py21cmfast.wrapper.inputs.AstroOptions

class py21cmfast.wrapper.inputs.AstroOptions

Bases: InputStruct

Options for the ionization routines which enable/disable certain modules.

Parameters:

  • USE_MINI_HALOS (bool, optional) – Set to True if using mini-halos parameterization. If True, USE_TS_FLUCT and INHOMO_RECO must be True.

  • USE_X_RAY_HEATING (bool, optional) – Whether to include X-ray heating (useful for debugging).

  • USE_CMB_HEATING (bool, optional) – Whether to include CMB heating. (cf Eq.4 of Meiksin 2021, arxiv.org/abs/2105.14516)

  • USE_LYA_HEATING (bool, optional) – Whether to use Lyman-alpha heating. (cf Sec. 3 of Reis+2021, doi.org/10.1093/mnras/stab2089)

  • INHOMO_RECO (bool, optional) – Whether to perform inhomogeneous recombinations. Increases the computation time.

  • USE_TS_FLUCT (bool, optional) – Whether to perform IGM spin temperature fluctuations (i.e. X-ray heating). Dramatically increases the computation time.

  • M_MIN_in_Mass (bool, optional) – Whether the minimum halo mass (for ionization) is defined by mass or virial temperature. Only has an effect when SOURCE_MODEL == ‘CONST-ION-EFF’

  • PHOTON_CONS_TYPE (str, optional) – Whether to perform a small correction to account for the inherent photon non-conservation. This can be one of three types of correction:

    no-photoncons: No photon cosnervation correction, z-photoncons: Photon conservation correction by adjusting the redshift of the N_ion source field (Park+22) alpha-photoncons: Adjustment to the escape fraction power-law slope, based on fiducial results in Park+22, This runs a series of global xH evolutions and one calibration simulation to find the adjustment as a function of xH f-photoncons: Adjustment to the escape fraction normalisation, runs one calibration simulation to find the adjustment as a function of xH where f’/f = xH_global/xH_calibration

  • FIX_VCB_AVG (bool, optional) – Determines whether to use a fixed vcb=VAVG (regardless of USE_RELATIVE_VELOCITIES). It includes the average effect of velocities but not its fluctuations. See Muñoz+21 (2110.13919).

  • USE_EXP_FILTER (bool, optional) – Use the exponential filter (MFP-epsilon(r) from Davies & Furlanetto 2021) when calculating ionising emissivity fields NOTE: this does not affect other field filters, and should probably be used with HII_FILTER==0 (real-space top-hat)

  • CELL_RECOMB (bool, optional) – An alternate way of counting recombinations based on the local cell rather than the filter region. This is part of the perspective shift (see Davies & Furlanetto 2021) from counting photons/atoms in a sphere and flagging a central pixel to counting photons which we expect to reach the central pixel, and taking the ratio of atoms in the pixel. This flag simply turns off the filtering of N_rec grids, and takes the recombinations in the central cell.

  • USE_UPPER_STELLAR_TURNOVER (bool, optional) – Whether to use an additional powerlaw in stellar mass fraction at high halo mass. The pivot mass scale and power-law index are controlled by two parameters, UPPER_STELLAR_TURNOVER_MASS and UPPER_STELLAR_TURNOVER_INDEX respectively. This is currently only implemented using the discrete halo model, and has no effect otherwise.

  • HALO_SCALING_RELATIONS_MEDIAN (bool, optional) – If True, halo scaling relation parameters (F_STAR10,t_STAR etc…) define the median of their conditional distributions If False, they describe the mean. This becomes important when using non-symmetric dristributions such as the log-normal

  • HII_FILTER (string) – Filter for the halo or density field used to generate ionization field Available options are: ‘spherical-tophat’, ‘sharp-k’, and ‘gaussian’

  • HEAT_FILTER (int) – Filter for the halo or density field used to generate the spin-temperature field Available options are: ‘spherical-tophat’, ‘sharp-k’, and ‘gaussian’

  • IONISE_ENTIRE_SPHERE (bool, optional) – If True, ionises the entire sphere on the filter scale when an ionised region is found in the excursion set.

  • INTEGRATION_METHOD_ATOMIC (str, optional) – The integration method to use for conditional MF integrals of atomic halos in the grids: NOTE: global integrals will use GSL QAG adaptive integration ‘GSL-QAG’: GSL QAG adaptive integration, ‘GAUSS-LEGENDRE’: Gauss-Legendre integration, previously forced in the interpolation tables, ‘GAMMA-APPROX’: Approximate integration, assuming sharp cutoffs and a triple power-law for sigma(M) based on EPS

  • INTEGRATION_METHOD_MINI (str, optional) – The integration method to use for conditional MF integrals of minihalos in the grids: ‘GSL-QAG’: GSL QAG adaptive integration, ‘GAUSS-LEGENDRE’: Gauss-Legendre integration, previously forced in the interpolation tables, ‘GAMMA-APPROX’: Approximate integration, assuming sharp cutoffs and a triple power-law for sigma(M) based on EPS

classmethod __init_subclass__()

Store each subclass for easy access.

Return type:

None

__str__()

Human-readable string representation of the object.

Return type:

str

asdict()

Return a dict representation of the instance.

Examples

This dict should be such that doing the following should work, i.e. it can be used exactly to construct a new instance of the same object:

>>> inp = InputStruct(**params)
>>> newinp =InputStruct(**inp.asdict())
>>> inp == newinp
Return type:

dict

clone(**kwargs)

Make a fresh copy of the instance with arbitrary parameters updated.

classmethod from_subdict(dct, safe=True)

Construct an instance of a parameter structure from a dictionary.

classmethod new(x=None, **kwargs)

Create a new instance of the struct.

Parameters:

x (dict | InputStruct | None) – Initial values for the struct. If x is a dictionary, it should map field names to their corresponding values. If x is an instance of this class, its attributes will be used as initial values. If x is None, the struct will be initialised with default values.

Other Parameters:

  • All other parameters should be passed as if directly to the class constructor

  • (i.e. as parameter names).

Parameters:

x (dict | Self | None)

Examples

>>> up = SimulationOptions({'HII_DIM': 250})
>>> up.HII_DIM
250
>>> up = SimulationOptions(up)
>>> up.HII_DIM
250
>>> up = SimulationOptions()
>>> up.HII_DIM
200
>>> up = SimulationOptions(HII_DIM=256)
>>> up.HII_DIM
256
CELL_RECOMB: bool
FIX_VCB_AVG: bool
HALO_SCALING_RELATIONS_MEDIAN: bool
HEAT_FILTER: FilterOptions
HII_FILTER: FilterOptions
INHOMO_RECO: bool
INTEGRATION_METHOD_ATOMIC: IntegralMethods
INTEGRATION_METHOD_MINI: IntegralMethods
IONISE_ENTIRE_SPHERE: bool
M_MIN_in_Mass: bool
PHOTON_CONS_TYPE: Literal['no-photoncons', 'z-photoncons', 'alpha-photoncons', 'f-photoncons']
USE_CMB_HEATING: bool
USE_EXP_FILTER: bool
USE_LYA_HEATING: bool
USE_MINI_HALOS: bool
USE_TS_FLUCT: bool
USE_UPPER_STELLAR_TURNOVER: bool
USE_X_RAY_HEATING: bool
property cdict: dict

A python dictionary containing the properties of the wrapped C-struct.

The memory pointed to by this dictionary is not owned by the wrapped C-struct, but is rather just a python dict. However, in contrast to asdict(), this method transforms the properties to what they should be in C (e.g. linear space vs. log-space) before putting them into the dict.

This dict also contains only the properties of the wrapped C-struct, rather than all properties of the InputStruct instance (some attributes of the python instance are there only to guide setting of defaults, and don’t appear in the C-struct at all).

Return type:

dict

property cstruct: py21cmfast.wrapper.structs.StructWrapper

The object pointing to the memory accessed by C-code for this struct.

Return type:

py21cmfast.wrapper.structs.StructWrapper

property struct: py21cmfast.wrapper.structs.StructWrapper

The python-wrapped struct associated with this input object.

Return type:

py21cmfast.wrapper.structs.StructWrapper