def test_rsp_plot():
rsp = nk.rsp_simulate(duration=120, sampling_rate=1000,
respiratory_rate=15)
rsp_summary, _ = nk.rsp_process(rsp, sampling_rate=1000)
nk.rsp_plot(rsp_summary)
# This will identify the latest figure.
fig = plt.gcf()
assert len(fig.axes) == 3
titles = ["Raw and Cleaned Signal",
"Breathing Rate",
"Breathing Amplitude"]
for (ax, title) in zip(fig.get_axes(), titles):
assert ax.get_title() == title
plt.close(fig)
def test_rsp_plot():
rsp = nk.rsp_simulate(duration=120, sampling_rate=1000,
respiratory_rate=15)
signals, _ = nk.rsp_process(rsp, sampling_rate=1000)
nk.rsp_plot(signals)
# this will identify the latest figure
fig = plt.gcf()
assert len(fig.axes) == 4
titles = ["Signal and Breathing Extrema",
"Breathing Period",
"Breathing Rate",
"Breathing Amplitude"]
for (ax, title) in zip(fig.get_axes(), titles):
assert ax.get_title() == title
plt.close(fig)
plot = nk.ecg_plot(signals, sampling_rate=250)
plot.set_size_inches(10, 6, forward=True)
plot.savefig("README_ecg.png", dpi=300, h_pad=3)
# =============================================================================
# Respiration (RSP) processing
# =============================================================================
# Generate one minute of RSP signal (recorded at 250 samples / second)
rsp = nk.rsp_simulate(duration=60, sampling_rate=250, respiratory_rate=15)
# Process it
signals, info = nk.rsp_process(rsp, sampling_rate=250)
# Visualise the processing
nk.rsp_plot(signals, sampling_rate=250)
# Save it
plot = nk.rsp_plot(signals, sampling_rate=250)
plot.set_size_inches(10, 6, forward=True)
plot.savefig("README_rsp.png", dpi=300, h_pad=3)
# =============================================================================
# Electromyography (EMG) processing
# =============================================================================
# Generate 10 seconds of EMG signal (recorded at 250 samples / second)
emg = nk.emg_simulate(duration=10, sampling_rate=250, burst_number=3)
# Process it
signals, _ = nk.emg_process(emg, sampling_rate=250)
# Generate synthetic signals
ecg = nk.ecg_simulate(duration=10, heart_rate=70)
rsp = nk.rsp_simulate(duration=10, respiratory_rate=15)
eda = nk.eda_simulate(duration=10, n_scr=3)
emg = nk.emg_simulate(duration=10, n_bursts=2)
# Visualise biosignals
data = pd.DataFrame({"ECG": ecg, "RSP": rsp, "EDA": eda, "EMG": emg})
data.plot(subplots=True, layout=(4, 1))
# Save it
plot = data.plot(subplots=True, layout=(4, 1))
plot[0][0].get_figure().savefig("README_simulation.png", dpi=300)
# =============================================================================
# Respiration (RSP) processing
# =============================================================================
# Generate one minute of respiratory signal
rsp = nk.rsp_simulate(duration=60, respiratory_rate=15)
# Process it
signals, info = nk.rsp_process(rsp)
# Visualise the processing
nk.rsp_plot(signals)
# Save it
plot = nk.rsp_plot(signals)
plot.savefig("README_respiration.png", dpi=300)