Note
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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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Total running time of the script: (0 minutes 8.505 seconds)