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#!/usr/bin/env python
"""Implementation of K coefficient and K-modified coefficient.
"""
__author__ = "Théo de la Hogue"
__credits__ = []
__copyright__ = "Copyright 2023, Ecole Nationale de l'Aviation Civile (ENAC)"
__license__ = "BSD"
from dataclasses import dataclass
from argaze import GazeFeatures
import numpy
@dataclass
class ScanPathAnalyzer(GazeFeatures.ScanPathAnalyzer):
"""Implementation of the K coefficient algorithm as described in:
**Krejtz K., Duchowski A., Krejtz I., Szarkowska A., & Kopacz A. (2016).**
*Discerning ambient/focal attention with coefficient K.*
ACM Transactions on Applied Perception (TAP, 1–20).
[https://doi.org/10.1145/2896452](https://doi.org/10.1145/2896452)
"""
def __post_init__(self):
super().__init__()
self.__K = 0
def analyze(self, scan_path: GazeFeatures.ScanPathType):
"""Analyze scan path."""
assert(len(scan_path) > 1)
durations = []
amplitudes = []
for scan_step in scan_path:
durations.append(scan_step.duration)
amplitudes.append(scan_step.last_saccade.amplitude)
durations = numpy.array(durations)
amplitudes = numpy.array(amplitudes)
duration_mean = numpy.mean(durations)
amplitude_mean = numpy.mean(amplitudes)
duration_std = numpy.std(durations)
amplitude_std = numpy.std(amplitudes)
Ks = []
for scan_step in scan_path:
Ks.append(((scan_step.duration - duration_mean) / duration_std) - ((scan_step.last_saccade.amplitude - amplitude_mean) / amplitude_std))
self.__K = numpy.array(Ks).mean()
@property
def K(self) -> float:
return self.__K
@dataclass
class AOIScanPathAnalyzer(GazeFeatures.AOIScanPathAnalyzer):
"""Implementation of the K-modified coefficient algorithm as described in:
**Lounis, C. A., Hassoumi, A., Lefrancois, O., Peysakhovich, V., & Causse, M. (2020, June).**
*Detecting ambient/focal visual attention in professional airline pilots with a modified Coefficient K: a full flight simulator study.*
ACM Symposium on Eye Tracking Research and Applications (ETRA'20, 1-6).
[https://doi.org/10.1145/3379157.3391412](https://doi.org/10.1145/3379157.3391412)
"""
def __post_init__(self):
super().__init__()
self.__K = 0
def analyze(self, aoi_scan_path: GazeFeatures.AOIScanPathType) -> float:
"""Analyze aoi scan path."""
assert(len(aoi_scan_path) > 1)
durations = []
amplitudes = []
for aoi_scan_step in aoi_scan_path:
durations.append(aoi_scan_step.duration)
amplitudes.append(aoi_scan_step.last_saccade.amplitude)
durations = numpy.array(durations)
amplitudes = numpy.array(amplitudes)
duration_mean = numpy.mean(durations)
amplitude_mean = numpy.mean(amplitudes)
duration_std = numpy.std(durations)
amplitude_std = numpy.std(amplitudes)
Ks = []
for aoi_scan_step in aoi_scan_path:
Ks.append(((aoi_scan_step.duration - duration_mean) / duration_std) - ((aoi_scan_step.last_saccade.amplitude - amplitude_mean) / amplitude_std))
self.__K = numpy.array(Ks).mean()
@property
def K(self):
return self.__K
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