Metadata column column types and datasets#4637
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joshmoore merged 21 commits intoome:metadata52from Jun 8, 2016
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Most methods for dataset loading and parsing were left unimplement. Now a `Dataset:`-style object can be passed to populate_metadata.py and images will be looked up by name. Note: there's a small bug with name lookup that will be corrected separately.
The assumptions for well/imaging naming in a plate or screen differ from those from image naming in a dataset since there's no unique way to reference an image in a dataset like there is well "A1" for example. This commit loosens some of those rules to allow image columns and image name columns to work together in the case of datasets. The assumption is that for population the ID of the image in a dataset won't be known. Instead names of images will be used as a unique identifier. Currently only a warning is issued if the name is not unique.
In general, populate_metadata.py looks to be in line for a refactoring. The number of if-clauses as well as the unhandled cases (like no catch-all for unknown targets in delete) is making this ever harder to work with. All tests passing.
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In order to allow Projects to smartly handle multiple images with the same name (though not in the same dataset), the internals of ValueResolver have been hidden within a ValueWrapper class. ValueResolver chooses once which ValueWrapper to use internally after which the various if/then blocks based on target object are no longer necessary (needs further refactoring). There *are* still if/then blocks basked on column-type. These could use some cleaning but will likely remain to be necessary for multiple-dispatch style handling.
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Merging for IDR-0.0.5 |
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--rebased-to #5218 |
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This PR carries on from work by @emilroz (PR 120) which makes it possible to specify the column types for OMERO.tables when using populate_metadata.py to parse the csv files and adds support for datasets and projects as the target object for a metadata table.