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Add PointCloud spatial distribution #3161

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merged 40 commits into from
Nov 13, 2024

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gonuke
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@gonuke gonuke commented Oct 5, 2024

Description

Allows users to define a list of points in space, each with a different relative intensity, to be sampled discretely. This is a valid SpatialDistribution and can be used anywhere that a SpatialDistribution is valid.

Fixes #3159

Checklist

  • I have performed a self-review of my own code
  • I have run clang-format (version 15) on any C++ source files (if applicable)
  • I have followed the style guidelines for Python source files (if applicable)
  • I have made corresponding changes to the documentation (if applicable)
  • I have added tests that prove my fix is effective or that my feature works (if applicable)

@gonuke gonuke marked this pull request as ready for review October 5, 2024 20:08
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Thanks for this snappy PR @gonuke! A useful distribution that we haven't been able to support before!

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Comment on lines 778 to 779
psoitions: numpy.ndarray (3xN)
The points in space to be sampled
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Suggested change
psoitions: numpy.ndarray (3xN)
The points in space to be sampled
positions: numpy.ndarray
The points in space to be sampled with shape (N, 3)

return cls(positions, strengths)



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Suggested change

"""
coord = {}

for axis in ('x','y','z'):
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I'm thinking the XML format of the data as a flat list of points (X1, Y1, Z1, X2, Y2, Z2, ...) would make the import export code simpler, and it isn't more or less readable in an XML format (for my brain anyway).

include/openmc/distribution_spatial.h Outdated Show resolved Hide resolved

for idx, axis in enumerate(('x','y','z')):
subelement = ET.SubElement(element, axis)
subelement.text = ' '.join(str(e) for e in self.positions[idx,:])
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subelement.text = ' '.join(str(e) for e in self.positions[idx,:])
subelement.text = ' '.join(str(e) for e in self.positions[..., idx])

I think?

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@gonuke Thanks for this PR! Out of curiosity, what is the intended application of this feature?

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gonuke commented Oct 10, 2024

We have a user who has an existing approximation of a volumetric source by a high density list of isotropic point sources. They want to use that source for comparison to other simulations.

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gonuke commented Oct 12, 2024

While it may have been elegant to add an istream operator for Position the version I added did not round-trip with the existing ostream operator and it is more convenient in XML to not use the verbose ostream format.

Thus, I've relied on just reading a list of doubles and packing them into Position in the reader.

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I just pushed a couple of small changes, but this looks good to me! @paulromano, you mentioned you'd like to have a look at this as well, so I'll give you a little time to review.

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gonuke commented Nov 13, 2024

Pinging @paulromano to see if this can move forward?

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Thanks @gonuke! I did a bit of refactoring and simplification. I'm good to merge but before I do, let me know if you object to any of my changes.

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gonuke commented Nov 13, 2024

All looks good to me - thanks @paulromano

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Thank you @gonuke!

@paulromano paulromano merged commit 58400cb into openmc-dev:develop Nov 13, 2024
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magnoxemo pushed a commit to magnoxemo/openmc that referenced this pull request Nov 22, 2024
Co-authored-by: Patrick Shriwise <[email protected]>
Co-authored-by: Paul Romano <[email protected]>
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Allow sampling source location from a point cloud with discrete probabilities
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