def PrintLineTableForCluster(cluster='NGC-0752'):
starNames = SDB.GetStarsForCluster(cluster)
allLineDict = {}
for starName in starNames:
starLines = LL.getLinesForStar(cluster, starName)
for line in starLines:
if (line[0], line[1]) not in allLineDict.keys():
allLineDict[(line[0], line[1])] = 1
else:
allLineDict[(line[0], line[1])] += 1
for line in sorted(allLineDict.keys()):
lookup, refs = LL.getLines(elements=[line[0]], \
wavelengthRange=[(line[1]-k.LambdaVarianceLimit, \
line[1]+k.LambdaVarianceLimit)],\
dataFormat=None)
if len(lookup) == 0:
continue
luline = lookup[0]
print(
k.LLTableFormat.format(line[1], line[0], luline[2], luline[3],
allLineDict[(line[0], line[1])], luline[5]))
def GetGiantStarParms(clusterName='NGC-0752', mass=1.7, metallicity=-0.03):
giantInfo = SD.GetGiantInfoForCluster(clusterName=clusterName)
# Returned Data format:
# [RA, DEC, Epoch, clusterName, starID, Teff, LogG, vTurb, Vmag, Bmag, s2n]
# We want:
# [(starID, Teff, LogG, Vturb, metallicity, mass, s2n)...]
retData = [(s[4], s[5], s[6], s[7], metallicity, mass, s[10])\
for s in giantInfo]
return retData
def MakeStarIDTable(clusterID='NGC-0752', outFile=d.TableDir + 'Table3.dat'):
stars = SDB.GetStarInfoForCluster(clusterName=clusterID)
fp = open(outFile, 'w')
fmt, db = BuildFormatString(table3Format,
DataLabels=table3Labels,
DataUnits=table3Units,
DataExp=table3Desc,
MakeBbBDesc=True)
fp.write(db)
def plotDwarfTeffLogg(cluster='NGC-0752',
isoPoints=None,
isoLabel=None,
compPointSets=None,
outfilename=None,
plotTitle=None):
stars = [s[4] for s in SDB.GetDwarfInfoForCluster(clusterName=cluster)]
CompPlotTeffLogg(stars=stars,
cluster=cluster,
isoPoints=isoPoints,
isoLabel=isoLabel,
compPointSets=compPointSets,
outfilename=outfilename,
plotTitle=plotTitle)
def MakeStarLineTable(starNames=[], clusterID='NGC-0752', ions=[], \
wls=[4500,8500], outFile=d.TableDir+'Table1.dat'):
if len(starNames) == 0:
starNames = SDB.GetStarsForCluster(clusterID)
fp = open(outFile, 'w')
fmt, db = BuildFormatString(table1Format,
DataLabels=table1Labels,
DataUnits=table1Units,
DataExp=table1Desc,
MakeBbBDesc=True)
fp.write(db)
for sn in starNames:
lines = LL.getLinesForStar(clusterID,
sn,
elements=ions,
wavelengthRange=wls,
dataFormat=None)
starID = int(sn[4:])
for l in lines:
fp.write(fmt.format(starID, l[0], l[1], l[4]) + '\n')
fp.close()
def CompPlotTeffLogg(stars=None,
cluster='NGC-0752',
isoPoints=None,
isoLabel=None,
compPointSets=None,
outfilename=None,
plotTitle=None):
# Creates a Teff-Logg plot of the stars in the passed cluster with the points
# passed (if any).
# Data Formats:
# stars = list of star ids which can be used as lookup into
# the database.
# cluster = Name of cluster. If no stars ids are passed, then
# plot all stars from this cluster.
# isoPoints = Isochrone points to overplot with a dashed line.
# isoLabel = A text label for the isochrone. If None, then the
# isochrone points are labeled as "Isochrone"
# compPointSets = A dictionary of reference points to also plot.
# format: {RefName:[[Teff, Logg],...],...}
# outfilename: If not None, then write the result to this file.
# Otherwise, just plot onscreen.
# plotTitle: Title printed on plot. Generally not used for
# publications.
if stars == None:
stars = SDB.GetStarsForCluster(cluster)
dbTeffs = []
dbLoggs = []
for sName in stars:
(Teff, Logg, unused) = \
SDB.GetStarParms(sName, clusterName=cluster)
dbTeffs.append(Teff)
dbLoggs.append(Logg)
minX = min(dbTeffs)
maxX = max(dbTeffs)
minY = min(dbLoggs)
maxY = max(dbLoggs)
params = {
'legend.fontsize': 'large',
'axes.labelsize': 'x-large',
'axes.titlesize': 'x-large',
'xtick.labelsize': 'x-large',
'ytick.labelsize': 'x-large'
}
pylab.rcParams.update(params)
fig = pyplot.figure()
axes = pyplot.gca()
pyplot.scatter(dbTeffs, dbLoggs, figure=fig,\
label='This work', marker=markers[0], color=colors[0])
mCount = 1
cCount = 1
if compPointSets is not None:
for setName in compPointSets.keys():
teffs = [i[0] for i in compPointSets[setName]]
loggs = [i[1] for i in compPointSets[setName]]
pyplot.scatter(teffs,
loggs,
figure=fig,
label=setName,
marker=markers[mCount],
color=colors[cCount])
mCount += 1
if mCount == len(markers): mCount = 0
cCount += 1
if cCount == len(colors): cCount = 0
minX = min(teffs + [minX])
maxX = max(teffs + [maxX])
minY = min(loggs + [minY])
maxY = max(loggs + [maxY])
if isoPoints is not None:
teffs = [i[0] for i in isoPoints]
loggs = [i[1] for i in isoPoints]
if isoLabel is not None:
pyplot.plot(teffs, loggs, 'b:', figure=fig, label=isoLabel)
else:
pyplot.plot(teffs, loggs, 'b:', figure=fig, label='Isochrone')
# We want the plot to look like an HR diagram, so reverse both axes:
axes.set_xlim(maxX + 50., minX - 50.)
axes.set_ylim(maxY + 0.05, minY - 0.05)
axes.set_xlabel(r'$T_{\rm{eff}}$')
axes.set_ylabel(r'log g')
axes.legend()
if plotTitle is not None:
axes.set_title(plotTitle)
if outfilename is not None:
pyplot.savefig(outfilename, figure=fig)
else:
pyplot.show()
pyplot.close()
return