code: def readDivPressure(fileName):
      
      try:
          df = pandas.read_csv(fileName, sep=None, engine='python')
          pandasformat = True
      except ValueError:
          pandasformat = False
      df.columns = ['site', 'divPressureValue']
      scaleFactor = max(df["divPressureValue"].abs())
      if scaleFactor > 0:
          df["divPressureValue"] = [x / scaleFactor for x in df["divPressureValue"]]
      assert len(df['site'].tolist()) == len(set(df['site'].tolist())),"There is at least one non-unique site in {0}".format(fileName)
      assert max(df["divPressureValue"].abs()) <= 1, "The scaling produced a diversifying pressure value with an absolute value greater than one."
      sites = df['site'].tolist()
      divPressure = {}
      for r in sites:
          divPressure[r] = df[df['site'] == r]["divPressureValue"].tolist()[0]
      return divPressure
docs: Reads in diversifying pressures from some file.
  
      Scale diversifying pressure values so absolute value of the max value is 1,
      unless all values are zero.
  
      Args:
          `fileName` (string or readable file-like object)
              File holding diversifying pressure values. Can be
              comma-, space-, or tab-separated file. The first column
              is the site (consecutively numbered, sites starting
              with one) and the second column is the diversifying pressure values.
  
      Returns:
          `divPressure` (dict keyed by ints)
              `divPressure[r][v]` is the diversifying pressure value of site `r`.