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EthoML · Jul 1, 2024 · 6f00c7f · 6f00c7f
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diff --git a/docs/vame-docs-app/docs/reference/sidebar.json b/docs/vame-docs-app/docs/reference/sidebar.json
@@ -6,7 +6,6 @@
         "reference/vame/analysis/generative_functions",
         "reference/vame/analysis/gif_creator",
         "reference/vame/analysis/pose_segmentation",
-        "reference/vame/analysis/segment_behavior",
         "reference/vame/analysis/tree_hierarchy",
         "reference/vame/analysis/umap_visualization",
         "reference/vame/analysis/videowriter"
@@ -21,6 +20,13 @@
       "label": "vame.initialize_project",
       "type": "category"
     },
+    {
+      "items": [
+        "reference/vame/logging/logger"
+      ],
+      "label": "vame.logging",
+      "type": "category"
+    },
     {
       "items": [
         "reference/vame/model/create_training",
@@ -32,6 +38,13 @@
       "label": "vame.model",
       "type": "category"
     },
+    {
+      "items": [
+        "reference/vame/schemas/states"
+      ],
+      "label": "vame.schemas",
+      "type": "category"
+    },
     {
       "items": [
         "reference/vame/util/align_egocentrical",

diff --git a/docs/vame-docs-app/docs/reference/vame/analysis/community_analysis.md b/docs/vame-docs-app/docs/reference/vame/analysis/community_analysis.md
@@ -286,7 +286,7 @@ Perform UMAP embedding for given file and parameters.
 
 ```python
 def umap_vis(cfg: dict, file: str, embed: np.ndarray,
-             community_labels_all: np.ndarray) -> None
+             community_labels_all: np.ndarray, save_path: str | None) -> None
 ```
 
 Create plotly visualizaton of UMAP embedding.
@@ -297,6 +297,7 @@ Create plotly visualizaton of UMAP embedding.
 - `file` _str_ - File path.
 - `embed` _np.ndarray_ - UMAP embedding.
 - `community_labels_all` _np.ndarray_ - Community labels.
+- `save_path` - Path to save the plot. If None it will not save the plot.
 
 
 **Returns**:
@@ -306,10 +307,13 @@ Create plotly visualizaton of UMAP embedding.
 #### community
 
 ```python
+@save_state(model=CommunityFunctionSchema)
 def community(config: str,
               cohort: bool = True,
               show_umap: bool = False,
-              cut_tree: int = None) -> None
+              cut_tree: int | None = None,
+              save_umap_figure: bool = True,
+              save_logs: bool = False) -> None
 ```
 
 Perform community analysis.

diff --git a/docs/vame-docs-app/docs/reference/vame/analysis/generative_functions.md b/docs/vame-docs-app/docs/reference/vame/analysis/generative_functions.md
@@ -115,7 +115,10 @@ Load PyTorch model.
 #### generative\_model
 
 ```python
-def generative_model(config: str, mode: str = "sampling") -> None
+@save_state(model=GenerativeModelFunctionSchema)
+def generative_model(config: str,
+                     mode: str = "sampling",
+                     save_logs: bool = False) -> plt.Figure
 ```
 
 Generative model.
@@ -128,5 +131,5 @@ Generative model.
 
 **Returns**:
 
-  None
+- `plt.Figure` - Plot of generated samples.
 
diff --git a/docs/vame-docs-app/docs/reference/vame/analysis/gif_creator.md b/docs/vame-docs-app/docs/reference/vame/analysis/gif_creator.md
@@ -44,7 +44,7 @@ def gif(
     config: str,
     pose_ref_index: int,
     subtract_background: bool = True,
-    start: int = None,
+    start: int | None = None,
     length: int = 500,
     max_lag: int = 30,
     label: str = 'community',
@@ -62,7 +62,7 @@ Create a GIF from the given configuration.
 - `start` _int, optional_ - Starting index. Defaults to None.
 - `length` _int, optional_ - Length of the video. Defaults to 500.
 - `max_lag` _int, optional_ - Maximum lag. Defaults to 30.
-- `label` _str, optional_ - Label type. Defaults to &#x27;community&#x27;.
+- `label` _str, optional_ - Label type [None, community, motif]. Defaults to &#x27;community&#x27;.
 - `file_format` _str, optional_ - File format. Defaults to &#x27;.mp4&#x27;.
 - `crop_size` _Tuple[int, int], optional_ - Crop size. Defaults to (300,300).
 

diff --git a/docs/vame-docs-app/docs/reference/vame/analysis/pose_segmentation.md b/docs/vame-docs-app/docs/reference/vame/analysis/pose_segmentation.md
@@ -32,8 +32,9 @@ Load the VAME model.
 #### embedd\_latent\_vectors
 
 ```python
-def embedd_latent_vectors(cfg: dict, files: List[str], model: RNN_VAE,
-                          fixed: bool) -> List[np.ndarray]
+def embedd_latent_vectors(
+        cfg: dict, files: List[str], model: RNN_VAE, fixed: bool,
+        tqdm_stream: TqdmToLogger | None) -> List[np.ndarray]
 ```
 
 Embed latent vectors for the given files using the VAME model.
@@ -44,6 +45,7 @@ Embed latent vectors for the given files using the VAME model.
 - `files` _List[str]_ - List of files names.
 - `model` _RNN_VAE_ - VAME model.
 - `fixed` _bool_ - Whether the model is fixed.
+- `tqdm_stream` _TqdmToLogger_ - TQDM Stream to redirect the tqdm output to logger.
 
 
 **Returns**:
@@ -134,7 +136,8 @@ Apply individual parametrization to each animal.
 #### pose\_segmentation
 
 ```python
-def pose_segmentation(config: str) -> None
+@save_state(model=PoseSegmentationFunctionSchema)
+def pose_segmentation(config: str, save_logs: bool = False) -> None
 ```
 
 Perform pose segmentation using the VAME model.

diff --git a/docs/vame-docs-app/docs/reference/vame/analysis/tree_hierarchy.md b/docs/vame-docs-app/docs/reference/vame/analysis/tree_hierarchy.md
@@ -14,7 +14,7 @@ Licensed under GNU General Public License v3.0
 
 ```python
 def hierarchy_pos(G: nx.Graph,
-                  root: str = None,
+                  root: str | None = None,
                   width: float = 0.5,
                   vert_gap: float = 0.2,
                   vert_loc: float = 0,
@@ -112,7 +112,7 @@ Draw a tree.
 #### traverse\_tree
 
 ```python
-def traverse_tree(T: nx.Graph, root_node: str = None) -> str
+def traverse_tree(T: nx.Graph, root_node: str | None = None) -> str
 ```
 
 Traverse a tree and return the traversal sequence.
@@ -130,7 +130,7 @@ Traverse a tree and return the traversal sequence.
 #### traverse\_tree
 
 ```python
-def traverse_tree(T: nx.Graph, root_node: str = None) -> str
+def traverse_tree(T: nx.Graph, root_node: str | None = None) -> str
 ```
 
 Traverse a tree and return the traversal sequence.
@@ -149,7 +149,7 @@ Traverse a tree and return the traversal sequence.
 
 ```python
 def traverse_tree_cutline(T: nx.Graph,
-                          root_node: str = None,
+                          root_node: str | None = None,
                           cutline: int = 2) -> List[List[str]]
 ```
 

diff --git a/docs/vame-docs-app/docs/reference/vame/analysis/umap_visualization.md b/docs/vame-docs-app/docs/reference/vame/analysis/umap_visualization.md
@@ -75,8 +75,10 @@ Visualize UMAP embedding with community labels.
 #### visualization
 
 ```python
+@save_state(model=VisualizationFunctionSchema)
 def visualization(config: Union[str, Path],
-                  label: Optional[str] = None) -> None
+                  label: Optional[str] = None,
+                  save_logs: bool = False) -> None
 ```
 
 Visualize UMAP embeddings based on configuration settings.

diff --git a/docs/vame-docs-app/docs/reference/vame/analysis/videowriter.md b/docs/vame-docs-app/docs/reference/vame/analysis/videowriter.md
@@ -13,8 +13,14 @@ Licensed under GNU General Public License v3.0
 #### get\_cluster\_vid
 
 ```python
-def get_cluster_vid(cfg: dict, path_to_file: str, file: str, n_cluster: int,
-                    videoType: str, flag: str) -> None
+def get_cluster_vid(cfg: dict,
+                    path_to_file: str,
+                    file: str,
+                    n_cluster: int,
+                    videoType: str,
+                    flag: str,
+                    output_video_type: str = ".mp4",
+                    tqdm_logger_stream: TqdmToLogger | None = None) -> None
 ```
 
 Generate cluster videos.
@@ -25,7 +31,7 @@ Generate cluster videos.
 - `path_to_file` _str_ - Path to the file.
 - `file` _str_ - Name of the file.
 - `n_cluster` _int_ - Number of clusters.
-- `videoType` _str_ - Type of video.
+- `videoType` _str_ - Type of input video.
 - `flag` _str_ - Flag indicating the type of video (motif or community).
 
 
@@ -36,7 +42,11 @@ Generate cluster videos.
 #### motif\_videos
 
 ```python
-def motif_videos(config: Union[str, Path], videoType: str = '.mp4') -> None
+@save_state(model=MotifVideosFunctionSchema)
+def motif_videos(config: Union[str, Path],
+                 videoType: str = '.mp4',
+                 output_video_type: str = '.mp4',
+                 save_logs: bool = False) -> None
 ```
 
 Generate motif videos.
@@ -45,6 +55,7 @@ Generate motif videos.
 
 - `config` _Union[str, Path]_ - Path to the configuration file.
 - `videoType` _str, optional_ - Type of video. Default is &#x27;.mp4&#x27;.
+- `output_video_type` _str, optional_ - Type of output video. Default is &#x27;.mp4&#x27;.
 
 
 **Returns**:
@@ -54,8 +65,10 @@ Generate motif videos.
 #### community\_videos
 
 ```python
+@save_state(model=CommunityVideosFunctionSchema)
 def community_videos(config: Union[str, Path],
-                     videoType: str = '.mp4') -> None
+                     videoType: str = '.mp4',
+                     save_logs: bool = False) -> None
 ```
 
 Generate community videos.

diff --git a/docs/vame-docs-app/docs/reference/vame/logging/logger.md b/docs/vame-docs-app/docs/reference/vame/logging/logger.md
@@ -0,0 +1,14 @@
+---
+sidebar_label: logger
+title: vame.logging.logger
+---
+
+## TqdmToLogger Objects
+
+```python
+class TqdmToLogger(io.StringIO)
+```
+
+Output stream for TQDM which will output to logger module instead of
+the StdOut.
+
diff --git a/docs/vame-docs-app/docs/reference/vame/model/create_training.md b/docs/vame-docs-app/docs/reference/vame/model/create_training.md
@@ -49,9 +49,13 @@ Interpolates all NaN values in the given array.
 #### plot\_check\_parameter
 
 ```python
-def plot_check_parameter(cfg: dict, iqr_val: float, num_frames: int,
-                         X_true: List[np.ndarray], X_med: np.ndarray,
-                         anchor_1: int, anchor_2: int) -> None
+def plot_check_parameter(cfg: dict,
+                         iqr_val: float,
+                         num_frames: int,
+                         X_true: List[np.ndarray],
+                         X_med: np.ndarray,
+                         anchor_1: int | None = None,
+                         anchor_2: int | None = None) -> None
 ```
 
 Plot the check parameter - z-scored data and the filtered data.
@@ -124,9 +128,11 @@ Create training dataset for fixed data.
 #### create\_trainset
 
 ```python
+@save_state(model=CreateTrainsetFunctionSchema)
 def create_trainset(config: str,
                     pose_ref_index: Optional[List] = None,
-                    check_parameter: bool = False) -> None
+                    check_parameter: bool = False,
+                    save_logs: bool = False) -> None
 ```
 
 Creates a training dataset for the VAME model.

diff --git a/docs/vame-docs-app/docs/reference/vame/model/dataloader.md b/docs/vame-docs-app/docs/reference/vame/model/dataloader.md
@@ -19,8 +19,8 @@ class SEQUENCE_DATASET(Dataset)
 #### \_\_init\_\_
 
 ```python
-def __init__(path_to_file: str, data: str, train: bool,
-             temporal_window: int) -> None
+def __init__(path_to_file: str, data: str, train: bool, temporal_window: int,
+             **kwargs) -> None
 ```
 
 Initialize the Sequence Dataset.

diff --git a/docs/vame-docs-app/docs/reference/vame/model/evaluate.md b/docs/vame-docs-app/docs/reference/vame/model/evaluate.md
@@ -75,7 +75,10 @@ Evaluate the temporal aspects of the trained model.
 #### evaluate\_model
 
 ```python
-def evaluate_model(config: str, use_snapshots: bool = False) -> None
+@save_state(model=EvaluateModelFunctionSchema)
+def evaluate_model(config: str,
+                   use_snapshots: bool = False,
+                   save_logs: bool = False) -> None
 ```
 
 Evaluate the trained model.