Comments (3)
I'd be happy to accept it, as long as it's understood to be a contributed level of support. I do have a pi or two I can test on, but I don't get them out very often. Also I'd prefer not to make a 1.3.3 or whatever's next just to support it, so it would be nice if the patch could be used for piwheels until a new version gets released for another reason.
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I'd be happy to accept it, as long as it's understood to be a contributed level of support.
Yup, wouldn't expect anything else.
Also I'd prefer not to make a 1.3.3 or whatever's next just to support it, so it would be nice if the patch could be used for piwheels until a new version gets released for another reason.
SGTM. I can see if they can manually upload my wheels that work or if we can figure out how they can build with exporting LDFLAGS
.
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ping @henryiii if you have time to review in the next week.
from boost-histogram.
Related Issues (20)
- [BUG]: Scaling a weighted histogram does not appropriately scale the variance HOT 6
- [FEAT] Add operators (mult/div/sub) for (weighted) histograms/accumulators HOT 6
- [BUG] np.cumsum fails on views with non-default storage type
- [BUG] Failure to conver awkward Masked array to numpy HOT 3
- [BUG] Indexing along two axes with list and single index raises RuntimeError
- [DOCS] add documentation for Nox
- [DOCS] change all the code directives to code-block
- [BUG] Investigate providing a better error message if sample= is missing
- [FEAT] Scaling a slice of a histogram
- [BUG] Cannot get index of huge numbers in IntCategory HOT 1
- [BUG] Issues with copying in child classes of weighted Histogram
- [FEAT] in multidimensional histograms allow the binning to vary along an axis
- Inconsistent filling of values on bin edges [BUG] HOT 1
- Pickling a histogram creates an extra copy of the array in memory HOT 1
- [BUG] Filling Integer Axis with doubles is buggy
- Version 1.4.0 and 1.5.0
- *Category axes do not support disabling overflow
- [BUG] Filling with unsigned ints in IntCategory axis raises TypeError HOT 2
- Histogram with WeightedMean storage returns wrong sum_of_weights_squared HOT 4
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