From 05d2557f6fa2f554def2586b4c21f09b2d9e0e33 Mon Sep 17 00:00:00 2001 From: jan Date: Sun, 3 Jul 2016 01:20:51 -0700 Subject: [PATCH] Style fixes --- fdfd_tools/functional.py | 54 ++++++++++++++++++++-------------------- 1 file changed, 27 insertions(+), 27 deletions(-) diff --git a/fdfd_tools/functional.py b/fdfd_tools/functional.py index 4d573db..1922964 100644 --- a/fdfd_tools/functional.py +++ b/fdfd_tools/functional.py @@ -13,7 +13,7 @@ from . import dx_lists_t, field_t __author__ = 'Jan Petykiewicz' -functional_matrix = Callable[[List[numpy.ndarray]], List[numpy.ndarray]] +functional_matrix = Callable[[field_t], field_t] def curl_h(dxes: dx_lists_t) -> functional_matrix: @@ -28,11 +28,11 @@ def curl_h(dxes: dx_lists_t) -> functional_matrix: def dH(f, ax): return (f - numpy.roll(f, 1, axis=ax)) / dxyz_b[ax] - def ch_fun(H: List[numpy.ndarray]) -> List[numpy.ndarray]: - E = [dH(H[2], 1) - dH(H[1], 2), - dH(H[0], 2) - dH(H[2], 0), - dH(H[1], 0) - dH(H[0], 1)] - return E + def ch_fun(h: field_t) -> field_t: + e = [dh(h[2], 1) - dh(h[1], 2), + dh(h[0], 2) - dh(h[2], 0), + dh(h[1], 0) - dh(h[0], 1)] + return e return ch_fun @@ -49,11 +49,11 @@ def curl_e(dxes: dx_lists_t) -> functional_matrix: def dE(f, ax): return (numpy.roll(f, -1, axis=ax) - f) / dxyz_a[ax] - def ce_fun(E: List[numpy.ndarray]) -> List[numpy.ndarray]: - H = [dE(E[2], 1) - dE(E[1], 2), - dE(E[0], 2) - dE(E[2], 0), - dE(E[1], 0) - dE(E[0], 1)] - return H + def ce_fun(e: field_t) -> field_t: + h = [de(e[2], 1) - de(e[1], 2), + de(e[0], 2) - de(e[2], 0), + de(e[1], 0) - de(e[0], 1)] + return h return ce_fun @@ -77,13 +77,13 @@ def e_full(omega: complex, ch = curl_h(dxes) ce = curl_e(dxes) - def op_1(E): - curls = ch(ce(E)) - return [c - omega ** 2 * e * x for c, e, x in zip(curls, epsilon, E)] + def op_1(e): + curls = ch(ce(e)) + return [c - omega ** 2 * e * x for c, e, x in zip(curls, epsilon, e)] - def op_mu(E): - curls = ch([m * y for m, y in zip(mu, ce(E))]) - return [c - omega ** 2 * e * x for c, e, x in zip(curls, epsilon, E)] + def op_mu(e): + curls = ch([m * y for m, y in zip(mu, ce(e))]) + return [c - omega ** 2 * p * x for c, p, x in zip(curls, epsilon, e)] if numpy.any(numpy.equal(mu, None)): return op_1 @@ -108,13 +108,13 @@ def eh_full(omega: complex, ch = curl_h(dxes) ce = curl_e(dxes) - def op_1(E, H): - return ([c - 1j * omega * e * x for c, e, x in zip(ch(H), epsilon, E)], - [c + 1j * omega * y for c, y in zip(ce(E), H)]) + def op_1(e, h): + return ([c - 1j * omega * p * x for c, p, x in zip(ch(h), epsilon, e)], + [c + 1j * omega * y for c, y in zip(ce(e), h)]) - def op_mu(E, H): - return ([c - 1j * omega * e * x for c, e, x in zip(ch(H), epsilon, E)], - [c + 1j * omega * m * y for c, m, y in zip(ce(E), mu, H)]) + def op_mu(e, h): + return ([c - 1j * omega * p * x for c, p, x in zip(ch(h), epsilon, e)], + [c + 1j * omega * m * y for c, m, y in zip(ce(e), mu, h)]) if numpy.any(numpy.equal(mu, None)): return op_1 @@ -137,11 +137,11 @@ def e2h(omega: complex, """ A2 = curl_e(dxes) - def e2h_1_1(E): - return [y / (-1j * omega) for y in A2(E)] + def e2h_1_1(e): + return [y / (-1j * omega) for y in A2(e)] - def e2h_mu(E): - return [y / (-1j * omega * m) for y, m in zip(A2(E), mu)] + def e2h_mu(e): + return [y / (-1j * omega * m) for y, m in zip(A2(e), mu)] if numpy.any(numpy.equal(mu, None)): return e2h_1_1