Merge pull request #109 from AllenNeuralDynamics/wip/pytest

Wip/pytest

parallax/__init__.py

@@ -4,7 +4,7 @@
 
 import os
 
-__version__ = "1.0.1"
+__version__ = "1.1.0"
 
 # allow multiple OpenMP instances
 os.environ["KMP_DUPLICATE_LIB_OK"] = "True"

tests/test__setting.py

@@ -0,0 +1,11 @@
+import pytest
+from PyQt5.QtWidgets import QApplication
+
+@pytest.fixture(scope="session")
+def qapp():
+    app = QApplication([])
+    yield app
+    app.quit()
+
+print("\nInitializing QApplication for tests...")
+

tests/test_calculator.py

@@ -0,0 +1,123 @@
+import pytest
+from unittest.mock import MagicMock
+from PyQt5.QtWidgets import QLineEdit, QComboBox
+import numpy as np
+from parallax.calculator import Calculator
+
+@pytest.fixture
+def setup_calculator(qtbot):
+    # Mocking the model and stage_controller
+    model = MagicMock()
+    reticle_selector = QComboBox()
+    stage_controller = MagicMock()
+
+    # Mock the model's stages and transforms
+    model.stages = {'stage1': MagicMock(), 'stage2': MagicMock()}
+    model.transforms = {'stage1': (np.eye(4), [1, 1, 1]), 'stage2': (None, None)}
+
+    # Initialize the Calculator widget
+    calculator = Calculator(model, reticle_selector, stage_controller)
+    qtbot.addWidget(calculator)
+    calculator.show()
+
+    return calculator, model, stage_controller
+
+def test_set_current_reticle(setup_calculator, qtbot):
+    calculator, model, stage_controller = setup_calculator
+
+    # Simulate selecting a reticle in the dropdown
+    calculator.reticle_selector.addItem("Global coords (A)")
+    calculator.reticle_selector.addItem("Global coords (B)")
+    calculator.reticle_selector.setCurrentIndex(1)
+
+    # Trigger reticle change
+    calculator._setCurrentReticle()
+
+    assert calculator.reticle == "B", "Reticle should be set to 'B'"
+
+@pytest.mark.parametrize("localX, localY, localZ, transM_LR, scale, expected_globalX, expected_globalY, expected_globalZ", [
+    # Case 1: Complex transformation with scaling (your initial case)
+    (10775.0, 6252.0, 6418.0, 
+     np.array([[0.991319402, 0.079625596, -0.104621259, -10801.14725],
+               [-0.092116645, 0.988422741, -0.120561228, 6332.440016],
+               [0.093810271, 0.129152044, 0.987177483, 6122.5096],
+               [0, 0, 0, 1]]), 
+     np.array([0.994494443, -0.988947511, -0.995326937]), 
+     -2.5, 4.2, 23.1),
+    
+    # Case 2: Basic translation vector without scaling
+    (100.0, 200.0, 300.0, 
+     np.array([[1, 0, 0, 10], 
+               [0, 1, 0, 20], 
+               [0, 0, 1, 30], 
+               [0, 0, 0, 1]]), 
+     np.array([1, 1, 1]), 
+     110.0, 220.0, 330.0)
+])
+def test_transform_local_to_global(setup_calculator, qtbot, localX, localY, localZ, transM_LR, scale, expected_globalX, expected_globalY, expected_globalZ):
+    calculator, model, stage_controller = setup_calculator
+
+    # Mock the QLineEdit fields for stage1
+    qtbot.keyClicks(calculator.findChild(QLineEdit, 'localX_stage1'), str(localX))
+    qtbot.keyClicks(calculator.findChild(QLineEdit, 'localY_stage1'), str(localY))
+    qtbot.keyClicks(calculator.findChild(QLineEdit, 'localZ_stage1'), str(localZ))
+
+    # Simulate conversion
+    calculator._convert('stage1', transM_LR, scale)
+
+    # Retrieve the global coordinates from the UI
+    globalX = calculator.findChild(QLineEdit, 'globalX_stage1').text()
+    globalY = calculator.findChild(QLineEdit, 'globalY_stage1').text()
+    globalZ = calculator.findChild(QLineEdit, 'globalZ_stage1').text()
+
+    # Convert text values to float for assertion
+    globalX = float(globalX)
+    globalY = float(globalY)
+    globalZ = float(globalZ)
+
+    # Check if the transformed values match expected values
+    assert globalX == pytest.approx(expected_globalX, abs=5), f"Expected globalX to be {expected_globalX}, got {globalX}"
+    assert globalY == pytest.approx(expected_globalY, abs=5), f"Expected globalY to be {expected_globalY}, got {globalY}"
+    assert globalZ == pytest.approx(expected_globalZ, abs=5), f"Expected globalZ to be {expected_globalZ}, got {globalZ}"
+
+def test_transform_global_to_local(setup_calculator, qtbot):
+    calculator, model, stage_controller = setup_calculator
+
+    # Mock the QLineEdit fields for stage1
+    qtbot.keyClicks(calculator.findChild(QLineEdit, 'globalX_stage1'), "15.0")
+    qtbot.keyClicks(calculator.findChild(QLineEdit, 'globalY_stage1'), "25.0")
+    qtbot.keyClicks(calculator.findChild(QLineEdit, 'globalZ_stage1'), "35.0")
+
+    # Mock transformation matrix and scale for stage1
+    transM_LR = np.array([[1, 0, 0, 5], [0, 1, 0, 5], [0, 0, 1, 5], [0, 0, 0, 1]])
+    scale = np.array([1, 1, 1])
+
+    # Simulate conversion
+    calculator._convert('stage1', transM_LR, scale)
+
+    localX = calculator.findChild(QLineEdit, 'localX_stage1').text()
+    localY = calculator.findChild(QLineEdit, 'localY_stage1').text()
+    localZ = calculator.findChild(QLineEdit, 'localZ_stage1').text()
+
+    assert localX == "10.00", f"Expected localX to be 10.00, got {localX}"
+    assert localY == "20.00", f"Expected localY to be 20.00, got {localY}"
+    assert localZ == "30.00", f"Expected localZ to be 30.00, got {localZ}"
+
+def test_clear_fields(setup_calculator, qtbot):
+    calculator, model, stage_controller = setup_calculator
+
+    # Set some values in the QLineEdit fields
+    calculator.findChild(QLineEdit, 'localX_stage1').setText("10.0")
+    calculator.findChild(QLineEdit, 'localY_stage1').setText("20.0")
+    calculator.findChild(QLineEdit, 'localZ_stage1').setText("30.0")
+
+    # Clear the fields
+    calculator._clear_fields('stage1')
+
+    localX = calculator.findChild(QLineEdit, 'localX_stage1').text()
+    localY = calculator.findChild(QLineEdit, 'localY_stage1').text()
+    localZ = calculator.findChild(QLineEdit, 'localZ_stage1').text()
+
+    assert localX == "", "Expected localX to be cleared"
+    assert localY == "", "Expected localY to be cleared"
+    assert localZ == "", "Expected localZ to be cleared"

tests/test_calibration_camera.py

@@ -0,0 +1,147 @@
+import pytest
+import numpy as np
+from unittest.mock import MagicMock, patch
+from parallax.calibration_camera import CalibrationStereo, OBJPOINTS
+
+@pytest.fixture
+def mock_model():
+    """Fixture to create a mock model for testing."""
+    model = MagicMock()
+    return model
+
+@pytest.fixture
+def intrinsic_data():
+    """Fixture for mock intrinsic data for both cameras."""
+    intrinsicA = [
+        np.array([[1.54e+04, 0.0e+00, 2.0e+03],
+                  [0.0e+00, 1.54e+04, 1.5e+03],
+                  [0.0e+00, 0.0e+00, 1.0e+00]]),
+        np.array([[0., 0., 0., 0., 0.]]),  # Distortion coefficients
+        (np.array([[-2.88], [-0.08], [-0.47]]),),  # rvecA
+        (np.array([[1.08], [1.01], [58.70]]),)  # tvecA
+    ]
+    intrinsicB = [
+        np.array([[1.54e+04, 0.0e+00, 2.0e+03],
+                  [0.0e+00, 1.54e+04, 1.5e+03],
+                  [0.0e+00, 0.0e+00, 1.0e+00]]),
+        np.array([[0., 0., 0., 0., 0.]]),  # Distortion coefficients
+        (np.array([[2.64], [-0.29], [0.35]]),),  # rvecB
+        (np.array([[1.24], [0.33], [56.22]]),)  # tvecB
+    ]
+    return intrinsicA, intrinsicB
+
+@pytest.fixture
+def imgpoints_data():
+    """Fixture for mock image points for both cameras."""
+    imgpointsA = [
+        np.array([
+            [1786, 1755], [1837, 1756], [1887, 1757], [1937, 1758], [1987, 1759],
+            [2036, 1760], [2086, 1761], [2136, 1762], [2186, 1763], [2235, 1764],
+            [2285, 1765], [2334, 1766], [2383, 1767], [2432, 1768], [2481, 1769],
+            [2530, 1770], [2579, 1771], [2628, 1772], [2676, 1773], [2725, 1774],
+            [2773, 1775]
+        ], dtype=np.float32),
+        np.array([
+            [2233, 2271], [2238, 2220], [2244, 2170], [2249, 2120], [2254, 2069],
+            [2259, 2019], [2264, 1968], [2269, 1918], [2275, 1866], [2280, 1816],
+            [2285, 1765], [2290, 1714], [2295, 1663], [2300, 1612], [2306, 1561],
+            [2311, 1509], [2316, 1459], [2321, 1407], [2327, 1355], [2332, 1304],
+            [2337, 1252]
+        ], dtype=np.float32)
+    ]
+    imgpointsB = [
+        np.array([
+            [1822, 1677], [1875, 1668], [1927, 1660], [1979, 1651], [2031, 1643],
+            [2083, 1635], [2135, 1626], [2187, 1618], [2239, 1609], [2290, 1601],
+            [2341, 1593], [2392, 1584], [2443, 1576], [2494, 1568], [2545, 1559],
+            [2596, 1551], [2647, 1543], [2698, 1535], [2748, 1526], [2799, 1518],
+            [2850, 1510]
+        ], dtype=np.float32),
+        np.array([
+            [2494, 2081], [2478, 2031], [2463, 1982], [2448, 1933], [2432, 1884],
+            [2417, 1835], [2402, 1786], [2387, 1738], [2371, 1689], [2356, 1640],
+            [2341, 1593], [2326, 1544], [2311, 1496], [2296, 1449], [2281, 1401],
+            [2267, 1354], [2252, 1306], [2237, 1259], [2222, 1212], [2208, 1165],
+            [2193, 1118]
+        ], dtype=np.float32)
+    ]
+    return imgpointsA, imgpointsB
+
+@pytest.fixture
+def setup_calibration_stereo(mock_model, intrinsic_data, imgpoints_data):
+    """Fixture to set up a CalibrationStereo instance."""
+    camA = "22517664"
+    camB = "22468054"
+    imgpointsA, imgpointsB = imgpoints_data
+    intrinsicA, intrinsicB = intrinsic_data
+
+    calib_stereo = CalibrationStereo(
+        model=mock_model,
+        camA=camA,
+        imgpointsA=imgpointsA,
+        intrinsicA=intrinsicA,
+        camB=camB,
+        imgpointsB=imgpointsB,
+        intrinsicB=intrinsicB
+    )
+    return calib_stereo
+
+def test_calibrate_stereo(setup_calibration_stereo):
+    """Test the stereo calibration process."""
+    calib_stereo = setup_calibration_stereo
+
+    # Mock the cv2.stereoCalibrate method with expected results
+    mock_retval = 0.4707333710438937
+    mock_R_AB = np.array([
+        [0.92893564, 0.32633462, 0.17488367],
+        [-0.3667657, 0.7465183, 0.55515165],
+        [0.05061134, -0.57984149, 0.81315579]
+    ])
+    mock_T_AB = np.array([[-10.35397621], [-32.59591834], [9.0524749]])
+    mock_E_AB = np.array([
+        [1.67041403, 12.14262756, -31.53105623],
+        [8.93319518, -3.04952897, 10.00252579],
+        [34.07699343, 2.90774401, -0.04753311]
+    ])
+    mock_F_AB = np.array([
+        [-5.14183388e-09, -3.73771847e-08, 1.56104641e-03],
+        [-2.74979764e-08, 9.38699691e-09, -4.33243885e-04],
+        [-1.56385384e-03, -7.71647099e-05, 1.00000000e+00]
+    ])
+
+    with patch('cv2.stereoCalibrate', return_value=(mock_retval, None, None, None, None, mock_R_AB, mock_T_AB, mock_E_AB, mock_F_AB)) as mock_stereo_calibrate:
+        retval, R_AB, T_AB, E_AB, F_AB = calib_stereo.calibrate_stereo()
+
+        # Use np.allclose() to check that the values match the expected ones.
+        assert np.isclose(retval, mock_retval, atol=1e-6)
+        assert np.allclose(R_AB, mock_R_AB, atol=1e-6)
+        assert np.allclose(T_AB, mock_T_AB, atol=1e-6)
+        assert np.allclose(E_AB, mock_E_AB, atol=1e-6)
+        assert np.allclose(F_AB, mock_F_AB, atol=1e-6)
+
+def test_triangulation(setup_calibration_stereo, imgpoints_data):
+    """Test the triangulation function for consistency."""
+    calib_stereo = setup_calibration_stereo
+    imgpointsA, imgpointsB = imgpoints_data
+
+    # Use the OBJPOINTS as the expected points.
+    expected_points_3d = OBJPOINTS
+
+    # Mock the triangulation result to match the expected object points.
+    homogeneous_coords = np.hstack([expected_points_3d, np.ones((expected_points_3d.shape[0], 1))])
+
+    with patch('cv2.triangulatePoints', return_value=homogeneous_coords.T) as mock_triangulate:
+        points_3d_hom = calib_stereo.triangulation(
+            calib_stereo.P_A, calib_stereo.P_B, imgpointsA[0], imgpointsB[0]
+        )
+
+        # Prevent division by zero by ensuring the last component isn't zero.
+        valid_indices = points_3d_hom[:, -1] != 0
+        points_3d_hom = points_3d_hom[valid_indices]
+        points_3d_hom = points_3d_hom / points_3d_hom[:, -1].reshape(-1, 1)
+
+        # Only compare valid points with the expected object points.
+        expected_valid_points = expected_points_3d[valid_indices]
+
+        # Verify that the triangulation result is similar to the expected object points.
+        assert np.allclose(points_3d_hom[:, :3], expected_valid_points, atol=1e-2)

tests/test_coords_transformation.py

@@ -0,0 +1,61 @@
+import numpy as np
+import pytest
+from parallax.coords_transformation import RotationTransformation
+
+@pytest.fixture
+def transformer():
+    return RotationTransformation()
+
+def test_roll(transformer):
+    # Test roll rotation around the x-axis
+    input_matrix = np.identity(3)
+    roll_angle = np.pi / 4  # 45 degrees
+    expected_output = np.array([[1, 0, 0],
+                                [0, np.sqrt(2) / 2, -np.sqrt(2) / 2],
+                                [0, np.sqrt(2) / 2, np.sqrt(2) / 2]])
+    output = transformer.roll(input_matrix, roll_angle)
+    assert np.allclose(output, expected_output), "Roll transformation failed."
+
+def test_pitch(transformer):
+    # Test pitch rotation around the y-axis
+    input_matrix = np.identity(3)
+    pitch_angle = np.pi / 6  # 30 degrees
+    expected_output = np.array([[np.sqrt(3) / 2, 0, 0.5],
+                                [0, 1, 0],
+                                [-0.5, 0, np.sqrt(3) / 2]])
+    output = transformer.pitch(input_matrix, pitch_angle)
+    assert np.allclose(output, expected_output), "Pitch transformation failed."
+
+def test_yaw(transformer):
+    # Test yaw rotation around the z-axis
+    input_matrix = np.identity(3)
+    yaw_angle = np.pi / 3  # 60 degrees
+    expected_output = np.array([[0.5, -np.sqrt(3) / 2, 0],
+                                [np.sqrt(3) / 2, 0.5, 0],
+                                [0, 0, 1]])
+    output = transformer.yaw(input_matrix, yaw_angle)
+    assert np.allclose(output, expected_output), "Yaw transformation failed."
+
+def test_extract_angles(transformer):
+    # Test extraction of roll, pitch, yaw from rotation matrix
+    rotation_matrix = transformer.combineAngles(np.pi / 4, np.pi / 6, np.pi / 3)
+    roll, pitch, yaw = transformer.extractAngles(rotation_matrix)
+
+    assert np.isclose(roll, np.pi / 4), f"Expected roll to be {np.pi / 4}, got {roll}"
+    assert np.isclose(pitch, np.pi / 6), f"Expected pitch to be {np.pi / 6}, got {pitch}"
+    assert np.isclose(yaw, np.pi / 3), f"Expected yaw to be {np.pi / 3}, got {yaw}"
+
+def test_fit_params(transformer):
+    # Test fitting parameters for transformation
+    measured_pts = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]])
+    global_pts = np.array([[2, 3, 4], [5, 6, 7], [8, 9, 10], [11, 12, 13]])
+
+    origin, rotation_matrix, scale, avg_err = transformer.fit_params(measured_pts, global_pts)
+
+    # Expected values based on the simplified test data
+    expected_origin = np.array([1, 1, 1])
+    expected_scale = np.array([1, 1, 1])
+
+    assert np.allclose(origin, expected_origin), f"Expected origin {expected_origin}, got {origin}"
+    assert np.allclose(scale, expected_scale), f"Expected scale {expected_scale}, got {scale}"
+    assert avg_err < 1e-7, f"Expected avg error to be near 0, got {avg_err}"