Publication date
November 2020
DOIAbstract
Minor fix in (again) gvar.dataset.avg_data to improve speed for large problems and to work around a bug in a scipy routine when covariance matrices have more than 2**31 elements
Minor fix in (again) gvar.dataset.avg_data to improve speed for large problems and to work around a bug in a scipy routine when covariance matrices have more than 2**31 elements
Fixes bugs in gvar.load and gvar.dump caused by (sort of) recent security upgrades to pyYAML
Another minor bug release. Fixes bug in evalcov_blocks and incompatibility with most recent numpy
Improves heuristics and documentation for gvar.dataset.svd_diagnosis. Updates gvar.svd including new...
More efficient handling of large sparse covariance matrices in gvar.svd (see gvar.evalcov_blocks())....
This release fixes lingering problems with gvar.dataset.avg_data(dataset) when dataset is a dictiona...
Significant rewrite of gvar.evalcov_blocks(g), making it much faster for large, dense covariance mat...
Small bug fixes, including one that would cause module gvar to complain about non-symmetric covarian...
Minor bug fix in correlate that was causing compilation problems on some machines
Minor fixes to avoid crashes in gvar.powerseries and when pickling objects of type gvar.GVar
Fixes issue with str(GVar) that was dropping significant digits in the mean when the standard deviat...
More tuning of gvar.evalcov, for better performance on dense matrices of size 15x15 or larger. Also...
Bug fixes including mismatched integer size problem that affects some Windows installations
Bug fix for gvar.gvar to remove problems caused when a GVar had exactly 0 standard deviation. Minor ...
Small update responding to a feature request: gvar.dataset.avg_data(dset) no longer discards data wh...
Very minor update: bug fix to avoid crashing gvar.evalcorr; json support from gvar.dump, gvar.load, ...
Fixes bugs in gvar.load and gvar.dump caused by (sort of) recent security upgrades to pyYAML
Another minor bug release. Fixes bug in evalcov_blocks and incompatibility with most recent numpy
Improves heuristics and documentation for gvar.dataset.svd_diagnosis. Updates gvar.svd including new...
More efficient handling of large sparse covariance matrices in gvar.svd (see gvar.evalcov_blocks())....
This release fixes lingering problems with gvar.dataset.avg_data(dataset) when dataset is a dictiona...
Significant rewrite of gvar.evalcov_blocks(g), making it much faster for large, dense covariance mat...
Small bug fixes, including one that would cause module gvar to complain about non-symmetric covarian...
Minor bug fix in correlate that was causing compilation problems on some machines
Minor fixes to avoid crashes in gvar.powerseries and when pickling objects of type gvar.GVar
Fixes issue with str(GVar) that was dropping significant digits in the mean when the standard deviat...
More tuning of gvar.evalcov, for better performance on dense matrices of size 15x15 or larger. Also...
Bug fixes including mismatched integer size problem that affects some Windows installations
Bug fix for gvar.gvar to remove problems caused when a GVar had exactly 0 standard deviation. Minor ...
Small update responding to a feature request: gvar.dataset.avg_data(dset) no longer discards data wh...
Very minor update: bug fix to avoid crashing gvar.evalcorr; json support from gvar.dump, gvar.load, ...
Fixes bugs in gvar.load and gvar.dump caused by (sort of) recent security upgrades to pyYAML
Another minor bug release. Fixes bug in evalcov_blocks and incompatibility with most recent numpy
Improves heuristics and documentation for gvar.dataset.svd_diagnosis. Updates gvar.svd including new...
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