Use cpdef's union and find

Typecast `union` as `void` to a-void the "C struct/union cannot be declared cpdef" error.

src/sage/combinat/bijectionist.py

@@ -614,7 +614,7 @@ def set_constant_blocks(self, P):
         P = sorted(self._sorter["A"](p) for p in P)
         for p in P:
             for a in p:
-                self._P._union(p[0], a)
+                self._P.union(p[0], a)
 
         self._compute_possible_block_values()
 
@@ -1678,7 +1678,7 @@ def merge_until_split():
                         try:
                             solution = different_values(tP[i1], tP[i2])
                         except StopIteration:
-                            tmp_P._union(tP[i1], tP[i2])
+                            tmp_P.union(tP[i1], tP[i2])
                             if len(multiple_preimages[tZ]) == 2:
                                 del multiple_preimages[tZ]
                             else:
@@ -1772,14 +1772,14 @@ def possible_values(self, p=None, optimal=False):
         # convert input to set of block representatives
         blocks = set()
         if p in self._A:
-            blocks.add(self._P._find(p))
+            blocks.add(self._P.find(p))
         elif isinstance(p, list):  # TODO: this looks very brittle
             for p1 in p:
                 if p1 in self._A:
-                    blocks.add(self._P._find(p1))
+                    blocks.add(self._P.find(p1))
                 elif isinstance(p1, list):
                     for p2 in p1:
-                        blocks.add(self._P._find(p2))
+                        blocks.add(self._P.find(p2))
 
         if optimal:
             if self._bmilp is None:
@@ -1941,9 +1941,9 @@ def _find_counterexample(self, P, s0, d, on_blocks):
 
             # try to find a solution which has a different
             # subdistribution on d than s0
-            z_in_d = sum(d[p] * bmilp._x[self._P._find(p), z]
+            z_in_d = sum(d[p] * bmilp._x[self._P.find(p), z]
                          for p in P
-                         if z in self._possible_block_values[self._P._find(p)])
+                         if z in self._possible_block_values[self._P.find(p)])
 
             # it is sufficient to require that z occurs less often as
             # a value among {a | d[a] == 1} than it does in
@@ -2191,14 +2191,14 @@ def _preprocess_intertwining_relations(self):
             # the blocks of the elements of the preimage
             updated_images = defaultdict(set)  # (p_1,...,p_k) to {a_1,....}
             for a_tuple, image_set in images.items():
-                representatives = tuple(P._find(a) for a in a_tuple)
+                representatives = tuple(P.find(a) for a in a_tuple)
                 updated_images[representatives].update(image_set)
 
             # merge blocks
             for a_tuple, image_set in updated_images.items():
                 image = image_set.pop()
                 while image_set:
-                    P._union(image, image_set.pop())
+                    P.union(image, image_set.pop())
                     something_changed = True
                 # we keep a representative
                 image_set.add(image)
@@ -2525,7 +2525,7 @@ def __init__(self, bijectionist: Bijectionist, solutions=None):
         self._solution_cache = []
         if solutions is not None:
             for solution in solutions:
-                self._add_solution({(P._find(a), z): value
+                self._add_solution({(P.find(a), z): value
                                     for (a, z), value in solution.items()})
 
     def show(self, variables=True):
@@ -2813,7 +2813,7 @@ def add_alpha_beta_constraints(self):
         Z_dict = {z: i for i, z in enumerate(Z)}
 
         for a in self._bijectionist._A:
-            p = self._bijectionist._P._find(a)
+            p = self._bijectionist._P.find(a)
             for z in self._bijectionist._possible_block_values[p]:
                 w_index = W_dict[self._bijectionist._alpha(a)]
                 z_index = Z_dict[z]
@@ -2867,7 +2867,7 @@ def add_distribution_constraints(self):
             tA_sum = [zero] * len(Z_dict)
             tZ_sum = [zero] * len(Z_dict)
             for a in tA:
-                p = self._bijectionist._P._find(a)
+                p = self._bijectionist._P.find(a)
                 for z in self._bijectionist._possible_block_values[p]:
                     tA_sum[Z_dict[z]] += self._x[p, z]
             for z in tZ:
@@ -2940,8 +2940,8 @@ def add_intertwining_relation_constraints(self):
                     continue
                 a = pi_rho.pi(*a_tuple)
                 if a in A:
-                    p_tuple = tuple(P._find(a) for a in a_tuple)
-                    p = P._find(a)
+                    p_tuple = tuple(P.find(a) for a in a_tuple)
+                    p = P.find(a)
                     if (p_tuple, p) not in pi_blocks:
                         pi_blocks.add((p_tuple, p))
                         for z_tuple in itertools.product(*[tZ[p] for p in p_tuple]):
@@ -3008,7 +3008,7 @@ def add_quadratic_relation_constraints(self):
                 z0 = phi(p)
                 assert all(phi(a) == z0 for a in block), "phi must be constant on the block %s" % block
                 for z in self._bijectionist._possible_block_values[p]:
-                    p0 = P._find(psi(z))
+                    p0 = P.find(psi(z))
                     if z0 in self._bijectionist._possible_block_values[p0]:
                         c = self._x[p, z] - self._x[p0, z0]
                         if c.is_zero():
@@ -3046,7 +3046,7 @@ def add_homomesic_constraints(self):
         tZ = self._bijectionist._possible_block_values
 
         def sum_q(q):
-            return sum(sum(z * self._x[P._find(a), z] for z in tZ[P._find(a)])
+            return sum(sum(z * self._x[P.find(a), z] for z in tZ[P.find(a)])
                        for a in q)
         q0 = Q[0]
         v0 = sum_q(q0)

src/sage/combinat/designs/designs_pyx.pyx

@@ -492,7 +492,7 @@ def is_group_divisible_design(groups,blocks,v,G=None,K=None,lambd=1,verbose=Fals
         for i in range(n):
             for j in range(i + 1, n):
                 if matrix[i * n + j] == 0:
-                    groups._union(i, j)
+                    groups.union(i, j)
         groups = list(groups.root_to_elements_dict().values())
 
     # Group sizes are element of G

src/sage/combinat/designs/incidence_structures.py

@@ -1029,7 +1029,7 @@ def is_connected(self) -> bool:
         for B in self._blocks:
             x = B[0]
             for i in range(1, len(B)):
-                D._union(x, B[i])
+                D.union(x, B[i])
         return D.number_of_subsets() == 1
 
     def is_simple(self) -> bool:

src/sage/combinat/posets/hasse_diagram.py

@@ -3230,36 +3230,36 @@ def fill_to_interval(S):
                 if part:  # Skip empty parts
                     c = part[0]
                     for e in fill_to_interval(part):
-                        cong._union(e, c)
+                        cong.union(e, c)
             t = cong.number_of_subsets()
 
             # Following is needed for cases like
             # posets.BooleanLattice(3).congruence([(0,1), (0,2), (0,4)])
             for c in list(cong):
                 r = c[0]
                 for v in fill_to_interval(c):
-                    cong._union(r, v)
+                    cong.union(r, v)
 
-        todo = {cong._find(e) for part in parts for e in part}
+        todo = {cong.find(e) for part in parts for e in part}
 
         while todo:
 
             # First check if we should stop now.
             for a, b in stop_pairs:
-                if cong._find(a) == cong._find(b):
+                if cong.find(a) == cong.find(b):
                     return None
 
             # We take one block and try to find as big interval
             # as possible to unify as a new block by the quadrilateral
             # argument.
-            block = sorted(cong.root_to_elements_dict()[cong._find(todo.pop())])
+            block = sorted(cong.root_to_elements_dict()[cong.find(todo.pop())])
 
             b = block[-1]
             for a in block:  # Quadrilateral up
                 for c in self.neighbor_out_iterator(a):
                     if c not in block:
                         d = jn[c, b]
-                        if cong._find(d) != cong._find(c):
+                        if cong.find(d) != cong.find(c):
                             break
                 else:
                     continue
@@ -3271,7 +3271,7 @@ def fill_to_interval(S):
                     for d in self.neighbor_in_iterator(b):
                         if d not in block:
                             c = mt[d, a]
-                            if cong._find(c) != cong._find(d):
+                            if cong.find(c) != cong.find(d):
                                 break
                     else:
                         continue
@@ -3289,10 +3289,10 @@ def fill_to_interval(S):
             # recursive process. In particular it may also combine to
             # [a, b] block we just used.
             while c is not None:
-                newblock = cong._find(c)
+                newblock = cong.find(c)
                 for i in self.interval(c, d):
-                    cong._union(newblock, i)
-                C = cong.root_to_elements_dict()[cong._find(newblock)]
+                    cong.union(newblock, i)
+                C = cong.root_to_elements_dict()[cong.find(newblock)]
                 mins = [i for i in C if all(i_ not in C for i_ in self.neighbor_in_iterator(i))]
                 maxs = [i for i in C if all(i_ not in C for i_ in self.neighbor_out_iterator(i))]
                 c = None  # To stop loop, if this is not changed below.
@@ -3305,7 +3305,7 @@ def fill_to_interval(S):
                         d = jn[d, m]
 
             # This removes duplicates from todo.
-            todo = {cong._find(x) for x in todo}
+            todo = {cong.find(x) for x in todo}
 
         return cong
 

src/sage/combinat/set_partition.py

@@ -2356,7 +2356,7 @@ def from_arcs(self, arcs, n):
         """
         P = DisjointSet(range(1, n + 1))
         for i, j in arcs:
-            P._union(i, j)
+            P.union(i, j)
         return self.element_class(self, P)
 
     def from_rook_placement_gamma(self, rooks, n):

src/sage/combinat/words/finite_word.py

@@ -5201,16 +5201,16 @@ def overlap_partition(self, other, delay=0, p=None, involution=None):
         S = zip(islice(self, int(delay), None), other)
         if involution is None:
             for a, b in S:
-                p._union(a, b)
+                p.union(a, b)
         elif isinstance(involution, WordMorphism):
             for a, b in S:
-                p._union(a, b)
+                p.union(a, b)
                 # take the first letter of the word
-                p._union(involution(a)[0], involution(b)[0])
+                p.union(involution(a)[0], involution(b)[0])
         elif callable(involution):
             for a, b in S:
-                p._union(a, b)
-                p._union(involution(a), involution(b))
+                p.union(a, b)
+                p.union(involution(a), involution(b))
         else:
             raise TypeError("involution (=%s) must be callable" % involution)
         return p

src/sage/graphs/connectivity.pyx

@@ -2540,7 +2540,7 @@ def spqr_tree(G, algorithm="Hopcroft_Tarjan", solver=None, verbose=0,
         if cocycles_count[fe] == 2 and len(virtual_edge_to_cycles[fe]) == 2:
             # This virtual edge is only between 2 cycles
             C1, C2 = virtual_edge_to_cycles[fe]
-            DS._union(C1, C2)
+            DS.union(C1, C2)
             cycles_list[C1].delete_edge(fe)
             cycles_list[C2].delete_edge(fe)
             cocycles_count[fe] -= 2

src/sage/graphs/generators/random.py

@@ -576,12 +576,12 @@ def RandomBlockGraph(m, k, kmax=None, incidence_structure=False, seed=None):
         # structure to keep a unique identifier per merged vertices
         DS = DisjointSet([i for u in B for i in B[u]])
         for u, v in T.edges(sort=True, labels=0):
-            DS._union(choice(B[u]), choice(B[v]))
+            DS.union(choice(B[u]), choice(B[v]))
 
         # We relabel vertices in the range [0, m*(k-1)] and build the incidence
         # structure
         new_label = {root: i for i, root in enumerate(DS.root_to_elements_dict())}
-        IS = [[new_label[DS._find(v)] for v in B[u]] for u in B]
+        IS = [[new_label[DS.find(v)] for v in B[u]] for u in B]
 
     if incidence_structure:
         return IS

src/sage/graphs/generic_graph.py

@@ -12657,11 +12657,11 @@ def contract_edges(self, edges):
         DS = DisjointSet(self.vertex_iterator())
 
         for u, v, label in edge_list:
-            DS._union(u, v)
+            DS.union(u, v)
 
         self.delete_edges(edge_list)
         edges_incident = []
-        vertices = [v for v in vertices if v != DS._find(v)]
+        vertices = [v for v in vertices if v != DS.find(v)]
         if self.is_directed():
             for v in vertices:
                 out_edges = self.edge_boundary([v])
@@ -12674,8 +12674,8 @@ def contract_edges(self, edges):
                 self.delete_vertex(v)
 
         for (u, v, label) in edges_incident:
-            root_u = DS._find(u)
-            root_v = DS._find(v)
+            root_u = DS.find(u)
+            root_v = DS.find(v)
             if root_v != root_u or self.allows_loops():
                 self.add_edge(root_u, root_v, label)
 

src/sage/graphs/graph_decompositions/modular_decomposition.py

@@ -456,7 +456,7 @@ def gamma_classes(graph):
             e = frozenset([v1, v])
             for vi in component[1:]:
                 ei = frozenset([vi, v])
-                pieces._union(e, ei)
+                pieces.union(e, ei)
     return {frozenset(chain.from_iterable(loe)): loe for loe in pieces}
 
 

src/sage/graphs/graph_decompositions/tree_decomposition.pyx

@@ -233,7 +233,7 @@ def is_valid_tree_decomposition(G, T):
         for Xi in X:
             for Xj in T.neighbor_iterator(Xi):
                 if Xj in X:
-                    D._union(Xi, Xj)
+                    D.union(Xi, Xj)
         if D.number_of_subsets() > 1:
             return False
 

src/sage/graphs/partial_cube.py

@@ -335,9 +335,9 @@ def is_partial_cube(G, certificate=False):
             if diff not in neighbors:
                 return fail
             neighbor = neighbors[diff]
-            unionfind._union(contracted.edge_label(v, w),
+            unionfind.union(contracted.edge_label(v, w),
                             contracted.edge_label(root, neighbor))
-            unionfind._union(contracted.edge_label(w, v),
+            unionfind.union(contracted.edge_label(w, v),
                             contracted.edge_label(neighbor, root))
             labeled.add_edge(v, w)
 
@@ -356,13 +356,13 @@ def is_partial_cube(G, certificate=False):
                 if vi == wi:
                     return fail
                 if newgraph.has_edge(vi, wi):
-                    unionfind._union(newgraph.edge_label(vi, wi), t)
+                    unionfind.union(newgraph.edge_label(vi, wi), t)
                 else:
                     newgraph.add_edge(vi, wi, t)
         contracted = newgraph
 
     # Make a digraph with edges labeled by the equivalence classes in unionfind
-    g = DiGraph({v: {w: unionfind._find((v, w)) for w in G[v]} for v in G})
+    g = DiGraph({v: {w: unionfind.find((v, w)) for w in G[v]} for v in G})
 
     # Associates to a vertex the token that acts on it, and check that
     # no two edges on a single vertex have the same label