code: def read_B_matrices(path):
      all_sheets = pd.read_excel(path, sheet_name=None, header=None)
  
      level_counts = {}
      for sheet_name, raw_table in all_sheets.items():
          level_counts[sheet_name] = {
              "index": raw_table.iloc[0, :].dropna().index[0] + 1,
              "header": raw_table.iloc[0, :].dropna().index[0] + 2,
          }
  
      stub_dict = {}
      for sheet_name, level_counts_sheet in level_counts.items():
          sheet_f = pd.read_excel(
              path,
              sheet_name=sheet_name,
              index_col=list(range(level_counts_sheet["index"])),
              header=list(range(level_counts_sheet["header"])),
          ).astype(np.float64)
          stub_dict[sheet_name] = sheet_f
  
      return stub_dict
  
imports: import numpy
  import pandas
  import seaborn
  import matplotlib.pyplot
  import warnings
  import itertools
label_desc: Use image node_id 32 for calling a global function with example usage: read_B_matrices(path) and returns: stub_dict