{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "%matplotlib inline"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Cloud viewer\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import numpy as np\nfrom itom import pointCloud\nfrom itom import polygonMesh\nfrom itom import ui\nfrom itom import dataObject\n\ntry:\n    from itom import pointCloud\nexcept Exception as ex:\n    ui.msgInformation(\n        \"PointCloud missing\",\n        \"your itom version is compiled without support of pointClouds\",\n    )\n    raise ex"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Create a data objects with X, Y and Z values of a topography\nas well as a 2.5D topography in terms of a data object.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "[X, Y] = np.meshgrid(np.arange(0, 5, 0.1), np.arange(0, 5, 0.1))\nZ = np.sin(X * 2) + np.cos(Y * 0.5)\nI = np.random.rand(*X.shape)  # further intensity\nC = dataObject.randN(\n    [X.shape[0], X.shape[1]], \"rgba32\"\n)  # further color information\ntopography = dataObject(Z).astype(\"float32\")\ntopography.axisScales = (0.1, 0.1)\ntopography[0, 0] = float(\"nan\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Create a point cloud from the X, Y and Z arrays with further intensity information.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "cloud1 = pointCloud.fromXYZI(X, Y, Z, I)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Create a point cloud from the topography image with further colour information.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "cloud2 = pointCloud.fromTopography(topography, color=C)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Create a point cloud from the X, Y and Z arrays with further colour information.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "cloud3 = pointCloud.fromXYZRGBA(X, Y, Z, C)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Create a point cloud from the X, Y and Z arrays with the Z-values as intensity information.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "cloud4 = pointCloud.fromXYZI(X, Y, Z - 0.1, Z)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Manually create triangular polygons for the whole surface\nthe polygons are regularly distributed and each rectangle is divided into two polygons.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "polygons = dataObject.zeros([2 * 49 * 49, 3], \"uint16\")\nc = 0\nfor row in range(0, 49):\n    for col in range(0, 49):\n        polygons[c, 0] = row * 50 + col\n        polygons[c, 1] = (row + 1) * 50 + col\n        polygons[c, 2] = row * 50 + 1 + col\n        c += 1\nfor row in range(0, 49):\n    for col in range(0, 49):\n        polygons[c, 0] = (row + 1) * 50 + col\n        polygons[c, 1] = (row + 1) * 50 + col + 1\n        polygons[c, 2] = row * 50 + col + 1\n        c += 1"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Create polygonal mesh structure from cloud3 and polygons.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "mesh = polygonMesh.fromCloudAndPolygons(cloud3, polygons)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "As alternative approach you can directly create the same polygonal mesh\nfrom the point cloud if you know that the point cloud is organized, hence,\nthe points are located like in a regular grid.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "mesh2 = polygonMesh.fromOrganizedCloud(cloud2)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Create GUI (3D Viewer)\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "gui = ui(\"cloudViewer.ui\", ui.TYPEWINDOW)\n\n# gui.plot.call(\"addPointCloud\",cloud1,\"cloud1\")\n# gui.plot.call(\"addPointCloud\",cloud2,\"cloud2\")\n# gui.plot.call(\"addPointCloud\",cloud3,\"cloud3\")\ngui.plot.call(\n    \"addPointCloud\", cloud4, \"cloud4\"\n)  # visualize cloud4 under the name 'cloud4'\ngui.plot.call(\n    \"setItemProperty\", \"cloud4\", \"PointSize\", 10\n)  # change the property PointSize of this point\n# gui.plot.call(\"addMesh\",mesh,\"mesh\")\ngui.plot.call(\n    \"addMesh\", mesh2, \"mesh2\"\n)  # visualize the mesh2 under the name 'mesh2'\ngui.show()"
      ]
    }
  ],
  "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",
      "version": "3.8.10"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
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