def _latex_(self, **options):
r"""
Returns the crystal graph as a latex string. This can be exported
to a file with self.latex_file('filename').
EXAMPLES::
sage: T = CrystalOfTableaux(['A',2],shape=[1])
sage: T._latex_() #optional - dot2tex
...
sage: view(T, pdflatex = True, tightpage = True) #optional - dot2tex graphviz
One can for example also color the edges using the following options::
sage: T = CrystalOfTableaux(['A',2],shape=[1])
sage: T._latex_(color_by_label = {0:"black", 1:"red", 2:"blue"}) #optional - dot2tex graphviz
...
"""
if not have_dot2tex():
print "dot2tex not available. Install after running \'sage -sh\'"
return
G=self.digraph()
G.set_latex_options(format="dot2tex", edge_labels = True,
edge_options = lambda (u,v,label): ({"backward":label ==0}), **options)
return G._latex_()
def digraph(self, subset=None, index_set=None):
r"""
Return the :class:`DiGraph` associated to ``self``.
INPUT:
- ``subset`` -- (optional) a subset of vertices for
which the digraph should be constructed
- ``index_set`` -- (optional) the index set to draw arrows
.. SEEALSO::
:meth:`sage.categories.crystals.Crystals.ParentMethods.digraph`
EXAMPLES::
sage: C = crystals.KirillovReshetikhin(['D',4,1], 2, 1)
sage: G = C.digraph()
sage: G.latex_options() # optional - dot2tex
LaTeX options for Digraph on 29 vertices:
{...'edge_options': <function <lambda> at 0x...>,...}
sage: view(G, tightpage=True) # optional - dot2tex graphviz, not tested (opens external window)
"""
G = Crystals().parent_class.digraph(self, subset, index_set)
if have_dot2tex():
f = lambda u_v_label: ({"backward": u_v_label[2] == 0})
G.set_latex_options(edge_options=f)
return G
def digraph(self, subset=None, index_set=None):
r"""
Return the :class:`DiGraph` associated to ``self``.
INPUT:
- ``subset`` -- (optional) a subset of vertices for
which the digraph should be constructed
- ``index_set`` -- (optional) the index set to draw arrows
.. SEEALSO::
:meth:`sage.categories.crystals.Crystals.ParentMethods.digraph`
EXAMPLES::
sage: C = crystals.KirillovReshetikhin(['D',4,1], 2, 1)
sage: G = C.digraph()
sage: G.latex_options() # optional - dot2tex
LaTeX options for Digraph on 29 vertices:
{...'edge_options': <function ... at ...>...}
sage: view(G, tightpage=True) # optional - dot2tex graphviz, not tested (opens external window)
"""
G = Crystals().parent_class.digraph(self, subset, index_set)
if have_dot2tex():
f = lambda u_v_label: ({"backward": u_v_label[2] == 0})
G.set_latex_options(edge_options=f)
return G
def _latex_(self, **options):
r"""
Returns the crystal graph as a latex string. This can be exported
to a file with self.latex_file('filename').
EXAMPLES::
sage: T = CrystalOfTableaux(['A',2],shape=[1])
sage: T._latex_() #optional - dot2tex
...
sage: view(T, pdflatex = True, tightpage = True) #optional - dot2tex graphviz
One can for example also color the edges using the following options::
sage: T = CrystalOfTableaux(['A',2],shape=[1])
sage: T._latex_(color_by_label = {0:"black", 1:"red", 2:"blue"}) #optional - dot2tex graphviz
...
"""
if not have_dot2tex():
print "dot2tex not available. Install after running \'sage -sh\'"
return
G=self.digraph()
G.set_latex_options(format="dot2tex", edge_labels = True,
edge_options = lambda (u,v,label): ({"backward":label ==0}), **options)
return G._latex_()
def digraph(self):
"""
Returns the DiGraph associated to self.
EXAMPLES::
sage: C = Crystals().example(5)
sage: C.digraph()
Digraph on 6 vertices
The edges of the crystal graph are by default colored using blue for edge 1, red for edge 2,
and green for edge 3::
sage: C = Crystals().example(3)
sage: G = C.digraph()
sage: view(G, pdflatex=True, tightpage=True) #optional - dot2tex graphviz
One may also overwrite the colors::
sage: C = Crystals().example(3)
sage: G = C.digraph()
sage: G.set_latex_options(color_by_label = {1:"red", 2:"purple", 3:"blue"})
sage: view(G, pdflatex=True, tightpage=True) #optional - dot2tex graphviz
Or one may add colors to yet unspecified edges::
sage: C = Crystals().example(4)
sage: G = C.digraph()
sage: C.cartan_type()._index_set_coloring[4]="purple"
sage: view(G, pdflatex=True, tightpage=True) #optional - dot2tex graphviz
TODO: add more tests
"""
from sage.graphs.all import DiGraph
d = {}
for x in self:
d[x] = {}
for i in self.index_set():
child = x.f(i)
if child is None:
continue
d[x][child]=i
G = DiGraph(d)
if have_dot2tex():
G.set_latex_options(format="dot2tex", edge_labels = True, color_by_label = self.cartan_type()._index_set_coloring,
edge_options = lambda (u,v,label): ({"backward":label ==0}))
return G
def digraph(self):
"""
Returns the DiGraph associated to self.
EXAMPLES::
sage: C = Crystals().example(5)
sage: C.digraph()
Digraph on 6 vertices
The edges of the crystal graph are by default colored using blue for edge 1, red for edge 2,
and green for edge 3::
sage: C = Crystals().example(3)
sage: G = C.digraph()
sage: view(G, pdflatex=True, tightpage=True) #optional - dot2tex graphviz
One may also overwrite the colors::
sage: C = Crystals().example(3)
sage: G = C.digraph()
sage: G.set_latex_options(color_by_label = {1:"red", 2:"purple", 3:"blue"})
sage: view(G, pdflatex=True, tightpage=True) #optional - dot2tex graphviz
Or one may add colors to yet unspecified edges::
sage: C = Crystals().example(4)
sage: G = C.digraph()
sage: C.cartan_type()._index_set_coloring[4]="purple"
sage: view(G, pdflatex=True, tightpage=True) #optional - dot2tex graphviz
TODO: add more tests
"""
from sage.graphs.all import DiGraph
d = {}
for x in self:
d[x] = {}
for i in self.index_set():
child = x.f(i)
if child is None:
continue
d[x][child]=i
G = DiGraph(d)
if have_dot2tex():
G.set_latex_options(format="dot2tex", edge_labels = True, color_by_label = self.cartan_type()._index_set_coloring,
edge_options = lambda (u,v,label): ({"backward":label ==0}))
return G
def digraph(self, subset=None, index_set=None):
"""
Return the DiGraph associated with ``self``. See
:meth:`~sage.categories.crystals.ParentMethods.digraph()` for more
information.
EXAMPLES::
sage: A = crystals.KirillovReshetikhin(['A',2,1], 2, 2).affinization()
sage: S = A.subcrystal(max_depth=3)
sage: G = A.digraph(subset=S)
"""
G = super(AffinizationOfCrystal, self).digraph(subset, index_set)
from sage.graphs.dot2tex_utils import have_dot2tex
if have_dot2tex():
G.set_latex_options(edge_options = lambda (u,v,label): ({}))
return G
def digraph(self, subset=None, index_set=None):
"""
Return the DiGraph associated with ``self``. See
:meth:`~sage.categories.crystals.ParentMethods.digraph()` for more
information.
EXAMPLES::
sage: A = crystals.KirillovReshetikhin(['A',2,1], 2, 2).affinization()
sage: S = A.subcrystal(max_depth=3)
sage: G = A.digraph(subset=S)
"""
G = super(AffinizationOfCrystal, self).digraph(subset, index_set)
from sage.graphs.dot2tex_utils import have_dot2tex
if have_dot2tex():
G.set_latex_options(edge_options=lambda (u, v, label): ({}))
return G
def _latex_(self, **options):
r"""
Return a latex representation of this Kleber tree.
EXAMPLES::
sage: KT = KleberTree(['D', 3], [[2,1], [2,1]])
sage: KT._latex_() #optional - dot2tex
...
sage: view(KT, pdflatex=True, tightpage=True) #optional - dot2tex graphviz
"""
if not have_dot2tex():
print "dot2tex not available. Install after running \'sage -sh\'"
return
G = self.digraph()
G.set_latex_options(format="dot2tex", edge_labels=True, **options)
return G._latex_()
def _latex_(self, **options):
r"""
Return a latex representation of this Kleber tree.
EXAMPLES::
sage: KT = KleberTree(['D', 3], [[2,1], [2,1]])
sage: KT._latex_() #optional - dot2tex
...
sage: view(KT, pdflatex=True, tightpage=True) #optional - dot2tex graphviz
"""
if not have_dot2tex():
print "dot2tex not available. Install after running \'sage -sh\'"
return
G = self.digraph()
G.set_latex_options(format="dot2tex", edge_labels=True, **options)
return G._latex_()
def digraph(self):
r"""
Return a DiGraph representation of this Kleber tree.
EXAMPLES::
sage: KT = KleberTree(['D', 4], [[2, 2]])
sage: KT.digraph()
Digraph on 3 vertices
"""
d = {}
for x in self:
d[x] = {}
if x.parent_node is None:
continue
d[x][x.parent_node] = tuple(x.up_root.to_vector())
G = DiGraph(d)
if have_dot2tex():
G.set_latex_options(format="dot2tex", edge_labels=True)
# edge_options = lambda (u,v,label): ({"backward":label ==0}))
return G
def digraph(self):
r"""
Return a DiGraph representation of this Kleber tree.
EXAMPLES::
sage: KT = KleberTree(['D', 4], [[2, 2]])
sage: KT.digraph()
Digraph on 3 vertices
"""
d = {}
for x in self:
d[x] = {}
if x.parent_node is None:
continue
d[x][x.parent_node] = tuple(x.up_root.to_vector())
G = DiGraph(d)
if have_dot2tex():
G.set_latex_options(format="dot2tex", edge_labels=True)
# edge_options = lambda (u,v,label): ({"backward":label ==0}))
return G
def _latex_(self, **options):
r"""
Returns the crystal graph as a latex string. This can be exported
to a file with self.latex_file('filename').
EXAMPLES::
sage: T = crystals.Tableaux(['A',2],shape=[1])
sage: T._latex_() #optional - dot2tex
'...tikzpicture...'
sage: view(T, pdflatex = True, tightpage = True) #optional - dot2tex graphviz
One can for example also color the edges using the following options::
sage: T = crystals.Tableaux(['A',2],shape=[1])
sage: T._latex_(color_by_label = {0:"black", 1:"red", 2:"blue"}) #optional - dot2tex graphviz
'...tikzpicture...'
"""
if not have_dot2tex():
print "dot2tex not available. Install after running \'sage -sh\'"
return
G=self.digraph()
G.set_latex_options(**options)
return G._latex_()
def digraph(self, subset=None, index_set=None, depth=None):
"""
Return the DiGraph associated to ``self``.
INPUT:
- ``subset`` -- (optional) a subset of vertices for
which the digraph should be constructed
- ``index_set`` -- (optional) the index set to draw arrows
- ``depth`` -- the depth to draw; optional only for finite crystals
EXAMPLES::
sage: T = crystals.Tableaux(['A',2], shape=[2,1])
sage: T.digraph()
Digraph on 8 vertices
sage: S = T.subcrystal(max_depth=2)
sage: len(S)
5
sage: G = T.digraph(subset=list(S))
sage: G.is_isomorphic(T.digraph(depth=2), edge_labels=True)
True
TESTS:
The following example demonstrates the speed improvement.
The speedup in non-affine types is small however::
sage: depth = 5
sage: C = crystals.AlcovePaths(['A',2,1], [1,1,0])
sage: general_digraph = Crystals().parent_class.digraph
sage: S = C.subcrystal(max_depth=depth, direction='lower')
sage: %timeit C.digraph(depth=depth) # not tested
10 loops, best of 3: 48.9 ms per loop
sage: %timeit general_digraph(C, subset=S) # not tested
10 loops, best of 3: 96.5 ms per loop
sage: G1 = C.digraph(depth=depth)
sage: G2 = general_digraph(C, subset=S)
sage: G1.is_isomorphic(G2, edge_labels=True)
True
"""
if subset is not None:
return Crystals().parent_class.digraph(self, subset, index_set)
if self not in Crystals().Finite() and depth is None:
raise NotImplementedError("crystals not known to be finite must"
" specify either the subset or depth")
from sage.graphs.all import DiGraph
if index_set is None:
index_set = self.index_set()
rank = 0
d = {g: {} for g in self.module_generators}
visited = set(d.keys())
while depth is None or rank < depth:
recently_visited = set()
for x in visited:
d.setdefault(x, {}) # does nothing if there's a default
for i in index_set:
xfi = x.f(i)
if xfi is not None:
d[x][xfi] = i
recently_visited.add(xfi)
if not recently_visited: # No new nodes, nothing more to do
break
rank += 1
visited = recently_visited
G = DiGraph(d)
if have_dot2tex():
G.set_latex_options(format="dot2tex",
edge_labels=True,
color_by_label=self.cartan_type()._index_set_coloring)
return G
def run(self, verbose=False, build_graph=False):
"""
Run the bijection from rigged configurations to tensor product of KR
tableaux.
INPUT:
- ``verbose`` -- (default: ``False``) display each step in the
bijection
- ``build_graph`` -- (default: ``False``) build the graph of each
step of the bijection
EXAMPLES::
sage: RC = RiggedConfigurations(['A', 4, 1], [[2, 1]])
sage: x = RC(partition_list=[[1],[1],[1],[1]])
sage: from sage.combinat.rigged_configurations.bij_type_A import RCToKRTBijectionTypeA
sage: RCToKRTBijectionTypeA(x).run()
[[2], [5]]
sage: bij = RCToKRTBijectionTypeA(x)
sage: bij.run(build_graph=True)
[[2], [5]]
sage: bij._graph
Digraph on 3 vertices
"""
from sage.combinat.crystals.letters import CrystalOfLetters
letters = CrystalOfLetters(
self.rigged_con.parent()._cartan_type.classical())
# This is technically bad, but because the first thing we do is append
# an empty list to ret_crystal_path, we correct this. We do it this
# way so that we do not have to remove an empty list after the
# bijection has been performed.
ret_crystal_path = []
for dim in self.rigged_con.parent().dims:
ret_crystal_path.append([])
# Iterate over each column
for dummy_var in range(dim[1]):
# Split off a new column if necessary
if self.cur_dims[0][1] > 1:
if verbose:
print("====================")
print(
repr(self.rigged_con.parent()(
*self.cur_partitions,
use_vacancy_numbers=True)))
print("--------------------")
print(ret_crystal_path)
print("--------------------\n")
print("Applying column split")
self.cur_dims[0][1] -= 1
self.cur_dims.insert(0, [dim[0], 1])
# Perform the corresponding splitting map on rigged configurations
# All it does is update the vacancy numbers on the RC side
for a in range(self.n):
self._update_vacancy_numbers(a)
if build_graph:
y = self.rigged_con.parent()(
*[x._clone() for x in self.cur_partitions],
use_vacancy_numbers=True)
self._graph.append(
[self._graph[-1][1], (y, len(self._graph)), 'ls'])
while self.cur_dims[0][0] > 0:
if verbose:
print("====================")
print(
repr(self.rigged_con.parent()(
*self.cur_partitions,
use_vacancy_numbers=True)))
print("--------------------")
print(ret_crystal_path)
print("--------------------\n")
self.cur_dims[0][0] -= 1 # This takes care of the indexing
b = self.next_state(self.cur_dims[0][0])
# Make sure we have a crystal letter
ret_crystal_path[-1].append(letters(b)) # Append the rank
if build_graph:
y = self.rigged_con.parent()(
*[x._clone() for x in self.cur_partitions],
use_vacancy_numbers=True)
self._graph.append([
self._graph[-1][1], (y, len(self._graph)),
letters(b)
])
self.cur_dims.pop(0) # Pop off the leading column
if build_graph:
self._graph.pop(0) # Remove the dummy at the start
from sage.graphs.digraph import DiGraph
from sage.graphs.dot2tex_utils import have_dot2tex
self._graph = DiGraph(self._graph)
if have_dot2tex():
self._graph.set_latex_options(format="dot2tex",
edge_labels=True)
# Basic check to make sure we end with the empty configuration
#tot_len = sum([len(rp) for rp in self.cur_partitions])
#if tot_len != 0:
# print "Invalid bijection end for:"
# print self.rigged_con
# print "-----------------------"
# print self.cur_partitions
# raise ValueError("Invalid bijection end")
return self.KRT(pathlist=ret_crystal_path)
def digraph(self, subset=None, index_set=None, depth=None):
"""
Return the DiGraph associated to ``self``.
INPUT:
- ``subset`` -- (optional) a subset of vertices for
which the digraph should be constructed
- ``index_set`` -- (optional) the index set to draw arrows
- ``depth`` -- the depth to draw; optional only for finite crystals
EXAMPLES::
sage: T = crystals.Tableaux(['A',2], shape=[2,1])
sage: T.digraph()
Digraph on 8 vertices
sage: S = T.subcrystal(max_depth=2)
sage: len(S)
5
sage: G = T.digraph(subset=list(S))
sage: G.is_isomorphic(T.digraph(depth=2), edge_labels=True)
True
TESTS:
The following example demonstrates the speed improvement.
The speedup in non-affine types is small however::
sage: depth = 5
sage: C = crystals.AlcovePaths(['A',2,1], [1,1,0])
sage: general_digraph = Crystals().parent_class.digraph
sage: S = C.subcrystal(max_depth=depth, direction='lower')
sage: %timeit C.digraph(depth=depth) # not tested
10 loops, best of 3: 48.9 ms per loop
sage: %timeit general_digraph(C, subset=S) # not tested
10 loops, best of 3: 96.5 ms per loop
sage: G1 = C.digraph(depth=depth)
sage: G2 = general_digraph(C, subset=S)
sage: G1.is_isomorphic(G2, edge_labels=True)
True
"""
if subset is not None:
return Crystals().parent_class.digraph(self, subset, index_set)
if self not in Crystals().Finite() and depth is None:
raise NotImplementedError(
"crystals not known to be finite must"
" specify either the subset or depth")
from sage.graphs.all import DiGraph
if index_set is None:
index_set = self.index_set()
rank = 0
d = {g: {} for g in self.module_generators}
visited = set(d.keys())
while depth is None or rank < depth:
recently_visited = set()
for x in visited:
d.setdefault(x, {}) # does nothing if there's a default
for i in index_set:
xfi = x.f(i)
if xfi is not None:
d[x][xfi] = i
recently_visited.add(xfi)
if not recently_visited: # No new nodes, nothing more to do
break
rank += 1
visited = recently_visited
G = DiGraph(d)
if have_dot2tex():
G.set_latex_options(
format="dot2tex",
edge_labels=True,
color_by_label=self.cartan_type()._index_set_coloring)
return G
def dual_equivalence_graph(self, X=None, index_set=None, directed=True):
r"""
Return the dual equivalence graph indexed by ``index_set``
on the subset ``X`` of ``self``.
Let `b \in B` be an element of weight `0`, so `\varepsilon_j(b)
= \varphi_j(b)` for all `j \in I`, where `I` is the indexing
set. We say `b'` is an `i`-elementary dual equivalence
transformation of `b` (where `i \in I`) if
* `\varepsilon_i(b) = 1` and `\varepsilon_{i-1}(b) = 0`, and
* `b' = f_{i-1} f_i e_{i-1} e_i b`.
We can do the inverse procedure by interchanging `i` and `i-1`
above.
.. NOTE::
If the index set is not an ordered interval, we let
`i - 1` mean the index appearing before `i` in `I`.
This definition comes from [Assaf08]_ Section 4 (where our
`\varphi_j(b)` and `\varepsilon_j(b)` are denoted by
`\epsilon(b, j)` and `-\delta(b, j)`, respectively).
The dual equivalence graph of `B` is defined to be the
colored graph whose vertices are the elements of `B` of
weight `0`, and whose edges of color `i` (for `i \in I`)
connect pairs `\{ b, b' \}` such that `b'` is an
`i`-elementary dual equivalence transformation of `b`.
.. NOTE::
This dual equivalence graph is a generalization of
`\mathcal{G}\left(\mathcal{X}\right)` in [Assaf08]_
Section 4 except we do not require
`\varepsilon_i(b) = 0, 1` for all `i`.
This definition can be generalized by choosing a subset `X`
of the set of all vertices of `B` of weight `0`, and
restricting the dual equivalence graph to the vertex set
`X`.
INPUT:
- ``X`` -- (optional) the vertex set `X` (default:
the whole set of vertices of ``self`` of weight `0`)
- ``index_set`` -- (optional) the index set `I`
(default: the whole index set of ``self``); this has
to be a subset of the index set of ``self`` (as a list
or tuple)
- ``directed`` -- (default: ``True``) whether to have the
dual equivalence graph be directed, where the head of
an edge `b - b'` is `b` and the tail is
`b' = f_{i-1} f_i e_{i-1} e_i b`)
.. SEEALSO::
:meth:`sage.combinat.partition.Partition.dual_equivalence_graph`
REFERENCES:
.. [Assaf08] Sami Assaf. *A combinatorial realization of Schur-Weyl
duality via crystal graphs and dual equivalence graphs*.
FPSAC 2008, 141-152, Discrete Math. Theor. Comput. Sci. Proc.,
AJ, Assoc. Discrete Math. Theor. Comput. Sci., (2008).
:arxiv:`0804.1587v1`
EXAMPLES::
sage: T = crystals.Tableaux(['A',3], shape=[2,2])
sage: G = T.dual_equivalence_graph()
sage: sorted(G.edges())
[([[1, 3], [2, 4]], [[1, 2], [3, 4]], 2),
([[1, 2], [3, 4]], [[1, 3], [2, 4]], 3)]
sage: T = crystals.Tableaux(['A',4], shape=[3,2])
sage: G = T.dual_equivalence_graph()
sage: sorted(G.edges())
[([[1, 3, 5], [2, 4]], [[1, 3, 4], [2, 5]], 4),
([[1, 3, 5], [2, 4]], [[1, 2, 5], [3, 4]], 2),
([[1, 3, 4], [2, 5]], [[1, 2, 4], [3, 5]], 2),
([[1, 2, 5], [3, 4]], [[1, 3, 5], [2, 4]], 3),
([[1, 2, 4], [3, 5]], [[1, 2, 3], [4, 5]], 3),
([[1, 2, 3], [4, 5]], [[1, 2, 4], [3, 5]], 4)]
sage: T = crystals.Tableaux(['A',4], shape=[3,1])
sage: G = T.dual_equivalence_graph(index_set=[1,2,3])
sage: G.vertices()
[[[1, 3, 4], [2]], [[1, 2, 4], [3]], [[1, 2, 3], [4]]]
sage: G.edges()
[([[1, 3, 4], [2]], [[1, 2, 4], [3]], 2),
([[1, 2, 4], [3]], [[1, 2, 3], [4]], 3)]
TESTS::
sage: T = crystals.Tableaux(['A',4], shape=[3,1])
sage: G = T.dual_equivalence_graph(index_set=[2,3])
sage: sorted(G.edges())
[([[1, 2, 4], [3]], [[1, 2, 3], [4]], 3),
([[2, 4, 5], [3]], [[2, 3, 5], [4]], 3)]
sage: sorted(G.vertices())
[[[1, 3, 4], [2]],
[[1, 2, 4], [3]],
[[2, 4, 5], [3]],
[[1, 2, 3], [4]],
[[2, 3, 5], [4]],
[[1, 1, 1], [5]],
[[1, 1, 5], [5]],
[[1, 5, 5], [5]],
[[2, 3, 4], [5]]]
"""
if index_set is None:
index_set = self.index_set()
def wt_zero(x):
for i in index_set:
if x.epsilon(i) != x.phi(i):
return False
return True
if X is None:
X = [x for x in self if wt_zero(x)]
checker = lambda x: True
elif any(not wt_zero(x) for x in X):
raise ValueError("the elements are not all weight 0")
else:
checker = lambda x: x in X
edges = []
for x in X:
for k, i in enumerate(index_set[1:]):
im = index_set[k]
if x.epsilon(i) == 1 and x.epsilon(im) == 0:
y = x.e(i).e(im).f(i).f(im)
if checker(y):
edges.append([x, y, i])
from sage.graphs.all import DiGraph
G = DiGraph([X, edges], format="vertices_and_edges", immutable=True)
if have_dot2tex():
G.set_latex_options(format="dot2tex", edge_labels=True,
color_by_label=self.cartan_type()._index_set_coloring)
return G
def dual_equivalence_class(self, index_set=None):
r"""
Return the dual equivalence class indexed by ``index_set``
of ``self``.
The dual equivalence class of an element `b \in B`
is the set of all elements of `B` reachable from
`b` via sequences of `i`-elementary dual equivalence
relations (i.e., `i`-elementary dual equivalence
transformations and their inverses) for `i` in the index
set of `B`.
For this to be well-defined, the element `b` has to be
of weight `0` with respect to `I`; that is, we need to have
`\varepsilon_j(b) = \varphi_j(b)` for all `j \in I`.
See [Assaf08]_. See also :meth:`dual_equivalence_graph` for
a definition of `i`-elementary dual equivalence
transformations.
INPUT:
- ``index_set`` -- (optional) the index set `I`
(default: the whole index set of the crystal); this has
to be a subset of the index set of the crystal (as a list
or tuple)
OUTPUT:
The dual equivalence class of ``self`` indexed by the
subset ``index_set``. This class is returned as an
undirected edge-colored multigraph. The color of an edge
is the index `i` of the dual equivalence relation it
encodes.
.. SEEALSO::
- :meth:`~sage.categories.regular_crystals.RegularCrystals.ParentMethods.dual_equivalence_graph`
- :meth:`sage.combinat.partition.Partition.dual_equivalence_graph`
EXAMPLES::
sage: T = crystals.Tableaux(['A',3], shape=[2,2])
sage: G = T(2,1,4,3).dual_equivalence_class()
sage: sorted(G.edges())
[([[1, 3], [2, 4]], [[1, 2], [3, 4]], 2),
([[1, 3], [2, 4]], [[1, 2], [3, 4]], 3)]
sage: T = crystals.Tableaux(['A',4], shape=[3,2])
sage: G = T(2,1,4,3,5).dual_equivalence_class()
sage: sorted(G.edges())
[([[1, 3, 5], [2, 4]], [[1, 3, 4], [2, 5]], 4),
([[1, 3, 5], [2, 4]], [[1, 2, 5], [3, 4]], 2),
([[1, 3, 5], [2, 4]], [[1, 2, 5], [3, 4]], 3),
([[1, 3, 4], [2, 5]], [[1, 2, 4], [3, 5]], 2),
([[1, 2, 4], [3, 5]], [[1, 2, 3], [4, 5]], 3),
([[1, 2, 4], [3, 5]], [[1, 2, 3], [4, 5]], 4)]
"""
if index_set is None:
index_set = self.index_set()
for i in index_set:
if self.epsilon(i) != self.phi(i):
raise ValueError("the element is not weight 0")
visited = set([])
todo = set([self])
edges = []
while todo:
x = todo.pop()
visited.add(x)
for k, i in enumerate(index_set[1:]):
im = index_set[k]
if x.epsilon(i) == 1 and x.epsilon(im) == 0:
y = x.e(i).e(im).f(i).f(im)
if [y, x, i] not in edges:
edges.append([x, y, i])
if y not in visited:
todo.add(y)
if x.epsilon(i) == 0 and x.epsilon(im) == 1:
y = x.e(im).e(i).f(im).f(i)
if [y, x, i] not in edges:
edges.append([x, y, i])
if y not in visited:
todo.add(y)
from sage.graphs.graph import Graph
G = Graph([visited, edges], format="vertices_and_edges",
immutable=True, multiedges=True)
if have_dot2tex():
G.set_latex_options(format="dot2tex", edge_labels=True,
color_by_label=self.cartan_type()._index_set_coloring)
return G
def dual_equivalence_graph(self,
X=None,
index_set=None,
directed=True):
r"""
Return the dual equivalence graph indexed by ``index_set``
on the subset ``X`` of ``self``.
Let `b \in B` be an element of weight `0`, so `\varepsilon_j(b)
= \varphi_j(b)` for all `j \in I`, where `I` is the indexing
set. We say `b'` is an `i`-elementary dual equivalence
transformation of `b` (where `i \in I`) if
* `\varepsilon_i(b) = 1` and `\varepsilon_{i-1}(b) = 0`, and
* `b' = f_{i-1} f_i e_{i-1} e_i b`.
We can do the inverse procedure by interchanging `i` and `i-1`
above.
.. NOTE::
If the index set is not an ordered interval, we let
`i - 1` mean the index appearing before `i` in `I`.
This definition comes from [As2008]_ Section 4 (where our
`\varphi_j(b)` and `\varepsilon_j(b)` are denoted by
`\epsilon(b, j)` and `-\delta(b, j)`, respectively).
The dual equivalence graph of `B` is defined to be the
colored graph whose vertices are the elements of `B` of
weight `0`, and whose edges of color `i` (for `i \in I`)
connect pairs `\{ b, b' \}` such that `b'` is an
`i`-elementary dual equivalence transformation of `b`.
.. NOTE::
This dual equivalence graph is a generalization of
`\mathcal{G}\left(\mathcal{X}\right)` in [As2008]_
Section 4 except we do not require
`\varepsilon_i(b) = 0, 1` for all `i`.
This definition can be generalized by choosing a subset `X`
of the set of all vertices of `B` of weight `0`, and
restricting the dual equivalence graph to the vertex set
`X`.
INPUT:
- ``X`` -- (optional) the vertex set `X` (default:
the whole set of vertices of ``self`` of weight `0`)
- ``index_set`` -- (optional) the index set `I`
(default: the whole index set of ``self``); this has
to be a subset of the index set of ``self`` (as a list
or tuple)
- ``directed`` -- (default: ``True``) whether to have the
dual equivalence graph be directed, where the head of
an edge `b - b'` is `b` and the tail is
`b' = f_{i-1} f_i e_{i-1} e_i b`)
.. SEEALSO::
:meth:`sage.combinat.partition.Partition.dual_equivalence_graph`
EXAMPLES::
sage: T = crystals.Tableaux(['A',3], shape=[2,2])
sage: G = T.dual_equivalence_graph()
sage: sorted(G.edges())
[([[1, 3], [2, 4]], [[1, 2], [3, 4]], 2),
([[1, 2], [3, 4]], [[1, 3], [2, 4]], 3)]
sage: T = crystals.Tableaux(['A',4], shape=[3,2])
sage: G = T.dual_equivalence_graph()
sage: sorted(G.edges())
[([[1, 3, 5], [2, 4]], [[1, 3, 4], [2, 5]], 4),
([[1, 3, 5], [2, 4]], [[1, 2, 5], [3, 4]], 2),
([[1, 3, 4], [2, 5]], [[1, 2, 4], [3, 5]], 2),
([[1, 2, 5], [3, 4]], [[1, 3, 5], [2, 4]], 3),
([[1, 2, 4], [3, 5]], [[1, 2, 3], [4, 5]], 3),
([[1, 2, 3], [4, 5]], [[1, 2, 4], [3, 5]], 4)]
sage: T = crystals.Tableaux(['A',4], shape=[3,1])
sage: G = T.dual_equivalence_graph(index_set=[1,2,3])
sage: G.vertices()
[[[1, 3, 4], [2]], [[1, 2, 4], [3]], [[1, 2, 3], [4]]]
sage: G.edges()
[([[1, 3, 4], [2]], [[1, 2, 4], [3]], 2),
([[1, 2, 4], [3]], [[1, 2, 3], [4]], 3)]
TESTS::
sage: T = crystals.Tableaux(['A',4], shape=[3,1])
sage: G = T.dual_equivalence_graph(index_set=[2,3])
sage: sorted(G.edges())
[([[1, 2, 4], [3]], [[1, 2, 3], [4]], 3),
([[2, 4, 5], [3]], [[2, 3, 5], [4]], 3)]
sage: sorted(G.vertices())
[[[1, 3, 4], [2]],
[[1, 2, 4], [3]],
[[2, 4, 5], [3]],
[[1, 2, 3], [4]],
[[2, 3, 5], [4]],
[[1, 1, 1], [5]],
[[1, 1, 5], [5]],
[[1, 5, 5], [5]],
[[2, 3, 4], [5]]]
"""
if index_set is None:
index_set = self.index_set()
def wt_zero(x):
for i in index_set:
if x.epsilon(i) != x.phi(i):
return False
return True
if X is None:
X = [x for x in self if wt_zero(x)]
checker = lambda x: True
elif any(not wt_zero(x) for x in X):
raise ValueError("the elements are not all weight 0")
else:
checker = lambda x: x in X
edges = []
for x in X:
for k, i in enumerate(index_set[1:]):
im = index_set[k]
if x.epsilon(i) == 1 and x.epsilon(im) == 0:
y = x.e(i).e(im).f(i).f(im)
if checker(y):
edges.append([x, y, i])
from sage.graphs.all import DiGraph
G = DiGraph([X, edges],
format="vertices_and_edges",
immutable=True)
if have_dot2tex():
G.set_latex_options(
format="dot2tex",
edge_labels=True,
color_by_label=self.cartan_type()._index_set_coloring)
return G
def dual_equivalence_class(self, index_set=None):
r"""
Return the dual equivalence class indexed by ``index_set``
of ``self``.
The dual equivalence class of an element `b \in B`
is the set of all elements of `B` reachable from
`b` via sequences of `i`-elementary dual equivalence
relations (i.e., `i`-elementary dual equivalence
transformations and their inverses) for `i` in the index
set of `B`.
For this to be well-defined, the element `b` has to be
of weight `0` with respect to `I`; that is, we need to have
`\varepsilon_j(b) = \varphi_j(b)` for all `j \in I`.
See [As2008]_. See also :meth:`dual_equivalence_graph` for
a definition of `i`-elementary dual equivalence
transformations.
INPUT:
- ``index_set`` -- (optional) the index set `I`
(default: the whole index set of the crystal); this has
to be a subset of the index set of the crystal (as a list
or tuple)
OUTPUT:
The dual equivalence class of ``self`` indexed by the
subset ``index_set``. This class is returned as an
undirected edge-colored multigraph. The color of an edge
is the index `i` of the dual equivalence relation it
encodes.
.. SEEALSO::
- :meth:`~sage.categories.regular_crystals.RegularCrystals.ParentMethods.dual_equivalence_graph`
- :meth:`sage.combinat.partition.Partition.dual_equivalence_graph`
EXAMPLES::
sage: T = crystals.Tableaux(['A',3], shape=[2,2])
sage: G = T(2,1,4,3).dual_equivalence_class()
sage: sorted(G.edges())
[([[1, 3], [2, 4]], [[1, 2], [3, 4]], 2),
([[1, 3], [2, 4]], [[1, 2], [3, 4]], 3)]
sage: T = crystals.Tableaux(['A',4], shape=[3,2])
sage: G = T(2,1,4,3,5).dual_equivalence_class()
sage: sorted(G.edges())
[([[1, 3, 5], [2, 4]], [[1, 3, 4], [2, 5]], 4),
([[1, 3, 5], [2, 4]], [[1, 2, 5], [3, 4]], 2),
([[1, 3, 5], [2, 4]], [[1, 2, 5], [3, 4]], 3),
([[1, 3, 4], [2, 5]], [[1, 2, 4], [3, 5]], 2),
([[1, 2, 4], [3, 5]], [[1, 2, 3], [4, 5]], 3),
([[1, 2, 4], [3, 5]], [[1, 2, 3], [4, 5]], 4)]
"""
if index_set is None:
index_set = self.index_set()
for i in index_set:
if self.epsilon(i) != self.phi(i):
raise ValueError("the element is not weight 0")
visited = set([])
todo = set([self])
edges = []
while todo:
x = todo.pop()
visited.add(x)
for k, i in enumerate(index_set[1:]):
im = index_set[k]
if x.epsilon(i) == 1 and x.epsilon(im) == 0:
y = x.e(i).e(im).f(i).f(im)
if [y, x, i] not in edges:
edges.append([x, y, i])
if y not in visited:
todo.add(y)
if x.epsilon(i) == 0 and x.epsilon(im) == 1:
y = x.e(im).e(i).f(im).f(i)
if [y, x, i] not in edges:
edges.append([x, y, i])
if y not in visited:
todo.add(y)
from sage.graphs.graph import Graph
G = Graph([visited, edges],
format="vertices_and_edges",
immutable=True,
multiedges=True)
if have_dot2tex():
G.set_latex_options(
format="dot2tex",
edge_labels=True,
color_by_label=self.cartan_type()._index_set_coloring)
return G
def markov_chain_digraph(self, action = 'promotion', labeling = 'identity'):
r"""
Returns the digraph of the action of generalized promotion or tau on ``self``
INPUT:
- ``action`` -- 'promotion' or 'tau' (default: 'promotion')
- ``labeling`` -- 'identity' or 'source' (default: 'identity')
.. todo::
- generalize this feature by accepting a family of operators as input
- move up in some appropriate category
This method creates a graph with vertices being the linear extensions of a given finite
poset and an edge from `\pi` to `\pi'` if `\pi' = \pi \partial_i` where `\partial_i` is
the promotion operator (see :meth:`promotion`) if ``action`` is set to ``promotion``
and `\tau_i` (see :meth:`tau`) if ``action`` is set to ``tau``. The label of the edge
is `i` (resp. `\pi_i`) if ``labeling`` is set to ``identity`` (resp. ``source``).
EXAMPLES::
sage: P = Poset(([1,2,3,4], [[1,3],[1,4],[2,3]]), linear_extension = True)
sage: L = P.linear_extensions()
sage: G = L.markov_chain_digraph(); G
Looped multi-digraph on 5 vertices
sage: sorted(G.vertices(), key = repr)
[[1, 2, 3, 4], [1, 2, 4, 3], [1, 4, 2, 3], [2, 1, 3, 4], [2, 1, 4, 3]]
sage: sorted(G.edges(), key = repr)
[([1, 2, 3, 4], [1, 2, 3, 4], 4), ([1, 2, 3, 4], [1, 2, 4, 3], 2), ([1, 2, 3, 4], [1, 2, 4, 3], 3),
([1, 2, 3, 4], [2, 1, 4, 3], 1), ([1, 2, 4, 3], [1, 2, 3, 4], 3), ([1, 2, 4, 3], [1, 2, 4, 3], 4),
([1, 2, 4, 3], [1, 4, 2, 3], 2), ([1, 2, 4, 3], [2, 1, 3, 4], 1), ([1, 4, 2, 3], [1, 2, 3, 4], 1),
([1, 4, 2, 3], [1, 2, 3, 4], 2), ([1, 4, 2, 3], [1, 4, 2, 3], 3), ([1, 4, 2, 3], [1, 4, 2, 3], 4),
([2, 1, 3, 4], [1, 2, 4, 3], 1), ([2, 1, 3, 4], [2, 1, 3, 4], 4), ([2, 1, 3, 4], [2, 1, 4, 3], 2),
([2, 1, 3, 4], [2, 1, 4, 3], 3), ([2, 1, 4, 3], [1, 4, 2, 3], 1), ([2, 1, 4, 3], [2, 1, 3, 4], 2),
([2, 1, 4, 3], [2, 1, 3, 4], 3), ([2, 1, 4, 3], [2, 1, 4, 3], 4)]
sage: G = L.markov_chain_digraph(labeling = 'source')
sage: sorted(G.vertices(), key = repr)
[[1, 2, 3, 4], [1, 2, 4, 3], [1, 4, 2, 3], [2, 1, 3, 4], [2, 1, 4, 3]]
sage: sorted(G.edges(), key = repr)
[([1, 2, 3, 4], [1, 2, 3, 4], 4), ([1, 2, 3, 4], [1, 2, 4, 3], 2), ([1, 2, 3, 4], [1, 2, 4, 3], 3),
([1, 2, 3, 4], [2, 1, 4, 3], 1), ([1, 2, 4, 3], [1, 2, 3, 4], 4), ([1, 2, 4, 3], [1, 2, 4, 3], 3),
([1, 2, 4, 3], [1, 4, 2, 3], 2), ([1, 2, 4, 3], [2, 1, 3, 4], 1), ([1, 4, 2, 3], [1, 2, 3, 4], 1),
([1, 4, 2, 3], [1, 2, 3, 4], 4), ([1, 4, 2, 3], [1, 4, 2, 3], 2), ([1, 4, 2, 3], [1, 4, 2, 3], 3),
([2, 1, 3, 4], [1, 2, 4, 3], 2), ([2, 1, 3, 4], [2, 1, 3, 4], 4), ([2, 1, 3, 4], [2, 1, 4, 3], 1),
([2, 1, 3, 4], [2, 1, 4, 3], 3), ([2, 1, 4, 3], [1, 4, 2, 3], 2), ([2, 1, 4, 3], [2, 1, 3, 4], 1),
([2, 1, 4, 3], [2, 1, 3, 4], 4), ([2, 1, 4, 3], [2, 1, 4, 3], 3)]
The edges of the graph are by default colored using blue for
edge 1, red for edge 2, green for edge 3, and yellow for edge 4::
sage: view(G) #optional - dot2tex graphviz
Alternatively, one may get the graph of the action of the ``tau`` operator::
sage: G = L.markov_chain_digraph(action='tau'); G
Looped multi-digraph on 5 vertices
sage: sorted(G.vertices(), key = repr)
[[1, 2, 3, 4], [1, 2, 4, 3], [1, 4, 2, 3], [2, 1, 3, 4], [2, 1, 4, 3]]
sage: sorted(G.edges(), key = repr)
[([1, 2, 3, 4], [1, 2, 3, 4], 2), ([1, 2, 3, 4], [1, 2, 4, 3], 3), ([1, 2, 3, 4], [2, 1, 3, 4], 1),
([1, 2, 4, 3], [1, 2, 3, 4], 3), ([1, 2, 4, 3], [1, 4, 2, 3], 2), ([1, 2, 4, 3], [2, 1, 4, 3], 1),
([1, 4, 2, 3], [1, 2, 4, 3], 2), ([1, 4, 2, 3], [1, 4, 2, 3], 1), ([1, 4, 2, 3], [1, 4, 2, 3], 3),
([2, 1, 3, 4], [1, 2, 3, 4], 1), ([2, 1, 3, 4], [2, 1, 3, 4], 2), ([2, 1, 3, 4], [2, 1, 4, 3], 3),
([2, 1, 4, 3], [1, 2, 4, 3], 1), ([2, 1, 4, 3], [2, 1, 3, 4], 3), ([2, 1, 4, 3], [2, 1, 4, 3], 2)]
sage: view(G) #optional - dot2tex graphviz
.. seealso:: :meth:`markov_chain_transition_matrix`, :meth:`promotion`, :meth:`tau`
TESTS::
sage: P = Poset(([1,2,3,4], [[1,3],[1,4],[2,3]]), linear_extension = True, facade = True)
sage: L = P.linear_extensions()
sage: G = L.markov_chain_digraph(labeling = 'source'); G
Looped multi-digraph on 5 vertices
"""
d = dict([x,dict([y,[]] for y in self)] for x in self)
if action == 'promotion':
R = range(self.poset().cardinality())
else:
R = range(self.poset().cardinality()-1)
if labeling == 'source':
for x in self:
for i in R:
child = getattr(x, action)(i+1)
d[x][child]+=[self.poset().unwrap(x[i])]
else:
for x in self:
for i in R:
child = getattr(x, action)(i+1)
d[x][child]+=[i+1]
G = DiGraph(d)
if have_dot2tex():
G.set_latex_options(format="dot2tex", edge_labels = True, color_by_label = {1:"blue", 2:"red", 3:"green", 4:"yellow"})
#G.set_latex_options(format="dot2tex", edge_labels = True, color_by_label = {1:"green", 2:"blue", 3:"brown", 4:"red"})
return G
def markov_chain_digraph(self, action='promotion', labeling='identity'):
r"""
Returns the digraph of the action of generalized promotion or tau on ``self``
INPUT:
- ``action`` -- 'promotion' or 'tau' (default: 'promotion')
- ``labeling`` -- 'identity' or 'source' (default: 'identity')
.. todo::
- generalize this feature by accepting a family of operators as input
- move up in some appropriate category
This method creates a graph with vertices being the linear extensions of a given finite
poset and an edge from `\pi` to `\pi'` if `\pi' = \pi \partial_i` where `\partial_i` is
the promotion operator (see :meth:`promotion`) if ``action`` is set to ``promotion``
and `\tau_i` (see :meth:`tau`) if ``action`` is set to ``tau``. The label of the edge
is `i` (resp. `\pi_i`) if ``labeling`` is set to ``identity`` (resp. ``source``).
EXAMPLES::
sage: P = Poset(([1,2,3,4], [[1,3],[1,4],[2,3]]), linear_extension = True)
sage: L = P.linear_extensions()
sage: G = L.markov_chain_digraph(); G
Looped multi-digraph on 5 vertices
sage: sorted(G.vertices(), key = repr)
[[1, 2, 3, 4], [1, 2, 4, 3], [1, 4, 2, 3], [2, 1, 3, 4], [2, 1, 4, 3]]
sage: sorted(G.edges(), key = repr)
[([1, 2, 3, 4], [1, 2, 3, 4], 4), ([1, 2, 3, 4], [1, 2, 4, 3], 2), ([1, 2, 3, 4], [1, 2, 4, 3], 3),
([1, 2, 3, 4], [2, 1, 4, 3], 1), ([1, 2, 4, 3], [1, 2, 3, 4], 3), ([1, 2, 4, 3], [1, 2, 4, 3], 4),
([1, 2, 4, 3], [1, 4, 2, 3], 2), ([1, 2, 4, 3], [2, 1, 3, 4], 1), ([1, 4, 2, 3], [1, 2, 3, 4], 1),
([1, 4, 2, 3], [1, 2, 3, 4], 2), ([1, 4, 2, 3], [1, 4, 2, 3], 3), ([1, 4, 2, 3], [1, 4, 2, 3], 4),
([2, 1, 3, 4], [1, 2, 4, 3], 1), ([2, 1, 3, 4], [2, 1, 3, 4], 4), ([2, 1, 3, 4], [2, 1, 4, 3], 2),
([2, 1, 3, 4], [2, 1, 4, 3], 3), ([2, 1, 4, 3], [1, 4, 2, 3], 1), ([2, 1, 4, 3], [2, 1, 3, 4], 2),
([2, 1, 4, 3], [2, 1, 3, 4], 3), ([2, 1, 4, 3], [2, 1, 4, 3], 4)]
sage: G = L.markov_chain_digraph(labeling = 'source')
sage: sorted(G.vertices(), key = repr)
[[1, 2, 3, 4], [1, 2, 4, 3], [1, 4, 2, 3], [2, 1, 3, 4], [2, 1, 4, 3]]
sage: sorted(G.edges(), key = repr)
[([1, 2, 3, 4], [1, 2, 3, 4], 4), ([1, 2, 3, 4], [1, 2, 4, 3], 2), ([1, 2, 3, 4], [1, 2, 4, 3], 3),
([1, 2, 3, 4], [2, 1, 4, 3], 1), ([1, 2, 4, 3], [1, 2, 3, 4], 4), ([1, 2, 4, 3], [1, 2, 4, 3], 3),
([1, 2, 4, 3], [1, 4, 2, 3], 2), ([1, 2, 4, 3], [2, 1, 3, 4], 1), ([1, 4, 2, 3], [1, 2, 3, 4], 1),
([1, 4, 2, 3], [1, 2, 3, 4], 4), ([1, 4, 2, 3], [1, 4, 2, 3], 2), ([1, 4, 2, 3], [1, 4, 2, 3], 3),
([2, 1, 3, 4], [1, 2, 4, 3], 2), ([2, 1, 3, 4], [2, 1, 3, 4], 4), ([2, 1, 3, 4], [2, 1, 4, 3], 1),
([2, 1, 3, 4], [2, 1, 4, 3], 3), ([2, 1, 4, 3], [1, 4, 2, 3], 2), ([2, 1, 4, 3], [2, 1, 3, 4], 1),
([2, 1, 4, 3], [2, 1, 3, 4], 4), ([2, 1, 4, 3], [2, 1, 4, 3], 3)]
The edges of the graph are by default colored using blue for
edge 1, red for edge 2, green for edge 3, and yellow for edge 4::
sage: view(G) # optional - dot2tex graphviz, not tested (opens external window)
Alternatively, one may get the graph of the action of the ``tau`` operator::
sage: G = L.markov_chain_digraph(action='tau'); G
Looped multi-digraph on 5 vertices
sage: sorted(G.vertices(), key = repr)
[[1, 2, 3, 4], [1, 2, 4, 3], [1, 4, 2, 3], [2, 1, 3, 4], [2, 1, 4, 3]]
sage: sorted(G.edges(), key = repr)
[([1, 2, 3, 4], [1, 2, 3, 4], 2), ([1, 2, 3, 4], [1, 2, 4, 3], 3), ([1, 2, 3, 4], [2, 1, 3, 4], 1),
([1, 2, 4, 3], [1, 2, 3, 4], 3), ([1, 2, 4, 3], [1, 4, 2, 3], 2), ([1, 2, 4, 3], [2, 1, 4, 3], 1),
([1, 4, 2, 3], [1, 2, 4, 3], 2), ([1, 4, 2, 3], [1, 4, 2, 3], 1), ([1, 4, 2, 3], [1, 4, 2, 3], 3),
([2, 1, 3, 4], [1, 2, 3, 4], 1), ([2, 1, 3, 4], [2, 1, 3, 4], 2), ([2, 1, 3, 4], [2, 1, 4, 3], 3),
([2, 1, 4, 3], [1, 2, 4, 3], 1), ([2, 1, 4, 3], [2, 1, 3, 4], 3), ([2, 1, 4, 3], [2, 1, 4, 3], 2)]
sage: view(G) # optional - dot2tex graphviz, not tested (opens external window)
.. SEEALSO:: :meth:`markov_chain_transition_matrix`, :meth:`promotion`, :meth:`tau`
TESTS::
sage: P = Poset(([1,2,3,4], [[1,3],[1,4],[2,3]]), linear_extension = True, facade = True)
sage: L = P.linear_extensions()
sage: G = L.markov_chain_digraph(labeling = 'source'); G
Looped multi-digraph on 5 vertices
"""
d = dict([x, dict([y, []] for y in self)] for x in self)
if action == 'promotion':
R = list(range(self.poset().cardinality()))
else:
R = list(range(self.poset().cardinality() - 1))
if labeling == 'source':
for x in self:
for i in R:
child = getattr(x, action)(i + 1)
d[x][child] += [self.poset().unwrap(x[i])]
else:
for x in self:
for i in R:
child = getattr(x, action)(i + 1)
d[x][child] += [i + 1]
G = DiGraph(d, format="dict_of_dicts")
if have_dot2tex():
G.set_latex_options(format="dot2tex",
edge_labels=True,
color_by_label={
1: "blue",
2: "red",
3: "green",
4: "yellow"
})
#G.set_latex_options(format="dot2tex", edge_labels = True, color_by_label = {1:"green", 2:"blue", 3:"brown", 4:"red"})
return G
def run(self, verbose=False, build_graph=False):
"""
Run the bijection from rigged configurations to tensor product of KR
tableaux for type `B_n^{(1)}`.
INPUT:
- ``verbose`` -- (default: ``False``) display each step in the
bijection
- ``build_graph`` -- (default: ``False``) build the graph of each
step of the bijection
EXAMPLES::
sage: RC = RiggedConfigurations(['B', 3, 1], [[2, 1]])
sage: from sage.combinat.rigged_configurations.bij_type_B import RCToKRTBijectionTypeB
sage: RCToKRTBijectionTypeB(RC(partition_list=[[1],[1,1],[1]])).run()
[[3], [0]]
sage: RC = RiggedConfigurations(['B', 3, 1], [[3, 1]])
sage: x = RC(partition_list=[[],[1],[1]])
sage: RCToKRTBijectionTypeB(x).run()
[[1], [3], [-2]]
sage: bij = RCToKRTBijectionTypeB(x)
sage: bij.run(build_graph=True)
[[1], [3], [-2]]
sage: bij._graph
Digraph on 6 vertices
"""
from sage.combinat.crystals.letters import CrystalOfLetters
letters = CrystalOfLetters(self.rigged_con.parent()._cartan_type.classical())
# This is technically bad, but because the first thing we do is append
# an empty list to ret_crystal_path, we correct this. We do it this
# way so that we do not have to remove an empty list after the
# bijection has been performed.
ret_crystal_path = []
for dim in self.rigged_con.parent().dims:
ret_crystal_path.append([])
# Check to see if we are a spinor
if dim[0] == self.n:
# Perform the spinor bijection by converting to type A_{2n-1}^{(2)}
# doing the bijection there and pulling back
from sage.combinat.rigged_configurations.bij_type_A2_odd import RCToKRTBijectionTypeA2Odd
from sage.combinat.rigged_configurations.rigged_configurations import RiggedConfigurations
from sage.combinat.rigged_configurations.rigged_partition import RiggedPartition, RiggedPartitionTypeB
# Convert to a type A_{2n-1}^{(2)} RC
RC = RiggedConfigurations(['A', 2*self.n-1, 2], self.cur_dims)
if verbose:
print("====================")
print(repr(RC(*self.cur_partitions, use_vacancy_numbers=True)))
print("--------------------")
print(ret_crystal_path)
print("--------------------\n")
print("Applying doubling map\n")
# Convert the n-th partition into a regular rigged partition
self.cur_partitions[-1] = RiggedPartition(self.cur_partitions[-1]._list,
self.cur_partitions[-1].rigging,
self.cur_partitions[-1].vacancy_numbers)
bij = RCToKRTBijectionTypeA2Odd(RC(*self.cur_partitions, use_vacancy_numbers=True))
for i in range(len(self.cur_dims)):
if bij.cur_dims[i][0] != self.n:
bij.cur_dims[i][1] *= 2
for i in range(self.n-1):
for j in range(len(bij.cur_partitions[i])):
bij.cur_partitions[i]._list[j] *= 2
bij.cur_partitions[i].rigging[j] *= 2
bij.cur_partitions[i].vacancy_numbers[j] *= 2
if build_graph:
y = self.rigged_con.parent()(*[x._clone() for x in self.cur_partitions], use_vacancy_numbers=True)
self._graph.append([self._graph[-1][1], (y, len(self._graph)), '2x'])
# Perform the type A_{2n-1}^{(2)} bijection
# Iterate over each column
for dummy_var in range(dim[1]):
# Split off a new column if necessary
if bij.cur_dims[0][1] > 1:
bij.cur_dims[0][1] -= 1
bij.cur_dims.insert(0, [dim[0], 1])
# Perform the corresponding splitting map on rigged configurations
# All it does is update the vacancy numbers on the RC side
for a in range(self.n):
bij._update_vacancy_numbers(a)
if build_graph:
y = self.rigged_con.parent()(*[x._clone() for x in self.cur_partitions], use_vacancy_numbers=True)
self._graph.append([self._graph[-1][1], (y, len(self._graph)), 'ls'])
while bij.cur_dims[0][0]: # > 0:
if verbose:
print("====================")
print(repr(RC(*bij.cur_partitions, use_vacancy_numbers=True)))
print("--------------------")
print(ret_crystal_path)
print("--------------------\n")
ht = bij.cur_dims[0][0]
bij.cur_dims[0][0] = bij._next_index(ht)
b = bij.next_state(ht)
# Make sure we have a crystal letter
ret_crystal_path[-1].append(letters(b)) # Append the rank
if build_graph:
y = self.rigged_con.parent()(*[x._clone() for x in self.cur_partitions], use_vacancy_numbers=True)
self._graph.append([self._graph[-1][1], (y, len(self._graph)), letters(b)])
bij.cur_dims.pop(0) # Pop off the leading column
self.cur_dims.pop(0) # Pop off the spin rectangle
self.cur_partitions = bij.cur_partitions
# Convert the n-th partition back into the special type B one
self.cur_partitions[-1] = RiggedPartitionTypeB(self.cur_partitions[-1])
# Convert back to a type B_n^{(1)}
if verbose:
print("====================")
print(repr(self.rigged_con.parent()(*bij.cur_partitions, use_vacancy_numbers=True)))
print("--------------------")
print(ret_crystal_path)
print("--------------------\n")
print("Applying halving map\n")
for i in range(self.n-1):
for j in range(len(self.cur_partitions[i])):
self.cur_partitions[i]._list[j] //= 2
self.cur_partitions[i].rigging[j] //= 2
self.cur_partitions[i].vacancy_numbers[j] //= 2
if build_graph:
y = self.rigged_con.parent()(*[x._clone() for x in self.cur_partitions], use_vacancy_numbers=True)
self._graph.append([self._graph[-1][1], (y, len(self._graph)), '1/2x'])
else:
# Perform the regular type B_n^{(1)} bijection
# Iterate over each column
for dummy_var in range(dim[1]):
# Split off a new column if necessary
if self.cur_dims[0][1] > 1:
if verbose:
print("====================")
print(repr(self.rigged_con.parent()(*self.cur_partitions, use_vacancy_numbers=True)))
print("--------------------")
print(ret_crystal_path)
print("--------------------\n")
print("Applying column split")
self.cur_dims[0][1] -= 1
self.cur_dims.insert(0, [dim[0], 1])
# Perform the corresponding splitting map on rigged configurations
# All it does is update the vacancy numbers on the RC side
for a in range(self.n):
self._update_vacancy_numbers(a)
if build_graph:
y = self.rigged_con.parent()(*[x._clone() for x in self.cur_partitions], use_vacancy_numbers=True)
self._graph.append([self._graph[-1][1], (y, len(self._graph)), '2x'])
while self.cur_dims[0][0]: #> 0:
if verbose:
print("====================")
print(repr(self.rigged_con.parent()(*self.cur_partitions, use_vacancy_numbers=True)))
print("--------------------")
print(ret_crystal_path)
print("--------------------\n")
self.cur_dims[0][0] -= 1 # This takes care of the indexing
b = self.next_state(self.cur_dims[0][0])
# Make sure we have a crystal letter
ret_crystal_path[-1].append(letters(b)) # Append the rank
if build_graph:
y = self.rigged_con.parent()(*[x._clone() for x in self.cur_partitions], use_vacancy_numbers=True)
self._graph.append([self._graph[-1][1], (y, len(self._graph)), letters(b)])
self.cur_dims.pop(0) # Pop off the leading column
if build_graph:
self._graph.pop(0) # Remove the dummy at the start
from sage.graphs.digraph import DiGraph
from sage.graphs.dot2tex_utils import have_dot2tex
self._graph = DiGraph(self._graph)
if have_dot2tex():
self._graph.set_latex_options(format="dot2tex", edge_labels=True)
return self.KRT(pathlist=ret_crystal_path)
def digraph(self, subset=None, index_set=None):
"""
Returns the DiGraph associated to ``self``.
INPUT:
- ``subset`` -- (Optional) A subset of vertices for
which the digraph should be constructed
- ``index_set`` -- (Optional) The index set to draw arrows
EXAMPLES::
sage: C = Crystals().example(5)
sage: C.digraph()
Digraph on 6 vertices
The edges of the crystal graph are by default colored using blue for edge 1, red for edge 2,
and green for edge 3::
sage: C = Crystals().example(3)
sage: G = C.digraph()
sage: view(G, pdflatex=True, tightpage=True) #optional - dot2tex graphviz
One may also overwrite the colors::
sage: C = Crystals().example(3)
sage: G = C.digraph()
sage: G.set_latex_options(color_by_label = {1:"red", 2:"purple", 3:"blue"})
sage: view(G, pdflatex=True, tightpage=True) #optional - dot2tex graphviz
Or one may add colors to yet unspecified edges::
sage: C = Crystals().example(4)
sage: G = C.digraph()
sage: C.cartan_type()._index_set_coloring[4]="purple"
sage: view(G, pdflatex=True, tightpage=True) #optional - dot2tex graphviz
Here is an example of how to take the top part up to a given depth of an infinite dimensional
crystal::
sage: C = CartanType(['C',2,1])
sage: La = C.root_system().weight_lattice().fundamental_weights()
sage: T = HighestWeightCrystal(La[0])
sage: S = T.subcrystal(max_depth=3)
sage: G = T.digraph(subset=S); G
Digraph on 5 vertices
sage: G.vertices()
[(1/2*Lambda[0] + Lambda[1] - Lambda[2] - 1/2*delta, -1/2*Lambda[0] + Lambda[1] - 1/2*delta),
(-Lambda[0] + 2*Lambda[1] - delta,), (Lambda[0] - 2*Lambda[1] + 2*Lambda[2] - delta,),
(1/2*Lambda[0] - Lambda[1] + Lambda[2] - 1/2*delta, -1/2*Lambda[0] + Lambda[1] - 1/2*delta), (Lambda[0],)]
Here is a way to construct a picture of a Demazure crystal using
the ``subset`` option::
sage: B = CrystalOfTableaux(['A',2], shape=[2,1])
sage: C = CombinatorialFreeModule(QQ,B)
sage: t = B.highest_weight_vector()
sage: b = C(t)
sage: D = B.demazure_operator(b,[2,1]); D
B[[[1, 1], [2]]] + B[[[1, 2], [2]]] + B[[[1, 3], [2]]] + B[[[1, 1], [3]]] + B[[[1, 3], [3]]]
sage: G = B.digraph(subset=D.support())
sage: G.vertices()
[[[1, 1], [2]], [[1, 2], [2]], [[1, 3], [2]], [[1, 1], [3]], [[1, 3], [3]]]
sage: view(G, pdflatex=True, tightpage=True) #optional - dot2tex graphviz
We can also choose to display particular arrows using the
``index_set`` option::
sage: C = KirillovReshetikhinCrystal(['D',4,1], 2, 1)
sage: G = C.digraph(index_set=[1,3])
sage: len(G.edges())
20
sage: view(G, pdflatex=True, tightpage=True) #optional - dot2tex graphviz
TODO: add more tests
"""
from sage.graphs.all import DiGraph
from sage.categories.highest_weight_crystals import HighestWeightCrystals
d = {}
if self in HighestWeightCrystals:
f = lambda (u,v,label): ({})
else:
f = lambda (u,v,label): ({"backward":label ==0})
# Parse optional arguments
if subset is None:
subset = self
if index_set is None:
index_set = self.index_set()
for x in subset:
d[x] = {}
for i in index_set:
child = x.f(i)
if child is None or child not in subset:
continue
d[x][child]=i
G = DiGraph(d)
if have_dot2tex():
G.set_latex_options(format="dot2tex",
edge_labels = True,
color_by_label = self.cartan_type()._index_set_coloring,
edge_options = f)
return G
def run(self, verbose=False, build_graph=False):
"""
Run the bijection from rigged configurations to tensor product of KR
tableaux for type `B_n^{(1)}`.
INPUT:
- ``verbose`` -- (default: ``False``) display each step in the
bijection
- ``build_graph`` -- (default: ``False``) build the graph of each
step of the bijection
EXAMPLES::
sage: RC = RiggedConfigurations(['B', 3, 1], [[2, 1]])
sage: from sage.combinat.rigged_configurations.bij_type_B import RCToKRTBijectionTypeB
sage: RCToKRTBijectionTypeB(RC(partition_list=[[1],[1,1],[1]])).run()
[[3], [0]]
sage: RC = RiggedConfigurations(['B', 3, 1], [[3, 1]])
sage: x = RC(partition_list=[[],[1],[1]])
sage: RCToKRTBijectionTypeB(x).run()
[[1], [3], [-2]]
sage: bij = RCToKRTBijectionTypeB(x)
sage: bij.run(build_graph=True)
[[1], [3], [-2]]
sage: bij._graph
Digraph on 6 vertices
"""
from sage.combinat.crystals.letters import CrystalOfLetters
letters = CrystalOfLetters(self.rigged_con.parent()._cartan_type.classical())
# This is technically bad, but because the first thing we do is append
# an empty list to ret_crystal_path, we correct this. We do it this
# way so that we do not have to remove an empty list after the
# bijection has been performed.
ret_crystal_path = []
for dim in self.rigged_con.parent().dims:
ret_crystal_path.append([])
# Check to see if we are a spinor
if dim[0] == self.n:
# Perform the spinor bijection by converting to type A_{2n-1}^{(2)}
# doing the bijection there and pulling back
from sage.combinat.rigged_configurations.bij_type_A2_odd import RCToKRTBijectionTypeA2Odd
from sage.combinat.rigged_configurations.rigged_configurations import RiggedConfigurations
from sage.combinat.rigged_configurations.rigged_partition import RiggedPartition, RiggedPartitionTypeB
# Convert to a type A_{2n-1}^{(2)} RC
RC = RiggedConfigurations(['A', 2*self.n-1, 2], self.cur_dims)
if verbose:
print("====================")
print(repr(RC(*self.cur_partitions, use_vacancy_numbers=True)))
print("--------------------")
print(ret_crystal_path)
print("--------------------\n")
print("Applying doubling map\n")
# Convert the n-th partition into a regular rigged partition
self.cur_partitions[-1] = RiggedPartition(self.cur_partitions[-1]._list,
self.cur_partitions[-1].rigging,
self.cur_partitions[-1].vacancy_numbers)
bij = RCToKRTBijectionTypeA2Odd(RC(*self.cur_partitions, use_vacancy_numbers=True))
for i in range(len(self.cur_dims)):
if bij.cur_dims[i][0] != self.n:
bij.cur_dims[i][1] *= 2
for i in range(self.n-1):
for j in range(len(bij.cur_partitions[i])):
bij.cur_partitions[i]._list[j] *= 2
bij.cur_partitions[i].rigging[j] *= 2
bij.cur_partitions[i].vacancy_numbers[j] *= 2
if build_graph:
y = self.rigged_con.parent()(*[x._clone() for x in self.cur_partitions], use_vacancy_numbers=True)
self._graph.append([self._graph[-1][1], (y, len(self._graph)), '2x'])
# Perform the type A_{2n-1}^{(2)} bijection
# Iterate over each column
for dummy_var in range(dim[1]):
# Split off a new column if necessary
if bij.cur_dims[0][1] > 1:
bij.cur_dims[0][1] -= 1
bij.cur_dims.insert(0, [dim[0], 1])
# Perform the corresponding splitting map on rigged configurations
# All it does is update the vacancy numbers on the RC side
for a in range(self.n):
bij._update_vacancy_numbers(a)
if build_graph:
y = self.rigged_con.parent()(*[x._clone() for x in self.cur_partitions], use_vacancy_numbers=True)
self._graph.append([self._graph[-1][1], (y, len(self._graph)), 'ls'])
while bij.cur_dims[0][0]: # > 0:
if verbose:
print("====================")
print(repr(RC(*bij.cur_partitions, use_vacancy_numbers=True)))
print("--------------------")
print(ret_crystal_path)
print("--------------------\n")
ht = bij.cur_dims[0][0]
bij.cur_dims[0][0] = bij._next_index(ht)
b = bij.next_state(ht)
# Make sure we have a crystal letter
ret_crystal_path[-1].append(letters(b)) # Append the rank
if build_graph:
y = self.rigged_con.parent()(*[x._clone() for x in self.cur_partitions], use_vacancy_numbers=True)
self._graph.append([self._graph[-1][1], (y, len(self._graph)), letters(b)])
bij.cur_dims.pop(0) # Pop off the leading column
self.cur_dims.pop(0) # Pop off the spin rectangle
self.cur_partitions = bij.cur_partitions
# Convert the n-th partition back into the special type B one
self.cur_partitions[-1] = RiggedPartitionTypeB(self.cur_partitions[-1])
# Convert back to a type B_n^{(1)}
if verbose:
print("====================")
print(repr(self.rigged_con.parent()(*bij.cur_partitions, use_vacancy_numbers=True)))
print("--------------------")
print(ret_crystal_path)
print("--------------------\n")
print("Applying halving map\n")
for i in range(self.n-1):
for j in range(len(self.cur_partitions[i])):
self.cur_partitions[i]._list[j] //= 2
self.cur_partitions[i].rigging[j] //= 2
self.cur_partitions[i].vacancy_numbers[j] //= 2
if build_graph:
y = self.rigged_con.parent()(*[x._clone() for x in self.cur_partitions], use_vacancy_numbers=True)
self._graph.append([self._graph[-1][1], (y, len(self._graph)), '1/2x'])
else:
# Perform the regular type B_n^{(1)} bijection
# Iterate over each column
for dummy_var in range(dim[1]):
# Split off a new column if necessary
if self.cur_dims[0][1] > 1:
if verbose:
print("====================")
print(repr(self.rigged_con.parent()(*self.cur_partitions, use_vacancy_numbers=True)))
print("--------------------")
print(ret_crystal_path)
print("--------------------\n")
print("Applying column split")
self.cur_dims[0][1] -= 1
self.cur_dims.insert(0, [dim[0], 1])
# Perform the corresponding splitting map on rigged configurations
# All it does is update the vacancy numbers on the RC side
for a in range(self.n):
self._update_vacancy_numbers(a)
if build_graph:
y = self.rigged_con.parent()(*[x._clone() for x in self.cur_partitions], use_vacancy_numbers=True)
self._graph.append([self._graph[-1][1], (y, len(self._graph)), '2x'])
while self.cur_dims[0][0]: #> 0:
if verbose:
print("====================")
print(repr(self.rigged_con.parent()(*self.cur_partitions, use_vacancy_numbers=True)))
print("--------------------")
print(ret_crystal_path)
print("--------------------\n")
self.cur_dims[0][0] -= 1 # This takes care of the indexing
b = self.next_state(self.cur_dims[0][0])
# Make sure we have a crystal letter
ret_crystal_path[-1].append(letters(b)) # Append the rank
if build_graph:
y = self.rigged_con.parent()(*[x._clone() for x in self.cur_partitions], use_vacancy_numbers=True)
self._graph.append([self._graph[-1][1], (y, len(self._graph)), letters(b)])
self.cur_dims.pop(0) # Pop off the leading column
if build_graph:
self._graph.pop(0) # Remove the dummy at the start
from sage.graphs.digraph import DiGraph
from sage.graphs.dot2tex_utils import have_dot2tex
self._graph = DiGraph(self._graph)
if have_dot2tex():
self._graph.set_latex_options(format="dot2tex", edge_labels=True)
return self.KRT(pathlist=ret_crystal_path)
def run(self, verbose=False, build_graph=False):
"""
Run the bijection from rigged configurations to tensor product of KR
tableaux.
INPUT:
- ``verbose`` -- (default: ``False``) display each step in the
bijection
- ``build_graph`` -- (default: ``False``) build the graph of each
step of the bijection
EXAMPLES::
sage: RC = RiggedConfigurations(['A', 4, 1], [[2, 1]])
sage: x = RC(partition_list=[[1],[1],[1],[1]])
sage: from sage.combinat.rigged_configurations.bij_type_A import RCToKRTBijectionTypeA
sage: RCToKRTBijectionTypeA(x).run()
[[2], [5]]
sage: bij = RCToKRTBijectionTypeA(x)
sage: bij.run(build_graph=True)
[[2], [5]]
sage: bij._graph
Digraph on 3 vertices
"""
from sage.combinat.crystals.letters import CrystalOfLetters
letters = CrystalOfLetters(self.rigged_con.parent()._cartan_type.classical())
# This is technically bad, but because the first thing we do is append
# an empty list to ret_crystal_path, we correct this. We do it this
# way so that we do not have to remove an empty list after the
# bijection has been performed.
ret_crystal_path = []
for dim in self.rigged_con.parent().dims:
ret_crystal_path.append([])
# Iterate over each column
for dummy_var in range(dim[1]):
# Split off a new column if necessary
if self.cur_dims[0][1] > 1:
if verbose:
print("====================")
print(repr(self.rigged_con.parent()(*self.cur_partitions, use_vacancy_numbers=True)))
print("--------------------")
print(ret_crystal_path)
print("--------------------\n")
print("Applying column split")
self.cur_dims[0][1] -= 1
self.cur_dims.insert(0, [dim[0], 1])
# Perform the corresponding splitting map on rigged configurations
# All it does is update the vacancy numbers on the RC side
for a in range(self.n):
self._update_vacancy_numbers(a)
if build_graph:
y = self.rigged_con.parent()(*[x._clone() for x in self.cur_partitions], use_vacancy_numbers=True)
self._graph.append([self._graph[-1][1], (y, len(self._graph)), 'ls'])
while self.cur_dims[0][0] > 0:
if verbose:
print("====================")
print(repr(self.rigged_con.parent()(*self.cur_partitions, use_vacancy_numbers=True)))
print("--------------------")
print(ret_crystal_path)
print("--------------------\n")
self.cur_dims[0][0] -= 1 # This takes care of the indexing
b = self.next_state(self.cur_dims[0][0])
# Make sure we have a crystal letter
ret_crystal_path[-1].append(letters(b)) # Append the rank
if build_graph:
y = self.rigged_con.parent()(*[x._clone() for x in self.cur_partitions], use_vacancy_numbers=True)
self._graph.append([self._graph[-1][1], (y, len(self._graph)), letters(b)])
self.cur_dims.pop(0) # Pop off the leading column
if build_graph:
self._graph.pop(0) # Remove the dummy at the start
from sage.graphs.digraph import DiGraph
from sage.graphs.dot2tex_utils import have_dot2tex
self._graph = DiGraph(self._graph)
if have_dot2tex():
self._graph.set_latex_options(format="dot2tex", edge_labels=True)
# Basic check to make sure we end with the empty configuration
#tot_len = sum([len(rp) for rp in self.cur_partitions])
#if tot_len != 0:
# print "Invalid bijection end for:"
# print self.rigged_con
# print "-----------------------"
# print self.cur_partitions
# raise ValueError("Invalid bijection end")
return self.KRT(pathlist=ret_crystal_path)
def run(self, verbose=False, build_graph=False):
"""
Run the bijection from rigged configurations to tensor product of KR
tableaux for type `D_n^{(1)}`.
INPUT:
- ``verbose`` -- (default: ``False``) display each step in the
bijection
- ``build_graph`` -- (default: ``False``) build the graph of each
step of the bijection
EXAMPLES::
sage: RC = RiggedConfigurations(['D', 4, 1], [[2, 1]])
sage: x = RC(partition_list=[[1],[1],[1],[1]])
sage: from sage.combinat.rigged_configurations.bij_type_D import RCToKRTBijectionTypeD
sage: RCToKRTBijectionTypeD(x).run()
[[2], [-3]]
sage: bij = RCToKRTBijectionTypeD(x)
sage: bij.run(build_graph=True)
[[2], [-3]]
sage: bij._graph
Digraph on 3 vertices
"""
from sage.combinat.crystals.letters import CrystalOfLetters
letters = CrystalOfLetters(self.rigged_con.parent()._cartan_type.classical())
# This is technically bad, but because the first thing we do is append
# an empty list to ret_crystal_path, we correct this. We do it this
# way so that we do not have to remove an empty list after the
# bijection has been performed.
ret_crystal_path = []
for dim in self.rigged_con.parent().dims:
ret_crystal_path.append([])
# Iterate over each column
for dummy_var in range(dim[1]):
# Split off a new column if necessary
if self.cur_dims[0][1] > 1:
self.cur_dims[0][1] -= 1
self.cur_dims.insert(0, [dim[0], 1])
# Perform the corresponding splitting map on rigged configurations
# All it does is update the vacancy numbers on the RC side
for a in range(self.n):
self._update_vacancy_numbers(a)
if build_graph:
y = self.rigged_con.parent()(*[x._clone() for x in self.cur_partitions], use_vacancy_numbers=True)
self._graph.append([self._graph[-1][1], (y, len(self._graph)), 'ls'])
# Check to see if we are a spinor
if dim[0] >= self.n - 1:
if verbose:
print("====================")
print(repr(self.rigged_con.parent()(*self.cur_partitions, use_vacancy_numbers=True)))
print("--------------------")
print(ret_crystal_path)
print("--------------------\n")
print("Applying doubling map")
self.doubling_map()
if build_graph:
y = self.rigged_con.parent()(*[x._clone() for x in self.cur_partitions], use_vacancy_numbers=True)
self._graph.append([self._graph[-1][1], (y, len(self._graph)), '2x'])
if dim[0] == self.n - 1:
if verbose:
print("====================")
print(repr(self.rigged_con.parent()(*self.cur_partitions, use_vacancy_numbers=True)))
print("--------------------")
print(ret_crystal_path)
print("--------------------\n")
b = self.next_state(self.n)
if b == self.n:
b = -self.n
ret_crystal_path[-1].append(letters(b)) # Append the rank
if build_graph:
y = self.rigged_con.parent()(*[x._clone() for x in self.cur_partitions], use_vacancy_numbers=True)
self._graph.append([self._graph[-1][1], (y, len(self._graph)), letters(b)])
while self.cur_dims[0][0] > 0:
if verbose:
print("====================")
print(repr(self.rigged_con.parent()(*self.cur_partitions, use_vacancy_numbers=True)))
print("--------------------")
print(ret_crystal_path)
print("--------------------\n")
self.cur_dims[0][0] -= 1 # This takes care of the indexing
b = self.next_state(self.cur_dims[0][0])
# Corrections for spinor
if dim[0] == self.n and b == -self.n \
and self.cur_dims[0][0] == self.n - 1:
b = -(self.n-1)
# Make sure we have a crystal letter
ret_crystal_path[-1].append(letters(b)) # Append the rank
if build_graph:
y = self.rigged_con.parent()(*[x._clone() for x in self.cur_partitions], use_vacancy_numbers=True)
self._graph.append([self._graph[-1][1], (y, len(self._graph)), letters(b)])
self.cur_dims.pop(0) # Pop off the leading column
# Check to see if we were a spinor
if dim[0] >= self.n-1:
if verbose:
print("====================")
print(repr(self.rigged_con.parent()(*self.cur_partitions, use_vacancy_numbers=True)))
print("--------------------")
print(ret_crystal_path)
print("--------------------\n")
print("Applying halving map")
self.halving_map()
if build_graph:
y = self.rigged_con.parent()(*[x._clone() for x in self.cur_partitions], use_vacancy_numbers=True)
self._graph.append([self._graph[-1][1], (y, len(self._graph)), '1/2x'])
if build_graph:
self._graph.pop(0) # Remove the dummy at the start
from sage.graphs.digraph import DiGraph
from sage.graphs.dot2tex_utils import have_dot2tex
self._graph = DiGraph(self._graph, format="list_of_edges")
if have_dot2tex():
self._graph.set_latex_options(format="dot2tex", edge_labels=True)
return self.KRT(pathlist=ret_crystal_path)
def run(self, verbose=False, build_graph=False):
"""
Run the bijection from rigged configurations to tensor product of KR
tableaux for type `D_n^{(1)}`.
INPUT:
- ``verbose`` -- (default: ``False``) display each step in the
bijection
- ``build_graph`` -- (default: ``False``) build the graph of each
step of the bijection
EXAMPLES::
sage: RC = RiggedConfigurations(['D', 4, 1], [[2, 1]])
sage: x = RC(partition_list=[[1],[1],[1],[1]])
sage: from sage.combinat.rigged_configurations.bij_type_D import RCToKRTBijectionTypeD
sage: RCToKRTBijectionTypeD(x).run()
[[2], [-3]]
sage: bij = RCToKRTBijectionTypeD(x)
sage: bij.run(build_graph=True)
[[2], [-3]]
sage: bij._graph
Digraph on 3 vertices
"""
from sage.combinat.crystals.letters import CrystalOfLetters
letters = CrystalOfLetters(
self.rigged_con.parent()._cartan_type.classical())
# This is technically bad, but because the first thing we do is append
# an empty list to ret_crystal_path, we correct this. We do it this
# way so that we do not have to remove an empty list after the
# bijection has been performed.
ret_crystal_path = []
for dim in self.rigged_con.parent().dims:
ret_crystal_path.append([])
# Iterate over each column
for dummy_var in range(dim[1]):
# Split off a new column if necessary
if self.cur_dims[0][1] > 1:
self.cur_dims[0][1] -= 1
self.cur_dims.insert(0, [dim[0], 1])
# Perform the corresponding splitting map on rigged configurations
# All it does is update the vacancy numbers on the RC side
for a in range(self.n):
self._update_vacancy_numbers(a)
if build_graph:
y = self.rigged_con.parent()(
*[x._clone() for x in self.cur_partitions],
use_vacancy_numbers=True)
self._graph.append(
[self._graph[-1][1], (y, len(self._graph)), 'ls'])
# Check to see if we are a spinor
if dim[0] >= self.n - 1:
if verbose:
print("====================")
print(
repr(self.rigged_con.parent()(
*self.cur_partitions,
use_vacancy_numbers=True)))
print("--------------------")
print(ret_crystal_path)
print("--------------------\n")
print("Applying doubling map")
self.doubling_map()
if build_graph:
y = self.rigged_con.parent()(
*[x._clone() for x in self.cur_partitions],
use_vacancy_numbers=True)
self._graph.append(
[self._graph[-1][1], (y, len(self._graph)), '2x'])
if dim[0] == self.n - 1:
if verbose:
print("====================")
print(
repr(self.rigged_con.parent()(
*self.cur_partitions,
use_vacancy_numbers=True)))
print("--------------------")
print(ret_crystal_path)
print("--------------------\n")
b = self.next_state(self.n)
if b == self.n:
b = -self.n
ret_crystal_path[-1].append(
letters(b)) # Append the rank
if build_graph:
y = self.rigged_con.parent()(
*[x._clone() for x in self.cur_partitions],
use_vacancy_numbers=True)
self._graph.append([
self._graph[-1][1], (y, len(self._graph)),
letters(b)
])
while self.cur_dims[0][0] > 0:
if verbose:
print("====================")
print(
repr(self.rigged_con.parent()(
*self.cur_partitions,
use_vacancy_numbers=True)))
print("--------------------")
print(ret_crystal_path)
print("--------------------\n")
self.cur_dims[0][0] -= 1 # This takes care of the indexing
b = self.next_state(self.cur_dims[0][0])
# Corrections for spinor
if dim[0] == self.n and b == -self.n \
and self.cur_dims[0][0] == self.n - 1:
b = -(self.n - 1)
# Make sure we have a crystal letter
ret_crystal_path[-1].append(letters(b)) # Append the rank
if build_graph:
y = self.rigged_con.parent()(
*[x._clone() for x in self.cur_partitions],
use_vacancy_numbers=True)
self._graph.append([
self._graph[-1][1], (y, len(self._graph)),
letters(b)
])
self.cur_dims.pop(0) # Pop off the leading column
# Check to see if we were a spinor
if dim[0] >= self.n - 1:
if verbose:
print("====================")
print(
repr(self.rigged_con.parent()(
*self.cur_partitions,
use_vacancy_numbers=True)))
print("--------------------")
print(ret_crystal_path)
print("--------------------\n")
print("Applying halving map")
self.halving_map()
if build_graph:
y = self.rigged_con.parent()(
*[x._clone() for x in self.cur_partitions],
use_vacancy_numbers=True)
self._graph.append([
self._graph[-1][1], (y, len(self._graph)), '1/2x'
])
if build_graph:
self._graph.pop(0) # Remove the dummy at the start
from sage.graphs.digraph import DiGraph
from sage.graphs.dot2tex_utils import have_dot2tex
self._graph = DiGraph(self._graph, format="list_of_edges")
if have_dot2tex():
self._graph.set_latex_options(format="dot2tex",
edge_labels=True)
return self.KRT(pathlist=ret_crystal_path)
def digraph(self, subset=None, index_set=None):
"""
Returns the DiGraph associated to ``self``.
INPUT:
- ``subset`` -- (Optional) A subset of vertices for
which the digraph should be constructed
- ``index_set`` -- (Optional) The index set to draw arrows
EXAMPLES::
sage: C = Crystals().example(5)
sage: C.digraph()
Digraph on 6 vertices
The edges of the crystal graph are by default colored using blue for edge 1, red for edge 2,
and green for edge 3::
sage: C = Crystals().example(3)
sage: G = C.digraph()
sage: view(G, pdflatex=True, tightpage=True) #optional - dot2tex graphviz
One may also overwrite the colors::
sage: C = Crystals().example(3)
sage: G = C.digraph()
sage: G.set_latex_options(color_by_label = {1:"red", 2:"purple", 3:"blue"})
sage: view(G, pdflatex=True, tightpage=True) #optional - dot2tex graphviz
Or one may add colors to yet unspecified edges::
sage: C = Crystals().example(4)
sage: G = C.digraph()
sage: C.cartan_type()._index_set_coloring[4]="purple"
sage: view(G, pdflatex=True, tightpage=True) #optional - dot2tex graphviz
Here is an example of how to take the top part up to a given depth of an infinite dimensional
crystal::
sage: C = CartanType(['C',2,1])
sage: La = C.root_system().weight_lattice().fundamental_weights()
sage: T = crystals.HighestWeight(La[0])
sage: S = T.subcrystal(max_depth=3)
sage: G = T.digraph(subset=S); G
Digraph on 5 vertices
sage: sorted(G.vertices(), key=str)
[(-Lambda[0] + 2*Lambda[1] - delta,),
(1/2*Lambda[0] + Lambda[1] - Lambda[2] - 1/2*delta, -1/2*Lambda[0] + Lambda[1] - 1/2*delta),
(1/2*Lambda[0] - Lambda[1] + Lambda[2] - 1/2*delta, -1/2*Lambda[0] + Lambda[1] - 1/2*delta),
(Lambda[0] - 2*Lambda[1] + 2*Lambda[2] - delta,),
(Lambda[0],)]
Here is a way to construct a picture of a Demazure crystal using
the ``subset`` option::
sage: B = crystals.Tableaux(['A',2], shape=[2,1])
sage: C = CombinatorialFreeModule(QQ,B)
sage: t = B.highest_weight_vector()
sage: b = C(t)
sage: D = B.demazure_operator(b,[2,1]); D
B[[[1, 1], [2]]] + B[[[1, 2], [2]]] + B[[[1, 3], [2]]] + B[[[1, 1], [3]]] + B[[[1, 3], [3]]]
sage: G = B.digraph(subset=D.support())
sage: G.vertices()
[[[1, 1], [2]], [[1, 2], [2]], [[1, 3], [2]], [[1, 1], [3]], [[1, 3], [3]]]
sage: view(G, pdflatex=True, tightpage=True) #optional - dot2tex graphviz
We can also choose to display particular arrows using the
``index_set`` option::
sage: C = crystals.KirillovReshetikhin(['D',4,1], 2, 1)
sage: G = C.digraph(index_set=[1,3])
sage: len(G.edges())
20
sage: view(G, pdflatex=True, tightpage=True) #optional - dot2tex graphviz
TODO: add more tests
"""
from sage.graphs.all import DiGraph
from sage.categories.highest_weight_crystals import HighestWeightCrystals
d = {}
if self in HighestWeightCrystals:
f = lambda u_v_label: ({})
else:
f = lambda u_v_label: ({"backward": u_v_label[2] == 0})
# Parse optional arguments
if subset is None:
subset = self
if index_set is None:
index_set = self.index_set()
for x in subset:
d[x] = {}
for i in index_set:
child = x.f(i)
if child is None or child not in subset:
continue
d[x][child]=i
G = DiGraph(d)
if have_dot2tex():
G.set_latex_options(format="dot2tex",
edge_labels = True,
color_by_label = self.cartan_type()._index_set_coloring,
edge_options = f)
return G
