class_docstr: Singular Spectrum Analysis object
class_docstr_tok: ["Singular","Spectrum","Analysis","object"]
docstr: View the contribution to variance of each singular value and its corresponding signal
docstr_tok: ["View","the","contribution","to","variance","of","each","singular","value","and","its","corresponding","signal"]
code: def view_s_contributions(
      self, adjust_scale=False, cumulative=False, return_df=False
  ):
      """View the contribution to variance of each singular value and its corresponding signal"""
      contribs = self.s_contributions.copy()
      contribs = contribs[contribs.Contribution != 0]
      if cumulative:
          contribs["Contribution"] = contribs.Contribution.cumsum()
      if adjust_scale:
          contribs = (1 / contribs).max() * 1.1 - (1 / contribs)
      ax = contribs.plot.bar(legend=False)
      ax.set_xlabel("Singular_i")
      ax.set_title(
          "Non-zero{} contribution of Singular_i {}".format(
              " cumulative" if cumulative else "",
              "(scaled)" if adjust_scale else "",
          )
      )
      if adjust_scale:
          ax.axes.get_yaxis().set_visible(False)
      vals = ax.get_yticks()
      ax.set_yticklabels(["{:3.0f}%".format(x * 100) for x in vals])
      if return_df:
          return contribs
  
imports: import numpy
  import pandas
  from numpy import matrix
  from scipy import linalg
  from matplotlib.pylab import rcParams
label_desc: Use image node_id 8 for calling the mySSA obj's underlying member method code with example usage: obj.view_s_contributions(adjust_scale, cumulative, return_df) and returns: contribs