# ==========================================================================
#
#   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
#
#          http://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.
#
# ==========================================================================*/

import itk
from sys import argv


#
#  Check input parameters
#  INPUTS(fixedImage):  {BrainProtonDensitySliceBorder20.png}
#  INPUTS(movingImage): {BrainProtonDensitySliceShifted13x17y.png}
#
if len(argv) < 4:
    print("Missing Parameters")
    print(
        "Usage: ImageRegistration4.py fixedImageFile  movingImageFile outputImagefile"
    )
    exit()


#
#  Define data types
#
FixedImageType = itk.Image[itk.F, 2]
MovingImageType = itk.Image[itk.F, 2]
TransformType = itk.TranslationTransform[itk.D, 2]
OptimizerType = itk.RegularStepGradientDescentOptimizerv4[itk.D]
RegistrationType = itk.ImageRegistrationMethodv4[FixedImageType, MovingImageType]
MetricType = itk.MattesMutualInformationImageToImageMetricv4[
    FixedImageType, MovingImageType
]


#
#  Read the fixed and moving images using filenames
#  from the command line arguments
#
fixedImageReader = itk.ImageFileReader[FixedImageType].New()
movingImageReader = itk.ImageFileReader[MovingImageType].New()

fixedImageReader.SetFileName(argv[1])
movingImageReader.SetFileName(argv[2])

fixedImageReader.Update()
movingImageReader.Update()

fixedImage = fixedImageReader.GetOutput()
movingImage = movingImageReader.GetOutput()


#
#  Instantiate the classes for the registration framework
#
registration = RegistrationType.New()
imageMetric = MetricType.New()
transform = TransformType.New()
optimizer = OptimizerType.New()

registration.SetOptimizer(optimizer)
registration.SetMetric(imageMetric)

numberOfBins = 24

imageMetric.SetNumberOfHistogramBins(numberOfBins)
imageMetric.SetUseMovingImageGradientFilter(False)
imageMetric.SetUseFixedImageGradientFilter(False)

registration.SetFixedImage(fixedImage)
registration.SetMovingImage(movingImage)

registration.SetInitialTransform(transform)


#
#  Define optimizer parameters
#
optimizer.SetLearningRate(8.00)
optimizer.SetMinimumStepLength(0.001)
optimizer.SetNumberOfIterations(100)
optimizer.ReturnBestParametersAndValueOn()
optimizer.SetRelaxationFactor(0.8)


#
# One level registration process without shrinking and smoothing.
#
registration.SetNumberOfLevels(1)
registration.SetSmoothingSigmasPerLevel([0])
registration.SetShrinkFactorsPerLevel([1])

registration.SetMetricSamplingStrategy(RegistrationType.RANDOM)
registration.SetMetricSamplingPercentage(0.20)


#
# Iteration Observer
#
def iterationUpdate():
    currentParameter = registration.GetOutput().Get().GetParameters()
    print(
        "M: %f   P: %f %f "
        % (
            optimizer.GetValue(),
            currentParameter.GetElement(0),
            currentParameter.GetElement(1),
        )
    )


iterationCommand = itk.PyCommand.New()
iterationCommand.SetCommandCallable(iterationUpdate)
optimizer.AddObserver(itk.IterationEvent(), iterationCommand)

print("Starting registration")


#
#  Start the registration process
#
registration.Update()


#
# Get the final parameters of the transformation
#
finalParameters = registration.GetOutput().Get().GetParameters()

print("Final Registration Parameters ")
print(f"Translation X =  {finalParameters.GetElement(0):f}")
print(f"Translation Y =  {finalParameters.GetElement(1):f}")


#
# Now, we use the final transform for resampling the
# moving image.
#
resampler = itk.ResampleImageFilter[MovingImageType, FixedImageType].New()
resampler.SetTransform(registration.GetTransform())
resampler.SetInput(movingImageReader.GetOutput())

region = fixedImage.GetLargestPossibleRegion()

resampler.SetSize(region.GetSize())
resampler.SetOutputOrigin(fixedImage.GetOrigin())
resampler.SetOutputSpacing(fixedImage.GetSpacing())
resampler.SetOutputDirection(fixedImage.GetDirection())
resampler.SetDefaultPixelValue(100)

OutputImageType = itk.Image[itk.UC, 2]
outputCast = itk.CastImageFilter[FixedImageType, OutputImageType].New()
outputCast.SetInput(resampler.GetOutput())


#
#  Write the resampled image
#
writer = itk.ImageFileWriter[OutputImageType].New()
writer.SetFileName(argv[3])
writer.SetInput(outputCast.GetOutput())
writer.Update()