def test_circle_acquisition_pattern_when_radius_is_greater_than_image(
self):
expected = self.setup.getExpectedOutputMatrix(self._testMethodName)
self.actual = aqc.circlePattern(self.mask_size, 1200)
self.assertTrue(self.setup.matrixEqual(expected, self.actual))
# Use this file as you wish to generate the images needed to answer the report
import src.project.Utilities as util
import numpy as np
import src.project.SelectiveImageAcquisition as sia
image = util.loadImage('images/brain.png')
rows, cols = image.shape
print(image.shape)
# code for cardiac cartesian
# mask = sia.cartesianPattern((rows, cols), 0.7)
mask = sia.circlePattern((rows, cols), 90)
shift_fft = util.getDFT(image)
filtered_image_fft = np.multiply(mask, shift_fft)
filtered_image = util.post_process_images(util.getImage(filtered_image_fft))
util.displayImage(filtered_image)