new background remove algoritm

rfg_adc_plotter/processing/__init__.py

@@ -1,5 +1,11 @@
 """Pure sweep-processing helpers."""
 
+from rfg_adc_plotter.processing.background import (
+    load_fft_background,
+    save_fft_background,
+    subtract_fft_background,
+    validate_fft_background,
+)
 from rfg_adc_plotter.processing.calibration import (
     build_calib_envelope,
     calibrate_freqs,
@@ -47,11 +53,15 @@ __all__ = [
     "get_calibration_base",
     "get_calibration_coeffs",
     "load_calib_envelope",
+    "load_fft_background",
     "normalize_by_envelope",
     "normalize_by_calib",
     "parse_spec_clip",
     "recalculate_calibration_c",
     "rolling_median_ref",
     "save_calib_envelope",
+    "save_fft_background",
     "set_calibration_base_value",
+    "subtract_fft_background",
+    "validate_fft_background",
 ]

rfg_adc_plotter/processing/background.py

@@ -0,0 +1,66 @@
+"""Helpers for persisted FFT background profiles."""
+
+from __future__ import annotations
+
+from pathlib import Path
+
+import numpy as np
+
+
+def validate_fft_background(background: np.ndarray) -> np.ndarray:
+    """Validate a saved FFT background payload."""
+    values = np.asarray(background)
+    if values.ndim != 1:
+        raise ValueError("FFT background must be a 1D array")
+    if not np.issubdtype(values.dtype, np.number):
+        raise ValueError("FFT background must be numeric")
+    values = np.asarray(values, dtype=np.float32).reshape(-1)
+    if values.size == 0:
+        raise ValueError("FFT background is empty")
+    return values
+
+
+def _normalize_background_path(path: str | Path) -> Path:
+    out = Path(path).expanduser()
+    if out.suffix.lower() != ".npy":
+        out = out.with_suffix(".npy")
+    return out
+
+
+def save_fft_background(path: str | Path, background: np.ndarray) -> str:
+    """Persist an FFT background profile as a .npy file."""
+    normalized_path = _normalize_background_path(path)
+    values = validate_fft_background(background)
+    np.save(normalized_path, values.astype(np.float32, copy=False))
+    return str(normalized_path)
+
+
+def load_fft_background(path: str | Path) -> np.ndarray:
+    """Load and validate an FFT background profile from a .npy file."""
+    normalized_path = _normalize_background_path(path)
+    loaded = np.load(normalized_path, allow_pickle=False)
+    return validate_fft_background(loaded)
+
+
+def subtract_fft_background(signal_mag: np.ndarray, background_mag: np.ndarray) -> np.ndarray:
+    """Subtract a background profile from FFT magnitudes in linear amplitude."""
+    signal = np.asarray(signal_mag, dtype=np.float32)
+    background = validate_fft_background(background_mag)
+    if signal.ndim == 1:
+        if signal.size != background.size:
+            raise ValueError("FFT background size does not match signal size")
+        valid = np.isfinite(signal) & np.isfinite(background)
+        out = np.full_like(signal, np.nan, dtype=np.float32)
+        if np.any(valid):
+            out[valid] = np.maximum(signal[valid] - background[valid], 0.0)
+        return out
+
+    if signal.ndim == 2:
+        if signal.shape[0] != background.size:
+            raise ValueError("FFT background size does not match signal rows")
+        background_2d = background[:, None]
+        valid = np.isfinite(signal) & np.isfinite(background_2d)
+        diff = signal - background_2d
+        return np.where(valid, np.maximum(diff, 0.0), np.nan).astype(np.float32, copy=False)
+
+    raise ValueError("FFT background subtraction supports only 1D or 2D signals")