nopcoder/hud_binding.py at main · dotpipe/nopcoder · GitHub

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class HUDBinding:

    def __init__(self):

        self.bindings = []

    def bind(self, shape_name, signal, mode="mid", sensitivity=1.0):

        self.bindings.append({
            "shape": shape_name,
            "signal": signal,
            "mode": mode,
            "sensitivity": sensitivity
        })

    # ---------------------------------
    # RESOLVE ACTIVE VISUALS
    # ---------------------------------
    def resolve(self, inventory, signals):

        active = []

        for b in self.bindings:

            value = signals.get(b["signal"], 0)

            shape = inventory.get(b["shape"])

            if not shape:
                continue

            threshold_low = 0.3 * b["sensitivity"]
            threshold_high = 0.7 * b["sensitivity"]

            if value < threshold_low and b["mode"] == "low":
                active.append(shape)

            elif threshold_low <= value <= threshold_high and b["mode"] == "mid":
                active.append(shape)

            elif value > threshold_high and b["mode"] == "high":
                active.append(shape)

        return active

    def adapt(self, signals, learning_rate=0.05):

        for b in self.bindings:

            value = signals.get(b["signal"], 0)

            # -----------------------------
            # LOW SIGNAL RESPONSE
            # -----------------------------
            if value < 0.3:

                b["sensitivity"] -= learning_rate

            # -----------------------------
            # HIGH SIGNAL RESPONSE
            # -----------------------------
            elif value > 0.7:

                b["sensitivity"] += learning_rate

            # clamp
            b["sensitivity"] = max(0.1, min(2.0, b["sensitivity"]))