def test_value(self):
key = "img"
for p in TEST_NDARRAYS:
shifter = ShiftIntensityd(keys=[key], offset=1.0)
result = shifter({key: p(self.imt)})
expected = self.imt + 1.0
assert_allclose(result[key], p(expected))
def test_value(self):
key = "img"
factor = np.random.rand()
offset = np.std(self.imt) * factor
shifter = ShiftIntensityd(keys=[key], offset=offset)
expected = shifter({key: self.imt})
std_shifter = StdShiftIntensityd(keys=[key], factor=factor)
result = std_shifter({key: self.imt})
np.testing.assert_allclose(result[key], expected[key], rtol=1e-5)
def test_factor(self):
key = "img"
stats = IntensityStatsd(keys=key, ops="max", key_prefix="orig")
shifter = ShiftIntensityd(keys=[key], offset=1.0, factor_key=["orig_max"])
data = {key: self.imt, PostFix.meta(key): {"affine": None}}
result = shifter(stats(data))
expected = self.imt + 1.0 * np.nanmax(self.imt)
np.testing.assert_allclose(result[key], expected)
import os
import tempfile
import unittest
import nibabel as nib
import numpy as np
from parameterized import parameterized
from monai.data import CacheNTransDataset
from monai.transforms import LoadNiftid, ShiftIntensityd
TEST_CASE_1 = [
[
LoadNiftid(keys="image"),
ShiftIntensityd(keys="image", offset=1.0),
ShiftIntensityd(keys="image", offset=2.0),
ShiftIntensityd(keys="image", offset=3.0),
],
(128, 128, 128),
]
class TestCacheNTransDataset(unittest.TestCase):
@parameterized.expand([TEST_CASE_1])
def test_n_trans(self, transform, expected_shape):
data_array = np.random.randint(0, 2, size=[128, 128, 128])
test_image = nib.Nifti1Image(data_array, np.eye(4))
with tempfile.TemporaryDirectory() as tempdir:
nib.save(test_image, os.path.join(tempdir, "test_image.nii.gz"))
test_data = [{"image": os.path.join(tempdir, "test_image.nii.gz")}]
def test_value(self):
key = "img"
shifter = ShiftIntensityd(keys=[key], offset=1.0)
result = shifter({key: self.imt})
expected = self.imt + 1.0
np.testing.assert_allclose(result[key], expected)