Add full profiles for Generomak plasma

[vsnever]

This PR solves #372 and contains the following changes in generomak/plasma/plasma.py:

• Adds the function get_full_profiles(), which blends core and edge profiles to form the full 2D profiles using the linear mask function, F(ψ_norm), as a modulator.
• Adds the function get_plasma(), which creates Generomak plasma from specified equilibrium and distributions. By default this function returns the plasma built from the full plasma profiles.
• Simplifies get_core_plasma() and get_edge_plasma() as both functions now call the new get_plasma() function.
• Removes the distributions argument from get_core_plasma(), because for non-default distributions the general get_plasma() function can be used directly.
• Corrects the default LCFS densities for neutral species and low ionised carbon in get_core_profiles_description() to better match the edge profiles.
• Fixes the toroidal rotation profile in get_core_profiles_description(). @Mateasek, could you please check if this fix is correct?
• Renames the function get_edge_distributions() to get_2d_distributions() and adds an optional profiles_2d argument, since this function can now be used with both edge and full 2D profiles. By default, the function returns distributions built with edge profiles.
• Slightly changes the structure of the dictionary returned by get_2d_distributions() to match the structure of the dictionary returned by get_core_distributions(). Since both dictionaries now have the same structure, they can be used with the get_plasma() function.
• Replaces all zero velocities in default profiles with negligible but non-zero values to avoid errors when blending.

Some outliers in the temperature profiles in hydrogen0.json and carbon0.json are replaced with reasonable values.

Two demos are added, both plotting the core, edge and blended Generomak 2D plasma profiles. The first demo uses the interpolators directly, while the second one samples the profiles from the Plasma objects.

[vsnever]

The Raysect-0.8-compat branch should be merged into the development branch to pass the tests.

[jacklovell]

Thanks for this Vlad. I'm a bit snowed under at the moment, but will take a look at this (and also merging raysect-0.8 into development) when I get time in a couple of weeks.

[Mateasek]

Hi @vsnever,

thanks for the review, I will find some time next week to look at this.

[vsnever]

With the last commit, I fixed the plasma neutrality issue for core profiles. The charge state distributions are now calculated using the ionisation balance tools. Also, manual adjustment of the LCFS values is no longer required, the core profiles match the profiles in the edge plasma quite well. However, the core profiles now depend on the atomic data that we have no control over. I think, this is not a big issue, because almost all Cherab demos use atomic data anyway.

[jacklovell]

However, the core profiles now depend on the atomic data that we have no control over. I think, this is not a big issue, because almost all Cherab demos use atomic data anyway.

You could avoid this by pre-computing the profiles using ionisation balance but then storing the computed values rather than computing them at instantiation time. The data then effectively depends on the atomic data at generation time but end users don't need to have it available when using Generomak.

[vsnever]

You could avoid this by pre-computing the profiles using ionisation balance but then storing the computed values rather than computing them at instantiation time. The data then effectively depends on the atomic data at generation time but end users don't need to have it available when using Generomak.

I added json files with precalculated core profiles as well as two functions to handle them: load_core_profiles() and get_core_interpolators(). All other functions and demo scripts now use get_core_interpolators() instead of get_core_profiles_description() by default.

The density profiles are very sharp functions near Ψ_norm=1, so to take this into account I changed how Ψ_norm is sampled for ionisation balance solver: psin_1d = np.append(1. - np.geomspace(1.e-4, 1, 1023)[::-1], [1.]).

In json files Ψ_norm is sampled in the same way: psin_norm = np.append(1. - np.geomspace(1.e-4, 1, 255)[::-1], [1.]).