code: def match_and_check(self, score_cols, pihat_threshold, caliper):
      if self.verbose:
          logger.info(
              "Preparing match for: caliper={:.03f}, "
              "pihat_threshold={:.03f}, "
              "score_cols={}".format(
                  caliper, pihat_threshold, score_cols
              )
          )
      df_matched = self.single_match(
          score_cols=score_cols,
          pihat_threshold=pihat_threshold,
          caliper=caliper,
      )
      tableone = create_table_one(
          df_matched, self.treatment_col, self.matching_covariates
      )
      self.check_table_one(
          tableone, df_matched, score_cols, pihat_threshold, caliper
      )
  
imports: import argparse
  import logging
  import sys
  import numpy
  import pandas
  from sklearn.neighbors import NearestNeighbors
  from sklearn.preprocessing import StandardScaler
  from sklearn.utils import check_random_state
label_desc: Use image node_id 4 for calling the MatchOptimizer obj's underlying member method code with example usage: obj.match_and_check(score_cols, pihat_threshold, caliper) without return types