Add 95% CI error bars to CE and CW examples (Sourcery refactored)

examples/merrill_1984_fig_2c_2d.py

@@ -41,6 +41,7 @@
 running as many simulations, however the Coombs results are consistently
 high.
 """
+
 import time
 from collections import Counter
 import numpy as np
@@ -93,7 +94,7 @@
         ranked_methods.keys() | rated_methods.keys() | {'CW'})}
     start_time = time.monotonic()
 
-    for iteration in range(n_elections):
+    for _ in range(n_elections):
         for n_cands in n_cands_list:
             v, c = normal_electorate(n_voters, n_cands, dims=D, corr=corr,
                                      disp=disp)

examples/merrill_1984_table_1_fig_1.py

@@ -24,6 +24,7 @@
 | SU max    | 100.0 |  84.1 |  79.6 |  78.4 |  77.3 |  77.5 |
 | CW        | 100.0 |  91.7 |  83.1 |  75.6 |  64.3 |  52.9 |
 """
+
 import time
 from collections import Counter
 import numpy as np
@@ -51,7 +52,7 @@
 
 start_time = time.monotonic()
 
-for iteration in range(n_elections):
+for _ in range(n_elections):
     for n_cands in n_cands_list:
         utilities = random_utilities(n_voters, n_cands)
 
@@ -126,11 +127,12 @@
 
 # Likelihood that social utility maximizer is Condorcet Winner
 x, y = zip(*sorted(condorcet_winner_count['SU max'].items()))
-table.append(['SU max', *np.array(y)/y_cw*100])
-
-# Likelihood of Condorcet Winner (normalized by n elections)
-table.append(['CW', *np.asarray(y_cw) / n_elections * 100])
-
+table.extend(
+    (
+        ['SU max', *np.array(y) / y_cw * 100],
+        ['CW', *np.asarray(y_cw) / n_elections * 100],
+    )
+)
 print(tabulate(table, ["Method", *x], tablefmt="pipe", floatfmt='.1f'))
 
 plt.plot([], [], 'k:', lw=0.8, label='Merrill')  # Dummy plot for label

examples/wikipedia_condorcet_paradox_likelihood.py

@@ -52,7 +52,7 @@ def simulate_batch(n_voters):
     condorcet_paradox_count = Counter()
     # Reuse the same chunk of memory to save time
     election = np.empty((n_voters, n_cands), dtype=np.uint8)
-    for iteration in range(batch_size):
+    for _ in range(batch_size):
         election[:] = impartial_culture(n_voters, n_cands)
         CW = condorcet(election)
         if CW is None: