Add PEC, PMC options for E, H wave operators
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@ -45,7 +45,8 @@ __author__ = 'Jan Petykiewicz'
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def e_full(omega: complex,
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dxes: dx_lists_t,
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epsilon: vfield_t,
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mu: vfield_t = None
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mu: vfield_t = None,
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pec: vfield_t = None,
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) -> sparse.spmatrix:
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"""
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Wave operator del x (1/mu * del x) - omega**2 * epsilon, for use with E-field,
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@ -57,19 +58,28 @@ def e_full(omega: complex,
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:param omega: Angular frequency of the simulation
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:param dxes: Grid parameters [dx_e, dx_h] as described in fdfd_tools.operators header
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:param epsilon: Vectorized dielectric constant
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:param mu: Vectorized magnetic permeability (default 1 everywhere)..
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:param mu: Vectorized magnetic permeability (default 1 everywhere).
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:param pec: Vectorized mask specifying PEC cells. Any cells where pec != 0 are interpreted
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as containing a perfect electrical conductor (PEC).
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:return: Sparse matrix containing the wave operator
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"""
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ce = curl_e(dxes)
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ch = curl_h(dxes)
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e = sparse.diags(epsilon)
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ev = epsilon
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if numpy.any(numpy.equal(pec, None)):
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pm = sparse.eye(epsilon.size)
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else:
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pm = sparse.diags(numpy.where(pec, 0, 1)) # Set pm to (not PEC)
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ev = numpy.where(pec, 1.0, ev) # Set epsilon to 1 at PEC
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e = sparse.diags(ev)
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if numpy.any(numpy.equal(mu, None)):
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m_div = sparse.eye(epsilon.size)
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else:
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m_div = sparse.diags(1 / mu)
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op = ch @ m_div @ ce - omega**2 * e
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op = pm @ ch @ m_div @ ce @ pm - omega**2 * e
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return op
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@ -99,7 +109,8 @@ def e_full_preconditioners(dxes: dx_lists_t
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def h_full(omega: complex,
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dxes: dx_lists_t,
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epsilon: vfield_t,
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mu: vfield_t = None
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mu: vfield_t = None,
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pmc: vfield_t = None,
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) -> sparse.spmatrix:
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"""
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Wave operator del x (1/epsilon * del x) - omega**2 * mu, for use with H-field,
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@ -110,18 +121,28 @@ def h_full(omega: complex,
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:param dxes: Grid parameters [dx_e, dx_h] as described in fdfd_tools.operators header
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:param epsilon: Vectorized dielectric constant
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:param mu: Vectorized magnetic permeability (default 1 everywhere)
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:param pmc: Vectorized mask specifying PMC cells. Any cells where pmc != 0 are interpreted
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as containing a perfect magnetic conductor (PMC).
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:return: Sparse matrix containing the wave operator
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"""
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ec = curl_e(dxes)
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hc = curl_h(dxes)
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e_div = sparse.diags(1 / epsilon)
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if numpy.any(numpy.equal(mu, None)):
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m = sparse.eye(epsilon.size)
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if mu is None:
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mv = numpy.ones_like(epsilon)
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else:
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m = sparse.diags(mu)
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mv = mu
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A = ec @ e_div @ hc - omega**2 * m
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if numpy.any(numpy.equal(pmc, None)):
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pe = sparse.eye(epsilon.size)
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else:
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pe = sparse.diags(numpy.where(pmc, 0, 1)) # Set pe to (not PMC)
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mv = numpy.where(pmc, 1.0, mv) # Set mu to 1 at PMC
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e_div = sparse.diags(1 / epsilon)
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m = sparse.diags(mv)
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A = pe @ ec @ e_div @ hc @ pe - omega**2 * m
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return A
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