ROI Insets

ROI’s can be powerful tools to help visualize data. In this case we will define ROI’s in hyperspy, sum the data within the ROI, and then plot the sum as a signal. Using the matplotlib.figure.SubFigure class we can create a custom layout to visualize and interact with the data.

Note

Plotting data with subfigures is slower than using separates figures.

We can connect these ROI’s using the hyperspy.api.interactive() function which allows us to move the ROI’s and see the sum of the underlying data.

import matplotlib.pyplot as plt
import hyperspy.api as hs
import numpy as np

rng = np.random.default_rng()

fig = plt.figure(figsize=(5, 3))
gs = fig.add_gridspec(6, 10)
sub1 = fig.add_subfigure(gs[0:6, 0:6])
sub2 = fig.add_subfigure(gs[0:2, 6:8])
sub3 = fig.add_subfigure(gs[2:4, 7:9])
sub4 = fig.add_subfigure(gs[4:6, 6:8])


s = hs.signals.Signal2D(rng.random((10, 10, 30, 30)))
r1 = hs.roi.RectangularROI(1, 1, 3, 3)
r2 = hs.roi.RectangularROI(4, 4, 6, 6)
r3 = hs.roi.RectangularROI(3, 7, 5, 9)

navigator = s.sum(axis=(2, 3)).T  # create a navigator signal
navigator.plot(fig=sub1, colorbar=False, axes_off=True, title="", plot_indices=False)


s2 = r1.interactive(s, navigation_signal=navigator, color="red")
s3 = r2.interactive(s, navigation_signal=navigator, color="g")
s4 = r3.interactive(s, navigation_signal=navigator, color="y")

s2_int = s2.sum()
s3_int = s3.sum()
s4_int = s4.sum()

s2_int.plot(fig=sub2, colorbar=False, axes_off=True, title="", plot_indices=False)
s3_int.plot(fig=sub3, colorbar=False, axes_off=True, title="", plot_indices=False)
s4_int.plot(fig=sub4, colorbar=False, axes_off=True, title="", plot_indices=False)

# Connect ROIS
for s, s_int, roi in zip([s2, s3, s4], [s2_int, s3_int, s4_int],[r1,r2,r3]):
    hs.interactive(
        s.sum,
        event=roi.events.changed,
        recompute_out_event=None,
        out=s_int,
    )

# Add Borders to the match the color of the ROI

for signal,color, label  in zip([s2_int, s3_int, s4_int], ["r", "g", "y"], ["b.", "c.", "d."]):
    edge =  hs.plot.markers.Squares(
    offset_transform="axes",
    offsets=(0.5, 0.5),
    units="width",
    widths=1,
    color=color,
    linewidth=5,
    facecolor="none",
    )

    signal.add_marker(edge)

    label = hs.plot.markers.Texts(
    texts=(label,), offsets=[[0.85, 0.85]], offset_transform="axes", sizes=2, color="w"
    )
    signal.add_marker(label)

# Label the big plot

label = hs.plot.markers.Texts(
    texts=("a.",), offsets=[[0.9, 0.9]], offset_transform="axes", sizes=10, color="w"
    )
navigator.add_marker(label)