add more test cases.

crip/postprocess.py

@@ -11,7 +11,7 @@
 from .utils import *
 
 
-def fovCropRadius(sid: float, sdd: float, detectorWidth: float, pixelSize: float, roundOff=True) -> float:
+def fovCropRadius(sid: float, sdd: float, detectorWidth: float, pixelSize: float, roundOff=True) -> Or[int, float]:
     ''' Compute the radius [pixel] of the valid FOV of the reconstruction.
         `sid` and `sdd` are Source-Isocenter-Distance and Source-Detector-Distance, respectively.
         `detectorWidth` is the width of the detector, i.e., `#elements * elementWidth`.
@@ -75,7 +75,7 @@ def huNoRescale(image: TwoOrThreeD, b: float = -1000, k: float = 1) -> TwoOrThre
 
 
 @ConvertListNDArray
-def postlogsToProjections(postlogs: TwoOrThreeD, flat: Or[TwoD, float]) -> TwoOrThreeD:
-    ''' Invert `postlog` images to the original projections according to `flat` field.
+def postlogsToRaws(postlogs: TwoOrThreeD, flat: Or[TwoD, float]) -> TwoOrThreeD:
+    ''' Invert `postlog` images to the original raw projections according to `flat` field.
     '''
     return np.exp(-postlogs) * flat

test/_asset/spectrum.txt

@@ -0,0 +1,5 @@
+keV omega
+30 10000
+31 15000
+32 20000
+33 -1

test/_genasset.py

@@ -0,0 +1 @@
+import numpy as np

test/test_lowdose.py

@@ -12,10 +12,8 @@ class Test_injectGaussianNoise:
 
     def test_1(self):
         noisy = injectGaussianNoise(self.clean, self.sigma, self.mu)
-
         assert isOfSameShape(noisy, self.clean)
 
         noise = noisy - self.clean
-        another = np.random.randn(*self.clean.shape) * self.sigma + self.mu
-
-        assert stats.ttest_ind(noise.flatten(), another.flatten(), equal_var=True).pvalue > 0.1
+        assert np.mean(noise) == pytest.approx(self.mu, abs=1)
+        assert np.std(noise) == pytest.approx(self.sigma, abs=1)

test/test_physics.py

@@ -0,0 +1,43 @@
+import os
+import pytest
+import numpy as np
+from crip.physics import *
+from crip.utils import CripException
+
+
+def test_getCommonDensity():
+    assert getCommonDensity('H2O') == 1.0
+    assert getCommonDensity('Water') == 1.0
+
+    with pytest.raises(CripException):
+        getCommonDensity('h2o')
+
+
+class Test_Spectrum:
+
+    def test_init(self):
+        s = Spectrum(omega=[0, 10, 20, 0, *[0] * (151 - 4)])
+        assert s.omega[1] == 10
+        assert s.omega[2] == 20
+        assert s.omega[3] == 0
+        assert s.omega[4:].sum() == 0
+        assert s.sumOmega == 30
+
+    def test_isMonochromatic(self):
+        omega = [0.0] * 151
+        omega[50] = 1.0
+        is_mono, energy = Spectrum(omega).isMonochromatic()
+        assert is_mono == True
+        assert energy == 50
+
+    def test_fromText(self):
+        spec = Spectrum.fromText('50 1\n51 2\n52 3\n53 4\n54 5\n55 -1\n')
+        assert list(spec.omega[50:56]) == [1, 2, 3, 4, 5, 0]
+
+    def test_fromFile(self):
+        spec = Spectrum.fromFile(os.path.join(os.path.dirname(__file__), '_asset/spectrum.txt'))
+        assert list(spec.omega[30:34]) == [10000, 15000, 20000, 0]
+
+    def test_monochromatic(self):
+        spec = Spectrum.monochromatic(100)
+        assert [spec.omega[100], spec.omega[101]] == [10**5, 0]

test/test_postprocess.py

@@ -0,0 +1,43 @@
+import pytest
+import numpy as np
+from crip.postprocess import *
+
+
+def test_fovCropRadius():
+    assert fovCropRadius(1000, 1000, 1000, 1) == 447
+
+
+class test_fovCrop():
+    twoD = np.ones((16, 16))
+    threeD = np.ones((2, 16, 16))
+
+    def test_twoD(self):
+        cropped = fovCrop(self.twoD, radius=8)
+        assert cropped[0, 0] == 0
+        assert cropped[8, 8] == 1
+
+    def test_threeD(self):
+        cropped = fovCrop(self.threeD, radius=8, fill=10)
+        assert np.all(cropped[:, 0, 0] == 10)
+        assert np.all(cropped[:, 8, 8] == 1)
+
+
+def test_muToHU():
+    image = np.array([[1, 2], [3, 4]])
+    assert np.allclose(muToHU(image, 1), [[0, 1000], [2000, 3000]])
+
+
+def test_huToMu():
+    image = np.array([[0, 1000], [2000, 3000]])
+    assert np.allclose(huToMu(image, 1), [[1, 2], [3, 4]])
+
+
+def test_huNoRescale():
+    image = np.array([[-1000, 0], [1000, 2000]])
+    assert np.allclose(huNoRescale(image), [[0, 1000], [2000, 3000]])
+
+
+def test_postlogsToRaws():
+    postlogs = np.array([[0, 1]])
+    flat = 1000
+    assert np.allclose(postlogsToRaws(postlogs, flat), [[flat, flat * np.exp(-1)]])

test/test_shared.py

@@ -0,0 +1,96 @@
+import pytest
+import numpy as np
+from crip.shared import *
+
+
+class Test_rotate():
+    twoD = np.array([[1, 2], [3, 4]])
+    threeD = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])
+
+    def test_twoD(self):
+        img = self.twoD
+        assert np.array_equal(rotate(img, 90), np.array([[3, 1], [4, 2]]))
+        assert np.array_equal(rotate(img, 180), np.array([[4, 3], [2, 1]]))
+        assert np.array_equal(rotate(img, 270), np.array([[2, 4], [1, 3]]))
+        assert np.array_equal(rotate(img, 360), img)
+        assert np.array_equal(rotate(img, 0), img)
+
+        with pytest.raises(CripException):
+            rotate(img, 45)
+
+    def test_threeD(self):
+        img = self.threeD
+        assert np.array_equal(rotate(img, 90), np.array([[[3, 1], [4, 2]], [[7, 5], [8, 6]]]))
+        assert np.array_equal(rotate(img, 180), np.array([[[4, 3], [2, 1]], [[8, 7], [6, 5]]]))
+        assert np.array_equal(rotate(img, 270), np.array([[[2, 4], [1, 3]], [[6, 8], [5, 7]]]))
+        assert np.array_equal(rotate(img, 360), img)
+        assert np.array_equal(rotate(img, 0), img)
+
+        with pytest.raises(CripException):
+            rotate(img, 45)
+
+
+class Test_verticalFlip():
+    twoD = np.array([[1, 2], [3, 4]])
+    threeD = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])
+
+    def test_twoD(self):
+        img = self.twoD
+        assert np.array_equal(verticalFlip(img), np.array([[3, 4], [1, 2]]))
+
+    def test_threeD(self):
+        img = self.threeD
+        assert np.array_equal(verticalFlip(img), np.array([[[3, 4], [1, 2]], [[7, 8], [5, 6]]]))
+
+
+class Test_horizontalFlip():
+    twoD = np.array([[1, 2], [3, 4]])
+    threeD = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])
+
+    def test_twoD(self):
+        img = self.twoD
+        assert np.array_equal(horizontalFlip(img), np.array([[2, 1], [4, 3]]))
+
+    def test_threeD(self):
+        img = self.threeD
+        assert np.array_equal(horizontalFlip(img), np.array([[[2, 1], [4, 3]], [[6, 5], [8, 7]]]))
+
+
+class Test_stackFlip():
+    twoD = np.array([[1, 2], [3, 4]])
+    threeD = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])
+
+    def test_twoD(self):
+        img = self.twoD
+        with pytest.raises(CripException):
+            stackFlip(img)
+
+    def test_threeD(self):
+        img = self.threeD
+        assert np.array_equal(stackFlip(img), np.array([[[5, 6], [7, 8]], [[1, 2], [3, 4]]]))
+
+
+class Test_resizeTo():
+    pass
+
+
+class Test_resizeBy():
+    pass
+
+
+class Test_resize3D():
+    pass
+
+
+def test_permute():
+    top = np.array([[1, 2], [3, 4]])
+    bottom = np.array([[5, 6], [7, 8]])
+    threeD = np.stack([top, bottom])
+
+
+def test_fitPolyV2D2():
+    pass
+
+
+def test_applyPolyV2D2():
+    pass

test/test_spec.py

@@ -0,0 +1,12 @@
+import pytest
+import numpy as np
+
+from crip.spec import *
+
+
+# def test_decompMaterial():
+#     src = Atten([1, 2])
+#     base1 = Atten([3, 4])
+#     base2 = Atten([5, 6])
+#     res = decompMaterial(src, base1, base2, mode='coeff')
+#     assert np.allclose(res, [0.2, 0.4])