ChTheo/RFG_stm32_ADC_receiver_GUI
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fix sub matplotlib

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This commit is contained in:
awe
2026-02-04 14:38:55 +03:00
parent e0f7678c3e
commit 5978d58dc5
1 changed files with 16 additions and 9 deletions
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25
rfg_adc_plotter/visualization/matplotlib_backend.py
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@ -461,17 +461,24 @@ def run_matplotlib(args):
# Обновление линии последнего свипа
if current_sweep is not None:
if x_shared is not None and current_sweep.size <= x_shared.size:
xs = x_shared[: current_sweep.size]
# Применяем вычитание медианы для отображения
display_sweep = current_sweep
if median_subtract_enabled and median_data is not None:
take_median = min(current_sweep.size, median_data.size)
display_sweep = current_sweep.copy()
display_sweep[:take_median] = current_sweep[:take_median] - median_data[:take_median]
if x_shared is not None and display_sweep.size <= x_shared.size:
xs = x_shared[: display_sweep.size]
else:
xs = np.arange(current_sweep.size, dtype=np.int32)
line_obj.set_data(xs, current_sweep)
xs = np.arange(display_sweep.size, dtype=np.int32)
line_obj.set_data(xs, display_sweep)
# Лимиты по X постоянные под текущую ширину
ax_line.set_xlim(0, max(1, current_sweep.size - 1))
ax_line.set_xlim(0, max(1, display_sweep.size - 1))
# Адаптивные Y-лимиты (если не задан --ylim)
if fixed_ylim is None:
y0 = float(np.nanmin(current_sweep))
y1 = float(np.nanmax(current_sweep))
y0 = float(np.nanmin(display_sweep))
y1 = float(np.nanmax(display_sweep))
if np.isfinite(y0) and np.isfinite(y1):
if y0 == y1:
pad = max(1.0, abs(y0) * 0.05)
@ -484,7 +491,7 @@ def run_matplotlib(args):
ax_line.set_ylim(y0, y1)
# Обновление спектра и фазы текущего свипа
take_fft = min(int(current_sweep.size), FFT_LEN)
take_fft = min(int(display_sweep.size), FFT_LEN)
if take_fft > 0 and freq_shared is not None:
# Создаем буфер для полного FFT (с отрицательными частотами)
fft_in = np.zeros((FFT_LEN,), dtype=np.float32)
@ -500,7 +507,7 @@ def run_matplotlib(args):
data_points = min(data_points, take_fft, FFT_LEN - start_idx)
# Подготовка данных с окном Хэннинга
seg = np.nan_to_num(current_sweep[:data_points], nan=0.0).astype(np.float32, copy=False)
seg = np.nan_to_num(display_sweep[:data_points], nan=0.0).astype(np.float32, copy=False)
win = np.hanning(data_points).astype(np.float32)
# Размещаем данные в правильной позиции