From 43d36230a137f018dbfce58e2ada5400502f45d1 Mon Sep 17 00:00:00 2001
From: Karamaz0V1 <florent.guiotte@gmail.com>
Date: Fri, 30 Mar 2018 12:10:46 +0200
Subject: [PATCH] HAPs Notebook

---
 Notebooks/HAPs.ipynb | 233 +++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 233 insertions(+)
 create mode 100644 Notebooks/HAPs.ipynb

diff --git a/Notebooks/HAPs.ipynb b/Notebooks/HAPs.ipynb
new file mode 100644
index 0000000..83cce89
--- /dev/null
+++ b/Notebooks/HAPs.ipynb
@@ -0,0 +1,233 @@
+{
+ "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)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}