Added tests for get_network_distribution

tests/test_networklength.py

@@ -1,5 +1,6 @@
 import pytest
 import numpy as np
+from shapely import LineString, Polygon
 from sleap_roots import Series
 from sleap_roots.convhull import get_chull_area, get_convhull
 from sleap_roots.lengths import get_max_length_pts, get_root_lengths
@@ -169,6 +170,103 @@ def test_get_network_solidity_rice(rice_h5):
     np.testing.assert_almost_equal(ratio, 0.03366254601775008, decimal=7)
 
 
+def test_get_network_distribution_one_point():
+    # Define inputs
+    primary_pts = np.array([[[1, 1], [2, 2], [3, 3]]])
+    lateral_pts = np.array(
+        [[[4, 4], [5, 5]], [[6, 6], [np.nan, np.nan]]]
+    )  # One of the roots has only one point
+    bounding_box = (0, 0, 10, 10)
+    fraction = 2 / 3
+    monocots = False
+
+    # Call the function
+    network_length = get_network_distribution(
+        primary_pts, lateral_pts, bounding_box, fraction, monocots
+    )
+
+    # Define the expected result
+    # Only the valid roots should be considered in the calculation
+    lower_box = Polygon(
+        [(0, 10 - 10 * (2 / 3)), (0, 10), (10, 10), (10, 10 - 10 * (2 / 3))]
+    )
+    expected_length = (
+        LineString(primary_pts[0]).intersection(lower_box).length
+        + LineString(lateral_pts[0]).intersection(lower_box).length
+    )
+
+    # Assert that the result is as expected
+    assert network_length == pytest.approx(expected_length)
+
+
+def test_get_network_distribution_empty_arrays():
+    primary_pts = np.full((2, 2), np.nan)
+    lateral_pts = np.full((2, 2, 2), np.nan)
+    bounding_box = (0, 0, 10, 10)
+
+    network_length = get_network_distribution(primary_pts, lateral_pts, bounding_box)
+    assert network_length == 0
+
+
+def test_get_network_distribution_with_nans():
+    primary_pts = np.array([[1, 1], [2, 2], [np.nan, np.nan]])
+    lateral_pts = np.array([[[4, 4], [5, 5], [np.nan, np.nan]]])
+    bounding_box = (0, 0, 10, 10)
+
+    network_length = get_network_distribution(primary_pts, lateral_pts, bounding_box)
+
+    lower_box = Polygon(
+        [(0, 10 - 10 * (2 / 3)), (0, 10), (10, 10), (10, 10 - 10 * (2 / 3))]
+    )
+    expected_length = (
+        LineString(primary_pts[:-1]).intersection(lower_box).length
+        + LineString(lateral_pts[0, :-1]).intersection(lower_box).length
+    )
+
+    assert network_length == pytest.approx(expected_length)
+
+
+def test_get_network_distribution_monocots():
+    primary_pts = np.array([[1, 1], [2, 2], [3, 3]])
+    lateral_pts = np.array([[[4, 4], [5, 5]]])
+    bounding_box = (0, 0, 10, 10)
+    monocots = True
+
+    network_length = get_network_distribution(
+        primary_pts, lateral_pts, bounding_box, monocots=monocots
+    )
+
+    lower_box = Polygon(
+        [(0, 10 - 10 * (2 / 3)), (0, 10), (10, 10), (10, 10 - 10 * (2 / 3))]
+    )
+    expected_length = (
+        LineString(lateral_pts[0]).intersection(lower_box).length
+    )  # Only lateral_pts are considered
+
+    assert network_length == pytest.approx(expected_length)
+
+
+def test_get_network_distribution_different_fraction():
+    primary_pts = np.array([[1, 1], [2, 2], [3, 3]])
+    lateral_pts = np.array([[[4, 4], [5, 5]]])
+    bounding_box = (0, 0, 10, 10)
+    fraction = 0.5
+
+    network_length = get_network_distribution(
+        primary_pts, lateral_pts, bounding_box, fraction=fraction
+    )
+
+    lower_box = Polygon(
+        [(0, 10 - 10 * fraction), (0, 10), (10, 10), (10, 10 - 10 * fraction)]
+    )
+    expected_length = (
+        LineString(primary_pts).intersection(lower_box).length
+        + LineString(lateral_pts[0]).intersection(lower_box).length
+    )
+
+    assert network_length == pytest.approx(expected_length)
+
+
 def test_get_network_distribution(canola_h5):
     series = Series.load(
         canola_h5, primary_name="primary_multi_day", lateral_name="lateral_3_nodes"