def test_compute_stats(data, with_units, with_err):
t, y, dy, params = data
y_unit = 1
if with_units:
y_unit = u.mag
t = t * u.day
y = y * u.mag
dy = dy * u.mag
params["period"] = params["period"] * u.day
params["duration"] = params["duration"] * u.day
params["transit_time"] = params["transit_time"] * u.day
params["depth"] = params["depth"] * u.mag
if not with_err:
dy = None
model = BoxLeastSquares(t, y, dy)
results = model.power(params["period"],
params["duration"],
oversample=1000)
stats = model.compute_stats(params["period"], params["duration"],
params["transit_time"])
# Test the calculated transit times
tt = params["period"] * np.arange(int(t.max() / params["period"]) + 1)
tt += params["transit_time"]
assert_quantity_allclose(tt, stats["transit_times"])
# Test that the other parameters are consistent with the periodogram
assert_allclose(stats["per_transit_count"], [9, 7, 7, 7, 8])
assert_quantity_allclose(np.sum(stats["per_transit_log_likelihood"]),
results["log_likelihood"])
assert_quantity_allclose(stats["depth"][0], results["depth"])
# Check the half period result
results_half = model.power(0.5 * params["period"],
params["duration"],
oversample=1000)
assert_quantity_allclose(stats["depth_half"][0], results_half["depth"])
# Skip the uncertainty tests when the input errors are None
if not with_err:
assert_quantity_allclose(stats["harmonic_amplitude"],
0.029945029964964204 * y_unit)
assert_quantity_allclose(stats["harmonic_delta_log_likelihood"],
-0.5875918155223113 * y_unit * y_unit)
return
assert_quantity_allclose(stats["harmonic_amplitude"],
0.033027988742275853 * y_unit)
assert_quantity_allclose(stats["harmonic_delta_log_likelihood"],
-12407.505922833765)
assert_quantity_allclose(stats["depth"][1], results["depth_err"])
assert_quantity_allclose(stats["depth_half"][1], results_half["depth_err"])
for f, k in zip((1.0, 1.0, 1.0, 0.0),
("depth", "depth_even", "depth_odd", "depth_phased")):
res = np.abs((stats[k][0] - f * params["depth"]) / stats[k][1])
assert res < 1, f'f={f}, k={k}, res={res}'
def test_compute_stats(data, with_units, with_err):
t, y, dy, params = data
y_unit = 1
if with_units:
y_unit = u.mag
t = t * u.day
y = y * u.mag
dy = dy * u.mag
params["period"] = params["period"] * u.day
params["duration"] = params["duration"] * u.day
params["transit_time"] = params["transit_time"] * u.day
params["depth"] = params["depth"] * u.mag
if not with_err:
dy = None
model = BoxLeastSquares(t, y, dy)
results = model.power(params["period"], params["duration"],
oversample=1000)
stats = model.compute_stats(params["period"], params["duration"],
params["transit_time"])
# Test the calculated transit times
tt = params["period"] * np.arange(int(t.max() / params["period"]) + 1)
tt += params["transit_time"]
assert_quantity_allclose(tt, stats["transit_times"])
# Test that the other parameters are consistent with the periodogram
assert_allclose(stats["per_transit_count"], np.array([9, 7, 7, 7, 8]))
assert_quantity_allclose(np.sum(stats["per_transit_log_likelihood"]),
results["log_likelihood"])
assert_quantity_allclose(stats["depth"][0], results["depth"])
# Check the half period result
results_half = model.power(0.5*params["period"], params["duration"],
oversample=1000)
assert_quantity_allclose(stats["depth_half"][0], results_half["depth"])
# Skip the uncertainty tests when the input errors are None
if not with_err:
assert_quantity_allclose(stats["harmonic_amplitude"],
0.029945029964964204 * y_unit)
assert_quantity_allclose(stats["harmonic_delta_log_likelihood"],
-0.5875918155223113 * y_unit * y_unit)
return
assert_quantity_allclose(stats["harmonic_amplitude"],
0.033027988742275853 * y_unit)
assert_quantity_allclose(stats["harmonic_delta_log_likelihood"],
-12407.505922833765)
assert_quantity_allclose(stats["depth"][1], results["depth_err"])
assert_quantity_allclose(stats["depth_half"][1], results_half["depth_err"])
for f, k in zip((1.0, 1.0, 1.0, 0.0),
("depth", "depth_even", "depth_odd", "depth_phased")):
assert np.abs((stats[k][0]-f*params["depth"]) / stats[k][1]) < 1.0
def test_absolute_times(data, timedelta):
# Make sure that we handle absolute times correctly. We also check that
# TimeDelta works properly when timedelta is True.
# The example data uses relative times
t, y, dy, params = data
# FIXME: There seems to be a numerical stability issue in that if we run
# the algorithm with the same values but offset in time, the transit_time
# is not offset by a fixed amount. To avoid this issue in this test, we
# make sure the first time is also the smallest so that internally the
# values of the relative time should be the same.
t[0] = 0.
# Add units
t = t * u.day
y = y * u.mag
dy = dy * u.mag
# We now construct a set of absolute times but keeping the rest the same.
start = Time('2019-05-04T12:34:56')
trel = TimeDelta(t) if timedelta else t
t = trel + start
# and we set up two instances of BoxLeastSquares, one with absolute and one
# with relative times.
bls1 = BoxLeastSquares(t, y, dy)
bls2 = BoxLeastSquares(trel, y, dy)
results1 = bls1.autopower(0.16 * u.day)
results2 = bls2.autopower(0.16 * u.day)
# All the results should match except transit time which should be
# absolute instead of relative in the first case.
for key in results1:
if key == 'transit_time':
assert_quantity_allclose((results1[key] - start).to(u.day), results2[key])
elif key == 'objective':
assert results1[key] == results2[key]
else:
assert_allclose(results1[key], results2[key])
# Check that model evaluation works fine
model1 = bls1.model(t, 0.2 * u.day, 0.05 * u.day, Time('2019-06-04T12:34:56'))
model2 = bls2.model(trel, 0.2 * u.day, 0.05 * u.day, TimeDelta(1 * u.day))
assert_quantity_allclose(model1, model2)
# Check model validation
with pytest.raises(TypeError) as exc:
bls1.model(t, 0.2 * u.day, 0.05 * u.day, 1 * u.day)
assert exc.value.args[0] == ('transit_time was provided as a relative time '
'but the BoxLeastSquares class was initialized '
'with absolute times.')
with pytest.raises(TypeError) as exc:
bls1.model(trel, 0.2 * u.day, 0.05 * u.day, Time('2019-06-04T12:34:56'))
assert exc.value.args[0] == ('t_model was provided as a relative time '
'but the BoxLeastSquares class was initialized '
'with absolute times.')
with pytest.raises(TypeError) as exc:
bls2.model(trel, 0.2 * u.day, 0.05 * u.day, Time('2019-06-04T12:34:56'))
assert exc.value.args[0] == ('transit_time was provided as an absolute time '
'but the BoxLeastSquares class was initialized '
'with relative times.')
with pytest.raises(TypeError) as exc:
bls2.model(t, 0.2 * u.day, 0.05 * u.day, 1 * u.day)
assert exc.value.args[0] == ('t_model was provided as an absolute time '
'but the BoxLeastSquares class was initialized '
'with relative times.')
# Check compute_stats
stats1 = bls1.compute_stats(0.2 * u.day, 0.05 * u.day, Time('2019-06-04T12:34:56'))
stats2 = bls2.compute_stats(0.2 * u.day, 0.05 * u.day, 1 * u.day)
for key in stats1:
if key == 'transit_times':
assert_quantity_allclose((stats1[key] - start).to(u.day), stats2[key], atol=1e-10 * u.day)
elif key.startswith('depth'):
for value1, value2 in zip(stats1[key], stats2[key]):
assert_quantity_allclose(value1, value2)
else:
assert_allclose(stats1[key], stats2[key])
# Check compute_stats validation
with pytest.raises(TypeError) as exc:
bls1.compute_stats(0.2 * u.day, 0.05 * u.day, 1 * u.day)
assert exc.value.args[0] == ('transit_time was provided as a relative time '
'but the BoxLeastSquares class was initialized '
'with absolute times.')
with pytest.raises(TypeError) as exc:
bls2.compute_stats(0.2 * u.day, 0.05 * u.day, Time('2019-06-04T12:34:56'))
assert exc.value.args[0] == ('transit_time was provided as an absolute time '
'but the BoxLeastSquares class was initialized '
'with relative times.')
# Check transit_mask
mask1 = bls1.transit_mask(t, 0.2 * u.day, 0.05 * u.day, Time('2019-06-04T12:34:56'))
mask2 = bls2.transit_mask(trel, 0.2 * u.day, 0.05 * u.day, 1 * u.day)
assert_equal(mask1, mask2)
# Check transit_mask validation
with pytest.raises(TypeError) as exc:
bls1.transit_mask(t, 0.2 * u.day, 0.05 * u.day, 1 * u.day)
assert exc.value.args[0] == ('transit_time was provided as a relative time '
'but the BoxLeastSquares class was initialized '
'with absolute times.')
with pytest.raises(TypeError) as exc:
bls1.transit_mask(trel, 0.2 * u.day, 0.05 * u.day, Time('2019-06-04T12:34:56'))
assert exc.value.args[0] == ('t was provided as a relative time '
'but the BoxLeastSquares class was initialized '
'with absolute times.')
with pytest.raises(TypeError) as exc:
bls2.transit_mask(trel, 0.2 * u.day, 0.05 * u.day, Time('2019-06-04T12:34:56'))
assert exc.value.args[0] == ('transit_time was provided as an absolute time '
'but the BoxLeastSquares class was initialized '
'with relative times.')
with pytest.raises(TypeError) as exc:
bls2.transit_mask(t, 0.2 * u.day, 0.05 * u.day, 1 * u.day)
assert exc.value.args[0] == ('t was provided as an absolute time '
'but the BoxLeastSquares class was initialized '
'with relative times.')