Added appendix E

rmd/84-a-mapper-induced-topology-preserving-cc-pooling-operation.rmd

@@ -1,3 +1,43 @@
 # A mapper-induced topology-preserving CC-pooling operation
 
-To be completed.
+In this section, we give an example of constructing a shape-preserving pooling operation on a CC $\mathcal{X}$. Specifically, we demonstrate the case in which $\mathcal{X}$ is a graph, and utilize the *mapper on graphs (MOG)* construction [@hajij2018mog], which is a graph skeletonization algorithm that can be used to augment $\mathcal{X}$ with topology-preserving higher-rank cells, as demonstrated in Figure \@ref(fig:hs). Although we only demonstrate the shape-preserving pooling construction on graphs, the method suggested herein can be easily extended to CCs.
+
+Let $\mathcal{X}$ be a connected graph and $g\colon\mathcal{X}^{0} \to [0,1]$ a scalar function. Let $\mathcal{U}=\{U_\alpha\}_{\alpha \in I}$ be a finite collection of open sets that covers the interval $[0,1]$. The MOG construction of a graph $MOG(V_{MOG},E_{MOG})$ based on the triplet ($\mathcal{X}$, $g$, $\mathcal{U}$) consists of the following steps:
+
+1. We first use the cover $\mathcal{U}$ to construct the pull-back cover $g^{\star}(\mathcal{U})=\{g^{-1}(U_{\alpha})\}_{\alpha \in I}$.
+2. The vertex set $V_{MOG}$ is formed by considering the connected components (i.e., maximal connected subgraphs) induced by $g^{-1}(U_\alpha)$ for each $\alpha$.
+3. The edge set $E_{MOG}$ is formed by considering the intersection among the connected components computed in step 2.
+
+Figure \@ref(fig:mog) shows an illustrative example of applying the MOG algorithm to a graph. Figure \@ref(fig:mog)(a) shows the graph on which the MOG algorithm is applied, while Figure \@ref(fig:mog)(b) visualizes the scalar function $g$ and the covering $\mathcal{U}$, which consists of four covering elements depicted in red, orange, yellow and blue colors.
+
+```{r mog, echo=FALSE, fig.align="center", fig.cap="An illustration of the MOG algorithm. The input to the MOG algorithm is a triplet $(\\mathcal{X}, g, \\mathcal{U})$, where $\\mathcal{X}$ is a graph, $g\\colon\\mathcal{X}^0\\to [0,1]$ is a scalar function defined on the vertex set of $\\mathcal{X}$, and  $\\mathcal{U}$ is a cover of $[0,1]$. (a): An input graph $\\mathcal{X}$. (b): The scalar function $g\\colon\\mathcal{X}\\to [0,1]$ is visualized by color-mapping its scalar values according to the displayed color bar. Figure (b) also shows the covering $\\mathcal{U}= \\{U_1,U_2, U_3, U_4\\}$ depicted in red, orange, yellow and blue colors. (c): We pull back via $g$ each cover element $U_i$ in $\\mathcal{U}$, and we compute the connected components in $g^{-1}(U_i)$. (d): The vertex set in the graph generated by the MOG algorithm consists of the connected components induced by $g^{-1}(U_i)$, while the edge set is formed by considering the intersection among the connected components. Note that the graph generated by the MOG algorithm approximates the shape of the input graph."}
+knitr::include_graphics('figures/graph_tda_appendix.png', dpi=NA)
+```
+
+The connected components obtained from the MOG algorithm can be used to augment a graph $\mathcal{X}$ with a skeleton $\mathcal{X}^2$ of dimension 2, thus constructing a CC, as described in Proposition \@ref(prp:augmented-cc). We denote the resulting CC by $\mathcal{X}_{g,\mathcal{U}}$. Figure \@ref(fig:mapper-as-pooling-operator) demonstrates the construction of a CC using this augmentation process based on the MOG algorithm.
+
+```{r mapper-as-pooling-operator, echo=FALSE, fig.align="center", fig.cap="A visual example of obtaining a CC from a graph via the MOG algorithm. (a): An input graph $\\mathcal{X}$. (b): The graph $\\mathcal{X}$ is augmented by the $2$-cells formed via the connected components obtained from applying the MOG algorithm to $\\mathcal{X}$. (c): The CC $X_{g,\\mathcal{U}}$ obtained by augmenting $\\mathcal{X}$ with these $2$-cells."}
+knitr::include_graphics('figures/augmented_mapper_cc.png', dpi=NA)
+```
+
+MOG is a topology-preserving graph skeletonization algorithm, which can be used to coarsen the size of an input graph $\mathcal{X}$. Such coarsening typically occurs when constructing a pooling layer. So, the skeleton $\mathcal{X}^2$ generated by the MOG algorithm can be utilized to obtain a feature-preserving pooling operation. Figure \@ref(fig:read-data) illustrates that the MOG algorithm coarsens an input graph to produce a graph that preserves topological features of the input graph.
+
+```{r read-data, echo=FALSE, fig.align="center", fig.cap="Illustration of coarsening a graph via the MOG algorithm. (a): Visualization of a graph and of a scalar function defined on it, which are used as inputs to the MOG algorithm. The scalar function is visualized by color-mapping its scalar values. (b): The resulting MOG graph. Notice how the MOG construction preserves the overall shape of the original graph."}
+knitr::include_graphics('figures/mapper_and_pooling.png', dpi=NA)
+```
+
+To recap, the MOG algorithm receives an input graph, and outputs a coarsened graph along with connected components. The connected components yield in turn a CC. The coarsened graph and the adjacency relation between the $2$-cells of the associated CC are related, as elaborated in Proposition \@ref(prp:connection-to-tda). Figure \@ref(fig:adjadj) conveys visually Proposition \@ref(prp:connection-to-tda).
+
+```{proposition, connection-to-tda, name="MOG as a CC"}
+Let $(\mathcal{X}, g, \mathcal{U})$ be a triplet consisting of a graph $\mathcal{X}$, a scalar function $g\colon\mathcal{X}^0\to [0,1]$ defined on the vertex set of $\mathcal{X}$, and a cover $\mathcal{U}$ of $[0,1]$. Let $MOG(\mathcal{X}$, $g$, $\mathcal{U})$ be the graph generated by the MOG algorithm upon receiving the triplet $(\mathcal{X}, g, \mathcal{U})$ as input. Furthermore, let $\mathcal{X}_{g,\mathcal{U}}$ be the CC constructed from the connected components that are generated by the MOG algorithm. The adjacency matrix of the graph $MOG(\mathcal{X}$, $g$, $\mathcal{U})$ is equivalent to the adjacency matrix $A_{2,2}$ of the CC $\mathcal{X}_{g,\mathcal{U}}$.
+```
+
+```{proof}
+The proof follows by observing that the $2$-cells, which are augmented to $\mathcal{X}$ to generate the CC $\mathcal{X}_{g,\mathcal{U}}$, are 2-adjacent if and only if they intersect on a vertex. Moreover, two cells intersect on a vertex if and only if there is an edge between them in the graph $MOG(\mathcal{X}, g, \mathcal{U})$ outputted by the MOG algorithm.
+```
+
+```{r adjadj, echo=FALSE, fig.align="center", fig.cap="Visual demonstration of how a MOG can be viewed as a CC. (a): Visualization of a CC $\\mathcal{X}_{g,\\mathcal{U}},$ which highlights the intersection between blue 2-cells. (b): The corresponding $MOG(\\mathcal{X}, g, \\mathcal{U})$ graph. There is a one-to-one correspondence between the blue 2-cells of $\\mathcal{X}_{g,\\mathcal{U}}$ on the left-hand side and the blue vertices of $MOG(\\mathcal{X}, g, \\mathcal{U})$ on the right-hand side. Further, two blue 2-cells of $\\mathcal{X}_{g,\\mathcal{U}}$ (left) intersect on an orange vertex if and only if there is an orange edge (right) that connects the corresponding two vertices of $MOG(\\mathcal{X}, g, \\mathcal{U})$."}
+knitr::include_graphics('figures/adjmog_adjcc_scaled.png', dpi=NA)
+```
+
+Given a CC $X_{g,\mathcal{U}}$ obtained from a graph $\mathcal{X}$ via the MOG algorithm, the map $B_{0,2}^T\colon\mathcal{C}^0(X_{g,\mathcal{U}})\to \mathcal{C}^2(X_{g,\mathcal{U}})$ can be used to induce a shape-preserving CC-pooling operation (Definition \@ref(def:pooling-exact-definition)). More specifically, a signal $\mathbf{H}_0$ supported on the vertices of $\mathcal{X}$ can be push-forwarded and pooled to a signal $\mathbf{H}_2$ supported on the 2-cells of $X_{g,\mathcal{U}}$.