class_docstr: Run tsfresh with the given parameters
class_docstr_tok: ["Run","tsfresh","with","the","given","parameters"]
code: def run(self):
      input_file = self._get_input_targets("data.csv")[0]
  
      with input_file.open("r") as f:
          df = pd.read_csv(f)
  
      start_time = time()
      extract_features(
          df,
          column_id="id",
          column_sort="time",
          n_jobs=self.n_jobs,
          default_fc_parameters=self.feature_parameter,
          disable_progressbar=True,
      )
      end_time = time()
  
      single_parameter_name = list(self.feature_parameter.keys())[0]
      single_parameter_params = self.feature_parameter[
          single_parameter_name
      ]
  
      result_json = {
          "time": end_time - start_time,
          "n_ids": self.num_ids,
          "n_jobs": self.n_jobs,
          "feature": single_parameter_name,
          "number_parameters": len(single_parameter_params)
          if single_parameter_params
          else 0,
          "time_series_length": int((df["id"] == 0).sum()),
          "try_number": self.try_number,
      }
  
      with self._get_output_target("result.json").open("w") as f:
          json.dump(result_json, f)
  
imports: import json
  from time import time
  import b2luigi
  import numpy
  import pandas
  from tsfresh.feature_extraction import ComprehensiveFCParameters, MinimalFCParameters, extract_features
label_desc: Use image node_id 2 for calling the TimingTask obj's underlying member method code with example usage: obj.run() without return types