sino normalization: update cuda test

nabu/reconstruction/tests/test_sino_normalization.py

@@ -14,8 +14,8 @@ def bootstrap(request):
     cls = request.cls
     cls.sino = get_data("sino_refill.npy")
     cls.tol = 1e-7
-    cls.norm_array_1D = np.arange(cls.sino.shape[-1])
-    cls.norm_array_2D = np.arange(cls.sino.size).reshape(cls.sino.shape)
+    cls.norm_array_1D = np.arange(cls.sino.shape[-1]) + 1
+    cls.norm_array_2D = np.arange(cls.sino.size).reshape(cls.sino.shape) + 1
 
 
 @pytest.mark.usefixtures("bootstrap")
@@ -47,6 +47,16 @@ class TestSinoNormalization:
         assert np.max(np.abs(res - ref)) < self.tol
 
 
+
+    def get_normalization_reference_result(self, op, normalization_arr):
+        # Perform explicit operations to compare with numpy.divide, numpy.subtract, etc
+        if op == "subtraction":
+            ref = self.sino - normalization_arr
+        elif op == "division":
+            ref = self.sino / normalization_arr
+        return ref
+
+
     def test_sino_array_subtraction_and_division(self):
         with pytest.raises(ValueError):
             SinoNormalization(kind="subtraction", sinos_shape=self.sino.shape)
@@ -58,12 +68,7 @@ class TestSinoNormalization:
             )
             sino = self.sino.copy()
             sino_normalization.normalize(sino)
-            # Perform explicit operations to compare with numpy.divide, numpy.subtract, etc
-            if op == "subtraction":
-                ref = self.sino - normalization_arr
-            elif op == "division":
-                ref = self.sino / normalization_arr
-            #
+            ref = self.get_normalization_reference_result(op, normalization_arr)
             assert np.allclose(sino, ref), "operation=%s, normalization_array dims=%d" % (op, normalization_arr.ndim)
 
         compare_normalizations(self.norm_array_1D, "subtraction")
@@ -73,22 +78,22 @@ class TestSinoNormalization:
 
 
     @pytest.mark.skipif(not(__has_pycuda__), reason="Need pycuda for sinogram normalization with cuda backend")
-    def xtest_sino_array_subtraction_cuda(self):
+    def test_sino_array_subtraction_cuda(self):
         with pytest.raises(ValueError):
             CudaSinoNormalization(kind="subtraction", sinos_shape=self.sino.shape)
 
-        array_1D = np.arange(self.sino.shape[-1])
-        array_2D = np.arange(self.sino.size).reshape(self.sino.shape)
-
-        def compare_normalizations(normalization_arr):
+        def compare_normalizations(normalization_arr, op):
             sino_normalization = CudaSinoNormalization(
-                kind="subtraction", sinos_shape=self.sino.shape,
+                kind=op, sinos_shape=self.sino.shape,
                 normalization_array=normalization_arr
             )
             sino = garray.to_gpu(self.sino)
             sino_normalization.normalize(sino)
-            ref = self.sino - normalization_arr
+            ref = self.get_normalization_reference_result(op, normalization_arr)
             assert np.allclose(sino.get(), ref)
 
-        compare_normalizations(array_1D)
-        compare_normalizations(array_2D)
+        compare_normalizations(self.norm_array_1D, "subtraction")
+        compare_normalizations(self.norm_array_2D, "subtraction")
+        compare_normalizations(self.norm_array_1D, "division")
+        compare_normalizations(self.norm_array_2D, "division")
+