Obsobj update to main/v2.0 #311
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…bility with obs dicts.
Also add logic for caching emission line variances from MLE.
Offloads likelihood computations to NoiseModel objects that are attached to individual Observation instances. Also updates lnprobfn to handle lists of observations, and adds some docstrings and rough tests. fitting ubdates for observation lists; dosctring modernization.
Numerous tweaks to observation generation from old style dicts; Changes to test_eline for new predict() api.
Observation object methods to convert to structures, fits, h5, etc. Better docstrings. New Observation.Lines subclass. Fix import error in sedmodel.
Includes option to try to pickle model params.
…ume FilterSet; require sedpy >= 0.3
Moves the SSPBasis and FastStepBasis to galaxy_basis module. Removes the ssp_basis, dust_basis, and boneyard modules. Removes the get_spectrum method from SSPBasis and subclasses; this is handled by SpecModel Remove various multicomponent hacks.
…ore descriptive fit_mle_elines()
…th noise modeling.
…e polynomial fitting; comment out broken bestfit model saving.
…nstrumental smoothing.
… class for uncorrelated kernels (like jitter).
Treat case of dummy observation that is not any of the recognized kinds; Bump python version requirement.
…t in lnlike_testing
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This is a condensed and updated version of #246 that fixes conflicts with the main branch.
It implements a new Observation class, which takes over responsibility for noise models and likelihood calculations, as well as instrumental smoothing for spectra. The lnprob function can now take an arbitrary list of observation objects.
List of significant changes:
Observationclass withSpectrum,PhotometryandLinessubclasses. These can be generated from or convert to old style dictionaries, as well as structured arrays for output to a number of formats.NoiseModel1Dclassfitting.lnprobfnthat handles an arbitrary list ofObservationobjects.SedModeland derived classes.smoothingmodule; relies on sedpy for smoothingRemaining things to do: