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diff --git a/docs/user_guide/gaze_analysis_pipeline/logging.md b/docs/user_guide/gaze_analysis_pipeline/logging.md new file mode 100644 index 0000000..422b43b --- /dev/null +++ b/docs/user_guide/gaze_analysis_pipeline/logging.md @@ -0,0 +1,97 @@ +Log gaze analysis +================= + +[ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) and [ArLayer](../../argaze.md/#argaze.ArFeatures.ArLayer) logging are optional pipeline steps. They are executed at each new scan path step to update logs. + +## Enable ArFrame and ArLayer logging + +[ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) and [ArLayer](../../argaze.md/#argaze.ArFeatures.ArLayer) have a log attribute to enable analysis logging. + +Here is the JSON ArFrame configuration file example where logging is enabled for the ArFrame and for one ArLayer: + +```json +{ + "name": "My FullHD screen", + "size": [1920, 1080], + "log": true, + ... + "layers": { + "MyLayer": { + "log": true, + ... + } + } +} +``` + +Then, here is how to access to logs dictionaries: + +```python +# Assuming that all timestamped gaze positions have been processed by ArFrame.look method +... + +# Access to ArFame scan path analysis logs +for analysis, log in ar_frame.logs.items(): + + # Do something with scan path analysis log + ... + +# Access to ArLayers AOI scan path analysis logs +for layer_name, layer in ar_frame.layers.items(): + + for analysis, log in layer.logs.items(): + + # Do something with AOI scan path analysis log + ... +``` + +!!! note + [ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) and its [ArLayers](../../argaze.md/#argaze.ArFeatures.ArLayer) logging are automatically done each time the [ArFrame.look](../../argaze.md/#argaze.ArFeatures.ArFrame.look) method is called. + [ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) logging records each scan path analysis into a dedicated timestamped data buffer each time a new scan path step happens. + [ArLayer](../../argaze.md/#argaze.ArFeatures.ArLayer) logging records each AOI scan path analysis into a dedicated timestamped data buffer each time a new AOI scan path step happens. + +## Export gaze analysis logs to CSV file + +It is possible to convert gaze analysis log as [Pandas DataFrame](https://pandas.pydata.org/docs/getting_started/intro_tutorials/01_table_oriented.html#min-tut-01-tableoriented) object which can be writen into a CSV file. + +```python +import pandas + +# Assuming that all timestamped gaze positions have been processed by ArFrame.look method +... + +# Export ArFame scan path analysis logs +for analysis, log in ar_frame.logs.items(): + + log.as_dataframe().to_csv(f'./{ar_frame.name}_{analysis}.csv') + +# Export ArLayers layers AOI scan path analysis logs +for layer_name, layer in ar_frame.layers.items(): + + for analysis, log in layer.logs.items(): + + log.as_dataframe().to_csv(f'./{ar_frame.name}_{layer_name}_{analysis}.csv') + +``` + +Assuming that [ArGaze.GazeAnalysis.Basic](../../argaze.md/#argaze.GazeAnalysis.Basic) scan path analysis module is enabled for 'My FullHD screen' ArFrame, a ***My FullHD screen_argaze.GazeAnalysis.Basic.csv*** file would be created: + +|timestamped|path_duration|step_fixation_durations_average|steps_number| +|:----------|:------------|:------------------------------|:-----------| +|3460 |1750 |563.0 |2 | +|4291 |2623 |652.0 |3 | +|4769 |3107 |544.0 |4 | +|6077 |4411 |652.8 |5 | +|6433 |4760 |595.1 |6 | +|7719 |6050 |652.8 |7 | +|... |... |... |... | + +Assuming that [ArGaze.GazeAnalysis.NGram](../../argaze.md/#argaze.GazeAnalysis.NGram) AOI scan path analysis module is enabled for 'MyLayer' ArLayer, a ***My FullHD screen_MyLayer_argaze.GazeAnalysis.NGram.csv*** file would be created: + +|timestamped|ngrams_count| +|:----------|:-----------| +|5687 |"{3: {}, 4: {}, 5: {}}"| +|6208 |"{3: {('upper_left_corner', 'lower_left_corner', 'lower_right_corner'): 1}, 4: {}, 5: {}}"| +|... |... | + + |