refactor: removes redundant calculation and uses pdme

This commit is contained in:
2024-05-02 23:12:21 -05:00
parent df4d0b5d15
commit 62bd63bf9b
3 changed files with 138 additions and 97 deletions

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import pdme.measurement
import pdme.measurement.input_types
from pdme.model import (
LogSpacedRandomCountMultipleDipoleFixedMagnitudeModel,
LogSpacedRandomCountMultipleDipoleFixedMagnitudeXYModel,
LogSpacedRandomCountMultipleDipoleFixedMagnitudeFixedOrientationModel,
)
import deepdog.direct_monte_carlo.dmc_filters
import numpy.random
import numpy.testing
import logging
_logger = logging.getLogger(__name__)
def fixed_z_model_func(
xmin,
xmax,
ymin,
ymax,
zmin,
zmax,
wexp_min,
wexp_max,
pfixed,
n_max,
prob_occupancy,
):
return LogSpacedRandomCountMultipleDipoleFixedMagnitudeFixedOrientationModel(
xmin,
xmax,
ymin,
ymax,
zmin,
zmax,
wexp_min,
wexp_max,
pfixed,
0,
0,
n_max,
prob_occupancy,
)
def get_model(orientation):
model_funcs = {
"fixedz": fixed_z_model_func,
"free": LogSpacedRandomCountMultipleDipoleFixedMagnitudeModel,
"fixedxy": LogSpacedRandomCountMultipleDipoleFixedMagnitudeXYModel,
}
model = model_funcs[orientation](
-10,
10,
-17.5,
17.5,
5,
7.5,
-5,
6.5,
10**3,
2,
0.99999999,
)
model.n = 2
model.rng = numpy.random.default_rng(1234)
return (
f"connors_geom-5height-orientation_{orientation}-pfixexp_{3}-dipole_count_{2}",
model,
)
def test_electric_field_x_dmc_filter():
dipoles_raw = [
[(1, 2, 3), (4, 5, 6), 1],
[(-1, 5, 2), (6, 5, 4), 10],
]
dipoles = [
pdme.measurement.OscillatingDipole(numpy.array(d[0]), numpy.array(d[1]), d[2])
for d in dipoles_raw
]
_logger.debug(f"dipoles: {dipoles}")
dot_inputs_raw = [
([-1, -1, 0], 1),
([-1, -1, 0], 2),
([-1, -1, 0], 3),
([-1, -1, 0], 4),
]
dot_inputs_array = pdme.measurement.input_types.dot_inputs_to_array(dot_inputs_raw)
_logger.debug(f"dot_inputs_array: {dot_inputs_array}")
arrangement = pdme.measurement.OscillatingDipoleArrangement(dipoles)
measurements = []
for input in dot_inputs_raw:
ex = sum(
[
dipole.s_electric_fieldx_at_position(*input)
for dipole in arrangement.dipoles
]
)
ex_low = ex * 0.5
ex_high = ex * 1.5
meas = pdme.measurement.DotRangeMeasurement(ex_low, ex_high, input[0], input[1])
measurements.append(meas)
filter = deepdog.direct_monte_carlo.dmc_filters.SingleDotSpinQubitFrequencyFilter(
measurements
)
samples = numpy.array(
[
[
[1, 2, 3, 4, 5, 6, 1],
[-1, 5, 2, 6, 5, 4, 10],
],
[
[10, 20, 30, 40, 50, 60, 1],
[-1, 5, 2, 6, 5, 4, 1],
],
[
[1, 1, 1, 1, 1, 1, 1],
[2, 2, 2, 2, 2, 2, 1],
],
]
)
expected = samples[
0:1
] # only expect to see the first guy, because that's what generated our thing
filtered = filter.filter_samples(samples)
assert len(filtered) != len(samples), "Should have filtered some out!"
numpy.testing.assert_array_equal(
filtered, expected, "The filter should have only returned the first one"
)