Python AffineTransform.from_start_step方法代码示例

# 需要导入模块: from nipy.core.api import AffineTransform [as 别名]
# 或者: from nipy.core.api.AffineTransform import from_start_step [as 别名]
 def setUp(self):
     names = ['zspace', 'yspace', 'xspace']
     shape = (10,20,30)
     self.img = Image(np.zeros(shape), 
                      AffineTransform.from_start_step(names, names, (0,)*3, (1,)*3))
     self.img2 = Image(np.ones(shape), 
                       AffineTransform.from_start_step(names, names, (0,)*3, (1,)*3))
                    
     shape = (3,5,4)
     self.img3 = Image(np.zeros(shape), 
                       AffineTransform.from_start_step(names, names, (0,)*3, (1,)*3))
     self.img4 = Image(np.zeros(shape), 
                       AffineTransform.from_start_step(names, names, (0,)*3, (1,)*3))

# 需要导入模块: from nipy.core.api import AffineTransform [as 别名]
# 或者: from nipy.core.api.AffineTransform import from_start_step [as 别名]
   def __init__(self, data, affine, axis_names, metadata={}, 
                lps=True):
      """ Creates a new nipy image with an affine mapping.

      Parameters
      ----------

      data : ndarray
         ndarray representing the data.

      affine : 4x4 ndarray
         affine transformation to the reference coordinate system

      axis_names : [string]
         names of the axes in the coordinate system.
      """

      if len(axis_names) < 3:
         raise ValueError('XYZImage must have a minimum of 3 axes')

      # The first three axes are assumed to be the
      # spatial ones
      xyz_transform = XYZTransform(affine, axis_names[:3], lps)
      nonspatial_names = axis_names[3:]
        
      if nonspatial_names:
         nonspatial_affine_transform = AffineTransform.from_start_step(nonspatial_names, nonspatial_names, [0]*(data.ndim-3), [1]*(data.ndim-3))
         full_dimensional_affine_transform = cmap_product(xyz_transform, nonspatial_affine_transform)
      else:
         full_dimensional_affine_transform = xyz_transform 

      self._xyz_transform = xyz_transform

      Image.__init__(self, data, full_dimensional_affine_transform,
                     metadata=metadata)

# 需要导入模块: from nipy.core.api import AffineTransform [as 别名]
# 或者: from nipy.core.api.AffineTransform import from_start_step [as 别名]
def test_nonaffine():
    # resamples an image along a curve through the image.
    #
    # FIXME: use the reference.evaluate.Grid to perform this nicer
    # FIXME: Remove pylab references
    def curve(x):  # function accept N by 1, returns N by 2
        return np.vstack([5 * np.sin(x.T), 5 * np.cos(x.T)]).T + [52, 47]

    for names in (("xy", "ij", "t", "u"), ("ij", "xy", "t", "s")):
        in_names, out_names, tin_names, tout_names = names
        g = AffineTransform.from_params(in_names, out_names, np.identity(3))
        img = Image(np.ones((100, 90)), g)
        img[50:55, 40:55] = 3.0
        tcoordmap = AffineTransform.from_start_step(tin_names, tout_names, [0], [np.pi * 1.8 / 100])
        ir = resample(img, tcoordmap, curve, (100,))
    if gui_review:
        import pylab

        pylab.figure(num=3)
        pylab.imshow(img, interpolation="nearest")
        d = curve(np.linspace(0, 1.8 * np.pi, 100))
        pylab.plot(d[0], d[1])
        pylab.gca().set_ylim([0, 99])
        pylab.gca().set_xlim([0, 89])
        pylab.figure(num=4)
        pylab.plot(np.asarray(ir))

# 需要导入模块: from nipy.core.api import AffineTransform [as 别名]
# 或者: from nipy.core.api.AffineTransform import from_start_step [as 别名]
    def __init__(self, data, affine, coord_sys, metadata=None):
        """ Creates a new nipy image with an affine mapping.

            Parameters
            ----------

            data : ndarray
                ndarray representing the data.
            affine : 4x4 ndarray
                affine transformation to the reference coordinate system
            coord_system : string
                name of the reference coordinate system.
        """

        function_domain = CoordinateSystem(['axis%d' % i for i in range(3)], 
                                        name=coord_sys)
        function_range = CoordinateSystem(['x','y','z'], name='world')
        spatial_coordmap = AffineTransform(function_domain, function_range,
                                           affine)

        nonspatial_names = ['axis%d' % i for i in range(3, data.ndim)]
        if nonspatial_names:
            nonspatial_coordmap = AffineTransform.from_start_step(nonspatial_names, nonspatial_names, [0]*(data.ndim-3), [1]*(data.ndim-3))
            full_coordmap = cmap_product(coordmap, nonspatial_coordmap)
        else:
            full_coordmap = spatial_coordmap 

        self._spatial_coordmap = spatial_coordmap

        self.coord_sys = coord_sys
        Image.__init__(self, data, full_coordmap) 
        if metadata is not None:
            self.metadata = metadata