Renaming logging doc file into recording. Updating examples.

1 files changed, 0 insertions, 152 deletions

diff --git a/docs/user_guide/gaze_analysis_pipeline/logging.md b/docs/user_guide/gaze_analysis_pipeline/logging.md
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--- a/docs/user_guide/gaze_analysis_pipeline/logging.md
+++ /dev/null
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-Record gaze analysis
-=================
-
-[ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) and [ArLayer](../../argaze.md/#argaze.ArFeatures.ArLayer) analysis can be recorded by registering observers to their **look** method.
-
-## Export gaze analysis to CSV file
-
-[ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) and [ArLayer](../../argaze.md/#argaze.ArFeatures.ArLayer) have an *observers* attribute to enable pipeline execution recording.
-
-Here is an extract from the JSON ArFrame configuration file where recording is enabled for the [ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) and for one [ArLayer](../../argaze.md/#argaze.ArFeatures.ArLayer) by loaded classes from Python files:
-
-```json
-{
-    "name": "My FullHD screen",
-    "size": [1920, 1080],
-    "observers": {
-        "my_recorders.ScanPathAnalysisRecorder": {
-            "path": "./scan_path_metrics.csv"
-        },
-    ...
-    "layers": {
-        "MyLayer": {
-            "observers": {
-                "my_recorders.AOIScanPathAnalysisRecorder": {
-                    "path": "./aoi_scan_path_metrics.csv"
-                }
-            },
-            ...
-        }
-    }
-}
-```
-
-!!! note
-    [ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) and its [ArLayers](../../argaze.md/#argaze.ArFeatures.ArLayer) automatically notify **look** method observers after each call.
-
-Here is *my_recorders.py* file:
-
-```python
-from argaze.utils import UtilsFeatures
-
-class ScanPathAnalysisRecorder(UtilsFeatures.FileWriter):
-
-    def __init__(self, **kwargs):
-
-        # Init FileWriter
-        super().__init__(**kwargs)
-
-        # Edit hearder line
-        self.header = "Timestamp (ms)", "Duration (ms)", "Steps number"
-
-    def on_look(self, timestamp, ar_frame, exception):
-        """Record scan path metrics"""
-
-        if ar_frame.is_analysis_available():
-
-            analysis = ar_frame.analysis()
-
-            data = (
-                timestamp, 
-                analysis['argaze.GazeAnalysis.Basic.ScanPathAnalyzer'].path_duration, 
-                analysis['argaze.GazeAnalysis.Basic.ScanPathAnalyzer'].steps_number
-            )
-
-            # Write to file
-            self.write(data)
-
-class AOIScanPathAnalysisRecorder(UtilsFeatures.FileWriter):
-
-    def __init__(self, **kwargs):
-
-        # Init FileWriter
-        super().__init__(**kwargs)
-
-        # Edit header line
-        self.header = "Timestamp (ms)", "NGram counts"
-
-    def on_look(self, timestamp, ar_layer, exception):
-        """Record aoi scan path metrics."""
-
-        if ar_layer.is_analysis_available():
-
-            data = (
-                timestamp,
-                ar_layer.analysis['argaze.GazeAnalysis.NGram.AOIScanPathAnalyzer'].ngrams_count
-            )
-
-            # Write to file
-            self.write(data)
-```
-
-Assuming that [ArGaze.GazeAnalysis.Basic](../../argaze.md/#argaze.GazeAnalysis.Basic) scan path analysis module is enabled for 'My FullHD screen' ArFrame, a ***scan_path_metrics.csv*** file would be created:
-
-|Timestamp (ms)|Duration (ms)|Steps number|
-|:-------------|:------------|:-----------|
-|3460          |1750         |2           |
-|4291          |2623         |3           |
-|4769          |3107         |4           |
-|6077          |4411         |5           |
-|6433          |4760         |6           |
-|7719          |6050         |7           |
-|...           |...          |...         |
-
-Assuming that [ArGaze.GazeAnalysis.NGram](../../argaze.md/#argaze.GazeAnalysis.NGram) AOI scan path analysis module is enabled for 'MyLayer' ArLayer, a ***aoi_scan_path_metrics.csv*** file would be created:
-
-|Timestamp (ms)|NGram counts|
-|:-------------|:-----------|
-|5687          |"{3: {}, 4: {}, 5: {}}"|
-|6208          |"{3: {('LeftPanel', 'GeoSector', 'CircularWidget'): 1}, 4: {}, 5: {}}"|
-|...           |...         |
-
-!!! note ""
-
-    Learn to [script the pipeline](./advanced_topics/scripting.md) to know more about [ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) and [ArLayers](../../argaze.md/#argaze.ArFeatures.ArLayer) attributes.
-
-### Export gaze analysis to video file
-
-As explained in [pipeline steps visualisation chapter](visualisation.md), it is possible to get [ArFrame.image](../../argaze.md/#argaze.ArFeatures.ArFrame.image) once timestamped gaze positions have been processed by [ArFrame.look](../../argaze.md/#argaze.ArFeatures.ArFrame.look) method.
-
-Here is the JSON ArFrame configuration file where [ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) observers are extended with a new my_frame_logger.VideoRecorder instance:
-
-```json
-{
-    "name": "My FullHD screen",
-    "size": [1920, 1080],
-    "observers": {
-        ...
-        "my_frame_logger.VideoRecorder": {
-            "path": "./video.mp4",
-            "width": 1920,
-            "height": 1080,
-            "fps": 15
-        },
-    ...
-}
-```
-
-Here is *my_frame_logger.py* file extended with a new VideoRecorder class:
-
-```python
-...
-
-class VideoRecorder(DataFeatures.PipelineStepObserver, UtilsFeatures.VideoWriter):
-
-    def on_look(self, timestamp, ar_frame, exception):
-        """Record frame image into video file."""
-
-        self.write(ar_frame.image())
-
-```
-
-Assuming that [ArFrame.image_parameters](../../argaze.md/#argaze.ArFeatures.ArFrame.image_parameters) are provided, ***video.mp4*** file would be created.
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