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use "is None" to check for default args

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numpy.any(numpy.equal(x, None)) is more general, because
`numpy.array(None) is not None`, but checking for that doesn't make much
sense if you're already type-checking
This commit is contained in:
Jan Petykiewicz 2022-10-04 17:27:44 -07:00
commit 4e240988c9
5 changed files with 25 additions and 25 deletions
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14
meanas/fdfd/waveguide_2d.py
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@ -239,7 +239,7 @@ def operator_e(
Returns:
Sparse matrix representation of the operator.
"""
if numpy.any(numpy.equal(mu, None)):
if mu is None:
mu = numpy.ones_like(epsilon)
Dfx, Dfy = deriv_forward(dxes[0])
@ -306,7 +306,7 @@ def operator_h(
Returns:
Sparse matrix representation of the operator.
"""
if numpy.any(numpy.equal(mu, None)):
if mu is None:
mu = numpy.ones_like(epsilon)
Dfx, Dfy = deriv_forward(dxes[0])
@ -513,7 +513,7 @@ def hxy2h(
Dfx, Dfy = deriv_forward(dxes[0])
hxy2hz = sparse.hstack((Dfx, Dfy)) / (1j * wavenumber)
if not numpy.any(numpy.equal(mu, None)):
if mu is not None:
mu_parts = numpy.split(mu, 3)
mu_xy = sparse.diags(numpy.hstack((mu_parts[0], mu_parts[1])))
mu_z_inv = sparse.diags(1 / mu_parts[2])
@ -547,7 +547,7 @@ def exy2e(
Dbx, Dby = deriv_back(dxes[1])
exy2ez = sparse.hstack((Dbx, Dby)) / (1j * wavenumber)
if not numpy.any(numpy.equal(epsilon, None)):
if epsilon is not None:
epsilon_parts = numpy.split(epsilon, 3)
epsilon_xy = sparse.diags(numpy.hstack((epsilon_parts[0], epsilon_parts[1])))
epsilon_z_inv = sparse.diags(1 / epsilon_parts[2])
@ -580,7 +580,7 @@ def e2h(
Sparse matrix representation of the operator.
"""
op = curl_e(wavenumber, dxes) / (-1j * omega)
if not numpy.any(numpy.equal(mu, None)):
if mu is not None:
op = sparse.diags(1 / mu) @ op
return op
@ -675,7 +675,7 @@ def h_err(
eps_inv = sparse.diags(1 / epsilon)
if numpy.any(numpy.equal(mu, None)):
if mu is None:
op = ce @ eps_inv @ ch @ h - omega ** 2 * h
else:
op = ce @ eps_inv @ ch @ h - omega ** 2 * (mu * h)
@ -708,7 +708,7 @@ def e_err(
ce = curl_e(wavenumber, dxes)
ch = curl_h(wavenumber, dxes)
if numpy.any(numpy.equal(mu, None)):
if mu is None:
op = ch @ ce @ e - omega ** 2 * (epsilon * e)
else:
mu_inv = sparse.diags(1 / mu)