fixed comments from draft pull request

docs/source/api_index.rst

@@ -13,6 +13,7 @@ Input/Output
     from_sleap_file
     from_dlc_file
     from_dlc_df
+    from_lp_file
 
 .. currentmodule:: movement.io.save_poses
 .. autosummary::

docs/source/getting_started.md

@@ -95,6 +95,14 @@ ds = load_poses.from_dlc_df(df, fps=30)
 ```
 :::
 
+:::{tab-item} Lightning Pose
+
+Load from Lightning Pose (LP) files (`.csv`):
+```python
+ds = load_poses.from_lp_file("/path/to/file.analysis.csv", fps=30)
+```
+:::
+
 ::::
 
 You can also try movement out on some sample data included in the package.

docs/source/sg_execution_times.rst

@@ -0,0 +1,37 @@
+
+:orphan:
+
+.. _sphx_glr_sg_execution_times:
+
+
+Computation times
+=================
+**00:00.401** total execution time for 1 file **from all galleries**:
+
+.. container::
+
+  .. raw:: html
+
+    <style scoped>
+    <link href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/5.3.0/css/bootstrap.min.css" rel="stylesheet" />
+    <link href="https://cdn.datatables.net/1.13.6/css/dataTables.bootstrap5.min.css" rel="stylesheet" />
+    </style>
+    <script src="https://code.jquery.com/jquery-3.7.0.js"></script>
+    <script src="https://cdn.datatables.net/1.13.6/js/jquery.dataTables.min.js"></script>
+    <script src="https://cdn.datatables.net/1.13.6/js/dataTables.bootstrap5.min.js"></script>
+    <script type="text/javascript" class="init">
+    $(document).ready( function () {
+        $('table.sg-datatable').DataTable({order: [[1, 'desc']]});
+    } );
+    </script>
+
+  .. list-table::
+   :header-rows: 1
+   :class: table table-striped sg-datatable
+
+   * - Example
+     - Time
+     - Mem (MB)
+   * - :ref:`sphx_glr_examples_load_and_explore_poses.py` (``../../examples/load_and_explore_poses.py``)
+     - 00:00.401
+     - 0.0

movement/io/load_poses.py

@@ -163,7 +163,7 @@ def from_sleap_file(
 def from_lp_file(
     file_path: Union[Path, str], fps: Optional[float] = None
 ) -> xr.Dataset:
-    """Load pose tracking data from a LightningPose output file
+    """Load pose tracking data from a LightningPose (LP) output file
     into an xarray Dataset.
 
     Parameters
@@ -180,14 +180,10 @@ def from_lp_file(
     xarray.Dataset
         Dataset containing the pose tracks, confidence scores, and metadata.
 
-    See Also
-    --------
-    movement.io.load_poses.from_dlc_df : Load pose tracks from a DataFrame.
-
     Examples
     --------
     >>> from movement.io import load_poses
-    >>> ds = load_poses.from_lp_file("path/to/file.h5", fps=30)
+    >>> ds = load_poses.from_lp_file("path/to/file.csv", fps=30)
     """
 
     return _from_lp_or_dlc_file(
@@ -235,35 +231,31 @@ def _from_lp_or_dlc_file(
     source_software: Literal["LightningPose", "DeepLabCut"],
     fps: Optional[float] = None,
 ) -> xr.Dataset:
-    """Loads pose tracking data from a DeepLabCut (DLC) output file or
-    a LightningPose file into an xarray Dataset.
+    """Loads pose tracking data from a DeepLabCut (DLC) or
+    a LightningPose (LP) output file into an xarray Dataset.
 
     Parameters
     ----------
     file_path : pathlib.Path or str
         Path to the file containing the DLC predicted poses, either in ".h5"
         or ".csv" format.
+    source_software : {'LightningPose', 'DeepLabCut'}
     fps : float, optional
         The number of frames per second in the video. If None (default),
         the `time` coordinates will be in frame numbers.
-    source_software : Can be either "DeepLabCut" or "LightningPose".
 
     Returns
     -------
     xarray.Dataset
         Dataset containing the pose tracks, confidence scores, and metadata.
-
-    See Also
-    --------
-    movement.io.load_poses.from_dlc_df : Load pose tracks from a DataFrame.
-    from_lp_file
-
     """
 
+    expected_suffix = [".csv"]
+    if source_software == "DeepLabCut":
+        expected_suffix.append(".h5")
+
     file = ValidFile(
-        file_path,
-        expected_permission="r",
-        expected_suffix=[".csv", ".h5"],
+        file_path, expected_permission="r", expected_suffix=expected_suffix
     )
 
     # Load the DLC poses into a DataFrame

tests/conftest.py

@@ -28,6 +28,8 @@ def pytest_configure():
             "SLEAP_three-mice_Aeon_proofread.predictions.slp",
             "SLEAP_three-mice_Aeon_mixed-labels.analysis.h5",
             "SLEAP_three-mice_Aeon_mixed-labels.predictions.slp",
+            "LP_mouse-face_AIND.predictions.csv",
+            "LP_mouse-twoview_AIND.predictions.csv",
         ]
     }