJhIOGvcte/8Gjy2fqE1MYyl13awGKjV6HQ6mIy+V8vBdqF3O3WE\nEFAFoGhKpX5hNSyj+gV2rmwaDxf+eXqV2mJrsgS19+tKUFEEWlZZ56hCQPX6Hu26yHm0VcEqPaNB\nB7M5HB63FzodGpee7lxx6evN46dKL8yoRwdLOMwRRulKjcVAP1s6nQ4GHWDQt53TiOgNOkRbIlBl\nrYHH/27H905HFb7vhagbVlsE5x0vasfjPMPP3frG+6arP09FCIjaW7XhMptYDnSA16s2OV5cbNvV\nkrX0TEY9Yi1hiLWEIy46HLGW8Hrfh/mHhZnazt8hi4GojdHpajedGA1S/Yf+1Ls04S8U+EtHbaKo\nzld65yuj+uXW9GPwk+P1Bj3cbm/jEq6fs3Y+TZXwhUrP41X9xxFdiDnCiNjakoizhCM2Oqz2NhyJ\nHSLRLclywccHkkR/dkQkM13dZp1QB2mgOZsdf0pdQdTfIcPh9OCMzYUKqxOVVhcqrU64G+zNV5/D\n6YXD6UVhmaPJ8b8dfjnGXt3zovK1FIuBiH52VFXAo6i+z4CEgNMrUGWtgculwO1R4Paq5711eRS4\nPSrcXt+tp+5WOf9K/1Lp4Ds1f2thMRBRSNVtYvIq51bWvi8Bj1d7v+5733DRaJz/8d7G4/zjvSpa\nuEPaJTEZ9YgMMyAizIiIMIPvK7ze9/7hRkSEnxsWWW9Y3YGiraXVi0FRFDz11FPYsmULXC4XsrKy\n8MQTTyA+Pr61oxAR0HjbfRPb8uu+95xnpeup3QtLb9DDUe2ut0KvnbbefU8TK+xL/WA6kHQ6aFfi\nDb6PDG88zLeyNyCyiZW8QR/8vfACrdWL4ZVXXsEnn3yCTZs2ITY2Fo8++ijmzZuHNWvWtHYUootS\n9wq3/oenSoMPSzUfdF5opdvwQ1gAYSYjqmvc/uMumvpwtamVtmbaensRNdrTqMF8ZOA7YNCAsNqD\nAMNMBt9t7ZfJaECYqXacsXacyfd9mFEPk6neY40GmEx1j/Wt0BMTolFtr4HJYOB5vxCCYsjNzcW9\n996L7t27AwAefvhhZGdno7CwEF27dm3tONRKhKi3O2TtiktR6lZsqnZl14KV7nlXkACMRj2cTq92\n/vX2LPnJ+ZxnXFt6dRsqTa6gTQZERZqgE/APa7gibmrF7Fuha1f6mmmN+qCeIt5g0CE+PgqV8B2z\nQq1cDFarFUVFRejbt69/WI8ePWCxWJCfn9/sYtDrABjkafS6v+lA5K6/L3pTt9rv1fNO559GCKhK\n3Yra90Hvwk/CAAAR4klEQVRc3QpbVQX0BgNcLs+5A7eaXFYzliPJK9Ng0xzNa9DBqDk4y3dQVrjJ\nCED4D+TSHBVs0DVxUJe+dl71Duxq8Dij4ULj9I0P2qrLVu+gMZNBD5PJdz6qpl5R6/U6xMaaUVXl\ngCrR77uudGS8PkmwsrdqMTgcvt2wLBbt/rgxMTGw2+3Nno/FEhnQXPUJIXwnlavxwOn2Njoi9XxH\nwDZ/fINTN9Teb3q8ql0BK637oVlb4D8StfbEeXUruCbv160g/Su6etPVH1dvmgvf/+nl1l+B+h+r\nua/XrNxlXPm0VGysOdQRLoqsuYHAZ2/VYjCbfeEbloDVam1UFhdit9e0aAWpqAI1Ti8cTg+qa28d\nTi+qnV5UN/F9e3t1qwP8Ky3tK8H6K05doxWk0aBDZEQYVEXxvXptuPLUN1ypNlg5G7SveJtcCeub\nnrZu/he7Ig3tq1cVUHw7WigAWnK+WVlfdQPyZpc1N9D87PHxLTs4rlWLISYmBsnJyTh06BD69OkD\nADh58iTsdjtSU1ObPR9VwLf5QxUoraxuekXv8vpLwOkOzEnP6r/drjvjZcOVnKHBSs6o18Fo1CMq\nMgyKV2m0eUCzUq3/6vI882+4MtW8Mj7PdBe7cvVte7WgstIekm2vQuCSl1v3Tkw2suYG5M0ua24g\n8Nlb/cPnyZMnY/Xq1RgyZAji4uKwfPlyZGVloVu3bi2aT1lVDbbtOYZKa8vPmmKJNCHGHIaYKBOi\no8IQExWGGLMJ0ea6733joiJM/vP7X8rZHUO9giUiaolWL4acnBxYrVb89re/hdvtxnXXXYfly5c3\n+/FCCHx7tBw795+Et3YlazTo0cFcu5KvXblHm031VvJhiI4yoYM5DJYok5T7FRMRtZZWLwaDwYD5\n8+dj/vz5F/X4Q8cqsePLEwCAuOhwzLwpHb/o1uFnv98xEVGgSHdKjPzjlQCA7kkWPHzrgFY9TJyI\n6OdAum0qJRW+XV4zr0hgKRARBYF0xVDt9ALwbUYiIqLAk64Y1NrzEfwcDhQiIgoF6YohOioMAFBS\nWR3iJERE7ZN0xdCjczQA4D+FZ0OchIiofZKuGMrO1AAAzPzgmYgoKKQrhh9PVQEArknvHOIkRETt\nk3TFIACYI43of0VCqKMQEbVL0hUDAFzXrwtMRimjExG1eVKuXdN78frQRETBImUx8N0CEVHwSLmG\nrXF5Qx2BiKjdkrIYKq3OUEcgImq3pCyGQF2RjYiIGpOyGNrbNZmJiNoSKYshOopHPRMRBYuUxdA1\nwRzqCERE7ZaUxRDLazEQEQWNlMUQbjKEOgIRUbslZTFEhkt3qWoiImlIWQx8x0BEFDzSFUNkuIGX\n9SQiCiLpisEcGRbqCERE7Zp0xcAT6BERBRfXskREpCFdMag8HQYRUVBJVwyKooY6AhFRuyZdMegN\n0kUmIpJKwNaybrcbjz/+OEaPHo0BAwZg+PDhWLZsGVwul2a6NWvWYOjQocjMzMS0adNw8uTJFi3H\nxGIgIgqqgK1lvV4v4uLisGLFCuTl5WHjxo3Yt28fli9f7p9m+/btWLt2LVauXIm9e/fiiiuuwD33\n3ANFaf71FYwGHsNARBRMATu3RFRUFObOneu/37VrV0yaNAlvvvmmf1hubi6mTJmC9PR0AMDcuXNx\n7bXX4sCBAxg8eHCzlqPT6aQ7wK0uL3O3Hlmzy5obkDe7rLmB4GUP6kmH9u7di7S0NP/9/Px8TJs2\nzX/fbDajZ8+eyM/Pb0ExALGxcp52m7lbn6zZZc0NyJtd1txA4LM3qxgeeeQRbNmy5bzj7777bs27\nBQB49dVXsX//fmzevNk/zOFwwGKxaKaLiYmB3W5vSWZUVTmk2m1Vr9chNtbM3K1I1uyy5gbkzS5r\nbqD52ePjLecd15RmFcNjjz2GefPmnXd8ZGSk5v6rr76K1atX47XXXkNycrJ/uNlsblQCVqu1UVn8\nFFUVUBS5foEAc4eCrNllzQ3Im13W3EDgszerGMxmM8zm5r1Veemll/D222/jjTfeQO/evTXj0tLS\ncOjQIYwaNQqA7x1EQUGBZnMTERGFVkD3/Vy2bBneeecdbNiwoVEpAMDkyZPx9ttv4/Dhw3A6nXj2\n2WfRrVs3DBo0KJAxiIjoEgTsw+fCwkKsW7cOJpMJv/nNb/zDk5OT8cEHHwAAbrrpJpSWliInJwc2\nmw2ZmZlYsWIFDAZeX4GIqK0IWDF07doVR44c+cnp7rrrLtx1112BWiwREQUYDyMmIiINFgMREWmw\nGIiISIPFQEREGiwGIiLSYDEQEZEGi4GIiDRYDEREpMFiICIiDRYDERFpsBiIiEiDxUBERBosBiIi\n0mAxEBGRBouBiIg0WAxERKTBYiAiIg0WAxERabAYiIhIg8VAREQaLAYiItJgMRARkQaLgYiINFgM\nRESkwWIgIiIN6YpBiFAnICJq36QrBq+ihjoCEVG7Jl0xKArfMhARBZN8xaDyHQMRUTAFpRiqq6sx\natQoXHnllY3GrVmzBkOHDkVmZiamTZuGkydPtmjeowb3DFRMIiJqQlCK4W9/+xu6devWaPj27dux\ndu1arFy5Env37sUVV1yBe+65B4qiNHvet45ODWRUIiJqwBjoGe7fvx95eXmYN28evvrqK8243Nxc\nTJkyBenp6QCAuXPn4tprr8WBAwcwePDgZi9Dr9cFNHOw1eVl7tYja3ZZcwPyZpc1NxC87AEthpqa\nGixYsABPPfUUqqurG43Pz8/HtGnT/PfNZjN69uyJ/Pz8FhVDbKw5EHFbHXO3Plmzy5obkDe7rLmB\nwGdvVjE88sgj2LJly3nH33333Zg7dy7+9re/YeTIkejXrx/27dvXaDqHwwGLxaIZFhMTA7vd3qLQ\nVVUOqKo8eyfp9TrExpqZuxXJml3W3IC82WXNDTQ/e3y85bzjmtKsYnjssccwb968846PjIxEXl4e\ndu/eja1bt553OrPZ3KgErFZro7L4KaoqpNxtlblbn6zZZc0NyJtd1txA4LM3qxjMZjPM5gu/Vdm7\ndy+Ki4sxfPhwAIDX64WiKBgyZAiWLFmCkSNHIi0tDYcOHcKoUaMA+N5BFBQUIC0t7dJ+CiIiCpiA\nfcZw5513YtKkSf77X3/9Nf7whz9g27ZtiI2NBQBMnjwZS5cuRXZ2Nnr37o1nn30W3bp1w6BBgwIV\ng4iILlHAisFisWg2CcXHxwMAOnfu7B920003obS0FDk5ObDZbMjMzMSKFStgMBgCFYOIiC6RTgj5\nTktXWWmXalugwaBDfLyFuVuRrNllzQ3Im13W3EDzsycmRrdovlIWAxERBY9050oiIqLgYjEQEZEG\ni4GIiDRYDEREpMFiICIiDRYDERFpsBiIiEiDxUBERBosBiIi0mAxEBGRRkiLQVEULFu2DFdffTUG\nDBiAOXPmoLKy8rzTf/755xg3bhwyMjIwfvx4fPHFF5rxBQUFmDZtGjIzMzFs2DCsW7dOiuzHjh3D\nfffdh6FDh2LAgAEYN24cNm3a1OZz15efn4++fftqrtDXlnN7vV48//zzGDFiBDIzMzFq1Cjs2rVL\niuy7du3CzTffjEGDBiErKwuLFy+Gy+UKae7S0lLcc889GDFiBFJTU7Ft27ZG01RUVGD27NkYMGAA\nrr76aixfvhyqqrbp3BUVFZg3bx5GjBiBAQMGIDs7G6tWrUKwziQU6Oe8zunTpzF48GBkZ2c3L4gI\noZdfflmMHj1anDhxQlitVjF79mwxffr0Jqc9ceKEyMjIEFu3bhUul0ts27ZN9O/fX5w8eVIIIYTX\n6xVjxowRf/7zn0V1dbU4ePCguPrqq8UHH3zQ5rN/8803YsOGDaKkpESoqir2798vBg0aJD788MM2\nnbuOx+MREydOFFOnThV33HFHwDMHI/ejjz4qJk+eLI4ePSpUVRUlJSWNfq62mL28vFz07dtXbNiw\nQSiKIoqLi8X48ePF008/HdLcpaWlYsOGDSIvL08MGzZMbN26tdE006ZNE7NmzRJWq1WcOHFCjB49\nWqxatapN5z5x4oRYtWqVOHHihFBVVRw5ckSMGDFCrFu3LuC5A529vpkzZ4o77rhDjBo1qlk5QloM\nw4cPF7m5uf77BQUFIiUlRZw6darRtM8995y49dZbNcNuvfVW8cILLwghhNi7d6/IyMgQdrvdP/6Z\nZ54Rt99+e5vP3pQHHnhALF68OHCBawUj94svvigef/xx8fzzzwetGAKZ+8cffxQpKSni6NGjQcna\nUCCzHzx4UKSkpAiXy+Uf/9RTT4mcnJyQ5q5vxIgRTa5gU1JSREFBgX9Ybm6uGDFiRGBDi8Dmbsry\n5cvFzJkzLzlnU4KRfcuWLWLGjBli8+bNzS6GkG1KslqtKCoqQt++ff3DevToAYvFgvz8/EbT5+fn\nIz09XTPsyiuv9E+bn5+PXr16aa40l56ejiNHjrT57A3V1NTg22+/RWpqapvPfeTIEWzZsgUPP/xw\nQLMGM/e+fftgsViwY8cODB06FMOHD8fChQtbfO3xUGTv06cPhg0bhrfeegterxeFhYX45JNP/FdF\nDFXun3LkyBFER0ejR48e/mHp6ekoLCwM6PMe6NwNqaqKr776KihXnQxG9rKyMjz33HN44oknWvS4\nkBWDw+EAgEbXe46JiWnyD8XhcCA6Ovq80zY1Pjo6Oij/7IHOXp+iKJg3bx46d+6MCRMmBDB14HN7\nvV788Y9/xJ/+9KcWX7e7JQKd+8yZM7Db7fjPf/6DHTt2IDc3F/n5+Vi6dGmbz67X6zFx4kSsXLkS\nGRkZGDlyJPr06YObb745pLl/it1ub/L/s25coAQ6d0NLlizB2bNnMX369EueV0PByL5w4UJMnz4d\nycnJLXpcyIqh7pV9wx/YarU2uZIxm82w2Wznnbap8TabLSgrrEBnr+PxePDggw+irKwMq1atgslk\natO516xZg169emHEiBEBzdlUDiCwfysAcP/998NisSApKQl33XUXPv744zaf/csvv8QjjzyCJUuW\n4Pvvv8eePXtgt9vxyCOPhDT3T7FYLE3+f9ZfViAEOnd9S5Ysweeff47XXnutUckFQqCzv/fee6is\nrMRtt93W4seGrBhiYmKQnJyMQ4cO+YedPHkSdru9yU0oaWlpOHz4sGbYv/71L/9burS0NBw/fhzV\n1dX+8YcPHw745phgZAcAl8uF2bNno7KyEmvXrg3KH16gc+/ZswefffYZhgwZgiFDhmDNmjXIy8vD\nkCFDUFVV1WZz9+nTBwCg0+k00zS8HwiBzn7o0CGkpqbi+uuvh8FgQEJCAiZPnoxPP/00pLl/Smpq\nKmw2G06ePOkfdvjwYXTt2jWgf+uBzg34Nh8tWLAAe/bswYYNGzSXKw6kQGffs2cPjhw5gmuuuQZD\nhgzB4sWLcerUKQwZMuSnN001/2ORwKv/CbzNZhNz5swRv//975uctqCgQGRkZIj33ntPuN1u8d57\n7zW5V9LixYtFTU2NOHz4sLjmmmvE+++/3+az2+12cfvtt4s777xT1NTUBCVvMHJXVFSI4uJi/9eT\nTz4pbr31VlFcXCwURWmzuRVFEePHjxd/+MMfhMPhEOXl5WLKlCni8ccfD2jmYGTPy8sTGRkZYvfu\n3UJVVVFRUSFmzpwppk6dGtLcQgjhdDqF0+kUw4cPF++8845wOp3C4/H4x0+bNk3MmTNH2Gy2Vtsr\n6VJzezweMXfuXPGb3/xGVFRUBDxrMLNXVVVp/j/Xr18vRowYIYqLi4Xb7b5gjpAWg9frFUuXLhWD\nBw8WmZmZYtasWf4nf9u2bSIzM1Mz/a5du8TYsWNFv379xNixY8Xu3bs1448fPy6mTp0qMjIyxHXX\nXSfWrFkjRfZ3331XpKSkiIyMDJGZmen/euyxx9p07oaCuVdSoHOfOnVKzJgxQ2RmZoqsrCyxePFi\n4XA4pMj+7rvvivHjx4sBAwaIq6++WsyZM0cUFRWFPHdKSkqjr+eff94/vry8XMyaNUtkZmaKwYMH\ni2XLlgX8BUSgc+/bt0+kpKSIvn37av43z7cLaVvK3lBL9kriNZ+JiEiDp8QgIiINFgMREWmwGIiI\nSIPFQEREGiwGIiLSYDEQEZEGi4GIiDRYDEREpPH/ATg/C864OkPJAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f63f0449a10>"
      ]
     },
     "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",
    "      \"type\":\"filters.range\",\n",
    "      \"limits\":\"Classification[1:1]\"\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);"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
	{
	"cells": [
	{
	"cell_type": "code",
	"execution_count": 18,
	"metadata": {},
	"outputs": [
	{
	"data": {
	"image/png": 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mX/tYo0GHmJhIOGvcte/8Gjy2fqE1MYyl13awGKjV6HQ6mIy+V8vBdqF3O3WE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\n",
	"text/plain": [
	"<matplotlib.figure.Figure at 0x7f63f0449a10>"
	]
	},
	"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",
	" \"type\":\"filters.range\",\n",
	" \"limits\":\"Classification[1:1]\"\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);"
	]
	}
	],
	"metadata": {
	"kernelspec": {
	"display_name": "Python 2",
	"language": "python",
	"name": "python2"
	},
	"language_info": {
	"codemirror_mode": {
	"name": "ipython",
	"version": 2
	},
	"file_extension": ".py",
	"mimetype": "text/x-python",
	"name": "python",
	"nbconvert_exporter": "python",
	"pygments_lexer": "ipython2",
	"version": "2.7.12"
	}
	},
	"nbformat": 4,
	"nbformat_minor": 2
	}