code: def conc_err_plot(fname):
      """Plots the error in the CE data.
  
      This plots the error in the CE predictions within a ternary concentration diagram.
  
      Parameters
      ----------
      fname : string containing the input file name.
      """
  
      energies = _read_data(fname)
      enthalpy = _energy_to_enthalpy(energies)
      this_errors = _find_error(enthalpy)
  
      points = []
      colors = []
      for er in this_errors:
          concs = er[0]
          points.append(
              (concs[0] * 100, concs[1] * 100, concs[2] * 100)
          )
          colors.append(er[1])
  
      scale = 100
      figure, tax = ternary.figure(scale=scale)
      tax.boundary(linewidth=1.0)
      tax.set_title("Errors in Convex Hull Predictions.", fontsize=20)
      tax.gridlines(multiple=10, color="blue")
      tax.scatter(
          points,
          vmax=max(colors),
          colormap=plt.cm.viridis,
          colorbar=True,
          c=colors,
          cmap=plt.cm.viridis,
      )
  
      tax.show()
  
imports: import ternary
  import matplotlib.pyplot
label_desc: Use image node_id 5 for calling a global function with example usage: conc_err_plot(fname) without return types