def completed_skirtruns(unless_filenames=None):
db = Database()
runids = sorted([
row['runid']
for row in db.select("runstatus='completed' or runstatus='archived'")
])
runs = [SkirtRun(runid) for runid in runids]
if unless_filenames != None:
runs = filter(
lambda run: not has_visualization_files(run, unless_filenames),
runs)
db.close()
return runs
# backup and open the local database
backup()
db = Database()
# remove SKIRT-runs that have been archived from the do-list
records = filter(lambda record: db.select("runid="+str(record['runid']))[0]['runstatus']!='archived', records)
print "--> .. of which {} have not yet been archived".format(len(records))
# synchronize the results from each completed run
for record in records:
runid = record['runid']
print "--> Synchronizing results for run-id {}...".format(runid)
# get the local and remote paths (creating the local directories if needed)
skirtrun = SkirtRun(runid, create=True)
local_runpath = skirtrun.runpath()
local_inpath = skirtrun.inpath()
local_outpath = skirtrun.outpath()
local_vispath = skirtrun.vispath()
remote_runpath = local_runpath.replace(config.results_path, config.cosma["results_path"])
remote_inpath = local_inpath.replace(config.results_path, config.cosma["results_path"])
remote_outpath = local_outpath.replace(config.results_path, config.cosma["results_path"])
remote_vispath = local_vispath.replace(config.results_path, config.cosma["results_path"])
# synchronize the files in each directory
# - skip subdirectories and symbolic links
# - for the vis directory, do not overwrite newer local versions
error = subprocess.call(("rsync", "-htvz", cosma_prefix+remote_runpath+"/*", local_runpath+"/"))
if error: raise ValueError("Error in rsync for run: " + str(error))
error = subprocess.call(("rsync", "-htvz", cosma_prefix+remote_inpath+"/*", local_inpath+"/"))
buildrange = sys.argv[2].lower()
update = "update".startswith(buildrange)
rebuild = "rebuild".startswith(buildrange)
runidrange = runids_in_range(buildrange)
if not update and not rebuild and not runidrange:
raise ValueError("Unknown build range: " + buildrange)
# -----------------------------------------------------------------
# get a list of relevant filename endings depending on the visualization type
filenames = filenames_for_vistype[vistype]
# construct the list of SKIRT-runs to be processed
if runidrange:
skirtruns = [SkirtRun(runid) for runid in runidrange]
else:
skirtruns = completed_skirtruns(filenames if update else None)
# =================================================================
# build density curves
if vistype == 'densities':
from pts.eagle.plotdensitycurves import plotdensitycurves
print "Building density curves for {} SKIRT-runs".format(len(skirtruns))
for skirtrun in skirtruns:
print "Building density curves for SKIRT-run {}...".format(
skirtrun.runid())
plotdensitycurves(skirtrun)
# -----------------------------------------------------------------
backup()
db = Database()
# remove SKIRT-runs that have been archived from the do-list
records = filter(
lambda record: db.select("runid=" + str(record['runid']))[0]['runstatus']
!= 'archived', records)
print "--> .. of which {} have not yet been archived".format(len(records))
# synchronize the results from each completed run
for record in records:
runid = record['runid']
print "--> Synchronizing results for run-id {}...".format(runid)
# get the local and remote paths (creating the local directories if needed)
skirtrun = SkirtRun(runid, create=True)
local_runpath = skirtrun.runpath()
local_inpath = skirtrun.inpath()
local_outpath = skirtrun.outpath()
local_vispath = skirtrun.vispath()
remote_runpath = local_runpath.replace(config.results_path,
config.cosma["results_path"])
remote_inpath = local_inpath.replace(config.results_path,
config.cosma["results_path"])
remote_outpath = local_outpath.replace(config.results_path,
config.cosma["results_path"])
remote_vispath = local_vispath.replace(config.results_path,
config.cosma["results_path"])
# synchronize the files in each directory
# - skip subdirectories and symbolic links
# get the eligible records
db = database.Database()
records = db.select("((stage='simulate' and status='succeeded') or (stage in ('observe', 'store', 'completed')))" \
" and label=?", (label,))
db.close()
size = len(records)
if size == 0:
raise ValueError("There are no simulated records with label " + label)
# assemble the statistics for all records
log.info("Assembling statistics for {} SKIRT simulations...".format(size))
time = np.zeros(size)
memory = np.zeros(size)
for index in range(size):
logfilepath = SkirtRun(records[index]["runid"]).simulation().logfilepath()
for line in open(logfilepath):
if " Finished simulation " in line:
segments = line.split()
processes = float(segments[segments.index("processes") - 1])
timeindex = segments.index(
"s") if "s" in segments else segments.index("s.")
walltime = float(segments[timeindex - 1])
time[index] = processes * walltime
if " Available memory: " in line:
segments = line.split()
memory[index] = float(segments[segments.index("usage:") + 1])
# construct the time histogram
log.info("Constructing plots...")
figure = plt.figure(figsize=(8, 8))
# dump it into file
outfile = open(outfilepath, 'w')
pickle.dump(collection, outfile)
outfile.close()
print "Created info collection " + outfilepath
# -----------------------------------------------------------------
# chain the command-line arguments into a query list
if len(sys.argv) <= 1: raise ValueError("This script expects one or more command-line arguments")
querylist = "('{}')".format("','".join(sys.argv[1:]))
namelist = "_".join(sys.argv[1:])
# get a list of SkirtRun objects for which to collect statistics, in order of run-id
db = Database()
query = "runstatus in ('completed','archived') and label in {0} and eaglesim in {0}".format(querylist)
runids = sorted([ row['runid'] for row in db.select(query) ])
skirtruns = [ SkirtRun(runid) for runid in runids ]
db.close()
# perform the collection
if len(skirtruns) > 0:
print "Collecting statistics from {} SKIRT-runs with label and eaglesim fields in {}...".format(len(skirtruns),querylist)
collect_info(skirtruns, os.path.join(config.collections_path,"{}_info_collection.dat".format(namelist)))
else:
print "There are no SKIRT-runs with label and eaglesim fields in {}.".format(querylist)
# -----------------------------------------------------------------
# verify that the offsite archive server is mounted
if len(runids) == 0:
print "No SKIRT-runs to be archived."
exit()
if not os.path.isdir(archive_path):
print "Please mount the offsite archive server and try again."
exit()
# open the database and process each SKIRT-run
db = Database()
for runid in runids:
print "--> Creating archives for SKIRT-run {}...".format(runid)
# get the paths for the in and out directories, and the corresponding zip archives
skirtrun = SkirtRun(runid)
indir = skirtrun.inpath()
outdir = skirtrun.outpath()
inzip = indir + ".zip"
outzip = outdir + ".zip"
# export the database record
info = db.select("runid=" + str(runid))[0]
infofile = open(os.path.join(indir, "database_record.txt"), "w")
infofile.write("# SKIRT-run database record\n")
for key in info.keys():
infofile.write(("{} = {}\n").format(key, info[key]))
infofile.close()
# create the archives
if os.path.isfile(inzip):
# verify that the offsite archive server is mounted
if len(runids) == 0:
print "No SKIRT-runs to be archived."
exit()
if not os.path.isdir(archive_path):
print "Please mount the offsite archive server and try again."
exit()
# open the database and process each SKIRT-run
db = Database()
for runid in runids:
print "--> Creating archives for SKIRT-run {}...".format(runid)
# get the paths for the in and out directories, and the corresponding zip archives
skirtrun = SkirtRun(runid)
indir = skirtrun.inpath()
outdir = skirtrun.outpath()
inzip = indir + ".zip"
outzip = outdir + ".zip"
# export the database record
info = db.select("runid=" + str(runid))[0]
infofile = open(os.path.join(indir, "database_record.txt"), 'w')
infofile.write('# SKIRT-run database record\n')
for key in info.keys():
infofile.write(("{} = {}\n").format(key, info[key]))
infofile.close()
# create the archives
if os.path.isfile(inzip): os.remove(inzip)