minor bug fixes

Author: szufix

mapel-elections/src/mapel/elections/cultures/group_separable.py

@@ -4,6 +4,7 @@
 def gs_mask(num_voters=None,
             num_candidates=None,
             tree_sampler=None,
+            seed=None,
             **kwargs):
 
     if type(tree_sampler) is str:
@@ -18,4 +19,4 @@ def gs_mask(num_voters=None,
     return pref_ordinal.group_separable(num_voters=num_voters,
                                         num_candidates=num_candidates,
                                         tree_sampler=tree_sampler,
-                                        **kwargs)
+                                        seed=seed)

mapel-elections/src/mapel/elections/cultures/guardians_plus.py

@@ -7,6 +7,7 @@
 
 # Auxiliary functions
 
+
 def distribute_in_matrix(n, m):
     if m == 0:
         return []
@@ -75,13 +76,13 @@ def generate_un_from_list(num_voters=None, num_candidates=None):
 
 
 def generate_un_from_matrix_votes(num_voters=None, num_candidates=None):
-    """ Generate real elections that have UN positionwise matrix """
+    """ Generate real election that have UN positionwise matrix """
     matrix = distribute_in_matrix(num_voters, num_candidates)
     return draw_election(matrix)
 
 
 def generate_idan_part_votes(num_voters=None, num_candidates=None, part_share=None, **kwargs):
-    """ Generate real elections between (ID) and (AN) """
+    """ Generate real election between (ID) and (AN) """
     if part_share is None:
         print("IDAN_part generation : params None : random param generated")
         part_size = np.random.choice(range(num_voters))
@@ -253,34 +254,33 @@ def generate_unst_mallows_votes(num_voters=None, num_candidates=None, params=Non
     return votes
 
 
-def generate_unst_topsize_votes(num_voters=None, num_candidates=None, params=None):
+def generate_unst_topsize_votes(num_voters=None, num_candidates=None, top_share=None, **kwargs):
     """ Generate kind of real elections between (UN) and (ST) """
-    if params is None or not ('top_share' in params):
+    if top_share is None:
         print("UNST_topsize generation : params None : random param generated")
         top_share = np.random.random()
     else:
-        top_share = params['top_share']
+        top_share = top_share
     top_size = int(round(top_share * num_candidates))
     better = top_size
     worse = num_candidates - top_size
     matrix = distribute_in_block_matrix(num_voters, [better, worse])
     return draw_election(matrix)
 
 
-def generate_idst_blocks_votes(num_voters=None, num_candidates=None, params=None):
+def generate_idst_blocks_votes(num_voters=None, num_candidates=None, no_blocks=None, **kwargs):
     """ Generate kind of real elections between (ID) and (UN) """
-    if params is None or not ('no_blocks' in params):
+    if no_blocks is None:
         print("IDST_blocks generation : params None : random param generated")
         no_blocks = np.random.choice(range(num_candidates + 1))
     else:
-        no_blocks = params['no_blocks']
+        no_blocks = no_blocks
     no_blocks = int(round(no_blocks))
     k = num_candidates // no_blocks
     r = num_candidates - k * no_blocks
     blocks = [k for _ in range(no_blocks)]
     with_one_more = list(np.random.choice(range(no_blocks), r, replace=False))
     for i in with_one_more:
         blocks[i] = blocks[i] + 1
-    print(blocks)
     matrix = distribute_in_block_matrix(num_voters, blocks)
     return draw_election(matrix)

mapel-elections/src/mapel/elections/distances/main_ordinal_distances.py

@@ -121,7 +121,7 @@ def compute_spearman_distance(election_1: OrdinalElection,
 
 
 def compute_spearman_distance_fastmap(
-    election_1: OrdinalElection, election_2: OrdinalElection, method: str = "bf"
+    election_1: OrdinalElection, election_2: OrdinalElection, method: str = "aa"
 ) -> tuple[int, Union[list, None]]:
     """Computes Isomorphic Spearman distance between elections using `fastmap` library.
 
@@ -169,7 +169,7 @@ def compute_spearman_distance_fastmap(
     except ImportError as e:
         raise ImportError("`fastmap` library module not found") from e
 
-    U, V = election_1.votes, election_2.votes
+    U, V = np.array(election_1.votes), np.array(election_2.votes)
     d = fastmap.spearman(U=U, V=V, method=method)
 
     return d, None

mapel-elections/src/mapel/elections/distances_.py

@@ -34,6 +34,7 @@
 
     'swap': mod.compute_swap_distance,
     'spearman': mod.compute_spearman_distance,
+    'spearman_aa': mod.compute_spearman_distance_fastmap,
 
     'blank': mod.compute_blank_distance,
 

mapel-elections/src/mapel/elections/features/scores.py

@@ -41,11 +41,16 @@ def highest_borda_score(election) -> dict:
     """
     if election.culture_id in LIST_OF_FAKE_MODELS:
         return {'value': None}
-    c = election.num_candidates
+    n = election.num_voters
+    m = election.num_candidates
     vectors = election.get_vectors()
-    borda = [sum([vectors[i][pos] * (c - pos - 1) for pos in range(c)])
-             for i in range(c)]
-    return {'value': max(borda) * election.num_voters}
+    scores = [0 for _ in range(m)]
+
+    for i in range(n):
+        for j in range(m):
+            scores[vectors[i][j]] += m - j - 1
+
+    return {'value': max(scores) * election.num_voters}
 
 
 def highest_plurality_score(election) -> dict: