Feed batch_size to function instead of global

endolith · Nov 2, 2023 · ee10c4f · ee10c4f
1 parent 2ed24c8
commit ee10c4f
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Showing 3 changed files with 9 additions and 6 deletions.
diff --git a/examples/niemi_1968_table_1.py b/examples/niemi_1968_table_1.py
@@ -65,7 +65,7 @@
 assert n_batches * batch_size == n_elections
 
 
-def simulate_batch(n_voters, n_cands):
+def simulate_batch(n_voters, n_cands, batch_size):
     condorcet_paradox_count = Counter()
     # Reuse the same chunk of memory to save time
     election = np.empty((n_voters, n_cands), dtype=np.uint8)
@@ -79,7 +79,8 @@ def simulate_batch(n_voters, n_cands):
 
 jobs = []
 for n_cands in n_cands_list:
-    jobs.extend([delayed(simulate_batch)(n_voters, n_cands)] * n_batches)
+    jobs.extend(n_batches *
+                [delayed(simulate_batch)(n_voters, n_cands, batch_size)])
 
 print(f'{len(jobs)} tasks total:')
 results = Parallel(n_jobs=-3, verbose=5)(jobs)

diff --git a/examples/niemi_1968_table_2.py b/examples/niemi_1968_table_2.py
@@ -41,7 +41,7 @@
 assert n_batches * batch_size == n_elections
 
 
-def simulate_batch(n_voters, n_cands):
+def simulate_batch(n_voters, n_cands, batch_size):
     condorcet_paradox_count = Counter()
     # Reuse the same chunk of memory to save time
     election = np.empty((n_voters, n_cands), dtype=np.uint8)
@@ -56,7 +56,8 @@ def simulate_batch(n_voters, n_cands):
 jobs = []
 for n_voters in n_voters_list:
     for n_cands in n_cands_list:
-        jobs.extend([delayed(simulate_batch)(n_voters, n_cands)] * n_batches)
+        jobs.extend(n_batches *
+                    [delayed(simulate_batch)(n_voters, n_cands, batch_size)])
 
 print(f'{len(jobs)} tasks total:')
 results = Parallel(n_jobs=-3, verbose=5)(jobs)

diff --git a/examples/wikipedia_condorcet_paradox_likelihood.py b/examples/wikipedia_condorcet_paradox_likelihood.py
@@ -49,7 +49,7 @@
 assert n_batches * batch_size == n_elections
 
 
-def simulate_batch(n_voters, n_cands):
+def simulate_batch(n_voters, n_cands, batch_size):
     condorcet_paradox_count = Counter()
     # Reuse the same chunk of memory to save time
     election = np.empty((n_voters, n_cands), dtype=np.uint8)
@@ -63,7 +63,8 @@ def simulate_batch(n_voters, n_cands):
 
 jobs = []
 for n_voters in WP_table:
-    jobs.extend([delayed(simulate_batch)(n_voters, n_cands)] * n_batches)
+    jobs.extend(n_batches *
+                [delayed(simulate_batch)(n_voters, n_cands, batch_size)])
 
 print(f'{len(jobs)} tasks total:')
 results = Parallel(n_jobs=-3, verbose=5)(jobs)