feat: init

test/model/analysis/test_camera.py

@@ -0,0 +1,56 @@
+import numpy as np
+import pytest
+
+
+@pytest.mark.skip("volatile")
+def test_compute_scmos_offset_and_variance_map():
+    from navigate.model.analysis.camera import compute_scmos_offset_and_variance_map
+
+    mu, sig = 100 * np.random.rand() + 1, 100 * np.random.rand() + 1
+    im = sig * np.random.randn(256, 256, 256) + mu
+
+    offset, variance = compute_scmos_offset_and_variance_map(im)
+
+    print(mu, sig)
+    # TODO: 1 is a bit high?
+    np.testing.assert_allclose(offset, mu, rtol=1)
+    np.testing.assert_allclose(variance, sig * sig, rtol=1)
+
+
+@pytest.mark.parametrize("local", [True, False])
+def test_compute_flatfield_map(local):
+    from navigate.model.analysis.camera import compute_flatfield_map
+
+    image = np.ones((256, 256))
+    offset = np.zeros((256, 256))
+    ffmap = compute_flatfield_map(image, offset, local)
+
+    np.testing.assert_allclose(ffmap, 0.5)
+
+
+def test_compute_noise_sigma():
+    from navigate.model.analysis.camera import compute_noise_sigma
+
+    Fn = np.random.rand()
+    qe = np.random.rand()
+    S = np.random.rand(256, 256)
+    Ib = np.random.rand()
+    Nr = np.random.rand()
+    M = np.random.rand()
+    sigma = compute_noise_sigma(Fn=Fn, qe=qe, S=S, Ib=Ib, Nr=Nr, M=M)
+    sigma_true = np.sqrt(Fn * Fn * qe * (S + Ib) + (Nr / M) ** 2)
+
+    np.testing.assert_allclose(sigma, sigma_true)
+
+
+def test_compute_signal_to_noise():
+    from navigate.model.analysis.camera import compute_signal_to_noise
+
+    A = np.random.rand() * 100 + 10
+    image = A * np.ones((256, 256))
+    offset = np.zeros((256, 256))
+    variance = 3 * A * A * np.ones((256, 256))
+
+    snr = compute_signal_to_noise(image, offset, variance)
+
+    np.testing.assert_allclose(snr, 0.5, rtol=0.2)