code: def polar_map(hist: Histogram2D, ax: Axes, *, show_zero: bool = True, show_colorbar: bool = True, **kwargs):
      
      data = get_data(hist, cumulative=False, flatten=True,
                      density=kwargs.pop("density", False))
  
      cmap = _get_cmap(kwargs)
      norm, cmap_data = _get_cmap_data(data, kwargs)
      colors = cmap(cmap_data)
  
      rpos, phipos = (arr.flatten() for arr in hist.get_bin_left_edges())
      dr, dphi = (arr.flatten() for arr in hist.get_bin_widths())
      rmax, _ = (arr.flatten() for arr in hist.get_bin_right_edges())
  
      bar_args = {}
      if "zorder" in kwargs:
          bar_args["zorder"] = kwargs.pop("zorder")
  
      alphas = _get_alpha_data(cmap_data, kwargs)
      if np.isscalar(alphas):
          alphas = np.ones_like(data) * alphas
  
      for i in range(len(rpos)):
          if data[i] > 0 or show_zero:
              bin_color = colors[i]
              # TODO: align = "edge"
              bars = ax.bar(phipos[i], dr[i], width=dphi[i], bottom=rpos[i], align='edge', color=bin_color,
                            edgecolor=kwargs.get("grid_color", cmap(0.5)), lw=kwargs.get("lw", 0.5),
                            alpha=alphas[i], **bar_args)
  
      ax.set_rmax(rmax.max())
      if show_colorbar:
          _add_colorbar(ax, cmap, cmap_data, norm)
docs: Polar map of polar histograms.
  
      Similar to map, but supports less parameters.