"""
Affine transforms
See http://www.cs.cornell.edu/courses/cs4620/2010fa/lectures/03transforms3D.pdf
"""
__all__ = [
"Zoom2D",
"RandomZoom2D",
"Rotate2D",
"RandomRotate2D",
"Shear2D",
"RandomShear2D",
"Translate2D",
"RandomTranslate2D",
]
import random
import math
import numpy as np
from ...core import ants_transform as tio
class Translate2D(object):
"""
Create an ANTs Affine Transform with a specified translation.
"""
def __init__(self, translation, reference=None, lazy=False):
"""
Initialize a Translate2D 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) != 2):
raise ValueError("translation argument must be list/tuple with two values!")
self.translation = translation
self.lazy = lazy
self.reference = reference
self.tx = tio.ANTsTransform(
precision="float", dimension=2, 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('r16'))
>>> tx = ants.contrib.Translate2D(translation=(10,0))
>>> img2_x = tx.transform(img)
>>> tx = ants.contrib.Translate2D(translation=(-10,0)) # other direction
>>> img2_x = tx.transform(img)
>>> tx = ants.contrib.Translate2D(translation=(0,10))
>>> img2_z = tx.transform(img)
>>> tx = ants.contrib.Translate2D(translation=(10,10))
>>> img2 = tx.transform(img)
"""
# convert to radians and unpack
translation_x, translation_y = self.translation
translation_matrix = np.array([[1, 0, translation_x], [0, 1, translation_y]])
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 RandomTranslate2D(object):
"""
Apply a Translate2D transform to an image, but with the
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 RandomTranslate2D 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('r16'))
>>> tx = ants.contrib.RandomShear2D(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]
)
self.params = (translation_x, translation_y)
tx = Translate2D(
(translation_x, translation_y), reference=self.reference, lazy=self.lazy
)
return tx.transform(X, y)
class Shear2D(object):
"""
Create an ANTs Affine Transform with a specified shear.
"""
def __init__(self, shear, reference=None, lazy=False):
"""
Initialize a Shear2D 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) != 2):
raise ValueError("shear argument must be list/tuple with two values!")
self.shear = shear
self.lazy = lazy
self.reference = reference
self.tx = tio.ANTsTransform(
precision="float", dimension=2, 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('r16'))
>>> tx = ants.contrib.Shear2D(shear=(10,0,0))
>>> img2_x = tx.transform(img)# x axis stays same
>>> tx = ants.contrib.Shear2D(shear=(-10,0,0)) # other direction
>>> img2_x = tx.transform(img)# x axis stays same
>>> tx = ants.contrib.Shear2D(shear=(0,10,0))
>>> img2_y = tx.transform(img) # y axis stays same
>>> tx = ants.contrib.Shear2D(shear=(0,0,10))
>>> img2_z = tx.transform(img) # z axis stays same
>>> tx = ants.contrib.Shear2D(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
shear_matrix = np.array([[1, shear_x, 0], [shear_y, 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 RandomShear2D(object):
"""
Apply a Shear2D 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 RandomShear2D 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('r16'))
>>> tx = ants.contrib.RandomShear2D(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])
self.params = (shear_x, shear_y)
tx = Shear2D((shear_x, shear_y), reference=self.reference, lazy=self.lazy)
return tx.transform(X, y)
class Rotate2D(object):
"""
Create an ANTs Affine Transform with a specified level
of rotation.
"""
def __init__(self, rotation, reference=None, lazy=False):
"""
Initialize a Rotate2D object
Arguments
---------
rotation : scalar
rotation value 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
"""
self.rotation = rotation
self.lazy = lazy
self.reference = reference
self.tx = tio.ANTsTransform(
precision="float", dimension=2, 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('r16'))
>>> tx = ants.contrib.Rotate2D(rotation=(10,-5,12))
>>> img2 = tx.transform(img)
"""
# unpack zoom range
rotation = self.rotation
# Rotation about X axis
theta = math.pi / 180 * rotation
rotation_matrix = np.array(
[[np.cos(theta), -np.sin(theta), 0], [np.sin(theta), np.cos(theta), 0]]
)
self.tx.set_parameters(rotation_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 RandomRotate2D(object):
"""
Apply a Rotated2D 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 RandomRotate2D 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('r16'))
>>> tx = ants.contrib.RandomRotate2D(rotation_range=(-10,10))
>>> img2 = tx.transform(img)
"""
# random draw in rotation range
rotation = random.gauss(self.rotation_range[0], self.rotation_range[1])
self.params = rotation
tx = Rotate2D(rotation, reference=self.reference, lazy=self.lazy)
return tx.transform(X, y)
class Zoom2D(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 Zoom2D 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) != 2):
raise ValueError("zoom_range argument must be list/tuple with two values!")
self.zoom = zoom
self.lazy = lazy
self.reference = reference
self.tx = tio.ANTsTransform(
precision="float", dimension=2, 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('r16'))
>>> tx = ants.contrib.Zoom2D(zoom=(0.8,0.8,0.8))
>>> img2 = tx.transform(img)
"""
# unpack zoom range
zoom_x, zoom_y = self.zoom
self.params = (zoom_x, zoom_y)
zoom_matrix = np.array([[zoom_x, 0, 0], [0, zoom_y, 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 RandomZoom2D(object):
"""
Apply a Zoom2D 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 RandomZoom2D 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('r16'))
>>> tx = ants.contrib.RandomZoom2D(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]))
)
self.params = (zoom_x, zoom_y)
tx = Zoom2D((zoom_x, zoom_y), reference=self.reference, lazy=self.lazy)
return tx.transform(X, y)
