codecov[bot]
commented
6 years ago Codecov Report
Merging #715 into master will increase coverage by
0.18%. The diff coverage is94.23%.
@@ Coverage Diff @@
## master #715 +/- ##
==========================================
+ Coverage 81.08% 81.26% +0.18%
==========================================
Files 35 35
Lines 3643 3641 -2
==========================================
+ Hits 2954 2959 +5
+ Misses 689 682 -7| Impacted Files | Coverage Δ | |
|---|---|---|
| src/Synthetic.jl | 68.88% <ø> (ø) |
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| src/ParallelRun.jl | 82.92% <ø> (ø) |
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| src/joint_infer.jl | 73.59% <ø> (ø) |
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| src/deterministic_vi/elbo_args.jl | 100% <ø> (ø) |
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| src/model/image_model.jl | 75% <ø> (ø) |
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| src/model/log_prob.jl | 90.57% <ø> (ø) |
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| src/AccuracyBenchmark.jl | 80.9% <100%> (-0.5%) |
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| src/model/imaged_sources.jl | 100% <100%> (ø) |
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| src/model/psf_model.jl | 100% <100%> (ø) |
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| src/SDSSIO.jl | 93.92% <100%> (+0.29%) |
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| ... and 1 more |
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jeff-regier
This is a step in making the core of Celeste independent of the SDSS data model.
It Makes the
Imagetype parametric in the last attribute (formerly called aRawPSF) which represents the rasterized PSF as a function of position in the image.Imagecan now contain any type ofAbstractPSFMap, which has one job: to return a rasterized PSF model, given a pixel position. This allows for different implementations, such asSDSSPSFMap, orConstantPSFMap(a non-varying PSF), or any other survey's PSF representation, without any of the rest of Celeste knowing the type or the implementation.The alternative to this would be fitting a spatially variable version of Celeste's PSF model (
Vector{PsfComponent}) and storing that inImage. (That would be cleaner in some ways and can of course still be done in the future.)Note: most of the big blocks of changes here are simply moving code around: the SDSS specific PSF has moved to SDSSIO.jl for example.