def get_diagnostic(self):
# find *.accelcands file
candlists = glob.glob(os.path.join(self.directory, "*.accelcands"))
pfdpngs = [os.path.split(fn)[-1] for fn in \
glob.glob(os.path.join(self.directory, "*.pfd.png"))]
if len(candlists) != 1:
raise DiagnosticError("Wrong number of candidate lists found (%d)!" % \
len(candlists))
candlist = accelcands.parse_candlist(candlists[0])
sigmas = []
for c in candlist:
base, accel = c.accelfile.split("_ACCEL_")
pngfn = "%s_Z%s_ACCEL_Cand_%d.pfd.png" % (base, accel, c.candnum)
if pngfn in pfdpngs:
sigmas.append(c.sigma)
if len(pfdpngs) > len(sigmas):
raise DiagnosticError("Not all *.pfd.png images were found " \
"in candlist! (%d > %d)" % \
(len(pfdpngs), len(sigmas)))
elif len(pfdpngs) < len(sigmas):
raise DiagnosticError("Some *.pfd.png image match multiple " \
"entries in candlist! (%d < %d)" % \
(len(pfdpngs), len(sigmas)))
self.value = min(sigmas)
def get_diagnostic(self):
# find *.accelcands file
candlists = glob.glob(os.path.join(self.directory, "*.accelcands"))
pfdpngs = [os.path.split(fn)[-1] for fn in \
glob.glob(os.path.join(self.directory, "*.pfd.png"))]
if len(candlists) != 1:
raise DiagnosticError("Wrong number of candidate lists found (%d)!" % \
len(candlists))
candlist = accelcands.parse_candlist(candlists[0])
sigmas = []
for c in candlist:
base, accel = c.accelfile.split("_ACCEL_")
pngfn = "%s_Z%s_ACCEL_Cand_%d.pfd.png" % (base, accel, c.candnum)
if pngfn in pfdpngs:
sigmas.append(c.sigma)
if len(pfdpngs) > len(sigmas):
raise DiagnosticError("Not all *.pfd.png images were found " \
"in candlist! (%d > %d)" % \
(len(pfdpngs), len(sigmas)))
elif len(pfdpngs) < len(sigmas):
raise DiagnosticError("Some *.pfd.png image match multiple " \
"entries in candlist! (%d < %d)" % \
(len(pfdpngs), len(sigmas)))
self.value = min(sigmas)
def get_diagnostic(self):
# find *.accelcands file
candlists = glob.glob(os.path.join(self.directory, "*.accelcands"))
if len(candlists) != 1:
raise DiagnosticError("Wrong number of candidate lists found (%d)!" % len(candlists))
candlist = accelcands.parse_candlist(candlists[0])
self.value = len(candlist)
def get_diagnostic(self):
# find *.accelcands file
candlists = glob.glob(os.path.join(self.directory, "*.accelcands"))
if len(candlists) != 1:
raise DiagnosticError("Wrong number of candidate lists found (%d)!" % \
len(candlists))
candlist = accelcands.parse_candlist(candlists[0])
self.value = len(candlist)
def get_diagnostic(self):
# find *.accelcands file
candlists = glob.glob(os.path.join(self.directory, "*.accelcands"))
if len(candlists) != 1:
raise DiagnosticError("Wrong number of candidate lists found (%d)!" % len(candlists))
candlist = accelcands.parse_candlist(candlists[0])
params = get_search_params(self.directory)
self.value = len([c for c in candlist if c.sigma >= params["to_prepfold_sigma"]])
def get_diagnostic(self):
# find *.accelcands file
candlists = glob.glob(os.path.join(self.directory, "*.accelcands"))
if len(candlists) != 1:
raise DiagnosticError("Wrong number of candidate lists found (%d)!" % \
len(candlists))
candlist = accelcands.parse_candlist(candlists[0])
params = get_search_params(self.directory)
self.value = len([c for c in candlist \
if c.sigma >= params['to_prepfold_sigma']])
def get_diagnostic(self):
# find *.accelcands file
candlists = glob.glob(os.path.join(self.directory, "*.accelcands"))
pfdpngs = [os.path.split(fn)[-1] for fn in \
glob.glob(os.path.join(self.directory, "*_ACCEL_*.pfd.png"))]
if len(candlists) != 1:
raise DiagnosticError("Wrong number of candidate lists found (%d)!" % \
len(candlists))
candlist = accelcands.parse_candlist(candlists[0])
sigmas = []
for c in candlist:
base, accel = c.accelfile.split("_ACCEL_")
pngfn = "%s_Z%s_ACCEL_Cand_%d.pfd.png" % (base, accel, c.candnum)
if pngfn in pfdpngs:
sigmas.append(c.sigma)
ffa_candlists = glob.glob(os.path.join(self.directory, "*.ffacands"))
ffa_pfdpngs = [os.path.split(fn)[-1] for fn in \
glob.glob(os.path.join(self.directory, "*_ffa_*.pfd.png"))]
if len(ffa_candlists) != 1:
raise DiagnosticError("Wrong number of ffa candidate lists found (%d)!" % \
len(ffa_candlists))
ffa_candlist = ffacands.parse_candlist(ffa_candlists[0])
#candlist.extend(ffa_candlist)
pfdpngs.extend(ffa_pfdpngs)
#sigmas = []
for c in ffa_candlist:
#base, accel = c.accelfile.split("_ACCEL_")
#pngfn = "%s_Z%s_ACCEL_Cand_%d.pfd.png" % (base, accel, c.candnum)
pngfn = "%s%.2fms_Cand.pfd.png"%(c.ffafile.replace("_cands.ffa","_ffa_"),c.period*1000)
if pngfn in ffa_pfdpngs:
sigmas.append(c.sigma)
if len(pfdpngs) > len(sigmas):
raise DiagnosticError("Not all *.pfd.png images were found " \
"in candlist! (%d > %d)" % \
(len(pfdpngs), len(sigmas)))
elif len(pfdpngs) < len(sigmas):
raise DiagnosticError("Some *.pfd.png image match multiple " \
"entries in candlist! (%d < %d)" % \
(len(pfdpngs), len(sigmas)))
if not sigmas:
errormsg = 'No candidates folded.'
raise DiagnosticNonFatalError(errormsg)
self.value = min(sigmas)
def get_diagnostic(self):
# find *.accelcands file
candlists = glob.glob(os.path.join(self.directory, "*.accelcands"))
if len(candlists) != 1:
raise DiagnosticError("Wrong number of candidate lists found (%d)!" % \
len(candlists))
candlist = accelcands.parse_candlist(candlists[0])
# find the search_params.txt file
paramfn = os.path.join(self.directory, 'search_params.txt')
if os.path.exists(paramfn):
tmp, params = {}, {}
execfile(paramfn, tmp, params)
else:
raise DiagnosticError("Search parameter file doesn't exist!")
self.value = len([c for c in candlist \
if c.sigma >= params['to_prepfold_sigma']])
def get_diagnostic(self):
# find *.accelcands file
candlists = glob.glob(os.path.join(self.directory, "*.accelcands"))
if len(candlists) != 1:
raise DiagnosticError("Wrong number of candidate lists found (%d)!" % \
len(candlists))
candlist = accelcands.parse_candlist(candlists[0])
# find the search_params.txt file
paramfn = os.path.join(self.directory, 'search_params.txt')
if os.path.exists(paramfn):
tmp, params = {}, {}
execfile(paramfn, tmp, params)
else:
raise DiagnosticError("Search parameter file doesn't exist!")
self.value = len([c for c in candlist \
if c.sigma >= params['to_prepfold_sigma']])
def get_candidates(versionnum, directory, header_id=None, timestamp_mjd=None, inst_cache=None):
"""Upload candidates to common DB.
Inputs:
versionnum: A combination of the githash values from
PRESTO and from the pipeline.
directory: The directory containing results from the pipeline.
header_id: header_id number for this beam, as returned by
spHeaderLoader/header.upload_header (default=None)
timestamp_mjd: mjd timstamp for this observation (default=None).
inst_cache: ratings2 RatingInstanceIDCache instance.
Ouput:
cands: List of candidates.
tempdir: Path of temporary directory that PFDs have been untarred,
returned so that it can be deleted after successful PFD upload.
"""
# find *.accelcands file
candlists = glob.glob(os.path.join(directory, "*.accelcands"))
ffa_candlists = glob.glob(os.path.join(directory, "*.ffacands"))
if len(candlists) != 1 or len(ffa_candlists) != 1:
raise PeriodicityCandidateError("Wrong number of candidate lists found accel" \
"candlists: (%d) and ffa candlists: (%d)" % \
(len(candlists)), len(ffa_candlists))
# Get list of candidates from *.accelcands file
candlist = accelcands.parse_candlist(candlists[0])
ffa_candlist = ffacands.parse_candlist(ffa_candlists[0])
# find the search_params.txt file
paramfn = os.path.join(directory, 'search_params.txt')
if os.path.exists(paramfn):
tmp, params = {}, {}
execfile(paramfn, tmp, params)
else:
raise PeriodicityCandidateError("Search parameter file doesn't exist!")
minsigma = params['to_prepfold_sigma']
foldedcands = [c for c in candlist \
if c.sigma > params['to_prepfold_sigma']]
foldedcands = foldedcands[:params['max_accel_cands_to_fold']]
foldedcands.sort(reverse=True) # Sort by descending sigma
ffa_foldedcands = [c for c in ffa_candlist \
if c.snr > params['to_prepfold_sigma']]
# if c.snr > params['ffa_snr']]# need something for ffa
ffa_foldedcands = ffa_foldedcands[:params['max_ffa_cands_to_fold']]
ffa_foldedcands.sort(reverse=True) # Sort by descending snr
# Open attribute file
attrib_fn = os.path.join(directory, 'candidate_attributes.txt')
attribs = np.loadtxt(attrib_fn,dtype='S')
# Create temporary directory
N = 6
prefix = "/localscratch/PALFA_pfds_"
suffix = "_tmp/"
String = ''.join(random.choice(string.ascii_uppercase + string.digits + string.ascii_lowercase) for _ in range(N))
tempdir = prefix+String+suffix
os.makedirs(tempdir)
#tempdir = tempname
if foldedcands or ffa_foldedcands:
pfd_tarfns = glob.glob(os.path.join(directory, "*_pfd.tgz"))
if len(pfd_tarfns) != 1:
raise PeriodicityCandidateError("Wrong number (%d) of *_pfd.tgz " \
"files found in %s" % (len(pfd_tarfns), \
directory))
rating_tarfns = glob.glob(os.path.join(directory, "*_pfd_rat.tgz"))
if len(rating_tarfns) != 1:
raise PeriodicityCandidateError("Wrong number (%d) of *_pfd_rat.tgz " \
"files found in %s" % (len(rating_tarfns), \
directory))
mjd = int(timestamp_mjd)
remote_pfd_base = os.path.join(config.upload.pfd_ftp_dir,str(mjd))
remote_pfd_dir = os.path.join(remote_pfd_base,\
os.path.basename(pfd_tarfns[0]).rstrip('_pfd.tgz'))
pfd_tarball = PFDTarball(pfd_tarfns[0],remote_pfd_base,tempdir)
pfd_tempdir, pfd_list = pfd_tarball.extract()
# extract ratings tarball
tar = tarfile.open(rating_tarfns[0])
try:
tar.extractall(path=tempdir)
except IOError:
if os.path.isdir(tempdir):
shutil.rmtree(tempdir)
raise PeriodicityCandidateError("Error while extracting pfd files " \
"from tarball (%s)!" % tarfn)
finally:
tar.close()
# Loop over candidates that were folded
cands = []
cands.append(pfd_tarball)
counter = 0
for ii, c in enumerate(foldedcands):
basefn = "%s_ACCEL_Cand_%d" % (c.accelfile.replace("ACCEL_", "Z"), \
c.candnum)
pfdfn = os.path.join(pfd_tempdir, basefn+".pfd")
pngfn = os.path.join(directory, basefn+".pfd.png")
ratfn = os.path.join(tempdir, basefn+".pfd.rat")
pfd = prepfold.pfd(pfdfn)
cand_attribs = dict(attribs[attribs[:,0] == basefn+".pfd"][:,1:])
try:
cand = PeriodicityCandidate(ii+1, pfd, c.snr, \
c.cpow, c.ipow, len(c.dmhits), \
c.numharm, versionnum, c.sigma, \
c.period, c.dm, cand_attribs, c.search_type, \
header_id=header_id)
except Exception:
raise PeriodicityCandidateError("PeriodicityCandidate could not be " \
"created (%s)!" % pfdfn)
pfd_size = dict(pfd_list)[pfdfn]
cand.add_dependent(PeriodicityCandidatePFD(pfdfn, pfd_size, remote_pfd_dir=remote_pfd_dir))
cand.add_dependent(PeriodicityCandidatePNG(pngfn))
ratvals = ratings2.rating_value.read_file(ratfn)
cand.add_dependent(PeriodicityCandidateRating(ratvals,inst_cache=inst_cache))
cands.append(cand)
counter +=1
for ii, c in enumerate(ffa_foldedcands):
basefn = "%s%.2fms_Cand" % (c.ffafile.replace("_cands.ffa","_ffa_"), c.period*1000)
pfdfn = os.path.join(pfd_tempdir, basefn+".pfd")
pngfn = os.path.join(directory, basefn+".pfd.png")
ratfn = os.path.join(tempdir, basefn+".pfd.rat")
pfd = prepfold.pfd(pfdfn)
cand_attribs = dict(attribs[attribs[:,0] == basefn+".pfd"][:,1:])
try:
cand = PeriodicityCandidate(counter+ii+1, pfd, c.snr, \
c.cpow, c.ipow, len(c.dmhits), \
c.numharm, versionnum, c.sigma, \
c.period, c.dm, cand_attribs, c.search_type, \
header_id=header_id)
except Exception:
raise PeriodicityCandidateError("PeriodicityCandidate could not be " \
"created (%s)!" % pfdfn)
pfd_size = dict(pfd_list)[pfdfn]
cand.add_dependent(PeriodicityCandidatePFD(pfdfn, pfd_size, remote_pfd_dir=remote_pfd_dir))
cand.add_dependent(PeriodicityCandidatePNG(pngfn))
ratvals = ratings2.rating_value.read_file(ratfn)
cand.add_dependent(PeriodicityCandidateRating(ratvals,inst_cache=inst_cache))
cands.append(cand)
#shutil.rmtree(tempdir)
return cands,tempdir
def check_candidates(header_id, versionnum, directory, dbname='common-copy'):
"""Check candidates in common DB.
Inputs:
header_id: header_id number for this beam, as returned by
spHeaderLoader/header.upload_header
versionnum: A combination of the githash values from
PRESTO and from the pipeline.
directory: The directory containing results from the pipeline.
dbname: Name of database to connect to, or a database
connection to use (Defaut: 'common-copy').
Output:
match: Boolean value. True if all candidates and plots match what
is in the DB, False otherwise.
"""
# find *.accelcands file
candlists = glob.glob(os.path.join(directory, "*.accelcands"))
if len(candlists) != 1:
raise PeriodicityCandidateError("Wrong number of candidate lists found (%d)!" % \
len(candlists))
# Get list of candidates from *.accelcands file
candlist = accelcands.parse_candlist(candlists[0])
minsigma = config.searching.to_prepfold_sigma
foldedcands = [c for c in candlist if c.sigma > minsigma]
foldedcands = foldedcands[:config.searching.max_cands_to_fold]
foldedcands.sort(reverse=True) # Sort by descending sigma
# Create temporary directory
tempdir = tempfile.mkdtemp(suffix="_tmp", prefix="PALFA_pfds_")
tarfns = glob.glob(os.path.join(directory, "*_pfd.tgz"))
if len(tarfns) != 1:
raise PeriodicityCandidateError("Wrong number (%d) of *_pfd.tgz " \
"files found in %s" % (len(tarfns), \
directory))
tar = tarfile.open(tarfns[0])
try:
tar.extractall(path=tempdir)
except IOError:
if os.path.isdir(tempdir):
shutil.rmtree(tempdir)
raise PeriodicityCandidateError("Error while extracting pfd files " \
"from tarball (%s)!" % tarfns[0])
finally:
tar.close()
# Loop over candidates that were folded
matches = []
if isinstance(dbname, database.Database):
db = dbname
else:
db = database.Database(dbname)
for ii, c in enumerate(foldedcands):
basefn = "%s_ACCEL_Cand_%d" % (c.accelfile.replace("ACCEL_", "Z"), \
c.candnum)
pfdfn = os.path.join(tempdir, basefn + ".pfd")
pngfn = os.path.join(directory, basefn + ".pfd.png")
pfd = prepfold.pfd(pfdfn)
try:
cand = PeridocityCandidate(header_id, ii+1, pfd, c.snr, \
c.cpow, c.ipow, len(c.dmhits), \
c.numharm, versionnum, c.sigma)
except Exception:
raise PeriodicityCandidateError("PeriodicityCandidate could not be " \
"created (%s)!" % pfdfn)
matches.append(cand.compare_with_db(dbname))
if not matches[-1]:
break
# Get candidate's ID number from common DB
db.execute("SELECT pdm_cand_id " \
"FROM pdm_candidates AS c " \
"LEFT JOIN versions AS v ON v.version_id = c.version_id " \
"WHERE c.header_id=%d AND c.cand_num=%d " \
"AND v.version_number='%s'" % \
(header_id, cand.cand_num, versionnum))
# For cand.compare_with_db() to return True there must be a unique
# entry in the common DB matching this candidate
r = db.cursor.fetchone()
cand_id = r[0]
pfdplot = PeriodicityCandidatePFD(cand_id, pfdfn)
matches.append(pfdplot.compare_with_db(dbname))
if not matches[-1]:
break
pngplot = PeriodicityCandidatePNG(cand_id, pngfn)
matches.append(pngplot.compare_with_db(dbname))
if not matches[-1]:
break
if type(dbname) == types.StringType:
db.close()
shutil.rmtree(tempdir)
return all(matches)
def upload_candidates(header_id, versionnum, directory, verbose=False, \
dry_run=False, *args, **kwargs):
"""Upload candidates to common DB.
Inputs:
header_id: header_id number for this beam, as returned by
spHeaderLoader/header.upload_header
versionnum: A combination of the githash values from
PRESTO and from the pipeline.
directory: The directory containing results from the pipeline.
verbose: An optional boolean value that determines if information
is printed to stdout.
dry_run: An optional boolean value. If True no connection to DB
will be made and DB command will not be executed.
(If verbose is True DB command will be printed
to stdout.)
*** NOTE: Additional arguments are passed to the uploader function.
Ouputs:
cand_ids: List of candidate IDs corresponding to these candidates
in the common DB. (Or a list of None values if
dry_run is True).
"""
# find *.accelcands file
candlists = glob.glob(os.path.join(directory, "*.accelcands"))
if len(candlists) != 1:
raise PeriodicityCandidateError("Wrong number of candidate lists found (%d)!" % \
len(candlists))
# Get list of candidates from *.accelcands file
candlist = accelcands.parse_candlist(candlists[0])
minsigma = config.searching.to_prepfold_sigma
foldedcands = [c for c in candlist if c.sigma > minsigma]
foldedcands = foldedcands[:config.searching.max_cands_to_fold]
foldedcands.sort(reverse=True) # Sort by descending sigma
# Create temporary directory
tempdir = tempfile.mkdtemp(suffix="_tmp", prefix="PALFA_pfds_")
tarfns = glob.glob(os.path.join(directory, "*_pfd.tgz"))
if len(tarfns) != 1:
raise PeriodicityCandidateError("Wrong number (%d) of *_pfd.tgz " \
"files found in %s" % (len(tarfns), \
directory))
tar = tarfile.open(tarfns[0])
try:
tar.extractall(path=tempdir)
except IOError:
if os.path.isdir(tempdir):
shutil.rmtree(tempdir)
raise PeriodicityCandidateError("Error while extracting pfd files " \
"from tarball (%s)!" % tarfns[0])
finally:
tar.close()
# Loop over candidates that were folded
results = []
for ii, c in enumerate(foldedcands):
basefn = "%s_ACCEL_Cand_%d" % (c.accelfile.replace("ACCEL_", "Z"), \
c.candnum)
pfdfn = os.path.join(tempdir, basefn + ".pfd")
pngfn = os.path.join(directory, basefn + ".pfd.png")
pfd = prepfold.pfd(pfdfn)
try:
cand = PeridocityCandidate(header_id, ii+1, pfd, c.snr, \
c.cpow, c.ipow, len(c.dmhits), \
c.numharm, versionnum, c.sigma)
except Exception:
raise PeriodicityCandidateError("PeriodicityCandidate could not be " \
"created (%s)!" % pfdfn)
if dry_run:
cand.get_upload_sproc_call()
if verbose:
print cand
results.append(None)
cand_id = -1
else:
cand_id = cand.upload(*args, **kwargs)
pfdplot = PeriodicityCandidatePFD(cand_id, pfdfn)
pngplot = PeriodicityCandidatePNG(cand_id, pngfn)
if dry_run:
pfdplot.get_upload_sproc_call()
pngplot.get_upload_sproc_call()
if verbose:
print pfdplot
print pngplot
else:
pfdplot.upload(*args, **kwargs)
pngplot.upload(*args, **kwargs)
shutil.rmtree(tempdir)
return results
def upload_candidates(header_id, versionnum, directory, verbose=False, \
dry_run=False, *args, **kwargs):
"""Upload candidates to common DB.
Inputs:
header_id: header_id number for this beam, as returned by
spHeaderLoader/header.upload_header
versionnum: A combination of the githash values from
PRESTO and from the pipeline.
directory: The directory containing results from the pipeline.
verbose: An optional boolean value that determines if information
is printed to stdout.
dry_run: An optional boolean value. If True no connection to DB
will be made and DB command will not be executed.
(If verbose is True DB command will be printed
to stdout.)
*** NOTE: Additional arguments are passed to the uploader function.
Ouputs:
cand_ids: List of candidate IDs corresponding to these candidates
in the common DB. (Or a list of None values if
dry_run is True).
"""
# find *.accelcands file
candlists = glob.glob(os.path.join(directory, "*.accelcands"))
if len(candlists) != 1:
raise PeriodicityCandidateError("Wrong number of candidate lists found (%d)!" % \
len(candlists))
# Get list of candidates from *.accelcands file
candlist = accelcands.parse_candlist(candlists[0])
minsigma = config.searching.to_prepfold_sigma
foldedcands = [c for c in candlist if c.sigma > minsigma]
foldedcands = foldedcands[:config.searching.max_cands_to_fold]
foldedcands.sort(reverse=True) # Sort by descending sigma
# Create temporary directory
tempdir = tempfile.mkdtemp(suffix="_tmp", prefix="PALFA_pfds_")
tarfns = glob.glob(os.path.join(directory, "*_pfd.tgz"))
if len(tarfns) != 1:
raise PeriodicityCandidateError("Wrong number (%d) of *_pfd.tgz " \
"files found in %s" % (len(tarfns), \
directory))
tar = tarfile.open(tarfns[0])
tar.extractall(path=tempdir)
tar.close()
# Loop over candidates that were folded
results = []
for ii, c in enumerate(foldedcands):
basefn = "%s_ACCEL_Cand_%d" % (c.accelfile.replace("ACCEL_", "Z"), \
c.candnum)
pfdfn = os.path.join(tempdir, basefn+".pfd")
pngfn = os.path.join(directory, basefn+".pfd.png")
pfd = prepfold.pfd(pfdfn)
try:
cand = PeridocityCandidate(header_id, ii+1, pfd, c.snr, \
c.cpow, c.ipow, len(c.dmhits), \
c.numharm, versionnum, c.sigma)
except Exception:
raise PeriodicityCandidateError("PeriodicityCandidate could not be " \
"created (%s)!" % pfdfn)
if dry_run:
cand.get_upload_sproc_call()
if verbose:
print cand
results.append(None)
cand_id = -1
else:
cand_id = cand.upload(*args, **kwargs)
pfdplot = PeriodicityCandidatePFD(cand_id, pfdfn)
pngplot = PeriodicityCandidatePNG(cand_id, pngfn)
if dry_run:
pfdplot.get_upload_sproc_call()
pngplot.get_upload_sproc_call()
if verbose:
print pfdplot
print pngplot
else:
pfdplot.upload(*args, **kwargs)
pngplot.upload(*args, **kwargs)
shutil.rmtree(tempdir)
return results
def get_candidates(versionnum, directory, header_id=None, timestamp_mjd=None, inst_cache=None):
"""Upload candidates to common DB.
Inputs:
versionnum: A combination of the githash values from
PRESTO and from the pipeline.
directory: The directory containing results from the pipeline.
header_id: header_id number for this beam, as returned by
spHeaderLoader/header.upload_header (default=None)
timestamp_mjd: mjd timstamp for this observation (default=None).
inst_cache: ratings2 RatingInstanceIDCache instance.
Ouput:
cands: List of candidates.
tempdir: Path of temporary directory that PFDs have been untarred,
returned so that it can be deleted after successful PFD upload.
"""
# find *.accelcands file
candlists = glob.glob(os.path.join(directory, "*.accelcands"))
if len(candlists) != 1:
raise PeriodicityCandidateError("Wrong number of candidate lists found (%d)!" % \
len(candlists))
# Get list of candidates from *.accelcands file
candlist = accelcands.parse_candlist(candlists[0])
# find the search_params.txt file
paramfn = os.path.join(directory, 'search_params.txt')
if os.path.exists(paramfn):
tmp, params = {}, {}
execfile(paramfn, tmp, params)
else:
raise PeriodicityCandidateError("Search parameter file doesn't exist!")
minsigma = params['to_prepfold_sigma']
foldedcands = [c for c in candlist \
if c.sigma > params['to_prepfold_sigma']]
foldedcands = foldedcands[:params['max_cands_to_fold']]
foldedcands.sort(reverse=True) # Sort by descending sigma
# Open attribute file
attrib_fn = os.path.join(directory, 'candidate_attributes.txt')
attribs = np.loadtxt(attrib_fn,dtype='S')
# Create temporary directory
tempdir = tempfile.mkdtemp(suffix="_tmp", prefix="pfds_", dir="/sps/hep/glast/data/survey_pulsar/")
if foldedcands:
pfd_tarfns = glob.glob(os.path.join(directory, "*_pfd.tgz"))
if len(pfd_tarfns) != 1:
raise PeriodicityCandidateError("Wrong number (%d) of *_pfd.tgz " \
"files found in %s" % (len(pfd_tarfns), \
directory))
bestprof_tarfns = glob.glob(os.path.join(directory, "*_bestprof.tgz"))
if len(bestprof_tarfns) != 1:
raise PeriodicityCandidateError("Wrong number (%d) of *_bestprof.tgz " \
"files found in %s" % (len(bestprof_tarfns), \
directory))
rating_tarfns = glob.glob(os.path.join(directory, "*_pfd_rat.tgz"))
if len(rating_tarfns) != 1:
raise PeriodicityCandidateError("Wrong number (%d) of *_pfd_rat.tgz " \
"files found in %s" % (len(rating_tarfns), \
directory))
for tarfn in [ pfd_tarfns[0], bestprof_tarfns[0], rating_tarfns[0] ]:
tar = tarfile.open(tarfn)
try:
tar.extractall(path=tempdir)
except IOError:
if os.path.isdir(tempdir):
shutil.rmtree(tempdir)
raise PeriodicityCandidateError("Error while extracting pfd files " \
"from tarball (%s)!" % tarfn)
finally:
tar.close()
# Loop over candidates that were folded
cands = []
for ii, c in enumerate(foldedcands):
basefn = "%s_ACCEL_Cand_%d" % (c.accelfile.replace("ACCEL_", "Z"), \
c.candnum)
pfdfn = os.path.join(tempdir, basefn+".pfd")
pngfn = os.path.join(directory, basefn+".pfd.png")
ratfn = os.path.join(tempdir, basefn+".pfd.rat")
pfd = prepfold.pfd(pfdfn)
cand_attribs = dict(attribs[attribs[:,0] == basefn+".pfd"][:,1:])
try:
cand = PeriodicityCandidate(ii+1, pfd, c.snr, \
c.cpow, c.ipow, len(c.dmhits), \
c.numharm, versionnum, c.sigma, \
c.period, c.dm, cand_attribs, header_id=header_id)
except Exception:
raise PeriodicityCandidateError("PeriodicityCandidate could not be " \
"created (%s)!" % pfdfn)
cand.add_dependent(PeriodicityCandidatePFD(pfdfn, timestamp_mjd=timestamp_mjd))
cand.add_dependent(PeriodicityCandidatePNG(pngfn))
ratvals = ratings2.rating_value.read_file(ratfn)
cand.add_dependent(PeriodicityCandidateRating(ratvals,inst_cache=inst_cache))
cands.append(cand)
#shutil.rmtree(tempdir)
return cands,tempdir
def get_candidates(versionnum, directory, header_id=None):
"""Upload candidates to common DB.
Inputs:
versionnum: A combination of the githash values from
PRESTO and from the pipeline.
directory: The directory containing results from the pipeline.
header_id: header_id number for this beam, as returned by
spHeaderLoader/header.upload_header (default=None)
Ouput:
cands: List of candidates.
"""
# find *.accelcands file
candlists = glob.glob(os.path.join(directory, "*.accelcands"))
if len(candlists) != 1:
raise PeriodicityCandidateError("Wrong number of candidate lists found (%d)!" % \
len(candlists))
# Get list of candidates from *.accelcands file
candlist = accelcands.parse_candlist(candlists[0])
# find the search_params.txt file
paramfn = os.path.join(directory, 'search_params.txt')
if os.path.exists(paramfn):
tmp, params = {}, {}
execfile(paramfn, tmp, params)
else:
raise PeriodicityCandidateError("Search parameter file doesn't exist!")
minsigma = params['to_prepfold_sigma']
foldedcands = [c for c in candlist \
if c.sigma > params['to_prepfold_sigma']]
foldedcands = foldedcands[:params['max_cands_to_fold']]
foldedcands.sort(reverse=True) # Sort by descending sigma
# Create temporary directory
tempdir = tempfile.mkdtemp(suffix="_tmp", prefix="PALFA_pfds_")
if foldedcands:
tarfns = glob.glob(os.path.join(directory, "*_pfd.tgz"))
if len(tarfns) != 1:
raise PeriodicityCandidateError("Wrong number (%d) of *_pfd.tgz " \
"files found in %s" % (len(tarfns), \
directory))
tar = tarfile.open(tarfns[0])
try:
tar.extractall(path=tempdir)
except IOError:
if os.path.isdir(tempdir):
shutil.rmtree(tempdir)
raise PeriodicityCandidateError("Error while extracting pfd files " \
"from tarball (%s)!" % tarfns[0])
finally:
tar.close()
# Loop over candidates that were folded
cands = []
for ii, c in enumerate(foldedcands):
basefn = "%s_ACCEL_Cand_%d" % (c.accelfile.replace("ACCEL_", "Z"), \
c.candnum)
pfdfn = os.path.join(tempdir, basefn + ".pfd")
pngfn = os.path.join(directory, basefn + ".pfd.png")
pfd = prepfold.pfd(pfdfn)
try:
cand = PeriodicityCandidate(ii+1, pfd, c.snr, \
c.cpow, c.ipow, len(c.dmhits), \
c.numharm, versionnum, c.sigma, \
header_id=header_id)
except Exception:
raise PeriodicityCandidateError("PeriodicityCandidate could not be " \
"created (%s)!" % pfdfn)
cand.add_dependent(PeriodicityCandidatePFD(pfdfn))
cand.add_dependent(PeriodicityCandidatePNG(pngfn))
cands.append(cand)
shutil.rmtree(tempdir)
return cands
def get_candidates(versionnum, directory, header_id=None):
"""Upload candidates to common DB.
Inputs:
versionnum: A combination of the githash values from
PRESTO and from the pipeline.
directory: The directory containing results from the pipeline.
header_id: header_id number for this beam, as returned by
spHeaderLoader/header.upload_header (default=None)
Ouput:
cands: List of candidates.
"""
# find *.accelcands file
candlists = glob.glob(os.path.join(directory, "*.accelcands"))
if len(candlists) != 1:
raise PeriodicityCandidateError("Wrong number of candidate lists found (%d)!" % \
len(candlists))
# Get list of candidates from *.accelcands file
candlist = accelcands.parse_candlist(candlists[0])
# find the search_params.txt file
paramfn = os.path.join(directory, 'search_params.txt')
if os.path.exists(paramfn):
tmp, params = {}, {}
execfile(paramfn, tmp, params)
else:
raise PeriodicityCandidateError("Search parameter file doesn't exist!")
minsigma = params['to_prepfold_sigma']
foldedcands = [c for c in candlist \
if c.sigma > params['to_prepfold_sigma']]
foldedcands = foldedcands[:params['max_cands_to_fold']]
foldedcands.sort(reverse=True) # Sort by descending sigma
# Create temporary directory
tempdir = tempfile.mkdtemp(suffix="_tmp", prefix="PALFA_pfds_")
if foldedcands:
tarfns = glob.glob(os.path.join(directory, "*_pfd.tgz"))
if len(tarfns) != 1:
raise PeriodicityCandidateError("Wrong number (%d) of *_pfd.tgz " \
"files found in %s" % (len(tarfns), \
directory))
tar = tarfile.open(tarfns[0])
try:
tar.extractall(path=tempdir)
except IOError:
if os.path.isdir(tempdir):
shutil.rmtree(tempdir)
raise PeriodicityCandidateError("Error while extracting pfd files " \
"from tarball (%s)!" % tarfns[0])
finally:
tar.close()
# Loop over candidates that were folded
cands = []
for ii, c in enumerate(foldedcands):
basefn = "%s_ACCEL_Cand_%d" % (c.accelfile.replace("ACCEL_", "Z"), \
c.candnum)
pfdfn = os.path.join(tempdir, basefn+".pfd")
pngfn = os.path.join(directory, basefn+".pfd.png")
pfd = prepfold.pfd(pfdfn)
try:
cand = PeriodicityCandidate(ii+1, pfd, c.snr, \
c.cpow, c.ipow, len(c.dmhits), \
c.numharm, versionnum, c.sigma, \
header_id=header_id)
except Exception:
raise PeriodicityCandidateError("PeriodicityCandidate could not be " \
"created (%s)!" % pfdfn)
cand.add_dependent(PeriodicityCandidatePFD(pfdfn))
cand.add_dependent(PeriodicityCandidatePNG(pngfn))
cands.append(cand)
shutil.rmtree(tempdir)
return cands
def check_candidates(header_id, versionnum, directory, dbname='common-copy'):
"""Check candidates in common DB.
Inputs:
header_id: header_id number for this beam, as returned by
spHeaderLoader/header.upload_header
versionnum: A combination of the githash values from
PRESTO and from the pipeline.
directory: The directory containing results from the pipeline.
dbname: Name of database to connect to, or a database
connection to use (Defaut: 'common-copy').
Output:
match: Boolean value. True if all candidates and plots match what
is in the DB, False otherwise.
"""
# find *.accelcands file
candlists = glob.glob(os.path.join(directory, "*.accelcands"))
if len(candlists) != 1:
raise PeriodicityCandidateError("Wrong number of candidate lists found (%d)!" % \
len(candlists))
# Get list of candidates from *.accelcands file
candlist = accelcands.parse_candlist(candlists[0])
minsigma = config.searching.to_prepfold_sigma
foldedcands = [c for c in candlist if c.sigma > minsigma]
foldedcands = foldedcands[:config.searching.max_cands_to_fold]
foldedcands.sort(reverse=True) # Sort by descending sigma
# Create temporary directory
tempdir = tempfile.mkdtemp(suffix="_tmp", prefix="PALFA_pfds_")
tarfns = glob.glob(os.path.join(directory, "*_pfd.tgz"))
if len(tarfns) != 1:
raise PeriodicityCandidateError("Wrong number (%d) of *_pfd.tgz " \
"files found in %s" % (len(tarfns), \
directory))
tar = tarfile.open(tarfns[0])
try:
tar.extractall(path=tempdir)
except IOError:
if os.path.isdir(tempdir):
shutil.rmtree(tempdir)
raise PeriodicityCandidateError("Error while extracting pfd files " \
"from tarball (%s)!" % tarfns[0])
finally:
tar.close()
# Loop over candidates that were folded
matches = []
if isinstance(dbname, database.Database):
db = dbname
else:
db = database.Database(dbname)
for ii, c in enumerate(foldedcands):
basefn = "%s_ACCEL_Cand_%d" % (c.accelfile.replace("ACCEL_", "Z"), \
c.candnum)
pfdfn = os.path.join(tempdir, basefn+".pfd")
pngfn = os.path.join(directory, basefn+".pfd.png")
pfd = prepfold.pfd(pfdfn)
try:
cand = PeridocityCandidate(header_id, ii+1, pfd, c.snr, \
c.cpow, c.ipow, len(c.dmhits), \
c.numharm, versionnum, c.sigma)
except Exception:
raise PeriodicityCandidateError("PeriodicityCandidate could not be " \
"created (%s)!" % pfdfn)
matches.append(cand.compare_with_db(dbname))
if not matches[-1]:
break
# Get candidate's ID number from common DB
db.execute("SELECT pdm_cand_id " \
"FROM pdm_candidates AS c " \
"LEFT JOIN versions AS v ON v.version_id = c.version_id " \
"WHERE c.header_id=%d AND c.cand_num=%d " \
"AND v.version_number='%s'" % \
(header_id, cand.cand_num, versionnum))
# For cand.compare_with_db() to return True there must be a unique
# entry in the common DB matching this candidate
r = db.cursor.fetchone()
cand_id = r[0]
pfdplot = PeriodicityCandidatePFD(cand_id, pfdfn)
matches.append(pfdplot.compare_with_db(dbname))
if not matches[-1]:
break
pngplot = PeriodicityCandidatePNG(cand_id, pngfn)
matches.append(pngplot.compare_with_db(dbname))
if not matches[-1]:
break
if type(dbname) == types.StringType:
db.close()
shutil.rmtree(tempdir)
return all(matches)
