def _get_bl_prop(self, array_name):
# In case a bl_array is selected
"""
Args:
array_name:
Returns:
object:
"""
if array_name not in CONF_LIM['minbase'].keys():
id1 = self._arrays_info.query(
'SE_ARRAYNAME == "%s"' % array_name).iloc[0].SE1
ap = self._arrays_info.query(
'SE_ARRAYNAME == "%s" and SE1 == %d' % (array_name, id1)
)[['AV1']]
ap.rename(columns={'AV1': 'antenna'}, inplace=True)
ap = ap[ap.antenna.str.contains('CM') == False]
if len(ap) == 0:
ap = self._arrays_info.query(
'SE_ARRAYNAME == "%s" and SE1 == %d' %
(array_name, id1))[['AV1']]
ap.rename(columns={'AV1': 'antenna'}, inplace=True)
conf = pd.merge(ap, self._ante_pad,
left_on='antenna', right_on='antenna')[
['pad', 'antenna']]
conf_file = self._dsa_path + 'conf/%s.txt' % array_name
conf.to_csv(conf_file, header=False,
index=False, sep=' ')
ac = rUV.ac.ArrayConfigurationCasaFile()
ac.createCasaConfig(conf_file)
ruv = rUV.compute_radialuv(conf_file + ".cfg")
num_bl = len(ruv)
num_ant = len(ap)
array_ar = rUV.compute_array_ar(ruv)
# If C36 is selected
else:
conf_file = (self._dsa_path +
'conf/%s.cfg' % array_name)
ruv = rUV.compute_radialuv(conf_file)
# noinspection PyTypeChecker
array_ar = rUV.compute_array_ar(ruv)
num_bl = len(ruv)
if array_name.startswith('C40'):
num_ant = 40
else:
num_ant = 36
return array_ar, num_bl, num_ant, ruv
def _get_sbbased_bl_prop(ruv, blmin, blmax, arrayfam):
"""
Args:
ruv:
blmin:
blmax:
arrayfam:
Returns:
Pandas.Series:
"""
if arrayfam != "TWELVE-M":
return pd.Series(
[pd.np.NaN, 0],
index=['array_ar_cond', 'num_bl_use'])
ruv = ruv[(ruv >= blmin) & (ruv <= blmax)]
if len(ruv) < 400.:
return pd.Series(
[pd.np.NaN, 0],
index=['array_ar_cond', 'num_bl_use'])
num_bl = len(ruv)
array_ar = rUV.compute_array_ar(ruv)
return pd.Series([array_ar, num_bl],
index=['array_ar_cond', 'num_bl_use'])
def _get_sbbased_bl_prop(ruv, blmin, blmax):
"""
:param ruv:
:param blmin:
:param blmax:
:return:
"""
ruv = ruv[(ruv >= blmin) & (ruv <= blmax)]
if len(ruv) < 300.:
return pd.Series(
[pd.np.NaN, 0],
index=['array_ar_cond', 'num_bl_use'])
num_bl = len(ruv)
array_ar = rUV.compute_array_ar(ruv)
return pd.Series([array_ar, num_bl],
index=['array_ar_cond', 'num_bl_use'])
