def test_align_data_maps_equal_maps_skip_set_5_multi_maps(self):
# test for DataMap align
data_map = MultiDataMap(self.new_style_multi_map)
data_map2 = MultiDataMap(self.new_style_multi_map)
data_map3 = MultiDataMap(self.new_style_multi_map)
data_map4 = MultiDataMap(self.new_style_multi_map)
data_map5 = MultiDataMap(self.new_style_multi_map)
# change single skip value
data_map.data[1].skip = True
# Perform an align
align_data_maps(data_map, data_map2, data_map3, data_map4, data_map5)
self.assertTrue(
data_map2.data[2].skip, "The skip field was not"
" alligned correctly in the second entrie")
self.assertTrue(
data_map3.data[2].skip, "The skip field was not"
" alligned correctly in the second entrie")
self.assertTrue(
data_map4.data[2].skip, "The skip field was not"
" alligned correctly in the second entrie")
self.assertTrue(
data_map5.data[2].skip, "The skip field was not"
" alligned correctly in the second entrie")
def _run_create_dbs_node(self, input_map, slice_paths_map,
assoc_theta, source_list_map):
"""
Decompose the input mapfiles into task for specific nodes and
distribute these to the node recipes. Wait for the jobs to finish and
return the list of created jobs.
"""
# Compile the command to be executed on the remote machine
node_command = " python3 %s" % (self.__file__.replace("master", "nodes"))
# create jobs
jobs = []
output_map = copy.deepcopy(input_map)
# Update the skip fields of the four maps. If 'skip' is True in any of
# these maps, then 'skip' must be set to True in all maps.
align_data_maps(input_map, output_map, slice_paths_map,
source_list_map)
source_list_map.iterator = slice_paths_map.iterator = \
input_map.iterator = DataMap.SkipIterator
for idx, (input_item, slice_item, source_list_item) in enumerate(zip(
input_map, slice_paths_map, source_list_map)):
host_ms, concat_ms = input_item.host, input_item.file
host_slice, slice_paths = slice_item.host, slice_item.file
# Create the parameters depending on the input_map
sourcedb_target_path = os.path.join(
concat_ms + self.inputs["sourcedb_suffix"])
# use unique working directories per job, to prevent interference between jobs on a global fs
working_dir = os.path.join(self.inputs['working_directory'], "imager_create_dbs_{0}".format(idx))
# The actual call for the node script
arguments = [concat_ms,
sourcedb_target_path,
self.inputs["monetdb_hostname"],
self.inputs["monetdb_port"],
self.inputs["monetdb_name"],
self.inputs["monetdb_user"],
self.inputs["monetdb_password"],
assoc_theta,
self.inputs["parmdb_executable"],
slice_paths,
self.inputs["parmdb_suffix"],
self.environment,
working_dir,
self.inputs["makesourcedb_path"],
source_list_item.file,
self.inputs["major_cycle"]]
jobs.append(ComputeJob(host_ms, node_command, arguments))
# Wait the nodes to finish
if len(jobs) > 0:
self._schedule_jobs(jobs)
return jobs, output_map
def _run_create_dbs_node(self, input_map, slice_paths_map,
assoc_theta, source_list_map):
"""
Decompose the input mapfiles into task for specific nodes and
distribute these to the node recipes. Wait for the jobs to finish and
return the list of created jobs.
"""
# Compile the command to be executed on the remote machine
node_command = " python %s" % (self.__file__.replace("master", "nodes"))
# create jobs
jobs = []
output_map = copy.deepcopy(input_map)
# Update the skip fields of the four maps. If 'skip' is True in any of
# these maps, then 'skip' must be set to True in all maps.
align_data_maps(input_map, output_map, slice_paths_map,
source_list_map)
source_list_map.iterator = slice_paths_map.iterator = \
input_map.iterator = DataMap.SkipIterator
for idx, (input_item, slice_item, source_list_item) in enumerate(zip(
input_map, slice_paths_map,source_list_map)):
host_ms, concat_ms = input_item.host, input_item.file
host_slice, slice_paths = slice_item.host, slice_item.file
# Create the parameters depending on the input_map
sourcedb_target_path = os.path.join(
concat_ms + self.inputs["sourcedb_suffix"])
# use unique working directories per job, to prevent interference between jobs on a global fs
working_dir = os.path.join(self.inputs['working_directory'], "imager_create_dbs_{0}".format(idx))
# The actual call for the node script
arguments = [concat_ms,
sourcedb_target_path,
self.inputs["monetdb_hostname"],
self.inputs["monetdb_port"],
self.inputs["monetdb_name"],
self.inputs["monetdb_user"],
self.inputs["monetdb_password"],
assoc_theta,
self.inputs["parmdb_executable"],
slice_paths,
self.inputs["parmdb_suffix"],
self.environment,
working_dir,
self.inputs["makesourcedb_path"],
source_list_item.file,
self.inputs["major_cycle"]]
jobs.append(ComputeJob(host_ms, node_command, arguments))
# Wait the nodes to finish
if len(jobs) > 0:
self._schedule_jobs(jobs)
return jobs, output_map
def _get_io_product_specs(self):
"""
Get input- and output-data product specifications from the
parset-file, and do some sanity checks.
"""
dps = self.parset.makeSubset(
self.parset.fullModuleName('DataProducts') + '.'
)
# convert input dataproducts from parset value to DataMap
self.input_data = DataMap([
tuple(os.path.join(location, filename).split(':')) + (skip,)
for location, filename, skip in zip(
dps.getStringVector('Input_Correlated.locations'),
dps.getStringVector('Input_Correlated.filenames'),
dps.getBoolVector('Input_Correlated.skip'))
])
self.logger.debug("%d Input_Correlated data products specified" %
len(self.input_data))
self.output_data = DataMap([
tuple(os.path.join(location, filename).split(':')) + (skip,)
for location, filename, skip in zip(
dps.getStringVector('Output_SkyImage.locations'),
dps.getStringVector('Output_SkyImage.filenames'),
dps.getBoolVector('Output_SkyImage.skip'))
])
self.logger.debug("%d Output_SkyImage data products specified" %
len(self.output_data))
self.output_correlated_data = DataMap([
tuple(os.path.join(location, filename).split(':')) + (skip,)
for location, filename, skip in zip(
dps.getStringVector('Output_Correlated.locations'),
dps.getStringVector('Output_Correlated.filenames'),
dps.getBoolVector('Output_Correlated.skip'))
])
# assure that the two output maps contain the same skip fields
align_data_maps( self.output_data, self.output_correlated_data)
self.logger.debug("%d Output_Correlated data products specified" %
len(self.output_correlated_data))
# # Sanity checks on input- and output data product specifications
# if not validate_data_maps(self.input_data, self.output_data):
# raise PipelineException(
# "Validation of input/output data product specification failed!"
# )#Turned off untill DataMap is extended..
# Target data is basically scratch data, consisting of one concatenated
# MS per image. It must be stored on the same host as the final image.
self.target_data = copy.deepcopy(self.output_data)
for idx, item in enumerate(self.target_data):
item.file = os.path.join(self.scratch_directory, 'ms_per_image_%d' % idx, 'concat.ms')
def test_align_data_maps_equal_maps_no_change(self):
data_map = MultiDataMap(self.new_style_multi_map)
data_map2 = MultiDataMap(self.new_style_multi_map)
data_map3 = MultiDataMap(self.new_style_multi_map)
# Perform an align
align_data_maps(data_map, data_map2)
# There should be no changes and the three maps should be the same
for entrie1, entrie2, entrie3 in zip(data_map, data_map2, data_map3):
self.assertEqual(entrie1, entrie3)
self.assertEqual(entrie2, entrie3)
def test_align_data_maps_equal_maps_no_change(self):
data_map = MultiDataMap(self.new_style_multi_map)
data_map2 = MultiDataMap(self.new_style_multi_map)
data_map3 = MultiDataMap(self.new_style_multi_map)
# Perform an align
align_data_maps(data_map, data_map2)
# There should be no changes and the three maps should be the same
for entrie1, entrie2, entrie3 in zip(data_map, data_map2, data_map3):
self.assertEqual(entrie1, entrie3)
self.assertEqual(entrie2, entrie3)
def test_align_data_maps_equal_maps_skip_set(self):
data_map = MultiDataMap(self.new_style_multi_map)
data_map2 = MultiDataMap(self.new_style_multi_map)
# Change a single entrie in the datamap to True
data_map.data[1].skip = True
# Perform an align
align_data_maps(data_map, data_map2)
# The second entrie.skip should be set to True
self.assertTrue(data_map2.data[2].skip, "The skip field was not"
" alligned correctly in the second entrie")
def test_align_data_maps_equal_maps_skip_set(self):
data_map = MultiDataMap(self.new_style_multi_map)
data_map2 = MultiDataMap(self.new_style_multi_map)
# Change a single entrie in the datamap to True
data_map.data[1].skip = True
# Perform an align
align_data_maps(data_map, data_map2)
# The second entrie.skip should be set to True
self.assertTrue(
data_map2.data[2].skip, "The skip field was not"
" alligned correctly in the second entrie")
def test_align_data_maps_equal_maps_skip_set_5_multi_maps(self):
# test for DataMap align
data_map = MultiDataMap(self.new_style_multi_map)
data_map2 = MultiDataMap(self.new_style_multi_map)
data_map3 = MultiDataMap(self.new_style_multi_map)
data_map4 = MultiDataMap(self.new_style_multi_map)
data_map5 = MultiDataMap(self.new_style_multi_map)
# change single skip value
data_map.data[1].skip = True
# Perform an align
align_data_maps(data_map, data_map2, data_map3, data_map4, data_map5)
self.assertTrue(data_map2.data[2].skip, "The skip field was not"
" alligned correctly in the second entrie")
self.assertTrue(data_map3.data[2].skip, "The skip field was not"
" alligned correctly in the second entrie")
self.assertTrue(data_map4.data[2].skip, "The skip field was not"
" alligned correctly in the second entrie")
self.assertTrue(data_map5.data[2].skip, "The skip field was not"
" alligned correctly in the second entrie")
def go(self):
if 'executable' in self.inputs:
executable = self.inputs['executable']
if self.inputs['nthreads']:
self.environment["OMP_NUM_THREADS"] = str(self.inputs['nthreads'])
if 'environment' in self.inputs:
self.environment.update(self.inputs['environment'])
self.logger.info("Starting %s run" % executable)
super(executable_args, self).go()
# args format stuff
args_format = {'args_format': self.inputs['args_format'],
'args_format_argument': self.inputs['args_format_argument'],
'args_format_option': self.inputs['args_format_option'],
'args_formatlongoption': self.inputs['args_format_longoption'],
'args_format_option_argument': self.inputs['args_format_option_argument']}
mapfile_dir = os.path.join(self.config.get("layout", "job_directory"), "mapfiles")
work_dir = os.path.join(self.inputs['working_directory'], self.inputs['job_name'])
# *********************************************************************
# try loading input/output data file, validate output vs the input location if
# output locations are provided
try:
inputmapfiles = []
inlist = []
if self.inputs['mapfile_in']:
inlist.append(self.inputs['mapfile_in'])
if self.inputs['mapfiles_in']:
for item in self.inputs['mapfiles_in']:
inlist.append(item)
self.inputs['mapfile_in'] = self.inputs['mapfiles_in'][0]
for item in inlist:
inputmapfiles.append(DataMap.load(item))
except Exception:
self.logger.error('Could not load input Mapfile %s' % inlist)
return 1
outputmapfiles = []
if self.inputs['mapfile_out']:
try:
outdata = DataMap.load(self.inputs['mapfile_out'])
outputmapfiles.append(outdata)
except Exception:
self.logger.error('Could not load output Mapfile %s' % self.inputs['mapfile_out'])
return 1
# sync skip fields in the mapfiles
align_data_maps(inputmapfiles[0], outputmapfiles[0])
elif self.inputs['mapfiles_out']:
for item in self.inputs['mapfiles_out']:
outputmapfiles.append(DataMap.load(item))
self.inputs['mapfile_out'] = self.inputs['mapfiles_out'][0]
else:
# ouput will be directed in the working directory if no output mapfile is specified
outdata = copy.deepcopy(inputmapfiles[0])
if not self.inputs['inplace']:
for item in outdata:
item.file = os.path.join(
self.inputs['working_directory'],
self.inputs['job_name'],
#os.path.basename(item.file) + '.' + os.path.split(str(executable))[1]
os.path.splitext(os.path.basename(item.file))[0] + '.' + self.inputs['stepname']
)
self.inputs['mapfile_out'] = os.path.join(mapfile_dir, self.inputs['stepname'] + '.' + 'mapfile')
self.inputs['mapfiles_out'].append(self.inputs['mapfile_out'])
else:
self.inputs['mapfile_out'] = self.inputs['mapfile_in']
self.inputs['mapfiles_out'].append(self.inputs['mapfile_out'])
outputmapfiles.append(outdata)
if not validate_data_maps(inputmapfiles[0], outputmapfiles[0]):
self.logger.error(
"Validation of data mapfiles failed!"
)
return 1
if self.inputs['outputsuffixes']:
# Handle multiple outputfiles
for name in self.inputs['outputsuffixes']:
outputmapfiles.append(copy.deepcopy(inputmapfiles[0]))
self.inputs['mapfiles_out'].append(os.path.join(mapfile_dir, self.inputs['stepname'] + name + '.' + 'mapfile'))
for item in outputmapfiles[-1]:
item.file = os.path.join(
work_dir,
os.path.splitext(os.path.basename(item.file))[0] + '.' + self.inputs['stepname'] + name
)
self.inputs['mapfile_out'] = self.inputs['mapfiles_out'][0]
# prepare arguments
arglist = self.inputs['arguments']
parsetdict = {}
if 'parset' in self.inputs:
parset = Parset()
parset.adoptFile(self.inputs['parset'])
for k in parset.keys:
parsetdict[k] = str(parset[k])
# construct multiple input data
if self.inputs['inputkey'] and not self.inputs['inputkey'] in self.inputs['inputkeys']:
self.inputs['inputkeys'].insert(0, self.inputs['inputkey'])
if not self.inputs['outputkeys'] and self.inputs['outputkey']:
self.inputs['outputkeys'].append(self.inputs['outputkey'])
if not self.inputs['skip_infile'] and len(self.inputs['inputkeys']) is not len(inputmapfiles):
self.logger.error("Number of input mapfiles %d and input keys %d have to match." %
(len(inputmapfiles), len(self.inputs['inputkeys'])))
return 1
filedict = {}
if self.inputs['inputkeys'] and not self.inputs['skip_infile']:
for key, filemap, mapname in zip(self.inputs['inputkeys'], inputmapfiles, inlist):
if not mapname in self.inputs['mapfiles_as_string']:
filedict[key] = []
for inp in filemap:
filedict[key].append(inp.file)
else:
if key != mapname:
filedict[key] = []
for inp in filemap:
filedict[key].append(mapname)
if self.inputs['outputkey']:
filedict[self.inputs['outputkey']] = []
for item in outputmapfiles[0]:
filedict[self.inputs['outputkey']].append(item.file)
# ********************************************************************
# Call the node side of the recipe
# Create and schedule the compute jobs
#command = "python %s" % (self.__file__.replace('master', 'nodes')).replace('executable_args', self.inputs['nodescript'])
recipe_dir_str = str(self.config.get('DEFAULT', 'recipe_directories'))
recipe_directories = recipe_dir_str.rstrip(']').lstrip('[').split(',')
pylist = os.getenv('PYTHONPATH').split(':')
command = None
for pl in pylist:
if os.path.isfile(os.path.join(pl,'lofarpipe/recipes/nodes/'+self.inputs['nodescript']+'.py')):
command = "python %s" % os.path.join(pl,'lofarpipe/recipes/nodes/'+self.inputs['nodescript']+'.py')
for pl in recipe_directories:
if os.path.isfile(os.path.join(pl,'nodes/'+self.inputs['nodescript']+'.py')):
command = "python %s" % os.path.join(pl,'nodes/'+self.inputs['nodescript']+'.py')
inputmapfiles[0].iterator = outputmapfiles[0].iterator = DataMap.SkipIterator
jobs = []
for i, (outp, inp,) in enumerate(zip(
outputmapfiles[0], inputmapfiles[0])
):
arglist_copy = copy.deepcopy(arglist)
parsetdict_copy = copy.deepcopy(parsetdict)
if filedict:
for name, value in filedict.iteritems():
replaced = False
if arglist_copy:
for arg in arglist:
if name == arg:
ind = arglist_copy.index(arg)
arglist_copy[ind] = arglist_copy[ind].replace(name, value[i])
replaced = True
if parsetdict_copy:
if name in parsetdict_copy.values():
for k, v in parsetdict_copy.iteritems():
if v == name:
parsetdict_copy[k] = value[i]
else:
if not replaced:
parsetdict_copy[name] = value[i]
jobs.append(
ComputeJob(
inp.host, command,
arguments=[
inp.file,
executable,
arglist_copy,
parsetdict_copy,
work_dir,
self.inputs['parsetasfile'],
args_format,
self.environment
],
resources={
"cores": self.inputs['nthreads']
}
)
)
max_per_node = self.inputs['max_per_node']
self._schedule_jobs(jobs, max_per_node)
jobresultdict = {}
resultmap = {}
for job, outp in zip(jobs, outputmapfiles[0]):
if job.results['returncode'] != 0:
outp.skip = True
if not self.inputs['error_tolerance']:
self.logger.error("A job has failed with returncode %d and error_tolerance is not set. Bailing out!" % job.results['returncode'])
return 1
for k, v in job.results.items():
if not k in jobresultdict:
jobresultdict[k] = []
jobresultdict[k].append(DataProduct(job.host, job.results[k], outp.skip))
if k == 'break':
self.outputs.update({'break': v})
# temp solution. write all output dict entries to a mapfile
#mapfile_dir = os.path.join(self.config.get("layout", "job_directory"), "mapfiles")
#check directory for stand alone mode
if not os.path.isdir(mapfile_dir):
try:
os.mkdir(mapfile_dir, )
except OSError as exc: # Python >2.5
if exc.errno == errno.EEXIST and os.path.isdir(mapfile_dir):
pass
else:
raise
for k, v in jobresultdict.items():
dmap = DataMap(v)
dmap.save(os.path.join(mapfile_dir, self.inputs['stepname'] + '.' + k + '.mapfile'))
resultmap[k + '.mapfile'] = os.path.join(mapfile_dir, self.inputs['stepname'] + '.' + k + '.mapfile')
self.outputs.update(resultmap)
# *********************************************************************
# Check job results, and create output data map file
if self.error.isSet():
# Abort if all jobs failed
if all(job.results['returncode'] != 0 for job in jobs):
self.logger.error("All jobs failed. Bailing out!")
return 1
else:
self.logger.warn(
"Some jobs failed, continuing with succeeded runs"
)
mapdict = {}
for item, name in zip(outputmapfiles, self.inputs['mapfiles_out']):
self.logger.debug("Writing data map file: %s" % name)
item.save(name)
mapdict[os.path.basename(name)] = name
self.outputs['mapfile'] = self.inputs['mapfile_out']
if self.inputs['outputsuffixes']:
self.outputs.update(mapdict)
return 0
def go(self):
"""
Steps:
1. Load and validate the input datamaps
2. Run the node parts of the recipe
3. Validate node output and format the recipe output
"""
super(selfcal_finalize, self).go()
# *********************************************************************
# 1. Load the datamaps
awimager_output_map = DataMap.load(self.inputs["awimager_output_map"])
ms_per_image_map = DataMap.load(self.inputs["ms_per_image_map"])
sourcelist_map = DataMap.load(self.inputs["sourcelist_map"])
sourcedb_map = DataMap.load(self.inputs["sourcedb_map"])
target_mapfile = DataMap.load(self.inputs["target_mapfile"])
output_image_mapfile = DataMap.load(
self.inputs["output_image_mapfile"])
concat_ms_mapfile = DataMap.load(self.inputs["concat_ms_map_path"])
output_correlated_map = DataMap.load(
self.inputs["output_correlated_mapfile"])
processed_ms_dir = self.inputs["processed_ms_dir"]
fillrootimagegroup_exec = self.inputs["fillrootimagegroup_exec"]
# Align the skip fields
align_data_maps(awimager_output_map, ms_per_image_map, sourcelist_map,
target_mapfile, output_image_mapfile, sourcedb_map,
concat_ms_mapfile, output_correlated_map)
# Set the correct iterator
sourcelist_map.iterator = awimager_output_map.iterator = \
ms_per_image_map.iterator = target_mapfile.iterator = \
output_image_mapfile.iterator = sourcedb_map.iterator = \
concat_ms_mapfile.iterator = output_correlated_map.iterator = \
DataMap.SkipIterator
# *********************************************************************
# 2. Run the node side of the recupe
command = " python3 %s" % (self.__file__.replace("master", "nodes"))
jobs = []
for (awimager_output_item, ms_per_image_item, sourcelist_item,
target_item, output_image_item, sourcedb_item, concat_ms_item,
correlated_item) in zip(awimager_output_map, ms_per_image_map,
sourcelist_map, target_mapfile,
output_image_mapfile, sourcedb_map,
concat_ms_mapfile, output_correlated_map):
# collect the files as argument
arguments = [
awimager_output_item.file,
ms_per_image_item.file,
sourcelist_item.file,
target_item.file,
output_image_item.file,
self.inputs["minbaseline"],
self.inputs["maxbaseline"],
processed_ms_dir,
fillrootimagegroup_exec,
self.environment,
sourcedb_item.file,
concat_ms_item.file,
correlated_item.file,
self.inputs["msselect_executable"],
]
self.logger.info(
"Starting finalize with the folowing args: {0}".format(
arguments))
jobs.append(ComputeJob(target_item.host, command, arguments))
self._schedule_jobs(jobs)
# *********************************************************************
# 3. Validate the performance of the node script and assign output
succesful_run = False
for (job, output_image_item,
output_correlated_item) in zip(jobs, output_image_mapfile,
output_correlated_map):
if not "hdf5" in job.results:
# If the output failed set the skip to True
output_image_item.skip = True
output_correlated_item = True
else:
succesful_run = True
# signal that we have at least a single run finished ok.
# No need to set skip in this case
if not succesful_run:
self.logger.warn("Not a single finalizer succeeded")
return 1
# Save the location of the output images
output_image_mapfile.save(self.inputs['placed_image_mapfile'])
self.logger.debug(
"Wrote mapfile containing placed hdf5 images: {0}".format(
self.inputs['placed_image_mapfile']))
# save the location of measurements sets
output_correlated_map.save(self.inputs['placed_correlated_mapfile'])
self.logger.debug("Wrote mapfile containing placed mss: {0}".format(
self.inputs['placed_correlated_mapfile']))
self.outputs["placed_image_mapfile"] = self.inputs[
'placed_image_mapfile']
self.outputs["placed_correlated_mapfile"] = self.inputs[
'placed_correlated_mapfile']
return 0
def go(self):
"""
This member contains all the functionality of the imager_awimager.
Functionality is all located at the node side of the script.
"""
super(selfcal_awimager, self).go()
self.logger.info("Starting imager_awimager run")
# *********************************************************************
# 1. collect the inputs and validate
input_map = DataMap.load(self.inputs['args'][0])
sourcedb_map = DataMap.load(self.inputs['sourcedb_path'])
if not validate_data_maps(input_map, sourcedb_map):
self.logger.error(
"the supplied input_ms mapfile and sourcedb mapfile"
"are incorrect. Aborting")
self.logger.error(repr(input_map))
self.logger.error(repr(sourcedb_map))
return 1
# *********************************************************************
# 2. Start the node side of the awimager recipe
# Compile the command to be executed on the remote machine
node_command = "python3 %s" % (self.__file__.replace("master", "nodes"))
jobs = []
output_map = copy.deepcopy(input_map)
align_data_maps(input_map, output_map, sourcedb_map)
sourcedb_map.iterator = input_map.iterator = output_map.iterator = \
DataMap.SkipIterator
for measurement_item, source_item in zip(input_map, sourcedb_map):
if measurement_item.skip or source_item.skip:
jobs.append(None)
continue
# both the sourcedb and the measurement are in a map
# unpack both
host , measurement_path = measurement_item.host, measurement_item.file
host2 , sourcedb_path = source_item.host, source_item.file
# construct and save the output name
arguments = [self.inputs['executable'],
self.environment,
self.inputs['parset'],
self.inputs['working_directory'],
self.inputs['output_image'],
measurement_path,
sourcedb_path,
self.inputs['mask_patch_size'],
self.inputs['autogenerate_parameters'],
self.inputs['specify_fov'],
self.inputs['fov'],
self.inputs['major_cycle'],
self.inputs['nr_cycles'],
self.inputs['perform_self_cal']
]
jobs.append(ComputeJob(host, node_command, arguments))
self._schedule_jobs(jobs)
# *********************************************************************
# 3. Check output of the node scripts
for job, output_item in zip(jobs, output_map):
# job == None on skipped job
if not "image" in job.results:
output_item.file = "failed"
output_item.skip = True
else:
output_item.file = job.results["image"]
output_item.skip = False
# Check if there are finished runs
succesfull_runs = None
for item in output_map:
if item.skip == False:
succesfull_runs = True
break
if not succesfull_runs:
self.logger.error(
"None of the started awimager run finished correct")
self.logger.error(
"No work left to be done: exiting with error status")
return 1
# If partial succes
if self.error.isSet():
self.logger.error("Failed awimager node run detected. continue with"
"successful tasks.")
self._store_data_map(self.inputs['mapfile'], output_map,
"mapfile containing produces awimages")
self.outputs["mapfile"] = self.inputs['mapfile']
return 0
def go(self):
"""
imager_bbs functionality. Called by framework performing all the work
"""
super(selfcal_bbs, self).go()
self.logger.info("Starting imager_bbs run")
# ********************************************************************
# 1. Load the and validate the data
ms_map = MultiDataMap.load(self.inputs['args'][0])
parmdb_map = MultiDataMap.load(self.inputs['instrument_mapfile'])
sourcedb_map = DataMap.load(self.inputs['sourcedb_mapfile'])
concat_ms_map = DataMap.load(self.inputs['concat_ms_map_path'])
# *********************************************************************
# 2. Start the node scripts
jobs = []
node_command = " python %s" % (self.__file__.replace(
"master", "nodes"))
map_dir = os.path.join(self.config.get("layout", "job_directory"),
"mapfiles")
run_id = str(self.inputs.get("id"))
# Update the skip fields of the four maps. If 'skip' is True in any of
# these maps, then 'skip' must be set to True in all maps.
align_data_maps(ms_map, parmdb_map, sourcedb_map, concat_ms_map)
ms_map.iterator = parmdb_map.iterator = sourcedb_map.iterator = \
concat_ms_map.iterator = DataMap.SkipIterator
# *********************************************************************
for (ms, parmdb, sourcedb, concat_ms) in zip(ms_map, parmdb_map,
sourcedb_map,
concat_ms_map):
#host is same for each entry (validate_data_maps)
host, ms_list = ms.host, ms.file
# Write data maps to MultaDataMaps
ms_list_path = os.path.join(map_dir,
host + "_ms_" + run_id + ".map")
MultiDataMap([tuple([host, ms_list, False])]).save(ms_list_path)
parmdb_list_path = os.path.join(
map_dir, host + "_parmdb_" + run_id + ".map")
MultiDataMap([tuple([host, parmdb.file,
False])]).save(parmdb_list_path)
sourcedb_list_path = os.path.join(map_dir,
host + "_sky_" + run_id + ".map")
MultiDataMap([tuple([host, [sourcedb.file],
False])]).save(sourcedb_list_path)
# THe concat ms does not have to be written: It already is a
# singular item (it is the output of the reduce step)
# redmine issue #6021
arguments = [
self.inputs['bbs_executable'], self.inputs['parset'],
ms_list_path, parmdb_list_path, sourcedb_list_path,
concat_ms.file, self.inputs['major_cycle']
]
jobs.append(ComputeJob(host, node_command, arguments))
# start and wait till all are finished
self._schedule_jobs(jobs)
# **********************************************************************
# 3. validate the node output and construct the output mapfile.
if self.error.isSet(): #if one of the nodes failed
self.logger.warn("Failed bbs node run detected, skipping work"
"on this work item for further computations")
# find failed job and set the skip field
for (ms_item, concat_item, job) in zip(ms_map, concat_ms_map, jobs):
if job.results["returncode"] == 0:
continue
else:
ms_item.skip = True
concat_item.skip = True
self.logger.warn("bbs failed on item: {0}".format(
ms_item.file))
# return the output: The measurement set that are calibrated:
# calibrated data is placed in the ms sets
MultiDataMap(ms_map).save(self.inputs['mapfile'])
# also save the concat_ms map with possible skips
DataMap(concat_ms_map).save(self.inputs['concat_ms_map_path'])
self.logger.info("Wrote file with calibrated data")
self.outputs['mapfile'] = self.inputs['mapfile']
return 0
def go(self):
if 'executable' in self.inputs:
executable = self.inputs['executable']
if self.inputs['nthreads']:
self.environment["OMP_NUM_THREADS"] = str(self.inputs['nthreads'])
if 'environment' in self.inputs:
self.environment.update(self.inputs['environment'])
self.logger.info("Starting %s run" % executable)
super(executable_args, self).go()
# args format stuff
args_format = {'args_format': self.inputs['args_format'],
'args_format_argument': self.inputs['args_format_argument'],
'args_format_option': self.inputs['args_format_option'],
'args_formatlongoption': self.inputs['args_format_longoption'],
'args_format_option_argument': self.inputs['args_format_option_argument']}
mapfile_dir = os.path.join(self.config.get("layout", "job_directory"), "mapfiles")
work_dir = os.path.join(self.inputs['working_directory'], self.inputs['job_name'])
# *********************************************************************
# try loading input/output data file, validate output vs the input location if
# output locations are provided
try:
inputmapfiles = []
inlist = []
if self.inputs['mapfile_in']:
inlist.append(self.inputs['mapfile_in'])
if self.inputs['mapfiles_in']:
for item in self.inputs['mapfiles_in']:
inlist.append(item)
self.inputs['mapfile_in'] = self.inputs['mapfiles_in'][0]
for item in inlist:
inputmapfiles.append(DataMap.load(item))
except Exception:
self.logger.error('Could not load input Mapfile %s' % inlist)
return 1
outputmapfiles = []
if self.inputs['mapfile_out']:
try:
outdata = DataMap.load(self.inputs['mapfile_out'])
outputmapfiles.append(outdata)
except Exception:
self.logger.error('Could not load output Mapfile %s' % self.inputs['mapfile_out'])
return 1
# sync skip fields in the mapfiles
align_data_maps(inputmapfiles[0], outputmapfiles[0])
elif self.inputs['mapfiles_out']:
for item in self.inputs['mapfiles_out']:
outputmapfiles.append(DataMap.load(item))
self.inputs['mapfile_out'] = self.inputs['mapfiles_out'][0]
else:
# ouput will be directed in the working directory if no output mapfile is specified
outdata = copy.deepcopy(inputmapfiles[0])
if not self.inputs['inplace']:
for item in outdata:
item.file = os.path.join(
self.inputs['working_directory'],
self.inputs['job_name'],
#os.path.basename(item.file) + '.' + os.path.split(str(executable))[1]
os.path.splitext(os.path.basename(item.file))[0] + '.' + self.inputs['stepname']
)
self.inputs['mapfile_out'] = os.path.join(mapfile_dir, self.inputs['stepname'] + '.' + 'mapfile')
self.inputs['mapfiles_out'].append(self.inputs['mapfile_out'])
else:
self.inputs['mapfile_out'] = self.inputs['mapfile_in']
self.inputs['mapfiles_out'].append(self.inputs['mapfile_out'])
outputmapfiles.append(outdata)
if not validate_data_maps(inputmapfiles[0], outputmapfiles[0]):
self.logger.error(
"Validation of data mapfiles failed!"
)
return 1
if self.inputs['outputsuffixes']:
# Handle multiple outputfiles
for name in self.inputs['outputsuffixes']:
outputmapfiles.append(copy.deepcopy(inputmapfiles[0]))
self.inputs['mapfiles_out'].append(os.path.join(mapfile_dir, self.inputs['stepname'] + name + '.' + 'mapfile'))
for item in outputmapfiles[-1]:
item.file = os.path.join(
work_dir,
os.path.splitext(os.path.basename(item.file))[0] + '.' + self.inputs['stepname'] + name
)
self.inputs['mapfile_out'] = self.inputs['mapfiles_out'][0]
# prepare arguments
arglist = self.inputs['arguments']
parsetdict = {}
if 'parset' in self.inputs:
parset = Parset()
parset.adoptFile(self.inputs['parset'])
for k in parset.keys:
parsetdict[k] = str(parset[k])
# construct multiple input data
if self.inputs['inputkey'] and not self.inputs['inputkey'] in self.inputs['inputkeys']:
self.inputs['inputkeys'].insert(0, self.inputs['inputkey'])
if not self.inputs['outputkeys'] and self.inputs['outputkey']:
self.inputs['outputkeys'].append(self.inputs['outputkey'])
if not self.inputs['skip_infile'] and len(self.inputs['inputkeys']) is not len(inputmapfiles):
self.logger.error("Number of input mapfiles %d and input keys %d have to match." %
(len(inputmapfiles), len(self.inputs['inputkeys'])))
return 1
filedict = {}
if self.inputs['inputkeys'] and not self.inputs['skip_infile']:
for key, filemap, mapname in zip(self.inputs['inputkeys'], inputmapfiles, inlist):
if not mapname in self.inputs['mapfiles_as_string']:
filedict[key] = []
for inp in filemap:
filedict[key].append(inp.file)
else:
if key != mapname:
filedict[key] = []
for inp in filemap:
filedict[key].append(mapname)
if self.inputs['outputkey']:
filedict[self.inputs['outputkey']] = []
for item in outputmapfiles[0]:
filedict[self.inputs['outputkey']].append(item.file)
# ********************************************************************
# Call the node side of the recipe
# Create and schedule the compute jobs
#command = "python3 %s" % (self.__file__.replace('master', 'nodes')).replace('executable_args', self.inputs['nodescript'])
recipe_dir_str = str(self.config.get('DEFAULT', 'recipe_directories'))
recipe_directories = recipe_dir_str.rstrip(']').lstrip('[').split(',')
pylist = os.getenv('PYTHONPATH').split(':')
command = None
for pl in pylist:
if os.path.isfile(os.path.join(pl,'lofarpipe/recipes/nodes/'+self.inputs['nodescript']+'.py')):
command = "python3 %s" % os.path.join(pl,'lofarpipe/recipes/nodes/'+self.inputs['nodescript']+'.py')
for pl in recipe_directories:
if os.path.isfile(os.path.join(pl,'nodes/'+self.inputs['nodescript']+'.py')):
command = "python3 %s" % os.path.join(pl,'nodes/'+self.inputs['nodescript']+'.py')
inputmapfiles[0].iterator = outputmapfiles[0].iterator = DataMap.SkipIterator
jobs = []
for i, (outp, inp,) in enumerate(zip(
outputmapfiles[0], inputmapfiles[0])
):
arglist_copy = copy.deepcopy(arglist)
parsetdict_copy = copy.deepcopy(parsetdict)
if filedict:
for name, value in filedict.items():
replaced = False
if arglist_copy:
for arg in arglist:
if name == arg:
ind = arglist_copy.index(arg)
arglist_copy[ind] = arglist_copy[ind].replace(name, value[i])
replaced = True
if parsetdict_copy:
if name in list(parsetdict_copy.values()):
for k, v in parsetdict_copy.items():
if v == name:
parsetdict_copy[k] = value[i]
else:
if not replaced:
parsetdict_copy[name] = value[i]
jobs.append(
ComputeJob(
inp.host, command,
arguments=[
inp.file,
executable,
arglist_copy,
parsetdict_copy,
work_dir,
self.inputs['parsetasfile'],
args_format,
self.environment
],
resources={
"cores": self.inputs['nthreads']
}
)
)
max_per_node = self.inputs['max_per_node']
self._schedule_jobs(jobs, max_per_node)
jobresultdict = {}
resultmap = {}
for job, outp in zip(jobs, outputmapfiles[0]):
if job.results['returncode'] != 0:
outp.skip = True
if not self.inputs['error_tolerance']:
self.logger.error("A job has failed with returncode %d and error_tolerance is not set. Bailing out!" % job.results['returncode'])
return 1
for k, v in list(job.results.items()):
if not k in jobresultdict:
jobresultdict[k] = []
jobresultdict[k].append(DataProduct(job.host, job.results[k], outp.skip))
if k == 'break':
self.outputs.update({'break': v})
# temp solution. write all output dict entries to a mapfile
#mapfile_dir = os.path.join(self.config.get("layout", "job_directory"), "mapfiles")
#check directory for stand alone mode
if not os.path.isdir(mapfile_dir):
try:
os.mkdir(mapfile_dir, )
except OSError as exc: # Python >2.5
if exc.errno == errno.EEXIST and os.path.isdir(mapfile_dir):
pass
else:
raise
for k, v in list(jobresultdict.items()):
dmap = DataMap(v)
dmap.save(os.path.join(mapfile_dir, self.inputs['stepname'] + '.' + k + '.mapfile'))
resultmap[k + '.mapfile'] = os.path.join(mapfile_dir, self.inputs['stepname'] + '.' + k + '.mapfile')
self.outputs.update(resultmap)
# *********************************************************************
# Check job results, and create output data map file
if self.error.isSet():
# Abort if all jobs failed
if all(job.results['returncode'] != 0 for job in jobs):
self.logger.error("All jobs failed. Bailing out!")
return 1
else:
self.logger.warn(
"Some jobs failed, continuing with succeeded runs"
)
mapdict = {}
for item, name in zip(outputmapfiles, self.inputs['mapfiles_out']):
self.logger.debug("Writing data map file: %s" % name)
item.save(name)
mapdict[os.path.basename(name)] = name
self.outputs['mapfile'] = self.inputs['mapfile_out']
if self.inputs['outputsuffixes']:
self.outputs.update(mapdict)
return 0
def go(self):
"""
Steps:
1. Load and validate the input datamaps
2. Run the node parts of the recipe
3. Validate node output and format the recipe output
"""
super(imager_finalize, self).go()
# *********************************************************************
# 1. Load the datamaps
awimager_output_map = DataMap.load(
self.inputs["awimager_output_map"])
ms_per_image_map = DataMap.load(
self.inputs["ms_per_image_map"])
sourcelist_map = DataMap.load(self.inputs["sourcelist_map"])
sourcedb_map = DataMap.load(self.inputs["sourcedb_map"])
target_mapfile = DataMap.load(self.inputs["target_mapfile"])
output_image_mapfile = DataMap.load(
self.inputs["output_image_mapfile"])
processed_ms_dir = self.inputs["processed_ms_dir"]
fillrootimagegroup_exec = self.inputs["fillrootimagegroup_exec"]
# Align the skip fields
align_data_maps(awimager_output_map, ms_per_image_map,
sourcelist_map, target_mapfile, output_image_mapfile,
sourcedb_map)
# Set the correct iterator
sourcelist_map.iterator = awimager_output_map.iterator = \
ms_per_image_map.iterator = target_mapfile.iterator = \
output_image_mapfile.iterator = sourcedb_map.iterator = \
DataMap.SkipIterator
# *********************************************************************
# 2. Run the node side of the recupe
command = " python %s" % (self.__file__.replace("master", "nodes"))
jobs = []
for (awimager_output_item, ms_per_image_item, sourcelist_item,
target_item, output_image_item, sourcedb_item) in zip(
awimager_output_map, ms_per_image_map, sourcelist_map,
target_mapfile, output_image_mapfile, sourcedb_map):
# collect the files as argument
arguments = [awimager_output_item.file,
ms_per_image_item.file,
sourcelist_item.file,
target_item.file,
output_image_item.file,
self.inputs["minbaseline"],
self.inputs["maxbaseline"],
processed_ms_dir,
fillrootimagegroup_exec,
self.environment,
sourcedb_item.file]
self.logger.info(
"Starting finalize with the folowing args: {0}".format(
arguments))
jobs.append(ComputeJob(target_item.host, command, arguments))
self._schedule_jobs(jobs)
# *********************************************************************
# 3. Validate the performance of the node script and assign output
succesful_run = False
for (job, output_image_item) in zip(jobs, output_image_mapfile):
if not "hdf5" in job.results:
# If the output failed set the skip to True
output_image_item.skip = True
else:
succesful_run = True
# signal that we have at least a single run finished ok.
# No need to set skip in this case
if not succesful_run:
self.logger.warn("Failed finalizer node run detected")
return 1
output_image_mapfile.save(self.inputs['placed_image_mapfile'])
self.logger.debug(
"Wrote mapfile containing placed hdf5 images: {0}".format(
self.inputs['placed_image_mapfile']))
self.outputs["placed_image_mapfile"] = self.inputs[
'placed_image_mapfile']
return 0
def go(self):
if 'executable' in self.inputs:
executable = self.inputs['executable']
if 'environment' in self.inputs:
self.environment.update(self.inputs['environment'])
self.logger.info("Starting %s run" % executable)
super(executable_args, self).go()
# args format stuff
args_format = {'args_format': self.inputs['args_format'],
'args_format_argument': self.inputs['args_format_argument'],
'args_format_option': self.inputs['args_format_option'],
'args_formatlongoption': self.inputs['args_format_longoption'],
'args_format_option_argument': self.inputs['args_format_option_argument']}
# *********************************************************************
# try loading input/output data file, validate output vs the input location if
# output locations are provided
try:
inputmapfiles = []
inlist = []
if self.inputs['mapfile_in']:
inlist.append(self.inputs['mapfile_in'])
if self.inputs['mapfiles_in']:
for item in self.inputs['mapfiles_in']:
inlist.append(item)
self.inputs['mapfile_in'] = self.inputs['mapfiles_in'][0]
for item in inlist:
inputmapfiles.append(DataMap.load(item))
except Exception:
self.logger.error('Could not load input Mapfile %s' % inlist)
return 1
outputmapfiles = []
prefix = os.path.join(self.inputs['working_directory'], self.inputs['job_name'])
if self.inputs['mapfile_out']:
try:
outdata = DataMap.load(self.inputs['mapfile_out'])
outputmapfiles.append(outdata)
except Exception:
self.logger.error('Could not load output Mapfile %s' % self.inputs['mapfile_out'])
return 1
# sync skip fields in the mapfiles
align_data_maps(inputmapfiles[0], outputmapfiles[0])
elif self.inputs['mapfiles_out']:
for item in self.inputs['mapfiles_out']:
outputmapfiles.append(DataMap.load(item))
self.inputs['mapfile_out'] = self.inputs['mapfiles_out'][0]
else:
# ouput will be directed in the working directory if no output mapfile is specified
outdata = copy.deepcopy(inputmapfiles[0])
if not self.inputs['inplace']:
for item in outdata:
item.file = os.path.join(
self.inputs['working_directory'],
self.inputs['job_name'],
#os.path.basename(item.file) + '.' + os.path.split(str(executable))[1]
os.path.splitext(os.path.basename(item.file))[0] + '.' + self.inputs['stepname']
)
self.inputs['mapfile_out'] = os.path.join(prefix, self.inputs['stepname'] + '.' + 'mapfile')
self.inputs['mapfiles_out'].append(self.inputs['mapfile_out'])
else:
self.inputs['mapfile_out'] = self.inputs['mapfile_in']
self.inputs['mapfiles_out'].append(self.inputs['mapfile_out'])
outputmapfiles.append(outdata)
if not validate_data_maps(inputmapfiles[0], outputmapfiles[0]):
self.logger.error(
"Validation of data mapfiles failed!"
)
return 1
if self.inputs['outputsuffixes']:
# Handle multiple outputfiles
for name in self.inputs['outputsuffixes']:
outputmapfiles.append(copy.deepcopy(inputmapfiles[0]))
self.inputs['mapfiles_out'].append(os.path.join(prefix, self.inputs['stepname'] + name + '.' + 'mapfile'))
for item in outputmapfiles[-1]:
item.file = os.path.join(
prefix,
os.path.splitext(os.path.basename(item.file))[0] + '.' + self.inputs['stepname'] + name
)
self.inputs['mapfile_out'] = self.inputs['mapfiles_out'][0]
# prepare arguments
arglist = self.inputs['arguments']
parsetdict = {}
if 'parset' in self.inputs:
parset = Parset()
parset.adoptFile(self.inputs['parset'])
for k in parset.keys:
parsetdict[k] = str(parset[k])
# construct multiple input data
if not self.inputs['inputkeys'] and self.inputs['inputkey']:
self.inputs['inputkeys'].append(self.inputs['inputkey'])
if not self.inputs['outputkeys'] and self.inputs['outputkey']:
self.inputs['outputkeys'].append(self.inputs['outputkey'])
if not self.inputs['skip_infile'] and len(self.inputs['inputkeys']) is not len(inputmapfiles):
self.logger.error("Number of input mapfiles %d and input keys %d have to match." %
len(self.inputs['inputkeys']), len(inputmapfiles))
return 1
filedict = {}
if self.inputs['inputkeys'] and not self.inputs['skip_infile']:
for key, filemap in zip(self.inputs['inputkeys'], inputmapfiles):
filedict[key] = []
for inp in filemap:
filedict[key].append(inp.file)
if self.inputs['outputkey']:
filedict[self.inputs['outputkey']] = []
for item in outputmapfiles[0]:
filedict[self.inputs['outputkey']].append(item.file)
# ********************************************************************
# Call the node side of the recipe
# Create and schedule the compute jobs
command = "python %s" % (self.__file__.replace('master', 'nodes')).replace('executable_args', self.inputs['nodescript'])
inputmapfiles[0].iterator = outputmapfiles[0].iterator = DataMap.SkipIterator
jobs = []
for i, (outp, inp,) in enumerate(zip(
outputmapfiles[0], inputmapfiles[0])
):
arglist_copy = copy.deepcopy(arglist)
parsetdict_copy = copy.deepcopy(parsetdict)
#if keylist:
#for name, value in zip(keylist, inputlist):
if filedict:
for name, value in filedict.iteritems():
if arglist_copy and name in arglist_copy:
ind = arglist_copy.index(name)
arglist_copy[ind] = value[i]
elif name in parsetdict_copy.values():
for k, v in parsetdict_copy.iteritems():
if v == name:
parsetdict_copy[k] = value[i]
else:
parsetdict_copy[name] = value[i]
jobs.append(
ComputeJob(
inp.host, command,
arguments=[
inp.file,
executable,
arglist_copy,
parsetdict_copy,
prefix,
self.inputs['parsetasfile'],
args_format,
#self.inputs['working_directory'],
self.environment
]
)
)
max_per_node = self.inputs['max_per_node']
self._schedule_jobs(jobs, max_per_node)
jobresultdict = {}
resultmap = {}
for job, outp in zip(jobs, outputmapfiles[0]):
if job.results['returncode'] != 0:
outp.skip = True
for k, v in job.results.items():
if not k in jobresultdict:
jobresultdict[k] = []
jobresultdict[k].append(DataProduct(job.host, job.results[k], outp.skip))
if k == 'break':
self.outputs.update({'break': v})
# temp solution. write all output dict entries to a mapfile
mapfile_dir = os.path.join(self.config.get("layout", "job_directory"), "mapfiles")
for k, v in jobresultdict.items():
dmap = DataMap(v)
dmap.save(os.path.join(mapfile_dir, k + '.mapfile'))
resultmap[k + '.mapfile'] = os.path.join(mapfile_dir, k + '.mapfile')
self.outputs.update(resultmap)
# *********************************************************************
# Check job results, and create output data map file
if self.error.isSet():
# Abort if all jobs failed
if all(job.results['returncode'] != 0 for job in jobs):
self.logger.error("All jobs failed. Bailing out!")
return 1
else:
self.logger.warn(
"Some jobs failed, continuing with succeeded runs"
)
mapdict = {}
for item, name in zip(outputmapfiles, self.inputs['mapfiles_out']):
self.logger.debug("Writing data map file: %s" % name)
item.save(name)
mapdict[os.path.basename(name)] = name
self.outputs['mapfile'] = self.inputs['mapfile_out']
if self.inputs['outputsuffixes']:
self.outputs.update(mapdict)
return 0