This post is inspired by a couple of exercises from the classical book, SICP. I found them pretty interesting as they were just using recursion & some common list operations to multiply matrices !! I also wanted to try out the Jupyter notebook kernel for MIT Scheme & play with some Latex along the way.

Suppose we represent vectors $ v = ( v_{i} )$ as sequences of numbers, and matrices $m = ( m_{i j} )$ as sequences of vectors (the rows of the matrix). For example, the matrix \(\left\{ \begin{array} \\ 1 & 2 & 3 & 4 \\ 4 & 5 & 6 & 6 \\ 6 & 7 & 8 & 9 \\ \end{array} \right\}\)

is represented as the sequence `((1 2 3 4) (4 5 6 6) (6 7 8 9))`

. With this representation, we can use sequence operations to concisely express the basic matrix and vector operations.

We will look at the following 4 basic operations on matrices:

`(dot-product v w)`

returns the sum $ \sum_{i} v_{i} w_{i} $`(matrix-*-vector m v)`

returns the vector`t`

, where $t_{i} = \sum_{j} m_{ij} v_{j}$`(transpose m)`

returns the matrix`n`

, where $n_{ij} = m_{ji}$`(matrix-*-matrix m n)`

returns the matrix`p`

, where $ p_{ij} = \sum_{k} m_{ik} n_{kj} $

Dot product of 2 vectors in this notation can be done by using 2 higher order functions, `map`

and `fold`

, both of which are implemented using recursion.

Implementation of `map`

:

```
(define (map proc items)
(if (null? items)
nil
(cons (proc (car items))
(map proc (cdr items)))))
```

Implementation of `fold-right`

:

```
(define (fold-right op initial sequence)
(if (null? sequence)
initial
(op (car sequence)
(fold-right op initial (cdr sequence)))))
```

We can use either `fold-left`

or `fold-right`

for `dot-product`

.

```MIT Scheme ;; Define dot product of 2 vectors of equal length (define (dot-product v w) (fold-right + 0 (map * v w)) )

;; testing our function (define vec1 (list 1 2 3) ) (define vec2 (list 1 1 1) )

(dot-product vec1 vec2)

```
6
Calculating a dot product was really easy with a couple of higher order functions!
Let's work with matrices now. We will now right a function to multiply a matrix and a vector:
```MIT Scheme
(define (matrix-*-vector m v)
(map (lambda (m-row)(dot-product m-row v) )
m)
)
;; testing the function
(define mat1 (list (list 1 0 0) (list 0 1 0) (list 0 0 1)))
(matrix-*-vector mat1 vec1)
```

```
(1 2 3)
```

Let’s look at transpose now! For this, we will need to implement a helper function, `accumulate-n`

, which is similar to `fold`

except that it takes as its third argument a sequence of sequences, which are all assumed to have the same number of elements.

```MIT Scheme ;; Defining helper functions for transpose to ;; apply the operation op to combine all the first elements of the sequences, ;; all the second elements of the sequences, and so on, ;; and returns a sequence of the results. (define (accumulate-n op init seqs) (if (null? (car seqs)) ‘() (cons (fold-right op init (map car seqs)) (accumulate-n op init (map cdr seqs)) ) ) )

(define (transpose mat) (accumulate-n cons ‘() mat) )

;; testing transpose (define mat2 (list (list 1 2 3) (list 4 5 6) (list 7 8 9))) (transpose mat2)

```
((1 4 7) (2 5 8) (3 6 9))
Now, let's use this transpose function to do matrix multiplication:
```MIT Scheme
; Matrix multiplication
(define (matrix-*-matrix m n)
(let ((n-cols (transpose n)))
(map (lambda (m-row)(matrix-*-vector n-cols m-row))
m)
)
)
;; For testing
(matrix-*-matrix mat2 mat1)
```

```
((1 2 3) (4 5 6) (7 8 9))
```

We can even write recursive procedures to create some special kinds of matrices, for eg, an identity matrix. Here is a recursive procudure to create an identity matrix of length `n`

:

```MIT Scheme ;; Create an identity matrix of length n ; N -> [List-of [List-of N]] (define (identityM n) (letrec ;; Documentation for letrec : https://groups.csail.mit.edu/mac/ftpdir/scheme-7.4/doc-html/scheme_3.html ( ;; N -> [List-of [List-of N]] (generate-matrix (lambda (row) (cond ((= row 0) ‘()) (else (cons (generate-row row n) (generate-matrix (- row 1)))))))

```
;; N N -> [List-of N]
(generate-row (lambda (row col)
;; col goes from column n to 0
(cond
((= col 0) '())
(else (cons (if (= row col) 1 0)
(generate-row row (- col 1)))))))
)
(generate-matrix n)
) )
```

(identitym 3) ```

```
((1 0 0) (0 1 0) (0 0 1))
```

If you found these functions interesting, I’de definitely encourage to go read SICP. I wrote about why I’m reading SICP here.

**PS** :
Here ‘s a nice tutorial on using Latex in Markdown here