# -*- coding: utf-8 -*-
from warnings import warn
import matplotlib.collections
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from ..misc import NeuroKitWarning
[docs]
def eda_plot(eda_signals, info=None, static=True):
"""**Visualize electrodermal activity (EDA) data**
Parameters
----------
eda_signals : DataFrame
DataFrame obtained from :func:`eda_process()`.
info : dict
The information Dict returned by ``eda_process()``. Defaults to ``None``.
static : bool
If True, a static plot will be generated with matplotlib.
If False, an interactive plot will be generated with plotly.
Defaults to True.
Returns
-------
See :func:`.ecg_plot` for details on how to access the figure, modify the size and save it.
Examples
--------
.. ipython:: python
import neurokit2 as nk
eda_signal = nk.eda_simulate(duration=30, scr_number=5, drift=0.1, noise=0, sampling_rate=250)
eda_signals, info = nk.eda_process(eda_signal, sampling_rate=250)
@savefig p_eda_plot1.png scale=100%
nk.eda_plot(eda_signals, info)
@suppress
plt.close()
See Also
--------
eda_process
"""
if info is None:
warn(
"'info' dict not provided. Some information might be missing."
+ " Sampling rate will be set to 1000 Hz.",
category=NeuroKitWarning,
)
info = {
"sampling_rate": 1000,
}
# Determine peaks, onsets, and half recovery.
peaks = np.where(eda_signals["SCR_Peaks"] == 1)[0]
onsets = np.where(eda_signals["SCR_Onsets"] == 1)[0]
half_recovery = np.where(eda_signals["SCR_Recovery"] == 1)[0]
# clean peaks that do not have onsets
if len(peaks) > len(onsets):
peaks = peaks[1:]
# Determine unit of x-axis.
x_label = "Time (seconds)"
x_axis = np.linspace(0, len(eda_signals) / info["sampling_rate"], len(eda_signals))
if static:
fig, (ax0, ax1, ax2) = plt.subplots(nrows=3, ncols=1, sharex=True)
last_ax = fig.get_axes()[-1]
last_ax.set_xlabel(x_label)
# Plot cleaned and raw electrodermal activity.
ax0.set_title("Raw and Cleaned Signal")
fig.suptitle("Electrodermal Activity (EDA)", fontweight="bold")
ax0.plot(x_axis, eda_signals["EDA_Raw"], color="#B0BEC5", label="Raw", zorder=1)
ax0.plot(
x_axis,
eda_signals["EDA_Clean"],
color="#9C27B0",
label="Cleaned",
linewidth=1.5,
zorder=1,
)
ax0.legend(loc="upper right")
# Plot skin conductance response.
ax1.set_title("Skin Conductance Response (SCR)")
# Plot Phasic.
ax1.plot(
x_axis,
eda_signals["EDA_Phasic"],
color="#E91E63",
label="Phasic Component",
linewidth=1.5,
zorder=1,
)
# Mark segments.
risetime_coord, amplitude_coord, halfr_coord = _eda_plot_dashedsegments(
eda_signals, ax1, x_axis, onsets, peaks, half_recovery
)
risetime = matplotlib.collections.LineCollection(
risetime_coord, colors="#FFA726", linewidths=1, linestyle="dashed"
)
ax1.add_collection(risetime)
amplitude = matplotlib.collections.LineCollection(
amplitude_coord, colors="#1976D2", linewidths=1, linestyle="solid"
)
ax1.add_collection(amplitude)
halfr = matplotlib.collections.LineCollection(
halfr_coord, colors="#FDD835", linewidths=1, linestyle="dashed"
)
ax1.add_collection(halfr)
ax1.legend(loc="upper right")
# Plot Tonic.
ax2.set_title("Skin Conductance Level (SCL)")
ax2.plot(
x_axis,
eda_signals["EDA_Tonic"],
color="#673AB7",
label="Tonic Component",
linewidth=1.5,
)
ax2.legend(loc="upper right")
else:
# Create interactive plot with plotly.
try:
import plotly.graph_objects as go
from plotly.subplots import make_subplots
except ImportError as e:
raise ImportError(
"NeuroKit error: ppg_plot(): the 'plotly'",
" module is required when 'static' is False.",
" Please install it first (`pip install plotly`).",
) from e
fig = make_subplots(
rows=3,
cols=1,
shared_xaxes=True,
vertical_spacing=0.05,
subplot_titles=(
"Raw and Cleaned Signal",
"Skin Conductance Response (SCR)",
"Skin Conductance Level (SCL)",
),
)
# Plot cleaned and raw electrodermal activity.
fig.add_trace(
go.Scatter(
x=x_axis,
y=eda_signals["EDA_Raw"],
mode="lines",
name="Raw",
line=dict(color="#B0BEC5"),
showlegend=True,
),
row=1,
col=1,
)
fig.add_trace(
go.Scatter(
x=x_axis,
y=eda_signals["EDA_Clean"],
mode="lines",
name="Cleaned",
line=dict(color="#9C27B0"),
showlegend=True,
),
row=1,
col=1,
)
# Plot skin conductance response.
fig.add_trace(
go.Scatter(
x=x_axis,
y=eda_signals["EDA_Phasic"],
mode="lines",
name="Phasic Component",
line=dict(color="#E91E63"),
showlegend=True,
),
row=2,
col=1,
)
# Mark segments.
_, _, _ = _eda_plot_dashedsegments(
eda_signals, fig, x_axis, onsets, peaks, half_recovery, static=static
)
# TODO add dashed segments to plotly version
# Plot skin conductance level.
fig.add_trace(
go.Scatter(
x=x_axis,
y=eda_signals["EDA_Tonic"],
mode="lines",
name="Tonic Component",
line=dict(color="#673AB7"),
showlegend=True,
),
row=3,
col=1,
)
# Add title to entire figure.
fig.update_layout(title_text="Electrodermal Activity (EDA)", title_x=0.5)
return fig
# =============================================================================
# Internals
# =============================================================================
def _eda_plot_dashedsegments(
eda_signals, ax, x_axis, onsets, peaks, half_recovery, static=True
):
# Mark onsets, peaks, and half-recovery.
onset_x_values = x_axis[onsets]
onset_y_values = eda_signals["EDA_Phasic"][onsets].values
peak_x_values = x_axis[peaks]
peak_y_values = eda_signals["EDA_Phasic"][peaks].values
halfr_x_values = x_axis[half_recovery]
halfr_y_values = eda_signals["EDA_Phasic"][half_recovery].values
end_onset = pd.Series(
eda_signals["EDA_Phasic"][onsets].values, eda_signals["EDA_Phasic"][peaks].index
)
risetime_coord = []
amplitude_coord = []
halfr_coord = []
for i in range(len(onsets)):
# Rise time.
start = (onset_x_values[i], onset_y_values[i])
end = (peak_x_values[i], onset_y_values[i])
risetime_coord.append((start, end))
for i in range(len(peaks)):
# SCR Amplitude.
start = (peak_x_values[i], onset_y_values[i])
end = (peak_x_values[i], peak_y_values[i])
amplitude_coord.append((start, end))
for i in range(len(half_recovery)):
# Half recovery.
end = (halfr_x_values[i], halfr_y_values[i])
peak_x_idx = np.where(peak_x_values < halfr_x_values[i])[0][-1]
start = (peak_x_values[peak_x_idx], halfr_y_values[i])
halfr_coord.append((start, end))
if static:
# Plot with matplotlib.
# Mark onsets, peaks, and half-recovery.
ax.scatter(
x_axis[onsets],
eda_signals["EDA_Phasic"][onsets],
color="#FFA726",
label="SCR - Onsets",
zorder=2,
)
ax.scatter(
x_axis[peaks],
eda_signals["EDA_Phasic"][peaks],
color="#1976D2",
label="SCR - Peaks",
zorder=2,
)
ax.scatter(
x_axis[half_recovery],
eda_signals["EDA_Phasic"][half_recovery],
color="#FDD835",
label="SCR - Half recovery",
zorder=2,
)
ax.scatter(x_axis[end_onset.index], end_onset.values, alpha=0)
else:
# Create interactive plot with plotly.
try:
import plotly.graph_objects as go
except ImportError as e:
raise ImportError(
"NeuroKit error: ppg_plot(): the 'plotly'",
" module is required when 'static' is False.",
" Please install it first (`pip install plotly`).",
) from e
# Plot with plotly.
# Mark onsets, peaks, and half-recovery.
ax.add_trace(
go.Scatter(
x=x_axis[onsets],
y=eda_signals["EDA_Phasic"][onsets],
mode="markers",
name="SCR - Onsets",
marker=dict(color="#FFA726"),
showlegend=True,
),
row=2,
col=1,
)
ax.add_trace(
go.Scatter(
x=x_axis[peaks],
y=eda_signals["EDA_Phasic"][peaks],
mode="markers",
name="SCR - Peaks",
marker=dict(color="#1976D2"),
showlegend=True,
),
row=2,
col=1,
)
ax.add_trace(
go.Scatter(
x=x_axis[half_recovery],
y=eda_signals["EDA_Phasic"][half_recovery],
mode="markers",
name="SCR - Half recovery",
marker=dict(color="#FDD835"),
showlegend=True,
),
row=2,
col=1,
)
ax.add_trace(
go.Scatter(
x=x_axis[end_onset.index],
y=end_onset.values,
mode="markers",
marker=dict(color="#FDD835", opacity=0),
showlegend=False,
),
row=2,
col=1,
)
return risetime_coord, amplitude_coord, halfr_coord
