Edit: Title updated to reflect what my question should have been, and hopefully lead other users here when they have the same problem.
Little bit of a mess, but this is a work-in-progress common lisp implementation of anydice that should output some ascii art representing a probability density function for a hash-table representing dice rolls. I've been trying to figure out exactly why, but I keep getting the error *** - SYSTEM::READ-EVAL-READER: variable BAR-CHARS has no value when attempting to run the file in clisp. The error is originating from the output function.
The code is messy and convoluted (but was previously working if the inner most loop of output is replaced with something simpler), but this specific error does not make sense to me. Am I not allowed to access the outer let* variables/bindings/whatever from the inner most loop/cond? Even when I substitute bar-chars for the list form directly, I get another error that char-decimal has no value either. I'm sure there's something about the loop macro interacting with the cond macro I'm missing, or the difference between setf, let*, multiple-value-bind, etc. But I've been trying to debug this specific problem for hours with no luck.
(defun sides-to-sequence (sides)
(check-type sides integer)
(loop for n from 1 below (1+ sides) by 1 collect n))
(defun sequence-to-distribution (sequence)
(check-type sequence list)
(setf distribution (make-hash-table))
(loop for x in sequence
do (setf (gethash x distribution) (1+ (gethash x distribution 0))))
distribution)
(defun distribution-to-sequence (distribution)
(check-type distribution hash-table)
(loop for key being each hash-key of distribution
using (hash-value value) nconc (loop repeat value collect key)))
(defun combinations (&rest lists)
(if (endp lists)
(list nil)
(mapcan (lambda (inner-val)
(mapcar (lambda (outer-val)
(cons outer-val
inner-val))
(car lists)))
(apply #'combinations (cdr lists)))))
(defun mapcar* (func lists) (mapcar (lambda (args) (apply func args)) lists))
(defun dice (left right)
(setf diceprobhash (make-hash-table))
(cond ((integerp right)
(setf right-distribution
(sequence-to-distribution (sides-to-sequence right))))
((listp right)
(setf right-distribution (sequence-to-distribution right)))
((typep right 'hash-table) (setf right-distribution right))
(t (error (make-condition 'type-error :datum right
:expected-type
(list 'integer 'list 'hash-table)))))
(cond ((integerp left)
(sequence-to-distribution
(mapcar* #'+
(apply 'combinations
(loop repeat left collect
(distribution-to-sequence right-distribution))))))
(t (error (make-condition 'type-error :datum left
:expected-type
(list 'integer))))))
(defmacro d (arg1 &optional arg2)
`(dice ,#(if (null arg2) (list 1 arg1) (list arg1 arg2))))
(defun distribution-to-probability (distribution)
(setf probability-distribution (make-hash-table))
(setf total-outcome-count
(loop for value being the hash-values of distribution sum value))
(loop for key being each hash-key of distribution using (hash-value value)
do (setf (gethash key probability-distribution)
(float (/ (gethash key distribution) total-outcome-count))))
probability-distribution)
(defun output (distribution)
(check-type distribution hash-table)
(format t " # %~%")
(let* ((bar-chars (list 9617 9615 9614 9613 9612 9611 9610 9609 9608))
(bar-width 100)
(bar-width-eighths (* bar-width 8))
(probability-distribution (distribution-to-probability distribution)))
(loop for key being each hash-key of
probability-distribution using (hash-value value)
do (format t "~4d ~5,2f ~{~a~}~%" key (* 100 value)
(loop for i from 0 below bar-width
do (setf (values char-column char-decimal)
(truncate (* value bar-width)))
collect
(cond ((< i char-column)
#.(code-char (car (last bar-chars))))
((> i char-column)
#.(code-char (first bar-chars)))
(t
#.(code-char (nth (truncate
(* 8 (- 1 char-decimal)))
bar-chars)))))))))
(output (d 2 (d 2 6)))
This is my first common lisp program I've hacked together, so I don't really want any criticism about formatting/style/performance/design/etc as I know it could all be better. Just curious what little detail I'm missing in the output function that is causing errors. And felt it necessary to include the whole file for debugging purposes.
loops scoping is perfectly conventional. But as jkiiski says, #. causes the following form to be evaluated at read time: bar-chars is not bound then.
Your code is sufficiently confusing that I can't work out whether there's any purpose to read-time evaluation like this. But almost certainly there is not: the uses for it are fairly rare.
I'm arduously struggling my way through the N-queens problem in SICP (the book; I spent a few days on it -- last question here: Solving Eight-queens in scheme). Here is what I have for the helper functions:
#lang sicp
; the SICP language in Racket already defines this:
; (define nil '()
; boilerplate: filter function and range functions
(define (filter func lst)
(cond
((null? lst)
nil)
(else
(if (func (car lst))
(cons (car lst) (filter func (cdr lst)))
(filter func (cdr lst))))))
(define (range a b)
(if (> a b)
nil
(cons a (range (+ 1 a) b))))
; Selectors/handlers to avoid confusion on the (col, row) notation:
; representing it a position as (col, row), using 1-based indexing
(define (make-position col row) (cons col (list row)))
(define (col p) (car p))
(define (row p) (cadr p))
; adding a new position to a board
(define (add-new-position existing-positions p)
(append existing-positions
(list (make-position (col p) (row p)))))
; The 'safe' function
(define (any? l proc)
(cond ((null? l) #f)
((proc (car l)) #t)
(else (any? (cdr l) proc))))
(define (none? l proc) (not (any? l proc)))
(define (safe? existing-positions p)
(let ((bool (lambda (x) x)) (r (row p)) (c (col p)))
(and
; is the row safe? i.e., no other queen occupies that row?
(none? (map (lambda (p) (= (row p) r)) existing-positions)
bool)
; safe from the diagonal going up
(none? (map (lambda (p) (= r (+ (row p) (- c (col p)))))
existing-positions)
bool)
; safe from the diagonal going down
(none? (map (lambda (p) (= r (- (row p) (- c (col p)))))
existing-positions)
bool))))
And now, with that boilerplate, the actual/monstrous first working version I have of the queens problem:
(define (positions-for-col col size)
(map (lambda (ri) (make-position col ri))
(range 1 size)))
(define (queens board-size)
(define possible-positions '())
(define safe-positions '())
(define all-new-position-lists '())
(define all-positions-list '())
; existing-positions is a LIST of pairs
(define (queen-cols col existing-positions)
(if (> col board-size)
(begin
(set! all-positions-list
(append all-positions-list (list existing-positions))))
(begin
; for the column, generate all possible positions,
; for example (3 1) (3 2) (3 3) ...
(set! possible-positions (positions-for-col col board-size))
; (display "Possible positions: ") (display possible-positions) (newline)
; filter out the positions that are not safe from existing queens
(set! safe-positions
(filter (lambda (pos) (safe? existing-positions pos))
possible-positions))
; (display "Safe positions: ") (display safe-positions) (newline)
(if (null? safe-positions)
; bail if we don't have any safe positions
'()
; otherwise, build a list of positions for each safe possibility
; and recursively call the function for the next column
(begin
(set! all-new-position-lists
(map (lambda (pos)
(add-new-position existing-positions pos))
safe-positions))
; (display "All positions lists: ") (display all-new-position-lists) (newline)
; call itself for the next column
(map (lambda (positions-list) (queen-cols (+ 1 col)
positions-list))
all-new-position-lists))))))
(queen-cols 1 '())
all-positions-list)
(queens 5)
(((1 1) (2 3) (3 5) (4 2) (5 4))
((1 1) (2 4) (3 2) (4 5) (5 3))
((1 2) (2 4) (3 1) (4 3) (5 5))
((1 2) (2 5) (3 3) (4 1) (5 4))
((1 3) (2 1) (3 4) (4 2) (5 5))
To be honest, I think I did all the set!s so that I could more easily debug things (is that common?) How could I remove the various set!s to make this a proper functional-procedure?
As an update, the most 'terse' I was able to get it is as follows, though it still appends to a list to build the positions:
(define (queens board-size)
(define all-positions-list '())
(define (queen-cols col existing-positions)
(if (> col board-size)
(begin
(set! all-positions-list
(append all-positions-list
(list existing-positions))))
(map (lambda (positions-list)
(queen-cols (+ 1 col) positions-list))
(map (lambda (pos)
(add-new-position existing-positions pos))
(filter (lambda (pos)
(safe? existing-positions pos))
(positions-for-col col board-size))))))
(queen-cols 1 nil)
all-positions-list)
Finally, I think here is the best I can do, making utilization of a 'flatmap' function that helps deal with nested lists:
; flatmap to help with reduction
(define (reduce function sequence initializer)
(let ((elem (if (null? sequence) nil (car sequence)))
(rest (if (null? sequence) nil (cdr sequence))))
(if (null? sequence)
initializer
(function elem
(reduce function rest initializer)))))
(define (flatmap proc seq)
(reduce append (map proc seq) nil))
; actual
(define (queens board-size)
(define (queen-cols col existing-positions)
(if (> col board-size)
(list existing-positions)
(flatmap
(lambda (positions-list)
(queen-cols (+ 1 col) positions-list))
(map
(lambda (pos)
(add-new-position existing-positions
pos))
(filter
(lambda (pos)
(safe? existing-positions pos))
(positions-for-col col board-size))))))
(queen-cols 1 nil))
Are there any advantages of this function over the one using set! or is it more a matter of preference (I find the set! one easier to read and debug).
When you are doing the SICP problems, it would be most beneficial if you strive to adhere to the spirit of the question. You can determine the spirit from the context: the topics covered till the point you are in the book, any helper code given, the terminology used etc. Specifically, avoid using parts of the scheme language that have not yet been introduced; the focus is not on whether you can solve the problem, it is on how you solve it. If you have been provided helper code, try to use it to the extent you can.
SICP has a way of building complexity; it does not introduce a concept unless it has presented enough motivation and justification for it. The underlying theme of the book is simplification through abstraction, and in this particular section you are introduced to various higher order procedures -- abstractions like accumulate, map, filter, flatmap which operate on sequences/lists, to make your code more structured, compact and ultimately easier to reason about.
As illustrated in the opening of this section, you could very well avoid the use of such higher programming constructs and still have programs that run fine, but their (liberal) use results in more structured, readable, top-down style code. It draws parallels from the design of signal processing systems, and shows how we can take inspiration from it to add structure to our code: using procedures like map, filter etc. compartmentalize our code's logic, not only making it look more hygienic but also more comprehensible.
If you prematurely use techniques which don't come until later in the book, you will be missing out on many key learnings which the authors intend for you from the present section. You need to shed the urge to think in an imperative way. Using set! is not a good way to do things in scheme, until it is. SICP forces you down a 'difficult' path by making you think in a functional manner for a reason -- it is for making your thinking (and code) elegant and 'clean'.
Just imagine how much more difficult it would be to reason about code which generates a tree recursive process, wherein each (child) function call is mutating the parameters of the function. Also, as I mentioned in the comments, assignment places additional burden upon the programmers (and on those who read their code) by making the order of the expressions have a bearing on the results of the computation, so it is harder to verify that the code does what is intended.
Edit: I just wanted to add a couple of points which I feel would add a bit more insight:
Your code using set! is not wrong (or even very inelegant), it is just that in doing so, you are being very explicit in telling what you are doing. Iteration also reduces the elegance a bit in addition to being bottom up -- it is generally harder to think bottom up.
I feel that teaching to do things recursively where possible is one of the aims of the book. You will find that recursion is a crucial technique, the use of which is inevitable throughout the book. For instance, in chapter 4, you will be writing evaluators (interpreters) where the authors evaluate the expressions recursively. Even much earlier, in section 2.3, there is the symbolic differentiation problem which is also an exercise in recursive evaluation of expressions. So even though you solved the problem imperatively (using set!, begin) and bottom-up iteration the first time, it is not the right way, as far as the problem statement is concerned.
Having said all this, here is my code for this problem (for all the structure and readability imparted by FP, comments are still indispensable):
; the board is a list of lists - a physical n x n board, where
; empty positions are 0 and filled positions are 1
(define (queens board-size)
(let ((empty-board (empty-board-gen board-size))) ; minor modification - making empty-board available to queen-cols
(define (queen-cols k)
(if (= k 0)
(list empty-board)
(filter (lambda (positions) (safe? k positions))
; the flatmap below generates a list of new positions
; by 'adjoining position'- adding 'board-size' number
; of new positions for each of the positions obtained
; recursively from (queen-cols (- k 1)), which have
; been found to be safe till column k-1. This new
; set (list) of positions is then filtered using the
; safe? function to filter out unsafe positions
(flatmap
(lambda (rest-of-queens)
; the map below adds 'board-size' number of new
; positions to 'rest-of-queens', which is an
; element of (queen-cols (- k 1))
(map (lambda (new-row)
(adjoin-position new-row k rest-of-queens))
(enumerate-interval 1 board-size)))
(queen-cols (- k 1))))))
(queen-cols board-size)) ; end of let block
)
; add a column having a queen placed at position (new-row, col).
(define (adjoin-position new-row col rest-queens)
(let ((board-dim (length rest-queens))) ;length of board
; first create a zero 'vector', put a queen in it at position
; 'new-row', then put (replace) this new vector/column at the
; 'col' position in rest-queens
(replace-elem (replace-elem 1 new-row (gen-zero-vector board-dim)) col rest-queens)))
(define (safe? k positions) ; the safe function
(let ((row-pos-k (non-zero-index (item-at-index k positions)))) ; get the row of the queen in column k
(define (iter-check col rem) ;iteratively check if column 'col' of the board is safe wrt the kth column
(let ((rw-col (non-zero-index (car rem)))) ; get the row of 'col' in which a queen is placed
(cond ((= k 1) #t); 1x1 board is always safe
((= col k) #t); if we reached the kth column, we are done
; some simple coordinate geometry
; checks if the row of the queen in col and kth
; column is same, and also checks if the 'slope' of
; the line connecting the queens of the two columns
; is 1 (i.e. if it's a diagonal), if either is true,
; the kth queen is not safe
((or (= row-pos-k rw-col) (= (- k col) (abs (- row-pos-k rw-col)))) #f)
(else (iter-check (+ col 1) (cdr rem)))))) ; check the next column
(iter-check 1 positions))) ; start checking from the first column
; helper functions follow
(define (item-at-index n items) ; given a list, return the nth element
(define (iter idx rem)
(if (= idx n)
(car rem)
(iter (+ idx 1) (cdr rem))))
(iter 1 items))
(define (non-zero-index items)
; gives the first non-zero element from items - used for
; determining the row at which a queen is placed
(define (iter a rem)
(if (> (car rem) 0)
a
(iter (+ a 1) (cdr rem))))
(iter 1 items))
(define (empty-board-gen n) ; the empty board is n lists, each list with n zeros
(map (lambda (x) (map (lambda (y) 0) (enumerate-interval 1 n))) (enumerate-interval 1 n)))
(define (replace-elem new-elem pos items) ; replace item at position pos in items by new-elem, ultimately used for replacing an empty column with a column which has a queen
(define (iter i res rem)
(if (= i pos)
(append res (list new-elem) (cdr rem))
(iter (+ i 1) (append res (list(car rem))) (cdr rem)))) (iter 1 '() items))
(define (gen-zero-vector n) ; generate a list of length n with only zeros as elements
(define (iter a res)
(if (> a n)
res
(iter (+ a 1) (append res (list 0))))) (iter 1 '()))
(define (flatmap proc seq)
(accumulate append '() (map proc seq)))
(define (length items) ; not particularly efficient way for length of a list
(accumulate + 0 (map (lambda (x) 1) items)))
(define (accumulate op null-value seq)
(if (null? seq)
null-value
(op (car seq) (accumulate op null-value (cdr seq)))))
(define (enumerate-interval low high) ; a list of integers from low to hi
(define (iter a b res)
(if (> a b)
res
(iter (+ a 1) b (append res (cons a '())))))
(iter low high '()))
There are many ways to tackle this problem. I'll attempt to write a short and concise solution using Racket-specific procedures, explaining each step of the way. A solution using only the Scheme procedures explained in SICP is also possible, but it'll be more verbose and I'd argue, more difficult to understand.
My aim is to write a functional-programming style solution reusing as many built-in procedures as possible, and avoiding mutation at all costs - this is the style that SICP encourages you to learn. I'll deviate from the template solution in SICP if I think we can get a clearer solution by reusing existing Racket procedures (it follows then, that this code must be executed using the #lang racket language), but I've provided another answer that fits exactly exercise 2.42 in the book, implemented in standard Scheme and compatible with #lang sicp.
First things first. Let's agree on how are we going to represent the board - this is a key point, the way we represent our data will have a big influence on how easy (or hard) is to implement our solution. I'll use a simple representation, with only the minimum necessary information.
Let's say a "board" is a list of row indexes. My origin of coordinates is the position (0, 0), on the top-left corner of the board. For the purpose of this exercise we only need to keep track of the row a queen is in, the column is implicitly represented by its index in the list and there can only be one queen per column. Using my representation, the list '(2 0 3 1) encodes the following board, notice how the queens' position is uniquely represented by its row number and its index:
0 1 2 3
0 . Q . .
1 . . . Q
2 Q . . .
3 . . Q .
Next, let's see how are we going to check if a new queen added at the end of the board is "safe" with respect to the previously existing queens. For this, we need to check if there are any other queens in the same row, or if there are queens in the diagonal lines starting from the new queen's position. We don't need to check for queens in the same column, we're trying to set a single new queen and there aren't any others in this row. Let's split this task in multiple procedures.
; main procedure for checking if a queen in the given
; column is "safe" in the board; there are no more
; queens to the "right" or in the same column
(define (safe? col board)
; we're only interested in the queen's row for the given column
(let ([row (list-ref board (sub1 col))])
; the queen must be safe on the row and on the diagonals
(and (safe-row? row board)
(safe-diagonals? row board))))
; check if there are any other queens in the same row,
; do this by counting how many times `row` appears in `board`
(define (safe-row? row board)
; only the queen we want to add can be in this row
; `curry` is a shorthand for writing a lambda that
; compares `row` to each element in `board`
(= (count (curry equal? row) board) 1))
; check if there are any other queens in either the "upper"
; or the "lower" diagonals starting from the current queen's
; position and going to the "left" of it
(define (safe-diagonals? row board)
; we want to traverse the row list from right-to-left so we
; reverse it, and remove the current queen from it; upper and
; lower positions are calculated starting from the current queen
(let loop ([lst (rest (reverse board))]
[upper (sub1 row)]
[lower (add1 row)])
; the queen is safe after checking all the list
(or (null? lst)
; the queen is not safe if we find another queen in
; the same row, either on the upper or lower diagonal
(and (not (= (first lst) upper))
(not (= (first lst) lower))
; check the next position, updating upper and lower
(loop (rest lst) (sub1 upper) (add1 lower))))))
Some optimizations could be done, for example stopping early if there's more than one queen in the same row or stopping when the diagonals' rows fall outside of the board, but they'll make the code harder to understand and I'll leave them as an exercise for the reader.
In the book they suggest we use an adjoin-position procedure that receives both row and column parameters; with my representation we only need the row so I'm renaming it to add-queen, it simply adds a new queen at the end of a board:
; add a new queen's row to the end of the board
(define (add-queen queen-row board)
(append board (list queen-row)))
Now for the fun part. With all of the above procedures in place, we need to try out different combinations of queens and filter out those that are not safe. We'll use higher-order procedures and recursion for implementing this backtracking solution, there's no need to use set! at all as long as we're in the right mindset.
This will be easier to understand if you read if from the "inside out", try to grok what the inner parts do before going to the outer parts, and always remember that we're unwinding our way in a recursive process: the first case that will get executed is when we have an empty board, the next case is when we have a board with only one queen in position and so on, until we finally have a full board.
; main procedure: returns a list of all safe boards of the given
; size using our previously defined board representation
(define (queens board-size)
; we need two values to perform our computation:
; `queen-col`: current row of the queen we're attempting to set
; `board-size`: the full size of the board we're trying to fill
; I implemented this with a named let instead of the book's
; `queen-cols` nested procedure
(let loop ([queen-col board-size])
; if there are no more columns to try exit the recursion
(if (zero? queen-col)
; base case: return a list with an empty list as its only
; element; remember that the output is a list of lists
; the book's `empty-board` is just the empty list '()
(list '())
; we'll generate queen combinations below, but only the
; safe ones will survive for the next recursive call
(filter (λ (board) (safe? queen-col board))
; append-map will flatten the results as we go, we want
; a list of lists, not a list of lists of lists of...
; this is equivalent to the book's flatmap implementation
(append-map
(λ (previous-boards)
(map (λ (new-queen-row)
; add a new queen row to each one of
; the previous valid boards we found
(add-queen new-queen-row previous-boards))
; generate all possible queen row values for this
; board size, this is similar to the book's
; `enumerate-interval` but starting from zero
(range board-size)))
; advance the recursion, try a smaller column
; position, as the recursion unwinds this will
; return only previous valid boards
(loop (sub1 queen-col)))))))
And that's all there is to it! I'll provide a couple of printing procedures (useful for testing) which should be self-explanatory; they take my compact board representation and print it in a more readable way. Queens are represented by 'o and empty spaces by 'x:
(define (print-board board)
(for-each (λ (row) (printf "~a~n" row))
(map (λ (row)
(map (λ (col) (if (= row col) 'o 'x))
board))
(range (length board)))))
(define (print-all-boards boards)
(for-each (λ (board) (print-board board) (newline))
boards))
We can verify that things work and that the number of solutions for the 8-queens problem is as expected:
(length (queens 8))
=> 92
(print-all-boards (queens 4))
(x x o x)
(o x x x)
(x x x o)
(x o x x)
(x o x x)
(x x x o)
(o x x x)
(x x o x)
As a bonus, here's another solution that works with the exact definition of queens as provided in the SICP book. I won't go into details because it uses the same board representation (except that here the indexes start in 1 not in 0) and safe? implementation of my previous answer, and the explanation for the queens procedure is essentially the same. I did some minor changes to favor standard Scheme procedures, so hopefully it'll be more portable.
#lang racket
; redefine procedures already explained in the book with
; Racket equivalents, delete them and use your own
; implementation to be able to run this under #lang sicp
(define flatmap append-map)
(define (enumerate-interval start end)
(range start (+ end 1)))
; new definitions required for this exercise
(define empty-board '())
(define (adjoin-position row col board)
; `col` is unused
(append board (list row)))
; same `safe?` implementation as before
(define (safe? col board)
(let ((row (list-ref board (- col 1))))
(and (safe-row? row board)
(safe-diagonals? row board))))
(define (safe-row? row board)
; reimplemented to use standard Scheme procedures
(= (length (filter (lambda (r) (equal? r row)) board)) 1))
(define (safe-diagonals? row board)
(let loop ((lst (cdr (reverse board)))
(upper (- row 1))
(lower (+ row 1)))
(or (null? lst)
(and (not (= (car lst) upper))
(not (= (car lst) lower))
(loop (cdr lst) (- upper 1) (+ lower 1))))))
; exact same implementation of `queens` as in the book
(define (queens board-size)
(define (queen-cols k)
(if (= k 0)
(list empty-board)
(filter
(lambda (positions) (safe? k positions))
(flatmap
(lambda (rest-of-queens)
(map (lambda (new-row)
(adjoin-position new-row k rest-of-queens))
(enumerate-interval 1 board-size)))
(queen-cols (- k 1))))))
(queen-cols board-size))
; debugging
(define (print-board board)
(for-each (lambda (row) (display row) (newline))
(map (lambda (row)
(map (lambda (col) (if (= row col) 'o 'x))
board))
(enumerate-interval 1 (length board)))))
(define (print-all-boards boards)
(for-each (lambda (board) (print-board board) (newline))
boards))
The above code is more in spirit with the original exercise, which asked you to implement just three definitions: empty-board, adjoin-position and safe?, thus this was more of a question about data representation. Unsurprisingly, the results are the same:
(length (queens 8))
=> 92
(print-all-boards (queens 4))
(x x o x)
(o x x x)
(x x x o)
(x o x x)
(x o x x)
(x x x o)
(o x x x)
(x x o x)
I'm looking at the LispWorks Hyperspec on dotimes but I don't understand what the third variable [result-form] is doing. The examples are as follows:
(dotimes (temp-one 10 temp-one)) => 10
(setq temp-two 0) => 0
(dotimes (temp-one 10 t) (incf temp-two)) => T
temp-two => 10
The Hyperspec says
...Then result-form is evaluated. At the time result-form is
processed, var is bound to the number of times the body was executed.
Not sure what this is saying. Why is the third variable necessary in these two dotimes examples? I seem to be able to leave it out entirely in the second example and it works. My next example (not sure where I found it),
(defun thing (n)
(let ((s 0))
(dotimes (i n s)
(incf s i))))
Puzzles me as well. What use is s serving?
Since dotimes is a macro, looking at it's macro expansion can make things clearer:
Take your first example and expand it:
(pprint (MACROEXPAND-1 '(dotimes (temp-one 10 temp-one))))
I get the following output: (Yours may vary depending on the CL implementation)
(BLOCK NIL
(LET ((#:G8255 10) (TEMP-ONE 0))
(DECLARE (CCL::UNSETTABLE TEMP-ONE))
(IF (CCL::INT>0-P #:G8255)
(TAGBODY
#:G8254 (LOCALLY (DECLARE (CCL::SETTABLE TEMP-ONE))
(SETQ TEMP-ONE (1+ TEMP-ONE)))
(UNLESS (EQL TEMP-ONE #:G8255) (GO #:G8254))))
TEMP-ONE))
There's a lot going on, but the key thing to look at is that temp-one is bound to the value 0, and is returned as the expression's value (in standard lisp evaluation order).
Take the last example:
(pprint (macroexpand-1 '(dotimes (i n s) (incf s i))))
outputs:
(BLOCK NIL
(LET ((#:G8253 N) (I 0))
(DECLARE (CCL::UNSETTABLE I))
(IF (CCL::INT>0-P #:G8253)
(TAGBODY
#:G8252 (INCF S I)
(LOCALLY (DECLARE (CCL::SETTABLE I))
(SETQ I (1+ I)))
(UNLESS (EQL I #:G8253) (GO #:G8252))))
S))
As you can see S here is treated the same way as temp-one in the example before.
Try one without passing the last variable:
(pprint (macroexpand-1 '(dotimes (i n) (do-something i))))
and you get:
(BLOCK NIL
(LET ((#:G8257 N) (I 0))
(DECLARE (CCL::UNSETTABLE I))
(IF (CCL::INT>0-P #:G8257)
(TAGBODY
#:G8256 (DO-SOMETHING I)
(LOCALLY (DECLARE (CCL::SETTABLE I))
(SETQ I (1+ I)))
(UNLESS (EQL I #:G8257) (GO #:G8256))))
NIL))
Notice how NIL is the return value.
Is it possible to write a Common Lisp macro that takes a list of dimensions and variables, a body (of iteration), and creates the code consisting of as many nested loops as specified by the list?
That is, something like:
(nested-loops '(2 5 3) '(i j k) whatever_loop_body)
should be expanded to
(loop for i from 0 below 2 do
(loop for j from 0 below 5 do
(loop for k from 0 below 3 do
whatever_loop_body)))
Follow up
As huaiyuan correctly pointed out, I have to know the parameters to pass to macro at compile time. If you actually need a function as I do, look below.
If you are ok with a macro, go for the recursive solution of 6502, is wonderful.
You don't need the quotes, since the dimensions and variables need to be known at compile time anyway.
(defmacro nested-loops (dimensions variables &body body)
(loop for range in (reverse dimensions)
for index in (reverse variables)
for x = body then (list y)
for y = `(loop for ,index from 0 to ,range do ,#x)
finally (return y)))
Edit:
If the dimensions cannot be decided at compile time, we'll need a function
(defun nested-map (fn dimensions)
(labels ((gn (args dimensions)
(if dimensions
(loop for i from 0 to (car dimensions) do
(gn (cons i args) (cdr dimensions)))
(apply fn (reverse args)))))
(gn nil dimensions)))
and to wrap the body in lambda when calling.
CL-USER> (nested-map (lambda (&rest indexes) (print indexes)) '(2 3 4))
(0 0 0)
(0 0 1)
(0 0 2)
(0 0 3)
(0 0 4)
(0 1 0)
(0 1 1)
(0 1 2)
(0 1 3)
(0 1 4)
(0 2 0)
(0 2 1)
...
Edit(2012-04-16):
The above version of nested-map was written to more closely reflect the original problem statement. As mmj said in the comments, it's probably more natural to make index range from 0 to n-1, and moving the reversing out of the inner loop should improve efficiency if we don't insist on row-major order of iterations. Also, it's probably more sensible to have the input function accept a tuple instead of individual indices, to be rank independent. Here is a new version with the stated changes:
(defun nested-map (fn dimensions)
(labels ((gn (args dimensions)
(if dimensions
(loop for i below (car dimensions) do
(gn (cons i args) (cdr dimensions)))
(funcall fn args))))
(gn nil (reverse dimensions))))
Then,
CL-USER> (nested-map #'print '(2 3 4))
Sometimes an approach that is useful is writing a recursive macro, i.e. a macro that generates code containing another invocation of the same macro unless the case is simple enough to be solved directly:
(defmacro nested-loops (max-values vars &rest body)
(if vars
`(loop for ,(first vars) from 0 to ,(first max-values) do
(nested-loops ,(rest max-values) ,(rest vars) ,#body))
`(progn ,#body)))
(nested-loops (2 3 4) (i j k)
(print (list i j k)))
In the above if the variable list is empty then the macro expands directly to the body forms, otherwise the generated code is a (loop...) on the first variable containing another (nested-loops ...) invocation in the do part.
The macro is not recursive in the normal sense used for functions (it's not calling itself directly) but the macroexpansion logic will call the same macro for the inner parts until the code generation has been completed.
Note that the max value forms used in the inner loops will be re-evaluated at each iteration of the outer loop. It doesn't make any difference if the forms are indeed numbers like in your test case, but it's different if they're for example function calls.
Hm. Here's an example of such a macro in common lisp. Note, though, that I am not sure, that this is actually a good idea. But we are all adults here, aren't we?
(defmacro nested-loop (control &body body)
(let ((variables ())
(lower-bounds ())
(upper-bounds ()))
(loop
:for ctl :in (reverse control)
:do (destructuring-bind (variable bound1 &optional (bound2 nil got-bound2)) ctl
(push variable variables)
(push (if got-bound2 bound1 0) lower-bounds)
(push (if got-bound2 bound2 bound1) upper-bounds)))
(labels ((recurr (vars lowers uppers)
(if (null vars)
`(progn ,#body)
`(loop
:for ,(car vars) :upfrom ,(car lowers) :to ,(car uppers)
:do ,(recurr (cdr vars) (cdr lowers) (cdr uppers))))))
(recurr variables lower-bounds upper-bounds))))
The syntax is slightly different from your proposal.
(nested-loop ((i 0 10) (j 15) (k 15 20))
(format t "~D ~D ~D~%" i j k))
expands into
(loop :for i :upfrom 0 :to 10
:do (loop :for j :upfrom 0 :to 15
:do (loop :for k :upfrom 15 :to 20
:do (progn (format t "~d ~d ~d~%" i j k)))))
The first argument to the macro is a list of list of the form
(variable upper-bound)
(with a lower bound of 0 implied) or
(variable lower-bound upper-bounds)
With a little more love applied, one could even have something like
(nested-loop ((i :upfrom 10 :below 20) (j :downfrom 100 :to 1)) ...)
but then, why bother, if loop has all these features already?
I'm a CommonLisp noob with a question. I have these two functions below.
A helper function:
(defun make-rests (positions rhythm)
"now make those positions negative numbers for rests"
(let ((resultant-rhythm rhythm))
(dolist (i positions resultant-rhythm)
(setf (nth i resultant-rhythm) (* (nth i resultant-rhythm) -1)))))
And a main function:
(defun test-return-rhythms (rhythms)
(let ((positions '((0 1) (0)))
(result nil))
(dolist (x positions (reverse result))
(push (make-rests x rhythms) result))))
When I run (test-return-rhythms '(1/4 1/8)), it evaluates to: ((1/4 -1/8) (1/4 -1/8))
However, I expected: (test-return-rhythms '(1/4 1/8)) to evaluate to: ((-1/4 -1/8) (-1/4 1/8)).
What am I doing wrong?
Your implementation of make-rests is destructive.
CL-USER> (defparameter *rhythm* '(1/4 1/4 1/4 1/4))
*RHYTHM*
CL-USER> (make-rests '(0 2) *rhythm*)
(-1/4 1/4 -1/4 1/4)
CL-USER> *rhythm*
(-1/4 1/4 -1/4 1/4)
So, if you run your test, the second iteration will see (-1/4 -1/8), and (make-rests '(0) '(-1/4 -1/8)) returns (1/4 -1/8). Your use of let in make-rests does not copy the list, it just creates a new binding that references it. Use copy-list in your let, or write a non-destructive version in the first place:
(defun make-rests (positions rhythm)
(loop for note in rhythm
for i from 0
collect (if (member i positions) (* note -1) note)))