class_docstr: Affine warp constraints class.
  
  `AffineWarpConstraints` allow for
  very succinct definitions of constraints on
  the values of entries in affine transform matrices.
docstr: Combines two sets of constraints into a coherent single set.
docstr_tok: ["Combines","two","sets","of","constraints","into","a","coherent","single","set","."]
code: def combine_with(self, additional_constraints):
      """Combines two sets of constraints into a coherent single set."""
      x = additional_constraints
      if not isinstance(additional_constraints, AffineWarpConstraints):
          x = AffineWarpConstraints(additional_constraints)
      new_constraints = []
      for left, right in zip(self._constraints, x.constraints):
          new_constraints.append(
              [self._combine(x, y) for x, y in zip(left, right)]
          )
      return AffineWarpConstraints(new_constraints)
  
imports: from __future__ import absolute_import, division, print_function
  from itertools import chain
  import numpy
  import tensorflow
  from niftynet.layer.base_layer import Layer, LayerFromCallable, Invertible
label_desc: Use image node_id 9 for calling the AffineWarpConstraints obj's underlying member method code with example usage: obj.combine_with(additional_constraints) and returns: AffineWarpConstraints