ChTheo/RFG_stm32_ADC_receiver_GUI
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WIP on normaliser: 2e6ad24 ad to gitignore

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This commit is contained in:
Theodor Chikin
2026-02-20 20:32:02 +03:00
parent 2e6ad24aaa 33bde7be5a
commit d56e439bf2
7 changed files with 116 additions and 23 deletions
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59
rfg_adc_plotter/gui/matplotlib_backend.py
View File

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

46
rfg_adc_plotter/gui/pyqtgraph_backend.py
View File

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