WIP: build basic toml format #57
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I've added support for julia> paramset = DefaultParameterSet()
DefaultParameterSet()
julia> paramset.M_d
0.02897
julia> paramset.R
8.3144598This means that you can also use julia> (;M_d, R) = paramset
DefaultParameterSet()
julia> M_d
0.02897 |
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May 18, 2022
62: [WIP] pilot parameter refactor r=odunbar a=odunbar ## Purpose of this PR Relating to issues #57 Provides a toml format for other packages to use. Currently see - PR [83](CliMA/Thermodynamics.jl#83) on `Clima/Thermodynamics` - PR [55](CliMA/CloudMicrophysics.jl#55) on `Clima/CloiudMicrophysics` Also we can now write **re-readable** log files ## In this PR - Documentation! See the latest documentor build below. - New wrapper ```ParamDict{FT}```around dictionary read from toml. Currently parametric on one type of all the values, provided when it is built (default is `Float64`). Construction: ```julia create_parameter_struct(override_filepath, default_filepath; dict_type="alias",value_type=Float64) # builds with override and custom default provided create_parameter_struct(override_filepath ; dict_type="alias",value_type=Float64) # builds, overriding the default from CLIMAParameters create_parameter_struct(; dict_type="alias",value_type=Float64) # builds using only default in CLIMAParameters ``` - Automated parameter logging on reading parameter values: (can do multiple parameters at once). At the call of this function, the type is enforced on the return values. ```julia get_parameter_values!(pd::ParamDict, names, component; log_component=true) #logs component in pd get_parameter_values(pd::ParamDict,names) # no logging in pd ``` - writing the re-readable log file in `log_parameter_information(pd::ParamDict,filepath)`. Example parameter tested in `CloudMicrophysics.jl`: ```toml # initial parameter file [molar_mass_water] alias = "molmass_water" value = 0.01801528 type = "float" ``` In this test, a copy of the parameters was created and stored in (1) Thermodynamics, (2) the general CloudMicrophysics, and (3) the specific 1-moment-based Microphysics scheme. Indeed the logfile shows this information below ```toml # log file [molar_mass_water] alias = "molmass_water" value = 0.01801528 type = "float" used_in = ["Thermodynamics", "CloudMicrophysicsParameters", "Microphysics_1M_Parameters"] ``` The `log_parameter_information(pd::ParamDict,filepath; warn_else_error="warn")` will also throw warnings if a parameter is in the override file, but unused in the simulation. This works as parameters from the override file are checked for whether they have gained a "used_in" tag, if not found then an this is logged as a warning or error - From PR #65, reading of array-type parameters - From PR #68, reading and writing for calibration tools ### TODO - still using alias based structs - still based on float, and array-of-float parameters Co-authored-by: odunbar <[email protected]>
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Can we close this one @simonbyrne? |
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Superseded by #62 |
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