--- a
+++ b/ants/contrib/sampling/affine3d.py
@@ -0,0 +1,802 @@
+"""
+Affine transforms
+
+See http://www.cs.cornell.edu/courses/cs4620/2010fa/lectures/03transforms3d.pdf
+"""
+
+__all__ = [
+    "Zoom3D",
+    "RandomZoom3D",
+    "Rotate3D",
+    "RandomRotate3D",
+    "Shear3D",
+    "RandomShear3D",
+    "Translate3D",
+    "RandomTranslate3D",
+    "Affine3D",
+]
+
+import random
+import math
+import numpy as np
+
+from ...core import ants_transform as tio
+
+class Affine3D(object):
+    """
+    Create a specified ANTs Affine Transform
+    """
+
+    def __init__(self, transformation, reference=None, lazy=False):
+        """
+        Initialize a Affine object
+
+        Arguments
+        ---------
+        transformation : array
+            affine transformation array (3x4)
+
+        reference : ANTsImage (optional but recommended)
+            image providing the reference space for the transform.
+            this will also set the transform fixed parameters.
+
+        lazy : boolean (default = False)
+            if True, calling the `transform` method only returns
+            the randomly generated transform and does not actually
+            transform the image
+        """
+        if (not isinstance(transformation, np.ndarray) or transformation.shape != (3,4)):
+            raise ValueError(
+                "transformation argument must be 3x4 Numpy array!"
+            )
+
+        self.transformation = transformation
+        self.lazy = lazy
+        self.reference = reference
+
+        self.tx = tio.ANTsTransform(
+            precision="float", dimension=3, transform_type="AffineTransform"
+        )
+        if self.reference is not None:
+            self.tx.set_fixed_parameters(self.reference.get_center_of_mass())
+
+    def transform(self, X=None, y=None):
+        """
+        Transform an image using an Affine transform with the given
+        translation parameters.  Return the transform if X=None.
+
+        Arguments
+        ---------
+        X : ANTsImage
+            Image to transform
+
+        y : ANTsImage (optional)
+            Another image to transform
+
+        Returns
+        -------
+        ANTsImage if y is None, else a tuple of ANTsImage types
+
+        Examples
+        --------
+        >>> import ants
+        >>> img = ants.image_read(ants.get_data('ch2'))
+        >>> tx = ants.contrib.Affine3D(transformation=np.array([[1, 0, 0, dx], [0, 1, 0, dy],[0, 0, 1, dz]])
+        >>> img2_x = tx.transform(img)# image translated by (dx, dy, dz)
+        """
+        # unpack
+
+        transformation_matrix = self.transformation
+
+
+        self.tx.set_parameters(transformation_matrix)
+        if self.lazy or X is None:
+            return self.tx
+        else:
+            if y is None:
+                return self.tx.apply_to_image(X, reference=self.reference)
+            else:
+                return (
+                    self.tx.apply_to_image(X, reference=self.reference),
+                    self.tx.apply_to_image(y, reference=self.reference),
+                )
+
+
+class Translate3D(object):
+    """
+    Create an ANTs Affine Transform with a specified translation.
+    """
+
+    def __init__(self, translation, reference=None, lazy=False):
+        """
+        Initialize a Translate3D object
+
+        Arguments
+        ---------
+        translation : list or tuple
+            translation values for each axis, in degrees.
+            Negative values can be used for translation in the
+            other direction
+
+        reference : ANTsImage (optional but recommended)
+            image providing the reference space for the transform.
+            this will also set the transform fixed parameters.
+
+        lazy : boolean (default = False)
+            if True, calling the `transform` method only returns
+            the randomly generated transform and does not actually
+            transform the image
+        """
+        if (not isinstance(translation, (list, tuple))) or (len(translation) != 3):
+            raise ValueError(
+                "translation argument must be list/tuple with three values!"
+            )
+
+        self.translation = translation
+        self.lazy = lazy
+        self.reference = reference
+
+        self.tx = tio.ANTsTransform(
+            precision="float", dimension=3, transform_type="AffineTransform"
+        )
+        if self.reference is not None:
+            self.tx.set_fixed_parameters(self.reference.get_center_of_mass())
+
+    def transform(self, X=None, y=None):
+        """
+        Transform an image using an Affine transform with the given
+        translation parameters.  Return the transform if X=None.
+
+        Arguments
+        ---------
+        X : ANTsImage
+            Image to transform
+
+        y : ANTsImage (optional)
+            Another image to transform
+
+        Returns
+        -------
+        ANTsImage if y is None, else a tuple of ANTsImage types
+
+        Examples
+        --------
+        >>> import ants
+        >>> img = ants.image_read(ants.get_data('ch2'))
+        >>> tx = ants.contrib.Translate3D(translation=(10,0,0))
+        >>> img2_x = tx.transform(img)# x axis stays same
+        >>> tx = ants.contrib.Translate3D(translation=(-10,0,0)) # other direction
+        >>> img2_x = tx.transform(img)# x axis stays same
+        >>> tx = ants.contrib.Translate3D(translation=(0,10,0))
+        >>> img2_y = tx.transform(img) # y axis stays same
+        >>> tx = ants.contrib.Translate3D(translation=(0,0,10))
+        >>> img2_z = tx.transform(img) # z axis stays same
+        >>> tx = ants.contrib.Translate3D(translation=(10,10,10))
+        >>> img2 = tx.transform(img)
+        """
+        # unpack
+        translation_x, translation_y, translation_z = self.translation
+
+        translation_matrix = np.array(
+            [
+                [1, 0, 0, translation_x],
+                [0, 1, 0, translation_y],
+                [0, 0, 1, translation_z],
+            ]
+        )
+        self.tx.set_parameters(translation_matrix)
+        if self.lazy or X is None:
+            return self.tx
+        else:
+            if y is None:
+                return self.tx.apply_to_image(X, reference=self.reference)
+            else:
+                return (
+                    self.tx.apply_to_image(X, reference=self.reference),
+                    self.tx.apply_to_image(y, reference=self.reference),
+                )
+
+
+class RandomTranslate3D(object):
+    """
+    Apply a Translate3D transform to an image, but with the shear
+    parameters randomly generated from a user-specified range.
+    The range is determined by a mean (first parameter) and standard deviation
+    (second parameter) via calls to random.gauss.
+    """
+
+    def __init__(self, translation_range, reference=None, lazy=False):
+        """
+        Initialize a RandomTranslate3D object
+
+        Arguments
+        ---------
+        translation_range : list or tuple
+            Lower and Upper bounds on rotation parameter, in degrees.
+            e.g. translation_range = (-10,10) will result in a random
+            draw of the rotation parameters between -10 and 10 degrees
+
+        reference : ANTsImage (optional but recommended)
+            image providing the reference space for the transform.
+            this will also set the transform fixed parameters.
+
+        lazy : boolean (default = False)
+            if True, calling the `transform` method only returns
+            the randomly generated transform and does not actually
+            transform the image
+        """
+        if (not isinstance(translation_range, (list, tuple))) or (
+            len(translation_range) != 2
+        ):
+            raise ValueError("shear_range argument must be list/tuple with two values!")
+
+        self.translation_range = translation_range
+        self.reference = reference
+        self.lazy = lazy
+
+    def transform(self, X=None, y=None):
+        """
+        Transform an image using an Affine transform with
+        translation parameters randomly generated from the user-specified
+        range.  Return the transform if X=None.
+
+        Arguments
+        ---------
+        X : ANTsImage
+            Image to transform
+
+        y : ANTsImage (optional)
+            Another image to transform
+
+        Returns
+        -------
+        ANTsImage if y is None, else a tuple of ANTsImage types
+
+        Examples
+        --------
+        >>> import ants
+        >>> img = ants.image_read(ants.get_data('ch2'))
+        >>> tx = ants.contrib.RandomShear3D(translation_range=(-10,10))
+        >>> img2 = tx.transform(img)
+        """
+        # random draw in translation range
+        translation_x = random.gauss(
+            self.translation_range[0], self.translation_range[1]
+        )
+        translation_y = random.gauss(
+            self.translation_range[0], self.translation_range[1]
+        )
+        translation_z = random.gauss(
+            self.translation_range[0], self.translation_range[1]
+        )
+        self.params = (translation_x, translation_y, translation_z)
+
+        tx = Translate3D(
+            (translation_x, translation_y, translation_z),
+            reference=self.reference,
+            lazy=self.lazy,
+        )
+
+        return tx.transform(X, y)
+
+
+class Shear3D(object):
+    """
+    Create an ANTs Affine Transform with a specified shear.
+    """
+
+    def __init__(self, shear, reference=None, lazy=False):
+        """
+        Initialize a Shear3D object
+
+        Arguments
+        ---------
+        shear : list or tuple
+            shear values for each axis, in degrees.
+            Negative values can be used for shear in the
+            other direction
+
+        reference : ANTsImage (optional but recommended)
+            image providing the reference space for the transform.
+            this will also set the transform fixed parameters.
+
+        lazy : boolean (default = False)
+            if True, calling the `transform` method only returns
+            the randomly generated transform and does not actually
+            transform the image
+        """
+        if (not isinstance(shear, (list, tuple))) or (len(shear) != 3):
+            raise ValueError("shear argument must be list/tuple with three values!")
+
+        self.shear = shear
+        self.lazy = lazy
+        self.reference = reference
+
+        self.tx = tio.ANTsTransform(
+            precision="float", dimension=3, transform_type="AffineTransform"
+        )
+        if self.reference is not None:
+            self.tx.set_fixed_parameters(self.reference.get_center_of_mass())
+
+    def transform(self, X=None, y=None):
+        """
+        Transform an image using an Affine transform with the given
+        shear parameters.  Return the transform if X=None.
+
+        Arguments
+        ---------
+        X : ANTsImage
+            Image to transform
+
+        y : ANTsImage (optional)
+            Another image to transform
+
+        Returns
+        -------
+        ANTsImage if y is None, else a tuple of ANTsImage types
+
+        Examples
+        --------
+        >>> import ants
+        >>> img = ants.image_read(ants.get_data('ch2'))
+        >>> tx = ants.contrib.Shear3D(shear=(10,0,0))
+        >>> img2_x = tx.transform(img)# x axis stays same
+        >>> tx = ants.contrib.Shear3D(shear=(-10,0,0)) # other direction
+        >>> img2_x = tx.transform(img)# x axis stays same
+        >>> tx = ants.contrib.Shear3D(shear=(0,10,0))
+        >>> img2_y = tx.transform(img) # y axis stays same
+        >>> tx = ants.contrib.Shear3D(shear=(0,0,10))
+        >>> img2_z = tx.transform(img) # z axis stays same
+        >>> tx = ants.contrib.Shear3D(shear=(10,10,10))
+        >>> img2 = tx.transform(img)
+        """
+        # convert to radians and unpack
+        shear = [math.pi / 180 * s for s in self.shear]
+        shear_x, shear_y, shear_z = shear
+
+        shear_matrix = np.array(
+            [
+                [1, shear_x, shear_x, 0],
+                [shear_y, 1, shear_y, 0],
+                [shear_z, shear_z, 1, 0],
+            ]
+        )
+        self.tx.set_parameters(shear_matrix)
+        if self.lazy or X is None:
+            return self.tx
+        else:
+            if y is None:
+                return self.tx.apply_to_image(X, reference=self.reference)
+            else:
+                return (
+                    self.tx.apply_to_image(X, reference=self.reference),
+                    self.tx.apply_to_image(y, reference=self.reference),
+                )
+
+
+class RandomShear3D(object):
+    """
+    Apply a Shear3D transform to an image, but with the shear
+    parameters randomly generated from a user-specified range.
+    The range is determined by a mean (first parameter) and standard deviation
+    (second parameter) via calls to random.gauss.
+    """
+
+    def __init__(self, shear_range, reference=None, lazy=False):
+        """
+        Initialize a RandomShear3D object
+
+        Arguments
+        ---------
+        shear_range : list or tuple
+            Lower and Upper bounds on rotation parameter, in degrees.
+            e.g. shear_range = (-10,10) will result in a random
+            draw of the rotation parameters between -10 and 10 degrees
+
+        reference : ANTsImage (optional but recommended)
+            image providing the reference space for the transform.
+            this will also set the transform fixed parameters.
+
+        lazy : boolean (default = False)
+            if True, calling the `transform` method only returns
+            the randomly generated transform and does not actually
+            transform the image
+        """
+        if (not isinstance(shear_range, (list, tuple))) or (len(shear_range) != 2):
+            raise ValueError("shear_range argument must be list/tuple with two values!")
+
+        self.shear_range = shear_range
+        self.reference = reference
+        self.lazy = lazy
+
+    def transform(self, X=None, y=None):
+        """
+        Transform an image using an Affine transform with
+        shear parameters randomly generated from the user-specified
+        range.  Return the transform if X=None.
+
+        Arguments
+        ---------
+        X : ANTsImage
+            Image to transform
+
+        y : ANTsImage (optional)
+            Another image to transform
+
+        Returns
+        -------
+        ANTsImage if y is None, else a tuple of ANTsImage types
+
+        Examples
+        --------
+        >>> import ants
+        >>> img = ants.image_read(ants.get_data('ch2'))
+        >>> tx = ants.contrib.RandomShear3D(shear_range=(-10,10))
+        >>> img2 = tx.transform(img)
+        """
+        # random draw in shear range
+        shear_x = random.gauss(self.shear_range[0], self.shear_range[1])
+        shear_y = random.gauss(self.shear_range[0], self.shear_range[1])
+        shear_z = random.gauss(self.shear_range[0], self.shear_range[1])
+        self.params = (shear_x, shear_y, shear_z)
+
+        tx = Shear3D(
+            (shear_x, shear_y, shear_z), reference=self.reference, lazy=self.lazy
+        )
+
+        return tx.transform(X, y)
+
+
+class Rotate3D(object):
+    """
+    Create an ANTs Affine Transform with a specified level
+    of rotation.
+    """
+
+    def __init__(self, rotation, reference=None, lazy=False):
+        """
+        Initialize a Rotate3D object
+
+        Arguments
+        ---------
+        rotation : list or tuple
+            rotation values for each axis, in degrees.
+            Negative values can be used for rotation in the
+            other direction
+
+        reference : ANTsImage (optional but recommended)
+            image providing the reference space for the transform.
+            this will also set the transform fixed parameters.
+
+        lazy : boolean (default = False)
+            if True, calling the `transform` method only returns
+            the randomly generated transform and does not actually
+            transform the image
+        """
+        if (not isinstance(rotation, (list, tuple))) or (len(rotation) != 3):
+            raise ValueError("rotation argument must be list/tuple with three values!")
+
+        self.rotation = rotation
+        self.lazy = lazy
+        self.reference = reference
+
+        self.tx = tio.ANTsTransform(
+            precision="float", dimension=3, transform_type="AffineTransform"
+        )
+        if self.reference is not None:
+            self.tx.set_fixed_parameters(self.reference.get_center_of_mass())
+
+    def transform(self, X=None, y=None):
+        """
+        Transform an image using an Affine transform with the given
+        rotation parameters.  Return the transform if X=None.
+
+        Arguments
+        ---------
+        X : ANTsImage
+            Image to transform
+
+        y : ANTsImage (optional)
+            Another image to transform
+
+        Returns
+        -------
+        ANTsImage if y is None, else a tuple of ANTsImage types
+
+        Examples
+        --------
+        >>> import ants
+        >>> img = ants.image_read(ants.get_data('ch2'))
+        >>> tx = ants.contrib.Rotate3D(rotation=(10,-5,12))
+        >>> img2 = tx.transform(img)
+        """
+        # unpack zoom range
+        rotation_x, rotation_y, rotation_z = self.rotation
+
+        # Rotation about X axis
+        theta_x = math.pi / 180 * rotation_x
+        rotate_matrix_x = np.array(
+            [
+                [1, 0, 0, 0],
+                [0, math.cos(theta_x), -math.sin(theta_x), 0],
+                [0, math.sin(theta_x), math.cos(theta_x), 0],
+                [0, 0, 0, 1],
+            ]
+        )
+
+        # Rotation about Y axis
+        theta_y = math.pi / 180 * rotation_y
+        rotate_matrix_y = np.array(
+            [
+                [math.cos(theta_y), 0, math.sin(theta_y), 0],
+                [0, 1, 0, 0],
+                [-math.sin(theta_y), 0, math.cos(theta_y), 0],
+                [0, 0, 0, 1],
+            ]
+        )
+
+        # Rotation about Z axis
+        theta_z = math.pi / 180 * rotation_z
+        rotate_matrix_z = np.array(
+            [
+                [math.cos(theta_z), -math.sin(theta_z), 0, 0],
+                [math.sin(theta_z), math.cos(theta_z), 0, 0],
+                [0, 0, 1, 0],
+                [0, 0, 0, 1],
+            ]
+        )
+        rotate_matrix = rotate_matrix_x.dot(rotate_matrix_y).dot(rotate_matrix_z)[:3, :]
+
+        self.tx.set_parameters(rotate_matrix)
+        if self.lazy or X is None:
+            return self.tx
+        else:
+            if y is None:
+                return self.tx.apply_to_image(X, reference=self.reference)
+            else:
+                return (
+                    self.tx.apply_to_image(X, reference=self.reference),
+                    self.tx.apply_to_image(y, reference=self.reference),
+                )
+
+
+class RandomRotate3D(object):
+    """
+    Apply a Rotate3D transform to an image, but with the zoom
+    parameters randomly generated from a user-specified range.
+    The range is determined by a mean (first parameter) and standard deviation
+    (second parameter) via calls to random.gauss.
+    """
+
+    def __init__(self, rotation_range, reference=None, lazy=False):
+        """
+        Initialize a RandomRotate3D object
+
+        Arguments
+        ---------
+        rotation_range : list or tuple
+            Lower and Upper bounds on rotation parameter, in degrees.
+            e.g. rotation_range = (-10,10) will result in a random
+            draw of the rotation parameters between -10 and 10 degrees
+
+        reference : ANTsImage (optional but recommended)
+            image providing the reference space for the transform.
+            this will also set the transform fixed parameters.
+
+        lazy : boolean (default = False)
+            if True, calling the `transform` method only returns
+            the randomly generated transform and does not actually
+            transform the image
+        """
+        if (not isinstance(rotation_range, (list, tuple))) or (
+            len(rotation_range) != 2
+        ):
+            raise ValueError(
+                "rotation_range argument must be list/tuple with two values!"
+            )
+
+        self.rotation_range = rotation_range
+        self.reference = reference
+        self.lazy = lazy
+
+    def transform(self, X=None, y=None):
+        """
+        Transform an image using an Affine transform with
+        rotation parameters randomly generated from the user-specified
+        range.  Return the transform if X=None.
+
+        Arguments
+        ---------
+        X : ANTsImage
+            Image to transform
+
+        y : ANTsImage (optional)
+            Another image to transform
+
+        Returns
+        -------
+        ANTsImage if y is None, else a tuple of ANTsImage types
+
+        Examples
+        --------
+        >>> import ants
+        >>> img = ants.image_read(ants.get_data('ch2'))
+        >>> tx = ants.contrib.RandomRotate3D(rotation_range=(-10,10))
+        >>> img2 = tx.transform(img)
+        """
+        # random draw in rotation range
+        rotation_x = random.gauss(self.rotation_range[0], self.rotation_range[1])
+        rotation_y = random.gauss(self.rotation_range[0], self.rotation_range[1])
+        rotation_z = random.gauss(self.rotation_range[0], self.rotation_range[1])
+        self.params = (rotation_x, rotation_y, rotation_z)
+
+        tx = Rotate3D(
+            (rotation_x, rotation_y, rotation_z),
+            reference=self.reference,
+            lazy=self.lazy,
+        )
+
+        return tx.transform(X, y)
+
+
+class Zoom3D(object):
+    """
+    Create an ANTs Affine Transform with a specified level
+    of zoom. Any value greater than 1 implies a "zoom-out" and anything
+    less than 1 implies a "zoom-in".
+    """
+
+    def __init__(self, zoom, reference=None, lazy=False):
+        """
+        Initialize a Zoom3D object
+
+        Arguments
+        ---------
+        zoom_range : list or tuple
+            Lower and Upper bounds on zoom parameter.
+            e.g. zoom_range = (0.7,0.9) will result in a random
+            draw of the zoom parameters between 0.7 and 0.9
+
+        reference : ANTsImage (optional but recommended)
+            image providing the reference space for the transform.
+            this will also set the transform fixed parameters.
+
+        lazy : boolean (default = False)
+            if True, calling the `transform` method only returns
+            the randomly generated transform and does not actually
+            transform the image
+        """
+        if (not isinstance(zoom, (list, tuple))) or (len(zoom) != 3):
+            raise ValueError(
+                "zoom_range argument must be list/tuple with three values!"
+            )
+
+        self.zoom = zoom
+        self.lazy = lazy
+        self.reference = reference
+
+        self.tx = tio.ANTsTransform(
+            precision="float", dimension=3, transform_type="AffineTransform"
+        )
+        if self.reference is not None:
+            self.tx.set_fixed_parameters(self.reference.get_center_of_mass())
+
+    def transform(self, X=None, y=None):
+        """
+        Transform an image using an Affine transform with the given
+        zoom parameters.  Return the transform if X=None.
+
+        Arguments
+        ---------
+        X : ANTsImage
+            Image to transform
+
+        y : ANTsImage (optional)
+            Another image to transform
+
+        Returns
+        -------
+        ANTsImage if y is None, else a tuple of ANTsImage types
+
+        Examples
+        --------
+        >>> import ants
+        >>> img = ants.image_read(ants.get_data('ch2'))
+        >>> tx = ants.contrib.Zoom3D(zoom=(0.8,0.8,0.8))
+        >>> img2 = tx.transform(img)
+        """
+        # unpack zoom range
+        zoom_x, zoom_y, zoom_z = self.zoom
+
+        self.params = (zoom_x, zoom_y, zoom_z)
+        zoom_matrix = np.array(
+            [[zoom_x, 0, 0, 0], [0, zoom_y, 0, 0], [0, 0, zoom_z, 0]]
+        )
+        self.tx.set_parameters(zoom_matrix)
+        if self.lazy or X is None:
+            return self.tx
+        else:
+            if y is None:
+                return self.tx.apply_to_image(X, reference=self.reference)
+            else:
+                return (
+                    self.tx.apply_to_image(X, reference=self.reference),
+                    self.tx.apply_to_image(y, reference=self.reference),
+                )
+
+
+class RandomZoom3D(object):
+    """
+    Apply a Zoom3D transform to an image, but with the zoom
+    parameters randomly generated from a user-specified range.
+    The range is determined by a mean (first parameter) and standard deviation
+    (second parameter) via calls to random.gauss.
+    """
+
+    def __init__(self, zoom_range, reference=None, lazy=False):
+        """
+        Initialize a RandomZoom3D object
+
+        Arguments
+        ---------
+        zoom_range : list or tuple
+            Lower and Upper bounds on zoom parameter.
+            e.g. zoom_range = (0.7,0.9) will result in a random
+            draw of the zoom parameters between 0.7 and 0.9
+
+        reference : ANTsImage (optional but recommended)
+            image providing the reference space for the transform
+            this will also set the transform fixed parameters.
+
+        lazy : boolean (default = False)
+            if True, calling the `transform` method only returns
+            the randomly generated transform and does not actually
+            transform the image
+        """
+        if (not isinstance(zoom_range, (list, tuple))) or (len(zoom_range) != 2):
+            raise ValueError("zoom_range argument must be list/tuple with two values!")
+
+        self.zoom_range = zoom_range
+        self.reference = reference
+        self.lazy = lazy
+
+    def transform(self, X=None, y=None):
+        """
+        Transform an image using an Affine transform with
+        zoom parameters randomly generated from the user-specified
+        range.  Return the transform if X=None.
+
+        Arguments
+        ---------
+        X : ANTsImage
+            Image to transform
+
+        y : ANTsImage (optional)
+            Another image to transform
+
+        Returns
+        -------
+        ANTsImage if y is None, else a tuple of ANTsImage types
+
+        Examples
+        --------
+        >>> import ants
+        >>> img = ants.image_read(ants.get_data('ch2'))
+        >>> tx = ants.contrib.RandomZoom3D(zoom_range=(0.8,0.9))
+        >>> img2 = tx.transform(img)
+        """
+        # random draw in zoom range
+        zoom_x = np.exp(
+            random.gauss(np.log(self.zoom_range[0]), np.log(self.zoom_range[1]))
+        )
+        zoom_y = np.exp(
+            random.gauss(np.log(self.zoom_range[0]), np.log(self.zoom_range[1]))
+        )
+        zoom_z = np.exp(
+            random.gauss(np.log(self.zoom_range[0]), np.log(self.zoom_range[1]))
+        )
+        self.params = (zoom_x, zoom_y, zoom_z)
+
+        tx = Zoom3D((zoom_x, zoom_y, zoom_z), reference=self.reference, lazy=self.lazy)
+
+        return tx.transform(X, y)