code: def plotmeanHPPC_Spectrum(
      hpcpmeanpool,
      spectrummean,
      signalsKey,
      frameSize,
      hopSize,
      wtype,
      title,
  ):
      figtitle = "Mean HPCP " + title + " window type " + str(wtype[0])
      fig = figure(
          num=None, figsize=(8, 5), dpi=80, facecolor="w", edgecolor="k"
      )
      fignamehpcp = figtitle
      plt.title(figtitle)
      for skey in signalsKey:
          plot(hpcpmeanpool[str(wtype)][str(skey)])
          tight_layout()
      legend(signalsKey)
      # show()
      fignamehpcp = fignamehpcp + ".png"
      fig.savefig(fignamehpcp, bbox_inches="tight")
      close("all")
      figtitle = "Spectrum " + title + " window type " + str(wtype[0])
      fig = figure(
          num=None, figsize=(8, 5), dpi=80, facecolor="w", edgecolor="k"
      )
      fignamescptr = figtitle
      plt.title(figtitle)
      for skey in signalsKey:
          plot(spectrummean[str(wtype)][str(skey)])
          tight_layout()
      legend(signalsKey)
      fignamescptr = fignamescptr + ".png"
      fig.savefig(fignamescptr, bbox_inches="tight")
      close("all")
      html = "<p>" + title + "</p>\n"
      html += '<p><img src="' + fignamehpcp + '"></p>\n\n'
      html += '<p><img src="' + fignamescptr + '"></p>\n\n'
      return html
  
file_path: essentia/test/src/qa/hpcp/test_hpcp_plots.py
imports: import numpy
  import essentia
  from essentia.standard import *
  from matplotlib.pyplot import imshow, show, plot, title, ylim, legend, figure, grid, GridSpec, subplot, text, tight_layout, yticks, locator_params, close
  import matplotlib.pyplot
  from test_hpcp_parameters import *
  from test_hpcp_extract import *
label_desc: Use image node_id 4 for calling a global function with example usage: plotmeanHPPC_Spectrum(hpcpmeanpool, spectrummean, signalsKey, frameSize, hopSize, wtype, title) and returns: html