def get_clipped_heartbeat_signals(self, i, start, interval,
composite_start, composite_end):
# Center signals in current interval at the R peak
heartbeat_time = self.peaks.time[interval] - self.peaks.time[
self.peaks.R.data[start + 1 + i]]
heartbeat_signal = self.peaks.signal[interval] - self.peaks.signal[
self.peaks.R.data[start + 1 + i]]
heartbeat_seis = self.peaks.seis[interval] - self.peaks.signal[
self.peaks.R.data[start + 1 + i]]
heartbeat_phono = self.peaks.phono[interval] - self.peaks.signal[
self.peaks.R.data[start + 1 + i]]
# Clip Front
remove_from_start = int(
np.where(heartbeat_time == 0)[0] - composite_start)
if remove_from_start != 0:
heartbeat_time = np.delete(heartbeat_time,
range(remove_from_start))
heartbeat_signal = np.delete(heartbeat_signal,
range(remove_from_start))
heartbeat_seis = np.delete(heartbeat_seis,
range(remove_from_start))
heartbeat_phono = np.delete(heartbeat_phono,
range(remove_from_start))
# Clip Back
remove_from_end = int((len(heartbeat_time) -
np.where(heartbeat_time == 0)[0]) -
composite_end)
if remove_from_end != 0:
heartbeat_time = np.delete(
heartbeat_time,
range(
len(heartbeat_time) - remove_from_end,
len(heartbeat_time)))
heartbeat_signal = np.delete(
heartbeat_signal,
range(
len(heartbeat_time) - remove_from_end,
len(heartbeat_time)))
heartbeat_seis = np.delete(
heartbeat_seis,
range(
len(heartbeat_time) - remove_from_end,
len(heartbeat_time)))
heartbeat_phono = np.delete(
heartbeat_phono,
range(
len(heartbeat_time) - remove_from_end,
len(heartbeat_time)))
# Normalize
heartbeat_signal = hb.normalize(heartbeat_signal)
heartbeat_seis = hb.normalize(heartbeat_seis)
heartbeat_phono = hb.normalize(heartbeat_phono)
return heartbeat_time, heartbeat_signal, heartbeat_seis, heartbeat_phono
def update_plot(self):
# Update index
self.i_text.set_text("Heartbeat: " + str(self.index + 1) + "/" + str(len(self.peaks.R.data) - 1))
self.signal = hb.normalize(self.peaks.signal[range(self.peaks.P.data[self.index], self.peaks.R.data[self.index + 1])])
# Pass through a Low pass
self.smoothed_signal = hb.lowpass_filter(signal = self.signal,
cutoff_freq = self.cutoff_freq)
# Calculate first derivative
self.first, _ = hb.get_derivatives(self.smoothed_signal)
# Update cross hairs
self.switch_signal(None)
# Plot ECG, Phono and Seismo
self.signal_line.set_data(range(len(self.signal)), self.signal_amp_slider.val * self.signal)
self.smooth_signal_line.set_data(range(len(self.signal)), self.signal_amp_slider.val * self.smoothed_signal)
self.first_line.set_data(range(len(self.signal)), (self.first_amp_slider.val * 5*self.first) + self.first_height_slider.val + 1)
self.ax.set_xlim(0, len(self.signal))
# T Peak
self.T_point.set_offsets((self.peaks.T.data[self.index] - self.peaks.P.data[self.index], self.signal_amp_slider.val * self.smoothed_signal[self.peaks.T.data[self.index] - self.peaks.P.data[self.index]]))
self.T_text.set_position((self.peaks.T.data[self.index] - self.peaks.P.data[self.index], self.signal_amp_slider.val * self.smoothed_signal[self.peaks.T.data[self.index] - self.peaks.P.data[self.index]] + 0.2))
# ST Start Peak
self.ST_start_point.set_offsets((self.peaks.ST_start.data[self.index] - self.peaks.P.data[self.index], self.signal_amp_slider.val * self.smoothed_signal[self.peaks.ST_start.data[self.index] - self.peaks.P.data[self.index]]))
self.ST_start_text.set_position((self.peaks.ST_start.data[self.index] - self.peaks.P.data[self.index], self.signal_amp_slider.val * self.smoothed_signal[self.peaks.ST_start.data[self.index] - self.peaks.P.data[self.index]] + 0.2))
# T''max Peak
self.dT_point.set_offsets((self.peaks.dT.data[self.index] - self.peaks.P.data[self.index], self.signal_amp_slider.val * self.smoothed_signal[self.peaks.dT.data[self.index] - self.peaks.P.data[self.index]]))
self.dT_text.set_position((self.peaks.dT.data[self.index] - self.peaks.P.data[self.index], self.signal_amp_slider.val * self.smoothed_signal[self.peaks.dT.data[self.index] - self.peaks.P.data[self.index]] + 0.2))
# # T''max Peak
# self.ddT_point.set_offsets((self.peaks.ddT.data[self.index] - self.peaks.P.data[self.index], self.signal_amp_slider.val * self.smoothed_signal[self.peaks.ddT.data[self.index] - self.peaks.P.data[self.index]]))
# self.ddT_text.set_position((self.peaks.ddT.data[self.index] - self.peaks.P.data[self.index], self.signal_amp_slider.val * self.smoothed_signal[self.peaks.ddT.data[self.index] - self.peaks.P.data[self.index]] + 0.2))
self.fig.canvas.draw()
def get_N_composite_signal_dataset(self,
N,
slide_step_size,
display=False,
dosage=None):
# Get all heartbeats in composite
composite_endpoints = self.get_N_composite_endpoints(
N, slide_step_size)
composites = []
count = 0
for start, end in composite_endpoints:
count += 1
# Find bounds for composite endpoints
composite_start, composite_end = self.get_composite_bounds(
start, end)
# Clip all heartbeats to same length
for i in range(N):
# Define current interval
interval = range(self.peaks.T.data[start + i],
self.peaks.P.data[start + i + 2])
# Clip signals and center them based off R peak
heartbeat_time, heartbeat_signal, heartbeat_seis, heartbeat_phono = self.get_clipped_heartbeat_signals(
i, start, interval, composite_start, composite_end)
# Cumulative sum
composite_time = heartbeat_time if i == 0 else composite_time + heartbeat_time
composite_signal = heartbeat_signal if i == 0 else composite_signal + heartbeat_signal
composite_seis = heartbeat_seis if i == 0 else composite_seis + heartbeat_seis
composite_phono = heartbeat_phono if i == 0 else composite_phono + heartbeat_phono
# Divide by sample size
composite_time /= N
composite_signal /= N
composite_seis /= N
composite_phono /= N
composites.append([
composite_time, composite_signal, composite_seis,
composite_phono
])
if display:
# Display
fig, axes2d = plt.subplots(nrows=N, ncols=3)
signal_lay_over_cell = fig.add_subplot(3, 3, 2)
seis_lay_over_cell = fig.add_subplot(3, 3, 5)
phono_lay_over_cell = fig.add_subplot(3, 3, 8)
composite_cell = fig.add_subplot(1, 3, 3)
if dosage is None:
plt.suptitle(
str(count) + " of " + str(len(composite_endpoints)) +
" INO Composites given " + str(N) +
" Heartbeats w/ Step Size of " + str(slide_step_size),
fontsize=20)
else:
plt.suptitle(
str(count) + " of " + str(len(composite_endpoints)) +
" INO Composites for Dosage " + str(dosage) +
" given " + str(N) + " Heartbeats w/ Step Size of " +
str(slide_step_size),
fontsize=20)
for i, row in enumerate(axes2d):
for j, cell in enumerate(row):
interval = range(self.peaks.T.data[start + i],
self.peaks.P.data[start + i + 2])
cell.set_xticks([])
cell.set_yticks([])
if j == 0:
if i == 0:
cell.set_title("Individual Signals")
cell.plot(
self.peaks.time[interval],
hb.normalize(self.peaks.signal[interval]))
cell.plot(self.peaks.time[interval],
hb.normalize(self.peaks.seis[interval]))
cell.plot(self.peaks.time[interval],
hb.normalize(self.peaks.phono[interval]))
cell.set_ylabel(start + i)
elif j == 1:
signal_lay_over_cell.plot(
self.peaks.time[interval] -
self.peaks.time[self.peaks.R.data[start + 1 +
i]],
hb.normalize(self.peaks.signal[interval] -
self.peaks.signal[
self.peaks.R.data[start + 1 +
i]]),
"--",
linewidth=0.5)
seis_lay_over_cell.plot(
self.peaks.time[interval] -
self.peaks.time[self.peaks.R.data[start + 1 +
i]],
hb.normalize(self.peaks.seis[interval] -
self.peaks.signal[
self.peaks.R.data[start + 1 +
i]]),
"--",
linewidth=0.5)
phono_lay_over_cell.plot(
self.peaks.time[interval] -
self.peaks.time[self.peaks.R.data[start + 1 +
i]],
hb.normalize(self.peaks.phono[interval] -
self.peaks.signal[
self.peaks.R.data[start + 1 +
i]]),
"--",
linewidth=0.5)
signal_lay_over_cell.set_xticks([])
signal_lay_over_cell.set_yticks([])
seis_lay_over_cell.set_xticks([])
seis_lay_over_cell.set_yticks([])
phono_lay_over_cell.set_xticks([])
phono_lay_over_cell.set_yticks([])
else:
if i == 0:
signal_lay_over_cell.plot(
composite_time,
hb.normalize(composite_signal),
'r',
linewidth=2,
label="Composite Signal")
signal_lay_over_cell.legend(loc='lower left')
seis_lay_over_cell.plot(
composite_time,
hb.normalize(composite_seis),
'r',
linewidth=2,
label="Composite Seis")
seis_lay_over_cell.legend(loc='lower left')
phono_lay_over_cell.plot(
composite_time,
hb.normalize(composite_phono),
'r',
linewidth=2,
label="Composite Phono")
phono_lay_over_cell.legend(loc='lower left')
composite_cell.plot(composite_signal,
'r',
label="EKG")
composite_cell.plot(composite_seis,
'b',
label="Seis",
linewidth=0.5)
composite_cell.plot(composite_phono,
'g',
label="Phono",
linewidth=0.5)
composite_cell.legend(loc='lower left')
composite_cell.set_xticks([])
composite_cell.set_yticks([])
composite_cell.set_title("Composite")
signal_lay_over_cell.set_title("Superimposed")
# Maximize Frame
mng = plt.get_current_fig_manager()
mng.full_screen_toggle()
plt.show()
self.composites = composites
return composites
def plot_signals(self):
# Create figure
self.fig, self.ax = plt.subplots()
self.signal = hb.normalize(self.peaks.signal[range(self.peaks.P.data[self.index], self.peaks.T.data[self.index + 1])])
# Determine what cutoff freq to use
self.cutoff_freq = 15 if np.mean(np.diff(self.peaks.R.data)) > 2500 else 10
# Pass through a Low pass
self.smoothed_signal = hb.lowpass_filter(signal = self.signal,
cutoff_freq = self.cutoff_freq)
# Calculate first derivative
self.first, _ = hb.get_derivatives(self.smoothed_signal)
# Plot ECG, Phono and Seismo
self.signal_line, = self.ax.plot(range(len(self.signal)), self.signal, linewidth = 0.75, c = "r", label = "ECG")
self.smooth_signal_line, = self.ax.plot(range(len(self.signal)), self.smoothed_signal, linewidth = 1, c = "b", label = "Low Pass ECG")
self.first_line, = self.ax.plot(range(len(self.signal)), 1 + 5*self.first,
'--', linewidth = 0.5, c = 'k', label = "ECG 1st Derv.")
self.ax.set_xlim(0, len(self.signal))
sig_min = min(self.signal)
sig_max = max(self.signal)
self.ax.set_ylim(sig_min - 0.2*(sig_max - sig_min), sig_max + 0.2*(sig_max - sig_min))
plt.legend(loc='upper right')
# T Peak
self.T_point = self.ax.scatter(self.peaks.T.data[self.index] - self.peaks.P.data[self.index], self.smoothed_signal[self.peaks.T.data[self.index] - self.peaks.P.data[self.index]], c = '#9467bd')
self.T_text = self.ax.text(self.peaks.T.data[self.index] - self.peaks.P.data[self.index], self.smoothed_signal[self.peaks.T.data[self.index] - self.peaks.P.data[self.index]] + 0.2, "T", fontsize=9, horizontalalignment = 'center')
# ST Start Peak
self.ST_start_point = self.ax.scatter(self.peaks.ST_start.data[self.index] - self.peaks.P.data[self.index], self.smoothed_signal[self.peaks.ST_start.data[self.index] - self.peaks.P.data[self.index]], c = 'y')
self.ST_start_text = self.ax.text(self.peaks.ST_start.data[self.index] - self.peaks.P.data[self.index], self.smoothed_signal[self.peaks.ST_start.data[self.index] - self.peaks.P.data[self.index]] + 0.2, "ST Start", fontsize=9, horizontalalignment = 'center')
# T'max Peak
self.dT_point = self.ax.scatter(self.peaks.dT.data[self.index] - self.peaks.P.data[self.index], self.smoothed_signal[self.peaks.dT.data[self.index] - self.peaks.P.data[self.index]], c = '#2ca02c')
self.dT_text = self.ax.text(self.peaks.dT.data[self.index] - self.peaks.P.data[self.index], self.smoothed_signal[self.peaks.dT.data[self.index] - self.peaks.P.data[self.index]] + 0.2, "T'max", fontsize=9, horizontalalignment = 'center')
# # T''max Peak
# self.ddT_point = self.ax.scatter(self.peaks.ddT.data[self.index] - self.peaks.P.data[self.index], self.smoothed_signal[self.peaks.ddT.data[self.index] - self.peaks.P.data[self.index]], c = '#2ca02c')
# self.ddT_text = self.ax.text(self.peaks.ddT.data[self.index] - self.peaks.P.data[self.index], self.smoothed_signal[self.peaks.ddT.data[self.index] - self.peaks.P.data[self.index]] + 0.2, "T''max", fontsize=9, horizontalalignment = 'center')
# Initalize axes and data points
self.x = range(len(self.signal))
self.y = self.smoothed_signal
# Cross hairs
self.lx = self.ax.axhline(color='k', linewidth=0.2) # the horiz line
self.ly = self.ax.axvline(color='k', linewidth=0.2) # the vert line
# Add data
left_shift = 0.45
start = 0.96
space = 0.04
self.ax.text(0.01, start, transform = self.ax.transAxes,
s = "Folder: " + self.folder_name, fontsize=12, horizontalalignment = 'left')
self.ax.text(0.01, start - space, transform = self.ax.transAxes,
s = "Dosage: " + str(self.dosage), fontsize=12, horizontalalignment = 'left')
self.i_text = self.ax.text(0.60 - left_shift, 1.1 - space, transform = self.ax.transAxes,
s = "Heartbeat: " + str(self.index + 1) + "/" + str(len(self.peaks.R.data) - 1), fontsize=12, horizontalalignment = 'left')
# Add index buttons
ax_prev = plt.axes([0.575 - left_shift, 0.9, 0.1, 0.075])
self.bprev = Button(ax_prev, 'Previous')
self.bprev.on_clicked(self.prev)
ax_next = plt.axes([0.8 - left_shift, 0.9, 0.1, 0.075])
self.b_next = Button(ax_next, 'Next')
self.b_next.on_clicked(self.next)
self.fig.canvas.mpl_connect('motion_notify_event', self.mouse_move)
self.fig.canvas.mpl_connect('button_press_event', self.on_click)
self.fig.canvas.mpl_connect('button_release_event', self.off_click)
# Add Sliders
start = 0.91
slider_width = 0.0075
slider_height = 0.47
self.cutoff_amp_slider = Slider(plt.axes([0.05, 0.15, 2*slider_width, slider_height]),
label = "Cutoff (Hz)",
valmin = 1,
valmax = 50,
valinit = self.cutoff_freq,
orientation = 'vertical',
valfmt='%0.0f')
self.cutoff_amp_slider.label.set_size(8)
self.cutoff_amp_slider.on_changed(self.switch_signal)
self.signal_amp_slider = Slider(plt.axes([start, 0.15, slider_width, slider_height]),
label = "ECG\n\nA",
valmin = 0.01,
valmax = 10,
valinit = 1,
orientation = 'vertical')
self.signal_amp_slider.label.set_size(8)
self.signal_amp_slider.on_changed(self.switch_signal)
self.signal_amp_slider.valtext.set_visible(False)
self.first_height_slider = Slider(plt.axes([start + 2*slider_width, 0.15, slider_width, slider_height]),
label = " 1st\n Derv.\nH",
valmin = 1.5 * min(self.signal),
valmax = 1.5 * max(self.signal),
valinit = 0,
orientation = 'vertical')
self.first_height_slider.label.set_size(8)
self.first_height_slider.on_changed(self.switch_signal)
self.first_height_slider.valtext.set_visible(False)
self.first_amp_slider = Slider(plt.axes([start + 3*slider_width, 0.15, slider_width, slider_height]),
label = "\nA",
valmin = 0.01,
valmax = 10,
valinit = 1,
orientation = 'vertical')
self.first_amp_slider.label.set_size(8)
self.first_amp_slider.on_changed(self.switch_signal)
self.first_amp_slider.valtext.set_visible(False)
# Maximize frame
mng = plt.get_current_fig_manager()
mng.full_screen_toggle()
plt.show()
