rename search_direction to direction
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@ -68,7 +68,7 @@ This module contains functions for generating and solving the
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k, f = find_k(frequency=1/1550,
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tolerance=(1/1550 - 1/1551),
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search_direction=[1, 0, 0],
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direction=[1, 0, 0],
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G_matrix=recip_lattice,
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epsilon=epsilon,
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band=0)
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@ -369,7 +369,7 @@ def eigsolve(num_modes: int,
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def find_k(frequency: float,
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tolerance: float,
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search_direction: numpy.ndarray,
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direction: numpy.ndarray,
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G_matrix: numpy.ndarray,
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epsilon: field_t,
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mu: field_t = None,
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@ -380,7 +380,7 @@ def find_k(frequency: float,
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:param frequency: Target frequency.
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:param tolerance: Target frequency tolerance.
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:param search_direction: k-vector direction to search along.
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:param direction: k-vector direction to search along.
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:param G_matrix: 3x3 matrix, with reciprocal lattice vectors as columns.
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:param epsilon: Dielectric constant distribution for the simulation.
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All fields are sampled at cell centers (i.e., NOT Yee-gridded)
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@ -390,10 +390,10 @@ def find_k(frequency: float,
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return: (k, actual_frequency) The found k-vector and its frequency
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"""
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search_direction = numpy.array(search_direction) / norm(search_direction)
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direction = numpy.array(direction) / norm(direction)
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def get_f(k0_mag: float, band: int = 0):
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k0 = search_direction * k0_mag
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k0 = direction * k0_mag
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n, _v = eigsolve(band + 1, k0, G_matrix=G_matrix, epsilon=epsilon)
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f = numpy.sqrt(numpy.abs(numpy.real(n[band])))
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return f
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@ -401,6 +401,6 @@ def find_k(frequency: float,
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res = scipy.optimize.minimize_scalar(lambda x: abs(get_f(x, band) - frequency), 0.25,
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method='Bounded', bounds=(0, 0.5),
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options={'xatol': abs(tolerance)})
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return res.x * search_direction, res.fun + frequency
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return res.x * direction, res.fun + frequency
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