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Updated Changelog.
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README.md

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@@ -62,12 +62,14 @@ inside of your `.bashrc` or `.zshrc` file. Finally,
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$ source ~/.zshrc
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To check that you have properly added the scripts, you can try in your system shell
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To check that you have properly added the scripts (and check that you installed the correct version), you can try in your system shell
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$ JudithInitialize.jl --test
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$ JudithInitialize.jl --version
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Your JudithExcalibur scripts are successfully linked.
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You are running JudithExcalibur 0.1.1
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Exiting
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Second, most of the scripts and IO routines require Python and several Python packages. Please install the following packages via your own package manager or a distribution like anaconda:
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* numpy

docs/changelog.md

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# Version 0.1.1
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Now includes a cookbook example for AK Sco.
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## Model specification
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New implemenation of models. Created the `AbstractParameters` type, with subtypes `ParametersStandard` and `ParametersTruncated`. Added new parameters type
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New implementation of models through parameter types in `model.jl`. Instead of separate model files for each new parameterization, which duplicated a lot of code and made things difficult to maintain, we are now collating all model types in `model.jl` by their parameters. We have created the `AbstractParameters` umbrella type, with subtypes `ParametersStandard`, `ParametersTruncated`, and `ParametersCavity`. Previous model specification routines like `Sigma(r::Float64, pars::Parameters)` (surface density) are now have overloaded methods for different models based upon these parameter types
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Sigma(r::Float64, pars::ParametersStandard)
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Sigma(r::Float64, pars::ParametersTruncated)
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Sigma(r::Float64, pars::ParametersCavity)
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And routines that are general to all models (e.g. velocity specification) are denoted by
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velocity{T}(r::T, pars::AbstractParameters)
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Note that model types `cavity` and `truncated` are still experimental and likely to change.
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Updated the `config.yaml` format to include new fields like `model: standard`. Changed the items in the `parameters` dictionary to be a single Float64 number, not an array of `[starting, jump]` like it was previously. An example is `assets/config.yaml`.
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To go along with this change, I have updated the automatic generation of the `config.yaml` file to include new fields like `model: standard`. Within the `config.yaml` file, items in the `parameters` dictionary are now simply a single Float64 number, not an array of `[starting, jump]` like it was previously.
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`model.jl` now handles the implementation of priors, that dispatch off of the parameter types. This greatly streamlines the function `fprob` in `venus.jl`.
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## One-off model synthesis and plotting
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Simplified synthesizing and plotting of models. Split `plot_model.jl` into `synthesize_model.jl` and separately `plot_chmaps.jl`.
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I've simplified synthesizing and plotting of models. What was previously `plot_model.jl` is now split into `synthesize_model.jl` and `plot_chmaps.jl`.
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Added new `plot_moments.jl` script which plots zeroth-moment.
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Added new `plot_moments.jl` script which plots the zeroth-moment image. Soon it will plot first moment as well.
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Created `InitializeWalkers.ipynb` that is copied to new directory to help specify walker starting positions.
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## MCMC Sampling
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Streamlined various model implementations into the `venus.jl` code.
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The specification of parameter types allowed me to greatly simplify the MCMC sampling code into a single script, `venus.jl`. I have moved previous sampling scripts to the `attic/` directory.
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`model.jl` now handles the implementation of priors. This greatly streamlines the function `fprob` in `venus.jl`.
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Created `InitializeWalkers.ipynb` that is copied to new directory to help specify walker starting positions. The user edits this with a Jupyter/IPython notebook.
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`plot_walkers.py` now includes ability to determine highest density interval for quoting credible intervals.
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## Cookbook
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We now have a [cookbook example](docs/cookbook.md) for AK Sco, check it out to get started!
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`plot_walkers.py` now includes ability to determine highest density interval for quoting credible intervals and should automatically label the parameters after reading from `config.yaml`.
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# Version 0.1.0
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Initial commit.
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Initial commit on the new versioning roadmap.

scripts/JudithInitialize.jl

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s = ArgParseSettings(description="Initialize a new project directory with the appropriate files. Can also be used to update RADMC-3D input files after making changes to config.yaml")
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@add_arg_table s begin
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"--test"
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help = "Print a test message to see you linked things correctly"
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"--version"
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help = "Print a the version number and exit."
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action = :store_true
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"--new-project"
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help = "Copy a stock configuration file to this directory. Can be 'standard', 'truncated', 'cavity'"
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assets_dir = Pkg.dir("JudithExcalibur") * "/assets/"
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# This is just for new users to test that the package is successfully installed.
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if parsed_args["test"]
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println("Your JudithExcalibur scripts are successfully linked.")
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println("Exiting")
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quit()
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end
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# The user is going to start modeling a new disk, so copy in the new configuration file.
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if parsed_args["new-project"] != "no"
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using JudithExcalibur.constants
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using JudithExcalibur.model
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# This is just for new users to test that the package is successfully installed.
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if parsed_args["version"]
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println("Your JudithExcalibur scripts are successfully linked.")
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println("You are running JudithExcalibur $JUDITHEXCALIBUR_VERSION")
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println("Exiting")
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quit()
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end
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# Create an output directory that will be useful for the results.
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out_base = config["out_base"]
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if !ispath(out_base)

src/constants.jl

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module constants
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export M_sun, M_earth, AU, pc, G, kB, amu, c_ang, cc, c_kms, mu_gas, m_H, m_CO, m_12CO, m_13CO, m_C18O, number_densities, molnames, arcsec, deg, fftspace, MCO, lam0_12CO, lam0_13CO, lam0_C18O, lam0s, nyquist_factor, r_out_factor, Av_sigmaH
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export JUDITHEXCALIBUR_VERSION
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JUDITHEXCALIBUR_VERSION = v"0.1.1"
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# Conversion from astronomical units to CGS units
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M_sun = 1.99e33 # [g]

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