Style fixes
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@ -13,7 +13,7 @@ from . import dx_lists_t, field_t
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__author__ = 'Jan Petykiewicz'
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functional_matrix = Callable[[List[numpy.ndarray]], List[numpy.ndarray]]
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functional_matrix = Callable[[field_t], field_t]
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def curl_h(dxes: dx_lists_t) -> functional_matrix:
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@ -28,11 +28,11 @@ def curl_h(dxes: dx_lists_t) -> functional_matrix:
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def dH(f, ax):
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return (f - numpy.roll(f, 1, axis=ax)) / dxyz_b[ax]
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def ch_fun(H: List[numpy.ndarray]) -> List[numpy.ndarray]:
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E = [dH(H[2], 1) - dH(H[1], 2),
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dH(H[0], 2) - dH(H[2], 0),
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dH(H[1], 0) - dH(H[0], 1)]
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return E
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def ch_fun(h: field_t) -> field_t:
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e = [dh(h[2], 1) - dh(h[1], 2),
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dh(h[0], 2) - dh(h[2], 0),
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dh(h[1], 0) - dh(h[0], 1)]
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return e
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return ch_fun
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@ -49,11 +49,11 @@ def curl_e(dxes: dx_lists_t) -> functional_matrix:
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def dE(f, ax):
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return (numpy.roll(f, -1, axis=ax) - f) / dxyz_a[ax]
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def ce_fun(E: List[numpy.ndarray]) -> List[numpy.ndarray]:
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H = [dE(E[2], 1) - dE(E[1], 2),
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dE(E[0], 2) - dE(E[2], 0),
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dE(E[1], 0) - dE(E[0], 1)]
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return H
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def ce_fun(e: field_t) -> field_t:
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h = [de(e[2], 1) - de(e[1], 2),
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de(e[0], 2) - de(e[2], 0),
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de(e[1], 0) - de(e[0], 1)]
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return h
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return ce_fun
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@ -77,13 +77,13 @@ def e_full(omega: complex,
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ch = curl_h(dxes)
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ce = curl_e(dxes)
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def op_1(E):
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curls = ch(ce(E))
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return [c - omega ** 2 * e * x for c, e, x in zip(curls, epsilon, E)]
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def op_1(e):
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curls = ch(ce(e))
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return [c - omega ** 2 * e * x for c, e, x in zip(curls, epsilon, e)]
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def op_mu(E):
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curls = ch([m * y for m, y in zip(mu, ce(E))])
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return [c - omega ** 2 * e * x for c, e, x in zip(curls, epsilon, E)]
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def op_mu(e):
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curls = ch([m * y for m, y in zip(mu, ce(e))])
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return [c - omega ** 2 * p * x for c, p, x in zip(curls, epsilon, e)]
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if numpy.any(numpy.equal(mu, None)):
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return op_1
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@ -108,13 +108,13 @@ def eh_full(omega: complex,
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ch = curl_h(dxes)
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ce = curl_e(dxes)
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def op_1(E, H):
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return ([c - 1j * omega * e * x for c, e, x in zip(ch(H), epsilon, E)],
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[c + 1j * omega * y for c, y in zip(ce(E), H)])
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def op_1(e, h):
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return ([c - 1j * omega * p * x for c, p, x in zip(ch(h), epsilon, e)],
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[c + 1j * omega * y for c, y in zip(ce(e), h)])
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def op_mu(E, H):
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return ([c - 1j * omega * e * x for c, e, x in zip(ch(H), epsilon, E)],
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[c + 1j * omega * m * y for c, m, y in zip(ce(E), mu, H)])
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def op_mu(e, h):
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return ([c - 1j * omega * p * x for c, p, x in zip(ch(h), epsilon, e)],
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[c + 1j * omega * m * y for c, m, y in zip(ce(e), mu, h)])
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if numpy.any(numpy.equal(mu, None)):
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return op_1
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@ -137,11 +137,11 @@ def e2h(omega: complex,
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"""
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A2 = curl_e(dxes)
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def e2h_1_1(E):
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return [y / (-1j * omega) for y in A2(E)]
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def e2h_1_1(e):
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return [y / (-1j * omega) for y in A2(e)]
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def e2h_mu(E):
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return [y / (-1j * omega * m) for y, m in zip(A2(E), mu)]
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def e2h_mu(e):
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return [y / (-1j * omega * m) for y, m in zip(A2(e), mu)]
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if numpy.any(numpy.equal(mu, None)):
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return e2h_1_1
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