code: def all_features():
      """Returns dictionary of all features in the module
  
      .. note:: Some of the features (hist4, corr) are relatively expensive to compute
      """
      features = {
          "mean": mean,
          "median": median,
          "gmean": gmean,
          "hmean": hmean,
          "vec_sum": vec_sum,
          "abs_sum": abs_sum,
          "abs_energy": abs_energy,
          "std": std,
          "var": var,
          "mad": median_absolute_deviation,
          "variation": variation,
          "min": minimum,
          "max": maximum,
          "skew": skew,
          "kurt": kurt,
          "mean_diff": mean_diff,
          "mean_abs_diff": means_abs_diff,
          "mse": mse,
          "mnx": mean_crossings,
          "hist4": hist(),
          "corr": corr2,
          "mean_abs_value": mean_abs,
          "zero_crossings": zero_crossing(),
          "slope_sign_changes": slope_sign_changes(),
          "waveform_length": waveform_length,
          "emg_var": emg_var,
          "root_mean_square": root_mean_square,
          "willison_amplitude": willison_amplitude(),
      }
      return features
  
imports: import numpy
  from scipy import stats
label_desc: Use image node_id 2 for calling a global function with example usage: all_features() and returns: features