ld2daps/Notebooks/HAPs.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Histogram APs"
   ]
  },
  {
   "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": [
    "# Specific Utils\n",
    "\n",
    "def DFC_filter(raster):\n",
    "    raster[raster > 1e4] = raster[raster < 1e4].max()\n",
    "\n",
    "def show(im):\n",
    "    plt.figure(figsize=(16*2,3*2))\n",
    "    plt.imshow(im)\n",
    "    plt.colorbar()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "raster_p = Path('../Data/phase1_rasters/Intensity_C3/UH17_GI3F051_TR.tif')\n",
    "raster   = triskele.read(raster_p)\n",
    "DFC_filter(raster)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "show(raster)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "area = np.array([25, 100, 500, 1e3, 5e3, 10e3, 50e3, 100e3, 150e3])\n",
    "\n",
    "t = triskele.Triskele(raster, verbose=False)\n",
    "attributes = t.filter(tree='tos-tree',\n",
    "                      area=area\n",
    "                     )\n",
    "attributes.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = attributes\n",
    "i = 3\n",
    "show(a[:,:,i].astype(np.float) - a[:,:,i+1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "patch_size = 5\n",
    "\n",
    "### \n",
    "amp = int((patch_size - 1 ) / 2)\n",
    "\n",
    "stack = list()\n",
    "for i in range(-amp, amp+1):\n",
    "    ai = i if i > 0 else None\n",
    "    bi = i if i < 0 else None\n",
    "    ci = -bi if bi is not None else None\n",
    "    di = -ai if ai is not None else None\n",
    "\n",
    "    for j in range(-amp, amp+1):\n",
    "        offset = np.zeros(raster.shape)\n",
    "        aj = j if j > 0 else None\n",
    "        bj = j if j < 0 else None\n",
    "        cj = -bj if bj is not None else None\n",
    "        dj = -aj if aj is not None else None\n",
    "        print('{}:{} {}:{} - {}:{} {}:{}'.format(ai, bi, ci, di, aj, bj, cj, dj))\n",
    "        offset[ai:bi, aj:bj] = raster[ci:di, cj:dj]\n",
    "        stack.append(offset)\n",
    "\n",
    "offset_stack = np.stack(stack, axis=2)\n",
    "offset_stack.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "offset_stack[-3,-3,:].reshape(-1,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "show(offset_stack[:,:,0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "del offset_stack"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "hist = np.stack(raster, raster[:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.repeat(100,10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pstl = list()\n",
    "\n",
    "for c, p in [(100, .06), (60, .1), (12, .5), (20, .3)]:\n",
    "    st = np.random.binomial(np.repeat(c,1e7), p)\n",
    "    pst = pd.DataFrame(st, columns=['{} - {}'.format(c, p)])\n",
    "    pstl.append(pst)\n",
    "    \n",
    "psta = pd.concat(pstl)\n",
    "pd.options.display.float_format = '{:.2f}'.format\n",
    "display(psta.describe())\n",
    "psta.hist(figsize=(16, 9))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.concat([pst, pst], axis=1)"
   ]
  }
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