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"""test_adjoint_utils.py
Check various components of the adjoint solver codebase, like
filters, which may not need explicit gradient computation
(i.e. forward and adjoint runs).
"""
import meep as mp
try:
import meep.adjoint as mpa
except:
import adjoint as mpa
import unittest
from enum import Enum
import numpy as np
import parameterized
from autograd import numpy as npa
from autograd import tensor_jacobian_product
from utils import ApproxComparisonTestCase
_TOL = 1e-6 if mp.is_single_precision() else 1e-14
## ensure reproducible results
rng = np.random.RandomState(9861548)
class TestAdjointUtils(ApproxComparisonTestCase):
@parameterized.parameterized.expand(
[
("1.0_1.0_20_conic", 1.0, 1.0, 20, 0.24, mpa.conic_filter),
("1.0_1.0_23_conic", 1.0, 1.0, 23, 0.24, mpa.conic_filter),
("0.887_1.56_conic", 0.887, 1.56, 20, 0.24, mpa.conic_filter),
("0.887_1.56_conic", 0.887, 1.56, 31, 0.24, mpa.conic_filter),
("0.887_1.56_gaussian", 0.887, 1.56, 20, 0.24, mpa.gaussian_filter),
("0.887_1.56_cylindrical", 0.887, 1.56, 20, 0.24, mpa.cylindrical_filter),
]
)
def test_filter_offset(self, test_name, Lx, Ly, resolution, radius, filter_func):
"""ensure that the filters are indeed zero-phase"""
print("Testing ", test_name)
Nx, Ny = int(resolution * Lx), int(resolution * Ly)
x = np.random.rand(Nx, Ny)
x = x + np.fliplr(x)
x = x + np.flipud(x)
y = filter_func(x, radius, Lx, Ly, resolution)
self.assertClose(y, np.fliplr(y), epsilon=_TOL)
self.assertClose(y, np.flipud(y), epsilon=_TOL)
if __name__ == "__main__":
unittest.main()
|
