Merge branch 'main' of https://github.com/COMSOC-Community/prefsampling

prefsampling/__init__.py

@@ -1,6 +1,6 @@
 __author__ = "Simon Rey and Stanisław Szufa"
 __email__ = "[email protected]"
-__version__ = "0.1.22"
+__version__ = "0.1.24"
 
 from enum import Enum
 from itertools import chain

prefsampling/ordinal/groupseparable.py

@@ -11,6 +11,8 @@
     schroeder_tree_brute_force,
     schroeder_tree_lescanne,
 )
+from prefsampling.tree.balanced import balanced_tree
+from prefsampling.tree.caterpillar import caterpillar_tree
 from prefsampling.inputvalidators import validate_num_voters_candidates
 from prefsampling.combinatorics import comb
 
@@ -36,15 +38,15 @@ class TreeSampler(Enum):
     Random Schröder trees sampled following Lescanne (2022)
     """
 
-    # CATERPILLAR = "Caterpillar Tree"
-    # """
-    # Caterpillar trees
-    # """
-    #
-    # BALANCED = "Balanced Tree"
-    # """
-    # Balanced trees
-    # """
+    CATERPILLAR = "Caterpillar Tree"
+    """
+    Caterpillar trees
+    """
+
+    BALANCED = "Balanced Tree"
+    """
+    Balanced trees
+    """
 
 
 @validate_num_voters_candidates
@@ -159,10 +161,10 @@ def group_separable(
             )
         else:
             raise ValueError("There is something weird with the tree_sampler value...")
-    # elif tree_sampler == TreeSampler.CATERPILLAR:
-    #     tree_root = caterpillar_tree(num_candidates)
-    # elif tree_sampler == TreeSampler.BALANCED:
-    #     tree_root = balanced_tree(num_candidates)
+    elif tree_sampler == TreeSampler.CATERPILLAR:
+        tree_root = caterpillar_tree(num_candidates)
+    elif tree_sampler == TreeSampler.BALANCED:
+        tree_root = balanced_tree(num_candidates)
     else:
         raise ValueError(
             "The `tree` argument needs to be one of the constant defined in the "
@@ -183,7 +185,7 @@ def group_separable(
     signatures = np.zeros((num_voters - 1, num_internal_nodes), dtype=bool)
     for r in range(num_internal_nodes):
         values_at_pos = rng.choice((True, False), size=num_voters - 1)
-        while r > 0 and not any(values_at_pos):
+        while r > 0 and not any(values_at_pos) and num_voters - 1 > 0:
             values_at_pos = rng.choice((True, False), size=num_voters - 1)
         for i in range(num_voters - 1):
             signatures[i][r] = values_at_pos[i]

prefsampling/ordinal/singlecrossing.py

@@ -134,13 +134,9 @@ def single_crossing(
         new_line[swap_indices[1]] = domain[line - 1][swap_indices[0]]
         domain.append(new_line)
 
-    votes = []
-    last_sampled_index = 0
-    votes.append(domain[0])
-    for i in range(1, num_voters):
-        index = rng.integers(last_sampled_index, domain_size)
-        votes.append(domain[index])
-        last_sampled_index = index
+    indeces = rng.integers(0, domain_size, num_voters)
+    indeces.sort()
+    votes = [domain[index] for index in indeces]
 
     return votes
 

prefsampling/tree/__init__.py

@@ -14,5 +14,5 @@
     "schroeder_tree_brute_force",
     "all_schroeder_tree",
     "caterpillar_tree",
-    "caterpillar_tree",
+    "balanced_tree",
 ]

prefsampling/tree/balanced.py

@@ -6,7 +6,7 @@
 from prefsampling.tree.node import Node
 
 
-def balanced_tree(num_leaves: int) -> Node:
+def balanced_tree(num_leaves: int, seed: int = None) -> Node:
     """
     Generates a balanced tree.
 
@@ -17,26 +17,20 @@ def balanced_tree(num_leaves: int) -> Node:
     """
     validate_int(num_leaves, "number of leaves", lower_bound=1)
     num_leaves = int(num_leaves)
-    root = Node("root")
-    ctr = 0
+    root = Node(0)
+    if num_leaves == 1:
+        return root
+    ctr = 1
 
     q = queue.Queue()
     q.put(root)
 
-    while q.qsize() * 2 < num_leaves:
+    while ctr < 2*num_leaves-1:
         tmp_root = q.get()
         for _ in range(2):
             inner_node = Node(ctr)
+            ctr += 1
             tmp_root.add_child(inner_node)
             q.put(inner_node)
-            ctr += 1
-
-    ctr = 0
-    while ctr < num_leaves:
-        tmp_root = q.get()
-        for _ in range(2):
-            node = Node(ctr)
-            tmp_root.add_child(node)
-            ctr += 1
 
     return root

prefsampling/tree/caterpillar.py

@@ -25,15 +25,17 @@ def caterpillar_tree(num_leaves: int, seed: int = None) -> Node:
 
     while num_leaves > 2:
         leaf = Node(ctr)
+        ctr += 1
         inner_node = Node(ctr)
+        ctr += 1
         tmp_root.add_child(leaf)
         tmp_root.add_child(inner_node)
         tmp_root = inner_node
         num_leaves -= 1
-        ctr += 1
 
     leaf_1 = Node(ctr)
-    leaf_2 = Node(ctr + 1)
+    ctr += 1
+    leaf_2 = Node(ctr)
     tmp_root.add_child(leaf_1)
     tmp_root.add_child(leaf_2)
 

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "flit_core.buildapi"
 
 [project]
 name = "prefsampling"
-version = "0.1.22"
+version = "0.1.24"
 description = "Algorithms to sample preferences of all kinds."
 authors = [
   { name = "Simon Rey", email = "[email protected]" },

tests/test_samplers/ordinal/test_ordinal_group_separable.py

@@ -13,6 +13,8 @@ def all_test_samplers_ordinal_group_separable():
         for tree_sampler in [
             TreeSampler.SCHROEDER,
             TreeSampler.SCHROEDER_LESCANNE,
+            TreeSampler.CATERPILLAR,
+            TreeSampler.BALANCED
         ]
     ]
 

tests/test_trees.py

@@ -62,8 +62,8 @@ def test_all_schroeder_trees(self):
             5: 45,
             6: 197,
             7: 903,
-            8: 4279,
-            9: 20793,
+            # 8: 4279,
+            # 9: 20793,
             # 10: 103049,
             # 11: 518859,
             # 12: 2646723