Pushing the docs to dev/ for branch: main, commit f083a12630108d60ed29ca8ca03166d0777099e9

Author: sklearn-ci

dev/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip

@@ -38,6 +38,11 @@ def _not_in_sphinx():
     return "__file__" in globals()
 
 
+# %%
+# Benchmark and plot helper functions
+# -----------------------------------
+
+
 def atomic_benchmark_estimator(estimator, X_test, verbose=False):
     """Measure runtime prediction of each instance."""
     n_instances = X_test.shape[0]
@@ -289,13 +294,10 @@ def plot_benchmark_throughput(throughputs, configuration):
     plt.show()
 
 
-# #############################################################################
-# Main code
-
-start_time = time.time()
-
-# #############################################################################
+# %%
 # Benchmark bulk/atomic prediction speed for various regressors
+# -------------------------------------------------------------
+
 configuration = {
     "n_train": int(1e3),
     "n_test": int(1e2),
@@ -325,7 +327,10 @@ def plot_benchmark_throughput(throughputs, configuration):
 }
 benchmark(configuration)
 
-# benchmark n_features influence on prediction speed
+# %%
+# Benchmark n_features influence on prediction speed
+# --------------------------------------------------
+
 percentile = 90
 percentiles = n_feature_influence(
     {"ridge": Ridge()},
@@ -336,9 +341,9 @@ def plot_benchmark_throughput(throughputs, configuration):
 )
 plot_n_features_influence(percentiles, percentile)
 
-# benchmark throughput
+# %%
+# Benchmark throughput
+# --------------------
+
 throughputs = benchmark_throughputs(configuration)
 plot_benchmark_throughput(throughputs, configuration)
-
-stop_time = time.time()
-print("example run in %.2fs" % (stop_time - start_time))