SphinxExamples/src/Numerics/Optimizers/ExhaustiveOptimizer/Code.py

#!/usr/bin/env python
# =========================================================================
#
#  Copyright NumFOCUS
#
#  Licensed under the Apache License, Version 2.0 (the "License");
#  you may not use this file except in compliance with the License.
#  You may obtain a copy of the License at
#
#         https://www.apache.org/licenses/LICENSE-2.0.txt
#
#  Unless required by applicable law or agreed to in writing, software
#  distributed under the License is distributed on an "AS IS" BASIS,
#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
#  See the License for the specific language governing permissions and
#  limitations under the License.
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#
 
# Python example demonstrating itk.ExhaustiveOptimizer usage
import sys
from math import pi
 
import itk
 
EXIT_SUCCESS = 0
EXIT_FAILURE = 1
 
 
def main(argv):
    if len(argv) < 3:
        raise Exception(f"Usage: {argv[0]} fixed_image moving_image")
 
    fixed_image = itk.imread(argv[1], itk.F)
    moving_image = itk.imread(argv[2], itk.F)
 
    dimension = fixed_image.GetImageDimension()
    FixedImageType = type(fixed_image)
    MovingImageType = type(moving_image)
 
    if dimension == 2:
        transform = itk.Euler2DTransform[itk.D].New()
    else:
        raise Exception(f"Unsupported dimension: {dimension}")
 
    TransformInitializerType = itk.CenteredTransformInitializer[
        itk.MatrixOffsetTransformBase[itk.D, dimension, dimension],
        FixedImageType,
        MovingImageType,
    ]
    initializer = TransformInitializerType.New(
        Transform=transform,
        FixedImage=fixed_image,
        MovingImage=moving_image,
    )
    initializer.InitializeTransform()
 
    metric = itk.MeanSquaresImageToImageMetricv4[FixedImageType, MovingImageType].New()
 
    optimizer = itk.ExhaustiveOptimizerv4[itk.D].New()
 
    def print_iteration():
        print(
            f"Iteration:"
            f"{optimizer.GetCurrentIteration()}\t"
            f"{list(optimizer.GetCurrentIndex())} \t"
            f"{optimizer.GetCurrentValue():10.4f}\t"
            f"{list(optimizer.GetCurrentPosition())}\t"
        )
 
    optimizer.AddObserver(itk.IterationEvent(), print_iteration)
 
    angles = 12
    optimizer.SetNumberOfSteps([int(angles / 2), 0, 0])
 
    # Initialize scales and set back to optimizer
    scales = optimizer.GetScales()
    scales.SetSize(3)
    scales.SetElement(0, 2.0 * pi / angles)
    scales.SetElement(1, 1.0)
    scales.SetElement(2, 1.0)
    optimizer.SetScales(scales)
 
    RegistrationType = itk.ImageRegistrationMethodv4[FixedImageType, MovingImageType]
    registration = RegistrationType.New(
        Metric=metric,
        Optimizer=optimizer,
        FixedImage=fixed_image,
        MovingImage=moving_image,
        InitialTransform=transform,
        NumberOfLevels=1,
    )
 
    try:
        registration.Update()
 
        print(
            f"MinimumMetricValue: {optimizer.GetMinimumMetricValue():.4f}\t"
            f"MaximumMetricValue: {optimizer.GetMaximumMetricValue():.4f}\n"
            f"MinimumMetricValuePosition: {list(optimizer.GetMinimumMetricValuePosition())}\t"
            f"MaximumMetricValuePosition: {list(optimizer.GetMaximumMetricValuePosition())}\n"
            f"StopConditionDescription: {optimizer.GetStopConditionDescription()}\t"
        )
 
    except Exception as e:
        print(f"Exception caught: {e}")
        return EXIT_FAILURE
 
    return EXIT_SUCCESS
 
 
if __name__ == "__main__":
    main(sys.argv)