def data(self,index,role):
if role == Qt.EditRole:
row = index.row()
column = index.column()
if column == 1: toret=atomicdata.lam2ion(self.fitpars[0][row])
elif column == 2: toret=round(self.fitpars[3][row],5)
elif column == 3: toret=round(self.fitpars[1][row],3)
elif column == 4: toret=round(self.fiterrors[1][row],3)
elif column == 5: toret=round(self.fitpars[2][row],3)
elif column == 6: toret=round(self.fiterrors[2][row],3)
elif column == 7: toret=round(self.fitpars[4][row],3)
elif column == 8: toret=round(self.fiterrors[4][row],3)
elif column == 9: toret=self.linecmts[0][row]
elif column == 10: toret=self.linecmts[1][row]
else: toret=QVariant(round(self.fitpars[column][row],3))
return toret
if index.isValid() and role == Qt.DisplayRole:
row = index.row()
column = index.column()
if column == 1: toret=atomicdata.lam2ion(self.fitpars[0][row])
elif column == 2: toret=round(self.fitpars[3][row],5)
elif column == 3: toret=round(self.fitpars[1][row],3)
elif column == 4: toret=round(self.fiterrors[1][row],3)
elif column == 5: toret=round(self.fitpars[2][row],3)
elif column == 6: toret=round(self.fiterrors[2][row],3)
elif column == 7: toret=round(self.fitpars[4][row],3)
elif column == 8: toret=round(self.fiterrors[4][row],3)
elif column == 9: toret=self.linecmts[0][row]
elif column == 10: toret=self.linecmts[1][row]
else: toret=QVariant(round(self.fitpars[column][row],3))
return toret
else: return None
def validateWavelength(self):
### Handle approximate wavelength entries by looking up precise values on focus exit
if self.lamBox.text()!='':
restlam=self.lamBox.text()
restlam=float(restlam)
try:
lam,fosc,gam=atomicdata.setatomicdata([restlam],precise=False)
self.lamBox.setText(str(lam[0]))
self.ionLabel.setText(atomicdata.lam2ion(lam[0]))
except:
pass
def validateWavelength(self):
### Handle approximate wavelength entries by looking up precise values on focus exit
if self.lamBox.text()!='':
restlam=self.lamBox.text()
restlam=float(restlam)
try:
lam,fosc,gam=atomicdata.setatomicdata([restlam],precise=False)
self.lamBox.setText(str(lam[0]))
self.ionLabel.setText(atomicdata.lam2ion(lam[0]))
except:
pass
def data(self,index,role):
if role == Qt.EditRole:
row = index.row()
column = index.column()
if column == 1: toret=atomicdata.lam2ion(self.fitpars[0][row])
elif column == 2: toret=round(self.fitpars[3][row],5)
elif column == 3: toret=round(self.fitpars[1][row],3)
elif column == 4: toret=round(self.fiterrors[1][row],3)
elif column == 5: toret=round(self.fitpars[2][row],3)
elif column == 6: toret=round(self.fiterrors[2][row],3)
elif column == 7: toret=round(self.fitpars[4][row],3)
elif column == 8: toret=round(self.fiterrors[4][row],3)
elif column == 9: toret=self.linecmts[0][row]
elif column == 10: toret=self.linecmts[1][row]
else: toret=QVariant(round(self.fitpars[column][row],3))
return toret
if index.isValid() and role == Qt.DisplayRole:
row = index.row()
column = index.column()
if column == 0: toret=round(self.fitpars[0][row],3)
elif column == 1:
toret=atomicdata.lam2ion(self.fitpars[0][row])
elif column == 2: toret=round(self.fitpars[3][row],5)
elif column == 3: toret=round(self.fitpars[1][row],3)
elif column == 4: toret=round(self.fiterrors[1][row],3)
elif column == 5: toret=round(self.fitpars[2][row],3)
elif column == 6: toret=round(self.fiterrors[2][row],3)
elif column == 7: toret=round(self.fitpars[4][row],3)
elif column == 8: toret=round(self.fiterrors[4][row],3)
elif column == 9: toret=self.linecmts[0][row]
elif column == 10: toret=self.linecmts[1][row]
else: toret=QVariant(round(self.fitpars[column][row],3))
return str(toret)
else: return None
def abscomponents_from_abslines(abslinelist, **kwargs):
'''
Organizes list of AbsLines into components based on the following order: redshift, velocity, and species
Parameters
----------
abslinelist : list
List of AbsLine objects
Returns
-------
complist : list
List AbsComponent objects
'''
### Import machine learning clustering algorithm for velocity grouping
from sklearn.cluster import MeanShift, estimate_bandwidth
from linetools.isgm.abscomponent import AbsComponent
### Populate arrays with line redshifts, velocity centroids, and name of species
zarr = np.zeros(len(abslinelist))
varr = np.zeros(len(abslinelist))
sparr = np.chararray(len(abslinelist), itemsize=6)
for i, absline in enumerate(abslinelist):
zarr[i] = absline.z
# import pdb; pdb.set_trace()
varr[i] = absline.attrib['vel'].value
sparr[i] = atomicdata.lam2ion(absline.wrest.value)
abslinelist = np.array(
abslinelist) # Convert to array for the indexing used below
### Group lines with the same redshifts and similar velocities
complines = []
uqzs = np.unique(zarr)
for uqz in uqzs:
### Identify velocity groups
thesez = np.where(zarr == uqz)[0]
X = np.array(list(zip(varr[thesez], np.zeros(len(varr[thesez])))),
dtype=float)
ms = MeanShift(bandwidth=7.)
ms.fit(X)
vidxs = ms.labels_
vs = ms.cluster_centers_
uqvidxs = np.unique(vidxs)
### Make lists of lines that will belong to each component
for idx in uqvidxs:
theseuqvs = thesez[np.where(
vidxs ==
idx)[0]] # isolate velocity-grouped lines with this redshift
uqsp = np.unique(
sparr[theseuqvs]
) # identify the unique species with lines in this group
### Get lines belonging to each species and add them to become components
for sp in uqsp:
spidx = theseuqvs[np.where(sparr[theseuqvs] == sp)]
complines.append(abslinelist[spidx])
### Instantiate the AbsComponents
comps = []
for lst in complines:
if '*' in lst[0].name:
linename = lst[0].name
starct = linename.count('*')
stars = '*' * starct
else:
stars = None
thiscomp = AbsComponent.from_abslines(lst.tolist(),
stars=stars,
chk_vel=False,
adopt_median=True,
**kwargs)
comps.append(thiscomp)
return comps
def writelinepars(fitpars,
fiterrors,
parinfo,
specfile,
outfilename,
linecmts=None):
'''
Write fit parameters out to file.
Parameters
----------
fitpars : list of lists
Parameters for fit ready for fitter!
fiterrors : array of numpy vectors
Error array for the fitting initialized to '0' for each param
parinfo : array of arrays
Flags to be used in fit
specfile : str
Name of the input file containing the spectrum
outfilename : str
Parameter output filename
linecmts : list of lists, optional
Reliability flags and comments, e.g., from igmguesses
'''
import os
### Set outputs and open files
bigfiletowrite = cfg.largeVPparfile
filetowrite = outfilename
if os.path.isfile(filetowrite):
VPparfile = open(filetowrite, 'wb')
bigparfile = open(bigfiletowrite, 'ab') # Append to the running list
else:
VPparfile = open(filetowrite, 'wb')
bigparfile = open(bigfiletowrite, 'wb')
### Prep header of line parameter file
if linecmts is not None:
header = b'specfile|restwave|zsys|col|sigcol|bval|sigbval|vel|sigvel|nflag|bflag|vflag|vlim1|vlim2|wobs1|wobs2|pix1|pix2|z_comp|trans|rely|comment \n'
else:
header = b'specfile|restwave|zsys|col|sigcol|bval|sigbval|vel|sigvel|nflag|bflag|vflag|vlim1|vlim2|wobs1|wobs2|pix1|pix2|z_comp|trans \n'
VPparfile.write(header)
bigparfile.write(header)
### Grab parameters/info for each line
for i in range(len(fitpars[0])):
zline = fitpars[3][i]
vlim1 = fitpars[5][i]
vlim2 = fitpars[6][i]
restwave = fitpars[0][i]
wobs1 = restwave * (1 + zline + vlim1 / 299792.458)
wobs2 = restwave * (1 + zline + vlim2 / 299792.458)
pix1 = jbg.closest(cfg.wave, wobs1)
pix2 = jbg.closest(cfg.wave, wobs2)
trans = atomicdata.lam2ion(fitpars[0][i])
z_comp = ltu.z_from_dv(fitpars[4][i] * u.km / u.s, zline)
if linecmts is not None:
towrite = jbg.pipedelimrow([
specfile, restwave,
round(zline, 5),
round(fitpars[1][i], 3),
round(fiterrors[1][i], 3),
round(fitpars[2][i], 3),
round(fiterrors[2][i], 3),
round(fitpars[4][i], 3),
round(fiterrors[4][i], 3), parinfo[1][i], parinfo[2][i],
parinfo[4][i], vlim1, vlim2, wobs1, wobs2, pix1, pix2,
round(z_comp, 5), trans, linecmts[0][i], linecmts[1][i]
])
else:
towrite = jbg.pipedelimrow([
specfile, restwave,
round(zline, 5),
round(fitpars[1][i], 3),
round(fiterrors[1][i], 3),
round(fitpars[2][i], 3),
round(fiterrors[2][i], 3),
round(fitpars[4][i], 3),
round(fiterrors[4][i], 3), parinfo[1][i], parinfo[2][i],
parinfo[4][i], vlim1, vlim2, wobs1, wobs2, pix1, pix2,
round(z_comp, 5), trans
])
VPparfile.write(towrite.encode())
bigparfile.write(towrite.encode())
VPparfile.close()
bigparfile.close()
print('Line parameters written to:')
print(filetowrite)
def readpars(filename, wave1=None, wave2=None):
'''
Parameters
----------
filename : str
Name of parameter input (or joebvp output) file
File should at least have following columns:
specfile|restwave|zsys|col|sigcol|bval|sigbval|vel|sigvel|nflag|bflag|vflag|vlim1|vlim2
wave1 : float, optional
Beginning of wavelength range over which to load lines (must be set with wave2)
wave2 : float, optional
End of wavelength range over which to load lines (must be set with wave1)
Returns
-------
fitpars : list of lists
Parameters for fit ready for fitter!
fiterrors : array of numpy vectors
Error array for the fitting initialized to '0' for each param
parinfo : array of arrays
Flags to be used in fit
linecmts: list of lists
Reliability and comment flags, e.g., from igmguesses
'''
linelist = ascii.read(filename)
linerestwave = linelist['restwave'].data
linez = linelist['zsys'].data
if (wave1 == None) & (wave2 == None):
lineshere = np.arange(len(linelist))
elif ((wave1 == None) | (wave2 == None)) | (wave1 >= wave2):
lineshere = np.arange(len(linelist))
warnings.warn(
'Note that both \'wave1\' and \'wave2\' must be declared or neither must be. \n Loading all lines in list.'
)
else:
lineobswave = linerestwave * (1. + linez)
lineshere = np.where((lineobswave > wave1) & (lineobswave < wave2))[0]
linelist = linelist[lineshere]
linelist['ions'] = atomicdata.lam2ion(linelist['restwave'])
linelist.sort(['ions', 'zsys', 'vel', 'restwave'])
linerestwave = linelist['restwave']
zs = linelist['zsys']
linecol = linelist['col']
lineb = linelist['bval']
linevel = linelist['vel']
linevlim1 = linelist['vlim1']
linevlim2 = linelist['vlim2']
colflag = linelist['nflag']
bflag = linelist['bflag']
velflag = linelist['vflag']
restwaves = linerestwave
if (('rely' in linelist.colnames) & ('comment' in linelist.colnames)):
pass
elif ('rely' in linelist.colnames):
linelist['comment'] = ['none'] * len(linelist)
else:
linelist['rely'] = ['-'] * len(linelist)
linelist['comment'] = ['none'] * len(linelist)
reliability = linelist['rely']
comment = linelist['comment']
initinfo = [colflag, bflag, velflag]
initpars = [restwaves, linecol, lineb, zs, linevel, linevlim1, linevlim2]
fitpars, parinfo = initlinepars(zs, restwaves, initpars, initinfo=initinfo)
fiterrors = np.zeros([5, len(fitpars[0])]) # Initialize errors to zero
linecmts = [reliability, comment]
#fiterrors[1] = colsig
#fiterrors[2] = bsig
#fiterrors[4] = velsig
return fitpars, fiterrors, parinfo, linecmts
def writelinepars(fitpars,fiterrors,parinfo, specfile, outfilename, linecmts=None): ''' Write fit parameters out to file. Parameters ---------- fitpars : list of lists Parameters for fit ready for fitter! fiterrors : array of numpy vectors Error array for the fitting initialized to '0' for each param parinfo : array of arrays Flags to be used in fit specfile : str Name of the input file containing the spectrum outfilename : str Parameter output filename linecmts : list of lists, optional Reliability flags and comments, e.g., from igmguesses ''' import os ### Set outputs and open files bigfiletowrite = cfg.largeVPparfile filetowrite = outfilename if os.path.isfile(filetowrite): VPparfile = open(filetowrite, 'wb') bigparfile = open(bigfiletowrite, 'ab') # Append to the running list else: VPparfile = open(filetowrite, 'wb') bigparfile = open(bigfiletowrite, 'wb') ### Prep header of line parameter file if linecmts is not None: header = 'specfile|restwave|zsys|col|sigcol|bval|sigbval|vel|sigvel|nflag|bflag|vflag|vlim1|vlim2|wobs1|wobs2|pix1|pix2|z_comp|trans|rely|comment \n' else: header = 'specfile|restwave|zsys|col|sigcol|bval|sigbval|vel|sigvel|nflag|bflag|vflag|vlim1|vlim2|wobs1|wobs2|pix1|pix2|z_comp|trans \n' VPparfile.write(header) bigparfile.write(header) ### Grab parameters/info for each line for i in range(len(fitpars[0])): zline = fitpars[3][i] vlim1 = fitpars[5][i] vlim2 = fitpars[6][i] restwave = fitpars[0][i] wobs1 = restwave * (1 + zline + vlim1 / 299792.458) wobs2 = restwave * (1 + zline + vlim2 / 299792.458) pix1 = jbg.closest(cfg.wave, wobs1) pix2 = jbg.closest(cfg.wave, wobs2) trans = atomicdata.lam2ion(fitpars[0][i]) z_comp = ltu.z_from_dv(fitpars[4][i]*u.km/u.s, zline) if linecmts is not None: towrite = jbg.pipedelimrow( [specfile, restwave, round(zline, 5), round(fitpars[1][i], 3), round(fiterrors[1][i], 3), round(fitpars[2][i], 3), round(fiterrors[2][i], 3), round(fitpars[4][i], 3), round(fiterrors[4][i], 3), parinfo[1][i], parinfo[2][i], parinfo[4][i], vlim1, vlim2, wobs1, wobs2, pix1, pix2,round(z_comp, 5), trans, linecmts[0][i],linecmts[1][i]]) else: towrite = jbg.pipedelimrow( [specfile, restwave, round(zline, 5), round(fitpars[1][i], 3), round(fiterrors[1][i], 3), round(fitpars[2][i], 3), round(fiterrors[2][i], 3), round(fitpars[4][i], 3), round(fiterrors[4][i], 3), parinfo[1][i], parinfo[2][i], parinfo[4][i], vlim1, vlim2, wobs1, wobs2, pix1, pix2, round(z_comp, 5),trans]) VPparfile.write(towrite) bigparfile.write(towrite) VPparfile.close() bigparfile.close() print 'Line parameters written to:' print filetowrite
def readpars(filename,wave1=None,wave2=None):
'''
Parameters
----------
filename : str
Name of parameter input (or joebvp output) file
File should at least have following columns:
specfile|restwave|zsys|col|sigcol|bval|sigbval|vel|sigvel|nflag|bflag|vflag|vlim1|vlim2
wave1 : float, optional
Beginning of wavelength range over which to load lines (must be set with wave2)
wave2 : float, optional
End of wavelength range over which to load lines (must be set with wave1)
Returns
-------
fitpars : list of lists
Parameters for fit ready for fitter!
fiterrors : array of numpy vectors
Error array for the fitting initialized to '0' for each param
parinfo : array of arrays
Flags to be used in fit
linecmts: list of lists
Reliability and comment flags, e.g., from igmguesses
'''
linelist = ascii.read(filename)
linerestwave = linelist['restwave'].data
linez = linelist['zsys'].data
if (wave1 == None)&(wave2 == None):
lineshere = range(len(linelist))
elif ((wave1 == None)|(wave2 == None))|(wave1>=wave2):
lineshere = range(len(linelist))
warnings.warn('Note that both \'wave1\' and \'wave2\' must be declared or neither must be. \n Loading all lines in list.')
else:
lineobswave = linerestwave * (1. + linez)
lineshere = np.where((lineobswave > wave1) & (lineobswave < wave2))[0]
linelist=linelist[lineshere]
linelist['ions']=atomicdata.lam2ion(linelist['restwave'])
linelist.sort(['ions','zsys','vel','restwave'])
linerestwave = linelist['restwave']
zs = linelist['zsys']
linecol = linelist['col']
lineb = linelist['bval']
linevel = linelist['vel']
linevlim1 = linelist['vlim1']
linevlim2 = linelist['vlim2']
colflag = linelist['nflag']
bflag = linelist['bflag']
velflag = linelist['vflag']
restwaves = linerestwave
if (('rely' in linelist.colnames)&('comment' in linelist.colnames)):
pass
elif ('rely' in linelist.colnames):
linelist['comment']=['none']*len(linelist)
else:
linelist['rely'] = ['-'] * len(linelist)
linelist['comment'] = ['none'] * len(linelist)
reliability = linelist['rely']
comment = linelist['comment']
initinfo = [colflag, bflag, velflag]
initpars = [restwaves, linecol, lineb, zs, linevel, linevlim1, linevlim2]
fitpars, parinfo = initlinepars(zs, restwaves, initpars, initinfo=initinfo)
fiterrors = np.zeros([5, len(fitpars[0])]) # Initialize errors to zero
linecmts = [reliability,comment]
#fiterrors[1] = colsig
#fiterrors[2] = bsig
#fiterrors[4] = velsig
return fitpars,fiterrors,parinfo,linecmts
