WIP on normaliser: 2e6ad24 ad to gitignore

rfg_adc_plotter/constants.py

@@ -1,5 +1,6 @@
 WF_WIDTH = 1000  # максимальное число точек в ряду водопада
 FFT_LEN = 2048   # длина БПФ для спектра/водопада спектров
+LOG_EXP = 2.0    # основание экспоненты для опции --logscale
 # Порог для инверсии сырых данных: если среднее значение свипа ниже порога —
 # считаем, что сигнал «меньше нуля» и домножаем свип на -1
 DATA_INVERSION_THRESHOLD = 10.0

rfg_adc_plotter/gui/matplotlib_backend.py

@@ -96,6 +96,7 @@ def run_matplotlib(args):
         stop_event,
         fancy=bool(args.fancy),
         bin_mode=bool(getattr(args, "bin_mode", False)),
+        logscale=bool(getattr(args, "logscale", False)),
     )
     reader.start()
 
@@ -106,6 +107,7 @@ def run_matplotlib(args):
     spec_mean_sec = float(getattr(args, "spec_mean_sec", 0.0))
     fixed_ylim = _parse_ylim(getattr(args, "ylim", None))
     norm_type = str(getattr(args, "norm_type", "projector")).strip().lower()
+    logscale_enabled = bool(getattr(args, "logscale", False))
 
     state = AppState(norm_type=norm_type)
     ring = RingBuffer(max_sweeps)
@@ -123,6 +125,8 @@ def run_matplotlib(args):
     # График последнего свипа
     line_obj, = ax_line.plot([], [], lw=1, color="tab:blue")
     line_norm_obj, = ax_line.plot([], [], lw=1, color="tab:green")
+    line_pre_exp_obj, = ax_line.plot([], [], lw=1, color="tab:red")
+    line_post_exp_obj, = ax_line.plot([], [], lw=1, color="tab:green")
     line_env_lo, = ax_line.plot([], [], lw=1, color="tab:orange", linestyle="--", alpha=0.7)
     line_env_hi, = ax_line.plot([], [], lw=1, color="tab:orange", linestyle="--", alpha=0.7)
     ax_line.set_title("Сырые данные", pad=1)
@@ -271,10 +275,7 @@ def run_matplotlib(args):
                 xs = ring.x_shared[: raw.size]
             else:
                 xs = np.arange(raw.size, dtype=np.int32)
-            def _norm_to_max(data):
+            line_obj.set_data(xs, raw)
-                m = float(np.nanmax(np.abs(data)))
-                return data / m if m > 0.0 else data
-            line_obj.set_data(xs, _norm_to_max(raw))
             if state.calib_mode == "file" and state.calib_file_envelope is not None:
                 upper = state.calib_file_envelope
                 lower = -upper
@@ -294,14 +295,38 @@ def run_matplotlib(args):
             else:
                 line_env_lo.set_data([], [])
                 line_env_hi.set_data([], [])
+            if logscale_enabled:
+                if state.current_sweep_pre_exp is not None:
+                    pre = state.current_sweep_pre_exp
+                    line_pre_exp_obj.set_data(xs[: pre.size], pre)
+                else:
+                    line_pre_exp_obj.set_data([], [])
+
+                post = state.current_sweep_post_exp if state.current_sweep_post_exp is not None else raw
+                line_post_exp_obj.set_data(xs[: post.size], post)
+
+                if state.current_sweep_processed is not None:
+                    proc = state.current_sweep_processed
+                    line_obj.set_data(xs[: proc.size], proc)
+                else:
+                    line_obj.set_data([], [])
+                line_norm_obj.set_data([], [])
+            else:
+                line_pre_exp_obj.set_data([], [])
+                line_post_exp_obj.set_data([], [])
                 if state.current_sweep_norm is not None:
-                line_norm_obj.set_data(xs[: state.current_sweep_norm.size], _norm_to_max(state.current_sweep_norm))
+                    line_norm_obj.set_data(
+                        xs[: state.current_sweep_norm.size], state.current_sweep_norm
+                    )
                 else:
                     line_norm_obj.set_data([], [])
             ax_line.set_xlim(FREQ_MIN, FREQ_MAX)
-            if fixed_ylim is None:
+            if fixed_ylim is not None:
-                ax_line.set_ylim(-1.05, 1.05)
+                ax_line.set_ylim(fixed_ylim)
-            ax_line.set_ylabel("/ max")
+            else:
+                ax_line.relim()
+                ax_line.autoscale_view(scalex=False, scaley=True)
+            ax_line.set_ylabel("Y")
 
             # Спектр — используем уже вычисленный в ring IFFT (временной профиль)
             if ring.last_fft_vals is not None and ring.fft_time_axis is not None:
@@ -345,7 +370,19 @@ def run_matplotlib(args):
             status_text.set_text(format_status(state.current_info))
             channel_text.set_text(state.format_channel_label())
 
-        return (line_obj, line_norm_obj, line_env_lo, line_env_hi, img_obj, fft_line_obj, img_fft_obj, status_text, channel_text)
+        return (
+            line_obj,
+            line_norm_obj,
+            line_pre_exp_obj,
+            line_post_exp_obj,
+            line_env_lo,
+            line_env_hi,
+            img_obj,
+            fft_line_obj,
+            img_fft_obj,
+            status_text,
+            channel_text,
+        )
 
     ani = FuncAnimation(fig, update, interval=interval_ms, blit=False)
     plt.show()

rfg_adc_plotter/gui/pyqtgraph_backend.py

@@ -113,6 +113,7 @@ def run_pyqtgraph(args):
         stop_event,
         fancy=bool(args.fancy),
         bin_mode=bool(getattr(args, "bin_mode", False)),
+        logscale=bool(getattr(args, "logscale", False)),
     )
     reader.start()
 
@@ -123,6 +124,7 @@ def run_pyqtgraph(args):
     spec_mean_sec = float(getattr(args, "spec_mean_sec", 0.0))
     fixed_ylim = _parse_ylim(getattr(args, "ylim", None))
     norm_type = str(getattr(args, "norm_type", "projector")).strip().lower()
+    logscale_enabled = bool(getattr(args, "logscale", False))
 
     state = AppState(norm_type=norm_type)
     ring = RingBuffer(max_sweeps)
@@ -138,6 +140,8 @@ def run_pyqtgraph(args):
     p_line.showGrid(x=True, y=True, alpha=0.3)
     curve = p_line.plot(pen=pg.mkPen((80, 120, 255), width=1))
     curve_norm = p_line.plot(pen=pg.mkPen((60, 180, 90), width=1))
+    curve_pre_exp = p_line.plot(pen=pg.mkPen((220, 60, 60), width=1))
+    curve_post_exp = p_line.plot(pen=pg.mkPen((60, 180, 90), width=1))
     curve_env_lo = p_line.plot(pen=pg.mkPen((255, 165, 0), width=1, style=QtCore.Qt.DashLine))
     curve_env_hi = p_line.plot(pen=pg.mkPen((255, 165, 0), width=1, style=QtCore.Qt.DashLine))
     p_line.setLabel("bottom", "Частота, ГГц")
@@ -293,10 +297,7 @@ def run_pyqtgraph(args):
         if state.current_sweep_raw is not None and ring.x_shared is not None:
             raw = state.current_sweep_raw
             xs = ring.x_shared[: raw.size] if raw.size <= ring.x_shared.size else np.arange(raw.size)
-            def _norm_to_max(data):
+            curve.setData(xs, raw, autoDownsample=True)
-                m = float(np.nanmax(np.abs(data)))
-                return data / m if m > 0.0 else data
-            curve.setData(xs, _norm_to_max(raw), autoDownsample=True)
             if state.calib_mode == "file" and state.calib_file_envelope is not None:
                 upper = state.calib_file_envelope
                 lower = -upper
@@ -316,13 +317,38 @@ def run_pyqtgraph(args):
             else:
                 curve_env_lo.setData([], [])
                 curve_env_hi.setData([], [])
+            if logscale_enabled:
+                if state.current_sweep_pre_exp is not None:
+                    pre = state.current_sweep_pre_exp
+                    curve_pre_exp.setData(xs[: pre.size], pre, autoDownsample=True)
+                else:
+                    curve_pre_exp.setData([], [])
+
+                post = state.current_sweep_post_exp if state.current_sweep_post_exp is not None else raw
+                curve_post_exp.setData(xs[: post.size], post, autoDownsample=True)
+
+                if state.current_sweep_processed is not None:
+                    proc = state.current_sweep_processed
+                    curve.setData(xs[: proc.size], proc, autoDownsample=True)
+                else:
+                    curve.setData([], [])
+                curve_norm.setData([], [])
+            else:
+                curve_pre_exp.setData([], [])
+                curve_post_exp.setData([], [])
                 if state.current_sweep_norm is not None:
-                curve_norm.setData(xs[: state.current_sweep_norm.size], _norm_to_max(state.current_sweep_norm), autoDownsample=True)
+                    curve_norm.setData(
+                        xs[: state.current_sweep_norm.size],
+                        state.current_sweep_norm,
+                        autoDownsample=True,
+                    )
                 else:
                     curve_norm.setData([], [])
-            if fixed_ylim is None:
+            if fixed_ylim is not None:
-                p_line.setYRange(-1.05, 1.05, padding=0)
+                p_line.setYRange(fixed_ylim[0], fixed_ylim[1], padding=0)
-            p_line.setLabel("left", "/ max")
+            else:
+                p_line.enableAutoRange(axis="y", enable=True)
+            p_line.setLabel("left", "Y")
 
             # Спектр — используем уже вычисленный в ring IFFT (временной профиль)
             if ring.last_fft_vals is not None and ring.fft_time_axis is not None:

rfg_adc_plotter/io/sweep_reader.py

@@ -9,7 +9,7 @@ from typing import Optional
 
 import numpy as np
 
-from rfg_adc_plotter.constants import DATA_INVERSION_THRESHOLD
+from rfg_adc_plotter.constants import DATA_INVERSION_THRESHOLD, LOG_EXP
 from rfg_adc_plotter.io.serial_source import SerialChunkReader, SerialLineSource
 from rfg_adc_plotter.types import SweepInfo, SweepPacket
 
@@ -25,6 +25,7 @@ class SweepReader(threading.Thread):
         stop_event: threading.Event,
         fancy: bool = False,
         bin_mode: bool = False,
+        logscale: bool = False,
     ):
         super().__init__(daemon=True)
         self._port_path = port_path
@@ -34,6 +35,7 @@ class SweepReader(threading.Thread):
         self._src: Optional[SerialLineSource] = None
         self._fancy = bool(fancy)
         self._bin_mode = bool(bin_mode)
+        self._logscale = bool(logscale)
         self._max_width: int = 0
         self._sweep_idx: int = 0
         self._last_sweep_ts: Optional[float] = None
@@ -92,6 +94,16 @@ class SweepReader(threading.Thread):
         except Exception:
             pass
 
+        pre_exp_sweep = None
+        if self._logscale:
+            try:
+                pre_exp_sweep = sweep.copy()
+                with np.errstate(over="ignore", invalid="ignore"):
+                    sweep = np.power(LOG_EXP, np.asarray(sweep, dtype=np.float64)).astype(np.float32)
+                sweep[~np.isfinite(sweep)] = np.nan
+            except Exception:
+                pass
+
         self._sweep_idx += 1
         if len(ch_list) > 1:
             sys.stderr.write(
@@ -129,6 +141,8 @@ class SweepReader(threading.Thread):
             "std": std,
             "dt_ms": dt_ms,
         }
+        if pre_exp_sweep is not None:
+            info["pre_exp_sweep"] = pre_exp_sweep
 
         try:
             self._q.put_nowait((sweep, info))

rfg_adc_plotter/main.py

@@ -86,6 +86,11 @@ def build_parser() -> argparse.ArgumentParser:
             "точки step,uint32(hi16,lo16),0x000A"
         ),
     )
+    parser.add_argument(
+        "--logscale",
+        action="store_true",
+        help="После поправки знака применять экспоненту LOG_EXP**x (LOG_EXP=2)",
+    )
     return parser
 
 

rfg_adc_plotter/state/app_state.py

@@ -34,7 +34,7 @@ def format_status(data: Mapping[str, Any]) -> str:
             return f"{fv:.3g}"
         return f"{fv:.3f}".rstrip("0").rstrip(".")
 
-    parts = [f"{k}:{_fmt(v)}" for k, v in data.items()]
+    parts = [f"{k}:{_fmt(v)}" for k, v in data.items() if k != "pre_exp_sweep"]
     return "  ".join(parts)
 
 
@@ -46,6 +46,9 @@ class AppState:
     """
 
     def __init__(self, norm_type: str = "projector"):
+        self.current_sweep_pre_exp: Optional[np.ndarray] = None
+        self.current_sweep_post_exp: Optional[np.ndarray] = None
+        self.current_sweep_processed: Optional[np.ndarray] = None
         self.current_sweep_raw: Optional[np.ndarray] = None
         self.current_sweep_norm: Optional[np.ndarray] = None
         self.last_calib_sweep: Optional[np.ndarray] = None
@@ -154,6 +157,9 @@ class AppState:
                 self.current_sweep_norm = None
         else:
             self.current_sweep_norm = None
+        self.current_sweep_processed = (
+            self.current_sweep_norm if self.current_sweep_norm is not None else self.current_sweep_raw
+        )
 
     def drain_queue(self, q: "Queue[SweepPacket]", ring: RingBuffer) -> int:
         """Вытащить все ожидающие свипы из очереди, обновить state и ring.
@@ -168,7 +174,10 @@ class AppState:
                 break
             drained += 1
             self.current_sweep_raw = s
+            self.current_sweep_post_exp = s
             self.current_info = info
+            pre_exp = info.get("pre_exp_sweep") if isinstance(info, dict) else None
+            self.current_sweep_pre_exp = pre_exp if isinstance(pre_exp, np.ndarray) else None
 
             ch = 0
             try:
@@ -204,6 +213,7 @@ class AppState:
                 self.current_sweep_norm = sweep_for_ring
 
             self._last_sweep_for_ring = sweep_for_ring
+            self.current_sweep_processed = sweep_for_ring
             ring.ensure_init(s.size)
             ring.push(sweep_for_ring)
         return drained