fix test cases; fix alphine linux build

GeoDaCenter · Dec 20, 2024 · def410d · def410d
1 parent 86ad5ad
commit def410d
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Showing 7 changed files with 154 additions and 90 deletions.
diff --git a/libgeoda b/libgeoda
diff --git a/pygeoda/clustering/azp.py b/pygeoda/clustering/azp.py
@@ -65,7 +65,7 @@ def azp_greedy(p, w, data, **kwargs):
 
     in_init_regions = VecInt(list(init_regions))
 
-    cluster_ids = gda_azp_greedy(p, w.gda_w, in_data, scale_method, inits, min_bounds, max_bounds, in_init_regions, distance_method, random_seed)
+    cluster_ids = gda_azp_greedy(p, w.gda_w, in_data, scale_method, inits, min_bounds, max_bounds, in_init_regions, distance_method, random_seed, 0)
 
     between_ss = gda_betweensumofsquare(cluster_ids, in_data)
     total_ss = gda_totalsumofsquare(in_data)
@@ -142,7 +142,7 @@ def azp_sa(p, w, data, cooling_rate=0.85, **kwargs):
 
     in_init_regions = VecInt(list(init_regions))
 
-    cluster_ids = gda_azp_sa(p, w.gda_w, in_data, scale_method, inits, cooling_rate, sa_maxit, min_bounds, max_bounds, in_init_regions, distance_method, random_seed)
+    cluster_ids = gda_azp_sa(p, w.gda_w, in_data, scale_method, inits, cooling_rate, sa_maxit, min_bounds, max_bounds, in_init_regions, distance_method, random_seed, 0)
 
     between_ss = gda_betweensumofsquare(cluster_ids, in_data)
     total_ss = gda_totalsumofsquare(in_data)
@@ -216,7 +216,7 @@ def azp_tabu(p, w, data, tabu_length, **kwargs):
 
     in_init_regions = VecInt(list(init_regions))
 
-    cluster_ids = gda_azp_tabu(p, w.gda_w, in_data, scale_method, inits, tabu_length, conv_tabu, min_bounds, max_bounds, in_init_regions, distance_method, random_seed)
+    cluster_ids = gda_azp_tabu(p, w.gda_w, in_data, scale_method, inits, tabu_length, conv_tabu, min_bounds, max_bounds, in_init_regions, distance_method, random_seed, 0)
 
     between_ss = gda_betweensumofsquare(cluster_ids, in_data)
     total_ss = gda_totalsumofsquare(in_data)

diff --git a/pygeoda/clustering/maxp.py b/pygeoda/clustering/maxp.py
@@ -64,7 +64,7 @@ def maxp_greedy(w, data, bound_variable, min_bound, **kwargs):
 
     in_init_regions = VecInt(list(init_regions))
 
-    cluster_ids = gda_maxp_greedy(w.gda_w, in_data, scale_method, iterations, min_bounds, max_bounds, in_init_regions, distance_method, random_seed, cpu_threads)
+    cluster_ids = gda_maxp_greedy(w.gda_w, in_data, scale_method, iterations, min_bounds, max_bounds, in_init_regions, distance_method, random_seed, cpu_threads, 0)
 
     between_ss = gda_betweensumofsquare(cluster_ids, in_data)
     total_ss = gda_totalsumofsquare(in_data)
@@ -140,7 +140,7 @@ def maxp_sa(w, data, bound_variable, min_bound, cooling_rate=0.85, **kwargs):
 
     in_init_regions = VecInt(list(init_regions))
 
-    cluster_ids = gda_maxp_sa(w.gda_w, in_data, scale_method, iterations, cooling_rate, sa_maxit, min_bounds, max_bounds, in_init_regions, distance_method, random_seed, cpu_threads)
+    cluster_ids = gda_maxp_sa(w.gda_w, in_data, scale_method, iterations, cooling_rate, sa_maxit, min_bounds, max_bounds, in_init_regions, distance_method, random_seed, cpu_threads, 0)
 
     between_ss = gda_betweensumofsquare(cluster_ids, in_data)
     total_ss = gda_totalsumofsquare(in_data)
@@ -213,7 +213,7 @@ def maxp_tabu(w, data, bound_variable, min_bound, tabu_length=10, **kwargs):
 
     in_init_regions = VecInt(list(init_regions))
 
-    cluster_ids = gda_maxp_tabu(w.gda_w, in_data, scale_method, iterations, tabu_length, conv_tabu, min_bounds, max_bounds, in_init_regions, distance_method, random_seed, cpu_threads)
+    cluster_ids = gda_maxp_tabu(w.gda_w, in_data, scale_method, iterations, tabu_length, conv_tabu, min_bounds, max_bounds, in_init_regions, distance_method, random_seed, cpu_threads, 0)
 
     between_ss = gda_betweensumofsquare(cluster_ids, in_data)
     total_ss = gda_totalsumofsquare(in_data)

diff --git a/pygeoda/clustering/redcap.py b/pygeoda/clustering/redcap.py
@@ -52,7 +52,7 @@ def redcap(k, w, data, method, **kwargs):
 
     #in_bound_variable = VecDouble(bound_variable)
 
-    cluster_ids = gda_redcap(k, w.gda_w, in_data, scale_method, method, distance_method, bound_variable, min_bound, random_seed, cpu_threads)
+    cluster_ids = gda_redcap(k, w.gda_w, in_data, scale_method, method, distance_method, bound_variable, min_bound, random_seed, cpu_threads, 0)
 
     between_ss = gda_betweensumofsquare(cluster_ids, in_data)
     total_ss = gda_totalsumofsquare(in_data)

diff --git a/pygeoda/clustering/schc.py b/pygeoda/clustering/schc.py
@@ -44,7 +44,7 @@ def schc(k, w, data, linkage_method, **kwargs):
     for d in data:
         in_data.push_back(d)
 
-    cluster_ids = gda_schc(k, w.gda_w, in_data, linkage_method, scale_method, distance_method, bound_variable, min_bound)
+    cluster_ids = gda_schc(k, w.gda_w, in_data, linkage_method, scale_method, distance_method, bound_variable, min_bound, 0)
 
     between_ss = gda_betweensumofsquare(cluster_ids, in_data)
     total_ss = gda_totalsumofsquare(in_data)

diff --git a/pygeoda/clustering/skater.py b/pygeoda/clustering/skater.py
@@ -39,7 +39,7 @@ def skater(k, w, data, **kwargs):
     for d in data:
         in_data.push_back(d)
 
-    cluster_ids = gda_skater(k, w.gda_w, in_data, scale_method, distance_method, bound_variable, min_bound, random_seed, cpu_threads)
+    cluster_ids = gda_skater(k, w.gda_w, in_data, scale_method, distance_method, bound_variable, min_bound, random_seed, cpu_threads, 0)
 
     between_ss = gda_betweensumofsquare(cluster_ids, in_data)
     total_ss = gda_totalsumofsquare(in_data)