Source code for meepmeep.backends.numba.point3dd.cos_phase_angle

#  MeepMeep: fast orbit calculations for exoplanet modelling
#  Copyright (C) 2022-2026 Hannu Parviainen
#
#  This program is free software: you can redistribute it and/or modify
#  it under the terms of the GNU General Public License as published by
#  the Free Software Foundation, either version 3 of the License, or
#  (at your option) any later version.
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"""Single-expansion-point 3D phase-angle cosine evaluators with parameter derivatives.

Derivative-returning counterpart of ``point3d.cos_phase_angle``. Unlike
``separation``, which collapses the position gradients to scalar
temporaries, the phase-angle cosine needs the full (x, y, z) position and
its three gradients, so the write-into kernel delegates to
``position._pos_cd_w`` and reduces through the chain rule. The position
gradients are therefore intermediate scratch reused across samples, which
makes the vector loops scratch-using: the serial kernels hoist one ``(7,)``
buffer triple and the parallel twins hoist per-thread buffers (explicit
twins rather than a dual-decorated shared body).
"""

from numba import njit, prange, types, get_num_threads, get_thread_id
from numba.extending import overload
from numpy import floor, sqrt, zeros, ndarray
from numpy.typing import NDArray

from ._common import _is_1d_array
from .position import _pos_cd_w


@njit(fastmath=True, inline='always')
def _cos_alpha_cd_w(time, c, dc, dca, dpx, dpy, dpz):
    """Write-into kernel shared by the scalar and vector evaluators.

    Writes the seven-parameter phase-angle-cosine gradient into the
    caller-provided ``(7,)`` buffer ``dca`` and returns the cosine.
    ``dpx``, ``dpy``, and ``dpz`` are ``(7,)`` scratch buffers for the
    position gradients; vector loops allocate them once and reuse them.
    """
    px, py, pz = _pos_cd_w(time, c, dc, dpx, dpy, dpz)
    r2 = px * px + py * py + pz * pz
    r = sqrt(r2)
    ca = -pz / r
    inv_r = 1.0 / r
    inv_r3 = inv_r / r2
    for k in range(7):
        # d(-z/r)/dtheta = -dz/r + z * (x*dx + y*dy + z*dz) / r^3
        dca[k] = -dpz[k] * inv_r + pz * (px * dpx[k] + py * dpy[k] + pz * dpz[k]) * inv_r3
    return ca


@njit(fastmath=True)
def _cos_alpha_cd_s(time, c, dc):
    """Scalar kernel for :func:`cos_alpha_cd`. See that function for documentation."""
    dca = zeros(7)
    dpx = zeros(7)
    dpy = zeros(7)
    dpz = zeros(7)
    ca = _cos_alpha_cd_w(time, c, dc, dca, dpx, dpy, dpz)
    return ca, dca


@njit(fastmath=True)
def cos_alpha_cd_v(time, c, dc):
    """Vector kernel for :func:`cos_alpha_cd`. See that function for documentation."""
    n = time.size
    ca = zeros(n)
    dca = zeros((n, 7))
    dpx = zeros(7)
    dpy = zeros(7)
    dpz = zeros(7)
    for j in range(n):
        ca[j] = _cos_alpha_cd_w(time[j], c, dc, dca[j], dpx, dpy, dpz)
    return ca, dca


@njit(fastmath=True, parallel=True)
def cos_alpha_cd_vp(time, c, dc):
    """Parallel (prange) twin of :func:`cos_alpha_cd_v`.

    Explicit twin rather than a dual-decorated shared body: the
    position-gradient scratch is hoisted per thread here
    (``zeros((get_num_threads(), 7))``, indexed with ``get_thread_id()``),
    while the serial kernel keeps its cheaper single hoisted buffer -
    one shared buffer would be a data race under ``prange``.
    """
    n = time.size
    ca = zeros(n)
    dca = zeros((n, 7))
    nt = get_num_threads()
    dpx = zeros((nt, 7))
    dpy = zeros((nt, 7))
    dpz = zeros((nt, 7))
    for j in prange(n):
        tid = get_thread_id()
        ca[j] = _cos_alpha_cd_w(time[j], c, dc, dca[j], dpx[tid], dpy[tid], dpz[tid])
    return ca, dca


[docs] def cos_alpha_cd(time: float | NDArray, c: NDArray, dc: NDArray): """ Evaluate the cosine of the orbital phase angle and its parameter derivatives at an expansion-point-centered time. Derivative-returning counterpart of `cos_phase_angle.cos_alpha_c`: forms the phase-angle cosine `cos alpha = -z / sqrt(x^2 + y^2 + z^2)` from the sky position and propagates the chain rule to its seven orbital-parameter partials. The phase angle alpha is the star-planet-observer angle, with z positive toward the observer; `cos alpha = +1` at superior conjunction (full phase) and `-1` at inferior conjunction (new phase). 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), mirroring the value-only `cos_phase_angle.cos_alpha_c`. Parameters ---------- time : float or ndarray Time(s) relative to the Taylor series expansion point. c : NDArray A (3, 5) Taylor coefficient matrix produced by `solve3d`. dc : NDArray 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 ------- ca : float or ndarray Cosine of the phase angle, in [-1, 1]. Shape (N,) for an array `time`. dca : NDArray Partial derivatives of `ca` with respect to `(tc, p, a, i, e, w, lan)`. Shape (7,) for a scalar `time`, (N, 7) for an array `time`. Notes ----- With `cos alpha = -z/r` and `r = sqrt(x^2 + y^2 + z^2)`, the chain-rule reduction used here is `d(cos alpha)/dtheta = -dz/dtheta / r + z * (x*dx/dtheta + y*dy/dtheta + z*dz/dtheta) / r^3`. The expression is regular for `r > 0`. """ if isinstance(time, ndarray): return cos_alpha_cd_v(time, c, dc) return _cos_alpha_cd_s(time, c, dc)
@overload(cos_alpha_cd, jit_options={'fastmath': True}) def _cos_alpha_cd_overload(time, c, dc): if _is_1d_array(time): def impl(time, c, dc): return cos_alpha_cd_v(time, c, dc) return impl if isinstance(time, types.Float): def impl(time, c, dc): return _cos_alpha_cd_s(time, c, dc) return impl return None @njit(fastmath=True) def _cos_alpha_d_s(time, tc, p, c, dc, te): """Scalar kernel for :func:`cos_alpha_d`. See that function for documentation.""" epoch = floor((time - tc - te + 0.5 * p) / p) return _cos_alpha_cd_s(time - (tc + te + epoch * p), c, dc) @njit(fastmath=True) def cos_alpha_d_v(time, tc, p, c, dc, te): """Vector kernel for :func:`cos_alpha_d`. See that function for documentation.""" n = time.size ca = zeros(n) dca = zeros((n, 7)) dpx = zeros(7) dpy = zeros(7) dpz = zeros(7) for j in range(n): epoch = floor((time[j] - tc - te + 0.5 * p) / p) ca[j] = _cos_alpha_cd_w(time[j] - (tc + te + epoch * p), c, dc, dca[j], dpx, dpy, dpz) return ca, dca @njit(fastmath=True, parallel=True) def cos_alpha_d_vp(time, tc, p, c, dc, te): """Parallel (prange) twin of :func:`cos_alpha_d_v`. Explicit twin with per-thread position-gradient scratch; see :func:`cos_alpha_cd_vp`. """ n = time.size ca = zeros(n) dca = zeros((n, 7)) nt = get_num_threads() dpx = zeros((nt, 7)) dpy = zeros((nt, 7)) dpz = zeros((nt, 7)) for j in prange(n): tid = get_thread_id() epoch = floor((time[j] - tc - te + 0.5 * p) / p) ca[j] = _cos_alpha_cd_w(time[j] - (tc + te + epoch * p), c, dc, dca[j], dpx[tid], dpy[tid], dpz[tid]) return ca, dca
[docs] def cos_alpha_d(time: float | NDArray, tc: float, p: float, c: NDArray, dc: NDArray, te: float = 0.0): """ Evaluate the cosine of the orbital phase angle and its parameter derivatives at an absolute time. Direct counterpart of `cos_alpha_cd`: epoch-folds the absolute time `time` around the expansion point and delegates to `cos_alpha_cd`. 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), mirroring the value-only `cos_phase_angle.cos_alpha`. Parameters ---------- time : float or ndarray Absolute observation time(s) in the same units as `tc` and `p`. tc : float Transit-centre time (time of inferior conjunction), on the same time axis as `time`. p : float Orbital period, used for epoch folding. c : NDArray A (3, 5) Taylor coefficient matrix produced by `solve3d`. dc : NDArray A (7, 3, 5) parameter-derivative tensor produced by `solve3d_d`, with the leading axis ordered as `(tc, p, a, i, e, w, lan)`. te : float, optional Expansion-point offset from the transit centre [days] - the same value that was passed to `solve3d_d`. Defaults to 0.0, the expansion point at the transit centre. Returns ------- ca : float or ndarray Cosine of the phase angle, in [-1, 1]. Shape (N,) for an array `time`. dca : NDArray Partial derivatives of `ca` with respect to `(tc, p, a, i, e, w, lan)`. Shape (7,) for a scalar `time`, (N, 7) for an array `time`. """ if isinstance(time, ndarray): return cos_alpha_d_v(time, tc, p, c, dc, te) return _cos_alpha_d_s(time, tc, p, c, dc, te)
@overload(cos_alpha_d, jit_options={'fastmath': True}) def _cos_alpha_d_overload(time, tc, p, c, dc, te=0.0): if _is_1d_array(time): def impl(time, tc, p, c, dc, te=0.0): return cos_alpha_d_v(time, tc, p, c, dc, te) return impl if isinstance(time, types.Float): def impl(time, tc, p, c, dc, te=0.0): return _cos_alpha_d_s(time, tc, p, c, dc, te) return impl return None