bin/sbank_pipe
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright (C) 2012-2017 Stephen Privitera
#
# This program is free software; you can redistribute it and/or modify it
# under the terms of the GNU General Public License as published by the
# Free Software Foundation; either version 2 of the License, or (at your
# option) any later version.
#
# This program is distributed in the hope that it will be useful, but
# WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General
# Public License for more details.
#
# You should have received a copy of the GNU General Public License along
# with this program; if not, write to the Free Software Foundation, Inc.,
# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
from __future__ import print_function
##############################################################################
# import standard modules and append the lalapps prefix to the python path
import getpass
import os
import socket
import sys
import tempfile
import shutil
##############################################################################
# import the modules we need to build the pipeline
from optparse import OptionParser
from glue.pipeline import DeepCopyableConfigParser as dcConfigParser
from glue import pipeline
from lalapps import inspiral
def which(prog):
out = shutil.which(prog)
if out is None:
raise ValueError("Could not find {} in your path, have you built the proper software and sourced the proper env. scripts?".format(prog))
return out
def log_path():
host = socket.getfqdn()
username = getpass.getuser()
#FIXME add more hosts as you need them
if 'caltech.edu' in host: return '/usr1/' + username
if 'phys.uwm.edu' in host: return '/localscratch/' + username
if 'aei.uni-hannover.de' in host: return '/local/user/' + username
if 'phy.syr.edu' in host: return '/usr1/' + username
else: return tempfile.gettempdir()
class bank_DAG(pipeline.CondorDAG):
def __init__(self, name, logpath = log_path()):
self.basename = name
tempfile.tempdir = logpath
tempfile.template = self.basename + '.dag.log.'
logfile = tempfile.mktemp()
fh = open( logfile, "w" )
fh.close()
pipeline.CondorDAG.__init__(self,logfile)
self.set_dag_file(self.basename)
self.jobsDict = {}
self.node_id = 0
self.output_cache = []
def add_node(self, node):
node.set_retry(3)
self.node_id += 1
node.add_macro("macroid", self.node_id)
pipeline.CondorDAG.add_node(self, node)
def write_cache(self):
out = self.basename + ".cache"
f = open(out,"w")
for c in self.output_cache:
f.write(str(c)+"\n")
f.close()
class SBankJob(inspiral.InspiralAnalysisJob):
def __init__(self,cp, tag_base="sbank"):
exec_name = 'sbank'
extension = 'xml'
sections = ['sbank']
inspiral.InspiralAnalysisJob.__init__(self,cp,sections,exec_name,extension)
self.tag_base = tag_base
self.set_sub_file(tag_base+'.sub')
self.set_stdout_file('logs/'+tag_base+'-$(macroid)-$(process).out')
self.set_stderr_file('logs/'+tag_base+'-$(macroid)-$(process).err')
if cp.has_section("accounting"):
self.add_condor_cmd('accounting_group', cp.get("accounting", "accounting-group"))
if cp.has_option("accounting", "accounting-group-user"):
self.add_condor_cmd('accounting_group_user', cp.get("accounting", "accounting-group-user"))
self.add_condor_cmd('getenv','True')
self.add_condor_cmd('request_memory', '3999')
self.add_condor_cmd('request_disk', '1MB')
if "OMP_NUM_THREADS" in os.environ:
self.add_condor_cmd('request_cpus', os.environ["OMP_NUM_THREADS"])
class SBankNode(pipeline.CondorDAGNode):
def __init__(self, job, dag, tag="SBANK", seed=0, bank_seed=[], mchirp_boundaries_file=None, mchirp_boundaries_index=None, p_node=[]):
pipeline.CondorDAGNode.__init__(self,job)
if (mchirp_boundaries_file is None) ^ (mchirp_boundaries_index is None):
raise ValueError("must supply both mchirp_boundaries_file and mchirp_boundaries_index or neither")
if mchirp_boundaries_file is not None:
self.add_var_arg("--mchirp-boundaries-file %s --mchirp-boundaries-index %s" % (mchirp_boundaries_file, mchirp_boundaries_index))
for bseed in bank_seed:
self.add_var_arg("--bank-seed %s" % bseed)
self.add_var_opt("seed", seed)
fout = "%s.xml.gz" % tag
self.add_var_opt("output-filename", fout)
self.add_output_file(fout)
for p in p_node:
self.add_parent(p)
dag.add_node(self)
class SBankChooseMchirpBoundariesJob(inspiral.InspiralAnalysisJob):
def __init__(self,cp, tag_base="sbank_choose_mchirp_boundaries"):
exec_name = 'sbank_choose_mchirp_boundaries'
extension = 'txt'
sections = ['split']
inspiral.InspiralAnalysisJob.__init__(self,cp,sections,exec_name,extension)
self.set_universe("local")
self.set_sub_file(tag_base+'.sub')
self.tag_base = tag_base
self.set_stdout_file('logs/'+tag_base+'-$(macroid)-$(process).out')
self.set_stderr_file('logs/'+tag_base+'-$(macroid)-$(process).err')
self.add_condor_cmd('request_memory', '1000')
self.add_condor_cmd('request_disk', '1MB')
if cp.has_section("accounting"):
self.add_condor_cmd('accounting_group', cp.get("accounting", "accounting-group"))
if cp.has_option("accounting", "accounting-group-user"):
self.add_condor_cmd('accounting_group_user', cp.get("accounting", "accounting-group-user"))
self.add_condor_cmd('getenv','True')
class SBankChooseMchirpBoundariesNode(pipeline.CondorDAGNode):
def __init__(self, job, dag, bank, tag = None, p_node=[]):
pipeline.CondorDAGNode.__init__(self,job)
self.add_file_arg(bank)
nbanks = int(self.job().get_opts()["nbanks"])
self.add_var_opt("nbanks", nbanks)
if tag:
output_fname = "%s_mchirp_boundaries.txt" % tag
else:
output_fname = "mchirp_boundaries.txt"
self.add_var_opt("output-file", output_fname)
self.add_output_file(output_fname)
for p in p_node:
self.add_parent(p)
dag.add_node(self)
class LWAddJob(pipeline.CondorDAGJob):
"""
A ligolw_add node. This node is used to combine the split template banks
into one aggregate bank.
"""
def __init__(self, cp, executable=which('ligolw_add'), tag_base='ligolw_add'):
"""
"""
self.__prog__ = 'ligolw_add'
self.__executable = executable
self.__universe = 'vanilla'
pipeline.CondorDAGJob.__init__(self,self.__universe,self.__executable)
self.add_condor_cmd('request_memory', '3999')
self.add_condor_cmd('request_disk', '1MB')
self.add_condor_cmd('getenv','True')
if cp.has_section("accounting"):
self.add_condor_cmd('accounting_group', cp.get("accounting", "accounting-group"))
if cp.has_option("accounting", "accounting-group-user"):
self.add_condor_cmd('accounting_group_user', cp.get("accounting", "accounting-group-user"))
self.tag_base = tag_base
self.add_condor_cmd('environment',"KMP_LIBRARY=serial;MKL_SERIAL=yes")
self.set_sub_file(tag_base+'.sub')
self.set_stdout_file('logs/'+tag_base+'-$(macroid)-$(process).out')
self.set_stderr_file('logs/'+tag_base+'-$(macroid)-$(process).err')
class LWAddNode(pipeline.CondorDAGNode):
"""
"""
def __init__(self, job, dag, xmls,output, p_node=[]):
pipeline.CondorDAGNode.__init__(self,job)
for x in xmls: self.add_file_arg(x)
self.add_var_opt("output", output)
self.add_output_file(output)
for p in p_node:
if p is not None:
self.add_parent(p)
dag.add_node(self)
usage = """
sbank_pipe generates a DAG for parallelizing the
construction of template banks via sbank. Its primary
input is an ini file, which takes form given below. Once you have an
ini file, create the DAG by
sbank_pipe --config-file INIFILE.ini --user-tag SBANK_PIPE
;;; BEGIN EXAMPLE INI ;;;
[condor] ; This section points to the executables, and provides condor options
universe = vanilla
sbank = /usr/bin/sbank
sbank_choose_mchirp_boundaries = /usr/bin/sbank_choose_mchirp_boundaries
;[accounting]
;accounting-group = ???
;specifying the user is only necessary for shared accounts
;accounting-group-user = ???
[sbank]
; This section contains the parameters of the entire bank parameter
; space you wish to cover. sbank_pipe will divide the space for you.
approximant = SEOBNRv2_ROM_DoubleSpin
match-min = 0.97
flow = 30.0
noise-model = aLIGOZeroDetHighPower
instrument = H1
mass1-min = 2.0
mass1-max = 296.0
mass2-min = 2.0
mass2-max = 296.0
mtotal-min = 4.0
mtotal-max = 350.0
mratio-min = 1.0
mratio-max = 14.0
spin1-max = 0.98
spin1-min = -0.98
spin2-max = 0.98
spin2-min = -0.98
aligned-spin =
neighborhood-param = dur
neighborhood-size = 0.5
checkpoint = 500
;cache-waveforms =
; please check your memory requirements before setting this option
; if jobs use too much memory, they will swap and run forever
coarse-match-df = 4.0
iterative-match-df-max= 1.0
; If you want to add precomputed banks to the workflow
;bank-seed = FILENAME[:APPROX]
[coarse-sbank]
; This section is for planning the splitting of the parameter
; space. To do so, we generate a "coarse" bank, i.e., a bank on the
; same parameter space but with a weaker convergence criteria. This
; process gives a rough measure of the density of templates the final
; bank will require. Use the max-new-templates option to prevent the job
; from running forever, but the more templates you have in the coarse
; bank, the less "over-coverage" you will incur from the bank
; splitting process. A good rule of thumb is that you want ~1000
; templates per split bank.
max-new-templates = 15000
match-min = 0.93
convergence-threshold = 1000
[split]
; This section configures the parallelization. nbanks are how many
; splits (in chirp mass) you want. You can crank it to infinity at the
; cost of overcoverage.
nbanks = 15
;;; END EXAMPLE INI ;;;
"""
def parse_command_line():
parser = OptionParser(usage=usage)
parser.add_option("--config-file", default=None, help="Read options for generating template bank placement pipeline from configuration ini file..")
parser.add_option("--user-tag", default="SBANK", help="Make your results feel special and give them a unique name.")
options, filenames = parser.parse_args()
return options, filenames
options, filenames = parse_command_line()
try: os.mkdir("logs")
except: pass
# create top level dag object
dag = bank_DAG(options.user_tag)
# read config file
cp = dcConfigParser()
cp.read(options.config_file)
# initialize sbank job objects
sbankJob = SBankJob(cp, tag_base=options.user_tag + "_sbank")
mm = cp.get("sbank", "match-min")
cp.remove_option("sbank", "match-min") # don't want it entering via add_ini_opts
# set up bank generation
# Two modes:
# 1. generate coarse, partition mchirp space, generate sub-banks, ligolw_add
# 2. take given bank, split it, and sim it
nbanks = int(cp.get("split","nbanks"))
# for layering, we prefer nbanks to be odd so that no second-stage job
# works on the bank boundary
if not (nbanks % 2):
nbanks += 1
cp.set("split", "nbanks", str(nbanks))
bank_names = []
bank_nodes = []
# set up sole coarse node to plan out the mini-sbank nodes
coarse_sbank_node = SBankNode(sbankJob, dag, "%s_SBANK_COARSE" % options.user_tag)
coarse_mm = cp.get("coarse-sbank", "match-min")
coarse_sbank_node.add_var_opt("match-min", coarse_mm)
coarse_thresh = cp.get("coarse-sbank", "convergence-threshold")
coarse_sbank_node.add_var_arg("--convergence-threshold %s" % coarse_thresh)
if cp.has_option("coarse-sbank", "max-new-templates"):
templates_max = int(cp.get("coarse-sbank", "max-new-templates"))
assert templates_max >= 3*nbanks # you need at least a few templates per bank
else:
templates_max = 15*nbanks # to prevent the coarse bank from running forever
coarse_sbank_node.add_var_arg("--max-new-templates %s" % templates_max)
xmlCoarse, = coarse_sbank_node.get_output_files()
pnode = [coarse_sbank_node]
bank_names.append(xmlCoarse)
bank_nodes.append(coarse_sbank_node)
# use coarse bank to choose mchirp regions of roughly equal template number
sbankChooseMchirpBoundariesJob = SBankChooseMchirpBoundariesJob(cp, tag_base=options.user_tag + "_mchirp_boundaries")
sbankChooseMchirpBoundariesNode = SBankChooseMchirpBoundariesNode(sbankChooseMchirpBoundariesJob, dag, xmlCoarse, options.user_tag, pnode)
mchirp_boundaries_fname, = sbankChooseMchirpBoundariesNode.get_output_files()
# generate a bank for each mchirp region
# first compute even numbered split banks
for j in range(0, nbanks, 2):
bank_node = SBankNode(sbankJob, dag, "%s_SBANK_SPLIT_BANK_%04d" % (options.user_tag, j), seed="%d" % (j*nbanks+1), mchirp_boundaries_file=mchirp_boundaries_fname, mchirp_boundaries_index=str(j), p_node=[sbankChooseMchirpBoundariesNode], bank_seed=[xmlCoarse])
bank_node.add_var_opt("match-min", mm)
bank_node.set_priority(1) # want complete bank before sims
bank_nodes.append(bank_node)
bank_name, = bank_node.get_output_files()
bank_names.append(bank_name)
# then compute odd numbered split banks using even banks as seeds
for j in range(1, nbanks, 2):
if j < nbanks - 1:
p_node = [bank_nodes[(j+1)//2], bank_nodes[(j+3)//2]]
bank_seed = [xmlCoarse, bank_names[(j+1)//2], bank_names[(j+3)//2]]
else:
p_node = [bank_nodes[(j+1)//2]]
bank_seed = [xmlCoarse, bank_names[(j+1)//2]]
bank_node = SBankNode(sbankJob, dag, "%s_SBANK_SPLIT_BANK_%04d" % (options.user_tag, j), seed="%d" % (j*nbanks+1), mchirp_boundaries_file=mchirp_boundaries_fname, mchirp_boundaries_index=str(j), p_node=p_node, bank_seed=bank_seed)
bank_node.add_var_opt("match-min", mm)
bank_node.set_priority(1) # want complete bank before sims
bank_nodes.append(bank_node)
bank_name, = bank_node.get_output_files()
bank_names.append(bank_name)
# recombine bank fragments under a common name
lwaddJob = LWAddJob(cp, tag_base=options.user_tag + "_lwadd")
lwaddNode = LWAddNode(lwaddJob, dag, bank_names, "SBANK_COMBINED-%s.xml.gz" % options.user_tag, bank_nodes)
# write the dag
dag.write_sub_files()
dag.write_script()
dag.write_cache()
dag.write_dag()