viz.py
import os
import numpy as np
def plot_raw_blinks(fname, raw, overwrite=True, show=False):
"""Plot detected (and corrected) blinks in raw pupillometry data."""
from bokeh.plotting import figure, output_file, show
from bokeh.models import BoxZoomTool, Range1d
## I/O handling.
if not os.path.splitext(fname.lower()) == '.html': fname = '%s.html' %fname
if os.path.isfile(fname): os.remove(fname)
## Initialize html file.
output_file(fname)
## Initialize figure.
x_range = (raw.times.min(), raw.times.max())
y_range = np.array((np.nanmin(raw.data[:,-1]),np.nanmax(raw.data[:,-1])))
y_range += 0.1 * np.concatenate([-np.diff(y_range), np.diff(y_range)])
plot = figure(plot_width=1200, plot_height=300, toolbar_location="right",
x_range = x_range, y_range=y_range, tools="wheel_zoom,reset",
x_axis_label='Time (s)', y_axis_label='Pupillometry (au)',
title="Blink Correction")
plot.add_tools(BoxZoomTool(dimensions="width"))
## Plot raw pupillometry data.
plot.line(raw.times, raw.data[:,-1], line_width=2)
## Plot blink periods.
X, Y = [], []
for i, j in raw.blinks:
X.append(raw.times[i:j])
Y.append(raw.data[i:j,-1])
plot.patch(np.hstack((X[-1],X[-1][::-1])),
np.hstack((np.ones_like(X[-1])*3000, np.ones_like(X[-1])*5000)),
color='black', alpha=0.07)
plot.multi_line(X, Y, line_width=2, line_color='orange')
## Save/display.
if show: show(plot)
# plot_raw_blinks("test", raw, show=True)
def plot_heatmaps(info_with_aoi, raw_pos_data, contrast, config):
"""Plot raw data heatmaps with overlaid AoIs.
Parameters
----------
info_with_aoi : instance of `Screen`
Eyetracking acquisition information with AoIs added.
raw_pos_data: array, shape(xdim, ydim)
Raw x,y gaze data.
contrast : array, shape(0,1)
Contrast for histogram plot.
config : int
Specifies the aoi configuration we wish to display.
Returns
-------
fig, ax : plt.figure
Figure and axis of plot.
Notes
-----
Requires matplotlib.
"""
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from matplotlib.patches import Rectangle
## Remove NaNs.
mask = ~np.any(np.isnan(raw_pos_data),axis=1)
x = raw_pos_data[mask,0]
y = raw_pos_data[mask,1]
x_y = np.column_stack([x,y])
## Compute 2D histogram in pixel space.
xedges = np.arange(0,info_with_aoi.xdim+1)
yedges = np.arange(0,info_with_aoi.ydim+1)
H, xedges, yedges = np.histogram2d(x, y,bins=(xedges, yedges))
H = H.T
fig, ax = plt.subplots(1, 1, figsize=(20, 20));
ax.imshow(H, interpolation='bilinear', cmap=cm.gnuplot, clim=(contrast[0], contrast[1]));
ax.imshow(info_with_aoi.indices[:,:,config-1].T, alpha = 0.2, cmap = cm.gray)
ax.set_xticks([]);
ax.set_yticks([]);
return fig, ax
