Difference between revisions of "Vcsn/News File"
From LRDE
(Fix tables) 
(Fix indentation) 

Line 1,176:  Line 1,176:  
: requires standard input automata, builds a standard automaton 
: requires standard input automata, builds a standard automaton 

; "general" 
; "general" 

−  : applies to any kind of automaton, does not guarantee a standard 
+  : applies to any kind of automaton, does not guarantee a standard automaton. In the static API, might require a nullable labelset, in the dyn:: API and Python, might turn the labelset into a nullable one. 
−  
−  automaton. In the static API, might require a nullable labelset, in the dyn:: API and Python, might turn the labelset into a nullable one. 

−  
; "auto" (default) 
; "auto" (default) 

−  : same as <code>"standard"</code> if input automata are standard, otherwise 
+  : same as <code>"standard"</code> if input automata are standard, otherwise same as <code>"general"</code>. 
−  
−  same as <code>"general"</code>. 

In Python, the operators <code>+</code>, <code>*</code> and <code>**</code> use the <code>"auto"</code> strategy. 
In Python, the operators <code>+</code>, <code>*</code> and <code>**</code> use the <code>"auto"</code> strategy. 

Line 1,244:  Line 1,239:  
To update your existing repository, run a command similar to: 
To update your existing repository, run a command similar to: 

−  $ git remote seturl origin git@gitlab.lrde.epita.fr:vcsn/vcsn 
+  <pre>$ git remote seturl origin git@gitlab.lrde.epita.fr:vcsn/vcsn</pre> 
−  
== 20150930 == 
== 20150930 == 

Line 1,319:  Line 1,313:  
; "delgado" 
; "delgado" 

−  : select a state whose removal would contribute a small 
+  : select a state whose removal would contribute a small expression (number of symbols, including <code>+</code>, etc.). 
−  
−  expression (number of symbols, including <code>+</code>, etc.). 

−  
; "delgado_label" 
; "delgado_label" 

−  : likewise, but count only the number of labels in the 
+  : likewise, but count only the number of labels in the expression. 
−  
−  expression. 

−  
; "best" 
; "best" 

: run all the heuristics, and return the shortest result. 
: run all the heuristics, and return the shortest result. 

Line 1,412:  Line 1,400:  
: a minimum set of transformations are applied. 
: a minimum set of transformations are applied. 

; "associative" 
; "associative" 

−  : sum and product are made associative, so <code>a+(b+c)</code> and <code>(a+b)+c</code> are 
+  : sum and product are made associative, so <code>a+(b+c)</code> and <code>(a+b)+c</code> are equal. 
−  
−  equal. 

−  
; "linear" 
; "linear" 

−  : sum is made commutative, and weights are factored, so <code>a+b+a</code> is equal 
+  : sum is made commutative, and weights are factored, so <code>a+b+a</code> is equal to <code>a+b</code> in B, and to <code><2>a+b</code> in Z. 
−  
−  to <code>a+b</code> in B, and to <code><2>a+b</code> in Z. 

−  
; "distributive" (or "series") 
; "distributive" (or "series") 

−  : product and exterior/scalar products are distributed over sum, so 
+  : product and exterior/scalar products are distributed over sum, so <code>[ab]a</code> is equal to <code>aa+ba</code>, and <code><2>[ab]</code> is equal to <code><2>a+<2>b</code>. 
−  
−  <code>[ab]a</code> is equal to <code>aa+ba</code>, and <code><2>[ab]</code> is equal to <code><2>a+<2>b</code>. 

Previously the default identities were "associative". They are now "linear", to match most users' expectations. 
Previously the default identities were "associative". They are now "linear", to match most users' expectations. 

Line 1,430:  Line 1,410:  
So, for instance we used to report: 
So, for instance we used to report: 

−  In [2]: c = vcsn.context('lal_char(az), z') 
+  <pre>In [2]: c = vcsn.context('lal_char(az), z') 
−  In [3]: c.expression('r+[aq]') 
+  In [3]: c.expression('r+[aq]') 
+  Out[3]: r + [aq] 

−  
−  In [4]: c.expression('[aq]+r+r') Out[4]: [^sz] + r 

+  In [4]: c.expression('[aq]+r+r') 

+  Out[4]: [^sz] + r</pre> 

we now report: 
we now report: 

−  In [3]: c.expression('r+[aq]') 
+  <pre>In [3]: c.expression('r+[aq]') 
+  Out[3]: [^sz] 

−  
−  In [4]: c.expression('[aq]+r+r') Out[4]: [aq] + <2>r 

+  In [4]: c.expression('[aq]+r+r') 

+  Out[4]: [aq] + <2>r</pre> 

== 20150529 == 
== 20150529 == 

Line 1,456:  Line 1,438:  
The main feature of <code>cotrie</code> is that its result is codeterministic, so it only takes a determinization to minimize it. It turns out that in Vcsn determinization is more efficient than minimization: 
The main feature of <code>cotrie</code> is that its result is codeterministic, so it only takes a determinization to minimize it. It turns out that in Vcsn determinization is more efficient than minimization: 

−  In [13]: %timeit c.trie('/usr/share/dict/words').minimize() 
+  <pre>In [13]: %timeit c.trie('/usr/share/dict/words').minimize() 
+  1 loops, best of 3: 18.8 s per loop 

−  
−  In [14]: %timeit c.cotrie('/usr/share/dict/words').determinize() 1 loops, best of 3: 7.54 s per loop 

+  In [14]: %timeit c.cotrie('/usr/share/dict/words').determinize() 

+  1 loops, best of 3: 7.54 s per loop</pre> 

These automata are isomorphic. 
These automata are isomorphic. 

Line 1,468:  Line 1,451:  
Rational expressions have long supported label classes in input, e.g., [abc09]. Polynomials also support them in output. However expressions never used classes, which may seriously hinder their readability. For instance, to compute an expression describe all words on {a,..., z} except 'hehe', we had: 
Rational expressions have long supported label classes in input, e.g., [abc09]. Polynomials also support them in output. However expressions never used classes, which may seriously hinder their readability. For instance, to compute an expression describe all words on {a,..., z} except 'hehe', we had: 

+  <pre>In [2]: c = vcsn.context('lal_char(az), b') 

−  In [2]: c = vcsn.context('lal_char(az), b') c.expression('(abcd){c}').derived_term().expression() Out[2]: +a(+b(+c))+(b+c+d+e+f+g+h+i+j+k+l+m+n+o+p+q+r+s+t+u+v+w+x+y+z+a(a+c+d+e+f+g+h+i+j+k+l+m+n+o+p+q+r+s+t+u+v+w+x+y+z+b(a+b+d+e+f+g+h+i+j+k+l+m+n+o+p+q+r+s+t+u+v+w+x+y+z+c(a+b+c+e+f+g+h+i+j+k+l+m+n+o+p+q+r+s+t+u+v+w+x+y+z+d(a+b+c+d+e+f+g+h+i+j+k+l+m+n+o+p+q+r+s+t+u+v+w+x+y+z)))))(a+b+c+d+e+f+g+h+i+j+k+l+m+n+o+p+q+r+s+t+u+v+w+x+y+z)* 

+  c.expression('(abcd){c}').derived_term().expression() 

−  
+  Out[2]: \e+a(\e+b(\e+c))+(b+c+d+e+f+g+h+i+j+k+l+m+n+o+p+q+r+s+t+u+v+w+x+y+z+a(a+c+d+e+f+g+h+i+j+k+l+m+n+o+p+q+r+s+t+u+v+w+x+y+z+b(a+b+d+e+f+g+h+i+j+k+l+m+n+o+p+q+r+s+t+u+v+w+x+y+z+c(a+b+c+e+f+g+h+i+j+k+l+m+n+o+p+q+r+s+t+u+v+w+x+y+z+d(a+b+c+d+e+f+g+h+i+j+k+l+m+n+o+p+q+r+s+t+u+v+w+x+y+z)))))(a+b+c+d+e+f+g+h+i+j+k+l+m+n+o+p+q+r+s+t+u+v+w+x+y+z)*</pre> 

Now expressions also support letter classes in output: 
Now expressions also support letter classes in output: 

−  Out[2]: +a(+b(+c))+([^a]+a([^b]+b([^c]+c([^d]+d[^]))))[^]* 
+  <pre>Out[2]: \e+a(\e+b(\e+c))+([^a]+a([^b]+b([^c]+c([^d]+d[^]))))[^]*</pre> 
−  
Classes are used only on ranges of at least four (unweighted) letters in strictly increasing order: 
Classes are used only on ranges of at least four (unweighted) letters in strictly increasing order: 

−  In [3]: c.expression('a+a+b+c+d+e+f+x+y+z+w') 
+  <pre>In [3]: c.expression('a+a+b+c+d+e+f+x+y+z+w') 
+  Out[3]: a+[afxz]+w</pre> 

−  
Negated classes are issued only if the letters are in strictly increasing alphabetical order, and are more than two thirds of the whole alphabet (otherwise a regular class is preferred). 
Negated classes are issued only if the letters are in strictly increasing alphabetical order, and are more than two thirds of the whole alphabet (otherwise a regular class is preferred). 

−  In [4]: c.expression('[aq]') 
+  <pre>In [4]: c.expression('[aq]') 
+  Out[4]: [aq] 

−  In [5]: c.expression('[aq]+r') 
+  In [5]: c.expression('[aq]+r') 
+  Out[5]: [^sz] 

−  In [6]: c.expression('r+[aq]') 
+  In [6]: c.expression('r+[aq]') 
+  Out[6]: r + [aq] 

−  
−  In [7]: c.expression('[aq]+r+r') Out[7]: [^sz] + r 

+  In [7]: c.expression('[aq]+r+r') 

+  Out[7]: [^sz] + r</pre> 

== 20150521 == 
== 20150521 == 

Line 1,502:  Line 1,488:  
Building a polynomial from a dictionary stored on disk, and then building the trie is a waste of time. It is now possible to build it directly from a file. 
Building a polynomial from a dictionary stored on disk, and then building the trie is a waste of time. It is now possible to build it directly from a file. 

−  In [2]: t = vcsn.B.trie('/usr/share/dict/words') 
+  <pre>In [2]: t = vcsn.B.trie('/usr/share/dict/words') 
−  
−  In [3]: t.info() Out[3]: {'is codeterministic': False, 'is complete': True, 'is deterministic': True, 'is empty': False, 'is epsacyclic': True, 'is normalized': False, 'is proper': True, 'is standard': True, 'is trim': True, 'is useless': False, 'is valid': True, 'number of accessible states': 792777, 'number of coaccessible states': 792777, 'number of codeterministic states': 792777, 'number of deterministic states': 792777, 'number of eps transitions': 0, 'number of final states': 235886, 'number of initial states': 1, 'number of states': 792777, 'number of transitions': 792776, 'number of useful states': 792777, 'type': 'mutable_automaton<letterset<char_letters()>, b>'} 

+  In [3]: t.info() 

+  Out[3]: {'is codeterministic': False, 

+  'is complete': True, 

+  'is deterministic': True, 

+  'is empty': False, 

+  'is epsacyclic': True, 

+  'is normalized': False, 

+  'is proper': True, 

+  'is standard': True, 

+  'is trim': True, 

+  'is useless': False, 

+  'is valid': True, 

+  'number of accessible states': 792777, 

+  'number of coaccessible states': 792777, 

+  'number of codeterministic states': 792777, 

+  'number of deterministic states': 792777, 

+  'number of eps transitions': 0, 

+  'number of final states': 235886, 

+  'number of initial states': 1, 

+  'number of states': 792777, 

+  'number of transitions': 792776, 

+  'number of useful states': 792777, 

+  'type': 'mutable_automaton<letterset<char_letters()>, b>'}</pre> 

== 20150514 == 
== 20150514 == 

Line 1,512:  Line 1,519:  
From a finite language/series represented as a polynomial (of words), build an automaton that has the shape of a trie (a prefix tree). 
From a finite language/series represented as a polynomial (of words), build an automaton that has the shape of a trie (a prefix tree). 

−  In [2]: series = '<2>+<3>a+<4>b+<5>abc+<6>abcd+<7>abdc' 
+  <pre>In [2]: series = '<2>\e+<3>a+<4>b+<5>abc+<6>abcd+<7>abdc' 
−  
−  In [3]: p = vcsn.context('law_char, z').polynomial(series); p Out[3]: <2>+ <3>a + <4>b + <5>abc + <6>abcd + <7>abdc 

+  In [3]: p = vcsn.context('law_char, z').polynomial(series); p 

−  In [4]: a = p.trie(); a Out[4]: mutable_automaton<letterset<char_letters(abcd)>, z> 

+  Out[3]: <2>\e + <3>a + <4>b + <5>abc + <6>abcd + <7>abdc 

+  In [4]: a = p.trie(); a 

−  In [5]: a.shortest(100) Out[5]: <2>+ <3>a + <4>b + <5>abc + <6>abcd + <7>abdc 

+  Out[4]: mutable_automaton<letterset<char_letters(abcd)>, z> 

+  In [5]: a.shortest(100) 

+  Out[5]: <2>\e + <3>a + <4>b + <5>abc + <6>abcd + <7>abdc</pre> 

== 20150501 == 
== 20150501 == 

Line 1,544:  Line 1,553:  
One can now specify both a maximum number of words, and a maximum size. It is also significantly faster. The Python binding automaton.enumerate was removed. 
One can now specify both a maximum number of words, and a maximum size. It is also significantly faster. The Python binding automaton.enumerate was removed. 

−  In [4]: a = vcsn.Z.expression('[01] 
+  <pre>In [4]: a = vcsn.Z.expression('[01]*1(<2>[01])*').standard() 
−  In [5]: a.shortest() 
+  In [5]: a.shortest() 
+  Out[5]: 1 

−  In [6]: a.shortest(3) 
+  In [6]: a.shortest(3) 
+  Out[6]: 1 + 01 + <2>10 

+  In [7]: a.shortest(len = 3) 

−  In [7]: a.shortest(len = 3) Out[7]: 1 + 01 + <2>10 + <3>11 + 001 + <2>010 + <3>011 + <4>100 + <5>101 + <6>110 + <7>111 

+  Out[7]: 1 + 01 + <2>10 + <3>11 + 001 + <2>010 + <3>011 + <4>100 + <5>101 + <6>110 + <7>111 

−  In [8]: a.shortest(len = 3, num = 5) 
+  In [8]: a.shortest(len = 3, num = 5) 
+  Out[8]: 1 + 01 + <2>10 + <3>11 + 001 

−  
−  In [9]: a.shortest(len = 30, num = 5) Out[9]: 1 + 01 + <2>10 + <3>11 + 001 

+  In [9]: a.shortest(len = 30, num = 5) 

+  Out[9]: 1 + 01 + <2>10 + <3>11 + 001</pre> 

== 20150325 == 
== 20150325 == 

Line 1,590:  Line 1,603:  
In order to facilitate the experiments with <code>join</code>, it is now provided as an algorithm. In Python, it is also available as the infix <code>or</code> operator. 
In order to facilitate the experiments with <code>join</code>, it is now provided as an algorithm. In Python, it is also available as the infix <code>or</code> operator. 

−  In [2]: c1 = vcsn.context('lat 
+  <pre>In [2]: c1 = vcsn.context('lat<lal_char(a), lan_char(x)>, z'); c1 
+  Out[2]: {a} × ({x})? → ℤ 

−  In [3]: c2 = vcsn.context('lat 
+  In [3]: c2 = vcsn.context('lat<lan_char(b), lal_char(y)>, q'); c2 
+  Out[3]: ({b})? × {y} → ℚ 

−  
−  In [4]: c1  c2 Out[4]: ({a,b})? × ({x,y})? → ℚ 

+  In [4]: c1  c2 

+  Out[4]: ({a,b})? × ({x,y})? → ℚ</pre> 

== 20150318 == 
== 20150318 == 

Line 1,634:  Line 1,649:  
This algorithm checks whether an automaton is letterized, i.e. whether each transition's label is a single letter (in the sense of the labelset). 
This algorithm checks whether an automaton is letterized, i.e. whether each transition's label is a single letter (in the sense of the labelset). 

−  In [2]: ctx = vcsn.context("law_char, b") 
+  <pre>In [2]: ctx = vcsn.context("law_char, b") 
−  In [3]: ctx.expression("abc").standard().is_letterized() 
+  In [3]: ctx.expression("abc").standard().is_letterized() 
+  Out[3]: False 

−  
−  In [4]: ctx.expression("a*(b+c)").standard().is_letterized() Out[4]: True 

+  In [4]: ctx.expression("a*(b+c)").standard().is_letterized() 

+  Out[4]: True</pre> 

== 20150302 == 
== 20150302 == 

Line 1,648:  Line 1,664:  
The <code>expression.zpc</code> function features an optional argument, which, when set to "compact", enables a variant, more compact, construction. 
The <code>expression.zpc</code> function features an optional argument, which, when set to "compact", enables a variant, more compact, construction. 

+  <pre>In [2]: vcsn.b.expression('ab').zpc() 

−  In [2]: vcsn.b.expression('ab').zpc() ╭───╮ ╭───╮ a ╭───╮ ╭───╮ b ╭───╮ ╭───╮ ──> │ 0 │ ────> │ 1 │ ───> │ 2 │ ────> │ 3 │ ───> │ 4 │ ────> │ 5 │ ──> ╰───╯ ╰───╯ ╰───╯ ╰───╯ ╰───╯ ╰───╯ 

+  ╭───╮ \e ╭───╮ a ╭───╮ \e ╭───╮ b ╭───╮ \e ╭───╮ 

−  
−  +  ──> │ 0 │ ────> │ 1 │ ───> │ 2 │ ────> │ 3 │ ───> │ 4 │ ────> │ 5 │ ──> 

+  ╰───╯ ╰───╯ ╰───╯ ╰───╯ ╰───╯ ╰───╯ 

+  In [3]: vcsn.b.expression('ab').zpc('compact') 

+  ╭───╮ a ╭───╮ \e ╭───╮ b ╭───╮ 

+  ──> │ 0 │ ───> │ 1 │ ────> │ 2 │ ───> │ 3 │ ──> 

+  ╰───╯ ╰───╯ ╰───╯ ╰───╯</pre> 

== 20150223 == 
== 20150223 == 

Line 1,658:  Line 1,679:  
Create the equivalent automaton, but with only singleletter transitions. Basically, do the conversion from law to lan. It also works recursively with multitape transducers. 
Create the equivalent automaton, but with only singleletter transitions. Basically, do the conversion from law to lan. It also works recursively with multitape transducers. 

−  In [2]: c = vcsn.context('lat 
+  <pre>In [2]: c = vcsn.context('lat<law_char, lal_char>, z') 
In [3]: a = c.expression("<2>'(abc,x)'").derived_term() 
In [3]: a = c.expression("<2>'(abc,x)'").derived_term() 

+  In [4]: print(a.format('daut')) 

−  In [4]: print(a.format('daut')) context = "lat<wordset<char_letters(abc)>, letterset<char_letters(x)>>, z" $ > 0 0 > 1 <2>(abc,x) 1 > $ 

+  context = "lat<wordset<char_letters(abc)>, letterset<char_letters(x)>>, z" 

−  
+  $ > 0 

−  In [5]: print(a.letterize().format('daut')) context = "lat<nullableset<letterset<char_letters(abc)>>, nullableset<letterset<char_letters(x)>>>, z" $ > 0 0 > 2 <2>(a,x) 1 > $ 2 > 3 (b,) 3 > 1 (c,) 

+  0 > 1 <2>(abc,x) 

+  1 > $ 

+  In [5]: print(a.letterize().format('daut')) 

+  context = "lat<nullableset<letterset<char_letters(abc)>>, nullableset<letterset<char_letters(x)>>>, z" 

+  $ > 0 

+  0 > 2 <2>(a,x) 

+  1 > $ 

+  2 > 3 (b,\e) 

+  3 > 1 (c,\e)</pre> 

== 20150210 == 
== 20150210 == 

Line 1,672:  Line 1,702:  
When typing multitape transducers, it is now no longer necessary to explicit the parenthesis inside (multi)letters. 
When typing multitape transducers, it is now no longer necessary to explicit the parenthesis inside (multi)letters. 

−  In [1]: import vcsn 
+  <pre>In [1]: import vcsn 
−  In [2]: c = vcsn.context('lat 
+  In [2]: c = vcsn.context('lat<lan_char, lan_char>, b') 
−  
−  In [3]: r = c.expression(r"'a,'+'(b,c)'+'d,f'") 

+  In [3]: r = c.expression(r"'a,\e'+'(b,c)'+'d,f'")</pre> 

=== has_bounded_lag: new algorithm === 
=== has_bounded_lag: new algorithm === 

This algorithm checks if a transducer has a bounded lag, i.e. if there is a maximum difference of length between the input words and their corresponding outputs. 
This algorithm checks if a transducer has a bounded lag, i.e. if there is a maximum difference of length between the input words and their corresponding outputs. 

−  In [1]: import vcsn 
+  <pre>In [1]: import vcsn 
−  
−  In [2]: c = vcsn.context('lat<lan_char, lan_char>, b') 

+  In [2]: c = vcsn.context('lat<lan_char, lan_char>, b') 

−  In [3]: c.expression(r"'a,'").standard().has_bounded_lag() Out[3]: True 

−  In [ 
+  In [3]: c.expression(r"'a,\e'").standard().has_bounded_lag() 
+  Out[3]: True 

+  In [4]: c.expression(r"'a,\e'*").standard().has_bounded_lag() 

+  Out[4]: False</pre> 

== 20141118 == 
== 20141118 == 

Line 1,722:  Line 1,752:  
So now, if the context of the input expression does not support <code>\e</code>, the Thompson automaton will be built with a generalized context which does support it: 
So now, if the context of the input expression does not support <code>\e</code>, the Thompson automaton will be built with a generalized context which does support it: 

−  In [1]: import vcsn 
+  <pre>In [1]: import vcsn 
−  In [2]: vcsn.context('lan_char, b').ratexp('a').thompson().context() 
+  In [2]: vcsn.context('lan_char, b').ratexp('a').thompson().context() 
+  Out[2]: lan<letterset<char_letters(a)>>, b 

−  In [3]: vcsn.context('law_char, b').ratexp('a').thompson().context() 
+  In [3]: vcsn.context('law_char, b').ratexp('a').thompson().context() 
+  Out[3]: wordset<char_letters(a)>, b 

−  
−  In [4]: vcsn.context('lal_char, b').ratexp('a').thompson().context() Out[4]: lan<letterset<char_letters(a)>>, b 

+  In [4]: vcsn.context('lal_char, b').ratexp('a').thompson().context() 

+  Out[4]: lan<letterset<char_letters(a)>>, b</pre> 

== 20141030 == 
== 20141030 == 

Line 1,752:  Line 1,784:  
So for instance: 
So for instance: 

−  <pre>lal_char(abc)_b 
+  <pre> lal_char(abc)_b 
−  > lal_char(abc), b 
+  > lal_char(abc), b 
−  +  lat<lal_char(ab),lal_char(xy)>_lat<q,r> 

−  > lat 
+  > lat<lal_char(ab), lal_char(xy)>, lat<q, r> 
−  
−  <pre>law_char(az)_ratexpset<law_char(AZ)_b></pre> 

−  > law_char(az), ratexpset<law_char(AZ), b> 

+  law_char(az)_ratexpset<law_char(AZ)_b> 

+  > law_char(az), ratexpset<law_char(AZ), b></pre> 

This syntax is not (and has never been) the intended one, it should be considered as the "internal" syntax. However, since the intended syntax is still not implemented, one, unfortunately, still has to deal with this inner syntax. 
This syntax is not (and has never been) the intended one, it should be considered as the "internal" syntax. However, since the intended syntax is still not implemented, one, unfortunately, still has to deal with this inner syntax. 

Line 1,771:  Line 1,802:  
Now, <code>proper</code> copies the result in a context with a denullabled labelset. So for instance: 
Now, <code>proper</code> copies the result in a context with a denullabled labelset. So for instance: 

−  In [2]: vcsn.context('lan_char(ab)_b').ratexp('(ab)*').thompson().proper() 
+  <pre>In [2]: vcsn.context('lan_char(ab)_b').ratexp('(ab)*').thompson().proper() 
+  Out[2]: mutable_automaton<lal_char(ab)_b></pre> 

−  
There is no measurable performance regression. However state numbers are now unrelated to the input automaton. 
There is no measurable performance regression. However state numbers are now unrelated to the input automaton. 

Line 1,781:  Line 1,812:  
The <code>vcsn.automaton</code> constructor now support a <code>filename</code> named argument to load an automaton from a file. 
The <code>vcsn.automaton</code> constructor now support a <code>filename</code> named argument to load an automaton from a file. 

−  vcsn.automaton(filename = 'a.gv 
+  <pre>vcsn.automaton(filename = 'a.gv') 
+  vcsn.automaton(filename = 'a.efsm', format = 'efsm')</pre> 

−  
=== minimize: default algorithm is "auto" === 
=== minimize: default algorithm is "auto" === 

Line 1,823:  Line 1,854:  
In addition to splitting (aka, breaking) a ratexp, it is now possible to split a polynomial. This, for instance, provides another way to compute the breaking derivation of a ratexp: 
In addition to splitting (aka, breaking) a ratexp, it is now possible to split a polynomial. This, for instance, provides another way to compute the breaking derivation of a ratexp: 

−  In [1]: r = vcsn.context('lal_char_z').ratexp('a(b+a)+a(a+b)') 
+  <pre>In [1]: r = vcsn.context('lal_char_z').ratexp('a(b+a)+a(a+b)') 
−  
−  In [2]: p = r.derivation('a'); p Out[2]: a+b + b+a 

−  In [ 
+  In [2]: p = r.derivation('a'); p 
+  Out[2]: a+b + b+a 

+  In [3]: p.split() 

−  In [4]: r.derivation('a', True) Out[4]: <2>a + <2>b 

+  Out[3]: <2>a + <2>b 

+  In [4]: r.derivation('a', True) 

+  Out[4]: <2>a + <2>b</pre> 

=== derivation: fix a Python bug === 
=== derivation: fix a Python bug === 

Line 1,893:  Line 1,926:  
Initial support for multiprecision rational numbers. 
Initial support for multiprecision rational numbers. 

−  < 
+  <pre>>>> a = vcsn.context('lal_char(abc)_qmp').ratexp('<2/3>a').standard() & 70 
+  >>> a('a') 

−  </blockquote></blockquote></blockquote> 

+  1180591620717411303424/2503155504993241601315571986085849</pre> 

Requires the GMP library. 
Requires the GMP library. 

Line 1,949:  Line 1,983:  
Series currently depend on the commutativity of their weightset, and only support a subset of the available operations. 
Series currently depend on the commutativity of their weightset, and only support a subset of the available operations. 

+  <pre>>>> vcsn.context('lal_char(a)_ratexpset<lal_char(x)_b>(series)') # series 

−  <blockquote><blockquote><blockquote>vcsn.context('lal_char(a)''ratexpset<lal_char(x)_b>(series)') # series vcsn.context('lal''char(a)''seriesset<lal_char(x)_b>') # series vcsn.context(ratexpset<lal_char(x)_b>''z') # trivial vcsn.context('lal_char(a)''ratexpset<lal_char(x)_b>(trivial)')# trivial e = vcsn.context('lal''char(ac)''z').ratexp('b+a+b'); e b+a+b s = vcsn.context('lal''char(ac)''z').series('b+a+b'); s a+<2>b (e+s).is''series() True 

+  >>> vcsn.context('lal_char(a)_seriesset<lal_char(x)_b>') # series 

−  </blockquote></blockquote></blockquote> 

+  >>> vcsn.context(ratexpset<lal_char(x)_b>_z') # trivial 

+  >>> vcsn.context('lal_char(a)_ratexpset<lal_char(x)_b>(trivial)')# trivial 

+  >>> e = vcsn.context('lal_char(ac)_z').ratexp('b+a+b'); e 

+  b+a+b 

+  >>> s = vcsn.context('lal_char(ac)_z').series('b+a+b'); s 

+  a+<2>b 

+  >>> (e+s).is_series() 

+  True</pre> 

=== has_twins_property: new algorithm === 
=== has_twins_property: new algorithm === 

Line 1,990:  Line 2,032:  
The speed improvements are (erebus: OS X i7 2.9GHz 8GB, Clang 3.5 O3 DNDEBUG): 
The speed improvements are (erebus: OS X i7 2.9GHz 8GB, Clang 3.5 O3 DNDEBUG): 

+  <pre> (1) (2) (3) 

−  <ol style="liststyletype: decimal;"> 

+  7.93s 7.80s 7.43s: a.determinize() # a = ladybird(21) 

−  <li><ol start="2" style="liststyletype: decimal;"> 

−  +  6.64s 6.45s 0.84s: a.determinize() # a = lal(azAZ09).ladybird(18)</pre> 

−  </li></ol> 

−  
where (1) is the "original" version, (2) is the version without the optional completion of the determinized automaton (yes, it was set to False in the bench of (1)), and (3) is the current version, which avoids considering unused letters. 
where (1) is the "original" version, (2) is the version without the optional completion of the determinized automaton (yes, it was set to False in the bench of (1)), and (3) is the current version, which avoids considering unused letters. 

Line 2,014:  Line 2,054:  
Minimizing an automaton now yields a decorated automaton keeping track of source state names. The new "subset decorator" code is decoupled from minimization and is intended to be used for other algorithms as well. 
Minimizing an automaton now yields a decorated automaton keeping track of source state names. The new "subset decorator" code is decoupled from minimization and is intended to be used for other algorithms as well. 

−  < 
+  <pre>>>> a = vcsn.context('lal_char(az)_b').ratexp('a+b*e+c+dc').standard(); a 
+  >>> a.minimize()</pre> 

−  </blockquote></blockquote></blockquote> 

The minimize algorithm no longer recognizes the "brzozowski" variant at the Static level, as it would require a very different, and likely uninteresting, decorator; the user can still directly call minimize_brzozowski at the Static level. We still support "brzozowski" as a variant at the Dyn and Python levels. 
The minimize algorithm no longer recognizes the "brzozowski" variant at the Static level, as it would require a very different, and likely uninteresting, decorator; the user can still directly call minimize_brzozowski at the Static level. We still support "brzozowski" as a variant at the Dyn and Python levels. 

Line 2,040:  Line 2,080:  
Lift arbitrary restrictions on the labelset of the 'weighted' and 'signature' minimization variants. 
Lift arbitrary restrictions on the labelset of the 'weighted' and 'signature' minimization variants. 

−  < 
+  <pre>>>> ctx = vcsn.context('law_char(az)_b') 
+  >>> ctx.ratexp('ab+<3>cd+ac').standard().minimize('weighted')</pre> 

−  </blockquote></blockquote></blockquote> 

== 20140604 == 
== 20140604 == 

Line 2,050:  Line 2,090:  
Coupled with the fact that automata can now display state names (as opposed to state numbers) in Dot output, one gets rich displays of automata. For instance: 
Coupled with the fact that automata can now display state names (as opposed to state numbers) in Dot output, one gets rich displays of automata. For instance: 

−  < 
+  <pre>>>> ctx = vcsn.context('lal_char(ab)_b') 
+  >>> ctx.ratexp('aa+ab').derived_term().determinize()</pre> 

−  </blockquote></blockquote></blockquote> 

now displays an automaton whose states are labeled as sets of ratexps: "{aa+ab}", "{a, b}", and "{}". 
now displays an automaton whose states are labeled as sets of ratexps: "{aa+ab}", "{a, b}", and "{}". 

Line 2,080:  Line 2,120:  
Lift the previous limitation of isisomorphic to deterministic lal automata. The sequential case keeps its linear complexity, but the new generic code has a worstcase complexity of O((n+1)!); however the common case is much faster, as we heuristically classify states according to in and outtransitions, restricting bruteforce search to states which are possible candidates for isomorphism. 
Lift the previous limitation of isisomorphic to deterministic lal automata. The sequential case keeps its linear complexity, but the new generic code has a worstcase complexity of O((n+1)!); however the common case is much faster, as we heuristically classify states according to in and outtransitions, restricting bruteforce search to states which are possible candidates for isomorphism. 

+  <pre>>>> ctx = vcsn.context('lal_char(az)_b') 

−  <blockquote><blockquote><blockquote>ctx = vcsn.context('lal_char(az)''b') a = ctx.ratexp('ab+<3>ab+ab+ac').standard() b = ctx.ratexp('ab+ac+<3>ab+ab').standard() a.is''isomorphic(b) True at = ctx.ratexp('abc').standard().transpose() c = ctx.ratexp('cba').standard() at.is_isomorphic(c) True 

+  >>> a = ctx.ratexp('ab+<3>ab+ab+ac').standard() 

−  </blockquote></blockquote></blockquote> 

+  >>> b = ctx.ratexp('ab+ac+<3>ab+ab').standard() 

+  >>> a.is_isomorphic(b) 

+  True 

+  >>> at = ctx.ratexp('abc').standard().transpose() 

+  >>> c = ctx.ratexp('cba').standard() 

+  >>> at.is_isomorphic(c) 

+  True</pre> 

== 20140522 == 
== 20140522 == 

Line 2,094:  Line 2,141:  
Instead of: 
Instead of: 

−  automaton_t aut{ctx} 
+  <pre>automaton_t aut{ctx}; 
+  auto s1 = aut.new_state(); 

−  
+  aut.set_initial(s1);</pre> 

write: 
write: 

−  auto aut = vcsn::make_mutable_automaton(ctx 
+  <pre>auto aut = vcsn::make_mutable_automaton(ctx); 
+  // or: auto aut = vcsn::make_shared_ptr<automaton_t>(ctx); 

−  
+  auto s1 = aut>new_state(); 

+  aut>set_initial(s1);</pre> 

== 20140521 == 
== 20140521 == 

Line 2,106:  Line 2,156:  
Polynomialsets are now usable as a generic weightset. Polynomials are mostly useful on law and ratexpset. 
Polynomialsets are now usable as a generic weightset. Polynomials are mostly useful on law and ratexpset. 

−  < 
+  <pre>>>> ctx = vcsn.context('lal_char(abc)_polynomialset<law_char(xyz)_z>') 
+  >>> ctx.ratexp('<x + xy + x + \e>a') 

−  </blockquote></blockquote></blockquote> 

+  <\e + <2>x + xy>a</pre> 

== 20140518 == 
== 20140518 == 

Line 2,114:  Line 2,165:  
We may now use '[^...]' to denote a letter other than the listed ones. The special case '[^]' denotes any character of the alphabet. 
We may now use '[^...]' to denote a letter other than the listed ones. The special case '[^]' denotes any character of the alphabet. 

−  < 
+  <pre>>>> c = vcsn.context('lal_char(09)_b') 
+  >>> c.ratexp('0+[^0][^]*') 

−  </blockquote></blockquote></blockquote> 

+  0+(1+2+3+4+5+6+7+8+9)(0+1+2+3+4+5+6+7+8+9)*</pre> 

=== ratexps: invalid letter classes are rejected === 
=== ratexps: invalid letter classes are rejected === 

Instead of being ignored, invalid intervals, or empty classes, are now rejected. 
Instead of being ignored, invalid intervals, or empty classes, are now rejected. 

+  <pre>>>> c.ratexp('[90]') 

−  <blockquote><blockquote><blockquote>c.ratexp('[90]') RuntimeError: invalid letter interval: 90 c.ratexp('[]') RuntimeError: invalid empty letter class 

+  RuntimeError: invalid letter interval: 90 

−  </blockquote></blockquote></blockquote> 

+  >>> c.ratexp('[]') 

+  RuntimeError: invalid empty letter class</pre> 

=== ratexps: improved support for letter classes === 
=== ratexps: improved support for letter classes === 

Previously letter classes were supported only for context on top of a simple alphabet (LAL, LAN and LAW). Generators of more complex contexts such as LAL x LAN are now supported: 
Previously letter classes were supported only for context on top of a simple alphabet (LAL, LAN and LAW). Generators of more complex contexts such as LAL x LAN are now supported: 

−  < 
+  <pre>>>> c = vcsn.context('lat<lal_char(abc),lan_char(xyz)>_b') 
+  >>> c.ratexp("['(a,x)''(c,z)']") 

−  </blockquote></blockquote></blockquote> 

+  (a,x)+(c,z) 

−  <blockquote><blockquote><blockquote>c.ratexp("[^'(a,x)''(c,z)']") (a,y)+(a,z)+(b,x)+(b,y)+(b,z)+(c,x)+(c,y) 

+  
−  </blockquote></blockquote></blockquote> 

−  +  >>> c.ratexp("[^'(a,x)''(c,z)']") 

+  (a,y)+(a,z)+(b,x)+(b,y)+(b,z)+(c,x)+(c,y) 

−  </blockquote></blockquote></blockquote> 

+  
−  <blockquote><blockquote><blockquote>c.ratexp("[^]") (a,x)+(a,y)+(a,z)+(b,x)+(b,y)+(b,z)+(c,x)+(c,y)+(c,z) 

+  >>> c.ratexp("['(a,x)''(a,z)']") 

−  </blockquote></blockquote></blockquote> 

+  (a,x)+(a,y)+(a,z) 

+  
+  >>> c.ratexp("[^]") 

+  (a,x)+(a,y)+(a,z)+(b,x)+(b,y)+(b,z)+(c,x)+(c,y)+(c,z)</pre> 

== 20140512 == 
== 20140512 == 

Line 2,140:  Line 2,198:  
A new algorithm has been introduced to allow the composition of two transducers. It computes the accessible part of the transducer resulting from the composition of the second tape of the first transducer with the first tape of the second one. 
A new algorithm has been introduced to allow the composition of two transducers. It computes the accessible part of the transducer resulting from the composition of the second tape of the first transducer with the first tape of the second one. 

+  <pre>>>> c1 = vcsn.context('lat<lan_char(abc),lan_char(ijk)>_b') 

−  <blockquote><blockquote><blockquote>c1 = vcsn.context('lat<lan_char(abc),lan_char(ijk)>''b') c2 = vcsn.context('lat<lan_char(ijk),lan_char(xyz)>''b') t1 = c1.ratexp("('(a,i)'+'(b,j)'+'(c,k)')''").thompson() t2 = c2.ratexp("('(i,x)'+'(j,y)'+'(k,z)')''").standard() t1.compose(t2).proper().shortest(8) (,) + (a,x) + (b,y) + (c,z) + (aa,xx) + (ab,xy) + (ac,xz) + (ba,yx) 

+  >>> c2 = vcsn.context('lat<lan_char(ijk),lan_char(xyz)>_b') 

−  </blockquote></blockquote></blockquote> 

+  >>> t1 = c1.ratexp("('(a,i)'+'(b,j)'+'(c,k)')*").thompson() 

+  >>> t2 = c2.ratexp("('(i,x)'+'(j,y)'+'(k,z)')*").standard() 

+  >>> t1.compose(t2).proper().shortest(8) 

+  (\e,\e) + (a,x) + (b,y) + (c,z) + (aa,xx) + (ab,xy) + (ac,xz) + (ba,yx)</pre> 

== 20140505 == 
== 20140505 == 

Line 2,164:  Line 2,226:  
Multiplication by a scalar on the left, and on the right, can be performed with implicit conversion of the weights. Instead of 
Multiplication by a scalar on the left, and on the right, can be performed with implicit conversion of the weights. Instead of 

−  < 
+  <pre>>>> z = vcsn.context('lal_char(ab)_z') 
+  >>> r = z.ratexp('[ab]*') 

−  </blockquote></blockquote></blockquote> 

+  >>> z.weight(2) * r * z.weight(3)</pre> 

one can now write 
one can now write 

+  <pre>>>> 2 * r * 3</pre> 

−  <blockquote><blockquote><blockquote>2 * r * 3 

−  </blockquote></blockquote></blockquote> 

and similarly for automata. 
and similarly for automata. 

Line 2,180:  Line 2,242:  
Vaucanson 2 is now also hosted on gitlab.lrde.epita.fr. It is also renamed vaucanson.git, rather than vaucanson2.git. To update your existing repository, run a command similar to: 
Vaucanson 2 is now also hosted on gitlab.lrde.epita.fr. It is also renamed vaucanson.git, rather than vaucanson2.git. To update your existing repository, run a command similar to: 

−  $ git remote seturl origin git@gitlab.lrde.epita.fr:vcsn/vaucanson 
+  <pre>$ git remote seturl origin git@gitlab.lrde.epita.fr:vcsn/vaucanson</pre> 
−  
or edit your .git/config file to update the URL. 
or edit your .git/config file to update the URL. 

Line 2,194:  Line 2,255:  
Static: 
Static: 

+  <pre>template <typename RatExpSet> 

−  template <typename RatExpSet> inline rat::ratexp_polynomial_t<RatExpSet> derivation(const RatExpSet& rs, const typename RatExpSet::value_t& e, const std::string& word, bool breaking = false) 

+  inline 

−  
+  rat::ratexp_polynomial_t<RatExpSet> 

+  derivation(const RatExpSet& rs, const typename RatExpSet::value_t& e, 

+  const std::string& word, bool breaking = false)</pre> 

Dyn: 
Dyn: 

−  polynomial derivation(const ratexp& exp, const std::string& s, 
+  <pre>polynomial derivation(const ratexp& exp, const std::string& s, 
+  bool breaking = false);</pre> 

−  
These signatures are now: 
These signatures are now: 

+  <pre>template <typename RatExpSet> 

−  template <typename RatExpSet> inline rat::ratexp_polynomial_t<RatExpSet> derivation(const RatExpSet& rs, const typename RatExpSet::value_t& e, const typename RatExpSet::labelset_t::word_t& word, bool breaking = false) 

+  inline 

+  rat::ratexp_polynomial_t<RatExpSet> 

+  derivation(const RatExpSet& rs, const typename RatExpSet::value_t& e, 

+  const typename RatExpSet::labelset_t::word_t& word, 

+  bool breaking = false) 

−  polynomial derivation(const ratexp& exp, const label& l, bool breaking = false); 

+  polynomial derivation(const ratexp& exp, const label& l, 

+  bool breaking = false);</pre> 

At the Python level, derivation was adjusted so that one may still pass a string, and see it upgraded, so both these calls work: 
At the Python level, derivation was adjusted so that one may still pass a string, and see it upgraded, so both these calls work: 

+  <pre>>>> ctx = vcsn.context('lal_char(ab)_z') 

−  <blockquote><blockquote><blockquote>ctx = vcsn.context('lal_char(ab)_z') r = ctx.ratexp('(<2>a)''') r.derivation(ctx.word('aa')) <4>(<2>a)'' r.derivation('aa') <4>(<2>a)* 

+  >>> r = ctx.ratexp('(<2>a)*') 

−  </blockquote></blockquote></blockquote> 

+  >>> r.derivation(ctx.word('aa')) 

+  <4>(<2>a)* 

+  >>> r.derivation('aa') 

+  <4>(<2>a)*</pre> 

=== Context extraction === 
=== Context extraction === 

Line 2,222:  Line 2,296:  
The synchronized product of automata is now variadic: the product of nautomata directly builds an automaton labeled with ntuples of original states. The Python operator, &, is modified to pretend it is variadic (rather than binary): it delays the computation until the result is needed. The ".value()" method allows to force the evaluation. 
The synchronized product of automata is now variadic: the product of nautomata directly builds an automaton labeled with ntuples of original states. The Python operator, &, is modified to pretend it is variadic (rather than binary): it delays the computation until the result is needed. The ".value()" method allows to force the evaluation. 

+  <pre>>>> ctx = vcsn.context('lal_char(ab)_z') 

−  <blockquote><blockquote><blockquote>ctx = vcsn.context('lal_char(ab)''z') a1 = ctx.de''bruijn(5) a = ctx.ratexp('a{5}').derived_term() import timeit timeit.timeit(lambda: (((a1&a1).value() & a1).value() & a).value(), number=1000) 1.9550061225891113 timeit.timeit(lambda: (a1 & a1 & a1 & a).value(), number=1000) 0.5792131423950195 

+  >>> a1 = ctx.de_bruijn(5) 

−  </blockquote></blockquote></blockquote> 

+  >>> a = ctx.ratexp('a{5}').derived_term() 

+  >>> import timeit 

+  >>> timeit.timeit(lambda: (((a1&a1).value() & a1).value() & a).value(), 

+  number=1000) 

+  1.9550061225891113 

+  >>> timeit.timeit(lambda: (a1 & a1 & a1 & a).value(), number=1000) 

+  0.5792131423950195</pre> 

Be aware that if the result is not needed, then it is simply not computed at all (hence, appears to be blazingly fast): 
Be aware that if the result is not needed, then it is simply not computed at all (hence, appears to be blazingly fast): 

−  < 
+  <pre>>>> timeit.timeit(lambda: a1 & a1 & a1 & a, number=1000) 
+  0.0039250850677490234</pre> 

−  </blockquote></blockquote></blockquote> 

=== "Fine grain" runtime compilation works === 
=== "Fine grain" runtime compilation works === 

Line 2,236:  Line 2,317:  
It is now possible to ask for the Brzozowski's minimization: 
It is now possible to ask for the Brzozowski's minimization: 

−  < 
+  <pre>>>> a = vcsn.context('lal_char(ab)_b').ratexp('a+b').standard() 
+  >>> a.minimize('moore').info()['number of states'] 

−  </blockquote></blockquote></blockquote> 

+  2 

+  >>> a.minimize('signature').info()['number of states'] 

+  2 

+  >>> a.minimize('brzozowski').info()['number of states'] 

+  2</pre> 

== 20140411 == 
== 20140411 == 

Line 2,254:  Line 2,340:  
Vaucanson 1 is now hosted on gitlab.lrde.epita.fr. It is also renamed vaucanson1.git, rather than just vaucanson.git. To update your existing repository, run a command similar to: 
Vaucanson 1 is now hosted on gitlab.lrde.epita.fr. It is also renamed vaucanson1.git, rather than just vaucanson.git. To update your existing repository, run a command similar to: 

−  $ git remote seturl origin git@gitlab.lrde.epita.fr:vcsn/vaucanson1 
+  <pre>$ git remote seturl origin git@gitlab.lrde.epita.fr:vcsn/vaucanson1</pre> 
−  
or edit your .git/config file to update the URL. 
or edit your .git/config file to update the URL. 

Line 2,282:  Line 2,367:  
Conversions of both labels and weights are performed if needed. 
Conversions of both labels and weights are performed if needed. 

−  < 
+  <pre>>>> a = vcsn.context('ratexpset<lal_char(xy)_b>_z').ratexp("<2>'x*'") 
+  >>> b = vcsn.context('lal_char(b)_q') .ratexp('<1/3>b') 

−  </blockquote></blockquote></blockquote> 

+  >>> a * b 

−  <blockquote><blockquote><blockquote>ab = vcsn.context('lal_char(ab)_z').ratexp('(a+b)*') bc = vcsn.context('lal_char(bc)_b').ratexp('(b+c)''') ab & bc (a+b)''&(b+c)* (ab & bc).info()['type'] 'ratexpset<lal_char(abc)_z>' 

+  <2>x*<1/3>b 

−  </blockquote></blockquote></blockquote> 

+  >>> (a*b).info()['type'] 

+  'ratexpset<ratexpset<lal_char(bxy)_b>_q>' 

+  
+  >>> ab = vcsn.context('lal_char(ab)_z').ratexp('(a+b)*') 

+  >>> bc = vcsn.context('lal_char(bc)_b').ratexp('(b+c)*') 

+  >>> ab & bc 

+  (a+b)*&(b+c)* 

+  >>> (ab & bc).info()['type'] 

+  'ratexpset<lal_char(abc)_z>'</pre> 

== 20140309 == 
== 20140309 == 

Line 2,292:  Line 2,386:  
Both work on automata and ratexps. Left multiplication now has its arguments in a more natural order in the C++ API: (weight, automaton), instead of the converse previously. TAFKit still has it the old way. The Python operator * (leftassociative) is overloaded to provide syntactic sugar. 
Both work on automata and ratexps. Left multiplication now has its arguments in a more natural order in the C++ API: (weight, automaton), instead of the converse previously. TAFKit still has it the old way. The Python operator * (leftassociative) is overloaded to provide syntactic sugar. 

+  <pre>>>> z = vcsn.context('lal_char(abc)_z') 

−  <blockquote><blockquote><blockquote>z = vcsn.context('lal_char(abc)_z') a = z.weight("12") * z.ratexp('ab').standard() * z.weight("23") a.ratexp() (<12>ab)<23> 

+  >>> a = z.weight("12") * z.ratexp('ab').standard() * z.weight("23") 

−  </blockquote></blockquote></blockquote> 

+  >>> a.ratexp() 

−  <blockquote><blockquote><blockquote>z.weight("12") * z.ratexp('ab') * z.weight("23") <12>(ab)<23> 

+  (<12>ab)<23> 

−  </blockquote></blockquote></blockquote> 

+  
+  >>> z.weight("12") * z.ratexp('ab') * z.weight("23") 

+  <12>(ab)<23></pre> 

== 20140308 == 
== 20140308 == 

Line 2,302:  Line 2,399:  
Conversions of both labels and weights are performed if needed. 
Conversions of both labels and weights are performed if needed. 

−  < 
+  <pre>>>> a = vcsn.context('ratexpset<lal_char(xy)_b>_z').ratexp("<2>'x*'") 
+  >>> b = vcsn.context('lal_char(b)_q') .ratexp('<1/3>b') 

−  </blockquote></blockquote></blockquote> 

+  >>> a + b 

+  <2>x*+<1/3>b</pre> 

=== concatenation accepts more heterogeneous arguments === 
=== concatenation accepts more heterogeneous arguments === 

As for products and union, it is now possible to compute the concatenation of automata with different types: 
As for products and union, it is now possible to compute the concatenation of automata with different types: 

−  < 
+  <pre>>>> z = vcsn.context('lal_char(a)_z').ratexp('<2>a') .derived_term() 
+  >>> q = vcsn.context('lal_char(b)_q').ratexp('<1/3>b').derived_term() 

−  </blockquote></blockquote></blockquote> 

+  >>> r = vcsn.context('lal_char(c)_r').ratexp('<.4>c') .derived_term() 

+  >>> (z*q*r).ratexp() 

+  <2>a<0.333333>b<0.4>c</pre> 

== 20140305 == 
== 20140305 == 

Line 2,334:  Line 2,436:  
As for products (Hadamard, shuffle, infiltration), it is now possible to compute the union of automata with different types: 
As for products (Hadamard, shuffle, infiltration), it is now possible to compute the union of automata with different types: 

−  < 
+  <pre>>>> z = vcsn.context('lal_char(a)_z').ratexp('<2>a') .derived_term() 
+  >>> q = vcsn.context('lal_char(b)_q').ratexp('<1/3>b').derived_term() 

−  </blockquote></blockquote></blockquote> 

+  >>> r = vcsn.context('lal_char(c)_r').ratexp('<.4>c') .derived_term() 

+  >>> (zqr).ratexp() 

+  <2>a+<0.333333>b+<0.4>c</pre> 

=== automaton product optimization. === 
=== automaton product optimization. === 

Line 2,342:  Line 2,447:  
Score changes on Luca's workstation (before/after): 
Score changes on Luca's workstation (before/after): 

−  4.60s 2.87s: a.product(a) 
+  <pre>4.60s 2.87s: a.product(a) # a = std([ae]?{50}) 
+  2.34s 2.37s: a.shuffle(a) # a = std([ae]?{50}) 

−  
+  4.01s 2.58s: a.infiltration(a) # a = std([ae]?{30}) 

+  4.17s 2.96s: a**12 # a = std([ae]*b(<2>[ae])*)</pre> 

== 20140218 == 
== 20140218 == 

Line 2,376:  Line 2,483:  
Given two automata, check whether they are isomorphic to one another. Currently implemented in the deterministic case only, for lal contexts. 
Given two automata, check whether they are isomorphic to one another. Currently implemented in the deterministic case only, for lal contexts. 

−  < 
+  <pre>>>> ctx = vcsn.context('lal_char(ab)_z') 
+  >>> ctx.ratexp('a+b*').standard().is_isomorphic(ctx.ratexp('b*+a').standard()) 

−  </blockquote></blockquote></blockquote> 

+  True</pre> 

=== weighted minimization (static, dyn, tafkit, Python) === 
=== weighted minimization (static, dyn, tafkit, Python) === 

Line 2,396:  Line 2,504:  
To install a Vaucanson virtual machine, please follow this procedure: 
To install a Vaucanson virtual machine, please follow this procedure: 

+  <pre>1. Install VirtualBox 

−  # Install VirtualBox From your distro, or from https://www.virtualbox.org/wiki/Downloads. 

−  +  From your distro, or from https://www.virtualbox.org/wiki/Downloads. 

−  # Download this Vagrantfile and save it somewhere. https://www.lrde.epita.fr/dload/vaucanson/2.0/Vagrantfile 

+  2. Install Vagrant 

−  For instance $ mkdir ~/src/vcsn2 $ cd ~/src/vcsn2 $ wget https://www.lrde.epita.fr/dload/vaucanson/2.0/Vagrantfile 

+  From your distro, or from http://www.vagrantup.com/downloads.html 

+  3. Download this Vagrantfile and save it somewhere. 

−  <ol start="4" style="liststyletype: decimal;"> 

+  https://www.lrde.epita.fr/dload/vaucanson/2.0/Vagrantfile 

−  <li>Run Vagrant (first time will be slow: let it download the VM)</li></ol> 

+  For instance 

−  $ cd ~/src/vcsn2 $ vagrant up 

+  $ mkdir ~/src/vcsn2 

+  $ cd ~/src/vcsn2 

+  $ wget https://www.lrde.epita.fr/dload/vaucanson/2.0/Vagrantfile 

+  4. Run Vagrant (first time will be slow: let it download the VM) 

−  Vaucanson is running! 

+  $ cd ~/src/vcsn2 

−  <ol start="5" style="liststyletype: decimal;"> 

+  $ vagrant up 

−  <li><p>Open http://localhost:8888 in your favorite browser.</p></li> 

−  <li><p>Experiment! (Hit ShiftEnter to evaluate): import vcsn vcsn.context('lal_char(abc)_z').ratexp('(<2>a+<3>b)*').derived_term()</p></li> 

−  <li><p>Turn your VM off when you are done $ vagrant halt</p></li></ol> 

+  Vaucanson is running! 

+  
+  5. Open http://localhost:8888 in your favorite browser. 

+  
+  6. Experiment! (Hit ShiftEnter to evaluate): 

+  import vcsn 

+  vcsn.context('lal_char(abc)_z').ratexp('(<2>a+<3>b)*').derived_term() 

+  
+  7. Turn your VM off when you are done 

+  $ vagrant halt</pre> 

== 20140129 == 
== 20140129 == 

Line 2,420:  Line 2,539:  
The "difference" algorithms generates a ratexp that accepts words of the lefthand side that are not accepted by the righthand side ratexp. Also bound as the "%" operator in Python. 
The "difference" algorithms generates a ratexp that accepts words of the lefthand side that are not accepted by the righthand side ratexp. Also bound as the "%" operator in Python. 

+  <pre>>>> ctx = vcsn.context('lal_char(abc)_b') 

−  <blockquote><blockquote><blockquote>ctx = vcsn.context('lal_char(abc)_b') l = ctx.ratexp('[abc]''') r = ctx.ratexp('[ab]''') l.difference(r) (a+b+c)''&(a+b+c)'' l % r (a+b+c)''&(a+b+c)'' 

+  >>> l = ctx.ratexp('[abc]*') 

−  </blockquote></blockquote></blockquote> 

+  >>> r = ctx.ratexp('[ab]*') 

+  >>> l.difference(r) 

+  (a+b+c)*&(a+b+c)* 

+  >>> l % r 

+  (a+b+c)*&(a+b+c)*</pre> 

== 20140127 == 
== 20140127 == 

Line 2,428:  Line 2,552:  
The "intersection" algorithm computes a ratexp that denotes the Hadamard product of two rational expressions. Also bound as the "&" operator in Python. 
The "intersection" algorithm computes a ratexp that denotes the Hadamard product of two rational expressions. Also bound as the "&" operator in Python. 

−  < 
+  <pre>>>> ctx = vcsn.context('lal_char(abc)_b') 
+  >>> r = ctx.ratexp('[abc]*') 

−  </blockquote></blockquote></blockquote> 

+  >>> r.intersection(r) 

+  (a+b+c)*&(a+b+c)* 

+  >>> r & r 

+  (a+b+c)*&(a+b+c)*</pre> 

=== ratexp concatenation: new algorithm (static, dyn, Python) === 
=== ratexp concatenation: new algorithm (static, dyn, Python) === 

The "concatenate" algorithm computes a ratexp that denotes the concatenation of two rational expressions. Also bound as the "*" operator in Python. 
The "concatenate" algorithm computes a ratexp that denotes the concatenation of two rational expressions. Also bound as the "*" operator in Python. 

−  < 
+  <pre>>>> ctx = vcsn.context('lal_char(abc)_b') 
+  >>> r = ctx.ratexp('[abc]*') 

−  </blockquote></blockquote></blockquote> 

+  >>> r.concatenate(r) 

+  (a+b+c)*(a+b+c)* 

+  >>> r * r 

+  (a+b+c)*(a+b+c)*</pre> 

=== Python API: Operators overloading on automata === 
=== Python API: Operators overloading on automata === 

Line 2,454:  Line 2,586:  
Compute the sum of two rational expressions. Also bound as the <code>+</code> operator in Python. 
Compute the sum of two rational expressions. Also bound as the <code>+</code> operator in Python. 

−  < 
+  <pre>>>> ctx = vcsn.context('lal_char(abc)_b') 
+  >>> r = ctx.ratexp('[abc]*') 

−  </blockquote></blockquote></blockquote> 

+  >>> r.sum(r) 

+  (a+b+c)*+(a+b+c)* 

+  >>> r + r 

+  (a+b+c)*+(a+b+c)*</pre> 

=== proper: an optional argument to avoid state deletion === 
=== proper: an optional argument to avoid state deletion === 

Line 2,466:  Line 2,602:  
Computes the starheight of an expression. 
Computes the starheight of an expression. 

−  < 
+  <pre>>>> vcsn.context('lal_char(ab)_b').ratexp('(a***+a**+a*)*').star_height() 
+  4</pre> 

−  </blockquote></blockquote></blockquote> 

=== Bison is no longer needed === 
=== Bison is no longer needed === 

Line 2,478:  Line 2,614:  
It is now possible to use ranges to define alphabets. For instance in Python, 
It is now possible to use ranges to define alphabets. For instance in Python, 

−  vcsn.context('lal_char(azAZ09_)_b') 
+  <pre>vcsn.context('lal_char(azAZ09_)_b')</pre> 
−  
builds a context whose alphabet covers letters, digits, and underscore. 
builds a context whose alphabet covers letters, digits, and underscore. 

Line 2,498:  Line 2,633:  
Before: 
Before: 

−  $ vcsn ladybird 2  vcsn determinize  vcsn auttoexp 
+  <pre>$ vcsn ladybird 2  vcsn determinize  vcsn auttoexp 
+  \e+a.(b+a.a+c.(a+c)*.b)*.(a+c.(a+c)*) 

−  
+  $ vcsn derivedterm Ee 'a:b:c'  vcsn auttoexp 

+  (a.b+b.a).c+(a.c+c.a).b+(b.c+c.b).a</pre> 

After: 
After: 

−  $ vcsn ladybird 2  vcsn determinize  vcsn auttoexp 
+  <pre>$ vcsn ladybird 2  vcsn determinize  vcsn auttoexp 
+  \e+a(b+aa+c(a+c)*b)*(a+c(a+c)*) 

−  
+  $ vcsn derivedterm Ee 'a:b:c'  vcsn auttoexp 

+  (ab+ba)c+(ac+ca)b+(bc+cb)a</pre> 

=== Shortlex order is now used for ratexps === 
=== Shortlex order is now used for ratexps === 

Line 2,510:  Line 2,649:  
Before: 
Before: 

−  $ vcsn derivation e '(a 
+  <pre>$ vcsn derivation e '(a*+b*)a(a*+b*)' aa 
+  a*+b* + a*.a.(a*+b*) + a*</pre> 

−  
After: 
After: 

−  $ vcsn derivation e '(a 
+  <pre>$ vcsn derivation e '(a*+b*)a(a*+b*)' aa 
+  a* + a*+b* + a*a(a*+b*)</pre> 

−  
=== ratexp implementation overhaul === 
=== ratexp implementation overhaul === 

Line 2,522:  Line 2,661:  
The abstractsyntax tree of the rational expressions now matches the usual (abstract) grammar: 
The abstractsyntax tree of the rational expressions now matches the usual (abstract) grammar: 

−  E ::=   a  E+F  E.F  E*  kE  Ek k is a weight 
+  <pre>E ::= \z  \e  a  E+F  E.F  E*  kE  Ek k is a weight</pre> 
−  
In other words, there are now 'leftweight' and 'rightweight' nodes that exist, whereas before, the six first cases carried left and right weights. Trivial identities are enforced, and, for instance, no tree for 'a k' exist: it is converted to 'k a'. 
In other words, there are now 'leftweight' and 'rightweight' nodes that exist, whereas before, the six first cases carried left and right weights. Trivial identities are enforced, and, for instance, no tree for 'a k' exist: it is converted to 'k a'. 

Line 2,540:  Line 2,678:  
The operator <code>&</code> denotes the intersection in the case of Boolean weights, or more generally, the Hadamard product. Only "derived_term" can compute an automaton from it, in which case: 
The operator <code>&</code> denotes the intersection in the case of Boolean weights, or more generally, the Hadamard product. Only "derived_term" can compute an automaton from it, in which case: 

−  derived_term(E & F) = product(derived_term(E), derived_term(F)) 
+  <pre>derived_term(E & F) = product(derived_term(E), derived_term(F))</pre> 
−  
The operator <code>:</code> denotes the shuffle product, aka interleave. For instance <code>a:b:c</code> denotes the language of the permutations of "abc". Only "derived_term" can compute an automaton from it, in which case: 
The operator <code>:</code> denotes the shuffle product, aka interleave. For instance <code>a:b:c</code> denotes the language of the permutations of "abc". Only "derived_term" can compute an automaton from it, in which case: 

−  derived_term(E : F) = shuffle(derived_term(E), derived_term(F)) 
+  <pre>derived_term(E : F) = shuffle(derived_term(E), derived_term(F))</pre> 
−  
=== minimization is much faster === 
=== minimization is much faster === 

Line 2,556:  Line 2,692:  
When dyn::make_context is presented with an unknown but valid context, it is compiled and loaded dynamically. For instance: 
When dyn::make_context is presented with an unknown but valid context, it is compiled and loaded dynamically. For instance: 

−  $ vcsn cat C 'lao_r' W e 
+  <pre>$ vcsn cat C 'lao_r' W e 3.14 
+  # Wait for the context to be compiled... 

−  
+  3.14</pre> 

The compiled context is currently left in /tmp for forthcoming runs. 
The compiled context is currently left in /tmp for forthcoming runs. 

−  $ ls /tmp/lao* 
+  <pre>$ ls /tmp/lao* 
+  /tmp/lao_r.cc /tmp/lao_r.o /tmp/lao_r.so</pre> 

−  
=== Python binding === 
=== Python binding === 

Revision as of 07:37, 17 March 2018
This file describes user visible changes in the course of the development of Vcsn, in reverse chronological order. On occasions, significant changes in the internal API may also be documented.
Vcsn 2.7 (To be released)
New features
vcsn score has several new options
The command vcsn score
benchmarks Vcsn. Its output can be processed with vcsn scorecompare
to see the trends in performances between versions.
The new option o
/output
allows to specify the output file name.
Better yet: option d
/dir
specifies the directory in which the score file is saved; its name will be forged from git describe
, something like v2.5050g01dbf326
. Such names are interpreted by vcsn scorecompare
to relate the benches to the git commit title. Both features need that you run these commands from a git repository of Vcsn.
Option j
/job
allows to run the benchmarks concurrently. This can be very useful to "warm" vcsn (have it compile the needed algorithms), or to get a nice approximation of the actual benches, however, sticking to a single bench at a time is recommended to get faithful measurements.
Bug fixes
Incorrect order for 8bit characters
Calling compare
on labels would lead to surprising results with 8bit characters (seen as negative ints). This resulted in the incorrect display of the expression [\x01\xfe]
as [\x80\xfe] + [\x01\x7f]
.
Both are fixed, and 1 is less than 254 again.
Vcsn 2.6 (20171113)
The Vcsn team is happy to announce the long overdue release of Vcsn 2.6. Most of our work was devoted to providing a better, smoother, user experience. This includes improvements in the build system, better performances, extended consistency, and more legible error messages. Multitape expressions also received a lot of attention.
For more information see the detailed news below.
We warmly thank our users who made valuable feedback (read "bug reports"): Victor Miller, Dominique Soudière and Harald Schilly. Dominique and Harald helped integrating Vcsn into CoCalc (formerly SageMathCloud).
People who contributed to this release:
 Akim Demaille
 Clément Démoulins
 Clément Gillard
 Sarasvati Moutoucomarapoulé
New features
Promotion from single to multitape
It is now possible to mix singletape expressions with multitape expressions. This is especially handy when using labels classes ([abc]
). For instance:
In [2]: zmin2 = vcsn.context('lat<lan, lan>, zmin') In [3]: zmin2.expression(r'([ab] + ⟨1⟩(\e[ab] + [ab]\e))*') Out[3]: (aa+bb+<1>(\e(a+b)+(a+b)\e))*
is a easy means to specify an expression generating an automaton that computes the editdistance (between words or languages). Or, with a wide alphabet:
In [4]: zmin = vcsn.context('lan(az), zmin') In [5]: zmin2 = zmin  zmin In [6]: zmin2 Out[6]: {abcdefghijklmnopqrstuvwxyz}? x {abcdefghijklmnopqrstuvwxyz}? > Zmin In [7]: zmin2.expression(r'([^] + ⟨1⟩(\e[^] + [^]\e))*')
In the future the display of expressions will also exploit this approach.
vcsn compile now links with precompiled contexts
If you write a program using dyn::, then it will benefit from all the precompiled algorithms.
vcsn compile now supports debug
Use this to avoid the removal of intermediate object files. On some platforms, such as macOS, the object file contains the debug symbols, so their removal makes the use of a debug harder.
vcsn compile now uses rpath
Programs/libraries generated by vcsn compile
needed to be told where the Vcsn libraries were installed. In practice, it meant that vcsn run
was needed to execute this program, and in some situations it was not even sufficient.
Now, vcsn compile myprog.cc
generates myprog
which can be run directly.
random_expression supports the tuple operator
It is now possible to generate multitape expressions such as (ax*)*
. Before, random_expression was limited to expressions on multitape labels such as (ax)*
.
In [1]: import vcsn In [2]: c = vcsn.context('lan(abc), q') In [3]: c2 = c  c In [4]: for i in range(10): ...: e = c2.random_expression(', +, ., *=.2, w.=.2, w="min=2, max=2"', length=10) ...: print('{:u}'.format(e)) ...: aa+(εb)*+⟨1/2⟩εε (ε+c)a(⟨2⟩ε+c) (εb+(ca)*)* εa+ab cb+⟨2⟩ε(ε+b) εa+((aε)(εb)(εc))*(bε) (ab+cε)(ab) ε*ε ε+aa+⟨2⟩(bε) (ε+ε*)ε
Generating expressions with compose operators is also supported.
In [5]: for i in range(10): ...: e = c2.random_expression('=.5, +, ., @=2', length=10, identities='none') ...: print('{:u}'.format(e)) ...: ((bε)ε)(ε(εa)) ε(εc)+((εa)(ab)+εc) ((εa)(εb))((ba)(cc)@bb) (bb@ε+ab)@(cε@bε) (ε+εa)@(εc@εa+bε) (εa+εc)((εb)(cε)) (aε)((ε+c)(a+ε)) cε@(aε)(εb@bε) (ε+εb)@εb+εa b(ε²)((ε+ε)+a)
New algorithms
A few algorithms were added:
context.compose
Composing
{abc} x {xyz}
with{xyz} x {ABC}
gives, of course,{abc} x {ABC}
.expansion.normalize, expansion.determinize
These are rather lowlevel features. The latter is used internally when derivedterm is asked for a deterministic automaton.
expansion.expression
The "projection" of an expansion as an expression.
label.compose
For instance
abx @ xc
>abc
.polynomial.compose
Additive extension of monomial composition. For instance composing
aex + aey + ae\e
withxEA + yEA + \eEA
gives<3>aeEA
.polynomial.shuffle and polynomial.infiltrate
The missing siblings of polynomial.conjunction.
Doxygen is no longer needed
By default, make install
generated and installed the C++ API documentation using Doxygen. It is now disabled by default, pass enabledoxygen
to configure
to restore it.
Bug Fixes
Severe performance regression when reading daut
Version 2.5 introduced a large penalty when reading daut files, especially large ones.
Tupling of automata could be wrong on weights
As a consequence, expression.inductive
was also producing incorrect automata from multitape expressions.
Polynomials featuring the zerolabel
Under some circumstances it was possible to have polynomials featuring monomials whose label is the zero of the labelset (e.g., \z
with expressions as labels). This is fixed.
Portability issues
Newest compilers are now properly supported.
Changes
Divisions
The division of expressions and automata now compute the product of the weights, not their quotient.
Handling of the compose operator
The support of the compose operators in expansions was completely rewritten. As a result, the derivedterm automata are often much smaller, since many useless states (non coaccessible) are no longer generated.
For instance the derivedterm automaton of (\ea)* @ (aa\e)*
has exactly two states. It used to have three additional useless states.
Better diagnostics
Many error messages have been improved.
The Daut automaton format now treats >
as a keyword, so 0>1 a
is now properly read instead of producing a weird error message because Vcsn thought your state was named 0>1
.
Vcsn 2.5 (20170128)
The Vcsners are proud to announce the release of Vcsn 2.5, aka the klightest release!
Noteworthy changes include:
 two new implementations to compute the klightest paths (aka "best" paths: with the smallest weights) in tropical automata.
 several new demos showing how to use the C++ library, including a translator from (French) text messages (aka SMS) into French.
 a new means for the users to configure Vcsn. This adds a new prerequisite to build Vcsn: libyamlcpp.
 a much better and faster caching system of runtime generated C++ code. Users of dyn (and therefore of Python) should note an improved amortization of the compilation costs.
 several portability issues reported by users were fixed.
For more information, please, see the detailed news below.
People who worked on this release:
 Akim Demaille
 Clément Démoulins
 Clément Gillard
 Sarasvati Moutoucomarapoulé
 Sébastien Piat
 Younes Khoudli
20170123
Improved error messages
Parse errors were improved with caretstyle reports for expressions and automata in dot (Graphviz) and daut syntax.
In [5]: vcsn.Q.expression('<1/2>a + <1/0>b') RuntimeError: 1.1014: Q: null denominator <1/2>a + <1/0>b ^^^^^ while reading expression: <1/2>a + <1/0>b In [6]: vcsn.automaton(''' ...: $ > 0 ...: 0 > 1 <1/2>a, b ...: 1 > $''') RuntimeError: 3.116: B: unexpected trailing characters: /2 while reading: 1/2 while reading: <1/2>a, b 0 > 1 <1/2>a, b ^^^^^^^^^^^^^^^^ while reading automaton In [7]: vcsn.automaton('digraph{vcsn_context="lal, b" 0>1[label="<2>a"]}') RuntimeError: 1.3548: B: invalid value: 2 while reading: 2 while reading: <2>a digraph{vcsn_context="lal, b" 0>1[label="<2>a"]} ^^^^^^^^^^^^^^ while reading automaton
20170114
"auto" automaton file format
Pass "auto" to read_automaton (in dyn, static, Python or the Tools) to let the system guess the automaton file format (daut, dot, etc.).
20170111
Sms2fr
New Natural Language Processing demonstration of the computations of the lightest paths. This application is a translator from SMS (i.e., text messages) to proper French. The implementation is based on Rewriting the orthography of SMS messages, François Yvon, In Natural Language Engineering, volume 16, 2010. The translator uses pretrained automata and through compositions with the automaton representing the text message, generates all possible translations of the word. The best solution is then found with a shortest path algorithm. An example is given in the Sms2fr.ipynb
notebook.
20170101
A richer dyn
The vcsn::dyn
API was enriched. All the dyn types now support the usual operators: comparisons (==
, !=
, <
, <=
, >
, >=
), and compositions (+
, *
, &
). New functions facilitate the creation of dyn
values from strings (make_word
, etc.). The file tests/demos/operators.cc
shows several examples, explained in the C++Library.ipynb
notebook. For instance:
// A simple automaton. auto a1 = make_automaton("context = lal, q\n" "$ 0 <1/2>\n" "0 1 <2>a, <6>b\n" "1 $\n", "daut"); // Its context. auto ctx = context_of(a1); // Evaluate it. assert(evaluate(a1, make_word(ctx, "a")) == make_weight(ctx, "1")); assert(evaluate(a1, make_word(ctx, "b")) == make_weight(ctx, "3")); // Concatenate to itself. auto a2 = a1 * a1; assert(evaluate(a2, make_word(ctx, "ab")) == make_weight(ctx, "3")); // Selfconjunction, aka "power 2". auto a3 = a1 & a1; assert(evaluate(a3, make_word(ctx, "b")) == make_weight(ctx, "9"));
20161225
Configuration
Vcsn now supports configuration files. They will be used to provide users with a means to customize Vcsn, for instance to tune the graphical rendering of the automata, to tailor the display of expressions, etc.
For a start, it provides a simple means to get the configuration information, including from Vcsn Tools.
$ vcsn ipython nobanner In [1]: import vcsn In [2]: vcsn.config('configuration.cxxflags') Out[2]: 'Qunusedarguments O3 g std=c++1z' $ vcsn configuration configuration.cxxflags Qunusedarguments O3 g std=c++1z
This adds a new dependency: libyamlcpp. Beware that version 0.5.2 is buggy and will not work properly. Use 0.5.1, or 0.5.3 or more recent.
20161220
compare: new algorithm
Threeway comparison is now available in all the layers, as compare
, for automata, expressions, labels, polynomials and weights. This is used in Python to implement the comparisons (<
, <=
, >
, =>
, ==
, !=
) of expressions, and of automata (<
, <=
, >
, =>
).
However, since the comparison on automata is performed on the list of transitions, automata that are "very much alike" (i.e., different only by superficial details) will be considered different, so ==
and !=
are still using a safer, but much slower, comparison.
In [2]: exp = vcsn.Q.expression In [3]: exp('a').compare(exp('b')) Out[3]: 1 In [4]: exp('a').compare(exp('a')) Out[4]: 0 In [5]: exp('<3>a').compare(exp('a')) Out[5]: 1
20161212
k shortest paths algorithms
Two algorithms for searching k shortest paths in graphs have been implemented: "Eppstein" and "Yen". Hence, we can now search for the k lightest (smallest with respect to weights, aka "best" paths) paths in an automaton through the "lightest" algorithm. "lightest" used to compute these paths with an inefficient heapbased implementation:
aut.lightest(5) aut.lightest(5, "auto")
Note that "auto" does not use the latter algorithm when returning only one path, as simpler shortest path algorithms would apply to the situation and be more efficient. It then uses Dijkstra's algorithm. It can now be called with the given Yen and Eppstein algorithms as follows:
aut.lightest(5, "eppstein") aut.lightest(5, "yen")
Yen's algorithm requires the given automaton to have no cycles, while Eppstein supports any type of automaton. For small values of k, Yen's algorithm has better performances than Eppstein, but with increasing values of k, Eppstein is always more efficient.
Vcsn 2.4 (20161116)
The Vcsn team is happy to announce the release of Vcsn 2.4, codenamed "the quotient tools"!
Noteworthy changes include, besides a few bug fixes:
an overhaul of the "Vcsn Tools" (previously known as TAFKit). Because the tools are now automatically generated, they are much more extensive than previously: (almost) all of the dyn algorithms are now available from the shell. It now also supports the 'daut' format for automata.
$ vcsn thompson Ee '[ab]*c'  vcsn proper  vcsn determinize  vcsn minimize  vcsn toexpression (a+b)*c $ vcsn randomexpression C 'lal(abc), z' '+, ., w., length=20, w="min=2, max=10"' (a+<2>(ac)+<5>(acca))a
an new method to construct an automaton from an extended expression:
expression.inductive
. This provides an alternative toexpression.derived_term
. Currently provides a single flavor: generation of standard automata.In [2]: vcsn.B.expression('! [ab]*a[ab]*').inductive().expression() Out[2]: +bb* In [3]: vcsn.B.expression('! [ab]*a[ab]*').automaton().expression() Out[3]: b*
full support for quotient operators on all entities: labels, expressions, automata, expansions, etc.
In [2]: c = vcsn.context('lan, q') ...: c Out[2]: {...}? > Q In [3]: label = vcsn.context('law, q').label ...: label('abc') / label('c') Out[3]: ab In [4]: exp = c.expression In [5]: exp('ab').ldivide(exp('ab*c')) Out[5]: ab{\}ab*c In [6]: e = exp('ab').ldivide(exp('ab*c')) ...: e Out[6]: ab{\}ab*c In [7]: e.automaton().expression() Out[7]: b*c
Operators {\} (left quotient) and {/} (right quotient) are available in the rational expressions:
In [8]: e = exp('ab {\} abc*') ...: e Out[8]: ab{\}abc* In [9]: e.expansion() Out[9]: \e.[b{\}bc*] In [10]: e.derived_term().expression() Out[10]: c* In [11]: e.inductive().expression() Out[11]: \e+cc*
automaton.evaluate
works properly on nonfree automata, including multitape automata:In [2]: c = vcsn.context('lan(az), nmin') ...: a = (cc).levenshtein() ...: a('foobar') Out[2]: 3
input/output support for FAdo's format for transducers, and improved compatibility with OpenFST.
For more information, please, see the detailed news below.
People who worked on this release:
 Akim Demaille
 Clément Gillard
 Lucien Boillod
 Sarasvati Moutoucomarapoulé
 Sébastien Piat
 Younes Khoudli
People who have influenced this release:
 Alexandre DuretLutz
 Jacques Sakarovitch
 Luca Saiu
 Sylvain Lombardy
20161104
random_automaton now generates weights
context.random_automaton
now takes an optional weights
parameter, allowing to set how the weights are generated. The syntax is the same as the param
string of random_weights
.
In [1]: import vcsn ctx = vcsn.context('lal_char(ab), z') a = ctx.random_automaton(3, weights='min=0, max=20') print(a.format('daut')) context = letterset<char_letters(ab)>, z $ > 0 0 > $ 0 > 2 <17>b 1 > 1 <13>b 1 > 2 <11>b 2 > 0 <18>a, <13>b 2 > 1 <12>a
20161031
eval is renamed evaluate
For consistency with the remainder of the API, we use the full, unabbreviated, name: evaluate.
20161018
weight_zero and weight_one are now available in Python
These methods return the "zero" and "one" weights of a context.
In [1]: import vcsn ctx = vcsn.context('lal_char, zmin') In [2]: ctx.weight_one() Out[2]: 0 In [3]: ctx.weight_zero() Out[3]: ∞
20161017
Left and right divisions are now supported on labels
It is now possible to call left and right divisions on labels from Python, using //
and /
operators (respectively).
In [1]: import vcsn ctx = vcsn.context('law_char, b') In [2]: l = ctx.label('a') r = ctx.label('abc') l // r # == l.ldivide(r) Out[2]: bc In [3]: l = ctx.label('abc') r = ctx.label('bc') l / r # == l.rdivide(r) Out[3]: a
20161011
TAFKit is replaced by Tools
The new command line interface is now automatically generated from the algorithms in dyn, allowing it to support a lot more functions than previously.
The supported algorithms are:
accessible add ambiguousword areequivalent areisomorphic cat cerny coaccessible codeterminize cominimize complement complete component compose concatenate condense conjugate conjunction constantterm contextof copy costandard cotrie debruijn delayautomaton derivation derivedterm determinize difference divkbaseb eliminatestate eval expand expressionone expressionzero factor focus getformat hasboundedlag haslighteningcycle hastwinsproperty identitiesof inductive infiltrate insplit isaccessible isambiguous iscoaccessible iscodeterministic iscomplete iscostandard iscycleambiguous isdeterministic isempty isepsacyclic isfunctional isletterized isnormalized isoutsorted ispartialidentity isproper isrealtime isstandard issynchronized issynchronizedby issynchronizing istrim isuseless isvalid join ladybird ldivide lessthan letterize levenshtein lgcd lift lightest lightestautomaton lweight makecontext makewordcontext minimize multiply normalize numcomponents numtapes pair partialidentity prefix project proper pushweights quotkbaseb randomautomaton randomautomatondeterministic randomexpression randomweight rdivide realtime reduce rweight scc setformat shortest shuffle sort split standard star starheight starnormalform strip subword suffix synchronize synchronizingword thompson toautomaton toexpansion toexpression transpose transposition trie trim tuple type u universal weightseries zpc
To get more information about a particular algorithm, you can type vcsn COMMAND h
or help
:
$ vcsn eval help usage: vcsn eval [OPTIONS...] [ARGS...] Available versions: eval: AUT:automaton P:polynomial > weight Evaluate P on AUT. eval: AUT:automaton L:word > weight Evaluate L on AUT. Try 'vcsn tools help' for more information.
You can for example generate the Thompson automaton that accepts ab*
:
$ vcsn thompson 'ab*' O daut $ > 0 0 > 1 a 1 > 4 \e 2 > 3 b 3 > 2 \e 3 > 5 \e 4 > 2 \e 4 > 5 \e 5 > $
For more information, please see the Executables documentation page, and vcsn tools h
.
20161004
FAdo: transducers and comments support
It is now possible to read and produce transducers in FAdo format. Comments are also supported in the parser.
In [1]: a = vcsn.automaton(data=''' @Transducer 0 2 * 0 # Final * Initial 0 0 @epsilon 1 0 0 0 0 0 1 @epsilon 1 0 1 1 0 1 @epsilon 0 2 1 @epsilon 1 2 1 0 0 1 1 1 1 1''') In [2]: print(a.format('fado')) @Transducer 0 2 * 0 0 0 @epsilon 1 0 0 0 0 0 1 @epsilon 1 0 1 1 0 1 @epsilon 0 2 1 @epsilon 1 2 1 0 0 1 1 1 1 1
20160927
daut native parser and producer
Daut is a simplified Dot syntax for automata. This format was only available in Python. It is now possible to read and produce it in C++.
$ vcsn cat A I daut O daut f lal_char_q.daut context = letterset<char_letters(abc)>, q $ > 0 <3> 0 > 1 <1/2>a, <1/3>b 1 > $ <2>
20160921
Improved compatibility with newer OpenFST
As OpenFST only supports a single initial state, pre is showed in case of several ones, with spontaneous transitions to them. Pre was represented by a very large integer which was read as a negative one in newer version of OpenFST, thus raising an error. The state number immediately after the highest state number is now used.
20160919
automaton.eval supports polynomials
It is now possible to evaluate polynomials of words on automata.
20160912
make_word_context is exposed in Python
It is now possible to call context.word_context()
to get the context of the words of any context.
20160908
automaton.eval supports nonfree labelsets
It is now possible to evaluate words on automata with nonfree labelsets.
For example, we can compute the edit distance between two words:
In [2]: c = vcsn.context('lan(az), nmin') a = (cc).levenshtein() a('foobar') Out[2]: 3 In [3]: a('barbaz') Out[3]: 1 In [4]: a('quxquuux') Out[4]: 2
20160728
expression: inductive
Implemented as a hidden feature in Vcsn 2.3, expression.inductive
is a new way of constructing automata from expressions, based on the algorithm given as argument. The only algorithm implemented yet is "standard" which uses standard operations to construct a standard automaton. The difference with expression.standard
is that it handles extended expressions.
For example, we can compute the automaton equivalent of such expressions with the inductive method whereas we cannot with the standard one:
In [2]: vcsn.B.expression('! [ab]*a[ab]*').inductive().expression() Out[2]: \e+bb*
expression.derived_term supports multitape expressions
Vcsn 2.3 already supports multitape expressions with the derivedterm algorithm, but it was restricted to the expansionbased computation. The derivativebased computation is now also supported.
This is only a proof of concept: the implementation is more complex and much slower than the expansionbased approach.
20160725
expression.derivation works on multitape expressions
It is now possible to compute derivatives wrt labels such as ax
, a\e
or \ex
. It is however forbidden wrt \e\e
.
20160723
automaton.info: levels of detail
Instead of a Boolean argument detailed
, info
now features an integer argument details
, defaulting to 2. A new level, 1, contains only basic information (number of states and transitions).
20160719
expression: partial_identity
The partial_identity
algorithm is now available on expressions too.
tuple: applies to contexts
It is now possible from dyn and Python to tuple several contexts. For instance vcsn.B  vcsn.Q
is lat<lal, lal>, q
.
Vcsn 2.3 (20160708)
About four hundred commits and five months after Vcsn 2.2, we are proud to announce the release of Vcsn 2.3, codenamed "the tuple release"!
As usual, many bugs were fixed (some quite old yet unnoticed so far!). Noteworthy changes include:
a particular effort was put on the documentation: there are thirtyfive new documentation pages, and about forty others were improved.
full support for a "tuple" operator on all entities: expressions, polynomials, automata, etc.
In [13]: aut = lambda e: vcsn.context('lan, q').expression(e).automaton() In [14]: a = aut('[ab]*')  aut('x') In [15]: a.shortest(6) Out[15]: x + ax + bx + aax + abx + bax
It is also available in the rational expressions themselves:
In [16]: c = vcsn.context('lat<lan, lan>, q'); c Out[16]: {...}? x {...}? > Q In [17]: e = c.expression('[ab]*x'); e Out[17]: (a+b)*x In [18]: e.shortest(6) Out[18]: \ex + ax + bx + aax + abx + bax
The derivedterm algorithm supports this operator, and generates equivalent multitape automata.
In [2]: vcsn.Q.expression('a**').derivation('a') RuntimeError: q: star: invalid value: 1
we now display:
In [2]: vcsn.Q.expression('a**').derivation('a') RuntimeError: Q: value is not starrable: 1 while computing derivative of: a** with respect to: a
%automaton a
, which allows interactive edition of automata, the notebooks now feature two new interactive editors: %context c
to edit/create context c
, and %expression e
for expressions (with an interactive display of the generated automata).People who worked on this release:
 Akim Demaille
 Clément Gillard
 Lucien Boillod
 Raoul Billion
 Sébastien Piat
 Thibaud Michaud
People who have influenced this release:
 Alexandre DuretLutz
 Jacques Sakarovitch
 Luca Saiu
 Sylvain Lombardy
20160628
Command line executables
The shell tools (formerly known as TAFKit) such as vcsn standard
, vcsn determinize
, etc. have finally been documented! Several issues have been fixed too.
20160627
expression widget
You can now use %expression
in the notebook to interactively edit an expression and its context while seeing the automaton it builds. You are also able to chose the identities you want to use for the expression, and the automaton generating algorithm used to render the automaton.
20160620
proper: more consistent signatures
The Python binding of automaton.proper
was different from the static and dyn:: versions for no sound reason: instead of a direction
argument taking backward
or forward
, it had a backward
argument taking an Boolean, and the prune
and direction
(well, backward
) arguments were swapped.
The signature in Python is now consistent: aut.proper(direction="backward", prune=False, algo="auto", lazy=False)
.
20160616
renamings
The following operations have been renamed, in all APIs (vcsn::, dyn::, Python, and TAFKit), and on all applicable types (automaton, expansion, expression, polynomial, weight).
infiltration > infiltrate ldiv > ldivide left_mult > lweight rdiv > rdivide right_mult > rweight sum > add
20160607
random_automaton: new name for random
Random generation of automata is now named random_automaton
.
20160527
polynomials: more basic operations
Polynomials now support (in the three layers) the addition, multiplication, exterior products, and conjunction.
In [4]: p = vcsn.context('law, q').polynomial In [5]: p0 = p('<2>a + <3>b + <4>c'); p1 = p('<5>a + <6>b + <7>d') In [6]: p0 + p1 Out[6]: <7>a + <9>b + <4>c + <7>d In [7]: p0 * p1 Out[7]: <10>aa + <12>ab + <14>ad + <15>ba + <18>bb + <21>bd + <20>ca + <24>cb + <28>cd In [8]: p0 * 2 Out[8]: <4>a + <6>b + <8>c In [9]: 2 * p0 Out[9]: <4>a + <6>b + <8>c In [10]: p0 & p1 Out[10]: <10>a + <18>b
20160525
tuple: applies to more types
The Cartesian product, dubbed "tuple" in Vcsn, was already available on expansions and expressions in the three layers (static, dyn, Python as 
). It is now also available on automata and on polynomials.
In [2]: exp = vcsn.context('lan, q').expression In [3]: a = exp('(<2>a)*').automaton() In [4]: b = exp('x+y').automaton() In [5]: (ab).shortest(8) Out[5]: \ex + \ey + <2>ax + <2>ay + <4>aax + <4>aay + <8>aaax + <8>aaay In [6]: a.shortest(4)  b.shortest(2) Out[6]: \ex + \ey + <2>ax + <2>ay + <4>aax + <4>aay + <8>aaax + <8>aaay
20160520
quotkbaseb: new algorithm
From a context, a divisor k, and a base b, gives a transducer that, when given a number in b divisible by k, outputs the quotient of the division of that number by k in b.
In [2]: c = vcsn.context('lat<lal_char(09), lal_char(09)>, b') In [3]: c.quotkbaseb(3, 2).shortest(10) Out[3]: \e\e + 00 + 0000 + 1101 + 000000 + 011001 + 110010 + 00000000 + 00110001 + 01100010 In [4]: c.quotkbaseb(7, 10).shortest(10) Out[4]: \e\e + 00 + 71 + 0000 + 0701 + 1402 + 2103 + 2804 + 3505 + 4206
20160502
expansions: support for &
In addition to automata, expressions and polynomials, the conjunction can now be performed on expansions.
20160430
sum: optimized version for deterministic automata
The sum of deterministic Boolean automata is now based on a synchronized productlike approach.
dyn: vast overhaul and factoring
The implementation of dyn:: values was revised and factored. No visible change.
20160414
random_expression
One may now generate random expressions.
In [2]: rand = vcsn.context('lal(abc), b').random_expression In [3]: rand('+,.', length=10) Out[3]: c(b+c+ca)c In [4]: rand('+,.', length=10) Out[4]: c+abcac In [5]: rand('+=1, .=1, *=.2', length=10) Out[5]: (b(a+b+c))* In [6]: rand('+=1, .=1, *=.2', length=10) Out[6]: bb*ca In [7]: rand('+=1, .=1, *=.2, &=1', length=10) Out[7]: c In [8]: rand('+=1, .=1, *=.2, &=1', length=10) Out[8]: a*cb* In [9]: rand('+=1, .=1, *=.2, &=1', length=10) Out[9]: a((a+a*)&b*)*
20160329
project: support for expressions and expansions
One may now project (multitape) automata, contexts, expansions, expressions, labels and polynomials.
20160315
expression: a dot output
Expressions now feature a "dot"
format to display graphically the structure of the expression. There are actually two flavors: "dot,logical"
(the default) which shows the semantic tree, and "dot,physical"
which shows the DAG that is used to implement the expression (i.e., nodes used multiple times are displayed only once).
Under IPython, experiment exp.SVG()
(logical) and exp.SVG(True)
(physical).
Python: format
The Python objects now support the format
protocol. For instance:
In [2]: c = vcsn.context('lal(abc), q') In [3]: for i in range(4): e = c.expression('[ab]*a[ab]{{{i}}}'.format(i=i)) print('{i:3d}  {e:t:20}  {e:u:20}  {n:3d}' .format(i=i, e=e, n=e.automaton().determinize().state_number())) 0  (a+b)*a  (a+b)*a  2 1  (a+b)*a(a+b)  (a+b)*a(a+b)  4 2  (a+b)*a(a+b){2}  (a+b)*a(a+b)²  8 3  (a+b)*a(a+b){3}  (a+b)*a(a+b)³  16
20160308
ldiv, rdiv: compute quotient between automata
automaton.ldiv
and automaton.rdiv
compute the left and right quotients of two automata.
In [1]: import vcsn ctx = vcsn.context('lal_char, b') aut = lambda e: ctx.expression(e).automaton() In [2]: aut('ab').ldiv(aut('abcd')).expression() Out[2]: cd In [3]: (aut('abcd') / (aut('cd')).expression() Out[3]: ab
Vcsn 2.2 (20160219)
We are very happy to announce the release of Vcsn 2.2! This version, codenamed "the lazy release", concludes the work from Antoine and Valentin, who left EPITA for their final internship.
In addition to the usual load of improvements (more doc and less bugs), this version features some noteworthy changes:
 several algorithms now offer a lazy variant: compose, conjunction, derived_term, determinize, insplit, and proper. Instead of completing the construction on invocation, the result is built incrementally, on demand, e.g., when requested by an evaluation.
This is especially useful for large computations a fraction of which is actually needed (e.g., composition of two large automata and then with a small one), or for computations that would not terminate (e.g., determinization of some weighted automata).
 the functions
automaton.lightest
andautomaton.lightest_automaton
explore the computations (i.e., paths of accepted words) with the smallest weights (dubbed "shortest paths" for tropicalmin semirings). They feature several implementations controlled via thealgo
argument.  rational expressions now support UTF8 operators in input and output. They also learned a few tricks to be better looking (e.g.,
aaa
=>a³
).  several new algorithms or improvements or generalizations of existing ones.
 a number of performance improvements.
Please, see the details below.
People who worked on this release:
 Akim Demaille
 Antoine Pietri
 Lucien Boillod
 Nicolas Barray
 Raoul Billion
 Sébastien Piat
 Thibaud Michaud
 Valentin Tolmer
People who have influenced this release:
 Alexandre DuretLutz
 Jacques Sakarovitch
 Luca Saiu
 Sylvain Lombardy
20160213
operations on automata: deterministic versions
In addition to the "general"
, "standard"
and "auto"
variants, multiply, sum and star now support a "deterministic"
variant, which guarantees a deterministic result.
Beware that with infinite semirings, some (deterministic) operations might not terminate.
20160205
conjugate: new algorithm
The automaton.conjugate
function builds an automaton whose language is the set of conjugates (i.e., "rotations", or "circular permutations") of the words accepted by the input automaton.
In [3]: vcsn.context('lan_char, b') \ .expression('(ab)*') \ .automaton() \ .conjugate() \ .expression() Out[3]: (ab)*+(ab)*{2}+(ba)*ba(ba)*
demangle: add a gdb prettyprinter for Vcsn types
vcsn gdb
runs gdb with a prettyprinter, which will automatically Vcsn's demangle()
function when a variable with a vcsn type is printed. Symbols are then much easier to read.
insplit: support for onthefly construction
The implementation of insplit
now supports a lazy
argument. This is especially useful when composing a small transducer with a big one, to avoid computing the insplit of the right transducer for many states, that are not going to be useful.
It is used in the composition algorithm for this very reason.
compose: support for onthefly construction
The implementation of compose
now supports a lazy
argument. This is especially useful when composing two big transducers, and then compose with several small ones. The result of the first composition, although huge, will never be completely computed, but the required states are computed and cached.
20160128
determinize: support for onthefly construction
The implementation of determinize
now supports a lazy
argument. This is especially useful when working on automata that do not admit a (finite) deterministic automaton.
For instance:
In [2]: a = vcsn.Z.expression('a*+(<2>a)*').automaton().determinize(lazy=True) In [3]: print(a.as_boxart()) ╭───╮ ──> │ 0 │ ╰───╯ In [4]: a('') Out[4]: 2 In [5]: print(a.as_boxart()) ╭───╮ a ╭─────────╮ ──> │ 0 │ ───> │ 1, ⟨2⟩2 │ ╰───╯ ╰─────────╯ │ │ ⟨2⟩ ∨ In [6]: a('aa') Out[6]: 5 In [7]: print(a.as_boxart()) ╭───╮ a ╭─────────╮ a ╭─────────╮ a ╭─────────╮ ──> │ 0 │ ───> │ 1, ⟨2⟩2 │ ───> │ 1, ⟨4⟩2 │ ───> │ 1, ⟨8⟩2 │ ╰───╯ ╰─────────╯ ╰─────────╯ ╰─────────╯ │ │ │ │ ⟨2⟩ │ ⟨3⟩ │ ⟨5⟩ ∨ ∨ ∨
20160114
lightest: algorithms for "shorter paths"
The automaton.lightest
looks for words (possibly several) whose evaluation is the smallest one in the automaton. In the case of ℕmin and other tropical semiring, this is often referred to as "shortest paths", but it applies to other semirings as well. It features the same interface as automaton.shortest
(which looks for shortest accepted words), but offers several variants, such as "dijkstra"
, "bellmanford"
, "auto"
...
The automaton.lightest_automaton
algorithm returns a slice of the automaton corresponding to the evaluation with the small weight. It also offers several variants.
20160109
derivedterm: support for onthefly construction
The implementation of derived_term
now supports a lazy
argument. This is especially useful when working on "infinite derivedterm automata" (which happens when requesting a deterministic automaton, or when using the complement operator).
For instance:
In [2]: a = vcsn.Z.expression('a*+(<2>a)*').derived_term(deterministic=True, lazy=True) In [3]: print(a.as_boxart()) ╭────────────╮ ──> │ a*+(⟨2⟩a)* │ ╰────────────╯ In [4]: a('') Out[4]: 2 In [5]: print(a.as_boxart()) ╭────────────╮ a ╭───────────────╮ ──> │ a*+(⟨2⟩a)* │ ───> │ a*+⟨2⟩(⟨2⟩a)* │ ╰────────────╯ ╰───────────────╯ │ │ ⟨2⟩ ∨ In [6]: a('aa') Out[6]: 5 In [7]: print(a.as_boxart()) ╭────────────╮ a ╭───────────────╮ a ╭───────────────╮ a ╭───────────────╮ ──> │ a*+(⟨2⟩a)* │ ───> │ a*+⟨2⟩(⟨2⟩a)* │ ───> │ a*+⟨4⟩(⟨2⟩a)* │ ───> │ a*+⟨8⟩(⟨2⟩a)* │ ╰────────────╯ ╰───────────────╯ ╰───────────────╯ ╰───────────────╯ │ │ │ │ ⟨2⟩ │ ⟨3⟩ │ ⟨5⟩ ∨ ∨ ∨
20151231
project is available on more structures
One may now project not only multitape automata, but also contexts, labels and polynomials.
20151223
haslighteningcycle: new name for hasnegativecycle
In static, dyn:: and Python, hasnegativecycle
is renamed haslighteningcycle
. It makes more sense as we consider (<1/2>a)*
to be a lightening cycle.
20151221
Operators on expressions and expansions
The dyn::complement
function is now available on expansions, in addition to expressions and automata. It is bound to the prefix ~
operator in Python. The dyn::tuple
function is available for expressions and expansions. It is bound to 
in Python.
20151210
Exponents in expressions
In addition to "ASCII exponents" in input (e.g., (ab){4}
), we now support them in output, possibly in UTF8:
In [7]: vcsn.B.expression('aa{2}a²') Out[7]: a{5} In [8]: print(vcsn.B.expression('aa{2}a²').format('utf8')) a⁵
This is especially nice in derivedterm automata.
Tag based dispatch in vcsn::
The treatments for which several algorithms exist (e.g., minimize/cominimize hopcropft, moore, weighted, signature, brzozowski, auto, determinize/codeterminize boolean, weighted, auto, sum/multiply/star standard, general, auto, etc.) now offer a cleaner tagbased interface in vcsn::, the static library. For instance, instead of:
auto m = minimize_moore(a);
write:
auto m = minimize(a, moore_tag{});
dot format
The HTML/XML style strings are now properly supported.
oneset and proper
The oneset labelset has a single label: one. It is used to denote automata with spontaneous transitions only. Applying proper on such automata resulted in an illformed automaton (with a single subliminal transition from pre to post). This is now fixed.
Flex 2.6
We are now compatible with the new Flex, which made backward incompatible changes in its API. Previous versions are supported too.
Text format
When displaying value sets, the text
format was improved, and the new format utf8
improves on top of it. An new format name sname
, replaces previous uses of text
:
In [2]: c = vcsn.context('lal_char(abc), expressionset<law_char(xyz), q>') In [3]: c.format('sname') Out[3]: 'letterset<char_letters(abc)>, expressionset<wordset<char_letters(xyz)>, q>' In [4]: c.format('text') Out[4]: '{abc} > RatE[{xyz}* > Q]' In [5]: c.format('utf8') Out[5]: '{abc} → RatE[{xyz}* → ℚ]'
When displaying values, the new format utf8
improves the result.
In [6]: e = c.expression('!(<x>a)*') In [7]: e.format('text') Out[8]: '(<x>a)*{c}' In [9]: e.format('utf8') Out[9]: '(⟨x⟩a)*ᶜ' In [10]: e.expansion().format('text') Out[10]: 'a.[(<x>a)*{c}] + b.[\\z{c}] + c.[\\z{c}]' In [11]: e.expansion().format('utf8') Out[11]: 'a⊙[(⟨x⟩a)*ᶜ] ⊕ b⊙[∅ᶜ] ⊕ c⊙[∅ᶜ]'
20151208
polynomial: conjunction
Conjunction of polynomials is now available in dyn. For polynomials of expressionsets, compute the conjunction of the expressions. Otherwise, keep the common labels and multiply their weights.
20151205
Syntactic sugar in expressions
One may now use UTF8 when entering expressions. The negation may also be denoted by a prefix !
, which binds weakly (less than concatenation).
Sugar  Plain ASCII 

∅

\z

ε

\e

⟨2⟩a

<2>a

a∗

a*

!a ¬a aᶜ

a{c}

aᵗ

a{T}

20151204
weight_series: fix general case
This algorithm can now be applied to any automaton. In case of ℕmin weightset the implementation does not change (shortest path). Otherwise, the result is computed by applying proper on the labels_are_one
version of the automaton.
New trivial identities
Two new trivial identities have been added (at the "trivial" level): neutrality of the universal language for conjunction ( & E => E, E & => E), and involutivity of complement on 𝔹 and 𝔽₂ (E{c}{c} => E). It is not applied in the other case, since in ℤ (<2>a)*{c}{c} is actually a*, not (<2>a)*.
20151202
leftmult and rightmult
The scalar product now also accept an argument to select the exact algorithm: "standard", "general", "auto". See 20151113 for more details.
20151202
toautomaton: trim automata
Now to_automaton
(or expression.automaton
under Python) always produces a trim automaton.
20151129
Improved display of letter classes
So far disjunction of letters were displayed as classes only if all the letters had the same weight. So <1>a + <2>[^a]
in an automaton resulted in an explicit list of letters. This is especially inappropriate for Levenshtein automata. We now display <1>a + <2>[^a]
.
20151120
weight_series: new algorithm
Compute the sum of all the weights of the accepted words (the sum of the image of the behavior of the automaton). This algorithm can be applied to any Nmin automaton, but requires acyclic automata for other weightsets.
20151119
trie and cotrie are enhanced
Both context.trie and context.cotrie accept data
, format
and filename
arguments. In addition to filename
, one can now pass directly a list of words as a data
string. Use format
to specify whether the lines are monomials or plain words  for instance whether <2>a
is the word a
with weight 2, or a fourletter word.
Minimize: new algorithm: hopcroft
There is now a new implementation of the minimization, based on the algorithm of Hopcroft. It can only be used on Boolean automata with a free labelset. On many examples, this algorithm shows better performances than "signature" but is still less efficient than "moore".
20151113
Automata: operations now work on all sorts of automata
Usual operations (sum
, multiply
which includes the case for repeated multiplication, star
) used to apply only to standard automata. In addition to sum
(for standard automata), there was union
, which applied to any automata, but nothing for multiplication and star.
Now sum
, star
and multiply
accept an algo
argument:
 "standard"
 requires standard input automata, builds a standard automaton
 "general"
 applies to any kind of automaton, does not guarantee a standard automaton. In the static API, might require a nullable labelset, in the dyn:: API and Python, might turn the labelset into a nullable one.
 "auto" (default)
 same as
"standard"
if input automata are standard, otherwise same as"general"
.
In Python, the operators +
, *
and **
use the "auto"
strategy.
The union
algorithms are removed, and in Python 
no longer denotes it. The left and right multiplication by a scalar were already implemented to adapt standard or non standard automata.
20151105
Expansions: more operations
Usual operations (addition, multiplication, multiplication by a scalar) are now available on expansions.
20151015
has_negative_cycles: new algorithm
Use automaton.has_negative_cycle to check whether an automaton has cycles with negative weights.
Minor bug fixes and improvements
 Spaces are now ignored in context names (e.g.,
lal < char (ab) >, b
).  Expressions that have a single tape but several were expected are now properly rejected.
 Tuples now display parentheses only when needed. For instance with weights in ℤ ⨉ ℤ, instead of
<(1, 2)>a
, we display<1, 2>a
.
Vcsn 2.1 (20151011)
About 10,000 hours (on the calendar, not of work!) after its first public release, the Vcsn team is very happy to announce the release of Vcsn 2.1!
It is quite hard to cherrypick a few new features that have been added in Vcsn 2.1, as shown by the 4k+ lines of messages below since 2.0. However, here are a few headlines:
 Many pages of documentation and examples have been written (see http://vcsn.lrde.epita.fr/dload/2.1/notebooks).
 Now http://vcsnsandbox.lrde.epita.fr/ provides a live demo.
 Transducers are much better supported, with improved syntax and several algorithms (e.g., letterize, synchronize, partial_identity, is_functional, etc.)
 Expressions now offer several sets of identities specifying how they should be normalized. More generally, input/output of expressions have been improved to match most users' expectations. New operators are accepted:
&
for conjunction,:
for shuffle,&:
for infiltration,{c}
(postfix) for complement, and<+
for deterministic choice.  When entering an automaton (e.g., with
%%automaton
in IPython) user state names are preserved.  Of course, many bugs were fixed, many algorithms were sped up, and internal details have been cleaned up.
 As Easter eggs, many features have also been added, but not advertised, until we are sure of how we want them to look like.
People who worked on this release:
 Akim Demaille
 Antoine Pietri
 Canh Luu
 Clément Démoulins
 Lucien Boillod
 Nicolas Barray
 Sébastien Piat
 Sylvain Lombardy
 Valentin Tolmer
 Yann BourgeoisCopigny
People who have influenced this release:
 Alexandre DuretLutz
 Jacques Sakarovitch
 Luca Saiu
Vcsn 2's repository has moved
To update your existing repository, run a command similar to:
$ git remote seturl origin git@gitlab.lrde.epita.fr:vcsn/vcsn
20150930
shortest: applies to any automaton
The restriction to freelabelsets is lifted: shortest applies to automata labeled with words, to transducers, etc.
20150928
project: new algorithm
Select a single tape from a multitape automaton (transducer).
20150923
expressions: spaces are now ignored
In an attempt to look like regexps, spaces were considered so far as characters.
20150917
derivedterm: deterministic automata
One can now require the construction of a deterministic automaton; there are two new algorithms: expansion,deterministic
and derivation,deterministic
.
20150915
Named automata
It is (finally) possible to keep user state names thanks to name_automaton<Aut>
. Now dyn::read_automaton
and (in Python) vcsn.automaton
accept an additional strip
argument (defaulting to true): if set, the user names will be stripped once the automaton is loaded. This applies to all the supported formats: Daut, Dot, Efsm, and FAdo.
However using %%automaton
names are kept by default. Pass s
/strip
to strip it.
20150907
Build fixes
Fixed (again) nasty sharedlibrary issues at runtime on Ubuntu due to their use of Wl,asneeded
. This affected Python only.
20150831
expression.info: more information
Now atom
(the number of occurrences of letters) is also reported as width
, and the depth
(also known as the height
: the height of the tree) is now included.
20150826
vcsn.automaton can guess the format
The vcsn.automaton function now accepts "auto" as format, which means "try to guess from the content".
20150825
levenshtein: new algorithm
The levenshtein
algorithm allows to build a transducer encoding the Levenshtein distance between two alphabets. This transducer can then be composed with two languages to obtain the editdistance algorithm, containing much information on the distance of the languages and their words.
partial_identity: new algorithm
The partial identity turns an automaton into a transducer realizing a partial identity. I.e., for each accepted input, the output will be the same as the input (plus the origin weight from the input automaton).
20150818
to_automaton: more algorithms
One can chose between both implementation of derived_term (stripped), using "derivation" or "expansion".
20150814
to_expression: more heuristics
There are three new heuristics:
 "delgado"
 select a state whose removal would contribute a small expression (number of symbols, including
+
, etc.).  "delgado_label"
 likewise, but count only the number of labels in the expression.
 "best"
 run all the heuristics, and return the shortest result.
The default algorithm remains "auto", which now denotes "best".
20150803
to_automaton: conversion from expression to automaton
Vcsn offers several means to build an automaton from an expression: thompson, zpc, standard and derivedterm. The latter even builds a decorated automaton, which, often, is not desired.
In C++ dyn::to_automaton
and in Python expression.automaton()
allow to build a simple automaton from an expression. It accepts an optional string argument to select the conversion algorithm. It defaults to "auto", which currently means the stripped derivedautomaton, but eventually, it will pick either "standard" for basic expressions (as it's the fastest algorithm), or "derivedterm" for extended expressions (as "standard" does not support these additional operators).
20150618
I/O in EFSM format are safer
We now correctly ensure the correspondence between our weightsets and OpenFST's arctype, and input and output.
As a consequence, we no longer support exchange of "traditional numerical" weightsets (such as "Z", "R", etc.), since, as far as we know, they don't feature a visàvis in OpenFST. It used to be accepted, but was meaningless.
Boolean weights are mapped to "standard", OpenFST's tropical semiring.
When reading EFSM files, we still try to use the smallest corresponding weightset. For instance, if the arc type is "standard" and and the weights are integral we use "zmin", otherwise, we use "rmin". Errors on reading the weight of final states have also been fixed.
20150616
automaton.expression, automaton.lift
They now accept an optional argument to specify the desired identities for the expressions.
20150615
power, chain have been renamed
Before, "chain" denoted the repeated concatenation for automata and expressions, and "power" meant repeated conjunction for automata and expressions. However, while aut ** 2
meant aut & aut
(conjunction), exp ** 2
meant exp * exp
(concatenation).
Clearly, from the Python point of view, **
is repeated *
, which is what most people would understand as "power".
So, to enforce consistency, and to avoid bad surprises, these functions were renamed.
Python  dyn::  Comment 

a * b

multiply(a, b)

Multiplication for automata and expressions (concatenation), polynomials, weights, labels etc. 
a ** n

multiply(a, n)

Repeated multiplication. 
a & b

conjunction(a, b)

Conjunction for automata and expressions. 
a & n

conjunction(a, n)

Repeated conjunction. 
20150611
eliminate_state: fixes
Sometimes there was a mismatch between the state numbers as displayed, and as expected by eliminate_state
. This is fixed.
The rendering was nonsensical when all the states were removed. This is now fixed.
Finally, passing 1 as argument, or no argument at all, delegates the choice of the state to eliminate to a heuristic.
20150604
expressions: new identities sets
Rational expressions in Vcsn are "normalized" according to a set of identities (such that <0>E => \z
whatever the expression E is).
Vcsn now supports four different sets of identities:
 "trivial"
 a minimum set of transformations are applied.
 "associative"
 sum and product are made associative, so
a+(b+c)
and(a+b)+c
are equal.  "linear"
 sum is made commutative, and weights are factored, so
a+b+a
is equal toa+b
in B, and to<2>a+b
in Z.  "distributive" (or "series")
 product and exterior/scalar products are distributed over sum, so
[ab]a
is equal toaa+ba
, and<2>[ab]
is equal to<2>a+<2>b
.
Previously the default identities were "associative". They are now "linear", to match most users' expectations.
So, for instance we used to report:
In [2]: c = vcsn.context('lal_char(az), z') In [3]: c.expression('r+[aq]') Out[3]: r + [aq] In [4]: c.expression('[aq]+r+r') Out[4]: [^sz] + r
we now report:
In [3]: c.expression('r+[aq]') Out[3]: [^sz] In [4]: c.expression('[aq]+r+r') Out[4]: [aq] + <2>r
20150529
nmin: new weightset
The new tropical semiring ⟨ℕ, +, min⟩ has been introduced. Compared to zmin, some optimizations can be done, for example in evaluation or in node distance where the absence of negative weights allows to trim some branches.
20150526
cotrie: new algorithm
In additional to trie
, which builds a deterministic treelike automaton (single initial state, multiple final states), vcsn now supports cotrie
which builds a "reversed trie": a codeterministic reversed treelike automaton (single final state, multiple initial states).
The main feature of cotrie
is that its result is codeterministic, so it only takes a determinization to minimize it. It turns out that in Vcsn determinization is more efficient than minimization:
In [13]: %timeit c.trie('/usr/share/dict/words').minimize() 1 loops, best of 3: 18.8 s per loop In [14]: %timeit c.cotrie('/usr/share/dict/words').determinize() 1 loops, best of 3: 7.54 s per loop
These automata are isomorphic.
20150522
expressions: output may use label classes
Rational expressions have long supported label classes in input, e.g., [abc09]. Polynomials also support them in output. However expressions never used classes, which may seriously hinder their readability. For instance, to compute an expression describe all words on {a,..., z} except 'hehe', we had:
In [2]: c = vcsn.context('lal_char(az), b') c.expression('(abcd){c}').derived_term().expression() Out[2]: \e+a(\e+b(\e+c))+(b+c+d+e+f+g+h+i+j+k+l+m+n+o+p+q+r+s+t+u+v+w+x+y+z+a(a+c+d+e+f+g+h+i+j+k+l+m+n+o+p+q+r+s+t+u+v+w+x+y+z+b(a+b+d+e+f+g+h+i+j+k+l+m+n+o+p+q+r+s+t+u+v+w+x+y+z+c(a+b+c+e+f+g+h+i+j+k+l+m+n+o+p+q+r+s+t+u+v+w+x+y+z+d(a+b+c+d+e+f+g+h+i+j+k+l+m+n+o+p+q+r+s+t+u+v+w+x+y+z)))))(a+b+c+d+e+f+g+h+i+j+k+l+m+n+o+p+q+r+s+t+u+v+w+x+y+z)*
Now expressions also support letter classes in output:
Out[2]: \e+a(\e+b(\e+c))+([^a]+a([^b]+b([^c]+c([^d]+d[^]))))[^]*
Classes are used only on ranges of at least four (unweighted) letters in strictly increasing order:
In [3]: c.expression('a+a+b+c+d+e+f+x+y+z+w') Out[3]: a+[afxz]+w
Negated classes are issued only if the letters are in strictly increasing alphabetical order, and are more than two thirds of the whole alphabet (otherwise a regular class is preferred).
In [4]: c.expression('[aq]') Out[4]: [aq] In [5]: c.expression('[aq]+r') Out[5]: [^sz] In [6]: c.expression('r+[aq]') Out[6]: r + [aq] In [7]: c.expression('[aq]+r+r') Out[7]: [^sz] + r
20150521
multiply: new name for 'concatenate'
In static, dyn:: and Python, concatenate
is renamed multiply
.
The "concatenation" of automata or rational expressions would never be called the concatenation in the case of series or polynomials etc. If we were to support automata weighted by automata, the weightset product would be this multiply.
20150520
trie: read directly from a file
Building a polynomial from a dictionary stored on disk, and then building the trie is a waste of time. It is now possible to build it directly from a file.
In [2]: t = vcsn.B.trie('/usr/share/dict/words') In [3]: t.info() Out[3]: {'is codeterministic': False, 'is complete': True, 'is deterministic': True, 'is empty': False, 'is epsacyclic': True, 'is normalized': False, 'is proper': True, 'is standard': True, 'is trim': True, 'is useless': False, 'is valid': True, 'number of accessible states': 792777, 'number of coaccessible states': 792777, 'number of codeterministic states': 792777, 'number of deterministic states': 792777, 'number of eps transitions': 0, 'number of final states': 235886, 'number of initial states': 1, 'number of states': 792777, 'number of transitions': 792776, 'number of useful states': 792777, 'type': 'mutable_automaton<letterset<char_letters()>, b>'}
20150514
trie: new algorithm
From a finite language/series represented as a polynomial (of words), build an automaton that has the shape of a trie (a prefix tree).
In [2]: series = '<2>\e+<3>a+<4>b+<5>abc+<6>abcd+<7>abdc' In [3]: p = vcsn.context('law_char, z').polynomial(series); p Out[3]: <2>\e + <3>a + <4>b + <5>abc + <6>abcd + <7>abdc In [4]: a = p.trie(); a Out[4]: mutable_automaton<letterset<char_letters(abcd)>, z> In [5]: a.shortest(100) Out[5]: <2>\e + <3>a + <4>b + <5>abc + <6>abcd + <7>abdc
20150501
delay_automaton: new automaton type
This algorithm transforms the automaton into an equivalent one, but where each state has been split depending on the delay between the tape, i.e. the difference of input length for each of the tapes.
issynchronized: new algorithm
This algorithm checks whether a transducer is synchronized, i.e. that the input is read on every tape at the same rate for as long as possible.
synchronize: new algorithm
This new algorithm allows to synchronize the tapes of a ktape transducer, i.e. "push" the letters towards the beginning of the transducer so that the input is read along every tape at the same rate for as long as possible.
hasboundedlag: new algorithm
This algorithm checks whether a ktape transducer has a bounded lag, i.e. if there exists a constant D such that the length of the input for each tape differs by at most D; or the output of the evaluation of a word through the transducer differs in length by at most D.
20150409
shortest now subsumes enumerate
One can now specify both a maximum number of words, and a maximum size. It is also significantly faster. The Python binding automaton.enumerate was removed.
In [4]: a = vcsn.Z.expression('[01]*1(<2>[01])*').standard() In [5]: a.shortest() Out[5]: 1 In [6]: a.shortest(3) Out[6]: 1 + 01 + <2>10 In [7]: a.shortest(len = 3) Out[7]: 1 + 01 + <2>10 + <3>11 + 001 + <2>010 + <3>011 + <4>100 + <5>101 + <6>110 + <7>111 In [8]: a.shortest(len = 3, num = 5) Out[8]: 1 + 01 + <2>10 + <3>11 + 001 In [9]: a.shortest(len = 30, num = 5) Out[9]: 1 + 01 + <2>10 + <3>11 + 001
20150325
product is renamed conjunction
After many hesitations, we finally decided to rename the synchronized product from product
to conjunction
. There are several reasons in favor of this change.
First product
is not adequate:
 we have several
products
: the Cauchy product (concatenation), the Hadamard product (synchronized product), the shuffle product, the infiltration product, and there are certainly more. product
is already used in the case of words and rational expressions to denote the concatenation, so, to be consistent,product
will denote the concatenation of automata too.*
is naturally associated toconcatenation
for words and rational expressions, it was associated toproduct
for automata. It is more consistent to useconcatenate
in each case.
Second conjunction
is a reasonable choice:
intersection
is acceptable for Boolean automata, but it is not satisfying in the case of weighted automata.synchronized_product
is too long, likewise forhadamard_product
, etc.hadamard
is a proper name, which we try to avoid. the etymology of
conjunction
is a perfect match with the semantics of the operation.  computer scientists are used to the correspondence between
conjunction
and&
.
The preference for verbs as algorithm names leads naturally to conjoin
. However conjunction
still seems more natural.
20150321
areequivalent: now uses realtime
One may, finally, compare LAL, LAN, and LAW automata.
join: improvements
The "join" of tuplesets now works properly, so one may, for instance, add automata on A? x B and A x B? to get an automata on A? x B?.
In order to facilitate the experiments with join
, it is now provided as an algorithm. In Python, it is also available as the infix or
operator.
In [2]: c1 = vcsn.context('lat<lal_char(a), lan_char(x)>, z'); c1 Out[2]: {a} × ({x})? → ℤ In [3]: c2 = vcsn.context('lat<lan_char(b), lal_char(y)>, q'); c2 Out[3]: ({b})? × {y} → ℚ In [4]: c1  c2 Out[4]: ({a,b})? × ({x,y})? → ℚ
20150318
infiltration: fix long standing bugs
Optimizations in the computation of the shuffleproduct broke the infiltrationproduct. This is fixed. However, the performances of infiltration are then degraded (about 2.5x). Conjunction (synchronized product) and shuffle are unaffected.
Besides, the support for variadic infiltration products was naive, and produced incorrect results. This is fixed by simply repeating the binary infiltration.
20150317
is_functional: new algorithm
Whether a transducer is functional, i.e., whether each input words maps to (at most) a single word.
Actually, was implemented in September 2014, but was not registered here.
20150316
Python 3 is now required
We have tried hard to remain compatible with Python 2, but support for Unicode is just too hard to get to work properly with both Python 2 and Python 3. Since there were constantly problems arising in one whose fixes break the other, we decided to drop support for Python 2. Given that all major platforms ship Python 3, we don't expect this to be a real problem.
20150315
Repeated minimization
Now, minimization and cominimization return automata of the same type  cominimization used to return an automaton whose type reveals the double transposition. In actually, calling several times the minimization and/or cominimization no longer generates decorators of decorators of etc.: the result is always a single layer decorator. Not only is this, in general, the desired result, it's also more 'economic' as it uses fewer automaton types (hence less runtime compilations).
20150303
realtime: new algorithm
Compute the letterized, proper equivalent of an automaton. The result automaton will have only letter transitions (no words, no spontaneous transitions). It comes with the is_realtime
algorithm, to check if an automaton is realtime or not.
is_letterized: new algorithm
This algorithm checks whether an automaton is letterized, i.e. whether each transition's label is a single letter (in the sense of the labelset).
In [2]: ctx = vcsn.context("law_char, b") In [3]: ctx.expression("abc").standard().is_letterized() Out[3]: False In [4]: ctx.expression("a*(b+c)").standard().is_letterized() Out[4]: True
20150302
zpc: new algorithm
This algorithm generates the ZPC automaton from an expression. It has a single initial state (whose final weight is the constant term of the expression), a unique distinct final state (which cannot be reached from the initial state via spontaneous transitions), and no cycles of spontaneous transitions.
The expression.zpc
function features an optional argument, which, when set to "compact", enables a variant, more compact, construction.
In [2]: vcsn.b.expression('ab').zpc() ╭───╮ \e ╭───╮ a ╭───╮ \e ╭───╮ b ╭───╮ \e ╭───╮ ──> │ 0 │ ────> │ 1 │ ───> │ 2 │ ────> │ 3 │ ───> │ 4 │ ────> │ 5 │ ──> ╰───╯ ╰───╯ ╰───╯ ╰───╯ ╰───╯ ╰───╯ In [3]: vcsn.b.expression('ab').zpc('compact') ╭───╮ a ╭───╮ \e ╭───╮ b ╭───╮ ──> │ 0 │ ───> │ 1 │ ────> │ 2 │ ───> │ 3 │ ──> ╰───╯ ╰───╯ ╰───╯ ╰───╯
20150223
letterize: new algorithm
Create the equivalent automaton, but with only singleletter transitions. Basically, do the conversion from law to lan. It also works recursively with multitape transducers.
In [2]: c = vcsn.context('lat<law_char, lal_char>, z') In [3]: a = c.expression("<2>'(abc,x)'").derived_term() In [4]: print(a.format('daut')) context = "lat<wordset<char_letters(abc)>, letterset<char_letters(x)>>, z" $ > 0 0 > 1 <2>(abc,x) 1 > $ In [5]: print(a.letterize().format('daut')) context = "lat<nullableset<letterset<char_letters(abc)>>, nullableset<letterset<char_letters(x)>>>, z" $ > 0 0 > 2 <2>(a,x) 1 > $ 2 > 3 (b,\e) 3 > 1 (c,\e)
20150210
Multitape expressions
When typing multitape transducers, it is now no longer necessary to explicit the parenthesis inside (multi)letters.
In [1]: import vcsn In [2]: c = vcsn.context('lat<lan_char, lan_char>, b') In [3]: r = c.expression(r"'a,\e'+'(b,c)'+'d,f'")
has_bounded_lag: new algorithm
This algorithm checks if a transducer has a bounded lag, i.e. if there is a maximum difference of length between the input words and their corresponding outputs.
In [1]: import vcsn In [2]: c = vcsn.context('lat<lan_char, lan_char>, b') In [3]: c.expression(r"'a,\e'").standard().has_bounded_lag() Out[3]: True In [4]: c.expression(r"'a,\e'*").standard().has_bounded_lag() Out[4]: False
20141118
Flex
The Flex program (a scanner generator) should no longer be required for builds from a tarball.
blind > focus
The blind
algorithm (and the blind_automaton
structure) has been renamed focus
(and focus_automaton
) as it is much clearer on its purpose.
20141114
scc: new algorithm
Create an automaton whose states correspond with a strongly connected component of the input automaton.
20141113
ratexp > expression
The name "ratexp" is an unattractive jargon, and since Vcsn will not feature other kinds of "expressions", it is hardly justified: it is the only abbreviation we use (automaton, context, expansion, polynomial, etc.).
So everywhere (static, dyn::, Python) "ratexp" was replaced by "expression" (including "make_ratexpset" > "make_expressionset", etc.).
20141107
thompson: the labelset no longer needs to feature a "one"
The Thompson automata count many spontaneous transitions, so require a labelset which supports \e
(e.g., lan
, law
). This is annoying, especially when teaching about Automata Theory: one does not want to dive into the arcane details of contexts.
So now, if the context of the input expression does not support \e
, the Thompson automaton will be built with a generalized context which does support it:
In [1]: import vcsn In [2]: vcsn.context('lan_char, b').ratexp('a').thompson().context() Out[2]: lan<letterset<char_letters(a)>>, b In [3]: vcsn.context('law_char, b').ratexp('a').thompson().context() Out[3]: wordset<char_letters(a)>, b In [4]: vcsn.context('lal_char, b').ratexp('a').thompson().context() Out[4]: lan<letterset<char_letters(a)>>, b
20141030
filter: new algorithm
Hide states of another automaton, revealing only selected ones. This does not copy the original automaton.
20141029
New project name: Vcsn
The Vaucanson 2 project, which was funded by a (French) program (ANR), is now "closed". Of course, it will continue to exist, but now there will be two Vaucansa! One will be led by Sylvain Lombardy and Jacques Sakarovitch, and the other by Alexandre DuretLutz and Akim Demaille from EPITA.
This file is about the latter, named "Vcsn".
20141027
WARNING: resyntaxed contexts
The syntax for contexts has changed: the separator between the labelset and the weightset is now a comma (possibly with spaces) instead of an underscore.
So for instance:
lal_char(abc)_b > lal_char(abc), b lat<lal_char(ab),lal_char(xy)>_lat<q,r> > lat<lal_char(ab), lal_char(xy)>, lat<q, r> law_char(az)_ratexpset<law_char(AZ)_b> > law_char(az), ratexpset<law_char(AZ), b>
This syntax is not (and has never been) the intended one, it should be considered as the "internal" syntax. However, since the intended syntax is still not implemented, one, unfortunately, still has to deal with this inner syntax.
20141023
proper: strip nullableset from labelsets
Our (current) implementation of proper
is inplace, and as a consequence, the result features the same context as the input automaton, with a nullable labelset.
Now, proper
copies the result in a context with a denullabled labelset. So for instance:
In [2]: vcsn.context('lan_char(ab)_b').ratexp('(ab)*').thompson().proper() Out[2]: mutable_automaton<lal_char(ab)_b>
There is no measurable performance regression. However state numbers are now unrelated to the input automaton.
20141020
Python: loading automata from files
The vcsn.automaton
constructor now support a filename
named argument to load an automaton from a file.
vcsn.automaton(filename = 'a.gv') vcsn.automaton(filename = 'a.efsm', format = 'efsm')
minimize: default algorithm is "auto"
Now minimize and cominimize both support the "auto" algorithm, which is the default value. It uses the "signature" algorithm for the Boolean automata, otherwise the "weighted" algorithm.
proper: forward closure available in dyn:: and Python
It is now possible to require a forward elimination of spontaneous transitions. Calling a.proper()
is equivalent to calling a.proper(prune = True, backward = True)
.
20141007
toexpression
The static and dyn:: algorithm that was named aut_to_exp
is now named to_expression
. In Python it is still automaton.ratexp()
.
costandard, is_costandard: new algorithms
Calling aut.costandard()
is equivalent to calling aut.transpose().standard().transpose()
, and aut.is_costandard()
is the same with aut.transpose().is_standard()
.
normalize: new algorithm
Composes standard and costandard on an automaton.
20141002
Strip vs. transpose
Up to now, stripping a transposed automaton returned the nontransposed automaton, without even stripping it. This has finally been addressed, and a.determinize().transpose().strip()
is now strictly equivalent to a.determinize().strip().transpose()
.
codeterminize, cominimize, is_codeterministic: new algorithms.
Calling aut.cominimize()
is equivalent to calling aut.transpose().minimize().transpose()
, and likewise for codeterminize
.
Available in dyn and Python.
20141001
split: now works on polynomials
In addition to splitting (aka, breaking) a ratexp, it is now possible to split a polynomial. This, for instance, provides another way to compute the breaking derivation of a ratexp:
In [1]: r = vcsn.context('lal_char_z').ratexp('a(b+a)+a(a+b)') In [2]: p = r.derivation('a'); p Out[2]: a+b + b+a In [3]: p.split() Out[3]: <2>a + <2>b In [4]: r.derivation('a', True) Out[4]: <2>a + <2>b
derivation: fix a Python bug
ratexp.derivation
features a breaking
optional argument, which defaulted to True
instead of False
.
transpose: fix the number of final and initial states
Because num_initials
and num_finals
were not "transposed", on occasions automaton.is_standard
could crash (when it thinks there is one initial state while there is none, but it still wants to check that its initial weight is one).
20140925
Automaton conjunction
On occasions, in Python, expressions such as (a & b)('a')
failed to behave properly. It does now, and does correspond to the evaluation of the word "a" on the conjunction (synchronized product) of automata a and b.
TikZ: state names
Conversion of automata into the TikZ format now includes the state "names" (e.g., derivedterm automata now show the states' rational expressions).
20140921
determinize: EmptyIn, EmptyOut
Now when given an empty automaton (no states), determinize returns an empty automaton, whereas it used to return an automaton with one state, initial. This is more consistent (e.g., when given a deterministic automaton, determinize now consistently returns the accessible part of its input).
20140917
is_cycle_ambiguous: new algorithm
Whether an automaton is cycleambiguous (or "exponentially ambiguous").
20140909
Build fixes
Portability issues with Mac OS X's own version of Flex are fixed.
Fixed runtime compilations failing to find Boost headers in some cases.
Fixed nasty sharedlibrary issues at runtime on Ubuntu due to their use of Wl,asneeded
.
20140904
Fixes
I/O with OpenFST now properly supports initial weights and multiple initial states.
Dot I/O of multipletape automata with initial weights is fixed.
Dot parse errors now provide locations.
The preconditions of reduce have been relaxed from labelsareletters to labelsetisfree.
20140903
determinize provides a better support for Z
The normalization of states now uses the GCD of the weights, which means that now all the Zautomata that are determinizable can be determinized in Z, without having to convert them as Qautomata.
New weightset: qmp
Initial support for multiprecision rational numbers.
>>> a = vcsn.context('lal_char(abc)_qmp').ratexp('<2/3>a').standard() & 70 >>> a('a') 1180591620717411303424/2503155504993241601315571986085849
Requires the GMP library.
20140901
compatibility with Boost 1.56
Some changes in Boost require adjustments.
20140802
ambiguous_word: new algorithm
Returns an ambiguous word of an automaton, or raises if the automaton is unambiguous.
20140730
Several fixes
The reduce algorithm applied only to notdecorated automata. Support for F2 was broken.
Improvements
Error messages about failed algorithm instantiations are much clearer: they display failed preconditions.
Blind is no longer limited to tape 0 or tape 1.
Vaucanson 2.0 (20140725)
More than two years after the initial commit in our repository, the Vaucanson team is happy to announce the first release of Vaucanson 2!
People who worked on this release:
 Akim Demaille
 Alexandre DuretLutz
 Alfred M. Szmidt
 Antoine Pietri
 Canh Luu
 Jacques Sakarovitch
 Luca Saiu
 Sylvain Lombardy
 Valentin Tolmer
20140724
"series" are now supported (static, dyn, Python)
Ratexpsets now take a constructor parameter specifying which set of identities to enforce, currently with two possible values: "trivial" and "series". Oldstyle ratexps only support trivial identities, while series also support sum commutativity and product distributivity over sum. Heterogeneous operations involving both trivial ratexps and series ratexps are possible.
In case of a ratexpset belonging to a context, the default value for the optional parameter is always trivial. The "seriesset" alias, which does not accept an identity parameter, is also supported.
"Series" is technically a misnomer: the data structure is a better approximation of the mathematical concept of series and in particular yields a semiring structure, but actual series equality remains undecidable in the general case.
Series currently depend on the commutativity of their weightset, and only support a subset of the available operations.
>>> vcsn.context('lal_char(a)_ratexpset<lal_char(x)_b>(series)') # series >>> vcsn.context('lal_char(a)_seriesset<lal_char(x)_b>') # series >>> vcsn.context(ratexpset<lal_char(x)_b>_z') # trivial >>> vcsn.context('lal_char(a)_ratexpset<lal_char(x)_b>(trivial)')# trivial >>> e = vcsn.context('lal_char(ac)_z').ratexp('b+a+b'); e b+a+b >>> s = vcsn.context('lal_char(ac)_z').series('b+a+b'); s a+<2>b >>> (e+s).is_series() True
has_twins_property: new algorithm
Computes whether an automaton has the twins property.
20140716
determinize supports weighted automata
The determinize algorithm (dyn and Python) now accepts an optional 'algo' argument.
When 'algo' is:
 "boolean"
 the fast Booleanonly implementation is used. It always terminates.
 "weighted"
 any weightset is supported. On some inputs, it may not terminate.
 "auto" (default value)
 "boolean" if the automaton is Boolean, "weighted" otherwise.
20140711
areequivalent is generalized
The 'are_equivalent' algorithm (a1.is_equivalent(a2) in Python) now supports weights in fields (e.g., Q or R), but also on Z. The labelset still must be free.
20140710
reduce: new algorithm on automata
Implements the Schützenberger algorithm for reduction of representations for any skew field. As a special case, automata with weights in Z are also supported.
20140704
determinization is more robust to large alphabets
In order to optimize (Boolean) determinization, 'determinize' no longer accepts an optional 'complete' argument to require a deterministic complete automaton. One must now call 'complete()' afterwards.
The speed improvements are (erebus: OS X i7 2.9GHz 8GB, Clang 3.5 O3 DNDEBUG):
(1) (2) (3) 7.93s 7.80s 7.43s: a.determinize() # a = ladybird(21) 6.64s 6.45s 0.84s: a.determinize() # a = lal(azAZ09).ladybird(18)
where (1) is the "original" version, (2) is the version without the optional completion of the determinized automaton (yes, it was set to False in the bench of (1)), and (3) is the current version, which avoids considering unused letters.
20140701
prefix, suffix, factor, subword: new algorithms
These four new functions (static, dyn and Python) take an automaton and return another that accepts a superset of its language:
 suffix makes each accessible state final (with unit weight)
 prefix makes each coaccessible state initial
 factor makes each useful state initial and final
 subword applies the Magnus transform: for each non spontaneous transition (src, label, weight, dst), it adds a spontaneous transition (src, one, weight, dst).
20140624
minimize: new subset decorators, except for the "brzozowski" variant
Minimizing an automaton now yields a decorated automaton keeping track of source state names. The new "subset decorator" code is decoupled from minimization and is intended to be used for other algorithms as well.
>>> a = vcsn.context('lal_char(az)_b').ratexp('a+b*e+c+dc').standard(); a >>> a.minimize()
The minimize algorithm no longer recognizes the "brzozowski" variant at the Static level, as it would require a very different, and likely uninteresting, decorator; the user can still directly call minimize_brzozowski at the Static level. We still support "brzozowski" as a variant at the Dyn and Python levels.
20140623
efsm: support for transducers
Exchange with OpenFST via efstcompile/efstdecompile now supports transducers.
20140615
TAFKit is phased out
Existing commands for TAFKit are left and are occasionally useful. However, today the last existing TAFKit test has been converted to Python: TAFKit is no longer checked at all by the test suite.
lift: now bound in Python
One can now lift automata and ratexps from Python.
20140619
Minimize: extend 'weighted' and 'signature' variants
Lift arbitrary restrictions on the labelset of the 'weighted' and 'signature' minimization variants.
>>> ctx = vcsn.context('law_char(az)_b') >>> ctx.ratexp('ab+<3>cd+ac').standard().minimize('weighted')
20140604
More systematic use of decorators
In addition to the venerable transpose_automaton
, several automaton decorator types have been introduced (blind_automaton
, determinized_automaton
, pair_automaton
, product_automaton
, ratexp_automaton
), and are now used in many algorithms, including: compose
, determinize
, product
, shuffle
, infiltration
, synchronizing_word
, etc.
Coupled with the fact that automata can now display state names (as opposed to state numbers) in Dot output, one gets rich displays of automata. For instance:
>>> ctx = vcsn.context('lal_char(ab)_b') >>> ctx.ratexp('aa+ab').derived_term().determinize()
now displays an automaton whose states are labeled as sets of ratexps: "{aa+ab}", "{a, b}", and "{}".
Use automaton.strip()
to remove state names.
20140530
dot2tex format
Automata now support for "dot2tex" format, meant to be used with the dot2tex program. It allows to combine TikZ's nice rendering of automata, LaTeX's math mode to render state and transition labels, with dot automatic layout.
IPython: an interactive display
Starting with IPython 2.0, running 'aut.display()' provides an interactive display of an automaton, with means to select the display mode (e.g., "dot", "dot2tex", etc.).
shuffle: now available on ratexps
Available in static, dyn, and Python.
20140528
Optimization: composing two automata transposition yields the identity
Transposing an automata twice now yields the original automata, instead of an automata wrapped by two decorator layers.
isisomorphic: extend to any context and any automata
Lift the previous limitation of isisomorphic to deterministic lal automata. The sequential case keeps its linear complexity, but the new generic code has a worstcase complexity of O((n+1)!); however the common case is much faster, as we heuristically classify states according to in and outtransitions, restricting bruteforce search to states which are possible candidates for isomorphism.
>>> ctx = vcsn.context('lal_char(az)_b') >>> a = ctx.ratexp('ab+<3>ab+ab+ac').standard() >>> b = ctx.ratexp('ab+ac+<3>ab+ab').standard() >>> a.is_isomorphic(b) True >>> at = ctx.ratexp('abc').standard().transpose() >>> c = ctx.ratexp('cba').standard() >>> at.is_isomorphic(c) True
20140522
Types such as vcsn::mutable_automaton<Ctx> used to support the so called "move semantics" only. In particular, simple assignment between automata was not possible. This intentional limitation was introduced to avoid accidental lose of performance by unexpected deep copies of automata, while keeping partly "value semantics".
This, however, resulted in too many constraints, especially when one wants to embed automata in other structures (which is for instance the case of transpose_automaton which wraps an automaton).
To address these issues, types such as vcsn::mutable_automaton<Ctx>
are now std::shared_ptr
. This does change the programming style, both when instantiating an automaton (typically now using make_mutable_automaton
), and when using it (with >
instead of .
):
Instead of:
automaton_t aut{ctx}; auto s1 = aut.new_state(); aut.set_initial(s1);
write:
auto aut = vcsn::make_mutable_automaton(ctx); // or: auto aut = vcsn::make_shared_ptr<automaton_t>(ctx); auto s1 = aut>new_state(); aut>set_initial(s1);
20140521
Polynomials are now usable as weights
Polynomialsets are now usable as a generic weightset. Polynomials are mostly useful on law and ratexpset.
>>> ctx = vcsn.context('lal_char(abc)_polynomialset<law_char(xyz)_z>') >>> ctx.ratexp('<x + xy + x + \e>a') <\e + <2>x + xy>a
20140518
ratexps: support for negated letter classes
We may now use '[^...]' to denote a letter other than the listed ones. The special case '[^]' denotes any character of the alphabet.
>>> c = vcsn.context('lal_char(09)_b') >>> c.ratexp('0+[^0][^]*') 0+(1+2+3+4+5+6+7+8+9)(0+1+2+3+4+5+6+7+8+9)*
ratexps: invalid letter classes are rejected
Instead of being ignored, invalid intervals, or empty classes, are now rejected.
>>> c.ratexp('[90]') RuntimeError: invalid letter interval: 90 >>> c.ratexp('[]') RuntimeError: invalid empty letter class
ratexps: improved support for letter classes
Previously letter classes were supported only for context on top of a simple alphabet (LAL, LAN and LAW). Generators of more complex contexts such as LAL x LAN are now supported:
>>> c = vcsn.context('lat<lal_char(abc),lan_char(xyz)>_b') >>> c.ratexp("['(a,x)''(c,z)']") (a,x)+(c,z) >>> c.ratexp("[^'(a,x)''(c,z)']") (a,y)+(a,z)+(b,x)+(b,y)+(b,z)+(c,x)+(c,y) >>> c.ratexp("['(a,x)''(a,z)']") (a,x)+(a,y)+(a,z) >>> c.ratexp("[^]") (a,x)+(a,y)+(a,z)+(b,x)+(b,y)+(b,z)+(c,x)+(c,y)+(c,z)
20140512
compose: new algorithm (static, dyn, Python)
A new algorithm has been introduced to allow the composition of two transducers. It computes the accessible part of the transducer resulting from the composition of the second tape of the first transducer with the first tape of the second one.
>>> c1 = vcsn.context('lat<lan_char(abc),lan_char(ijk)>_b') >>> c2 = vcsn.context('lat<lan_char(ijk),lan_char(xyz)>_b') >>> t1 = c1.ratexp("('(a,i)'+'(b,j)'+'(c,k)')*").thompson() >>> t2 = c2.ratexp("('(i,x)'+'(j,y)'+'(k,z)')*").standard() >>> t1.compose(t2).proper().shortest(8) (\e,\e) + (a,x) + (b,y) + (c,z) + (aa,xx) + (ab,xy) + (ac,xz) + (ba,yx)
20140505
insplit: new algorithm (static, dyn, Python)
It is now possible to do the insplitting of an automaton, i.e. to get the equivalent automaton such that each state have either only incoming epsilontransitions or no incoming epsilontransitions. This is the first step in a product algorithm that supports epsilontransitions.
20140502
Multiplication by a weight no longer requires a standard automaton
The rightmultiplication by a weight uselessly required a standard automaton; it now accepts any automaton. The leftmultiplication keeps its specification for standard automata, but now supports nonstandard automata, in which case the weight is put on the initial arrows.
Multiplication by 0 is fixed
The multiplication of an automaton by the null weight results in the "zero automaton": a single state, initial, and no transitions.
20140427
Python syntactic sugar
Multiplication by a scalar on the left, and on the right, can be performed with implicit conversion of the weights. Instead of
>>> z = vcsn.context('lal_char(ab)_z') >>> r = z.ratexp('[ab]*') >>> z.weight(2) * r * z.weight(3)
one can now write
>>> 2 * r * 3
and similarly for automata.
Besides, repeated &product can be denoted with the same symbol, &: 'a & 3' denotes 'a & a & a'.
20140422
Vaucanson 2 has moved
Vaucanson 2 is now also hosted on gitlab.lrde.epita.fr. It is also renamed vaucanson.git, rather than vaucanson2.git. To update your existing repository, run a command similar to:
$ git remote seturl origin git@gitlab.lrde.epita.fr:vcsn/vaucanson
or edit your .git/config file to update the URL.
You may also visit http://gitlab.lrde.epita.fr/vcsn/vaucanson.
dyn::label is born
The family of dynamic object (which includes dyn::automaton, dyn::weight, dyn::polynomial, dyn::ratexp, and others) now features a dyn::label. Several algorithms dealing with labels used the "std::string" C++ type to this end. This was inadequate, and the corresponding signatures have been cleaned bottom up.
For instance "derivation" used to have the following signatures
Static:
template <typename RatExpSet> inline rat::ratexp_polynomial_t<RatExpSet> derivation(const RatExpSet& rs, const typename RatExpSet::value_t& e, const std::string& word, bool breaking = false)
Dyn:
polynomial derivation(const ratexp& exp, const std::string& s, bool breaking = false);
These signatures are now:
template <typename RatExpSet> inline rat::ratexp_polynomial_t<RatExpSet> derivation(const RatExpSet& rs, const typename RatExpSet::value_t& e, const typename RatExpSet::labelset_t::word_t& word, bool breaking = false) polynomial derivation(const ratexp& exp, const label& l, bool breaking = false);
At the Python level, derivation was adjusted so that one may still pass a string, and see it upgraded, so both these calls work:
>>> ctx = vcsn.context('lal_char(ab)_z') >>> r = ctx.ratexp('(<2>a)*') >>> r.derivation(ctx.word('aa')) <4>(<2>a)* >>> r.derivation('aa') <4>(<2>a)*
Context extraction
It is now possible to obtain an automaton or a ratexp's context. In dyn, use "dyn::context_of(obj)", in Python use "obj.context()".
Copy can now change the type of the automaton
vcsn::copy used to support only "homogeneous" duplications. It also offers access to the the origins (a map from resulting states to origin states).
Variadic product of automata
The synchronized product of automata is now variadic: the product of nautomata directly builds an automaton labeled with ntuples of original states. The Python operator, &, is modified to pretend it is variadic (rather than binary): it delays the computation until the result is needed. The ".value()" method allows to force the evaluation.
>>> ctx = vcsn.context('lal_char(ab)_z') >>> a1 = ctx.de_bruijn(5) >>> a = ctx.ratexp('a{5}').derived_term() >>> import timeit >>> timeit.timeit(lambda: (((a1&a1).value() & a1).value() & a).value(), number=1000) 1.9550061225891113 >>> timeit.timeit(lambda: (a1 & a1 & a1 & a).value(), number=1000) 0.5792131423950195
Be aware that if the result is not needed, then it is simply not computed at all (hence, appears to be blazingly fast):
>>> timeit.timeit(lambda: a1 & a1 & a1 & a, number=1000) 0.0039250850677490234
"Fine grain" runtime compilation works
So far dyn:: provided support for "context" runtime compilation, i.e., if a context is unknown (e.g., "lat<lal_char(ab), lal_char(xy)>_b"), C++ code is emitted, compiled, and loaded. Now Vaucanson also supports peralgorithm runtime compilation.
Brzozowski minimization.
It is now possible to ask for the Brzozowski's minimization:
>>> a = vcsn.context('lal_char(ab)_b').ratexp('a+b').standard() >>> a.minimize('moore').info()['number of states'] 2 >>> a.minimize('signature').info()['number of states'] 2 >>> a.minimize('brzozowski').info()['number of states'] 2
20140411
GCC is back in business
GCC compiles Vaucanson incorrectly (i.e., Vaucanson appears to behave incorrectly, but it is actually the compiler that is incorrect). For this reason, some features were disabled with such a compiler, and recently GCC support was completely dropped.
Efforts were put in finding reasonable workarounds for these bugs, and now GCC is, again, supported. Parts that used to be disabled are now supported.
For more information on this bug, see the following problem report http://gcc.gnu.org/bugzilla/show_bug.cgi?id=51253.
20140410
Vaucanson 1 has moved
Vaucanson 1 is now hosted on gitlab.lrde.epita.fr. It is also renamed vaucanson1.git, rather than just vaucanson.git. To update your existing repository, run a command similar to:
$ git remote seturl origin git@gitlab.lrde.epita.fr:vcsn/vaucanson1
or edit your .git/config file to update the URL.
You may also visit http://gitlab.lrde.epita.fr/vcsn/vaucanson1.
20140405
conjunctions of ratexps
The intersection
operation on ratexps is renamed as conjunction
.
20140328
Improve treatment of nullable labelsets
As introduced earlier, nullablesets are now written lan<...>
, for instance lan<lal_char(ab)>_b
. The former syntax, e.g., lan_char(ab)_b
, is kept for backward compatibility and ease of use.
Up to now, lan<>
would only work on lal and labelsets with already a one
provided, making the improvement quite useless. Now lan<...>
will manufacture a one
for the labelsets that don't have one, so it can be wrapped around anything.
In addition to that, simplifications are applied; for instance lan<lan<lan_char(ab)>>_b
actually builds lan<lal_char(ab)>_b
. Similarly, lan<lat<lan_char(ab), law_char(ab), ratexpset<lal_char(ab)_b>>>_b
generates lat<lan<lal_char(ab)>, law_char(ab), ratexpset<lal_char(ab)_b>>_b
, since the tuple wrapped in the outer lan already has a one
, given that all of its components have one.
20140326
concatenation and conjunction of ratexps accept more heterogeneous arguments
Conversions of both labels and weights are performed if needed.
>>> a = vcsn.context('ratexpset<lal_char(xy)_b>_z').ratexp("<2>'x*'") >>> b = vcsn.context('lal_char(b)_q') .ratexp('<1/3>b') >>> a * b <2>x*<1/3>b >>> (a*b).info()['type'] 'ratexpset<ratexpset<lal_char(bxy)_b>_q>' >>> ab = vcsn.context('lal_char(ab)_z').ratexp('(a+b)*') >>> bc = vcsn.context('lal_char(bc)_b').ratexp('(b+c)*') >>> ab & bc (a+b)*&(b+c)* >>> (ab & bc).info()['type'] 'ratexpset<lal_char(abc)_z>'
20140309
leftmult and rightmult are bound in Python
Both work on automata and ratexps. Left multiplication now has its arguments in a more natural order in the C++ API: (weight, automaton), instead of the converse previously. TAFKit still has it the old way. The Python operator * (leftassociative) is overloaded to provide syntactic sugar.
>>> z = vcsn.context('lal_char(abc)_z') >>> a = z.weight("12") * z.ratexp('ab').standard() * z.weight("23") >>> a.ratexp() (<12>ab)<23> >>> z.weight("12") * z.ratexp('ab') * z.weight("23") <12>(ab)<23>
20140308
sum of rational expressions accepts more heterogeneous arguments
Conversions of both labels and weights are performed if needed.
>>> a = vcsn.context('ratexpset<lal_char(xy)_b>_z').ratexp("<2>'x*'") >>> b = vcsn.context('lal_char(b)_q') .ratexp('<1/3>b') >>> a + b <2>x*+<1/3>b
concatenation accepts more heterogeneous arguments
As for products and union, it is now possible to compute the concatenation of automata with different types:
>>> z = vcsn.context('lal_char(a)_z').ratexp('<2>a') .derived_term() >>> q = vcsn.context('lal_char(b)_q').ratexp('<1/3>b').derived_term() >>> r = vcsn.context('lal_char(c)_r').ratexp('<.4>c') .derived_term() >>> (z*q*r).ratexp() <2>a<0.333333>b<0.4>c
20140305
Bug: standardization of automata
The standardization of an automaton no longer leaves former initial states that became nonaccessible.
Bug: rightmult on automata
Its behavior was completely wrong.
20140221
parse and display letter classes in transitions
It is now possible to directly write labels of transitions with letter classes. For instance '[aky]' denotes every letter between a and k in the alphabet, or y.
Transition labels with equal weights are displayed this way. For instance 'g, a, b, d, c, f' becomes [adfg] and '<2>a, <2>b, <2>c" is displayed '<2>[abc]', but 'a, b' stays in this form.
20140220
union accepts more heterogeneous arguments
As for products (Hadamard, shuffle, infiltration), it is now possible to compute the union of automata with different types:
>>> z = vcsn.context('lal_char(a)_z').ratexp('<2>a') .derived_term() >>> q = vcsn.context('lal_char(b)_q').ratexp('<1/3>b').derived_term() >>> r = vcsn.context('lal_char(c)_r').ratexp('<.4>c') .derived_term() >>> (zqr).ratexp() <2>a+<0.333333>b+<0.4>c
automaton product optimization.
An optimization enabled by state renumbering.
Score changes on Luca's workstation (before/after):
4.60s 2.87s: a.product(a) # a = std([ae]?{50}) 2.34s 2.37s: a.shuffle(a) # a = std([ae]?{50}) 4.01s 2.58s: a.infiltration(a) # a = std([ae]?{30}) 4.17s 2.96s: a**12 # a = std([ae]*b(<2>[ae])*)
20140218
state renumbering is not automatic any longer
In view of several forthcoming inplace algorithms on automata including edit, we changed the automaton output code not to automatically renumber states at the static, dyn and Python levels. A new "sort" algorithm is available to renumber states (breadthfirst and then by outgoing transition label) and reorder transitions (by label) in a predictable way, when explicitly requested. TAFKit output is automatically sorted.
Having a predictable numbering will enable future optimizations on automaton product and other algorithms accessing all the transition from a given state by label.
20140214
double_ring: New Python binding
Returns a double ring automaton.
20140211
ratexpset can be used for LabelSet
Contexts such as ratexpset<lal_char(ab)_b>_b
are now valid. The eliminate_state algorithm works properly on automata of such type.
20140210
ratexp.info: New Python binding
Like automaton.info, returns a dictionary of properties of the ratexp.
20140207
areisomorphic/isisomorphic: new algorithm (static, dyn, TAFKit, Python)
Given two automata, check whether they are isomorphic to one another. Currently implemented in the deterministic case only, for lal contexts.
>>> ctx = vcsn.context('lal_char(ab)_z') >>> ctx.ratexp('a+b*').standard().is_isomorphic(ctx.ratexp('b*+a').standard()) True
weighted minimization (static, dyn, tafkit, Python)
A third implementation of the minimization algorithm named "weighted" is now available, supporting any lal context.
The new variant is a more widely applicable generalization of the "signature" implementation. The new variant is the default for nonboolean weightsets; it requires a trim automaton but does not rely on determinism or other properties. Preliminary measures show performance to be close to "signature", or even clearly superior in the case of sparse automata such as dictionaries.
Vaucanson 2b.3 (20140203)
Release of our fourth beta, vaucanson2b.3. Available on MacPorts as "vaucanson".
See https://www.lrde.epita.fr/wiki/Vaucanson/Vaucanson2b3.
A Virtual Machine for easy experiments
Installing Vaucanson 2 on some platforms can be tedious. Clément Démoulins contributed a Virtual Machine that makes it easy to experiment with Vaucanson 2 without having to compile it. He also contributed a Vagrantfile to make it even easier to deploy.
To install a Vaucanson virtual machine, please follow this procedure:
1. Install VirtualBox From your distro, or from https://www.virtualbox.org/wiki/Downloads. 2. Install Vagrant From your distro, or from http://www.vagrantup.com/downloads.html 3. Download this Vagrantfile and save it somewhere. https://www.lrde.epita.fr/dload/vaucanson/2.0/Vagrantfile For instance $ mkdir ~/src/vcsn2 $ cd ~/src/vcsn2 $ wget https://www.lrde.epita.fr/dload/vaucanson/2.0/Vagrantfile 4. Run Vagrant (first time will be slow: let it download the VM) $ cd ~/src/vcsn2 $ vagrant up Vaucanson is running! 5. Open http://localhost:8888 in your favorite browser. 6. Experiment! (Hit ShiftEnter to evaluate): import vcsn vcsn.context('lal_char(abc)_z').ratexp('(<2>a+<3>b)*').derived_term() 7. Turn your VM off when you are done $ vagrant halt
20140129
ratexp difference: new algorithm (static, dyn, Python)
The "difference" algorithms generates a ratexp that accepts words of the lefthand side that are not accepted by the righthand side ratexp. Also bound as the "%" operator in Python.
>>> ctx = vcsn.context('lal_char(abc)_b') >>> l = ctx.ratexp('[abc]*') >>> r = ctx.ratexp('[ab]*') >>> l.difference(r) (a+b+c)*&(a+b+c)* >>> l % r (a+b+c)*&(a+b+c)*
20140127
ratexp intersection: new algorithm (static, dyn, Python)
The "intersection" algorithm computes a ratexp that denotes the Hadamard product of two rational expressions. Also bound as the "&" operator in Python.
>>> ctx = vcsn.context('lal_char(abc)_b') >>> r = ctx.ratexp('[abc]*') >>> r.intersection(r) (a+b+c)*&(a+b+c)* >>> r & r (a+b+c)*&(a+b+c)*
ratexp concatenation: new algorithm (static, dyn, Python)
The "concatenate" algorithm computes a ratexp that denotes the concatenation of two rational expressions. Also bound as the "*" operator in Python.
>>> ctx = vcsn.context('lal_char(abc)_b') >>> r = ctx.ratexp('[abc]*') >>> r.concatenate(r) (a+b+c)*(a+b+c)* >>> r * r (a+b+c)*(a+b+c)*
Python API: Operators overloading on automata
The Python API now overloads the following operators for automata:
+
, sum of two automata&
, product of two automata~
, complement of an automaton*
, concatenation of two automata%
, difference between two automata
, union of two automata**
, power of an automaton
20140124
ratexp sum: new algorithm (static, dyn, Python)
Compute the sum of two rational expressions. Also bound as the +
operator in Python.
>>> ctx = vcsn.context('lal_char(abc)_b') >>> r = ctx.ratexp('[abc]*') >>> r.sum(r) (a+b+c)*+(a+b+c)* >>> r + r (a+b+c)*+(a+b+c)*
proper: an optional argument to avoid state deletion
The proper algorithm eliminates the states that become inaccessible in the course of spontaneoustransition elimination. This can be disabled by passing "false" as additional argument to proper (static, dyn, Python).
20140117
star_height: new algorithm (static, dynamic, Python)
Computes the starheight of an expression.
>>> vcsn.context('lal_char(ab)_b').ratexp('(a***+a**+a*)*').star_height() 4
Bison is no longer needed
To install Vaucanson from a tarball, Bison is no longer needed. Of course, modifying one of grammar files will fail, unless Bison 3.0 is installed.
20140113
Letter classes in context specifications
It is now possible to use ranges to define alphabets. For instance in Python,
vcsn.context('lal_char(azAZ09_)_b')
builds a context whose alphabet covers letters, digits, and underscore.
Vaucanson 2b.2 (20140110)
Release of our third beta, vaucanson2b.2. Available on MacPorts as "vaucanson".
Letter classes
Letter classes are available in ratexps: [ad09_]
is expanded into (a+b+c+d+0+1+2+3+4+5+6+7+8+9+_)
. The negation, [^...]
, is not supported.
20140102
The '.' operator is no longer printed
The prettyprinting of (nonLAW) ratexps is simplified.
Before:
$ vcsn ladybird 2  vcsn determinize  vcsn auttoexp \e+a.(b+a.a+c.(a+c)*.b)*.(a+c.(a+c)*) $ vcsn derivedterm Ee 'a:b:c'  vcsn auttoexp (a.b+b.a).c+(a.c+c.a).b+(b.c+c.b).a
After:
$ vcsn ladybird 2  vcsn determinize  vcsn auttoexp \e+a(b+aa+c(a+c)*b)*(a+c(a+c)*) $ vcsn derivedterm Ee 'a:b:c'  vcsn auttoexp (ab+ba)c+(ac+ca)b+(bc+cb)a
Shortlex order is now used for ratexps
This changes the prettyprinting of polynomials of ratexps, for instance the result of derivations.
Before:
$ vcsn derivation e '(a*+b*)a(a*+b*)' aa a*+b* + a*.a.(a*+b*) + a*
After:
$ vcsn derivation e '(a*+b*)a(a*+b*)' aa a* + a*+b* + a*a(a*+b*)
ratexp implementation overhaul
Although internal, this change is documented as it deeply changes the way ratexps are handled in C++ code.
The abstractsyntax tree of the rational expressions now matches the usual (abstract) grammar:
E ::= \z  \e  a  E+F  E.F  E*  kE  Ek k is a weight
In other words, there are now 'leftweight' and 'rightweight' nodes that exist, whereas before, the six first cases carried left and right weights. Trivial identities are enforced, and, for instance, no tree for 'a k' exist: it is converted to 'k a'.
20131219
Many of these listed features were actually developed over the last month.
products accept more heterogeneous arguments
It is already possible to compute the (regular, infiltration and shuffle) products of automata with different types of "basic" weightsets (e.g. B, Z, Q, R).
It is now also possible when weights are ratexps. For instance the product of an automaton with weights in Q and an automaton with weights in RatE yields an automaton with weights in QRatE.
New ratexp operators: &
(intersection) and :
(shuffle)
The operator &
denotes the intersection in the case of Boolean weights, or more generally, the Hadamard product. Only "derived_term" can compute an automaton from it, in which case:
derived_term(E & F) = product(derived_term(E), derived_term(F))
The operator :
denotes the shuffle product, aka interleave. For instance a:b:c
denotes the language of the permutations of "abc". Only "derived_term" can compute an automaton from it, in which case:
derived_term(E : F) = shuffle(derived_term(E), derived_term(F))
minimization is much faster
There are now two different implementations of the minimization, namely "moore" and "signature". Both require a trim automaton as input, and "signature" accepts nondeterministic automata.
The "moore" minimization is currently the fastest.
context runtime compilation
When dyn::make_context is presented with an unknown but valid context, it is compiled and loaded dynamically. For instance:
$ vcsn cat C 'lao_r' W e 3.14 # Wait for the context to be compiled... 3.14
The compiled context is currently left in /tmp for forthcoming runs.
$ ls /tmp/lao* /tmp/lao_r.cc /tmp/lao_r.o /tmp/lao_r.so
Python binding
It is now possible to use Vaucanson from Python. The Python binding is on top of the dyn API, and inherits all its features.
This Python API is objectoriented, contrary to dyn which is a list of types (context, ratexp, automaton, etc.) and functions (derived_term, determinize, etc.):
dyn:: functions  Python methods 

* derived_term(ratexp) > automaton

* ratexp.derived_term() > automaton

Documentation is forthcoming, but for instance:
$ python Python 2.7.6 (default, Nov 12 2013, 13:26:39) [GCC 4.2.1 Compatible Apple Clang 4.1 ((tags/Apple/clang421.11.66))] on darwin Type "help", "copyright", "credits" or "license" for more information. >>> import vcsn >>> b = vcsn.context('lal_char(abc)_b') >>> b lal_char(abc)_b >>> r1 = b.ratexp('(a+b)*') >>> r1 (a+b)* >>> a1 = r1.derived_term() >>> a2 = b.ratexp('(b+c)*').standard() >>> a1.product(a2).ratexp() \e+b.b* >>>
20131203
products accept heterogeneous arguments
It is now possible to compute the (regular, infiltration and shuffle) products of a (B, Z, Q, R) automaton with a (B, Z, Q, R) automaton.
$ vcsn derivedterm C 'lal_char(ab)_q' e '(<1/2>a+<1/3>b)*' > q.gv $ vcsn derivedterm C 'lal_char(ab)_z' e '(<2>a+<3>b)*' > z.gv $ vcsn derivedterm C 'lal_char(ab)_r' e '(<.2>a+<.3>b)*' > r.gv $ vcsn product f z.gv q.gv  vcsn auttoexp (a+b)* $ vcsn product f q.gv z.gv  vcsn auttoexp (a+b)* $ vcsn product f q.gv z.gv q.gv  vcsn auttoexp (<1/2>a+<1/3>b)* $ vcsn product f q.gv z.gv z.gv  vcsn auttoexp (<2>a+<3>b)* $ vcsn product f q.gv r.gv  vcsn auttoexp (<0.1>a+<0.1>b)* $ vcsn product f z.gv r.gv  vcsn auttoexp (<0.4>a+<0.9>b)* $ vcsn product f z.gv r.gv q.gv  vcsn auttoexp (<0.2>a+<0.3>b)*
20131202
TikZ output now uses standalone
The TikZ output can now both be compiled as a standalone document, and be used inlined (as LaTeX source) in another document. Read the document of the "standalone" package (e.g., run 'texdoc standalone').
Data library path
TAFKit is now able to find installed files. Control the search path via the environment variable VCSN_DATA_PATH (a ":"separated list of directories).
$ vcsn auttoexp f lal_char_z/c1.gv (a+b)*.b.(<2>a+<2>b)*
dot format parsing is much faster
We now require Bison 3.0 to build Vaucanson. In exchange, we get is very significant speedup. On erebus (Mac OS X i7 2.9GHz 8GB, GCC 4.8 O3) reading standard('a?{500}') goes from 30s to 1.2s.
20131125
minimize: new algorithm (static, dynamic, TAFKit)
Given a deterministic Boolean lal automaton, compute its minimal equivalent automaton using Moore's algorithm.
Example:
$ vcsn standard e '(a+b+c+d){100}' o 100.gv $ vcsn cat f 100.gv O info  grep 'number of states' number of states: 401 $ vcsn minimize f 100.gv o 100min.gv $ vcsn cat f 100min.gv O info  grep 'number of states' number of states: 101 $ vcsn areequivalent f 100.gv 100min.gv true
fraction parsing bug fixes
Negative denominators used to be silently mangled, and zero denominators were accepted without failing.
20131122
split: new algorithm (static, dynamic, TAFKit)
Implements the breaking of a ratexp into a polynomial of ratexps, as required by breaking derivation, and broken derived terms. Not named "break", as this is a C++ keyword.
20131120
products accept heterogeneous arguments
It is now possible to compute the (regular, infiltration and shuffle) products of a Bautomaton with any other kind of automaton.
$ vcsn standard C 'lal_char(ab)_b' e 'a' o a.gv $ vcsn standard C 'lal_char(ab)_ratexpset<lal_char(uv)_b>' \ e '(<u>a+<v>b)*' o ab.gv $ vcsn product f ab.gv a.gv  vcsn shortest f  4 <u>a $ vcsn shuffle f ab.gv a.gv  vcsn shortest f  4 a + <u+u>aa + <v>ab + <v>ba $ vcsn infiltration f ab.gv a.gv  vcsn shortest f  4 <u+\e>a + <u.u+u+u>aa + <u.v+v>ab + <v.u+v>ba
20131119
shortest: accepts the number of words as argument (defaults to 1)
$ vcsn shortest O text Ee '(a+b)*' 2 \e + a $ vcsn enumerate O text Ee '(a+b)*' 2 \e + a + b + aa + ab + ba + bb
difference: new algorithm (static, dynamic, TAFKit)
Computes the difference between an automaton and a Bautomaton (on LAL only):
$ vcsn derivedterm e '(?@lal_char(ab)_z)(<2>a+<3>b)*' o lhs.gv $ vcsn derivedterm e '(a+b)*b(a+b)*' o rhs.gv $ vcsn difference f lhs.gv rhs.gv  vcsn auttoexp (<2>a)* $ vcsn difference f rhs.gv rhs.gv  vcsn auttoexp \z
product accepts heterogeneous arguments
It is now possible to compute the product of (for instance) a Zautomaton with a Bautomaton.
$ vcsn standard C 'lal_char(abc)_z' e '(<2>a+<3>b+<5>c)*' o 1.gv $ vcsn standard C 'lal_char(b)_b' e 'b*' o 2.gv $ vcsn product f 1.gv 2.gv  vcsn auttoexp \e+<3>b.(<3>b)* $ vcsn product f 2.gv 1.gv  vcsn auttoexp \e+<3>b.(<3>b)*
Vaucanson 2b.1 (20131113)
Release of our second beta, vaucanson2b.1. Available on MacPorts as "vaucanson".
20131107
TAFKit: infiltration, product, shuffle: accept multiple arguments
You may pass several (one or more) arguments to vcsn product, infiltration and shuffle.
infiltration, product, shuffle: accept non commutative semirings
Beware that the (well defined) behavior of the resulting automata is no longer what one might expect.
$ vcsn standard C 'lal_char(ab)_ratexpset<lal_char(uv)_b>' \ e '<u>a<v>b' o uv.gv $ vcsn standard C 'lal_char(ab)_ratexpset<lal_char(xy)_b>' \ e '<x>a<y>b' o xy.gv $ vcsn product f uv.gv xy.gv  vcsn enumerate f  4 <u.x.v.y>ab $ vcsn shuffle f uv.gv xy.gv  vcsn enumerate f  4 <u.x.v.y+u.x.y.v+x.u.v.y+x.u.y.v>aabb <u.v.x.y+x.y.u.v>abab $ vcsn infiltration f uv.gv xy.gv  vcsn enumerate f  4 <u.x.v.y>ab <u.x.v.y+x.u.v.y>aab <u.x.v.y+u.x.y.v>abb <u.x.v.y+u.x.y.v+x.u.v.y+x.u.y.v>aabb <u.v.x.y+x.y.u.v>abab
Input/Output fixes
Support for EFSM in input/output is improved to support weights. Output was significantly sped up.
Before:
0.64s: standard Ee 'a?{500}' O dot >a500.gv 4.47s: standard Ee 'a?{500}' O efsm >a500.efsm 4.04s: standard Ee 'a?{500}' O fado >a500.fado 4.83s: standard Ee 'a?{500}' O grail>a500.grail 1.03s: standard Ee 'a?{500}' O tikz >a500.tikz
After:
0.76s: standard Ee 'a?{500}' O dot >a500.gv 0.37s: standard Ee 'a?{500}' O efsm >a500.efsm 0.35s: standard Ee 'a?{500}' O fado >a500.fado 0.35s: standard Ee 'a?{500}' O grail>a500.grail 0.68s: standard Ee 'a?{500}' O tikz >a500.tikz
20131104
boolean weight parsing bug fix
The weight parser used to ignore all characters after the first one, so that for example "1q" was considered valid and equivalent to "1".
20131031
product and infiltrationproduct are much faster
On erebus (MacBook Pro i7 2.9GHz 8GB, GCC 4.8 O3), with "vcsn standard E e 'a?70' o a70.gv":
Before:
13.01s: product q f a70.gv a70.gv 0.23s: shuffle q f a70.gv a70.gv 16.64s: infiltration q f a70.gv a70.gv
After:
0.77s: product q f a70.gv a70.gv 0.19s: shuffle q f a70.gv a70.gv 0.87s: infiltration q f a70.gv a70.gv
20131030
TAFKit: option name changes
The former options W and L (to specify the weightset and labelset) are removed, definitively replaced by C, to specify the context.
In addition to A and E (input is an automaton/ratexp), option W now replaces option w (input is a weight), and option P denotes "polynomials". Note that "polynomials" are actually linear combinations of labels, weighted by weights, so for instance "LAL" contexts accept only singleletter labels, used LAW to accept words.
$ vcsn cat C 'law_char(ab)_z' P e 'a+ab + <1>a+ab+<10>bb' <2>ab + <10>bb
internal overhaul
Better names were chosen for the various details of the dyn:: value support:
abstract_automaton > automaton_base abstract_context > context_base abstract_polynomial > polynomial_base concrete_abstract_polynomial > polynomial_wrapper abstract_ratexp > ratexp_base concrete_abstract_ratexp > ratexp_wrapper abstract_ratexpset > ratexpset_base concrete_abstract_ratexpset > ratexpset_wrapper abstract_weight > weight_base concrete_abstract_weight > weight_wrapper
Note that _base
is slightly misleading, as it actually applies to the wrappers, and not to the static objects. For instance, weightset_wrapper derives from weightset_base, but b
, z
, and the other (static) weightsets do not derive from weightset_base
. It would therefore be more precise to name weightset_base
as weightset_wrapper_base
, but that might be uselessly long. Names may change again in the future.
Because dyn::polynomial
and dyn::weight
store the corresponding polynomialset/weightset, there is no need (so far?) for a dyn::polynomialset
/dyn::weightset
. Therefore, abstract_polynomialset
and abstract_weightset
were removed.
For consistency (and many other benefits), automaton_wrapper
and context_wrapper
were introduced. Now, the whole static API is completely independent of the dyn API, and the dyn API consists only of wrappers of "static"level valuesinstead of inheritance for automata and contexts.
20131025
renamings (static, dynamic, TAFKit)
derive > derivation derivedterms > derivedterm infiltrate > infiltration
20131024
tafkit: option q for "quiet"
Equivalent to "O null": do not generate output.
starnormalform: new algorithm (static, dynamic, TAFKit)
Compute an equivalent rational expression where starred subexpressions have a non null constant term. Yields the same standard automaton, but built faster.
$ vcsn starnormalform e '(a*b*)*' (a+b)*
Valid only for Boolean automata.
ratexp printing: minimize parentheses
Print rational expressions with the minimum required number of parentheses, making some large expressions considerably easier to read. For example
Before:
$ vcsn expand C 'law_char(abc)_z' e '(a+b)?{2}*' (\e+<2>a+<2>b+(aa)+(ab)+(ba)+(bb))* $ vcsn ladybird 2  vcsn determinize  vcsn auttoexp \e+(a.((b+(a.a)+(c.((a+c)*).b))*).(a+(c.((a+c)*))))
After:
$ vcsn expand C 'law_char(abc)_z' e '(a+b)?{2}*' (\e+<2>a+<2>b+aa+ab+ba+bb)* $ vcsn ladybird 2  vcsn determinize  vcsn auttoexp \e+a.(b+a.a+c.(a+c)*.b)*.(a+c.(a+c)*)
expand: new algorithm (static, dynamic, TAFKit)
Given a rational expression, distribute product over addition (recursively under the starred subexpressions) group and sort the equal monomials.
$ vcsn expand C 'lal_char(abc)_z' e '(a+b)?{2}*' (\e+<2>a+<2>b+(a.a)+(a.b)+(b.a)+(b.b))*
Vaucanson 2b.0 (20131022)
Release of our first beta, vaucanson2b.0.
20131017
shuffle, infiltrate: new algorithms (static, dynamic, TAFKit)
New algorithms on LAL automata: computes the shuffleproduct and infiltration of two automata. These (and now product as well) require weightsets to be commutative semirings.
$ vcsn standard C 'lal_char(ab)_z' E e 'ab' o ab.gv $ vcsn product f ab.gv ab.gv  vcsn enumerate O text f  4 ab $ vcsn shuffle f ab.gv ab.gv  vcsn enumerate O text f  4 <4>aabb + <2>abab $ vcsn infiltrate f ab.gv ab.gv  vcsn enumerate O text f  4 ab + <2>aab + <2>abb + <4>aabb + <2>abab
20131015
derivedterms: new algorithm (static, dynamic, TAFKit)
In addition to thompson and standard, this is a third means to build an automaton from a (weighted) rational expression. It corresponds to the Antimirov definition of derivatives (implemented by "derive"). It requires LAL rational expressions.
$ vcsn derivedterms C 'lal_char(ab)_q' e '(<1/6>a*+<1/3>b*)*' digraph { vcsn_context = "lal_char(ab)_q" rankdir = LR { node [style = invis, shape = none, label = "", width = 0, height = 0] I0 F0 F1 F2 } { node [shape = circle] 0 1 2 } I0 > 0 0 > F0 [label = "<2>"] 0 > 1 [label = "<1/3>a"] 0 > 2 [label = "<2/3>b"] 1 > F1 [label = "<2>"] 1 > 1 [label = "<4/3>a"] 1 > 2 [label = "<2/3>b"] 2 > F2 [label = "<2>"] 2 > 1 [label = "<1/3>a"] 2 > 2 [label = "<5/3>b"] }
vcsn eliminatestate
This tool allows one to eliminate states one after the other.
$ vcsn eliminatestate f lao.gv 2
Its interface is likely to change, or to be completely removed.
Smaller libraries
Some compiler magic was used to reduce the size of the libraries (about 20% on Mac OS X using GCC 4.8). TAFKit might start faster.
20131014
determinize: by default no longer forces the result to be complete
The determinization (static, dynamic, TAFKit) now admits an optional second argument (defaulting to '0'), a Boolean stating whether the result must be complete.
20131012
polynomialset fully replaces entryset
The 'entryset' type is removed, as polynomialset now provides a strict superset of its features.
20131011
derive: new algorithm (static, dynamic, TAFKit)
New algorithm on LAL automata: computes the derivation of rational expressions with respect to a word.
$ vcsn derive C 'lal_char(a)_z' e '(<2>a)*' a <2>(<2>a)* $ vcsn derive C 'lal_char(a)_z' e '(<2>a)*' aa <4>(<2>a)* $ vcsn derive C 'lal_char(a)_z' e '(<2>a)*' aaaa <16>(<2>a)* $ vcsn derive C 'lal_char(a)_z' e '(<2>a)*' b \z $ vcsn derive C 'lal_char(ab)_q' e '(<1/6>a*+<1/3>b*)*' a <1/3>(a*).(((<1/6>a*)+(<1/3>b*))*) $ vcsn derive C 'lal_char(ab)_q' e '(<1/6>a*+<1/3>b*)*' aa <4/9>(a*).(((<1/6>a*)+(<1/3>b*))*)
20131008
enumerate returns a dyn::polynomial
The 'enumerate' algorithm use to cheat, and returned a std::vector<string> (each string being a prettyprinting of the monomial, e.g., "<2>a"). It now returns a dyn::polynomial.
vcsnenumerate is biased to prefer the 'list' output format:
$ vcsn enumerate Ee 'a*' 3 \e a aa aaa
however the proper syntax for polynomials can be asked for.
$ vcsn enumerate O text Ee 'a*' 3 \e + a + aa + aaa
New dyn:: type: polynomial
A new member joins the dyn:: family of types (i.e., automaton, ratexp, ratexpset, weight, weightset). Currently there are no means to read such a value from TAFKit, but there is output support with two different output format:
 'text' (aka 'default') Prints the polynomial this usual way, e.g., "<2>a+<3>b".
 'list' Prints one monomial per line, e.g. '<2>a <3>b'
20131002
mutable_automaton: speed improvement
"set_transition" used to invoke twice "get_transition", which had a serious performance impact on some algorithms. This is fixed.
Before:
9.08s (0.33s+8.75s): ladybird 21  determinize O null 16.88s (0.85s+16.03s): thompson C "lan_char(a)_b" Ee "a?{2000}"  proper O null 21.30s (9.76s+11.54s): standard Ee "(a+b+c+d)?{100}"  auttoexp O null 7.29s (0.04s+7.25s): standard C "lal_char(ab)_z" Ee "(a+b)*b(<2>a+<2>b)*"  power O null f 10 0.04s (0.04s): standard E e "(a?){70}" o a70.gv 24.20s (24.20s): product O null f a70.gv a70.gv
After:
8.54s (0.13s+8.41s): ladybird 21  determinize O null 11.87s (0.86s+11.01s): thompson C "lan_char(a)_b" Ee "a?{2000}"  proper O null 21.03s (9.40s+11.63s): standard Ee "(a+b+c+d)?{100}"  auttoexp O null 6.58s (0.06s+6.52s): standard C "lal_char(ab)_z" Ee "(a+b)*b(<2>a+<2>b)*"  power O null f 10 0.07s (0.07s): standard E e "(a?){70}" o a70.gv 13.16s (13.16s): product O null f a70.gv a70.gv
Note in particular that the spontaneous transition elimination algorithm is faster, going from 16s to 11s on a MacBook Pro i7 2.9GHz 8GB RAM, on the following sequence.
$ vcsn thompson C 'lan_char(a)_b' Ee 'a?{2000}'  vcsn proper O null
20131001
random: new algorithm (static, dynamic, TAFKit)
Random generation of automata. Subject to changes. Accepts four arguments: number of states, density (of transitions, defaults to .1, 1 generates a clique), number of initial states (defaults to 1), and number of final states (defaults to 1).
So far LAL and LAN only, no support for random weights.
$ vcsn random O fado 3 @DFA 0 0 d 1 1 c 2 2 d 2 $ vcsn random O fado 3 @DFA 2 0 c 1 1 d 2 2 c 0 $ vcsn random C 'lan_char(ab)_b' O fado 3 @NFA 1 * 0 0 @epsilon 1 1 b 2 2 b 1
20130924
Overhaul of the package
Thanks to Automake 1.14 features, there is now a single Makefile, which significantly speeds up the compilation of the package. The testsuite now uses the Test Anything Protocol, which results in more verbose results.
Beware that because of subtle issues (in the generated Makefile snippets that track dependencies), you are highly recommend to "make clean" after upgrading from the Git repository, and then "make" as usual.
20130920
proper: faster implementation
The spontaneous transition elimination algorithm is now faster, going from 102s to 15s on a MacBook Pro i7 2.9GHz 8GB RAM, on the following sequence.
$ vcsn thompson C 'lan_char(a)_b' Ee 'a?{2000}'  vcsn proper O null
20130917
isambiguous
New algorithm (static, dynamic, TAFKit) on LAL automata: whether some word is the label of at least two successful computations.
$ vcsn isambiguous <<\EOF digraph { vcsn_context="lal_char(ab)_b" I > 0 0 > 1 [label = "a"] 0 > 2 [label = "a"] 1 > F } EOF false $ vcsn isambiguous <<\EOF digraph { vcsn_context="lal_char(ab)_b" I > 0 0 > 1 [label = "a"] 0 > 2 [label = "a"] 1 > F 2 > F } EOF true
Also reported in the 'info' format for automata.
product: recover the original states
Similarly to 'determinize', the (static version of) 'product' can now be queried to get a map from states of the result to pairs of original states.
20130908
Sum of standard automata is fixed
See the previous entry: the computation of the initial transition was wrong, which resulted in the production of nonstandard automata. This is fixed:
$ vcsn standard C 'lal_char(a)_ratexpset<lal_char(x)_b>' e '<x>a*' > 1.gv $ vcsn standard C 'lal_char(b)_ratexpset<lal_char(y)_b>' e '<y>b*' > 2.gv $ vcsn sum f 1.gv 2.gv digraph { vcsn_context = "lal_char(ab)_ratexpset<lal_char(xy)_b>" rankdir = LR { node [style = invis, shape = none, label = "", width = 0, height = 0] I0 F0 F1 F2 } { node [shape = circle] 0 1 2 } I0 > 0 0 > F0 [label = "<x+y>"] 0 > 1 [label = "<x>a"] 0 > 2 [label = "<y>b"] 1 > F1 1 > 1 [label = "a"] 2 > F2 2 > 2 [label = "b"] }
20130906
Operations on automata are generalized
Operations (union, sum, concatenate, chain) were uselessly restricted to LAL. Besides, the contexts were improperly computed (both labelset and weightset). This is fixed.
$ vcsn standard C 'lal_char(a)_ratexpset<lal_char(x)_b>' e '<x>a*' > 1.gv $ vcsn standard C 'lal_char(b)_ratexpset<lal_char(y)_b>' e '<y>b*' > 2.gv $ vcsn sum f 1.gv 2.gv digraph { vcsn_context = "lal_char(ab)_ratexpset<lal_char(xy)_b>" rankdir = LR { node [style = invis, shape = none, label = "", width = 0, height = 0] I0 F0 F1 F2 } { node [shape = circle] 0 1 2 } I0 > 0 [label = "<\\e+\\e+\\e>"] 0 > F0 [label = "<x+y>"] 0 > 1 [label = "<x>a"] 0 > 2 [label = "<y>b"] 1 > F1 1 > 1 [label = "a"] 2 > F2 2 > 2 [label = "b"] }
20130904
doublering
New algorithm (static, dynamic, TAFKit).
$ vcsn doublering C 'lal_char(ab)_b' 6 1 3 4 5 digraph { vcsn_context = "lal_char(ab)_b" rankdir = LR { node [style = invis, shape = none, label = "", width = 0, height = 0] I0 F1 F3 F4 F5 } { node [shape = circle] 0 1 2 3 4 5 } I0 > 0 0 > 1 [label = "a"] 0 > 5 [label = "b"] 1 > F1 1 > 0 [label = "b"] 1 > 2 [label = "a"] 2 > 1 [label = "b"] 2 > 3 [label = "a"] 3 > F3 3 > 2 [label = "b"] 3 > 4 [label = "a"] 4 > F4 4 > 3 [label = "b"] 4 > 5 [label = "a"] 5 > F5 5 > 0 [label = "a"] 5 > 4 [label = "b"] }
It is advised to pass "layout = circo" to Dot for the rendering.
concatenation, chain
New algorithm on standard automata (static, dynamic, TAFKit).
rightmult
New algorithm on standard automata (static, dynamic, TAFKit). Same limitations as leftmult, see below.
20130903
leftmult
New algorithm on standard automata (static, dynamic, TAFKit).
The TAFKit version is (currently) troublesome, as it does not infer the context to parse the weight from the automaton: be sure to specify C:
$ vcsn standard C 'lal_char(a)_z' e a  vcsn leftmult 12 vcsnleftmult: left_mult: no implementation available for mutable_automaton<lal_char_z> x b $ vcsn standard C 'lal_char(a)_z' e a  vcsn leftmult C 'lal_char(a)_z' 12 digraph { vcsn_context = "lal_char(a)_z" rankdir = LR { node [style = invis, shape = none, label = "", width = 0, height = 0] I0 F1 } { node [shape = circle] 0 1 } I0 > 0 0 > 1 [label = "<12>a"] 1 > F1 }
tafkit: option w for weights as input
Currently only vcsncat supports it.
$ vcsn cat w e 2 vcsncat: invalid Boolean: 2 $ vcsn cat w e 1 1 $ vcsn cat C 'lal_char(a)_z' w e 2 2
concatenate, star, sum
New algorithms on standard automata (static, dynamic, TAFKit).
20130902
union
New algorithm on automata (static as "union_a", dynamic as "union_a", TAFKit as "union"). Plain graph union.
isvalid
New algorithm on rational expressions (static, dynamic, TAFKit).
$ vcsn isvalid C 'lal_char(a)_r' E e '(<.5>\e)*' true $ vcsn isvalid C 'lal_char(a)_r' E e '\e*' false
For consistency, isvalid is now also available for automata in dyn:: and TAFKit (it used to be static only, visible from "info" output).
$ vcsn thompson C 'lan_char(a)_r' e '(<.5>\e)*'  vcsn isvalid true $ vcsn thompson C 'lan_char(a)_r' e '\e*'  vcsn isvalid false
20130813
More RatExp quantifiers
In addition to "", there is "?"/"{?}" and "{+}". Support for "{}" is added for symmetry.
$ vcsn cat Ee 'a?' \e+a $ vcsn cat Ee 'a?{3}' (\e+a).(\e+a).(\e+a) $ vcsn cat Ee '(a+b){+}' (a+b).((a+b)*)
20130802
I/O EFSM format support
We are now able to produce and read EFSM format (designed as an interface to OpenFST). This is not (yet) thoroughly tested for weighted automata.
$ vcsn ladybird O efsm 4  efstcompile  fstdeterminize  efstdecompile  vcsn cat I efsm O info type: mutable_automaton<lal_char(abc)_b> number of states: 15 number of initial states: 1 number of final states: 8 number of accessible states: 15 number of coaccessible states: 15 number of useful states: 15 number of transitions: 43 number of deterministic states: 15 number of eps transitions: 0 is complete: 0 is deterministic: 1 is empty: 0 is epsacyclic: 1 is normalized: 0 is proper: 1 is standard: 0 is trim: 1 is useless: 0 is valid: 1
Output in EFSM format is improved
State numbers now start appropriately at 0 (instead of 2), and when there is a single initial state, no "preinitial state" is output; this avoids the introduction of spontaneous transitions in deterministic automata.
Before (see news of 20130701):
$ vcsn ladybird O efsm 2 #! /bin/sh cat >transitions.fsm <<\EOFSM 0 2 \e 2 2 3 a 3 3 b 3 3 c 3 2 c 3 2 a EOFSM cat >isymbols.txt <<\EOFSM \e 0 a 1 b 2 c 3 EOFSM fstcompile acceptor keep_isymbols isymbols=isymbols.txt transitions.fsm
Now:
$ vcsn ladybird O efsm 2 #! /bin/sh cat >isymbols.txt <<\EOFSM \e 0 a 1 b 2 c 3 EOFSM cat >transitions.fsm <<\EOFSM 0 1 a 1 0 a 1 1 b 1 0 c 1 1 c 0 EOFSM fstcompile acceptor keep_isymbols isymbols=isymbols.txt transitions.fsm
I/O FAdo format support
We are now able to produce and read FAdo format.
$ vcsn ladybird O fado 4  \ python c "from FAdo import fa nfa = fa.readFromFile('/dev/stdin')[0] dfa = nfa.toDFA() fa.saveToFile('dl4.fado', dfa)" $ vcsn cat I fado O info f dl4.fado type: mutable_automaton<lal_char(abc)_b> number of states: 15 number of initial states: 1 number of final states: 8 number of accessible states: 15 number of coaccessible states: 15 number of useful states: 15 number of transitions: 43 number of deterministic states: 15 number of eps transitions: 0 is complete: 0 is deterministic: 1 is empty: 0 is epsacyclic: 1 is normalized: 0 is proper: 1 is standard: 0 is trim: 1 is useless: 0 is valid: 1
constantterm
New algorithm on rational expressions (static, dynamic, TAFKit).
$ vcsn constantterm e '(?@lal_char(a)_b)(\e)*' 1 $ vcsn constantterm e '(?@lal_char(a)_z)(\e)*' vcsnconstantterm: z: star: invalid value: 1 $ vcsn constantterm C 'law_char(ab)_ratexpset<law_char(wxyz)_b>' \ e '<w>(<x>a*+<y>b*)*<z>' w.((x+y)*).z
20130726
Automaton library
The set of library automata for existing contexts is now complete with respect to what Vaucanson 1 provided. Automata families are not, and will not, be part of this library ; for instance, instead of looking for ladybird6.gv, use 'vcsn ladybird 6'.
lal_char_b: a1.gv b1.gv evena.gv oddb.gv lal_char_z: b1.gv binary.gv c1.gv d1.gv lal_char_zmin: minab.gv minblocka.gv slowgrow.gv
Currently one must specify their path:
$ vcsn evaluate f share/vcsn/lal_char_zmin/minab.gv aabbba 3
20130725
TAFKit: works on standard input by default
The very frequent "f " sequence is no longer required: by default the input is stdin.
$ vcsn ladybird 2  vcsn determinize  vcsn auttoexp \e+(a.((b+(a.a)+(c.((a+c)*).b))*).(a+(c.((a+c)*))))
20130718
standard
New algorithm on automata (static, dynamic, TAFKit). Corresponds to "standardize" in Vaucanson 1.
isstandard
New algorithm on automata (static, dynamic, TAFKit). Also reported in "info" format.
u
New automata factory (static, dynamic, TAFKit): Brzozowski's universal witness.
20130717
New formats: grail and fado
$ vcsn standard O fado e 'a+b' @DFA 1 2 0 a 1 0 b 2 $ vcsn standard O fado e 'a+ab' @NFA 1 3 * 0 0 a 1 2 b 3 0 a 2 $ vcsn standard O grail e 'a+ab' (START)  0 0 a 1 2 b 3 0 a 2 1  (FINAL) 3  (FINAL)
20130714
power
New algorithm on automata (static, dynamic, TAFKit).
$ vcsn standard e '(?@lal_char(01)_z)(0+1)*1(<2>0+<2>1)*' >binary.gv $ vcsn power f binary.gv 0  vcsn enumerate f 2 \e 0 1 00 01 10 11 $ vcsn power f binary.gv 1  vcsn enumerate f 2 1 <2>10 <3>11 $ vcsn power f binary.gv 2  vcsn enumerate f 2 1 <4>10 <9>11 $ vcsn power f binary.gv 4  vcsn enumerate f 2 1 <16>10 <81>11 $ vcsn power f binary.gv 8  vcsn enumerate f 2 1 <256>10 <6561>11
20130713
divkbaseb
New algorithm (static, dynamic, TAFKit).
$ vcsn divkbaseb C 'lal_char(01)_b' 3 2 digraph { vcsn_context = "lal_char(01)_b" rankdir = LR { node [style = invis, shape = none, label = "", width = 0, height = 0] I0 F0 } { node [shape = circle] 0 1 2 } I0 > 0 0 > F0 0 > 0 [label = "0"] 0 > 1 [label = "1"] 1 > 0 [label = "1"] 1 > 2 [label = "0"] 2 > 1 [label = "0"] 2 > 2 [label = "1"] }
20130712
enumerate produces a list of weighted words
enumerate now also provides the weight of the words. It is also fixed: it no longer reports words with nul weight (e.g., 'a' in 'a+<1>a').
$ vcsn standard e '(?@lal_char(01)_z)(0+1)*1(<2>0+<2>1)*' \  vcsn enumerate f  3 1 01 <2>10 <3>11 001 <2>010 <3>011 <4>100 <5>101 <6>110 <7>111
shortest is fixed and modified similarly.
$ vcsn standard e '(?@lal_char(ab)_z)(a+<5>bb+<1>a)' \  vcsn shortest f  <5>bb
20130704
WeightSet: added support for rational weights
We can now use automata with rational numbers as their weights.
$ vcsn standard e "(?@lal_char(ab)_q)(<1/2>a+<2>b)*" \  vcsn evaluate f  aaabbbb 2 $ vcsn standard e "(?@lal_char(ab)_q)(<1/2>a+<2>b)*"\  vcsn evaluate f  aaab 1/4
20130701
new format: efsm (and new tool: efstcompile)
The former output format ("fsm") is dropped, replaced by an adhoc "extended FSM" format: "efsm". The FSM format focuses only on the transitions, and lacks information about the labels (which are expected to be mapped to numbers), weights, whether it's an acceptor or transducer, etc.
The efsm format is designed to be simple to use with OpenFST: just run "efstcompile" instead of "fstcompile". As a matter fact, the new "efstcompile" tool is rather dumb, as it simply executes the "efsm" file.
$ vcsn ladybird O efsm 2 #! /bin/sh cat >transitions.fsm <<\EOFSM 0 2 \e 2 2 3 a 3 3 b 3 3 c 3 2 c 3 2 a EOFSM cat >isymbols.txt <<\EOFSM \e 0 a 1 b 2 c 3 EOFSM fstcompile acceptor keep_isymbols isymbols=isymbols.txt transitions.fsm $ vcsn ladybird O efsm 8  efstcompile  fstdeterminize  fstinfo \  grep '# of states' # of states 256
20130628
new binary: vcsn
To give a flavor of what TAFKit should be (a single tool instead of one per command), the new "vcsn" script bounces to the vcsn* tools. It does not support  as TAKKit 1 did.
$ vcsn areequivalent Ee '(a*b*)*' '(a+b)*' true
20130626
proper
Now removes states to which no transition arrive after spontaneous transitions removal.
Thompson
Only the concatenation yielded an automaton whose projection on Boolean weights was different from the Thompson of the projection of the rational expression on Boolean. This is now fixed.
isnormalized
New algorithm (static, dynamic, TAFKit).
20130625
identity, unit => one
Labels new define one() and is_one() instead of identity() and is_identity().
We now use LAO, "labels are one", instead of LAU, "labels are unit".
WeightSets now define one() and is_one() instead of unit() and is_unit().
20130621
shortest, enumerate
New algorithms (static, dynamic, TAFKit).
20130620
universal
Now accepts (LAL Boolean) rational expressions.
areequivalent
Now accepts (LAL Boolean) rational expressions. It cannot compare a rational expression with an automaton (or viceversa). This is a temporary defect which shell be addressed once TAFKit is properly developed.
$ vcsnareequivalent Ee '(a*b*)*' '(a+b)*' true $ vcsnareequivalent Ee '(a*b)*' '(a+b)*' false
dyn: overhaul
Consistency is enforced in dyn. In particular the very first dynamic/static bridge (which was not identified as such), vcsn::rat::abstract_ratexpset, is now part of dyn::.
dyn::weight now aggregates its WeightSet instead of a Context. More similar conversions were performed, and other are to come.
20130619
dot
The output now shows useless states (and their transitions) in gray.
20130618
areequivalent
New algorithm (static, dynamic, TAFKit). Currently works only for LAL Boolean automata.
$ vcsnstandard e 'a(ba)*' o a1.gv $ vcsnstandard e '(ab)*a' o a2.gv $ vcsnareequivalent f a1.gv a2.gv true
20130617
is_trim, is_useless, is_empty
New algorithms (static, dynamic, TAFKit).
accessible_states, coaccessible_states, useful_states
New algorithms, static only.
num_accessible_states, num_coaccessible_states, num_useful_states
New algorithms, static only. Available in the "info" display.
copy accepts a predicate
It is now possible to filter the states to keep. Either as a predicate, or a set of states. For instance:
template <typename Aut> Aut trim(const Aut& a) { return vcsn::copy(a, useful_states(a)); }
universal
New algorithm (static, dynamic, and TAFKit). Requires a LAL Boolean automaton.
$ vcsnuniversal f a1.gv digraph { vcsn_context = "lal_char(ab)_b" rankdir = LR node [shape = circle] { node [style = invis, shape = none, label = "", width = 0, height = 0] I0 F2 } { 0 1 2 } I0 > 0 0 > 0 [label = "a, b"] 0 > 1 [label = "a"] 1 > 0 [label = "a, b"] 1 > 1 [label = "a, b"] 1 > 2 [label = "b"] 2 > F2 2 > 0 [label = "a, b"] 2 > 1 [label = "a, b"] 2 > 2 [label = "a, b"] }
complement
New algorithm (static, dynamic, and TAFKit). Requires a complete deterministic LAL Boolean automaton.
$ vcsnstandard e '(?@lal_char(ab)_b)a' \  vcsndeterminize f \  vcsncomplement f \  vcsnauttoexp f \e+((b+(a.(a+b))).((a+b)*))
20130613
isdeterministic
It is conforming with the specifications: all the states must be deterministic, not just the reachable ones.
info output adjustments
It now displays whether the automaton "is complete" and the number of deterministic states if LAL, otherwise "N/A". It also reports "is deterministic: N/A" for nonLAL.
Invalid labels are rejected
Under some circumstances, some invalid transitions could be accepted by the Dot parser (e.g., "aa" or "" in LAL). This is fixed.
20130605
Support for entries is removed.
Member types, functions, and variables, about entries, have been removed. The services provided by entries in Vaucanson 1 are provided by LAU automata, so entries are not as useful in Vaucanson 2. And anyway, if needed, it should rather be a set of free standing functions.
20130527
Refactoring: epsremoval => proper
Epsremoval is renamed to Proper.
20130524
Syntax for rationalexpressions has changed!
Angular brackets are now used for weights. Instead of
$ vcsnstandard e '(?@lal_char(01)_z)(0+1)*1({2}1+{2}0)*' o binary.dot
run
$ vcsnstandard e '(?@lal_char(01)_z)(0+1)*1(<2>1+<2>0)*' o binary.dot
Braces are now used instead of (*...) for generalized quantifiers.
a{0} => \e a{1} => a a{2} => a.a a{5} => a.a.a.a.a a{0,1} => \e+a a{0,2} => \e+a+a.a a{0,3} => \e+a+a.a+a.a.a a{1,2} => a.(\e+a a{1,3} => a.(\e+a+a.a) a{2,5} => a.a.(\e+a+a.a+a.a.a) a{0,} => a* a{1,} => a.(a*) a{4,} => a.a.a.a.(a*)
20130523
info output
Now displays the number of spontaneous transitions (0 for LAL).
20130429
Digits as letters
Recently broken by accident, support for digits as letters is restored.
$ vcsnstandard e '(?@lal_char(01)_z)(0+1)*1({2}1+{2}0)*' o binary.dot $ vcsnevaluate f binary.dot '11111111' 255 $ vcsnevaluate f binary.dot '101010' 42
20130426
Dot parser
This parser is now stricter than it used to be: be sure to escape backslashes in input Dot files, i.e.,
0 > 2 [label = "\e"]
is now invalid, write
0 > 2 [label = "\\e"]
This change was made because Graphviz treats "" (and renders it) exactly like "e".
20130425
New algorithm: Thompson
Conversion from rational expression to automata. Requires lan or law. The handling of weights might be changed in the near future.
$ vcsnthompson Ee '(?@lan_char(abc)_z){2}(a+{3}b+c)*{5}' digraph { vcsn_context = "lan_char(abc)_z" rankdir = LR node [shape = circle] { node [style = invis, shape = none, label = "", width = 0, height = 0] I8 F9 } { 0 1 2 3 4 5 6 7 8 9 } I8 > 8 0 > 2 [label = "\\e"] 0 > 4 [label = "\\e"] 0 > 6 [label = "\\e"] 1 > 0 [label = "\\e"] 1 > 9 [label = "{5}\\e"] 2 > 3 [label = "a"] 3 > 1 [label = "\\e"] 4 > 5 [label = "{3}b"] 5 > 1 [label = "\\e"] 6 > 7 [label = "c"] 7 > 1 [label = "\\e"] 8 > 0 [label = "{2}\\e"] 8 > 9 [label = "{10}\\e"] 9 > F9 }
20130422
standard is the new name for standardof
The "of" is useless, inconsistent with the other algorithms, and with the TAFKit v1 name.
20130418
Evaluation is fixed
Several initializations were incorrect, expecting the zero to be 0 (which is not the case for zmin for instance). There might also be some speed up.
20130416
New output format: tikz
Layout is dumb, yet this is useful to prepare LaTeX documents.
20130412
New output format: info
This pseudo format displays facts about the automaton (number of states and so on) or rational expressions (number of nodes).
isepsacyclic
Can now be called on LAL automata, for consistency with isproper and isvalid.
20130411
Dot
The states are now numbered from 0.
Clang Compatibility
Clang++ (3.2 and 3.3) can now compile Vaucanson.
20130318
New LabelSet: nullableset
Initial support for "Labels are nullable".
$ cat lan.dot digraph lan { vcsn_context = "lan_char(a)_b" I1 > 1 2 > F2 1 > 2 [label = "a"] 1 > 2 [label = "\e"] } $ vcsncat Af lan.dot digraph { vcsn_context = "lan_char(a)_b" rankdir = LR node [shape = circle] { node [style = invis, shape = none, label = "", width = 0, height = 0] I1 F2 } { 1 2 } I1 > 1 1 > 2 [label = "\\e, a"] 2 > F2 } $ vcsnepsremoval Af lan.dot digraph { vcsn_context = "lan_char(a)_b" rankdir = LR node [shape = circle] { node [style = invis, shape = none, label = "", width = 0, height = 0] I1 F2 F1 } { 1 2 } I1 > 1 1 > F1 1 > 2 [label = "a"] 2 > F2 }
isproper
New dyn algorithm and tool (vcsnisproper).
20130308
determinize speedup
Determinization algorithm is five times faster.
Before:
$ time bin/vcsndebruijn 18  bin/vcsndeterminize Af  Onull real 0m13.049s user 0m12.773s sys 0m0.276s $ time bin/vcsndebruijn 20  bin/vcsndeterminize Af  Onull real 0m56.780s user 0m55.775s sys 0m0.988s
Now:
$ time bin/vcsndebruijn 18  bin/vcsndeterminize Af  Onull real 0m2.181s user 0m2.048s sys 0m0.132s $ time bin/vcsndebruijn 20  bin/vcsndeterminize Af  Onull real 0m8.653s user 0m8.177s sys 0m0.476s
20130226
hierarchy and API clean up
dyn:: was cleaned. Some headers were renamed:
vcsn/ctx/abstract_context.hh > vcsn/dyn/context.hh vcsn/algos/dyn.hh > vcsn/dyn/algos.hh vcsn/core/automaton.hh > vcsn/dyn/automaton.hh
dyn::make_automaton was introduced to hide implementation details.
20130221
LabelSet renamings
The name LetterSet, UnitSet, and WordSet were not compliant. They have been renamed as letterset, unitset, and wordset.
20130220
Generalized quantifier as syntactic sugar for rational expressions
The new "(* min, max)" quantifier (postfix, like "*") allows to specify "powers" of an expression. For instance:
({a}b)(*0) => \e ({a}b)(*1) => {a}b ({a}b)(*2) => {a}b.{a}b ({a}b)(*5) => {a}b.{a}b.{a}b.{a}b.{a}b ({a}b)(*0,1) => \e+{a}b ({a}b)(*0,2) => \e+{a}b+({a}b.{a}b) ({a}b)(*0,3) => \e+{a}b+({a}b.{a}b)+({a}b.{a}b.{a}b) ({a}b)(*1,2) => {a}b.(\e+{a}b) ({a}b)(*1,3) => {a}b.(\e+{a}b+({a}b.{a}b)) ({a}b)(*2,5) => {a}b.{a}b.(\e+{a}b+({a}b.{a}b)+({a}b.{a}b.{a}b)) ({a}b)(*0,) => ({a}b)* ({a}b)(*1,) => {a}b.(({a}b)*) ({a}b)(*4,) => {a}b.{a}b.{a}b.{a}b.(({a}b)*)
20130218
Comment in rational expressions
The (?#...) construct allows to embed comments in rational expressions. They are discarded. There is no means to include a closing parenthesis in this construct.
Context in rational expressions
The (?@...) allows a rational expression to "carry" its context. Contrast for instance the two following runs.
$ vcsncat C 'lal_char(xyz)_z' Ee '{42}x+{51}z' {42}x+{51}z $ vcsncat Ee '(?@lal_char(xyz)_z){42}x+{51}z' {42}x+{51}z
This will be used, eventually, so that TAFKitlike tools propagate the context in runs such as:
$ vcsncat Ee '(?@lal_char(xyz)_z){42}x+{51}z'  vcsntranspose Ef  1.15: invalid Boolean: 42
Currently it fails, as the "default" context is "lal_char(abc)_b".
New output format: fsm
An initial, and rough, support for Open FSM's format is provided. Currently there is no support at all for the weights.
$ vcsndebruijn O fsm 12  fstcompile  fstdeterminize  wc l 1216
New output format: null
The output is discarded. This is useful for benching.
20130214
New algorithms: isdeterministic and complete
isdeterministic takes an automaton as argument and exits with code status 0 if the given automaton is deterministic, 2 otherwise.
complete also takes an automaton as argument and make it complete. If the given automaton is already complete, then it is unchanged.
20130212
Overhaul of the LAU, LAL, LAW implementation
So far a context was a triple: <Kind, LabelSet, WeightSet>, where (for instance), Kind is labels_are_letters, LabelSet is set_alphabet<char_letters>, and WeightSet is zmin). This is troublesome on several regards, the clearest being that the LabelSet makes no sense for LAU.
Now contexts are pairs: <LabelSet, WeightSet>, where this time the LabelSet (same name as before, different concept) can be a instance of UnitSet for LAU, WordSet for LAW, or LetterSet for LAL. These structures, in turn, are parameterized by the effective set of generators to use: for instance, LetterSet<set_alphabet<char_letters>>. Of course UnitSet is not parameterized.
As a first visible consequence, the name of the LAU contexts has changed:
lau_char_br => lau_br lau_char(xyz)_ratexpset<lal_char(abc)_b> => lau_ratexpset<lal_char(abc)_b>
20130124
options renamed
The options to select the input and output format are renamed I and O (instead of i and o).
new option: o for output file
The vcsn* tools now support 'o FILE' to save the output in FILE.
20130122
product: strengthened preconditions
The product of automata requires LAL automata. The output alphabet is the intersection of the ones of the operands. This works as expected when the automata have disjoint alphabets.
20130118
dyn::product and vcsnproduct
They compute the product of automata.
20130114
vcsndeterminize and vcsnevaluate use the common command line options
These tools support C, g, etc. like the other tools. See "vcsn<tool> h".
context names are now complete
Context names used to describe the "static" structure only (e.g., lal_char_ratexpset<law_char_b>
). It now includes the "dynamic" part, currently only the list of generators (e.g., lal_char(abc)_ratexpset<law_char(xyz)_b>
).
This context strings are both printed and read by the various tools. For instance:
$ vcsnstandardof C 'law_char(xyz)_ratexpset<law_char(abc)_z>' \ e '{abc}xyz'  vcsnauttoexp f  {abc}xyz
Note that the second tool, vcsnauttoexp, found the context in its input, the standard automaton in Dot format.
20130113
dyn::ratexpset, dyn::context
These are now handled by shared pointer, consistently with dyn::automaton and dyn::ratexp.
Nasty memory management issues have been fixed.
vcsndebruijn
It now supports the same arguments as the other vcsn* tools. It also no longer requires 'a' and 'b' to be accepted letters, and it uses the whole alphabet. For instance "vcsndebruijn g 'xyz' 3" generates an automaton for "(x+y+z)x(x+y+z)^3".
dyn::ladybird, vcsnladybird
New dynamic algorithm, and new tool (which also supports the common command line options).
20130112
contexts are renamed
Contexts have both a name and an identifier. The name is used to display in a readable form the nature of the context, for instance in Dot output. The identifier is used for instance headers, or predefined contexts, and libraries.
So far names and identifiers are equal, but this will change.
As a first step, identifiers/names are now <Kind><LabelSet><WeightSet> instead of <LabelSet><WeightSet><Kind>. For instance:
char_b_lal => lal_char_b char_br_lal => lal_char_br char_zr_lal => lal_char_zr char_br_lau => lau_char_br char_br_law => law_char_br char_zr_law => law_char_zr
20130111
pprat is removed
It was designed for the test suite. The vcsn* tools are now sufficient for the test suite, and are exposed to the user.
vcsn*: option overhaul The different tools had already too many different calling conventions. They are now (quite) consistent.
vcsnauttoexp
Calls the default implementation of auttoexp.
$ vcsnstandardof Wz e '{2}(ab){3}'  vcsnauttoexp Af  ({2}a.b){3} $ vcsnstandardof Wz Lw e '{2}(ab){3}'  vcsnauttoexp Af  {6}ab
vcsnlift
It now also supports lifting rational expressions.
$ vcsnlift C char_b_lal Ee 'abc' {a.b.c}\e
20130110
dotty > dot
The name "dotty" was incorrect (as it denotes a program instead of the format). Therefore, every occurrence of "dotty" is now mapped to "dot".
dot
The Dot output (input and output) now uses ", " as a label separator, instead of " + ".
20121226
dyn: input/output
Routines: dyn::read_(automatonratexp)_(filestring) and dyn::print take the input format. Available input/output are:  "dotty".  "text".  "xml".
20121219
genset is replaced by labelset
Through out the code.
20121218
dyn: input
New routines: dyn::read_(automatonratexp)_(filestring).
dyn: output
New routines: dyn::print, for both automata and RatExps.
bin: new tools
vcsncat, vcsntranspose (both on RatExps only currently). vcsnstandardof. vcsnlift.
20121213
krat > rat
kratexp, kratexpset etc. are renamed as ratexp, ratexpset, etc.
labels are unit
labelsareempty/lae were mapped to labelsareunit/lau.
20121031
dyn::context
For consistency with dyn::automaton, vcsn::ctx::abstract_context is renamed vcsn::dyn::context. Eventually, we might turn it into a shared pointer too.
dyn::de_bruijn, bin/vcsndebruijn
New tools, useful for tests for instance.
$ vcsndebruijn char_b_lal 2 digraph { vcsn_context = "char_b_lal" vcsn_genset = "ab" rankdir = LR node [shape = circle] { node [style = invis, shape = none, label = "", width = 0, height = 0] I1 F4 } I1 > 1 1 > 1 [label = "a + b"] 1 > 2 [label = "a"] 2 > 3 [label = "a + b"] 3 > 4 [label = "a + b"] 4 > F4 }
20121022
dyn::parse_file and parse_string
They construct dyn::automaton's.
dyn::eval
For bad reasons, currently works only for char_b_lal
vcsndeterminize and vcsnevaluate
Two new shell commands to write tests.
20121012
pprat works with abstract algorithms
pprat now uses only abstract (aka, dynamic) algorithms! On OS X, it is now a 77KB program; it was 11MB before.
This schedules its death: either it will be replaced by a set of smaller grain commands (vcsndeterminize, vcsnstandardof, etc.) from which test cases will be easier to write, or it will be replaced by some early implementation of a TAFKitlike unified program (instead of one per context).
20121009
automata provide a vname
To dispatch algorithms such as dotty, we not only need to know the context type name, but also the automaton type name, as mutable_automaton
and transpose_automaton
are two different types for instance.
20121008
dotparser
Because it uses only algorithms made abstract (make_context
, make_automaton_editor
, and dotty
), the dot parser now works for any of the precompiled contexts!
20120926
add_entry
In addition to the add_entry method of mutable_automaton, there is now an add_entry
algorithm, which is templated by the automaton type. This algorithm provides an abstract interface to an unknown type of automaton.
20120924
renamings
For consistency, polynomials is renamed polynomialset.
mutable_automaton::add_entry and del_entry
The first of these new functions allows to add directly a list of transition between two states by passing the corresponding entry_t
(this is most useful when reading an automaton with entries, such as with the Dot parser). The second one removes every existing transition between two states.
20120801
labels are empty
Initial work on labelsareempty automata. See the unit/char_z_lae test. The labels are not displayed, but the "{...}" to denote the weights, are kept:
digraph { vcsn_context=char_z_lae vcsn_genset="" rankdir=LR node [shape=circle] { node [style=invis,shape=none,label="",width=0,height=0] I1 F2 } I1 > 1 2 > F2 [label="{10}"] 1 > 2 [label="{51}"] 2 > 3 [label="{3}"] 2 > 1 1 > 1 [label="{42}"] 1 > 3 }
In that case, the transitions do not store labels.
lift now returns a labelsareempty automaton/ratexp
Accordingly, pprat l (lift) now displays:
$ pprat Lw l 'ab+cd' digraph { vcsn_context=char_kratexpset<char_b_law>_lae vcsn_genset="abcd" rankdir=LR node [shape=circle] { node [style=invis,shape=none,label="",width=0,height=0] I1 F2 F3 } 1 > 2 [label="{ab}"] 2 > F2 I1 > 1 3 > F3 1 > 3 [label="{cd}"] }
20120731
dotparser
It is now possible to load an automaton from its dotty output. Actually, it is possible to write simpler automata. This is no yet fully generic: it works properly only for char_b_lal
.
The test program unit/parsedot gives access to it. When fed with the following input file:
digraph { vcsn_context=char_b_lal vcsn_genset="a" {1} > {2 3} > {4 5 6} [label=a] I > 1 {4 5 6} > F }
it produces an automaton, and dumps it using the dotty algorithm:
digraph { vcsn_context=char_b_lal vcsn_genset="a" rankdir=LR node [shape=circle] { node [style=invis,shape=none,label="",width=0,height=0] I1 F4 F5 F6 } 1 > 2 [label="a"] 1 > 3 [label="a"] 2 > 4 [label="a"] 2 > 5 [label="a"] 2 > 6 [label="a"] 3 > 4 [label="a"] 3 > 5 [label="a"] 3 > 6 [label="a"] I1 > 1 4 > F4 5 > F5 6 > F6 }
20120725
pprat uses L for labels instead of A
For consistency, since we now also use the name "labels" to denote the leaves of rational expressions (others that and ), A is renamed L.
Metadata are embedded in the Dot file
The pseudo name "A" which was used in every dotty output is no longer defined, as it is both optional and useless. The context name and the alphabet are also provided. For instance:
$ ./tests/unit/ladybirdb 2  sed 4q digraph { vcsn_context=char_b_lal vcsn_genset="abc" $ pprat s L z 'abc'  sed 4q digraph { vcsn_context=char_z_lal vcsn_genset="abcd" $ pprat s L zr A w 'abc'  sed 4q digraph { vcsn_context=char_kratexpset<char_z_law>_law vcsn_genset="abcd"
This is an experimentation, and the current choice is somewhat unsatisfactory. Instead of
vcsn_context=char_b_lal vcsn_genset="abc"
it is probably more sensible to use
vcsn_context="char_b_lal{abc}"
or maybe
vcsn_context="char{abc}_b_lal"
so that when weightsets depend for instance upon an alphabet, it can be specified too. Instead of
vcsn_context=char_kratexpset<char_z_law>_law vcsn_genset="abcd"
(which does not define the alphabet used for the weightset), one would expect:
vcsn_context=char_kratexpset<char_z_law{xyz}>_law{abcd}
or maybe
vcsn_context=char{abcd}_kratexpset<char{xyz}_z_law>_law
Also, the name "kratexpset" is of course open to discussion:
vcsn_context=char_rat<char_z_laz{xyw}>_law{abcd}
polynomials::conv
It is now possible to read back polynomials such as "a+b+{2}a".
static_assert
It is used more extensively to forbid meaningless calls, such as determinizing a law automaton.
20120713
Precompiled contexts
Several predefined contexts come with their own header (e.g., "ctx/char_b_lal"), and their own library (e.g., "libchar_b_lal"). This is provide for char_{b,z,zmin}_{lal,law}.
z_min renamed zmin
Consistently with Vaucanson 1.4.
20120710
transposition
Transposition on automaton is a read/write view: operations such as del_state
, add_transition
, etc. on a transposed automaton actually modify the wrapped automaton: set_final
calls set_initial
and so forth.
As an extreme example, the following snippet:
using context_t = vcsn::ctx::char_b; using automaton_t = vcsn::mutable_automaton<context_t>; using tr_automaton_t = vcsn::details::transpose_automaton<automaton_t>; context_t ctx{{'a', 'b'}}; auto ks = ctx.make_kratexpset(); auto aut = vcsn::standard_of<tr_automaton_t>(ctx, ks.conv("a+a+a+a"));
applies the standardof algorithm to a transposed mutable_automaton
. In other words,
aut.strip();
is the transposition of a standard automaton, except that it is a mutable_automaton
, not a transpose_automaton<mutable_automaton>
.
20120709
transposition
The "transpose" operation is implemented on words, weights, kratexps, and automata. pprat provides support to transpose on kratexps (option t):
pprat W zrr t {{{2}ab}cd}abcd => {{{2}ba}dc}dcba pprat W zrr t {ab}(abcd)*{cd} => ({dc}(dcba)*{ba})
and on (standard) automata (option T):
$ pprat A w W br s '{ab}(\e+a+b({abc}c{bcd})*){cd}' > forward.dot $ pprat A w W br T s '{ab}(\e+a+b({abc}c{bcd})*){cd}' > transpose.dot $ diff W80 t y forward.dot transpose.dot digraph A { digraph A { rankdir=LR rankdir=LR node [shape=circle] node [shape=circle] { { node [style=invis,shape=none,la node [style=invis,shape=none,la I1 I1 > I2 > I4 F1 F1 F2 < F4 < } } 1 > F1 [label="{(ab).(cd)}"]  I1 > 1 [label="{(dc).(ba)}"] I1 > 1  1 > F1 2 > F2 [label="{cd}"]  I2 > 2 [label="{dc}"] 1 > 2 [label="{ab}a"]  2 > 1 [label="{ba}a"] 4 > F4 [label="{cd}"]  I4 > 4 [label="{dc}"] 4 > 4 [label="{(abc).(bcd)}c"]  4 > 4 [label="{(dcb).(cba)}c"] 1 > 3 [label="{ab}b"]  3 > 1 [label="{ba}b"] 3 > 4 [label="{(abc).(bcd)}c"]  4 > 3 [label="{(dcb).(cba)}c"] } }
20120619
aut_to_exp
An initial version of aut_to_exp
is available. The new pprat option a provides an access to this algorithm: apply aut_to_exp
to the standard_of
an expression.
pprat a 'a*' => \e+(a.(a*)) pprat a '(a+b)c' => (a.c)+(b.c) pprat W z a '{2}({3}a+{5}b){7}c{11}' => (({6}a.{7}c)+({10}b.{7}c)){11}
Currently, the only "heuristic" implemented eliminates the states in order. There are probably possible improvements.
pprat a '(a+b)*'  wc c => 265
pprat: a and w are renamed A and W
new factory: de Bruijn
Builds automata for (a+b)a(a+b)^n.
20120618
standard_of is part of vcsn::
It used to be in vcsn::rat::.
20120614
kratexpset/abstract_kratexpset
kratexpset, i.e. the object that provides operation on kratexps (with specified Gen and Weight), used to derive from abstract_kratexp (which is "opaque": it does not know the precise type that is used underneath).
Now, from abstract_kratexp we derive a concrete_abstract_kratexpset which aggregates a kratexpset. This means that kratexpset no longer derives from a weaklytyped ancestor, and can provide simple and stronglytyped routines.
kratexpset/kratexp
For consistency with weightset/weight, genset/gen, kratexps (note the s) is renamed as kratexpset and std::shared_ptr<const rat::node> as kratexp.
lift
A new algorithm which creates, from an automaton, another one with the same states and transitions, but the new automaton features only spontaneous transitions, whose weights correspond to the labels (and weights) of the initial one.
For instance:
$ pprat aw wz sl '({2}\e+{3}a){4}' digraph A { rankdir=LR node [shape=circle] { node [style=invis,shape=none,label="",width=0,height=0] I1 F1 F2 } 1 > F1 [label="{8}"] I1 > 1 2 > F2 [label="{4}"] 1 > 2 [label="{3}a"] } digraph A { rankdir=LR node [shape=circle] { node [style=invis,shape=none,label="",width=0,height=0] I1 F1 F2 } 1 > F1 [label="{{8}\\e}"] I1 > 1 2 > F2 [label="{{4}\\e}"] 1 > 2 [label="{{3}a}\\e"] }
RatExps: fix is_unit
is_unit simply checked that the expression was , but did not check that weight itself was the unit.
VCSN_DEBUG
This variable allows to force the display of weights.
20120611
Now contexts are mutable, and hold (shared) pointers to (immutable) gensets and weightsets. This way, we can alter contexts (e.g., the ladybird factory can add the letters it needs in a new genset), yet there is good sharing, and identity can still be used to distinguish, for instance, two gensets defined equally.
It is also simpler to really expose them as pointers, so every "weightset().mul", etc. must be rewritten as "weightset()>mul".
20120608
Contexts
The Kind parameter is now part of the context. The same type of Kind is now use for both RatExps and automata. This results in many significant simplifications.
For instance, again, the test case for product:
Before:
using context_t = vcsn::ctx::char_z; context_t ctx { {'a', 'b', 'c'} }; using automaton_t = vcsn::mutable_automaton<context_t, vcsn::labels_are_letters>; automaton_t aut1(ctx);
After:
using context_t = vcsn::ctx::char_z; context_t ctx { {'a', 'b', 'c'} }; using automaton_t = vcsn::mutable_automaton<context_t>;
Or the source of pprat:
Before:
using atom_kind_t = typename Factory::kind_t; using label_kind_t = typename vcsn::label_kind<atom_kind_t>::type; using context_t = vcsn::ctx::context<typename Factory::genset_t, typename Factory::weightset_t, label_kind_t>; context_t ctx{factory.genset(), factory.weightset()}; using automaton_t = vcsn::mutable_automaton<context_t>; auto aut = vcsn::rat::standard_of<automaton_t>(ctx, e);
After:
using context_t = typename Factory::context_t; using automaton_t = vcsn::mutable_automaton<context_t>; auto aut = vcsn::rat::standard_of<automaton_t>(factory.context(), e);
20120605
Contexts
"Contexts" were introduced to factor two aspects that are required through out the library: the GenSet type (i.e., the nature of the generators), and the WeightSet type (i.e., the nature of the weights). Not only do contexts define these types, they must also be instantiated so that "runtime" details be known: for instance the set of generators is dynamic (what are the allowed letters), and on occasion the weightset also needs runtime information (e.g., when RatExp are parameterized by RatExp, what is the alphabet of the latter ones?).
As an example of the changes on the user side, consider the product testcase.
Before:
typedef vcsn::set_alphabet<vcsn::char_letters> alpha_t; typedef vcsn::mutable_automaton<alpha_t, vcsn::z, vcsn::labels_are_letters> automaton_t; vcsn::z z; alpha_t alpha{'a', 'b', 'c'}; automaton_t aut1(alpha, z);
After:
using context_t = vcsn::ctx::char_z; context_t ctx { {'a', 'b', 'c'} }; using automaton_t = vcsn::mutable_automaton<context_t, vcsn::labels_are_letters>; automaton_t aut1(ctx);
20120530
RatExp: atoms are words
Expressions such as "(ab)(ab)" used to be equivalent to "(abab)" (a single fourletter atom). Now:
pprat aw '(ab)(ab)' => (ab).(ab) pprat aw 'abab' => abab pprat aw 'ab.ab' => (ab).(ab) pprat aw 'ab(ab)abc*' => (ab).(ab).(ab).(c*)
20120528
New algorithm: eval, evaluates a word over an (weighted) automaton
Defined in vcsn/algos/eval.hh as vcsn::eval.
New algorithm: determinize, Boolean automaton determinization
Defined in vcsn/algos/determinize.hh as vcsn::determinize.
20120525
RatExp: changes in the display
Fixed the output of "atoms are words" expressions. For instance "(ab)" used to be displayed as "ab" (which is wrong as it is parsed as "a(b)"). It is now properly displayed as "(ab)".
RatExp: slight changes in the grammar
A star is now valid after a weight:
$ pprat w z '{2}ab{3}*' ({2}(a.b){3})*
20120511
dotty: define initial/final states first
In order to improve readability, instead of
digraph A { rankdir=LR node [shape=circle]; F1 [style=invis,shape=none,label="",width=0,height=0] 1 > F1 [label="{a.a.((d.d)*)}"] 3 > 2 [label="{(d.d)*}b"] I1 [style=invis,shape=none,label="",width=0,height=0] I1 > 1 1 > 2 [label="{a.a.((d.d)*)}b"] F3 [style=invis,shape=none,label="",width=0,height=0] 3 > F3 [label="{(d.d)*}"] 2 > 3 [label="b"] }
we now produce
digraph A { rankdir=LR node [shape=circle] { node [style=invis,shape=none,label="",width=0,height=0] I1 F1 F3 } 1 > F1 [label="{a.a.((d.d)*)}"] 3 > 2 [label="{(d.d)*}b"] I1 > 1 1 > 2 [label="{a.a.((d.d)*)}b"] 3 > F3 [label="{(d.d)*}"] 2 > 3 [label="b"] }
20120510
RatExp: support for the kind of atoms
As a major overhaul, the rational expressions (vcsn::rat::node) are now parameterized by Atom, which denotes the atom value. The kratexps structure is now parameterized by the Kind, from which it is deduced, from the GenSet parameter, whether we should use word_t or letter_t atoms.
pprat: an option a
To provide useraccess to these feature, pprat now supports an option a, which accepts "letters" or "words" as argument, with obvious meaning. For instance:
pprat a letters 'abc' => a.b.c pprat a letters 'abc.abc' => a.b.c.a.b.c pprat w br al '{aa}bb{c}dd{a}' => ({a.a}(b.b).{c}(d.d)){a} pprat a words 'abc' => abc pprat a words 'abc.abc' => abc.abc pprat w br aw '{aa}bb{c}dd{a}' => ({aa}bb.{c}dd){a}
Of course, this also works with the "standardof" option:
$ pprat w br al '{aa}({dd}\e+bb)*' {a.a}(({d.d}\e+(b.b))*) $ pprat s w br al '{aa}({dd}\e+bb)*' digraph A { rankdir=LR node [shape=circle]; F1 [style=invis,shape=none,label="",width=0,height=0] 1 > F1 [label="{a.a.((d.d)*)}"] 3 > 2 [label="{(d.d)*}b"] I1 [style=invis,shape=none,label="",width=0,height=0] I1 > 1 1 > 2 [label="{a.a.((d.d)*)}b"] F3 [style=invis,shape=none,label="",width=0,height=0] 3 > F3 [label="{(d.d)*}"] 2 > 3 [label="b"] }
versus:
$ pprat w br aw '{aa}({dd}\e+bb)*' {aa}(({dd}\e+bb)*) $ pprat s w br aw '{aa}({dd}\e+bb)*' digraph A { rankdir=LR node [shape=circle]; F1 [style=invis,shape=none,label="",width=0,height=0] 1 > F1 [label="{aa.(dd*)}"] 2 > 2 [label="{dd*}bb"] F2 [style=invis,shape=none,label="",width=0,height=0] 2 > F2 [label="{dd*}"] 1 > 2 [label="{aa.(dd*)}bb"] I1 [style=invis,shape=none,label="",width=0,height=0] I1 > 1 }
20120507
RatExp: in some case the weights could be lost
"Associativity" was applied too eagerly, which would result in loss of some weights. E.g. {a}bb{c}dd resulted in b.b.d.d, not it evaluates to {a}(b.b).{c}(d.d).
20120503
RatExp: improved prettyprinting
The outermost pair of parentheses is removed if useless. For instance:
(a.b) => a.b (a+b+c) => a+b+c (a*) => a*
But in the following examples they are kept.
{3}(a.b){4} {3}(a*) (a+b){4}
standardof: star is fixed
Standardof seems to be correct.
20120425
Expressions overhaul
They are immutable: we no longer make side effects on expressions. They are shared_ptr, no longer plain pointers. They can be used like the other values, by value.
20120419
standardof is fully implemented
Support for star was implemented, and checked for B and Z. For implementation reasons, one cannot yet use rational expressions as weights.
20120418
mutable_automata::mul_weight
RatExp::head and tail
dotty
In order to improve the readability of its output, it no longer "defines" the reachable states. See the following diff:
digraph A { rankdir=LR node [shape=circle];  1  2  3  4 I1 [style=invis,shape=none,label="",width=0,height=0] I1 > 1 [label="{6}"] F1 [style=invis,shape=none,label="",width=0,height=0] 1 > F1 1 > 2 [label="a"] 1 > 3 [label="a"] 2 > 4 [label="{3}b"] F4 [style=invis,shape=none,label="",width=0,height=0] 4 > F4 4 > 3 [label="a"] }
standardof: many fixes in the handling of the weights
An expression such as {12}\e
used to leave the weight in the initial transition; it is now on the final transition. More generally the initial transition always has unit as weight.
The product and sum of expressions now handle the left and right weights.
Accepting initial states in expressions such as "+a" are no longer lost.
20120411
Many renamings
alphabet_t/alphabet() > genset_t/genset(), etc. factory > abstract_kratexp. factory_ > kratexp. initials() > initial_transitions(), etc. invalid_state > null_state, etc. nb_state() > num_states(), etc. polynomial > polynomials, etc.
20120409
product
An implementation of the product of two automata is available.
20120407
z_min
An example of tropical semiring, to test show_unit().
20120405
char_letters::special()
This method return a special, reserved character, that is used to label initial and final transitions. This character is not part of the alphabet and is never output.
20120404
standardof
Initial work on "+".
mutable_automata are implemented using a pre() and post() states
What is missing is the correct '$' letter on the initial and final transitions. The current value is the default value for label_t. The previous interface has been preserved (but maybe we should clean it) except for one change: initial() and final() have been changed to return a pseudo container of transitions. These transitions give us both the weight and the initial/final state. The following methods are new: pre(), post() returns the preinitial and postfinal state. all_states() returns all states, including pre() and post() all_transitions() returns all transitions, including initial and final transitions all_entries() likewise for entries all_out(s), all_in(s) likewise for outgoing and ingoing transitions The methods get_initial_weight(s) and get_final_weight(s) are slower now, because they need to locate the corresponding initial/final transition. For the same reason, is_initial(), is_final() are also slower.
20120403
standardof
Initial version of standardof is implemented. Can be tested with pprat's new option s:
$ pprat wz s '{123}a' digraph A { rankdir=LR node [shape=circle]; 1 I1 [style=invis,shape=none,label="",width=0,height=0] I1 > 1 2 F2 [style=invis,shape=none,label="",width=0,height=0] 2 > F2 1 > 2 [label="{123}a"] }
mutable_automaton uses unsigned for state_t and transition_t.
This allows to store states in a std::vector<stored_state_t>. Likewise for transitions. Erased elements are marked (so they are skipped over during iteration), and added to a free store to be reused later.
mutable_automaton does not store any weight when WeightSet == b.
mutable_automaton has a readonly entry interface
entries() is a pseudo container that filters transitions() to see each (src,dst) pair at most once. entry_at(src, dst) and entry_at(t) return a polynomial describing the entry between (src, dst) or (src_of(t), dst_of(t)). entryset() returns the WeightSet that can be used to manipulate these polynomials.
make checkrat, make checkunit
There is a check target for each subdirectory of tests/.
20120402
Alphabets are checked
pprat is hardcoded to use a, b, c, d for all the alphabets (including for inner rational expressions):
$ pprat w b e 'y' 1.1: invalid word: y: invalid letter: y
Weights are checked
As follows:
$ pprat w b e '{12}a' 1.15: invalid Boolean: 12
Unfortunately the locations are bad currently for complex weights:
$ pprat w zr e '{x}a' 1.14: 1.1: invalid word: x: invalid letter: x
To be fixed.
20120330
G++ 4.7 is required
We use constructs that are not supported by 4.6 (e.g., constructor delegation).
zrr
As a demonstration that rational expressions can be weights of rational expressions, pprat supports 'w zrr' (Rat<Rat<Z>>):
$ pprat w zr e '{{{2}{3}a}u}x{{{4}{5}\e}\e}' {{{120}a}u}x