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Visualizing patterns

The EBSD and EBSDMasterPattern signals have a powerful and versatile plot() method provided by HyperSpy. Its uses are greatly detailed in HyperSpy’s visualisation user guide. This section details example uses specific to EBSD and EBSDMasterPattern signals.

Let’s import the necessary libraries and a Nickel EBSD test data set [Ånes et al., 2019]

# Exchange inline for notebook or qt5 (from pyqt) for interactive plotting
%matplotlib inline

import matplotlib.pyplot as plt
import numpy as np
import pyvista
import skimage.exposure as ske
import skimage.transform as skt

import hyperspy.api as hs
import kikuchipy as kp
from orix import io, plot, quaternion, vector


# See https://docs.pyvista.org/user-guide/jupyter/index.html
pyvista.set_jupyter_backend("panel")

/tmp/ipykernel_7683/2126874160.py:16: PyVistaDeprecationWarning: `panel` backend is deprecated and is planned for future removal.
  pyvista.set_jupyter_backend("panel")

# Use kp.load("data.h5") to load your own data
s = kp.data.nickel_ebsd_large(allow_download=True)  # External download
s

<EBSD, title: patterns Scan 1, dimensions: (75, 55|60, 60)>

Navigate in custom map

Correlating results from e.g. crystal and phase structure determination, i.e. indexing, with experimental patterns can inform their interpretation. When calling plot() without any input parameters, the navigator map is a grey scale image with pixel values corresponding to the sum of all detector intensities within that pattern

s.plot()

The upper panel shows the navigation axes, in this case 2D, with the current beam position in the upper left corner shown as a red square the size of one pixel. This square can be made larger/smaller with +/-. The square can be moved either by the keyboard arrows or the mouse. The lower panel shows the image on the detector in the current beam position.

Any BaseSignal signal with a 2D signal_shape corresponding to the scan navigation_shape can be passed in to the navgiator parameter in plot(), including a virtual image showing diffraction contrast, any quality metric map, or an orientation map or a phase map.

Virtual image

A virtual backscatter electron (VBSE) image created from any detector region of interest with the get_virtual_bse_intensity() method or get_rgb_image() explained in the virtual backscatter electron imaging tutorial, can be used as a navigator for a scan s

vbse_imager = kp.imaging.VirtualBSEImager(s)
print(vbse_imager)
print(vbse_imager.grid_shape)

VirtualBSEImager for <EBSD, title: patterns Scan 1, dimensions: (75, 55|60, 60)>
(5, 5)

vbse_rgb = vbse_imager.get_rgb_image(r=(3, 1), b=(3, 2), g=(3, 3))
vbse_rgb

<VirtualBSEImage, title: , dimensions: (|75, 55)>

s.plot(navigator=vbse_rgb, cmap="viridis")

Any image

Images made into a Signal2D can be used as navigators, like a quality metric map like the image quality map calculated using get_image_quality()

s.remove_static_background()
s.remove_dynamic_background()

[########################################] | 100% Completed | 205.97 ms
[########################################] | 100% Completed | 922.45 ms

iq = s.get_image_quality()
s_iq = hs.signals.Signal2D(iq)
s.plot(navigator=s_iq)

[########################################] | 100% Completed | 406.78 ms

We can obtain an RGB signal from an RGB image using get_rgb_navigator(). Let’s load an orientation map from dictionary indexing in the pattern matching tutorial

rgb_z = plt.imread(
    "../_static/image/visualizing_patterns/ni_large_rgb_z.png"
)
rgb_z = rgb_z[..., :3]  # Drop the alpha channel
s_rgb_z = kp.draw.get_rgb_navigator(rgb_z)

s.plot(navigator=s_rgb_z, colorbar=False)

Plot multiple signals

HyperSpy provides the function plot_signals() to plot multiple signals with the same navigator, as explained in their documentation. This enables e.g. plotting of experimental and best matching simulated patterns side-by-side as a visual inspection of indexing results. See the pattern matching tutorial for a demonstration.

Plot master patterns

EBSDMasterPattern signals can be navigated along their energy axis and/or their northern/southern hemisphere. Let’s reload the Nickel master pattern used in the previous section, but this time in the stereographic projection.

# Only a single energy, 20 keV
mp_stereo = kp.data.nickel_ebsd_master_pattern_small(
    projection="stereographic", hemisphere="both"
)
print(mp_stereo.axes_manager)

<Axes manager, axes: (2|401, 401)>
            Name |   size |  index |  offset |   scale |  units
================ | ====== | ====== | ======= | ======= | ======
      hemisphere |      2 |      0 |       0 |       1 |
---------------- | ------ | ------ | ------- | ------- | ------
           width |    401 |      0 |  -2e+02 |       1 |     px
          height |    401 |      0 |  -2e+02 |       1 |     px

As can be seen from the axes manager, the master pattern has two navigation axes, the northern and southern hemispheres, thus, when plotting, we get a navigation slider

mp_stereo.plot()

We can plot the master pattern on the sphere, provided it is in the stereographic projection and that both hemispheres are loaded if it is non-centrosymmetric, using EBSDMasterPattern.plot_spherical(). The initial orientation of the sphere corresponds to the orientation of the stereographic and Lambert projections.

# Interactive!
mp_stereo.plot_spherical(style="points")