def test_probably_not_a_transient(self):
"""
No source at 250MHz, but we detect a source at 50MHz.
Not necessarily a transient.
Should trivially ignore 250MHz data when looking at a new 50MHz source.
"""
img_params = self.img_params
img0 = img_params[0]
# This time around, we just manually exclude the steady src from
# the first image detections.
steady_low_freq_src = MockSource(
example_extractedsource_tuple(ra=img_params[0]['centre_ra'],
dec=img_params[0]['centre_decl']
),
lightcurve=defaultdict(lambda :self.always_detectable_flux)
)
# Insert first image, no sources.
tkp.db.Image(data=img_params[0],dataset=self.dataset)
# Now set up second image.
img1 = tkp.db.Image(data=img_params[1],dataset=self.dataset)
xtr = steady_low_freq_src.simulate_extraction(img1,
extraction_type='blind')
insert_extracted_sources(img1._id, [xtr], 'blind')
associate_extracted_sources(img1._id, deRuiter_r, self.new_source_sigma_margin)
transients = get_newsources_for_dataset(self.dataset.id)
# Should have no marked transients
self.assertEqual(len(transients), 0)
def test_probably_not_a_transient(self):
"""
No source at 250MHz, but we detect a source at 50MHz.
Not necessarily a transient.
Should trivially ignore 250MHz data when looking at a new 50MHz source.
"""
img_params = self.img_params
img0 = img_params[0]
# This time around, we just manually exclude the steady src from
# the first image detections.
steady_low_freq_src = MockSource(
example_extractedsource_tuple(ra=img_params[0]['centre_ra'],
dec=img_params[0]['centre_decl']),
lightcurve=defaultdict(lambda: self.always_detectable_flux))
# Insert first image, no sources.
tkp.db.Image(data=img_params[0], dataset=self.dataset)
# Now set up second image.
img1 = tkp.db.Image(data=img_params[1], dataset=self.dataset)
xtr = steady_low_freq_src.simulate_extraction(img1,
extraction_type='blind')
insert_extracted_sources(img1._id, [xtr], 'blind')
associate_extracted_sources(img1._id, deRuiter_r,
self.new_source_sigma_margin)
transients = get_newsources_for_dataset(self.dataset.id)
# Should have no marked transients
self.assertEqual(len(transients), 0)
def test_marginal_transient(self):
"""
( flux1 > (rms_min0*(det0 + margin) )
but ( flux1 < (rms_max0*(det0 + margin) )
--> Possible transient
If it was in a region of rms_min, we would (almost certainly) have seen
it in the first image. So new source --> Possible transient.
But if it was in a region of rms_max, then perhaps we would have missed
it. In which case, new source --> Just seeing deeper.
Note that if we are tiling overlapping images, then the first time
a field is processed with image-centre at the edge of the old field,
we may get a bunch of unhelpful 'possible transients'.
Furthermore, this will pick up fluctuating sources near the
image-margins even with a fixed field of view.
But without a more complex store of image-rms-per-position, we cannot
do better.
Hopefully we can use a 'distance from centre' feature to separate out
the good and bad candidates in this case.
"""
img_params = self.img_params
#Must pick flux value carefully to fire correct logic branch:
marginal_transient_flux = self.reliably_detected_at_image_centre_flux
marginal_transient = MockSource(
example_extractedsource_tuple(ra=img_params[0]['centre_ra'],
dec=img_params[0]['centre_decl']),
lightcurve={img_params[1]['taustart_ts'] : marginal_transient_flux}
)
#First, check that we've set up the test correctly:
rms_min0 = img_params[0]['rms_min']
rms_max0 = img_params[0]['rms_max']
det0 = img_params[0]['detection_thresh']
self.assertTrue(marginal_transient_flux <
rms_max0*(det0 + self.new_source_sigma_margin ) )
self.assertTrue(marginal_transient_flux >
rms_min0*(det0 + self.new_source_sigma_margin ) )
for pars in self.img_params:
img = tkp.db.Image(data=pars,dataset=self.dataset)
xtr = marginal_transient.simulate_extraction(img,
extraction_type='blind')
if xtr is not None:
img.insert_extracted_sources([xtr],'blind')
img.associate_extracted_sources(deRuiter_r, self.new_source_sigma_margin)
newsources = get_newsources_for_dataset(self.dataset.id)
#Should have one 'possible' transient
self.assertEqual(len(newsources),1)
self.assertTrue(
newsources[0]['low_thresh_sigma'] > self.new_source_sigma_margin)
self.assertTrue(
newsources[0]['high_thresh_sigma'] < self.new_source_sigma_margin)
def test_probably_not_a_transient(self):
"""
( flux1 < (rms_min0*(det0 + margin) )
--> Probably not a transient
NB even if
avg_source_flux == rms_min0*det0 + epsilon
we might not detect it in the
first image, due to noise fluctuations. So we provide the
user-tunable marginal_detection_thresh, to ignore these 'noise'
transients.
"""
img_params = self.img_params
img0 = img_params[0]
marginal_steady_src_flux = self.barely_detectable_flux
# This time around, we just manually exclude the steady src from
# the first image detections.
marginal_steady_src = MockSource(
example_extractedsource_tuple(ra=img_params[0]['centre_ra'],
dec=img_params[0]['centre_decl']
),
lightcurve=defaultdict(lambda :marginal_steady_src_flux)
)
# First, check that we've set up the test correctly
rms_min0 = img_params[0]['rms_min']
det0 = img_params[0]['detection_thresh']
self.assertTrue(marginal_steady_src_flux <
rms_min0 * (det0 + self.new_source_sigma_margin))
# Insert first image, no sources.
tkp.db.Image(data=img_params[0], dataset=self.dataset)
# Now set up second image.
img1 = tkp.db.Image(data=img_params[1], dataset=self.dataset)
xtr = marginal_steady_src.simulate_extraction(img1,
extraction_type='blind')
insert_extracted_sources(img1._id, [xtr], 'blind')
associate_extracted_sources(img1._id, deRuiter_r, self.new_source_sigma_margin)
newsources = get_newsources_for_dataset(self.dataset.id)
# Should have no flagged new sources
self.assertEqual(len(newsources), 0)
def test_probably_not_a_transient(self):
"""
( flux1 < (rms_min0*(det0 + margin) )
--> Probably not a transient
NB even if
avg_source_flux == rms_min0*det0 + epsilon
we might not detect it in the
first image, due to noise fluctuations. So we provide the
user-tunable marginal_detection_thresh, to ignore these 'noise'
transients.
"""
img_params = self.img_params
img0 = img_params[0]
marginal_steady_src_flux = self.barely_detectable_flux
# This time around, we just manually exclude the steady src from
# the first image detections.
marginal_steady_src = MockSource(
example_extractedsource_tuple(ra=img_params[0]['centre_ra'],
dec=img_params[0]['centre_decl']
),
lightcurve=defaultdict(lambda :marginal_steady_src_flux)
)
#First, check that we've set up the test correctly:
rms_min0 = img_params[0]['rms_min']
det0 = img_params[0]['detection_thresh']
self.assertTrue(marginal_steady_src_flux <
rms_min0*(det0 + self.new_source_sigma_margin ) )
#Insert first image, no sources.
tkp.db.Image(data=img_params[0],dataset=self.dataset)
#Now set up second image.
img1 = tkp.db.Image(data=img_params[1],dataset=self.dataset)
xtr = marginal_steady_src.simulate_extraction(img1,
extraction_type='blind')
img1.insert_extracted_sources([xtr],'blind')
img1.associate_extracted_sources(deRuiter_r, self.new_source_sigma_margin)
newsources = get_newsources_for_dataset(self.dataset.id)
#Should have no flagged new sources
self.assertEqual(len(newsources),0)
def test_certain_transient(self):
"""
flux1 > (rms_max0*(det0+margin)
--> Definite transient
Nice and bright, must be new - mark it definite transient.
"""
img_params = self.img_params
bright_transient = MockSource(example_extractedsource_tuple(
ra=img_params[0]['centre_ra'], dec=img_params[0]['centre_decl']),
lightcurve={
img_params[1]['taustart_ts']:
self.always_detectable_flux
})
#First, check that we've set up the test correctly:
rms_max0 = img_params[0]['rms_max']
det0 = img_params[0]['detection_thresh']
self.assertTrue(bright_transient.lightcurve.values()[0] > rms_max0 *
(det0 + self.new_source_sigma_margin))
for pars in self.img_params:
img = tkp.db.Image(data=pars, dataset=self.dataset)
xtr = bright_transient.simulate_extraction(img,
extraction_type='blind')
if xtr is not None:
insert_extracted_sources(img._id, [xtr], 'blind')
associate_extracted_sources(img._id, deRuiter_r,
self.new_source_sigma_margin)
newsources = get_newsources_for_dataset(self.dataset.id)
#Should have one 'definite' transient
self.assertEqual(len(newsources), 1)
self.assertTrue(
newsources[0]['low_thresh_sigma'] > self.new_source_sigma_margin)
self.assertTrue(
newsources[0]['high_thresh_sigma'] > self.new_source_sigma_margin)
self.assertTrue(newsources[0]['low_thresh_sigma'] > newsources[0]
['high_thresh_sigma'])
def test_certain_transient(self):
"""
flux1 > (rms_max0*(det0+margin)
--> Definite transient
Nice and bright, must be new - mark it definite transient.
"""
img_params = self.img_params
bright_transient = MockSource(
example_extractedsource_tuple(ra=img_params[0]['centre_ra'],
dec=img_params[0]['centre_decl']),
lightcurve={img_params[1]['taustart_ts']:
self.always_detectable_flux}
)
#First, check that we've set up the test correctly:
rms_max0 = img_params[0]['rms_max']
det0 = img_params[0]['detection_thresh']
self.assertTrue(bright_transient.lightcurve.values()[0] >
rms_max0*(det0 + self.new_source_sigma_margin ) )
for pars in self.img_params:
img = tkp.db.Image(data=pars,dataset=self.dataset)
xtr = bright_transient.simulate_extraction(img,
extraction_type='blind')
if xtr is not None:
insert_extracted_sources(img._id, [xtr], 'blind')
associate_extracted_sources(img._id, deRuiter_r, self.new_source_sigma_margin)
newsources = get_newsources_for_dataset(self.dataset.id)
#Should have one 'definite' transient
self.assertEqual(len(newsources),1)
self.assertTrue(
newsources[0]['low_thresh_sigma'] > self.new_source_sigma_margin)
self.assertTrue(
newsources[0]['high_thresh_sigma'] > self.new_source_sigma_margin)
self.assertTrue(
newsources[0]['low_thresh_sigma'] >
newsources[0]['high_thresh_sigma'])
