done

rfg_adc_plotter/gui/matplotlib_backend.py

@@ -12,7 +12,7 @@ from rfg_adc_plotter.constants import FFT_LEN, FREQ_SPAN_GHZ, IFFT_LEN
 _IFFT_T_MAX_NS = float((IFFT_LEN - 1) / (FREQ_SPAN_GHZ * 1e9) * 1e9)
 from rfg_adc_plotter.io.sweep_reader import SweepReader
 from rfg_adc_plotter.processing.normalizer import build_calib_envelopes
-from rfg_adc_plotter.state.app_state import BACKGROUND_PATH, CALIB_ENVELOPE_PATH, AppState, format_status
+from rfg_adc_plotter.state.app_state import AppState, format_status
 from rfg_adc_plotter.state.ring_buffer import RingBuffer
 from rfg_adc_plotter.types import SweepPacket
 
@@ -82,7 +82,8 @@ def run_matplotlib(args):
         import matplotlib
         import matplotlib.pyplot as plt
         from matplotlib.animation import FuncAnimation
-        from matplotlib.widgets import CheckButtons, Slider
+        from matplotlib.widgets import Button as MplButton
+        from matplotlib.widgets import CheckButtons, RadioButtons, Slider, TextBox
     except Exception as e:
         sys.stderr.write(f"[error] Нужны matplotlib и её зависимости: {e}\n")
         sys.exit(1)
@@ -111,6 +112,7 @@ def run_matplotlib(args):
     logscale_enabled = bool(getattr(args, "logscale", False))
 
     state = AppState(norm_type=norm_type)
+    state.configure_capture_import(fancy=bool(args.fancy), logscale=bool(getattr(args, "logscale", False)))
     ring = RingBuffer(max_sweeps)
 
     # --- Создание фигуры ---
@@ -118,10 +120,12 @@ def run_matplotlib(args):
     (ax_line, ax_img), (ax_fft, ax_spec) = axs
     if hasattr(fig.canvas.manager, "set_window_title"):
         fig.canvas.manager.set_window_title(args.title)
-    fig.subplots_adjust(wspace=0.25, hspace=0.35, left=0.07, right=0.90, top=0.92, bottom=0.08)
+    fig.subplots_adjust(wspace=0.25, hspace=0.35, left=0.07, right=0.90, top=0.92, bottom=0.22)
 
     # Статусная строка
     status_text = fig.text(0.01, 0.01, "", ha="left", va="bottom", fontsize=8, family="monospace")
+    pipeline_text = fig.text(0.01, 0.03, "", ha="left", va="bottom", fontsize=8, family="monospace")
+    ref_text = fig.text(0.01, 0.05, "", ha="left", va="bottom", fontsize=8, family="monospace")
 
     # График последнего свипа
     line_obj, = ax_line.plot([], [], lw=1, color="tab:blue")
@@ -178,15 +182,144 @@ def run_matplotlib(args):
         ax_sctr = fig.add_axes([0.98, 0.55, 0.02, 0.35])
         ax_cb = fig.add_axes([0.92, 0.45, 0.08, 0.08])
         ax_cb_file = fig.add_axes([0.92, 0.36, 0.08, 0.08])
+        ax_line_mode = fig.add_axes([0.92, 0.10, 0.08, 0.08])
         ymin_slider = Slider(ax_smin, "Y min", 0, max(1, fft_bins - 1), valinit=0, valstep=1, orientation="vertical")
         ymax_slider = Slider(ax_smax, "Y max", 0, max(1, fft_bins - 1), valinit=max(1, fft_bins - 1), valstep=1, orientation="vertical")
         contrast_slider = Slider(ax_sctr, "Int max", 0, 100, valinit=100, valstep=1, orientation="vertical")
         calib_cb = CheckButtons(ax_cb, ["калибровка"], [False])
         calib_file_cb = CheckButtons(ax_cb_file, ["из файла"], [False])
+        line_mode_rb = RadioButtons(ax_line_mode, ("raw", "processed"), active=0)
+        try:
+            ax_line_mode.set_title("Линия", fontsize=8, pad=2)
+        except Exception:
+            pass
+        line_mode_state = {"value": "raw"}
 
         import os as _os
-        if not _os.path.isfile(CALIB_ENVELOPE_PATH):
+        try:
-            ax_cb_file.set_visible(False)
+            import tkinter as _tk
+            from tkinter import filedialog as _tk_filedialog
+            _tk_available = True
+        except Exception:
+            _tk = None
+            _tk_filedialog = None
+            _tk_available = False
+
+        # Нижняя панель путей и кнопок (работает без Qt; выбор файла через tkinter опционален).
+        ax_calib_path = fig.add_axes([0.07, 0.14, 0.40, 0.04])
+        ax_calib_load = fig.add_axes([0.48, 0.14, 0.07, 0.04])
+        ax_calib_pick = fig.add_axes([0.56, 0.14, 0.06, 0.04])
+        ax_calib_sample = fig.add_axes([0.63, 0.14, 0.09, 0.04])
+        ax_calib_save = fig.add_axes([0.73, 0.14, 0.10, 0.04])
+
+        ax_bg_path = fig.add_axes([0.07, 0.09, 0.40, 0.04])
+        ax_bg_load = fig.add_axes([0.48, 0.09, 0.07, 0.04])
+        ax_bg_pick = fig.add_axes([0.56, 0.09, 0.06, 0.04])
+        ax_bg_sample = fig.add_axes([0.63, 0.09, 0.09, 0.04])
+        ax_bg_save2 = fig.add_axes([0.73, 0.09, 0.10, 0.04])
+
+        calib_path_box = TextBox(ax_calib_path, "Калибр", initial=state.calib_envelope_path)
+        bg_path_box = TextBox(ax_bg_path, "Фон", initial=state.background_path)
+
+        calib_load_btn2 = MplButton(ax_calib_load, "Загруз.")
+        calib_pick_btn2 = MplButton(ax_calib_pick, "Файл")
+        calib_sample_btn2 = MplButton(ax_calib_sample, "sample")
+        calib_save_btn2 = MplButton(ax_calib_save, "Сохр env")
+
+        bg_load_btn2 = MplButton(ax_bg_load, "Загруз.")
+        bg_pick_btn2 = MplButton(ax_bg_pick, "Файл")
+        bg_sample_btn2 = MplButton(ax_bg_sample, "sample")
+        bg_save_btn2 = MplButton(ax_bg_save2, "Сохр фон")
+
+        if not _tk_available:
+            try:
+                calib_pick_btn2.label.set_text("Файл-")
+                bg_pick_btn2.label.set_text("Файл-")
+            except Exception:
+                pass
+
+        def _tb_text(tb):
+            try:
+                return str(tb.text).strip()
+            except Exception:
+                return ""
+
+        def _pick_file_dialog(initial_path: str) -> str:
+            if not _tk_available or _tk is None or _tk_filedialog is None:
+                return ""
+            root = None
+            try:
+                root = _tk.Tk()
+                root.withdraw()
+                root.attributes("-topmost", True)
+            except Exception:
+                root = None
+            try:
+                return str(
+                    _tk_filedialog.askopenfilename(
+                        initialdir=_os.path.dirname(initial_path) or ".",
+                        initialfile=_os.path.basename(initial_path) or "",
+                        title="Выбрать файл эталона (.npy или capture)",
+                    )
+                )
+            finally:
+                try:
+                    if root is not None:
+                        root.destroy()
+                except Exception:
+                    pass
+
+        def _sync_path_boxes():
+            try:
+                if _tb_text(calib_path_box) != state.calib_envelope_path:
+                    calib_path_box.set_val(state.calib_envelope_path)
+            except Exception:
+                pass
+            try:
+                if _tb_text(bg_path_box) != state.background_path:
+                    bg_path_box.set_val(state.background_path)
+            except Exception:
+                pass
+
+        def _refresh_status_texts():
+            pipeline_text.set_text(state.format_pipeline_status())
+            ref_text.set_text(state.format_reference_status())
+            try:
+                fig.canvas.draw_idle()
+            except Exception:
+                pass
+
+        def _line_mode() -> str:
+            return str(line_mode_state.get("value", "raw"))
+
+        def _refresh_checkboxes():
+            try:
+                # file-mode чекбокс показываем всегда; он активен при наличии пути/данных.
+                ax_cb_file.set_visible(True)
+            except Exception:
+                pass
+
+        def _load_calib_from_ui():
+            p = _tb_text(calib_path_box)
+            if p:
+                state.set_calib_envelope_path(p)
+            ok = state.load_calib_reference()
+            if ok and bool(calib_file_cb.get_status()[0]):
+                state.set_calib_mode("file")
+                state.set_calib_enabled(bool(calib_cb.get_status()[0]))
+            _sync_path_boxes()
+            _refresh_checkboxes()
+            _refresh_status_texts()
+            return ok
+
+        def _load_bg_from_ui():
+            p = _tb_text(bg_path_box)
+            if p:
+                state.set_background_path(p)
+            ok = state.load_background_reference()
+            _sync_path_boxes()
+            _refresh_status_texts()
+            return ok
 
         def _on_ylim_change(_val):
             try:
@@ -200,7 +333,7 @@ def run_matplotlib(args):
         def _on_calib_file_clicked(_v):
             use_file = bool(calib_file_cb.get_status()[0])
             if use_file:
-                ok = state.load_calib_envelope(CALIB_ENVELOPE_PATH)
+                ok = _load_calib_from_ui()
                 if ok:
                     state.set_calib_mode("file")
                 else:
@@ -208,17 +341,15 @@ def run_matplotlib(args):
             else:
                 state.set_calib_mode("live")
             state.set_calib_enabled(bool(calib_cb.get_status()[0]))
+            _refresh_status_texts()
 
         def _on_calib_clicked(_v):
-            import os as _os2
-            if _os2.path.isfile(CALIB_ENVELOPE_PATH):
-                ax_cb_file.set_visible(True)
             state.set_calib_enabled(bool(calib_cb.get_status()[0]))
-            fig.canvas.draw_idle()
+            _refresh_checkboxes()
+            _refresh_status_texts()
 
         ax_btn_bg = fig.add_axes([0.92, 0.27, 0.08, 0.05])
         ax_cb_bg = fig.add_axes([0.92, 0.20, 0.08, 0.06])
-        from matplotlib.widgets import Button as MplButton
         save_bg_btn = MplButton(ax_btn_bg, "Сохр. фон")
         bg_cb = CheckButtons(ax_cb_bg, ["вычет фона"], [False])
 
@@ -226,21 +357,88 @@ def run_matplotlib(args):
             ok = state.save_background()
             if ok:
                 state.load_background()
-            fig.canvas.draw_idle()
+            _sync_path_boxes()
+            _refresh_status_texts()
 
         def _on_bg_clicked(_v):
             state.set_background_enabled(bool(bg_cb.get_status()[0]))
+            _refresh_status_texts()
+
+        def _on_calib_load_btn(_event):
+            _load_calib_from_ui()
+
+        def _on_calib_pick_btn(_event):
+            path = _pick_file_dialog(_tb_text(calib_path_box) or state.calib_envelope_path)
+            if not path:
+                return
+            state.set_calib_envelope_path(path)
+            _sync_path_boxes()
+            _refresh_status_texts()
+
+        def _on_calib_sample_btn(_event):
+            state.set_calib_envelope_path(_os.path.join("sample_data", "no_antennas_35dB_attenuators"))
+            _sync_path_boxes()
+            if _load_calib_from_ui() and not bool(calib_file_cb.get_status()[0]):
+                calib_file_cb.set_active(0)
+
+        def _on_calib_save_btn(_event):
+            state.save_calib_envelope()
+            _sync_path_boxes()
+            _refresh_status_texts()
+
+        def _on_bg_load_btn(_event):
+            _load_bg_from_ui()
+
+        def _on_bg_pick_btn(_event):
+            path = _pick_file_dialog(_tb_text(bg_path_box) or state.background_path)
+            if not path:
+                return
+            state.set_background_path(path)
+            _sync_path_boxes()
+            _refresh_status_texts()
+
+        def _on_bg_sample_btn(_event):
+            state.set_background_path(_os.path.join("sample_data", "empty"))
+            _sync_path_boxes()
+            _load_bg_from_ui()
+
+        def _on_bg_save_btn2(_event):
+            ok = state.save_background()
+            if ok:
+                state.load_background()
+            _sync_path_boxes()
+            _refresh_status_texts()
+
+        def _on_line_mode_clicked(label):
+            line_mode_state["value"] = str(label)
+            try:
+                fig.canvas.draw_idle()
+            except Exception:
+                pass
 
         save_bg_btn.on_clicked(_on_save_bg)
         bg_cb.on_clicked(_on_bg_clicked)
+        calib_load_btn2.on_clicked(_on_calib_load_btn)
+        calib_pick_btn2.on_clicked(_on_calib_pick_btn)
+        calib_sample_btn2.on_clicked(_on_calib_sample_btn)
+        calib_save_btn2.on_clicked(_on_calib_save_btn)
+        bg_load_btn2.on_clicked(_on_bg_load_btn)
+        bg_pick_btn2.on_clicked(_on_bg_pick_btn)
+        bg_sample_btn2.on_clicked(_on_bg_sample_btn)
+        bg_save_btn2.on_clicked(_on_bg_save_btn2)
+        line_mode_rb.on_clicked(_on_line_mode_clicked)
 
         ymin_slider.on_changed(_on_ylim_change)
         ymax_slider.on_changed(_on_ylim_change)
         contrast_slider.on_changed(lambda _v: fig.canvas.draw_idle())
         calib_cb.on_clicked(_on_calib_clicked)
         calib_file_cb.on_clicked(_on_calib_file_clicked)
+        _sync_path_boxes()
+        _refresh_checkboxes()
+        _refresh_status_texts()
     except Exception:
         calib_cb = None
+        line_mode_state = {"value": "raw"}
 
     FREQ_MIN = 3.323
     FREQ_MAX = 14.323
@@ -276,23 +474,37 @@ def run_matplotlib(args):
                 xs = ring.x_shared[: raw.size]
             else:
                 xs = np.arange(raw.size, dtype=np.int32)
-            line_obj.set_data(xs, raw)
+            line_mode = str(line_mode_state.get("value", "raw"))
+            main = state.current_sweep_processed if line_mode == "processed" else raw
+            if main is not None:
+                line_obj.set_data(xs[: main.size], main)
+            else:
+                line_obj.set_data([], [])
+            if line_mode == "raw":
                 if state.calib_mode == "file" and state.calib_file_envelope is not None:
-                upper = state.calib_file_envelope
+                    upper = np.asarray(state.calib_file_envelope, dtype=np.float32)
-                lower = -upper
+                    n_env = min(xs.size, upper.size)
-                m_env = float(np.nanmax(np.abs(upper)))
+                    if n_env > 0:
-                if m_env <= 0.0:
+                        x_env = xs[:n_env]
-                    m_env = 1.0
+                        y_env = upper[:n_env]
-                line_env_lo.set_data(xs[: upper.size], lower / m_env)
+                        line_env_lo.set_data(x_env, -y_env)
-                line_env_hi.set_data(xs[: upper.size], upper / m_env)
+                        line_env_hi.set_data(x_env, y_env)
+                    else:
+                        line_env_lo.set_data([], [])
+                        line_env_hi.set_data([], [])
                 elif state.last_calib_sweep is not None:
-                calib = state.last_calib_sweep
+                    calib = np.asarray(state.last_calib_sweep, dtype=np.float32)
-                m_calib = float(np.nanmax(np.abs(calib)))
-                if m_calib <= 0.0:
-                    m_calib = 1.0
                     lower, upper = build_calib_envelopes(calib)
-                line_env_lo.set_data(xs[: calib.size], lower / m_calib)
+                    n_env = min(xs.size, lower.size, upper.size)
-                line_env_hi.set_data(xs[: calib.size], upper / m_calib)
+                    if n_env > 0:
+                        line_env_lo.set_data(xs[:n_env], lower[:n_env])
+                        line_env_hi.set_data(xs[:n_env], upper[:n_env])
+                    else:
+                        line_env_lo.set_data([], [])
+                        line_env_hi.set_data([], [])
+                else:
+                    line_env_lo.set_data([], [])
+                    line_env_hi.set_data([], [])
             else:
                 line_env_lo.set_data([], [])
                 line_env_hi.set_data([], [])
@@ -306,16 +518,19 @@ def run_matplotlib(args):
                 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 line_mode == "processed":
                     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([], [])
+                else:
+                    line_obj.set_data(xs[: raw.size], raw)
                 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:
+                if line_mode == "raw" and state.current_sweep_norm is not None:
                     line_norm_obj.set_data(
                         xs[: state.current_sweep_norm.size], state.current_sweep_norm
                     )
@@ -370,6 +585,11 @@ def run_matplotlib(args):
         if changed and state.current_info:
             status_text.set_text(format_status(state.current_info))
             channel_text.set_text(state.format_channel_label())
+            pipeline_text.set_text(state.format_pipeline_status())
+            ref_text.set_text(state.format_reference_status())
+        elif changed:
+            pipeline_text.set_text(state.format_pipeline_status())
+            ref_text.set_text(state.format_reference_status())
 
         return (
             line_obj,
@@ -382,6 +602,8 @@ def run_matplotlib(args):
             fft_line_obj,
             img_fft_obj,
             status_text,
+            pipeline_text,
+            ref_text,
             channel_text,
         )
 

rfg_adc_plotter/gui/pyqtgraph_backend.py

@@ -1,5 +1,6 @@
 """PyQtGraph-бэкенд реалтайм-плоттера свипов."""
 
+import os
 import sys
 import threading
 from queue import Queue
@@ -10,7 +11,7 @@ import numpy as np
 from rfg_adc_plotter.constants import FREQ_SPAN_GHZ, IFFT_LEN
 from rfg_adc_plotter.io.sweep_reader import SweepReader
 from rfg_adc_plotter.processing.normalizer import build_calib_envelopes
-from rfg_adc_plotter.state.app_state import BACKGROUND_PATH, CALIB_ENVELOPE_PATH, AppState, format_status
+from rfg_adc_plotter.state.app_state import AppState, format_status
 from rfg_adc_plotter.state.ring_buffer import RingBuffer
 from rfg_adc_plotter.types import SweepPacket
 
@@ -90,6 +91,18 @@ def _visible_levels(
     return (vmin, vmax)
 
 
+def _short_path(path: str, max_len: int = 48) -> str:
+    p = str(path or "").strip()
+    if not p:
+        return "(не задан)"
+    if len(p) <= max_len:
+        return p
+    base = os.path.basename(p)
+    if len(base) <= max_len:
+        return f".../{base}"
+    return "..." + p[-(max_len - 3) :]
+
+
 def run_pyqtgraph(args):
     """Быстрый GUI на PyQtGraph. Требует pyqtgraph и PyQt5/PySide6."""
     try:
@@ -128,13 +141,22 @@ def run_pyqtgraph(args):
     logscale_enabled = bool(getattr(args, "logscale", False))
 
     state = AppState(norm_type=norm_type)
+    state.configure_capture_import(fancy=bool(args.fancy), logscale=bool(getattr(args, "logscale", False)))
     ring = RingBuffer(max_sweeps)
 
+    try:
+        _qt_text_selectable = QtCore.Qt.TextSelectableByMouse
+    except Exception:
+        try:
+            _qt_text_selectable = QtCore.Qt.TextInteractionFlag.TextSelectableByMouse
+        except Exception:
+            _qt_text_selectable = None
+
     # --- Создание окна ---
     pg.setConfigOptions(useOpenGL=True, antialias=False)
     app = pg.mkQApp(args.title)
     win = pg.GraphicsLayoutWidget(show=True, title=args.title)
-    win.resize(1200, 600)
+    win.resize(1280, 760)
 
     # График последнего свипа (слева-сверху)
     p_line = win.addPlot(row=0, col=0, title="Сырые данные")
@@ -196,32 +218,58 @@ def run_pyqtgraph(args):
     img_fft = pg.ImageItem()
     p_spec.addItem(img_fft)
 
-    # Чекбоксы калибровки — в одном контейнере
+    # Блок управления калибровкой
     calib_widget = QtWidgets.QWidget()
-    calib_layout = QtWidgets.QHBoxLayout(calib_widget)
+    calib_layout = QtWidgets.QVBoxLayout(calib_widget)
     calib_layout.setContentsMargins(2, 2, 2, 2)
-    calib_layout.setSpacing(8)
+    calib_layout.setSpacing(4)
+
+    calib_row_1 = QtWidgets.QHBoxLayout()
+    calib_row_1.setSpacing(8)
+    calib_row_2 = QtWidgets.QHBoxLayout()
+    calib_row_2.setSpacing(6)
 
     calib_cb = QtWidgets.QCheckBox("калибровка")
     calib_file_cb = QtWidgets.QCheckBox("из файла")
-    calib_file_cb.setEnabled(False)  # активируется только если файл существует
+    calib_file_cb.setEnabled(False)
+    calib_path_label = QtWidgets.QLabel()
+    calib_path_label.setMinimumWidth(260)
+    if _qt_text_selectable is not None:
+        calib_path_label.setTextInteractionFlags(_qt_text_selectable)
+    calib_pick_btn = QtWidgets.QPushButton("Файл…")
+    calib_load_btn = QtWidgets.QPushButton("Загрузить")
+    calib_save_btn = QtWidgets.QPushButton("Сохранить env")
+    calib_sample_btn = QtWidgets.QPushButton("sample calib")
 
-    calib_layout.addWidget(calib_cb)
+    calib_row_1.addWidget(calib_cb)
-    calib_layout.addWidget(calib_file_cb)
+    calib_row_1.addWidget(calib_file_cb)
+    calib_row_1.addStretch(1)
+
+    calib_row_2.addWidget(QtWidgets.QLabel("Калибр:"))
+    calib_row_2.addWidget(calib_path_label, 1)
+    calib_row_2.addWidget(calib_pick_btn)
+    calib_row_2.addWidget(calib_load_btn)
+    calib_row_2.addWidget(calib_save_btn)
+    calib_row_2.addWidget(calib_sample_btn)
+
+    calib_layout.addLayout(calib_row_1)
+    calib_layout.addLayout(calib_row_2)
 
     cb_container_proxy = QtWidgets.QGraphicsProxyWidget()
     cb_container_proxy.setWidget(calib_widget)
     win.addItem(cb_container_proxy, row=2, col=1)
 
-    def _check_file_cb_available():
+    def _refresh_calib_controls():
-        import os
+        calib_path_label.setText(_short_path(state.calib_envelope_path))
-        calib_file_cb.setEnabled(os.path.isfile(CALIB_ENVELOPE_PATH))
+        calib_path_label.setToolTip(state.calib_envelope_path)
-
+        calib_load_btn.setEnabled(bool(state.calib_envelope_path) and os.path.isfile(state.calib_envelope_path))
-    _check_file_cb_available()
+        calib_save_btn.setEnabled(state.last_calib_sweep is not None)
+        # Переключатель file-mode доступен, если файл существует или уже загружен в память.
+        calib_file_cb.setEnabled(state.has_calib_envelope_file() or state.calib_file_envelope is not None)
 
     def _on_calib_file_toggled(checked):
         if checked:
-            ok = state.load_calib_envelope(CALIB_ENVELOPE_PATH)
+            ok = state.load_calib_reference()
             if ok:
                 state.set_calib_mode("file")
             else:
@@ -229,43 +277,196 @@ def run_pyqtgraph(args):
         else:
             state.set_calib_mode("live")
         state.set_calib_enabled(calib_cb.isChecked())
+        _refresh_calib_controls()
+        _refresh_pipeline_label()
 
     def _on_calib_toggled(_v):
-        _check_file_cb_available()
         state.set_calib_enabled(calib_cb.isChecked())
+        _refresh_calib_controls()
+        _refresh_pipeline_label()
+
+    def _on_pick_calib_path():
+        path, _ = QtWidgets.QFileDialog.getOpenFileName(
+            win,
+            "Выбрать источник калибровки (.npy или capture)",
+            state.calib_envelope_path,
+            "Все файлы (*);;NumPy (*.npy)",
+        )
+        if not path:
+            return
+        state.set_calib_envelope_path(path)
+        if calib_file_cb.isChecked():
+            if state.load_calib_reference():
+                state.set_calib_mode("file")
+                state.set_calib_enabled(calib_cb.isChecked())
+            else:
+                calib_file_cb.setChecked(False)
+        _refresh_calib_controls()
+        _refresh_pipeline_label()
+
+    def _on_load_calib():
+        if state.load_calib_reference():
+            if calib_file_cb.isChecked():
+                state.set_calib_mode("file")
+                state.set_calib_enabled(calib_cb.isChecked())
+        _refresh_calib_controls()
+        _refresh_pipeline_label()
+
+    def _on_save_calib():
+        if state.save_calib_envelope():
+            if calib_file_cb.isChecked():
+                state.load_calib_envelope()
+                state.set_calib_mode("file")
+                state.set_calib_enabled(calib_cb.isChecked())
+        _refresh_calib_controls()
+        _refresh_pipeline_label()
+
+    def _on_sample_calib():
+        sample_path = os.path.join("sample_data", "no_antennas_35dB_attenuators")
+        state.set_calib_envelope_path(sample_path)
+        if state.load_calib_reference():
+            calib_file_cb.setChecked(True)
+            state.set_calib_mode("file")
+            state.set_calib_enabled(calib_cb.isChecked())
+        _refresh_calib_controls()
+        _refresh_pipeline_label()
 
     calib_cb.stateChanged.connect(_on_calib_toggled)
     calib_file_cb.stateChanged.connect(lambda _v: _on_calib_file_toggled(calib_file_cb.isChecked()))
+    calib_pick_btn.clicked.connect(_on_pick_calib_path)
+    calib_load_btn.clicked.connect(_on_load_calib)
+    calib_save_btn.clicked.connect(_on_save_calib)
+    calib_sample_btn.clicked.connect(_on_sample_calib)
 
-    # Кнопка сохранения фона + чекбокс вычета фона
+    # Блок управления фоном
     bg_widget = QtWidgets.QWidget()
-    bg_layout = QtWidgets.QHBoxLayout(bg_widget)
+    bg_layout = QtWidgets.QVBoxLayout(bg_widget)
     bg_layout.setContentsMargins(2, 2, 2, 2)
-    bg_layout.setSpacing(8)
+    bg_layout.setSpacing(4)
 
-    save_bg_btn = QtWidgets.QPushButton("Сохр. фон")
+    bg_row_1 = QtWidgets.QHBoxLayout()
+    bg_row_1.setSpacing(8)
+    bg_row_2 = QtWidgets.QHBoxLayout()
+    bg_row_2.setSpacing(6)
+
+    save_bg_btn = QtWidgets.QPushButton("Сохранить фон")
+    load_bg_btn = QtWidgets.QPushButton("Загрузить")
+    bg_pick_btn = QtWidgets.QPushButton("Файл…")
+    bg_sample_btn = QtWidgets.QPushButton("sample bg")
     bg_cb = QtWidgets.QCheckBox("вычет фона")
-    bg_cb.setEnabled(False)
+    bg_cb.setEnabled(False)  # активируется при успешной загрузке/сохранении
+    bg_path_label = QtWidgets.QLabel()
+    bg_path_label.setMinimumWidth(260)
+    if _qt_text_selectable is not None:
+        bg_path_label.setTextInteractionFlags(_qt_text_selectable)
 
-    bg_layout.addWidget(save_bg_btn)
+    bg_row_1.addWidget(bg_cb)
-    bg_layout.addWidget(bg_cb)
+    bg_row_1.addStretch(1)
+
+    bg_row_2.addWidget(QtWidgets.QLabel("Фон:"))
+    bg_row_2.addWidget(bg_path_label, 1)
+    bg_row_2.addWidget(bg_pick_btn)
+    bg_row_2.addWidget(load_bg_btn)
+    bg_row_2.addWidget(save_bg_btn)
+    bg_row_2.addWidget(bg_sample_btn)
+
+    bg_layout.addLayout(bg_row_1)
+    bg_layout.addLayout(bg_row_2)
 
     bg_container_proxy = QtWidgets.QGraphicsProxyWidget()
     bg_container_proxy.setWidget(bg_widget)
     win.addItem(bg_container_proxy, row=2, col=0)
 
+    def _refresh_bg_controls():
+        bg_path_label.setText(_short_path(state.background_path))
+        bg_path_label.setToolTip(state.background_path)
+        load_bg_btn.setEnabled(bool(state.background_path) and os.path.isfile(state.background_path))
+        bg_cb.setEnabled(state.background is not None or state.background_source_type == "capture_raw")
+
+    def _on_pick_bg_path():
+        path, _ = QtWidgets.QFileDialog.getOpenFileName(
+            win,
+            "Выбрать источник фона (.npy или capture)",
+            state.background_path,
+            "Все файлы (*);;NumPy (*.npy)",
+        )
+        if not path:
+            return
+        state.set_background_path(path)
+        if bg_cb.isChecked():
+            if not state.load_background_reference():
+                bg_cb.setChecked(False)
+        _refresh_bg_controls()
+        _refresh_pipeline_label()
+
+    def _on_load_bg():
+        state.load_background_reference()
+        _refresh_bg_controls()
+        _refresh_pipeline_label()
+
     def _on_save_bg():
         ok = state.save_background()
         if ok:
             state.load_background()
-            bg_cb.setEnabled(True)
+        _refresh_bg_controls()
+        _refresh_pipeline_label()
 
+    def _on_bg_toggled(_v):
+        state.set_background_enabled(bg_cb.isChecked())
+        _refresh_pipeline_label()
+
+    def _on_sample_bg():
+        sample_path = os.path.join("sample_data", "empty")
+        state.set_background_path(sample_path)
+        if state.load_background_reference():
+            bg_cb.setEnabled(True)
+        _refresh_bg_controls()
+        _refresh_pipeline_label()
+
+    bg_pick_btn.clicked.connect(_on_pick_bg_path)
+    load_bg_btn.clicked.connect(_on_load_bg)
     save_bg_btn.clicked.connect(_on_save_bg)
-    bg_cb.stateChanged.connect(lambda _v: state.set_background_enabled(bg_cb.isChecked()))
+    bg_cb.stateChanged.connect(_on_bg_toggled)
+    bg_sample_btn.clicked.connect(_on_sample_bg)
+
+    # Переключатель отображения верхнего линейного графика
+    line_mode_widget = QtWidgets.QWidget()
+    line_mode_layout = QtWidgets.QHBoxLayout(line_mode_widget)
+    line_mode_layout.setContentsMargins(2, 2, 2, 2)
+    line_mode_layout.setSpacing(8)
+    line_mode_layout.addWidget(QtWidgets.QLabel("Линия:"))
+    line_mode_raw_rb = QtWidgets.QRadioButton("raw")
+    line_mode_proc_rb = QtWidgets.QRadioButton("processed")
+    line_mode_raw_rb.setChecked(True)
+    line_mode_layout.addWidget(line_mode_raw_rb)
+    line_mode_layout.addWidget(line_mode_proc_rb)
+    line_mode_layout.addStretch(1)
+    line_mode_proxy = QtWidgets.QGraphicsProxyWidget()
+    line_mode_proxy.setWidget(line_mode_widget)
+    win.addItem(line_mode_proxy, row=6, col=0, colspan=2)
+
+    def _line_mode() -> str:
+        return "processed" if line_mode_proc_rb.isChecked() else "raw"
 
     # Статусная строка
     status = pg.LabelItem(justify="left")
     win.addItem(status, row=3, col=0, colspan=2)
+    pipeline_status = pg.LabelItem(justify="left")
+    win.addItem(pipeline_status, row=4, col=0, colspan=2)
+    ref_status = pg.LabelItem(justify="left")
+    win.addItem(ref_status, row=5, col=0, colspan=2)
+
+    def _refresh_pipeline_label():
+        txt = state.format_pipeline_status()
+        trace = state.format_stage_trace()
+        if trace:
+            txt = f"{txt} | trace: {trace}"
+        pipeline_status.setText(txt)
+        ref_status.setText(state.format_reference_status())
+
+    _refresh_calib_controls()
+    _refresh_bg_controls()
+    _refresh_pipeline_label()
 
     _imshow_initialized = [False]
 
@@ -293,28 +494,46 @@ def run_pyqtgraph(args):
         if changed and not _imshow_initialized[0] and ring.is_ready:
             _init_imshow_extents()
             _imshow_initialized[0] = True
+        if changed:
+            _refresh_calib_controls()
+            _refresh_bg_controls()
+            _refresh_pipeline_label()
 
         # Линейный график свипа
         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)
-            curve.setData(xs, raw, autoDownsample=True)
+            line_mode = _line_mode()
+            main = state.current_sweep_processed if line_mode == "processed" else raw
+            if main is not None:
+                curve.setData(xs[: main.size], main, autoDownsample=True)
+            else:
+                curve.setData([], [])
+            if line_mode == "raw":
                 if state.calib_mode == "file" and state.calib_file_envelope is not None:
-                upper = state.calib_file_envelope
+                    upper = np.asarray(state.calib_file_envelope, dtype=np.float32)
-                lower = -upper
+                    n_env = min(xs.size, upper.size)
-                m_env = float(np.nanmax(np.abs(upper)))
+                    if n_env > 0:
-                if m_env <= 0.0:
+                        x_env = xs[:n_env]
-                    m_env = 1.0
+                        y_env = upper[:n_env]
-                curve_env_lo.setData(xs[: upper.size], lower / m_env, autoDownsample=True)
+                        curve_env_lo.setData(x_env, -y_env, autoDownsample=True)
-                curve_env_hi.setData(xs[: upper.size], upper / m_env, autoDownsample=True)
+                        curve_env_hi.setData(x_env, y_env, autoDownsample=True)
+                    else:
+                        curve_env_lo.setData([], [])
+                        curve_env_hi.setData([], [])
                 elif state.last_calib_sweep is not None:
-                calib = state.last_calib_sweep
+                    calib = np.asarray(state.last_calib_sweep, dtype=np.float32)
-                m_calib = float(np.nanmax(np.abs(calib)))
-                if m_calib <= 0.0:
-                    m_calib = 1.0
                     lower, upper = build_calib_envelopes(calib)
-                curve_env_lo.setData(xs[: calib.size], lower / m_calib, autoDownsample=True)
+                    n_env = min(xs.size, upper.size, lower.size)
-                curve_env_hi.setData(xs[: calib.size], upper / m_calib, autoDownsample=True)
+                    if n_env > 0:
+                        curve_env_lo.setData(xs[:n_env], lower[:n_env], autoDownsample=True)
+                        curve_env_hi.setData(xs[:n_env], upper[:n_env], autoDownsample=True)
+                    else:
+                        curve_env_lo.setData([], [])
+                        curve_env_hi.setData([], [])
+                else:
+                    curve_env_lo.setData([], [])
+                    curve_env_hi.setData([], [])
             else:
                 curve_env_lo.setData([], [])
                 curve_env_hi.setData([], [])
@@ -328,16 +547,19 @@ def run_pyqtgraph(args):
                 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 line_mode == "processed":
                     if state.current_sweep_processed is not None:
                         proc = state.current_sweep_processed
                         curve.setData(xs[: proc.size], proc, autoDownsample=True)
                     else:
                         curve.setData([], [])
+                else:
+                    curve.setData(xs[: raw.size], raw, autoDownsample=True)
                 curve_norm.setData([], [])
             else:
                 curve_pre_exp.setData([], [])
                 curve_post_exp.setData([], [])
-                if state.current_sweep_norm is not None:
+                if line_mode == "raw" and state.current_sweep_norm is not None:
                     curve_norm.setData(
                         xs[: state.current_sweep_norm.size],
                         state.current_sweep_norm,
@@ -385,6 +607,8 @@ def run_pyqtgraph(args):
             except Exception:
                 pass
             ch_text.setText(state.format_channel_label())
+        elif changed:
+            _refresh_pipeline_label()
 
         # Водопад спектров — новые данные справа (без реверса)
         if changed and ring.is_ready:

rfg_adc_plotter/io/capture_reference_loader.py

@@ -0,0 +1,227 @@
+"""Загрузка эталонов (калибровка/фон) из .npy или бинарных capture-файлов."""
+
+from __future__ import annotations
+
+from collections import Counter
+from dataclasses import dataclass
+import os
+from typing import Iterable, List, Optional, Tuple
+
+import numpy as np
+
+from rfg_adc_plotter.io.sweep_parser_core import BinaryRecordStreamParser, SweepAssembler
+from rfg_adc_plotter.types import SweepPacket
+
+
+@dataclass(frozen=True)
+class CaptureParseSummary:
+    path: str
+    format: str  # "npy" | "bin_capture"
+    sweeps_total: int
+    sweeps_valid: int
+    channels_seen: Tuple[int, ...]
+    dominant_width: Optional[int]
+    dominant_n_valid: Optional[int]
+    aggregation: str
+    warnings: Tuple[str, ...]
+
+
+@dataclass(frozen=True)
+class ReferenceLoadResult:
+    vector: np.ndarray
+    summary: CaptureParseSummary
+    kind: str  # "calibration_envelope" | "background_raw" | "background_processed"
+    source_type: str  # "npy" | "capture"
+
+
+def detect_reference_file_format(path: str) -> Optional[str]:
+    """Определить формат файла эталона: .npy или бинарный capture."""
+    p = str(path).strip()
+    if not p or not os.path.isfile(p):
+        return None
+    if p.lower().endswith(".npy"):
+        return "npy"
+
+    try:
+        size = os.path.getsize(p)
+    except Exception:
+        return None
+    if size <= 0 or (size % 8) != 0:
+        return None
+
+    try:
+        with open(p, "rb") as f:
+            sample = f.read(min(size, 8 * 2048))
+    except Exception:
+        return None
+
+    if len(sample) < 8:
+        return None
+
+    # Быстрый sniff aligned-записей: в валидных записях байт 6 == 0x0A.
+    recs = len(sample) // 8
+    if recs <= 0:
+        return None
+    marker_hits = 0
+    start_hits = 0
+    for i in range(0, recs * 8, 8):
+        b = sample[i : i + 8]
+        if b[6] == 0x0A:
+            marker_hits += 1
+            if b[:6] == b"\xff\xff\xff\xff\xff\xff":
+                start_hits += 1
+    if marker_hits >= max(4, int(recs * 0.8)) and start_hits >= 1:
+        return "bin_capture"
+    return None
+
+
+def load_capture_sweeps(path: str, *, fancy: bool = False, logscale: bool = False) -> List[SweepPacket]:
+    """Загрузить свипы из бинарного capture-файла в формате --bin."""
+    parser = BinaryRecordStreamParser()
+    assembler = SweepAssembler(fancy=fancy, logscale=logscale, debug=False)
+    sweeps: List[SweepPacket] = []
+
+    with open(path, "rb") as f:
+        while True:
+            chunk = f.read(65536)
+            if not chunk:
+                break
+            events = parser.feed(chunk)
+            for ev in events:
+                packets = assembler.consume_binary_event(ev)
+                if packets:
+                    sweeps.extend(packets)
+    tail = assembler.finalize_current()
+    if tail is not None:
+        sweeps.append(tail)
+
+    return sweeps
+
+
+def _mode_int(values: Iterable[int]) -> Optional[int]:
+    vals = [int(v) for v in values]
+    if not vals:
+        return None
+    ctr = Counter(vals)
+    return int(max(ctr.items(), key=lambda kv: (kv[1], kv[0]))[0])
+
+
+def aggregate_capture_reference(
+    sweeps: List[SweepPacket],
+    *,
+    channel: int = 0,
+    method: str = "median",
+    path: str = "",
+) -> Tuple[np.ndarray, CaptureParseSummary]:
+    """Отфильтровать и агрегировать свипы из capture в один эталонный вектор."""
+    ch_target = int(channel)
+    meth = str(method).strip().lower() or "median"
+    warnings: list[str] = []
+
+    if meth != "median":
+        warnings.append(f"aggregation '{meth}' не поддерживается, использую median")
+        meth = "median"
+
+    channels_seen: set[int] = set()
+    candidate_rows: list[np.ndarray] = []
+    widths: list[int] = []
+    n_valids: list[int] = []
+
+    for sweep, info in sweeps:
+        chs = info.get("chs") if isinstance(info, dict) else None
+        ch_set: set[int] = set()
+        if isinstance(chs, (list, tuple, set)):
+            for v in chs:
+                try:
+                    ch_set.add(int(v))
+                except Exception:
+                    pass
+        else:
+            try:
+                ch_set.add(int(info.get("ch", 0)))  # type: ignore[union-attr]
+            except Exception:
+                pass
+        channels_seen.update(ch_set)
+        if ch_target not in ch_set:
+            continue
+
+        row = np.asarray(sweep, dtype=np.float32).reshape(-1)
+        candidate_rows.append(row)
+        widths.append(int(row.size))
+        n_valids.append(int(np.count_nonzero(np.isfinite(row))))
+
+    sweeps_total = len(sweeps)
+    if not candidate_rows:
+        summary = CaptureParseSummary(
+            path=path,
+            format="bin_capture",
+            sweeps_total=sweeps_total,
+            sweeps_valid=0,
+            channels_seen=tuple(sorted(channels_seen)),
+            dominant_width=None,
+            dominant_n_valid=None,
+            aggregation=meth,
+            warnings=tuple(warnings + [f"канал ch{ch_target} не найден"]),
+        )
+        raise ValueError(summary.warnings[-1])
+
+    dominant_width = _mode_int(widths)
+    dominant_n_valid = _mode_int(n_valids)
+    if dominant_width is None or dominant_n_valid is None:
+        summary = CaptureParseSummary(
+            path=path,
+            format="bin_capture",
+            sweeps_total=sweeps_total,
+            sweeps_valid=0,
+            channels_seen=tuple(sorted(channels_seen)),
+            dominant_width=dominant_width,
+            dominant_n_valid=dominant_n_valid,
+            aggregation=meth,
+            warnings=tuple(warnings + ["не удалось определить доминирующие параметры свипа"]),
+        )
+        raise ValueError(summary.warnings[-1])
+
+    valid_rows: list[np.ndarray] = []
+    n_valid_threshold = max(1, int(np.floor(0.95 * dominant_n_valid)))
+    for row in candidate_rows:
+        if row.size != dominant_width:
+            continue
+        n_valid = int(np.count_nonzero(np.isfinite(row)))
+        if n_valid < n_valid_threshold:
+            continue
+        valid_rows.append(row)
+
+    if not valid_rows:
+        warnings.append("после фильтрации не осталось валидных свипов")
+        summary = CaptureParseSummary(
+            path=path,
+            format="bin_capture",
+            sweeps_total=sweeps_total,
+            sweeps_valid=0,
+            channels_seen=tuple(sorted(channels_seen)),
+            dominant_width=dominant_width,
+            dominant_n_valid=dominant_n_valid,
+            aggregation=meth,
+            warnings=tuple(warnings),
+        )
+        raise ValueError(summary.warnings[-1])
+
+    # Детерминированная агрегация: медиана по валидным свипам.
+    stack = np.stack(valid_rows, axis=0).astype(np.float32, copy=False)
+    vector = np.nanmedian(stack, axis=0).astype(np.float32, copy=False)
+
+    if len(valid_rows) < len(candidate_rows):
+        warnings.append(f"отфильтровано {len(candidate_rows) - len(valid_rows)} неполных/нестандартных свипов")
+
+    summary = CaptureParseSummary(
+        path=path,
+        format="bin_capture",
+        sweeps_total=sweeps_total,
+        sweeps_valid=len(valid_rows),
+        channels_seen=tuple(sorted(channels_seen)),
+        dominant_width=dominant_width,
+        dominant_n_valid=dominant_n_valid,
+        aggregation=meth,
+        warnings=tuple(warnings),
+    )
+    return vector, summary

rfg_adc_plotter/io/sweep_parser_core.py

@@ -0,0 +1,247 @@
+"""Переиспользуемые компоненты парсинга бинарных свипов и сборки SweepPacket."""
+
+from __future__ import annotations
+
+from collections import deque
+import time
+from typing import Iterable, List, Optional, Sequence, Set, Tuple
+
+import numpy as np
+
+from rfg_adc_plotter.constants import DATA_INVERSION_THRESHOLD, LOG_EXP
+from rfg_adc_plotter.types import SweepInfo, SweepPacket
+
+# Binary parser events:
+#   ("start", ch)
+#   ("point", ch, x, y)
+BinaryEvent = Tuple[str, int] | Tuple[str, int, int, int]
+
+
+def u32_to_i32(v: int) -> int:
+    """Преобразование 32-bit слова в знаковое значение."""
+    return v - 0x1_0000_0000 if (v & 0x8000_0000) else v
+
+
+class BinaryRecordStreamParser:
+    """Инкрементальный парсер бинарных записей протокола (по 8 байт)."""
+
+    def __init__(self):
+        self._buf = bytearray()
+        self.bytes_consumed: int = 0
+        self.start_count: int = 0
+        self.point_count: int = 0
+        self.desync_count: int = 0
+
+    def feed(self, data: bytes) -> List[BinaryEvent]:
+        if data:
+            self._buf += data
+        events: List[BinaryEvent] = []
+        buf = self._buf
+
+        while len(buf) >= 8:
+            w0 = int(buf[0]) | (int(buf[1]) << 8)
+            w1 = int(buf[2]) | (int(buf[3]) << 8)
+            w2 = int(buf[4]) | (int(buf[5]) << 8)
+
+            if w0 == 0xFFFF and w1 == 0xFFFF and w2 == 0xFFFF and buf[6] == 0x0A:
+                ch = int(buf[7])
+                events.append(("start", ch))
+                del buf[:8]
+                self.bytes_consumed += 8
+                self.start_count += 1
+                continue
+
+            if buf[6] == 0x0A:
+                ch = int(buf[7])
+                value_u32 = (w1 << 16) | w2
+                events.append(("point", ch, int(w0), u32_to_i32(value_u32)))
+                del buf[:8]
+                self.bytes_consumed += 8
+                self.point_count += 1
+                continue
+
+            del buf[:1]
+            self.bytes_consumed += 1
+            self.desync_count += 1
+
+        return events
+
+    def buffered_size(self) -> int:
+        return len(self._buf)
+
+    def clear_buffer_keep_tail(self, max_tail: int = 262_144):
+        if len(self._buf) > max_tail:
+            del self._buf[:-max_tail]
+
+
+class SweepAssembler:
+    """Собирает точки в свип и применяет ту же постобработку, что realtime parser."""
+
+    def __init__(self, fancy: bool = False, logscale: bool = False, debug: bool = False):
+        self._fancy = bool(fancy)
+        self._logscale = bool(logscale)
+        self._debug = bool(debug)
+
+        self._max_width: int = 0
+        self._sweep_idx: int = 0
+        self._last_sweep_ts: Optional[float] = None
+        self._n_valid_hist = deque()
+
+        self._xs: list[int] = []
+        self._ys: list[int] = []
+        self._cur_channel: Optional[int] = None
+        self._cur_channels: set[int] = set()
+
+    def reset_current(self):
+        self._xs.clear()
+        self._ys.clear()
+        self._cur_channel = None
+        self._cur_channels.clear()
+
+    def add_point(self, ch: int, x: int, y: int):
+        if self._cur_channel is None:
+            self._cur_channel = int(ch)
+        self._cur_channels.add(int(ch))
+        self._xs.append(int(x))
+        self._ys.append(int(y))
+
+    def start_new_sweep(self, ch: int, now_ts: Optional[float] = None) -> Optional[SweepPacket]:
+        packet = self.finalize_current(now_ts=now_ts)
+        self.reset_current()
+        self._cur_channel = int(ch)
+        self._cur_channels.add(int(ch))
+        return packet
+
+    def consume_binary_event(self, event: BinaryEvent, now_ts: Optional[float] = None) -> List[SweepPacket]:
+        out: List[SweepPacket] = []
+        tag = event[0]
+        if tag == "start":
+            packet = self.start_new_sweep(int(event[1]), now_ts=now_ts)
+            if packet is not None:
+                out.append(packet)
+            return out
+        # point
+        _tag, ch, x, y = event  # type: ignore[misc]
+        self.add_point(int(ch), int(x), int(y))
+        return out
+
+    def finalize_arrays(
+        self,
+        xs: Sequence[int],
+        ys: Sequence[int],
+        channels: Optional[Set[int]],
+        now_ts: Optional[float] = None,
+    ) -> Optional[SweepPacket]:
+        if self._debug:
+            if not xs:
+                import sys
+                sys.stderr.write("[debug] _finalize_current: xs пуст — свип пропущен\n")
+            else:
+                import sys
+                sys.stderr.write(
+                    f"[debug] _finalize_current: {len(xs)} точек → свип #{self._sweep_idx + 1}\n"
+                )
+        if not xs:
+            return None
+
+        ch_list = sorted(channels) if channels else [0]
+        ch_primary = ch_list[0] if ch_list else 0
+        max_x = max(int(v) for v in xs)
+        width = max_x + 1
+        self._max_width = max(self._max_width, width)
+        target_width = self._max_width if self._fancy else width
+
+        sweep = np.full((target_width,), np.nan, dtype=np.float32)
+        try:
+            idx = np.asarray(xs, dtype=np.int64)
+            vals = np.asarray(ys, dtype=np.float32)
+            sweep[idx] = vals
+        except Exception:
+            for x, y in zip(xs, ys):
+                xi = int(x)
+                if 0 <= xi < target_width:
+                    sweep[xi] = float(y)
+
+        n_valid_cur = int(np.count_nonzero(np.isfinite(sweep)))
+
+        if self._fancy:
+            try:
+                known = ~np.isnan(sweep)
+                if np.any(known):
+                    known_idx = np.nonzero(known)[0]
+                    for i0, i1 in zip(known_idx[:-1], known_idx[1:]):
+                        if i1 - i0 > 1:
+                            avg = (sweep[i0] + sweep[i1]) * 0.5
+                            sweep[i0 + 1 : i1] = avg
+                    first_idx = int(known_idx[0])
+                    last_idx = int(known_idx[-1])
+                    if first_idx > 0:
+                        sweep[:first_idx] = sweep[first_idx]
+                    if last_idx < sweep.size - 1:
+                        sweep[last_idx + 1 :] = sweep[last_idx]
+            except Exception:
+                pass
+
+        try:
+            m = float(np.nanmean(sweep))
+            if np.isfinite(m) and m < DATA_INVERSION_THRESHOLD:
+                sweep *= -1.0
+        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:
+            import sys
+            sys.stderr.write(f"[warn] Sweep {self._sweep_idx}: изменялся номер канала: {ch_list}\n")
+
+        now = float(time.time() if now_ts is None else now_ts)
+        if self._last_sweep_ts is None:
+            dt_ms = float("nan")
+        else:
+            dt_ms = (now - self._last_sweep_ts) * 1000.0
+        self._last_sweep_ts = now
+
+        self._n_valid_hist.append((now, n_valid_cur))
+        while self._n_valid_hist and (now - self._n_valid_hist[0][0]) > 1.0:
+            self._n_valid_hist.popleft()
+        if self._n_valid_hist:
+            n_valid = float(sum(v for _t, v in self._n_valid_hist) / len(self._n_valid_hist))
+        else:
+            n_valid = float(n_valid_cur)
+
+        if n_valid_cur > 0:
+            vmin = float(np.nanmin(sweep))
+            vmax = float(np.nanmax(sweep))
+            mean = float(np.nanmean(sweep))
+            std = float(np.nanstd(sweep))
+        else:
+            vmin = vmax = mean = std = float("nan")
+
+        info: SweepInfo = {
+            "sweep": self._sweep_idx,
+            "ch": ch_primary,
+            "chs": ch_list,
+            "n_valid": n_valid,
+            "min": vmin,
+            "max": vmax,
+            "mean": mean,
+            "std": std,
+            "dt_ms": dt_ms,
+        }
+        if pre_exp_sweep is not None:
+            info["pre_exp_sweep"] = pre_exp_sweep
+
+        return (sweep, info)
+
+    def finalize_current(self, now_ts: Optional[float] = None) -> Optional[SweepPacket]:
+        return self.finalize_arrays(self._xs, self._ys, self._cur_channels, now_ts=now_ts)

rfg_adc_plotter/io/sweep_reader.py

@@ -3,15 +3,12 @@
 import sys
 import threading
 import time
-from collections import deque
 from queue import Full, Queue
 from typing import Optional
 
-import numpy as np
+from rfg_adc_plotter.io.sweep_parser_core import BinaryRecordStreamParser, SweepAssembler
-
-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
+from rfg_adc_plotter.types import SweepPacket
 
 
 class SweepReader(threading.Thread):
@@ -38,119 +35,13 @@ class SweepReader(threading.Thread):
         self._bin_mode = bool(bin_mode)
         self._logscale = bool(logscale)
         self._debug = bool(debug)
-        self._max_width: int = 0
+        self._assembler = SweepAssembler(fancy=self._fancy, logscale=self._logscale, debug=self._debug)
-        self._sweep_idx: int = 0
-        self._last_sweep_ts: Optional[float] = None
-        self._n_valid_hist = deque()
-
-    @staticmethod
-    def _u32_to_i32(v: int) -> int:
-        """Преобразование 32-bit слова в знаковое значение."""
-        return v - 0x1_0000_0000 if (v & 0x8000_0000) else v
 
     def _finalize_current(self, xs, ys, channels: Optional[set]):
-        if self._debug:
+        packet = self._assembler.finalize_arrays(xs, ys, channels)
-            if not xs:
+        if packet is None:
-                sys.stderr.write("[debug] _finalize_current: xs пуст — свип пропущен\n")
-            else:
-                sys.stderr.write(f"[debug] _finalize_current: {len(xs)} точек → свип #{self._sweep_idx + 1}\n")
-        if not xs:
             return
-        ch_list = sorted(channels) if channels else [0]
+        sweep, info = packet
-        ch_primary = ch_list[0] if ch_list else 0
-        max_x = max(xs)
-        width = max_x + 1
-        self._max_width = max(self._max_width, width)
-        target_width = self._max_width if self._fancy else width
-
-        sweep = np.full((target_width,), np.nan, dtype=np.float32)
-        try:
-            idx = np.asarray(xs, dtype=np.int64)
-            vals = np.asarray(ys, dtype=np.float32)
-            sweep[idx] = vals
-        except Exception:
-            for x, y in zip(xs, ys):
-                if 0 <= x < target_width:
-                    sweep[x] = float(y)
-
-        finite_pre = np.isfinite(sweep)
-        n_valid_cur = int(np.count_nonzero(finite_pre))
-
-        if self._fancy:
-            try:
-                known = ~np.isnan(sweep)
-                if np.any(known):
-                    known_idx = np.nonzero(known)[0]
-                    for i0, i1 in zip(known_idx[:-1], known_idx[1:]):
-                        if i1 - i0 > 1:
-                            avg = (sweep[i0] + sweep[i1]) * 0.5
-                            sweep[i0 + 1 : i1] = avg
-                    first_idx = int(known_idx[0])
-                    last_idx = int(known_idx[-1])
-                    if first_idx > 0:
-                        sweep[:first_idx] = sweep[first_idx]
-                    if last_idx < sweep.size - 1:
-                        sweep[last_idx + 1 :] = sweep[last_idx]
-            except Exception:
-                pass
-
-        try:
-            m = float(np.nanmean(sweep))
-            if np.isfinite(m) and m < DATA_INVERSION_THRESHOLD:
-                sweep *= -1.0
-        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(
-                f"[warn] Sweep {self._sweep_idx}: изменялся номер канала: {ch_list}\n"
-            )
-        now = time.time()
-        if self._last_sweep_ts is None:
-            dt_ms = float("nan")
-        else:
-            dt_ms = (now - self._last_sweep_ts) * 1000.0
-        self._last_sweep_ts = now
-        self._n_valid_hist.append((now, n_valid_cur))
-        while self._n_valid_hist and (now - self._n_valid_hist[0][0]) > 1.0:
-            self._n_valid_hist.popleft()
-        if self._n_valid_hist:
-            n_valid = float(sum(v for _t, v in self._n_valid_hist) / len(self._n_valid_hist))
-        else:
-            n_valid = float(n_valid_cur)
-
-        if n_valid_cur > 0:
-            vmin = float(np.nanmin(sweep))
-            vmax = float(np.nanmax(sweep))
-            mean = float(np.nanmean(sweep))
-            std = float(np.nanstd(sweep))
-        else:
-            vmin = vmax = mean = std = float("nan")
-        info: SweepInfo = {
-            "sweep": self._sweep_idx,
-            "ch": ch_primary,
-            "chs": ch_list,
-            "n_valid": n_valid,
-            "min": vmin,
-            "max": vmax,
-            "mean": mean,
-            "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))
         except Full:
@@ -263,6 +154,7 @@ class SweepReader(threading.Thread):
         ys: list[int] = []
         cur_channel: Optional[int] = None
         cur_channels: set[int] = set()
+        parser = BinaryRecordStreamParser()
 
         # Бинарный протокол (4 слова LE u16 = 8 байт на запись):
         #   старт свипа: 0xFFFF, 0xFFFF, 0xFFFF, (ch<<8)|0x0A
@@ -274,7 +166,6 @@ class SweepReader(threading.Thread):
         #   Признак записи: байт 6 == 0x0A, байт 7 — номер канала.
         #   При десинхронизации сдвигаемся на 1 БАЙТ (не слово) для самосинхронизации.
 
-        buf = bytearray()
         _dbg_byte_count = 0
         _dbg_desync_count = 0
         _dbg_sweep_count = 0
@@ -282,20 +173,15 @@ class SweepReader(threading.Thread):
         while not self._stop.is_set():
             data = chunk_reader.read_available()
             if data:
-                buf += data
+                events = parser.feed(data)
             else:
                 time.sleep(0.0005)
                 continue
 
-            while len(buf) >= 8:
+            for ev in events:
-                # Читаем 4 LE u16 слова прямо из байтового буфера
+                tag = ev[0]
-                w0 = int(buf[0]) | (int(buf[1]) << 8)
+                if tag == "start":
-                w1 = int(buf[2]) | (int(buf[3]) << 8)
+                    ch_new = int(ev[1])
-                w2 = int(buf[4]) | (int(buf[5]) << 8)
-
-                # Старт свипа: три слова 0xFFFF + маркер 0x0A в байте 6, канал в байте 7
-                if w0 == 0xFFFF and w1 == 0xFFFF and w2 == 0xFFFF and buf[6] == 0x0A:
-                    ch_new = buf[7]
                     if self._debug:
                         sys.stderr.write(f"[debug] BIN: старт свипа, ch={ch_new}\n")
                         _dbg_sweep_count += 1
@@ -305,41 +191,22 @@ class SweepReader(threading.Thread):
                     cur_channels.clear()
                     cur_channel = ch_new
                     cur_channels.add(cur_channel)
-                    del buf[:8]
-                    _dbg_byte_count += 8
                     continue
 
-                # Точка данных: маркер 0x0A в байте 6, канал в байте 7
+                _tag, ch_from_term, step, value_i32 = ev  # type: ignore[misc]
-                if buf[6] == 0x0A:
-                    ch_from_term = buf[7]
                 if cur_channel is None:
-                        cur_channel = ch_from_term
+                    cur_channel = int(ch_from_term)
-                    cur_channels.add(cur_channel)
+                cur_channels.add(int(cur_channel))
-                    xs.append(w0)
+                xs.append(int(step))
-                    value_u32 = (w1 << 16) | w2
+                ys.append(int(value_i32))
-                    ys.append(self._u32_to_i32(value_u32))
-                    del buf[:8]
-                    _dbg_byte_count += 8
                 _dbg_point_count += 1
                 if self._debug and _dbg_point_count <= 3:
                     sys.stderr.write(
-                            f"[debug] BIN точка: step={w0} hi={w1:#06x} lo={w2:#06x} "
+                        f"[debug] BIN точка: step={int(step)} ch={int(ch_from_term)} → value={int(value_i32)}\n"
-                            f"ch={ch_from_term} → value={self._u32_to_i32((w1 << 16) | w2)}\n"
                     )
-                    continue
 
-                # Поток не выровнен; сдвигаемся на 1 байт до ресинхронизации.
+            _dbg_byte_count = parser.bytes_consumed
-                _dbg_desync_count += 1
+            _dbg_desync_count = parser.desync_count
-                _dbg_byte_count += 1
-                if self._debug and _dbg_desync_count <= 8:
-                    hex6 = " ".join(f"{buf[k]:02x}" for k in range(min(8, len(buf))))
-                    sys.stderr.write(
-                        f"[debug] BIN десинхронизация #{_dbg_desync_count}: "
-                        f"байты [{hex6}] не совпадают ни с одним шаблоном\n"
-                    )
-                if self._debug and _dbg_desync_count == 9:
-                    sys.stderr.write("[debug] BIN: дальнейшие десинхронизации не выводятся (слишком много)\n")
-                del buf[:1]
 
             if self._debug and _dbg_byte_count > 0 and _dbg_byte_count % 4000 < 8:
                 sys.stderr.write(
@@ -347,8 +214,8 @@ class SweepReader(threading.Thread):
                     f"десинхронизаций={_dbg_desync_count}, точек={_dbg_point_count}, свипов={_dbg_sweep_count}\n"
                 )
 
-            if len(buf) > 1_000_000:
+            if parser.buffered_size() > 1_000_000:
-                del buf[:-262144]
+                parser.clear_buffer_keep_tail(262_144)
 
         self._finalize_current(xs, ys, cur_channels)
 

rfg_adc_plotter/processing/fourier.py

@@ -0,0 +1,43 @@
+"""Преобразование свипа в IFFT-временной профиль (дБ)."""
+
+from typing import Optional
+
+import numpy as np
+
+from rfg_adc_plotter.constants import FREQ_SPAN_GHZ, IFFT_LEN, SWEEP_LEN, ZEROS_LOW, ZEROS_MID
+
+
+def build_ifft_time_axis_ns() -> np.ndarray:
+    """Временная ось IFFT в наносекундах."""
+    return (
+        np.arange(IFFT_LEN, dtype=np.float64) / (FREQ_SPAN_GHZ * 1e9) * 1e9
+    ).astype(np.float32)
+
+
+def compute_ifft_db_profile(sweep: Optional[np.ndarray]) -> np.ndarray:
+    """Построить IFFT-профиль свипа в дБ.
+
+    Цепочка:
+    raw/processed sweep -> двусторонний спектр (заполнение нулями) ->
+    ifftshift -> ifft -> |x| -> 20log10.
+    """
+    bins = IFFT_LEN
+    if sweep is None:
+        return np.full((bins,), np.nan, dtype=np.float32)
+
+    s = np.asarray(sweep)
+    if s.size == 0:
+        return np.full((bins,), np.nan, dtype=np.float32)
+
+    sig = np.zeros(SWEEP_LEN, dtype=np.float32)
+    take = min(int(s.size), SWEEP_LEN)
+    seg = np.nan_to_num(s[:take], nan=0.0).astype(np.float32, copy=False)
+    sig[:take] = seg
+
+    data = np.zeros(IFFT_LEN, dtype=np.complex64)
+    data[ZEROS_LOW + ZEROS_MID :] = sig
+
+    spec = np.fft.ifftshift(data)
+    result = np.fft.ifft(spec)
+    mag = np.abs(result).astype(np.float32)
+    return (mag + 1e-9).astype(np.float32)

rfg_adc_plotter/processing/pipeline.py

@@ -0,0 +1,415 @@
+"""Явный pipeline предобработки свипов перед помещением в RingBuffer."""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+import os
+from typing import Optional, Tuple
+
+import numpy as np
+
+from rfg_adc_plotter.io.capture_reference_loader import (
+    CaptureParseSummary,
+    aggregate_capture_reference,
+    detect_reference_file_format,
+    load_capture_sweeps,
+)
+from rfg_adc_plotter.processing.normalizer import (
+    build_calib_envelopes,
+    normalize_by_calib,
+    normalize_by_envelope,
+)
+
+DEFAULT_CALIB_ENVELOPE_PATH = "calib_envelope.npy"
+DEFAULT_BACKGROUND_PATH = "background.npy"
+
+
+def _normalize_path(path: str) -> str:
+    return str(path).strip()
+
+
+def _normalize_save_npy_path(path: str) -> str:
+    p = _normalize_path(path)
+    if not p:
+        return p
+    _root, ext = os.path.splitext(p)
+    if ext:
+        return p
+    return f"{p}.npy"
+
+
+def _summary_for_npy(path: str) -> CaptureParseSummary:
+    return CaptureParseSummary(
+        path=path,
+        format="npy",
+        sweeps_total=0,
+        sweeps_valid=0,
+        channels_seen=tuple(),
+        dominant_width=None,
+        dominant_n_valid=None,
+        aggregation="median",
+        warnings=tuple(),
+    )
+
+
+@dataclass(frozen=True)
+class SweepProcessingResult:
+    """Результат предобработки одного свипа."""
+
+    processed_sweep: np.ndarray
+    normalized_sweep: Optional[np.ndarray]
+    calibration_applied: bool
+    background_applied: bool
+    calibration_source: str  # off|live|npy|capture
+    background_source: str   # off|npy|capture(raw)|capture(raw->calib)
+    is_calibration_reference: bool
+    stage_trace: Tuple[str, ...]
+
+
+class SweepPreprocessor:
+    """Управляет калибровкой/фоном и применяет их к входному свипу."""
+
+    def __init__(
+        self,
+        norm_type: str = "projector",
+        calib_envelope_path: str = DEFAULT_CALIB_ENVELOPE_PATH,
+        background_path: str = DEFAULT_BACKGROUND_PATH,
+        auto_save_live_calib_envelope: bool = True,
+    ):
+        self.norm_type = str(norm_type).strip().lower() or "projector"
+        self.calib_enabled = False
+        self.calib_mode = "live"  # live | file
+        self.background_enabled = False
+        self.auto_save_live_calib_envelope = bool(auto_save_live_calib_envelope)
+
+        self.calib_envelope_path = _normalize_path(calib_envelope_path)
+        self.background_path = _normalize_path(background_path)
+
+        self.last_calib_sweep: Optional[np.ndarray] = None
+        self.calib_file_envelope: Optional[np.ndarray] = None
+
+        # background — в текущем домене вычитания (raw или normalized), UI использует для preview/state
+        self.background: Optional[np.ndarray] = None
+        # raw background loaded from capture file; преобразуется на лету при активной калибровке
+        self.background_raw_capture: Optional[np.ndarray] = None
+
+        # Источники и метаданные загрузки
+        self.calib_external_source_type: str = "none"        # none|npy|capture
+        self.background_source_type: str = "none"            # none|npy_processed|capture_raw
+        self.calib_reference_summary: Optional[CaptureParseSummary] = None
+        self.background_reference_summary: Optional[CaptureParseSummary] = None
+        self.last_reference_error: str = ""
+
+        # Параметры офлайн-парсинга capture (должны совпадать с live parser по настройке UI)
+        self.capture_fancy: bool = False
+        self.capture_logscale: bool = False
+        self.reference_aggregation_method: str = "median"
+
+    # ---- Конфигурация ----
+    def set_calib_mode(self, mode: str):
+        m = str(mode).strip().lower()
+        self.calib_mode = "file" if m == "file" else "live"
+
+    def set_calib_enabled(self, enabled: bool):
+        self.calib_enabled = bool(enabled)
+
+    def set_background_enabled(self, enabled: bool):
+        self.background_enabled = bool(enabled)
+
+    def set_capture_parse_options(self, *, fancy: Optional[bool] = None, logscale: Optional[bool] = None):
+        if fancy is not None:
+            self.capture_fancy = bool(fancy)
+        if logscale is not None:
+            self.capture_logscale = bool(logscale)
+
+    def set_calib_envelope_path(self, path: str):
+        p = _normalize_path(path)
+        if p:
+            if p != self.calib_envelope_path:
+                self.calib_file_envelope = None
+                if self.calib_external_source_type in ("npy", "capture"):
+                    self.calib_external_source_type = "none"
+                    self.calib_reference_summary = None
+            self.calib_envelope_path = p
+
+    def set_background_path(self, path: str):
+        p = _normalize_path(path)
+        if p:
+            if p != self.background_path:
+                self.background = None
+                self.background_raw_capture = None
+                self.background_source_type = "none"
+                self.background_reference_summary = None
+            self.background_path = p
+
+    def has_calib_envelope_file(self) -> bool:
+        return bool(self.calib_envelope_path) and os.path.isfile(self.calib_envelope_path)
+
+    def has_background_file(self) -> bool:
+        return bool(self.background_path) and os.path.isfile(self.background_path)
+
+    # ---- Загрузка/сохранение .npy ----
+    def _save_array(self, arr: np.ndarray, current_path: str, path: Optional[str]) -> str:
+        target = _normalize_save_npy_path(path if path is not None else current_path)
+        if not target:
+            raise ValueError("Пустой путь сохранения")
+        np.save(target, arr)
+        return target
+
+    def save_calib_envelope(self, path: Optional[str] = None) -> bool:
+        """Сохранить огибающую из последнего live-калибровочного свипа (экспорт .npy)."""
+        if self.last_calib_sweep is None:
+            return False
+        try:
+            _lower, upper = build_calib_envelopes(self.last_calib_sweep)
+            self.calib_envelope_path = self._save_array(upper, self.calib_envelope_path, path)
+            self.last_reference_error = ""
+            return True
+        except Exception as exc:
+            self.last_reference_error = f"save calib envelope failed: {exc}"
+            return False
+
+    def save_background(self, sweep_for_ring: Optional[np.ndarray], path: Optional[str] = None) -> bool:
+        """Сохранить текущий свип (в текущем домене обработки) как .npy-фон."""
+        if sweep_for_ring is None:
+            return False
+        try:
+            bg = np.asarray(sweep_for_ring, dtype=np.float32).copy()
+            self.background_path = self._save_array(bg, self.background_path, path)
+            self.background = bg
+            self.background_raw_capture = None
+            self.background_source_type = "npy_processed"
+            self.background_reference_summary = _summary_for_npy(self.background_path)
+            self.last_reference_error = ""
+            return True
+        except Exception as exc:
+            self.last_reference_error = f"save background failed: {exc}"
+            return False
+
+    # ---- Загрузка эталонов (.npy или capture) ----
+    def _detect_source_kind(self, path: str, source_kind: str) -> Optional[str]:
+        sk = str(source_kind).strip().lower() or "auto"
+        if sk == "auto":
+            return detect_reference_file_format(path)
+        if sk in ("npy", "bin_capture", "capture"):
+            return "bin_capture" if sk == "capture" else sk
+        return None
+
+    def _load_npy_vector(self, path: str) -> np.ndarray:
+        arr = np.load(path)
+        return np.asarray(arr, dtype=np.float32).reshape(-1)
+
+    def load_calib_reference(
+        self,
+        path: Optional[str] = None,
+        *,
+        source_kind: str = "auto",
+        method: str = "median",
+    ) -> bool:
+        """Загрузить калибровку из .npy (огибающая) или raw capture файла."""
+        if path is not None:
+            self.set_calib_envelope_path(path)
+        p = self.calib_envelope_path
+        if not p or not os.path.isfile(p):
+            self.last_reference_error = f"Файл калибровки не найден: {p}"
+            return False
+
+        fmt = self._detect_source_kind(p, source_kind)
+        if fmt is None:
+            self.last_reference_error = f"Неизвестный формат файла калибровки: {p}"
+            return False
+
+        try:
+            if fmt == "npy":
+                env = self._load_npy_vector(p)
+                self.calib_file_envelope = env
+                self.calib_external_source_type = "npy"
+                self.calib_reference_summary = _summary_for_npy(p)
+                self.last_reference_error = ""
+                return True
+
+            sweeps = load_capture_sweeps(p, fancy=self.capture_fancy, logscale=self.capture_logscale)
+            vec, summary = aggregate_capture_reference(
+                sweeps,
+                channel=0,
+                method=method or self.reference_aggregation_method,
+                path=p,
+            )
+            _lower, upper = build_calib_envelopes(vec)
+            self.calib_file_envelope = np.asarray(upper, dtype=np.float32)
+            self.calib_external_source_type = "capture"
+            self.calib_reference_summary = summary
+            self.last_reference_error = ""
+            return True
+        except Exception as exc:
+            self.last_reference_error = f"Ошибка загрузки калибровки: {exc}"
+            return False
+
+    def load_background_reference(
+        self,
+        path: Optional[str] = None,
+        *,
+        source_kind: str = "auto",
+        method: str = "median",
+    ) -> bool:
+        """Загрузить фон из .npy (готовый домен) или raw capture файла."""
+        if path is not None:
+            self.set_background_path(path)
+        p = self.background_path
+        if not p or not os.path.isfile(p):
+            self.last_reference_error = f"Файл фона не найден: {p}"
+            return False
+
+        fmt = self._detect_source_kind(p, source_kind)
+        if fmt is None:
+            self.last_reference_error = f"Неизвестный формат файла фона: {p}"
+            return False
+
+        try:
+            if fmt == "npy":
+                bg = self._load_npy_vector(p)
+                self.background = bg
+                self.background_raw_capture = None
+                self.background_source_type = "npy_processed"
+                self.background_reference_summary = _summary_for_npy(p)
+                self.last_reference_error = ""
+                return True
+
+            sweeps = load_capture_sweeps(p, fancy=self.capture_fancy, logscale=self.capture_logscale)
+            vec, summary = aggregate_capture_reference(
+                sweeps,
+                channel=0,
+                method=method or self.reference_aggregation_method,
+                path=p,
+            )
+            self.background_raw_capture = np.asarray(vec, dtype=np.float32)
+            # Для UI/preview текущий background отражает текущий домен (пока raw по умолчанию).
+            self.background = self.background_raw_capture
+            self.background_source_type = "capture_raw"
+            self.background_reference_summary = summary
+            self.last_reference_error = ""
+            return True
+        except Exception as exc:
+            self.last_reference_error = f"Ошибка загрузки фона: {exc}"
+            return False
+
+    # Совместимые обертки для старого API (строго .npy)
+    def load_calib_envelope(self, path: Optional[str] = None) -> bool:
+        target = path if path is not None else self.calib_envelope_path
+        return self.load_calib_reference(target, source_kind="npy")
+
+    def load_background(self, path: Optional[str] = None) -> bool:
+        target = path if path is not None else self.background_path
+        return self.load_background_reference(target, source_kind="npy")
+
+    # ---- Нормировка / фон ----
+    def _normalize_against_active_reference(self, raw: np.ndarray) -> Tuple[Optional[np.ndarray], bool, str]:
+        if not self.calib_enabled:
+            return None, False, "off"
+
+        if self.calib_mode == "file":
+            if self.calib_file_envelope is None:
+                return None, False, "off"
+            src = "capture" if self.calib_external_source_type == "capture" else "npy"
+            return normalize_by_envelope(raw, self.calib_file_envelope), True, src
+
+        if self.last_calib_sweep is None:
+            return None, False, "off"
+        return normalize_by_calib(raw, self.last_calib_sweep, self.norm_type), True, "live"
+
+    def _transform_raw_background_for_current_domain(self, calib_applied: bool) -> Optional[np.ndarray]:
+        if self.background_raw_capture is None:
+            return None
+        if not calib_applied:
+            return self.background_raw_capture
+
+        # Порядок pipeline фиксирован: raw -> calibration -> background -> IFFT.
+        # Поэтому raw-фон из capture нужно привести в тот же домен, что и текущий sweep_for_ring.
+        if self.calib_mode == "file" and self.calib_file_envelope is not None:
+            return normalize_by_envelope(self.background_raw_capture, self.calib_file_envelope)
+        if self.calib_mode == "live" and self.last_calib_sweep is not None:
+            return normalize_by_calib(self.background_raw_capture, self.last_calib_sweep, self.norm_type)
+        return None
+
+    def _effective_background(self, calib_applied: bool) -> Tuple[Optional[np.ndarray], str]:
+        if self.background_source_type == "capture_raw":
+            bg = self._transform_raw_background_for_current_domain(calib_applied)
+            if bg is None:
+                return None, "capture(raw->calib:missing-calib)"
+            self.background = np.asarray(bg, dtype=np.float32)
+            return self.background, ("capture(raw->calib)" if calib_applied else "capture(raw)")
+        if self.background_source_type == "npy_processed" and self.background is not None:
+            return self.background, "npy"
+        if self.background is not None:
+            return self.background, "unknown"
+        return None, "off"
+
+    def _subtract_background(self, sweep: np.ndarray, calib_applied: bool) -> Tuple[np.ndarray, bool, str]:
+        if not self.background_enabled:
+            return sweep, False, "off"
+        bg, bg_src = self._effective_background(calib_applied)
+        if bg is None:
+            return sweep, False, f"{bg_src}:missing"
+        out = np.asarray(sweep, dtype=np.float32).copy()
+        w = min(out.size, bg.size)
+        if w > 0:
+            out[:w] -= bg[:w]
+        return out, True, bg_src
+
+    def process(self, sweep: np.ndarray, channel: int, update_references: bool = True) -> SweepProcessingResult:
+        """Применить к свипу калибровку/фон и вернуть явные этапы обработки."""
+        raw = np.asarray(sweep, dtype=np.float32)
+        ch = int(channel)
+
+        if ch == 0:
+            if update_references:
+                self.last_calib_sweep = raw
+                if self.auto_save_live_calib_envelope:
+                    self.save_calib_envelope()
+
+            # ch0 всегда остаётся live-калибровочной ссылкой (raw), но при file-калибровке
+            # можем применять её и к ch0 для отображения/обработки независимо от канала.
+            calib_applied = False
+            calib_source = "off"
+            normalized: Optional[np.ndarray] = None
+            if self.calib_enabled and self.calib_mode == "file":
+                normalized, calib_applied, calib_source = self._normalize_against_active_reference(raw)
+
+            base = normalized if normalized is not None else raw
+            processed, bg_applied, bg_source = self._subtract_background(base, calib_applied=calib_applied)
+
+            stages = ["parsed_sweep", "raw_sweep", "ch0_live_calibration_reference"]
+            stages.append(f"calibration_{calib_source}" if calib_applied else "calibration_off")
+            stages.append(f"background_{bg_source}" if bg_applied else "background_off")
+            stages.extend(["ring_buffer", "ifft_db"])
+
+            return SweepProcessingResult(
+                processed_sweep=processed,
+                normalized_sweep=normalized,
+                calibration_applied=calib_applied,
+                background_applied=bg_applied,
+                calibration_source=calib_source if calib_applied else "off",
+                background_source=bg_source if bg_applied else "off",
+                is_calibration_reference=True,
+                stage_trace=tuple(stages),
+            )
+
+        normalized, calib_applied, calib_source = self._normalize_against_active_reference(raw)
+        base = normalized if normalized is not None else raw
+        processed, bg_applied, bg_source = self._subtract_background(base, calib_applied)
+
+        stages = ["parsed_sweep", "raw_sweep"]
+        stages.append(f"calibration_{calib_source}" if calib_applied else "calibration_off")
+        stages.append(f"background_{bg_source}" if bg_applied else "background_off")
+        stages.extend(["ring_buffer", "ifft_db"])
+
+        return SweepProcessingResult(
+            processed_sweep=processed,
+            normalized_sweep=normalized,
+            calibration_applied=calib_applied,
+            background_applied=bg_applied,
+            calibration_source=calib_source if calib_applied else "off",
+            background_source=bg_source if bg_applied else "off",
+            is_calibration_reference=False,
+            stage_trace=tuple(stages),
+        )

rfg_adc_plotter/state/app_state.py

@@ -1,21 +1,20 @@
 """Состояние приложения: текущие свипы и настройки калибровки/нормировки."""
 
-import os
 from queue import Empty, Queue
-from typing import Any, Dict, Mapping, Optional
+from typing import Any, Mapping, Optional
 
 import numpy as np
 
-from rfg_adc_plotter.processing.normalizer import (
+from rfg_adc_plotter.processing.pipeline import (
-    build_calib_envelopes,
+    DEFAULT_BACKGROUND_PATH,
-    normalize_by_calib,
+    DEFAULT_CALIB_ENVELOPE_PATH,
-    normalize_by_envelope,
+    SweepPreprocessor,
 )
 from rfg_adc_plotter.state.ring_buffer import RingBuffer
 from rfg_adc_plotter.types import SweepInfo, SweepPacket
 
-CALIB_ENVELOPE_PATH = "calib_envelope.npy"
+CALIB_ENVELOPE_PATH = DEFAULT_CALIB_ENVELOPE_PATH
-BACKGROUND_PATH = "background.npy"
+BACKGROUND_PATH = DEFAULT_BACKGROUND_PATH
 
 
 def format_status(data: Mapping[str, Any]) -> str:
@@ -39,11 +38,7 @@ def format_status(data: Mapping[str, Any]) -> str:
 
 
 class AppState:
-    """Весь изменяемый GUI-state: текущие данные, калибровка, настройки.
+    """Весь изменяемый GUI-state: текущие данные + pipeline предобработки."""
-
-    Методы drain_queue и set_calib_enabled заменяют одноимённые closures
-    с nonlocal из оригинального кода.
-    """
 
     def __init__(self, norm_type: str = "projector"):
         self.current_sweep_pre_exp: Optional[np.ndarray] = None
@@ -51,115 +46,264 @@ class AppState:
         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
         self.current_info: Optional[SweepInfo] = None
-        self.calib_enabled: bool = False
+        self.norm_type: str = str(norm_type).strip().lower()
-        self.norm_type: str = norm_type
+        self.preprocessor = SweepPreprocessor(norm_type=self.norm_type)
-        # "live" — нормировка по текущему ch0-свипу; "file" — по огибающей из файла
-        self.calib_mode: str = "live"
-        self.calib_file_envelope: Optional[np.ndarray] = None
-        # Вычет фона
-        self.background: Optional[np.ndarray] = None
-        self.background_enabled: bool = False
         self._last_sweep_for_ring: Optional[np.ndarray] = None
+        self._last_stage_trace: tuple[str, ...] = tuple()
 
-    def _normalize(self, raw: np.ndarray, calib: np.ndarray) -> np.ndarray:
+    def configure_capture_import(self, *, fancy: Optional[bool] = None, logscale: Optional[bool] = None):
-        if self.calib_mode == "file" and self.calib_file_envelope is not None:
+        self.preprocessor.set_capture_parse_options(fancy=fancy, logscale=logscale)
-            return normalize_by_envelope(raw, self.calib_file_envelope)
-        return normalize_by_calib(raw, calib, self.norm_type)
 
-    def save_calib_envelope(self, path: str = CALIB_ENVELOPE_PATH) -> bool:
+    # ---- Свойства pipeline (для совместимости с GUI) ----
-        """Вычислить огибающую из last_calib_sweep и сохранить в файл.
+    @property
+    def calib_enabled(self) -> bool:
+        return self.preprocessor.calib_enabled
 
-        Возвращает True при успехе.
+    @property
-        """
+    def calib_mode(self) -> str:
-        if self.last_calib_sweep is None:
+        return self.preprocessor.calib_mode
-            return False
-        try:
-            _lower, upper = build_calib_envelopes(self.last_calib_sweep)
-            np.save(path, upper)
-            return True
-        except Exception as exc:
-            import sys
-            sys.stderr.write(f"[warn] Не удалось сохранить огибающую: {exc}\n")
-            return False
 
-    def load_calib_envelope(self, path: str = CALIB_ENVELOPE_PATH) -> bool:
+    @property
-        """Загрузить огибающую из файла.
+    def calib_file_envelope(self) -> Optional[np.ndarray]:
+        return self.preprocessor.calib_file_envelope
 
-        Возвращает True при успехе.
+    @property
-        """
+    def last_calib_sweep(self) -> Optional[np.ndarray]:
-        if not os.path.isfile(path):
+        return self.preprocessor.last_calib_sweep
-            return False
+
-        try:
+    @property
-            env = np.load(path)
+    def background(self) -> Optional[np.ndarray]:
-            self.calib_file_envelope = np.asarray(env, dtype=np.float32)
+        return self.preprocessor.background
-            return True
+
-        except Exception as exc:
+    @property
-            import sys
+    def background_enabled(self) -> bool:
-            sys.stderr.write(f"[warn] Не удалось загрузить огибающую: {exc}\n")
+        return self.preprocessor.background_enabled
-            return False
+
+    @property
+    def calib_source_type(self) -> str:
+        return self.preprocessor.calib_external_source_type
+
+    @property
+    def background_source_type(self) -> str:
+        return self.preprocessor.background_source_type
+
+    @property
+    def calib_reference_summary(self):
+        return self.preprocessor.calib_reference_summary
+
+    @property
+    def background_reference_summary(self):
+        return self.preprocessor.background_reference_summary
+
+    @property
+    def last_reference_error(self) -> str:
+        return self.preprocessor.last_reference_error
+
+    @property
+    def calib_envelope_path(self) -> str:
+        return self.preprocessor.calib_envelope_path
+
+    @property
+    def background_path(self) -> str:
+        return self.preprocessor.background_path
+
+    # ---- Управление файлами калибровки/фона ----
+    def set_calib_envelope_path(self, path: str):
+        self.preprocessor.set_calib_envelope_path(path)
+        self._refresh_current_processed()
+
+    def set_background_path(self, path: str):
+        self.preprocessor.set_background_path(path)
+        self._refresh_current_processed()
+
+    def has_calib_envelope_file(self) -> bool:
+        return self.preprocessor.has_calib_envelope_file()
+
+    def has_background_file(self) -> bool:
+        return self.preprocessor.has_background_file()
+
+    def save_calib_envelope(self, path: Optional[str] = None) -> bool:
+        return self.preprocessor.save_calib_envelope(path)
+
+    def load_calib_reference(self, path: Optional[str] = None) -> bool:
+        ok = self.preprocessor.load_calib_reference(path)
+        if ok:
+            self._refresh_current_processed()
+        return ok
+
+    def load_calib_envelope(self, path: Optional[str] = None) -> bool:
+        return self.load_calib_reference(path)
 
     def set_calib_mode(self, mode: str):
-        """Переключить режим калибровки: 'live' или 'file'."""
+        self.preprocessor.set_calib_mode(mode)
-        self.calib_mode = mode
+        self._refresh_current_processed()
 
-    def save_background(self, path: str = BACKGROUND_PATH) -> bool:
+    def save_background(self, path: Optional[str] = None) -> bool:
-        """Сохранить текущий sweep_for_ring как фоновый спектр.
+        return self.preprocessor.save_background(self._last_sweep_for_ring, path)
 
-        Сохраняет последний свип, который был записан в ринг-буфер
+    def load_background_reference(self, path: Optional[str] = None) -> bool:
-        (нормированный, если калибровка включена, иначе сырой).
+        ok = self.preprocessor.load_background_reference(path)
-        Возвращает True при успехе.
+        if ok:
-        """
+            self._refresh_current_processed()
-        if self._last_sweep_for_ring is None:
+        return ok
-            return False
-        try:
-            np.save(path, self._last_sweep_for_ring)
-            return True
-        except Exception as exc:
-            import sys
-            sys.stderr.write(f"[warn] Не удалось сохранить фон: {exc}\n")
-            return False
 
-    def load_background(self, path: str = BACKGROUND_PATH) -> bool:
+    def load_background(self, path: Optional[str] = None) -> bool:
-        """Загрузить фоновый спектр из файла.
+        return self.load_background_reference(path)
-
-        Возвращает True при успехе.
-        """
-        if not os.path.isfile(path):
-            return False
-        try:
-            bg = np.load(path)
-            self.background = np.asarray(bg, dtype=np.float32)
-            return True
-        except Exception as exc:
-            import sys
-            sys.stderr.write(f"[warn] Не удалось загрузить фон: {exc}\n")
-            return False
 
     def set_background_enabled(self, enabled: bool):
-        """Включить/выключить вычет фона."""
+        self.preprocessor.set_background_enabled(enabled)
-        self.background_enabled = enabled
+        self._refresh_current_processed()
 
     def set_calib_enabled(self, enabled: bool):
-        """Включить/выключить режим калибровки, пересчитать norm-свип."""
+        self.preprocessor.set_calib_enabled(enabled)
-        self.calib_enabled = enabled
+        self._refresh_current_processed()
-        if self.calib_enabled and self.current_sweep_raw is not None:
+
-            if self.calib_mode == "file" and self.calib_file_envelope is not None:
+    # ---- Вспомогательные методы для UI ----
-                self.current_sweep_norm = normalize_by_envelope(
+    def _current_channel(self) -> Optional[int]:
-                    self.current_sweep_raw, self.calib_file_envelope
+        if not isinstance(self.current_info, dict):
-                )
+            return None
-            elif self.calib_mode == "live" and self.last_calib_sweep is not None:
+        try:
-                self.current_sweep_norm = self._normalize(
+            return int(self.current_info.get("ch", 0))
-                    self.current_sweep_raw, self.last_calib_sweep
+        except Exception:
-                )
+            return 0
+
+    def _apply_result_to_current(self, result) -> None:
+        self._last_stage_trace = tuple(result.stage_trace)
+        if result.is_calibration_reference:
+            self.current_sweep_norm = None
+        elif result.calibration_applied or result.background_applied:
+            self.current_sweep_norm = result.processed_sweep
         else:
             self.current_sweep_norm = None
-        else:
+        self.current_sweep_processed = result.processed_sweep
+        self._last_sweep_for_ring = result.processed_sweep
+
+    def _refresh_current_processed(self):
+        if self.current_sweep_raw is None:
             self.current_sweep_norm = None
-        self.current_sweep_processed = (
+            self.current_sweep_processed = None
-            self.current_sweep_norm if self.current_sweep_norm is not None else self.current_sweep_raw
+            self._last_stage_trace = tuple()
+            return
+        ch = self._current_channel() or 0
+        result = self.preprocessor.process(self.current_sweep_raw, ch, update_references=False)
+        self._apply_result_to_current(result)
+
+    def format_pipeline_status(self) -> str:
+        """Краткое описание pipeline для UI: от распарсенного свипа до IFFT."""
+        ch = self._current_channel()
+        if ch is None:
+            ch_txt = "?"
+        else:
+            ch_txt = str(ch)
+
+        reader_stage = "log-exp" if self.current_sweep_pre_exp is not None else "linear"
+
+        if ch == 0:
+            file_calib_applies = (
+                self.calib_enabled
+                and self.calib_mode == "file"
+                and self.calib_file_envelope is not None
             )
+            if self.calib_enabled and self.calib_mode == "file":
+                calib_stage = self.format_calib_source_status()
+            else:
+                calib_stage = "calib[off]"
+
+            if not self.background_enabled:
+                bg_stage = "bg[off]"
+            elif self.background_source_type == "capture_raw":
+                if self.background is None:
+                    bg_stage = (
+                        "bg[capture(raw->calib):missing]"
+                        if file_calib_applies
+                        else "bg[capture(raw):missing]"
+                    )
+                else:
+                    bg_stage = "bg[capture(raw->calib)]" if file_calib_applies else "bg[capture(raw)]"
+            elif self.background_source_type == "npy_processed":
+                bg_stage = "bg[npy]" if self.background is not None else "bg[npy:missing]"
+            else:
+                bg_stage = "bg[sub]" if self.background is not None else "bg[missing]"
+            return (
+                f"pipeline ch{ch_txt}: parsed -> {reader_stage} -> raw -> "
+                f"live-calib-ref -> {calib_stage} -> {bg_stage} -> ring -> IFFT(dB)"
+            )
+
+        calib_stage = self.format_calib_source_status()
+        bg_stage = self.format_background_source_status()
+
+        return (
+            f"pipeline ch{ch_txt}: parsed -> {reader_stage} -> raw -> "
+            f"{calib_stage} -> {bg_stage} -> ring -> IFFT(dB)"
+        )
+
+    def _format_summary(self, summary) -> str:
+        if summary is None:
+            return ""
+        parts: list[str] = []
+        if getattr(summary, "sweeps_valid", 0) or getattr(summary, "sweeps_total", 0):
+            parts.append(f"valid:{summary.sweeps_valid}/{summary.sweeps_total}")
+        if getattr(summary, "dominant_width", None) is not None:
+            parts.append(f"w:{summary.dominant_width}")
+        chs = getattr(summary, "channels_seen", tuple())
+        if chs:
+            parts.append("chs:" + ",".join(str(v) for v in chs))
+        warns = getattr(summary, "warnings", tuple())
+        if warns:
+            parts.append(f"warn:{warns[0]}")
+        return " ".join(parts)
+
+    def format_calib_source_status(self) -> str:
+        if not self.calib_enabled:
+            return "calib[off]"
+        if self.calib_mode == "live":
+            return "calib[live]" if self.last_calib_sweep is not None else "calib[live:no-ref]"
+        if self.calib_file_envelope is None:
+            return "calib[file:missing]"
+        if self.calib_source_type == "capture":
+            return "calib[capture]"
+        if self.calib_source_type == "npy":
+            return "calib[npy]"
+        return "calib[file]"
+
+    def format_background_source_status(self) -> str:
+        if not self.background_enabled:
+            return "bg[off]"
+        src = self.background_source_type
+        if src == "capture_raw":
+            if self.calib_enabled:
+                can_map = (
+                    (self.calib_mode == "file" and self.calib_file_envelope is not None)
+                    or (self.calib_mode == "live" and self.last_calib_sweep is not None)
+                )
+                if not can_map:
+                    return "bg[capture(raw->calib):missing]"
+            if self.background is None:
+                return "bg[capture(raw->calib):missing]"
+            return "bg[capture(raw->calib)]" if self.calib_enabled else "bg[capture(raw)]"
+        if src == "npy_processed":
+            return "bg[npy]" if self.background is not None else "bg[npy:missing]"
+        if self.background is not None:
+            return "bg[sub]"
+        return "bg[missing]"
+
+    def format_reference_status(self) -> str:
+        parts: list[str] = []
+        calib_s = self._format_summary(self.calib_reference_summary)
+        if calib_s:
+            parts.append(f"calib[{calib_s}]")
+        bg_s = self._format_summary(self.background_reference_summary)
+        if bg_s:
+            parts.append(f"bg[{bg_s}]")
+        if self.last_reference_error:
+            parts.append(f"err:{self.last_reference_error}")
+        return " | ".join(parts)
+
+    def format_stage_trace(self) -> str:
+        if not self._last_stage_trace:
+            return ""
+        return " -> ".join(self._last_stage_trace)
 
     def drain_queue(self, q: "Queue[SweepPacket]", ring: RingBuffer) -> int:
         """Вытащить все ожидающие свипы из очереди, обновить state и ring.
@@ -173,49 +317,23 @@ class AppState:
             except Empty:
                 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:
                 ch = int(info.get("ch", 0)) if isinstance(info, dict) else 0
             except Exception:
                 ch = 0
 
-            # Канал 0 — опорный (калибровочный) свип
+            result = self.preprocessor.process(s, ch, update_references=True)
-            if ch == 0:
+            self._apply_result_to_current(result)
-                self.last_calib_sweep = s
-                self.save_calib_envelope()
-                self.current_sweep_norm = None
-                sweep_for_ring = s
-                self._last_sweep_for_ring = sweep_for_ring
-            else:
-                can_normalize = self.calib_enabled and (
-                    (self.calib_mode == "file" and self.calib_file_envelope is not None)
-                    or (self.calib_mode == "live" and self.last_calib_sweep is not None)
-                )
-                if can_normalize:
-                    calib_ref = self.last_calib_sweep if self.last_calib_sweep is not None else s
-                    self.current_sweep_norm = self._normalize(s, calib_ref)
-                    sweep_for_ring = self.current_sweep_norm
-                else:
-                    self.current_sweep_norm = None
-                    sweep_for_ring = s
 
-            # Вычет фона (в том же домене что и sweep_for_ring)
-            if self.background_enabled and self.background is not None and ch != 0:
-                w = min(sweep_for_ring.size, self.background.size)
-                sweep_for_ring = sweep_for_ring.copy()
-                sweep_for_ring[:w] -= self.background[:w]
-                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)
+            ring.push(result.processed_sweep)
         return drained
 
     def format_channel_label(self) -> str:

rfg_adc_plotter/state/ring_buffer.py

@@ -6,14 +6,10 @@ from typing import Optional, Tuple
 import numpy as np
 
 from rfg_adc_plotter.constants import (
-    FFT_LEN,
-    FREQ_SPAN_GHZ,
     IFFT_LEN,
-    SWEEP_LEN,
     WF_WIDTH,
-    ZEROS_LOW,
-    ZEROS_MID,
 )
+from rfg_adc_plotter.processing.fourier import build_ifft_time_axis_ns, compute_ifft_db_profile
 
 
 class RingBuffer:
@@ -51,10 +47,8 @@ class RingBuffer:
             self.ring = np.full((self.max_sweeps, self.width), np.nan, dtype=np.float32)
             self.ring_time = np.full((self.max_sweeps,), np.nan, dtype=np.float64)
             self.ring_fft = np.full((self.max_sweeps, self.fft_bins), np.nan, dtype=np.float32)
-            # Временная ось IFFT: шаг dt = 1/(FREQ_SPAN_GHZ*1e9), переведём в нс
+            # Временная ось IFFT вынесена в processing.fourier для явного pipeline.
-            self.fft_time_axis = (
+            self.fft_time_axis = build_ifft_time_axis_ns()
-                np.arange(IFFT_LEN, dtype=np.float64) / (FREQ_SPAN_GHZ * 1e9) * 1e9
-            ).astype(np.float32)
             self.head = 0
         # Обновляем x_shared если пришёл свип большего размера
         if self.x_shared is None or sweep_width > self.x_shared.size:
@@ -75,29 +69,7 @@ class RingBuffer:
         self._push_fft(s)
 
     def _push_fft(self, s: np.ndarray):
-        bins = self.ring_fft.shape[1]  # = IFFT_LEN = 1953
+        fft_row = compute_ifft_db_profile(s)
-        if s is None or s.size == 0:
-            fft_row = np.full((bins,), np.nan, dtype=np.float32)
-        else:
-            # 1. Взять первые SWEEP_LEN отсчётов (остаток — нули если свип короче)
-            sig = np.zeros(SWEEP_LEN, dtype=np.float32)
-            take = min(int(s.size), SWEEP_LEN)
-            seg = np.nan_to_num(s[:take], nan=0.0).astype(np.float32, copy=False)
-            sig[:take] = seg
-
-            # 2. Собрать двусторонний спектр:
-            #    [ZEROS_LOW нулей | ZEROS_MID нулей | SWEEP_LEN данных]
-            #    = [-14.3..-3.2 ГГц | -3.2..+3.2 ГГц | +3.2..+14.3 ГГц]
-            data = np.zeros(IFFT_LEN, dtype=np.complex64)
-            data[ZEROS_LOW + ZEROS_MID:] = sig
-
-            # 3. ifftshift + ifft → временной профиль
-            spec = np.fft.ifftshift(data)
-            result = np.fft.ifft(spec)
-
-            # 4. Амплитуда в дБ
-            mag = np.abs(result).astype(np.float32)
-            fft_row = (20.0 * np.log10(mag + 1e-9)).astype(np.float32)
 
         prev_head = (self.head - 1) % self.ring_fft.shape[0]
         self.ring_fft[prev_head, :] = fft_row

tests/test_capture_reference_loader.py

@@ -0,0 +1,84 @@
+from pathlib import Path
+
+import numpy as np
+
+from rfg_adc_plotter.io.capture_reference_loader import (
+    aggregate_capture_reference,
+    detect_reference_file_format,
+    load_capture_sweeps,
+)
+from rfg_adc_plotter.processing.pipeline import SweepPreprocessor
+
+
+ROOT = Path(__file__).resolve().parents[1]
+SAMPLE_BG = ROOT / "sample_data" / "empty"
+SAMPLE_CALIB = ROOT / "sample_data" / "no_antennas_35dB_attenuators"
+
+
+def test_detect_reference_file_format_for_sample_capture():
+    assert detect_reference_file_format(str(SAMPLE_BG)) == "bin_capture"
+    assert detect_reference_file_format(str(SAMPLE_CALIB)) == "bin_capture"
+
+
+def test_load_capture_sweeps_parses_binary_capture():
+    sweeps = load_capture_sweeps(str(SAMPLE_BG), fancy=False, logscale=False)
+    assert len(sweeps) > 100
+    sweep0, info0 = sweeps[0]
+    assert isinstance(sweep0, np.ndarray)
+    assert "ch" in info0
+    channels = set()
+    for _s, info in sweeps:
+        chs = info.get("chs", [info.get("ch", 0)])
+        channels.update(int(v) for v in chs)
+    assert channels == {0}
+
+
+def test_aggregate_capture_reference_filters_incomplete_sweeps():
+    sweeps = load_capture_sweeps(str(SAMPLE_BG), fancy=False, logscale=False)
+    vector, summary = aggregate_capture_reference(sweeps, channel=0, method="median", path=str(SAMPLE_BG))
+    assert isinstance(vector, np.ndarray)
+    assert vector.dtype == np.float32
+    assert summary.sweeps_total == len(sweeps)
+    assert summary.sweeps_valid > 0
+    assert summary.sweeps_valid < summary.sweeps_total
+    assert summary.dominant_width in (759, 758)  # sample_data starts at x=1..758 => width=759
+
+
+def test_preprocessor_can_load_capture_calib_and_background_and_apply():
+    p = SweepPreprocessor(norm_type="projector", auto_save_live_calib_envelope=False)
+    p.set_capture_parse_options(fancy=False, logscale=False)
+
+    assert p.load_calib_reference(str(SAMPLE_CALIB))
+    p.set_calib_mode("file")
+    p.set_calib_enabled(True)
+    assert p.calib_file_envelope is not None
+    assert p.calib_external_source_type == "capture"
+
+    assert p.load_background_reference(str(SAMPLE_BG))
+    p.set_background_enabled(True)
+    assert p.background_source_type == "capture_raw"
+
+    n = min(758, int(p.calib_file_envelope.size))
+    sweep = np.linspace(-100.0, 100.0, n, dtype=np.float32)
+    res = p.process(sweep, channel=1, update_references=False)
+    assert res.calibration_applied is True
+    assert res.background_applied is True
+    assert res.calibration_source == "capture"
+    assert "background_capture(raw->calib)" in res.stage_trace
+
+
+def test_preprocessor_applies_background_for_ch0_reference_too():
+    p = SweepPreprocessor(norm_type="projector", auto_save_live_calib_envelope=False)
+    p.set_capture_parse_options(fancy=False, logscale=False)
+    assert p.load_background_reference(str(SAMPLE_BG))
+    p.set_background_enabled(True)
+
+    n = min(758, int(p.background.size)) if p.background is not None else 758
+    raw = np.linspace(-10.0, 10.0, n, dtype=np.float32)
+    res = p.process(raw, channel=0, update_references=True)
+
+    assert res.is_calibration_reference is True
+    assert res.background_applied is True
+    assert np.any(np.abs(res.processed_sweep - raw) > 0)
+    assert p.last_calib_sweep is not None
+    assert np.allclose(p.last_calib_sweep[:n], raw[:n], equal_nan=True)