{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import collections\n",
    "\n",
    "import ld2dap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "layers_files = [\n",
    "    '../Data/phase1_rasters/DEM+B_C123/UH17_GEM051_TR.tif',\n",
    "    '../Data/phase1_rasters/DEM_C123_3msr/UH17_GEG051_TR.tif',\n",
    "    '../Data/phase1_rasters/DEM_C123_TLI/UH17_GEG05_TR.tif',\n",
    "    '../Data/phase1_rasters/DSM_C12/UH17c_GEF051_TR.tif',\n",
    "    '../Data/phase1_rasters/Intensity_C1/UH17_GI1F051_TR.tif',\n",
    "    '../Data/phase1_rasters/Intensity_C2/UH17_GI2F051_TR.tif',\n",
    "    '../Data/phase1_rasters/Intensity_C3/UH17_GI3F051_TR.tif'\n",
    "]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Node Streaming Self-Dual Attribute Profiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "l = ld2dap.LoadTIFF(layers_files[0])\n",
    "t = ld2dap.Treshold(1e4)\n",
    "a = ld2dap.SelfDualAttributeProfiles(area = [1e3, 1e6])#, sd=[.4,.6,.8], moi=[.5,.9])\n",
    "f = ld2dap.Differential()\n",
    "d = ld2dap.ShowFig(stack_id='all', symb=False)\n",
    "o = ld2dap.RawOutput()\n",
    "\n",
    "o.input = a\n",
    "d.input = f\n",
    "f.input = a\n",
    "a.input = t\n",
    "t.input = l\n",
    "\n",
    "d.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "(o.data[:,:,0] == o.data[:,:,13]).all()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(o.metadata[1]), o.data.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Algorithm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Metadata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "A = {'area': 2, 'sd': 3, 'moi': 2}\n",
    "raster_count = 2\n",
    "\n",
    "att_len = list(A.values())\n",
    "att_len = np.tile(att_len, raster_count)\n",
    "display(att_len)\n",
    "\n",
    "start = np.cumsum(att_len)[:-1]\n",
    "start = np.hstack(([0], start))\n",
    "start\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data\n",
    "\n",
    "Duplicate origin in attributes to respect Stack construction\n",
    "\n",
    "#### Insert a raster in a stack"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "stack = o.data.copy()\n",
    "raster = stack[:,:,0]\n",
    "\n",
    "stack.shape, raster.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "where = 3\n",
    "nstack = np.insert(stack, where, raster, axis=2)\n",
    "nstack.shape, (nstack[:,:,0] == nstack[:,:,where]).all()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Insert same raster in multiple places"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "raster_broadcast = np.tile(raster, (2, 1, 1))\n",
    "raster_broadcast = np.rollaxis(raster_broadcast, 0, 3)\n",
    "raster_broadcast.shape, (raster_broadcast[:,:,1] == raster).all()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "nstack = np.insert(stack, (3,5), raster_broadcast, axis=2)\n",
    "nstack.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check if offset is ok:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "(stack[:,:,3] == nstack[:,:,4]).all()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Index where origin should be placed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "raster_count = 2\n",
    "\n",
    "att_len = {'area': 3, 'sd': 4, 'moi': 3}\n",
    "where = np.array(list(att_len.values()))\n",
    "where = where[where != 0] - 1\n",
    "\n",
    "where[0] += 1\n",
    "display(where)\n",
    "count = sum(where)\n",
    "display(count)\n",
    "\n",
    "where = np.cumsum(where[:-1])\n",
    "origins_dcount = where.size\n",
    "display(where)\n",
    "\n",
    "offset = np.repeat(np.arange(raster_count) * count, where.size)\n",
    "display(offset)\n",
    "where = np.tile(where, (raster_count)) + offset\n",
    "where"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Repeat multiple origins"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "origins_index = np.arange(raster_count) * count\n",
    "display(origins_index)\n",
    "origins = stack[:,:,origins_index]\n",
    "origins.shape, (origins[:,:,0] == stack[:,:,0]).all(), (origins[:,:,1] == stack[:,:,8]).all()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "rorigins = np.repeat(origins, 2, axis=2)\n",
    "rorigins.shape, \\\n",
    "(rorigins[:,:,0] == rorigins[:,:,1]).all() and (origins[:,:,0] == rorigins[:,:,1]).all(), \\\n",
    "(rorigins[:,:,2] == rorigins[:,:,3]).all() and (origins[:,:,1] == rorigins[:,:,2]).all()"
   ]
  }
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