def __init__(self, geometry):
"""
Parameters
----------
geometry : GeometryCone3D
The geometry used for reconstruction
"""
self.geometry = geometry
self.initializer = tf.contrib.layers.xavier_initializer()
self.cosine_weight = tf.get_variable(name='cosine_weight', dtype=tf.float32,
initializer=ct_weights.cosine_weights_3d(geometry),
trainable=True)
self.recon_filter = tf.get_variable(name='recon_filter', dtype=tf.float32,
initializer=filters.ram_lak_3D(geometry),
trainable=True)
self.relu_alpha = tf.get_variable(name='relu_alpha', shape=(1), dtype=tf.float32,
initializer=tf.constant_initializer(0),
trainable=True)
# for multi perceptron if needed
self.mlp_all = tf.get_variable(name='mlp_all', dtype=tf.float32, initializer=tf.ones(1), trainable=False)
self.mlp_one = tf.get_variable(name='mlp_one', dtype=tf.float32, initializer=tf.ones(1), trainable=False)
self.mlp_two = tf.get_variable(name='mlp_two', dtype=tf.float32, initializer=tf.ones(1), trainable=False)
def __init__(self, geometry):
"""
Parameters
----------
geometry : GeometryCone3D
The geometry used for reconstruction
"""
self.geometry = geometry
self.cosine_weight = tf.get_variable(
name='cosine_weight',
dtype=tf.float32,
initializer=ct_weights.cosine_weights_3d(geometry),
trainable=True)
self.recon_filter = tf.get_variable(
name='recon_filter',
dtype=tf.float32,
initializer=filters.ram_lak_3D(geometry),
trainable=True)
self.relu_alpha = tf.get_variable(
name='relu_alpha',
shape=(1),
dtype=tf.float32,
initializer=tf.constant_initializer(0),
trainable=True)
def __init__(self, geometry):
self.geometry = geometry
self.cosine_weight = tf.get_variable(
name='cosine_weight',
dtype=tf.float32,
initializer=ct_weights.cosine_weights_3d(self.geometry),
trainable=False)
self.redundancy_weight = tf.get_variable(
name='redundancy_weight',
dtype=tf.float32,
initializer=ct_weights.parker_weights_3d(self.geometry),
trainable=False)
self.filter = tf.get_variable(name='reco_filter',
dtype=tf.float32,
initializer=ram_lak_3D(self.geometry),
trainable=False)
def __init__(self, geometry):
"""
Parameters
----------
geometry : GeometryCone3D
The geometry used for reconstruction
"""
self.geometry = geometry
self.cosine_weight = tf.get_variable(
name='cosine_weight',
dtype=tf.float32,
initializer=ct_weights.cosine_weights_3d(self.geometry),
trainable=False)
self.filter = tf.get_variable(name='reco_filter',
dtype=tf.float32,
initializer=ram_lak_3D(self.geometry),
trainable=False)
