pec5d: add pec5d/ipt_sensor.py

pec5d/ipt_sensor.py

@@ -0,0 +1,98 @@
+# pec5d/ipt_sensor.py
+"""
+IPT-SENSOR-Φ — Invisible Pressure Sensor device model.
+
+Sensing modalities:
+  photonic (432-528nm coherence) · bio-signal (HRV/GSR/EEG collective) ·
+  information field (sentiment entropy/narrative velocity) · social
+  (network topology shift) · environmental (ion density/geomagnetic) ·
+  quantum (entanglement coherence fluctuation)
+
+Outputs: Pressure Index (0.0-1.0) · Gradient Vector · Tipping Point ETA ·
+         Resonance Frequency Signature
+
+Form factors: IPT-MINI (desktop) · IPT-GRID (mesh) · IPT-PULSE (wearable)
+              IPT-CORAL (embedded in drones/bio-chips)
+"""
+
+from __future__ import annotations
+
+import time
+from typing import Any, Dict, List, Optional
+
+import numpy as np
+
+from pec5d.constants import CARRIER_HZ, PHI
+
+
+class IPTSensor:
+    """IPT-SENSOR-Φ — pressure field monitoring device."""
+
+    MODALITIES = [
+        "photonic_resonance",
+        "bio_signal",
+        "information_field",
+        "social_topology",
+        "environmental",
+        "quantum_coherence",
+    ]
+    FORM_FACTORS = {
+        "mini": "IPT-MINI — USB desktop ambient monitor",
+        "grid": "IPT-GRID — mesh network, city-scale",
+        "pulse": "IPT-PULSE — wearable personal field",
+        "coral": "IPT-CORAL — embedded in drones & bio-chips",
+    }
+
+    def __init__(self, form_factor: str = "mini"):
+        if form_factor not in self.FORM_FACTORS:
+            raise ValueError(f"unknown form factor '{form_factor}'")
+        self.form_factor = form_factor
+        self.calibration_hz = CARRIER_HZ
+        self.readings: List[Dict[str, Any]] = []
+        self.active = False
+
+    def initialize(self) -> "IPTSensor":
+        """Calibrate and activate the sensor."""
+        print(f"📡 IPT-SENSOR-Φ initializing — {self.FORM_FACTORS[self.form_factor]}")
+        print(f"  Calibration: {self.calibration_hz} Hz · Φ-aligned sampling")
+        self.active = True
+        return self
+
+    def read(self) -> Dict[str, Any]:
+        """One pressure field reading."""
+        rng = np.random.default_rng()
+        modalities = {
+            m: round(float(rng.random()), 4) for m in self.MODALITIES
+        }
+        pressure_index = round(float(np.mean(list(modalities.values()))), 4)
+        reading = {
+            "pressure_index": pressure_index,
+            "gradient_vector": [round(float(v), 4) for v in rng.standard_normal(5)],
+            "tipping_point_eta_days": int(rng.integers(3, 180)),
+            "resonance_signature": round(CARRIER_HZ * PHI, 2),
+            "modalities": modalities,
+            "form_factor": self.form_factor,
+            "timestamp": time.time(),
+        }
+        self.readings.append(reading)
+        return reading
+
+    def calibrate(self) -> Dict[str, Any]:
+        """Continuous self-calibration via quantum reference."""
+        return {
+            "baseline_hz": self.calibration_hz,
+            "phi_window": PHI,
+            "self_calibrated": True,
+        }
+
+    def get_state(self) -> Dict[str, Any]:
+        return {
+            "active": self.active,
+            "form_factor": self.form_factor,
+            "form_factor_desc": self.FORM_FACTORS[self.form_factor],
+            "modalities": self.MODALITIES,
+            "readings": len(self.readings),
+            "last_pressure_index": (
+                self.readings[-1]["pressure_index"] if self.readings else None
+            ),
+        }