def test_median(self):
if Database().engine == "monetdb":
qry = """
SELECT sys.median(id) as median_id
,sys.median(rms_max) as median_rms_max
FROM image
WHERE dataset = %(dataset_id)s
"""
else:
qry = """
SELECT median(id) as median_id
,median(rms_max) as median_rms_max
FROM image
WHERE dataset = %(dataset_id)s
"""
cursor = execute(qry, {"dataset_id": self.dataset.id})
results = db_subs.get_db_rows_as_dicts(cursor)
# self.assertAlmostEqual(results[0]['median_id'], median(self.image_ids))
self.assertAlmostEqual(results[0]["median_rms_max"], median([p["rms_max"] for p in self.im_params]))
def test_median(self):
if Database().engine == 'monetdb':
qry = ("""
SELECT sys.median(id) as median_id
,sys.median(rms_max) as median_rms_max
FROM image
WHERE dataset = %(dataset_id)s
""")
else:
qry = ("""
SELECT median(id) as median_id
,median(rms_max) as median_rms_max
FROM image
WHERE dataset = %(dataset_id)s
""")
cursor = execute(qry, {'dataset_id': self.dataset.id})
results = db_subs.get_db_rows_as_dicts(cursor)
# self.assertAlmostEqual(results[0]['median_id'], median(self.image_ids))
self.assertAlmostEqual(results[0]['median_rms_max'],
median([p['rms_max'] for p in self.im_params]))
def test_one2one_flux_infinite_error(self):
dataset = tkp.db.DataSet(database=self.database,
data={'description': 'flux test set: 1-1'})
n_images = 3
im_params = db_subs.generate_timespaced_dbimages_data(n_images)
src_list = []
src = db_subs.example_extractedsource_tuple()
src0 = src._replace(flux=2.0)
src_list.append(src0)
src1 = src._replace(flux=2.5)
src_list.append(src1)
src2 = src._replace(flux=0.0001,
flux_err=float('inf'),
peak=0.0001,
peak_err=float('inf'))
src_list.append(src2)
for idx, im in enumerate(im_params):
image = tkp.db.Image(database=self.database,
dataset=dataset,
data=im)
image.insert_extracted_sources([src_list[idx]])
associate_extracted_sources(image.id, deRuiter_r=3.717)
query = """\
SELECT rf.avg_f_int
,rf.f_datapoints
FROM runningcatalog r
,runningcatalog_flux rf
WHERE r.dataset = %(dataset)s
AND r.id = rf.runcat
"""
cursor = tkp.db.execute(query, {'dataset': dataset.id})
results = db_subs.get_db_rows_as_dicts(cursor)
self.assertEqual(len(results), 1)
self.assertEqual(results[0]['f_datapoints'], 2)
self.assertAlmostEqual(results[0]['avg_f_int'],
(src0.flux + src1.flux) / 2.0)
def test_one2one_flux_infinite_error(self):
dataset = tkp.db.DataSet(database=self.database, data={'description': 'flux test set: 1-1'})
n_images = 3
im_params = db_subs.generate_timespaced_dbimages_data(n_images)
src_list = []
src = db_subs.example_extractedsource_tuple()
src0 = src._replace(flux=2.0)
src_list.append(src0)
src1 = src._replace(flux=2.5)
src_list.append(src1)
src2 = src._replace(flux=0.0001, flux_err=float('inf'),
peak=0.0001, peak_err=float('inf'))
src_list.append(src2)
for idx, im in enumerate(im_params):
image = tkp.db.Image(database=self.database, dataset=dataset, data=im)
image.insert_extracted_sources([src_list[idx]])
associate_extracted_sources(image.id, deRuiter_r=3.717)
query = """\
SELECT rf.avg_f_int
,rf.f_datapoints
FROM runningcatalog r
,runningcatalog_flux rf
WHERE r.dataset = %(dataset)s
AND r.id = rf.runcat
"""
cursor = tkp.db.execute(query, {'dataset': dataset.id})
results = db_subs.get_db_rows_as_dicts(cursor)
self.assertEqual(len(results),1)
self.assertEqual(results[0]['f_datapoints'],2)
self.assertAlmostEqual(results[0]['avg_f_int'],
(src0.flux + src1.flux)/2.0 )
