forked from jan/fdfd_tools
		
	Style fixes
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				| @ -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 | ||||
|  | ||||
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