Coq - disj_conj_intro_patterns for inductive propositions - constructor

Given an arbitrary Inductive proposition definition in Coq, is there a general formula for deriving a reasonable disj_conj_intro_pattern to use when calling the induction tactic on the inductive proposition?
In general, a complete intro_pattern for any one of an inductive definition's constructors may require (names for) more than one hypothesis and more than one inductive hypothesis, and in this case the ordering of names provided in the pattern may include all the parameters, followed by one hypothesis and a corresponding inductive hypothesis, followed by one or more additional pairs consisting of a hypothesis and an inductive hypothesis. For instance, Software Foundations includes the following:
Inductive exp_match {T} : list T -> reg_exp T -> Prop :=
| MEmpty : exp_match [] EmptyStr
| MChar : forall x, exp_match [x] (Char x)
| MApp : forall s1 re1 s2 re2,
exp_match s1 re1 ->
exp_match s2 re2 ->
exp_match (s1 ++ s2) (App re1 re2)
| MUnionL : forall s1 re1 re2,
exp_match s1 re1 ->
exp_match s1 (Union re1 re2)
| MUnionR : forall re1 s2 re2,
exp_match s2 re2 ->
exp_match s2 (Union re1 re2)
| MStar0 : forall re, exp_match [] (Star re)
| MStarApp : forall s1 s2 re,
exp_match s1 re ->
exp_match s2 (Star re) ->
exp_match (s1 ++ s2) (Star re).
Notation "s =~ re" := (exp_match s re) (at level 80).
Theorem in_re_match : forall T (s : list T) (re : reg_exp T) (x : T),
s =~ re ->
In x s ->
In x (re_chars re).
Proof.
intros T s re x Hmatch Hin.
induction Hmatch
as [
|x'
|s1 re1 s2 re2 Hmatch1 IH1 Hmatch2 IH2
|s1 re1 re2 Hmatch IH|re1 s2 re2 Hmatch IH
|re|s1 s2 re Hmatch1 IH1 Hmatch2 IH2].
In this example, the intro_patterns for MApp and MStarApp each have two pairs of hypothesis and inductive hypothesis -- presumably because these two constructors each contain an expression of the form
x -> y -> z
About this, the current Reference Manual only seems to say
induction term as disj_conj_intro_pattern
This behaves as induction term but uses the names in
disj_conj_intro_pattern to name the variables introduced in the
context. The disj_conj_intro_pattern must typically be of the form [
p11 … p1n1 | … | pm1 … pmnm ] with m being the number of constructors
of the type of term. Each variable introduced by induction in the
context of the ith goal gets its name from the list pi1 … pini in
order. If there are not enough names, induction invents names for the
remaining variables to introduce. More generally, the pij can be any
disjunctive/conjunctive introduction pattern (see Section 8.3.2). For
instance, for an inductive type with one constructor, the pattern
notation (p1 , … , pn) can be used instead of [ p1 … pn ].
This does not seems to specify how to determine the correct form for a complete disj_conj_intro_pattern for a given Inductive definition.
Is my above empirical observation that 1) formal parameters of each constructor come first, followed by hypotheses of the constructor paired with corresponding inductive hypotheses; and 2) the number of pairs of hypothesis and inductive hypothesis follows from the number of hypotheses in the constructor, the sum of the matter? Or is there any more to it?
Is there other relevant documentation on this besides the Tactics chapter of the Reference Manual and the very general discussion of patterns in Gallina grammar in chapter 1?

If I understand your question correctly, then the answer is 'yes'. You can derive an intro pattern for induction.
Coq automatically generates an induction principle for any inductive definition and names it adding _ind as a suffix, so the induction principle for exp_match becomes exp_match_ind. If you explore the type of exp_match_ind using the Check command you'll be able to produce the required intro pattern.
Check exp_match_ind.
(* output:
exp_match_ind
: forall (T : Type) (P : list T -> reg_exp T -> Prop),
P [] EmptyStr ->
(forall x : T, P [x] (Char x)) ->
(forall (s1 : list T) (re1 : reg_exp T)
(s2 : list T) (re2 : reg_exp T),
s1 =~ re1 ->
P s1 re1 ->
s2 =~ re2 -> P s2 re2 -> P (s1 ++ s2) (App re1 re2)) ->
(forall (s1 : list T) (re1 re2 : reg_exp T),
s1 =~ re1 -> P s1 re1 -> P s1 (Union re1 re2)) ->
(forall (re1 : reg_exp T) (s2 : list T) (re2 : reg_exp T),
s2 =~ re2 -> P s2 re2 -> P s2 (Union re1 re2)) ->
(forall re : reg_exp T, P [] (Star re)) ->
(forall (s1 s2 : list T) (re : reg_exp T),
s1 =~ re ->
P s1 re ->
s2 =~ Star re -> P s2 (Star re) -> P (s1 ++ s2) (Star re)) ->
forall (l : list T) (r : reg_exp T), l =~ r ->
P l r
*)
This type says that (if you skip the initial forall "header") that you need to prove a bunch of subgoals to prove the goal P l r. Every -> at the top level separates the subgoals:
1) MEmpty case:
P [] EmptyStr
There is no hypotheses, that's why we start with
induction Hmatch as [ | -- notice there is nothing to the left of |.
2) MChar case:
(forall x : T, P [x] (Char x))
The intro pattern in this case is simple: for some x' we need to prove P [x'] (Char x'). Our pattern at this point becomes: [ | x'...
3) MApp case:
(forall (s1 : list T) (re1 : reg_exp T)
(s2 : list T) (re2 : reg_exp T), (* s1 re1 s2 re2 *)
s1 =~ re1 -> (* Hmatch1 *)
P s1 re1 -> (* IH1 *)
s2 =~ re2 -> (* Hmatch2 *)
P s2 re2 -> (* IH2 *)
P (s1 ++ s2) (App re1 re2)) (* the current subgoal *)
I've marked variables and hypotheses in the comments above according to the ones used in theorem in_re_match. Our pattern at this point becomes: [ | x' | s1 re1 s2 re2 Hmatch1 IH1 Hmatch2 IH2...
The rest of the subgoals can be done analogously, resulting in the pattern used in the theorem.

Related

How to Implement functions from type signatures?

I have the following two type signatures in Haskell:
foo :: (a -> (a,b)) -> a -> [b]
bar :: (a -> b) -> (a -> b -> c) -> a -> c
I want to write a concrete implementation of these two functions but I'm really struggling to understand where to start.
I understand that foo takes a function (a -> (a,b)) and returns a and a list containing b.
And bar takes a function (b -> c) which returns a function (a -> b -> c) which finally returns a and c.
Can anyone show me an example of a concrete implementation?
How do I know where to start with something like this and what goes on the left side of the definition?
You have some misunderstandings there:
I understand that foo takes a function (a -> (a,b)) and returns a and a list containing b.
No, it doesn't return a. It expects it as another argument, in addition to that function.
And bar takes a function (b -> c) which returns a function (a -> b -> c) which finally returns a and c.
Same here. Given g :: a -> b, bar returns a function bar g :: (a -> b -> c) -> a -> c. This function, in turn, given a function h :: (a -> b -> c), returns a function of type a -> c. And so it goes.
It's just like playing with pieces of a puzzle:
foo :: (a -> (a,b)) -> a -> [b]
-- g :: a -> (a,b)
-- x :: a
-- g x :: (a,b)
foo g x = [b] where
(a,b) = g x
bar :: (a -> b) -> (a -> b -> c) -> a -> c
-- g :: a -> b
-- x :: a
-- g x :: b
-- h :: a -> b -> c
-- h x :: b -> c
-- h x (g x) :: c
bar g h x = c where
c = ....
There's not much free choice for us here. Although, there are more ways to get more values of type b, for foo. Instead of ignoring that a in (a,b) = g x, we can use it in more applications of g, so there actually are many more possibilities there, like
foo2 :: (a -> (a,b)) -> a -> [b]
foo2 g x = [b1,b2] where
(a1,b1) = g x
(a2,b2) = g a1
and many more. Still, the types guide the possible implementations. foo can even make use of foo in its implementation, according to the types:
foo3 :: (a -> (a,b)) -> a -> [b]
foo3 g x = b : bs where
(a,b) = g x
bs = ...
So now, with this implementation, the previous two become its special cases: foo g x === take 1 (foo3 g x) and foo2 g x === take 2 (foo3 g x). Having the most general definition is probably best.
In addition to #will-nes's answer, it will be useful to treat (->) as a right-associative infix operator. So something like f: a -> b -> c is the same as f: a -> (b -> c). So this is saying f is a function that takes a value of type a and returns you a value of type b -> c, which is, another function, one that takes a value of type b and returns you a value of type c.
So the types in your example can be re-written as follows
foo :: (a -> (a,b)) -> (a -> [b])
bar :: (a -> b) -> ((a -> (b -> c)) -> (a -> c))
Similarly, you can think of arguments to a function in pieces as well, as being left-associative (like + and -), though there's no explicit operator in this case. foo a b c d e is the same as ((((foo a) b) c) d) e. For example, let's say we have a function f: Int -> Int -> Int (which is the same as f: Int -> (Int -> Int)). You don't have to provide both arguments at once. So you can write g = f 1, which has the type (Int -> Int). And then you can provide an argument to g, like g 2, which has the type Int. f 1 2 and let g = f 1 in g 2 are more or less the same. Here's a more concrete example of how this works:
Prelude> f = (+)
Prelude> g = f 1
Prelude> g 2
3
Prelude> :t f
f :: Num a => a -> a -> a
Prelude> :t g
g :: Num a => a -> a
Prelude> :t g 2
g 2 :: Num a => a
In #will-nes's sample implementation examples, he defines the functions with all of the arguments up front, but you don't have to think of them that way. Just think of f: a -> b -> c as taking a value of type a and returning another function. While most of the methods you encounter will use all of their arguments up-front, there might be cases in which you don't want to do that. Here's an example:
veryExpensive :: A -> B
unstagedFun :: A -> (B -> C) -> C
unstagedFun a f = f (veryExpensive a)
stagedFun :: A -> (B -> C) -> C
stagedFun a = let b = veryExpensive a in \f -> f b
(You can also rewrite the latter as let b = veryExpensive a in ($ b))
Of course, with compiler optimizations, I wouldn't be surprised if the unstaged version staged automatically, but hopefully this offers some motivation for thinking of functions as not having multiple arguments, but rather, as a single argument, but they may return other functions that may themselves return functions (but also only take a single argument).

Finding inverse functions [duplicate]

In pure functional languages like Haskell, is there an algorithm to get the inverse of a function, (edit) when it is bijective? And is there a specific way to program your function so it is?
In some cases, yes! There's a beautiful paper called Bidirectionalization for Free! which discusses a few cases -- when your function is sufficiently polymorphic -- where it is possible, completely automatically to derive an inverse function. (It also discusses what makes the problem hard when the functions are not polymorphic.)
What you get out in the case your function is invertible is the inverse (with a spurious input); in other cases, you get a function which tries to "merge" an old input value and a new output value.
No, it's not possible in general.
Proof: consider bijective functions of type
type F = [Bit] -> [Bit]
with
data Bit = B0 | B1
Assume we have an inverter inv :: F -> F such that inv f . f ≡ id. Say we have tested it for the function f = id, by confirming that
inv f (repeat B0) -> (B0 : ls)
Since this first B0 in the output must have come after some finite time, we have an upper bound n on both the depth to which inv had actually evaluated our test input to obtain this result, as well as the number of times it can have called f. Define now a family of functions
g j (B1 : B0 : ... (n+j times) ... B0 : ls)
= B0 : ... (n+j times) ... B0 : B1 : ls
g j (B0 : ... (n+j times) ... B0 : B1 : ls)
= B1 : B0 : ... (n+j times) ... B0 : ls
g j l = l
Clearly, for all 0<j≤n, g j is a bijection, in fact self-inverse. So we should be able to confirm
inv (g j) (replicate (n+j) B0 ++ B1 : repeat B0) -> (B1 : ls)
but to fulfill this, inv (g j) would have needed to either
evaluate g j (B1 : repeat B0) to a depth of n+j > n
evaluate head $ g j l for at least n different lists matching replicate (n+j) B0 ++ B1 : ls
Up to that point, at least one of the g j is indistinguishable from f, and since inv f hadn't done either of these evaluations, inv could not possibly have told it apart – short of doing some runtime-measurements on its own, which is only possible in the IO Monad.
                                                                                                                                   ⬜
You can look it up on wikipedia, it's called Reversible Computing.
In general you can't do it though and none of the functional languages have that option. For example:
f :: a -> Int
f _ = 1
This function does not have an inverse.
Not in most functional languages, but in logic programming or relational programming, most functions you define are in fact not functions but "relations", and these can be used in both directions. See for example prolog or kanren.
Tasks like this are almost always undecidable. You can have a solution for some specific functions, but not in general.
Here, you cannot even recognize which functions have an inverse. Quoting Barendregt, H. P. The Lambda Calculus: Its Syntax and Semantics. North Holland, Amsterdam (1984):
A set of lambda-terms is nontrivial if it is neither the empty nor the full set. If A and B are two nontrivial, disjoint sets of lambda-terms closed under (beta) equality, then A and B are recursively inseparable.
Let's take A to be the set of lambda terms that represent invertible functions and B the rest. Both are non-empty and closed under beta equality. So it's not possible to decide whether a function is invertible or not.
(This applies to the untyped lambda calculus. TBH I don't know if the argument can be directly adapted to a typed lambda calculus when we know the type of a function that we want to invert. But I'm pretty sure it will be similar.)
If you can enumerate the domain of the function and can compare elements of the range for equality, you can - in a rather straightforward way. By enumerate I mean having a list of all the elements available. I'll stick to Haskell, since I don't know Ocaml (or even how to capitalise it properly ;-)
What you want to do is run through the elements of the domain and see if they're equal to the element of the range you're trying to invert, and take the first one that works:
inv :: Eq b => [a] -> (a -> b) -> (b -> a)
inv domain f b = head [ a | a <- domain, f a == b ]
Since you've stated that f is a bijection, there's bound to be one and only one such element. The trick, of course, is to ensure that your enumeration of the domain actually reaches all the elements in a finite time. If you're trying to invert a bijection from Integer to Integer, using [0,1 ..] ++ [-1,-2 ..] won't work as you'll never get to the negative numbers. Concretely, inv ([0,1 ..] ++ [-1,-2 ..]) (+1) (-3) will never yield a value.
However, 0 : concatMap (\x -> [x,-x]) [1..] will work, as this runs through the integers in the following order [0,1,-1,2,-2,3,-3, and so on]. Indeed inv (0 : concatMap (\x -> [x,-x]) [1..]) (+1) (-3) promptly returns -4!
The Control.Monad.Omega package can help you run through lists of tuples etcetera in a good way; I'm sure there's more packages like that - but I don't know them.
Of course, this approach is rather low-brow and brute-force, not to mention ugly and inefficient! So I'll end with a few remarks on the last part of your question, on how to 'write' bijections. The type system of Haskell isn't up to proving that a function is a bijection - you really want something like Agda for that - but it is willing to trust you.
(Warning: untested code follows)
So can you define a datatype of Bijection s between types a and b:
data Bi a b = Bi {
apply :: a -> b,
invert :: b -> a
}
along with as many constants (where you can say 'I know they're bijections!') as you like, such as:
notBi :: Bi Bool Bool
notBi = Bi not not
add1Bi :: Bi Integer Integer
add1Bi = Bi (+1) (subtract 1)
and a couple of smart combinators, such as:
idBi :: Bi a a
idBi = Bi id id
invertBi :: Bi a b -> Bi b a
invertBi (Bi a i) = (Bi i a)
composeBi :: Bi a b -> Bi b c -> Bi a c
composeBi (Bi a1 i1) (Bi a2 i2) = Bi (a2 . a1) (i1 . i2)
mapBi :: Bi a b -> Bi [a] [b]
mapBi (Bi a i) = Bi (map a) (map i)
bruteForceBi :: Eq b => [a] -> (a -> b) -> Bi a b
bruteForceBi domain f = Bi f (inv domain f)
I think you could then do invert (mapBi add1Bi) [1,5,6] and get [0,4,5]. If you pick your combinators in a smart way, I think the number of times you'll have to write a Bi constant by hand could be quite limited.
After all, if you know a function is a bijection, you'll hopefully have a proof-sketch of that fact in your head, which the Curry-Howard isomorphism should be able to turn into a program :-)
I've recently been dealing with issues like this, and no, I'd say that (a) it's not difficult in many case, but (b) it's not efficient at all.
Basically, suppose you have f :: a -> b, and that f is indeed a bjiection. You can compute the inverse f' :: b -> a in a really dumb way:
import Data.List
-- | Class for types whose values are recursively enumerable.
class Enumerable a where
-- | Produce the list of all values of type #a#.
enumerate :: [a]
-- | Note, this is only guaranteed to terminate if #f# is a bijection!
invert :: (Enumerable a, Eq b) => (a -> b) -> b -> Maybe a
invert f b = find (\a -> f a == b) enumerate
If f is a bijection and enumerate truly produces all values of a, then you will eventually hit an a such that f a == b.
Types that have a Bounded and an Enum instance can be trivially made RecursivelyEnumerable. Pairs of Enumerable types can also be made Enumerable:
instance (Enumerable a, Enumerable b) => Enumerable (a, b) where
enumerate = crossWith (,) enumerate enumerate
crossWith :: (a -> b -> c) -> [a] -> [b] -> [c]
crossWith f _ [] = []
crossWith f [] _ = []
crossWith f (x0:xs) (y0:ys) =
f x0 y0 : interleave (map (f x0) ys)
(interleave (map (flip f y0) xs)
(crossWith f xs ys))
interleave :: [a] -> [a] -> [a]
interleave xs [] = xs
interleave [] ys = []
interleave (x:xs) ys = x : interleave ys xs
Same goes for disjunctions of Enumerable types:
instance (Enumerable a, Enumerable b) => Enumerable (Either a b) where
enumerate = enumerateEither enumerate enumerate
enumerateEither :: [a] -> [b] -> [Either a b]
enumerateEither [] ys = map Right ys
enumerateEither xs [] = map Left xs
enumerateEither (x:xs) (y:ys) = Left x : Right y : enumerateEither xs ys
The fact that we can do this both for (,) and Either probably means that we can do it for any algebraic data type.
Not every function has an inverse. If you limit the discussion to one-to-one functions, the ability to invert an arbitrary function grants the ability to crack any cryptosystem. We kind of have to hope this isn't feasible, even in theory!
In some cases, it is possible to find the inverse of a bijective function by converting it into a symbolic representation. Based on this example, I wrote this Haskell program to find inverses of some simple polynomial functions:
bijective_function x = x*2+1
main = do
print $ bijective_function 3
print $ inverse_function bijective_function (bijective_function 3)
data Expr = X | Const Double |
Plus Expr Expr | Subtract Expr Expr | Mult Expr Expr | Div Expr Expr |
Negate Expr | Inverse Expr |
Exp Expr | Log Expr | Sin Expr | Atanh Expr | Sinh Expr | Acosh Expr | Cosh Expr | Tan Expr | Cos Expr |Asinh Expr|Atan Expr|Acos Expr|Asin Expr|Abs Expr|Signum Expr|Integer
deriving (Show, Eq)
instance Num Expr where
(+) = Plus
(-) = Subtract
(*) = Mult
abs = Abs
signum = Signum
negate = Negate
fromInteger a = Const $ fromIntegral a
instance Fractional Expr where
recip = Inverse
fromRational a = Const $ realToFrac a
(/) = Div
instance Floating Expr where
pi = Const pi
exp = Exp
log = Log
sin = Sin
atanh = Atanh
sinh = Sinh
cosh = Cosh
acosh = Acosh
cos = Cos
tan = Tan
asin = Asin
acos = Acos
atan = Atan
asinh = Asinh
fromFunction f = f X
toFunction :: Expr -> (Double -> Double)
toFunction X = \x -> x
toFunction (Negate a) = \a -> (negate a)
toFunction (Const a) = const a
toFunction (Plus a b) = \x -> (toFunction a x) + (toFunction b x)
toFunction (Subtract a b) = \x -> (toFunction a x) - (toFunction b x)
toFunction (Mult a b) = \x -> (toFunction a x) * (toFunction b x)
toFunction (Div a b) = \x -> (toFunction a x) / (toFunction b x)
with_function func x = toFunction $ func $ fromFunction x
simplify X = X
simplify (Div (Const a) (Const b)) = Const (a/b)
simplify (Mult (Const a) (Const b)) | a == 0 || b == 0 = 0 | otherwise = Const (a*b)
simplify (Negate (Negate a)) = simplify a
simplify (Subtract a b) = simplify ( Plus (simplify a) (Negate (simplify b)) )
simplify (Div a b) | a == b = Const 1.0 | otherwise = simplify (Div (simplify a) (simplify b))
simplify (Mult a b) = simplify (Mult (simplify a) (simplify b))
simplify (Const a) = Const a
simplify (Plus (Const a) (Const b)) = Const (a+b)
simplify (Plus a (Const b)) = simplify (Plus (Const b) (simplify a))
simplify (Plus (Mult (Const a) X) (Mult (Const b) X)) = (simplify (Mult (Const (a+b)) X))
simplify (Plus (Const a) b) = simplify (Plus (simplify b) (Const a))
simplify (Plus X a) = simplify (Plus (Mult 1 X) (simplify a))
simplify (Plus a X) = simplify (Plus (Mult 1 X) (simplify a))
simplify (Plus a b) = (simplify (Plus (simplify a) (simplify b)))
simplify a = a
inverse X = X
inverse (Const a) = simplify (Const a)
inverse (Mult (Const a) (Const b)) = Const (a * b)
inverse (Mult (Const a) X) = (Div X (Const a))
inverse (Plus X (Const a)) = (Subtract X (Const a))
inverse (Negate x) = Negate (inverse x)
inverse a = inverse (simplify a)
inverse_function x = with_function inverse x
This example only works with arithmetic expressions, but it could probably be generalized to work with lists as well. There are also several implementations of computer algebra systems in Haskell that may be used to find the inverse of a bijective function.
No, not all functions even have inverses. For instance, what would the inverse of this function be?
f x = 1

Haskell function composition - two one-dimensional functions to a two dimensional function

Let's assume I have a function f in Haskell, It takes a Double and returns a Double, and I have function g that also takes a Double and returns a Double.
Now, I can apply f to g like this: f . g.
Now, let's take a higher-dimensional function f, that
takes two Doubles and outputs one:
f :: Double -> Double -> Double
or
f :: (Double, Double) -> Double
And I have two g functions as well:
g1 :: Double -> Double, g2 :: Double -> Double
Now, I want to compose the functions to get something like:
composition x = f (g1 x) (g2 x)
Can this be achieved just by using the dot (.) operator?
You can make use of liftA2 :: Applicative f => (a -> b -> c) -> f a -> f b -> f c for this:
composition = liftA2 f g1 g2
Since a function is an applicative [src]:
instance Applicative ((->) r) where
pure = const
(<*>) f g x = f x (g x)
liftA2 q f g x = q (f x) (g x)
and liftA2 is implemented as [src]:
liftA2 :: (a -> b -> c) -> f a -> f b -> f c
liftA2 f x = (<*>) (fmap f x)
this will thus be resolved to:
liftA2 f g1 g2 x = (<*>) (fmap f g1) g2 x
= (fmap f g1 <*> g2) x
= (f . g1 <*> g2) x
= (\fa ga xa -> fa xa (ga xa)) (f . g1) g2 x
= (f . g1) x (g2 x)
= f (g1 x) (g2 x)
You can try this:
import Control.Arrow
composition = f . (g1 &&& g2)
(&&&) turns g1 :: a -> b and g2 :: a -> c into g1 &&& g2 :: a -> (b, c). Then you can apply normal composition.

Abstracting Function in Haskell

I am currently taking a class in Haskell and am having a bit of trouble understanding how functions are passed as parameters. For this assignment, we were tasked with creating a program that would evaluate expressions. To reduce boiler plating, I wanted to abstract the function by creating a helper function that would take in an operator as an input and return the result
Main Function:
eval :: EDict -> Expr -> Maybe Double
eval _ (Val x) = Just x
eval d (Var i) = find d i
eval d (Add x y) = evalOp d (+) x y
eval d (Mul x y) = evalOp d (*) x y
eval d (Sub x y) = evalOp d (-) x y
Helper Function:
evalOp:: EDict -> ((Num a) => a -> a -> a) -> Expr -> Expr -> Maybe Double
evalOp d op x y =
let r = eval d x
s = eval d y
in case (r, s) of
(Just m, Just n) -> Just (m `op` n)
_ -> Nothing
Other definitions
data Expr
= Val Double
| Add Expr Expr
| Mul Expr Expr
| Sub Expr Expr
| Dvd Expr Expr
| Var Id
| Def Id Expr Expr
deriving (Eq, Show)
type Dict k d = [(k,d)]
define :: Dict k d -> k -> d -> Dict k d
define d s v = (s,v):d
find :: Eq k => Dict k d -> k -> Maybe d
find [] _ = Nothing
find ( (s,v) : ds ) name | name == s = Just v
| otherwise = find ds name
type EDict = Dict String Double
I looked into how +,-, and * are to be passed into other functions and found that these operators are defined by the following definition:
ghci> :t (*)
(*) :: (Num a) => a -> a -> a
However, when I run my code I get the following compilation error:
Illegal polymorphic or qualified type: Num a => a -> a -> a
Perhaps you intended to use RankNTypes or Rank2Types
In the type signature for ‘evalOp’:
evalOp :: EDict
-> ((Num a) => a -> a -> a) -> Expr -> Expr -> Maybe Double
I am not really sure why this is happening as I gave my function the proper parameters as defined by Haskell. Any help would be greatly appreciated as I am still very new to the language.
Right now, your Expr data type is constrained to Double-valued expressions, so there is no need to deal with polymorphism.
evalOp:: EDict -> (Double -> Double -> Double) -> Expr -> Expr -> Maybe Double
evalOp d op x y =
let r = eval d x
s = eval d y
in case (r, s) of
(Just m, Just n) -> Just (m `op` n)
_ -> Nothing
(+) :: Num a => a -> a -> a is a valid argument for evalOp, because its type can be "restricted" to Double -> Double -> Double.
> let f :: Double -> Double -> Double; f = (+)
> f 3 5
8.0
If your expression type were parameterized, then you would put a Num a constraint on your functions (not just on the arguments that involve a, because you want the same a throughout the function).
data Expr a
= Val a
| Add (Expr a) (Expr a)
| Mul (Expr a) (Expr a)
| Sub (Expr a) (Expr a)
| Dvd (Expr a) (Expr a)
| Var Id
| Def Id (Expr a) (Expr a)
deriving (Eq, Show)
type EDict a = Dict String a
evalOp:: Num a => EDict a -> (a -> a -> a) -> Expr a -> Expr a -> Maybe a
evalOp d op x y =
let r = eval d x
s = eval d y
in case (r, s) of
(Just m, Just n) -> Just (m `op` n)
_ -> Nothing
eval :: Num a => EDict a -> Expr a -> Maybe a
eval _ (Val x) = Just x
eval d (Var i) = find d i
eval d (Add x y) = evalOp d (+) x y
eval d (Mul x y) = evalOp d (*) x y
eval d (Sub x y) = evalOp d (-) x y
The error is telling you that you cannot nest a type qualifier inside one of the types in your function chain. Instead, put all of the qualifiers at the beginning of the type signature:
evalOp:: (Num a) => EDict -> (a -> a -> a) -> Expr -> Expr -> Maybe Double
See Haskell - Illegal Polymorphic type? for a more thorough discussion.

Haskell, how to check for a palindrom

I have a small question. How could I extend my function to return True even if a character is a capital letter or not.
My function works for Strings in lists:
f1 w = w == reverse w
Test:
*Main> let test = ["Boob"]
*Main> f1 test
True
*Main> let test2 = "Boob"
*Main> f1 test2
False
regards,
martin
what about
import Data.Char (toLower)
f1 :: String -> Bool
f1 w = w == reverse w
f2 :: String -> Bool
f2 str = f1 $ map toLower str
but what I would suggest is using good names for your functions
testPalindrome = f1
ignoreCase = map toLower
then
testPalindrome' = testPalindrome . ignoreCase
Update:
The . is concatenation of functions:
(.) :: (b -> c) -> (a -> b) -> (a -> c)
(g . f) x = g (f x)
f
A -----> B
\ |
\ |
g.f \ |g
\ |
V V
C
Update2
#dfeuer mentioned in the comments a very elegant solution
import Data.Function (on)
import Data.Char (toLower)
(=~=) :: String -> String -> Bool
-- | Equivalence of Strings, by ignoring the case
(=~=) = (==) `on` toLower
testPalindrome :: String -> Bool
testPalindrome w = w =~= reverse w
The function on (used infix with backtick syntax) takes a function (==) and a "modifier-function" toLower and applies it to the arguments of that function.
(f `on` g) x y = f (g x) (g y)
this is especially useful with binary operators like (==), (<) and so on.