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base: qoherent:71f23e3a967e26c983a0507a831c06ff77933b9c
Branches Tags
qoherent:main
qoherent:docs/sdr-guides-update
qoherent:agent-naming-fix
qoherent:zfp-oss
qoherent:screens-connection
qoherent:dataset-manager-v2
qoherent:v0.1.5
qoherent:0.1.4
qoherent:v0.1.3
qoherent:v0.1.2
qoherent:v0.1.1
qoherent:v0.1.0
..
compare: qoherent:70f132c54c90207428cd77e553238e44670ae49f
Branches Tags
qoherent:docs/sdr-guides-update
qoherent:agent-naming-fix
qoherent:main
qoherent:zfp-oss
qoherent:screens-connection
qoherent:dataset-manager-v2
qoherent:v0.1.5
qoherent:0.1.4
qoherent:v0.1.3
qoherent:v0.1.2
qoherent:v0.1.1
qoherent:v0.1.0

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71f23e3a96 ... 70f132c54c

1 changed files with 7 additions and 54 deletions
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61
src/ria_toolkit_oss/viz/recording.py
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@ -54,18 +54,6 @@ def spectrogram(rec: Recording, thumbnail: bool = False) -> Figure:
frequencies_shifted = np.fft.fftshift(frequencies)
Sxx_shifted = np.fft.fftshift(Sxx_log_norm, axes=0)
# Downsample heatmap for performance (max 500x500 = 250,000 points)
max_freq_bins = 500
max_time_bins = 500
freq_step = max(1, len(frequencies_shifted) // max_freq_bins)
time_step = max(1, len(times) // max_time_bins)
if freq_step > 1 or time_step > 1:
Sxx_shifted = Sxx_shifted[::freq_step, ::time_step]
frequencies_shifted = frequencies_shifted[::freq_step]
times = times[::time_step]
fig = go.Figure(
data=go.Heatmap(
z=Sxx_shifted,
@ -114,19 +102,11 @@ def iq_time_series(rec: Recording) -> Figure:
complex_signal = rec.data[0]
sample_rate = int(rec.metadata.get("sample_rate", 1))
plot_length = len(complex_signal)
# Downsample for performance (max 10,000 points)
max_points = 10000
step = max(1, plot_length // max_points)
if step > 1:
complex_signal = complex_signal[::step]
plot_length = len(complex_signal)
t = np.arange(0, plot_length, 1) * step / sample_rate
t = np.arange(0, plot_length, 1) / sample_rate
fig = go.Figure()
# Use Scattergl for WebGL-accelerated rendering
fig.add_trace(go.Scattergl(x=t, y=complex_signal.real, mode="lines", name="I (In-phase)", line=dict(width=0.6)))
fig.add_trace(go.Scattergl(x=t, y=complex_signal.imag, mode="lines", name="Q (Quadrature)", line=dict(width=0.6)))
fig.add_trace(go.Scatter(x=t, y=complex_signal.real, mode="lines", name="I (In-phase)", line=dict(width=0.6)))
fig.add_trace(go.Scatter(x=t, y=complex_signal.imag, mode="lines", name="Q (Quadrature)", line=dict(width=0.6)))
fig.update_layout(
title="IQ Time Series",
@ -159,15 +139,8 @@ def frequency_spectrum(rec: Recording) -> Figure:
log_spectrum = np.log10(spectrum + epsilon)
scaled_log_spectrum = (log_spectrum - log_spectrum.min()) / (log_spectrum.max() - log_spectrum.min())
# Downsample for performance (max 10,000 points)
max_points = 10000
if len(freqs) > max_points:
step = len(freqs) // max_points
freqs = freqs[::step]
scaled_log_spectrum = scaled_log_spectrum[::step]
fig = go.Figure()
fig.add_trace(go.Scattergl(x=freqs, y=scaled_log_spectrum, mode="lines", name="Spectrum", line=dict(width=0.4)))
fig.add_trace(go.Scatter(x=freqs, y=scaled_log_spectrum, mode="lines", name="Spectrum", line=dict(width=0.4)))
fig.update_layout(
title="Frequency Spectrum",
@ -201,7 +174,7 @@ def constellation(rec: Recording) -> Figure:
q_ds = complex_signal.imag[::step]
fig = go.Figure()
fig.add_trace(go.Scattergl(x=i_ds, y=q_ds, mode="lines", name="Constellation", line=dict(width=0.2)))
fig.add_trace(go.Scatter(x=i_ds, y=q_ds, mode="lines", name="Constellation", line=dict(width=0.2)))
fig.update_layout(
title="Constellation",
@ -248,7 +221,7 @@ def power_spectral_density(rec: Recording) -> Figure:
fig = go.Figure()
fig.add_trace(
go.Scattergl(x=frequencies_shifted, y=psd_db, mode="lines", name="PSD", line=dict(width=0.8, color="#00D9FF"))
go.Scatter(x=frequencies_shifted, y=psd_db, mode="lines", name="PSD", line=dict(width=0.8, color="#00D9FF"))
)
fig.update_layout(
@ -284,16 +257,8 @@ def fft_plot(rec: Recording) -> Figure:
magnitude = np.abs(fft_result)
magnitude_db = 20 * np.log10(magnitude + 1e-10)
max_points = 10000
if len(freqs) > max_points:
step = len(freqs) // max_points
freqs = freqs[::step]
magnitude_db = magnitude_db[::step]
fig = go.Figure()
fig.add_trace(
go.Scattergl(x=freqs, y=magnitude_db, mode="lines", name="FFT", line=dict(width=0.6, color="#FF6B9D"))
)
fig.add_trace(go.Scatter(x=freqs, y=magnitude_db, mode="lines", name="FFT", line=dict(width=0.6, color="#FF6B9D")))
fig.update_layout(
title="FFT Magnitude",
@ -349,18 +314,6 @@ def spectrogram_3d(rec: Recording) -> Figure:
frequencies_shifted = np.fft.fftshift(frequencies)
Sxx_shifted = np.fft.fftshift(Sxx_log, axes=0)
# Downsample to prevent browser memory issues (max ~40,000 total points)
max_freq_bins = 200
max_time_bins = 200
freq_step = max(1, len(frequencies_shifted) // max_freq_bins)
time_step = max(1, len(times) // max_time_bins)
if freq_step > 1 or time_step > 1:
Sxx_shifted = Sxx_shifted[::freq_step, ::time_step]
frequencies_shifted = frequencies_shifted[::freq_step]
times = times[::time_step]
fig = go.Figure(
data=[
go.Surface(