code: def load_data(self):
          
          data = []
          valid_dates = []
          mrms_files = np.array(sorted(os.listdir(self.path + self.variable + "/")))
          mrms_file_dates = np.array([m_file.split("_")[-2].split("-")[0]
              for m_file in mrms_files])
          old_mrms_file = None
          file_obj = None
          for t in range(self.all_dates.shape[0]):
              file_index = np.where(mrms_file_dates == self.all_dates[t].strftime("%Y%m%d"))[0]
              if len(file_index) > 0:
                  mrms_file = mrms_files[file_index][0]
                  if mrms_file is not None:
                      if file_obj is not None:
                          file_obj.close()
                      file_obj = Dataset(self.path + self.variable + "/" + mrms_file)
                      #old_mrms_file = mrms_file
                      
                      if "time" in file_obj.variables.keys():
                          time_var = "time"
                      else:
                          time_var = "date"
                      file_valid_dates = pd.DatetimeIndex(num2date(file_obj.variables[time_var][:],
                                                                   file_obj.variables[time_var].units))
                  else:
                      file_valid_dates = pd.DatetimeIndex([])
                  time_index = np.where(file_valid_dates.values == self.all_dates.values[t])[0]
                  if len(time_index) > 0:
                      data.append(file_obj.variables[self.variable][time_index[0]])
                      valid_dates.append(self.all_dates[t])
          if file_obj is not None:
              file_obj.close()
          self.data = np.array(data)
          self.data[self.data < 0] = 0
          self.data[self.data > 150] = 150
          self.valid_dates = pd.DatetimeIndex(valid_dates)
docs: Loads data files and stores the output in the data attribute.