pint.templates.lcprimitives.LCTopHat

class pint.templates.lcprimitives.LCTopHat(**kwargs)

Bases: LCPrimitive

Represent a top hat function.

Parameters:

Width right edge minus left edge Location center of top hat

Generally, class-specific setup work is performed in init. Here, init is called and certain guaranteed default members are established.

Methods

approx_derivative(phases[, log10_ens, ...])
approx_gradient(phases[, log10_ens, eps])
approx_hessian(phases[, log10_ens, eps])
cdf(x[, log10_ens])
center_gauss_prior([enable])	[Convenience] Set gauss mode to current params.
check_bounds([p])
check_gradient([atol, rtol, quiet])
closest_to_peak(phases)	Return the minimum distance between a member of the array of phases and the position of the mode of the primitive.
copy()
derivative(phases[, log10_ens, order])	Return d^np(phi)/dphi^n, with n=order.
dict_string()	Return a string to express the object as a dictionary that can be easily instantiated using its keys.
enable_gauss_prior([enable])	[Convenience] Turn on gaussian prior.
eval_string()	Return a string that can be evaluated to instantiate a nearly- identical object.
fwhm()	Return the full-width at half-maximum of the light curve model.
get_bounds([free])
get_errors([free])
get_fixed_energy_version([log10_en])
get_free_mask()	Return a mask with True if parameters are free, else False.
get_gauss_prior_parameters()
get_location([error])
get_norm([error])
get_parameter_names([free])
get_parameters([free])
get_width([error, hwhm, right])	Return the width of the distribution.
gradient(phases[, log10_ens, free])	Return the gradient of the primitives wrt the parameters.
gradient_derivative(phases[, log10_ens, free])	Return d/dphi(gradient).
hwhm([right])	Return the half-width at half-maximum of the light curve model.
init()
integrate([x1, x2, log10_ens])	Base implemention with scipy quad.
is_energy_dependent()
is_two_sided()	True if primitive is asymmetric.
num_parameters([free])
parse_kwargs(kwargs)
random(n)	Default is accept/reject.
sanity_checks([eps])	A few checks on normalization, integration, etc.
set_errors(errs)
set_location(loc)
set_parameters(p[, free])

hwhm(right=False)

Return the half-width at half-maximum of the light curve model.

__call__(phases, wrap=True)

Call self as a function.

random(n)

Default is accept/reject.

center_gauss_prior(enable=False)

[Convenience] Set gauss mode to current params.

closest_to_peak(phases)

Return the minimum distance between a member of the array of phases and the position of the mode of the primitive.

derivative(phases, log10_ens=3, order=1)

Return d^np(phi)/dphi^n, with n=order.

dict_string()

Return a string to express the object as a dictionary that can be easily instantiated using its keys.

enable_gauss_prior(enable=True)

[Convenience] Turn on gaussian prior.

eval_string()

Return a string that can be evaluated to instantiate a nearly- identical object.

fwhm()

Return the full-width at half-maximum of the light curve model.

get_free_mask()

Return a mask with True if parameters are free, else False.

get_width(error=False, hwhm=False, right=False)

Return the width of the distribution.

Parameters:

• error (bool) – if True, return tuple with value and error

• hwhm (bool) – if True, scale width to be HWHM

• right (bool) – if True, return “right” component, else “left”. There is no distinction for symmetric dists.

gradient(phases, log10_ens=3, free=False)

Return the gradient of the primitives wrt the parameters.

gradient_derivative(phases, log10_ens=3, free=False)

Return d/dphi(gradient). This is needed for computing the hessian of the profile for parameters that affect the timing model and hence pulse phase.

integrate(x1=0, x2=1, log10_ens=3)

Base implemention with scipy quad.

is_two_sided()

True if primitive is asymmetric. Default is False, two-sided child classes should override.

sanity_checks(eps=1e-06)

A few checks on normalization, integration, etc.