def test_generate_signal():
# Inputs for generate_signal
dimensions = np.array([10, 10, 10]) # What is the size of the brain
feature_size = [3]
feature_type = ['cube']
feature_coordinates = np.array([[5, 5, 5]])
signal_magnitude = [30]
# Generate a volume representing the location and quality of the signal
volume = sim.generate_signal(
dimensions=dimensions,
feature_coordinates=feature_coordinates,
feature_type=feature_type,
feature_size=feature_size,
signal_magnitude=signal_magnitude,
)
assert np.all(volume.shape == dimensions), "Check signal shape"
assert np.max(volume) == signal_magnitude, "Check signal magnitude"
assert np.sum(volume > 0) == math.pow(feature_size[0],
3), ("Check feature size")
assert volume[5, 5, 5] == signal_magnitude, "Check signal location"
assert volume[5, 5, 1] == 0, "Check noise location"
feature_coordinates = np.array([[5, 5, 5], [3, 3, 3], [7, 7, 7]])
# Check feature size is correct
volume = sim.generate_signal(dimensions=dimensions,
feature_coordinates=feature_coordinates,
feature_type=['loop', 'cavity', 'sphere'],
feature_size=[3],
signal_magnitude=signal_magnitude)
assert volume[5, 5, 5] == 0, "Loop is empty"
assert volume[3, 3, 3] == 0, "Cavity is empty"
assert volume[7, 7, 7] != 0, "Sphere is not empty"
# Check feature size manipulation
volume = sim.generate_signal(dimensions=dimensions,
feature_coordinates=feature_coordinates,
feature_type=['loop', 'cavity', 'sphere'],
feature_size=[1],
signal_magnitude=signal_magnitude)
assert volume[5, 6, 6] == 0, "Loop is too big"
assert volume[3, 5, 5] == 0, "Cavity is too big"
assert volume[7, 9, 9] == 0, "Sphere is too big"
# Check that out of bounds feature coordinates are corrected
feature_coordinates = np.array([0, 2, dimensions[2]])
x, y, z = sim._insert_idxs(feature_coordinates, feature_size[0],
dimensions)
assert x[1] - x[0] == 2, "x min not corrected"
assert y[1] - y[0] == 3, "y was corrected when it shouldn't be"
assert z[1] - z[0] == 1, "z max not corrected"
# Check that signal patterns are created
feature_coordinates = np.array([[5, 5, 5]])
volume = sim.generate_signal(
dimensions=dimensions,
feature_coordinates=feature_coordinates,
feature_type=feature_type,
feature_size=feature_size,
signal_magnitude=signal_magnitude,
signal_constant=0,
)
assert volume[4:7, 4:7, 4:7].std() > 0, "Signal is constant"
def test_generate_signal():
# Inputs for generate_signal
dimensions = np.array([10, 10, 10]) # What is the size of the brain
feature_size = [3]
feature_type = ['cube']
feature_coordinates = np.array([[5, 5, 5]])
signal_magnitude = [30]
# Generate a volume representing the location and quality of the signal
volume = sim.generate_signal(dimensions=dimensions,
feature_coordinates=feature_coordinates,
feature_type=feature_type,
feature_size=feature_size,
signal_magnitude=signal_magnitude,
)
assert np.all(volume.shape == dimensions), "Check signal shape"
assert np.max(volume) == signal_magnitude, "Check signal magnitude"
assert np.sum(volume > 0) == math.pow(feature_size[0], 3), (
"Check feature size")
assert volume[5, 5, 5] == signal_magnitude, "Check signal location"
assert volume[5, 5, 1] == 0, "Check noise location"
feature_coordinates = np.array(
[[5, 5, 5], [3, 3, 3], [7, 7, 7]])
# Check feature size is correct
volume = sim.generate_signal(dimensions=dimensions,
feature_coordinates=feature_coordinates,
feature_type=['loop', 'cavity', 'sphere'],
feature_size=[3],
signal_magnitude=signal_magnitude)
assert volume[5, 5, 5] == 0, "Loop is empty"
assert volume[3, 3, 3] == 0, "Cavity is empty"
assert volume[7, 7, 7] != 0, "Sphere is not empty"
# Check feature size manipulation
volume = sim.generate_signal(dimensions=dimensions,
feature_coordinates=feature_coordinates,
feature_type=['loop', 'cavity', 'sphere'],
feature_size=[1],
signal_magnitude=signal_magnitude)
assert volume[5, 6, 6] == 0, "Loop is too big"
assert volume[3, 5, 5] == 0, "Cavity is too big"
assert volume[7, 9, 9] == 0, "Sphere is too big"
# Check that out of bounds feature coordinates are corrected
feature_coordinates = np.array([0, 2, dimensions[2]])
x, y, z = sim._insert_idxs(feature_coordinates, feature_size[0],
dimensions)
assert x[1] - x[0] == 2, "x min not corrected"
assert y[1] - y[0] == 3, "y was corrected when it shouldn't be"
assert z[1] - z[0] == 1, "z max not corrected"
# Check that signal patterns are created
feature_coordinates = np.array([[5, 5, 5]])
volume = sim.generate_signal(dimensions=dimensions,
feature_coordinates=feature_coordinates,
feature_type=feature_type,
feature_size=feature_size,
signal_magnitude=signal_magnitude,
signal_constant=0,
)
assert volume[4:7, 4:7, 4:7].std() > 0, "Signal is constant"