docs: def plot_ecg_pan_tompkins_steps(time, orig_ecg, pre_process_ecg, sampling_rate, titles):
      """
      -----
      Brief
      -----
      With this plotting function it will be possible to plot simultaneously (in pairs) "Original"/
      "Filtered"/"Differentiated"/"Rectified"/"Integrated" ECG signals used at "Pan-Tompkins R Peaks
      Detection Algorithm".
  
      -----------
      Description
      -----------
      Function intended to generate a Bokeh figure with 1x2 format, being 1 the of rows and 2 the number
      of columns.
  
      At the first column is plotted the ECG signal resulting from pre-process step i while in the second
      column it is presented the ECG signal resulting from pre-process step i+1.
  
      Applied in the Notebook titled "Event Detection - R Peaks (ECG)".
  
      ----------
      Parameters
      ----------
      time : list
          List containing the time-axis sequence of values.
  
      orig_ecg : list
          Sequence of sampled values (Original ECG).
  
      pre_process_ecg : list
          Sequence of sampled values (Pre-Processed ECG).
  
      sampling_rate : int
          Acquisition sampling rate (Hz)
  
      titles : list
          List containing the title of each subplot.
  
      """
  
      if len(titles) == 2:
          # Representation of the output of Step 1 of Pan-Tompkins R-Peak Detection Algorithm.
          # List that store the figure handler
          list_figures_1 = [[]]
  
          # Plotting of Original Signal
          list_figures_1[-1].append(figure(x_axis_label='Time (s)', y_axis_label='Raw Data',
                                           title=titles[0], **opensignals_kwargs("figure")))
          list_figures_1[-1][-1].line(time[:sampling_rate], orig_ecg[:sampling_rate], **opensignals_kwargs("line"))
  
          # Plotting of Filtered Signal
          list_figures_1[-1].append(figure(x_axis_label='Time (s)', y_axis_label='Raw Data',
                                           title=titles[1], **opensignals_kwargs("figure")))
          list_figures_1[-1][-1].line(time[:sampling_rate], pre_process_ecg[:sampling_rate], **opensignals_kwargs("line"))
  
          # Grid-Plot.
          opensignals_style([item for sublist in list_figures_1 for item in sublist])
          grid_plot_1 = gridplot(list_figures_1, **opensignals_kwargs("gridplot"))
          show(grid_plot_1)
      else:
          raise RuntimeError("The field 'title' must be a list of strings with size 2 !")