# -*- coding: utf-8 -*-
#+TITLE: Constructing and transforming formulas
#+DESCRIPTION: Code example for constructing and transforming formulas in Spot
#+INCLUDE: setup.org
#+HTML_LINK_UP: tut.html
#+PROPERTY: header-args:python :results output :exports both
#+PROPERTY: header-args:C+++ :results verbatim :exports both

This page explains how to build formulas and how to iterate over their
syntax trees.

We will first describe how to build a formula from scratch, by using
the constructors associated to each operators, and show the basic
accessor methods for formulas.  We will do that for C++ first, and
then Python.  Once these basics are covered, we will show examples for
traversing and transforming formulas (again in C++ then Python).

* Constructing formulas

** C++

The =spot::formula= class contains static methods that act as
constructors for each supported operator.

The Boolean constants true and false are returned by =formula::tt()=
and =formula:ff()=.  Atomic propositions can be built with
=formula::ap("name")=.  Unary and binary operators use a
straightforward syntax like =formula::F(arg)= or =formula::U(first,
second)=, while n-ary operators take an initializer list as argument
as in =formula::And({arg1, arg2, arg3})=.

Here is the list of supported operators:

#+BEGIN_SRC C++ :exports code
  // atomic proposition
  formula::ap(string)
  // constants
  formula::ff();
  formula::tt();
  formula::eword();               // empty word (for regular expressions)
  // unary operators
  formula::Not(arg);
  formula::X(arg);
  formula::X(arg, min, max);     // X[min..max] arg
  formula::F(arg);
  formula::F(arg, min, max);     // F[min..max] arg
  formula::G(arg);
  formula::G(arg, min, max);     // G[min..max] arg
  formula::Closure(arg);
  formula::NegClosure(arg);
  formula::first_match(arg);      // SVA's first match operator
  // binary operators
  formula::Xor(left, right);
  formula::Implies(left, right);
  formula::Equiv(left, right);
  formula::U(left, right);        // (strong) until
  formula::R(left, right);        // (weak) release
  formula::W(left, right);        // weak until
  formula::M(left, right);        // strong release
  formula::EConcat(left, right);  // Seq
  formula::UConcat(left, right);  // Triggers
  // n-ary operators
  formula::Or({args,...});        // omega-rational Or
  formula::OrRat({args,...});     // rational Or (for regular expressions)
  formula::And({args,...});       // omega-rational And
  formula::AndRat({args,...});    // rational And (for regular expressions)
  formula::AndNLM({args,...});    // non-length-matching rational And (for r.e.)
  formula::Concat({args,...});    // concatenation (for regular expressions)
  formula::Fusion({args,...});    // concatenation (for regular expressions)
  // star-like operators
  formula::Star(arg, min, max);   // Star (for a Kleene star, set min=0 and omit max)
  formula::FStar(arg, min, max);  // Fusion Star
  // syntactic sugar built on top of previous operators
  formula::sugar_goto(arg, min, max); // arg[->min..max]
  formula::sugar_equal(arg, min, max); // arg[=min..max]
  formula::sugar_delay(left, right, min, max); // left ##[min..max] right
#+END_SRC

These functions implement some very limited type of automatic
simplifications called /trivial identities/.  For instance
=formula::F(formula::X(formula::tt()))= will return the same formula
as =formula::tt()=.  These simplifications are those that involve the
true and false constants, impotence (=F(F(e))=F(e)=), involutions
(=Not(Not(e))=e=), associativity
(=And({And({e1,e2},e3})=And({e1,e2,e3})=).  See [[https://spot.lrde.epita.fr/tl.pdf][tl.pdf]] for a list of
these /trivial identities/.

In addition, the arguments of commutative operators
(e.g. =Xor(e1,e2)=Xor(e2,e1)=) are always reordered.  The order used
always put the Boolean subformulas before the temporal subformulas,
sorts the atomic propositions in alphabetic order, and otherwise order
subformulas by their unique identifier (a constant incremented each
time a new subformula is created).  This reordering is useful to favor
sharing of subformulas, but also helps algorithms that perform
memoization.

Building a formula using these operators is quite straightforward.
The second part of the following example shows how to print some
detail of the top-level operator in the formula.

#+BEGIN_SRC C++
  #include <iostream>
  #include <spot/tl/formula.hh>
  #include <spot/tl/print.hh>

  int main()
  {
    // Build FGa -> (GFb & GFc)
    spot::formula fga = spot::formula::F(spot::formula::G(spot::formula::ap("a")));
    spot::formula gfb = spot::formula::G(spot::formula::F(spot::formula::ap("b")));
    spot::formula gfc = spot::formula::G(spot::formula::F(spot::formula::ap("c")));
    spot::formula f = spot::formula::Implies(fga, spot::formula::And({gfb, gfc}));

    std::cout << f << '\n';

    // kindstr() prints the name of the operator
    // size() return the number of operands of the operators
    std::cout << f.kindstr() << ", " << f.size() << " children\n";
    // operator[] accesses each operand
    std::cout << "left: " << f[0] << ", right: " << f[1] << '\n';
    // you can also iterate over all operands using a for loop
    for (auto child: f)
      std::cout << "  * " << child << '\n';
    // the type of the operator can be accessed with kind(), which
    // return an element of the spot::op enum.
    std::cout << f[1][0]
              << (f[1][0].kind() == spot::op::F ? " is F\n" : " is not F\n");
    // however because writing f.kind() == spot::op::XXX is quite common, there
    // is also a is() shortcut:
    std::cout << f[1][1]
              << (f[1][1].is(spot::op::G) ? " is G\n" : " is not G\n");
    return 0;
  }
#+END_SRC

#+RESULTS:
: FGa -> (GFb & GFc)
: Implies, 2 children
: left: FGa, right: GFb & GFc
:   * FGa
:   * GFb & GFc
: GFb is not F
: GFc is G

** Python

The Python equivalent is similar:

#+BEGIN_SRC python
  import spot

  # Build FGa -> (GFb & GFc)
  fga = spot.formula.F(spot.formula.G(spot.formula.ap("a")))
  gfb = spot.formula.G(spot.formula.F(spot.formula.ap("b")));
  gfc = spot.formula.G(spot.formula.F(spot.formula.ap("c")));
  f = spot.formula.Implies(fga, spot.formula.And([gfb, gfc]));

  print(f)

  # kindstr() prints the name of the operator
  # size() return the number of operands of the operators
  print("{}, {} children".format(f.kindstr(), f.size()))
  # [] accesses each operand
  print("left: {f[0]}, right: {f[1]}".format(f=f))
  # you can also iterate over all operands using a for loop
  for child in f:
     print("  *", child)
  # the type of the operator can be accessed with kind(), which returns
  # an op_XXX constant (corresponding the the spot::op enum of C++)
  print(f[1][0], "is F" if f[1][0].kind() == spot.op_F else "is not F")
  # "is" is keyword in Python, the so shortcut is called _is:
  print(f[1][1], "is G" if f[1][1]._is(spot.op_G) else "is not G")
#+END_SRC

#+RESULTS:
: FGa -> (GFb & GFc)
: Implies, 2 children
: left: FGa, right: GFb & GFc
:   * FGa
:   * GFb & GFc
: GFb is not F
: GFc is G

* Transforming formulas

** C++

In Spot, Formula objects are immutable: this allows identical subtrees
to be shared among multiple formulas.  Algorithms that "transform"
formulas (for instance the [[file:tut02.org][relabeling function]]) actually recursively
traverse the input formula to construct the output formula.

Using the operators described in the previous section is enough to
write algorithms on formulas.  However there are two special methods
that makes it a lot easier: =traverse= and =map=.

=traverse= takes a function =fun=, and applies it to each subformulas
of a given formula, including that starting formula itself.  The
formula is explored in a DFS fashion (without skipping subformula that
appear twice).  The children of a formula are explored only if =fun=
returns =false=.  If =fun= returns =true=, that indicates to stop the
recursion.

In the following we use a lambda function to count the number of =G=
in the formula.  We also print each subformula to show the recursion,
and stop the recursion as soon as we encounter a subformula without
sugar (the =is_sugar_free_ltl()= method is a constant-time operation
that tells whether a formula contains a =F= or =G= operator) to save
time time by not exploring further.

#+NAME: gcount_cpp
#+BEGIN_SRC C++
  #include <iostream>
  #include <spot/tl/formula.hh>
  #include <spot/tl/print.hh>
  #include <spot/tl/parse.hh>

  int main()
  {
    spot::formula f = spot::parse_formula("FGa -> (GFb & GF(c & b & d))");

    int gcount = 0;
    f.traverse([&gcount](spot::formula f)
               {
                 std::cout << f << '\n';
                 if (f.is(spot::op::G))
                   ++gcount;
                 return f.is_sugar_free_ltl();
               });
    std::cout << "=== " << gcount << " G seen ===\n";
    return 0;
  }
#+END_SRC

#+RESULTS: gcount_cpp
#+begin_example
FGa -> (GFb & GF(b & c & d))
FGa
Ga
a
GFb & GF(b & c & d)
GFb
Fb
b
GF(b & c & d)
F(b & c & d)
b & c & d
=== 3 G seen ===
#+end_example

The other useful operation is =map=.  This also takes a functional
argument, but that function should input a formula and output a
replacement formula.  =f.map(fun)= applies =fun= to all children of
=f=, and assemble the result under the same top-level operator as =f=.

Here is a demonstration of how to exchange all =F= and =G= operators
in a formula:

#+NAME: xchg_fg_cpp
#+BEGIN_SRC C++
  #include <iostream>
  #include <spot/tl/formula.hh>
  #include <spot/tl/print.hh>
  #include <spot/tl/parse.hh>

  spot::formula xchg_fg(spot::formula in)
  {
     if (in.is(spot::op::F))
       return spot::formula::G(xchg_fg(in[0]));
     if (in.is(spot::op::G))
       return spot::formula::F(xchg_fg(in[0]));
     // No need to transform subformulas without F or G
     if (in.is_sugar_free_ltl())
       return in;
     // Apply xchg_fg recursively on any other operator's children
     return in.map(xchg_fg);
  }

  int main()
  {
    spot::formula f = spot::parse_formula("FGa -> (GFb & GF(c & b & d))");
    std::cout << "before: " << f << '\n';
    std::cout << "after:  " << xchg_fg(f) << '\n';
    return 0;
  }
#+END_SRC

#+RESULTS: xchg_fg_cpp
: before: FGa -> (GFb & GF(b & c & d))
: after:  GFa -> (FGb & FG(b & c & d))


*** Additional tricks about =map= and =traverse= in C++

As seen above, the first argument of =map()= and =traverse()= is a
function =fun()= (or actually any object that as an =operator()=) that
will be applied to subformulas.  If additional arguments are passed to
=map()= or =traverse()=, those will be passed on to =fun()= after the
formula.

For instance instead of having a lambda capturing the [[gcount_cpp][=gcount=
variable in the first example]], we could pass a reference to this
variable:

#+BEGIN_SRC C++
  #include <iostream>
  #include <spot/tl/formula.hh>
  #include <spot/tl/print.hh>
  #include <spot/tl/parse.hh>

  int main()
  {
    spot::formula f = spot::parse_formula("FGa -> (GFb & GF(c & b & d))");

    int gcount = 0;
    f.traverse([](spot::formula f, int& count)
               {
                 if (f.is(spot::op::G))
                   ++count;
                 return f.is_sugar_free_ltl();
               }, gcount);
    std::cout << "=== " << gcount << " G seen ===\n";
    return 0;
  }
#+END_SRC

#+RESULTS:
: === 3 G seen ===

(Here we have removed the print statement inside the lambda to focus
more on how =gcount= get passed as the =&count= reference.  Here there
is no real advantage to passing such reference by argument instead of
capturing them in the lambda.

The possibility to pass additional arguments is however more useful in
the case of =map=.  Let's write a variant of our [[xchg_fg_cpp][=xchg_fg()= example]]
that counts the number of exchanges performed.  First, we do it
without lambda:

#+BEGIN_SRC C++
  #include <iostream>
  #include <spot/tl/formula.hh>
  #include <spot/tl/print.hh>
  #include <spot/tl/parse.hh>

  spot::formula xchg_fg(spot::formula in, int& count)
  {
     if (in.is(spot::op::F, spot::op::G))
       ++count;
     if (in.is(spot::op::F))
       return spot::formula::G(xchg_fg(in[0], count));
     if (in.is(spot::op::G))
       return spot::formula::F(xchg_fg(in[0], count));
     // No need to transform subformulas without F or G
     if (in.is_sugar_free_ltl())
       return in;
     // Apply xchg_fg recursively on any other operator's children
     return in.map(xchg_fg, count);
  }

  int main()
  {
    spot::formula f = spot::parse_formula("FGa -> (GFb & GF(c & b & d))");
    std::cout << "before: " << f << '\n';
    int count = 0;
    std::cout << "after:  " << xchg_fg(f, count) << '\n';
    std::cout << "exchanges:  " << count << '\n';
    return 0;
  }
#+END_SRC

#+RESULTS:
: before: FGa -> (GFb & GF(b & c & d))
: after:  GFa -> (FGb & FG(b & c & d))
: exchanges:  6

Now let's pretend that we want to define =xchg_fg= as a lambda, and
=count= to by captured by reference.  In order to call pass the lambda
recursively to =map=, the lambda needs to know its address.
Unfortunately, if the lambda is stored with type =auto=, it cannot
capture itself.  A solution is to use =std::function= but that has a
large penalty cost.  We can work around that by assuming that that
address will be passed as an argument (=self=) to the lambda:

#+BEGIN_SRC C++
  #include <iostream>
  #include <spot/tl/formula.hh>
  #include <spot/tl/print.hh>
  #include <spot/tl/parse.hh>

  int main()
  {
    spot::formula f = spot::parse_formula("FGa -> (GFb & GF(c & b & d))");
    std::cout << "before: " << f << '\n';

    int count = 0;
    auto xchg_fg = [&count](spot::formula in, auto&& self) -> spot::formula
    {
      if (in.is(spot::op::F, spot::op::G))
        ++count;
      if (in.is(spot::op::F))
        return spot::formula::G(self(in[0], self));
      if (in.is(spot::op::G))
        return spot::formula::F(self(in[0], self));
      // No need to transform subformulas without F or G
      if (in.is_sugar_free_ltl())
        return in;
      // Apply xchg_fg recursively on any other operator's children
      return in.map(self, self);
    };
    std::cout << "after:  " << xchg_fg(f, xchg_fg) << '\n';
    std::cout << "exchanges:  " << count << '\n';
    return 0;
  }
#+END_SRC

#+RESULTS:
: before: FGa -> (GFb & GF(b & c & d))
: after:  GFa -> (FGb & FG(b & c & d))
: exchanges:  6


** Python

The Python version of the above two examples uses a very similar
syntax.  Python only supports a very limited form of lambda
expressions, so we have to write a standard function instead:

#+BEGIN_SRC python
  import spot

  gcount = 0
  def countg(f):
      global gcount
      print(f)
      if f._is(spot.op_G):
          gcount += 1
      return f.is_sugar_free_ltl()

  f = spot.formula("FGa -> (GFb & GF(c & b & d))")
  f.traverse(countg)
  print("===", gcount, "G seen ===")
#+END_SRC

#+RESULTS:
#+begin_example
FGa -> (GFb & GF(b & c & d))
FGa
Ga
a
GFb & GF(b & c & d)
GFb
Fb
b
GF(b & c & d)
F(b & c & d)
b & c & d
=== 3 G seen ===
#+end_example

Here is the =F= and =G= exchange:

#+BEGIN_SRC python
  import spot

  def xchg_fg(i):
     if i._is(spot.op_F):
        return spot.formula.G(xchg_fg(i[0]));
     if i._is(spot.op_G):
        return spot.formula.F(xchg_fg(i[0]));
     # No need to transform subformulas without F or G
     if i.is_sugar_free_ltl():
        return i;
     # Apply xchg_fg recursively on any other operator's children
     return i.map(xchg_fg);

  f = spot.formula("FGa -> (GFb & GF(c & b & d))")
  print("before:", f)
  print("after: ", xchg_fg(f))
#+END_SRC

#+RESULTS:
: before: FGa -> (GFb & GF(b & c & d))
: after:  GFa -> (FGb & FG(b & c & d))

Like in C++, extra arguments to =map= and =traverse= are passed as
additional to the function given in the first argument.

#  LocalWords:  utf html args accessor Unary arg ary initializer SRC
#  LocalWords:  unary SVA's tl pdf subformulas subformula memoization
#  LocalWords:  iostream FGa GFb GFc fga gfb gfc kindstar kindstr DFS
#  LocalWords:  enum subtrees gcount cpp GF Fb xchg fg GFa FGb countg
