revisions

revisions

sleap/gui/app.py

@@ -511,13 +511,13 @@ def add_submenu_choices(menu, title, options, key):
             export_csv_menu,
             "export_csv_current_all_frames",
             "Current Video (all frames)...",
-            self.commands.exportCSVFile(all_frames=True),
+            lambda: self.commands.exportCSVFile(all_frames=True),
         )
         add_menu_item(
             export_csv_menu,
             "export_csv_all_all_frames",
             "All Videos (all frames)...",
-            lambda: self.commands.exportCSVFile(all_frames=True),
+            lambda: self.commands.exportCSVFile(all_videos=True, all_frames=True),
         )
 
         add_menu_item(fileMenu, "export_nwb", "Export NWB...", self.commands.exportNWB)

sleap/gui/commands.py

@@ -1143,23 +1143,23 @@ def do_action(cls, context: CommandContext, params: dict):
             else:
                 adaptor = SleapAnalysisAdaptor
 
-        if params['all_frames']:
-            adaptor.write(
-                filename=output_path,
-                all_frames=params.get('all_frames', False),
-                source_object=context.labels,
-                source_path=context.state["filename"],
-                video=video,
-                )
-        else:
-            adaptor.write(
-                filename=output_path,
-                all_frames=False,
-                source_object=context.labels,
-                source_path=context.state["filename"],
-                video=video,
-                )
-            
+            if 'all_frames' in params and params['all_frames']:
+                adaptor.write(
+                    filename=output_path,
+                    all_frames=True,
+                    source_object=context.labels,
+                    source_path=context.state["filename"],
+                    video=video,
+                    )
+            else:
+                adaptor.write(
+                    filename=output_path,
+                    all_frames=False,
+                    source_object=context.labels,
+                    source_path=context.state["filename"],
+                    video=video,
+                    )
+
     @staticmethod
     def ask(context: CommandContext, params: dict) -> bool:
         def ask_for_filename(default_name: str, csv: bool) -> str:

sleap/info/write_tracking_h5.py

@@ -287,7 +287,7 @@ def write_occupancy_file(
     print(f"Saved as {output_path}")
 
 
-def write_csv_file(output_path, data_dict):
+def write_csv_file(output_path, data_dict, all_frames):
 
     """Write CSV file with data from given dictionary.
 
@@ -348,7 +348,6 @@ def write_csv_file(output_path, data_dict):
             tracks.append(detection)
 
     tracks = pd.DataFrame(tracks)
-    all_frames = globals().get('all_frames', False)
 
     if all_frames:
         tracks = tracks.set_index('frame_idx')
@@ -443,7 +442,7 @@ def main(
     )
 
     if csv:
-        write_csv_file(output_path, data_dict)
+        write_csv_file(output_path, data_dict, all_frames=all_frames)
     else:
         write_occupancy_file(output_path, data_dict, transpose=True)
 

sleap/io/format/csv.py

@@ -45,7 +45,7 @@ def write(
         filename: str,
         source_object: Labels,
         source_path: str = None,
-        all_frames: bool= False,
+        all_frames: bool = False,
         video: Video = None,
     ):
         """Writes csv file for :py:class:`Labels` `source_object`.
@@ -54,15 +54,14 @@ def write(
             filename: The filename for the output file.
             source_object: The :py:class:`Labels` from which to get data from.
             source_path: Path for the labels object
-            all_frames: A boolean flag to determine whether to include all frames
-                or only those with tracking data in the export.
-            video: The :py:class:`Video` from which toget data from. If no `video` is
+            all_frames: A boolean flag to determine whether to include all frames or
+                only those with tracking data in the export.
+            video: The :py:class:`Video` from which to get data from. If no `video` is
                 specified, then the first video in `source_object` videos list will be
                 used. If there are no :py:class:`Labeled Frame`s in the `video`, then no
                 analysis file will be written.
         """
         from sleap.info.write_tracking_h5 import main as write_analysis
-
         write_analysis(
             labels=source_object,
             output_path=filename,

tests/gui/test_commands.py

@@ -279,6 +279,66 @@ def assert_videos_written(num_videos: int, labels_path: str = None):
     ExportAnalysisFile.do_action(context=context, params=params)
     assert_videos_written(num_videos=2, labels_path=context.state["filename"])
 
+    # Test with all_videos True and all_frames True
+    params = {"all_videos": True, "all_frames": True, "csv": csv}
+    okay = ExportAnalysisFile_ask(context=context, params=params)
+    assert okay == True
+    ExportAnalysisFile.do_action(context=context, params=params)
+    assert_videos_written(num_videos=2, labels_path=context.state["filename"])
+
+    # Test with all_videos False and all_frames True
+    params = {"all_videos": False, "all_frames": True, "csv": csv}
+    okay = ExportAnalysisFile_ask(context=context, params=params)
+    assert okay == True
+    ExportAnalysisFile.do_action(context=context, params=params)
+    assert_videos_written(num_videos=1, labels_path=context.state["filename"])
+
+    # Test with all_videos False and all_frames False
+    params = {"all_videos": False, "all_frames": False, "csv": csv}
+    okay = ExportAnalysisFile_ask(context=context, params=params)
+    assert okay == True
+    ExportAnalysisFile.do_action(context=context, params=params)
+    assert_videos_written(num_videos=1, labels_path=context.state["filename"])
+
+    # Add labels path and test with all_videos True and all_frames True (single video)
+    context.state["filename"] = str(tmpdir.with_name("path.to.labels"))
+    params = {"all_videos": True, "all_frames": True, "csv": csv}
+    okay = ExportAnalysisFile_ask(context=context, params=params)
+    assert okay == True
+    ExportAnalysisFile.do_action(context=context, params=params)
+    assert_videos_written(num_videos=2, labels_path=context.state["filename"])
+
+    # Add a video (no labels) and test with all_videos True and all_frames True
+    labels.add_video(small_robot_mp4_vid)
+
+    params = {"all_videos": True, "all_frames": True, "csv": csv}
+    okay = ExportAnalysisFile_ask(context=context, params=params)
+    assert okay == True
+    ExportAnalysisFile.do_action(context=context, params=params)
+    assert_videos_written(num_videos=2, labels_path=context.state["filename"])
+
+    # Test with videos with the same filename
+    (tmpdir / "session1").mkdir()
+    (tmpdir / "session2").mkdir()
+    shutil.copy(
+        centered_pair_predictions.video.backend.filename,
+        tmpdir / "session1" / "video.mp4",
+    )
+    shutil.copy(small_robot_mp4_vid.backend.filename, tmpdir / "session2" / "video.mp4")
+    labels.videos[0].backend.filename = str(tmpdir / "session1" / "video.mp4")
+    labels.videos[1].backend.filename = str(tmpdir / "session2" / "video.mp4")
+    params = {"all_videos": True, "csv": csv}
+    okay = ExportAnalysisFile_ask(context=context, params=params)
+    assert okay == True
+    ExportAnalysisFile.do_action(context=context, params=params)
+    assert_videos_written(num_videos=2, labels_path=context.state["filename"])
+
+    # Remove all videos and test
+    all_videos = list(labels.videos)
+    for video in all_videos:
+        labels.remove_video(labels.videos[-1])
+
+    params = {"all_videos": True, "all_frames": True, "csv": csv}
     # Test with videos with the same filename
     (tmpdir / "session1").mkdir()
     (tmpdir / "session2").mkdir()