Deepak Mallubhotla
9c3f5aa286
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84 lines
1.6 KiB
Python
84 lines
1.6 KiB
Python
import numpy
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from tantri.dipoles import (
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DipoleTO,
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DipoleTimeSeries,
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DotPosition,
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DipoleMeasurementType,
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)
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import logging
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_logger = logging.getLogger(__name__)
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def test_multiple_apsd(snapshot):
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dot_name = "dot1"
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num_series_to_create = 100
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num_ts_points = 1000
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delta_t = 0.01
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rng = numpy.random.default_rng(1234)
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dots = [DotPosition(numpy.array([0, 0, 0]), dot_name)]
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d1 = DipoleTO(
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numpy.array([0, 0, 10]),
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numpy.array([5, 3, 2]),
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15,
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)
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ts_gen = DipoleTimeSeries(
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[d1],
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dots,
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DipoleMeasurementType.ELECTRIC_POTENTIAL,
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delta_t,
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rng_to_use=rng,
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)
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estimated_psd = ts_gen.generate_average_apsd(num_series_to_create, num_ts_points)
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assert estimated_psd == snapshot
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def test_multiple_apsd_compare_analytic():
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dot_name = "dot1"
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num_series_to_create = 500
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num_ts_points = 10000
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delta_t = 0.001
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rng = numpy.random.default_rng(1234)
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dots = [DotPosition(numpy.array([0, 0, 0]), dot_name)]
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d1 = DipoleTO(
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numpy.array([0, 0, 10]),
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numpy.array([5, 3, 2]),
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15,
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)
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ts_gen = DipoleTimeSeries(
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[d1],
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dots,
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DipoleMeasurementType.ELECTRIC_POTENTIAL,
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delta_t,
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rng_to_use=rng,
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)
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def s_analytic_potential(f: float, dot: DotPosition, dipole: DipoleTO):
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g = dipole.w / ((numpy.pi * f) ** 2 + dipole.w**2)
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rdiff = dot.r - dipole.s
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return 2 * g * ((rdiff.dot(dipole.p) / (numpy.linalg.norm(rdiff) ** 3)) ** 2)
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estimated_psd = ts_gen.generate_average_apsd(num_series_to_create, num_ts_points)
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_logger.warning(estimated_psd)
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analytic = numpy.array(
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[s_analytic_potential(f, dots[0], d1) for f in estimated_psd.freqs]
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)
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numpy.testing.assert_allclose(
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estimated_psd.psd_dict[dot_name], analytic, rtol=1.5, atol=1e-7
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)
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