rendering techniques notebook

Author: philipc2

notebooks/02-methods/02-rendering-techniques.ipynb

@@ -7,13 +7,17 @@
     "# Rendering Techniques\n",
     "---\n",
     "\n",
-    "Since Unstructured Grids are significantly more complex than Structured (a.k.a. Regular) Grids, the choice of rendering technique plays an important role in obtaining high-resolution, accurate, and scalable visualizations. \n",
+    "Since Unstructured Grids require significantly more overhead to represent compared to Structured (a.k.a. Regular) grids, the choice of rendering technique plays an important in obtaining high-resolution, accurate, and scalable visualuations. \n",
+    "\n",
     "\n",
     "This notebook introduces relevant concepts and techniques that will be mentioned and used throughout this Cookbook."
    ]
   },
   {
    "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false
+   },
    "source": [
     "## Vector (Shape) Geometries\n",
     "\n",
@@ -26,70 +30,40 @@
     "Rendering each face as a polygon will lead to visuals that look like this, which are extremely high-quality and represent the exact geometry of each face.\n",
     "\n",
     "\n",
-    "<img src=\"../images/rendering/polygons.png\" alt=\"Continents\" width=\"800\"/>"
-   ],
-   "metadata": {
-    "collapsed": false
-   }
+    "<img src=\"../images/rendering/polygons.png\" alt=\"Continents\" width=\"400\"/>"
+   ]
   },
   {
    "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false
+   },
    "source": [
     "Another example of Vector Geometries is encountered when adding features to a visualization, such as Contents or Borders. The geometries of these features are drawn onto our screen.\n",
     "\n",
     "\n",
-    "<img src=\"../images/rendering/contients.jpg\" alt=\"Continents\" width=\"800\"/>"
-   ],
-   "metadata": {
-    "collapsed": false
-   }
+    "<img src=\"../images/rendering/contients.jpg\" alt=\"Continents\" width=\"600\"/>"
+   ]
   },
   {
    "cell_type": "markdown",
-   "source": [
-    "The following examples show examples of how different elements of an unstructured grid can be represented geometrically."
-   ],
    "metadata": {
     "collapsed": false
-   }
+   },
+   "source": [
+    "The following code snippets show how we can represent each of the main unstructured grid geometries.\n"
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "outputs": [],
-   "source": [
-    "import shapely as sp"
-   ],
-   "metadata": {
-    "collapsed": false
-   }
-  },
-  {
-   "cell_type": "markdown",
-   "source": [
-    "A point is represented using a pair of Longitude and Latitude Values"
-   ],
    "metadata": {
     "collapsed": false
-   }
-  },
-  {
-   "cell_type": "markdown",
-   "source": [
-    "sp.Point([0.0, 0.0])"
-   ],
-   "metadata": {
-    "collapsed": false
-   }
-  },
-  {
-   "cell_type": "markdown",
+   },
+   "outputs": [],
    "source": [
-    "An Edge is represented using a pair of points. "
-   ],
-   "metadata": {
-    "collapsed": false
-   }
+    "import shapely as sp"
+   ]
   },
   {
    "cell_type": "code",
@@ -102,59 +76,52 @@
     "collapsed": false
    }
   },
-  {
-   "cell_type": "markdown",
-   "source": [
-    "A Polygon is represented in terms of it's exterior coordinates, each of which are points."
-   ],
-   "metadata": {
-    "collapsed": false
-   }
-  },
   {
    "cell_type": "code",
    "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [],
    "source": [
     "sp.Polygon([[100, 40], [100, 50], [90, 50], [90, 40], [100, 40]])"
-   ],
-   "metadata": {
-    "collapsed": false
-   }
+   ]
   },
   {
    "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false
+   },
    "source": [
     "## Rasterization\n",
     "\n",
-    "Rendering each geometry directly is an expensive operation for even moderately large datasets. \n",
+    "While there is definitely merit in rendering each geometric shape directly, this operation is extremely computationally expensive for large datasets.\n",
     "\n",
-    "Rasterization todo..\n",
+    "Rasterization is a technique in computer graphics that converts vector (a.k.a geometric shapes) graphics into a raster image, which is simply a series of pixels.\n",
     "\n",
+    "The figure below shows how rasterization approximates the geometry of geometries.\n",
     "\n",
-    "<img src=\"../images/rendering/raster_example.png\" alt=\"Rasterization Example\" width=\"800\"/>"
-   ],
-   "metadata": {
-    "collapsed": false
-   }
+    "\n",
+    "<img src=\"../images/rendering/raster_example.png\" alt=\"Rasterization Example\" width=\"1000\"/>"
+   ]
   },
   {
    "cell_type": "markdown",
-   "source": [
-    "Below is an example of rastered polygons plotted against the expected geometry.\n",
-    "\n",
-    "<img src=\"../images/rendering/raster-vs-vector.png\" alt=\"raster and vector\" width=\"800\"/>"
-   ],
    "metadata": {
     "collapsed": false
-   }
+   },
+   "source": [
+    "Below is an example of rasterized polygons plotted against the expected geometry.\n",
+    "\n",
+    "<img src=\"../images/rendering/raster-vs-vector.png\" alt=\"raster and vector\" width=\"400\"/>"
+   ]
   },
   {
    "cell_type": "markdown",
-   "source": [],
    "metadata": {
     "collapsed": false
-   }
+   },
+   "source": []
   }
  ],
  "metadata": {
@@ -173,7 +140,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.11"
+   "version": "3.11.5"
   },
   "nbdime-conflicts": {
    "local_diff": [