| 16 |
|
help="samples you want to run on") |
| 17 |
|
parser.add_option("-F", "--folderTag", dest="ftag", default="", |
| 18 |
|
help="Creats a new folder structure for outputs or uses an existing one with the given name") |
| 19 |
+ |
parser.add_option("-N", "--number-of-events", dest="nevents_split", default=100000, |
| 20 |
+ |
help="Number of events per file when splitting.") |
| 21 |
+ |
parser.add_option("-P", "--philipp-love-progress-bars", dest="philipp_love_progress_bars", default=False, |
| 22 |
+ |
help="If you share the love of Philipp...") |
| 23 |
+ |
|
| 24 |
|
(opts, args) = parser.parse_args(sys.argv) |
| 25 |
|
|
| 26 |
< |
import os,shutil,pickle,subprocess,ROOT |
| 26 |
> |
import os,shutil,pickle,subprocess,ROOT,re |
| 27 |
|
ROOT.gROOT.SetBatch(True) |
| 28 |
|
from myutils import BetterConfigParser, Sample, ParseInfo |
| 29 |
|
import getpass |
| 99 |
|
print 'Exit' |
| 100 |
|
sys.exit(-1) |
| 101 |
|
|
| 102 |
< |
repDict = {'en':en,'logpath':logPath,'job':'','task':opts.task,'queue': 'all.q','timestamp':timestamp} |
| 102 |
> |
repDict = {'en':en,'logpath':logPath,'job':'','task':opts.task,'queue': 'all.q','timestamp':timestamp,'additional':'','job_id':''} |
| 103 |
|
def submit(job,repDict): |
| 104 |
|
repDict['job'] = job |
| 105 |
< |
command = 'qsub -V -cwd -q %(queue)s -l h_vmem=6G -N %(job)s_%(en)s%(task)s -o %(logpath)s/%(timestamp)s_%(job)s_%(en)s_%(task)s.out -e %(logpath)s/%(timestamp)s_%(job)s_%(en)s_%(task)s.err runAll.sh %(job)s %(en)s ' %(repDict) + opts.task |
| 105 |
> |
command = 'qsub -V -cwd -q %(queue)s -l h_vmem=6G -N %(job)s_%(en)s%(task)s -o %(logpath)s/%(timestamp)s_%(job)s_%(en)s_%(task)s.out -e %(logpath)s/%(timestamp)s_%(job)s_%(en)s_%(task)s.err runAll.sh %(job)s %(en)s ' %(repDict) + opts.task + ' ' + repDict['job_id'] + ' ' + repDict['additional'] |
| 106 |
|
print command |
| 107 |
|
subprocess.call([command], shell=True) |
| 108 |
|
|
| 131 |
|
for item in Plot_vars: |
| 132 |
|
submit(item,repDict) |
| 133 |
|
|
| 134 |
+ |
|
| 135 |
|
elif opts.task == 'dc': |
| 136 |
|
repDict['queue'] = 'all.q' |
| 137 |
|
for item in DC_vars: |
| 143 |
|
elif opts.task == 'prep': |
| 144 |
|
submit('prepare',repDict) |
| 145 |
|
|
| 146 |
< |
elif opts.task == 'eval' or opts.task == 'sys' or opts.task == 'syseval': |
| 146 |
> |
elif opts.task == 'sys' or opts.task == 'syseval': |
| 147 |
> |
path = config.get("Directories","SYSin") |
| 148 |
> |
samplesinfo = config.get("Directories","samplesinfo") |
| 149 |
> |
info = ParseInfo(samplesinfo,path) |
| 150 |
> |
if ( opts.samples == ""): |
| 151 |
> |
for job in info: |
| 152 |
> |
if (job.subsample): continue |
| 153 |
> |
submit(job.name,repDict) |
| 154 |
> |
else: |
| 155 |
> |
for sample in samplesList: |
| 156 |
> |
submit(sample,repDict) |
| 157 |
> |
|
| 158 |
> |
elif opts.task == 'eval': |
| 159 |
> |
path = config.get("Directories","MVAin") |
| 160 |
> |
samplesinfo = config.get("Directories","samplesinfo") |
| 161 |
> |
info = ParseInfo(samplesinfo,path) |
| 162 |
|
if ( opts.samples == ""): |
| 163 |
|
for job in info: |
| 164 |
+ |
if (job.subsample): continue |
| 165 |
|
submit(job.name,repDict) |
| 166 |
|
else: |
| 167 |
|
for sample in samplesList: |
| 168 |
|
submit(sample,repDict) |
| 169 |
|
|
| 170 |
< |
os.system('qstat') |
| 171 |
< |
os.system('./qstat.py') |
| 170 |
> |
|
| 171 |
> |
elif( opts.task == 'split' ): |
| 172 |
> |
path = config.get("Directories","SPLITin") |
| 173 |
> |
samplesinfo = config.get("Directories","samplesinfo") |
| 174 |
> |
repDict['additional']=opts.nevents_split |
| 175 |
> |
info = ParseInfo(samplesinfo,path) |
| 176 |
> |
if ( opts.samples == ""): |
| 177 |
> |
for job in info: |
| 178 |
> |
if (job.subsample): continue |
| 179 |
> |
submit(job.name,repDict) |
| 180 |
> |
else: |
| 181 |
> |
for sample in samplesList: |
| 182 |
> |
submit(sample,repDict) |
| 183 |
> |
|
| 184 |
> |
#BDT optimisation |
| 185 |
> |
elif opts.task == 'mva_opt': |
| 186 |
> |
total_number_of_steps=1 |
| 187 |
> |
setting = '' |
| 188 |
> |
for par in (config.get('Optimisation','parameters').split(',')): |
| 189 |
> |
scan_par=eval(config.get('Optimisation',par)) |
| 190 |
> |
setting+=par+'='+str(scan_par[0])+':' |
| 191 |
> |
if len(scan_par) > 1 and scan_par[2] != 0: |
| 192 |
> |
total_number_of_steps+=scan_par[2] |
| 193 |
> |
setting=setting[:-1] # eliminate last column at the end of the setting string |
| 194 |
> |
print setting |
| 195 |
> |
repDict['additional']=setting |
| 196 |
> |
repDict['job_id']=config.get('Optimisation','training') |
| 197 |
> |
submit('OPT_main_set',repDict) |
| 198 |
> |
main_setting=setting |
| 199 |
> |
|
| 200 |
> |
#Scanning all the parameters found in the training config in the Optimisation sector |
| 201 |
> |
for par in (config.get('Optimisation','parameters').split(',')): |
| 202 |
> |
scan_par=eval(config.get('Optimisation',par)) |
| 203 |
> |
print par |
| 204 |
> |
if len(scan_par) > 1 and scan_par[2] != 0: |
| 205 |
> |
for step in range(scan_par[2]): |
| 206 |
> |
value = (scan_par[0])+((1+step)*(scan_par[1]-scan_par[0])/scan_par[2]) |
| 207 |
> |
print value |
| 208 |
> |
setting=re.sub(par+'.*?:',par+'='+str(value)+':',main_setting) |
| 209 |
> |
repDict['additional']=setting |
| 210 |
> |
# repDict['job_id']=config.get('Optimisation','training') |
| 211 |
> |
submit('OPT_'+par+str(value),repDict) |
| 212 |
> |
# submit(config.get('Optimisation','training'),repDict) |
| 213 |
> |
print setting |
| 214 |
> |
|
| 215 |
> |
|
| 216 |
> |
os.system('qstat') |
| 217 |
> |
if (opts.philipp_love_progress_bars): |
| 218 |
> |
os.system('./qstat.py') |
