Operations on vectors

This example shows how to perform some basic operations slicing and selecting vectors. This is designed to be very flexible and powerful. Many operations such as slicing with a boolean array are supported.

Additionally, lazy operations are supported and can be chained together. These are often faster than their non-lazy counterparts as dask very effectively prunes the computation graph.

import pyxem as pxm
import hyperspy.api as hs

hs.set_log_level("ERROR")

s = pxm.data.tilt_boundary_data()
temp = s.template_match_disk(disk_r=5, subtract_min=False)

vectors = s.get_diffraction_vectors(threshold_abs=0.4, min_distance=5)

# Plotting all the vectors

s.plot()
all_vectors = vectors.to_markers(color="red", sizes=10, alpha=0.5)
s.add_marker(all_vectors)

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slic_vectors = (vectors.ivec[:, vectors.ivec[0] < 10]).to_markers(
    color="green", sizes=5, alpha=0.5
)

s.plot()
s.add_marker([all_vectors, slic_vectors])

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slic_vectors = (
    vectors.ivec[:, (vectors.ivec[0] > 0) * (vectors.ivec[0] < 10)]
).to_markers(color="w", sizes=5, alpha=0.5)
s.plot()
s.add_marker([all_vectors, slic_vectors])

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vect_magnitudes = (vectors.ivec[0] ** 2 + vectors.ivec[1] ** 2) ** 0.5
slic_vectors = vectors.ivec[:, vect_magnitudes < 20].to_markers(
    color="w", sizes=5, alpha=0.5
)
s.plot()
s.add_marker([all_vectors, slic_vectors])
s.add_marker([all_vectors, slic_vectors])

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slic_vectors = (vectors.ivec[:, vectors.ivec["intensity"] < 0.5]).to_markers(
    color="w", sizes=5, alpha=0.5
)
s.plot()
s.add_marker([all_vectors, slic_vectors])
s.add_marker([all_vectors, slic_vectors])

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