VHbb/python/submitThem.py

#! /usr/bin/env python
from optparse import OptionParser
import sys
import time
import os
import shutil

parser = OptionParser()
parser.add_option("-T", "--tag", dest="tag", default="8TeV",
                      help="Tag to run the analysis with, example '8TeV' uses config8TeV and pathConfig8TeV to run the analysis")
parser.add_option("-J", "--task", dest="task", default="",
                      help="Task to be done, i.e. 'dc' for Datacards, 'prep' for preparation of Trees, 'plot' to produce plots or 'eval' to write the MVA output or 'sys' to write regression and systematics (or 'syseval' for both). ")
parser.add_option("-M", "--mass", dest="mass", default="125",
              help="Mass for DC or Plots, 110...135")
parser.add_option("-S","--samples",dest="samples",default="",
              help="samples you want to run on")
parser.add_option("-F", "--folderTag", dest="ftag", default="",
                      help="Creats a new folder structure for outputs or uses an existing one with the given name")
parser.add_option("-N", "--number-of-events", dest="nevents_split", default=100000,
                      help="Number of events per file when splitting.")
parser.add_option("-P", "--philipp-love-progress-bars", dest="philipp_love_progress_bars", default=False,
                      help="If you share the love of Philipp...")

(opts, args) = parser.parse_args(sys.argv)

import os,shutil,pickle,subprocess,ROOT,re
ROOT.gROOT.SetBatch(True)
from myutils import BetterConfigParser, Sample, ParseInfo, sample_parser
import getpass

if opts.tag == "":
    print "Please provide tag to run the analysis with, example '-T 8TeV' uses config8TeV and pathConfig8TeV to run the analysis."
    sys.exit(123)

if opts.task == "":
    print "Please provide a task.\n-J prep:\tpreparation of Trees\n-J sys:\t\twrite regression and systematics\n-J eval:\tcreate MVA output\n-J plot:\tproduce Plots\n-J dc:\t\twrite workspaces and datacards"
    sys.exit(123)


en = opts.tag

#create the list with the samples to run over
samplesList=opts.samples.split(",")
timestamp = time.asctime().replace(' ','_').replace(':','-')

# the list of the config is taken from the path config
pathconfig = BetterConfigParser()
pathconfig.read('%sconfig/paths'%(en))
_configs = pathconfig.get('Configuration','List').split(" ")
configs = [ '%sconfig/'%(en) + c for c in _configs  ]

if not opts.ftag == '':
    tagDir = pathconfig.get('Directories','tagDir')
    DirStruct={'tagDir':tagDir,'ftagdir':'%s/%s/'%(tagDir,opts.ftag),'logpath':'%s/%s/%s/'%(tagDir,opts.ftag,'Logs'),'plotpath':'%s/%s/%s/'%(tagDir,opts.ftag,'Plots'),'limitpath':'%s/%s/%s/'%(tagDir,opts.ftag,'Limits'),'confpath':'%s/%s/%s/'%(tagDir,opts.ftag,'config') }

    for keys in ['tagDir','ftagdir','logpath','plotpath','limitpath','confpath']:
        try:
            os.stat(DirStruct[keys])
        except:
            os.mkdir(DirStruct[keys])

    pathfile = open('%sconfig/paths'%(en))
    buffer = pathfile.readlines()
    pathfile.close()
    os.rename('%sconfig/paths'%(en),'%sconfig/paths.bkp'%(en))
    pathfile = open('%sconfig/paths'%(en),'w')
    for line in buffer:
        if line.startswith('plotpath'):
            line = 'plotpath: %s\n'%DirStruct['plotpath']
        elif line.startswith('logpath'):
            line = 'logpath: %s\n'%DirStruct['logpath']
        elif line.startswith('limits'):
            line = 'limits: %s\n'%DirStruct['limitpath']
        pathfile.write(line)
    pathfile.close()

    #copy config files
    for item in configs:
        shutil.copyfile(item,'%s/%s/%s'%(tagDir,opts.ftag,item.strip(en)))


print configs
config = BetterConfigParser()
config.read(configs)

def dump_config(configs,output_file):
    """
    Dump all the configs in a output file
    Args:
        output_file: the file where the log will be dumped 
        configs: list of files (string) to be dumped
    Returns:
        nothing
    """
    outf = open(output_file,'w') 
    for i in configs:
        try:
            f=open(i,'r')
            outf.write(f.read())
        except: print '@WARNING: Config' + i + ' not found. It will not be used.'

def compile_macro(config,macro):
    """
    Creates the library from a macro using CINT compiling it in scratch to avoid
    problems with the linking in the working nodes.
    Args:
        config: configuration file where the macro path is specified
        macro: macro name to be compiled
    Returns:
        nothing
    """
    submitDir = os.getcwd()
    _macro=macro+'.h'
    library = config.get(macro,'library')
    libDir=os.path.dirname(library)
    os.chdir(libDir)
    if not os.path.exists(library):
        print '@INFO: Compiling ' + _macro
        scratchDir='/scratch/%s/'%(getpass.getuser())
        shutil.copyfile(libDir+'/'+_macro,'/scratch/%s/%s'%(getpass.getuser(),_macro))
        os.chdir(scratchDir)
        ROOT.gROOT.ProcessLine('.L %s+'%(scratchDir+_macro))
        shutil.copyfile('/scratch/%s/%s'%(getpass.getuser(),os.path.basename(library)),library)
    os.chdir(submitDir)
        
compile_macro(config,'BTagReshaping')
compile_macro(config,'VHbbNameSpace')

logPath = config.get("Directories","logpath")
logo = open('%s/data/submit.txt' %config.get('Directories','vhbbpath')).readlines()
counter = 0

#check if the logPath exist. If not exit
if( not os.path.isdir(logPath) ):
    print '@ERROR : ' + logPath + ': dir not found.'
    print '@ERROR : Create it before submitting '
    print 'Exit'
    sys.exit(-1)
    
repDict = {'en':en,'logpath':logPath,'job':'','task':opts.task,'queue': 'all.q','timestamp':timestamp,'additional':'','job_id':''}
def submit(job,repDict):
    global counter
    repDict['job'] = job
    nJob = counter % len(logo)
    counter += 1
    if opts.philipp_love_progress_bars:
        repDict['name'] = '"%s"' %logo[nJob].strip()
    else:
        repDict['name'] = '%(job)s_%(en)s%(task)s' %repDict
    command = 'qsub -V -cwd -q %(queue)s -l h_vmem=6G -N %(name)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']
    print command
    dump_config(configs,"%(logpath)s/%(timestamp)s_%(job)s_%(en)s_%(task)s.config" %(repDict))
    subprocess.call([command], shell=True)

if opts.task == 'train':
    train_list = (config.get('MVALists','List_for_submitscript')).split(',')
    print train_list
    for item in train_list:
        submit(item,repDict)


if opts.task == 'dc':
    #DC_vars = config.items('Limit')
    DC_vars= (config.get('LimitGeneral','List')).split(',')
    print DC_vars

if opts.task == 'plot':
    Plot_vars= (config.get('Plot_general','List')).split(',')

if not opts.task == 'prep':
    path = config.get("Directories","samplepath")
    samplesinfo = config.get("Directories","samplesinfo")
    info = ParseInfo(samplesinfo,path)

if opts.task == 'plot': 
    repDict['queue'] = 'all.q'
    for item in Plot_vars:
        submit(item,repDict)

if opts.task == 'trainReg':
    repDict['queue'] = 'all.q'
    submit('trainReg',repDict)


elif opts.task == 'dc':
    repDict['queue'] = 'all.q'
    for item in DC_vars:
        if 'ZH%s'%opts.mass in item:
            submit(item,repDict) 
        elif opts.mass == 'all':
            submit(item,repDict)
            
elif opts.task == 'prep':
    if ( opts.samples == ""):
        path = config.get("Directories","PREPin")
        samplesinfo = config.get("Directories","samplesinfo")
        info = ParseInfo(samplesinfo,path)
        for job in info:
            submit(job.name,repDict)

    else:
        for sample in samplesList:
            submit(sample,repDict)
elif opts.task == 'sys' or opts.task == 'syseval':
    path = config.get("Directories","SYSin")
    samplesinfo = config.get("Directories","samplesinfo")
    info = ParseInfo(samplesinfo,path)
    if opts.samples == "":
        for job in info:
            if (job.subsample): 
                continue #avoid multiple submissions form subsamples
            # TO FIX FOR SPLITTED SAMPLE
            submit(job.name,repDict)
    else:
        for sample in samplesList:
            submit(sample,repDict)

elif opts.task == 'eval':
    repDict['queue'] = 'long.q'
    path = config.get("Directories","MVAin")
    samplesinfo = config.get("Directories","samplesinfo")
    info = ParseInfo(samplesinfo,path)
    if opts.samples == "":
        for job in info:
            if (job.subsample): 
                continue #avoid multiple submissions from subsamples
            if(info.checkSplittedSampleName(job.identifier)): # if multiple entries for one name  (splitted samples) use the identifier to submit
                print '@INFO: Splitted samples: submit through identifier'
                submit(job.identifier,repDict)
            else: submit(job.name,repDict)
    else:
        for sample in samplesList:
            print sample
            submit(sample,repDict)


elif( opts.task == 'split' ):
        path = config.get("Directories","SPLITin")
        samplesinfo = config.get("Directories","samplesinfo")
        repDict['job_id']=opts.nevents_split
        info = ParseInfo(samplesinfo,path)
        if ( opts.samples == "" ):
                for job in info:
                        if (job.subsample): continue #avoid multiple submissions from subsamples
                        submit(job.name,repDict)
        else:
                for sample in samplesList:
                        submit(sample,repDict)

#BDT optimisation
elif opts.task == 'mva_opt':
    total_number_of_steps=1
    setting = ''
    for par in (config.get('Optimisation','parameters').split(',')):
        scan_par=eval(config.get('Optimisation',par))
        setting+=par+'='+str(scan_par[0])+':'
        if len(scan_par) > 1 and scan_par[2] != 0:
            total_number_of_steps+=scan_par[2]
    setting=setting[:-1] # eliminate last column at the end of the setting string
    print setting
    repDict['additional']=setting
    repDict['job_id']=config.get('Optimisation','training')
    submit('OPT_main_set',repDict)
    main_setting=setting

    #Scanning all the parameters found in the training config in the Optimisation sector
    for par in (config.get('Optimisation','parameters').split(',')):
        scan_par=eval(config.get('Optimisation',par))
        print par
        if len(scan_par) > 1 and scan_par[2] != 0:
            for step in range(scan_par[2]):
                value = (scan_par[0])+((1+step)*(scan_par[1]-scan_par[0])/scan_par[2])
                print value
                setting=re.sub(par+'.*?:',par+'='+str(value)+':',main_setting)
                repDict['additional']=setting
#               repDict['job_id']=config.get('Optimisation','training')
                submit('OPT_'+par+str(value),repDict)
#               submit(config.get('Optimisation','training'),repDict)
                print setting


os.system('qstat')
if (opts.philipp_love_progress_bars):
    os.system('./qstat.py') 
Revision:	1.39
Committed:	Mon Apr 8 08:02:00 2013 UTC (12 years, 1 month ago) by peller
Content type:	text/x-python
Branch:	MAIN
CVS Tags:	lhcp_UnblindFix, hcp_Unblind, lhcp_11April, LHCP_PreAppFixAfterFreeze, HEAD
Changes since 1.38:	+37 -37 lines
Log Message:	set default to 8TeV
#	User	Rev	Content
1	nmohr	1.1	#! /usr/bin/env python
2	nmohr	1.6	from optparse import OptionParser
3	bortigno	1.26	import sys
4	peller	1.28	import time
5			import os
6			import shutil
7	nmohr	1.7
8	nmohr	1.6	parser = OptionParser()
9	peller	1.39	parser.add_option("-T", "--tag", dest="tag", default="8TeV",
10	nmohr	1.6	help="Tag to run the analysis with, example '8TeV' uses config8TeV and pathConfig8TeV to run the analysis")
11	peller	1.9	parser.add_option("-J", "--task", dest="task", default="",
12	nmohr	1.19	help="Task to be done, i.e. 'dc' for Datacards, 'prep' for preparation of Trees, 'plot' to produce plots or 'eval' to write the MVA output or 'sys' to write regression and systematics (or 'syseval' for both). ")
13	peller	1.9	parser.add_option("-M", "--mass", dest="mass", default="125",
14	peller	1.39	help="Mass for DC or Plots, 110...135")
15	bortigno	1.10	parser.add_option("-S","--samples",dest="samples",default="",
16	peller	1.39	help="samples you want to run on")
17	peller	1.28	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	bortigno	1.30	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	bortigno	1.26	(opts, args) = parser.parse_args(sys.argv)
25
26	bortigno	1.30	import os,shutil,pickle,subprocess,ROOT,re
27	nmohr	1.27	ROOT.gROOT.SetBatch(True)
28	bortigno	1.31	from myutils import BetterConfigParser, Sample, ParseInfo, sample_parser
29	bortigno	1.26	import getpass
30	nmohr	1.6
31			if opts.tag == "":
32	peller	1.39	print "Please provide tag to run the analysis with, example '-T 8TeV' uses config8TeV and pathConfig8TeV to run the analysis."
33			sys.exit(123)
34	peller	1.9
35			if opts.task == "":
36			print "Please provide a task.\n-J prep:\tpreparation of Trees\n-J sys:\t\twrite regression and systematics\n-J eval:\tcreate MVA output\n-J plot:\tproduce Plots\n-J dc:\t\twrite workspaces and datacards"
37			sys.exit(123)
38
39	peller	1.28
40			en = opts.tag
41
42	bortigno	1.11	#create the list with the samples to run over
43			samplesList=opts.samples.split(",")
44	peller	1.28	timestamp = time.asctime().replace(' ','_').replace(':','-')
45
46	bortigno	1.35	# the list of the config is taken from the path config
47	peller	1.28	pathconfig = BetterConfigParser()
48			pathconfig.read('%sconfig/paths'%(en))
49	bortigno	1.35	_configs = pathconfig.get('Configuration','List').split(" ")
50			configs = [ '%sconfig/'%(en) + c for c in _configs ]
51	peller	1.28
52			if not opts.ftag == '':
53			tagDir = pathconfig.get('Directories','tagDir')
54			DirStruct={'tagDir':tagDir,'ftagdir':'%s/%s/'%(tagDir,opts.ftag),'logpath':'%s/%s/%s/'%(tagDir,opts.ftag,'Logs'),'plotpath':'%s/%s/%s/'%(tagDir,opts.ftag,'Plots'),'limitpath':'%s/%s/%s/'%(tagDir,opts.ftag,'Limits'),'confpath':'%s/%s/%s/'%(tagDir,opts.ftag,'config') }
55
56			for keys in ['tagDir','ftagdir','logpath','plotpath','limitpath','confpath']:
57			try:
58			os.stat(DirStruct[keys])
59			except:
60			os.mkdir(DirStruct[keys])
61
62			pathfile = open('%sconfig/paths'%(en))
63			buffer = pathfile.readlines()
64			pathfile.close()
65			os.rename('%sconfig/paths'%(en),'%sconfig/paths.bkp'%(en))
66			pathfile = open('%sconfig/paths'%(en),'w')
67			for line in buffer:
68			if line.startswith('plotpath'):
69			line = 'plotpath: %s\n'%DirStruct['plotpath']
70			elif line.startswith('logpath'):
71			line = 'logpath: %s\n'%DirStruct['logpath']
72			elif line.startswith('limits'):
73			line = 'limits: %s\n'%DirStruct['limitpath']
74			pathfile.write(line)
75			pathfile.close()
76
77			#copy config files
78			for item in configs:
79			shutil.copyfile(item,'%s/%s/%s'%(tagDir,opts.ftag,item.strip(en)))
80
81
82	nmohr	1.6	print configs
83			config = BetterConfigParser()
84			config.read(configs)
85	peller	1.28
86	bortigno	1.37	def dump_config(configs,output_file):
87			"""
88			Dump all the configs in a output file
89			Args:
90			output_file: the file where the log will be dumped
91			configs: list of files (string) to be dumped
92			Returns:
93			nothing
94			"""
95			outf = open(output_file,'w')
96			for i in configs:
97			try:
98			f=open(i,'r')
99			outf.write(f.read())
100			except: print '@WARNING: Config' + i + ' not found. It will not be used.'
101	bortigno	1.35
102			def compile_macro(config,macro):
103			"""
104			Creates the library from a macro using CINT compiling it in scratch to avoid
105			problems with the linking in the working nodes.
106			Args:
107			config: configuration file where the macro path is specified
108			macro: macro name to be compiled
109			Returns:
110			nothing
111			"""
112			submitDir = os.getcwd()
113			_macro=macro+'.h'
114			library = config.get(macro,'library')
115			libDir=os.path.dirname(library)
116			os.chdir(libDir)
117			if not os.path.exists(library):
118			print '@INFO: Compiling ' + _macro
119			scratchDir='/scratch/%s/'%(getpass.getuser())
120			shutil.copyfile(libDir+'/'+_macro,'/scratch/%s/%s'%(getpass.getuser(),_macro))
121			os.chdir(scratchDir)
122			ROOT.gROOT.ProcessLine('.L %s+'%(scratchDir+_macro))
123			shutil.copyfile('/scratch/%s/%s'%(getpass.getuser(),os.path.basename(library)),library)
124			os.chdir(submitDir)
125
126			compile_macro(config,'BTagReshaping')
127			compile_macro(config,'VHbbNameSpace')
128
129	nmohr	1.6	logPath = config.get("Directories","logpath")
130	nmohr	1.34	logo = open('%s/data/submit.txt' %config.get('Directories','vhbbpath')).readlines()
131			counter = 0
132
133	bortigno	1.14	#check if the logPath exist. If not exit
134			if( not os.path.isdir(logPath) ):
135	bortigno	1.35	print '@ERROR : ' + logPath + ': dir not found.'
136			print '@ERROR : Create it before submitting '
137	nmohr	1.34	print 'Exit'
138			sys.exit(-1)
139
140	bortigno	1.30	repDict = {'en':en,'logpath':logPath,'job':'','task':opts.task,'queue': 'all.q','timestamp':timestamp,'additional':'','job_id':''}
141	nmohr	1.6	def submit(job,repDict):
142	nmohr	1.34	global counter
143			repDict['job'] = job
144			nJob = counter % len(logo)
145			counter += 1
146			if opts.philipp_love_progress_bars:
147			repDict['name'] = '"%s"' %logo[nJob].strip()
148			else:
149			repDict['name'] = '%(job)s_%(en)s%(task)s' %repDict
150			command = 'qsub -V -cwd -q %(queue)s -l h_vmem=6G -N %(name)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']
151			print command
152	bortigno	1.37	dump_config(configs,"%(logpath)s/%(timestamp)s_%(job)s_%(en)s_%(task)s.config" %(repDict))
153	nmohr	1.34	subprocess.call([command], shell=True)
154	nmohr	1.1
155	peller	1.29	if opts.task == 'train':
156			train_list = (config.get('MVALists','List_for_submitscript')).split(',')
157			print train_list
158			for item in train_list:
159			submit(item,repDict)
160
161
162	peller	1.9	if opts.task == 'dc':
163	peller	1.18	#DC_vars = config.items('Limit')
164			DC_vars= (config.get('LimitGeneral','List')).split(',')
165			print DC_vars
166
167	peller	1.9	if opts.task == 'plot':
168	peller	1.15	Plot_vars= (config.get('Plot_general','List')).split(',')
169	peller	1.8
170	peller	1.12	if not opts.task == 'prep':
171			path = config.get("Directories","samplepath")
172	nmohr	1.21	samplesinfo = config.get("Directories","samplesinfo")
173	nmohr	1.27	info = ParseInfo(samplesinfo,path)
174	peller	1.8
175	peller	1.9	if opts.task == 'plot':
176	peller	1.23	repDict['queue'] = 'all.q'
177	peller	1.9	for item in Plot_vars:
178	peller	1.15	submit(item,repDict)
179	peller	1.9
180	nmohr	1.36	if opts.task == 'trainReg':
181			repDict['queue'] = 'all.q'
182			submit('trainReg',repDict)
183
184	bortigno	1.30
185	peller	1.9	elif opts.task == 'dc':
186	nmohr	1.38	repDict['queue'] = 'all.q'
187	peller	1.9	for item in DC_vars:
188	peller	1.22	if 'ZH%s'%opts.mass in item:
189	peller	1.18	submit(item,repDict)
190	nmohr	1.38	elif opts.mass == 'all':
191	peller	1.18	submit(item,repDict)
192	peller	1.17
193	peller	1.9	elif opts.task == 'prep':
194	nmohr	1.33	if ( opts.samples == ""):
195			path = config.get("Directories","PREPin")
196			samplesinfo = config.get("Directories","samplesinfo")
197			info = ParseInfo(samplesinfo,path)
198			for job in info:
199			submit(job.name,repDict)
200	peller	1.9
201	nmohr	1.33	else:
202			for sample in samplesList:
203			submit(sample,repDict)
204	bortigno	1.30	elif opts.task == 'sys' or opts.task == 'syseval':
205			path = config.get("Directories","SYSin")
206			samplesinfo = config.get("Directories","samplesinfo")
207			info = ParseInfo(samplesinfo,path)
208	peller	1.39	if opts.samples == "":
209	bortigno	1.30	for job in info:
210	nmohr	1.34	if (job.subsample):
211			continue #avoid multiple submissions form subsamples
212			# TO FIX FOR SPLITTED SAMPLE
213	bortigno	1.30	submit(job.name,repDict)
214			else:
215			for sample in samplesList:
216			submit(sample,repDict)
217
218			elif opts.task == 'eval':
219	nmohr	1.38	repDict['queue'] = 'long.q'
220	bortigno	1.30	path = config.get("Directories","MVAin")
221			samplesinfo = config.get("Directories","samplesinfo")
222			info = ParseInfo(samplesinfo,path)
223	peller	1.39	if opts.samples == "":
224	bortigno	1.10	for job in info:
225	nmohr	1.34	if (job.subsample):
226			continue #avoid multiple submissions from subsamples
227			if(info.checkSplittedSampleName(job.identifier)): # if multiple entries for one name (splitted samples) use the identifier to submit
228			print '@INFO: Splitted samples: submit through identifier'
229			submit(job.identifier,repDict)
230			else: submit(job.name,repDict)
231	bortigno	1.10	else:
232	bortigno	1.11	for sample in samplesList:
233	peller	1.39	print sample
234	bortigno	1.10	submit(sample,repDict)
235	peller	1.20
236	bortigno	1.30
237			elif( opts.task == 'split' ):
238			path = config.get("Directories","SPLITin")
239			samplesinfo = config.get("Directories","samplesinfo")
240	bortigno	1.32	repDict['job_id']=opts.nevents_split
241	bortigno	1.30	info = ParseInfo(samplesinfo,path)
242	bortigno	1.32	if ( opts.samples == "" ):
243	bortigno	1.30	for job in info:
244	bortigno	1.32	if (job.subsample): continue #avoid multiple submissions from subsamples
245	bortigno	1.30	submit(job.name,repDict)
246			else:
247			for sample in samplesList:
248			submit(sample,repDict)
249
250			#BDT optimisation
251			elif opts.task == 'mva_opt':
252	peller	1.39	total_number_of_steps=1
253			setting = ''
254			for par in (config.get('Optimisation','parameters').split(',')):
255			scan_par=eval(config.get('Optimisation',par))
256			setting+=par+'='+str(scan_par[0])+':'
257			if len(scan_par) > 1 and scan_par[2] != 0:
258			total_number_of_steps+=scan_par[2]
259			setting=setting[:-1] # eliminate last column at the end of the setting string
260			print setting
261			repDict['additional']=setting
262			repDict['job_id']=config.get('Optimisation','training')
263			submit('OPT_main_set',repDict)
264			main_setting=setting
265
266			#Scanning all the parameters found in the training config in the Optimisation sector
267			for par in (config.get('Optimisation','parameters').split(',')):
268			scan_par=eval(config.get('Optimisation',par))
269			print par
270			if len(scan_par) > 1 and scan_par[2] != 0:
271			for step in range(scan_par[2]):
272			value = (scan_par[0])+((1+step)*(scan_par[1]-scan_par[0])/scan_par[2])
273			print value
274			setting=re.sub(par+'.*?:',par+'='+str(value)+':',main_setting)
275			repDict['additional']=setting
276			# repDict['job_id']=config.get('Optimisation','training')
277			submit('OPT_'+par+str(value),repDict)
278			# submit(config.get('Optimisation','training'),repDict)
279			print setting
280	bortigno	1.30
281
282			os.system('qstat')
283			if (opts.philipp_love_progress_bars):
284	peller	1.39	os.system('./qstat.py')