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feat!: add Tag parameter to SpectralData
This enormously simplifies derived datatypes, and removed the API forwarding macro that was unreliable to maintain. Follows from the Tagging idea introduced with BinnedData, and allows derived types to be implemented more easily. Updated OGIP, XMM and NuSTAR datatypes to use this tagging system instead of adding new types. Modified test cases to sync with changes.
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,87 +1,24 @@ | ||
| struct NuSTAR <: AbstractInstrument end | ||
| struct XmmEPIC <: AbstractInstrument end | ||
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| struct NuStarData{T,H} <: AbstractDataset | ||
| data::SpectralData{T} | ||
| paths::SpectralDataPaths | ||
| observation_id::String | ||
| exposure_id::String | ||
| object::String | ||
| header::H | ||
| end | ||
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| NuStarData(spec_path; rmf_matrix_index = 3, rmf_energy_index = 2, kwargs...) = NuStarData( | ||
| load_ogip_dataset( | ||
| function NuStarData(spec_path; rmf_matrix_index = 3, rmf_energy_index = 2, kwargs...) | ||
| OGIPDataset( | ||
| spec_path; | ||
| rmf_matrix_index = rmf_matrix_index, | ||
| tag = NuSTAR(), | ||
| rmf_energy_index = rmf_energy_index, | ||
| rmf_matrix_index = rmf_matrix_index, | ||
| kwargs..., | ||
| )..., | ||
| ) | ||
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| make_label(data::NuStarData) = data.observation_id | ||
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| @_forward_SpectralData_api NuStarData.data | ||
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| function Base.show(io::IO, @nospecialize(data::NuStarData{T})) where {T} | ||
| print(io, "NuStarData[obs_id=$(data.observation_id)]") | ||
| end | ||
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| function _printinfo(io, data::NuStarData{T}) where {T} | ||
| descr = """NuStarData: | ||
| . Object : $(data.object) | ||
| . Observation ID : $(data.observation_id) | ||
| . Exposure ID : $(data.exposure_id) | ||
| """ | ||
| print(io, descr) | ||
| _printinfo(io, data.data) | ||
| ) | ||
| end | ||
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| abstract type AbstractXmmNewtonDevice end | ||
| struct XmmEPIC <: AbstractXmmNewtonDevice end | ||
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| struct XmmData{T,H,D} <: AbstractDataset | ||
| device::D | ||
| data::SpectralData{T} | ||
| paths::SpectralDataPaths | ||
| observation_id::String | ||
| exposure_id::String | ||
| object::String | ||
| header::H | ||
| end | ||
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| XmmData( | ||
| device::AbstractXmmNewtonDevice, | ||
| spec_path; | ||
| rmf_matrix_index = 2, | ||
| rmf_energy_index = 3, | ||
| kwargs..., | ||
| ) = XmmData( | ||
| device, | ||
| load_ogip_dataset( | ||
| function XmmData(spec_path; rmf_matrix_index = 2, rmf_energy_index = 3, kwargs...) | ||
| OGIPDataset( | ||
| spec_path; | ||
| rmf_matrix_index = rmf_matrix_index, | ||
| tag = XmmEPIC(), | ||
| rmf_energy_index = rmf_energy_index, | ||
| rmf_matrix_index = rmf_matrix_index, | ||
| kwargs..., | ||
| )..., | ||
| ) | ||
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| make_label(data::XmmData) = data.observation_id | ||
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| @_forward_SpectralData_api XmmData.data | ||
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| function Base.show(io::IO, @nospecialize(data::XmmData{T})) where {T} | ||
| print(io, "XmmData[dev=$(data.device),obs_id=$(data.observation_id)]") | ||
| ) | ||
| end | ||
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| function _printinfo(io, data::XmmData{T}) where {T} | ||
| descr = """XmmData for $(Base.typename(typeof(data.device)).name): | ||
| . Object : $(data.object) | ||
| . Observation ID : $(data.observation_id) | ||
| . Exposure ID : $(data.exposure_id) | ||
| """ | ||
| print(io, descr) | ||
| _printinfo(io, data.data) | ||
| end | ||
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| export NuStarData, XmmData, XmmEPIC |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,21 +1,12 @@ | ||
| using Test, SpectralFitting | ||
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| # path to the data directory | ||
| data1 = SpectralFitting.XmmData( | ||
| SpectralFitting.XmmEPIC(), | ||
| joinpath(testdir, "xmm/pn_spec_grp.fits"), | ||
| ) | ||
| data1 = SpectralFitting.XmmData(joinpath(testdir, "xmm/pn_spec_grp.fits")) | ||
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| # smoke test | ||
| model = GaussianLine() + PowerLaw(a = FitParam(0.2)) | ||
| sim = simulate( | ||
| model, | ||
| data1.data.response, | ||
| data1.data.ancillary; | ||
| seed = 8, | ||
| exposure_time = 1e1, | ||
| ) | ||
| sim = simulate(model, data1.response, data1.ancillary; seed = 8, exposure_time = 1e1) | ||
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| # TODO: add a fit. can't do it at the moment as the simulated datasets don't | ||
| # support masking the model domain, so we have singular values at high energies |