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eventcv_core/representation/
averaged_time_surface.rs

1use super::{
2    age_ms, event_index, frame_len, reference_time, validate_positive, EventFrame, EventFrameData,
3    Representation, RepresentationError, RepresentationKind,
4};
5use crate::EventStream;
6
7/// Averaged time surface (HATS-style): where [`super::TimeSurface`] keeps only each pixel's
8/// *latest* exponential response, this averages `exp(-age / τ)` over **all** events that hit
9/// the pixel, so recurring activity reads brighter than a single stale hit. Two channels
10/// (positive / negative), `f32`, each pixel the mean response of its events (0 where none).
11#[derive(Clone, Copy, Debug)]
12pub struct AveragedTimeSurface {
13    tau_ms: f64,
14}
15
16impl AveragedTimeSurface {
17    pub fn new(tau_ms: f64) -> Self {
18        Self { tau_ms }
19    }
20}
21
22impl Default for AveragedTimeSurface {
23    fn default() -> Self {
24        Self::new(30.0)
25    }
26}
27
28impl Representation for AveragedTimeSurface {
29    type Output = EventFrame;
30
31    fn generate(&self, stream: &EventStream) -> Result<EventFrame, RepresentationError> {
32        validate_positive(self.tau_ms, "tau_ms")?;
33        let (width, height, length) = frame_len(stream, 2)?;
34        let plane_len = width * height;
35        let mut sums = vec![0.0_f64; length];
36        let mut counts = vec![0_u64; length];
37
38        if let Some(reference) = reference_time(stream) {
39            for event in stream.iter() {
40                let index =
41                    event_index(event, width, height)? + if event.polarity { 0 } else { plane_len };
42                let response = (-age_ms(stream, reference, event.timestamp) / self.tau_ms).exp();
43                sums[index] += response;
44                counts[index] += 1;
45            }
46        }
47
48        let values = sums
49            .into_iter()
50            .zip(counts)
51            .map(|(sum, count)| {
52                if count == 0 {
53                    0.0
54                } else {
55                    (sum / count as f64) as f32
56                }
57            })
58            .collect();
59
60        Ok(EventFrame {
61            data: EventFrameData::F32(values),
62            channels: 2,
63            width,
64            height,
65            kind: RepresentationKind::AveragedTimeSurface,
66            channel_names: vec!["positive".to_owned(), "negative".to_owned()],
67        })
68    }
69}
70
71#[cfg(test)]
72mod tests {
73    use ndarray::array;
74
75    use super::{AveragedTimeSurface, Representation};
76    use crate::{representation::EventFrameData, EventStream};
77
78    #[test]
79    fn averages_all_events_at_a_pixel() {
80        // Two positive events at (0,0): the newest (t=30_000) gives 1.0, the older
81        // (t=20_000, age 10 ms, τ=10 ms) gives e^-1; the pixel is their mean.
82        let stream = EventStream::from_array2(
83            array![[0, 0, 30_000, 1], [0, 0, 20_000, 1], [1, 0, 10_000, 0]],
84            2,
85            1,
86            0.001,
87        );
88
89        let frame = AveragedTimeSurface::new(10.0).generate(&stream).unwrap();
90        let EventFrameData::F32(values) = frame.data() else {
91            panic!("averaged time surfaces must use float32 data");
92        };
93
94        let expected_mean = (1.0 + (-1.0_f32).exp()) / 2.0;
95        assert!((values[0] - expected_mean).abs() < 1e-6);
96        assert_eq!(values[1], 0.0); // no positive events at (1,0)
97                                    // negative channel: the single event at (1,0) has age 20 ms → e^-2
98        assert!((values[3] - (-2.0_f32).exp()).abs() < 1e-6);
99    }
100
101    #[test]
102    fn rejects_invalid_tau() {
103        let stream = EventStream::from_array2(array![[0, 0, 10, 1]], 1, 1, 0.001);
104
105        let error = AveragedTimeSurface::new(0.0).generate(&stream).unwrap_err();
106
107        assert_eq!(error.to_string(), "tau_ms must be finite and positive");
108    }
109}