def set_lines(self, verbose=True, use_cache=True, use_ISM_table=True):
""" Parse the lines of interest
Parameters
----------
verbose : bool, optional
use_cache : bool, optional
cache the linelist for faster repeat performance
use_ISM_table : bool, optional
For speed, use a saved ISM table instead of reading from original source files.
"""
import warnings
global CACHE
key = self.list
if use_cache and key in CACHE['data']:
self._data = CACHE['data'][key]
return
elif use_ISM_table and self.list in ('ISM', 'Strong', 'EUV', 'HI'):
data = QTable(Table.read(lt_path + '/data/lines/ISM_table.fits'))
if self.list != 'ISM':
cond = data['is_' + self.list]
self._data = data[cond]
else:
self._data = data
CACHE['data'][key] = self._data
return
indices = []
set_flags = []
# Default list
# Loop on lines
if self.list in ['H2', 'CO']:
gdi = np.where(self._fulltable['mol'] == self.list)[0]
if len(gdi) == 0:
raise IndexError(
'set_lines: Found no {:s} molecules! Read more data'.format(self.list))
indices.append(gdi)
elif self.list == 'ISM':
set_flags.append('fISM')
elif self.list == 'Strong':
set_flags.append('fSI')
elif self.list == 'HI':
set_flags.append('fHI')
elif self.list == 'EUV':
set_flags.append('fEUV')
elif self.list == 'Galaxy':
set_flags.append('fgE')
set_flags.append('fgA')
else:
raise ValueError(
'set_lines: Not ready for this: {:s}'.format(self.list))
# Deal with Defined sets
# import pdb
# pdb.set_trace()
if len(set_flags) > 0:
# Read standard file
set_data = lilp.read_sets()
# Speed up
wrest = self._fulltable['wrest'].value # Assuming Angstroms
for sflag in set_flags:
gdset = np.where(set_data[sflag] == 1)[0]
# Match to wavelengths
for igd in gdset:
mt = np.where(
np.abs(set_data[igd]['wrest'] - wrest) < 9e-5)[0]
if len(mt) == 1:
for imt in mt:
# Over-ride name!
self._fulltable[imt][
'name'] = set_data[igd]['name']
# if set_data[igd]['name'] == 'DI 1215':
# xdb.set_trace()
indices.append(mt[0])
elif len(mt) > 1:
#
wmsg = 'WARNING: Multiple lines with wrest={:g}'.format(
set_data[igd]['wrest'])
warnings.warn(wmsg)
warnings.warn(
'Taking the first entry. Maybe use higher precision.')
indices.append(mt[0])
else:
if verbose:
print('set_lines: Did not find {:s} in data Tables'.format(
set_data[igd]['name']))
# Collate (should grab unique ones!)
all_idx = np.unique(np.array(indices))
# Parse and sort (consider masking instead)
tmp_tab = self._fulltable[all_idx]
tmp_tab.sort('wrest')
#
self._data = tmp_tab
CACHE['data'][key] = self._data
def set_lines(self, verbose=True, use_cache=True, use_ISM_table=True):
""" Parse the lines of interest
Parameters
----------
verbose : bool, optional
use_cache : bool, optional
cache the linelist for faster repeat performance
use_ISM_table : bool, optional
For speed, use a saved ISM table instead of reading from original source files.
"""
global CACHE
key = self.list
if use_cache and key in CACHE['data']:
self._data = CACHE['data'][key]
return
elif use_ISM_table and self.list in ('ISM', 'Strong', 'HI'):
data = Table.read(lt_path + '/data/lines/ISM_table.fits')
if self.list != 'ISM':
cond = data['is_' + self.list]
self._data = data[cond]
else:
self._data = data
CACHE['data'][key] = self._data
return
indices = []
set_flags = []
# Default list
# Loop on lines
if self.list in ['H2', 'CO']:
gdi = np.where(self._fulltable['mol'] == self.list)[0]
if len(gdi) == 0:
raise IndexError(
'set_lines: Found no {:s} molecules! Read more data'.
format(self.list))
indices.append(gdi)
elif self.list == 'ISM':
set_flags.append('fISM')
elif self.list == 'Strong':
set_flags.append('fSI')
elif self.list == 'HI':
set_flags.append('fHI')
elif self.list == 'EUV':
set_flags.append('fEUV')
elif self.list == 'Galaxy':
set_flags.append('fgE')
set_flags.append('fgA')
else:
raise ValueError('set_lines: Not ready for this: {:s}'.format(
self.list))
# Deal with Defined sets
if len(set_flags) > 0:
# Read standard file
set_data = lilp.read_sets()
# Speed up
wrest = self._fulltable['wrest'] # Assuming Angstroms
for sflag in set_flags:
gdset = np.where(set_data[sflag] == 1)[0]
# Match to wavelengths
for igd in gdset:
mt = np.where(
np.abs(set_data['wrest'][igd] - wrest) < 9e-5)[0]
if len(mt) == 1:
self._fulltable['name'][mt[0]] = set_data['name'][igd]
indices.append(mt[0])
elif len(mt) > 1:
#
wmsg = 'WARNING: Multiple lines with wrest={:g}'.format(
set_data['wrest'][igd])
warnings.warn(wmsg)
warnings.warn(
'Taking the first entry. Maybe use higher precision.'
)
indices.append(mt[0])
else:
if verbose:
print(
'set_lines: Did not find {:s} in data Tables'.
format(set_data[igd]['name']))
# Collate (should grab unique ones!)
all_idx = np.unique(np.array(indices))
# Parse and sort (consider masking instead)
tmp_tab = self._fulltable[all_idx]
tmp_tab.sort('wrest')
#
self._data = tmp_tab
CACHE['data'][key] = self._data
def set_lines(self, verbose=True, use_cache=True):#, gd_lines=None):
''' Parse the lines of interest
'''
import warnings
global CACHE
key = tuple(self.lists)
if use_cache and key in CACHE['data']:
self._data = CACHE['data'][key]
return
indices = []
set_flags = []
# Default list
# Loop on lines
for llist in self.lists:
if llist in ['H2','CO']:
gdi = np.where(self._fulltable['mol'] == llist)[0]
if len(gdi) == 0:
raise IndexError(
'set_lines: Found no {:s} molecules! Read more data'.format(llist))
indices.append(gdi)
elif llist == 'ISM':
set_flags.append('fISM')
elif llist == 'Strong':
set_flags.append('fSI')
elif llist == 'HI':
set_flags.append('fHI')
elif llist == 'EUV':
set_flags.append('fEUV')
else:
raise ValueError('set_lines: Not ready for this: {:s}'.format(llist))
# Deal with Defined sets
#import pdb
#pdb.set_trace()
if len(set_flags) > 0:
# Read standard file
set_data = lilp.read_sets()
# Speed up
wrest = self._fulltable['wrest'].value # Assuming Angstroms
for sflag in set_flags:
gdset = np.where(set_data[sflag] == 1)[0]
# Match to wavelengths
for igd in gdset:
mt = np.where(
np.abs(set_data[igd]['wrest']-wrest) < 9e-5 )[0]
if len(mt) == 1:
for imt in mt:
# Over-ride name!
self._fulltable[imt]['name'] = set_data[igd]['name']
#if set_data[igd]['name'] == 'DI 1215':
# xdb.set_trace()
indices.append(mt[0])
elif len(mt) > 1:
#
wmsg = 'WARNING: Multiple lines with wrest={:g}'.format(
set_data[igd]['wrest'])
warnings.warn(wmsg)
warnings.warn('Taking the first entry. Maybe use higher precision.')
indices.append(mt[0])
else:
if verbose:
print('set_lines: Did not find {:s} in data Tables'.format(
set_data[igd]['name']))
# Collate (should grab unique ones!)
#all_idx = np.unique( np.concatenate( [np.array(itt) for itt in indices] ) )
all_idx = np.unique( np.array(indices) )
# Parse and sort (consider masking instead)
tmp_tab = self._fulltable[all_idx]
tmp_tab.sort('wrest')
#
self._data = tmp_tab
CACHE['data'][key] = self._data
