Related
I need a function that does this:
>>> func (+1) [1,2,3]
[[2,2,3],[2,3,3],[2,3,4]]
My real case is more complex, but this example shows the gist of the problem. The main difference is that in reality using indexes would be infeasible. The List should be a Traversable or Foldable.
EDIT: This should be the signature of the function:
func :: Traversable t => (a -> a) -> t a -> [t a]
And closer to what I really want is the same signature to traverse but can't figure out the function I have to use, to get the desired result.
func :: (Traversable t, Applicative f) :: (a -> f a) -> t a -> f (t a)
It looks like #Benjamin Hodgson misread your question and thought you wanted f applied to a single element in each partial result. Because of this, you've ended up thinking his approach doesn't apply to your problem, but I think it does. Consider the following variation:
import Control.Monad.State
indexed :: (Traversable t) => t a -> (t (Int, a), Int)
indexed t = runState (traverse addIndex t) 0
where addIndex x = state (\k -> ((k, x), k+1))
scanMap :: (Traversable t) => (a -> a) -> t a -> [t a]
scanMap f t =
let (ti, n) = indexed (fmap (\x -> (x, f x)) t)
partial i = fmap (\(k, (x, y)) -> if k < i then y else x) ti
in map partial [1..n]
Here, indexed operates in the state monad to add an incrementing index to elements of a traversable object (and gets the length "for free", whatever that means):
> indexed ['a','b','c']
([(0,'a'),(1,'b'),(2,'c')],3)
and, again, as Ben pointed out, it could also be written using mapAccumL:
indexed = swap . mapAccumL (\k x -> (k+1, (k, x))) 0
Then, scanMap takes the traversable object, fmaps it to a similar structure of before/after pairs, uses indexed to index it, and applies a sequence of partial functions, where partial i selects "afters" for the first i elements and "befores" for the rest.
> scanMap (*2) [1,2,3]
[[2,2,3],[2,4,3],[2,4,6]]
As for generalizing this from lists to something else, I can't figure out exactly what you're trying to do with your second signature:
func :: (Traversable t, Applicative f) => (a -> f a) -> t a -> f (t a)
because if you specialize this to a list you get:
func' :: (Traversable t) => (a -> [a]) -> t a -> [t a]
and it's not at all clear what you'd want this to do here.
On lists, I'd use the following. Feel free to discard the first element, if not wanted.
> let mymap f [] = [[]] ; mymap f ys#(x:xs) = ys : map (f x:) (mymap f xs)
> mymap (+1) [1,2,3]
[[1,2,3],[2,2,3],[2,3,3],[2,3,4]]
This can also work on Foldable, of course, after one uses toList to convert the foldable to a list. One might still want a better implementation that would avoid that step, though, especially if we want to preserve the original foldable type, and not just obtain a list.
I just called it func, per your question, because I couldn't think of a better name.
import Control.Monad.State
func f t = [evalState (traverse update t) n | n <- [0..length t - 1]]
where update x = do
n <- get
let y = if n == 0 then f x else x
put (n-1)
return y
The idea is that update counts down from n, and when it reaches 0 we apply f. We keep n in the state monad so that traverse can plumb n through as you walk across the traversable.
ghci> func (+1) [1,1,1]
[[2,1,1],[1,2,1],[1,1,2]]
You could probably save a few keystrokes using mapAccumL, a HOF which captures the pattern of traversing in the state monad.
This sounds a little like a zipper without a focus; maybe something like this:
data Zippy a b = Zippy { accum :: [b] -> [b], rest :: [a] }
mapZippy :: (a -> b) -> [a] -> [Zippy a b]
mapZippy f = go id where
go a [] = []
go a (x:xs) = Zippy b xs : go b xs where
b = a . (f x :)
instance (Show a, Show b) => Show (Zippy a b) where
show (Zippy xs ys) = show (xs [], ys)
mapZippy succ [1,2,3]
-- [([2],[2,3]),([2,3],[3]),([2,3,4],[])]
(using difference lists here for efficiency's sake)
To convert to a fold looks a little like a paramorphism:
para :: (a -> [a] -> b -> b) -> b -> [a] -> b
para f b [] = b
para f b (x:xs) = f x xs (para f b xs)
mapZippy :: (a -> b) -> [a] -> [Zippy a b]
mapZippy f xs = para g (const []) xs id where
g e zs r d = Zippy nd zs : r nd where
nd = d . (f e:)
For arbitrary traversals, there's a cool time-travelling state transformer called Tardis that lets you pass state forwards and backwards:
mapZippy :: Traversable t => (a -> b) -> t a -> t (Zippy a b)
mapZippy f = flip evalTardis ([],id) . traverse g where
g x = do
modifyBackwards (x:)
modifyForwards (. (f x:))
Zippy <$> getPast <*> getFuture
In Haskell, I recently found the following function useful:
listCase :: (a -> [a] -> b) -> [a] -> [b]
listCase f [] = []
listCase f (x:xs) = f x xs : listCase f xs
I used it to generate sliding windows of size 3 from a list, like this:
*Main> listCase (\_ -> take 3) [1..5]
[[2,3,4],[3,4,5],[4,5],[5],[]]
Is there a more general recursion scheme which captures this pattern? More specifically, that allows you to generate a some structure of results by repeatedly breaking data into a "head" and "tail"?
What you are asking for is a comonad. This may sound scarier than monad, but is a simpler concept (YMMV).
Comonads are Functors with additional structure:
class Functor w => Comonad w where
extract :: w a -> a
duplicate :: w a -> w (w a)
extend :: (w a -> b) -> w a -> w b
(extendand duplicate can be defined in terms of each other)
and laws similar to the monad laws:
duplicate . extract = id
duplicate . fmap extract = id
duplicate . duplicate = fmap duplicate . duplicate
Specifically, the signature (a -> [a] -> b) takes non-empty Lists of type a. The usual type [a] is not an instance of a comonad, but the non-empty lists are:
data NE a = T a | a :. NE a deriving Functor
instance Comonad NE where
extract (T x) = x
extract (x :. _) = x
duplicate z#(T _) = T z
duplicate z#(_ :. xs) = z :. duplicate xs
The comonad laws allow only this instance for non-empty lists (actually a second one).
Your function then becomes
extend (take 3 . drop 1 . toList)
Where toList :: NE a -> [a] is obvious.
This is worse than the original, but extend can be written as =>> which is simpler if applied repeatedly.
For further information, you may start at What is the Comonad typeclass in Haskell?.
This looks like a special case of a (jargon here but it can help with googling) paramorphism, a generalisation of primitive recursion to all initial algebras.
Reimplementing ListCase
Let's have a look at how to reimplement your function using such a combinator. First we define the notion of paramorphism: a recursion principle where not only the result of the recursive call is available but also the entire substructure this call was performed on:
The type of paraList tells me that in the (:) case, I will have access to the head, the tail and the value of the recursive call on the tail and that I need to provide a value for the base case.
module ListCase where
paraList :: (a -> [a] -> b -> b) -- cons
-> b -- nil
-> [a] -> b -- resulting function on lists
paraList c n [] = n
paraList c n (x : xs) = c x xs $ paraList c n xs
We can now give an alternative definition of listCase:
listCase' :: (a -> [a] -> b) -> [a] -> [b]
listCase' c = paraList (\ x xs tl -> c x xs : tl) []
Considering the general case
In the general case, we are interested in building a definition of paramorphism for all data structures defined as the fixpoint of a (strictly positive) functor. We use the traditional fixpoint operator:
newtype Fix f = Fix { unFix :: f (Fix f) }
This builds an inductive structure layer by layer. The layers have an f shape which maybe better grasped by recalling the definition of List using this formalism. A layer is either Nothing (we're done!) or Just (head, tail):
newtype ListF a as = ListF { unListF :: Maybe (a, as) }
type List a = Fix (ListF a)
nil :: List a
nil = Fix $ ListF $ Nothing
cons :: a -> List a -> List a
cons = curry $ Fix . ListF .Just
Now that we have this general framework, we can define para generically for all Fix f where f is a functor:
para :: Functor f => (f (Fix f, b) -> b) -> Fix f -> b
para alg = alg . fmap (\ rec -> (rec, para alg rec)) . unFix
Of course, ListF a is a functor. Meaning we could use para to reimplement paraList and listCase.
instance Functor (ListF a) where fmap f = ListF . fmap (fmap f) . unListF
paraList' :: (a -> List a -> b -> b) -> b -> List a -> b
paraList' c n = para $ maybe n (\ (a, (as, b)) -> c a as b) . unListF
listCase'' :: (a -> List a -> b) -> List a -> List b
listCase'' c = paraList' (\ x xs tl -> cons (c x xs) tl) nil
You can implement a simple bijection toList, fromList to test it if you want. I could not be bothered to reimplement take so it's pretty ugly:
toList :: [a] -> List a
toList = foldr cons nil
fromList :: List a -> [a]
fromList = paraList' (\ x _ tl -> x : tl) []
*ListCase> fmap fromList . fromList . listCase'' (\ _ as -> toList $ take 3 $ fromList as). toList $ [1..5]
[[2,3,4],[3,4,5],[4,5],[5],[]]
Completely new to Haskell and learning through Learn Haskell the greater good.
I am looking at the map function
map :: (a -> b) -> [a] -> [b]
map _ [] = []
map f (x:xs) = f x : map f xs
is it possible to add a predicate to this? for example, to only map to every other element in the list?
You can code your own version of map to apply f only to even (or odd) positions as follows. (Below indices start from 0)
mapEven :: (a->a) -> [a] -> [a]
mapEven f [] = []
mapEven f (x:xs) = f x : mapOdd f xs
mapOdd :: (a->a) -> [a] -> [a]
mapOdd f [] = []
mapOdd f (x:xs) = x : mapEven f xs
If instead you want to exploit the library functions, you can do something like
mapEven :: (a->a) -> [a] -> [a]
mapEven f = map (\(flag,x) -> if flag then f x else x) . zip (cycle [True,False])
or even
mapEven :: (a->a) -> [a] -> [a]
mapEven f = map (uncurry (\flag -> if flag then f else id)) . zip (cycle [True,False])
If you want to filter using an arbitrary predicate on the index, then:
mapPred :: (Int -> Bool) -> (a->a) -> [a] -> [a]
mapPred p f = map (\(i,x) -> if p i then f x else x) . zip [0..]
A more direct solution can be reached using zipWith (as #amalloy suggests).
mapEven :: (a->a) -> [a] -> [a]
mapEven f = zipWith (\flag x -> if flag then f x else x) (cycle [True,False])
This can be further refined as follows
mapEven :: (a->a) -> [a] -> [a]
mapEven f = zipWith ($) (cycle [f,id])
The "canonical" way to perform filtering based on positions is to zip the sequence with the naturals, so as to append an index to each element:
> zip [1, 1, 2, 3, 5, 8, 13] [0..]
[(1,0),(1,1),(2,2),(3,3),(5,4),(8,5),(13,6)]
This way you can filter the whole thing using the second part of the tuples, and then map a function which discards the indices:
indexedFilterMap p f xs = (map (\(x,_) -> f x)) . (filter (\(_,y) -> p y)) $ (zip xs [0..])
oddFibsPlusOne = indexedFilterMap odd (+1) [1, 1, 2, 3, 5, 8, 13]
To be specific to you question, one might simply put
mapEveryOther f = indexedFilterMap odd f
You can map with a function (a lambda is also possible):
plusIfOdd :: Int -> Int
plusIfOdd a
| odd a = a
| otherwise = a + 100
map plusIfOdd [1..5]
As a first step, write the function for what you want to do to the individual element of the list:
applytoOdd :: Integral a => (a -> a) -> a -> a
applytoOdd f x = if odd x
then (f x)
else x
So applytoOdd function will apply the function f to the element if the element is odd or else return the same element if it is even. Now you can apply map to that like this:
λ> let a = [1,2,3,4,5]
λ> map (applytoOdd (+ 100)) a
[101,2,103,4,105]
Or if you want to add 200 to it, then:
λ> map (applytoOdd (+ 200)) a
[201,2,203,4,205]
Looking on the comments, it seems you want to map based on the index position. You can modify your applytoOdd method appropriately for that:
applytoOdd :: Integral a => (b -> b) -> (a, b) -> b
applytoOdd f (x,y) = if odd x
then (f y)
else y
Here, the type variable a corresponds to the index element. If it's odd you are applying the function to the actual element of the list. And then in ghci:
λ> map (applytoOdd (+ 100)) (zip [1..5] [1..])
[101,2,103,4,105]
λ> map (applytoOdd (+ 200)) (zip [1..5] [1..])
[201,2,203,4,205]
Or use a list comprehension:
mapOdd f x = if odd x then f x else x
[ mapOdd (+100) x | x <- [1,2,3,4,5]]
I'm glad that you're taking the time to learn about Haskell. It's an amazing language. However it does require you to develop a certain mindset. So here's what I do when I face a problem in Haskell. Let's start with your problem statement:
Is it possible to add a predicate to the map function? For example, to only map to every other element in the list?
So you have two questions:
Is it possible to add a predicate to the map function?
How to map to every other element in the list?
So the way people think in Haskell is via type signatures. For example, when an engineer is designing a building she visualizes how the building should look for the top (top view), the front (front view) and the side (side view). Similarly when functional programmers write code they visualize their code in terms of type signatures.
Let's start with what we know (i.e. the type signature of the map function):
map :: (a -> b) -> [a] -> [b]
Now you want to add a predicate to the map function. A predicate is a function of the type a -> Bool. Hence a map function with a predicate will be of the type:
mapP :: (a -> Bool) -> (a -> b) -> [a] -> [b]
However, in your case, you also want to keep the unmapped values. For example mapP odd (+100) [1,2,3,4,5] should result in [101,2,103,4,105] and not [101,103,105]. Hence it follows that the type of the input list should match the type of the output list (i.e. a and b must be of the same type). Hence mapP should be of the type:
mapP :: (a -> Bool) -> (a -> a) -> [a] -> [a]
It's easy to implement a function like this:
map :: (a -> Bool) -> (a -> a) -> [a] -> [a]
mapP p f = map (\x -> if p x then f x else x)
Now to answer your second question (i.e. how to map to every other element in the list). You could use zip and unzip as follows:
snd . unzip . mapP (odd . fst) (fmap (+100)) $ zip [1..] [1,2,3,4,5]
Here's what's happening:
We first zip the index of each element with the element itself. Hence zip [1..] [1,2,3,4,5] results in [(1,1),(2,2),(3,3),(4,4),(5,5)] where the fst value of each pair is the index.
For every odd index element we apply the (+100) function to the element. Hence the resulting list is [(1,101),(2,2),(3,103),(4,4),(5,105)].
We unzip the list resulting in two separate lists ([1,2,3,4,5],[101,2,103,4,105]).
We discard the list of indices and keep the list of mapped results using snd.
We can make this function more general. The type signature of the resulting function would be:
mapI :: ((Int, a) -> Bool) -> (a -> a) -> [a] -> [a]
The definition of the mapI function is simple enough:
mapI :: ((Int, a) -> Bool) -> (a -> a) -> [a] -> [a]
mapI p f = snd . unzip . mapP p (fmap f) . zip [1..]
You can use it as follows:
mapI (odd . fst) (+100) [1,2,3,4,5]
Hope that helps.
Is it possible to add a predicate to this? for example, to only map to every other element in the list?
Yes, but functions should ideally do one relatively simple thing only. If you need to do something more complicated, ideally you should try doing it by composing two or more functions.
I'm not 100% sure I understand your question, so I'll show a few examples. First: if what you mean is that you only want to map in cases where a supplied predicate returns true of the input element, but otherwise just leave it alone, then you can do that by reusing the map function:
mapIfTrue :: (a -> Bool) -> (a -> a) -> [a] -> [a]
mapIfTrue pred f xs = map step xs
where step x | pred x = f x
| otherwise = x
If what you mean is that you want to discard list elements that don't satisfy the predicate, and apply the function to the remaining ones, then you can do that by combining map and filter:
filterMap :: (a -> Bool) -> (a -> b) -> [a] -> [b]
filterMap pred f xs = map f (filter pred xs)
Mapping the function over every other element of the list is different from these two, because it's not a predicate over the elements of the list; it's either a structural transformation of the list of a stateful traversal of it.
Also, I'm not clear whether you mean to discard or keep the elements you're not applying the function to, which would imply different answers. If you're discarding them, then you can do it by just discarding alternate list elements and then mapping the function over the remaining ones:
keepEven :: [a] -> [a]
keepEven xs = step True xs
where step _ [] = []
step True (x:xs) = x : step False xs
step False (_:xs) = step True xs
mapEven :: (a -> b) -> [a] -> [b]
mapEven f xs = map f (keepEven xs)
If you're keeping them, one way you could do it is by tagging each list element with its position, filtering the list to keep only the ones in even positions, discard the tags and then map the function:
-- Note: I'm calling the first element of a list index 0, and thus even.
mapEven :: (a -> a) -> [a] -> [a]
mapEven f xs = map aux (filter evenIndex (zip [0..] xs))
where evenIndex (i, _) = even i
aux (_, x) = f x
As another answer mentioned, zip :: [a] -> [b] -> [(a, b)] combines two lists pairwise by position.
But this is the general philosophy: to do a complex thing, use a combination of general-purpose generic functions. If you're familiar with Unix, it's similar to that.
Another simple way to write the last one. It's longer, but keep in mind that evens, odds and interleave all are generic and reusable:
evens, odds :: [a] -> [a]
evens = alternate True
odds = alternate False
alternate :: Bool -> [a] -> [a]
alternate _ [] = []
alternate True (x:xs) = x : alternate False xs
alternate False (_:xs) = alternate True xs
interleave :: [a] -> [a] -> [a]
interleave [] ys = ys
interleave (x:xs) ys = x : interleave ys xs
mapEven :: (a -> a) -> [a] -> [a]
mapEven f xs = interleave (map f (evens xs)) (odds xs)
You can't use a predicate because predicates operate on list values, not their indices.
I quite like this format for what you're trying to do, since it makes the case handling quite clear for the function:
newMap :: (t -> t) -> [t] -> [t]
newMap f [] = [] -- no items in list
newMap f [x] = [f x] -- one item in list
newMap f (x:y:xs) = (f x) : y : newMap f xs -- 2 or more items in list
For example, running:
newMap (\x -> x + 1) [1,2,3,4]
Yields:
[2,2,4,4]
I admit this is my homework. But I really couldn't find a good solution after working hard on it.
There might be some stupid ways to accomplish this, like:
myHead (x:[]) = x
myHead (x:y:xs) = fst (x, y)
But I don't think that's what the teacher wants.
BTW, error-handling is not required.
Thanks in advance!
There's a very natural function that's not in the prelude called "uncons" which is the inverse of uncurried cons.
cons :: a -> [a] -> [a]
uncurry cons :: (a, [a]) -> [a]
uncons :: [a] -> (a, [a])
uncons (x:xs) = (x, xs)
You can use it to implement head as
head = fst . uncons
Why is uncons natural?
You can think of a list as the datatype that's defined through the use of two constructor functions
nil :: [a]
nil = []
cons :: (a, [a]) -> [a]
cons (a,as) = a:as
You can also think of it as the data type which is deconstructed by a function
destruct :: [a] -> Maybe (a, [a])
destruct [] = Nothing
destruct (a:as) = Just (a, as)
It's well beyond this answer to explain why those are so definitively tied to the list type, but one way to look at it is to try to define
nil :: f a
cons :: (a, f a) -> f a
or
destruct :: f a -> Maybe (a, f a)
for any other container type f. You'll find that they all have very close relationships with lists.
You can almost already see uncons in the second case of the definition of destruct, but there's a Just in the way. This is uncons is better paired with head and tail which are not defined on empty lists
head [] = error "Prelude.head"
so we can adjust the previous answer to work for infinite streams. Here we can think of infinite streams as being constructed by one function
data Stream a = Next a (Stream a)
cons :: (a, Stream a) -> Stream a
cons (a, as) = Next a as
and destructed by one function
uncons :: Stream a -> (a, Stream a)
uncons (Next a as) = (a, as)
-- a. k. a.
uncons stream = (head stream, tail stream)
the two being inverses of one another.
Now we can get head for Streams by getting the first element of the return tuple from uncons
head = fst . uncons
And that's what head models in the Prelude, so we can pretend like lists are infinite streams and define head in that way
uncons :: [a] -> (a, [a])
uncons (a:as) = (a, as)
-- a. k. a.
uncons list = (head list, tail list)
head = fst . uncons
Perhaps you're expected write to your own cons List type, then it might make more sense. Although type synonyms can't be recursive, so you end up using a non-tuple data constructor, making the tuple superfluous.. it would look like:
data List a = Nil | List (a, List a)
deriving( Show )
head :: List a -> a
head (List c) = fst c
Like already said in the comments, this is just a silly task and you won't get something you could call a good implementation of head.
Your solution, for those requirements, is just fine – as the only change I would replace (x:y:xs) with (x:y:_) since xs isn't used at all (which would actually cause a compiler warning in some settings). In fact, you could do that with y as well:
myHead (x:_:_) = fst (x, undefined)
There would be alternatives that look perhaps not quite so useless use of fst, i.e. don't just build a tuple by hand and immediately deconstruct it again:
myHead' [x] = x
myHead' xs = myHead' . fst $ splitAt 1 xs
myHead'' = foldr1 $ curry fst
myHead''' = fromJust . find ((==0) . fst) . zip [0..]
but you could rightfully say that these are just ridiculous.
I wanted to make a generic function that folds over a wide range of inputs (see Making a single function work on lists, ByteStrings and Texts (and perhaps other similar representations)). As one answer suggested, the ListLike is just for that. Its FoldableLL class defines an abstraction for anything that is foldable. However, I need a monadic fold. So I need to define foldM in terms of foldl/foldr.
So far, my attempts failed. I tried to define
foldM'' :: (Monad m, LL.FoldableLL full a) => (b -> a -> m b) -> b -> full -> m b
foldM'' f z = LL.foldl (\acc x -> acc >>= (`f` x)) (return z)
but it runs out of memory on large inputs - it builds a large unevaluated tree of computations. For example, if I pass a large text file to
main :: IO ()
main = getContents >>= foldM'' idx 0 >> return ()
where
-- print the current index if 'a' is found
idx !i 'a' = print i >> return (i + 1)
idx !i _ = return (i + 1)
it eats up all memory and fails.
I have a feeling that the problem is that the monadic computations are composed in a wrong order - like ((... >>= ...) >>= ...) instead of (... >>= (... >>= ...)) but so far I didn't find out how to fix it.
Workaround: Since ListLike exposes mapM_, I constructed foldM on ListLikes by wrapping the accumulator into the state monad:
modifyT :: (Monad m) => (s -> m s) -> StateT s m ()
modifyT f = get >>= \x -> lift (f x) >>= put
foldLLM :: (LL.ListLike full a, Monad m) => (b -> a -> m b) -> b -> full -> m b
foldLLM f z c = execStateT (LL.mapM_ (\x -> modifyT (\b -> f b x)) c) z
While this works fine on large data sets, it's not very nice. And it doesn't answer the original question, if it's possible to define it on data that are just FoldableLL (without mapM_).
So the goal is to reimplement foldM using either foldr or foldl. Which one should it be? We want the input to be processed lazily and allow for infinte lists, this rules out foldl. So foldr is it going to be.
So here is the definition of foldM from the standard library.
foldM :: (Monad m) => (a -> b -> m a) -> a -> [b] -> m a
foldM _ a [] = return a
foldM f a (x:xs) = f a x >>= \fax -> foldM f fax xs
The thing to remember about foldr is that its arguments simply replace [] and : in the list (ListLike abstracts over that, but it still serves as a guiding principle).
So what should [] be replaced with? Clearly with return a. But where does a come from? It won’t be the initial a that is passed to foldM – if the list is not empty, when foldr reaches the end of the list, the accumulator should have changed. So we replace [] by a function that takes an accumulator and returns it in the underlying monad: \a -> return a (or simply return). This also gives the type of the thing that foldr will calculate: a -> m a.
And what should we replace : with? It needs to be a function b -> (a -> m a) -> (a -> m a), taking the first element of the list, the processed tail (lazily, of course) and the current accumulator. We can figure it out by taking hints from the code above: It is going to be \x rest a -> f a x >>= rest. So our implementation of foldM will be (adjusting the type variables to match them in the code above):
foldM'' :: (Monad m) => (a -> b -> m a) -> a -> [b] -> m a
foldM'' f z list = foldr (\x rest a -> f a x >>= rest) return list z
And indeed, now your program can consume arbitrary large input, spitting out the results as you go.
We can even prove, inductively, that the definitions are semantically equal (although we should probably do coinduction or take-induction to cater for infinite lists).
We want to show
foldM f a xs = foldM'' f a xs
for all xs :: [b]. For xs = [] we have
foldM f a []
≡ return a -- definition of foldM
≡ foldr (\x rest a -> f a x >>= rest) return [] a -- definition of foldr
≡ foldM'' f a [] -- definition of foldM''
and, assuming we have it for xs, we show it for x:xs:
foldM f a (x:xs)
≡ f a x >>= \fax -> foldM f fax xs --definition of foldM
≡ f a x >>= \fax -> foldM'' f fax xs -- induction hypothesis
≡ f a x >>= \fax -> foldr (\x rest a -> f a x >>= rest) return xs fax -- definition of foldM''
≡ f a x >>= foldr (\x rest a -> f a x >>= rest) return xs -- eta expansion
≡ foldr (\x rest a -> f a x >>= rest) return (x:xs) -- definition of foldr
≡ foldM'' f a (x:xs) -- definition of foldM''
Of course this equational reasoning does not tell you anything about the performance properties you were interested in.