class_docstr: An instance which returns a dense multi-dimensional "meshgrid".
  
  An instance which returns a dense (or fleshed out) mesh-grid
  when indexed, so that each returned argument has the same shape.
  The dimensions and number of the output arrays are equal to the
  number of indexing dimensions.  If the step length is not a complex
  number, then the stop is not inclusive.
  
  However, if the step length is a **complex number** (e.g. 5j), then
  the integer part of its magnitude is interpreted as specifying the
  number of points to create between the start and stop values, where
  the stop value **is inclusive**.
  
  Returns
  -------
  mesh-grid `ndarrays` all of the same dimensions
  
  See Also
  --------
  ogrid : like `mgrid` but returns open (not fleshed out) mesh grids
  meshgrid: return coordinate matrices from coordinate vectors
  r_ : array concatenator
  :ref:`how-to-partition`
  
  Examples
  --------
  >>> np.mgrid[0:5, 0:5]
  array([[[0, 0, 0, 0, 0],
          [1, 1, 1, 1, 1],
          [2, 2, 2, 2, 2],
          [3, 3, 3, 3, 3],
          [4, 4, 4, 4, 4]],
         [[0, 1, 2, 3, 4],
          [0, 1, 2, 3, 4],
          [0, 1, 2, 3, 4],
          [0, 1, 2, 3, 4],
          [0, 1, 2, 3, 4]]])
  >>> np.mgrid[-1:1:5j]
  array([-1. , -0.5,  0. ,  0.5,  1. ])
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code: def __init__(self):
      super().__init__(sparse=False)
  
imports: import functools
  import sys
  import math
  import warnings
  import numpy
  from .._utils import set_module
  import numpy.core.numeric
  from numpy.core.numeric import ScalarType, array
  from numpy.core.numerictypes import issubdtype
  import numpy.matrixlib
  from .function_base import diff
  from numpy.core.multiarray import ravel_multi_index, unravel_index
  from numpy.core import overrides, linspace
  from numpy.lib.stride_tricks import as_strided
label_desc: Use image node_id 1 to create a new MGridClass object from inherited base classes: nd_grid with example: obj = MGridClass()