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#!/usr/bin/env python
# Copyright (c) 2019, Anthony Latorre <tlatorre at uchicago>
#
# 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 3 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, see <https://www.gnu.org/licenses/>.
"""
Script to combine the fit results from jobs submitted to the grid. It's
expected to be run from a cron job:
PATH=/usr/bin:$HOME/local/bin
SDDM_DATA=$HOME/sddm/src
DQXX_DIR=$HOME/dqxx
0 * * * * module load hdf5; module load py-h5py; module load zlib; cat-grid-jobs --loglevel debug --logfile cat.log --output-dir $HOME/fit_results
The script will loop through all entries in the database and try to combine the
fit results into a single output file.
"""
from __future__ import print_function, division
import os
import sys
import numpy as np
from datetime import datetime
import h5py
from os.path import join, split
from subprocess import check_call
from sddm import splitext, which
from sddm.logger import Logger
log = Logger()
def cat_grid_jobs(conn, output_dir):
zdab_cat = which("zdab-cat")
if zdab_cat is None:
log.warn("couldn't find zdab-cat in path!",file=sys.stderr)
return
c = conn.cursor()
results = c.execute('SELECT filename, uuid FROM state').fetchall()
unique_results = set(results)
for filename, uuid in unique_results:
head, tail = split(filename)
root, ext = splitext(tail)
# First, find all hdf5 result files
fit_results = c.execute("SELECT submit_file FROM state WHERE state = 'SUCCESS' AND filename = ? AND uuid = ?", (filename, uuid)).fetchall()
fit_results = [fit_result_filename[0] for fit_result_filename in fit_results]
fit_results = ['%s.hdf5' % splitext(fit_result_filename)[0] for fit_result_filename in fit_results]
if len(fit_results) == 0:
log.debug("No fit results found for %s (%s)" % (tail, uuid))
continue
output = join(output_dir,"%s_%s_fit_results.hdf5" % (root,uuid))
if os.path.exists(output):
total_fits = 0
for fit_result_filename in fit_results:
fit_result_head, fit_result_tail = split(fit_result_filename)
if not os.path.exists(fit_result_filename):
log.warn("File '%s' does not exist!" % filename)
continue
with h5py.File(fit_result_filename,'r') as f:
if 'git_sha1' not in f.attrs:
log.warn("No git sha1 found for '%s'. Skipping..." % fit_result_filename)
continue
total_fits += f['fits'].shape[0]
with h5py.File(output,'r') as fout:
if 'fits' in fout:
if fout['fits'].shape[0] >= total_fits:
log.debug("skipping %s because there are already %i fit results" % (tail,total_fits))
continue
# First we get the full event list along with the data cleaning word, FTP
# position, FTK, and RSP energy from the original zdab and then add the fit
# results.
#
# Note: We send stderr to /dev/null since there can be a lot of warnings
# about PMT types and fit results
with open(os.devnull, 'w') as f:
log.debug("zdab-cat %s -o %s" % (filename,output))
check_call([zdab_cat,filename,"-o",output],stderr=f)
total_events = 0
events_with_fit = 0
total_fits = 0
with h5py.File(output,"a") as fout:
total_events = fout['ev'].shape[0]
for fit_result_filename in fit_results:
fit_result_head, fit_result_tail = split(fit_result_filename)
if not os.path.exists(fit_result_filename):
log.warn("File '%s' does not exist!" % fit_result_filename)
continue
with h5py.File(fit_result_filename) as f:
if 'git_sha1' not in f.attrs:
log.warn("No git sha1 found for %s. Skipping..." % fit_result_tail)
continue
# Check to see if the git sha1 match
if fout.attrs['git_sha1'] != f.attrs['git_sha1']:
log.debug("git_sha1 is %s for current version but %s for %s" % (fout.attrs['git_sha1'],f.attrs['git_sha1'],fit_result_tail))
# get fits which match up with the events
valid_fits = f['fits'][np.isin(f['fits'][:][['run','gtid']],fout['ev'][:][['run','gtid']])]
# Add the fit results
fout['fits'].resize((fout['fits'].shape[0]+valid_fits.shape[0],))
fout['fits'][-valid_fits.shape[0]:] = valid_fits
events_with_fit += len(np.unique(valid_fits[['run','gtid']]))
total_fits += len(np.unique(f['fits']['run','gtid']))
log.notice("%s (%s): added %i/%i fit results to a total of %i events" % (tail, uuid, events_with_fit, total_fits, total_events))
if __name__ == '__main__':
import argparse
import sqlite3
parser = argparse.ArgumentParser("concatenate fit results from grid jobs into a single file")
parser.add_argument("--db", type=str, help="database file", default=None)
parser.add_argument('--loglevel',
help="logging level (debug, verbose, notice, warning)",
default='notice')
parser.add_argument('--logfile', default=None,
help="filename for log file")
parser.add_argument('--output-dir', default=None,
help="output directory for fit results")
args = parser.parse_args()
log.set_verbosity(args.loglevel)
if args.logfile:
log.set_logfile(args.logfile)
home = os.path.expanduser("~")
if args.db is None:
args.db = join(home,'state.db')
if args.output_dir is None:
args.output_dir = home
else:
if not os.path.exists(args.output_dir):
log.debug("mkdir %s" % args.output_dir)
os.mkdir(args.output_dir)
conn = sqlite3.connect(args.db)
cat_grid_jobs(conn, args.output_dir)
conn.close()
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