docs: def acquire_subsamples_gp1(input_data, file_name=None):
      """
      Function invoked for plotting a grid-plot with 3x2 format, showing the differences in ECG
      signals accordingly to the chosen sampling frequency.
  
      Applied in the cell with tag "subsampling_grid_plot_1".
  
      ----------
      Parameters
      ----------
      input_data : dict
          Dictionary with ECG signal to present.
  
      file_name : str
          Path containing the destination folder where the Bokeh figure will be stored.
      """
  
      # Generation of the HTML file where the plot will be stored.
      #file_name = _generate_bokeh_file(file_name)
  
      # Number of acquired samples (Original sample_rate = 4000 Hz)
      fs_orig = 4000
      nbr_samples_orig = len(input_data)
      data_interp = {"4000": {}}
      data_interp["4000"]["data"] = input_data
      data_interp["4000"]["time"] = numpy.linspace(0, nbr_samples_orig / fs_orig, nbr_samples_orig)
  
      # Constants
      time_orig = data_interp["4000"]["time"]
      data_orig = data_interp["4000"]["data"]
  
      # ============ Interpolation of data accordingly to the desired sampling frequency ============
      # sample_rate in [3000, 1000, 500, 200, 100] - Some of the available sample frequencies at Plux
      # acquisition systems
      # sample_rate in [50, 20] - Non-functional sampling frequencies (Not available at Plux devices
      # because of their limited application)
      for sample_rate in [3000, 1000, 500, 200, 100, 50, 20]:
          fs_str = str(sample_rate)
          nbr_samples_interp = int((nbr_samples_orig * sample_rate) / fs_orig)
          data_interp[fs_str] = {}
          data_interp[fs_str]["time"] = numpy.linspace(0, nbr_samples_orig / fs_orig,
                                                       nbr_samples_interp)
          data_interp[fs_str]["data"] = numpy.interp(data_interp[fs_str]["time"], time_orig,
                                                     data_orig)
  
      # List that store the figure handler.
      list_figures = []
  
      # Generation of Bokeh Figures.
      for iter_nbr, sample_rate in enumerate(["4000", "3000", "1000", "500", "200", "100"]):
          # If figure number is a multiple of 3 or if we are generating the first figure...
          if iter_nbr == 0 or iter_nbr % 2 == 0:
              list_figures.append([])
  
          # Plotting phase.
          list_figures[-1].append(figure(x_axis_label='Time (s)', y_axis_label='Raw Data',
                                         title="Sampling Frequency: " + sample_rate + " Hz",
                                         **opensignals_kwargs("figure")))
          list_figures[-1][-1].line(data_interp[sample_rate]["time"][:int(sample_rate)],
                                    data_interp[sample_rate]["data"][:int(sample_rate)],
                                    **opensignals_kwargs("line"))