I have a function:
someFun :: Applicative f => f a -> b -> f c
someFun x y = …
The argument for y that I need to give someFun is an “f b”
Lets say I have values
someX :: Applicative f => f a
someY :: Applicative f => f b
I tried to do
LiftA (someFun someX) someY
But that gives me f (f c)
I need to result in an f c
What you are asking for is the thing that Monads can do but Applicatives cannot. With a Monad instance, this is just join:
join :: Monad m => m (m a) -> m a
What you ask for is impossible, but at least now you have a perfect example of what you can do with a Monad that you can't do with an Applicative.
Related
In Haskell Applicatives are considered stronger than Functor that means we can define Functor using Applicative like
-- Functor
fmap :: (a -> b) -> f a -> f b
fmap f fa = pure f <*> fa
and Monads are considered stronger than Applicatives & Functors that means.
-- Functor
fmap :: (a -> b) -> f a -> f b
fmap f fa = fa >>= return . f
-- Applicative
pure :: a -> f a
pure = return
(<*>) :: f (a -> b) -> f a -> f b
(<*>) = ??? -- Can we define this in terms return & bind? without using "ap"
I have read that Monads are for sequencing actions. But I feel like the only thing a Monad can do is Join or Flatten and the rest of its capabilities comes from Applicatives.
join :: m (m a) -> m a
-- & where is the sequencing in this part? I don't get it.
If Monad is really for sequencing actions then How come we can define Applicatives (which are not considered to strictly operate in sequence, some kind of parallel computing)?
As monads are Monoids in the Category of endofunctors. There are Commutative monoids as well, which necessarily need not work in order. That means the Monad instances for Commutative Monoids also need an ordering?
Edit:
I found an excellent page
http://wiki.haskell.org/What_a_Monad_is_not
If Monad is really for sequencing actions then How come we can define Applicatives (which are not considered to strictly operate in sequence, some kind of parallel computing)?
Not quite. All monads are applicatives, but only some applicatives are monads. So given a monad you can always define an applicative instance in terms of bind and return, but if all you have is the applicative instance then you cannot define a monad without more information.
The applicative instance for a monad would look like this:
instance (Monad m) => Applicative m where
pure = return
f <*> v = do
f' <- f
v' <- v
return $ f' v'
Of course this evaluates f and v in sequence, because its a monad and that is what monads do. If this applicative does not do things in a sequence then it isn't a monad.
Modern Haskell, of course, defines this the other way around: the Applicative typeclass is a subset of Functor so if you have a Functor and you can define (<*>) then you can create an Applicative instance. Monad is in turn defined as a subset of Applicative, so if you have an Applicative instance and you can define (>>=) then you can create a Monad instance. But you can't define (>>=) in terms of (<*>).
See the Typeclassopedia for more details.
We can copy the definition of ap and desugar it:
ap f a = do
xf <- f
xa <- a
return (xf xa)
Hence,
f <*> a = f >>= (\xf -> a >>= (\xa -> return (xf xa)))
(A few redundant parentheses added for clarity.)
(<*>) :: f (a -> b) -> f a -> f b
(<*>) = ??? -- Can we define this in terms return & bind? without using "ap"
Recall that <*> has the type signature of f (a -> b) -> f a -> f b, and >>= has m a -> (a -> m b) -> m b. So how can we infer m (a -> b) -> m a -> m b from m a -> (a -> m b) -> m b?
To define f <*> x with >>=, the first parameter of >>= should be f obviously, so we can write the first transformation:
f <*> x = f >>= k -- k to be defined
where the function k takes as a parameter a function with the type of a -> b, and returns a result of m b such that the whole definition aligns with the type signature of bind >>=. For k, we can write:
k :: (a -> b) -> m b
k = \xf -> h x
Note that the function h should use x from f <*> x since x is related to the result of m b in some way like the function xf of a -> b.
For h x, it's easy to get:
h :: m a -> m b
h x = x >>= return . xf
Put the above three definations together, and we get:
f <*> x = f >>= \xf -> x >>= return . xf
So even though you don't know the defination of ap, you can still get the final result as shown by #chi according to the type signature.
I have this F-Algebra (introduced in a previous question), and I want to cast an effectful algebra upon it. Through desperate trial, I managed to put together a monadic catamorphism that works. I wonder if it may be generalized to an applicative, and if not, why.
This is how I defined Traversable:
instance Traversable Expr where
traverse f (Branch xs) = fmap Branch $ traverse f xs
traverse f (Leaf i ) = pure $ Leaf i
This is the monadic catamorphism:
type AlgebraM a f b = a b -> f b
cataM :: (Monad f, Traversable a) => AlgebraM a f b -> Fix a -> f b
cataM f x = f =<< (traverse (cataM f) . unFix $ x)
And this is how it works:
λ let printAndReturn x = print x >> pure x
λ cataM (printAndReturn . evalSum) $ branch [branch [leaf 1, leaf 2], leaf 3]
1
2
3
3
6
6
My idea now is that I could rewrite like this:
cataA :: (Applicative f, Traversable a) => AlgebraM a f b -> Fix a -> f b
cataA f x = do
subtree <- traverse (cataA f) . unFix $ x
value <- f subtree
return value
Unfortunately, value here depends on subtree and, according to a paper on applicative do-notation, in such case we cannot desugar to Applicative. It seems like there's no way around this; we need a monad to float up from the depths of nesting.
Is it true? Can I safely conclude that only flat structures can be folded with applicative effects alone?
Can I safely conclude that only flat structures can be folded with applicative effects alone?
You can say that again! After all, "flattening nested structures" is exactly what makes a monad a monad, rather than Applicative which can only combine adjacent structures. Compare (a version of) the signatures of the two abstractions:
class Functor f => Applicative f where
pure :: a -> f a
(<.>) :: f a -> f b -> f (a, b)
class Applicative m => Monad m where
join :: m (m a) -> m a
What Monad adds to Applicative is the ability to flatten nested ms into one m. That's why []'s join is concat. Applicative only lets you smash together heretofore-unrelated fs.
It's no coincidence that the free monad's Free constructor contains a whole f full of Free fs, whereas the free applicative's Ap constructor only contains one Ap f.
data Free f a = Return a | Free (f (Free f a))
data Ap f a where
Pure :: a -> Ap f a
Cons :: f a -> Ap f b -> Ap f (a, b)
Hopefully that gives you some intuition as to why you should expect that it's not possible to fold a tree using an Applicative.
Let's play a little type tennis to see how it shakes out. We want to write
cataA :: (Traversable f, Applicative m) => (f a -> m a) -> Fix f -> m a
cataA f (Fix xs) = _
We have xs :: f (Fix f) and a Traversable for f. My first instinct here is to traverse the f to fold the contained subtrees:
cataA f (Fix xs) = _ $ traverse (cataA f) xs
The hole now has a goal type of m (f a) -> m a. Since there's an f :: f a -> m a knocking about, let's try going under the m to convert the contained fs:
cataA f (Fix xs) = _ $ fmap f $ traverse (cataA f) xs
Now we have a goal type of m (m a) -> m a, which is join. So you do need a Monad after all.
Here is how we can define KleisliFunctor:
class (Monad m, Functor f) => KleisliFunctor m f where
kmap :: (a -> m b) -> f a -> f b
kmap f = kjoin . fmap f
kjoin :: f (m a) -> f a
kjoin = kmap id
Does this type class
class (Functor f, Monad m) => Absorb f m where
(>>~) :: f a -> (a -> m b) -> m b
a >>~ f = ajoin $ fmap f a
ajoin :: f (m a) -> m a
ajoin a = a >>~ id
fit somewhere into category theory? What are the laws? Are they
a >>~ g . f === fmap f a >>~ g
a >>~ (f >=> g) === a >>~ f >>= g
?
This is a speculative answer. Proceed with caution.
Let's first consider KleisliFunctor, focusing on the bind-like arrow mapping:
class (Monad m, Functor f) => KleisliFunctor m f where
kmap :: (a -> m b) -> f a -> f b
For this to actually be a functor from the Kleisli category of m to Hask, kmap has to follow the relevant functor laws:
-- Mapping the identity gives identity (in the other category).
kmap return = id
-- Mapping a composed arrow gives a composed arrow (in the other category).
kmap (g <=< f) = kmap g . kmap f
The fact that there are two Functors involved makes things a little unusual, but not unreasonable -- for instance, the laws do hold for mapMaybe, which is the first concrete example the KleisliFunctor post alludes to.
As for Absorb, I will flip the bind-like method for the sake of clarity:
class (Functor f, Monad m) => Absorb f m where
(~<<) :: (a -> m b) -> f a -> m b
If we are looking for something analogous to KleisliFunctor, a question that immediately arises is which category would have functions of type f a -> m b as arrows. It certainly cannot be Hask, as its identity (of type f a -> m a) cannot be id. We would have to figure out not only identity but also composition. For something that is not entirely unlike Monad...
idAbsorb :: f a -> m a
compAbsorb :: (f b -> m c) -> (f a -> m b) -> (f a -> m c)
... the only plausible thing I can think of right now is having a monad morphism as idAbsorb and using a second monad morphism in the opposite direction (that is, from m to f) so that compAbsorb can be implemented by applying the first function, then going back to f and finally applying the second function. We would need to work that out in order to see if my assumptions are appropriate, if this approach works, and if it leads to something useful for your purposes.
I am trying to write my own foldMap function as an excersice to learn Haskell
Currently it looks like this
class Functor f => Foldable f where
fold :: Monoid m => f m -> m
foldMap :: Monoid m => (a -> m) -> f a -> m
foldMap g a = fold (<>) mempty (fmap g a)
However when compiling it it gives the following error
Could not deduce (Monoid ((f m -> m) -> fm -> m)) arising from use of 'fold'
from the context (Foldable f) bound by the class declaration for 'Foldable' at (file location)
or from (Monoid m) bound by the type signature for foldMap :: Monoid m => (a -> m) -> f a -> m at (file location
In the expression fold (<>) mempty (fmap g a)
In an equation for 'foldMap':
foldMap g a = fold (<>) mempty (fmap g a)
I can't figure out what the compiler is trying to tell me with this error, can anyone tell me what goes wrong with my foldMap?
Maybe we should do an answer with the actual solution:
I hope it's now clear, that this is a possible definition:
class Functor f => Foldable f where
fold :: Monoid m => f m -> m
foldMap :: Monoid m => (a -> m) -> f a -> m
foldMap g a = fold $ fmap g a
follow the types
Andrew and Lee already gave you a high level explanation but maybe I can give you another view on it:
Let's just follow the types to oget to this answer:
We want a function f a -> m where m is a monoid and f is a functor. In addition we have a function g :: a -> m we can use to get from some a into the monoid - nice.
Now we get some additional functions:
fold :: f m -> m from our own class
fmap :: (a -> b) -> f a -> f b from the Functor f
Ok we need f a -> m now if only the a would be an m then we could use fold ... dang.
But wait: we can make a a into a m using g- but the a is packed into f ... dang.
Oh wait: we can make a f a into a f m using fmap .... ding-ding-ding
So let's do it:
make f a into f m: fmap g a
use fold on it: fold (fmap g a)
or using $:
foldMap g a = fold $ fmap g a
example
Let's get something so we can try:
module Foldable where
import Data.Monoid
class Functor f => Foldable f where
fold :: Monoid m => f m -> m
foldMap :: Monoid m => (a -> m) -> f a -> m
foldMap g a = fold $ fmap g a
instance Foldable [] where
fold [] = mempty
fold (x:xs) = mappend x (fold xs)
here is a simple example using this with Sum and [1..4]:
λ> foldMap Sum [1..4]
Sum {getSum = 10}
which seems fine to me.
A Monoid has two functions, mappend and mempty, and you can use (<>) in place of mappend.
Typeclasses work because the compiler inserts the appropriate definition for the function depending on the types of the data, so (happily) there's no need to pass around the function in question.
The mistake you've made is to unnecessarily pass the Monoid functions you're using in.
For example, if I defined a function to test if something was in a list like this:
isin :: Eq a => a -> [a] -> Bool
isin equalityFunction a list = any (equalityFunction a) list
I'd have unnecessarily tried to pass the equalityFunction as an argument, and the type signature doesn't match it.
Instead I should define
isin :: Eq a => a -> [a] -> Bool
isin a list = any (== a) list
using the standard name for the equality function as defined in the Eq typeclass.
Similarly, you neither need nor should pass the (<>) or empty arguments.
I want to map over Applicative form.
The type of map-like function would be like below:
mapX :: (Applicative f) => (f a -> f b) -> f [a] -> f [b]
used as:
result :: (Applicative f) => f [b]
result = mapX f xs
where f :: f a -> f b
f = ...
xs :: f[a]
xs = ...
As the background of this post, I try to write fluid simulation program using Applicative style referring to Paul Haduk's "The Haskell School of Expression", and I want to express the simulation with Applicative style as below:
x, v, a :: Sim VArray
x = x0 +: integral (v * dt)
v = v0 +: integral (a * dt)
a = (...calculate acceleration with x v...)
instance Applicative Sim where
...
where Sim type means the process of simulation computation and VArray means Array of Vector (x,y,z). X, v a are the arrays of position, velocity and acceleration, respectively.
Mapping over Applicative form comes when definining a.
I've found one answer to my question.
After all, my question is "How to lift high-order functions (like map
:: (a -> b) -> [a] -> [b]) to the Applicative world?" and the answer
I've found is "To build them using lifted first-order functions."
For example, the "mapX" is defined with lifted first-order functions
(headA, tailA, consA, nullA, condA) as below:
mapX :: (f a -> f b) -> f [a] -> f [b]
mapX f xs0 = condA (nullA xs0) (pure []) (consA (f x) (mapA f xs))
where
x = headA xs0
xs = tailA xs0
headA = liftA head
tailA = liftA tail
consA = liftA2 (:)
nullA = liftA null
condA b t e = liftA3 aux b t e
where aux b t e = if b then t else e
First, I don't think your proposed type signature makes much sense. Given an applicative list f [a] there's no general way to turn that into [f a] -- so there's no need for a function of type f a -> f b. For the sake of sanity, we'll reduce that function to a -> f b (to transform that into the other is trivial, but only if f is a monad).
So now we want:
mapX :: (Applicative f) => (a -> f b) -> f [a] -> f [b]
What immediately comes to mind now is traverse which is a generalization of mapM. Traverse, specialized to lists:
traverse :: (Applicative f) => (a -> f b) -> [a] -> f [b]
Close, but no cigar. Again, we can lift traverse to the required type signature, but this requires a monad constraint: mapX f xs = xs >>= traverse f.
If you don't mind the monad constraint, this is fine (and in fact you can do it more straightforwardly just with mapM). If you need to restrict yourself to applicative, then this should be enough to illustrate why you proposed signature isn't really possible.
Edit: based on further information, here's how I'd start to tackle the underlying problem.
-- your sketch
a = liftA sum $ mapX aux $ liftA2 neighbors (x!i) nbr
where aux :: f Int -> f Vector3
-- the type of "liftA2 neighbors (x!i) nbr" is "f [Int]
-- my interpretation
a = liftA2 aux x v
where
aux :: VArray -> VArray -> VArray
aux xi vi = ...
If you can't write aux like that -- as a pure function from the positions and velocities at one point in time to the accelerations, then you have bigger problems...
Here's an intuitive sketch as to why. The stream applicative functor takes a value and lifts it into a value over time -- a sequence or stream of values. If you have access to a value over time, you can derive properties of it. So velocity can be defined in terms of acceleration, position can be defined in terms of velocity, and soforth. Great! But now you want to define acceleration in terms of position and velocity. Also great! But you should not need, in this instance, to define acceleration in terms of velocity over time. Why, you may ask? Because velocity over time is all acceleration is to begin with. So if you define a in terms of dv, and v in terms of integral(a) then you've got a closed loop, and your equations are not propertly determined -- either there are, even given initial conditions, infinitely many solutions, or there are no solutions at all.
If I'm thinking about this right, you can't do this just with an applicative functor; you'll need a monad. If you have an Applicative—call it f—you have the following three functions available to you:
fmap :: (a -> b) -> f a -> f b
pure :: a -> f a
(<*>) :: f (a -> b) -> f a -> f b
So, given some f :: f a -> f b, what can you do with it? Well, if you have some xs :: [a], then you can map it across: map (f . pure) xs :: [f b]. And if you instead have fxs :: f [a], then you could instead do fmap (map (f . pure)) fxs :: f [f b].1 However, you're stuck at this point. You want some function of type [f b] -> f [b], and possibly a function of type f (f b) -> f b; however, you can't define these on applicative functors (edit: actually, you can define the former; see the edit). Why? Well, if you look at fmap, pure, and <*>, you'll see that you have no way to get rid of (or rearrange) the f type constructor, so once you have [f a], you're stuck in that form.
Luckily, this is what monads are for: computations which can "change shape", so to speak. If you have a monad m, then in addition to the above, you get two extra methods (and return as a synonym for pure):
(>>=) :: m a -> (a -> m b) -> m b
join :: m (m a) -> m a
While join is only defined in Control.Monad, it's just as fundamental as >>=, and can sometimes be clearer to think about. Now we have the ability to define your [m b] -> m [b] function, or your m (m b) -> m b. The latter one is just join; and the former is sequence, from the Prelude. So, with monad m, you can define your mapX as
mapX :: Monad m => (m a -> m b) -> m [a] -> m [b]
mapX f mxs = mxs >>= sequence . map (f . return)
However, this would be an odd way to define it. There are a couple of other useful functions on monads in the prelude: mapM :: Monad m => (a -> m b) -> [a] -> m [b], which is equivalent to mapM f = sequence . map f; and (=<<) :: (a -> m b) -> m a -> m b, which is equivalent to flip (>>=). Using those, I'd probably define mapX as
mapX :: Monad m => (m a -> m b) -> m [a] -> m [b]
mapX f mxs = mapM (f . return) =<< mxs
Edit: Actually, my mistake: as John L kindly pointed out in a comment, Data.Traversable (which is a base package) supplies the function sequenceA :: (Applicative f, Traversable t) => t (f a) => f (t a); and since [] is an instance of Traversable, you can sequence an applicative functor. Nevertheless, your type signature still requires join or =<<, so you're still stuck. I would probably suggest rethinking your design; I think sclv probably has the right idea.
1: Or map (f . pure) <$> fxs, using the <$> synonym for fmap from Control.Applicative.
Here is a session in ghci where I define mapX the way you wanted it.
Prelude>
Prelude> import Control.Applicative
Prelude Control.Applicative> :t pure
pure :: Applicative f => a -> f a
Prelude Control.Applicative> :t (<*>)
(<*>) :: Applicative f => f (a -> b) -> f a -> f b
Prelude Control.Applicative> let mapX fun ma = pure fun <*> ma
Prelude Control.Applicative> :t mapX
mapX :: Applicative f => (a -> b) -> f a -> f b
I must however add that fmap is better to use, since Functor is less expressive than Applicative (that means that using fmap will work more often).
Prelude> :t fmap
fmap :: Functor f => (a -> b) -> f a -> f b
edit:
Oh, you have some other signature for mapX, anyway, you maybe meant the one I suggested (fmap)?