feat: init

test/model/test_aslm_analysis.py

@@ -0,0 +1,145 @@
+# Copyright (c) 2021-2025  The University of Texas Southwestern Medical Center.
+# All rights reserved.
+
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted for academic and research use only
+# (subject to the limitations in the disclaimer below)
+# provided that the following conditions are met:
+
+#      * Redistributions of source code must retain the above copyright notice,
+#      this list of conditions and the following disclaimer.
+
+#      * Redistributions in binary form must reproduce the above copyright
+#      notice, this list of conditions and the following disclaimer in the
+#      documentation and/or other materials provided with the distribution.
+
+#      * Neither the name of the copyright holders nor the names of its
+#      contributors may be used to endorse or promote products derived from this
+#      software without specific prior written permission.
+
+# NO EXPRESS OR IMPLIED LICENSES TO ANY PARTY'S PATENT RIGHTS ARE GRANTED BY
+# THIS LICENSE. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND
+# CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A
+# PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
+# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
+# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
+# BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
+# IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+# POSSIBILITY OF SUCH DAMAGE.
+
+# Standard Library Imports
+import unittest
+
+# Third Party Imports
+import numpy as np
+import pytest
+
+# Local Imports
+# sys.path.append('../../../')
+
+
+def box(size):
+    x = np.linspace(0, 1, 100)
+    X, Y = np.meshgrid(x, x)
+    l = (1 - size) / 2  # noqa
+    u = l + size
+    image = (X > l) & (X < u) & (Y > l) & (Y < u)
+    return image.astype(float)
+
+
+def power_tent(r, off, scale, sigma, alpha):
+    return off + scale * (1 - np.abs(sigma * r) ** alpha)
+
+
+def power_tent_res(x, r, val):
+    return power_tent(r, *x) - val
+
+
+def rsq(res_func, x, r, val):
+    ss_err = (res_func(x, r, val) ** 2).sum()
+    ss_tot = ((val - val.mean()) ** 2).sum()
+    rsq = 1 - (ss_err / ss_tot)
+    return rsq
+
+
+def test_fast_normalized_dct_shannon_entropy_tent():
+    from scipy.ndimage import gaussian_filter
+    from scipy.optimize import least_squares
+
+    from navigate.model.analysis.image_contrast import (
+        fast_normalized_dct_shannon_entropy,
+    )
+
+    im = box(0.5)
+
+    r = range(0, 60)
+    points = np.zeros((len(r),))
+    for i in r:
+        points[i] = fast_normalized_dct_shannon_entropy(gaussian_filter(im, i), 1)[0]
+
+    res = least_squares(
+        power_tent_res, [np.min(points), np.max(points), 1, 0.5], args=(r, points)
+    )
+
+    assert rsq(power_tent_res, res.x, r, points) > 0.9
+
+
+def test_fast_normalized_dct_shannon_entropy():
+    from navigate.model.analysis.image_contrast import (
+        fast_normalized_dct_shannon_entropy,
+    )
+
+    # image_array = np.ones((np.random.randint(1,4),128,128)).squeeze()
+    image_array = np.ones((128, 128)).squeeze()
+    psf_support_diameter_xy = np.random.randint(3, 10)
+
+    entropy = fast_normalized_dct_shannon_entropy(image_array, psf_support_diameter_xy)
+
+    assert np.all(entropy == 0)
+
+
+"""
+Delete the below assert once the calculate entropy function is found
+"""
+
+
+def test_entropy():
+    assert True
+
+
+try:
+    # from navigate.model.navigate_analysis import Analysis as navigate_analysis
+    from navigate.model.navigate_debug_model import calculate_entropy
+
+    class TestNavigateAnalysis(unittest.TestCase):
+        """
+        Unit Tests for the Navigate Analysis Module
+        """
+
+        @pytest.mark.skip(reason="file path not found")
+        def test_calculate_entropy_on(self):
+            """
+            Test the calculation of the Shannon Entropy
+            """
+            dct_array = np.ones((128, 128))
+            otf_support_x = 3
+            otf_support_y = 3
+            # This trys to call from the navigate_analysis module however its only
+            # located in the navigate_debug_model
+            # entropy = navigate_analysis.calculate_entropy()
+            entropy = calculate_entropy(
+                self,
+                dct_array=dct_array,
+                otf_support_x=otf_support_x,
+                otf_support_y=otf_support_y,
+            )
+            self.assertEqual(entropy, 0)
+
+except ImportError as e:
+    print(e)
+
+if __name__ == "__main__":
+    unittest.main()