def _search_files(self):
"""
Search for the data-files. The value of `self.inputs['job_name']` is
used to compose the glob search pattern. It is split into parts
separated by '_'. The first part should (in principle) be identical to
the MAC/SAS observation ID (e.g., L29066). The second (optional) part
specifies the sub-array-pointing(e.g., 1); it defaults to 0.
"""
job_name_parts = self.inputs['job_name'].split('_')
job = job_name_parts[0]
sap = 0
try:
errmsg = (
"Job-name part indicating sub-array-pointing index is %s, "
"defaulting to 0")
sap = int(job_name_parts[1])
except IndexError:
self.logger.debug(errmsg % "missing")
except ValueError:
self.logger.warn(errmsg % "non-numeric")
ms_pattern = os.path.join(
self.inputs['observation_dir'],
'%s_SAP%03d_SB???_uv.MS{,.dppp}' % (job, sap))
self.logger.debug("Searching for data files: %s" % ms_pattern)
data = findFiles(ms_pattern, '-1d')
return list(zip(data[0], data[1]))
def tally_data_map(data, glob, logger=None):
"""
Verify that the file specified in the data map `data` exist on the cluster.
The glob pattern `glob` should contain the pattern to be used in the search.
This function will return a list of booleans: True for each item in `data`
that is present on the cluster; False otherwise.
This method is deprecated, because the new data-map file keep track of the
`skip` attribute of each data product in the data-map.
"""
import os
from lofar.mstools import findFiles
# Determine the directories to search. Get unique directory names from
# `data` by creating a set first.
dirs = list(set(os.path.dirname(d.file) for d in data))
# Compose the filename glob-pattern.
glob = ' '.join(os.path.join(d, glob) for d in dirs)
# Search the file on the cluster using the glob-pattern; turn them into a
# list of tuples.
if logger:
logger.debug("Searching for file: %s" % glob)
found = zip(*findFiles(glob, '-1d'))
# Return a mask containing True if file exists, False otherwise
return [(f.host, f.file) in found for f in data]
def tally_data_map(data, glob, logger=None):
"""
Verify that the file specified in the data map `data` exist on the cluster.
The glob pattern `glob` should contain the pattern to be used in the search.
This function will return a list of booleans: True for each item in `data`
that is present on the cluster; False otherwise.
This method is deprecated, because the new data-map file keep track of the
`skip` attribute of each data product in the data-map.
"""
import os
from lofar.mstools import findFiles
# Determine the directories to search. Get unique directory names from
# `data` by creating a set first.
dirs = list(set(os.path.dirname(d.file) for d in data))
# Compose the filename glob-pattern.
glob = ' '.join(os.path.join(d, glob) for d in dirs)
# Search the file on the cluster using the glob-pattern; turn them into a
# list of tuples.
if logger:
logger.debug("Searching for file: %s" % glob)
found = zip(*findFiles(glob, '-1d'))
# Return a mask containing True if file exists, False otherwise
return [(f.host, f.file) in found for f in data]
def _search_files(self):
"""
Search for the data-files. The value of `self.inputs['job_name']` is
used to compose the glob search pattern. It is split into parts
separated by '_'. The first part should (in principle) be identical to
the MAC/SAS observation ID (e.g., L29066). The second (optional) part
specifies the sub-array-pointing(e.g., 1); it defaults to 0.
"""
job_name_parts = self.inputs['job_name'].split('_')
job = job_name_parts[0]
sap = 0
try:
errmsg = (
"Job-name part indicating sub-array-pointing index is %s, "
"defaulting to 0"
)
sap = int(job_name_parts[1])
except IndexError:
self.logger.debug(errmsg % "missing")
except ValueError:
self.logger.warn(errmsg % "non-numeric")
ms_pattern = os.path.join(
self.inputs['observation_dir'],
'%s_SAP%03d_SB???_uv.MS{,.dppp}' % (job, sap)
)
self.logger.debug("Searching for data files: %s" % ms_pattern)
data = findFiles(ms_pattern, '-1d')
return zip(data[0], data[1])