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Load and execute pipeline
=========================

The [ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) class defines a rectangular area where timestamped gaze positions are projected in and inside which they need to be analyzed.

![Frame](../../img/ar_frame.png)

## Load JSON configuration file

The [ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) internal pipeline is entirely customizable from a JSON configuration file thanks to [ArFrame.from_json](../../argaze.md/#argaze.ArFeatures.ArFrame.from_json) class method. 

Here is a simple JSON [ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) configuration file example:

```json
{
	"name": "My FullHD screen",
	"size": [1920, 1080],
	"gaze_movement_identifier": {
		"DispersionThresholdIdentification": {
			"deviation_max_threshold": 50,
			"duration_min_threshold": 200
		}
	},
	"scan_path": {
		"duration_max": 30000
	},
	"scan_path_analyzers": {
		"Basic": {},
		"ExploreExploitRatio": {
            "short_fixation_duration_threshold": 0
        }
	}
}
```

Then, here is how to load the JSON file:

```python
from argaze import ArFeatures

# Load ArFrame
with ArFeatures.ArFrame.from_json('./configuration.json') as ar_frame:

	# Do something with ArFrame
	...
```

Now, let's understand the meaning of each JSON entry.

### *name*

The name of the [ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame). Basically useful for visualisation purpose.

### *size*

The size of the [ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) defines the dimension of the rectangular area where gaze positions are projected. Be aware that gaze positions have to be in the same range of value to be projected in.

!!! warning "Free spatial unit"
	Gaze positions can either be integer or float, pixels, millimeters or what ever you need. The only concern is that all spatial values used in further configurations have to be all the same unit.

### *gaze_movement_identifier*

The first [ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) pipeline step is to identify fixations or saccades from consecutive timestamped gaze positions.

![Gaze movement identifier](../../img/gaze_movement_identifier.png)

The identification algorithm can be selected by instantiating a particular [GazeMovementIdentifier from GazeAnalysis submodule](pipeline_modules/gaze_movement_identifiers.md) or [from another python package](advanced_topics/module_loading.md).

In the example file, the choosen identification algorithm is the [Dispersion Threshold Identification (I-DT)](../../argaze.md/#argaze.GazeAnalysis.DispersionThresholdIdentification) which has two specific *deviation_max_threshold* and *duration_min_threshold* attributes.

!!! note
	In ArGaze, [Fixation](../../argaze.md/#argaze.GazeFeatures.Fixation) and [Saccade](../../argaze.md/#argaze.GazeFeatures.Saccade) are considered as particular [GazeMovements](../../argaze.md/#argaze.GazeFeatures.GazeMovement).

!!! warning "Mandatory"
	JSON *gaze_movement_identifier* entry is mandatory. Otherwise, the ScanPath and ScanPathAnalyzers steps are disabled.

### *scan_path*

The second [ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) pipeline step aims to build a [ScanPath](../../argaze.md/#argaze.GazeFeatures.ScanPath) defined as a list of [ScanSteps](../../argaze.md/#argaze.GazeFeatures.ScanStep) made by a fixation and a consecutive saccade.

![Scan path](../../img/scan_path.png)

Once fixations and saccades are identified, they are automatically appended to the ScanPath if required.

The [ScanPath.duration_max](../../argaze.md/#argaze.GazeFeatures.ScanPath.duration_max) attribute is the duration from which older scan steps are removed each time new scan steps are added.

!!! note "Optional"
	JSON *scan_path* entry is not mandatory. If scan_path_analyzers entry is not empty, the ScanPath step is automatically enabled.

### *scan_path_analyzers*

Finally, the last [ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) pipeline step consists in passing the previously built [ScanPath](../../argaze.md/#argaze.GazeFeatures.ScanPath) to each loaded [ScanPathAnalyzer](../../argaze.md/#argaze.GazeFeatures.ScanPathAnalyzer).

Each analysis algorithm can be selected by instantiating a particular [ScanPathAnalyzer from GazeAnalysis submodule](pipeline_modules/scan_path_analyzers.md) or [from another python package](advanced_topics/module_loading.md).

In the example file, the choosen analysis algorithms are the [Basic](../../argaze.md/#argaze.GazeAnalysis.Basic) module and the [ExploreExploitRatio](../../argaze.md/#argaze.GazeAnalysis.ExploreExploitRatio) module which has one specific *short_fixation_duration_threshold* attribute.

## Pipeline execution

Timestamped gaze positions have to be passed one by one to [ArFrame.look](../../argaze.md/#argaze.ArFeatures.ArFrame.look) method to execute the whole instantiated pipeline. 

!!! warning "Mandatory"

	[ArFrame.look](../../argaze.md/#argaze.ArFeatures.ArFrame.look) method must be called from a *try* block to catch pipeline exceptions.

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

    try:

    	# Look ArFrame at a timestamped gaze position
    	ar_frame.look(timestamped_gaze_position)

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

	At this point, the [ArFrame.look](../../argaze.md/#argaze.ArFeatures.ArFrame.look) method only process gaze movement identification and scan path analysis without any AOI neither any logging or visualisation supports.

	Read the next chapters to learn how to [describe AOI](aoi_2d_description.md), [add AOI analysis](aoi_analysis.md), [log gaze analysis](logging.md) and [visualize pipeline steps](visualisation.md).