from .baseconfig import F2003Class, fortran_class, numpy_1d, CAMBError, np, \
AllocatableArrayDouble, f_pointer
from ctypes import c_int, c_double, byref, POINTER, c_bool
[docs]
class DarkEnergyModel(F2003Class):
"""
Abstract base class for dark energy model implementations.
"""
_fields_ = [
("__is_cosmological_constant", c_bool),
("__num_perturb_equations", c_int)]
def validate_params(self):
return True
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class DarkEnergyEqnOfState(DarkEnergyModel):
"""
Abstract base class for models using w and wa parameterization with use w(a) = w + (1-a)*wa parameterization,
or call set_w_a_table to set another tabulated w(a). If tabulated w(a) is used, w and wa are set
to approximate values at z=0.
See :meth:`.model.CAMBparams.set_initial_power_function` for a convenience constructor function to
set a general interpolated P(k) model from a python function.
"""
_fortran_class_module_ = 'DarkEnergyInterface'
_fortran_class_name_ = 'TDarkEnergyEqnOfState'
_fields_ = [
("w", c_double, "w(0)"),
("wa", c_double, "-dw/da(0)"),
("cs2", c_double, "fluid rest-frame sound speed squared"),
("use_tabulated_w", c_bool, "using an interpolated tabulated w(a) rather than w, wa above"),
("__no_perturbations", c_bool, "turn off perturbations (unphysical, so hidden in Python)")
]
_methods_ = [('SetWTable', [numpy_1d, numpy_1d, POINTER(c_int)])]
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def set_params(self, w=-1.0, wa=0, cs2=1.0):
"""
Set the parameters so that P(a)/rho(a) = w(a) = w + (1-a)*wa
:param w: w(0)
:param wa: -dw/da(0)
:param cs2: fluid rest-frame sound speed squared
"""
self.w = w
self.wa = wa
self.cs2 = cs2
self.validate_params()
def validate_params(self):
if not self.use_tabulated_w and self.wa + self.w > 0:
raise CAMBError('dark energy model has w + wa > 0, giving w>0 at high redshift')
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def set_w_a_table(self, a, w):
"""
Set w(a) from numerical values (used as cubic spline). Note this is quite slow.
:param a: array of scale factors
:param w: array of w(a)
:return: self
"""
if len(a) != len(w):
raise ValueError('Dark energy w(a) table non-equal sized arrays')
if not np.isclose(a[-1], 1):
raise ValueError('Dark energy w(a) arrays must end at a=1')
if np.any(a <= 0):
raise ValueError('Dark energy w(a) table cannot be set for a<=0')
a = np.ascontiguousarray(a, dtype=np.float64)
w = np.ascontiguousarray(w, dtype=np.float64)
self.f_SetWTable(a, w, byref(c_int(len(a))))
return self
def __getstate__(self):
if self.use_tabulated_w:
raise TypeError("Cannot save class with splines")
return super().__getstate__()
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@fortran_class
class DarkEnergyFluid(DarkEnergyEqnOfState):
"""
Class implementing the w, wa or splined w(a) parameterization using the constant sound-speed single fluid model
(as for single-field quintessence).
"""
_fortran_class_module_ = 'DarkEnergyFluid'
_fortran_class_name_ = 'TDarkEnergyFluid'
def validate_params(self):
super().validate_params()
if not self.use_tabulated_w:
if self.wa and (self.w < -1 - 1e-6 or 1 + self.w + self.wa < - 1e-6):
raise CAMBError('fluid dark energy model does not support w crossing -1')
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def set_w_a_table(self, a, w):
# check w array has elements that do not cross -1
if np.sign(1 + np.max(w)) - np.sign(1 + np.min(w)) == 2:
raise CAMBError('fluid dark energy model does not support w crossing -1')
super().set_w_a_table(a, w)
[docs]
@fortran_class
class DarkEnergyPPF(DarkEnergyEqnOfState):
"""
Class implementing the w, wa or splined w(a) parameterization in the PPF perturbation approximation
(`arXiv:0808.3125 <https://arxiv.org/abs/0808.3125>`_)
Use inherited methods to set parameters or interpolation table.
Note PPF is not a physical model and just designed to allow crossing -1 in an ad hoc smooth way. For models
with w>-1 but far from cosmological constant, it can give quite different answers to the fluid model with c_s^2=1.
"""
# cannot declare c_Gamma_ppf directly here as have not defined all fields in DarkEnergyEqnOfState (TCubicSpline)
_fortran_class_module_ = 'DarkEnergyPPF'
_fortran_class_name_ = 'TDarkEnergyPPF'
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@fortran_class
class AxionEffectiveFluid(DarkEnergyModel):
"""
Example implementation of a specific (early) dark energy fluid model
(`arXiv:1806.10608 <https://arxiv.org/abs/1806.10608>`_).
Not well tested, but should serve to demonstrate how to make your own custom classes.
"""
_fields_ = [
("w_n", c_double, "effective equation of state parameter"),
("fde_zc", c_double, "energy density fraction at z=zc"),
("zc", c_double, "decay transition redshift (not same as peak of energy density fraction)"),
("theta_i", c_double, "initial condition field value")]
_fortran_class_name_ = 'TAxionEffectiveFluid'
_fortran_class_module_ = 'DarkEnergyFluid'
def set_params(self, w_n, fde_zc, zc, theta_i=None):
self.w_n = w_n
self.fde_zc = fde_zc
self.zc = zc
if theta_i is not None:
self.theta_i = theta_i
# base class for scalar field quintessence models
[docs]
class Quintessence(DarkEnergyModel):
r"""
Abstract base class for single scalar field quintessence models.
For each model the field value and derivative are stored and splined at sampled scale factor values.
To implement a new model, need to define a new derived class in Fortran,
defining Vofphi and setting up initial conditions and interpolation tables (see TEarlyQuintessence as example).
"""
_fields_ = [
("DebugLevel", c_int),
("astart", c_double),
("integrate_tol", c_double),
("sampled_a", AllocatableArrayDouble),
("phi_a", AllocatableArrayDouble),
("phidot_a", AllocatableArrayDouble),
("__npoints_linear", c_int),
("__npoints_log", c_int),
("__dloga", c_double),
("__da", c_double),
("__log_astart", c_double),
("__max_a_log", c_double),
("__ddphi_a", AllocatableArrayDouble),
("__ddphidot_a", AllocatableArrayDouble),
("__state", f_pointer)
]
_fortran_class_module_ = 'Quintessence'
def __getstate__(self):
raise TypeError("Cannot save class with splines")
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@fortran_class
class EarlyQuintessence(Quintessence):
r"""
Example early quintessence (axion-like, as `arXiv:1908.06995 <https://arxiv.org/abs/1908.06995>`_) with potential
V(\phi) = m^2f^2 (1 - cos(\phi/f))^n + \Lambda_{cosmological constant}
"""
_fields_ = [
("n", c_double, "power index for potential"),
("f", c_double, r"f/Mpl (sqrt(8\piG)f); only used for initial search value when use_zc is True"),
("m", c_double, "mass parameter in reduced Planck mass units; "
"only used for initial search value when use_zc is True"),
("theta_i", c_double, "phi/f initial field value"),
("frac_lambda0", c_double, "fraction of dark energy in cosmological constant today (approximated as 1)"),
("use_zc", c_bool, "solve for f, m to get specific critical redshift zc and fde_zc"),
("zc", c_double, "redshift of peak fractional early dark energy density"),
("fde_zc", c_double, "fraction of early dark energy density to total at peak"),
("npoints", c_int, "number of points for background integration spacing"),
("min_steps_per_osc", c_int, "minimum number of steps per background oscillation scale"),
("fde", AllocatableArrayDouble, "after initialized, the calculated background early dark energy "
"fractions at sampled_a"),
("__ddfde", AllocatableArrayDouble)
]
_fortran_class_name_ = 'TEarlyQuintessence'
def set_params(self, n, f=0.05, m=5e-54, theta_i=0.0, use_zc=True, zc=None, fde_zc=None):
self.n = n
self.f = f
self.m = m
self.theta_i = theta_i
self.use_zc = use_zc
if use_zc:
if zc is None or fde_zc is None:
raise ValueError("must set zc and fde_zc if using 'use_zc'")
self.zc = zc
self.fde_zc = fde_zc
# short names for models that support w/wa
F2003Class._class_names.update({'fluid': DarkEnergyFluid, 'ppf': DarkEnergyPPF})