add cost estimates

README.rst

@@ -212,15 +212,11 @@ cost of the MODULO decompositions, with and without the memory-saving option.
 Given a dataset of size ``n_s \times n_t``, we consider the computation of ``n_r`` modes. When using the memory saving option, we refer to 
 ``n_t' = n_t / n_p`` as the number of time steps in each partition, and to ``n_s' = n_s / n_p`` as the number of spatial points in each partition.
 
-|                  | Phase 1: \(D\)                        | Phase 2: \(K\)                                    | Phase 3: \(\Psi\)                             | Phase 4: \(\Phi\)                                                |
-|------------------|---------------------------------------|--------------------------------------------------|----------------------------------------------|-----------------------------------------------------------------|
-| No Memory Saving | \(n_s \times n_t\)                    | \(n_t^2\)                                        | \(n_t^2 + n_t \times n_r\)                   | \(n_s \times n_t + n_t \times n_r + n_s \times n_r\)            |
-| Memory Saving    | /                                     | \(n_s \times n_t' + n_t' \times n_t'\)           | \(n_t^2 + r \cdot n_t\)                      | \((n_s \times n_t') + n_s' \times n_t + n_s \times n_r\)        |
 
-
-<script type="text/javascript" async
-  src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.7/MathJax.js?config=TeX-MML-AM_CHTML">
-</script>
+|                  | Phase 1: $D$     | Phase 2: $K$                         | Phase 3: $\\Psi$         | Phase 4: $\\Phi$                                     |
+|------------------|------------------|--------------------------------------|--------------------------|------------------------------------------------------|
+| No Memory Saving | $n_s \times n_t$ | $n_t^2$                              | $n_t^2 + n_t \times n_r$ | $n_s \times n_t + n_t \times n_r + n_s \times n_r$   |
+| Memory Saving    |      /           | $n_s \times n_t' + n_t' \times n_t'$ | $n_t^2 + r \cdot n_t$    | $n_s \times n_t' + n_s' \times n_t + n_s \times n_r$ |
 
 As shown in the table, the computational cost of the decomposition is dominated by the computation of the correlation matrix ``K`` in Phase 2. The 
 memory-saving option significantly reduces the computational cost of this phase, as the correlation matrix is computed for each partition, rather than