Comments (5)
Yes, will have to add more versatile creation of RData instances for other purposes anyways.
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I don't think there are any simple conversion functions as a ReturnDataView
is a relatively complex class with caching ane attributes that are C pointers. Wouldn't it be sufficient to create a simple dataclass (instead of the dict) that mocks ReturnDataView
attributes?
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I don't think there are any simple conversion functions as a
ReturnDataView
is a relatively complex class with caching ane attributes that are C pointers. Wouldn't it be sufficient to create a simple dataclass (instead of the dict) that mocksReturnDataView
attributes?
Yes that is essentially what was done before. I will do a simple AttributeDict then. Works but won't be very nice, as the expected data type is ignored.
from pypesto.
I don't think there are any simple conversion functions as a
ReturnDataView
is a relatively complex class with caching ane attributes that are C pointers. Wouldn't it be sufficient to create a simple dataclass (instead of the dict) that mocksReturnDataView
attributes?Yes that is essentially what was done before. I will do a simple AttributeDict then. Works but won't be very nice, as the expected data type is ignored.
Agreed. But it also shouldn't be too difficult though to simply insert those columns into a copy of the measurement_df, right?
from pypesto.
I don't think there are any simple conversion functions as a
ReturnDataView
is a relatively complex class with caching ane attributes that are C pointers. Wouldn't it be sufficient to create a simple dataclass (instead of the dict) that mocksReturnDataView
attributes?Yes that is essentially what was done before. I will do a simple AttributeDict then. Works but won't be very nice, as the expected data type is ignored.
Agreed. But it also shouldn't be too difficult though to simply insert those columns into a copy of the measurement_df, right?
Should be possible, but implementing that functionality here could lead to issues, as the logic has been moved to AMICI. Long-term, either pyPESTO should keep/construct actual AMICI RData, or AMICI's function be made more generic. But fine for the moment I think.
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Related Issues (20)
- `Ensemble.from_optimization_{history,endpoints}` assumes that `OptimizerResult.id` is always convertible to `int`
- Relative: implement log-normal distribution
- ImportError: cannot import name 'gaussian' from 'scipy.signal' HOT 5
- What's the purpose of `Ensemble.predictions`? HOT 1
- General Discussion regarding Ensemble HOT 7
- Handling of simulation failures in AmiciPredictor
- Frequent timeouts of RTD builds HOT 3
- Waterfall plot error: `order_by_id` and `start_indices` do not work together
- Optimization with conditions specific for observables fails HOT 4
- Frequent timeouts for `mac (3.11)` workflow runs HOT 3
- Check pypesto/sample/geweke_test.py calculate_zscore/spectrum0/spectrum
- Frequent readthedocs timeout HOT 1
- `pyjulia` is no longer maintained
- Roadrunner petab test case 0018 fails on Mac HOT 3
- Lazy loading of optimization results from HDF5
- Aggregated Objective does not return expected outputs using `return_dict` HOT 7
- NegLogParameterPriors evaluates prior density also on fixed parameters HOT 6
- AmiciObjective: For sensi_orders>0, check that sensitivities wrt all relevant parameters are computed
- PetabImporter does not respect estimate=0 HOT 3
- KeyError for parameter with amici prefix HOT 2
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