update all test to use pytest and xp/dev matrix

gschramm · Dec 23, 2023 · cb74010 · cb74010
1 parent dc0a103
commit cb74010
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Showing 4 changed files with 95 additions and 231 deletions.
diff --git a/test/parallelproj/test_nontof_joseph.py b/test/parallelproj/test_nontof_joseph.py
@@ -1,14 +1,34 @@
 from __future__ import annotations
 
-import unittest
+import pytest
 import parallelproj
 import numpy.array_api as nparr
 import array_api_compat.numpy as np
 
 from types import ModuleType
 
+# generate list of array_api modules / device combinations to test
+xp_dev_list = [(np, 'cpu')]
 
-def fwd_test(xp: ModuleType,
+if np.__version__ >= '1.25':
+    xp_dev_list.append((nparr, 'cpu'))
+
+if parallelproj.cupy_enabled:
+    import array_api_compat.cupy as cp
+    xp_dev_list.append((cp, 'cuda'))
+
+if parallelproj.torch_enabled:
+    import array_api_compat.torch as torch
+    xp_dev_list.append((torch, 'cpu'))
+
+    if parallelproj.cuda_present:
+        xp_dev_list.append((torch, 'cuda'))
+
+pytestmark = pytest.mark.parametrize("xp,dev", xp_dev_list)
+
+#---------------------------------------------------------------------------------------
+
+def test_fwd(xp: ModuleType,
              dev: str,
              verbose: bool = True,
              rtol: float = 1e-5,
@@ -97,7 +117,7 @@ def fwd_test(xp: ModuleType,
 #--------------------------------------------------------------------------
 
 
-def adjointness_test(xp: ModuleType,
+def test_adjointness(xp: ModuleType,
                      dev: str,
                      nLORs: int = 1000000,
                      seed: int = 1,
@@ -166,63 +186,3 @@ def adjointness_test(xp: ModuleType,
     isclose = (abs(ip_a - ip_b) <= atol + rtol * abs(ip_b))
 
     assert isclose
-
-
-#--------------------------------------------------------------------------
-
-
-class TestNonTOFJoseph(unittest.TestCase):
-    """test for non TOF joseph projections"""
-
-    def test_fwd(self):
-        fwd_test(np, 'cpu')
-        if np.__version__ >= '1.25':
-            fwd_test(nparr, 'cpu')
-
-    if parallelproj.cupy_enabled:
-
-        def test_fwd_cp(self):
-            import array_api_compat.cupy as cp
-            fwd_test(cp, 'cuda')
-
-    if parallelproj.torch_enabled:
-
-        def test_fwd_torch(self):
-            import array_api_compat.torch as torch
-            fwd_test(torch, 'cpu')
-
-    if parallelproj.torch_enabled and parallelproj.cupy_enabled:
-
-        def test_fwd_torch_cuda(self):
-            import array_api_compat.torch as torch
-            fwd_test(torch, 'cuda')
-
-    def test_adjoint(self):
-        """test non TOF joseph forward projection using different backends"""
-        adjointness_test(np, 'cpu')
-        if np.__version__ >= '1.25':
-            adjointness_test(nparr, 'cpu')
-
-    if parallelproj.cupy_enabled:
-
-        def test_adjoint_cp(self):
-            import array_api_compat.cupy as cp
-            adjointness_test(cp, 'cuda')
-
-    if parallelproj.torch_enabled:
-
-        def test_adjoint_torch(self):
-            import array_api_compat.torch as torch
-            adjointness_test(torch, 'cpu')
-
-    if parallelproj.torch_enabled and parallelproj.cupy_enabled:
-
-        def test_adjoint_torch_cuda(self):
-            import array_api_compat.torch as torch
-            adjointness_test(torch, 'cuda')
-
-
-#--------------------------------------------------------------------------
-
-if __name__ == '__main__':
-    unittest.main()
diff --git a/test/parallelproj/test_projectors.py b/test/parallelproj/test_projectors.py
@@ -1,11 +1,31 @@
 from __future__ import annotations
 
-import unittest
+import pytest
 import parallelproj
 import numpy.array_api as nparr
 import array_api_compat
 import array_api_compat.numpy as np
 
+# generate list of array_api modules / device combinations to test
+xp_dev_list = [(np, 'cpu')]
+
+if np.__version__ >= '1.25':
+    xp_dev_list.append((nparr, 'cpu'))
+
+if parallelproj.cupy_enabled:
+    import array_api_compat.cupy as cp
+    xp_dev_list.append((cp, 'cuda'))
+
+if parallelproj.torch_enabled:
+    import array_api_compat.torch as torch
+    xp_dev_list.append((torch, 'cpu'))
+
+    if parallelproj.cuda_present:
+        xp_dev_list.append((torch, 'cuda'))
+
+pytestmark = pytest.mark.parametrize("xp,dev", xp_dev_list)
+
+#---------------------------------------------------------------------------------------
 
 def allclose(x, y, atol: float = 1e-8, rtol: float = 1e-5) -> bool:
     """check if two arrays are close to each other, given absolute and relative error
@@ -15,7 +35,7 @@ def allclose(x, y, atol: float = 1e-8, rtol: float = 1e-5) -> bool:
     return bool(xp.all(xp.less_equal(xp.abs(x - y), atol + rtol * xp.abs(y))))
 
 
-def parallelviewprojector_test(xp, dev, verbose=True):
+def test_parallelviewprojector(xp, dev, verbose=True):
     image_shape = (2, 2)
     voxel_size = (2., 2.)
     image_origin = (-1., -1.)
@@ -87,37 +107,3 @@ def parallelviewprojector_test(xp, dev, verbose=True):
     assert allclose(x3d_fwd[..., 0], exp_result_dp0)
     assert allclose(x3d_fwd[..., 1], exp_result_dp1)
     assert allclose(x3d_fwd[..., 2], exp_result_dp2)
-
-
-#--------------------------------------------------------------------------
-
-
-class TestParallelViewProjector(unittest.TestCase):
-
-    def test(self):
-        parallelviewprojector_test(np, 'cpu')
-
-        if np.__version__ >= '1.25':
-            parallelviewprojector_test(nparr, 'cpu')
-
-    if parallelproj.cupy_enabled:
-
-        def test_cp(self):
-            import array_api_compat.cupy as cp
-            parallelviewprojector_test(cp, 'cuda')
-
-    if parallelproj.torch_enabled:
-
-        def test_torch(self):
-            import torch
-            parallelviewprojector_test(torch, 'cpu')
-
-    if parallelproj.torch_enabled and parallelproj.cuda_present:
-
-        def test_torch_cuda(self):
-            import torch
-            parallelviewprojector_test(torch, dev='cuda')
-
-
-if __name__ == '__main__':
-    unittest.main()
diff --git a/test/parallelproj/test_toflm_joseph.py b/test/parallelproj/test_toflm_joseph.py
@@ -1,10 +1,30 @@
-import unittest
+import pytest
 import parallelproj
 import numpy.array_api as nparr
 import array_api_compat.numpy as np
 
 from types import ModuleType
 
+# generate list of array_api modules / device combinations to test
+xp_dev_list = [(np, 'cpu')]
+
+if np.__version__ >= '1.25':
+    xp_dev_list.append((nparr, 'cpu'))
+
+if parallelproj.cupy_enabled:
+    import array_api_compat.cupy as cp
+    xp_dev_list.append((cp, 'cuda'))
+
+if parallelproj.torch_enabled:
+    import array_api_compat.torch as torch
+    xp_dev_list.append((torch, 'cpu'))
+
+    if parallelproj.cuda_present:
+        xp_dev_list.append((torch, 'cuda'))
+
+pytestmark = pytest.mark.parametrize("xp,dev", xp_dev_list)
+
+#---------------------------------------------------------------------------------------
 
 def isclose(x: float,
             y: float,
@@ -16,7 +36,7 @@ def isclose(x: float,
     return bool(abs(x - y) <= (atol + rtol * abs(y)))
 
 
-def tof_lm_fwd_test(xp: ModuleType,
+def test_tof_lm_fwd(xp: ModuleType,
                     dev: str,
                     verbose: bool = True,
                     atol: float = 1e-6) -> bool:
@@ -112,10 +132,10 @@ def tof_lm_fwd_test(xp: ModuleType,
         )
         print('')
 
-    return bool(res1 * res2 * res3)
+    assert bool(res1 * res2 * res3)
 
 
-def adjointness_test(xp: ModuleType,
+def test_adjointness(xp: ModuleType,
                      dev: str,
                      nLORs: int = 10000,
                      seed: int = 1,
@@ -184,8 +204,6 @@ def adjointness_test(xp: ModuleType,
     ip_a = float(xp.sum(back_img * img))
     ip_b = float(xp.sum(img_fwd * lst))
 
-    res = isclose(ip_a, ip_b)
-
     if verbose:
         print(
             f'module = {xp.__name__}  -  cuda_enabled {parallelproj.num_visible_cuda_devices > 0}'
@@ -194,64 +212,4 @@ def adjointness_test(xp: ModuleType,
         print('ip_b = ', ip_b)
         print('')
 
-    return res
-
-
-#--------------------------------------------------------------------------
-
-
-class TestLMTOFJoseph(unittest.TestCase):
-    """test for TOF joseph projections"""
-
-    def test_fwd(self):
-        tof_lm_fwd_test(np, 'cpu')
-        if np.__version__ >= '1.25':
-            tof_lm_fwd_test(nparr, 'cpu')
-
-    if parallelproj.cupy_enabled:
-
-        def test_fwd_cp(self):
-            import array_api_compat.cupy as cp
-            tof_lm_fwd_test(cp, 'cuda')
-
-    if parallelproj.torch_enabled:
-
-        def test_fwd_torch(self):
-            import array_api_compat.torch as torch
-            tof_lm_fwd_test(torch, 'cpu')
-
-    if parallelproj.torch_enabled and parallelproj.cupy_enabled:
-
-        def test_fwd_torch_cuda(self):
-            import array_api_compat.torch as torch
-            tof_lm_fwd_test(torch, 'cuda')
-
-    def test_adjoint(self):
-        """test non TOF joseph forward projection using different backends"""
-        adjointness_test(np, 'cpu')
-        if np.__version__ >= '1.25':
-            adjointness_test(nparr, 'cpu')
-
-    if parallelproj.cupy_enabled:
-
-        def test_adjoint_cp(self):
-            import array_api_compat.cupy as cp
-            adjointness_test(cp, 'cuda')
-
-    if parallelproj.torch_enabled:
-
-        def test_adjoint_torch(self):
-            import array_api_compat.torch as torch
-            adjointness_test(torch, 'cpu')
-
-    if parallelproj.torch_enabled and parallelproj.cupy_enabled:
-
-        def test_adjoint_torch_cuda(self):
-            import array_api_compat.torch as torch
-            adjointness_test(torch, 'cuda')
-
-
-#--------------------------------------------------------------------------
-
-if __name__ == '__main__':
-    unittest.main()
+    assert isclose(ip_a, ip_b)