split node tests into standalone files

tests/node_tests/test_psdf.py

@@ -0,0 +1,35 @@
+import numpy as np
+from backend.data_types import DataField
+
+
+def test_psdf_node():
+    from backend.nodes.fft_2d import FFT2D
+    from backend.nodes.psdf import PSDF
+
+    field = DataField(
+        data=np.random.default_rng(17).standard_normal((64, 64)),
+        xreal=2.0e-6, yreal=1.0e-6, si_unit_xy="m", si_unit_z="nm",
+    )
+
+    fft_node = FFT2D()
+    psdf_node = PSDF()
+
+    fft_psdf = fft_node.process(field, windowing="hann", level="plane")[3]
+    psdf, = psdf_node.process(field, windowing="hann", level="plane")
+    assert np.allclose(psdf.data, fft_psdf.data)
+    assert psdf.data.shape == field.data.shape
+    assert psdf.domain == "frequency"
+    assert psdf.si_unit_xy == "1/m"
+    assert psdf.si_unit_z == "nm^2 m^2"
+    assert np.all(psdf.data >= 0.0)
+
+    white = DataField(
+        data=np.random.default_rng(123).standard_normal((128, 128)),
+        xreal=1.0e-6, yreal=1.0e-6, si_unit_xy="m", si_unit_z="m",
+    )
+    psdf_white, = psdf_node.process(white, windowing="none", level="none")
+    variance = float(np.var(white.data))
+    dk_x = psdf_white.xreal / psdf_white.xres
+    dk_y = psdf_white.yreal / psdf_white.yres
+    integral = float(np.sum(psdf_white.data) * dk_x * dk_y)
+    assert 0.8 < integral / variance < 1.2