def test_match():
c1 = Catalog()
c1['RA'] = np.arange(10, dtype=float)
c1['DEC'] = np.arange(10, dtype=float)
c2 = Table()
c2['ra'] = np.arange(20, dtype=float) + 0.5 / 3600
c2['dec'] = np.arange(20, dtype=float) - 0.5 / 3600
match = c1.match(c2, colc2=('ra', 'dec'), full_output=False)
assert len(match) == 10
assert_almost_equal(match['Distance'], 0.705, decimal=2)
# create a duplicate match
c1['RA'][4] = c1['RA'][3] - 0.1 / 3600
c1['DEC'][4] = c1['DEC'][3] - 0.1 / 3600
c2['ra'][:5] = np.arange(5, dtype=float) + 0.1 / 3600
c2['dec'][:5] = np.arange(5, dtype=float) + 0.1 / 3600
match, nomatch1, nomatch2 = c1.match(c2,
colc2=('ra', 'dec'),
radius=0.5,
full_output=True)
assert len(match) == 4
assert len(nomatch1) == 6
assert len(nomatch2) == 16
assert type(nomatch2) == type(c2)
def test_meta():
c1 = Catalog(idname='ID', raname='RA', decname='DEC')
c1['ID'] = np.arange(10, dtype=int)
c1['RA'] = np.arange(10, dtype=float)
c1['DEC'] = np.arange(10, dtype=float)
assert c1.meta['idname'] is c1.meta['IDNAME']
c2 = Table()
c2['id'] = np.arange(20, dtype=int)
c2['RA'] = np.arange(20, dtype=float) + 0.5 / 3600
c2['DEC'] = np.arange(20, dtype=float) - 0.5 / 3600
c2.meta['idname'] = 'id'
c2.meta['raname'] = 'RA'
match, nomatch1, nomatch2 = c1.match(c2, full_output=True)
assert len(match) == 10
assert type(match.meta) == type(c1.meta)
assert match.meta['idname'] == 'ID'
assert match.meta['idname_1'] == 'ID'
assert match.meta['idname_2'] == 'id'
assert match.meta['raname'] == 'RA_1'
assert match.meta['raname_1'] == 'RA_1'
assert match.meta['raname_2'] == 'RA_2'
assert nomatch1.meta['idname'] == 'ID'
assert nomatch2.meta['idname'] == 'id'