class_docstr: A transformation from an input 3D space to an output 3D space defined
  by an affine matrix.
  
  It is defined by the affine matrix , and the name of the input and output
  spaces.
docstr: Create a new affine transform object.
  
  Parameters
  ----------
  
  input_space: string
      Name of the input space
  output_space: string
      Name of the output space
  affine: 4x4 ndarray
      Affine matrix giving the coordinate mapping between the
      input and output space.
docstr_tok: ["Create","a","new","affine","transform","object",".","Parameters","--","--","--","--","--","input_space",":","string","Name","of","the","input","space","output_space",":","string","Name","of","the","output","space","affine",":","4x4","ndarray","Affine","matrix","giving","the","coordinate","mapping","between","the","input","and","output","space","."]
code: def __init__(self, input_space, output_space, affine):
      """Create a new affine transform object.
  
      Parameters
      ----------
  
      input_space: string
          Name of the input space
      output_space: string
          Name of the output space
      affine: 4x4 ndarray
          Affine matrix giving the coordinate mapping between the
          input and output space.
      """
      assert hasattr(
          affine, "__array__"
      ), "affine argument should be an array-like"
      self.affine = affine
      self.input_space = input_space
      self.output_space = output_space
  
file_path: nipy/nipy/labs/datasets/transforms/affine_transform.py
imports: import numpy
  from .affine_utils import apply_affine
  from .transform import Transform
label_desc: Use image node_id 1 to create a new AffineTransform object from inherited base classes: Transform with example: obj = AffineTransform(input_space, output_space, affine)