# -*- coding: utf-8 -*- from . import curvature from . import diff from . import utils import numpy as np def calc_expansion(x, z, metric, curv, surf, direction = 1): """ Calculate expansion of null geodesics on a sequence of surfaces [1]. The surfaces are specified as level surfaces of F(r, θ) = r - h(θ). [1] Alcubierre (2008): Introduction to 3+1 Numerical Relativity, chapter 6.7, specifically equation (6.7.13). :param array_like x: 1D array of x coordinates. :param array_like z: 1D array of z-coordinates. :param array_like metric: 4D array of spatial metric values at the grid formed by x and z. metric[i, j, k, l] is the ijth component of the metric at the point (X=x[l], Z=z[k]). :param array_like curv: values of the extrinsic curvature, otherwise same as metric. :param callable surf: A callable that specifies the surfaces. Accepts an array of θ and returns the array of correponding h. :param int direction: Values of 1/-1 specify that the expansion of outgoing or ingoing geodesics is to be computed. :rtype: array_like, shape (z.shape[0], x.shape[0]) :return: Expansion values at the grid formed from x and z. """ dX = [x[1] - x[0], 0, z[1] - z[0]] X, Z = np.meshgrid(x, z) R = np.sqrt(X ** 2 + Z ** 2) Theta = np.where(R > 1e-8, np.arccos(Z / R), 0.0) metric_u = utils.matrix_invert(metric) Gamma = curvature.calc_christoffel(x, z, metric) trK = np.einsum('ij...,ij...', metric_u, curv) F = R[:] for i in range(Theta.shape[0]): F[i] -= surf.eval(Theta[i]) dF = np.empty((3,) + F.shape) dF[0] = diff.fd4(F, 1, dX[0]) dF[1] = 0.0 dF[2] = diff.fd4(F, 0, dX[2]) s_l = direction * dF[:] s_u = np.einsum('ij...,j...->i...', metric_u, s_l) s_u /= np.sqrt(np.einsum('ij...,i...,j...', metric, s_u, s_u)) ds_u = np.zeros((3,) + s_u.shape) for i in range(3): for j in range(3): if i == 1 or j == 1: continue diff_dir = 1 if (i == 0) else 0 ds_u[i, j] = diff.fd4(s_u[j], diff_dir, dX[i]) ds_u[1, 1] = np.where(np.abs(X) > 1e-8, s_u[0] / X, ds_u[0, 0]) Div_s_u = np.einsum('ii...', ds_u) + np.einsum('iki...,k...', Gamma, s_u) H = Div_s_u - trK + np.einsum('ij...,i...,j...', curv, s_u, s_u) return H