def run(self,Test=True, Verbose=False, UseGtlike=False):
# Convert everything to a float
ra = float(self.xref)
dec = float(self.yref)
nxdeg = float(self.nxdeg)
nydeg = float(self.nydeg)
binsize = float(self.binsz)
# Get the current working directory
WorkingDirectory = os.getcwd()
# Define the output, log, and job directories
if self.outdir == None:
OutputDirectory = WorkingDirectory
LogDirectory = "%s/dtsmap/" % WorkingDirectory
JobsDirectory = "%s/dtsmap/" % WorkingDirectory
else:
OutputDirectory = self.outdir
LogDirectory = self.outdir
JobsDirectory = self.outdir
# Define the directory where this script is located
try:
ScriptDirectory = os.path.dirname(os.path.realpath(__file__))
except:
ScriptDirectory = None
# Creating the necessary directories
if(os.path.isdir(OutputDirectory)==False):
print "\nCreating Directory: " + OutputDirectory
cmd = "mkdir " + OutputDirectory
os.system(cmd)
if(os.path.isdir(LogDirectory)==False):
print "\nCreating Directory: " + LogDirectory
cmd = "mkdir " + LogDirectory
os.system(cmd)
if(os.path.isdir(JobsDirectory)==False):
print "\nCreating Directory: " + JobsDirectory
cmd = "mkdir " + JobsDirectory
os.system(cmd)
# Calculate tsmap grid
ra_min = ra - self.nxdeg/2.0
ra_max = ra + self.nxdeg/2.0
dec_min = dec - self.nydeg/2.0
dec_max = dec + self.nydeg/2.0
# Calcualate the range of ra and dec values
ra_range = numpy.arange(ra_min,ra_max+binsize,binsize)
dec_range = numpy.arange(dec_min,dec_max+binsize,binsize)
xsize = len(ra_range)
ysize = len(dec_range)
# Make sure that we don't have any ra values below zero or greater than 360, they should wrap ra instead.
for i in range(len(ra_range)):
if ra_range[i] < 0:
ra_range[i] = ra_range[i] + 360.0
if ra_range[i] > 360:
ra_range[i] = ra_range[i] - 360.0
# Make sure that we don't have any dec values below or above +/- 90, they should instead wrap in both ra and dec.
for i in range(len(dec_range)):
if dec_range[i] < -90:
dec_range[i] = ((dec_range[i] + 90) + 90)*-1
ra_range[i] = ra_range[i] + 180.0
if dec_range[i] > 90:
dec_range[i] = 90 - (dec_range[i] - 90)
ra_range[i] = ra_range[i] + 180
print "\nTS map grid size: %s x %s" % (len(ra_range), len(dec_range))
print "RA: %s to %s, Dec: %s to %s" % (ra_range[-1], ra_range[0], dec_range[0], dec_range[-1])
print "Bin size: %s deg" % binsize
print " "
print "(%.2f, %.2f) (%.2f, %.2f)" % (ra_range[-1], dec_range[-1], ra_range[0], dec_range[-1])
print " -----------------------------"
print " | |"
print " | |"
print " | |"
print " | |"
print " | (%.2f, %.2f) |" % (float(ra), float(dec))
print " | x |"
print " | |"
print " | |"
print " | |"
print " | |"
print " -----------------------------"
print "(%.2f, %.2f) (%.2f, %.2f)" % (ra_range[-1], dec_range[0], ra_range[0], dec_range[-1])
print "\nSubmitting a total of %s Jobs" % (xsize * ysize)
# Mark the start time
startTime = time.time()
# Loop through all combinations of Ra and Dec and submit a job for each one
RaDecPairs = {}
binNumbers = []
binNumber = 0
# Keep track of the jobs submitted. This allows the user to specify how many jobs should be running at any given time.
JobsInQueue = 0
for raStep in ra_range:
for decStep in dec_range:
# Check to see if the number of jobs in the queue is greater than the max. If so, wait for the jobs to leave the queue before submitting more.
while JobsInQueue >= int(self.maxJobs):
print "\nMaximum number of submitted jobs (%s) reached. Waiting..." % self.maxJobs
print "Total number of remaining jobs to submit: %s" % remainingJobs
# Wait 30 seconds before polling the job statuses
time.sleep(60)
# Get the number of jobs actively in the queue
command = "bjobs -g %s | wc" % JobsDirectory
process = subprocess.Popen(command, shell=True, stdin=subprocess.PIPE, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, close_fds=True)
lines = process.stdout.readlines()
# Extract the number of jobs that are running
JobsInQueue = int(lines[0].split()[0])
# Setup the job
logfile = LogDirectory + "/dtsmap_bin%s.log" % binNumber
# Make the job name
try:
sourceNumber = int(self.outdir.split('/')[-1].replace('dtsmap_Source',''))
jobName = "dts_S%sb%s" % (sourceNumber, binNumber)
except:
jobName = "dtsmap_b%s" % binNumber
# Construct the command
command = """dtsmap.py scfile=%s evfile=%s expmap=%s expcube=%s cmap=%s srcmdl=%s irfs=%s source=%s optimizer=%s ftol=%s nxdeg=%s nydeg=%s binsz=%s coordsys=%s xref=%s yref=%s proj=%s statistic=%s binNumber=%s outfile=%s outdir=%s PerformAnalysis=1""" % (self.scfile,
self.evfile, self.expmap, self.expcube, self.cmap, self.srcmdl, self.irfs, self.source, self.optimizer, self.ftol, self.nxdeg,
self.nydeg, self.binsz, self.coordsys, raStep, decStep, self.proj, self.statistic, binNumber, self.outfile, OutputDirectory)
# Specify where to find the python script
if ScriptDirectory != None:
command = ScriptDirectory + "/" + command
# Construct the process call
process = 'bsub -o ' + logfile + ' -J ' + jobName + ' -q xlong -R rhel60 -g ' + JobsDirectory + ' "' + command + '"'
# Display the command
if Verbose == True:
print process
# Start the process
if Test == False:
if self.batch == True:
subprocess.call(process, shell=True)
else:
os.system(command)
# Put the ra, dec, and bin info in a dictionary for easy retrieval later
RaDecPairs[binNumber] = [raStep,decStep]
# Increment the bin number
binNumbers.append(binNumber)
binNumber = binNumber + 1
# Increment the bin number
JobsInQueue = JobsInQueue + 1
# Get the number of remaining jobs
remainingJobs = ((xsize * ysize) - binNumber)
print "\nTotal number of jobs submitted: %s" % binNumber
print "All jobs submitted."
nJobs = -1
while nJobs != 0:
# Determine the number of jobs still running
command = "bjobs -g %s | wc" % JobsDirectory
process = subprocess.Popen(command, shell=True, stdin=subprocess.PIPE, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, close_fds=True)
lines = process.stdout.readlines()
# Display the results and the elapsed time since the start of the analysis
if 'No unfinished job found' in lines[0]:
nJobs = 0
print '\nAll Jobs Complete.'
# Display the elapsed time
elapsedTimeSeconds = time.time() - startTime
elapsedTimeMinutes = elapsedTimeSeconds/60.0
elapsedTimeHours = elapsedTimeMinutes/60.0
# Modify the units depending on the amount of time that has elapsed
if elapsedTimeMinutes > 60:
print "Total Elapsed Time: %.2f Hours" % elapsedTimeHours
else:
print "Total Elapsed Time: %.2f Minutes" % elapsedTimeMinutes
# Make sure we actually break out of this while loop!
break
else:
# Get the number of jobs in the queue from the stdout
nJobs = int(lines[0].split()[0])
print "\nJobs Remaining: %s" % nJobs
# Display the elapsed time
elapsedTimeSeconds = time.time() - startTime
elapsedTimeMinutes = elapsedTimeSeconds/60.0
elapsedTimeHours = elapsedTimeMinutes/60.0
if elapsedTimeMinutes > 60:
print "Elapsed Time: %.2f Hours" % elapsedTimeHours
else:
print "Elapsed Time: %.2f Minutes" % elapsedTimeMinutes
# Wait 120 seconds before polling the job statuses
time.sleep(120)
if UseGtlike == True:
# Gather the results (gtlike)
command = "grep 'TS value' %s/likelihoodResults_bin*.txt" % LogDirectory
process = subprocess.Popen(command, shell=True, stdin=subprocess.PIPE, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, close_fds=True)
lines = process.stdout.readlines()
else:
# Gather the results (pylikelihood)
command = "grep 'TS = ' %s/dtsmap_bin*.log" % LogDirectory
process = subprocess.Popen(command, shell=True, stdin=subprocess.PIPE, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, close_fds=True)
lines = process.stdout.readlines()
# Read in the results
binNumbersReadIn = []
TSs = []
for line in lines:
if ('No match' in line) or ('grep' in line):
print "Error: *** No available likelihood results ***"
print "Check your science tools setup and try again..."
print "Exiting.\n"
Results = {'MaxTS':None, 'MaxRA':None, 'MaxDec':None, 'Error':None, 'Index':None, 'IndexError':None, 'Flux':None,'FluxError':None, 'MaxBin':None}
return Results
else:
if UseGtlike == True:
# For use with gtlike results
binNumber = int(line.split()[0].split('/')[-1].replace('.txt:\'TS','').replace('likelihoodResults_bin','').strip())
TS = float("%.2f" % float(line.split()[2].strip().replace("'","").replace(',','')))
binNumbersReadIn.append(binNumber)
TSs.append(TS)
else:
# For use with pylikelihood results
binNumber = int(line.split()[0].split('/')[-1].replace('.log:TS','').replace('dtsmap_bin','').strip())
TS = float("%.2f" % float(line.split()[2].strip().replace("'","").replace(',','')))
binNumbersReadIn.append(binNumber)
TSs.append(TS)
# Put the results in a dictionary for easy retrieval later
LikelihoodResults = {key:value for key, value in zip(binNumbersReadIn,TSs)}
# Make an matrix to store the values. Saving any missing values as NaNs
TSMap = numpy.zeros(shape=(xsize, ysize))
binNumber = 0
xStep = 0
yStep = 0
for raStep in ra_range:
yStep = 0
for decStep in dec_range:
if binNumber in LikelihoodResults:
TSMap[xStep][yStep] = LikelihoodResults[binNumber]
pass
else:
print "Bad bin: %s" % binNumber
TSMap[xStep][yStep] = numpy.nan
pass
if TSMap[xStep][yStep] < -1:
TSMap[xStep][yStep] = numpy.nan
pass
binNumber = binNumber + 1
yStep = yStep + 1
pass
xStep = xStep + 1
pass
# # Loop through the results matrix and fill any missing values with interpolations from nearby pixels
# binNumber = 0
# xStep = 0
# yStep = 0
# for raStep in ra_range:
# yStep = 0
# for decStep in dec_range:
# if numpy.isnan(TSMap[xStep][yStep]) == True:
# # try:
# # TSMap[xStep][yStep] = numpy.mean([TSMap[xStep-1,yStep-1],TSMap[xStep-1,yStep],TSMap[xStep-1,yStep+1],TSMap[xStep,yStep-1],TSMap[xStep,yStep+1],TSMap[xStep+1,yStep-1],TSMap[xStep+1,yStep],TSMap[xStep+1,yStep+1]])
# try:
# if numpy.isnan(TSMap[xStep-1][yStep]) == False and numpy.isnan(TSMap[xStep+1][yStep]) == False:
# TSMap[xStep][yStep] = (TSMap[xStep-1][yStep] + TSMap[xStep+1][yStep]) / 2.0
# elif numpy.isnan(TSMap[xStep][yStep-1]) == False and numpy.isnan(TSMap[xStep][yStep+1]) == False:
# TSMap[xStep][yStep] = (TSMap[xStep][yStep-1] + TSMap[xStep][yStep+1]) / 2.0
# else:
# TSMap[xStep][yStep] = numpy.nan
# except:
# TSMap[xStep][yStep] = numpy.nan
# yStep = yStep + 1
# pass
# xStep = xStep + 1
# Finding the maximum TS
MaxTS = numpy.nanmax(TSMap)
MaxBin = numpy.nanargmax(TSMap)
# Check to see if a maximum couldn't be found.
if numpy.isnan(MaxBin) == True:
print "\nAnalysis Complete."
print "Maximum TS: %s" % 'None'
print "Coordinates: RA = %s, Dec = %s" % ('NA', 'NA')
print "*** Unable to locate maximum TS ***"
print '\nCleaning up...'
# Cat the gtlike log files
cmd = "cat %s/likelihoodResults_bin*.txt > dtsmap_LikelihoodResults.txt" % self.outdir
# print cmd
os.system(cmd)
# Cat the log files
cmd = "cat %s/dtsmap_bin*.log > dtsmap_LikelihoodFits.log" % self.outdir
# print cmd
os.system(cmd)
# Erase the individual xml files
cmd = "rm %s/ModelSource_bin*.xml" % self.outdir
# print cmd
os.system(cmd)
print 'Done.'
Results = {'MaxTS':None, 'MaxRA':None, 'MaxDec':None, 'Error':None, 'Index':None, 'IndexError':None, 'Flux':None,'FluxError':None, 'MaxBin':None}
return Results
else:
MaxRa = RaDecPairs[MaxBin][0]
MaxDec = RaDecPairs[MaxBin][1]
# Define default spectral parameters
index = 'NA'
indexError = 'NA'
flux = 'NA'
fluxError = 'NA'
if UseGtlike == True:
# Extract the fit parameters for the bin with the maximum TS (gtlike)
MaxBinFile = "%s/dtsmap_bin%s.log" % (LogDirectory, MaxBin)
for line in fileinput.input([MaxBinFile]):
if 'Index:' in line:
lineContents = line.split()
index = lineContents[1]
indexError = lineContents[3]
if 'Flux:' in line:
lineContents = line.split()
flux = lineContents[1]
fluxError = lineContents[3]
break
fileinput.close()
else:
# Extract the spectral fit parameters for the bin with the maximum TS (pyLikelihood)
MaxBinFile = "%s/dtsmap_bin%s.log" % (LogDirectory, MaxBin)
for line in fileinput.input([MaxBinFile]):
if 'Flux =' in line:
lineContents = line.split()
flux = float(lineContents[2])
fluxError = float(lineContents[4])
if 'Index =' in line:
lineContents = line.split()
index = float(lineContents[2])
indexError = float(lineContents[4])
fileinput.close()
# Rotate and flip the matrix in order to it to match ra and dec ordering conventions
TSMapRotated = numpy.rot90(TSMap)
TSMapFlippedUp = numpy.flipud(TSMapRotated)
TSMapFlippedLeft2Right = numpy.fliplr(TSMapFlippedUp)
MaxRa = RaDecPairs[numpy.nanargmax(TSMap)][0]
MaxDec = RaDecPairs[numpy.nanargmax(TSMap)][1]
# Import the basemap module
sys.path.append("/nfs/slac/g/ki/ki08/kocevski/LATBA/lib/python_rhel6-64/")
from mpl_toolkits.basemap import Basemap
# Create the figure
fig = plot.figure()
ax = fig.add_subplot(111)
# Create a base map on which to plot the results
#m = Basemap(llcrnrlon=ra_range[-1], llcrnrlat=dec_range[0], urcrnrlon=ra_range[0], urcrnrlat=dec_range[-1], projection='laea', lon_0 = ra, lat_0 = dec,resolution ='l',area_thresh=1000.)# ,celestial=True )
m = Basemap(height=5.5e5,width=5.5e5, projection='laea', lon_0 = ra*-1, lat_0 = dec, resolution ='l', area_thresh=1000., celestial=True )
# Set the plot limits (in map coordinates)
xMin, yMin = m(ra_range[0], dec_range[0])
xMax, yMax = m(ra_range[-1], dec_range[-1])
m.lonmin = xMin
m.lonmax = xMax
m.latmin = yMin
m.latmax = yMax
# Plot the matrix as an image
extent=[xMax, xMin, yMin, yMax]
#m.imshow(TSMapFlippedLeft2Right, origin='lower', extent=extent)
m.imshow(TSMapFlippedLeft2Right, origin='lower')
# Setup the map grid
m.drawmapboundary(fill_color='#ffffff')
m.drawparallels(numpy.arange(181)-90,labels=[1,0,0,0], fmt=customDecLabel, color='grey', linewidth=0)
m.drawmeridians(numpy.arange(0,360,1),labels=[0,0,0,1], fmt=customRALabel, color='grey', linewidth=0)
m.suppress_ticks = False
m.fix_aspect = False
# Force the aspect ratio to be 1:1
try:
forceAspect(ax,aspect=1)
#extent=[xMax, xMin, yMin, yMax]
#ax.set_aspect(abs((extent[1]-extent[0])/(extent[3]-extent[2])))
except Exception, message:
print traceback.format_exc()
def run(self, Test=True, Verbose=False, UseGtlike=False):
# Convert everything to a float
ra = float(self.xref)
dec = float(self.yref)
nxdeg = float(self.nxdeg)
nydeg = float(self.nydeg)
binsize = float(self.binsz)
# Get the current working directory
WorkingDirectory = os.getcwd()
# Define the output, log, and job directories
if self.outdir == None:
OutputDirectory = WorkingDirectory
LogDirectory = "%s/dtsmap/" % WorkingDirectory
JobsDirectory = "%s/dtsmap/" % WorkingDirectory
else:
OutputDirectory = self.outdir
LogDirectory = self.outdir
JobsDirectory = self.outdir
# Define the directory where this script is located
try:
ScriptDirectory = os.path.dirname(os.path.realpath(__file__))
except:
ScriptDirectory = None
# Creating the necessary directories
if (os.path.isdir(OutputDirectory) == False):
print "\nCreating Directory: " + OutputDirectory
cmd = "mkdir " + OutputDirectory
os.system(cmd)
if (os.path.isdir(LogDirectory) == False):
print "\nCreating Directory: " + LogDirectory
cmd = "mkdir " + LogDirectory
os.system(cmd)
if (os.path.isdir(JobsDirectory) == False):
print "\nCreating Directory: " + JobsDirectory
cmd = "mkdir " + JobsDirectory
os.system(cmd)
# Calculate tsmap grid
ra_min = ra - self.nxdeg / 2.0
ra_max = ra + self.nxdeg / 2.0
dec_min = dec - self.nydeg / 2.0
dec_max = dec + self.nydeg / 2.0
# Calcualate the range of ra and dec values
ra_range = numpy.arange(ra_min, ra_max + binsize, binsize)
dec_range = numpy.arange(dec_min, dec_max + binsize, binsize)
xsize = len(ra_range)
ysize = len(dec_range)
# Make sure that we don't have any ra values below zero or greater than 360, they should wrap ra instead.
for i in range(len(ra_range)):
if ra_range[i] < 0:
ra_range[i] = ra_range[i] + 360.0
if ra_range[i] > 360:
ra_range[i] = ra_range[i] - 360.0
# Make sure that we don't have any dec values below or above +/- 90, they should instead wrap in both ra and dec.
for i in range(len(dec_range)):
if dec_range[i] < -90:
dec_range[i] = ((dec_range[i] + 90) + 90) * -1
ra_range[i] = ra_range[i] + 180.0
if dec_range[i] > 90:
dec_range[i] = 90 - (dec_range[i] - 90)
ra_range[i] = ra_range[i] + 180
print "\nTS map grid size: %s x %s" % (len(ra_range), len(dec_range))
print "RA: %s to %s, Dec: %s to %s" % (ra_range[-1], ra_range[0],
dec_range[0], dec_range[-1])
print "Bin size: %s deg" % binsize
print " "
print "(%.2f, %.2f) (%.2f, %.2f)" % (ra_range[-1], dec_range[-1],
ra_range[0], dec_range[-1])
print " -----------------------------"
print " | |"
print " | |"
print " | |"
print " | |"
print " | (%.2f, %.2f) |" % (float(ra), float(dec))
print " | x |"
print " | |"
print " | |"
print " | |"
print " | |"
print " -----------------------------"
print "(%.2f, %.2f) (%.2f, %.2f)" % (ra_range[-1], dec_range[0],
ra_range[0], dec_range[-1])
print "\nSubmitting a total of %s Jobs" % (xsize * ysize)
# Mark the start time
startTime = time.time()
# Loop through all combinations of Ra and Dec and submit a job for each one
RaDecPairs = {}
binNumbers = []
binNumber = 0
# Keep track of the jobs submitted. This allows the user to specify how many jobs should be running at any given time.
JobsInQueue = 0
for raStep in ra_range:
for decStep in dec_range:
# Check to see if the number of jobs in the queue is greater than the max. If so, wait for the jobs to leave the queue before submitting more.
while JobsInQueue >= int(self.maxJobs):
print "\nMaximum number of submitted jobs (%s) reached. Waiting..." % self.maxJobs
print "Total number of remaining jobs to submit: %s" % remainingJobs
# Wait 30 seconds before polling the job statuses
time.sleep(60)
# Get the number of jobs actively in the queue
command = "bjobs -g %s | wc" % JobsDirectory
process = subprocess.Popen(command,
shell=True,
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
close_fds=True)
lines = process.stdout.readlines()
# Extract the number of jobs that are running
JobsInQueue = int(lines[0].split()[0])
# Setup the job
logfile = LogDirectory + "/dtsmap_bin%s.log" % binNumber
# Make the job name
try:
sourceNumber = int(
self.outdir.split('/')[-1].replace(
'dtsmap_Source', ''))
jobName = "dts_S%sb%s" % (sourceNumber, binNumber)
except:
jobName = "dtsmap_b%s" % binNumber
# Construct the command
command = """dtsmap.py scfile=%s evfile=%s expmap=%s expcube=%s cmap=%s srcmdl=%s irfs=%s source=%s optimizer=%s ftol=%s nxdeg=%s nydeg=%s binsz=%s coordsys=%s xref=%s yref=%s proj=%s statistic=%s binNumber=%s outfile=%s outdir=%s PerformAnalysis=1""" % (
self.scfile, self.evfile, self.expmap, self.expcube,
self.cmap, self.srcmdl, self.irfs, self.source,
self.optimizer, self.ftol, self.nxdeg, self.nydeg,
self.binsz, self.coordsys, raStep, decStep, self.proj,
self.statistic, binNumber, self.outfile, OutputDirectory)
# Specify where to find the python script
if ScriptDirectory != None:
command = ScriptDirectory + "/" + command
# Construct the process call
process = 'bsub -o ' + logfile + ' -J ' + jobName + ' -q xlong -R rhel60 -g ' + JobsDirectory + ' "' + command + '"'
# Display the command
if Verbose == True:
print process
# Start the process
if Test == False:
if self.batch == True:
subprocess.call(process, shell=True)
else:
os.system(command)
# Put the ra, dec, and bin info in a dictionary for easy retrieval later
RaDecPairs[binNumber] = [raStep, decStep]
# Increment the bin number
binNumbers.append(binNumber)
binNumber = binNumber + 1
# Increment the bin number
JobsInQueue = JobsInQueue + 1
# Get the number of remaining jobs
remainingJobs = ((xsize * ysize) - binNumber)
print "\nTotal number of jobs submitted: %s" % binNumber
print "All jobs submitted."
nJobs = -1
while nJobs != 0:
# Determine the number of jobs still running
command = "bjobs -g %s | wc" % JobsDirectory
process = subprocess.Popen(command,
shell=True,
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
close_fds=True)
lines = process.stdout.readlines()
# Display the results and the elapsed time since the start of the analysis
if 'No unfinished job found' in lines[0]:
nJobs = 0
print '\nAll Jobs Complete.'
# Display the elapsed time
elapsedTimeSeconds = time.time() - startTime
elapsedTimeMinutes = elapsedTimeSeconds / 60.0
elapsedTimeHours = elapsedTimeMinutes / 60.0
# Modify the units depending on the amount of time that has elapsed
if elapsedTimeMinutes > 60:
print "Total Elapsed Time: %.2f Hours" % elapsedTimeHours
else:
print "Total Elapsed Time: %.2f Minutes" % elapsedTimeMinutes
# Make sure we actually break out of this while loop!
break
else:
# Get the number of jobs in the queue from the stdout
nJobs = int(lines[0].split()[0])
print "\nJobs Remaining: %s" % nJobs
# Display the elapsed time
elapsedTimeSeconds = time.time() - startTime
elapsedTimeMinutes = elapsedTimeSeconds / 60.0
elapsedTimeHours = elapsedTimeMinutes / 60.0
if elapsedTimeMinutes > 60:
print "Elapsed Time: %.2f Hours" % elapsedTimeHours
else:
print "Elapsed Time: %.2f Minutes" % elapsedTimeMinutes
# Wait 120 seconds before polling the job statuses
time.sleep(120)
if UseGtlike == True:
# Gather the results (gtlike)
command = "grep 'TS value' %s/likelihoodResults_bin*.txt" % LogDirectory
process = subprocess.Popen(command,
shell=True,
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
close_fds=True)
lines = process.stdout.readlines()
else:
# Gather the results (pylikelihood)
command = "grep 'TS = ' %s/dtsmap_bin*.log" % LogDirectory
process = subprocess.Popen(command,
shell=True,
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
close_fds=True)
lines = process.stdout.readlines()
# Read in the results
binNumbersReadIn = []
TSs = []
for line in lines:
if ('No match' in line) or ('grep' in line):
print "Error: *** No available likelihood results ***"
print "Check your science tools setup and try again..."
print "Exiting.\n"
Results = {
'MaxTS': None,
'MaxRA': None,
'MaxDec': None,
'Error': None,
'Index': None,
'IndexError': None,
'Flux': None,
'FluxError': None,
'MaxBin': None
}
return Results
else:
if UseGtlike == True:
# For use with gtlike results
binNumber = int(line.split()[0].split('/')[-1].replace(
'.txt:\'TS', '').replace('likelihoodResults_bin',
'').strip())
TS = float("%.2f" % float(line.split()[2].strip().replace(
"'", "").replace(',', '')))
binNumbersReadIn.append(binNumber)
TSs.append(TS)
else:
# For use with pylikelihood results
binNumber = int(line.split()[0].split('/')[-1].replace(
'.log:TS', '').replace('dtsmap_bin', '').strip())
TS = float("%.2f" % float(line.split()[2].strip().replace(
"'", "").replace(',', '')))
binNumbersReadIn.append(binNumber)
TSs.append(TS)
# Put the results in a dictionary for easy retrieval later
LikelihoodResults = {
key: value
for key, value in zip(binNumbersReadIn, TSs)
}
# Make an matrix to store the values. Saving any missing values as NaNs
TSMap = numpy.zeros(shape=(xsize, ysize))
binNumber = 0
xStep = 0
yStep = 0
for raStep in ra_range:
yStep = 0
for decStep in dec_range:
if binNumber in LikelihoodResults:
TSMap[xStep][yStep] = LikelihoodResults[binNumber]
pass
else:
print "Bad bin: %s" % binNumber
TSMap[xStep][yStep] = numpy.nan
pass
if TSMap[xStep][yStep] < -1:
TSMap[xStep][yStep] = numpy.nan
pass
binNumber = binNumber + 1
yStep = yStep + 1
pass
xStep = xStep + 1
pass
# # Loop through the results matrix and fill any missing values with interpolations from nearby pixels
# binNumber = 0
# xStep = 0
# yStep = 0
# for raStep in ra_range:
# yStep = 0
# for decStep in dec_range:
# if numpy.isnan(TSMap[xStep][yStep]) == True:
# # try:
# # TSMap[xStep][yStep] = numpy.mean([TSMap[xStep-1,yStep-1],TSMap[xStep-1,yStep],TSMap[xStep-1,yStep+1],TSMap[xStep,yStep-1],TSMap[xStep,yStep+1],TSMap[xStep+1,yStep-1],TSMap[xStep+1,yStep],TSMap[xStep+1,yStep+1]])
# try:
# if numpy.isnan(TSMap[xStep-1][yStep]) == False and numpy.isnan(TSMap[xStep+1][yStep]) == False:
# TSMap[xStep][yStep] = (TSMap[xStep-1][yStep] + TSMap[xStep+1][yStep]) / 2.0
# elif numpy.isnan(TSMap[xStep][yStep-1]) == False and numpy.isnan(TSMap[xStep][yStep+1]) == False:
# TSMap[xStep][yStep] = (TSMap[xStep][yStep-1] + TSMap[xStep][yStep+1]) / 2.0
# else:
# TSMap[xStep][yStep] = numpy.nan
# except:
# TSMap[xStep][yStep] = numpy.nan
# yStep = yStep + 1
# pass
# xStep = xStep + 1
# Finding the maximum TS
MaxTS = numpy.nanmax(TSMap)
MaxBin = numpy.nanargmax(TSMap)
# Check to see if a maximum couldn't be found.
if numpy.isnan(MaxBin) == True:
print "\nAnalysis Complete."
print "Maximum TS: %s" % 'None'
print "Coordinates: RA = %s, Dec = %s" % ('NA', 'NA')
print "*** Unable to locate maximum TS ***"
print '\nCleaning up...'
# Cat the gtlike log files
cmd = "cat %s/likelihoodResults_bin*.txt > dtsmap_LikelihoodResults.txt" % self.outdir
# print cmd
os.system(cmd)
# Cat the log files
cmd = "cat %s/dtsmap_bin*.log > dtsmap_LikelihoodFits.log" % self.outdir
# print cmd
os.system(cmd)
# Erase the individual xml files
cmd = "rm %s/ModelSource_bin*.xml" % self.outdir
# print cmd
os.system(cmd)
print 'Done.'
Results = {
'MaxTS': None,
'MaxRA': None,
'MaxDec': None,
'Error': None,
'Index': None,
'IndexError': None,
'Flux': None,
'FluxError': None,
'MaxBin': None
}
return Results
else:
MaxRa = RaDecPairs[MaxBin][0]
MaxDec = RaDecPairs[MaxBin][1]
# Define default spectral parameters
index = 'NA'
indexError = 'NA'
flux = 'NA'
fluxError = 'NA'
if UseGtlike == True:
# Extract the fit parameters for the bin with the maximum TS (gtlike)
MaxBinFile = "%s/dtsmap_bin%s.log" % (LogDirectory, MaxBin)
for line in fileinput.input([MaxBinFile]):
if 'Index:' in line:
lineContents = line.split()
index = lineContents[1]
indexError = lineContents[3]
if 'Flux:' in line:
lineContents = line.split()
flux = lineContents[1]
fluxError = lineContents[3]
break
fileinput.close()
else:
# Extract the spectral fit parameters for the bin with the maximum TS (pyLikelihood)
MaxBinFile = "%s/dtsmap_bin%s.log" % (LogDirectory, MaxBin)
for line in fileinput.input([MaxBinFile]):
if 'Flux =' in line:
lineContents = line.split()
flux = float(lineContents[2])
fluxError = float(lineContents[4])
if 'Index =' in line:
lineContents = line.split()
index = float(lineContents[2])
indexError = float(lineContents[4])
fileinput.close()
# Rotate and flip the matrix in order to it to match ra and dec ordering conventions
TSMapRotated = numpy.rot90(TSMap)
TSMapFlippedUp = numpy.flipud(TSMapRotated)
TSMapFlippedLeft2Right = numpy.fliplr(TSMapFlippedUp)
MaxRa = RaDecPairs[numpy.nanargmax(TSMap)][0]
MaxDec = RaDecPairs[numpy.nanargmax(TSMap)][1]
# Import the basemap module
sys.path.append(
"/nfs/slac/g/ki/ki08/kocevski/LATBA/lib/python_rhel6-64/")
from mpl_toolkits.basemap import Basemap
# Create the figure
fig = plot.figure()
ax = fig.add_subplot(111)
# Create a base map on which to plot the results
#m = Basemap(llcrnrlon=ra_range[-1], llcrnrlat=dec_range[0], urcrnrlon=ra_range[0], urcrnrlat=dec_range[-1], projection='laea', lon_0 = ra, lat_0 = dec,resolution ='l',area_thresh=1000.)# ,celestial=True )
m = Basemap(height=5.5e5,
width=5.5e5,
projection='laea',
lon_0=ra * -1,
lat_0=dec,
resolution='l',
area_thresh=1000.,
celestial=True)
# Set the plot limits (in map coordinates)
xMin, yMin = m(ra_range[0], dec_range[0])
xMax, yMax = m(ra_range[-1], dec_range[-1])
m.lonmin = xMin
m.lonmax = xMax
m.latmin = yMin
m.latmax = yMax
# Plot the matrix as an image
extent = [xMax, xMin, yMin, yMax]
#m.imshow(TSMapFlippedLeft2Right, origin='lower', extent=extent)
m.imshow(TSMapFlippedLeft2Right, origin='lower')
# Setup the map grid
m.drawmapboundary(fill_color='#ffffff')
m.drawparallels(numpy.arange(181) - 90,
labels=[1, 0, 0, 0],
fmt=customDecLabel,
color='grey',
linewidth=0)
m.drawmeridians(numpy.arange(0, 360, 1),
labels=[0, 0, 0, 1],
fmt=customRALabel,
color='grey',
linewidth=0)
m.suppress_ticks = False
m.fix_aspect = False
# Force the aspect ratio to be 1:1
try:
forceAspect(ax, aspect=1)
#extent=[xMax, xMin, yMin, yMax]
#ax.set_aspect(abs((extent[1]-extent[0])/(extent[3]-extent[2])))
except Exception, message:
print traceback.format_exc()
def Plot(UseGtlike=False):
# ra = 260.21
# dec = -77.92
# binsize = 0.25
# LogDirectory = '/Users/kocevski/Research/Analysis/FAVA/Results/dtsmap_Source18'
ra = 99.2
dec = -3.92
binsize = 0.25
LogDirectory = '/Users/kocevski/Research/Analysis/FAVA/Results/dtsmap_Source27'
nxdeg = 5
nydeg = 5
ra_min = ra - nxdeg/2.0
ra_max = ra + nxdeg/2.0
dec_min = dec - nydeg/2.0
dec_max = dec + nydeg/2.0
# Calcualate the range of ra and dec values
ra_range = numpy.arange(ra_min,ra_max+binsize,binsize)
dec_range = numpy.arange(dec_min,dec_max+binsize,binsize)
xsize = len(ra_range)
ysize = len(dec_range)
# Make sure that we don't have any ra values below zero or greater than 360, they should wrap ra instead.
for i in range(len(ra_range)):
if ra_range[i] < 0:
ra_range[i] = ra_range[i] + 360.0
if ra_range[i] > 360:
ra_range[i] = ra_range[i] - 360.0
# Make sure that we don't have any dec values below or above +/- 90, they should instead wrap in both ra and dec.
for i in range(len(dec_range)):
if dec_range[i] < -90:
dec_range[i] = ((dec_range[i] + 90) + 90)*-1
ra_range[i] = ra_range[i] + 180.0
if dec_range[i] > 90:
dec_range[i] = 90 - (dec_range[i] - 90)
ra_range[i] = ra_range[i] + 180
RaDecMap = numpy.zeros(shape=(xsize, ysize))
RaDecMap = RaDecMap.astype(str)
RaDecPairs = {}
binNumbers = []
binNumber = 0
xStep = 0
yStep = 0
for raStep in ra_range:
yStep = 0
for decStep in dec_range:
RaDecPairs[binNumber] = [raStep,decStep]
RaDecMap[xStep][yStep] = "%s,%s" % (raStep,decStep)
binNumbers.append(binNumber)
binNumber = binNumber + 1
yStep = yStep + 1
pass
xStep = xStep + 1
pass
# Gather the results (pylikelihood)
command = "grep 'TS = ' %s/dtsmap_bin*.log" % LogDirectory
process = subprocess.Popen(command, shell=True, stdin=subprocess.PIPE, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, close_fds=True)
lines = process.stdout.readlines()
# Read in the results
binNumbersReadIn = []
TSs = []
for line in lines:
if ('No match' in line) or ('grep' in line):
print "Error: *** No available likelihood results ***"
print "Check your science tools setup and try again..."
print "Exiting.\n"
Results = {'MaxTS':None, 'MaxRA':None, 'MaxDec':None, 'Error':None, 'Index':None, 'IndexError':None, 'Flux':None,'FluxError':None, 'MaxBin':None}
return Results
else:
# For use with pylikelihood results
binNumber = int(line.split()[0].split('/')[-1].replace('.log:TS','').replace('dtsmap_bin','').strip())
TS = float("%.2f" % float(line.split()[2].strip().replace("'","").replace(',','')))
binNumbersReadIn.append(binNumber)
TSs.append(TS)
# Put the results in a dictionary for easy retrieval later
LikelihoodResults = {key:value for key, value in zip(binNumbersReadIn,TSs)}
# Make an matrix to store the values. Saving any missing values as NaNs
TSMap = numpy.zeros(shape=(xsize, ysize))
binNumber = 0
xStep = 0
yStep = 0
for raStep in ra_range:
yStep = 0
for decStep in dec_range:
if binNumber in LikelihoodResults:
TSMap[xStep][yStep] = LikelihoodResults[binNumber]
pass
else:
print "Bad bin: %s" % binNumber
TSMap[xStep][yStep] = numpy.nan
pass
if TSMap[xStep][yStep] < -1:
TSMap[xStep][yStep] = numpy.nan
pass
binNumber = binNumber + 1
yStep = yStep + 1
pass
xStep = xStep + 1
pass
# Loop through the results matrix and fill any missing values with interpolations from nearby pixels
binNumber = 0
xStep = 0
yStep = 0
for raStep in ra_range:
yStep = 0
for decStep in dec_range:
if numpy.isnan(TSMap[xStep][yStep]) == True:
# try:
# TSMap[xStep][yStep] = numpy.mean([TSMap[xStep-1,yStep-1],TSMap[xStep-1,yStep],TSMap[xStep-1,yStep+1],TSMap[xStep,yStep-1],TSMap[xStep,yStep+1],TSMap[xStep+1,yStep-1],TSMap[xStep+1,yStep],TSMap[xStep+1,yStep+1]])
try:
if numpy.isnan(TSMap[xStep-1][yStep]) == False and numpy.isnan(TSMap[xStep+1][yStep]) == False:
TSMap[xStep][yStep] = (TSMap[xStep-1][yStep] + TSMap[xStep+1][yStep]) / 2.0
elif numpy.isnan(TSMap[xStep][yStep-1]) == False and numpy.isnan(TSMap[xStep][yStep+1]) == False:
TSMap[xStep][yStep] = (TSMap[xStep][yStep-1] + TSMap[xStep][yStep+1]) / 2.0
else:
TSMap[xStep][yStep] = numpy.nan
except:
TSMap[xStep][yStep] = numpy.nan
yStep = yStep + 1
pass
xStep = xStep + 1
# Finding the maximum TS
MaxTS = numpy.nanmax(TSMap)
MaxBin = numpy.nanargmax(TSMap)
# Check to see if a maximum couldn't be found.
if numpy.isnan(MaxBin) == True:
print "\nAnalysis Complete."
print "Maximum TS: %s" % 'None'
print "Coordinates: RA = %s, Dec = %s" % ('NA', 'NA')
print "*** Unable to locate maximum TS ***"
print '\nCleaning up...'
# Cat the gtlike log files
cmd = "cat %s/likelihoodResults_bin*.txt > dtsmap_LikelihoodResults.txt" % self.outdir
# print cmd
os.system(cmd)
# Cat the log files
cmd = "cat %s/dtsmap_bin*.log > dtsmap_LikelihoodFits.log" % self.outdir
# print cmd
os.system(cmd)
# Erase the individual xml files
cmd = "rm %s/ModelSource_bin*.xml" % self.outdir
# print cmd
os.system(cmd)
print 'Done.'
Results = {'MaxTS':None, 'MaxRA':None, 'MaxDec':None, 'Error':None, 'Index':None, 'IndexError':None, 'Flux':None,'FluxError':None, 'MaxBin':None}
return Results
else:
MaxRa = RaDecPairs[MaxBin][0]
MaxDec = RaDecPairs[MaxBin][1]
# Define default spectral parameters
index = 'NA'
indexError = 'NA'
flux = 'NA'
fluxError = 'NA'
if UseGtlike == True:
# Extract the fit parameters for the bin with the maximum TS (gtlike)
MaxBinFile = "%s/dtsmap_bin%s.log" % (LogDirectory, MaxBin)
for line in fileinput.input([MaxBinFile]):
if 'Index:' in line:
lineContents = line.split()
index = lineContents[1]
indexError = lineContents[3]
if 'Flux:' in line:
lineContents = line.split()
flux = lineContents[1]
fluxError = lineContents[3]
break
fileinput.close()
else:
# Extract the spectral fit parameters for the bin with the maximum TS (pyLikelihood)
MaxBinFile = "%s/dtsmap_bin%s.log" % (LogDirectory, MaxBin)
for line in fileinput.input([MaxBinFile]):
if 'Flux =' in line:
lineContents = line.split()
flux = float(lineContents[2])
fluxError = float(lineContents[4])
if 'Index =' in line:
lineContents = line.split()
index = float(lineContents[2])
indexError = float(lineContents[4])
fileinput.close()
# Rotate and flip the matrix in order to it to match ra and dec ordering conventions
TSMapRotated = numpy.rot90(TSMap)
TSMapFlippedUp = numpy.flipud(TSMapRotated)
TSMapFlippedLeft2Right = numpy.fliplr(TSMapFlippedUp)
MaxRa = RaDecPairs[numpy.nanargmax(TSMap)][0]
MaxDec = RaDecPairs[numpy.nanargmax(TSMap)][1]
# Import the basemap module
sys.path.append("/nfs/slac/g/ki/ki08/kocevski/LATBA/lib/python_rhel6-64/")
from mpl_toolkits.basemap import Basemap
# Create the figure
fig = plot.figure()
ax = fig.add_subplot(111)
# Create a base map on which to plot the results
m = Basemap(height=5.5e5,width=5.5e5, projection='laea', lon_0 = ra*-1, lat_0 = dec, resolution ='l', area_thresh=1000., celestial=True )
# Set the plot limits (in map coordinates)
xMin, yMin = m(ra_range[0], dec_range[0])
xMax, yMax = m(ra_range[-1], dec_range[-1])
m.lonmin = xMin
m.lonmax = xMax
m.latmin = yMin
m.latmax = yMax
# Plot the matrix as an image
extent=[xMax, xMin, yMin, yMax]
#m.imshow(TSMapFlippedLeft2Right, origin='lower', extent=extent)
m.imshow(TSMapFlippedLeft2Right, origin='lower')
# Setup the map grid
m.drawmapboundary(fill_color='#ffffff')
m.drawparallels(numpy.arange(181)-90,labels=[1,0,0,0], fmt=customDecLabel, color='grey', linewidth=0.25)
m.drawmeridians(numpy.arange(0,360,1),labels=[0,0,0,1], fmt=customRALabel, color='grey', linewidth=0.25)
m.suppress_ticks = False
m.fix_aspect = False
# Force the aspect ratio to be 1:1
try:
forceAspect(ax,aspect=1)
#extent=[xMax, xMin, yMin, yMax]
#ax.set_aspect(abs((extent[1]-extent[0])/(extent[3]-extent[2])))
except Exception, message:
print traceback.format_exc()