cuda

sgoldenlab · Sep 20, 2024 · 6ff22bc · 6ff22bc
1 parent 842386a
commit 6ff22bc
Show file tree

Hide file tree

Showing 3 changed files with 11 additions and 22 deletions.
diff --git a/docs/_static/img/simba.data_processors.cuda.geometry.is_inside_polygon.webp b/docs/_static/img/simba.data_processors.cuda.geometry.is_inside_polygon.webp
diff --git a/simba/data_processors/cuda/geometry.py b/simba/data_processors/cuda/geometry.py
@@ -135,6 +135,10 @@ def is_inside_polygon(x: np.ndarray, y: np.ndarray) -> np.ndarray:
     the polygon defined by the vertices in `y`. The result is an array where each element indicates whether
     the corresponding point is inside the polygon.
 
+    .. image:: _static/img/simba.data_processors.cuda.geometry.is_inside_polygon.webp
+       :width: 450
+       :align: center
+
     .. csv-table::
        :header: EXPECTED RUNTIMES
        :file: ../../../docs/tables/is_inside_polygon.csv
@@ -144,7 +148,7 @@ def is_inside_polygon(x: np.ndarray, y: np.ndarray) -> np.ndarray:
        :header-rows: 1
 
     .. seealso::
-       For numba CPU function see :func:`~simba.mixins.feature_extraction_mixin.FeatureExtractionMixin.framewise_inside_polygon_roi`
+       For jitted CPU function see :func:`~simba.mixins.feature_extraction_mixin.FeatureExtractionMixin.framewise_inside_polygon_roi`
 
     :param np.ndarray x: An array of shape (N, 2) where each row represents a point in 2D space. The points are checked against the polygon.
     :param np.ndarray y: An array of shape (M, 2) where each row represents a vertex of the polygon in 2D space.

diff --git a/simba/mixins/train_model_mixin.py b/simba/mixins/train_model_mixin.py
@@ -1492,19 +1492,9 @@ def _read_data_file_helper(file_path: str,
         if clf_names != None:
             for clf_name in clf_names:
                 if not clf_name in df.columns:
-                    raise ColumnNotFoundError(
-                        column_name=clf_name,
-                        file_name=file_path,
-                        source=TrainModelMixin._read_data_file_helper.__name__,
-                    )
-                elif (
-                        len(set(df[clf_name].unique()) - {0, 1}) > 0
-                        and raise_bool_clf_error
-                ):
-                    raise InvalidInputError(
-                        msg=f"The annotation column for a classifier should contain only 0 or 1 values. However, in file {file_path} the {clf_name} field contains additional value(s): {list(set(df[clf_name].unique()) - {0, 1})}.",
-                        source=TrainModelMixin._read_data_file_helper.__name__,
-                    )
+                    raise MissingColumnsError(msg=f'The SimBA project specifies a classifier named "{clf_name}" that could not be found in your dataset for file {file_path}. Make sure that your project_config.ini is created correctly.', source=TrainModelMixin._read_data_file_helper.__name__)
+                elif (len(set(df[clf_name].unique()) - {0, 1}) > 0 and raise_bool_clf_error):
+                    raise InvalidInputError(msg=f"The annotation column for a classifier should contain only 0 or 1 values. However, in file {file_path} the {clf_name} field column contains additional value(s): {list(set(df[clf_name].unique()) - {0, 1})}.", source=TrainModelMixin._read_data_file_helper.__name__)
         timer.stop_timer()
         print(f"Reading complete {vid_name} (elapsed time: {timer.elapsed_time_str}s)...")
 
@@ -1599,14 +1589,9 @@ def _read_data_file_helper_futures(
         if clf_names != None:
             for clf_name in clf_names:
                 if not clf_name in df.columns:
-                    raise ColumnNotFoundError(column_name=clf_name, file_name=file_path)
-                elif (
-                        len(set(df[clf_name].unique()) - {0, 1}) > 0
-                        and raise_bool_clf_error
-                ):
-                    raise InvalidInputError(
-                        msg=f"The annotation column for a classifier should contain only 0 or 1 values. However, in file {file_path} the {clf_name} field contains additional value(s): {list(set(df[clf_name].unique()) - {0, 1})}."
-                    )
+                    raise MissingColumnsError(msg=f'The SimBA project specifies a classifier named "{clf_name}" that could not be found in your dataset for file {file_path}. Make sure that your project_config.ini is created correctly.')
+                elif (len(set(df[clf_name].unique()) - {0, 1}) > 0 and raise_bool_clf_error):
+                    raise InvalidInputError(msg=f"The annotation column for a classifier should contain only 0 or 1 values. However, in file {file_path} the {clf_name} field contains additional value(s): {list(set(df[clf_name].unique()) - {0, 1})}.")
         timer.stop_timer()
         return df, vid_name, timer.elapsed_time_str, frm_numbers