API reference

DQuality provides the following funtionalities:

• “PV”: Before data collection start, verify that the experiment setup PVs, i.e. all required setup data, are valid and their values are within a predefined range.
• “Hdf”: verify the correctness of the data and meta-data structure in an hdf5 file.
• “Hdf Dependencies”: verify dependencies between the data and meta-data structure in an hdf5 file.
• “Data”: verify the quality of the data after data is collected in a file. A set of QC functions is provided to assess the image quality against different criteria (mean, dynamic range, structural similarity, multi-scale structural similarity, visual information fidelity, most apparent distortion, etc.) [C4]. The resulting “limit”, related to the quantitive QC functions, defines whether the data is of good or poor quality. The limit values, at first, are set by the research/tests with trial data sets. The QC function “limit” range will eventually be learned by implementing a learning mechanism. Any calculated “result” quality parameter is stored, in the case of hdf format, in the file itself with a corresponding tag. If the data file format supports only raw data (no meta-data), the quality parameter results are stored in a separate file with a name corresponding to the data file.
• “Monitor”, “Monitor_polling”: monitor the active data collection directory and run “Data” on each new file.
• “Accumulator”: monitor the active data collection directory where each new file is part of the same data set.
• “Realtime”: verifies the quality of the active EPICS Channel Access data in a real time.
• “Check”: provides a wrapper to “PV”, “Hdf”, “Hdf Dependencies”, “Data”, “Monitor”, and “Accumulator”.
• “realtime.Check”: provides a wrapper to “Realtime”.

DQuality Modules:

• dquality.realtime.real_time
• dquality.realtime.check

• dquality.accumulator
• dquality.check
• dquality.data
• dquality.hdf
• dquality.hdf_dependency
• dquality.monitor
• dquality.pv