model.HydrostaticEquilibrium#

class model.HydrostaticEquilibrium(fields, properties=None, dm_virial=None, star_virial=None)[source]#

Equivalent to ClusterModel

Methods

`__init__`(fields[, properties, dm_virial, ...])	Initialize the `model.ClusterModel` instance.
`check_dm_virial`()	Equivalent to `self.dm_virial.check_virial`
`check_hse`()	Determine the deviation of the model from hydrostatic equilibrium.
`check_star_virial`()	Equivalent to `self.star_virial.check_virial`
`correct`([mode])	Correct the `model.ClusterModel` instance.
`create_dataset`(domain_dimensions[, ...])
`find_field_at_radius`(field, r)	Find the value of a field in the profiles at radius r.
`find_radius_for_density`(density)	Determine the radius at which the model reaches the specified density
`from_arrays`(fields[, stellar_density])	Initialize the `model.ClusterModel` from `fields` alone.
`from_dens_and_entr`(rmin, rmax, density, entropy)	Construct the model from density and entropy.
`from_dens_and_tden`(rmin, rmax, density, ...)	Construct a hydrostatic equilibrium model using gas density and total density profiles
`from_dens_and_temp`(rmin, rmax, density, ...)	Construct a hydrostatic equilibrium model using gas density and temperature profiles.
`from_h5_file`(filename[, r_min, r_max])	Initialize a `model.ClusterModel` instance from HDF5 file.
`generate_dm_particles`(num_particles[, ...])	Generate a set of dark matter particles in virial equilibrium.
`generate_gas_particles`(num_particles[, ...])	Generate a set of gas particles in hydrostatic equilibrium.
`generate_star_particles`(num_particles[, ...])	Generate a set of star particles in virial equilibrium.
`generate_tracer_particles`(num_particles[, ...])	Generate a set of tracer particles based on the gas distribution.
`items`()	Equivalent to `self.fields.items()`
`keys`()	Equivalent to `self.fields.keys()`
`mass_in_radius`(radius)	Determine the mass within a given radius.
`no_gas`(rmin, rmax, total_density[, ...])	Initialize a `model.ClusterModel` which is composed only of collisionless species.
`panel_plot`([fields, r_min, r_max, fig, ...])	Plot all of the selected fields in a grid of axes.
`plot`(field[, r_min, r_max, fig, ax, defaults])	Plot a field vs radius from this model using Matplotlib.
`set_field`(name, value)	Set a field with name name to value value, which is an unyt_array.
`set_magnetic_field_from_beta`(beta[, gaussian])	Set a magnetic field radial profile from a plasma beta parameter, assuming beta = p_th/p_B.
`set_magnetic_field_from_density`(B0[, eta, ...])	Set a magnetic field radial profile assuming it is proportional to some power of the density, usually 2/3.
`set_rmax`(r_max)	Truncate the model at a specified maximal radius.
`values`()	Equivalent to `self.fields.values()`
`write_model_to_ascii`(output_filename[, ...])	Write the equilibrium model to an ascii text file.
`write_model_to_binary`(output_filename[, ...])	Write the model to unformatted Fortran binary.
`write_model_to_h5`(output_filename[, in_cgs, ...])	Write the equilibrium model to an HDF5 file.

Attributes

`default_fields`	The default included fields that can be accessed.
`dm_virial`	The `virial.VirialEquilibrium` instance associated with the dark matter virialization process.
`is_physical`	Determines if the `model.ClusterModel` instance is physically realizable.
`properties`	The properties of the `model.ClusterModel` instance.
`star_virial`	The `virial.VirialEquilibrium` instance associated with the stellar virialization process.
`fields`	The `fields` associated with the `Potential` object.
`num_elements`	The number of elements in each `field` array.