VesiscanClinicalAndroid/app/src/main/java/com/example/medilightv2android/managers/BladderSeekRTracker.kt

package com.example.medilightv2android.managers

import kotlin.math.abs

/**
 * R-fit trend tracker — watches per-frame sphere-fit radius and classifies:
 *   RISING  — sliding toward bladder centre (R increasing)
 *   PEAK    — at / near session maximum R
 *   FALLING — sliding past centre (R decreasing)
 *   NOISE   — fluctuating without clear trend
 *   IDLE    — no valid fit (too few channels)
 *
 * Ported from CKLaw BladderSeekRTracker.kt.
 */
class BladderSeekRTracker(
    private val historySize: Int = 8,
    private val peakToleranceMm: Double = 1.5,
    private val noiseDeltaMm: Double = 0.4,
) {
    enum class Trend { RISING, PEAK, FALLING, NOISE, IDLE }

    data class Status(
        val currentR: Double?,
        val bestR: Double,
        val trend: Trend,
        val improvementMm: Double,
        val hintEn: String,
    )

    private val history = ArrayDeque<Double>()
    var bestR: Double = 0.0
        private set

    fun reset() {
        history.clear()
        bestR = 0.0
    }

    fun submit(r: Double?): Status {
        if (r == null || r.isNaN() || r <= 0.0) {
            return Status(null, bestR, Trend.IDLE, 0.0,
                "Not enough channels — check signal")
        }
        history.addLast(r)
        while (history.size > historySize) history.removeFirst()
        if (r > bestR) bestR = r

        val trend = computeTrend(r)
        val gap = r - bestR
        val en = when (trend) {
            Trend.RISING -> "Getting closer (R=${"%.0f".format(r)}mm)"
            Trend.PEAK -> "At peak (R=${"%.0f".format(r)}mm)"
            Trend.FALLING -> "Past peak — reverse (best ${"%.0f".format(bestR)}mm)"
            Trend.NOISE -> "Searching (R=${"%.0f".format(r)}mm)"
            Trend.IDLE -> ""
        }
        return Status(r, bestR, trend, gap, en)
    }

    private fun computeTrend(currentR: Double): Trend {
        if (history.size < 3) return Trend.NOISE
        if (bestR - currentR < peakToleranceMm) return Trend.PEAK
        val prev = history.toList().dropLast(1).takeLast(3)
        val prevMean = prev.average()
        val delta = currentR - prevMean
        return when {
            abs(delta) < noiseDeltaMm -> Trend.NOISE
            delta > 0 -> Trend.RISING
            else -> Trend.FALLING
        }
    }
}