Upload app.py

app.py

@@ -32,6 +32,7 @@ from quread.metrics import (
     MetricThresholds,
 )
 from quread.layout_mapper import parse_layout_csv_text
+from quread.trends import compute_metric_trends
 
 # --- Qubit cap (configurable) ---
 DEFAULT_MAX_QUBITS = 16  # safe default for CPU Spaces; change if you want
@@ -448,6 +449,55 @@ def _ideal_vs_noisy_plot(
     return fig
 
 
+def _metric_label(metric_key: str) -> str:
+    labels = {
+        "composite_risk": "Composite risk",
+        "gate_error": "Gate error",
+        "readout_error": "Readout error",
+        "decoherence_risk": "Decoherence risk",
+        "fidelity": "Fidelity",
+        "state_fidelity": "State fidelity",
+        "process_fidelity": "Process fidelity",
+        "coherence_health": "Coherence health",
+    }
+    return labels.get(metric_key, metric_key.replace("_", " ").title())
+
+
+def _plot_metric_trends(series, labels, ranking_rows, metric_key, top_k):
+    if series.size == 0:
+        fig, ax = plt.subplots(figsize=(7, 3))
+        ax.set_title("No trend data")
+        ax.axis("off")
+        fig.tight_layout()
+        return fig
+
+    k = max(1, min(int(top_k), len(ranking_rows)))
+    selected_qubits = [int(ranking_rows[i]["qubit"]) for i in range(k)]
+    x = np.arange(series.shape[0])
+    fig, ax = plt.subplots(figsize=(8, 4))
+    for q in selected_qubits:
+        ax.plot(x, series[:, q], marker="o", linewidth=2, label=f"q{q}")
+
+    xticks = labels
+    if len(xticks) > 12:
+        step = max(1, len(xticks) // 10)
+        keep = [idx for idx in range(len(xticks)) if idx % step == 0 or idx == len(xticks) - 1]
+        ax.set_xticks(keep)
+        ax.set_xticklabels([xticks[i] for i in keep], rotation=35, ha="right")
+    else:
+        ax.set_xticks(x)
+        ax.set_xticklabels(xticks, rotation=35, ha="right")
+
+    ax.set_ylim(0.0, 1.0)
+    ax.set_ylabel(_metric_label(metric_key))
+    ax.set_xlabel("Snapshot")
+    ax.set_title(f"Temporal drift: top {k} qubits by latest {_metric_label(metric_key).lower()}")
+    ax.grid(alpha=0.2, linestyle="--")
+    ax.legend(ncols=2, fontsize=8)
+    fig.tight_layout()
+    return fig
+
+
 # ---------- Styling ----------
 CSS = """
 #title h1 { font-size: 38px !important; margin-bottom: 4px; letter-spacing: -0.02em; }
@@ -686,6 +736,45 @@ with gr.Blocks(theme=theme, css=CSS, title="Quread.ai — State Vector Studio")
                                 hotspot_detail_md = gr.Markdown()
                                 hotspot_detail_plot = gr.Plot()
 
+                    with gr.Group(elem_classes=["card"]):
+                        gr.Markdown("<div class='section-title'>Temporal Drift (Calibration Snapshots)</div>")
+                        with gr.Row():
+                            trend_metric = gr.Dropdown(
+                                choices=[
+                                    "composite_risk",
+                                    "gate_error",
+                                    "readout_error",
+                                    "decoherence_risk",
+                                    "fidelity",
+                                    "state_fidelity",
+                                    "process_fidelity",
+                                    "coherence_health",
+                                ],
+                                value="composite_risk",
+                                label="Trend metric",
+                            )
+                            trend_top_k = gr.Slider(1, 32, value=8, step=1, label="Trend lines (top qubits)")
+                            trend_btn = gr.Button("Analyze drift", variant="secondary")
+                        with gr.Accordion("Snapshot Input", open=False):
+                            trend_snapshots_file = gr.File(
+                                label="Snapshots file (.json/.jsonl/.txt)",
+                                file_types=[".json", ".jsonl", ".txt"],
+                                type="filepath",
+                            )
+                            trend_snapshots_text = gr.Textbox(
+                                lines=8,
+                                label="Snapshots JSON/JSONL (optional)",
+                                placeholder='[{"timestamp":"2026-02-12","qubits":{"0":{"gate_error":0.012,"readout_error":0.02,"t1_us":82,"t2_us":61,"fidelity":0.991}}}]',
+                            )
+                            gr.Markdown("<div class='small-note'>If both are provided, file input is used.</div>")
+                        trend_status = gr.Markdown("Upload snapshots and click Analyze drift.")
+                        trend_plot = gr.Plot()
+                        trend_table = gr.Dataframe(
+                            headers=["qubit", "latest", "baseline", "delta"],
+                            interactive=False,
+                            label="Latest ranking (highest selected metric first)",
+                        )
+
                 with gr.Tab("Explain"):
                     with gr.Group(elem_classes=["card"]):
                         gr.Markdown("<div class='section-title'>Explain (GPT-4o)</div>")
@@ -1079,6 +1168,88 @@ with gr.Blocks(theme=theme, css=CSS, title="Quread.ai — State Vector Studio")
         )
         return _write_tmp("qubit_metrics.csv", to_metrics_csv(metrics))
 
+    def _trend_from_snapshots(
+        qc,
+        n_qubits,
+        snapshots_file,
+        snapshots_text,
+        trend_metric_value,
+        trend_top_qubits,
+        activity_w,
+        gate_error_w,
+        readout_error_w,
+        decoherence_w,
+        fidelity_w,
+        warning_thr,
+        critical_thr,
+    ):
+        text = _read_uploaded_text(snapshots_file).strip()
+        if not text:
+            text = str(snapshots_text or "").strip()
+
+        if not text:
+            fig, ax = plt.subplots(figsize=(7, 3))
+            ax.set_title("Temporal drift")
+            ax.text(0.5, 0.5, "Provide calibration snapshots (JSON/JSONL).", ha="center", va="center")
+            ax.axis("off")
+            fig.tight_layout()
+            return fig, "No snapshots provided.", []
+
+        csv_text = to_csv(qc.history)
+        weights, thresholds = _metric_controls_to_models(
+            activity_w,
+            gate_error_w,
+            readout_error_w,
+            decoherence_w,
+            fidelity_w,
+            warning_thr,
+            critical_thr,
+        )
+
+        try:
+            series, labels, ranking, meta = compute_metric_trends(
+                csv_text,
+                int(n_qubits),
+                text,
+                metric=str(trend_metric_value),
+                state_vector=np.asarray(qc.state, dtype=complex),
+                weights=weights,
+                thresholds=thresholds,
+            )
+        except Exception as exc:
+            fig, ax = plt.subplots(figsize=(7, 3))
+            ax.set_title("Temporal drift")
+            ax.text(0.5, 0.5, f"Unable to parse snapshots: {exc}", ha="center", va="center")
+            ax.axis("off")
+            fig.tight_layout()
+            return fig, f"Drift analysis failed: {exc}", []
+
+        fig = _plot_metric_trends(
+            series,
+            labels,
+            ranking,
+            str(meta.get("metric", trend_metric_value)),
+            int(trend_top_qubits),
+        )
+        table_rows = []
+        for row in ranking:
+            table_rows.append(
+                [
+                    int(row["qubit"]),
+                    round(float(row["latest"]), 6),
+                    round(float(row["baseline"]), 6),
+                    round(float(row["delta"]), 6),
+                ]
+            )
+        status = (
+            f"Snapshots parsed: {int(meta.get('parsed', 0))}"
+            f" | Skipped: {int(meta.get('skipped', 0))}"
+            f" | Format: {meta.get('format', 'unknown')}"
+            f" | Points: {int(meta.get('points', 0))}"
+            f" | Metric: {meta.get('metric', trend_metric_value)}"
+        )
+        return fig, status, table_rows
+
     heat_btn.click(
         fn=_heat_and_hotspots_from_current,
         inputs=[
@@ -1121,6 +1292,26 @@ with gr.Blocks(theme=theme, css=CSS, title="Quread.ai — State Vector Studio")
         outputs=[metrics_csv_dl],
     )
 
+    trend_btn.click(
+        fn=_trend_from_snapshots,
+        inputs=[
+            qc_state,
+            n_qubits,
+            trend_snapshots_file,
+            trend_snapshots_text,
+            trend_metric,
+            trend_top_k,
+            w_activity,
+            w_gate,
+            w_readout,
+            w_decoherence,
+            w_fidelity,
+            thr_warning,
+            thr_critical,
+        ],
+        outputs=[trend_plot, trend_status, trend_table],
+    )
+
     synopsys_tcl_dl.click(
         fn=_dl_synopsys_tcl,
         inputs=[