def test_to_epochs(self):
"""Test oxi_peaks function"""
ppg = import_ppg('1')[0, :] # Import PPG recording
events = import_ppg('1')[1, :] # Import events
events[2] = 1
epochs = to_epochs(ppg,
events,
sfreq=75,
verbose=True,
apply_baseline=(-1, 0))
assert epochs.ndim == 2
epochs = to_epochs(list(ppg),
list(events),
sfreq=75,
apply_baseline=None)
reject = np.arange(0, len(ppg))
reject[50:55] = 1
epochs = to_epochs(ppg,
events,
sfreq=75,
apply_baseline=-1,
reject=reject,
verbose=True)
with pytest.raises(ValueError):
epochs = to_epochs(ppg[1:], events, sfreq=75)
def test_to_rr(self):
ppg = import_ppg().ppg.to_numpy()
signal, peaks = oxi_peaks(ppg)
rr = to_rr(peaks)
assert rr.mean() == 874.2068965517242
rr = to_rr(np.where(peaks)[0])
assert rr.mean() == 874.2068965517242
def test_interpolate_clipping(self):
df = import_ppg()
clean_signal = interpolate_clipping(df.ppg.to_numpy())
assert clean_signal.mean().round() == 100
clean_signal = interpolate_clipping(list(df.ppg.to_numpy()))
assert clean_signal.mean().round() == 100
clean_signal = interpolate_clipping(df.ppg.to_numpy())
df.ppg.iloc[0], df.ppg.iloc[-1] = 255, 255
clean_signal = interpolate_clipping(df.ppg.to_numpy())
def test_interpolate_clipping(self):
ppg = import_ppg('1')[0]
clean_signal = interpolate_clipping(ppg)
assert clean_signal.mean().round() == 100
clean_signal = interpolate_clipping(list(ppg))
assert clean_signal.mean().round() == 100
clean_signal = interpolate_clipping(ppg)
ppg[0], ppg[-1] = 255, 255
clean_signal = interpolate_clipping(ppg)
def test_norm_triggers(self):
ppg = import_ppg('1')[0, :] # Import PPG recording
signal, peaks = oxi_peaks(ppg)
peaks[np.where(peaks)[0] + 1] = 1
peaks[np.where(peaks)[0] + 2] = 1
y = norm_triggers(peaks)
assert sum(y) == 378
peaks = -peaks
y = norm_triggers(peaks, threshold=-1, direction='lower')
assert sum(y) == 378
def test_to_angle(self):
"""Test to_angles function"""
rr = import_rr().rr.values
# Create event vector
events = rr + np.random.normal(500, 100, len(rr))
ang = to_angles(list(np.cumsum(rr)), list(np.cumsum(events)))
assert ~np.any(np.asarray(ang) < 0)
assert ~np.any(np.asarray(ang) > np.pi * 2)
ppg = import_ppg('1')[0, :] # Import PPG recording
signal, peaks = oxi_peaks(ppg)
ang = to_angles(peaks, peaks)
def test_heart_rate(self):
"""Test heart_rate function"""
ppg = import_ppg('1')[0, :] # Import PPG recording
signal, peaks = oxi_peaks(ppg)
heartrate, time = heart_rate(peaks)
assert len(heartrate) == len(time)
heartrate, time = heart_rate(list(peaks))
assert len(heartrate) == len(time)
heartrate, time = heart_rate(peaks,
unit='bpm',
kind='cubic',
sfreq=500)
assert len(heartrate) == len(time)
def test_norm_triggers(self):
ppg = import_ppg('1')[0, :] # Import PPG recording
signal, peaks = oxi_peaks(ppg)
peaks[np.where(peaks)[0] + 1] = 1
peaks[np.where(peaks)[0] + 2] = 1
peaks[-1:] = 1
y = norm_triggers(peaks)
assert sum(y) == 379
peaks = -peaks.astype(int)
y = norm_triggers(peaks, threshold=-1, direction='lower')
assert sum(y) == 379
with pytest.raises(ValueError):
norm_triggers(None)
with pytest.raises(ValueError):
norm_triggers(peaks, direction='invalid')
def test_heart_rate(self):
"""Test heart_rate function"""
ppg = import_ppg().ppg.to_numpy() # Import PPG recording
signal, peaks = oxi_peaks(ppg)
heartrate, time = heart_rate(peaks)
assert len(heartrate) == len(time)
heartrate, time = heart_rate(list(peaks))
assert len(heartrate) == len(time)
heartrate, time = heart_rate(peaks,
unit='bpm',
kind='cubic',
sfreq=500)
assert len(heartrate) == len(time)
with pytest.raises(ValueError):
heartrate, time = heart_rate([1, 2, 3])
# Author: Nicolas Legrand <*****@*****.**>
# Licence: GPL v3
#%%
import plotly
from systole.detection import rr_artefacts
from systole import import_rr, import_ppg
from systole.plotly import plot_subspaces, plot_frequency, plot_raw,\
plot_timedomain, plot_nonlinear
#%%
# Raw data
# --------
#
ppg = import_ppg()[0]
plot_raw(ppg)
#%%
# HRV analyses
# ------------
rr = import_rr().rr.values
#%%
# Frequency domain
# ----------------
plot1 = plot_timedomain(rr)
plotly.io.show(plot1)
#%%
def test_to_epochs(self):
"""Test oxi_peaks function"""
ppg = import_ppg('1')[0, :] # Import PPG recording
events = import_ppg('1')[1, :] # Import events
epochs = to_epochs(ppg, events, sfreq=75)
assert epochs.ndim == 2
import matplotlib.pyplot as plt
from systole import import_ppg
from systole.detection import interpolate_clipping
df = import_ppg()
clean_signal = interpolate_clipping(df.ppg.to_numpy())
plt.plot(df.time, clean_signal, color='#F15854')
plt.plot(df.time, df.ppg, color='#5DA5DA')
plt.axhline(y=255, linestyle='--', color='k')
plt.xlabel('Time (s)')
plt.ylabel('PPG level (a.u)')
def report_oxi(signal, file_name='report.png', dpi=600):
"""Generate HRV report.
Parameters
----------
signal : 1d array-like
PPG singal.
file_name : str
Output file name.
dpi : int
Image quality.
"""
from systole import import_ppg
signal = import_ppg('1')[0]
plot_oximeter(signal)
# Find peaks
signal, peaks = oxi_peaks(signal)
# Extract instantaneous heartrate
sfreq = 1000
noisy_hr, time = heart_rate(peaks, sfreq=sfreq, unit='bpm', kind='cubic')
time = np.arange(0, len(signal) / sfreq, 1 / sfreq)
fig = plt.figure(figsize=(8, 13))
gs = fig.add_gridspec(4, 3)
fig_ax1 = fig.add_subplot(gs[0, :])
fig_ax1.plot(time, signal, linewidth=.2)
fig_ax1.set_ylabel('PPG level')
fig_ax1.set_xlim(0, time[-1])
fig_ax1.set_title('Signal', fontweight='bold')
fig_ax2 = fig.add_subplot(gs[1, :])
fig_ax2.plot(time, noisy_hr, linewidth=.8, color='r')
fig_ax2.set_ylabel('BPM')
fig_ax2.set_xlabel('Time (s)')
fig_ax2.set_xlim(0, time[-1])
fig_ax2.set_title('RR time-course', fontweight='bold')
# HRV
rr = np.diff(np.where(peaks)[0])
fig_ax3 = fig.add_subplot(gs[2, 0])
fig_ax3.hist(rr, bins=30, alpha=.5)
fig_ax3.hist(rr[(rr <= 400) | (rr >= 1500)], bins=30, color='r')
fig_ax3.set_title('Distribution', fontweight='bold')
fig_ax3.set_ylabel('Count')
fig_ax3.set_xlabel('RR(s)')
fig_ax4 = fig.add_subplot(gs[2, 1])
plot_psd(rr, show=True, ax=fig_ax4)
fig_ax5 = fig.add_subplot(gs[2, 2])
fig_ax5.plot(rr[:-1], rr[1:], color='gray', markersize=1, alpha=0.8)
fig_ax5.set_title('Pointcare Plot', fontweight='bold')
fig_ax5.set_ylabel('$RR_{n+1}$')
fig_ax5.set_xlabel('$RR_n$')
plt.tight_layout(h_pad=0.05)
if file_name is not None:
plt.savefig(file_name, dpi=dpi)
plt.close()
import pandas as pd
import unittest
import pytest
import matplotlib
from unittest import TestCase
from systole.plotting import plot_hr, plot_events, plot_oximeter,\
plot_subspaces, circular, plot_circular, plot_psd
from systole import import_ppg, import_rr, serialSim
from systole.recording import Oximeter
serial = serialSim()
oxi = Oximeter(serial=serial, add_channels=1).setup().read(10)
oxi.channels['Channel_0'][100] = 1
# Simulate oximeter instance from recorded signal
ppg = import_ppg().ppg.to_numpy()
oxi = Oximeter(serial=None, add_channels=1)
oxi.threshold = [0] * 75
oxi.peaks = [0] * 75
oxi.instant_rr = [0] * 75
oxi.recording = list(ppg[:75])
for i in range(len(ppg[75:750])):
oxi.add_paquet(ppg[75 + i])
oxi.channels['Channel_0'] = np.zeros(750, dtype=int)
oxi.channels['Channel_0'][np.random.choice(np.arange(0, 750), 5)] = 1
oxi.times = list(np.arange(0, 10, 1 / 75))
# Create angular data
x = np.random.normal(np.pi, 0.5, 100)
y = np.random.uniform(0, np.pi * 2, 100)
z = np.concatenate([
def test_report_oxi(self):
ppg = import_ppg('1')[0, :] # Import PPG recording
report_oxi(ppg, file_name=None)
def test_oxi_peaks(self):
"""Test oxi_peaks function"""
ppg = import_ppg('1')[0, :] # Import PPG recording
signal, peaks = oxi_peaks(ppg)
assert len(signal) == len(peaks)
assert np.all(np.unique(peaks) == [0, 1])
def test_oxi_peaks(self):
"""Test oxi_peaks function"""
df = import_ppg() # Import PPG recording
signal, peaks = oxi_peaks(df.ppg.to_numpy())
assert len(signal) == len(peaks)
assert np.all(np.unique(peaks) == [0, 1])
