meepmeep.numba3d.ev_signal_cd

meepmeep.numba3d.ev_signal_cd(time: float | ndarray[tuple[Any, ...], dtype[_ScalarT]], alpha: float, mass_ratio: float, inc: float, c: ndarray[tuple[Any, ...], dtype[_ScalarT]], dc: ndarray[tuple[Any, ...], dtype[_ScalarT]])

Evaluate the ellipsoidal-variation signal and its parameter derivatives at an expansion-point-centered time.

Derivative-returning counterpart of ev_signal.ev_signal_c: forms \(S = -\alpha\,q\,\sin^2 i\,(2 c_z^2 - 1)/d^3\) and propagates the chain rule through both the position (and hence the distance) and the explicit \(\sin^2 i\) factor.

Accepts a scalar time or a 1-D array of times and dispatches to the appropriate kernel at compile time (inside @njit) or at call time (pure Python).

Parameters:

timefloat or ndarray

Time(s) relative to the Taylor series expansion point.

alphafloat

Gravity-darkening coefficient (Lillo-Box et al. 2014, Eq. 7).

mass_ratiofloat

Planet-to-star mass ratio \(M_p / M_\star\).

incfloat

Orbital inclination [radians]. This is the orbital inclination, the same quantity as the i axis of the gradient; its full derivative (the implicit position contribution plus the explicit sin^2 i prefactor) is accumulated into the single inclination slot (slot 3).

cNDArray

A (3, 5) Taylor coefficient matrix produced by solve3d.

dcNDArray

A (7, 3, 5) parameter-derivative tensor produced by solve3d_d, with the leading axis ordered as (tc, p, a, i, e, w, lan).

Returns:

outfloat or ndarray

Ellipsoidal variation signal. Shape (N,) for an array time.

doutNDArray

Partial derivatives of out with respect to (tc, p, a, i, e, w, lan, alpha, mass_ratio). Shape (9,) for a scalar time, (N, 9) for an array time.