@@ -0,0 +1,1161 @@
+import pytest%0Aimport numpy as np%0Afrom plantcv.plantcv import landmark_reference_pt_dist, outputs%0A%0A%0A@pytest.mark.parametrize(%22points,centroid,bline%22, %5B%0A    %5B%5B(10, 1000)%5D, (10, 10), (10, 10)%5D,%0A    %5B%5B%5D, (0, 0), (0, 0)%5D,%0A    %5B%5B(0.0139, 0.2569), (0.2361, 0.2917), (0.3542, 0.3819), (0.3542, 0.4167), (0.375, 0.4236), (0.7431, 0.3681),%0A      (0.8958, 0.3542), (0.9931, 0.3125), (0.1667, 0.5139), (0.4583, 0.8889), (0.4931, 0.5903), (0.3889, 0.5694),%0A      (0.4792, 0.4306), (0.2083, 0.5417), (0.3194, 0.5278), (0.3889, 0.375), (0.3681, 0.3472), (0.2361, 0.0139),%0A      (0.5417, 0.2292), (0.7708, 0.3472), (0.6458, 0.3472), (0.6389, 0.5208), (0.6458, 0.625)%5D, (0.4685, 0.4945),%0A     (0.4685, 0.2569)%5D%0A%5D)%0Adef test_landmark_reference_pt_dist(points, centroid, bline):%0A    # Clear previous outputs%0A    outputs.clear()%0A    landmark_reference_pt_dist(points_r=points, centroid_r=centroid, bline_r=bline)%0A    assert len(outputs.observations%5B'default'%5D.keys()) == 8%0A%0A%0Adef test_landmark_reference_pt_dist_bad_centroid():%0A    result = landmark_reference_pt_dist(points_r=%5B%5D, centroid_r=('a', 'b'), bline_r=(0, 0))%0A    assert np.array_equal(np.unique(result), np.array(%5B%22NA%22%5D))%0A

Add landmark_reference_pt_dist tests module