feat: init

test/model/features/test_autofocus.py

@@ -0,0 +1,134 @@
+# 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
+
+# Local imports
+from navigate.model.features.autofocus import power_tent
+from navigate.model.features.autofocus import Autofocus
+from test.model.dummy import DummyModel
+
+
+class TestPowerTentFunction(unittest.TestCase):
+    def test_power_tent(self):
+        # Test with known parameters and expected result
+        x = 2.0
+        x_offset = 1.0
+        y_offset = 0.0
+        amplitude = 2.0
+        sigma = 0.5
+        alpha = 2.0
+
+        # Calculate the expected result manually
+        expected_result = y_offset + amplitude * (
+            1 - np.abs(sigma * (x - x_offset)) ** alpha
+        )
+
+        # Call the function and check if the result is close to the expected result
+        result = power_tent(x, x_offset, y_offset, amplitude, sigma, alpha)
+        self.assertAlmostEqual(result, expected_result, places=6)
+
+    def test_power_tent_boundary_cases(self):
+        # Test some boundary cases
+        x_offset = 0.0
+        y_offset = 0.0
+        amplitude = 1.0
+        sigma = 1.0
+        alpha = 1.0
+
+        # Test at x = x_offset, should be y_offset + amplitude
+        result = power_tent(x_offset, x_offset, y_offset, amplitude, sigma, alpha)
+        self.assertAlmostEqual(result, y_offset + amplitude, places=6)
+
+        # Test at x = x_offset + 1, should be y_offset
+        result = power_tent(x_offset + 1, x_offset, y_offset, amplitude, sigma, alpha)
+        self.assertAlmostEqual(result, y_offset, places=6)
+
+
+class TestAutofocusClass(unittest.TestCase):
+    def setUp(self):
+        # Initialize an instance of the Autofocus class for testing
+        model = DummyModel()
+        model.active_microscope_name = "Mesoscale"
+        self.autofocus = Autofocus(model=model, device="stage", device_ref="f")
+
+    def test_get_autofocus_frame_num(self):
+        # Test the get_autofocus_frame_num method
+        settings = {
+            "coarse_selected": True,
+            "coarse_range": 8.0,
+            "coarse_step_size": 2.0,
+            "fine_selected": True,
+            "fine_range": 5.0,
+            "fine_step_size": 1.0,
+        }
+        self.autofocus.model.configuration = {
+            "experiment": {
+                "AutoFocusParameters": {"Mesoscale": {"stage": {"f": settings}}}
+            }
+        }
+        # Both Fine and Coarse Selected
+        frames = self.autofocus.get_autofocus_frame_num()
+        self.assertEqual(frames, 11)  # Expected number of frames
+
+        # Only Coarse Selected
+        self.autofocus.model.configuration["experiment"]["AutoFocusParameters"][
+            "Mesoscale"
+        ]["stage"]["f"]["fine_selected"] = False
+        self.autofocus.model.configuration["experiment"]["AutoFocusParameters"][
+            "Mesoscale"
+        ]["stage"]["f"]["coarse_selected"] = True
+        frames = self.autofocus.get_autofocus_frame_num()
+        self.assertEqual(frames, 5)  # Expected number of frames
+
+        # Only Fine Selected
+        self.autofocus.model.configuration["experiment"]["AutoFocusParameters"][
+            "Mesoscale"
+        ]["stage"]["f"]["fine_selected"] = True
+        self.autofocus.model.configuration["experiment"]["AutoFocusParameters"][
+            "Mesoscale"
+        ]["stage"]["f"]["coarse_selected"] = False
+        frames = self.autofocus.get_autofocus_frame_num()
+        self.assertEqual(frames, 6)  # Expected number of frames
+
+    def test_get_steps(self):
+        # Test the get_steps method
+        steps, pos_offset = self.autofocus.get_steps(10.0, 2.0)
+        self.assertEqual(steps, 6)  # Expected number of steps
+        self.assertEqual(pos_offset, 8.0)  # Expected position offset
+
+
+if __name__ == "__main__":
+    unittest.main()