test export_csv method added to Labels class

tests/io/test_dataset.py

@@ -1,9 +1,11 @@
 import os
+import pandas as pd
 import pytest
 import numpy as np
 from pathlib import Path, PurePath
 
 import sleap
+from sleap.info.write_tracking_h5 import get_nodes_as_np_strings
 from sleap.skeleton import Skeleton
 from sleap.instance import Instance, Point, LabeledFrame, PredictedInstance, Track
 from sleap.io.video import Video, MediaVideo
@@ -1559,3 +1561,47 @@ def test_export_nwb(centered_pair_predictions: Labels, tmpdir):
     # Read from NWB file
     read_labels = NDXPoseAdaptor.read(NDXPoseAdaptor, filehandle.FileHandle(filename))
     assert_read_labels_match(centered_pair_predictions, read_labels)
+
+
+@pytest.mark.parametrize("labels_fixture_name", [
+    "centered_pair_labels",
+    "centered_pair_predictions",
+    "min_labels",
+    "min_labels_slp",
+    "min_labels_robot"
+])
+def test_export_csv(labels_fixture_name, tmpdir, request):
+    # Retrieve Labels fixture by name
+    labels_fixture = request.getfixturevalue(labels_fixture_name)
+
+    # Generate the filename for the CSV file
+    csv_filename = Path(tmpdir) / (labels_fixture_name + "_export.csv")
+
+    # Export to CSV file
+    labels_fixture.export_csv(str(csv_filename))
+
+    # Assert that the CSV file was created
+    assert csv_filename.is_file(), f"CSV file '{csv_filename}' was not created"
+
+
+def test_exported_csv(tmpdir, min_labels_slp, minimal_instance_predictions_csv_path):
+    # Construct the filename for the CSV file
+    filename_csv = str(tmpdir + "\\analysis.csv")
+    labels = min_labels_slp
+    # Export to CSV file
+    labels.export_csv(filename_csv)
+    # Read the CSV file
+    labels_csv = pd.read_csv(filename_csv)
+
+    # Read the csv file fixture
+    csv_predictions = pd.read_csv(minimal_instance_predictions_csv_path)
+
+    assert labels_csv.equals(csv_predictions)
+
+    # check number of cols
+    assert len(labels_csv.columns) - 3 == len(get_nodes_as_np_strings(labels)) * 3
+
+
+
+
+