Also cache undefined Rij values #1634
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If we know that the correlaton coefficient is undefined for this particular combination of data sets then we can cache that knowledge and avoid the cost of rediscovering this fact for other symmetry-related combinations of the same data sets. This shouldn't change any results, and will only likely have any significant performance benefit when dealing with many sparse data sets (i.e. where there are many pairs of data sets where it isn't possible to calculate a valid correlation coefficient). Co-authored-by: Daniel Paley <dwpaley@lbl.gov>
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## main #1634 +/- ##
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Coverage 66.63% 66.63%
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Files 616 616
Lines 68950 68950
Branches 9600 9600
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+ Hits 45944 45946 +2
+ Misses 21070 21068 -2
Partials 1936 1936 |
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If we know that the correlaton coefficient is undefined for this particular combination of data sets then we can cache that knowledge and avoid the cost of rediscovering this fact for other symmetry-related combinations of the same data sets. This shouldn't change any results, and will only likely have any significant performance benefit when dealing with many sparse data sets (i.e. where there are many pairs of data sets where it isn't possible to calculate a valid correlation coefficient). Co-authored-by: Daniel Paley <dwpaley@lbl.gov>
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Bugfixes -------- - ``dials.cosym``: Cache cases where Rij is undefined, rather than recalculating each time. This can have significant performance benefits when handling large numbers of sparse data sets. (#1634) - ``dials.cosym``: Fix factor of 2 error when calculating target weights (#1635) - ``dials.cosym``: Fix broken ``engine=scipy`` option (#1636)
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Bugfixes -------- - ``dials.cosym``: Cache cases where Rij is undefined, rather than recalculating each time. This can have significant performance benefits when handling large numbers of sparse data sets. (#1634) - ``dials.cosym``: Fix factor of 2 error when calculating target weights (#1635) - ``dials.cosym``: Fix broken ``engine=scipy`` option (#1636)
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Features -------- - ``dials.cosym``: Significantly faster via improved computation of functional, gradients and curvatures (#1639) - ``dials.integrate``: Added parameter ``valid_foreground_threshold=``, to require a minimum fraction of valid pixels before profile fitting is attempted (#1640) Bugfixes -------- - ``dials.cosym``: Cache cases where Rij is undefined, rather than recalculating each time. This can have significant performance benefits when handling large numbers of sparse data sets. (#1634) - ``dials.cosym``: Fix factor of 2 error when calculating target weights (#1635) - ``dials.cosym``: Fix broken ``engine=scipy`` option (#1636) - ``dials.integrate``: Reject reflections with a high number of invalid pixels, which were being integrated since 3.4.0. This restores better merging statistics, and prevents many reflections being incorrect profiled as zero-intensity. (#1640)
DiamondLightSource-build-server
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Features -------- - ``dials.cosym``: Significantly faster via improved computation of functional, gradients and curvatures (#1639) - ``dials.integrate``: Added parameter ``valid_foreground_threshold=``, to require a minimum fraction of valid pixels before profile fitting is attempted (#1640) Bugfixes -------- - ``dials.cosym``: Cache cases where Rij is undefined, rather than recalculating each time. This can have significant performance benefits when handling large numbers of sparse data sets. (#1634) - ``dials.cosym``: Fix factor of 2 error when calculating target weights (#1635) - ``dials.cosym``: Fix broken ``engine=scipy`` option (#1636) - ``dials.integrate``: Reject reflections with a high number of invalid pixels, which were being integrated since 3.4.0. This restores better merging statistics, and prevents many reflections being incorrect profiled as zero-intensity. (#1640)
DiamondLightSource-build-server
added a commit
that referenced
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Apr 1, 2021
Features -------- - ``dials.cosym``: Significantly faster via improved computation of functional, gradients and curvatures (#1639) - ``dials.integrate``: Added parameter ``valid_foreground_threshold=``, to require a minimum fraction of valid pixels before profile fitting is attempted (#1640) Bugfixes -------- - ``dials.cosym``: Cache cases where Rij is undefined, rather than recalculating each time. This can have significant performance benefits when handling large numbers of sparse data sets. (#1634) - ``dials.cosym``: Fix factor of 2 error when calculating target weights (#1635) - ``dials.cosym``: Fix broken ``engine=scipy`` option (#1636) - ``dials.integrate``: Reject reflections with a high number of invalid pixels, which were being integrated since 3.4.0. This restores better merging statistics, and prevents many reflections being incorrect profiled as zero-intensity. (#1640) - Fix rare crash in symmetry calculations when no resolution limit could be calculated (#1641)
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If we know that the correlaton coefficient is undefined for this particular combination of data sets then we can cache that knowledge and avoid the cost of rediscovering this fact for other symmetry-related combinations of the same data sets.
This shouldn't change any results, and will only likely have any significant performance benefit when dealing with many sparse data sets (i.e. where there are many pairs of data sets where it isn't possible to calculate a valid correlation coefficient).
Co-authored-by: Daniel Paley dwpaley@lbl.gov