class_docstr: The main purpose of these class is to have auto adjust of axes size
  to the data with different layout of cuts.
class_docstr_tok: ["The","main","purpose","of","these","class","is","to","have","auto","adjust","of","axes","size","to","the","data","with","different","layout","of","cuts","."]
docstr: Plot the edges of a 3D map in all the views.
  
  Parameters
  -----------
  map: 3D ndarray
      The 3D map to be plotted. If it is a masked array, only
      the non-masked part will be plotted.
  affine: 4x4 ndarray
      The affine matrix giving the transformation from voxel
      indices to world space.
  color: matplotlib color: string or (r, g, b) value
      The color used to display the edge map
docstr_tok: ["Plot","the","edges","of","a","3D","map","in","all","the","views",".","Parameters","--","--","--","--","--","-","map",":","3D","ndarray","The","3D","map","to","be","plotted",".","If","it","is","a","masked","array",",","only","the","non-masked","part","will","be","plotted",".","affine",":","4x4","ndarray","The","affine","matrix","giving","the","transformation","from","voxel","indices","to","world","space",".","color",":","matplotlib","color",":","string","or","(","r",",","g",",","b",")","value","The","color","used","to","display","the","edge","map"]
code: def edge_map(self, map, affine, color="r"):
      """Plot the edges of a 3D map in all the views.
  
      Parameters
      -----------
      map: 3D ndarray
          The 3D map to be plotted. If it is a masked array, only
          the non-masked part will be plotted.
      affine: 4x4 ndarray
          The affine matrix giving the transformation from voxel
          indices to world space.
      color: matplotlib color: string or (r, g, b) value
          The color used to display the edge map
      """
      map, affine = _xyz_order(map, affine)
      kwargs = {"cmap": cm.alpha_cmap(color=color)}
      data_bounds = get_bounds(map.shape, affine)
  
      # For each ax, cut the data and plot it
      for cut_ax in self.axes.values():
          try:
              cut = cut_ax.do_cut(map, affine)
              edge_mask = _edge_map(cut)
          except IndexError:
              # We are cutting outside the indices of the data
              continue
          cut_ax.draw_cut(
              edge_mask,
              data_bounds,
              data_bounds,
              type="imshow",
              **kwargs,
          )
  
imports: import matplotlib
  import matplotlib.pyplot
  import numpy
  from matplotlib import transforms
  from nipy.utils import is_iterable
  from ..datasets import VolumeImg
  from .None import cm
  from .coord_tools import coord_transform, find_cut_coords, get_bounds, get_mask_bounds
  from .edge_detect import _edge_map
label_desc: Use image node_id 8 for calling the BaseSlicer obj's underlying member method code with example usage: obj.edge_map(map, affine, color) without return types