TidalPy.structures.world_builder package

Submodules

TidalPy.structures.world_builder.config_handler module

TidalPy.structures.world_builder.config_handler.check_for_duplicate_worlds(world_configs: dict)[source]

Check for duplicate world_types in the world config listing.

Parameters:: world_configs (dict) – Dictionary of world_types (in the format [<name>: <config filepath>])

TidalPy.structures.world_builder.config_handler.clean_world_config(world_config: dict, make_copy: bool = True)[source]

Provides a clean copy of a world’s configuration, deleting any items initialized by TidalPy

Parameters:

world_config (dict) – World’s configuration dictionary
make_copy (bool = True) – Determines if a copy of the dictionary is made. Otherwise changes in this function will affect any other pointers to this dict object.

Returns:

cleaned_dict – Cleaned dictionary with no TidalPy entries

Return type:

dict

TidalPy.structures.world_builder.config_handler.get_world_configs()[source]

TidalPy.structures.world_builder.iterative_builder module

Planet Iteration Package

The goal of this package is to provide the user an easy, but less accurate, way to estiamte the interior structure: of planets. It was designed with exoplanets in mind where some measurements (moment of inertia, etc) are completely unknown.
TODO: This is not the fastest nor most accurate way to do this. It was a quick and dirty way to get some estimates: In the future a more robust method should be developed. It should also be able to handle MOI, etc. for a more accurate answer. Ideally it would also be able to change the number/composition of layers to better fit the data. That latter part is probably a much bigger task
TODO: This could be sped up by only calling on the burnman builder (instead of having to initialize all of TidalPy: at each iteration step).

TidalPy.structures.world_builder.iterative_builder.world_iterative_builder(base_world, goal_radius, goal_mass, ice_mass_frac: float = None, initial_core_density: float = 10000.0, initial_mantle_density: float = 4000.0, ice_density: float = 920.0, tolerance=0.05)[source]

Takes a baseline planet that is close to ideal and iterates on the constructor until there is convergence in the mass and radius

Parameters:

base_world – Instantiated world object that acts as the starting point of the iteration
goal_radius (float) – The final desired radius
goal_mass (float) – The final desired mass
ice_mass_frac (float) – The mass fraction of ice (or other envelope, just change the density) on the planet.
initial_core_density (float) – Initial (average) core density used in the first iteration. The closer this is to the final value, the faster the iteration.
initial_mantle_density (float) – Initial (average) mantle density used in the first iteration. The closer this is to the final value, the faster the iteration.
ice_density (float) – Density of the ice layer
tolerance (float) – The tolerance on final vs. goal mass and radius.

Returns:

Final, instantiated, planet which the iterated mass and radius values

Return type:

iterated_world

TidalPy.structures.world_builder.world_builder module

TidalPy.structures.world_builder.world_builder.build_from_world(old_world, new_config: dict, new_name: str = None)[source]

Constructs a new world based on a previously built one.

The old_world should have characteristics close to the one you desire. For example, if you wanted to make an Io-like: world except that it has an ice layer overtop of it, then choose Europa as a starting point since it would have a similar layer structure and size to the desired world.
If instead, you wish to simply scale up or down a world (turn Earth into a super-Earth or Io into a super-io,: then look into using the scale_from_world function instead.