Script the pipeline
===================

All gaze analysis pipeline objects are accessible from Python script.
This could be particularly useful for realtime gaze interaction applications.

## Load ArFrame configuration from dictionary

First of all, [ArFrame](../../../argaze.md/#argaze.ArFeatures.ArFrame) configuration can be loaded from a python dictionary.

```python
from argaze import ArFeatures

# Edit a dict with ArFrame configuration
configuration = {
	"name": "My FullHD screen",
    "size": (1920, 1080),
    ...
    "gaze_movement_identifier": {
        ...
    },
    "scan_path": {
        ...
    },
    "scan_path_analyzers": {
        ...
    },
    "heatmap": {
        ...
    },
    "layers": {
        "MyLayer": {
            ...
        },
        ...
    },
    "image_parameters": {
        ...
    }
}

# Load ArFrame
ar_frame = ArFeatures.ArFrame.from_dict(configuration)

# Do something with ArFrame
...
```

## Access to ArFrame and ArLayers attributes

Then, once the configuration is loaded, it is possible to access to its attributes: [read ArFrame code reference](../../../argaze.md/#argaze.ArFeatures.ArFrame) to get a complete list of what is available.

Thus, the [ArFrame.layers](../../../argaze.md/#argaze.ArFeatures.ArFrame) attribute allows to access each loaded layer and so, access to their attributes: [read ArLayer code reference](../../../argaze.md/#argaze.ArFeatures.ArLayer) to get a complete list of what is available.

```python
from argaze import ArFeatures

# Assuming the ArFrame is loaded
...

# Iterate over each ArFrame layers
for name, ar_layer in ar_frame.layers.items():
    ...
```

## Pipeline execution updates

Calling [ArFrame.look](../../../argaze.md/#argaze.ArFeatures.ArFrame.look) method leads to update many data into the pipeline.

```python
# Assuming that timestamped gaze positions are available
...

    try:

        # Look ArFrame at a timestamped gaze position and iterate over analysis
        for element, module, analysis in ar_frame.look(timestamp, gaze_position):

            # Ckeck if analysis comes from frame
            if ArFeatures.is_frame(element):

                # Do something with scan path module analysis
                ...

            # Ckeck if analysis comes from frame
            elif ArFeatures.is_layer(element):

                # Do something with aoi scan path module analysis
                ...

        # Do something with calibrated gaze position
        ... ar_frame.gaze_position

        # Check if a gaze movement has been identified
        if ar_frame.gaze_movement.valid and ar_frame.gaze_movement.finished:

            # Do something with identified fixation
            if GazeFeatures.is_fixation(ar_frame.gaze_movement):
                ...

            # Do something with identified saccade
            elif GazeFeatures.is_saccade(ar_frame.gaze_movement):
                ...

    # Do something with pipeline exception
    except Exception as e:
        
        ...
```

Let's understand the meaning of each data.

### *element, module, analysis*

Looking at [ArFrame](../../../argaze.md/#argaze.ArFeatures.ArFrame) leads inner [ArFrame](../../../argaze.md/#argaze.ArFeatures.ArFrame) scan path analyzers and inner [Arlayers](../../../argaze.md/#argaze.ArFeatures.ArLayer) aoi scan path analysis to produce analysis. 

The *element* returning analysis can be tested thanks to [ArFeatures.is_frame](../../../argaze.md/#argaze.ArFeatures.is_frame) and [ArFeatures.is_layer](../../../argaze.md/#argaze.ArFeatures.is_layer) functions.

The *module* is the type of scan path or aoi scan path analyzer.

The *analysis* is a dictionnary containing all analysis produced by the module.

### *ar_frame.gaze_position*

This is the calibrated [GazePosition](../../../argaze.md/#argaze.GazeFeatures.GazePosition) returned by [GazePositionCalibrator](../../../argaze.md/#argaze.GazeFeatures.GazePositionCalibrator) if one is instanciated else, it is the given [GazePosition](../../../argaze.md/#argaze.GazeFeatures.GazePosition).

### *ar_frame.gaze_movement*

A [GazeMovement](../../../argaze.md/#argaze.GazeFeatures.GazeMovement) once it have been identified by [ArFrame.gaze_movement_identifier](../../../argaze.md/#argaze.ArFeatures.ArFrame) object from incoming consecutive timestamped gaze positions. If no gaze movement have been identified, it returns an [UnvalidGazeMovement](../../../argaze.md/#argaze.GazeFeatures.UnvalidGazeMovement). 

This could also be the current gaze movement if [ArFrame.filter_in_progress_identification](../../../argaze.md/#argaze.ArFeatures.ArFrame) attribute is false.
In that case, the returned gaze movement *finished* flag is false.

Then, the returned gaze movement type can be tested thanks to [GazeFeatures.is_fixation](../../../argaze.md/#argaze.GazeFeatures.is_fixation) and [GazeFeatures.is_saccade](../../../argaze.md/#argaze.GazeFeatures.is_saccade) functions.

### *ar_frame.new_analysis_available* and *ar_layer.new_analysis_available*

This flag allows to now when new scan path and aoi scan path analysis are available.

### *analyzer.analysis*

A dictionary containing all data produced by an analyzer.

## Setup ArFrame image parameters

[ArFrame.image](../../../argaze.md/#argaze.ArFeatures.ArFrame.image) method parameters can be configured thanks to a python dictionary.

```python
# Assuming ArFrame is loaded
...

# Edit a dict with ArFrame image parameters
image_parameters = {
    "draw_scan_path": {
        ...
    },
    "draw_layers": {
        "MyLayer": {
            ...
        }
    },
    ...
}

# Pass image parameters to ArFrame
ar_frame_image = ar_frame.image(**image_parameters)

# Do something with ArFrame image
...
```