Visualizing patterns

The EBSD object has a powerful and versatile plot() method provided by HyperSpy, and its uses are greatly detailed in HyperSpy’s visualisation user guide. This section details example uses specific to EBSD objects.

Note

The Nickel data set used in this section can be downloaded from [Anes2019].

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()

Example of a standard navigator map (right), and the detector (left). This is the standard view when calling s.plot().

However, any BaseSignal object with a two-dimensional 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_image() method, explained in the Virtual backscatter electron imaging section, can be used as a navigator for a scan s:

>>> import hyperspy.api as hs
>>> roi = hs.roi.RectangularROI(left=18, top=20, right=23, bottom=25)
>>> vbse = s.get_virtual_image(roi)
>>> s
<EBSD, title: Pattern_c, dimensions: (200, 149|60, 60)>
>>> vbse
<EBSD, title: Virtual Dark Field, dimensions: (|200, 149)>
>>> s.plot(navigator=vbse)

Navigator map vbse (left) with pixel values corresponding to the sum of the intensities within the rectangular, green aperture (roi) in the pattern (right).

Any image

Images loaded into a Signal2D object can be used as navigators. E.g. a quality metric map, like the orientation similarity obtained from dictionary indexing with EMsoft (see e.g. [Marquardt2017]):

>>> import matplotlib.pyplot as plt
>>> import hyperspy.api as hs
>>> osm = plt.imread('path/to/orientation_similarity_map.png'))
>>> s_osm = hs.signals.Signal2D(osm)
>>> s_osm
<Signal2D, title: , dimensions: (|2140, 1603)>
>>> s_osm = s_osm.rebin(new_shape=s.axes_manager.navigation_shape)
>>> s_osm
<Signal2D, title: , dimensions: (|200, 149)>
>>> s.plot(navigator=s_osm)

A quality metric map s_osm, in this case an orientation similarity map from dictionary indexing with EMsoft, as navigator map.

Using colour images, e.g. an orientation om or phase map, is a bit more involved:

>>> om = plt.imread('/path/to/orientation_map.jpg')
>>> om_scaled = ske.rescale_intensity(om, out_range=np.uint8)
>>> s_om = hs.signals.Signal2D(om_scaled)
>>> s_om
<Signal2D, title: , dimensions: (149|3, 200)>
>>> s_om = s_om.transpose(signal_axes=1)
>>> print(s_om, s_om.data.dtype)
<Signal1D, title: , dimensions: (200, 149|3)> uint8
>>> s_om.change_dtype('rgb8')
>>> s_om
<Signal2D, title: , dimensions: (|200, 149)> [('R', 'u1'), ('G', 'u1'), ('B', 'u1')]
>>> s.plot(navigator=s_om)

An orientation map s_om as a navigator map.

Plot multiple scans

HyperSpy provides the function plot_signals() to plot multiple signals with the same navigator, as explained in the HyperSpy user guide. This enables e.g. plotting of experimental and simulated patterns side by side as a visual inspection of the indexing results:

>>> import hyperspy.api as hs
>>> import h5py
>>> with h5py.File('/path/to/simulated_patterns/sim.h5', mode='r') as f:
        patterns = f['EMData/EBSD/EBSDPatterns'][()]
>>> s_sim = kp.signals.EBSD(patterns.reshape(s.data.shape))
>>> hs.plot.plot_signals([s, s_sim], navigator=s_om)

Plotting of experimental and simulated patterns side by side for visual inspection, using an orientation map as navigator.