Add PointCloud spatial distribution #3161
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openmc/stats/multivariate.py
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| psoitions: numpy.ndarray (3xN) | ||
| The points in space to be sampled |
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| 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) |
openmc/stats/multivariate.py
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| return cls(positions, strengths) | ||
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openmc/stats/multivariate.py
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| """ | ||
| coord = {} | ||
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| 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).
openmc/stats/multivariate.py
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| 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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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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While it may have been elegant to add an Thus, I've relied on just reading a list of doubles and packing them into |
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Some small line suggestions here @gonuke. I went ahead and added test that samples the external source distribution on the C++ side and factored out a function in the XML interface for parsing a set of Positions from a flat array of values on a node. Hope that's okay!
Thanks again for this addition.
openmc/stats/multivariate.py
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| if given_positions is None: | ||
| raise ValueError('No positions were provided') |
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I think I'd opt to let the check_iterable_type throw an error here instead.
…rance and number of particles.
Co-authored-by: Patrick Shriwise <pshriwise@gmail.com>
Co-authored-by: Patrick Shriwise <pshriwise@gmail.com>
Co-authored-by: Patrick Shriwise <pshriwise@gmail.com>
Co-authored-by: Patrick Shriwise <pshriwise@gmail.com>
Co-authored-by: Patrick Shriwise <pshriwise@gmail.com>
Co-authored-by: Patrick Shriwise <pshriwise@gmail.com>
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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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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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All looks good to me - thanks @paulromano |
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
SpatialDistributionand can be used anywhere that aSpatialDistributionis valid.Fixes #3159
Checklist