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rfg_adc_plotter/processing/calibration.py

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+"""Frequency-axis calibration helpers."""
+
+from __future__ import annotations
+
+from typing import Any, Mapping
+
+import numpy as np
+
+from rfg_adc_plotter.constants import SWEEP_FREQ_MAX_GHZ, SWEEP_FREQ_MIN_GHZ
+from rfg_adc_plotter.types import SweepData
+
+
+def recalculate_calibration_c(
+    base_coeffs: np.ndarray,
+    f_min: float = SWEEP_FREQ_MIN_GHZ,
+    f_max: float = SWEEP_FREQ_MAX_GHZ,
+) -> np.ndarray:
+    """Recalculate coefficients while preserving sweep edges."""
+    coeffs = np.asarray(base_coeffs, dtype=np.float64).reshape(-1)
+    if coeffs.size < 3:
+        out = np.zeros((3,), dtype=np.float64)
+        out[: coeffs.size] = coeffs
+        coeffs = out
+    c0, c1, c2 = float(coeffs[0]), float(coeffs[1]), float(coeffs[2])
+    x0 = float(f_min)
+    x1 = float(f_max)
+    y0 = c0 + c1 * x0 + c2 * (x0 ** 2)
+    y1 = c0 + c1 * x1 + c2 * (x1 ** 2)
+    if not (np.isfinite(y0) and np.isfinite(y1)) or y1 == y0:
+        return np.asarray([c0, c1, c2], dtype=np.float64)
+    scale = (x1 - x0) / (y1 - y0)
+    shift = x0 - scale * y0
+    return np.asarray(
+        [
+            shift + scale * c0,
+            scale * c1,
+            scale * c2,
+        ],
+        dtype=np.float64,
+    )
+
+
+CALIBRATION_C_BASE = np.asarray([0.0, 1.0, 0.025], dtype=np.float64)
+CALIBRATION_C = recalculate_calibration_c(CALIBRATION_C_BASE)
+
+
+def get_calibration_base() -> np.ndarray:
+    return np.asarray(CALIBRATION_C_BASE, dtype=np.float64).copy()
+
+
+def get_calibration_coeffs() -> np.ndarray:
+    return np.asarray(CALIBRATION_C, dtype=np.float64).copy()
+
+
+def set_calibration_base_value(index: int, value: float) -> np.ndarray:
+    """Update one base coefficient and recalculate the working coefficients."""
+    global CALIBRATION_C
+    CALIBRATION_C_BASE[int(index)] = float(value)
+    CALIBRATION_C = recalculate_calibration_c(CALIBRATION_C_BASE)
+    return get_calibration_coeffs()
+
+
+def calibrate_freqs(sweep: Mapping[str, Any]) -> SweepData:
+    """Return a sweep copy with calibrated and resampled frequency axis."""
+    freqs = np.asarray(sweep["F"], dtype=np.float64).copy()
+    values = np.asarray(sweep["I"], dtype=np.float64).copy()
+    coeffs = np.asarray(CALIBRATION_C, dtype=np.float64)
+    if freqs.size > 0:
+        freqs = coeffs[0] + coeffs[1] * freqs + coeffs[2] * (freqs * freqs)
+
+    if freqs.size >= 2:
+        freqs_cal = np.linspace(float(freqs[0]), float(freqs[-1]), freqs.size, dtype=np.float64)
+        values_cal = np.interp(freqs_cal, freqs, values).astype(np.float64)
+    else:
+        freqs_cal = freqs.copy()
+        values_cal = values.copy()
+
+    return {
+        "F": freqs_cal,
+        "I": values_cal,
+    }