Source code for meepmeep.backends.numba.point2d.separation

#  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.
#
#  This program is distributed in the hope that it will be useful,
#  but WITHOUT ANY WARRANTY; without even the implied warranty of
#  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
#  GNU General Public License for more details.
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"""Single-expansion-point 2D sky-projected planet-star separation evaluators."""

from numba import njit, prange, types
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_c_s


@njit(fastmath=True, inline='always')
def _sep_c_s(time, c):
    """Scalar kernel for :func:`sep_c`. See that function for documentation."""
    px, py = _pos_c_s(time, c)
    return sqrt(px ** 2 + py ** 2)


def _sep_c_v_body(time, c):
    """Vector-kernel body for :func:`sep_c`; see that function for documentation.

    Compiled twice: ``sep_c_v`` is the serial kernel (``prange`` compiles
    as a plain ``range`` without ``parallel=True``) and ``sep_c_vp`` the
    parallel twin. The loop writes only into per-sample output elements,
    so no per-thread scratch is needed.
    """
    n = time.size
    d = zeros(n)
    for j in prange(n):
        d[j] = _sep_c_s(time[j], c)
    return d


sep_c_v = njit(fastmath=True)(_sep_c_v_body)
sep_c_vp = njit(fastmath=True, parallel=True)(_sep_c_v_body)


[docs] def sep_c(time: float | NDArray, c: NDArray) -> float | NDArray: """ Evaluate the sky-projected planet-star separation in the units of stellar radii at an expansion-point-centered time. Centered counterpart of `sep`: assumes `time` has already been shifted to be relative to the expansion point, evaluates the 2D position, and returns `sqrt(x^2 + y^2)`. 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 ---------- time : float or NDArray Time relative to the Taylor series expansion point. c : NDArray A (2, 5) coefficient matrix produced by `solve2d`. Returns ------- d : float or NDArray Projected planet-star center distance in units of stellar radii. """ if isinstance(time, ndarray): return sep_c_v(time, c) return _sep_c_s(time, c)
@overload(sep_c, jit_options={'fastmath': True}, inline='always') def _sep_c_overload(time, c): if _is_1d_array(time): def impl(time, c): return sep_c_v(time, c) return impl if isinstance(time, types.Float): def impl(time, c): return _sep_c_s(time, c) return impl return None @njit(fastmath=True, inline='always') def _sep_s(time, tc, p, c, te): """Scalar kernel for :func:`sep`. See that function for documentation.""" epoch = floor((time - tc - te + 0.5 * p) / p) return _sep_c_s(time - (tc + te + epoch * p), c) def _sep_v_body(time, tc, p, c, te): """Vector-kernel body for :func:`sep`; see that function for documentation. Compiled twice: ``sep_v`` is the serial kernel (``prange`` compiles as a plain ``range`` without ``parallel=True``) and ``sep_vp`` the parallel twin. The loop writes only into per-sample output elements, so no per-thread scratch is needed. """ n = time.size d = zeros(n) for j in prange(n): epoch = floor((time[j] - tc - te + 0.5 * p) / p) d[j] = _sep_c_s(time[j] - (tc + te + epoch * p), c) return d sep_v = njit(fastmath=True)(_sep_v_body) sep_vp = njit(fastmath=True, parallel=True)(_sep_v_body)
[docs] def sep(time: float | NDArray, tc: float, p: float, c: NDArray, te: float = 0.0) -> float | NDArray: """ Evaluate the projected planet-star separation at an absolute time. Computes the sky-plane (x, y) position and returns the Euclidean distance `sqrt(x^2 + y^2)`. This is the quantity most commonly used by transit light-curve models, where it represents the center-to-center separation between the planet and star projected onto the plane of the sky. 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 ---------- time : float or NDArray Absolute observation time(s). tc : float Transit-centre time (time of inferior conjunction), on the same time axis as `time`. p : float Orbital period. c : NDArray A (2, 5) coefficient matrix produced by `solve2d`. te : float, optional Expansion-point offset from the transit centre [days] - the same value that was passed to `solve2d`. Defaults to 0.0, the expansion point at the transit centre. Returns ------- d : float or NDArray Projected planet-star center distance in units of stellar radii. Always non-negative; the sign of the line-of-sight depth (transit vs. eclipse) is not encoded here. """ if isinstance(time, ndarray): return sep_v(time, tc, p, c, te) return _sep_s(time, tc, p, c, te)
@overload(sep, jit_options={'fastmath': True}, inline='always') def _sep_overload(time, tc, p, c, te=0.0): if _is_1d_array(time): def impl(time, tc, p, c, te=0.0): return sep_v(time, tc, p, c, te) return impl if isinstance(time, types.Float): def impl(time, tc, p, c, te=0.0): return _sep_s(time, tc, p, c, te) return impl return None