Refactor array checks in unit tests to ensure consistent dtype handling

Author: PierreRaybaut

cdl/tests/features/images/average_app_test.py

@@ -39,7 +39,8 @@ def test_image_average():
         panel.objview.select_groups([0])
         panel.processor.compute_average()
         res_data = panel.objview.get_sel_objects(include_groups=True)[0].data
-    check_array_result("Average", res_data, data)
+    exp_data = np.array(data, dtype=float)
+    check_array_result("Average", res_data, exp_data)
 
 
 if __name__ == "__main__":

cdl/tests/features/images/fft2d_unit_test.py

@@ -34,7 +34,9 @@ def test_image_fft_interactive():
         data2 = alg.ifft2d(f)
         execenv.print("OK")
         execenv.print("Comparing original and FFT/iFFT images...", end=" ")
-        check_array_result("Image FFT/iFFT", data2, data)
+        check_array_result(
+            "Image FFT/iFFT", np.array(data2.real, dtype=data.dtype), data, rtol=1e-3
+        )
         execenv.print("OK")
 
         images = [data, f.real, f.imag, np.abs(f), data2.real, data2.imag]

cdl/tests/features/images/processing_unit_test.py

@@ -68,7 +68,7 @@ def test_image_calibration() -> None:
     # Test with a = 1 and b = 0: should do nothing
     p.a, p.b = 1.0, 0.0
     dst = cpi.compute_calibration(src, p)
-    exp = src.data
+    exp = np.array(src.data, dtype=float)
     check_array_result("Calibration[identity]", dst.data, exp)
 
     # Testing with random values of a and b

cdl/tests/features/signals/fft1d_unit_test.py

@@ -66,7 +66,7 @@ def test_signal_fft() -> None:
 
     # Check that the inverse FFT reconstructs the original signal
     check_array_result("Cosine signal FFT/iFFT X reconstruction", s1.y, ifft.y.real)
-    check_array_result("Cosine signal FFT/iFFT Y reconstruction", s1.x, ifft.x)
+    check_array_result("Cosine signal FFT/iFFT Y reconstruction", s1.x, ifft.x.real)
 
     # Check FFT properties
     mag = np.abs(fft.y)
@@ -112,7 +112,7 @@ def test_signal_magnitude_spectrum() -> None:
     check_scalar_result("Cosine negative frequency", fpk1, -freq, rtol=0.001)
 
     # Check that the magnitude spectrum is correct
-    check_array_result("Cosine signal magnitude spectrum X", mag.x, fft.x)
+    check_array_result("Cosine signal magnitude spectrum X", mag.x, fft.x.real)
     check_array_result("Cosine signal magnitude spectrum Y", mag.y, np.abs(fft.y))
 
 
@@ -129,7 +129,7 @@ def test_signal_phase_spectrum() -> None:
     check_scalar_result("Cosine negative frequency", fpk1, -freq, rtol=0.001)
 
     # Check that the phase spectrum is correct
-    check_array_result("Cosine signal phase spectrum X", phase.x, fft.x)
+    check_array_result("Cosine signal phase spectrum X", phase.x, fft.x.real)
     exp_phase = np.rad2deg(np.angle(fft.y))
     check_array_result("Cosine signal phase spectrum Y", phase.y, exp_phase)