text: """Plot a single parameter."""
  import itertools
  import numpy as np
  
  from matplotlib import pyplot as plt
  
  from bioplottemplates import log
  from bioplottemplates.libs import libmsg, libutil
  from bioplottemplates.logger import S, T
  
  
  def plot(
          x_data,
          y_data,
          *,
          labels="No label provided",
          title=None,
          xlabel=None,
          ylabel=None,
          colors=('b', 'g', 'r', 'c', 'm', 'y', 'k'),
          alpha=0.7,
          xmax=None,
          xmin=None,
          ymax=None,
          ymin=None,
          grid=True,
          grid_color="lightgrey",
          grid_ls="-",
          grid_lw=1,
          grid_alpha=0.5,
          legend=True,
          legend_fs=6,
          legend_loc=4,
          vert_lines=None,
          figsize=(8, 6),
          filename='plot_param.pdf',
          **kwargs
          ):
      """
      Plot a single plot with the combined RMSD.
      
      Bellow parameters concern data representation and are considered
      of highest importance because their incorrect use can mislead
      data analysis and consequent conclusions.
      
      Plot style parameters concernning only plot style, i.e., colors,
      shapes, fonts, etc... and which do not distort the actual data,
      are not listed in the paremeter list bellow. We hope these
      parameter names are self-explanatory and are listed in the function
      definition.
      
      Parameters
      ----------
      x_data : interable of numbers
          Container of the X axis data. Should be accepted
          by matplotlib.
      
      y_data : np.ndarray, shape=(M,)
          Container of the Y axis data.
          Where M is the RMSDs data for the combined chains.
      
      labels : str, optional
          The label to represent in plot legend.
          If a list of series is provided, a list of labels
          can be provided as well.
          Defauts to: "no labels provided".
      
      filename : str, optional
          The file name with which the plot figure will be saved
          in disk. Defaults to rmsd_individual_chains_one_subplot.pdf.
          You can change the file type by specifying its extention in
          the file name.
      
      fig_size : tuple of float or int
          The size ratio of the subplot in the figure.
      """
      log.info(T("Plotting parameter:"))
      
      # prepares data in
      y_data = np.array(y_data)
      if y_data.ndim == 1:
          y_data = y_data[np.newaxis, :]
      
      plot_labels = libutil.make_list(labels)
      plot_colors = libutil.make_list(colors)
      plot_colors = itertools.cycle(plot_colors)
      
      assert y_data.shape[0] == len(plot_labels), (
          '{} vs {}'.format(y_data.shape[0], len(plot_labels)))
      # done data preparation
  
      fig, ax = plt.subplots(nrows=1, ncols=1, figsize=figsize)
      plt.tight_layout(rect=[0.05, 0.02, 0.995, 0.985])
      
      fig.suptitle(
          title,
          x=0.5,
          y=0.990,
          va="top",
          ha="center",
          )
  
      for yy, ll in zip(y_data, plot_labels):
          ax.plot(
              x_data,
              yy,
              label=ll,
              color=next(plot_colors),
              alpha=alpha,
              )
      
      ax.set_xlabel(xlabel, weight='bold')
      ax.set_ylabel(ylabel, weight='bold')
      
      # setting axes scales
  
      xmin = xmin or x_data[0]
      xmax = xmax or x_data[-1]
      ymin = ymin or np.array(y_data).min()
      ymax = ymax or np.array(y_data).max()
  
      ax.set_xlim(xmin, xmax)
      ax.set_ylim(ymin, ymax)
      
      if grid:
          ax.grid(
              color=grid_color,
              linestyle=grid_ls,
              linewidth=grid_lw,
              alpha=grid_alpha,
              )
      if isinstance(vert_lines, (list, tuple)):
          for line in vert_lines:
              ax.axvline(x=float(line), color='k')
  
      if legend:
          ax.legend(
              fontsize=legend_fs,
              loc=legend_loc,
              )
      
      fig.savefig(filename)
      log.info(S(libmsg.fig_saved.format(filename)))
          
      plt.close("all")
      
      return
  