How can i add a hover recognizer to an object in prolog?
I want a rule to be called when the user hovers an object with the mouse.
something like that:
send(S,recogniser,click_gesture(left,'',single,and(message(#prolog, add ,X, Y)))).
but for mouse hover gesture.
You must work with the mouse's events.
Here is an example : I have a button, when the mouse is over the button, the shape is modified.
You can know when the mouse enters the area of the object and when it leaves it.
:- pce_begin_class(my_button, button).
variable(enter, any, both, "flag pour le dessin lorsque la souris survole le bouton").
event(G, Ev:event) :->
( send(Ev, is_a, area_enter) ->
send(G, slot, enter, in),
send(G, redraw)
; send(Ev, is_a, area_exit) ->
send(G, slot, enter, out),
send(G, redraw)
; send_super(G, event, Ev)
).
initialise(P, Lbl):->
send(P, send_super, initialise,Lbl),
send(P, font, font(times, normal, 15)),
send(P, compute),
send(P, slot, enter, out).
% méthode d'affichage redéfinissable
'_redraw_area'(P, _A:area):->
"Draw a "::
% on affiche le texte
get(P, label, Lbl),
new(Str1, string(Lbl)),
get_object(P, area, area(X0,Y0,W,H)),
( get(P, status, preview) -> X is X0 + 2, Y is Y0 + 2, Up = #off
; X = X0, Y = Y0, Up = #on),
( get(P, slot, enter, out) -> new(E, elevation(1)); new(E, elevation(3))),
send(P, draw_box, X, Y, W, H, 5, E, Up),
send(P, draw_text, Str1, font(times, normal, 15), X, Y, W, H, center, center),
get(P, default_button, #on),
X1 is X+3, Y1 is Y+3, W1 is W - 6, H1 is H- 6,
send(P, save_graphics_state),
send(P, graphics_state,texture := dotted),
send(P, draw_box, X1, Y1, W1, H1, 5),
send(P, restore_graphics_state).
:- pce_end_class.
Related
I've tried to get a vectorfunction like
syms x
fn=function_handle([x^2;1])
Output is #(x) [x.^2;1]
Thats leads of course in an error while calling fn with vectorarguments
(Dimensions mismatch)
Is there a way to avoid the issue?
I've tried fn=function_handle([x^2;1+0*x])
but the codeoptimation - or whatever - deletes the 0*x - term.
Any suggestions?
If you think about it, what function_handle does here is reasonable, since the scenario you require here cannot be reliably predicted in advance. So I don't think there is an obvious option to change its behaviour.
You could deal with this in a couple of ways.
One way is to treat the function handle as unvectorised, and rely on external vectorization, e.g.
f = function_handle([x^2; 1]);
[arrayfun( f, [1,2,3,4,5], 'uniformoutput', false ){:}]
Alternatively, you could introduce a symbolic helper constant c, and call f appropriately. You can also create a wrapper function that uses an appropriate default constant. Examples:
f = function_handle([x^2; c], 'vars', [x,c]);
f( [1,2,3,4,5], [1,1,1,1,1] )
g = #(x) f( x, ones(size(x)) );
g([1,2,3,4,5])
or
f = function_handle([x^2; (x+c)/x], 'vars', [x,c]);
f([1,2,3,4,5], 0)
g = #(x) f( x, 0 )
g([1,2,3,4,5])
Thank you.
Today, i'm happy of a solution i've found.
I turn the arrayfcn into a cellfcn:
f_h_Cell=#(x, y) {x .* y, 0}
nf = #(x) #mifCell2Mat (f_h_Cell (x (size (x) (1) * 0 / 2 + 1:size (x) (1) * 1 / 2,{':'} (ones (1, ndims (x) - 1)){:}), x (size (x) (1) * 1 / 2 + 1:size (x) (1) * 2 / 2, {':'} (ones (1, ndims (x) - 1)) {:})))
and then:
function res=mifCell2Mat(resCell)
resCell=transpose(resCell);
[~,idx]=max(cellfun(#numel,resCell));
refSize=(size(resCell{idx}));
resCell=cellfun(#(x) x+zeros(refSize),resCell,'uniformoutput',false);
res=cell2mat(resCell);
endfunction
All automate calling following function
f=fcn(name,domain,parms,fcn);
so a simple f.nf([x;y;z]) call gives the result.
Of course it doesn't work, if there are numel's between 1 and say size=[10,10] of
eg size=[10,1], but so what ... In most cases it work's for me (until now: allways).
Oh, while i read my code just here, i've found a little bug:
refSize=(size(resCell{idx}));
must of course change to
refSize=(size(resCell{idx(1)}));
cause there a possible more than one max sizes in the idx, so i've picked the first. I do first a test of constant outDims, so that these workaround only occours, if there are constants. In the other cases (if all outDims contain domainvars) a simple anonymous function of a matrix-handle appears to the user:
f_h_Mat=#(x, y) [x .* y; x]
nf=#(x) f_h_Mat (x (size (x) (1) * 0 / 2 + 1:size (x) (1) * 1 / 2, {':'} (ones (1, ndims (x) - 1)) {:}), x (size
(x) (1) * 1 / 2 + 1:size (x) (1) * 2 / 2, {':'} (ones (1, ndims (x) - 1)) {:}))
I am trying to make a function in Octave where you give octave a function f(x,y) as a string, a change in X, a change in Y, a starting point, and the size of a matrix, the function will create a matrix populated with the values of f(x,y) at each point in the matrix.
This is for an application that displays a 3d graph, using the matrix to map each value to a block
# funcStr: The function whose Z values are being calculated
# dx: the change in x that each block in the x direction represents
# dy: the change in y that each block in the y direction represents
# startPt: the point (in an array of x, y) that center block represents
# res: the side length (in blocks) of the plane
pkg load symbolic
syms x y
function[zValues] = calculateZValues(funcStr, dx, dy, startPt, res)
zValues = zeros(res);
eqn = #(x, y) inline(funcStr);
startX = startPt{1};
startY = startPt{2};
for yOffset = 1:res
for xOffset = 1:res
xCoord = startX + dx * xOffset;
yCoord = startY + dy * yOffset;
zValues(res * yOffset + xOffset) = double(subs(eqn, #(x, y), {xCoord, yCoord}));
endfor
endfor
endfunction
The error I am getting is:
>> calculateZValues("x*y", 1, 1, {0,0}, 10)
parse error near line 20 of file /home/rahul/Documents/3dGraph/graph/calculateZValues.m
anonymous function bodies must be single expressions
>>> zValues(res * yOffset + xOffset) = double(subs(eqn, #(x, y), {xCoord, yCoord}));
I have no idea what the issue is. I have replaced the #(x,y) part with {x,y} in the line referenced by the error but it says nothing or it raises an error about the function subs not being declared. I have also tried moving the pkg and syms lines above the function header
I'm still trying to wrap my head around agda, so I wrote a little tic-tac-toe game Type
data Game : Player -> Vec Square 9 -> Set where
start : Game x ( - ∷ - ∷ - ∷
- ∷ - ∷ - ∷
- ∷ - ∷ - ∷ [] )
xturn : {gs : Vec Square 9} -> (n : ℕ) -> Game x gs -> n < (#ofMoves gs) -> Game o (makeMove gs x n )
oturn : {gs : Vec Square 9} -> (n : ℕ) -> Game o gs -> n < (#ofMoves gs) -> Game x (makeMove gs o n )
Which will hold a valid game path.
Here #ofMoves gs would return the number of empty Squares,
n < (#ofMoves gs) would prove that the nth move is valid,
and makeMove gs x n replaces the nth empty Square in the game state vector.
After a few stimulating games against myself, I decided to shoot for something more awesome. The goal was to create a function that would take an x player and an o player and pit them against each other in an epic battle to the death.
--two programs enter, one program leaves
gameMaster : {p : Player } -> {gs : Vec Square 9} --FOR ALL
-> ({gs : Vec Square 9} -> Game x gs -> (0 < (#ofMoves gs)) -> Game o (makeMove gs x _ )) --take an x player
-> ({gs : Vec Square 9} -> Game o gs -> (0 < (#ofMoves gs)) -> Game x (makeMove gs o _ )) --take an o player
-> ( Game p gs) --Take an initial configuration
-> GameCondition --return a winner
gameMaster {_} {gs} _ _ game with (gameCondition gs)
... | xWin = xWin
... | oWin = oWin
... | draw = draw
... | ongoing with #ofMoves gs
... | 0 = draw --TODO: really just prove this state doesn't exist, it will always be covered by gameCondition gs = draw
gameMaster {x} {gs} fx fo game | ongoing | suc nn = gameMaster (fx) (fo) (fx game (s≤s z≤n)) -- x move
gameMaster {o} {gs} fx fo game | ongoing | suc nn = gameMaster (fx) (fo) (fo game (s≤s z≤n)) -- o move
Here (0 < (#ofMoves gs)) is "short hand" for a proof that that the game is ongoing,
gameCondition gs will return the game state as you would expect (one of xWin, oWin, draw, or ongoing)
I want to prove that there are valid moves (the s≤s z≤n part). This should be possible since suc nn <= #ofMoves gs. I have no idea how how to make this work in agda.
I'll try to answer some of your questions, but I don't think you're apporaching this from the right angle. While you certainly can work with bounded numbers using explicit proofs, you'll most likely be more successful with data type instead.
For your makeMove (I've renamed it to move in the rest of the answer), you need a number bounded by the available free squares. That is, when you have 4 free squares, you want to be able to call move only with 0, 1, 2 and 3. There's one very nice way to achieve that.
Looking at Data.Fin, we find this interesting data type:
data Fin : ℕ → Set where
zero : {n : ℕ} → Fin (suc n)
suc : {n : ℕ} (i : Fin n) → Fin (suc n)
Fin 0 is empty (both zero and suc construct Fin n for n greater or equal than 1). Fin 1 only has zero, Fin 2 has zero and suc zero, and so on. This represents exactly what we need: a number bounded by n. You might have seen this used in the implementation of safe vector lookup:
lookup : ∀ {a n} {A : Set a} → Fin n → Vec A n → A
lookup zero (x ∷ xs) = x
lookup (suc i) (x ∷ xs) = lookup i xs
The lookup _ [] case is impossible, because Fin 0 has no elements!
How to apply this nicely to your problem? Firstly, we'll have to track how many empty squares we have. This allows us to prove that gameMaster is indeed a terminating function (the number of empty squares is always decreasing). Let's write a variant of Vec which tracks not only length, but also the empty squares:
data Player : Set where
x o : Player
data SquareVec : (len : ℕ) (empty : ℕ) → Set where
[] : SquareVec 0 0
-∷_ : ∀ {l e} → SquareVec l e → SquareVec (suc l) (suc e)
_∷_ : ∀ {l e} (p : Player) → SquareVec l e → SquareVec (suc l) e
Notice that I got rid of the Square data type; instead, the empty square is baked directly into the -∷_ constructor. Instead of - ∷ rest we have -∷ rest.
We can now write the move function. What should its type be? Well, it'll take a SquareVec with at least one empty square, a Fin e (where e is the number of empty squares) and a Player. The Fin e guarantees us that this function can always find the appropriate empty square:
move : ∀ {l e} → Player → SquareVec l (suc e) → Fin (suc e) → SquareVec l e
move p ( -∷ sqs) zero = p ∷ sqs
move {e = zero} p ( -∷ sqs) (suc ())
move {e = suc e} p ( -∷ sqs) (suc fe) = -∷ move p sqs fe
move p (p′ ∷ sqs) fe = p′ ∷ move p sqs fe
Notice that this function gives us a SquareVec with exactly one empty square filled. This function couldn't have filled more than one or no empty squares at all!
We walk down the vector looking for an empty square; once we find it, the Fin argument tells us whether it's the square we want to fill in. If it's zero, we fill in the player; if it isn't, we continue searching the rest of the vector but with a smaller number.
Now, the game representation. Thanks to the extra work we did earlier, we can simplify the Game data type. The move-p constructor just tells us where the move happened and that's it! I got rid of the Player index for simplicity; but it would work just fine with it.
data Game : ∀ {e} → SquareVec 9 e → Set where
start : Game empty
move-p : ∀ {e} {gs} p (fe : Fin (suc e)) → Game gs → Game (move p gs fe)
Oh, what's empty? It's shortcut for your - ∷ - ∷ ...:
empty : ∀ {n} → SquareVec n n
empty {zero} = []
empty {suc _} = -∷ empty
Now, the states. I separated the states into a state of a possibly running game and a state of an ended game. Again, you can use your original GameCondition:
data State : Set where
win : Player → State
draw : State
going : State
data FinalState : Set where
win : Player → FinalState
draw : FinalState
For the following code, we'll need these imports:
open import Data.Empty
open import Data.Product
open import Relation.Binary.PropositionalEquality
And a function to determine the game state. Fill in with your actual implementation; this one just lets players play until the board is completly full.
-- Dummy implementation.
state : ∀ {e} {gs : SquareVec 9 e} → Game gs → State
state {zero} gs = draw
state {suc _} gs = going
Next, we need to prove that the State cannot be going when there are no empty squares:
zero-no-going : ∀ {gs : SquareVec 9 0} (g : Game gs) → state g ≢ going
zero-no-going g ()
Again, this is the proof for the dummy state, the proof for your actual implementation will be very different.
Now, we have all the tools we need to implement gameMaster. Firstly, we'll have to decide what its type is. Much like your version, we'll take two functions that represent the AI, one for o and other for x. Then we'll take the game state and produce FinalState. In this version, I'm actually returning the final board so we can see how the game progressed.
Now, the AI functions will return just the turn they want to make instead of returning whole new game state. This is easier to work with.
Brace yourself, here's the type signature I conjured up:
AI : Set
AI = ∀ {e} {sqv : SquareVec 9 (suc e)} → Game sqv → Fin (suc e)
gameMaster : ∀ {e} {sqv : SquareVec 9 e} (sp : Player)
(x-move o-move : AI) → Game sqv →
FinalState × (Σ[ e′ ∈ ℕ ] Σ[ sqv′ ∈ SquareVec 9 e′ ] Game sqv′)
Notice that the AI functions take a game state with at least one empty square and return a move. Now for the implementation.
gameMaster sp xm om g with state g
... | win p = win p , _ , _ , g
... | draw = draw , _ , _ , g
... | going = ?
So, if the current state is win or draw, we'll return the corresponding FinalState and the current board. Now, we have to deal with the going case. We'll pattern match on e (the number of empty squares) to figure out whether the game is at the end or not:
gameMaster {zero} sp xm om g | going = ?
gameMaster {suc e} x xm om g | going = ?
gameMaster {suc e} o xm om g | going = ?
The zero case cannot happen, we proved earlier that state cannot return going when the number of empty squares is zero. How to apply that proof here?
We have pattern matched on state g and we now know that state g ≡ going; but sadly Agda already forgot this information. This is what Dominique Devriese was hinting at: the inspect machinery allows us to retain the proof!
Instead of pattern matching on just state g, we'll also pattern matching on inspect state g:
gameMaster sp xm om g with state g | inspect state g
... | win p | _ = win p , _ , _ , g
... | draw | _ = draw , _ , _ , g
gameMaster {zero} sp xm om g | going | [ pf ] = ?
gameMaster {suc e} x xm om g | going | _ = ?
gameMaster {suc e} o xm om g | going | _ = ?
pf is now the proof that state g ≡ going, which we can feed to zero-no-going:
gameMaster {zero} sp xm om g | going | [ pf ]
= ⊥-elim (zero-no-going g pf)
The other two cases are easy: we just apply the AI function and recursively apply gameMaster to the result:
gameMaster {suc e} x xm om g | going | _
= gameMaster o xm om (move-p x (xm g) g)
gameMaster {suc e} o xm om g | going | _
= gameMaster x xm om (move-p o (om g) g)
I wrote some dumb AIs, the first one fills the first available empty square; the second one fills the last one.
player-lowest : AI
player-lowest _ = zero
max : ∀ {e} → Fin (suc e)
max {zero} = zero
max {suc e} = suc max
player-highest : AI
player-highest _ = max
Now, let's match player-lowest against player-lowest! In the Emacs, type C-c C-n gameMaster x player-lowest player-lowest start <RET>:
draw ,
0 ,
x ∷ (o ∷ (x ∷ (o ∷ (x ∷ (o ∷ (x ∷ (o ∷ (x ∷ [])))))))) ,
move-p x zero
(move-p o zero
(move-p x zero
(move-p o zero
(move-p x zero
(move-p o zero
(move-p x zero
(move-p o zero
(move-p x zero start))))))))
We can see that all squares are filled and they alternate between x and o. Matching player-lowest with player-highest gives us:
draw ,
0 ,
x ∷ (x ∷ (x ∷ (x ∷ (x ∷ (o ∷ (o ∷ (o ∷ (o ∷ [])))))))) ,
move-p x zero
(move-p o (suc zero)
(move-p x zero
(move-p o (suc (suc (suc zero)))
(move-p x zero
(move-p o (suc (suc (suc (suc (suc zero)))))
(move-p x zero
(move-p o (suc (suc (suc (suc (suc (suc (suc zero)))))))
(move-p x zero start))))))))
If you really want to work with the proofs, then I suggest the following representation of Fin:
Fin₂ : ℕ → Set
Fin₂ n = ∃ λ m → m < n
fin⟶fin₂ : ∀ {n} → Fin n → Fin₂ n
fin⟶fin₂ zero = zero , s≤s z≤n
fin⟶fin₂ (suc n) = map suc s≤s (fin⟶fin₂ n)
fin₂⟶fin : ∀ {n} → Fin₂ n → Fin n
fin₂⟶fin {zero} (_ , ())
fin₂⟶fin {suc _} (zero , _) = zero
fin₂⟶fin {suc _} (suc _ , s≤s p) = suc (fin₂⟶fin (_ , p))
Not strictly related to the question, but inspect uses rather interesting trick which might be worth mentioning. To understand this trick, we'll have to take a look at how with works.
When you use with on an expression expr, Agda goes through the types of all arguments and replaces any occurence of expr with a fresh variable, let's call it w. For example:
test : (n : ℕ) → Vec ℕ (n + 0) → ℕ
test n v = ?
Here, the type of v is Vec ℕ (n + 0), as you would expect.
test : (n : ℕ) → Vec ℕ (n + 0) → ℕ
test n v with n + 0
... | w = ?
However, once we abstract over n + 0, the type of v suddenly changes to Vec ℕ w. If you later want to use something which contains n + 0 in its type, the substitution won't take place again - it's a one time deal.
In the gameMaster function, we applied with to state g and pattern matched to find out it's going. By the time we use zero-no-going, state g and going are two separate things which have no relation as far as Agda is concerned.
How do we preserve this information? We somehow need to get state g ≡ state g and have the with replace only state g on either side - this would give us the needed state g ≡ going.
What the inspect does is that it hides the function application state g. We have to write a function hide in a way that Agda cannot see hide state g and state g are in fact the same thing.
One possible way to hide something is to use the fact that for any type A, A and ⊤ → A are isomorphic - that is, we can freely go from one representation to the other without losing any information.
However, we cannot use the ⊤ as defined in the standard library. In a moment I'll show why, but for now, we'll define a new type:
data Unit : Set where
unit : Unit
And what it means for a value to be hidden:
Hidden : Set → Set
Hidden A = Unit → A
We can easily reveal the hidden value by applying unit to it:
reveal : {A : Set} → Hidden A → A
reveal f = f unit
The last step we need to take is the hide function:
hide : {A : Set} {B : A → Set} →
((x : A) → B x) → ((x : A) → Hidden (B x))
hide f x unit = f x
Why wouldn't this work with ⊤? If you declare ⊤ as record, Agda can figure out on its own that tt is the only value. So, when faced with hide f x, Agda won't stop at the third argument (because it already knows how it must look like) and automatically reduce it to λ _ → f x. Data types defined with the data keyword don't have these special rules, so hide f x remains that way until someone reveals it and the type checker cannot see that there's a f x subexpression inside hide f x.
The rest is just arranging stuff so we can get the proof later:
data Reveal_is_ {A : Set} (x : Hidden A) (y : A) : Set where
[_] : (eq : reveal x ≡ y) → Reveal x is y
inspect : {A : Set} {B : A → Set}
(f : (x : A) → B x) (x : A) → Reveal (hide f x) is (f x)
inspect f x = [ refl ]
So, there you have it:
inspect state g : Reveal (hide state g) is (state g)
-- pattern match on (state g)
inspect state g : Reveal (hide state g) is going
When you then reveal hide state g, you'll get state g and finally the proof that state g ≡ going.
I think you are looking for an Agda technique known by the name "inspect" or "inspect on steroids". It allows you to obtain an equality proof for the knowledge learned from a with pattern match. I recommend you read the code in the following mail and try to understand how it works. Focus on how the function foo at the bottom needs to remember that "f x = z" and does so by with-matching on "inspect (hide f x)" together with "f x":
https://lists.chalmers.se/pipermail/agda/2011/003286.html
To use this in actual code, I recommend you import Relation.Binary.PropositionalEquality from the Agda standard library and use its version of inspect (which is superficially different from the code above). It has the following example code:
f x y with g x | inspect g x
f x y | c z | [ eq ] = ...
Note: "Inspect on steroids" is an updated version of an older approach at the inspect idiom.
I hope this helps...
I have a JPanel and a vector of JButtons and want to add each button to the panel.
The issue I'm having is that I have a variable btns that represents the vector of buttons, but the macro function just sees it as a symbol, not a vector. Is there a way to expand it somehow?
Here's the code:
(defmacro add_all [panel btns]
;; help?
)
(let [x 10, y 10
btns get_buttons] ;; just a vector of JButton objects
(doto (JPanel.)
(.setLayout (GridLayout. x y))
(add-all btns)))
I would like this to expand to:
(doto (JPanel.)
(.setLayout (GridLayout. x y))
(.add (btns 0))
(.add (btns 1))
;; etc
(.add (btns 99)))
There's no need for a macro (and indeed the problem as stated cannot be solved with a macro). Just write a function which operates on a panel and a seq of buttons:
(defn add-all [panel buttons]
(doseq [button buttons]
(.add panel button)))
I have another question about Wolfram Mathematica. Is there someone that knows how I can plot a graphic on the y axis?
I hope that the figure helps.
ParametricPlot[{5 Sin[y], y}, {y, -2 \[Pi], 2 \[Pi]},
Frame -> True, AxesLabel -> {"x", "y"}]
EDIT
None of the answers given thus far can work with Plot's Filling option. Plot's output contains a GraphicsComplex in that case (which, incidentally, breaks Mr.Wizard's replacements). To get the filling capability (it doesn't work for a standard plot without filling) you could use the following:
Plot[Sin[x], {x, 0, 2 \[Pi]}, Filling -> Axis] /. List[x_, y_] -> List[y, x]
Plot[{Sin[x], .5 Sin[2 x]}, {x, 0, 2 \[Pi]}, Filling -> {1 -> {2}}]
/. List[x_, y_] -> List[y, x]
You can flip the axes after plotting with Reverse:
g = Plot[Sin[x], {x, 0, 9}];
Show[g /. x_Line :> Reverse[x, 3], PlotRange -> Automatic]
With a minor change this works for plots using Filling as well:
g1 = Plot[{Sin[x], .5 Sin[2 x]}, {x, 0, 2 \[Pi]}];
g2 = Plot[{Sin[x], .5 Sin[2 x]}, {x, 0, 2 \[Pi]}, Filling -> {1 -> {2}}];
Show[# /. x_Line | x_GraphicsComplex :> x~Reverse~3,
PlotRange -> Automatic] & /# {g1, g2}
(It may be more robust to replace the RHS of :> with MapAt[#~Reverse~2 &, x, 1])
As a Function
Here is the form I recommend one use. It includes flipping of the original PlotRange rather than forcing PlotRange -> All:
axisFlip = # /. {
x_Line | x_GraphicsComplex :>
MapAt[#~Reverse~2 &, x, 1],
x : (PlotRange -> _) :>
x~Reverse~2 } &;
To be used like: axisFlip # g1 or axisFlip # {g1, g2}
A different effect can be had with Rotate:
Show[g /. x_Line :> Rotate[x, Pi/2, {0,0}], PlotRange -> Automatic]
One possibility is to use a ParametricPlot like this:
ParametricPlot[
{-y*Exp[-y^2], y}, {y, -0.3, 4},
PlotRange -> {{-2, 2}, All},
AxesLabel -> {"x", "y"},
AspectRatio -> 1/4
]
Just for fun:
ContourPlot is another alternative.
Using Thies function:
ContourPlot[-y*Exp[-y^2/2] - x == 0,
{x, -2, 2}, {y, 0, 4},
Axes -> True, Frame -> None]
RegionPlot is another
RegionPlot[-y*Exp[-y^2/2] > x,
{x, -2.1, 2.1}, {y, -.1, 4.1},
Axes -> True, Frame -> None, PlotStyle -> White,
PlotRange -> {{-2, 2}, {0, 4}}]
And finally, a REALLY convoluted way using ListCurvePathPlot and Solve:
Off[Solve::ifun, FindMaxValue::fmgz];
ListCurvePathPlot[
Join ##
Table[
{x, y} /. Solve[-y*Exp[-y^2/2] == x, y],
{x, FindMaxValue[-y*Exp[-y^2/2], y], 0, .01}],
PlotRange -> {{-2, 2}, {0, 4}}]
On[Solve::ifun, FindMaxValue::fmgz];
Off Topic
Answer to Sjoerd's None of the answers given thus far can work with Plot's Filling option.
Reply: Not necessary
f={.5 Sin[2 y],Sin[y]};
RegionPlot[Min#f<=x<=Max#f,{x,-1,1},{y,-0.1,2.1 Pi},
Axes->True,Frame->None,
PlotRange->{{-2,2},{0,2 Pi}},
PlotPoints->500]
Depending on how you wanted the axis labels to show, you could just wrap the code for the original Plot in the Rotate function.