Add fit flag for Parameter
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Advanced the specs submodule pointer from 95b520a to c5dc877 to incorporate the latest changes from the specs repository.
Introduces an optional 'fit' boolean to the Parameter model and related method, indicating if a parameter should be varied during optimization. Also reorders the '@context' dictionary entries for consistency across multiple classes.
jmrohwer
approved these changes
Sep 22, 2025
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I have added two further commits to handle non-fitted parameters in the ThinLayer itself. Also, the standard errors were not written back to the new EnzymeML document after fitting, which is now fixed. @JR-1991 please review. Tested with a real-life dataset used in last-weeks CRC1333 course. |
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Looks good to me - Merging! |
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This pull request makes improvements to the
pyenzyme/versions/v2.pydata model, primarily by the addition of afitattribute to parameters and the consistent placement of the"schema": "https://schema.org/"entry in context definitions. ThisParameter handling improvements:
fitattribute to theParametermodel to indicate whether the parameter should be varied during optimization. This is now included both in the model definition and when adding parameters viaadd_to_parameters. [1] [2] [3]Submodule update:
specssubmodule to the current main branch of EnzymeML specs, reflecting the latest changes in the external dependency.Related PRs
Since this is a general change to the EnzymeML data model, other libraries have been synced as well. Once this PR is merged, all others will be merged as well:
fitflag toParameterenzymeml-ts#5fitflag toParameterenzymeml-go#1fitflag toParameterenzymeml-rs#10fitflag toParameterEnzymeML.jl#1This change is