code: def plot_corr(
      dcorr,
      xnames=None,
      ynames=None,
      title=None,
      normcolor=False,
      ax=None,
      cmap="RdYlBu_r",
  ):
      """Plot correlation of many variables in a tight color grid.
  
      Parameters
      ----------
      dcorr : ndarray
          Correlation matrix, square 2-D array.
      xnames : list[str], optional
          Labels for the horizontal axis.  If not given (None), then the
          matplotlib defaults (integers) are used.  If it is an empty list, [],
          then no ticks and labels are added.
      ynames : list[str], optional
          Labels for the vertical axis.  Works the same way as `xnames`.
          If not given, the same names as for `xnames` are re-used.
      title : str, optional
          The figure title. If None, the default ('Correlation Matrix') is used.
          If ``title=''``, then no title is added.
      normcolor : bool or tuple of scalars, optional
          If False (default), then the color coding range corresponds to the
          range of `dcorr`.  If True, then the color range is normalized to
          (-1, 1).  If this is a tuple of two numbers, then they define the range
          for the color bar.
      ax : AxesSubplot, optional
          If `ax` is None, then a figure is created. If an axis instance is
          given, then only the main plot but not the colorbar is created.
      cmap : str or Matplotlib Colormap instance, optional
          The colormap for the plot.  Can be any valid Matplotlib Colormap
          instance or name.
  
      Returns
      -------
      Figure
          If `ax` is None, the created figure.  Otherwise the figure to which
          `ax` is connected.
  
      Examples
      --------
      >>> import numpy as np
      >>> import matplotlib.pyplot as plt
      >>> import statsmodels.graphics.api as smg
  
      >>> hie_data = sm.datasets.randhie.load_pandas()
      >>> corr_matrix = np.corrcoef(hie_data.data.T)
      >>> smg.plot_corr(corr_matrix, xnames=hie_data.names)
      >>> plt.show()
  
      .. plot:: plots/graphics_correlation_plot_corr.py
      """
      if ax is None:
          create_colorbar = True
      else:
          create_colorbar = False
  
      fig, ax = utils.create_mpl_ax(ax)
  
      nvars = dcorr.shape[0]
  
      if ynames is None:
          ynames = xnames
      if title is None:
          title = "Correlation Matrix"
      if isinstance(normcolor, tuple):
          vmin, vmax = normcolor
      elif normcolor:
          vmin, vmax = -1.0, 1.0
      else:
          vmin, vmax = None, None
  
      axim = ax.imshow(
          dcorr,
          cmap=cmap,
          interpolation="nearest",
          extent=(0, nvars, 0, nvars),
          vmin=vmin,
          vmax=vmax,
      )
  
      # create list of label positions
      labelPos = np.arange(0, nvars) + 0.5
  
      if isinstance(ynames, list) and len(ynames) == 0:
          ax.set_yticks([])
      elif ynames is not None:
          ax.set_yticks(labelPos)
          ax.set_yticks(labelPos[:-1] + 0.5, minor=True)
          ax.set_yticklabels(
              ynames[::-1],
              fontsize="small",
              horizontalalignment="right",
          )
  
      if isinstance(xnames, list) and len(xnames) == 0:
          ax.set_xticks([])
      elif xnames is not None:
          ax.set_xticks(labelPos)
          ax.set_xticks(labelPos[:-1] + 0.5, minor=True)
          ax.set_xticklabels(
              xnames,
              fontsize="small",
              rotation=45,
              horizontalalignment="right",
          )
  
      if not title == "":
          ax.set_title(title)
  
      if create_colorbar:
          fig.colorbar(axim, use_gridspec=True)
      fig.tight_layout()
  
      ax.tick_params(which="minor", length=0)
      ax.tick_params(direction="out", top=False, right=False)
      try:
          ax.grid(True, which="minor", linestyle="-", color="w", lw=1)
      except AttributeError:
          # Seems to fail for axes created with AxesGrid.  MPL bug?
          pass
  
      return fig
  
imports: import numpy
  from .None import utils
label_desc: Use image node_id 1 for calling a global function with example usage: plot_corr(dcorr, xnames, ynames, title, normcolor, ax, cmap) and returns: fig