diff --git a/.gitattributes b/.gitattributes
index ab9b8a75aa5c991e14e42196c03c30b3d381346d..b0dfd153a02cc8bddbc473169ebc74115d52224c 100644
--- a/.gitattributes
+++ b/.gitattributes
@@ -1230,6 +1230,9 @@ CEP/Pipeline/framework/lofarpipe/CMakeLists.txt eol=lf
CEP/Pipeline/framework/lofarpipe/GRIDInterface/docs/Design[!!-~]Lofar[!!-~]Batch[!!-~]scheduler.docx -text
CEP/Pipeline/framework/lofarpipe/GRIDInterface/docs/LOFAR[!!-~]batch[!!-~]scheduler[!!-~]interface.docx -text
CEP/Pipeline/framework/lofarpipe/GRIDInterface/docs/Presentation[!!-~]LOFAR[!!-~]DPU[!!-~]XML[!!-~]interface.pptx -text
+CEP/Pipeline/framework/lofarpipe/GRIDInterface/src/dpu_xml_interface.py -text
+CEP/Pipeline/framework/lofarpipe/GRIDInterface/src/pipeline_job.py -text
+CEP/Pipeline/framework/lofarpipe/GRIDInterface/src/tar_cal.xml -text
CEP/Pipeline/framework/lofarpipe/__init__.py eol=lf
CEP/Pipeline/framework/lofarpipe/cuisine/COPYING eol=lf
CEP/Pipeline/framework/lofarpipe/cuisine/README eol=lf
diff --git a/CEP/Pipeline/framework/lofarpipe/GRIDInterface/src/dpu_xml_interface.py b/CEP/Pipeline/framework/lofarpipe/GRIDInterface/src/dpu_xml_interface.py
new file mode 100644
index 0000000000000000000000000000000000000000..7e01bf664f6189aa5afb60ade401afb80f59b49c
--- /dev/null
+++ b/CEP/Pipeline/framework/lofarpipe/GRIDInterface/src/dpu_xml_interface.py
@@ -0,0 +1,436 @@
+"""
+Interface to the DPU that converts a XML input file into a batch of DPU jobs.
+"""
+
+import os
+import sys
+import time
+
+from xml.dom import minidom
+from xml.parsers.expat import ExpatError
+
+from common.net.dpu_client_test import dpu_IO
+from common.config.Environment import Env
+from awlofar.toolbox.msss.pipeline_job import cep_pipeline_job
+from lofar.parameterset import parameterset
+from lofarpipe.support.data_map import *
+
+class pipeline:
+ """
+ The pipeline class stores and interprets the information about the pipeline
+ that was read from the XML file.
+ """
+
+ def __init__(self, id, predecessors='', inputs='', outputs='', parset=''):
+ self.id = id
+ self.predecessors_as_str = predecessors
+ self.inputs = inputs
+ self.output = outputs
+ self.parset_as_str = str(parset)
+ self.parset = parameterset()
+
+ def read_parset(self):
+ """
+ Convert the string containing a parset into parameterset object.
+ """
+ self.parset.adoptArgv(str(self.parset_as_str).split('\n'))
+
+ def get_predecessors(self):
+ """
+ Convert the string containing the pipeline's predecessors into
+ a Python list by splitting on the comma symbol.
+ An empty list is returned if the pipeline does not have any predecessors.
+ """
+ if self.predecessors_as_str:
+ return self.predecessors_as_str.split(',')
+ else:
+ # In this case, the predecessors_as_str attribute was an empty string.
+ return []
+
+ def get_command(self):
+ """
+ Read the pipeline's top-level Python script, used to start the pipeline, from its parset.
+ """
+ return self.parset.getString('ObsSW.Observation.ObservationControl.PythonControl.pythonProgram', '')
+
+ def get_tasks(self):
+ """
+ Convert the pipeline into DPU tasks. We assume that the pipeline can be parallelized by
+ creating independent tasks for all its input files. Furthermore, we do take into account
+ that there might be dependencies between different pipelines. In that case, task number i
+ for input file i of the next pipeline will start when task number i for input file i of the
+ previous pipeline has finished.
+
+ As an example, the following shows how a calibration pipeline followed by a target pipeline
+ (which should wait for the calibration pipeline to finish) are parallelized:
+
+ Tasks
+ 0 1 ... N
+ Pipeline 0: SB000 SB001 SB00N (all executed independently)
+ (calibration)
+
+ Pipeline 1: SB000 SB001 SB00N (horizontally independent, but vertically depending on the previous task)
+ (target)
+
+ The dependencies between the pipelines will be handled at a later stage.
+ """
+
+ # First, interpret the parset and get all the information about the
+ # input and output files as was defined in the XML.
+ self.read_parset()
+ inputs_filenames_keys = map(lambda input: str( input['filenames']), self.inputs.values())
+ inputs_locations_keys = map(lambda input: str( input['locations']), self.inputs.values())
+ inputs_skip_keys = map(lambda input: str( input['skip']), self.inputs.values())
+ outputs_filenames_keys = map(lambda output: str(output['filenames']), self.outputs.values())
+ outputs_locations_keys = map(lambda output: str(output['locations']), self.outputs.values())
+ outputs_skip_keys = map(lambda output: str(output['skip']), self.outputs.values())
+
+ input_map_list = []
+ output_map_list = []
+ # Combine the information about each input and output into tuples.
+ # Note that the order of these keys are used when creating the individual jobs:
+ # filenames, locations, skip values
+ input_map_keys = zip(inputs_filenames_keys, inputs_locations_keys, inputs_skip_keys )
+ output_map_keys = zip(outputs_filenames_keys, outputs_locations_keys, outputs_skip_keys )
+
+ # Create a DataMap for each input and each output.
+ for filename, location, skip in input_map_keys:
+ input_map_list.append(
+ DataMap([
+ tuple(os.path.join(location, filename).split(':')) + (skip,)
+ for filename, location, skip in zip(
+ self.parset.getStringVector(filename),
+ self.parset.getStringVector(location),
+ self.parset.getBoolVector(skip))
+ ])
+ )
+
+ for filename, location, skip in output_map_keys:
+ output_map_list.append(
+ DataMap([
+ tuple(os.path.join(location, filename).split(':')) + (skip,)
+ for filename, location, skip in zip(
+ self.parset.getStringVector(filename),
+ self.parset.getStringVector(location),
+ self.parset.getBoolVector(skip))
+ ])
+ )
+
+ # Align the data maps in order to validate them and set the skip values
+ # in the same way for each input and output.
+ align_data_maps(*(input_map_list+output_map_list))
+
+ # Finally, convert everything into individual tasks.
+ pipeline_jobs = []
+ job_data_product_keys = input_map_keys + output_map_keys
+ for idx, job_data_products in enumerate(zip(*(input_map_list+ output_map_list))):
+ job = cep_pipeline_job()
+ # Clone the parset by creating another instance.
+ job_parset = parameterset()
+ job_parset.adoptArgv(str(self.parset_as_str).split('\n'))
+ job_should_be_skipped = False
+
+ # Now replace all input and output information by the (single) data
+ # element that should be processed by this task.
+ for [job_data_product, job_data_product_key] in zip(job_data_products, job_data_product_keys):
+ job_should_be_skipped = job_data_product.skip
+ job.host = job_data_product.host
+ # We assume that the job will be launched on the node where the
+ # data is stored.
+ host = 'localhost'
+ filename = os.path.basename(job_data_product.file)
+ file_location = os.path.dirname(job_data_product.file)
+ skip = job_data_product.skip
+ # Remember that the key order is determined in a previous zip.
+ job_parset.replace(job_data_product_key[0], str([filename]))
+ job_parset.replace(job_data_product_key[1], str([host + ":" + file_location]))
+ job_parset.replace(job_data_product_key[2], str([skip]))
+
+ if job_should_be_skipped :
+ # If skip was True for either one of the input/output elements,
+ # we should skip this job but increase the job index.
+ continue
+
+ job.parset_as_dict = job_parset.dict()
+ job.command = self.get_command()
+ job.name = self.id + "_" + str(idx)
+ pipeline_jobs.append(job)
+
+ return pipeline_jobs
+
+
+class pipeline_xml_parser:
+ """
+ This class can be used to parse a XML input file that should be converted
+ into DPU jobs.
+ """
+
+ def parse(self, xmlfile):
+ """
+ Try to parse the XML file into a XML Document object. This will also
+ check if the input file is a valid XML file.
+ """
+
+ try:
+ self.xml = minidom.parse(xmlfile).documentElement
+ return True
+ except ExpatError as e:
+ self.parse_error = e
+ return False
+
+ def get_child_text(self, tagname, node=None):
+ """
+ Try to find a child with a given tag name and return its (text)
+ value. If no parent node was specified, the root node of the XML
+ document will be used, i.e. the entire document will be searched.
+ If no child with the given tag name can be found, an empty string
+ is returned.
+ """
+ if node == None:
+ node = self.xml
+ children = node.getElementsByTagName(tagname)
+ if len(children) > 0 and len(children[0].childNodes) > 0:
+ return children[0].firstChild.data
+ else:
+ return ''
+
+ def get_child_cdata(self, tagname, node):
+ """
+ For a given node, try to find a descendant with a given tag name and that
+ contains a CDATA section. This CDATA, if found, will be returned as a
+ string. Otherwise, an empty string is returned.
+ """
+ elements = node.getElementsByTagName(tagname)
+ result = ''
+ for el in elements:
+ for child in el.childNodes:
+ if child.nodeType == self.xml.CDATA_SECTION_NODE:
+ result = child.data
+ return result
+
+ def node_to_dict(self, node):
+ """
+ Convert the XML subtree starting at the specified node into a Python
+ dictionary. All branches (element nodes) are used as dictionary keys,
+ while the leaves are used as values. Note that the function is
+ recursive and, hence, the resulting dictionary itself can contain
+ other dictionaries again.
+ """
+ d = {}
+ for child in node.childNodes:
+ if child.nodeType == self.xml.ELEMENT_NODE:
+ d[child.nodeName] = self.node_to_dict(child)
+ if child.nodeType == self.xml.TEXT_NODE and not child.nodeValue.strip() == '':
+ return child.nodeValue
+ return d
+
+
+ def get_inputs(self, pipeline):
+ """
+ Return the inputs of a pipeline node as a dictionary.
+ """
+ inputs_node = pipeline.getElementsByTagName("inputs")
+ if len(inputs_node) > 0:
+ return self.node_to_dict(inputs_node[0])
+ else:
+ return {}
+
+ def get_outputs(self, pipeline):
+ """
+ Return the outputs of a pipeline node as a dictionary.
+ """
+ outputs_node = pipeline.getElementsByTagName("outputs")
+ if len(outputs_node) > 0:
+ return self.node_to_dict(outputs_node[0])
+ else:
+ return {}
+
+ def get_pipeline_block_id(self):
+ """
+ Return the block id of the pipeline node.
+ """
+ idtags = self.xml.getElementsByTagName('pipeline_block_id');
+ if len(idtags) > 0:
+ return idtags[0].firstChild.data
+
+ def get_pipelines(self):
+ """
+ Find all pipelines described in the XML file, convert them into
+ pipeline objects that store all the corresponding information
+ and return them as a list.
+ The function assumes that all pipelines at least have a pipeline_id,
+ so it uses this to find pipelines in the XML file.
+ """
+ pipelines = []
+ pipeline_ids = self.xml.getElementsByTagName('pipeline_id')
+ for id_elem in pipeline_ids:
+ id = id_elem.firstChild.data
+ pipeline_node = id_elem.parentNode
+ pipeline_obj = pipeline(id)
+ pipeline_obj.predecessors_as_str = self.get_child_text('predecessors', pipeline_node)
+ pipeline_obj.inputs = self.get_inputs(pipeline_node)
+ pipeline_obj.outputs = self.get_outputs(pipeline_node)
+ pipeline_obj.parset_as_str = self.get_child_cdata('config', pipeline_node)
+ pipelines.append(pipeline_obj)
+ return pipelines
+
+
+class dpu_xml_interface:
+ """
+ The dpu_xml_interface class starts the DPU XML interface application and
+ performs the following steps:
+
+ - parse the arguments, make sure that a XML file is passed as argument;
+ - parse the XML file and get all the pipeline objects stored in it;
+ - determine a suitable order for the pipelines, based on their predecessors;
+ - cut the pipeline into individual, independent tasks;
+ - submit the these individual tasks in the correct way and order to the DPU;
+ - keep polling the job statuses until all jobs have finished.
+
+ """
+
+ # DPU client object
+ dpu = dpu_IO(dpu_name=Env['dpu_name'], dbinfo=('dummy', 'awdummy', 'dummy', 'dummy'))
+
+ def usage(self):
+ """
+ Display usage.
+ """
+ exit("Usage: %s [options] <xml file>" % sys.argv[0])
+
+ def exit(self, error, code=1):
+ """
+ Print an error and exit.
+ """
+ print >> sys.stderr, "Error!\n", error
+ sys.exit(code)
+
+ def parse_arguments(self):
+ """
+ Parse the input arguments and return the name of the given XML file.
+ """
+ if len(sys.argv) < 2:
+ return self.usage()
+
+ xml_filename = sys.argv[1]
+ if not os.path.exists(xml_filename):
+ self.exit("The specified XML file cannot be found: %s." % xml_filename)
+
+ return xml_filename
+
+ def order_pipelines(self, pipelines_unsorted):
+ """
+ Order the pipelines based on the dependecies that are specified with
+ the predecessors information. Each pipeline can have one or more
+ predecessors that have to complete before the pipeline itself can run.
+
+ We determine the order by iteratively going over all pipelines and
+ moving pipelines into a new (ordered) list if they either do not have
+ any predecessor or if all their predecessors are already in the new
+ list. We keep doing this until the original list is empty, meaning
+ that all dependencies were handled correctly.
+ If during a single iteration nothing changes, it means we have a
+ circular dependency that cannot be met.
+ """
+ pipelines = []
+ pipelines_ids = []
+ #TODO: how to run/store multiple independent pipelines?
+ while len(pipelines_unsorted) > 0:
+ changed = False
+ for pipeline in pipelines_unsorted:
+ if all(predecessor in pipelines_ids for predecessor in pipeline.get_predecessors()):
+ # The above will also evaluate to True for pipelines with no predecessors.
+ pipelines.append(pipeline)
+ pipelines_ids.append(pipeline.id)
+ pipelines_unsorted.remove(pipeline)
+ changed = True
+ if not changed:
+ # No changes are made during this iteration, which means that
+ # there is a circular dependency.
+ self.exit("A circular dependency between some pipelines was found.")
+
+ return pipelines
+
+ def submit_jobs(self, jobs):
+ """
+ Submit a list of jobs to the DPU and return the DPU keys.
+ The jobs parameter should be a list of lists, where the order of the
+ lists determine their dependencies. Seen as a matrix, each column
+ will be a job that runs the tasks (rows) sequentially. All columns
+ are considered to be independent and, therefore, will be submitted
+ as independent DPU jobs.
+ """
+ dpu_jobs = {}
+ dpu_job_keys = {'SUBMITTED': [], 'FAILED': [], 'DONE': []}
+
+ # Get all "columns" of the jobs matrix.
+ for seq_jobs in zip(*jobs):
+ # TODO: use one thread per job submission to submit all at once (submitting jobs can take a couple of seconds)
+
+ # Map the column to individual tasks and set the right node
+ # (i.e. where the data is stored) and the right mode for each task.
+ job = map(lambda job: {'DPU_JOBS':[job], 'DPU_NODES':[job.host], 'DPU_MODE':'SEQ'}, seq_jobs)
+
+ # Request a DPU key and submit the job.
+ key = self.dpu.getkey()
+ if self.dpu.submitjobs(key, jobs=job, code=None):
+ dpu_job_keys['SUBMITTED'].append(key)
+ else:
+ print "Error while submitting job:", job.name
+ dpu_job_keys['FAILED'].append(key)
+
+ return dpu_job_keys
+
+ def wait_for_jobs(self, dpu_job_keys):
+ """
+ This will start a loop that will run until all jobs have finished.
+ Once a job finishes, we put the corresponding key in an appropriate list
+ depending on the status of the job.
+ """
+
+ print "Waiting for all jobs to complete..."
+ while not len(dpu_job_keys['SUBMITTED']) == 0:
+ time.sleep(10)
+ for key in dpu_job_keys['SUBMITTED']:
+ status = self.dpu.getstatus(key)
+ if status.startswith('FINISHED'):
+ dpu_job_keys['SUBMITTED'].remove(key)
+ if status.endswith('0/0/0/0'):
+ dpu_job_keys['DONE'].append(key)
+ else:
+ dpu_job_keys['FAILED'].append(key)
+
+ # TODO: retrieve jobs when done? What to do with logs?
+ print dpu_job_keys
+
+
+ def main(self):
+ """
+ Main function that runs all the individual steps.
+ """
+
+ # Parse the input arguments.
+ xmlfile = self.parse_arguments()
+
+ # Create a XML parser object and parse the given XML file.
+ self.xml_parser = pipeline_xml_parser()
+ if not(self.xml_parser.parse(xmlfile)):
+ self.exit("Error while parsing the XML file:\n%s" % self.xml_parser.parse_error)
+
+ # Get all pipelines from the XML file and determine a correct order.
+ pipelines = self.xml_parser.get_pipelines()
+ pipelines = self.order_pipelines(pipelines)
+
+ # Convert all pipelines into individual tasks.
+ jobs = []
+ for p in pipelines:
+ jobs.append(p.get_tasks())
+
+ # Submit the jobs and wait for them to complete.
+ dpu_job_keys = self.submit_jobs(jobs)
+ self.wait_for_jobs(dpu_job_keys)
+
+ return 0
+
+if __name__ == '__main__':
+ sys.exit(dpu_xml_interface().main())
diff --git a/CEP/Pipeline/framework/lofarpipe/GRIDInterface/src/pipeline_job.py b/CEP/Pipeline/framework/lofarpipe/GRIDInterface/src/pipeline_job.py
new file mode 100644
index 0000000000000000000000000000000000000000..7c19e4a4020d83e0d5f22a523ae772a2f6978350
--- /dev/null
+++ b/CEP/Pipeline/framework/lofarpipe/GRIDInterface/src/pipeline_job.py
@@ -0,0 +1,40 @@
+"""
+DPU pipeline jobs that can be used by the DPU XML interface.
+"""
+
+import subprocess
+import time
+
+"""
+Base class containing the main functionality for a pipeline job.
+"""
+class pipeline_job:
+
+ def __init__(self, command='', parset={}, name=''):
+ self.command = command
+ self.parset_as_dict = parset
+ self.name = name
+
+ def execute(self):
+ pass
+
+
+"""
+Pipeline job that can be used to run on the CEP cluster. It assumes that the
+data is already stored on the node where the job is running and that an
+appropriate startPython.sh script is available to start pipeline runs.
+"""
+class cep_pipeline_job(pipeline_job):
+
+ def execute(self):
+ f = open(self.name, "w")
+ for key,value in self.parset_as_dict.items():
+ f.write(key + "=" + str(value) + "\n")
+ f.close()
+
+ #time.sleep(15)
+
+ p = subprocess.Popen("startPython.sh " + self.command + " " + self.name + " 0 0 0", stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True)
+ self.stdout, self.stderr = p.communicate()
+ # Clean up statefile etc
+
diff --git a/CEP/Pipeline/framework/lofarpipe/GRIDInterface/src/tar_cal.xml b/CEP/Pipeline/framework/lofarpipe/GRIDInterface/src/tar_cal.xml
new file mode 100644
index 0000000000000000000000000000000000000000..a447100218b7bc745dbaadc5b922091e663d0d49
--- /dev/null
+++ b/CEP/Pipeline/framework/lofarpipe/GRIDInterface/src/tar_cal.xml
@@ -0,0 +1,2675 @@
+<?xml version="1.0" encoding="ISO-8859-1"?>
+<pipeline_block>
+ <pipeline_block_id>f9304969b5104da6999a5b1db6c715dd</pipeline_block_id>
+ <dpu_block_config></dpu_block_config>
+ <comment>A valid batch pipeline block: calibration pipeline + target pipeline </comment>
+ <msss_calibration_pipeline>
+ <pipeline_id>observation64405</pipeline_id>
+ <comments></comments>
+ <predecessors></predecessors>
+ <inputs>
+ <Input_correlated>
+ <locations>ObsSW.Observation.DataProducts.Input_Correlated.locations</locations>
+ <filenames>ObsSW.Observation.DataProducts.Input_Correlated.filenames</filenames>
+ <skip>ObsSW.Observation.DataProducts.Input_Correlated.skip</skip>
+ </Input_correlated>
+ </inputs>
+ <outputs>
+ <Output_Correlated>
+ <filenames>ObsSW.Observation.DataProducts.Output_Correlated.filenames</filenames>
+ <locations>ObsSW.Observation.DataProducts.Output_Correlated.locations</locations>
+ <skip>ObsSW.Observation.DataProducts.Output_Correlated.skip</skip>
+ </Output_Correlated>
+ <Output_InstrumentModel>
+ <filenames>ObsSW.Observation.DataProducts.Output_InstrumentModel.filenames</filenames>
+ <locations>ObsSW.Observation.DataProducts.Output_InstrumentModel.locations</locations>
+ <skip>ObsSW.Observation.DataProducts.Output_InstrumentModel.skip</skip>
+ </Output_InstrumentModel>
+ </outputs>
+ <dpu_pipeline_config></dpu_pipeline_config>
+ <config>
+ <![CDATA["
+ObsSW.Observation.DataProducts.Input_Correlated.filenames=[L64371_SAP000_SB000_uv.MS,L64371_SAP000_SB001_uv.MS]
+ObsSW.Observation.DataProducts.Input_Correlated.locations=[lce040:/data/scratch/klijn/calibrator_pipeline,lce041:/data/scratch/klijn/calibrator_pipeline]
+ObsSW.Observation.DataProducts.Input_Correlated.skip=[0,0]
+ObsSW.Observation.DataProducts.Output_InstrumentModel.filenames=[L64405_SAP000_SB000_inst.INST,L64405_SAP000_SB001_inst.INST]
+
+# BOB you should adapt this output location if running
+ObsSW.Observation.DataProducts.Output_InstrumentModel.locations=[lce040:/data/scratch/droge/calibrator_test/,lce041:/data/scratch/droge/calibrator_test/]
+#
+ObsSW.Observation.DataProducts.Output_Correlated.filenames=[L64371_SAP000_SB000_dppp.MS,L64371_SAP000_SB001_dppp.MS]
+ObsSW.Observation.DataProducts.Output_Correlated.locations=[lce040:/data/scratch/droge/calibrator_test/,lce041:/data/scratch/droge/calibrator_test/]
+ObsSW.Observation.DataProducts.Output_Correlated.skip=[0,0]
+
+ObsSW.Observation.DataProducts.Output_InstrumentModel.skip=[0,0]
+Clock160.channelWidth=610.3515625
+Clock160.samplesPerSecond=155648
+Clock160.subbandWidth=156.250
+Clock160.systemClock=160
+Clock200.channelWidth=762.939453125
+Clock200.samplesPerSecond=196608
+Clock200.subbandWidth=195.3125
+Clock200.systemClock=200
+ObsSW.Observation.Campaign.CO_I=Wise, Dr. Michael
+ObsSW.Observation.Campaign.PI=Verhoef, Ir. Bastiaan
+ObsSW.Observation.Campaign.contact=Verhoef, Ir. Bastiaan
+ObsSW.Observation.Campaign.name=test-lofar
+ObsSW.Observation.Campaign.title=test-lofar
+ObsSW.Observation.DataProducts.Input_Beamformed.dirmask=
+ObsSW.Observation.DataProducts.Input_Beamformed.enabled=false
+ObsSW.Observation.DataProducts.Input_Beamformed.filenames=[]
+ObsSW.Observation.DataProducts.Input_Beamformed.identifications=[]
+ObsSW.Observation.DataProducts.Input_Beamformed.locations=[]
+ObsSW.Observation.DataProducts.Input_Beamformed.mountpoints=[]
+ObsSW.Observation.DataProducts.Input_Beamformed.namemask=
+ObsSW.Observation.DataProducts.Input_Beamformed.skip=[]
+ObsSW.Observation.DataProducts.Input_CoherentStokes.dirmask=
+ObsSW.Observation.DataProducts.Input_CoherentStokes.enabled=false
+ObsSW.Observation.DataProducts.Input_CoherentStokes.filenames=[]
+ObsSW.Observation.DataProducts.Input_CoherentStokes.identifications=[]
+ObsSW.Observation.DataProducts.Input_CoherentStokes.locations=[]
+ObsSW.Observation.DataProducts.Input_CoherentStokes.mountpoints=[]
+ObsSW.Observation.DataProducts.Input_CoherentStokes.namemask=
+ObsSW.Observation.DataProducts.Input_CoherentStokes.skip=[]
+ObsSW.Observation.DataProducts.Input_Correlated.dirmask=L${OBSID}
+ObsSW.Observation.DataProducts.Input_Correlated.enabled=true
+ObsSW.Observation.DataProducts.Input_IncoherentStokes.dirmask=
+ObsSW.Observation.DataProducts.Input_IncoherentStokes.enabled=false
+ObsSW.Observation.DataProducts.Input_IncoherentStokes.filenames=[]
+ObsSW.Observation.DataProducts.Input_IncoherentStokes.identifications=[]
+ObsSW.Observation.DataProducts.Input_IncoherentStokes.locations=[]
+ObsSW.Observation.DataProducts.Input_IncoherentStokes.mountpoints=[]
+ObsSW.Observation.DataProducts.Input_IncoherentStokes.namemask=
+ObsSW.Observation.DataProducts.Input_IncoherentStokes.skip=[]
+ObsSW.Observation.DataProducts.Input_InstrumentModel.dirmask=
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+ObsSW.Observation.Scheduler.priority=0.0
+ObsSW.Observation.Scheduler.reason=
+ObsSW.Observation.Scheduler.referenceFrame=0
+ObsSW.Observation.Scheduler.reservation=0
+ObsSW.Observation.Scheduler.storageSelectionMode=1
+ObsSW.Observation.Scheduler.taskDuration=3600
+ObsSW.Observation.Scheduler.taskID=127
+ObsSW.Observation.Scheduler.taskName=Calibration M51
+ObsSW.Observation.Scheduler.taskType=0
+ObsSW.Observation.Scheduler.windowMaximumTime=
+ObsSW.Observation.Scheduler.windowMinimumTime=
+ObsSW.Observation.VirtualInstrument.imageNodeList=[]
+ObsSW.Observation.VirtualInstrument.minimalNrStations=1
+ObsSW.Observation.VirtualInstrument.partitionList=["R00"]
+ObsSW.Observation.VirtualInstrument.stationList=[]
+ObsSW.Observation.VirtualInstrument.stationSet=
+ObsSW.Observation.VirtualInstrument.storageCapacity=760
+ObsSW.Observation.VirtualInstrument.storageNodeList=[]
+ObsSW.Observation.antennaArray=LBA
+ObsSW.Observation.antennaSet=LBA_INNER
+ObsSW.Observation.bandFilter=LBA_30_90
+ObsSW.Observation.channelWidth=762.939453125
+ObsSW.Observation.channelsPerSubband=64
+ObsSW.Observation.claimPeriod=10
+ObsSW.Observation.clockMode=<<Clock200
+ObsSW.Observation.existingAntennaFields=["LBA","HBA","HBA0","HBA1"]
+ObsSW.Observation.existingStations=["CS001","CS002","CS003","CS004","CS005","CS006","CS007","CS011","CS013","CS017","CS021","CS024","CS026","CS028","CS030","CS031","CS101","CS103","CS201","CS301","CS302","CS401","CS501","RS106","RS205","RS208","RS306","RS307","RS406","RS503","DE601","DE602","DE603","DE604","DE605","FR606","UK608"]
+ObsSW.Observation.longBaselines=false
+ObsSW.Observation.nrAnaBeams=0
+ObsSW.Observation.nrBeamformers=0
+ObsSW.Observation.nrBeams=0
+ObsSW.Observation.nrPolarisations=2
+ObsSW.Observation.nrSlotsInFrame=61
+ObsSW.Observation.nrTBBSettings=0
+ObsSW.Observation.preparePeriod=10
+ObsSW.Observation.processSubtype=Calibration Pipeline
+ObsSW.Observation.processType=Pipeline
+ObsSW.Observation.receiverList=[]
+ObsSW.Observation.referencePhaseCenter=[3826577.110, 461022.900, 5064892.758]
+ObsSW.Observation.sampleClock=200
+ObsSW.Observation.samplesPerSecond=196608
+ObsSW.Observation.startTime=2012-08-31 13:35:00
+ObsSW.Observation.stopTime=2012-08-31 14:35:00
+ObsSW.Observation.strategy=MSSS calibrator pipeline
+ObsSW.Observation.subbandWidth=195.3125
+ObsSW.Observation.topologyID=mom_msss_131277.1.P1
+_DPname=LOFAR_ObsSW_TempObs0050
+prefix=LOFAR.
+ "]]>
+ </config>
+ </msss_calibration_pipeline>
+ <msss_target_pipeline>
+ <pipeline_id>observation64406</pipeline_id>
+ <comments></comments>
+ <predecessors>observation64405</predecessors>
+ <inputs>
+ <Input_InstrumentModel>
+ <locations>ObsSW.Observation.DataProducts.Input_InstrumentModel.locations</locations>
+ <filenames>ObsSW.Observation.DataProducts.Input_InstrumentModel.filenames</filenames>
+ <skip>ObsSW.Observation.DataProducts.Input_InstrumentModel.skip</skip>
+ </Input_InstrumentModel>
+ <Input_correlated>
+ <locations>ObsSW.Observation.DataProducts.Input_Correlated.locations</locations>
+ <filenames>ObsSW.Observation.DataProducts.Input_Correlated.filenames</filenames>
+ <skip>ObsSW.Observation.DataProducts.Input_Correlated.skip</skip>
+ </Input_correlated>
+ </inputs>
+ <outputs>
+ <Output_Correlated>
+ <filenames>ObsSW.Observation.DataProducts.Output_Correlated.filenames</filenames>
+ <locations>ObsSW.Observation.DataProducts.Output_Correlated.locations</locations>
+ <skip>ObsSW.Observation.DataProducts.Output_Correlated.skip</skip>
+ </Output_Correlated>
+ </outputs>
+ <dpu_pipeline_config></dpu_pipeline_config>
+ <config>
+ <![CDATA["
+ObsSW.Observation.DataProducts.Input_Correlated.filenames=[L64372_SAP000_SB000_uv.MS,L64372_SAP000_SB001_uv.MS]
+ObsSW.Observation.DataProducts.Input_Correlated.locations=[lce040:/data/scratch/klijn/target_pipeline,lce041:/data/scratch/klijn/target_pipeline]
+ObsSW.Observation.DataProducts.Input_Correlated.skip=[0,0]
+ObsSW.Observation.DataProducts.Input_InstrumentModel.filenames=[L64405_SAP000_SB000_inst.INST,L64405_SAP000_SB001_inst.INST]
+ObsSW.Observation.DataProducts.Input_InstrumentModel.locations=[lce040:/data/scratch/klijn/target_pipeline,lce041:/data/scratch/klijn/target_pipeline]
+ObsSW.Observation.DataProducts.Input_InstrumentModel.skip=[0,0]
+# Again the output locations should be changed to a location you can write to
+ObsSW.Observation.DataProducts.Output_Correlated.filenames=[L64406_SB000_uv.dppp.MS,L64406_SB001_uv.dppp.MS]
+ObsSW.Observation.DataProducts.Output_Correlated.locations=[lce040:/data/scratch/droge/target_pipeline,lce041:/data/scratch/droge/target_pipeline]
+ObsSW.Observation.DataProducts.Output_Correlated.skip=[0,0]
+#
+Clock160.channelWidth=610.3515625
+Clock160.samplesPerSecond=155648
+Clock160.subbandWidth=156.250
+Clock160.systemClock=160
+Clock200.channelWidth=762.939453125
+Clock200.samplesPerSecond=196608
+Clock200.subbandWidth=195.3125
+Clock200.systemClock=200
+ObsSW.Observation.Campaign.CO_I=Wise, Dr. Michael
+ObsSW.Observation.Campaign.PI=Verhoef, Ir. Bastiaan
+ObsSW.Observation.Campaign.contact=Verhoef, Ir. Bastiaan
+ObsSW.Observation.Campaign.name=test-lofar
+ObsSW.Observation.Campaign.title=test-lofar
+ObsSW.Observation.DataProducts.Input_Beamformed.dirmask=
+ObsSW.Observation.DataProducts.Input_Beamformed.enabled=false
+ObsSW.Observation.DataProducts.Input_Beamformed.filenames=[]
+ObsSW.Observation.DataProducts.Input_Beamformed.identifications=[]
+ObsSW.Observation.DataProducts.Input_Beamformed.locations=[]
+ObsSW.Observation.DataProducts.Input_Beamformed.mountpoints=[]
+ObsSW.Observation.DataProducts.Input_Beamformed.namemask=
+ObsSW.Observation.DataProducts.Input_Beamformed.skip=[]
+ObsSW.Observation.DataProducts.Input_CoherentStokes.dirmask=
+ObsSW.Observation.DataProducts.Input_CoherentStokes.enabled=false
+ObsSW.Observation.DataProducts.Input_CoherentStokes.filenames=[]
+ObsSW.Observation.DataProducts.Input_CoherentStokes.identifications=[]
+ObsSW.Observation.DataProducts.Input_CoherentStokes.locations=[]
+ObsSW.Observation.DataProducts.Input_CoherentStokes.mountpoints=[]
+ObsSW.Observation.DataProducts.Input_CoherentStokes.namemask=
+ObsSW.Observation.DataProducts.Input_CoherentStokes.skip=[]
+ObsSW.Observation.DataProducts.Input_Correlated.dirmask=L${OBSID}
+ObsSW.Observation.DataProducts.Input_Correlated.enabled=true
+ObsSW.Observation.DataProducts.Input_IncoherentStokes.dirmask=
+ObsSW.Observation.DataProducts.Input_IncoherentStokes.enabled=false
+ObsSW.Observation.DataProducts.Input_IncoherentStokes.filenames=[]
+ObsSW.Observation.DataProducts.Input_IncoherentStokes.identifications=[]
+ObsSW.Observation.DataProducts.Input_IncoherentStokes.locations=[]
+ObsSW.Observation.DataProducts.Input_IncoherentStokes.mountpoints=[]
+ObsSW.Observation.DataProducts.Input_IncoherentStokes.namemask=
+ObsSW.Observation.DataProducts.Input_IncoherentStokes.skip=[]
+ObsSW.Observation.DataProducts.Input_InstrumentModel.dirmask=L${OBSID}
+ObsSW.Observation.DataProducts.Input_InstrumentModel.enabled=true
+ObsSW.Observation.DataProducts.Input_SkyImage.dirmask=
+ObsSW.Observation.DataProducts.Input_SkyImage.enabled=false
+ObsSW.Observation.DataProducts.Input_SkyImage.filenames=[]
+ObsSW.Observation.DataProducts.Input_SkyImage.identifications=[]
+ObsSW.Observation.DataProducts.Input_SkyImage.locations=[]
+ObsSW.Observation.DataProducts.Input_SkyImage.mountpoints=[]
+ObsSW.Observation.DataProducts.Input_SkyImage.namemask=
+ObsSW.Observation.DataProducts.Input_SkyImage.skip=[]
+ObsSW.Observation.DataProducts.Output_BeamFormed_.CoherentStokesBeam.Offset.angle1=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.CoherentStokesBeam.Offset.angle2=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.CoherentStokesBeam.Offset.coordType=RA
+ObsSW.Observation.DataProducts.Output_BeamFormed_.CoherentStokesBeam.Offset.equinox=J2000
+ObsSW.Observation.DataProducts.Output_BeamFormed_.CoherentStokesBeam.Pointing.angle1=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.CoherentStokesBeam.Pointing.angle2=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.CoherentStokesBeam.Pointing.coordType=RA
+ObsSW.Observation.DataProducts.Output_BeamFormed_.CoherentStokesBeam.Pointing.equinox=J2000
+ObsSW.Observation.DataProducts.Output_BeamFormed_.CoherentStokesBeam.SubArrayPointingIdentifier=MoM
+ObsSW.Observation.DataProducts.Output_BeamFormed_.CoherentStokesBeam.beamNumber=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.CoherentStokesBeam.centralFrequencies=[]
+ObsSW.Observation.DataProducts.Output_BeamFormed_.CoherentStokesBeam.channelWidth=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.CoherentStokesBeam.channelsPerSubband=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.CoherentStokesBeam.dispersionMeasure=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.CoherentStokesBeam.numberOfSubbands=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.CoherentStokesBeam.stationSubbands=[]
+ObsSW.Observation.DataProducts.Output_BeamFormed_.FlysEyeBeam.Station.coordSystAF0=ITRF2005
+ObsSW.Observation.DataProducts.Output_BeamFormed_.FlysEyeBeam.Station.coordSystAF1=ITRF2005
+ObsSW.Observation.DataProducts.Output_BeamFormed_.FlysEyeBeam.Station.coordXAF0=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.FlysEyeBeam.Station.coordXAF1=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.FlysEyeBeam.Station.coordYAF0=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.FlysEyeBeam.Station.coordYAF1=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.FlysEyeBeam.Station.coordZAF0=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.FlysEyeBeam.Station.coordZAF1=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.FlysEyeBeam.Station.name=
+ObsSW.Observation.DataProducts.Output_BeamFormed_.FlysEyeBeam.Station.nameAF0=LBA
+ObsSW.Observation.DataProducts.Output_BeamFormed_.FlysEyeBeam.Station.nameAF1=LBA
+ObsSW.Observation.DataProducts.Output_BeamFormed_.FlysEyeBeam.Station.nrAntennaField=1
+ObsSW.Observation.DataProducts.Output_BeamFormed_.FlysEyeBeam.Station.stationType=Core
+ObsSW.Observation.DataProducts.Output_BeamFormed_.FlysEyeBeam.SubArrayPointingIdentifier=MoM
+ObsSW.Observation.DataProducts.Output_BeamFormed_.FlysEyeBeam.beamNumber=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.FlysEyeBeam.centralFrequencies=[]
+ObsSW.Observation.DataProducts.Output_BeamFormed_.FlysEyeBeam.channelWidth=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.FlysEyeBeam.channelsPerSubband=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.FlysEyeBeam.dispersionMeasure=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.FlysEyeBeam.numberOfSubbands=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.FlysEyeBeam.stationSubbands=[]
+ObsSW.Observation.DataProducts.Output_BeamFormed_.IncoherentStokesBeam.SubArrayPointingIdentifier=MoM
+ObsSW.Observation.DataProducts.Output_BeamFormed_.IncoherentStokesBeam.beamNumber=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.IncoherentStokesBeam.centralFrequencies=[]
+ObsSW.Observation.DataProducts.Output_BeamFormed_.IncoherentStokesBeam.channelWidth=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.IncoherentStokesBeam.channelsPerSubband=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.IncoherentStokesBeam.dispersionMeasure=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.IncoherentStokesBeam.numberOfSubbands=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.IncoherentStokesBeam.stationSubbands=[]
+ObsSW.Observation.DataProducts.Output_BeamFormed_.beamTypes=[]
+ObsSW.Observation.DataProducts.Output_BeamFormed_.fileFormat=HDF5
+ObsSW.Observation.DataProducts.Output_BeamFormed_.filename=
+ObsSW.Observation.DataProducts.Output_BeamFormed_.location=
+ObsSW.Observation.DataProducts.Output_BeamFormed_.nrOfCoherentStokesBeams=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.nrOfFlysEyeBeams=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.nrOfIncoherentStokesBeams=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.percentageWritten=0
+ObsSW.Observation.DataProducts.Output_BeamFormed_.size=0
+ObsSW.Observation.DataProducts.Output_Beamformed.archived=false
+ObsSW.Observation.DataProducts.Output_Beamformed.deleted=false
+ObsSW.Observation.DataProducts.Output_Beamformed.dirmask=
+ObsSW.Observation.DataProducts.Output_Beamformed.enabled=false
+ObsSW.Observation.DataProducts.Output_Beamformed.filenames=[]
+ObsSW.Observation.DataProducts.Output_Beamformed.identifications=[]
+ObsSW.Observation.DataProducts.Output_Beamformed.locations=[]
+ObsSW.Observation.DataProducts.Output_Beamformed.mountpoints=[]
+ObsSW.Observation.DataProducts.Output_Beamformed.namemask=
+ObsSW.Observation.DataProducts.Output_Beamformed.percentageWritten=[]
+ObsSW.Observation.DataProducts.Output_Beamformed.retentiontime=14
+ObsSW.Observation.DataProducts.Output_Beamformed.skip=[]
+ObsSW.Observation.DataProducts.Output_CoherentStokes.archived=false
+ObsSW.Observation.DataProducts.Output_CoherentStokes.deleted=false
+ObsSW.Observation.DataProducts.Output_CoherentStokes.dirmask=
+ObsSW.Observation.DataProducts.Output_CoherentStokes.enabled=false
+ObsSW.Observation.DataProducts.Output_CoherentStokes.filenames=[]
+ObsSW.Observation.DataProducts.Output_CoherentStokes.identifications=[]
+ObsSW.Observation.DataProducts.Output_CoherentStokes.locations=[]
+ObsSW.Observation.DataProducts.Output_CoherentStokes.mountpoints=[]
+ObsSW.Observation.DataProducts.Output_CoherentStokes.namemask=
+ObsSW.Observation.DataProducts.Output_CoherentStokes.percentageWritten=[]
+ObsSW.Observation.DataProducts.Output_CoherentStokes.retentiontime=14
+ObsSW.Observation.DataProducts.Output_CoherentStokes.skip=[]
+ObsSW.Observation.DataProducts.Output_Correlated.archived=false
+ObsSW.Observation.DataProducts.Output_Correlated.deleted=false
+ObsSW.Observation.DataProducts.Output_Correlated.dirmask=L${OBSID}
+ObsSW.Observation.DataProducts.Output_Correlated.enabled=true
+ObsSW.Observation.DataProducts.Output_Correlated_[0].centralFrequency=0
+ObsSW.Observation.DataProducts.Output_Correlated_[0].channelWidth=0
+ObsSW.Observation.DataProducts.Output_Correlated_[0].channelsPerSubband=0
+ObsSW.Observation.DataProducts.Output_Correlated_[0].duration=0
+ObsSW.Observation.DataProducts.Output_Correlated_[0].fileFormat=AIPS
+ObsSW.Observation.DataProducts.Output_Correlated_[0].filename=
+ObsSW.Observation.DataProducts.Output_Correlated_[0].integrationInterval=0
+ObsSW.Observation.DataProducts.Output_Correlated_[0].location=
+ObsSW.Observation.DataProducts.Output_Correlated_[0].percentageWritten=0
+ObsSW.Observation.DataProducts.Output_Correlated_[0].size=0
+ObsSW.Observation.DataProducts.Output_Correlated_[0].startTime=
+ObsSW.Observation.DataProducts.Output_Correlated_[0].stationSubband=0
+ObsSW.Observation.DataProducts.Output_Correlated_[0].subband=0
+ObsSW.Observation.DataProducts.Output_Correlated_[10].centralFrequency=0
+ObsSW.Observation.DataProducts.Output_Correlated_[10].channelWidth=0
+ObsSW.Observation.DataProducts.Output_Correlated_[10].channelsPerSubband=0
+ObsSW.Observation.DataProducts.Output_Correlated_[10].duration=0
+ObsSW.Observation.DataProducts.Output_Correlated_[10].fileFormat=AIPS
+ObsSW.Observation.DataProducts.Output_Correlated_[10].filename=
+ObsSW.Observation.DataProducts.Output_Correlated_[10].integrationInterval=0
+ObsSW.Observation.DataProducts.Output_Correlated_[10].location=
+ObsSW.Observation.DataProducts.Output_Correlated_[10].percentageWritten=0
+ObsSW.Observation.DataProducts.Output_Correlated_[10].size=0
+ObsSW.Observation.DataProducts.Output_Correlated_[10].startTime=
+ObsSW.Observation.DataProducts.Output_Correlated_[10].stationSubband=0
+ObsSW.Observation.DataProducts.Output_Correlated_[10].subband=0
+ObsSW.Observation.DataProducts.Output_Correlated_[11].centralFrequency=0
+ObsSW.Observation.DataProducts.Output_Correlated_[11].channelWidth=0
+ObsSW.Observation.DataProducts.Output_Correlated_[11].channelsPerSubband=0
+ObsSW.Observation.DataProducts.Output_Correlated_[11].duration=0
+ObsSW.Observation.DataProducts.Output_Correlated_[11].fileFormat=AIPS
+ObsSW.Observation.DataProducts.Output_Correlated_[11].filename=
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+ObsSW.Observation.DataProducts.Output_Correlated_[11].location=
+ObsSW.Observation.DataProducts.Output_Correlated_[11].percentageWritten=0
+ObsSW.Observation.DataProducts.Output_Correlated_[11].size=0
+ObsSW.Observation.DataProducts.Output_Correlated_[11].startTime=
+ObsSW.Observation.DataProducts.Output_Correlated_[11].stationSubband=0
+ObsSW.Observation.DataProducts.Output_Correlated_[11].subband=0
+ObsSW.Observation.DataProducts.Output_Correlated_[12].centralFrequency=0
+ObsSW.Observation.DataProducts.Output_Correlated_[12].channelWidth=0
+ObsSW.Observation.DataProducts.Output_Correlated_[12].channelsPerSubband=0
+ObsSW.Observation.DataProducts.Output_Correlated_[12].duration=0
+ObsSW.Observation.DataProducts.Output_Correlated_[12].fileFormat=AIPS
+ObsSW.Observation.DataProducts.Output_Correlated_[12].filename=
+ObsSW.Observation.DataProducts.Output_Correlated_[12].integrationInterval=0
+ObsSW.Observation.DataProducts.Output_Correlated_[12].location=
+ObsSW.Observation.DataProducts.Output_Correlated_[12].percentageWritten=0
+ObsSW.Observation.DataProducts.Output_Correlated_[12].size=0
+ObsSW.Observation.DataProducts.Output_Correlated_[12].startTime=
+ObsSW.Observation.DataProducts.Output_Correlated_[12].stationSubband=0
+ObsSW.Observation.DataProducts.Output_Correlated_[12].subband=0
+ObsSW.Observation.DataProducts.Output_Correlated_[13].centralFrequency=0
+ObsSW.Observation.DataProducts.Output_Correlated_[13].channelWidth=0
+ObsSW.Observation.DataProducts.Output_Correlated_[13].channelsPerSubband=0
+ObsSW.Observation.DataProducts.Output_Correlated_[13].duration=0
+ObsSW.Observation.DataProducts.Output_Correlated_[13].fileFormat=AIPS
+ObsSW.Observation.DataProducts.Output_Correlated_[13].filename=
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+ObsSW.Observation.DataProducts.Output_Correlated_[13].location=
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+ObsSW.Observation.DataProducts.Output_Correlated_[13].size=0
+ObsSW.Observation.DataProducts.Output_Correlated_[13].startTime=
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+ObsSW.Observation.DataProducts.Output_Correlated_[13].subband=0
+ObsSW.Observation.DataProducts.Output_Correlated_[14].centralFrequency=0
+ObsSW.Observation.DataProducts.Output_Correlated_[14].channelWidth=0
+ObsSW.Observation.DataProducts.Output_Correlated_[14].channelsPerSubband=0
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+ObsSW.Observation.DataProducts.Output_Correlated_[15].centralFrequency=0
+ObsSW.Observation.DataProducts.Output_Correlated_[15].channelWidth=0
+ObsSW.Observation.DataProducts.Output_Correlated_[15].channelsPerSubband=0
+ObsSW.Observation.DataProducts.Output_Correlated_[15].duration=0
+ObsSW.Observation.DataProducts.Output_Correlated_[15].fileFormat=AIPS
+ObsSW.Observation.DataProducts.Output_Correlated_[15].filename=
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+ObsSW.Observation.DataProducts.Output_Correlated_[15].size=0
+ObsSW.Observation.DataProducts.Output_Correlated_[15].startTime=
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+ObsSW.Observation.DataProducts.Output_Correlated_[15].subband=0
+ObsSW.Observation.DataProducts.Output_Correlated_[16].centralFrequency=0
+ObsSW.Observation.DataProducts.Output_Correlated_[16].channelWidth=0
+ObsSW.Observation.DataProducts.Output_Correlated_[16].channelsPerSubband=0
+ObsSW.Observation.DataProducts.Output_Correlated_[16].duration=0
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+ObsSW.Observation.DataProducts.Output_Correlated_[16].filename=
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+ObsSW.Observation.DataProducts.Output_Correlated_[17].filename=
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+ObsSW.Observation.DataProducts.Output_Correlated_[18].subband=0
+ObsSW.Observation.DataProducts.Output_Correlated_[19].centralFrequency=0
+ObsSW.Observation.DataProducts.Output_Correlated_[19].channelWidth=0
+ObsSW.Observation.DataProducts.Output_Correlated_[19].channelsPerSubband=0
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+ "]]>
+ </config>
+ </msss_target_pipeline>
+</pipeline_block>