ampl parser

.gitignore

@@ -0,0 +1,8 @@
+.venv/
+env/
+__pycache__/
+*.py[cod]
+.pytest_cache/
+.Python
+my_picocom_logfile.txt
+sample_data/

README.md

@@ -0,0 +1,205 @@
+# RFG STM32 ADC Receiver GUI
+
+PyQtGraph-приложение для чтения свипов из последовательного порта и отображения:
+
+- текущего свипа
+- водопада по свипам
+- FFT текущего свипа
+- B-scan по FFT
+
+После рефакторинга проект разделен на пакет `rfg_adc_plotter`. Старый запуск через `RFG_ADC_dataplotter.py` сохранен как совместимый wrapper.
+
+## Структура
+
+- `RFG_ADC_dataplotter.py` — совместимый entrypoint
+- `rfg_adc_plotter/cli.py` — CLI-аргументы
+- `rfg_adc_plotter/io/` — чтение порта и парсеры протоколов
+- `rfg_adc_plotter/processing/` — FFT, нормировка, калибровка, поиск пиков
+- `rfg_adc_plotter/state/` — runtime state и кольцевые буферы
+- `rfg_adc_plotter/gui/pyqtgraph_backend.py` — GUI на PyQtGraph
+- `replay_pty.py` — воспроизведение захвата через виртуальный PTY
+
+## Зависимости
+
+Минимально нужны:
+
+```bash
+python3 -m venv .venv
+. .venv/bin/activate
+pip install numpy pyqtgraph PyQt5
+```
+
+Если `pyserial` не установлен, приложение попробует открыть порт через raw TTY.
+
+## Быстрый старт
+
+Запуск через старый entrypoint:
+
+```bash
+.venv/bin/python RFG_ADC_dataplotter.py /dev/ttyACM0
+```
+
+Запуск напрямую через пакет:
+
+```bash
+.venv/bin/python -m rfg_adc_plotter.main /dev/ttyACM0
+```
+
+Показать справку:
+
+```bash
+.venv/bin/python RFG_ADC_dataplotter.py --help
+```
+
+## Примеры запуска
+
+Обычный запуск с живого порта:
+
+```bash
+.venv/bin/python -m rfg_adc_plotter.main /dev/ttyACM0 --baud 115200
+```
+
+Больше истории в водопаде и ограничение FPS:
+
+```bash
+.venv/bin/python -m rfg_adc_plotter.main /dev/ttyACM0 --max-sweeps 400 --max-fps 20
+```
+
+Фиксированный диапазон по оси Y:
+
+```bash
+.venv/bin/python -m rfg_adc_plotter.main /dev/ttyACM0 --ylim -1000,1000
+```
+
+С включенной нормировкой `simple`:
+
+```bash
+.venv/bin/python -m rfg_adc_plotter.main /dev/ttyACM0 --norm-type simple
+```
+
+Режим измерения ширины главного пика FFT:
+
+```bash
+.venv/bin/python -m rfg_adc_plotter.main /dev/ttyACM0 --calibrate
+```
+
+Поиск топ-3 пиков относительно rolling median reference:
+
+```bash
+.venv/bin/python -m rfg_adc_plotter.main /dev/ttyACM0 --peak_search --peak_ref_window 1.5
+```
+
+Вычитание среднего спектра по последним секундам:
+
+```bash
+.venv/bin/python -m rfg_adc_plotter.main /dev/ttyACM0 --spec-mean-sec 3
+```
+
+## Протоколы ввода
+
+ASCII-протокол по умолчанию:
+
+```bash
+.venv/bin/python -m rfg_adc_plotter.main /dev/ttyACM0
+```
+
+Legacy binary:
+
+```bash
+.venv/bin/python -m rfg_adc_plotter.main /dev/ttyACM0 --bin
+```
+
+`--bin` понимает mixed 8-байтный поток:
+- `0x000A,step,ch1_i16,ch2_i16` для CH1/CH2 из `kamil_adc` (`tty:/tmp/ttyADC_data`)
+- `0x001A,step,data_i16,0x0000` для логарифмического детектора
+
+Для `0x000A` сырая кривая строится как `ch1^2 + ch2^2`, а FFT рассчитывается от комплексного сигнала `ch1 + i*ch2`.
+Для `0x001A` signed `data_i16` сначала переводится в В, затем raw отображается как `V`, а FFT рассчитывается от `exp(V)`.
+Параметр `--tty-range-v` применяется к обоим типам `--bin`-данных.
+
+Logscale binary с парой `int32`:
+
+```bash
+.venv/bin/python -m rfg_adc_plotter.main /dev/ttyACM0 --logscale
+```
+
+Complex binary `16-bit x2`:
+
+```bash
+.venv/bin/python -m rfg_adc_plotter.main /dev/ttyACM0 --parser_16_bit_x2
+```
+
+Тестовый парсер для экспериментального `16-bit x2` потока:
+
+```bash
+.venv/bin/python -m rfg_adc_plotter.main /dev/ttyACM0 --parser_test
+```
+
+Комплексный ASCII-поток `step real imag`:
+
+```bash
+.venv/bin/python -m rfg_adc_plotter.main /dev/ttyACM0 --parser_complex_ascii
+```
+
+## Локальная проверка через replay_pty
+
+Если есть лог-файл захвата, его можно воспроизвести как виртуальный последовательный порт.
+
+В первом терминале:
+
+```bash
+.venv/bin/python replay_pty.py my_picocom_logfile.txt --pty /tmp/ttyVIRT0 --speed 1.0
+```
+
+Во втором терминале:
+
+```bash
+.venv/bin/python -m rfg_adc_plotter.main /tmp/ttyVIRT0
+```
+
+Максимально быстрый replay:
+
+```bash
+.venv/bin/python replay_pty.py my_picocom_logfile.txt --pty /tmp/ttyVIRT0 --speed 0
+```
+
+## Удаленный захват по SSH
+
+В приложении SSH-источник не встроен. Для удаленной проверки нужно сначала получить поток или лог на локальную машину, а затем либо:
+
+- запускать GUI напрямую на локальном PTY
+- сохранять поток в файл и воспроизводить его через `replay_pty.py`
+
+Пример команды для ручной диагностики удаленного устройства:
+
+```bash
+ssh 192.148.0.148 'ls -l /dev/ttyACM0'
+```
+
+Если на удаленной машине есть доступ к потоку, удобнее сохранять его в файл и уже этот файл гонять локально через `replay_pty.py`.
+
+Для локального `tty`-потока из `kamil_adc` используйте:
+
+```bash
+.venv/bin/python -m rfg_adc_plotter.main /tmp/ttyADC_data --bin
+```
+
+## Проверка и тесты
+
+Синтаксическая проверка:
+
+```bash
+python3 -m compileall RFG_ADC_dataplotter.py replay_pty.py rfg_adc_plotter tests
+```
+
+Запуск тестов:
+
+```bash
+.venv/bin/python -m unittest discover -s tests -v
+```
+
+## Замечания
+
+- Поддерживается только PyQtGraph backend.
+- `--backend mpl` оставлен только для совместимости CLI и завершится ошибкой.
+- Каталоги `sample_data/` и локальные логи добавлены в `.gitignore` и не считаются частью обязательного tracked-состояния репозитория.

replay_pty.py

@@ -0,0 +1,94 @@
+#!/usr/bin/env python3
+"""Replay a capture file through a pseudo-TTY for local GUI verification."""
+
+from __future__ import annotations
+
+import argparse
+import os
+import sys
+import time
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(
+        description="Воспроизводит лог-файл через PTY как виртуальный серийный порт."
+    )
+    parser.add_argument("file", help="Путь к лог-файлу (например my_picocom_logfile.txt)")
+    parser.add_argument(
+        "--pty",
+        default="/tmp/ttyVIRT0",
+        help="Путь симлинка PTY (по умолчанию /tmp/ttyVIRT0)",
+    )
+    parser.add_argument(
+        "--speed",
+        type=float,
+        default=1.0,
+        help=(
+            "Множитель скорости воспроизведения: "
+            "1.0 = реальное время при --baud, "
+            "2.0 = вдвое быстрее, "
+            "0 = максимально быстро"
+        ),
+    )
+    parser.add_argument(
+        "--baud",
+        type=int,
+        default=115200,
+        help="Скорость (бод) для расчета задержек (по умолчанию 115200)",
+    )
+    args = parser.parse_args()
+
+    if not os.path.isfile(args.file):
+        sys.stderr.write(f"[error] Файл не найден: {args.file}\n")
+        raise SystemExit(1)
+
+    master_fd, slave_fd = os.openpty()
+    slave_path = os.ttyname(slave_fd)
+    os.close(slave_fd)
+
+    try:
+        os.unlink(args.pty)
+    except FileNotFoundError:
+        pass
+    os.symlink(slave_path, args.pty)
+
+    print(f"PTY slave : {slave_path}")
+    print(f"Симлинк   : {args.pty}  ->  {slave_path}")
+    print(f"Запустите : python3 -m rfg_adc_plotter.main {args.pty}")
+    print("Ctrl+C для остановки.\n")
+
+    if args.speed > 0:
+        bytes_per_sec = args.baud / 10.0 * args.speed
+        delay_per_byte = 1.0 / bytes_per_sec
+    else:
+        delay_per_byte = 0.0
+
+    chunk_size = 4096
+    loop = 0
+    try:
+        while True:
+            loop += 1
+            print(f"[loop {loop}] {args.file}")
+            with open(args.file, "rb") as handle:
+                while True:
+                    chunk = handle.read(chunk_size)
+                    if not chunk:
+                        break
+                    os.write(master_fd, chunk)
+                    if delay_per_byte > 0:
+                        time.sleep(delay_per_byte * len(chunk))
+    except KeyboardInterrupt:
+        print("\nОстановлено.")
+    finally:
+        try:
+            os.unlink(args.pty)
+        except Exception:
+            pass
+        try:
+            os.close(master_fd)
+        except Exception:
+            pass
+
+
+if __name__ == "__main__":
+    main()

rfg_adc_plotter/__init__.py

@@ -0,0 +1,3 @@
+"""RFG ADC plotter package."""
+
+__all__ = []

rfg_adc_plotter/cli.py

@@ -0,0 +1,145 @@
+"""Command-line parser for the ADC plotter."""
+
+from __future__ import annotations
+
+import argparse
+
+
+def build_parser() -> argparse.ArgumentParser:
+    parser = argparse.ArgumentParser(
+        description=(
+            "Читает свипы из виртуального COM-порта и рисует: "
+            "последний свип и водопад (реалтайм)."
+        )
+    )
+    parser.add_argument(
+        "port",
+        help="Путь к порту, например /dev/ttyACM1 или COM3 (COM10+: \\\\.\\COM10)",
+    )
+    parser.add_argument("--baud", type=int, default=115200, help="Скорость (по умолчанию 115200)")
+    parser.add_argument("--max-sweeps", type=int, default=200, help="Количество видимых свипов в водопаде")
+    parser.add_argument("--max-fps", type=float, default=30.0, help="Лимит частоты отрисовки, кадров/с")
+    parser.add_argument("--cmap", default="viridis", help="Цветовая карта водопада")
+    parser.add_argument(
+        "--spec-clip",
+        default="2,98",
+        help=(
+            "Процентильная обрезка уровней водопада спектров, %% (min,max). "
+            "Напр. 2,98. 'off' — отключить"
+        ),
+    )
+    parser.add_argument(
+        "--spec-mean-sec",
+        type=float,
+        default=0.0,
+        help=(
+            "Вычитание среднего по каждой частоте за последние N секунд "
+            "в водопаде спектров (0 — отключить)"
+        ),
+    )
+    parser.add_argument("--title", default="ADC Sweeps", help="Заголовок окна")
+    parser.add_argument(
+        "--fancy",
+        action="store_true",
+        help="Заполнять выпавшие точки средними значениями между соседними",
+    )
+    parser.add_argument(
+        "--ylim",
+        type=str,
+        default=None,
+        help="Фиксированные Y-пределы для кривой формата min,max (например -1000,1000). По умолчанию авто",
+    )
+    parser.add_argument(
+        "--backend",
+        choices=["auto", "pg", "mpl"],
+        default="pg",
+        help="Совместимый флаг. Поддерживаются только auto и pg; mpl удален.",
+    )
+    parser.add_argument(
+        "--opengl",
+        action="store_true",
+        help="Включить OpenGL-ускорение для PyQtGraph. По умолчанию используется CPU-отрисовка.",
+    )
+    parser.add_argument(
+        "--norm-type",
+        choices=["projector", "simple"],
+        default="projector",
+        help="Тип нормировки: projector (по огибающим в [-1,+1]) или simple (raw/calib)",
+    )
+    parser.add_argument(
+        "--bin",
+        dest="bin_mode",
+        action="store_true",
+        help=(
+            "8-байтный бинарный протокол: либо legacy старт "
+            "0xFFFF,0xFFFF,0xFFFF,(CH<<8)|0x0A и точки step,uint32(hi16,lo16),0x000A, "
+            "либо mixed поток 0x000A,step,ch1_i16,ch2_i16 и 0x001A,step,data_i16,0x0000. "
+            "Для 0x000A: после парсинга int16 переводятся в В, "
+            "сырая кривая = ch1^2+ch2^2 (В^2), FFT вход = ch1+i*ch2 (В). "
+            "Для 0x001A: code_i16 переводится в В, raw = V, FFT вход = exp(V)"
+        ),
+    )
+    parser.add_argument(
+        "--tty-range-v",
+        type=float,
+        default=5.0,
+        help=(
+            "Полный диапазон для пересчета tty int16 в напряжение ±V "
+            "(для --bin 0x000A CH1/CH2 и 0x001A log-detector, по умолчанию 5.0)"
+        ),
+    )
+    parser.add_argument(
+        "--logscale",
+        action="store_true",
+        help=(
+            "Новый бинарный протокол: точка несет пару int32 (avg_1, avg_2), "
+            "а свип считается как |10**(avg_1*0.001) - 10**(avg_2*0.001)|"
+        ),
+    )
+    parser.add_argument(
+        "--parser_16_bit_x2",
+        action="store_true",
+        help=(
+            "Бинарный complex-протокол c парой int16 (Re, Im): "
+            "старт 0xFFFF,0xFFFF,0xFFFF,(CH<<8)|0x0A; точка step,re_lo16,im_lo16,0xFFFF"
+        ),
+    )
+    parser.add_argument(
+        "--parser_test",
+        action="store_true",
+        help=(
+            "Тестовый парсер для complex-формата 16-bit x2: "
+            "одиночный 0xFFFF завершает точку, серия 0xFFFF начинает новый свип"
+        ),
+    )
+    parser.add_argument(
+        "--parser_complex_ascii",
+        action="store_true",
+        help=(
+            "ASCII-поток из трех чисел на строку: step real imag. "
+            "Новый свип определяется по сбросу/повтору step, FFT строится по комплексным данным"
+        ),
+    )
+    parser.add_argument(
+        "--calibrate",
+        action="store_true",
+        help=(
+            "Режим измерения ширины главного пика FFT: рисует красные маркеры "
+            "границ и фона и выводит ширину пика в статус"
+        ),
+    )
+    parser.add_argument(
+        "--peak_search",
+        action="store_true",
+        help=(
+            "Поиск топ-3 пиков на FFT относительно референса (скользящая медиана) "
+            "с отрисовкой bounding box и параметров пиков"
+        ),
+    )
+    parser.add_argument(
+        "--peak_ref_window",
+        type=float,
+        default=1.0,
+        help="Ширина окна скользящей медианы для --peak_search, ГГц/м по оси FFT (по умолчанию 1.0)",
+    )
+    return parser

rfg_adc_plotter/constants.py

@@ -0,0 +1,17 @@
+"""Shared constants for sweep parsing and visualization."""
+
+WF_WIDTH = 1000
+FFT_LEN = 2048
+BACKGROUND_MEDIAN_SWEEPS = 64
+
+SWEEP_FREQ_MIN_GHZ = 3.3
+SWEEP_FREQ_MAX_GHZ = 6.3
+
+LOG_BASE = 10.0
+LOG_SCALER = 0.001
+LOG_POSTSCALER = 10.0
+LOG_EXP_LIMIT = 300.0
+
+C_M_S = 299_792_458.0
+
+DATA_INVERSION_THRESHOLD = 10.0

rfg_adc_plotter/gui/__init__.py

@@ -0,0 +1,5 @@
+"""GUI backends."""
+
+from rfg_adc_plotter.gui.pyqtgraph_backend import run_pyqtgraph
+
+__all__ = ["run_pyqtgraph"]

rfg_adc_plotter/io/__init__.py

@@ -0,0 +1,6 @@
+"""I/O helpers for serial sources and sweep parsing."""
+
+from rfg_adc_plotter.io.serial_source import SerialChunkReader, SerialLineSource
+from rfg_adc_plotter.io.sweep_reader import SweepReader
+
+__all__ = ["SerialChunkReader", "SerialLineSource", "SweepReader"]

rfg_adc_plotter/io/serial_source.py

@@ -0,0 +1,177 @@
+"""Serial input helpers with pyserial and raw TTY fallbacks."""
+
+from __future__ import annotations
+
+import io
+import os
+import sys
+from typing import Optional
+
+
+def try_open_pyserial(path: str, baud: int, timeout: float):
+    try:
+        import serial  # type: ignore
+    except Exception:
+        return None
+    try:
+        return serial.Serial(path, baudrate=baud, timeout=timeout)
+    except Exception:
+        return None
+
+
+class FDReader:
+    """Buffered wrapper around a raw TTY file descriptor."""
+
+    def __init__(self, fd: int):
+        self._fd = fd
+        raw = os.fdopen(fd, "rb", closefd=False)
+        self._file = raw
+        self._buf = io.BufferedReader(raw, buffer_size=65536)
+
+    def fileno(self) -> int:
+        return self._fd
+
+    def readline(self) -> bytes:
+        return self._buf.readline()
+
+    def close(self) -> None:
+        try:
+            self._buf.close()
+        except Exception:
+            pass
+
+
+def open_raw_tty(path: str, baud: int) -> Optional[FDReader]:
+    """Open a TTY without pyserial and configure it via termios."""
+    try:
+        import termios
+        import tty
+    except Exception:
+        return None
+
+    try:
+        fd = os.open(path, os.O_RDONLY | os.O_NOCTTY)
+    except Exception:
+        return None
+
+    try:
+        attrs = termios.tcgetattr(fd)
+        tty.setraw(fd)
+
+        baud_map = {
+            9600: termios.B9600,
+            19200: termios.B19200,
+            38400: termios.B38400,
+            57600: termios.B57600,
+            115200: termios.B115200,
+            230400: getattr(termios, "B230400", None),
+            460800: getattr(termios, "B460800", None),
+        }
+        speed = baud_map.get(baud) or termios.B115200
+
+        attrs[4] = speed
+        attrs[5] = speed
+        cc = attrs[6]
+        cc[termios.VMIN] = 1
+        cc[termios.VTIME] = 0
+        attrs[6] = cc
+        termios.tcsetattr(fd, termios.TCSANOW, attrs)
+    except Exception:
+        try:
+            os.close(fd)
+        except Exception:
+            pass
+        return None
+
+    return FDReader(fd)
+
+
+class SerialLineSource:
+    """Unified line-oriented wrapper for pyserial and raw TTY readers."""
+
+    def __init__(self, path: str, baud: int, timeout: float = 1.0):
+        self._pyserial = try_open_pyserial(path, baud, timeout)
+        self._fdreader: Optional[FDReader] = None
+        self._using = "pyserial" if self._pyserial is not None else "raw"
+        if self._pyserial is None:
+            self._fdreader = open_raw_tty(path, baud)
+            if self._fdreader is None:
+                msg = f"Не удалось открыть порт '{path}' (pyserial и raw TTY не сработали)"
+                if sys.platform.startswith("win"):
+                    msg += ". На Windows нужен pyserial: pip install pyserial"
+                raise RuntimeError(msg)
+
+    def readline(self) -> bytes:
+        if self._pyserial is not None:
+            try:
+                return self._pyserial.readline()
+            except Exception:
+                return b""
+        try:
+            return self._fdreader.readline()  # type: ignore[union-attr]
+        except Exception:
+            return b""
+
+    def close(self) -> None:
+        try:
+            if self._pyserial is not None:
+                self._pyserial.close()
+            elif self._fdreader is not None:
+                self._fdreader.close()
+        except Exception:
+            pass
+
+
+class SerialChunkReader:
+    """Fast non-blocking chunk reader for serial sources."""
+
+    def __init__(self, src: SerialLineSource):
+        self._src = src
+        self._ser = src._pyserial
+        self._fd: Optional[int] = None
+        if self._ser is not None:
+            try:
+                self._ser.timeout = 0
+            except Exception:
+                pass
+        else:
+            try:
+                self._fd = src._fdreader.fileno()  # type: ignore[union-attr]
+                try:
+                    os.set_blocking(self._fd, False)
+                except Exception:
+                    pass
+            except Exception:
+                self._fd = None
+
+    def read_available(self) -> bytes:
+        """Return currently available bytes or b"" when nothing is ready."""
+        if self._ser is not None:
+            try:
+                available = int(getattr(self._ser, "in_waiting", 0))
+            except Exception:
+                available = 0
+            if available > 0:
+                try:
+                    return self._ser.read(available)
+                except Exception:
+                    return b""
+            return b""
+
+        if self._fd is None:
+            return b""
+
+        out = bytearray()
+        while True:
+            try:
+                chunk = os.read(self._fd, 65536)
+                if not chunk:
+                    break
+                out += chunk
+                if len(chunk) < 65536:
+                    break
+            except BlockingIOError:
+                break
+            except Exception:
+                break
+        return bytes(out)

rfg_adc_plotter/io/sweep_parser_core.py

@@ -0,0 +1,673 @@
+"""Reusable sweep parsers and sweep assembly helpers."""
+
+from __future__ import annotations
+
+import math
+import time
+from collections import deque
+from typing import List, Optional, Sequence, Set
+
+import numpy as np
+
+from rfg_adc_plotter.constants import DATA_INVERSION_THRESHOLD, LOG_BASE, LOG_EXP_LIMIT, LOG_POSTSCALER, LOG_SCALER
+from rfg_adc_plotter.types import (
+    ParserEvent,
+    PointEvent,
+    SignalKind,
+    StartEvent,
+    SweepAuxCurves,
+    SweepInfo,
+    SweepPacket,
+)
+
+
+def u32_to_i32(value: int) -> int:
+    return value - 0x1_0000_0000 if (value & 0x8000_0000) else value
+
+
+def u16_to_i16(value: int) -> int:
+    return value - 0x1_0000 if (value & 0x8000) else value
+
+
+def log_value_to_linear(value: int) -> float:
+    exponent = max(-LOG_EXP_LIMIT, min(LOG_EXP_LIMIT, float(value) * LOG_SCALER))
+    return float(LOG_BASE ** exponent)
+
+
+def log_pair_to_sweep(avg_1: int, avg_2: int) -> float:
+    value_1 = log_value_to_linear(avg_1)
+    value_2 = log_value_to_linear(avg_2)
+    return abs(value_1 - value_2) * LOG_POSTSCALER
+
+
+def tty_ch_pair_to_sweep(ch_1: int, ch_2: int) -> float:
+    """Reduce a raw CH1/CH2 TTY point to power-like scalar ``ch1^2 + ch2^2``."""
+    ch_1_i = int(ch_1)
+    ch_2_i = int(ch_2)
+    return float((ch_1_i * ch_1_i) + (ch_2_i * ch_2_i))
+
+
+class AsciiSweepParser:
+    """Incremental parser for ASCII sweep streams."""
+
+    def __init__(self):
+        self._buf = bytearray()
+
+    def feed(self, data: bytes) -> List[ParserEvent]:
+        if data:
+            self._buf += data
+        events: List[ParserEvent] = []
+        while True:
+            nl = self._buf.find(b"\n")
+            if nl == -1:
+                break
+            line = bytes(self._buf[:nl])
+            del self._buf[: nl + 1]
+            if line.endswith(b"\r"):
+                line = line[:-1]
+            if not line:
+                continue
+            if line.startswith(b"Sweep_start"):
+                events.append(StartEvent())
+                continue
+
+            parts = line.split()
+            if len(parts) < 3:
+                continue
+            head = parts[0].lower()
+            try:
+                if head == b"s":
+                    if len(parts) >= 4:
+                        ch = int(parts[1], 10)
+                        x = int(parts[2], 10)
+                        y = int(parts[3], 10)
+                    else:
+                        ch = 0
+                        x = int(parts[1], 10)
+                        y = int(parts[2], 10)
+                elif head.startswith(b"s"):
+                    ch = int(head[1:], 10)
+                    x = int(parts[1], 10)
+                    y = int(parts[2], 10)
+                else:
+                    continue
+            except Exception:
+                continue
+            events.append(PointEvent(ch=int(ch), x=int(x), y=float(y)))
+        return events
+
+
+class ComplexAsciiSweepParser:
+    """Incremental parser for ASCII ``step real imag`` streams."""
+
+    def __init__(self):
+        self._buf = bytearray()
+        self._last_step: Optional[int] = None
+        self._seen_points = False
+
+    def feed(self, data: bytes) -> List[ParserEvent]:
+        if data:
+            self._buf += data
+        events: List[ParserEvent] = []
+        while True:
+            nl = self._buf.find(b"\n")
+            if nl == -1:
+                break
+            line = bytes(self._buf[:nl])
+            del self._buf[: nl + 1]
+            if line.endswith(b"\r"):
+                line = line[:-1]
+            if not line:
+                continue
+
+            if line.lower().startswith(b"sweep_start"):
+                self._last_step = None
+                self._seen_points = False
+                events.append(StartEvent())
+                continue
+
+            parts = line.split()
+            if len(parts) < 3:
+                continue
+            try:
+                step = int(parts[0], 10)
+                real = float(parts[1])
+                imag = float(parts[2])
+            except Exception:
+                continue
+            if step < 0 or (not math.isfinite(real)) or (not math.isfinite(imag)):
+                continue
+
+            if self._seen_points and self._last_step is not None and step <= self._last_step:
+                events.append(StartEvent())
+            self._seen_points = True
+            self._last_step = step
+            events.append(
+                PointEvent(
+                    ch=0,
+                    x=step,
+                    y=float(abs(complex(real, imag))),
+                    aux=(float(real), float(imag)),
+                )
+            )
+        return events
+
+
+class LegacyBinaryParser:
+    """Byte-resynchronizing parser for supported 8-byte binary record formats."""
+
+    def __init__(self):
+        self._buf = bytearray()
+        self._last_step: Optional[int] = None
+        self._seen_points = False
+        self._mode: Optional[str] = None
+        self._current_signal_kind: Optional[SignalKind] = None
+
+    @staticmethod
+    def _u16_at(buf: bytearray, offset: int) -> int:
+        return int(buf[offset]) | (int(buf[offset + 1]) << 8)
+
+    def _emit_legacy_start(self, events: List[ParserEvent], ch: int) -> None:
+        self._mode = "legacy"
+        self._last_step = None
+        self._seen_points = False
+        self._current_signal_kind = None
+        events.append(StartEvent(ch=int(ch)))
+
+    def _emit_bin_start(self, events: List[ParserEvent], signal_kind: SignalKind) -> None:
+        self._mode = "bin"
+        self._last_step = None
+        self._seen_points = False
+        self._current_signal_kind = signal_kind
+        events.append(StartEvent(ch=0, signal_kind=signal_kind))
+
+    def _emit_tty_start(self, events: List[ParserEvent]) -> None:
+        self._emit_bin_start(events, signal_kind="bin_iq")
+
+    def _emit_legacy_point(self, events: List[ParserEvent], step: int, value_word_hi: int, value_word_lo: int, ch: int) -> None:
+        self._mode = "legacy"
+        self._current_signal_kind = None
+        if self._seen_points and self._last_step is not None and step <= self._last_step:
+            events.append(StartEvent(ch=int(ch)))
+        self._seen_points = True
+        self._last_step = int(step)
+        value = u32_to_i32((int(value_word_hi) << 16) | int(value_word_lo))
+        events.append(PointEvent(ch=int(ch), x=int(step), y=float(value)))
+
+    def _prepare_bin_point(self, events: List[ParserEvent], step: int, signal_kind: SignalKind) -> None:
+        self._mode = "bin"
+        if self._current_signal_kind != signal_kind:
+            if self._seen_points:
+                events.append(StartEvent(ch=0, signal_kind=signal_kind))
+            self._last_step = None
+            self._seen_points = False
+            self._current_signal_kind = signal_kind
+        if self._seen_points and self._last_step is not None and step <= self._last_step:
+            events.append(StartEvent(ch=0, signal_kind=signal_kind))
+            self._last_step = None
+            self._seen_points = False
+        self._seen_points = True
+        self._last_step = int(step)
+
+    def _emit_tty_point(self, events: List[ParserEvent], step: int, ch_1_word: int, ch_2_word: int) -> None:
+        self._prepare_bin_point(events, step=int(step), signal_kind="bin_iq")
+        ch_1 = u16_to_i16(int(ch_1_word))
+        ch_2 = u16_to_i16(int(ch_2_word))
+        events.append(
+            PointEvent(
+                ch=0,
+                x=int(step),
+                y=tty_ch_pair_to_sweep(ch_1, ch_2),
+                aux=(float(ch_1), float(ch_2)),
+                signal_kind="bin_iq",
+            )
+        )
+
+    def _emit_logdet_point(self, events: List[ParserEvent], step: int, value_word: int) -> None:
+        self._prepare_bin_point(events, step=int(step), signal_kind="bin_logdet")
+        value = u16_to_i16(int(value_word))
+        events.append(
+            PointEvent(
+                ch=0,
+                x=int(step),
+                y=float(value),
+                signal_kind="bin_logdet",
+            )
+        )
+
+    def feed(self, data: bytes) -> List[ParserEvent]:
+        if data:
+            self._buf += data
+        events: List[ParserEvent] = []
+        while len(self._buf) >= 8:
+            w0 = self._u16_at(self._buf, 0)
+            w1 = self._u16_at(self._buf, 2)
+            w2 = self._u16_at(self._buf, 4)
+            w3 = self._u16_at(self._buf, 6)
+
+            is_legacy_start = (w0 == 0xFFFF and w1 == 0xFFFF and w2 == 0xFFFF and self._buf[6] == 0x0A)
+            is_tty_start = (w0 == 0x000A and w1 == 0xFFFF and w2 == 0xFFFF and w3 == 0xFFFF)
+            is_legacy_point = (self._buf[6] == 0x0A and w0 != 0xFFFF)
+            is_tty_point = (w0 == 0x000A and w1 != 0xFFFF)
+            is_logdet_point = (w0 == 0x001A and w3 == 0x0000)
+
+            if is_legacy_start:
+                self._emit_legacy_start(events, ch=int(self._buf[7]))
+                del self._buf[:8]
+                continue
+
+            if is_tty_start:
+                self._emit_tty_start(events)
+                del self._buf[:8]
+                continue
+
+            if is_logdet_point:
+                self._emit_logdet_point(events, step=int(w1), value_word=int(w2))
+                del self._buf[:8]
+                continue
+
+            if self._mode == "legacy":
+                if is_legacy_point:
+                    self._emit_legacy_point(
+                        events,
+                        step=int(w0),
+                        value_word_hi=int(w1),
+                        value_word_lo=int(w2),
+                        ch=int(self._buf[7]),
+                    )
+                    del self._buf[:8]
+                    continue
+                if is_tty_point and (not is_legacy_point):
+                    self._emit_tty_point(events, step=int(w1), ch_1_word=int(w2), ch_2_word=int(w3))
+                    del self._buf[:8]
+                    continue
+                del self._buf[:1]
+                continue
+
+            if self._mode == "bin":
+                if is_tty_point:
+                    self._emit_tty_point(events, step=int(w1), ch_1_word=int(w2), ch_2_word=int(w3))
+                    del self._buf[:8]
+                    continue
+                if is_legacy_point and (not is_tty_point):
+                    self._emit_legacy_point(
+                        events,
+                        step=int(w0),
+                        value_word_hi=int(w1),
+                        value_word_lo=int(w2),
+                        ch=int(self._buf[7]),
+                    )
+                    del self._buf[:8]
+                    continue
+                del self._buf[:1]
+                continue
+
+            # Mode is still unknown. Accept only unambiguous point shapes to avoid
+            # jumping between tty and legacy interpretations on coincidental bytes.
+            if is_tty_point and (not is_legacy_point):
+                self._emit_tty_point(events, step=int(w1), ch_1_word=int(w2), ch_2_word=int(w3))
+                del self._buf[:8]
+                continue
+
+            if is_legacy_point and (not is_tty_point):
+                self._emit_legacy_point(
+                    events,
+                    step=int(w0),
+                    value_word_hi=int(w1),
+                    value_word_lo=int(w2),
+                    ch=int(self._buf[7]),
+                )
+                del self._buf[:8]
+                continue
+
+            del self._buf[:1]
+        return events
+
+
+class LogScaleBinaryParser32:
+    """Byte-resynchronizing parser for 32-bit logscale pair records."""
+
+    def __init__(self):
+        self._buf = bytearray()
+        self._last_step: Optional[int] = None
+        self._seen_points = False
+
+    @staticmethod
+    def _u16_at(buf: bytearray, offset: int) -> int:
+        return int(buf[offset]) | (int(buf[offset + 1]) << 8)
+
+    def feed(self, data: bytes) -> List[ParserEvent]:
+        if data:
+            self._buf += data
+        events: List[ParserEvent] = []
+        while len(self._buf) >= 12:
+            words = [self._u16_at(self._buf, idx * 2) for idx in range(6)]
+            if words[0:5] == [0xFFFF] * 5 and (words[5] & 0x00FF) == 0x000A:
+                self._last_step = None
+                self._seen_points = False
+                events.append(StartEvent(ch=int((words[5] >> 8) & 0x00FF)))
+                del self._buf[:12]
+                continue
+            if (words[5] & 0x00FF) == 0x000A and words[0] != 0xFFFF:
+                ch = int((words[5] >> 8) & 0x00FF)
+                if self._seen_points and self._last_step is not None and words[0] <= self._last_step:
+                    events.append(StartEvent(ch=ch))
+                self._seen_points = True
+                self._last_step = int(words[0])
+                avg_1 = u32_to_i32((words[1] << 16) | words[2])
+                avg_2 = u32_to_i32((words[3] << 16) | words[4])
+                events.append(
+                    PointEvent(
+                        ch=ch,
+                        x=int(words[0]),
+                        y=log_pair_to_sweep(avg_1, avg_2),
+                        aux=(float(avg_1), float(avg_2)),
+                    )
+                )
+                del self._buf[:12]
+                continue
+            del self._buf[:1]
+        return events
+
+
+class LogScale16BitX2BinaryParser:
+    """Byte-resynchronizing parser for 16-bit x2 logscale records."""
+
+    def __init__(self):
+        self._buf = bytearray()
+        self._current_channel = 0
+        self._last_step: Optional[int] = None
+        self._seen_points = False
+
+    @staticmethod
+    def _u16_at(buf: bytearray, offset: int) -> int:
+        return int(buf[offset]) | (int(buf[offset + 1]) << 8)
+
+    def feed(self, data: bytes) -> List[ParserEvent]:
+        if data:
+            self._buf += data
+        events: List[ParserEvent] = []
+        while len(self._buf) >= 8:
+            words = [self._u16_at(self._buf, idx * 2) for idx in range(4)]
+            if words[0:3] == [0xFFFF, 0xFFFF, 0xFFFF] and (words[3] & 0x00FF) == 0x000A:
+                self._current_channel = int((words[3] >> 8) & 0x00FF)
+                self._last_step = None
+                self._seen_points = False
+                events.append(StartEvent(ch=self._current_channel))
+                del self._buf[:8]
+                continue
+            if words[3] == 0xFFFF and words[0] != 0xFFFF:
+                if self._seen_points and self._last_step is not None and words[0] <= self._last_step:
+                    events.append(StartEvent(ch=self._current_channel))
+                self._seen_points = True
+                self._last_step = int(words[0])
+                real = u16_to_i16(words[1])
+                imag = u16_to_i16(words[2])
+                events.append(
+                    PointEvent(
+                        ch=self._current_channel,
+                        x=int(words[0]),
+                        y=float(abs(complex(real, imag))),
+                        aux=(float(real), float(imag)),
+                    )
+                )
+                del self._buf[:8]
+                continue
+            del self._buf[:1]
+        return events
+
+
+class ParserTestStreamParser:
+    """Parser for the special test 16-bit x2 stream format."""
+
+    def __init__(self):
+        self._buf = bytearray()
+        self._buf_pos = 0
+        self._point_buf: list[int] = []
+        self._ffff_run = 0
+        self._current_channel = 0
+        self._expected_step: Optional[int] = None
+        self._in_sweep = False
+        self._local_resync = False
+
+    def _consume_point(self) -> Optional[PointEvent]:
+        if len(self._point_buf) != 3:
+            return None
+        step = int(self._point_buf[0])
+        if step <= 0:
+            return None
+        if self._expected_step is not None and step < self._expected_step:
+            return None
+        real = u16_to_i16(int(self._point_buf[1]))
+        imag = u16_to_i16(int(self._point_buf[2]))
+        self._expected_step = step + 1
+        return PointEvent(
+            ch=self._current_channel,
+            x=step,
+            y=float(abs(complex(real, imag))),
+            aux=(float(real), float(imag)),
+        )
+
+    def feed(self, data: bytes) -> List[ParserEvent]:
+        if data:
+            self._buf += data
+        events: List[ParserEvent] = []
+
+        while (self._buf_pos + 1) < len(self._buf):
+            word = int(self._buf[self._buf_pos]) | (int(self._buf[self._buf_pos + 1]) << 8)
+            self._buf_pos += 2
+
+            if word == 0xFFFF:
+                self._ffff_run += 1
+                continue
+
+            if self._ffff_run > 0:
+                bad_point_on_delim = False
+                if self._in_sweep and self._point_buf and not self._local_resync:
+                    point = self._consume_point()
+                    if point is None:
+                        self._local_resync = True
+                        bad_point_on_delim = True
+                    else:
+                        events.append(point)
+                    self._point_buf.clear()
+
+                if self._ffff_run >= 2:
+                    if (word & 0x00FF) == 0x000A:
+                        self._current_channel = (word >> 8) & 0x00FF
+                        self._in_sweep = True
+                        self._expected_step = 1
+                        self._local_resync = False
+                        self._point_buf.clear()
+                        events.append(StartEvent(ch=self._current_channel))
+                        self._ffff_run = 0
+                        continue
+                    if self._in_sweep:
+                        self._local_resync = True
+                    self._ffff_run = 0
+                    continue
+
+                if self._local_resync and not bad_point_on_delim:
+                    self._local_resync = False
+                    self._point_buf.clear()
+                self._ffff_run = 0
+
+            if self._in_sweep and not self._local_resync:
+                self._point_buf.append(word)
+                if len(self._point_buf) > 3:
+                    self._point_buf.clear()
+                    self._local_resync = True
+
+        if self._buf_pos >= 262144:
+            del self._buf[: self._buf_pos]
+            self._buf_pos = 0
+        if (len(self._buf) - self._buf_pos) > 1_000_000:
+            tail = self._buf[self._buf_pos :]
+            if len(tail) > 262144:
+                tail = tail[-262144:]
+            self._buf = bytearray(tail)
+            self._buf_pos = 0
+        return events
+
+
+class SweepAssembler:
+    """Collect parser events into sweep packets matching runtime expectations."""
+
+    def __init__(self, fancy: bool = False, apply_inversion: bool = True):
+        self._fancy = bool(fancy)
+        self._apply_inversion = bool(apply_inversion)
+        self._max_width = 0
+        self._sweep_idx = 0
+        self._last_sweep_ts: Optional[float] = None
+        self._n_valid_hist = deque()
+        self._xs: list[int] = []
+        self._ys: list[float] = []
+        self._aux_1: list[float] = []
+        self._aux_2: list[float] = []
+        self._cur_channel: Optional[int] = None
+        self._cur_signal_kind: Optional[SignalKind] = None
+        self._cur_channels: set[int] = set()
+
+    def _reset_current(self) -> None:
+        self._xs.clear()
+        self._ys.clear()
+        self._aux_1.clear()
+        self._aux_2.clear()
+        self._cur_channel = None
+        self._cur_signal_kind = None
+        self._cur_channels.clear()
+
+    def _scatter(self, xs: Sequence[int], values: Sequence[float], width: int) -> np.ndarray:
+        series = np.full((width,), np.nan, dtype=np.float32)
+        try:
+            idx = np.asarray(xs, dtype=np.int64)
+            vals = np.asarray(values, dtype=np.float32)
+            series[idx] = vals
+        except Exception:
+            for x, y in zip(xs, values):
+                xi = int(x)
+                if 0 <= xi < width:
+                    series[xi] = float(y)
+        return series
+
+    @staticmethod
+    def _fill_missing(series: np.ndarray) -> None:
+        known = ~np.isnan(series)
+        if not np.any(known):
+            return
+        known_idx = np.nonzero(known)[0]
+        for i0, i1 in zip(known_idx[:-1], known_idx[1:]):
+            if i1 - i0 > 1:
+                avg = (series[i0] + series[i1]) * 0.5
+                series[i0 + 1 : i1] = avg
+        first_idx = int(known_idx[0])
+        last_idx = int(known_idx[-1])
+        if first_idx > 0:
+            series[:first_idx] = series[first_idx]
+        if last_idx < series.size - 1:
+            series[last_idx + 1 :] = series[last_idx]
+
+    def consume(self, event: ParserEvent) -> Optional[SweepPacket]:
+        if isinstance(event, StartEvent):
+            packet = self.finalize_current()
+            self._reset_current()
+            if event.ch is not None:
+                self._cur_channel = int(event.ch)
+            self._cur_signal_kind = event.signal_kind
+            return packet
+
+        point_ch = int(event.ch)
+        point_signal_kind = event.signal_kind
+        packet: Optional[SweepPacket] = None
+        if self._cur_channel is None:
+            self._cur_channel = point_ch
+        elif point_ch != self._cur_channel:
+            if self._xs:
+                # Never mix channels in a single sweep packet: otherwise
+                # identical step indexes can overwrite each other.
+                packet = self.finalize_current()
+                self._reset_current()
+            self._cur_channel = point_ch
+        if self._cur_signal_kind != point_signal_kind:
+            if self._xs:
+                packet = self.finalize_current()
+                self._reset_current()
+                self._cur_channel = point_ch
+            self._cur_signal_kind = point_signal_kind
+
+        self._cur_channels.add(point_ch)
+        self._xs.append(int(event.x))
+        self._ys.append(float(event.y))
+        if event.aux is not None:
+            self._aux_1.append(float(event.aux[0]))
+            self._aux_2.append(float(event.aux[1]))
+        return packet
+
+    def finalize_current(self) -> Optional[SweepPacket]:
+        if not self._xs:
+            return None
+
+        ch_list = sorted(self._cur_channels) if self._cur_channels else [0]
+        ch_primary = ch_list[0] if ch_list else 0
+        width = max(int(max(self._xs)) + 1, 1)
+        self._max_width = max(self._max_width, width)
+        target_width = self._max_width if self._fancy else width
+
+        sweep = self._scatter(self._xs, self._ys, target_width)
+        aux_curves: SweepAuxCurves = None
+        if self._aux_1 and self._aux_2 and len(self._aux_1) == len(self._xs):
+            aux_curves = (
+                self._scatter(self._xs, self._aux_1, target_width),
+                self._scatter(self._xs, self._aux_2, target_width),
+            )
+
+        n_valid_cur = int(np.count_nonzero(np.isfinite(sweep)))
+
+        if self._fancy:
+            self._fill_missing(sweep)
+            if aux_curves is not None:
+                self._fill_missing(aux_curves[0])
+                self._fill_missing(aux_curves[1])
+
+        if self._apply_inversion:
+            try:
+                mean_value = float(np.nanmean(sweep))
+                if np.isfinite(mean_value) and mean_value < DATA_INVERSION_THRESHOLD:
+                    sweep *= -1.0
+            except Exception:
+                pass
+
+        self._sweep_idx += 1
+        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()
+        n_valid = float(sum(value for _ts, value in self._n_valid_hist) / len(self._n_valid_hist))
+
+        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,
+            "signal_kind": self._cur_signal_kind,
+            "n_valid": n_valid,
+            "min": vmin,
+            "max": vmax,
+            "mean": mean,
+            "std": std,
+            "dt_ms": dt_ms,
+        }
+        return (sweep, info, aux_curves)

rfg_adc_plotter/io/sweep_reader.py

@@ -0,0 +1,381 @@
+"""Background sweep reader thread."""
+
+from __future__ import annotations
+
+import sys
+import threading
+import time
+from queue import Full, Queue
+
+from rfg_adc_plotter.io.serial_source import SerialChunkReader, SerialLineSource
+from rfg_adc_plotter.io.sweep_parser_core import (
+    AsciiSweepParser,
+    ComplexAsciiSweepParser,
+    LegacyBinaryParser,
+    LogScale16BitX2BinaryParser,
+    LogScaleBinaryParser32,
+    ParserTestStreamParser,
+    SweepAssembler,
+)
+from rfg_adc_plotter.types import ParserEvent, PointEvent, StartEvent, SweepPacket
+
+_PARSER_16_BIT_X2_PROBE_BYTES = 64 * 1024
+_LEGACY_STREAM_MIN_RECORDS = 32
+_LEGACY_STREAM_MIN_MATCH_RATIO = 0.95
+_TTY_STREAM_MIN_MATCH_RATIO = 0.60
+_DEBUG_FRAME_LOG_EVERY = 10
+_NO_INPUT_WARN_INTERVAL_S = 5.0
+_NO_PACKET_WARN_INTERVAL_S = 5.0
+_NO_PACKET_HINT_AFTER_S = 10.0
+
+
+def _u16le_at(data: bytes, offset: int) -> int:
+    return int(data[offset]) | (int(data[offset + 1]) << 8)
+
+
+def _looks_like_legacy_8byte_stream(data: bytes) -> bool:
+    """Heuristically detect supported 8-byte binary streams on an arbitrary byte offset."""
+    buf = bytes(data)
+    for offset in range(8):
+        blocks = (len(buf) - offset) // 8
+        if blocks < _LEGACY_STREAM_MIN_RECORDS:
+            continue
+        min_matches = max(_LEGACY_STREAM_MIN_RECORDS, int(blocks * _LEGACY_STREAM_MIN_MATCH_RATIO))
+        matched_steps_legacy: list[int] = []
+        matched_steps_tty: list[int] = []
+        matched_steps_logdet: list[int] = []
+        for block_idx in range(blocks):
+            base = offset + (block_idx * 8)
+            if (_u16le_at(buf, base + 6) & 0x00FF) != 0x000A:
+                w0 = _u16le_at(buf, base)
+                w1 = _u16le_at(buf, base + 2)
+                w3 = _u16le_at(buf, base + 6)
+                if w0 == 0x000A and w1 != 0xFFFF:
+                    matched_steps_tty.append(w1)
+                elif w0 == 0x001A and w3 == 0x0000:
+                    matched_steps_logdet.append(w1)
+                continue
+            matched_steps_legacy.append(_u16le_at(buf, base))
+
+        if len(matched_steps_legacy) >= min_matches:
+            monotonic_or_reset = 0
+            for prev_step, next_step in zip(matched_steps_legacy, matched_steps_legacy[1:]):
+                if next_step == (prev_step + 1) or next_step <= prev_step:
+                    monotonic_or_reset += 1
+            if monotonic_or_reset >= max(4, len(matched_steps_legacy) - 4):
+                return True
+
+        tty_min_matches = max(_LEGACY_STREAM_MIN_RECORDS, int(blocks * _TTY_STREAM_MIN_MATCH_RATIO))
+        if len(matched_steps_tty) >= tty_min_matches:
+            monotonic_or_reset = 0
+            for prev_step, next_step in zip(matched_steps_tty, matched_steps_tty[1:]):
+                if next_step == (prev_step + 1) or next_step <= 2:
+                    monotonic_or_reset += 1
+            if monotonic_or_reset >= max(4, len(matched_steps_tty) - 4):
+                return True
+
+        if len(matched_steps_logdet) >= tty_min_matches:
+            monotonic_or_reset = 0
+            for prev_step, next_step in zip(matched_steps_logdet, matched_steps_logdet[1:]):
+                if next_step == (prev_step + 1) or next_step <= 2:
+                    monotonic_or_reset += 1
+            if monotonic_or_reset >= max(4, len(matched_steps_logdet) - 4):
+                return True
+
+    return False
+
+
+def _is_valid_parser_16_bit_x2_probe(events: list[ParserEvent]) -> bool:
+    """Accept only plausible complex streams and ignore resync noise."""
+    point_steps: list[int] = []
+    for event in events:
+        if isinstance(event, PointEvent):
+            point_steps.append(int(event.x))
+
+    if len(point_steps) < 3:
+        return False
+
+    monotonic_or_small_reset = 0
+    for prev_step, next_step in zip(point_steps, point_steps[1:]):
+        if next_step == (prev_step + 1) or next_step <= 2:
+            monotonic_or_small_reset += 1
+    return monotonic_or_small_reset >= max(2, len(point_steps) - 3)
+
+
+class SweepReader(threading.Thread):
+    """Read a serial source in the background and emit completed sweep packets."""
+
+    def __init__(
+        self,
+        port_path: str,
+        baud: int,
+        out_queue: "Queue[SweepPacket]",
+        stop_event: threading.Event,
+        fancy: bool = False,
+        bin_mode: bool = False,
+        logscale: bool = False,
+        parser_16_bit_x2: bool = False,
+        parser_test: bool = False,
+        parser_complex_ascii: bool = False,
+    ):
+        super().__init__(daemon=True)
+        self._port_path = port_path
+        self._baud = int(baud)
+        self._queue = out_queue
+        self._stop_event = stop_event
+        self._fancy = bool(fancy)
+        self._bin_mode = bool(bin_mode)
+        self._logscale = bool(logscale)
+        self._parser_16_bit_x2 = bool(parser_16_bit_x2)
+        self._parser_test = bool(parser_test)
+        self._parser_complex_ascii = bool(parser_complex_ascii)
+        self._src: SerialLineSource | None = None
+        self._frames_read = 0
+        self._frames_dropped = 0
+        self._started_at = time.perf_counter()
+
+    def _resolve_parser_mode_label(self) -> str:
+        if self._parser_complex_ascii:
+            return "complex_ascii"
+        if self._parser_test:
+            return "parser_test_16x2"
+        if self._parser_16_bit_x2:
+            return "parser_16_bit_x2"
+        if self._logscale:
+            return "logscale_32"
+        if self._bin_mode:
+            return "legacy_8byte"
+        return "ascii"
+
+    def _build_parser(self):
+        if self._parser_complex_ascii:
+            return ComplexAsciiSweepParser(), SweepAssembler(fancy=self._fancy, apply_inversion=False)
+        if self._parser_test:
+            return ParserTestStreamParser(), SweepAssembler(fancy=self._fancy, apply_inversion=False)
+        if self._parser_16_bit_x2:
+            return LogScale16BitX2BinaryParser(), SweepAssembler(fancy=self._fancy, apply_inversion=False)
+        if self._logscale:
+            return LogScaleBinaryParser32(), SweepAssembler(fancy=self._fancy, apply_inversion=False)
+        if self._bin_mode:
+            return LegacyBinaryParser(), SweepAssembler(fancy=self._fancy, apply_inversion=True)
+        return AsciiSweepParser(), SweepAssembler(fancy=self._fancy, apply_inversion=True)
+
+    @staticmethod
+    def _consume_events(assembler: SweepAssembler, events) -> list[SweepPacket]:
+        packets: list[SweepPacket] = []
+        for event in events:
+            packet = assembler.consume(event)
+            if packet is not None:
+                packets.append(packet)
+        return packets
+
+    def _probe_parser_16_bit_x2(self, chunk_reader: SerialChunkReader):
+        parser = LogScale16BitX2BinaryParser()
+        probe_buf = bytearray()
+        probe_events: list[ParserEvent] = []
+        probe_started_at = time.perf_counter()
+
+        while not self._stop_event.is_set() and len(probe_buf) < _PARSER_16_BIT_X2_PROBE_BYTES:
+            data = chunk_reader.read_available()
+            if not data:
+                time.sleep(0.0005)
+                continue
+            probe_buf += data
+            probe_events.extend(parser.feed(data))
+            if _is_valid_parser_16_bit_x2_probe(probe_events):
+                assembler = SweepAssembler(fancy=self._fancy, apply_inversion=False)
+                probe_packets = self._consume_events(assembler, probe_events)
+                n_points = int(sum(1 for event in probe_events if isinstance(event, PointEvent)))
+                n_starts = int(sum(1 for event in probe_events if isinstance(event, StartEvent)))
+                probe_ms = (time.perf_counter() - probe_started_at) * 1000.0
+                sys.stderr.write(
+                    "[info] parser_16_bit_x2 probe: bytes:%d events:%d points:%d starts:%d parser:16x2 elapsed_ms:%.1f\n"
+                    % (
+                        len(probe_buf),
+                        len(probe_events),
+                        n_points,
+                        n_starts,
+                        probe_ms,
+                    )
+                )
+                return parser, assembler, probe_packets
+
+        probe_looks_legacy = bool(probe_buf) and _looks_like_legacy_8byte_stream(bytes(probe_buf))
+        n_points = int(sum(1 for event in probe_events if isinstance(event, PointEvent)))
+        n_starts = int(sum(1 for event in probe_events if isinstance(event, StartEvent)))
+        probe_ms = (time.perf_counter() - probe_started_at) * 1000.0
+        if probe_looks_legacy:
+            sys.stderr.write(
+                "[info] parser_16_bit_x2 probe: bytes:%d events:%d points:%d starts:%d parser:legacy(fallback) elapsed_ms:%.1f\n"
+                % (
+                    len(probe_buf),
+                    len(probe_events),
+                    n_points,
+                    n_starts,
+                    probe_ms,
+                )
+            )
+            sys.stderr.write("[info] parser_16_bit_x2: fallback -> legacy\n")
+            parser = LegacyBinaryParser()
+            assembler = SweepAssembler(fancy=self._fancy, apply_inversion=True)
+            probe_packets = self._consume_events(assembler, parser.feed(bytes(probe_buf)))
+            return parser, assembler, probe_packets
+
+        sys.stderr.write(
+            "[warn] parser_16_bit_x2 probe inconclusive: bytes:%d events:%d points:%d starts:%d parser:16x2 elapsed_ms:%.1f\n"
+            % (
+                len(probe_buf),
+                len(probe_events),
+                n_points,
+                n_starts,
+                probe_ms,
+            )
+        )
+        sys.stderr.write(
+            "[hint] parser_16_bit_x2: if source is 8-byte tty CH1/CH2 stream (0x000A,step,ch1,ch2), try --bin\n"
+        )
+        assembler = SweepAssembler(fancy=self._fancy, apply_inversion=False)
+        return parser, assembler, []
+
+    def _enqueue(self, packet: SweepPacket) -> None:
+        dropped = False
+        try:
+            self._queue.put_nowait(packet)
+        except Full:
+            try:
+                _ = self._queue.get_nowait()
+                dropped = True
+            except Exception:
+                pass
+            try:
+                self._queue.put_nowait(packet)
+            except Exception:
+                pass
+        if dropped:
+            self._frames_dropped += 1
+
+        self._frames_read += 1
+        if self._frames_read % _DEBUG_FRAME_LOG_EVERY == 0:
+            sweep, info, _aux = packet
+            try:
+                queue_size = self._queue.qsize()
+            except Exception:
+                queue_size = -1
+            elapsed_s = max(time.perf_counter() - self._started_at, 1e-9)
+            frames_per_sec = float(self._frames_read) / elapsed_s
+            sweep_idx = info.get("sweep") if isinstance(info, dict) else None
+            channel = info.get("ch") if isinstance(info, dict) else None
+            sys.stderr.write(
+                "[debug] reader frames:%d rate:%.2f/s last_sweep:%s ch:%s width:%d queue:%d dropped:%d\n"
+                % (
+                    self._frames_read,
+                    frames_per_sec,
+                    str(sweep_idx),
+                    str(channel),
+                    int(getattr(sweep, "size", 0)),
+                    int(queue_size),
+                    self._frames_dropped,
+                )
+            )
+
+    def run(self) -> None:
+        try:
+            self._src = SerialLineSource(self._port_path, self._baud, timeout=1.0)
+            queue_cap = int(getattr(self._queue, "maxsize", -1))
+            sys.stderr.write(f"[info] Открыл порт {self._port_path} ({self._src._using})\n")
+            sys.stderr.write(
+                "[info] reader start: parser:%s fancy:%d queue_max:%d source:%s\n"
+                % (
+                    self._resolve_parser_mode_label(),
+                    int(self._fancy),
+                    queue_cap,
+                    getattr(self._src, "_using", "unknown"),
+                )
+            )
+        except Exception as exc:
+            sys.stderr.write(f"[error] {exc}\n")
+            return
+
+        try:
+            chunk_reader = SerialChunkReader(self._src)
+            if self._parser_16_bit_x2:
+                parser, assembler, pending_packets = self._probe_parser_16_bit_x2(chunk_reader)
+            else:
+                parser, assembler = self._build_parser()
+                pending_packets = []
+
+            for packet in pending_packets:
+                self._enqueue(packet)
+
+            loop_started_at = time.perf_counter()
+            last_input_at = loop_started_at
+            last_packet_at = loop_started_at if self._frames_read > 0 else loop_started_at
+            last_no_input_warn_at = loop_started_at
+            last_no_packet_warn_at = loop_started_at
+            parser_hint_emitted = False
+
+            while not self._stop_event.is_set():
+                data = chunk_reader.read_available()
+                now_s = time.perf_counter()
+                if not data:
+                    input_idle_s = now_s - last_input_at
+                    if (
+                        input_idle_s >= _NO_INPUT_WARN_INTERVAL_S
+                        and (now_s - last_no_input_warn_at) >= _NO_INPUT_WARN_INTERVAL_S
+                    ):
+                        sys.stderr.write(
+                            "[warn] reader no input bytes for %.1fs on %s (parser:%s)\n"
+                            % (
+                                input_idle_s,
+                                self._port_path,
+                                self._resolve_parser_mode_label(),
+                            )
+                        )
+                        last_no_input_warn_at = now_s
+
+                    packets_idle_s = now_s - last_packet_at
+                    if (
+                        packets_idle_s >= _NO_PACKET_WARN_INTERVAL_S
+                        and (now_s - last_no_packet_warn_at) >= _NO_PACKET_WARN_INTERVAL_S
+                    ):
+                        try:
+                            queue_size = self._queue.qsize()
+                        except Exception:
+                            queue_size = -1
+                        sys.stderr.write(
+                            "[warn] reader no sweep packets for %.1fs (input_idle:%.1fs queue:%d parser:%s)\n"
+                            % (
+                                packets_idle_s,
+                                input_idle_s,
+                                int(queue_size),
+                                self._resolve_parser_mode_label(),
+                            )
+                        )
+                        last_no_packet_warn_at = now_s
+                        if (
+                            self._parser_16_bit_x2
+                            and (not parser_hint_emitted)
+                            and (now_s - self._started_at) >= _NO_PACKET_HINT_AFTER_S
+                        ):
+                            sys.stderr.write(
+                                "[hint] parser_16_bit_x2 still has no sweeps; if source is tty CH1/CH2, rerun with --bin\n"
+                            )
+                            parser_hint_emitted = True
+                    time.sleep(0.0005)
+                    continue
+
+                last_input_at = now_s
+                packets = self._consume_events(assembler, parser.feed(data))
+                if packets:
+                    last_packet_at = now_s
+                for packet in packets:
+                    self._enqueue(packet)
+            packet = assembler.finalize_current()
+            if packet is not None:
+                self._enqueue(packet)
+        finally:
+            try:
+                if self._src is not None:
+                    self._src.close()
+            except Exception:
+                pass

rfg_adc_plotter/main.py

@@ -0,0 +1,26 @@
+"""Main entrypoint for the modularized ADC plotter."""
+
+from __future__ import annotations
+
+import sys
+
+from rfg_adc_plotter.cli import build_parser
+
+
+def main() -> None:
+    args = build_parser().parse_args()
+    if args.backend == "mpl":
+        sys.stderr.write("[error] Matplotlib backend removed. Use --backend pg or --backend auto.\n")
+        raise SystemExit(2)
+
+    from rfg_adc_plotter.gui.pyqtgraph_backend import run_pyqtgraph
+
+    try:
+        run_pyqtgraph(args)
+    except Exception as exc:
+        sys.stderr.write(f"[error] PyQtGraph бэкенд недоступен: {exc}\n")
+        raise SystemExit(1) from exc
+
+
+if __name__ == "__main__":
+    main()

rfg_adc_plotter/processing/__init__.py

@@ -0,0 +1,79 @@
+"""Pure sweep-processing helpers."""
+
+from rfg_adc_plotter.processing.background import (
+    load_fft_background,
+    save_fft_background,
+    subtract_fft_background,
+    validate_fft_background,
+)
+from rfg_adc_plotter.processing.calibration import (
+    build_calib_envelope,
+    build_complex_calibration_curve,
+    calibrate_freqs,
+    get_calibration_base,
+    get_calibration_coeffs,
+    load_calib_envelope,
+    load_complex_calibration,
+    recalculate_calibration_c,
+    save_calib_envelope,
+    save_complex_calibration,
+    set_calibration_base_value,
+)
+from rfg_adc_plotter.processing.fft import (
+    compute_distance_axis,
+    compute_fft_complex_row,
+    compute_fft_mag_row,
+    compute_fft_row,
+    fft_mag_to_db,
+)
+from rfg_adc_plotter.processing.formatting import (
+    compute_auto_ylim,
+    format_status_kv,
+    parse_spec_clip,
+)
+from rfg_adc_plotter.processing.normalization import (
+    build_calib_envelopes,
+    fit_complex_calibration_to_width,
+    normalize_by_complex_calibration,
+    normalize_by_envelope,
+    normalize_by_calib,
+)
+from rfg_adc_plotter.processing.peaks import (
+    find_peak_width_markers,
+    find_top_peaks_over_ref,
+    rolling_median_ref,
+)
+
+__all__ = [
+    "build_calib_envelopes",
+    "build_calib_envelope",
+    "build_complex_calibration_curve",
+    "calibrate_freqs",
+    "compute_auto_ylim",
+    "compute_distance_axis",
+    "compute_fft_complex_row",
+    "compute_fft_mag_row",
+    "compute_fft_row",
+    "fft_mag_to_db",
+    "find_peak_width_markers",
+    "find_top_peaks_over_ref",
+    "format_status_kv",
+    "get_calibration_base",
+    "get_calibration_coeffs",
+    "load_calib_envelope",
+    "load_complex_calibration",
+    "load_fft_background",
+    "fit_complex_calibration_to_width",
+    "normalize_by_complex_calibration",
+    "normalize_by_envelope",
+    "normalize_by_calib",
+    "parse_spec_clip",
+    "recalculate_calibration_c",
+    "rolling_median_ref",
+    "save_calib_envelope",
+    "save_complex_calibration",
+    "save_fft_background",
+    "set_calibration_base_value",
+    "subtract_fft_background",
+    "validate_fft_background",
+]

rfg_adc_plotter/processing/background.py

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

rfg_adc_plotter/processing/calibration.py

@@ -0,0 +1,169 @@
+"""Frequency-axis calibration helpers."""
+
+from __future__ import annotations
+
+from pathlib import Path
+from typing import Any, Mapping
+
+import numpy as np
+
+from rfg_adc_plotter.constants import SWEEP_FREQ_MAX_GHZ, SWEEP_FREQ_MIN_GHZ
+from rfg_adc_plotter.processing.normalization import build_calib_envelopes
+from rfg_adc_plotter.types import SweepData
+
+
+def recalculate_calibration_c(
+    base_coeffs: np.ndarray,
+    f_min: float = SWEEP_FREQ_MIN_GHZ,
+    f_max: float = SWEEP_FREQ_MAX_GHZ,
+) -> np.ndarray:
+    """Recalculate coefficients while preserving sweep edges."""
+    coeffs = np.asarray(base_coeffs, dtype=np.float64).reshape(-1)
+    if coeffs.size < 3:
+        out = np.zeros((3,), dtype=np.float64)
+        out[: coeffs.size] = coeffs
+        coeffs = out
+    c0, c1, c2 = float(coeffs[0]), float(coeffs[1]), float(coeffs[2])
+    x0 = float(f_min)
+    x1 = float(f_max)
+    y0 = c0 + c1 * x0 + c2 * (x0 ** 2)
+    y1 = c0 + c1 * x1 + c2 * (x1 ** 2)
+    if not (np.isfinite(y0) and np.isfinite(y1)) or y1 == y0:
+        return np.asarray([c0, c1, c2], dtype=np.float64)
+    scale = (x1 - x0) / (y1 - y0)
+    shift = x0 - scale * y0
+    return np.asarray(
+        [
+            shift + scale * c0,
+            scale * c1,
+            scale * c2,
+        ],
+        dtype=np.float64,
+    )
+
+
+CALIBRATION_C_BASE = np.asarray([0.0, 1.0, 0.025], dtype=np.float64)
+CALIBRATION_C = recalculate_calibration_c(CALIBRATION_C_BASE)
+
+
+def get_calibration_base() -> np.ndarray:
+    return np.asarray(CALIBRATION_C_BASE, dtype=np.float64).copy()
+
+
+def get_calibration_coeffs() -> np.ndarray:
+    return np.asarray(CALIBRATION_C, dtype=np.float64).copy()
+
+
+def set_calibration_base_value(index: int, value: float) -> np.ndarray:
+    """Update one base coefficient and recalculate the working coefficients."""
+    global CALIBRATION_C
+    CALIBRATION_C_BASE[int(index)] = float(value)
+    CALIBRATION_C = recalculate_calibration_c(CALIBRATION_C_BASE)
+    return get_calibration_coeffs()
+
+
+def calibrate_freqs(sweep: Mapping[str, Any]) -> SweepData:
+    """Return a sweep copy with calibrated and resampled frequency axis."""
+    freqs = np.asarray(sweep["F"], dtype=np.float64).copy()
+    values_in = np.asarray(sweep["I"]).reshape(-1)
+    values = np.asarray(
+        values_in,
+        dtype=np.complex128 if np.iscomplexobj(values_in) else np.float64,
+    ).copy()
+    coeffs = np.asarray(CALIBRATION_C, dtype=np.float64)
+    if freqs.size > 0:
+        freqs = coeffs[0] + coeffs[1] * freqs + coeffs[2] * (freqs * freqs)
+
+    if freqs.size >= 2:
+        freqs_cal = np.linspace(float(freqs[0]), float(freqs[-1]), freqs.size, dtype=np.float64)
+        if np.iscomplexobj(values):
+            values_real = np.interp(freqs_cal, freqs, values.real.astype(np.float64, copy=False))
+            values_imag = np.interp(freqs_cal, freqs, values.imag.astype(np.float64, copy=False))
+            values_cal = (values_real + (1j * values_imag)).astype(np.complex64)
+        else:
+            values_cal = np.interp(freqs_cal, freqs, values).astype(np.float64)
+    else:
+        freqs_cal = freqs.copy()
+        values_cal = values.copy()
+
+    return {
+        "F": freqs_cal,
+        "I": values_cal,
+    }
+
+
+def build_calib_envelope(sweep: np.ndarray) -> np.ndarray:
+    """Build the active calibration envelope from a raw sweep."""
+    values = np.asarray(sweep, dtype=np.float32).reshape(-1)
+    if values.size == 0:
+        raise ValueError("Calibration sweep is empty")
+    _, upper = build_calib_envelopes(values)
+    return np.asarray(upper, dtype=np.float32)
+
+
+def build_complex_calibration_curve(ch1: np.ndarray, ch2: np.ndarray) -> np.ndarray:
+    """Build a complex calibration curve as ``ch1 + 1j*ch2``."""
+    ch1_arr = np.asarray(ch1, dtype=np.float32).reshape(-1)
+    ch2_arr = np.asarray(ch2, dtype=np.float32).reshape(-1)
+    width = min(ch1_arr.size, ch2_arr.size)
+    if width <= 0:
+        raise ValueError("Complex calibration source is empty")
+    curve = ch1_arr[:width].astype(np.complex64) + (1j * ch2_arr[:width].astype(np.complex64))
+    return validate_complex_calibration_curve(curve)
+
+
+def validate_calib_envelope(envelope: np.ndarray) -> np.ndarray:
+    """Validate a saved calibration envelope payload."""
+    values = np.asarray(envelope, dtype=np.float32).reshape(-1)
+    if values.size == 0:
+        raise ValueError("Calibration envelope is empty")
+    if not np.issubdtype(values.dtype, np.number):
+        raise ValueError("Calibration envelope must be numeric")
+    return values
+
+
+def validate_complex_calibration_curve(curve: np.ndarray) -> np.ndarray:
+    """Validate a saved complex calibration payload."""
+    values = np.asarray(curve).reshape(-1)
+    if values.size == 0:
+        raise ValueError("Complex calibration curve is empty")
+    if not np.issubdtype(values.dtype, np.number):
+        raise ValueError("Complex calibration curve must be numeric")
+    return np.asarray(values, dtype=np.complex64)
+
+
+def _normalize_calib_path(path: str | Path) -> Path:
+    out = Path(path).expanduser()
+    if out.suffix.lower() != ".npy":
+        out = out.with_suffix(".npy")
+    return out
+
+
+def save_calib_envelope(path: str | Path, envelope: np.ndarray) -> str:
+    """Persist a calibration envelope as a .npy file and return the final path."""
+    normalized_path = _normalize_calib_path(path)
+    values = validate_calib_envelope(envelope)
+    np.save(normalized_path, values.astype(np.float32, copy=False))
+    return str(normalized_path)
+
+
+def load_calib_envelope(path: str | Path) -> np.ndarray:
+    """Load and validate a calibration envelope from a .npy file."""
+    normalized_path = _normalize_calib_path(path)
+    loaded = np.load(normalized_path, allow_pickle=False)
+    return validate_calib_envelope(loaded)
+
+
+def save_complex_calibration(path: str | Path, curve: np.ndarray) -> str:
+    """Persist a complex calibration curve as a .npy file and return the final path."""
+    normalized_path = _normalize_calib_path(path)
+    values = validate_complex_calibration_curve(curve)
+    np.save(normalized_path, values.astype(np.complex64, copy=False))
+    return str(normalized_path)
+
+
+def load_complex_calibration(path: str | Path) -> np.ndarray:
+    """Load and validate a complex calibration curve from a .npy file."""
+    normalized_path = _normalize_calib_path(path)
+    loaded = np.load(normalized_path, allow_pickle=False)
+    return validate_complex_calibration_curve(loaded)

rfg_adc_plotter/processing/fft.py

@@ -0,0 +1,511 @@
+"""FFT helpers for line and waterfall views."""
+
+from __future__ import annotations
+
+from typing import Optional, Tuple
+
+import numpy as np
+
+from rfg_adc_plotter.constants import C_M_S, FFT_LEN, SWEEP_FREQ_MAX_GHZ, SWEEP_FREQ_MIN_GHZ
+
+
+def _finite_freq_bounds(freqs: Optional[np.ndarray]) -> Optional[Tuple[float, float]]:
+    """Return finite frequency bounds for the current working segment."""
+    if freqs is None:
+        return None
+    freq_arr = np.asarray(freqs, dtype=np.float64).reshape(-1)
+    finite = freq_arr[np.isfinite(freq_arr)]
+    if finite.size < 2:
+        return None
+    f_min = float(np.min(finite))
+    f_max = float(np.max(finite))
+    if not np.isfinite(f_min) or not np.isfinite(f_max) or f_max <= f_min:
+        return None
+    return f_min, f_max
+
+
+def _coerce_sweep_array(sweep: np.ndarray) -> np.ndarray:
+    values = np.asarray(sweep).reshape(-1)
+    if np.iscomplexobj(values):
+        return np.asarray(values, dtype=np.complex64)
+    return np.asarray(values, dtype=np.float32)
+
+
+def _interp_signal(x_uniform: np.ndarray, x_known: np.ndarray, y_known: np.ndarray) -> np.ndarray:
+    if np.iscomplexobj(y_known):
+        real = np.interp(x_uniform, x_known, np.asarray(y_known.real, dtype=np.float64))
+        imag = np.interp(x_uniform, x_known, np.asarray(y_known.imag, dtype=np.float64))
+        return (real + (1j * imag)).astype(np.complex64)
+    return np.interp(x_uniform, x_known, np.asarray(y_known, dtype=np.float64)).astype(np.float32)
+
+
+def _fit_complex_bins(values: np.ndarray, bins: int) -> np.ndarray:
+    arr = np.asarray(values, dtype=np.complex64).reshape(-1)
+    if bins <= 0:
+        return np.zeros((0,), dtype=np.complex64)
+    if arr.size == bins:
+        return arr
+    out = np.full((bins,), np.nan + 0j, dtype=np.complex64)
+    take = min(arr.size, bins)
+    out[:take] = arr[:take]
+    return out
+
+
+def _extract_positive_exact_band(
+    sweep: np.ndarray,
+    freqs: Optional[np.ndarray],
+) -> Optional[Tuple[np.ndarray, np.ndarray, float, float]]:
+    """Return sorted positive band data and exact-grid parameters."""
+    if freqs is None:
+        return None
+
+    sweep_arr = _coerce_sweep_array(sweep)
+    freq_arr = np.asarray(freqs, dtype=np.float64).reshape(-1)
+    take = min(int(sweep_arr.size), int(freq_arr.size))
+    if take <= 1:
+        return None
+
+    sweep_seg = sweep_arr[:take]
+    freq_seg = freq_arr[:take]
+    valid = np.isfinite(freq_seg) & np.isfinite(sweep_seg) & (freq_seg > 0.0)
+    if int(np.count_nonzero(valid)) < 2:
+        return None
+
+    freq_band = np.asarray(freq_seg[valid], dtype=np.float64)
+    sweep_band = np.asarray(sweep_seg[valid])
+    order = np.argsort(freq_band, kind="mergesort")
+    freq_band = freq_band[order]
+    sweep_band = sweep_band[order]
+
+    n_band = int(freq_band.size)
+    if n_band <= 1:
+        return None
+
+    f_min = float(freq_band[0])
+    f_max = float(freq_band[-1])
+    if (not np.isfinite(f_min)) or (not np.isfinite(f_max)) or f_max <= f_min:
+        return None
+
+    df_ghz = float((f_max - f_min) / max(1, n_band - 1))
+    if (not np.isfinite(df_ghz)) or df_ghz <= 0.0:
+        return None
+
+    return freq_band, sweep_band, f_max, df_ghz
+
+
+def _positive_exact_shift_size(f_max: float, df_ghz: float) -> int:
+    if (not np.isfinite(f_max)) or (not np.isfinite(df_ghz)) or f_max <= 0.0 or df_ghz <= 0.0:
+        return 0
+    return int(np.arange(-f_max, f_max + (0.5 * df_ghz), df_ghz, dtype=np.float64).size)
+
+
+def _resolve_positive_exact_band_size(
+    f_min: float,
+    f_max: float,
+    n_band: int,
+    max_shift_len: Optional[int],
+) -> int:
+    if n_band <= 2:
+        return max(2, int(n_band))
+    if max_shift_len is None:
+        return int(n_band)
+
+    limit = int(max_shift_len)
+    if limit <= 1:
+        return max(2, int(n_band))
+
+    span = float(f_max - f_min)
+    if (not np.isfinite(span)) or span <= 0.0:
+        return int(n_band)
+
+    df_current = float(span / max(1, int(n_band) - 1))
+    if _positive_exact_shift_size(f_max, df_current) <= limit:
+        return int(n_band)
+
+    denom = max(2.0 * f_max, 1e-12)
+    approx = int(np.floor(1.0 + ((float(limit - 1) * span) / denom)))
+    target = min(int(n_band), max(2, approx))
+    while target > 2:
+        df_try = float(span / max(1, target - 1))
+        if _positive_exact_shift_size(f_max, df_try) <= limit:
+            break
+        target -= 1
+    return max(2, target)
+
+
+def _normalize_positive_exact_band(
+    freq_band: np.ndarray,
+    sweep_band: np.ndarray,
+    *,
+    max_shift_len: Optional[int] = None,
+) -> Optional[Tuple[np.ndarray, np.ndarray, float, float]]:
+    freq_arr = np.asarray(freq_band, dtype=np.float64).reshape(-1)
+    sweep_arr = np.asarray(sweep_band).reshape(-1)
+    width = min(int(freq_arr.size), int(sweep_arr.size))
+    if width <= 1:
+        return None
+
+    freq_arr = freq_arr[:width]
+    sweep_arr = sweep_arr[:width]
+    f_min = float(freq_arr[0])
+    f_max = float(freq_arr[-1])
+    if (not np.isfinite(f_min)) or (not np.isfinite(f_max)) or f_max <= f_min:
+        return None
+
+    target_band = _resolve_positive_exact_band_size(f_min, f_max, int(freq_arr.size), max_shift_len)
+    if target_band < int(freq_arr.size):
+        target_freqs = np.linspace(f_min, f_max, target_band, dtype=np.float64)
+        target_sweep = _interp_signal(target_freqs, freq_arr, sweep_arr)
+        freq_arr = target_freqs
+        sweep_arr = np.asarray(target_sweep).reshape(-1)
+
+    n_band = int(freq_arr.size)
+    if n_band <= 1:
+        return None
+
+    df_ghz = float((f_max - f_min) / max(1, n_band - 1))
+    if (not np.isfinite(df_ghz)) or df_ghz <= 0.0:
+        return None
+
+    return freq_arr, sweep_arr, f_max, df_ghz
+
+
+def _resolve_positive_only_exact_geometry(
+    freqs: Optional[np.ndarray],
+    *,
+    max_shift_len: Optional[int] = None,
+) -> Optional[Tuple[int, float]]:
+    """Return (N_shift, df_hz) for the exact centered positive-only mode."""
+    if freqs is None:
+        return None
+
+    freq_arr = np.asarray(freqs, dtype=np.float64).reshape(-1)
+    finite = np.asarray(freq_arr[np.isfinite(freq_arr) & (freq_arr > 0.0)], dtype=np.float64)
+    if finite.size < 2:
+        return None
+
+    finite.sort(kind="mergesort")
+    f_min = float(finite[0])
+    f_max = float(finite[-1])
+    if (not np.isfinite(f_min)) or (not np.isfinite(f_max)) or f_max <= f_min:
+        return None
+
+    n_band = int(finite.size)
+    target_band = _resolve_positive_exact_band_size(f_min, f_max, n_band, max_shift_len)
+    n_band = max(2, min(n_band, target_band))
+    df_ghz = float((f_max - f_min) / max(1, n_band - 1))
+    if (not np.isfinite(df_ghz)) or df_ghz <= 0.0:
+        return None
+
+    n_shift = _positive_exact_shift_size(f_max, df_ghz)
+    if n_shift <= 1:
+        return None
+    return int(n_shift), float(df_ghz * 1e9)
+
+
+def prepare_fft_segment(
+    sweep: np.ndarray,
+    freqs: Optional[np.ndarray],
+    fft_len: int = FFT_LEN,
+) -> Optional[Tuple[np.ndarray, int]]:
+    """Prepare a sweep segment for FFT on a uniform frequency grid."""
+    take_fft = min(int(sweep.size), int(fft_len))
+    if take_fft <= 0:
+        return None
+
+    sweep_arr = _coerce_sweep_array(sweep)
+    sweep_seg = sweep_arr[:take_fft]
+    fallback_dtype = np.complex64 if np.iscomplexobj(sweep_seg) else np.float32
+    fallback = np.nan_to_num(sweep_seg, nan=0.0).astype(fallback_dtype, copy=False)
+    if freqs is None:
+        return fallback, take_fft
+
+    freq_arr = np.asarray(freqs)
+    if freq_arr.size < take_fft:
+        return fallback, take_fft
+
+    freq_seg = np.asarray(freq_arr[:take_fft], dtype=np.float64)
+    valid = np.isfinite(sweep_seg) & np.isfinite(freq_seg)
+    if int(np.count_nonzero(valid)) < 2:
+        return fallback, take_fft
+
+    x_valid = freq_seg[valid]
+    y_valid = sweep_seg[valid]
+    order = np.argsort(x_valid, kind="mergesort")
+    x_valid = x_valid[order]
+    y_valid = y_valid[order]
+    x_unique, unique_idx = np.unique(x_valid, return_index=True)
+    y_unique = y_valid[unique_idx]
+    if x_unique.size < 2 or x_unique[-1] <= x_unique[0]:
+        return fallback, take_fft
+
+    x_uniform = np.linspace(float(x_unique[0]), float(x_unique[-1]), take_fft, dtype=np.float64)
+    resampled = _interp_signal(x_uniform, x_unique, y_unique)
+    return resampled, take_fft
+
+
+def build_symmetric_ifft_spectrum(
+    sweep: np.ndarray,
+    freqs: Optional[np.ndarray],
+    fft_len: int = FFT_LEN,
+) -> Optional[np.ndarray]:
+    """Build a centered symmetric spectrum over [-f_max, f_max] for IFFT."""
+    if fft_len <= 0:
+        return None
+
+    bounds = _finite_freq_bounds(freqs)
+    if bounds is None:
+        f_min = float(SWEEP_FREQ_MIN_GHZ)
+        f_max = float(SWEEP_FREQ_MAX_GHZ)
+    else:
+        f_min, f_max = bounds
+
+    freq_axis = np.linspace(-f_max, f_max, int(fft_len), dtype=np.float64)
+    neg_idx_all = np.flatnonzero(freq_axis <= (-f_min))
+    pos_idx_all = np.flatnonzero(freq_axis >= f_min)
+    band_len = int(min(neg_idx_all.size, pos_idx_all.size))
+    if band_len <= 1:
+        return None
+
+    neg_idx = neg_idx_all[:band_len]
+    pos_idx = pos_idx_all[-band_len:]
+    prepared = prepare_fft_segment(sweep, freqs, fft_len=band_len)
+    if prepared is None:
+        return None
+
+    fft_seg, take_fft = prepared
+    if take_fft != band_len:
+        fft_dtype = np.complex64 if np.iscomplexobj(fft_seg) else np.float32
+        fft_seg = np.asarray(fft_seg[:band_len], dtype=fft_dtype)
+        if fft_seg.size < band_len:
+            padded = np.zeros((band_len,), dtype=fft_dtype)
+            padded[: fft_seg.size] = fft_seg
+            fft_seg = padded
+
+    window = np.hanning(band_len).astype(np.float32)
+    band_dtype = np.complex64 if np.iscomplexobj(fft_seg) else np.float32
+    band = np.nan_to_num(fft_seg, nan=0.0).astype(band_dtype, copy=False) * window
+
+    spectrum = np.zeros((int(fft_len),), dtype=band_dtype)
+    spectrum[pos_idx] = band
+    spectrum[neg_idx] = np.conj(band[::-1]) if np.iscomplexobj(band) else band[::-1]
+    return spectrum
+
+
+def build_positive_only_centered_ifft_spectrum(
+    sweep: np.ndarray,
+    freqs: Optional[np.ndarray],
+    fft_len: int = FFT_LEN,
+) -> Optional[np.ndarray]:
+    """Build a centered spectrum with zeros from -f_max to +f_min."""
+    if fft_len <= 0:
+        return None
+
+    bounds = _finite_freq_bounds(freqs)
+    if bounds is None:
+        f_min = float(SWEEP_FREQ_MIN_GHZ)
+        f_max = float(SWEEP_FREQ_MAX_GHZ)
+    else:
+        f_min, f_max = bounds
+
+    freq_axis = np.linspace(-f_max, f_max, int(fft_len), dtype=np.float64)
+    pos_idx = np.flatnonzero(freq_axis >= f_min)
+    band_len = int(pos_idx.size)
+    if band_len <= 1:
+        return None
+
+    prepared = prepare_fft_segment(sweep, freqs, fft_len=band_len)
+    if prepared is None:
+        return None
+
+    fft_seg, take_fft = prepared
+    if take_fft != band_len:
+        fft_dtype = np.complex64 if np.iscomplexobj(fft_seg) else np.float32
+        fft_seg = np.asarray(fft_seg[:band_len], dtype=fft_dtype)
+        if fft_seg.size < band_len:
+            padded = np.zeros((band_len,), dtype=fft_dtype)
+            padded[: fft_seg.size] = fft_seg
+            fft_seg = padded
+
+    window = np.hanning(band_len).astype(np.float32)
+    band_dtype = np.complex64 if np.iscomplexobj(fft_seg) else np.float32
+    band = np.nan_to_num(fft_seg, nan=0.0).astype(band_dtype, copy=False) * window
+
+    spectrum = np.zeros((int(fft_len),), dtype=band_dtype)
+    spectrum[pos_idx] = band
+    return spectrum
+
+
+def build_positive_only_exact_centered_ifft_spectrum(
+    sweep: np.ndarray,
+    freqs: Optional[np.ndarray],
+    *,
+    max_shift_len: Optional[int] = None,
+) -> Optional[np.ndarray]:
+    """Build centered spectrum exactly as zeros[-f_max..+f_min) + measured positive band."""
+    prepared = _extract_positive_exact_band(sweep, freqs)
+    if prepared is None:
+        return None
+
+    freq_band, sweep_band, _f_max, _df_ghz = prepared
+    normalized = _normalize_positive_exact_band(
+        freq_band,
+        sweep_band,
+        max_shift_len=max_shift_len,
+    )
+    if normalized is None:
+        return None
+
+    freq_band, sweep_band, f_max, df_ghz = normalized
+    f_shift = np.arange(-f_max, f_max + (0.5 * df_ghz), df_ghz, dtype=np.float64)
+    if f_shift.size <= 1:
+        return None
+
+    band_dtype = np.complex64 if np.iscomplexobj(sweep_band) else np.float32
+    band = np.nan_to_num(np.asarray(sweep_band, dtype=band_dtype), nan=0.0)
+    spectrum = np.zeros((int(f_shift.size),), dtype=band_dtype)
+    idx = np.round((freq_band - f_shift[0]) / df_ghz).astype(np.int64)
+    idx = np.clip(idx, 0, spectrum.size - 1)
+    spectrum[idx] = band
+    return spectrum
+
+
+def fft_mag_to_db(mag: np.ndarray) -> np.ndarray:
+    """Convert magnitude to dB with safe zero handling."""
+    mag_arr = np.asarray(mag, dtype=np.float32)
+    safe_mag = np.maximum(mag_arr, 0.0)
+    return (20.0 * np.log10(safe_mag + 1e-9)).astype(np.float32, copy=False)
+
+
+def _compute_fft_complex_row_direct(
+    sweep: np.ndarray,
+    freqs: Optional[np.ndarray],
+    bins: int,
+) -> np.ndarray:
+    prepared = prepare_fft_segment(sweep, freqs, fft_len=FFT_LEN)
+    if prepared is None:
+        return np.full((bins,), np.nan + 0j, dtype=np.complex64)
+
+    fft_seg, take_fft = prepared
+    fft_in = np.zeros((FFT_LEN,), dtype=np.complex64)
+    window = np.hanning(take_fft).astype(np.float32)
+    fft_in[:take_fft] = np.asarray(fft_seg, dtype=np.complex64) * window
+    spec = np.fft.ifft(fft_in)
+    return _fit_complex_bins(spec, bins)
+
+
+def _normalize_fft_mode(mode: str | None, symmetric: Optional[bool]) -> str:
+    if symmetric is not None:
+        return "symmetric" if symmetric else "direct"
+    normalized = str(mode or "symmetric").strip().lower()
+    if normalized in {"direct", "ordinary", "normal"}:
+        return "direct"
+    if normalized in {"symmetric", "sym", "mirror"}:
+        return "symmetric"
+    if normalized in {"positive_only", "positive-centered", "positive_centered", "zero_left"}:
+        return "positive_only"
+    if normalized in {"positive_only_exact", "positive-centered-exact", "positive_centered_exact", "zero_left_exact"}:
+        return "positive_only_exact"
+    raise ValueError(f"Unsupported FFT mode: {mode!r}")
+
+
+def compute_fft_complex_row(
+    sweep: np.ndarray,
+    freqs: Optional[np.ndarray],
+    bins: int,
+    *,
+    mode: str = "symmetric",
+    symmetric: Optional[bool] = None,
+) -> np.ndarray:
+    """Compute a complex FFT/IFFT row on the distance axis."""
+    if bins <= 0:
+        return np.zeros((0,), dtype=np.complex64)
+
+    fft_mode = _normalize_fft_mode(mode, symmetric)
+    if fft_mode == "direct":
+        return _compute_fft_complex_row_direct(sweep, freqs, bins)
+
+    if fft_mode == "positive_only":
+        spectrum_centered = build_positive_only_centered_ifft_spectrum(sweep, freqs, fft_len=FFT_LEN)
+    elif fft_mode == "positive_only_exact":
+        spectrum_centered = build_positive_only_exact_centered_ifft_spectrum(
+            sweep,
+            freqs,
+            max_shift_len=bins,
+        )
+    else:
+        spectrum_centered = build_symmetric_ifft_spectrum(sweep, freqs, fft_len=FFT_LEN)
+    if spectrum_centered is None:
+        return np.full((bins,), np.nan + 0j, dtype=np.complex64)
+
+    spec = np.fft.ifft(np.fft.ifftshift(np.asarray(spectrum_centered, dtype=np.complex64)))
+    return _fit_complex_bins(spec, bins)
+
+
+def compute_fft_mag_row(
+    sweep: np.ndarray,
+    freqs: Optional[np.ndarray],
+    bins: int,
+    *,
+    mode: str = "symmetric",
+    symmetric: Optional[bool] = None,
+) -> np.ndarray:
+    """Compute a linear FFT magnitude row."""
+    complex_row = compute_fft_complex_row(sweep, freqs, bins, mode=mode, symmetric=symmetric)
+    return np.abs(complex_row).astype(np.float32, copy=False)
+
+
+def compute_fft_row(
+    sweep: np.ndarray,
+    freqs: Optional[np.ndarray],
+    bins: int,
+    *,
+    mode: str = "symmetric",
+    symmetric: Optional[bool] = None,
+) -> np.ndarray:
+    """Compute a dB FFT row."""
+    return fft_mag_to_db(compute_fft_mag_row(sweep, freqs, bins, mode=mode, symmetric=symmetric))
+
+
+def compute_distance_axis(
+    freqs: Optional[np.ndarray],
+    bins: int,
+    *,
+    mode: str = "symmetric",
+    symmetric: Optional[bool] = None,
+) -> np.ndarray:
+    """Compute the one-way distance axis for IFFT output."""
+    if bins <= 0:
+        return np.zeros((0,), dtype=np.float64)
+    fft_mode = _normalize_fft_mode(mode, symmetric)
+    if fft_mode == "positive_only_exact":
+        geometry = _resolve_positive_only_exact_geometry(freqs, max_shift_len=bins)
+        if geometry is None:
+            return np.arange(bins, dtype=np.float64)
+        n_shift, df_hz = geometry
+        if (not np.isfinite(df_hz)) or df_hz <= 0.0 or n_shift <= 0:
+            return np.arange(bins, dtype=np.float64)
+        step_m = C_M_S / (2.0 * float(n_shift) * df_hz)
+        return np.arange(bins, dtype=np.float64) * step_m
+
+    if fft_mode in {"symmetric", "positive_only"}:
+        bounds = _finite_freq_bounds(freqs)
+        if bounds is None:
+            f_max = float(SWEEP_FREQ_MAX_GHZ)
+        else:
+            _, f_max = bounds
+        df_ghz = (2.0 * f_max) / max(1, FFT_LEN - 1)
+    else:
+        if freqs is None:
+            return np.arange(bins, dtype=np.float64)
+        freq_arr = np.asarray(freqs, dtype=np.float64)
+        finite = freq_arr[np.isfinite(freq_arr)]
+        if finite.size < 2:
+            return np.arange(bins, dtype=np.float64)
+        df_ghz = float((finite[-1] - finite[0]) / max(1, finite.size - 1))
+    df_hz = abs(df_ghz) * 1e9
+    if not np.isfinite(df_hz) or df_hz <= 0.0:
+        return np.arange(bins, dtype=np.float64)
+
+    step_m = C_M_S / (2.0 * FFT_LEN * df_hz)
+    return np.arange(bins, dtype=np.float64) * step_m

rfg_adc_plotter/processing/formatting.py

@@ -0,0 +1,71 @@
+"""Formatting and display-range helpers."""
+
+from __future__ import annotations
+
+from typing import Any, Mapping, Optional, Tuple
+
+import numpy as np
+
+
+def format_status_kv(data: Mapping[str, Any]) -> str:
+    """Convert status metrics into a compact single-line representation."""
+
+    def _fmt(value: Any) -> str:
+        if value is None:
+            return "NA"
+        try:
+            f_value = float(value)
+        except Exception:
+            return str(value)
+        if not np.isfinite(f_value):
+            return "nan"
+        if abs(f_value) >= 1000 or (0 < abs(f_value) < 0.01):
+            return f"{f_value:.3g}"
+        return f"{f_value:.3f}".rstrip("0").rstrip(".")
+
+    return "  ".join(f"{key}:{_fmt(value)}" for key, value in data.items())
+
+
+def parse_spec_clip(spec: Optional[str]) -> Optional[Tuple[float, float]]:
+    """Parse a waterfall percentile clip specification."""
+    if not spec:
+        return None
+    value = str(spec).strip().lower()
+    if value in ("off", "none", "no"):
+        return None
+    try:
+        p0, p1 = value.replace(";", ",").split(",")
+        low = float(p0)
+        high = float(p1)
+        if not (0.0 <= low < high <= 100.0):
+            return None
+        return (low, high)
+    except Exception:
+        return None
+
+
+def compute_auto_ylim(*series_list: Optional[np.ndarray]) -> Optional[Tuple[float, float]]:
+    """Compute a common Y-range with a small padding."""
+    y_min: Optional[float] = None
+    y_max: Optional[float] = None
+    for series in series_list:
+        if series is None:
+            continue
+        arr = np.asarray(series)
+        if arr.size == 0:
+            continue
+        finite = arr[np.isfinite(arr)]
+        if finite.size == 0:
+            continue
+        cur_min = float(np.min(finite))
+        cur_max = float(np.max(finite))
+        y_min = cur_min if y_min is None else min(y_min, cur_min)
+        y_max = cur_max if y_max is None else max(y_max, cur_max)
+
+    if y_min is None or y_max is None:
+        return None
+    if y_min == y_max:
+        pad = max(1.0, abs(y_min) * 0.05)
+    else:
+        pad = 0.05 * (y_max - y_min)
+    return (y_min - pad, y_max + pad)

rfg_adc_plotter/processing/normalization.py

@@ -0,0 +1,230 @@
+"""Sweep normalization helpers."""
+
+from __future__ import annotations
+
+from typing import Tuple
+
+import numpy as np
+
+
+def normalize_sweep_simple(raw: np.ndarray, calib: np.ndarray) -> np.ndarray:
+    """Simple element-wise raw/calib normalization."""
+    width = min(raw.size, calib.size)
+    if width <= 0:
+        return raw
+    out = np.full_like(raw, np.nan, dtype=np.float32)
+    with np.errstate(divide="ignore", invalid="ignore"):
+        out[:width] = raw[:width] / calib[:width]
+    out = np.nan_to_num(out, nan=np.nan, posinf=np.nan, neginf=np.nan)
+    return out
+
+
+def build_calib_envelopes(calib: np.ndarray) -> Tuple[np.ndarray, np.ndarray]:
+    """Estimate smooth lower/upper envelopes from local extrema."""
+    n = int(calib.size)
+    if n <= 0:
+        empty = np.zeros((0,), dtype=np.float32)
+        return empty, empty
+
+    values = np.asarray(calib, dtype=np.float32)
+    finite = np.isfinite(values)
+    if not np.any(finite):
+        zeros = np.zeros_like(values, dtype=np.float32)
+        return zeros, zeros
+
+    if not np.all(finite):
+        x = np.arange(n, dtype=np.float32)
+        values = values.copy()
+        values[~finite] = np.interp(x[~finite], x[finite], values[finite]).astype(np.float32)
+
+    if n < 3:
+        return values.copy(), values.copy()
+
+    x = np.arange(n, dtype=np.float32)
+
+    def _moving_average(series: np.ndarray, window: int) -> np.ndarray:
+        width = max(1, int(window))
+        if width <= 1 or series.size <= 2:
+            return np.asarray(series, dtype=np.float32).copy()
+        if width % 2 == 0:
+            width += 1
+        pad = width // 2
+        padded = np.pad(np.asarray(series, dtype=np.float32), (pad, pad), mode="edge")
+        kernel = np.full((width,), 1.0 / float(width), dtype=np.float32)
+        return np.convolve(padded, kernel, mode="valid").astype(np.float32)
+
+    def _smooth_extrema_envelope(use_max: bool) -> np.ndarray:
+        step = max(3, n // 32)
+        node_idx_list = []
+        for start in range(0, n, step):
+            stop = min(n, start + step)
+            segment = values[start:stop]
+            idx_rel = int(np.argmax(segment) if use_max else np.argmin(segment))
+            node_idx_list.append(start + idx_rel)
+
+        extrema_idx = np.unique(np.asarray(node_idx_list, dtype=np.int64))
+        if extrema_idx.size == 0:
+            extrema_idx = np.asarray([int(np.argmax(values) if use_max else np.argmin(values))], dtype=np.int64)
+
+        node_idx = np.unique(np.concatenate(([0], extrema_idx, [n - 1]))).astype(np.int64)
+        node_vals = values[node_idx].astype(np.float32, copy=True)
+        node_vals[0] = float(values[extrema_idx[0]])
+        node_vals[-1] = float(values[extrema_idx[-1]])
+        node_vals = _moving_average(node_vals, 3)
+        node_vals[0] = float(values[extrema_idx[0]])
+        node_vals[-1] = float(values[extrema_idx[-1]])
+
+        envelope = np.interp(x, node_idx.astype(np.float32), node_vals).astype(np.float32)
+        smooth_window = max(1, n // 64)
+        if smooth_window > 1:
+            envelope = _moving_average(envelope, smooth_window)
+        return envelope
+
+    upper = _smooth_extrema_envelope(use_max=True)
+    lower = _smooth_extrema_envelope(use_max=False)
+
+    swap = lower > upper
+    if np.any(swap):
+        tmp = upper[swap].copy()
+        upper[swap] = lower[swap]
+        lower[swap] = tmp
+
+    return lower, upper
+
+
+def normalize_sweep_projector(raw: np.ndarray, calib: np.ndarray) -> np.ndarray:
+    """Project raw values between calibration envelopes into [-1000, 1000]."""
+    width = min(raw.size, calib.size)
+    if width <= 0:
+        return raw
+
+    out = np.full_like(raw, np.nan, dtype=np.float32)
+    raw_seg = np.asarray(raw[:width], dtype=np.float32)
+    lower, upper = build_calib_envelopes(np.asarray(calib[:width], dtype=np.float32))
+    span = upper - lower
+
+    finite_span = span[np.isfinite(span) & (span > 0)]
+    if finite_span.size > 0:
+        eps = max(float(np.median(finite_span)) * 1e-6, 1e-9)
+    else:
+        eps = 1e-9
+
+    valid = (
+        np.isfinite(raw_seg)
+        & np.isfinite(lower)
+        & np.isfinite(upper)
+        & (span > eps)
+    )
+    if np.any(valid):
+        proj = np.empty_like(raw_seg, dtype=np.float32)
+        proj[valid] = ((2.0 * (raw_seg[valid] - lower[valid]) / span[valid]) - 1.0) * 1000.0
+        proj[valid] = np.clip(proj[valid], -1000.0, 1000.0)
+        proj[~valid] = np.nan
+        out[:width] = proj
+    return out
+
+
+def resample_envelope(envelope: np.ndarray, width: int) -> np.ndarray:
+    """Resample an envelope to the target sweep width on the index axis."""
+    target_width = int(width)
+    if target_width <= 0:
+        return np.zeros((0,), dtype=np.float32)
+
+    values = np.asarray(envelope, dtype=np.float32).reshape(-1)
+    if values.size == 0:
+        return np.full((target_width,), np.nan, dtype=np.float32)
+    if values.size == target_width:
+        return values.astype(np.float32, copy=True)
+
+    x_src = np.arange(values.size, dtype=np.float32)
+    finite = np.isfinite(values)
+    if not np.any(finite):
+        return np.full((target_width,), np.nan, dtype=np.float32)
+    if int(np.count_nonzero(finite)) == 1:
+        fill = float(values[finite][0])
+        return np.full((target_width,), fill, dtype=np.float32)
+
+    x_dst = np.linspace(0.0, float(values.size - 1), target_width, dtype=np.float32)
+    return np.interp(x_dst, x_src[finite], values[finite]).astype(np.float32)
+
+
+def fit_complex_calibration_to_width(calib: np.ndarray, width: int) -> np.ndarray:
+    """Fit a complex calibration curve to the signal width via trim/pad with ones."""
+    target_width = int(width)
+    if target_width <= 0:
+        return np.zeros((0,), dtype=np.complex64)
+
+    values = np.asarray(calib, dtype=np.complex64).reshape(-1)
+    if values.size <= 0:
+        return np.ones((target_width,), dtype=np.complex64)
+    if values.size == target_width:
+        return values.astype(np.complex64, copy=True)
+    if values.size > target_width:
+        return np.asarray(values[:target_width], dtype=np.complex64)
+
+    out = np.ones((target_width,), dtype=np.complex64)
+    out[: values.size] = values
+    return out
+
+
+def normalize_by_complex_calibration(
+    signal: np.ndarray,
+    calib: np.ndarray,
+    eps: float = 1e-9,
+) -> np.ndarray:
+    """Normalize complex signal by a complex calibration curve with zero protection."""
+    sig_arr = np.asarray(signal, dtype=np.complex64).reshape(-1)
+    if sig_arr.size <= 0:
+        return sig_arr.copy()
+
+    calib_fit = fit_complex_calibration_to_width(calib, sig_arr.size)
+    eps_abs = max(abs(float(eps)), 1e-12)
+    denom = np.asarray(calib_fit, dtype=np.complex64).copy()
+    safe_denom = (
+        np.isfinite(denom.real)
+        & np.isfinite(denom.imag)
+        & (np.abs(denom) >= eps_abs)
+    )
+    if np.any(~safe_denom):
+        denom[~safe_denom] = np.complex64(1.0 + 0.0j)
+
+    out = np.full(sig_arr.shape, np.nan + 0j, dtype=np.complex64)
+    valid_sig = np.isfinite(sig_arr.real) & np.isfinite(sig_arr.imag)
+    if np.any(valid_sig):
+        with np.errstate(divide="ignore", invalid="ignore"):
+            out[valid_sig] = sig_arr[valid_sig] / denom[valid_sig]
+
+    out_real = np.nan_to_num(out.real, nan=np.nan, posinf=np.nan, neginf=np.nan)
+    out_imag = np.nan_to_num(out.imag, nan=np.nan, posinf=np.nan, neginf=np.nan)
+    return (out_real + (1j * out_imag)).astype(np.complex64, copy=False)
+
+
+def normalize_by_envelope(raw: np.ndarray, envelope: np.ndarray) -> np.ndarray:
+    """Normalize a sweep by an envelope with safe resampling and zero protection."""
+    raw_in = np.asarray(raw).reshape(-1)
+    raw_dtype = np.complex64 if np.iscomplexobj(raw_in) else np.float32
+    raw_arr = np.asarray(raw_in, dtype=raw_dtype).reshape(-1)
+    if raw_arr.size == 0:
+        return raw_arr.copy()
+
+    env = resample_envelope(envelope, raw_arr.size)
+    out = np.full(raw_arr.shape, np.nan + 0j if np.iscomplexobj(raw_arr) else np.nan, dtype=raw_dtype)
+    den_eps = np.float32(1e-9)
+    valid = np.isfinite(raw_arr) & np.isfinite(env)
+    if np.any(valid):
+        with np.errstate(divide="ignore", invalid="ignore"):
+            denom = env[valid] + np.where(env[valid] >= 0.0, den_eps, -den_eps)
+            out[valid] = raw_arr[valid] / denom
+    if np.iscomplexobj(out):
+        out_real = np.nan_to_num(out.real, nan=np.nan, posinf=np.nan, neginf=np.nan)
+        out_imag = np.nan_to_num(out.imag, nan=np.nan, posinf=np.nan, neginf=np.nan)
+        return (out_real + (1j * out_imag)).astype(np.complex64, copy=False)
+    return np.nan_to_num(out, nan=np.nan, posinf=np.nan, neginf=np.nan)
+
+
+def normalize_by_calib(raw: np.ndarray, calib: np.ndarray, norm_type: str) -> np.ndarray:
+    """Apply the selected normalization method."""
+    norm = str(norm_type).strip().lower()
+    if norm == "simple":
+        return normalize_sweep_simple(raw, calib)
+    return normalize_sweep_projector(raw, calib)

rfg_adc_plotter/processing/peaks.py

@@ -0,0 +1,209 @@
+"""Peak-search helpers for FFT visualizations."""
+
+from __future__ import annotations
+
+from typing import Dict, List, Optional
+
+import numpy as np
+
+
+def find_peak_width_markers(xs: np.ndarray, ys: np.ndarray) -> Optional[Dict[str, float]]:
+    """Find the dominant non-zero peak and its half-height width."""
+    x_arr = np.asarray(xs, dtype=np.float64)
+    y_arr = np.asarray(ys, dtype=np.float64)
+    valid = np.isfinite(x_arr) & np.isfinite(y_arr) & (x_arr > 0.0)
+    if int(np.count_nonzero(valid)) < 3:
+        return None
+
+    x = x_arr[valid]
+    y = y_arr[valid]
+    x_min = float(x[0])
+    x_max = float(x[-1])
+    x_span = x_max - x_min
+    central_mask = (x >= (x_min + 0.25 * x_span)) & (x <= (x_min + 0.75 * x_span))
+    if int(np.count_nonzero(central_mask)) > 0:
+        central_idx = np.flatnonzero(central_mask)
+        peak_idx = int(central_idx[int(np.argmax(y[central_mask]))])
+    else:
+        peak_idx = int(np.argmax(y))
+    peak_y = float(y[peak_idx])
+    shoulder_gap = max(1, min(8, y.size // 64 if y.size > 0 else 1))
+    shoulder_width = max(4, min(32, y.size // 16 if y.size > 0 else 4))
+    left_lo = max(0, peak_idx - shoulder_gap - shoulder_width)
+    left_hi = max(0, peak_idx - shoulder_gap)
+    right_lo = min(y.size, peak_idx + shoulder_gap + 1)
+    right_hi = min(y.size, right_lo + shoulder_width)
+    background_parts = []
+    if left_hi > left_lo:
+        background_parts.append(float(np.nanmedian(y[left_lo:left_hi])))
+    if right_hi > right_lo:
+        background_parts.append(float(np.nanmedian(y[right_lo:right_hi])))
+    if background_parts:
+        background = float(np.mean(background_parts))
+    else:
+        background = float(np.nanpercentile(y, 10))
+    if not np.isfinite(peak_y) or not np.isfinite(background) or peak_y <= background:
+        return None
+
+    half_level = background + 0.5 * (peak_y - background)
+
+    def _interp_cross(x0: float, y0: float, x1: float, y1: float) -> float:
+        if not (np.isfinite(x0) and np.isfinite(y0) and np.isfinite(x1) and np.isfinite(y1)):
+            return x1
+        dy = y1 - y0
+        if dy == 0.0:
+            return x1
+        t = (half_level - y0) / dy
+        t = min(1.0, max(0.0, t))
+        return x0 + t * (x1 - x0)
+
+    left_x = float(x[0])
+    for i in range(peak_idx, 0, -1):
+        if y[i - 1] <= half_level <= y[i]:
+            left_x = _interp_cross(float(x[i - 1]), float(y[i - 1]), float(x[i]), float(y[i]))
+            break
+
+    right_x = float(x[-1])
+    for i in range(peak_idx, x.size - 1):
+        if y[i] >= half_level >= y[i + 1]:
+            right_x = _interp_cross(float(x[i]), float(y[i]), float(x[i + 1]), float(y[i + 1]))
+            break
+
+    width = right_x - left_x
+    if not np.isfinite(width) or width <= 0.0:
+        return None
+
+    return {
+        "background": background,
+        "left": left_x,
+        "right": right_x,
+        "width": width,
+        "amplitude": peak_y,
+    }
+
+
+def rolling_median_ref(xs: np.ndarray, ys: np.ndarray, window_ghz: float) -> np.ndarray:
+    """Compute a rolling median reference on a fixed-width X window."""
+    x = np.asarray(xs, dtype=np.float64)
+    y = np.asarray(ys, dtype=np.float64)
+    out = np.full(y.shape, np.nan, dtype=np.float64)
+    if x.size == 0 or y.size == 0 or x.size != y.size:
+        return out
+    width = float(window_ghz)
+    if not np.isfinite(width) or width <= 0.0:
+        return out
+    half = 0.5 * width
+    for i in range(x.size):
+        xi = x[i]
+        if not np.isfinite(xi):
+            continue
+        left = np.searchsorted(x, xi - half, side="left")
+        right = np.searchsorted(x, xi + half, side="right")
+        if right <= left:
+            continue
+        segment = y[left:right]
+        finite = np.isfinite(segment)
+        if not np.any(finite):
+            continue
+        out[i] = float(np.nanmedian(segment))
+    return out
+
+
+def find_top_peaks_over_ref(
+    xs: np.ndarray,
+    ys: np.ndarray,
+    ref: np.ndarray,
+    top_n: int = 3,
+) -> List[Dict[str, float]]:
+    """Find the top-N non-overlapping peaks above a reference curve."""
+    x = np.asarray(xs, dtype=np.float64)
+    y = np.asarray(ys, dtype=np.float64)
+    r = np.asarray(ref, dtype=np.float64)
+    if x.size < 3 or y.size != x.size or r.size != x.size:
+        return []
+
+    valid = np.isfinite(x) & np.isfinite(y) & np.isfinite(r)
+    if not np.any(valid):
+        return []
+    delta = np.full_like(y, np.nan, dtype=np.float64)
+    delta[valid] = y[valid] - r[valid]
+
+    candidates: List[int] = []
+    for i in range(1, x.size - 1):
+        if not (np.isfinite(delta[i - 1]) and np.isfinite(delta[i]) and np.isfinite(delta[i + 1])):
+            continue
+        if delta[i] <= 0.0:
+            continue
+        left_ok = delta[i] > delta[i - 1]
+        right_ok = delta[i] >= delta[i + 1]
+        alt_left_ok = delta[i] >= delta[i - 1]
+        alt_right_ok = delta[i] > delta[i + 1]
+        if (left_ok and right_ok) or (alt_left_ok and alt_right_ok):
+            candidates.append(i)
+    if not candidates:
+        return []
+
+    candidates.sort(key=lambda i: float(delta[i]), reverse=True)
+
+    def _interp_cross(x0: float, y0: float, x1: float, y1: float, y_cross: float) -> float:
+        dy = y1 - y0
+        if not np.isfinite(dy) or dy == 0.0:
+            return x1
+        t = (y_cross - y0) / dy
+        t = min(1.0, max(0.0, t))
+        return x0 + t * (x1 - x0)
+
+    picked: List[Dict[str, float]] = []
+    for idx in candidates:
+        peak_y = float(y[idx])
+        peak_ref = float(r[idx])
+        peak_h = float(delta[idx])
+        if not (np.isfinite(peak_y) and np.isfinite(peak_ref) and np.isfinite(peak_h)) or peak_h <= 0.0:
+            continue
+
+        half_level = peak_ref + 0.5 * peak_h
+
+        left_x = float(x[0])
+        for i in range(idx, 0, -1):
+            y0 = float(y[i - 1])
+            y1 = float(y[i])
+            if np.isfinite(y0) and np.isfinite(y1) and (y0 <= half_level <= y1):
+                left_x = _interp_cross(float(x[i - 1]), y0, float(x[i]), y1, half_level)
+                break
+
+        right_x = float(x[-1])
+        for i in range(idx, x.size - 1):
+            y0 = float(y[i])
+            y1 = float(y[i + 1])
+            if np.isfinite(y0) and np.isfinite(y1) and (y0 >= half_level >= y1):
+                right_x = _interp_cross(float(x[i]), y0, float(x[i + 1]), y1, half_level)
+                break
+
+        width = float(right_x - left_x)
+        if not np.isfinite(width) or width <= 0.0:
+            continue
+
+        overlap = False
+        for peak in picked:
+            if not (right_x <= peak["left"] or left_x >= peak["right"]):
+                overlap = True
+                break
+        if overlap:
+            continue
+
+        picked.append(
+            {
+                "x": float(x[idx]),
+                "peak_y": peak_y,
+                "ref": peak_ref,
+                "height": peak_h,
+                "left": left_x,
+                "right": right_x,
+                "width": width,
+            }
+        )
+        if len(picked) >= int(max(1, top_n)):
+            break
+
+    picked.sort(key=lambda peak: peak["x"])
+    return picked

rfg_adc_plotter/state/__init__.py

@@ -0,0 +1,7 @@
+"""Runtime state helpers."""
+
+from rfg_adc_plotter.state.background_buffer import BackgroundMedianBuffer
+from rfg_adc_plotter.state.ring_buffer import RingBuffer
+from rfg_adc_plotter.state.runtime_state import RuntimeState
+
+__all__ = ["BackgroundMedianBuffer", "RingBuffer", "RuntimeState"]

rfg_adc_plotter/state/background_buffer.py

@@ -0,0 +1,49 @@
+"""Rolling median buffer for persisted FFT background capture."""
+
+from __future__ import annotations
+
+from typing import Optional
+
+import numpy as np
+
+
+class BackgroundMedianBuffer:
+    """Store recent FFT rows and expose their median profile."""
+
+    def __init__(self, max_rows: int):
+        self.max_rows = max(1, int(max_rows))
+        self.width = 0
+        self.head = 0
+        self.count = 0
+        self.rows: Optional[np.ndarray] = None
+
+    def reset(self) -> None:
+        self.width = 0
+        self.head = 0
+        self.count = 0
+        self.rows = None
+
+    def push(self, fft_mag: np.ndarray) -> None:
+        values = np.asarray(fft_mag, dtype=np.float32).reshape(-1)
+        if values.size == 0:
+            return
+        if self.rows is None or self.width != values.size:
+            self.width = values.size
+            self.rows = np.full((self.max_rows, self.width), np.nan, dtype=np.float32)
+            self.head = 0
+            self.count = 0
+        self.rows[self.head, :] = values
+        self.head = (self.head + 1) % self.max_rows
+        self.count = min(self.count + 1, self.max_rows)
+
+    def median(self) -> Optional[np.ndarray]:
+        if self.rows is None or self.count <= 0:
+            return None
+        rows = self.rows[: self.count] if self.count < self.max_rows else self.rows
+        valid_rows = np.any(np.isfinite(rows), axis=1)
+        if not np.any(valid_rows):
+            return None
+        median = np.nanmedian(rows[valid_rows], axis=0).astype(np.float32, copy=False)
+        if not np.any(np.isfinite(median)):
+            return None
+        return np.nan_to_num(median, nan=0.0).astype(np.float32, copy=False)

rfg_adc_plotter/state/ring_buffer.py

@@ -0,0 +1,266 @@
+"""Ring buffers for raw sweeps and FFT waterfall rows."""
+
+from __future__ import annotations
+
+import time
+from typing import Optional
+
+import numpy as np
+
+from rfg_adc_plotter.constants import FFT_LEN, SWEEP_FREQ_MAX_GHZ, SWEEP_FREQ_MIN_GHZ, WF_WIDTH
+from rfg_adc_plotter.processing.fft import compute_distance_axis, compute_fft_mag_row, fft_mag_to_db
+
+
+class RingBuffer:
+    """Store raw sweeps, FFT rows, and matching time markers."""
+
+    def __init__(self, max_sweeps: int):
+        self.max_sweeps = int(max_sweeps)
+        self.fft_bins = FFT_LEN // 2 + 1
+        self.fft_mode = "symmetric"
+        self.width = 0
+        self.head = 0
+        self.ring: Optional[np.ndarray] = None
+        self.ring_time: Optional[np.ndarray] = None
+        self.ring_fft: Optional[np.ndarray] = None
+        self.ring_fft_input: Optional[np.ndarray] = None
+        self.x_shared: Optional[np.ndarray] = None
+        self.distance_axis: Optional[np.ndarray] = None
+        self.last_fft_mag: Optional[np.ndarray] = None
+        self.last_fft_db: Optional[np.ndarray] = None
+        self.last_freqs: Optional[np.ndarray] = None
+        self.y_min_fft: Optional[float] = None
+        self.y_max_fft: Optional[float] = None
+        self.last_push_valid_points = 0
+        self.last_push_fft_valid = False
+        self.last_push_axis_valid = False
+
+    @property
+    def is_ready(self) -> bool:
+        return self.ring is not None and self.ring_fft is not None
+
+    @property
+    def fft_symmetric(self) -> bool:
+        return self.fft_mode == "symmetric"
+
+    def reset(self) -> None:
+        """Drop all buffered sweeps and derived FFT state."""
+        self.width = 0
+        self.head = 0
+        self.ring = None
+        self.ring_time = None
+        self.ring_fft = None
+        self.ring_fft_input = None
+        self.x_shared = None
+        self.distance_axis = None
+        self.last_fft_mag = None
+        self.last_fft_db = None
+        self.last_freqs = None
+        self.y_min_fft = None
+        self.y_max_fft = None
+        self.last_push_valid_points = 0
+        self.last_push_fft_valid = False
+        self.last_push_axis_valid = False
+
+    def _promote_fft_cache(self, fft_mag: np.ndarray) -> bool:
+        fft_mag_arr = np.asarray(fft_mag, dtype=np.float32).reshape(-1)
+        if fft_mag_arr.size <= 0:
+            self.last_push_fft_valid = False
+            return False
+        fft_db = fft_mag_to_db(fft_mag_arr)
+        finite_db = fft_db[np.isfinite(fft_db)]
+        if finite_db.size <= 0:
+            self.last_push_fft_valid = False
+            return False
+
+        self.last_fft_mag = fft_mag_arr.copy()
+        self.last_fft_db = fft_db
+        fr_min = float(np.min(finite_db))
+        fr_max = float(np.max(finite_db))
+        self.y_min_fft = fr_min if self.y_min_fft is None else min(self.y_min_fft, fr_min)
+        self.y_max_fft = fr_max if self.y_max_fft is None else max(self.y_max_fft, fr_max)
+        self.last_push_fft_valid = True
+        return True
+
+    def _promote_distance_axis(self, axis: np.ndarray) -> bool:
+        axis_arr = np.asarray(axis, dtype=np.float64).reshape(-1)
+        if axis_arr.size <= 0 or not np.all(np.isfinite(axis_arr)):
+            self.last_push_axis_valid = False
+            return False
+        self.distance_axis = axis_arr.copy()
+        self.last_push_axis_valid = True
+        return True
+
+    def ensure_init(self, sweep_width: int) -> bool:
+        """Allocate or resize buffers. Returns True when geometry changed."""
+        target_width = max(int(sweep_width), int(WF_WIDTH))
+        changed = False
+        if self.ring is None or self.ring_time is None or self.ring_fft is None:
+            self.width = target_width
+            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)
+            self.ring_fft_input = np.full((self.max_sweeps, self.width), np.nan + 0j, dtype=np.complex64)
+            self.head = 0
+            changed = True
+        elif target_width != self.width:
+            new_ring = np.full((self.max_sweeps, target_width), np.nan, dtype=np.float32)
+            new_fft_input = np.full((self.max_sweeps, target_width), np.nan + 0j, dtype=np.complex64)
+            take = min(self.width, target_width)
+            new_ring[:, :take] = self.ring[:, :take]
+            if self.ring_fft_input is not None:
+                new_fft_input[:, :take] = self.ring_fft_input[:, :take]
+            self.ring = new_ring
+            self.ring_fft_input = new_fft_input
+            self.width = target_width
+            changed = True
+
+        if self.x_shared is None or self.x_shared.size != self.width:
+            self.x_shared = np.linspace(
+                SWEEP_FREQ_MIN_GHZ,
+                SWEEP_FREQ_MAX_GHZ,
+                self.width,
+                dtype=np.float32,
+            )
+            changed = True
+        return changed
+
+    def set_fft_mode(self, mode: str) -> bool:
+        """Switch FFT mode and rebuild cached FFT rows from stored sweeps."""
+        normalized_mode = str(mode).strip().lower()
+        if normalized_mode in {"ordinary", "normal"}:
+            normalized_mode = "direct"
+        if normalized_mode in {"sym", "mirror"}:
+            normalized_mode = "symmetric"
+        if normalized_mode in {"positive-centered", "positive_centered", "zero_left"}:
+            normalized_mode = "positive_only"
+        if normalized_mode in {"positive-centered-exact", "positive_centered_exact", "zero_left_exact"}:
+            normalized_mode = "positive_only_exact"
+        if normalized_mode not in {"direct", "symmetric", "positive_only", "positive_only_exact"}:
+            raise ValueError(f"Unsupported FFT mode: {mode!r}")
+        if normalized_mode == self.fft_mode:
+            return False
+
+        self.fft_mode = normalized_mode
+        self.y_min_fft = None
+        self.y_max_fft = None
+        self.last_push_fft_valid = False
+        self.last_push_axis_valid = False
+
+        if self.ring is None or self.ring_fft is None:
+            return True
+
+        self.ring_fft.fill(np.nan)
+        for row_idx in range(self.ring.shape[0]):
+            fft_source_row = self.ring_fft_input[row_idx] if self.ring_fft_input is not None else self.ring[row_idx]
+            if not np.any(np.isfinite(fft_source_row)):
+                continue
+            finite_idx = np.flatnonzero(np.isfinite(fft_source_row))
+            if finite_idx.size <= 0:
+                continue
+            row_width = int(finite_idx[-1]) + 1
+            fft_source = fft_source_row[:row_width]
+            freqs = self.last_freqs[:row_width] if self.last_freqs is not None and self.last_freqs.size >= row_width else self.last_freqs
+            fft_mag = compute_fft_mag_row(
+                fft_source,
+                freqs,
+                self.fft_bins,
+                mode=self.fft_mode,
+            )
+            self.ring_fft[row_idx, :] = fft_mag
+
+        if self.last_freqs is not None:
+            self._promote_distance_axis(
+                compute_distance_axis(
+                    self.last_freqs,
+                    self.fft_bins,
+                    mode=self.fft_mode,
+                )
+            )
+
+        last_idx = (self.head - 1) % self.max_sweeps
+        if self.ring_fft.shape[0] > 0:
+            last_fft = self.ring_fft[last_idx]
+            self._promote_fft_cache(last_fft)
+            finite = self.ring_fft[np.isfinite(self.ring_fft)]
+            if finite.size > 0:
+                finite_db = fft_mag_to_db(finite.astype(np.float32, copy=False))
+                self.y_min_fft = float(np.nanmin(finite_db))
+                self.y_max_fft = float(np.nanmax(finite_db))
+        return True
+
+    def set_symmetric_fft_enabled(self, enabled: bool) -> bool:
+        """Backward-compatible wrapper for the old two-state FFT switch."""
+        return self.set_fft_mode("symmetric" if enabled else "direct")
+
+    def push(
+        self,
+        sweep: np.ndarray,
+        freqs: Optional[np.ndarray] = None,
+        *,
+        fft_input: Optional[np.ndarray] = None,
+    ) -> None:
+        """Push a processed sweep and refresh raw/FFT buffers."""
+        if sweep is None or sweep.size == 0:
+            return
+        self.ensure_init(int(sweep.size))
+        if self.ring is None or self.ring_time is None or self.ring_fft is None or self.ring_fft_input is None:
+            return
+
+        row = np.full((self.width,), np.nan, dtype=np.float32)
+        take = min(self.width, int(sweep.size))
+        row[:take] = np.asarray(sweep[:take], dtype=np.float32)
+        self.last_push_valid_points = int(np.count_nonzero(np.isfinite(row[:take])))
+        self.ring[self.head, :] = row
+        self.ring_time[self.head] = time.time()
+        if freqs is not None:
+            self.last_freqs = np.asarray(freqs, dtype=np.float64).copy()
+
+        fft_source = np.asarray(fft_input if fft_input is not None else sweep).reshape(-1)
+        fft_row = np.full((self.width,), np.nan + 0j, dtype=np.complex64)
+        fft_take = min(self.width, int(fft_source.size))
+        fft_row[:fft_take] = np.asarray(fft_source[:fft_take], dtype=np.complex64)
+        self.ring_fft_input[self.head, :] = fft_row
+
+        fft_mag = compute_fft_mag_row(fft_source, freqs, self.fft_bins, mode=self.fft_mode)
+        self.ring_fft[self.head, :] = fft_mag
+        self._promote_fft_cache(fft_mag)
+        self._promote_distance_axis(compute_distance_axis(freqs, self.fft_bins, mode=self.fft_mode))
+        self.head = (self.head + 1) % self.max_sweeps
+
+    def get_display_raw(self) -> np.ndarray:
+        if self.ring is None:
+            return np.zeros((1, 1), dtype=np.float32)
+        base = self.ring if self.head == 0 else np.roll(self.ring, -self.head, axis=0)
+        return base.T
+
+    def get_display_raw_decimated(self, max_points: int) -> np.ndarray:
+        """Return a display-oriented raw waterfall with optional frequency decimation."""
+        if self.ring is None:
+            return np.zeros((1, 1), dtype=np.float32)
+
+        limit = int(max_points)
+        if limit <= 0 or self.width <= limit:
+            return self.get_display_raw()
+
+        row_order = np.arange(self.ring.shape[0], dtype=np.int64)
+        if self.head:
+            row_order = np.roll(row_order, -self.head)
+        col_idx = np.linspace(0, self.width - 1, limit, dtype=np.int64)
+        return self.ring[np.ix_(row_order, col_idx)].T
+
+    def get_display_fft_linear(self) -> np.ndarray:
+        if self.ring_fft is None:
+            return np.zeros((1, 1), dtype=np.float32)
+        base = self.ring_fft if self.head == 0 else np.roll(self.ring_fft, -self.head, axis=0)
+        return base.T
+
+    def get_last_fft_linear(self) -> Optional[np.ndarray]:
+        if self.last_fft_mag is None:
+            return None
+        return np.asarray(self.last_fft_mag, dtype=np.float32).copy()
+
+    def get_display_times(self) -> Optional[np.ndarray]:
+        if self.ring_time is None:
+            return None
+        return self.ring_time if self.head == 0 else np.roll(self.ring_time, -self.head)

rfg_adc_plotter/state/runtime_state.py

@@ -0,0 +1,54 @@
+"""Mutable state container for the PyQtGraph backend."""
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Dict, List, Optional
+
+import numpy as np
+
+from rfg_adc_plotter.constants import BACKGROUND_MEDIAN_SWEEPS
+from rfg_adc_plotter.state.background_buffer import BackgroundMedianBuffer
+from rfg_adc_plotter.state.ring_buffer import RingBuffer
+from rfg_adc_plotter.types import SweepAuxCurves, SweepInfo
+
+
+@dataclass
+class RuntimeState:
+    ring: RingBuffer
+    range_min_ghz: float = 0.0
+    range_max_ghz: float = 0.0
+    full_current_freqs: Optional[np.ndarray] = None
+    full_current_sweep_raw: Optional[np.ndarray] = None
+    full_current_sweep_codes: Optional[np.ndarray] = None
+    full_current_fft_source: Optional[np.ndarray] = None
+    full_current_aux_curves: SweepAuxCurves = None
+    full_current_aux_curves_codes: SweepAuxCurves = None
+    current_freqs: Optional[np.ndarray] = None
+    current_distances: Optional[np.ndarray] = None
+    current_sweep_raw: Optional[np.ndarray] = None
+    current_fft_source: Optional[np.ndarray] = None
+    current_fft_input: Optional[np.ndarray] = None
+    current_fft_complex: Optional[np.ndarray] = None
+    current_aux_curves: SweepAuxCurves = None
+    current_sweep_norm: Optional[np.ndarray] = None
+    current_fft_mag: Optional[np.ndarray] = None
+    current_fft_db: Optional[np.ndarray] = None
+    last_calib_sweep: Optional[np.ndarray] = None
+    calib_envelope: Optional[np.ndarray] = None
+    calib_file_path: Optional[str] = None
+    complex_calib_curve: Optional[np.ndarray] = None
+    complex_calib_file_path: Optional[str] = None
+    background_buffer: BackgroundMedianBuffer = field(
+        default_factory=lambda: BackgroundMedianBuffer(BACKGROUND_MEDIAN_SWEEPS)
+    )
+    background_profile: Optional[np.ndarray] = None
+    background_file_path: Optional[str] = None
+    current_info: Optional[SweepInfo] = None
+    current_peak_width: Optional[float] = None
+    current_peak_amplitude: Optional[float] = None
+    peak_candidates: List[Dict[str, float]] = field(default_factory=list)
+    plot_dirty: bool = False
+
+    def mark_dirty(self) -> None:
+        self.plot_dirty = True

rfg_adc_plotter/types.py

@@ -0,0 +1,34 @@
+"""Shared runtime and parser types."""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+from typing import Any, Dict, Literal, Optional, Tuple, TypeAlias, Union
+
+import numpy as np
+
+
+Number = Union[int, float]
+SignalKind = Literal["bin_iq", "bin_logdet"]
+SweepInfo = Dict[str, Any]
+SweepData = Dict[str, np.ndarray]
+SweepAuxCurves = Optional[Tuple[np.ndarray, np.ndarray]]
+SweepPacket = Tuple[np.ndarray, SweepInfo, SweepAuxCurves]
+
+
+@dataclass(frozen=True)
+class StartEvent:
+    ch: Optional[int] = None
+    signal_kind: Optional[SignalKind] = None
+
+
+@dataclass(frozen=True)
+class PointEvent:
+    ch: int
+    x: int
+    y: float
+    aux: Optional[Tuple[float, float]] = None
+    signal_kind: Optional[SignalKind] = None
+
+
+ParserEvent: TypeAlias = Union[StartEvent, PointEvent]

tests/test_background_buffer.py

@@ -0,0 +1,44 @@
+from __future__ import annotations
+
+import numpy as np
+import unittest
+
+from rfg_adc_plotter.state.background_buffer import BackgroundMedianBuffer
+
+
+class BackgroundMedianBufferTests(unittest.TestCase):
+    def test_buffer_returns_median_for_partial_fill(self):
+        buffer = BackgroundMedianBuffer(max_rows=4)
+        buffer.push(np.asarray([1.0, 5.0, 9.0], dtype=np.float32))
+        buffer.push(np.asarray([3.0, 7.0, 11.0], dtype=np.float32))
+
+        median = buffer.median()
+
+        self.assertIsNotNone(median)
+        self.assertTrue(np.allclose(median, np.asarray([2.0, 6.0, 10.0], dtype=np.float32)))
+
+    def test_buffer_wraparound_keeps_latest_rows(self):
+        buffer = BackgroundMedianBuffer(max_rows=2)
+        buffer.push(np.asarray([1.0, 5.0], dtype=np.float32))
+        buffer.push(np.asarray([3.0, 7.0], dtype=np.float32))
+        buffer.push(np.asarray([9.0, 11.0], dtype=np.float32))
+
+        median = buffer.median()
+
+        self.assertIsNotNone(median)
+        self.assertTrue(np.allclose(median, np.asarray([6.0, 9.0], dtype=np.float32)))
+
+    def test_buffer_reset_clears_state(self):
+        buffer = BackgroundMedianBuffer(max_rows=2)
+        buffer.push(np.asarray([1.0, 2.0], dtype=np.float32))
+
+        buffer.reset()
+
+        self.assertIsNone(buffer.rows)
+        self.assertIsNone(buffer.median())
+        self.assertEqual(buffer.count, 0)
+        self.assertEqual(buffer.head, 0)
+
+
+if __name__ == "__main__":
+    unittest.main()

tests/test_cli.py

@@ -0,0 +1,57 @@
+from __future__ import annotations
+
+import subprocess
+import sys
+import unittest
+from pathlib import Path
+
+from rfg_adc_plotter.cli import build_parser
+
+
+ROOT = Path(__file__).resolve().parents[1]
+
+
+def _run(*args: str) -> subprocess.CompletedProcess[str]:
+    return subprocess.run(
+        [sys.executable, *args],
+        cwd=ROOT,
+        text=True,
+        capture_output=True,
+        check=False,
+    )
+
+
+class CliTests(unittest.TestCase):
+    def test_logscale_and_opengl_are_opt_in(self):
+        args = build_parser().parse_args(["/dev/null"])
+        self.assertFalse(args.logscale)
+        self.assertFalse(args.opengl)
+        self.assertAlmostEqual(float(args.tty_range_v), 5.0, places=6)
+
+        args_log = build_parser().parse_args(["/dev/null", "--logscale", "--opengl", "--tty-range-v", "2.5"])
+        self.assertTrue(args_log.logscale)
+        self.assertTrue(args_log.opengl)
+        self.assertAlmostEqual(float(args_log.tty_range_v), 2.5, places=6)
+
+    def test_wrapper_help_works(self):
+        proc = _run("RFG_ADC_dataplotter.py", "--help")
+        self.assertEqual(proc.returncode, 0)
+        self.assertIn("usage:", proc.stdout)
+        self.assertIn("--peak_search", proc.stdout)
+
+    def test_module_help_works(self):
+        proc = _run("-m", "rfg_adc_plotter.main", "--help")
+        self.assertEqual(proc.returncode, 0)
+        self.assertIn("usage:", proc.stdout)
+        self.assertIn("--parser_16_bit_x2", proc.stdout)
+        self.assertIn("--parser_complex_ascii", proc.stdout)
+        self.assertIn("--opengl", proc.stdout)
+
+    def test_backend_mpl_reports_removal(self):
+        proc = _run("-m", "rfg_adc_plotter.main", "/dev/null", "--backend", "mpl")
+        self.assertNotEqual(proc.returncode, 0)
+        self.assertIn("Matplotlib backend removed", proc.stderr)
+
+
+if __name__ == "__main__":
+    unittest.main()

tests/test_processing.py

@@ -0,0 +1,694 @@
+from __future__ import annotations
+
+import os
+import tempfile
+import numpy as np
+import unittest
+
+from rfg_adc_plotter.constants import C_M_S, FFT_LEN, SWEEP_FREQ_MAX_GHZ, SWEEP_FREQ_MIN_GHZ
+from rfg_adc_plotter.gui.pyqtgraph_backend import (
+    apply_distance_cut_to_axis,
+    apply_working_range,
+    apply_working_range_to_aux_curves,
+    build_logdet_voltage_fft_input,
+    build_main_window_layout,
+    coalesce_packets_for_ui,
+    compute_background_subtracted_bscan_levels,
+    compute_aux_phase_curve,
+    convert_tty_i16_to_voltage,
+    decimate_curve_for_display,
+    resolve_axis_bounds,
+    resolve_heavy_refresh_stride,
+    resolve_initial_window_size,
+    resolve_distance_cut_start,
+    sanitize_curve_data_for_display,
+    sanitize_image_for_display,
+    set_image_rect_if_ready,
+    resolve_visible_fft_curves,
+    resolve_visible_aux_curves,
+)
+from rfg_adc_plotter.processing.calibration import (
+    build_calib_envelope,
+    build_complex_calibration_curve,
+    calibrate_freqs,
+    load_calib_envelope,
+    load_complex_calibration,
+    recalculate_calibration_c,
+    save_calib_envelope,
+    save_complex_calibration,
+)
+from rfg_adc_plotter.processing.background import (
+    load_fft_background,
+    save_fft_background,
+    subtract_fft_background,
+)
+from rfg_adc_plotter.processing.fft import (
+    build_positive_only_exact_centered_ifft_spectrum,
+    build_positive_only_centered_ifft_spectrum,
+    build_symmetric_ifft_spectrum,
+    compute_distance_axis,
+    compute_fft_complex_row,
+    compute_fft_mag_row,
+    compute_fft_row,
+    fft_mag_to_db,
+)
+from rfg_adc_plotter.processing.normalization import (
+    build_calib_envelopes,
+    fit_complex_calibration_to_width,
+    normalize_by_calib,
+    normalize_by_complex_calibration,
+    normalize_by_envelope,
+    resample_envelope,
+)
+from rfg_adc_plotter.processing.peaks import find_peak_width_markers, find_top_peaks_over_ref, rolling_median_ref
+
+
+class ProcessingTests(unittest.TestCase):
+    def test_convert_tty_i16_to_voltage_maps_and_clips_full_range(self):
+        codes = np.asarray([-32768.0, -16384.0, 0.0, 16384.0, 32767.0], dtype=np.float32)
+        volts = convert_tty_i16_to_voltage(codes, 5.0)
+
+        self.assertEqual(volts.shape, codes.shape)
+        self.assertAlmostEqual(float(volts[0]), -5.0, places=6)
+        self.assertAlmostEqual(float(volts[2]), 0.0, places=6)
+        self.assertAlmostEqual(float(volts[-1]), 5.0, places=6)
+        self.assertTrue(np.all(volts >= -5.0))
+        self.assertTrue(np.all(volts <= 5.0))
+
+    def test_build_logdet_voltage_fft_input_converts_codes_and_exponentiates(self):
+        codes = np.asarray([-32768.0, 0.0, 32767.0], dtype=np.float32)
+        volts, fft_input = build_logdet_voltage_fft_input(codes, 5.0)
+
+        self.assertEqual(volts.shape, codes.shape)
+        self.assertEqual(fft_input.shape, codes.shape)
+        self.assertAlmostEqual(float(volts[0]), -5.0, places=6)
+        self.assertAlmostEqual(float(volts[1]), 0.0, places=6)
+        self.assertAlmostEqual(float(volts[2]), 5.0, places=6)
+        self.assertTrue(np.allclose(fft_input, np.exp(volts.astype(np.float32))))
+
+    def test_build_logdet_voltage_fft_input_clips_exp_argument_and_respects_range(self):
+        codes = np.asarray([32767.0], dtype=np.float32)
+        volts_5, fft_5 = build_logdet_voltage_fft_input(codes, 5.0, exp_input_limit=2.0)
+        volts_10, fft_10 = build_logdet_voltage_fft_input(codes, 10.0, exp_input_limit=2.0)
+
+        self.assertAlmostEqual(float(volts_5[0]), 5.0, places=6)
+        self.assertAlmostEqual(float(volts_10[0]), 10.0, places=6)
+        self.assertAlmostEqual(float(fft_5[0]), float(np.exp(np.float32(2.0))), places=5)
+        self.assertAlmostEqual(float(fft_10[0]), float(np.exp(np.float32(2.0))), places=5)
+        self.assertTrue(np.isfinite(fft_5[0]))
+        self.assertTrue(np.isfinite(fft_10[0]))
+
+    def test_recalculate_calibration_preserves_requested_edges(self):
+        coeffs = recalculate_calibration_c(np.asarray([0.0, 1.0, 0.025], dtype=np.float64), 3.3, 14.3)
+        y0 = coeffs[0] + coeffs[1] * 3.3 + coeffs[2] * (3.3 ** 2)
+        y1 = coeffs[0] + coeffs[1] * 14.3 + coeffs[2] * (14.3 ** 2)
+        self.assertTrue(np.isclose(y0, 3.3))
+        self.assertTrue(np.isclose(y1, 14.3))
+
+    def test_calibrate_freqs_returns_monotonic_axis_and_same_shape(self):
+        sweep = {"F": np.linspace(3.3, 14.3, 32), "I": np.linspace(-1.0, 1.0, 32)}
+        calibrated = calibrate_freqs(sweep)
+        self.assertEqual(calibrated["F"].shape, (32,))
+        self.assertEqual(calibrated["I"].shape, (32,))
+        self.assertTrue(np.all(np.diff(calibrated["F"]) >= 0.0))
+
+    def test_calibrate_freqs_keeps_complex_payload(self):
+        sweep = {
+            "F": np.linspace(3.3, 14.3, 32),
+            "I": np.exp(1j * np.linspace(0.0, np.pi, 32)).astype(np.complex64),
+        }
+        calibrated = calibrate_freqs(sweep)
+
+        self.assertEqual(calibrated["F"].shape, (32,))
+        self.assertEqual(calibrated["I"].shape, (32,))
+        self.assertTrue(np.iscomplexobj(calibrated["I"]))
+        self.assertTrue(np.all(np.isfinite(calibrated["I"])))
+
+    def test_normalizers_and_envelopes_return_finite_ranges(self):
+        calib = (np.sin(np.linspace(0.0, 4.0 * np.pi, 64)) * 5.0).astype(np.float32)
+        raw = calib * 0.75
+        lower, upper = build_calib_envelopes(calib)
+        self.assertEqual(lower.shape, calib.shape)
+        self.assertEqual(upper.shape, calib.shape)
+        self.assertTrue(np.all(lower <= upper))
+        self.assertTrue(np.all(np.isfinite(upper)))
+        self.assertLess(
+            float(np.mean(np.abs(np.diff(upper, n=2)))),
+            float(np.mean(np.abs(np.diff(calib, n=2)))),
+        )
+
+        simple = normalize_by_calib(raw, calib + 10.0, norm_type="simple")
+        projector = normalize_by_calib(raw, calib, norm_type="projector")
+        self.assertEqual(simple.shape, raw.shape)
+        self.assertEqual(projector.shape, raw.shape)
+        self.assertTrue(np.any(np.isfinite(simple)))
+        self.assertTrue(np.any(np.isfinite(projector)))
+
+    def test_file_calibration_envelope_roundtrip_and_division(self):
+        raw = (np.sin(np.linspace(0.0, 8.0 * np.pi, 128)) * 50.0 + 100.0).astype(np.float32)
+        envelope = build_calib_envelope(raw)
+        normalized = normalize_by_envelope(raw, envelope)
+        resampled = resample_envelope(envelope, 96)
+
+        self.assertEqual(envelope.shape, raw.shape)
+        self.assertEqual(normalized.shape, raw.shape)
+        self.assertEqual(resampled.shape, (96,))
+        self.assertTrue(np.any(np.isfinite(normalized)))
+        self.assertTrue(np.all(np.isfinite(envelope)))
+
+        with tempfile.TemporaryDirectory() as tmp_dir:
+            path = os.path.join(tmp_dir, "calibration_envelope")
+            saved_path = save_calib_envelope(path, envelope)
+            loaded = load_calib_envelope(saved_path)
+            self.assertTrue(saved_path.endswith(".npy"))
+            self.assertTrue(np.allclose(loaded, envelope))
+
+    def test_normalize_by_envelope_adds_small_epsilon_to_zero_denominator(self):
+        raw = np.asarray([1.0, 2.0, 3.0], dtype=np.float32)
+        envelope = np.asarray([0.0, 1.0, -1.0], dtype=np.float32)
+        normalized = normalize_by_envelope(raw, envelope)
+
+        self.assertTrue(np.all(np.isfinite(normalized)))
+        self.assertGreater(normalized[0], 1e8)
+        self.assertAlmostEqual(float(normalized[1]), 2.0, places=5)
+        self.assertAlmostEqual(float(normalized[2]), -3.0, places=5)
+
+    def test_normalize_by_envelope_supports_complex_input(self):
+        raw = np.asarray([1.0 + 1.0j, 2.0 - 2.0j], dtype=np.complex64)
+        envelope = np.asarray([1.0, 2.0], dtype=np.float32)
+        normalized = normalize_by_envelope(raw, envelope)
+
+        self.assertTrue(np.iscomplexobj(normalized))
+        self.assertTrue(np.all(np.isfinite(normalized)))
+        self.assertTrue(np.allclose(normalized, np.asarray([1.0 + 1.0j, 1.0 - 1.0j], dtype=np.complex64)))
+
+    def test_load_calib_envelope_rejects_empty_payload(self):
+        with tempfile.TemporaryDirectory() as tmp_dir:
+            path = os.path.join(tmp_dir, "empty.npy")
+            np.save(path, np.zeros((0,), dtype=np.float32))
+            with self.assertRaises(ValueError):
+                load_calib_envelope(path)
+
+    def test_complex_calibration_curve_roundtrip(self):
+        ch1 = np.asarray([1.0, 2.0, 3.0], dtype=np.float32)
+        ch2 = np.asarray([0.5, -1.0, 4.0], dtype=np.float32)
+        curve = build_complex_calibration_curve(ch1, ch2)
+        expected = np.asarray([1.0 + 0.5j, 2.0 - 1.0j, 3.0 + 4.0j], dtype=np.complex64)
+
+        self.assertTrue(np.iscomplexobj(curve))
+        self.assertTrue(np.allclose(curve, expected))
+
+        with tempfile.TemporaryDirectory() as tmp_dir:
+            path = os.path.join(tmp_dir, "complex_calibration")
+            saved_path = save_complex_calibration(path, curve)
+            loaded = load_complex_calibration(saved_path)
+            self.assertTrue(saved_path.endswith(".npy"))
+            self.assertEqual(loaded.dtype, np.complex64)
+            self.assertTrue(np.allclose(loaded, expected))
+
+    def test_fit_complex_calibration_to_width_pads_or_trims(self):
+        calib = np.asarray([1.0 + 1.0j, 2.0 + 2.0j], dtype=np.complex64)
+        padded = fit_complex_calibration_to_width(calib, 4)
+        trimmed = fit_complex_calibration_to_width(
+            np.asarray([1.0 + 1.0j, 2.0 + 2.0j, 3.0 + 3.0j], dtype=np.complex64),
+            2,
+        )
+
+        self.assertEqual(padded.shape, (4,))
+        self.assertTrue(np.allclose(padded, np.asarray([1.0 + 1.0j, 2.0 + 2.0j, 1.0 + 0.0j, 1.0 + 0.0j], dtype=np.complex64)))
+        self.assertEqual(trimmed.shape, (2,))
+        self.assertTrue(np.allclose(trimmed, np.asarray([1.0 + 1.0j, 2.0 + 2.0j], dtype=np.complex64)))
+
+    def test_normalize_by_complex_calibration_handles_zero_and_length_mismatch(self):
+        signal = np.asarray([2.0 + 2.0j, 4.0 + 0.0j, 3.0 + 3.0j], dtype=np.complex64)
+        calib = np.asarray([1.0 + 1.0j, 0.0 + 0.0j], dtype=np.complex64)
+        normalized = normalize_by_complex_calibration(signal, calib)
+        expected = np.asarray([2.0 + 0.0j, 4.0 + 0.0j, 3.0 + 3.0j], dtype=np.complex64)
+
+        self.assertTrue(np.iscomplexobj(normalized))
+        self.assertTrue(np.all(np.isfinite(normalized)))
+        self.assertTrue(np.allclose(normalized, expected))
+
+    def test_fft_background_roundtrip_and_rejects_non_1d_payload(self):
+        background = np.asarray([0.5, 1.5, 2.5], dtype=np.float32)
+        with tempfile.TemporaryDirectory() as tmp_dir:
+            path = os.path.join(tmp_dir, "fft_background")
+            saved_path = save_fft_background(path, background)
+            loaded = load_fft_background(saved_path)
+            self.assertTrue(saved_path.endswith(".npy"))
+            self.assertTrue(np.allclose(loaded, background))
+
+            invalid_path = os.path.join(tmp_dir, "fft_background_invalid.npy")
+            np.save(invalid_path, np.zeros((2, 2), dtype=np.float32))
+            with self.assertRaises(ValueError):
+                load_fft_background(invalid_path)
+
+    def test_subtract_fft_background_clamps_negative_residuals_to_zero(self):
+        signal = np.asarray([1.0, 2.0, 3.0], dtype=np.float32)
+        background = np.asarray([1.0, 1.5, 5.0], dtype=np.float32)
+        subtracted = subtract_fft_background(signal, background)
+
+        self.assertTrue(np.allclose(subtracted, np.asarray([0.0, 0.5, 0.0], dtype=np.float32)))
+        self.assertTrue(np.allclose(subtract_fft_background(signal, signal), 0.0))
+
+    def test_apply_working_range_crops_sweep_to_selected_band(self):
+        freqs = np.linspace(3.3, 14.3, 12, dtype=np.float64)
+        sweep = np.arange(12, dtype=np.float32)
+        cropped_freqs, cropped_sweep = apply_working_range(freqs, sweep, 5.0, 9.0)
+
+        self.assertGreater(cropped_freqs.size, 0)
+        self.assertEqual(cropped_freqs.shape, cropped_sweep.shape)
+        self.assertGreaterEqual(float(np.min(cropped_freqs)), 5.0)
+        self.assertLessEqual(float(np.max(cropped_freqs)), 9.0)
+
+    def test_apply_working_range_returns_empty_when_no_points_match(self):
+        freqs = np.linspace(3.3, 14.3, 12, dtype=np.float64)
+        sweep = np.arange(12, dtype=np.float32)
+        cropped_freqs, cropped_sweep = apply_working_range(freqs, sweep, 20.0, 21.0)
+
+        self.assertEqual(cropped_freqs.shape, (0,))
+        self.assertEqual(cropped_sweep.shape, (0,))
+
+    def test_apply_working_range_to_aux_curves_uses_same_mask_as_raw_sweep(self):
+        freqs = np.linspace(3.3, 14.3, 6, dtype=np.float64)
+        sweep = np.asarray([0.0, 1.0, np.nan, 3.0, 4.0, 5.0], dtype=np.float32)
+        aux = (
+            np.asarray([10.0, 11.0, 12.0, 13.0, 14.0, 15.0], dtype=np.float32),
+            np.asarray([20.0, 21.0, 22.0, 23.0, 24.0, 25.0], dtype=np.float32),
+        )
+
+        cropped_freqs, cropped_sweep = apply_working_range(freqs, sweep, 4.0, 12.5)
+        cropped_aux = apply_working_range_to_aux_curves(freqs, sweep, aux, 4.0, 12.5)
+
+        self.assertIsNotNone(cropped_aux)
+        self.assertEqual(cropped_aux[0].shape, cropped_freqs.shape)
+        self.assertEqual(cropped_aux[1].shape, cropped_freqs.shape)
+        self.assertEqual(cropped_aux[0].shape, cropped_sweep.shape)
+        self.assertTrue(np.allclose(cropped_aux[0], np.asarray([11.0, 13.0, 14.0], dtype=np.float32)))
+        self.assertTrue(np.allclose(cropped_aux[1], np.asarray([21.0, 23.0, 24.0], dtype=np.float32)))
+
+    def test_resolve_visible_aux_curves_obeys_checkbox_state(self):
+        aux = (
+            np.asarray([1.0, 2.0], dtype=np.float32),
+            np.asarray([3.0, 4.0], dtype=np.float32),
+        )
+
+        self.assertIsNone(resolve_visible_aux_curves(aux, enabled=False))
+        visible = resolve_visible_aux_curves(aux, enabled=True)
+        self.assertIsNotNone(visible)
+        self.assertTrue(np.allclose(visible[0], aux[0]))
+        self.assertTrue(np.allclose(visible[1], aux[1]))
+
+    def test_compute_aux_phase_curve_returns_atan2_of_aux_channels(self):
+        aux = (
+            np.asarray([1.0, 1.0, -1.0, 0.0], dtype=np.float32),
+            np.asarray([0.0, 1.0, 1.0, 1.0], dtype=np.float32),
+        )
+
+        phase = compute_aux_phase_curve(aux)
+
+        self.assertIsNotNone(phase)
+        expected = np.asarray([0.0, np.pi / 4.0, 3.0 * np.pi / 4.0, np.pi / 2.0], dtype=np.float32)
+        self.assertEqual(phase.shape, expected.shape)
+        self.assertTrue(np.allclose(phase, expected, atol=1e-6))
+
+    def test_decimate_curve_for_display_preserves_small_series(self):
+        xs = np.linspace(3.3, 14.3, 64, dtype=np.float64)
+        ys = np.linspace(-1.0, 1.0, 64, dtype=np.float32)
+
+        decimated_x, decimated_y = decimate_curve_for_display(xs, ys, max_points=128)
+
+        self.assertTrue(np.allclose(decimated_x, xs))
+        self.assertTrue(np.allclose(decimated_y, ys))
+
+    def test_decimate_curve_for_display_limits_points_and_keeps_endpoints(self):
+        xs = np.linspace(3.3, 14.3, 10000, dtype=np.float64)
+        ys = np.sin(np.linspace(0.0, 12.0 * np.pi, 10000)).astype(np.float32)
+
+        decimated_x, decimated_y = decimate_curve_for_display(xs, ys, max_points=512)
+
+        self.assertLessEqual(decimated_x.size, 512)
+        self.assertEqual(decimated_x.shape, decimated_y.shape)
+        self.assertAlmostEqual(float(decimated_x[0]), float(xs[0]), places=12)
+        self.assertAlmostEqual(float(decimated_x[-1]), float(xs[-1]), places=12)
+        self.assertAlmostEqual(float(decimated_y[0]), float(ys[0]), places=6)
+        self.assertAlmostEqual(float(decimated_y[-1]), float(ys[-1]), places=6)
+
+    def test_coalesce_packets_for_ui_keeps_newest_packets(self):
+        packets = [
+            (np.asarray([float(idx)], dtype=np.float32), {"sweep": idx}, None)
+            for idx in range(6)
+        ]
+
+        kept, skipped = coalesce_packets_for_ui(packets, max_packets=2)
+
+        self.assertEqual(skipped, 4)
+        self.assertEqual(len(kept), 2)
+        self.assertEqual(int(kept[0][1]["sweep"]), 4)
+        self.assertEqual(int(kept[1][1]["sweep"]), 5)
+
+    def test_coalesce_packets_for_ui_never_returns_empty_for_non_empty_input(self):
+        packets = [
+            (np.asarray([1.0], dtype=np.float32), {"sweep": 1}, None),
+        ]
+
+        kept, skipped = coalesce_packets_for_ui(packets, max_packets=0)
+
+        self.assertEqual(skipped, 0)
+        self.assertEqual(len(kept), 1)
+        self.assertEqual(int(kept[0][1]["sweep"]), 1)
+
+    def test_coalesce_packets_for_ui_switches_to_latest_only_on_large_backlog(self):
+        packets = [
+            (np.asarray([float(idx)], dtype=np.float32), {"sweep": idx}, None)
+            for idx in range(40)
+        ]
+
+        kept, skipped = coalesce_packets_for_ui(packets, max_packets=8, backlog_packets=40)
+
+        self.assertEqual(skipped, 39)
+        self.assertEqual(len(kept), 1)
+        self.assertEqual(int(kept[0][1]["sweep"]), 39)
+
+    def test_resolve_heavy_refresh_stride_increases_with_backlog(self):
+        self.assertEqual(resolve_heavy_refresh_stride(0, max_packets=8), 1)
+        self.assertEqual(resolve_heavy_refresh_stride(20, max_packets=8), 2)
+        self.assertEqual(resolve_heavy_refresh_stride(40, max_packets=8), 4)
+
+    def test_sanitize_curve_data_for_display_rejects_fully_nonfinite_series(self):
+        xs, ys = sanitize_curve_data_for_display(
+            np.asarray([np.nan, np.nan], dtype=np.float64),
+            np.asarray([np.nan, np.nan], dtype=np.float32),
+        )
+
+        self.assertEqual(xs.shape, (0,))
+        self.assertEqual(ys.shape, (0,))
+
+    def test_sanitize_image_for_display_rejects_fully_nonfinite_frame(self):
+        data = sanitize_image_for_display(np.full((4, 4), np.nan, dtype=np.float32))
+
+        self.assertIsNone(data)
+
+    def test_set_image_rect_if_ready_skips_uninitialized_image(self):
+        class _DummyImageItem:
+            def __init__(self):
+                self.calls = 0
+
+            def width(self):
+                return None
+
+            def height(self):
+                return None
+
+            def setRect(self, *_args):
+                self.calls += 1
+
+        image_item = _DummyImageItem()
+        applied = set_image_rect_if_ready(image_item, 0.0, 0.0, 10.0, 1.0)
+
+        self.assertFalse(applied)
+        self.assertEqual(image_item.calls, 0)
+
+    def test_resolve_axis_bounds_rejects_nonfinite_ranges(self):
+        bounds = resolve_axis_bounds(np.asarray([np.nan, np.inf], dtype=np.float64))
+
+        self.assertIsNone(bounds)
+
+    def test_resolve_distance_cut_start_interpolates_with_percent(self):
+        axis = np.asarray([0.0, 1.0, 2.0, 3.0], dtype=np.float64)
+        cut_start = resolve_distance_cut_start(axis, 50.0)
+
+        self.assertIsNotNone(cut_start)
+        self.assertAlmostEqual(float(cut_start), 1.5, places=6)
+
+    def test_apply_distance_cut_to_axis_keeps_farthest_point_for_extreme_cut(self):
+        axis = np.asarray([0.0, 1.0, 2.0, 3.0], dtype=np.float64)
+        cut_axis, keep_mask = apply_distance_cut_to_axis(axis, 10.0)
+
+        self.assertEqual(cut_axis.shape, (1,))
+        self.assertEqual(keep_mask.shape, axis.shape)
+        self.assertTrue(bool(keep_mask[-1]))
+        self.assertAlmostEqual(float(cut_axis[0]), 3.0, places=6)
+
+    def test_resolve_initial_window_size_stays_within_small_screen(self):
+        width, height = resolve_initial_window_size(800, 480)
+
+        self.assertLessEqual(width, 800)
+        self.assertLessEqual(height, 480)
+        self.assertGreaterEqual(width, 640)
+        self.assertGreaterEqual(height, 420)
+
+    def test_build_main_window_layout_uses_splitter_and_scroll_area(self):
+        os.environ.setdefault("QT_QPA_PLATFORM", "offscreen")
+        try:
+            from PyQt5 import QtCore, QtWidgets
+        except Exception as exc:  # pragma: no cover - environment-dependent
+            self.skipTest(f"Qt unavailable: {exc}")
+
+        app = QtWidgets.QApplication.instance() or QtWidgets.QApplication([])
+        main_window = QtWidgets.QWidget()
+        try:
+            _layout, splitter, _plot_layout, settings_widget, settings_layout, settings_scroll = build_main_window_layout(
+                QtCore,
+                QtWidgets,
+                main_window,
+            )
+            self.assertIsInstance(splitter, QtWidgets.QSplitter)
+            self.assertIsInstance(settings_scroll, QtWidgets.QScrollArea)
+            self.assertIs(settings_scroll.widget(), settings_widget)
+            self.assertIsInstance(settings_layout, QtWidgets.QVBoxLayout)
+        finally:
+            main_window.close()
+
+    def test_background_subtracted_bscan_levels_ignore_zero_floor(self):
+        disp_fft_lin = np.zeros((4, 8), dtype=np.float32)
+        disp_fft_lin[1, 2:6] = np.asarray([0.05, 0.1, 0.5, 2.0], dtype=np.float32)
+        disp_fft_lin[2, 1:6] = np.asarray([0.08, 0.2, 0.7, 3.0, 9.0], dtype=np.float32)
+        disp_fft = fft_mag_to_db(disp_fft_lin)
+
+        levels = compute_background_subtracted_bscan_levels(disp_fft_lin, disp_fft)
+
+        self.assertIsNotNone(levels)
+        positive_vals = disp_fft[disp_fft_lin > 0.0]
+        self.assertAlmostEqual(levels[0], float(np.nanpercentile(positive_vals, 15.0)), places=5)
+        self.assertAlmostEqual(levels[1], float(np.nanpercentile(positive_vals, 99.7)), places=5)
+        zero_floor = disp_fft[disp_fft_lin == 0.0]
+        self.assertLess(float(np.nanmax(zero_floor)), levels[0])
+
+    def test_background_subtracted_bscan_levels_fallback_when_residuals_too_sparse(self):
+        disp_fft_lin = np.zeros((3, 4), dtype=np.float32)
+        disp_fft_lin[1, 2] = 1.0
+        disp_fft = fft_mag_to_db(disp_fft_lin)
+
+        levels = compute_background_subtracted_bscan_levels(disp_fft_lin, disp_fft)
+
+        self.assertIsNone(levels)
+
+    def test_fft_helpers_return_expected_shapes(self):
+        sweep = np.sin(np.linspace(0.0, 4.0 * np.pi, 128)).astype(np.float32)
+        freqs = np.linspace(3.3, 14.3, 128, dtype=np.float64)
+        mag = compute_fft_mag_row(sweep, freqs, 513)
+        row = compute_fft_row(sweep, freqs, 513)
+        axis = compute_distance_axis(freqs, 513)
+        self.assertEqual(mag.shape, (513,))
+        self.assertEqual(row.shape, (513,))
+        self.assertEqual(axis.shape, (513,))
+        self.assertTrue(np.all(np.diff(axis) >= 0.0))
+
+    def test_symmetric_ifft_spectrum_has_zero_gap_and_mirrored_band(self):
+        sweep = np.linspace(1.0, 2.0, 128, dtype=np.float32)
+        freqs = np.linspace(4.0, 10.0, 128, dtype=np.float64)
+        spectrum = build_symmetric_ifft_spectrum(sweep, freqs, fft_len=FFT_LEN)
+
+        self.assertIsNotNone(spectrum)
+        freq_axis = np.linspace(-10.0, 10.0, FFT_LEN, dtype=np.float64)
+        neg_idx_all = np.flatnonzero(freq_axis <= (-4.0))
+        pos_idx_all = np.flatnonzero(freq_axis >= 4.0)
+        band_len = int(min(neg_idx_all.size, pos_idx_all.size))
+        neg_idx = neg_idx_all[:band_len]
+        pos_idx = pos_idx_all[-band_len:]
+        zero_mask = (freq_axis > (-4.0)) & (freq_axis < 4.0)
+
+        self.assertTrue(np.allclose(spectrum[zero_mask], 0.0))
+        self.assertTrue(np.allclose(spectrum[neg_idx], spectrum[pos_idx][::-1]))
+
+    def test_positive_only_centered_spectrum_keeps_zeros_until_positive_min(self):
+        sweep = np.linspace(1.0, 2.0, 128, dtype=np.float32)
+        freqs = np.linspace(4.0, 10.0, 128, dtype=np.float64)
+        spectrum = build_positive_only_centered_ifft_spectrum(sweep, freqs, fft_len=FFT_LEN)
+
+        self.assertIsNotNone(spectrum)
+        freq_axis = np.linspace(-10.0, 10.0, FFT_LEN, dtype=np.float64)
+        zero_mask = freq_axis < 4.0
+        pos_idx = np.flatnonzero(freq_axis >= 4.0)
+
+        self.assertTrue(np.allclose(spectrum[zero_mask], 0.0))
+        self.assertTrue(np.any(np.abs(spectrum[pos_idx]) > 0.0))
+
+    def test_positive_only_exact_spectrum_uses_direct_index_insertion_without_window(self):
+        sweep = np.asarray([1.0, 2.0, 3.0], dtype=np.float32)
+        freqs = np.asarray([4.0, 5.0, 6.0], dtype=np.float64)
+        spectrum = build_positive_only_exact_centered_ifft_spectrum(sweep, freqs)
+
+        self.assertIsNotNone(spectrum)
+        df = (6.0 - 4.0) / 2.0
+        f_shift = np.arange(-6.0, 6.0 + (0.5 * df), df, dtype=np.float64)
+        idx = np.round((freqs - f_shift[0]) / df).astype(np.int64)
+        zero_mask = (f_shift > -6.0) & (f_shift < 4.0)
+
+        self.assertEqual(int(spectrum.size), int(f_shift.size))
+        self.assertTrue(np.allclose(spectrum[zero_mask], 0.0))
+        self.assertTrue(np.allclose(spectrum[idx], sweep))
+
+    def test_complex_symmetric_ifft_spectrum_uses_conjugate_mirror(self):
+        sweep = np.exp(1j * np.linspace(0.0, np.pi, 128)).astype(np.complex64)
+        freqs = np.linspace(4.0, 10.0, 128, dtype=np.float64)
+        spectrum = build_symmetric_ifft_spectrum(sweep, freqs, fft_len=FFT_LEN)
+
+        self.assertIsNotNone(spectrum)
+        freq_axis = np.linspace(-10.0, 10.0, FFT_LEN, dtype=np.float64)
+        neg_idx_all = np.flatnonzero(freq_axis <= (-4.0))
+        pos_idx_all = np.flatnonzero(freq_axis >= 4.0)
+        band_len = int(min(neg_idx_all.size, pos_idx_all.size))
+        neg_idx = neg_idx_all[:band_len]
+        pos_idx = pos_idx_all[-band_len:]
+
+        self.assertTrue(np.iscomplexobj(spectrum))
+        self.assertTrue(np.allclose(spectrum[neg_idx], np.conj(spectrum[pos_idx][::-1])))
+
+    def test_compute_fft_helpers_accept_complex_input(self):
+        sweep = np.exp(1j * np.linspace(0.0, 2.0 * np.pi, 128)).astype(np.complex64)
+        freqs = np.linspace(3.3, 14.3, 128, dtype=np.float64)
+        complex_row = compute_fft_complex_row(sweep, freqs, 513, mode="positive_only")
+        mag = compute_fft_mag_row(sweep, freqs, 513, mode="positive_only")
+        row = compute_fft_row(sweep, freqs, 513, mode="positive_only")
+
+        self.assertEqual(complex_row.shape, (513,))
+        self.assertTrue(np.iscomplexobj(complex_row))
+        self.assertEqual(mag.shape, (513,))
+        self.assertEqual(row.shape, (513,))
+        self.assertTrue(np.allclose(mag, np.abs(complex_row), equal_nan=True))
+        self.assertTrue(np.any(np.isfinite(mag)))
+        self.assertTrue(np.any(np.isfinite(row)))
+
+    def test_compute_fft_complex_row_positive_only_exact_matches_manual_ifftshift_ifft(self):
+        sweep = np.asarray([1.0 + 1.0j, 2.0 + 0.0j, 3.0 - 1.0j], dtype=np.complex64)
+        freqs = np.asarray([4.0, 5.0, 6.0], dtype=np.float64)
+        bins = 16
+        row = compute_fft_complex_row(sweep, freqs, bins, mode="positive_only_exact")
+
+        df = (6.0 - 4.0) / 2.0
+        f_shift = np.arange(-6.0, 6.0 + (0.5 * df), df, dtype=np.float64)
+        manual_shift = np.zeros((f_shift.size,), dtype=np.complex64)
+        idx = np.round((freqs - f_shift[0]) / df).astype(np.int64)
+        manual_shift[idx] = sweep
+        manual_ifft = np.fft.ifft(np.fft.ifftshift(manual_shift))
+        expected = np.full((bins,), np.nan + 0j, dtype=np.complex64)
+        expected[: manual_ifft.size] = np.asarray(manual_ifft, dtype=np.complex64)
+
+        self.assertEqual(row.shape, (bins,))
+        self.assertTrue(np.allclose(row, expected, equal_nan=True))
+
+    def test_positive_only_exact_distance_axis_uses_exact_grid_geometry(self):
+        freqs = np.asarray([4.0, 5.0, 6.0], dtype=np.float64)
+        bins = 8
+        axis = compute_distance_axis(freqs, bins, mode="positive_only_exact")
+
+        # With a small bins budget the exact-mode grid is downsampled so
+        # internal IFFT length does not exceed visible bins.
+        df_hz = 2e9
+        n_shift = int(np.arange(-6.0, 6.0 + 1.0, 2.0, dtype=np.float64).size)
+        expected_step = C_M_S / (2.0 * n_shift * df_hz)
+        expected = np.arange(bins, dtype=np.float64) * expected_step
+
+        self.assertEqual(axis.shape, (bins,))
+        self.assertTrue(np.allclose(axis, expected))
+
+    def test_positive_only_exact_mode_remains_stable_when_input_points_double(self):
+        bins = FFT_LEN // 2 + 1
+        tau_s = 45e-9
+
+        freqs_400 = np.linspace(3.3, 14.3, 400, dtype=np.float64)
+        freqs_800 = np.linspace(3.3, 14.3, 800, dtype=np.float64)
+        sweep_400 = np.exp(-1j * 2.0 * np.pi * freqs_400 * 1e9 * tau_s).astype(np.complex64)
+        sweep_800 = np.exp(-1j * 2.0 * np.pi * freqs_800 * 1e9 * tau_s).astype(np.complex64)
+
+        mag_400 = compute_fft_mag_row(sweep_400, freqs_400, bins, mode="positive_only_exact")
+        mag_800 = compute_fft_mag_row(sweep_800, freqs_800, bins, mode="positive_only_exact")
+
+        self.assertEqual(mag_400.shape, mag_800.shape)
+        finite = np.isfinite(mag_400) & np.isfinite(mag_800)
+        self.assertGreater(int(np.count_nonzero(finite)), int(0.95 * bins))
+
+        idx_400 = int(np.nanargmax(mag_400))
+        idx_800 = int(np.nanargmax(mag_800))
+        peak_400 = float(np.nanmax(mag_400))
+        peak_800 = float(np.nanmax(mag_800))
+
+        self.assertLess(abs(idx_400 - idx_800), 64)
+        self.assertGreater(idx_400, 8)
+        self.assertGreater(idx_800, 8)
+        self.assertLess(idx_400, bins - 8)
+        self.assertLess(idx_800, bins - 8)
+        self.assertGreater(peak_400, 0.05)
+        self.assertGreater(peak_800, 0.05)
+
+    def test_resolve_visible_fft_curves_handles_complex_mode(self):
+        complex_row = np.asarray([1.0 + 2.0j, -3.0 + 4.0j], dtype=np.complex64)
+        mag = np.abs(complex_row).astype(np.float32)
+
+        abs_curve, real_curve, imag_curve = resolve_visible_fft_curves(
+            complex_row,
+            mag,
+            complex_mode=True,
+            show_abs=True,
+            show_real=False,
+            show_imag=True,
+        )
+
+        self.assertTrue(np.allclose(abs_curve, mag))
+        self.assertIsNone(real_curve)
+        self.assertTrue(np.allclose(imag_curve, np.asarray([2.0, 4.0], dtype=np.float32)))
+
+    def test_resolve_visible_fft_curves_preserves_legacy_abs_mode(self):
+        mag = np.asarray([1.0, 2.0, 3.0], dtype=np.float32)
+
+        abs_curve, real_curve, imag_curve = resolve_visible_fft_curves(
+            None,
+            mag,
+            complex_mode=False,
+            show_abs=True,
+            show_real=True,
+            show_imag=True,
+        )
+
+        self.assertTrue(np.allclose(abs_curve, mag))
+        self.assertIsNone(real_curve)
+        self.assertIsNone(imag_curve)
+
+    def test_symmetric_distance_axis_uses_windowed_frequency_bounds(self):
+        freqs = np.linspace(4.0, 10.0, 128, dtype=np.float64)
+        axis = compute_distance_axis(freqs, 513, mode="symmetric")
+        df_hz = (2.0 * 10.0 / max(1, FFT_LEN - 1)) * 1e9
+        expected_step = 299_792_458.0 / (2.0 * FFT_LEN * df_hz)
+
+        self.assertEqual(axis.shape, (513,))
+        self.assertTrue(np.all(np.diff(axis) >= 0.0))
+        self.assertAlmostEqual(float(axis[1] - axis[0]), expected_step, places=15)
+
+    def test_peak_helpers_find_reference_and_peak_boxes(self):
+        xs = np.linspace(0.0, 10.0, 200)
+        ys = np.exp(-((xs - 5.0) ** 2) / 0.4) * 10.0 + 1.0
+        ref = rolling_median_ref(xs, ys, 2.0)
+        peaks = find_top_peaks_over_ref(xs, ys, ref, top_n=3)
+        width = find_peak_width_markers(xs, ys)
+        self.assertEqual(ref.shape, ys.shape)
+        self.assertEqual(len(peaks), 1)
+        self.assertGreater(peaks[0]["x"], 4.0)
+        self.assertLess(peaks[0]["x"], 6.0)
+        self.assertIsNotNone(width)
+        self.assertGreater(width["width"], 0.0)
+
+
+if __name__ == "__main__":
+    unittest.main()

tests/test_ring_buffer.py

@@ -0,0 +1,176 @@
+from __future__ import annotations
+
+import numpy as np
+import unittest
+import warnings
+from unittest.mock import patch
+
+from rfg_adc_plotter.processing.fft import compute_fft_mag_row
+from rfg_adc_plotter.state.ring_buffer import RingBuffer
+
+
+class RingBufferTests(unittest.TestCase):
+    def test_ring_buffer_initializes_on_first_push(self):
+        ring = RingBuffer(max_sweeps=4)
+        sweep = np.linspace(-1.0, 1.0, 64, dtype=np.float32)
+        ring.push(sweep, np.linspace(3.3, 14.3, 64))
+        self.assertIsNotNone(ring.ring)
+        self.assertIsNotNone(ring.ring_fft)
+        self.assertIsNotNone(ring.ring_time)
+        self.assertIsNotNone(ring.distance_axis)
+        self.assertIsNotNone(ring.get_last_fft_linear())
+        self.assertIsNotNone(ring.last_fft_db)
+        self.assertEqual(ring.ring.shape[0], 4)
+        self.assertEqual(ring.ring_fft.shape, (4, ring.fft_bins))
+
+    def test_ring_buffer_reallocates_when_sweep_width_grows(self):
+        ring = RingBuffer(max_sweeps=3)
+        ring.push(np.ones((32,), dtype=np.float32), np.linspace(3.3, 14.3, 32))
+        first_width = ring.width
+        ring.push(np.ones((2048,), dtype=np.float32), np.linspace(3.3, 14.3, 2048))
+        self.assertGreater(ring.width, first_width)
+        self.assertIsNotNone(ring.ring)
+        self.assertEqual(ring.ring.shape, (3, ring.width))
+
+    def test_ring_buffer_tracks_latest_fft_and_display_arrays(self):
+        ring = RingBuffer(max_sweeps=2)
+        ring.push(np.linspace(0.0, 1.0, 64, dtype=np.float32), np.linspace(3.3, 14.3, 64))
+        ring.push(np.linspace(1.0, 0.0, 64, dtype=np.float32), np.linspace(3.3, 14.3, 64))
+        raw = ring.get_display_raw()
+        fft = ring.get_display_fft_linear()
+        self.assertEqual(raw.shape[1], 2)
+        self.assertEqual(fft.shape[1], 2)
+        self.assertIsNotNone(ring.last_fft_db)
+        self.assertEqual(ring.last_fft_db.shape, (ring.fft_bins,))
+
+    def test_ring_buffer_can_return_decimated_display_raw(self):
+        ring = RingBuffer(max_sweeps=3)
+        sweep_a = np.linspace(0.0, 1.0, 4096, dtype=np.float32)
+        sweep_b = np.linspace(1.0, 2.0, 4096, dtype=np.float32)
+        sweep_c = np.linspace(2.0, 3.0, 4096, dtype=np.float32)
+        freqs = np.linspace(3.3, 14.3, 4096, dtype=np.float64)
+        ring.push(sweep_a, freqs)
+        ring.push(sweep_b, freqs)
+        ring.push(sweep_c, freqs)
+
+        raw = ring.get_display_raw_decimated(256)
+
+        self.assertEqual(raw.shape, (256, 3))
+        self.assertAlmostEqual(float(raw[0, -1]), float(sweep_c[0]), places=6)
+        self.assertAlmostEqual(float(raw[-1, -1]), float(sweep_c[-1]), places=6)
+
+    def test_ring_buffer_can_switch_fft_mode_and_rebuild_fft_rows(self):
+        ring = RingBuffer(max_sweeps=2)
+        sweep = np.linspace(0.0, 1.0, 64, dtype=np.float32)
+        freqs = np.linspace(3.3, 14.3, 64, dtype=np.float64)
+        ring.push(sweep, freqs)
+        fft_before = ring.last_fft_db.copy()
+        axis_before = ring.distance_axis.copy()
+
+        changed = ring.set_symmetric_fft_enabled(False)
+
+        self.assertTrue(changed)
+        self.assertFalse(ring.fft_symmetric)
+        self.assertEqual(ring.get_display_raw().shape[1], 2)
+        self.assertIsNotNone(ring.get_last_fft_linear())
+        self.assertEqual(ring.last_fft_db.shape, fft_before.shape)
+        self.assertFalse(np.allclose(ring.last_fft_db, fft_before))
+        self.assertFalse(np.allclose(ring.distance_axis, axis_before))
+
+    def test_ring_buffer_can_switch_to_positive_only_fft_mode(self):
+        ring = RingBuffer(max_sweeps=2)
+        sweep = np.linspace(0.0, 1.0, 64, dtype=np.float32)
+        freqs = np.linspace(3.3, 14.3, 64, dtype=np.float64)
+        ring.push(sweep, freqs)
+
+        changed = ring.set_fft_mode("positive_only")
+
+        self.assertTrue(changed)
+        self.assertEqual(ring.fft_mode, "positive_only")
+        self.assertIsNotNone(ring.last_fft_db)
+        self.assertEqual(ring.last_fft_db.shape, (ring.fft_bins,))
+        self.assertIsNotNone(ring.distance_axis)
+
+    def test_ring_buffer_can_switch_to_positive_only_exact_fft_mode(self):
+        ring = RingBuffer(max_sweeps=2)
+        sweep = np.linspace(0.0, 1.0, 64, dtype=np.float32)
+        freqs = np.linspace(3.3, 14.3, 64, dtype=np.float64)
+        ring.push(sweep, freqs)
+
+        changed = ring.set_fft_mode("positive_only_exact")
+
+        self.assertTrue(changed)
+        self.assertEqual(ring.fft_mode, "positive_only_exact")
+        self.assertIsNotNone(ring.last_fft_db)
+        self.assertEqual(ring.last_fft_db.shape, (ring.fft_bins,))
+        self.assertIsNotNone(ring.distance_axis)
+
+    def test_ring_buffer_rebuilds_fft_from_complex_input(self):
+        ring = RingBuffer(max_sweeps=2)
+        freqs = np.linspace(3.3, 14.3, 64, dtype=np.float64)
+        complex_input = np.exp(1j * np.linspace(0.0, 2.0 * np.pi, 64)).astype(np.complex64)
+        display_sweep = np.abs(complex_input).astype(np.float32)
+        ring.push(display_sweep, freqs, fft_input=complex_input)
+
+        ring.set_fft_mode("direct")
+
+        expected = compute_fft_mag_row(complex_input, freqs, ring.fft_bins, mode="direct")
+        self.assertTrue(np.allclose(ring.get_last_fft_linear(), expected))
+        self.assertFalse(np.iscomplexobj(ring.get_display_fft_linear()))
+        self.assertTrue(np.allclose(ring.get_display_raw()[: display_sweep.size, -1], display_sweep))
+
+    def test_ring_buffer_reset_clears_cached_history(self):
+        ring = RingBuffer(max_sweeps=2)
+        ring.push(np.linspace(0.0, 1.0, 64, dtype=np.float32), np.linspace(4.0, 10.0, 64))
+
+        ring.reset()
+
+        self.assertIsNone(ring.ring)
+        self.assertIsNone(ring.ring_fft)
+        self.assertIsNone(ring.distance_axis)
+        self.assertIsNone(ring.last_fft_db)
+        self.assertEqual(ring.width, 0)
+        self.assertEqual(ring.head, 0)
+
+    def test_ring_buffer_push_ignores_all_nan_fft_without_runtime_warning(self):
+        ring = RingBuffer(max_sweeps=2)
+        freqs = np.linspace(3.3, 14.3, 64, dtype=np.float64)
+        ring.push(np.linspace(0.0, 1.0, 64, dtype=np.float32), freqs)
+        fft_before = ring.last_fft_db.copy()
+        y_min_before = ring.y_min_fft
+        y_max_before = ring.y_max_fft
+
+        with warnings.catch_warnings():
+            warnings.simplefilter("error", RuntimeWarning)
+            with patch(
+                "rfg_adc_plotter.state.ring_buffer.compute_fft_mag_row",
+                return_value=np.full((ring.fft_bins,), np.nan, dtype=np.float32),
+            ):
+                ring.push(np.linspace(1.0, 2.0, 64, dtype=np.float32), freqs)
+
+        self.assertFalse(ring.last_push_fft_valid)
+        self.assertTrue(np.allclose(ring.last_fft_db, fft_before))
+        self.assertEqual(ring.y_min_fft, y_min_before)
+        self.assertEqual(ring.y_max_fft, y_max_before)
+
+    def test_ring_buffer_set_fft_mode_ignores_all_nan_rebuild_without_runtime_warning(self):
+        ring = RingBuffer(max_sweeps=2)
+        freqs = np.linspace(3.3, 14.3, 64, dtype=np.float64)
+        ring.push(np.linspace(0.0, 1.0, 64, dtype=np.float32), freqs)
+        fft_before = ring.last_fft_db.copy()
+
+        with warnings.catch_warnings():
+            warnings.simplefilter("error", RuntimeWarning)
+            with patch(
+                "rfg_adc_plotter.state.ring_buffer.compute_fft_mag_row",
+                return_value=np.full((ring.fft_bins,), np.nan, dtype=np.float32),
+            ):
+                ring.set_fft_mode("direct")
+
+        self.assertFalse(ring.last_push_fft_valid)
+        self.assertTrue(np.allclose(ring.last_fft_db, fft_before))
+        self.assertEqual(ring.fft_mode, "direct")
+
+
+if __name__ == "__main__":
+    unittest.main()

tests/test_sweep_parser_core.py

@@ -0,0 +1,416 @@
+from __future__ import annotations
+
+import math
+import unittest
+
+from rfg_adc_plotter.io.sweep_parser_core import (
+    AsciiSweepParser,
+    ComplexAsciiSweepParser,
+    LegacyBinaryParser,
+    LogScale16BitX2BinaryParser,
+    LogScaleBinaryParser32,
+    ParserTestStreamParser,
+    PointEvent,
+    StartEvent,
+    SweepAssembler,
+    log_pair_to_sweep,
+)
+
+
+def _u16le(word: int) -> bytes:
+    w = int(word) & 0xFFFF
+    return bytes((w & 0xFF, (w >> 8) & 0xFF))
+
+
+def _pack_legacy_start(ch: int) -> bytes:
+    return b"\xff\xff" * 3 + bytes((0x0A, int(ch) & 0xFF))
+
+
+def _pack_legacy_point(ch: int, step: int, value_i32: int) -> bytes:
+    value = int(value_i32) & 0xFFFF_FFFF
+    return b"".join(
+        [
+            _u16le(step),
+            _u16le((value >> 16) & 0xFFFF),
+            _u16le(value & 0xFFFF),
+            bytes((0x0A, int(ch) & 0xFF)),
+        ]
+    )
+
+
+def _pack_log_start(ch: int) -> bytes:
+    return b"\xff\xff" * 5 + bytes((0x0A, int(ch) & 0xFF))
+
+
+def _pack_log_point(step: int, avg1: int, avg2: int, ch: int = 0) -> bytes:
+    a1 = int(avg1) & 0xFFFF_FFFF
+    a2 = int(avg2) & 0xFFFF_FFFF
+    return b"".join(
+        [
+            _u16le(step),
+            _u16le((a1 >> 16) & 0xFFFF),
+            _u16le(a1 & 0xFFFF),
+            _u16le((a2 >> 16) & 0xFFFF),
+            _u16le(a2 & 0xFFFF),
+            bytes((0x0A, int(ch) & 0xFF)),
+        ]
+    )
+
+
+def _pack_log16_start(ch: int) -> bytes:
+    return b"\xff\xff" * 3 + bytes((0x0A, int(ch) & 0xFF))
+
+
+def _pack_log16_point(step: int, avg1: int, avg2: int) -> bytes:
+    return b"".join(
+        [
+            _u16le(step),
+            _u16le(avg1),
+            _u16le(avg2),
+            _u16le(0xFFFF),
+        ]
+    )
+
+
+def _pack_tty_start() -> bytes:
+    return b"".join([_u16le(0x000A), _u16le(0xFFFF), _u16le(0xFFFF), _u16le(0xFFFF)])
+
+
+def _pack_tty_point(step: int, ch1: int, ch2: int) -> bytes:
+    return b"".join(
+        [
+            _u16le(0x000A),
+            _u16le(step),
+            _u16le(ch1),
+            _u16le(ch2),
+        ]
+    )
+
+
+def _pack_logdet_point(step: int, value: int) -> bytes:
+    return b"".join(
+        [
+            _u16le(0x001A),
+            _u16le(step),
+            _u16le(value),
+            _u16le(0x0000),
+        ]
+    )
+
+
+class SweepParserCoreTests(unittest.TestCase):
+    def test_ascii_parser_emits_start_and_points(self):
+        parser = AsciiSweepParser()
+        events = parser.feed(b"Sweep_start\ns 1 2 -3\ns2 4 5\n")
+        self.assertIsInstance(events[0], StartEvent)
+        self.assertIsInstance(events[1], PointEvent)
+        self.assertIsInstance(events[2], PointEvent)
+        self.assertEqual(events[1].ch, 1)
+        self.assertEqual(events[1].x, 2)
+        self.assertEqual(events[1].y, -3.0)
+        self.assertEqual(events[2].ch, 2)
+        self.assertEqual(events[2].x, 4)
+        self.assertEqual(events[2].y, 5.0)
+
+    def test_legacy_binary_parser_resynchronizes_after_garbage(self):
+        parser = LegacyBinaryParser()
+        stream = b"\x00junk" + _pack_legacy_start(3) + _pack_legacy_point(3, 1, -2)
+        events = parser.feed(stream)
+        self.assertIsInstance(events[0], StartEvent)
+        self.assertEqual(events[0].ch, 3)
+        self.assertIsInstance(events[1], PointEvent)
+        self.assertEqual(events[1].ch, 3)
+        self.assertEqual(events[1].x, 1)
+        self.assertEqual(events[1].y, -2.0)
+
+    def test_legacy_binary_parser_detects_new_sweep_on_step_reset(self):
+        parser = LegacyBinaryParser()
+        stream = b"".join(
+            [
+                _pack_legacy_point(3, 1, -2),
+                _pack_legacy_point(3, 2, -3),
+                _pack_legacy_point(3, 1, -4),
+            ]
+        )
+        events = parser.feed(stream)
+        self.assertIsInstance(events[0], PointEvent)
+        self.assertIsInstance(events[1], PointEvent)
+        self.assertIsInstance(events[2], StartEvent)
+        self.assertEqual(events[2].ch, 3)
+        self.assertIsInstance(events[3], PointEvent)
+        self.assertEqual(events[3].x, 1)
+        self.assertEqual(events[3].y, -4.0)
+
+    def test_legacy_binary_parser_accepts_tty_ch1_ch2_stream(self):
+        parser = LegacyBinaryParser()
+        stream = b"".join(
+            [
+                _pack_tty_start(),
+                _pack_tty_point(1, 100, 90),
+                _pack_tty_point(2, 120, 95),
+            ]
+        )
+
+        events = parser.feed(stream)
+
+        self.assertIsInstance(events[0], StartEvent)
+        self.assertEqual(events[0].ch, 0)
+        self.assertIsInstance(events[1], PointEvent)
+        self.assertEqual(events[1].x, 1)
+        self.assertEqual(events[1].y, 18100.0)
+        self.assertEqual(events[1].aux, (100.0, 90.0))
+        self.assertEqual(events[1].signal_kind, "bin_iq")
+        self.assertIsInstance(events[2], PointEvent)
+        self.assertEqual(events[2].x, 2)
+        self.assertEqual(events[2].y, 23425.0)
+        self.assertEqual(events[2].aux, (120.0, 95.0))
+        self.assertEqual(events[2].signal_kind, "bin_iq")
+
+    def test_legacy_binary_parser_detects_new_tty_sweep_on_step_reset(self):
+        parser = LegacyBinaryParser()
+        stream = b"".join(
+            [
+                _pack_tty_start(),
+                _pack_tty_point(1, 100, 90),
+                _pack_tty_point(2, 110, 95),
+                _pack_tty_point(1, 120, 80),
+            ]
+        )
+
+        events = parser.feed(stream)
+
+        self.assertIsInstance(events[0], StartEvent)
+        self.assertIsInstance(events[1], PointEvent)
+        self.assertIsInstance(events[2], PointEvent)
+        self.assertIsInstance(events[3], StartEvent)
+        self.assertEqual(events[3].ch, 0)
+        self.assertIsInstance(events[4], PointEvent)
+        self.assertEqual(events[4].x, 1)
+        self.assertEqual(events[4].aux, (120.0, 80.0))
+        self.assertEqual(events[4].signal_kind, "bin_iq")
+
+    def test_legacy_binary_parser_tty_mode_does_not_flip_to_legacy_on_ch2_low_byte_0x0a(self):
+        parser = LegacyBinaryParser()
+        stream = b"".join(
+            [
+                _pack_tty_start(),
+                _pack_tty_point(1, 100, 0x040A),  # low byte is 0x0A: used to be misparsed as legacy
+                _pack_tty_point(2, 120, 0x0410),
+            ]
+        )
+
+        events = parser.feed(stream)
+
+        self.assertEqual(len(events), 3)
+        self.assertIsInstance(events[0], StartEvent)
+        self.assertEqual(events[0].ch, 0)
+
+        self.assertIsInstance(events[1], PointEvent)
+        self.assertEqual(events[1].ch, 0)
+        self.assertEqual(events[1].x, 1)
+        self.assertEqual(events[1].aux, (100.0, 1034.0))
+        self.assertEqual(events[1].y, 1079156.0)
+
+        self.assertIsInstance(events[2], PointEvent)
+        self.assertEqual(events[2].ch, 0)
+        self.assertEqual(events[2].x, 2)
+        self.assertEqual(events[2].aux, (120.0, 1040.0))
+        self.assertEqual(events[2].y, 1096000.0)
+
+    def test_legacy_binary_parser_accepts_logdet_stream(self):
+        parser = LegacyBinaryParser()
+        stream = b"".join(
+            [
+                _pack_logdet_point(1, 0x0F77),
+                _pack_logdet_point(2, 0xF234),
+            ]
+        )
+
+        events = parser.feed(stream)
+
+        self.assertEqual(len(events), 2)
+        self.assertIsInstance(events[0], PointEvent)
+        self.assertEqual(events[0].x, 1)
+        self.assertEqual(events[0].y, 3959.0)
+        self.assertIsNone(events[0].aux)
+        self.assertEqual(events[0].signal_kind, "bin_logdet")
+        self.assertIsInstance(events[1], PointEvent)
+        self.assertEqual(events[1].x, 2)
+        self.assertEqual(events[1].y, -3532.0)
+        self.assertEqual(events[1].signal_kind, "bin_logdet")
+
+    def test_legacy_binary_parser_splits_packet_on_bin_signal_kind_change(self):
+        parser = LegacyBinaryParser()
+        stream = b"".join(
+            [
+                _pack_tty_start(),
+                _pack_tty_point(1, 100, 90),
+                _pack_tty_point(2, 110, 95),
+                _pack_logdet_point(3, 0x0F77),
+            ]
+        )
+
+        events = parser.feed(stream)
+
+        self.assertIsInstance(events[0], StartEvent)
+        self.assertEqual(events[0].signal_kind, "bin_iq")
+        self.assertIsInstance(events[1], PointEvent)
+        self.assertEqual(events[1].signal_kind, "bin_iq")
+        self.assertIsInstance(events[2], PointEvent)
+        self.assertEqual(events[2].signal_kind, "bin_iq")
+        self.assertIsInstance(events[3], StartEvent)
+        self.assertEqual(events[3].signal_kind, "bin_logdet")
+        self.assertIsInstance(events[4], PointEvent)
+        self.assertEqual(events[4].x, 3)
+        self.assertEqual(events[4].signal_kind, "bin_logdet")
+
+    def test_complex_ascii_parser_detects_new_sweep_on_step_reset(self):
+        parser = ComplexAsciiSweepParser()
+        events = parser.feed(b"0 3 4\n1 5 12\n0 8 15\n")
+
+        self.assertIsInstance(events[0], PointEvent)
+        self.assertEqual(events[0].x, 0)
+        self.assertEqual(events[0].y, 5.0)
+        self.assertEqual(events[0].aux, (3.0, 4.0))
+        self.assertIsInstance(events[1], PointEvent)
+        self.assertEqual(events[1].y, 13.0)
+        self.assertIsInstance(events[2], StartEvent)
+        self.assertIsInstance(events[3], PointEvent)
+        self.assertEqual(events[3].aux, (8.0, 15.0))
+
+    def test_logscale_32_parser_keeps_channel_and_aux_values(self):
+        parser = LogScaleBinaryParser32()
+        stream = _pack_log_start(5) + _pack_log_point(7, 1500, 700, ch=5)
+        events = parser.feed(stream)
+        self.assertIsInstance(events[0], StartEvent)
+        self.assertEqual(events[0].ch, 5)
+        self.assertIsInstance(events[1], PointEvent)
+        self.assertEqual(events[1].ch, 5)
+        self.assertEqual(events[1].x, 7)
+        self.assertAlmostEqual(events[1].y, log_pair_to_sweep(1500, 700), places=6)
+        self.assertEqual(events[1].aux, (1500.0, 700.0))
+
+    def test_logscale_32_parser_detects_new_sweep_on_step_reset(self):
+        parser = LogScaleBinaryParser32()
+        stream = b"".join(
+            [
+                _pack_log_point(1, 1500, 700, ch=5),
+                _pack_log_point(2, 1400, 650, ch=5),
+                _pack_log_point(1, 1300, 600, ch=5),
+            ]
+        )
+        events = parser.feed(stream)
+        self.assertIsInstance(events[0], PointEvent)
+        self.assertIsInstance(events[1], PointEvent)
+        self.assertIsInstance(events[2], StartEvent)
+        self.assertEqual(events[2].ch, 5)
+        self.assertIsInstance(events[3], PointEvent)
+        self.assertEqual(events[3].x, 1)
+        self.assertAlmostEqual(events[3].y, log_pair_to_sweep(1300, 600), places=6)
+
+    def test_log_pair_to_sweep_is_order_independent(self):
+        self.assertAlmostEqual(log_pair_to_sweep(1500, 700), log_pair_to_sweep(700, 1500), places=6)
+
+    def test_logscale_16bit_parser_uses_last_start_channel(self):
+        parser = LogScale16BitX2BinaryParser()
+        stream = _pack_log16_start(2) + _pack_log16_point(1, 100, 90)
+        events = parser.feed(stream)
+        self.assertIsInstance(events[0], StartEvent)
+        self.assertEqual(events[0].ch, 2)
+        self.assertIsInstance(events[1], PointEvent)
+        self.assertEqual(events[1].ch, 2)
+        self.assertAlmostEqual(events[1].y, math.hypot(100.0, 90.0), places=6)
+        self.assertEqual(events[1].aux, (100.0, 90.0))
+
+    def test_logscale_16bit_parser_detects_new_sweep_on_step_reset(self):
+        parser = LogScale16BitX2BinaryParser()
+        stream = b"".join(
+            [
+                _pack_log16_start(2),
+                _pack_log16_point(1, 100, 90),
+                _pack_log16_point(2, 110, 95),
+                _pack_log16_point(1, 120, 80),
+            ]
+        )
+        events = parser.feed(stream)
+        self.assertIsInstance(events[0], StartEvent)
+        self.assertIsInstance(events[1], PointEvent)
+        self.assertIsInstance(events[2], PointEvent)
+        self.assertIsInstance(events[3], StartEvent)
+        self.assertEqual(events[3].ch, 2)
+        self.assertIsInstance(events[4], PointEvent)
+        self.assertEqual(events[4].x, 1)
+        self.assertAlmostEqual(events[4].y, math.hypot(120.0, 80.0), places=6)
+
+    def test_parser_test_stream_parser_recovers_point_after_single_separator(self):
+        parser = ParserTestStreamParser()
+        stream = b"".join(
+            [
+                b"\xff\xff\xff\xff",
+                bytes((0x0A, 4)),
+                _u16le(1),
+                _u16le(100),
+                _u16le(90),
+                _u16le(0xFFFF),
+            ]
+        )
+        events = parser.feed(stream)
+        events.extend(parser.feed(_u16le(2)))
+        self.assertIsInstance(events[0], StartEvent)
+        self.assertEqual(events[0].ch, 4)
+        self.assertIsInstance(events[1], PointEvent)
+        self.assertEqual(events[1].ch, 4)
+        self.assertEqual(events[1].x, 1)
+        self.assertAlmostEqual(events[1].y, math.hypot(100.0, 90.0), places=6)
+        self.assertEqual(events[1].aux, (100.0, 90.0))
+
+    def test_sweep_assembler_builds_aux_curves_without_inversion(self):
+        assembler = SweepAssembler(fancy=False, apply_inversion=False)
+        self.assertIsNone(assembler.consume(StartEvent(ch=1, signal_kind="bin_iq")))
+        assembler.consume(PointEvent(ch=1, x=1, y=10.0, aux=(100.0, 90.0), signal_kind="bin_iq"))
+        assembler.consume(PointEvent(ch=1, x=2, y=20.0, aux=(110.0, 95.0), signal_kind="bin_iq"))
+        sweep, info, aux = assembler.finalize_current()
+        self.assertEqual(sweep.shape[0], 3)
+        self.assertEqual(info["ch"], 1)
+        self.assertEqual(info["signal_kind"], "bin_iq")
+        self.assertIsNotNone(aux)
+        self.assertEqual(aux[0][1], 100.0)
+        self.assertEqual(aux[1][2], 95.0)
+
+    def test_sweep_assembler_splits_packet_on_channel_switch(self):
+        assembler = SweepAssembler(fancy=False, apply_inversion=False)
+        self.assertIsNone(assembler.consume(PointEvent(ch=1, x=1, y=10.0)))
+        packet = assembler.consume(PointEvent(ch=2, x=1, y=20.0))
+        self.assertIsNotNone(packet)
+
+        sweep_1, info_1, aux_1 = packet
+        self.assertIsNone(aux_1)
+        self.assertEqual(info_1["ch"], 1)
+        self.assertEqual(info_1["chs"], [1])
+        self.assertAlmostEqual(float(sweep_1[1]), 10.0, places=6)
+
+        sweep_2, info_2, aux_2 = assembler.finalize_current()
+        self.assertIsNone(aux_2)
+        self.assertEqual(info_2["ch"], 2)
+        self.assertEqual(info_2["chs"], [2])
+        self.assertAlmostEqual(float(sweep_2[1]), 20.0, places=6)
+
+    def test_sweep_assembler_splits_packet_on_signal_kind_switch(self):
+        assembler = SweepAssembler(fancy=False, apply_inversion=False)
+        self.assertIsNone(assembler.consume(PointEvent(ch=0, x=1, y=10.0, signal_kind="bin_iq")))
+        packet = assembler.consume(PointEvent(ch=0, x=1, y=20.0, signal_kind="bin_logdet"))
+        self.assertIsNotNone(packet)
+
+        sweep_1, info_1, aux_1 = packet
+        self.assertIsNone(aux_1)
+        self.assertEqual(info_1["signal_kind"], "bin_iq")
+        self.assertAlmostEqual(float(sweep_1[1]), 10.0, places=6)
+
+        sweep_2, info_2, aux_2 = assembler.finalize_current()
+        self.assertIsNone(aux_2)
+        self.assertEqual(info_2["signal_kind"], "bin_logdet")
+        self.assertAlmostEqual(float(sweep_2[1]), 20.0, places=6)
+
+
+if __name__ == "__main__":
+    unittest.main()

tests/test_sweep_reader.py

@@ -0,0 +1,262 @@
+from __future__ import annotations
+
+import contextlib
+import io
+import threading
+import time
+import unittest
+from queue import Queue
+from unittest.mock import patch
+
+from rfg_adc_plotter.io import sweep_reader as sweep_reader_module
+from rfg_adc_plotter.io.sweep_reader import SweepReader, _PARSER_16_BIT_X2_PROBE_BYTES
+
+
+def _u16le(word: int) -> bytes:
+    value = int(word) & 0xFFFF
+    return bytes((value & 0xFF, (value >> 8) & 0xFF))
+
+
+def _pack_legacy_point(ch: int, step: int, value_i32: int) -> bytes:
+    value = int(value_i32) & 0xFFFF_FFFF
+    return b"".join(
+        [
+            _u16le(step),
+            _u16le((value >> 16) & 0xFFFF),
+            _u16le(value & 0xFFFF),
+            bytes((0x0A, int(ch) & 0xFF)),
+        ]
+    )
+
+
+def _pack_log16_start(ch: int) -> bytes:
+    return b"\xff\xff" * 3 + bytes((0x0A, int(ch) & 0xFF))
+
+
+def _pack_log16_point(step: int, real: int, imag: int) -> bytes:
+    return b"".join(
+        [
+            _u16le(step),
+            _u16le(real),
+            _u16le(imag),
+            _u16le(0xFFFF),
+        ]
+    )
+
+
+def _pack_tty_start() -> bytes:
+    return b"".join(
+        [
+            _u16le(0x000A),
+            _u16le(0xFFFF),
+            _u16le(0xFFFF),
+            _u16le(0xFFFF),
+        ]
+    )
+
+
+def _pack_tty_point(step: int, ch1: int, ch2: int) -> bytes:
+    return b"".join(
+        [
+            _u16le(0x000A),
+            _u16le(step),
+            _u16le(ch1),
+            _u16le(ch2),
+        ]
+    )
+
+
+def _pack_logdet_point(step: int, value: int) -> bytes:
+    return b"".join(
+        [
+            _u16le(0x001A),
+            _u16le(step),
+            _u16le(value),
+            _u16le(0x0000),
+        ]
+    )
+
+
+def _chunk_bytes(data: bytes, size: int = 4096) -> list[bytes]:
+    return [data[idx : idx + size] for idx in range(0, len(data), size)]
+
+
+class _FakeSerialLineSource:
+    def __init__(self, path: str, baud: int, timeout: float = 1.0):
+        self.path = path
+        self.baud = baud
+        self.timeout = timeout
+        self._using = "fake"
+
+    def close(self) -> None:
+        pass
+
+
+class _FakeChunkReader:
+    payload_chunks: list[bytes] = []
+
+    def __init__(self, src):
+        self._src = src
+        self._chunks = list(type(self).payload_chunks)
+
+    def read_available(self) -> bytes:
+        if self._chunks:
+            return self._chunks.pop(0)
+        return b""
+
+
+class SweepReaderTests(unittest.TestCase):
+    def _start_reader(self, payload: bytes, **reader_kwargs):
+        queue: Queue = Queue()
+        stop_event = threading.Event()
+        stderr = io.StringIO()
+        _FakeChunkReader.payload_chunks = _chunk_bytes(payload)
+        reader = SweepReader(
+            "/tmp/fake-tty",
+            115200,
+            queue,
+            stop_event,
+            **reader_kwargs,
+        )
+        stack = contextlib.ExitStack()
+        stack.enter_context(patch.object(sweep_reader_module, "SerialLineSource", _FakeSerialLineSource))
+        stack.enter_context(patch.object(sweep_reader_module, "SerialChunkReader", _FakeChunkReader))
+        stack.enter_context(contextlib.redirect_stderr(stderr))
+        reader.start()
+        return stack, reader, queue, stop_event, stderr
+
+    def test_parser_16_bit_x2_falls_back_to_legacy_stream(self):
+        payload = bytearray()
+        while len(payload) < (_PARSER_16_BIT_X2_PROBE_BYTES + 24):
+            payload += _pack_legacy_point(3, 1, -2)
+            payload += _pack_legacy_point(3, 2, -3)
+            payload += _pack_legacy_point(3, 1, -4)
+
+        stack, reader, queue, stop_event, stderr = self._start_reader(bytes(payload), parser_16_bit_x2=True)
+        try:
+            sweep, info, aux = queue.get(timeout=2.0)
+            self.assertEqual(info["ch"], 3)
+            self.assertIsNone(aux)
+            self.assertGreaterEqual(sweep.shape[0], 3)
+            self.assertIn("fallback -> legacy", stderr.getvalue())
+        finally:
+            stop_event.set()
+            reader.join(timeout=1.0)
+            stack.close()
+
+    def test_parser_16_bit_x2_falls_back_to_tty_ch1_ch2_stream(self):
+        payload = bytearray()
+        while len(payload) < (_PARSER_16_BIT_X2_PROBE_BYTES + 24):
+            payload += _pack_tty_start()
+            payload += _pack_tty_point(1, 100, 90)
+            payload += _pack_tty_point(2, 120, 95)
+            payload += _pack_tty_point(1, 80, 70)
+
+        stack, reader, queue, stop_event, stderr = self._start_reader(bytes(payload), parser_16_bit_x2=True)
+        try:
+            sweep, info, aux = queue.get(timeout=2.0)
+            self.assertEqual(info["ch"], 0)
+            self.assertIsNotNone(aux)
+            self.assertGreaterEqual(sweep.shape[0], 3)
+            self.assertAlmostEqual(float(sweep[1]), 18100.0, places=6)
+            self.assertAlmostEqual(float(sweep[2]), 23425.0, places=6)
+            self.assertIn("fallback -> legacy", stderr.getvalue())
+        finally:
+            stop_event.set()
+            reader.join(timeout=1.0)
+            stack.close()
+
+    def test_parser_16_bit_x2_keeps_true_complex_stream(self):
+        payload = b"".join(
+            [
+                _pack_log16_start(2),
+                _pack_log16_point(1, 3, 4),
+                _pack_log16_point(2, 5, 12),
+                _pack_log16_point(1, 8, 15),
+            ]
+        )
+
+        stack, reader, queue, stop_event, stderr = self._start_reader(payload, parser_16_bit_x2=True)
+        try:
+            sweep, info, aux = queue.get(timeout=1.0)
+            self.assertEqual(info["ch"], 2)
+            self.assertIsNotNone(aux)
+            self.assertAlmostEqual(float(sweep[1]), 5.0, places=6)
+            self.assertAlmostEqual(float(sweep[2]), 13.0, places=6)
+            self.assertNotIn("fallback -> legacy", stderr.getvalue())
+        finally:
+            stop_event.set()
+            reader.join(timeout=1.0)
+            stack.close()
+
+    def test_parser_16_bit_x2_falls_back_to_logdet_1a00_stream(self):
+        payload = bytearray()
+        while len(payload) < (_PARSER_16_BIT_X2_PROBE_BYTES + 24):
+            payload += _pack_logdet_point(1, 0x0F77)
+            payload += _pack_logdet_point(2, 0x0FCB)
+            payload += _pack_logdet_point(1, 0x0F88)
+
+        stack, reader, queue, stop_event, stderr = self._start_reader(bytes(payload), parser_16_bit_x2=True)
+        try:
+            sweep, info, aux = queue.get(timeout=2.0)
+            self.assertEqual(info["signal_kind"], "bin_logdet")
+            self.assertIsNone(aux)
+            self.assertGreaterEqual(sweep.shape[0], 3)
+            self.assertAlmostEqual(float(sweep[1]), 3959.0, places=6)
+            self.assertIn("fallback -> legacy", stderr.getvalue())
+        finally:
+            stop_event.set()
+            reader.join(timeout=1.0)
+            stack.close()
+
+    def test_parser_16_bit_x2_probe_inconclusive_logs_hint(self):
+        payload = b"\x00" * (_PARSER_16_BIT_X2_PROBE_BYTES + 128)
+
+        stack, reader, queue, stop_event, stderr = self._start_reader(payload, parser_16_bit_x2=True)
+        try:
+            deadline = time.time() + 1.5
+            logs = ""
+            while time.time() < deadline:
+                logs = stderr.getvalue()
+                if "probe inconclusive" in logs:
+                    break
+                time.sleep(0.02)
+            self.assertTrue(queue.empty())
+            self.assertIn("probe inconclusive", logs)
+            self.assertIn("try --bin", logs)
+        finally:
+            stop_event.set()
+            reader.join(timeout=1.0)
+            stack.close()
+
+    def test_reader_logs_no_input_warning_when_source_is_idle(self):
+        with patch.object(sweep_reader_module, "_NO_INPUT_WARN_INTERVAL_S", 0.02), patch.object(
+            sweep_reader_module, "_NO_PACKET_WARN_INTERVAL_S", 0.02
+        ):
+            stack, reader, _queue, stop_event, stderr = self._start_reader(b"", parser_16_bit_x2=False)
+            try:
+                time.sleep(0.12)
+                logs = stderr.getvalue()
+                self.assertIn("no input bytes", logs)
+                self.assertIn("no sweep packets", logs)
+            finally:
+                stop_event.set()
+                reader.join(timeout=1.0)
+                stack.close()
+
+    def test_reader_join_does_not_raise_when_stopped(self):
+        stack, reader, _queue, stop_event, _stderr = self._start_reader(b"", parser_16_bit_x2=True)
+        try:
+            time.sleep(0.01)
+            stop_event.set()
+            reader.join(timeout=1.0)
+            self.assertFalse(reader.is_alive())
+        finally:
+            stop_event.set()
+            if reader.is_alive():
+                reader.join(timeout=1.0)
+            stack.close()
+
+
+if __name__ == "__main__":
+    unittest.main()