Can someone please help me understand predicates using the following example:
sig Light{}
sig LightState { color: Light -> one Color}
sig Junction {lights: set Light}
fun redLigths(s:LightState) : set Light{ s.color.Red}
pred mostlyRed(s:LightState, j:Junction){
lone j.lights - redLigths(s)
}
I have the below questions about the above code:
1) What happens if the above predicate is true?
2) What happends if it is false?
3) Can someone show me a bit of alloy code that uses the above code and clarifies the meaning of predicates through the code.
I am just trying to understand how do we use the above predicate.
Nothing "happens" until you place a call to a predicate or a function in a command to find an example or counterexample.
First, use the right terminology, nothing 'happens' when a predicate is true; it's the more like the other way around, an instance (an allocation of atoms to sets) satisfies (or doesn't) some condition, making the predicate true (or false).
Also, your model is incomplete, because there is no sig declaration for Color (which should include an attribute called Red).
I assume you want to model a world with crossroads containing traffic lights, if so I would use the following model:
abstract sig Color {}
one sig Red,Yellow,Green extends Color {}
sig Light {
color: Color
}
sig Junction {
lights : set Light
}
// This is just for realism, make sure each light belongs to exactly one junction
fact {
Light = Junction.lights
no x,y:Junction | x!=y and some x.lights & y.lights
}
fun count[j:Junction, c:Color] : Int {
#{x:Light | x in j.lights and x.color=c}
}
pred mostly[j:Junction, c:Color] {
no cc:Color | cc!=c and count[j,cc]>=count[j,c]
}
run{
some j:Junction | mostly[j,Red]
} for 10 Light, 2 Junction, 10 int
Looking at the above, i'm using the # operator to count the number of atoms in a set, and I'm specifying a bitwidth of 10 to integers just so that I don't stumble into an overflow when using the # operator for large sets.
When you execute this, you will get an instance with at least one junction that has mostly red lights, it will be marked as $j in the visualizer.
Hope this helps.
sig Light{}
sig LightState { color: Light -> one Color}
sig Junction {lights: set Light}
fun redLigths(s:LightState) : set Light{ s.color.Red}
pred mostlyRed(s:LightState, j:Junction){
lone j.lights - redLigths(s)
}
What the predicate simply means in the example you gave is;
The difference between the set A, in this case the relation (j.lights) and another set say B, returned from the function redligths, of which the Predicate will always constraint the constraint analyser to return only red light when you run the Predicate "mostlyRed".
And note that the multiplicity "lone" you added to the predicate's body only evaluate after the difference between the set A and B (as I assumed) has been evaluated, to make sure that at most one atom of red is returned. I hope my explanation was helpful. I will welcome positive criticism. Thanks
Related
Here are the signatures :
abstract sig Color{}
lone sig Red, Blue, Yellow, Green extends Color{}
abstract sig Vertex{
couleur: Color
}
abstract sig Digraph{
vertices: set Vertex,
edges: set(Vertex -> Vertex)
}
fact{
vertices.couleur != edges.couleur
}
I get an error saying that I can't use "!=" between 2 expressions that aren't the same arity. I get why, but I don't know how I can solve this.
What I want to do is, forbidding the two vertices color to be the same in an edge. Any ideas ?
The answer is very simple: the expression vertices.couleur != edges.couleur does not typecheck since vertices and edges, and thus also the operands of !=, are of different arity. (Essentially, you are trying to compare a set of Color to a set of (Color -> Vertex).)
As an example, if you take the image of the edges relation (by projecting it onto the universal set), you will not get the error:
fact {
vertices.couleur != edges.univ.couleur
}
(For more info about the basic operators in Alloy, it would be useful to check the tutorial and/or the Alloy book.)
The following model produces instances with exactly 2 address relations when the number of Books is limited to 1, however, if more Books are allowed it will create instances with 0-3 address relations. My misunderstanding of how Alloy works?
sig Name{}
sig Addr{}
sig Book { addr: Name -> lone Addr }
pred show(b:Book) { #b.addr = 2 }
// nr. of address relations in every Book should be 2
run show for 3 but 2 Book
// works as expected with 1 Book
Each instance of show should include one Book, labeled as being the b of show, which has two address pairs. But show does not say that every book must have two address pairs, only that at least one must have two address pairs.
[Postscript]
When you ask Alloy to show you an instance of a predicate, for example by the command run show, then Alloy should show you an instance: that is (quoting section 5.2.1 of Software abstractions, which you already have open) "an assignment of values to the variables of the constraint for which the constraint evaluates to true." In any given universe, there may be many other possible assignments of values to the variables for which the constraint evaluates to false; the existence of such possible non-suitable assignments is unavoidable in any universe with more than one atom.
Informally, we can think of a run command for a predicate P with arguments X, Y, Z as requesting that Alloy show us universes which satisfy the expression
some X, Y, Z : univ | P[X, Y, Z]
The run command does not amount to the expression
all X, Y, Z : univ | P[X, Y, Z]
If you want to see only universes in which every book has two pairs in its addr relation, then say so:
pred all_books_have_2 { all b : Book | #b.addr = 2 }
I think it's better that run have implicit existential quantification, rather than implicit universal quantification. One way to see why is to imagine a model that defines trees, such as:
sig Node { parent : lone Node }
fact parent_acyclic { no n : Node | n in n.^parent }
Suppose we get tired of seeing universes in which every tree is trivial and contains a single node. I'd like to be able to define a predicate that guarantees at least one tree with depth greater than 1, by writing
pred nontrivial[n : Node]{ some n.parent }
Given the constraint that trees be acyclic, there can never be a non-empty universe in which the predicate nontrivial holds for all nodes. So if run and pred had the semantics you have been supposing, we could not use nontrivial to find universes containing non-trivial trees.
I hope this helps.
For an university project I'm trying to write the chinese game of Go (http://en.wikipedia.org/wiki/Go_%28game%29) in Alloy. (i'm using the 4.2 version)
I managed to write the base structure. Go's played on a board 9 x 9 wide, but i'm using a smaller set of 3 x 3 for checking it faster.
The board is made of crosses which can either be empty or occupied by black or white stones.
abstract sig Colour {}
one sig White, Black, Empty extends Colour {}
abstract sig Cross {
Status: one Colour,
near: some Cross,
group: lone Group
}
one sig C11, C12, C13,
C21, C22, C23,
C31, C32, C33 extends Cross {}
sig Group {
stones : some Cross,
freedom : some Cross
}
pred closeStones {
near=
C11->C12 + C11->C21 +
C12->C11 + C12->C13 + C12->C22 +
C13->C12 + C13->C23 +
C21->C22 + C21->C11 + C21->C31 +
C22->C21 + C22->C23 + C22->C12 + C22->C32 +
C23->C22 + C23->C13 + C23->C33 +
C31->C32 + C31->C21 +
C32->C31 + C32->C33 + C32->C22 +
C33->C32 + C33->C23
}
fact stones2 {
all g : Group |
all c : Cross |
(c.group=g) iff c in g.stones
}
fact noGroup{
all c : Cross | (c.Status=Empty) iff c.group=none
}
fact groupNearStones {
all disj c,d : Cross |
((d in c.near) and c.Status=d.Status)
iff
d.group=c.group
}
The problem is: following Go rules, every stones must be considered as part of a group. This group is made of all the adiacent stones with the same colour.
My fact "groupNearStones" should be sufficient to describe that condition, but this way I can't get groups made of more of 3 stones.
I've tried rewriting it in different ways, but either the analizer says it found "0 variables" or it groups up all the stones with the same status, regardless of wheter they're near each other or not.
If you could give me any insight I will be grateful, since i'm breaking my head on this simple matter for days.
Ask yourself two questions.
First: in Go, what constitutes a group? You say yourself: it is a set of adjacent stones with the same color. Not that every stone in the group must be adjacent to every other; it suffices for every stone to be adjacent to another stone in the group.
So from a formal point of view: given a stone S, the set of stones in the group as S is the transitive closure of the stones reachable through the relation same_color_and_adjacent, or S.*same_color_and_adjacent.
Second: what constitutes being the same color and adjacent? I think you can define this easily, with what you have.
On a side issue; you may find it easier to scale the model to arbitrary sizes of boards if you reify the notion of rows and columns.
I hope this helps.
[Addendum:] Apparently it doesn't help enough. I'll try to be a bit more explicit, but I want the full solution to come from you and not from me.
Note that the point of defining a relation like same_color_and_adjacent is not to eliminate the formulation of facts or predicates in your model, but to make them easier to write and to write correctly. It's not magic.
Consider first a reformulation of your fact groupNearStones in terms of a single relation that holds for pairs of stones which are adjacent and have the same color. The relation can be defined by modifying your declaration for Cross:
abstract sig Cross {
Status: one Colour,
near: some Cross,
group: lone Group,
near_and_similar : some Cross
}{
near_and_similar = near & { c : Cross | c.#Status = Status}
}
Now your existing fact can be written as:
fact groupNearStones2 {
all disj c,d : Cross |
d in c.near_and_similar
iff
d.group=c.group
}
Actually, I would write both versions of groupNearStones as predicates, not facts. That would allow you to check that the new formulation is really equivalent to the old one by running a check like:
pred GNS_equal_GNS2 {
groupNearStones iff groupNearStones2
}
(I have not run such a check; I'm being a little lazy.)
Now, let us consider the problems you mention:
You never get groups containing more than three stones. Actually, given the formulation of groupNearStones, I'm surprised you get groups with more than two. Consider what groupNearStones says: any two stones in a group are adjacent and have the same color. Draw a board on a piece of paper and draw a group of five stones. Now ask whether such a group satisfies the fact groupNearStones. Say the group is C11, C12, C13, C21, C22. What does groupNearStones say about the pair C21, C13?
Do you see the problem? Are the relations near and 'close enough to be in the same group' really the same? If they are not the same, are they related?
Hint: think about transitive closure.
You never get groups containing a single stone.
How surprising is this, given that groupNearStones says that c.group = d.group only if c and d are disjoint? If you never get single-stone groups, then every stone that should be a single-stone group is not classed as being in any group at all, since such a stone must not satisfy the expression s.group = s.group.
Do you see the problem?
Hint: think about reflexive transitive closure.
I'm curious as to when evaluation sets in, apparently certain operators are rather transformed into clauses than evaluated:
abstract sig Element {}
one sig A,B,C extend Element {}
one sig Test {
test: set Element
}
pred Test1 { Test.test = A+B }
pred Test2 { Test.test = Element-C }
and run it for Test1 and Test2 respectively will give different number of vars/clauses, specifically:
Test1: 0 vars, 0 primary vars, 0 clauses
Test2: 5 vars, 3 primary vars, 4 clauses
So although Element is abstract and all its members and their cardinalities are known, the difference seems not to be computed in advance, while the sum is. I don't want to make any assumptions, so I'm interested in why that is. Is the + operator special?
To give some context, I tried to limit the domain of a relation and found, that using only + seems to be more efficient, even when the sets are completely known in advance.
To give some context, I tried to limit the domain of a relation and found, that using only + seems to be more efficient, even when the sets are completely known in advance.
That is pretty much the right conclusion. The reason is the fact that the Alloy Analyzer tries to infer relation bounds from certain Alloy idioms. It uses a conservative approximation that is always sound for set union and product, but not for set difference. That's why for Test1 in the example above the Alloy Analyzer infers a fixed bound for the test relation (this/Test.test: [[[A$0], [B$0]]]) so no solver needs to be invoked; for Test2, the bound for the test relation cannot be shrunk so is set to be the most permissive (this/Test.test: [[], [[A$0], [B$0], [C$0]]]), thus a solver needs to be invoked to find a solution satisfying the constraints given the bounds.
i need to model hydrocarbon structure using alloy
basically i need to design alkane, alkene and alkyne groups
i have created following signatures(alkene example)
sig Hydrogen{}
sig Carbon{}
sig alkenegrp{
c:one Carbon,
h:set Hydrogen,
doublebond:lone alkenegrp
}
sig alkene{
unit : set alkenegrp
}
fact{
all a:alkenegrp|a not in a.doublebond.*doublebond
all a:alkenegrp|#a.h=mul[#(a.c),2]
}
pred show_alkene{
#alkene>1
}
run show_alkene
this works from alkene but when ever i try to design the same for alkane or alkyne by changing the fact like all a:alkynegrp|#a.h=minus[mul[#(a.c),2],2] it doesnt work.
Can anyone suggest how do i implement it?
My problem statement is
In Organic chemistry saturated hydrocarbons are organic compound composed entirely of single
bonds and are saturated with hydrogen. The general formula for saturated hydrocarbons is
CnH2n+2(assuming non-cyclic structures). Also called as alkanes. Unsaturated hydrocarbons
have one or more double or triple bonds between carbon atoms. Those with double bond are
called alkenes. Those with one double bond have the formula CnH2n (assuming non-cyclic
structures). Those containing triple bonds are called alkynes, with general formula CnH2n-2.
Model hydrocarbons and give predicates to generate instances of alkane, alkene and alkyne.
We have tried as:
sig Hydrogen{}
sig Carbon{}
sig alkane{
c:one Carbon,
h:set Hydrogen,
n:lone alkane
}
fact{
//(#h)=add [mul[(#c),2],2]
//all a:alkane|a not in a.*n
all a:alkane|#a.h=mul[#(a.c),2]
}
pred show_alkane(){}
run show_alkan
e
General formula for alkane is CnH2n+2,for multiplication we can use mul inbuilt function but we can not write for addtion as we have to do CnH2n+2.What should we write so that it can work for alkane
I understand alkanes, alkenes, and alkynes a little better now, but I still don't understand why you think your Alloy model doesn't work.
To express the CnH2n-2 constraint, you can certainly write what you suggested
all a:alkynegrp |
#a.h = minus[mul[#(a.c), 2], 2]
The problem is only that in your alkane sig declaration you said c: one Carbon, which is going to fix the number of carbon atoms to exactly 1, so minus[mul[#(a.c), 2], 2] is always going to evaluate to exactly 0. I assume you want to alloy for any number of carbons (since Cn) so you should change it from c: one Carbon to c: set Carbon. If you then run the show_alkane predicate, you should get some instances where the number of carbons is greater than 1 and thus, the number of hydrogens is greater than 0.
Also, for the alkane formula
all a:alkynegrp |
#a.h = plus[mul[#(a.c), 2], 2]
the default scope of 3 will not suffice, because you will need at least 4 atoms of hydrogen when a.c is non-empty, but you can fix that by explicitly giving a scope
run show_alkane for 8
If this wasn't the problem you were talking about, please be more specific about why you think "it doesn't work", i.e., what is it that you expect Alloy to do and what is it that Alloy actually does.