Rework data handling#15
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- Add species type flags to get_species_from_enzymeml() util function to allow filtering for specific types of species. - Remove unnecessary display of proteins in PeakAssigner and PeakRangeAssigner using the new species type flags.
- Add save_data_model() method to serialise the NMRpy data model. - Change handling of data arrays: They are now saved as numpy.ndarrays in each Fid object and only copied as lists into the data model upon serialisation.
- Resolve Pydantic serialisation issues (complex → string conversion). - Optimise processing loops for faster execution and lower memory usage.
torogi94
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Nov 11, 2025
* Update EnzymeML species handling - Add species type flags to get_species_from_enzymeml() util function to allow filtering for specific types of species. - Remove unnecessary display of proteins in PeakAssigner and PeakRangeAssigner using the new species type flags. * Add flags for keeping data models upon saving * Change data array handling of NMRpy data model - Add save_data_model() method to serialise the NMRpy data model. - Change handling of data arrays: They are now saved as numpy.ndarrays in each Fid object and only copied as lists into the data model upon serialisation. * Update data_objects.py - Resolve Pydantic serialisation issues (complex → string conversion). - Optimise processing loops for faster execution and lower memory usage. * Change keep_data_model flag to False
torogi94
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Nov 13, 2025
* Update EnzymeML species handling - Add species type flags to get_species_from_enzymeml() util function to allow filtering for specific types of species. - Remove unnecessary display of proteins in PeakAssigner and PeakRangeAssigner using the new species type flags. * Add flags for keeping data models upon saving * Change data array handling of NMRpy data model - Add save_data_model() method to serialise the NMRpy data model. - Change handling of data arrays: They are now saved as numpy.ndarrays in each Fid object and only copied as lists into the data model upon serialisation. * Update data_objects.py - Resolve Pydantic serialisation issues (complex → string conversion). - Optimise processing loops for faster execution and lower memory usage. * Change keep_data_model flag to False
torogi94
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Mar 14, 2026
* Update EnzymeML species handling - Add species type flags to get_species_from_enzymeml() util function to allow filtering for specific types of species. - Remove unnecessary display of proteins in PeakAssigner and PeakRangeAssigner using the new species type flags. * Add flags for keeping data models upon saving * Change data array handling of NMRpy data model - Add save_data_model() method to serialise the NMRpy data model. - Change handling of data arrays: They are now saved as numpy.ndarrays in each Fid object and only copied as lists into the data model upon serialisation. * Update data_objects.py - Resolve Pydantic serialisation issues (complex → string conversion). - Optimise processing loops for faster execution and lower memory usage. * Change keep_data_model flag to False
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PeakAssignerorPeakRangeAssigner, proteins are now excluded from the list of selectable species. Addedproteins=True,complexes=True, andsmall_molecules=Trueflags to theget_species_from_enzymeml()function to allow for more granular control over which species are pulled from EnzymeML.keep_data_model=Falseandkeep_enzymeml=Trueflags tosave_to_file()method to allow for removal of possibly storage-intensive data models.save_data_model()method to save on memory size and computation time.