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)