Upload eda_translator.py

quread/eda_translator.py

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+from __future__ import annotations
+
+from dataclasses import dataclass
+from typing import Dict, List, Any
+
+import numpy as np
+
+
+@dataclass
+class EDATranslatorConfig:
+    warning_threshold: float = 0.45
+    critical_threshold: float = 0.70
+    max_timing_derate: float = 1.15
+    base_guardband_mv: float = 5.0
+    max_guardband_mv: float = 60.0
+
+
+def _clip01(v: float) -> float:
+    return float(np.clip(float(v), 0.0, 1.0))
+
+
+def _tier(risk: float, cfg: EDATranslatorConfig) -> str:
+    if risk >= float(cfg.critical_threshold):
+        return "CRITICAL"
+    if risk >= float(cfg.warning_threshold):
+        return "WARNING"
+    return "OK"
+
+
+def build_eda_mapping(
+    metrics: Dict[str, np.ndarray],
+    *,
+    cfg: EDATranslatorConfig | None = None,
+) -> List[Dict[str, Any]]:
+    cfg = cfg or EDATranslatorConfig()
+    required = [
+        "composite_risk",
+        "gate_error",
+        "readout_error",
+        "decoherence_risk",
+        "fidelity",
+    ]
+    for key in required:
+        if key not in metrics:
+            raise ValueError(f"Missing required metric: {key}")
+
+    n = int(len(metrics["composite_risk"]))
+    rows: List[Dict[str, Any]] = []
+    for q in range(n):
+        risk = _clip01(float(metrics["composite_risk"][q]))
+        gate_error = _clip01(float(metrics["gate_error"][q]))
+        readout_error = _clip01(float(metrics["readout_error"][q]))
+        decoherence_risk = _clip01(float(metrics["decoherence_risk"][q]))
+        fidelity = _clip01(float(metrics["fidelity"][q]))
+
+        tier = _tier(risk, cfg)
+        timing_derate = 1.0 + risk * (float(cfg.max_timing_derate) - 1.0)
+        guardband_mv = float(cfg.base_guardband_mv) + risk * (
+            float(cfg.max_guardband_mv) - float(cfg.base_guardband_mv)
+        )
+        route_priority = "HIGH" if tier == "CRITICAL" else ("MEDIUM" if tier == "WARNING" else "LOW")
+
+        rows.append(
+            {
+                "qubit": q,
+                "tier": tier,
+                "composite_risk": risk,
+                "gate_error": gate_error,
+                "readout_error": readout_error,
+                "decoherence_risk": decoherence_risk,
+                "fidelity": fidelity,
+                "timing_derate": float(timing_derate),
+                "guardband_mv": float(guardband_mv),
+                "route_priority": route_priority,
+            }
+        )
+
+    rows.sort(key=lambda r: r["composite_risk"], reverse=True)
+    return rows
+
+
+def to_synopsys_tcl(mapping_rows: List[Dict[str, Any]]) -> str:
+    out = []
+    out.append("# ------------------------------------------------------------")
+    out.append("# Generated by Quread: Quantum reliability -> Synopsys TCL")
+    out.append("# Placeholder variable names; adapt to your flow objects.")
+    out.append("# ------------------------------------------------------------")
+    out.append("")
+    out.append("set quread_risk_rows {}")
+    out.append("")
+
+    for row in mapping_rows:
+        q = int(row["qubit"])
+        tier = row["tier"]
+        risk = float(row["composite_risk"])
+        derate = float(row["timing_derate"])
+        gb = float(row["guardband_mv"])
+        route = row["route_priority"]
+        out.append(f"# q{q}: tier={tier} risk={risk:.4f} route={route}")
+        out.append(f"set quread_q{q}_risk {risk:.6f}")
+        out.append(f"set quread_q{q}_tier {tier}")
+        out.append(f"set quread_q{q}_timing_derate {derate:.6f}")
+        out.append(f"set quread_q{q}_guardband_mv {gb:.3f}")
+        out.append(
+            f"lappend quread_risk_rows [list q{q} $quread_q{q}_risk $quread_q{q}_tier $quread_q{q}_timing_derate $quread_q{q}_guardband_mv {route}]"
+        )
+        out.append("")
+
+    out.append("# Example integration hook:")
+    out.append("# foreach row $quread_risk_rows {")
+    out.append("#   lassign $row q risk tier derate guardband route")
+    out.append("#   # apply derate/guardband to path groups or physical regions")
+    out.append("# }")
+    out.append("")
+    return "\n".join(out) + "\n"
+
+
+def to_cadence_skill_reliability(mapping_rows: List[Dict[str, Any]]) -> str:
+    out = []
+    out.append("; ------------------------------------------------------------")
+    out.append("; Generated by Quread: Quantum reliability -> Cadence SKILL")
+    out.append("; Placeholder object bindings; map to your layout DB conventions.")
+    out.append("; ------------------------------------------------------------")
+    out.append("")
+    out.append("qureadRiskRows = nil")
+    out.append("")
+
+    for row in mapping_rows:
+        q = int(row["qubit"])
+        tier = row["tier"]
+        risk = float(row["composite_risk"])
+        derate = float(row["timing_derate"])
+        gb = float(row["guardband_mv"])
+        route = row["route_priority"]
+        out.append(
+            f'qureadRiskRows = cons(list("q{q}" {risk:.6f} "{tier}" {derate:.6f} {gb:.3f} "{route}") qureadRiskRows)'
+        )
+
+    out.append("")
+    out.append("qureadRiskRows = reverse(qureadRiskRows)")
+    out.append("")
+    out.append("; Example integration hook:")
+    out.append("; foreach(row qureadRiskRows")
+    out.append(';   printf("Qubit=%s risk=%L tier=%s derate=%L guardband(mV)=%L route=%s\\n"')
+    out.append(";          car(row) cadr(row) caddr(row) cadddr(row) car(cddddr(row)) cadr(cddddr(row)))")
+    out.append("; )")
+    out.append("")
+    return "\n".join(out) + "\n"