Module Widefield-Imaging-Acquisition.test.test_calculations

Classes

class TestData (methodName='runTest')

A class whose instances are single test cases.

By default, the test code itself should be placed in a method named 'runTest'.

If the fixture may be used for many test cases, create as many test methods as are needed. When instantiating such a TestCase subclass, specify in the constructor arguments the name of the test method that the instance is to execute.

Test authors should subclass TestCase for their own tests. Construction and deconstruction of the test's environment ('fixture') can be implemented by overriding the 'setUp' and 'tearDown' methods respectively.

If it is necessary to override the init method, the base class init method must always be called. It is important that subclasses should not change the signature of their init method, since instances of the classes are instantiated automatically by parts of the framework in order to be run.

When subclassing TestCase, you can set these attributes: * failureException: determines which exception will be raised when the instance's assertion methods fail; test methods raising this exception will be deemed to have 'failed' rather than 'errored'. * longMessage: determines whether long messages (including repr of objects used in assert methods) will be printed on failure in addition to any explicit message passed. * maxDiff: sets the maximum length of a diff in failure messages by assert methods using difflib. It is looked up as an instance attribute so can be configured by individual tests if required.

Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.

Expand source code

class TestData(unittest.TestCase):
    def test_frames_acquired_from_camera_signal(self):
        """Test that the frames acquired from the camera signal are correctly calculated"""
        x_values = np.linspace(0, 5, 11)
        y_values = signal.square(2 * np.pi * x_values)
        np.testing.assert_array_equal(
            np.array([0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5]),
            calc.frames_acquired_from_camera_signal(y_values),
        )

    def test_average_baseline(self):
        """Test that the baselines are correctly averaged"""
        frames = [np.array([[1, 2, 3], [4, 5, 6]]), np.array([[7, 8, 9], [10, 11, 12]])]
        np.testing.assert_array_equal(
            [np.array([[4, 5, 6], [7, 8, 9]])], calc.average_baseline(frames)
        )

    def test_get_baseline_frame_indices(self):
        """Test that the baseline frame indices are correctly calculated"""
        baseline_indices = [[0, 2], [3, 5], [6, 9]]
        frames_acquired = [0, 0, 0, 0, 0, 1, 1, 2, 3, 3]
        self.assertEqual(
            [[0, 0], [0, 1], [1, 3]],
            calc.get_baseline_frame_indices(baseline_indices, frames_acquired),
        )
        pass

    def test_map_activation(self):
        """Test that the activation is correctly mapped to the baseline"""
        frames = [np.array([[1, 2, 3], [4, 5, 6]]), np.array([[7, 8, 9], [10, 11, 12]])]
        baseline = np.array([[0, 3, 1], [1, 1, 1]])
        np.testing.assert_array_equal(
            [np.array([[1, -1, 2], [3, 4, 5]]), np.array([[7, 5, 8], [9, 10, 11]])],
            calc.map_activation(frames, baseline),
        )

Ancestors

• unittest.case.TestCase

Methods

def test_average_baseline(self)

Test that the baselines are correctly averaged

Expand source code

def test_average_baseline(self):
    """Test that the baselines are correctly averaged"""
    frames = [np.array([[1, 2, 3], [4, 5, 6]]), np.array([[7, 8, 9], [10, 11, 12]])]
    np.testing.assert_array_equal(
        [np.array([[4, 5, 6], [7, 8, 9]])], calc.average_baseline(frames)
    )

def test_frames_acquired_from_camera_signal(self)

Test that the frames acquired from the camera signal are correctly calculated

Expand source code

def test_frames_acquired_from_camera_signal(self):
    """Test that the frames acquired from the camera signal are correctly calculated"""
    x_values = np.linspace(0, 5, 11)
    y_values = signal.square(2 * np.pi * x_values)
    np.testing.assert_array_equal(
        np.array([0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5]),
        calc.frames_acquired_from_camera_signal(y_values),
    )

def test_get_baseline_frame_indices(self)

Test that the baseline frame indices are correctly calculated

Expand source code

def test_get_baseline_frame_indices(self):
    """Test that the baseline frame indices are correctly calculated"""
    baseline_indices = [[0, 2], [3, 5], [6, 9]]
    frames_acquired = [0, 0, 0, 0, 0, 1, 1, 2, 3, 3]
    self.assertEqual(
        [[0, 0], [0, 1], [1, 3]],
        calc.get_baseline_frame_indices(baseline_indices, frames_acquired),
    )
    pass

def test_map_activation(self)

Test that the activation is correctly mapped to the baseline

Expand source code

def test_map_activation(self):
    """Test that the activation is correctly mapped to the baseline"""
    frames = [np.array([[1, 2, 3], [4, 5, 6]]), np.array([[7, 8, 9], [10, 11, 12]])]
    baseline = np.array([[0, 3, 1], [1, 1, 1]])
    np.testing.assert_array_equal(
        [np.array([[1, -1, 2], [3, 4, 5]]), np.array([[7, 5, 8], [9, 10, 11]])],
        calc.map_activation(frames, baseline),
    )