Merge branch 'scoring' of github.com:priyakasimbeg/algorithmic-effici…

…ency into scoring

scoring/score_submissions.py

@@ -88,9 +88,15 @@ def get_summary_df(workload, workload_df, include_test_split=False):
   summary_df['time to best eval on val (s)'] = workload_df.apply(
       lambda x: x['accumulated_submission_time'][x['index best eval on val']],
       axis=1)
-  summary_df['time to target on val (s)'] = summary_df.apply(
-      lambda x: x['time to best eval on val (s)']
-      if x['val target reached'] else np.inf,
+  workload_df['val target reached'] = workload_df[validation_metric].apply(
+      lambda x: target_op(x, validation_target)).apply(np.any)
+  workload_df['index to target on val'] = workload_df.apply(
+      lambda x: np.argmax(target_op(x[validation_metric], validation_target))
+      if x['val target reached'] else np.nan,
+      axis=1)
+  summary_df['time to target on val (s)'] = workload_df.apply(
+      lambda x: x['accumulated_submission_time'][int(x[
+          'index to target on val'])] if x['val target reached'] else np.inf,
       axis=1)
 
   # test metrics