code: def _plotly_viz_correlation_matrix(association_matrix):
      """Plot the heatmap for the association matrix.
  
      Args:
          association_matrix (DataFrame): The association matrix
  
      Returns:
          The plotly figure
      """
      # Plot lower left triangle
      x_ind, y_ind = np.triu_indices(association_matrix.shape[0])
      corr = association_matrix.to_numpy()
      for x, y in zip(x_ind, y_ind):
          corr[x, y] = None
  
      # Set up the color scale
      cscale = mpl_to_plotly_cmap(get_p_RdBl_cmap())
  
      # Generate a custom diverging colormap
      fig = go.Figure(
          data=[
              go.Heatmap(
                  z=np.flip(corr, axis=0),
                  x=association_matrix.columns.values,
                  y=association_matrix.columns.values[::-1],
                  connectgaps=False,
                  xgap=2,
                  ygap=2,
                  zmid=0,
                  colorscale=cscale,
                  colorbar={"title": "Strength"},
              )
          ],
          layout=go.Layout(
              autosize=False,
              width=get_option("display.plotly.fig_width"),
              height=get_option("display.plotly.fig_height"),
              title={
                  "text": "Correlation Matrix",
                  "font": {
                      "size": get_option("display.plotly.title_size")
                  },
              },
              xaxis=go.layout.XAxis(
                  automargin=True,
                  tickangle=270,
                  ticks="",
                  showgrid=False,
              ),
              yaxis=go.layout.YAxis(
                  automargin=True, ticks="", showgrid=False
              ),
              plot_bgcolor="rgb(0,0,0,0)",
              paper_bgcolor="rgb(0,0,0,0)",
          ),
      )
  
      if _in_notebook():
          po.init_notebook_mode(connected=True)
          return po.iplot(fig, config={"displayModeBar": False})
      else:
          return fig
  
imports: import warnings
  import pandas
  import numpy
  from scipy.cluster import hierarchy
  from sklearn.metrics import matthews_corrcoef
  from scipy.stats import chi2_contingency
  import seaborn
  import matplotlib.pyplot
  import plotly.graph_objs
  import plotly.offline
  from data_describe.config._config import get_option
  from data_describe.misc.colors import get_p_RdBl_cmap, mpl_to_plotly_cmap
  from data_describe._widget import BaseWidget
  from data_describe.compat import _is_dataframe, _in_notebook, _requires
  from data_describe.backends import _get_viz_backend, _get_compute_backend
label_desc: Use image node_id 9 for calling a global function with example usage: _plotly_viz_correlation_matrix(association_matrix) and returns: po, fig