def test_input_iter_one():
args = argparse.Namespace
args.file = None
args.data = None
args.iter = 1
graph = WorkflowGraph()
prod = TestProducer()
graph.add(prod)
inputs = p.create_inputs(args, graph)
tools.eq_(inputs[prod.id], 1)
def test_input_file():
args = argparse.Namespace
import tempfile
namedfile = tempfile.NamedTemporaryFile()
with namedfile as temp:
data = '{ "TestProducer": 20}'
try:
temp.write(data)
except:
temp.write(bytes(data, 'UTF-8'))
temp.flush()
temp.seek(0)
args.file = namedfile.name
args.data = None
args.iter = 1
graph = WorkflowGraph()
prod = TestProducer()
graph.add(prod)
inputs = p.create_inputs(args, graph)
tools.eq_(inputs[prod.id], 20)
waveform_reader,
(plot_stream, {
"source": "waveform_reader",
"output_dir": "./output-images",
"tag": "observed-image"
})
]
# processes.append((fn, params))
chain = create_iterative_chain(processes, FunctionPE_class=SimpleFunctionPE)
watcher = WatchDirectory(0)
watcher_xml = WatchDirectory(1)
downloadPE.name = "downloadPE"
graph = WorkflowGraph()
graph.add(downloadPE)
graph.connect(downloadPE, 'output', watcher, "input")
graph.connect(downloadPE, 'output', watcher_xml, "input")
graph.connect(watcher, 'output', chain, "input")
graph.connect(watcher_xml, 'output', xmlr, "input")
# injectProv(graph,SeismoPE)
# graph=attachProvenanceRecorderPE(graph,ProvenanceRecorderToFileBulk,username=os.environ['USER_NAME'],runId=os.environ['RUN_ID'])
# Store to local path
#ProvenancePE.PROV_PATH = os.environ['PROV_PATH']
#
# Size of the provenance bulk before sent to storage or sensor
#ProvenancePE.BULK_SIZE = 20
#injectProv(graph, (SeismoPE,), save_mode=ProvenancePE.SAVE_MODE_FILE,
waveformr = SimpleFunctionPE(waveform_reader)
xmlr = SimpleFunctionPE(stationxml_reader)
downloadPE = SimpleFunctionPE(download_data)
processes=[waveform_reader,(plot_stream,{"source":"waveform_reader","output_dir": "./output-images","tag": "observed-image"})]
#processes.append((fn, params))
chain = create_iterative_chain(processes, FunctionPE_class=SimpleFunctionPE)
watcher = WatchDirectory(0)
watcher_xml = WatchDirectory(1)
downloadPE.name = "downloadPE"
graph = WorkflowGraph()
graph.add(downloadPE)
graph.connect(downloadPE, 'output', watcher, "input")
graph.connect(downloadPE, 'output', watcher_xml, "input")
graph.connect(watcher, 'output', chain, "input")
graph.connect(watcher_xml, 'output', xmlr, "input")
#injectProv(graph,SeismoPE)
#graph=attachProvenanceRecorderPE(graph,ProvenanceRecorderToFileBulk,username=os.environ['USER_NAME'],runId=os.environ['RUN_ID'])
#Store to local path
ProvenancePE.PROV_PATH=os.environ['PROV_PATH']
#Size of the provenance bulk before sent to storage or sensor
ProvenancePE.BULK_SIZE=20
NPROC,
"downloadPE": [{
"input": {
"minimum_interstation_distance_in_m": 100,
"channel_priorities": ["BH[E,N,Z]", "EH[E,N,Z]"],
"location_priorities": ["", "00", "10"],
"mseed_path": "./data",
"stationxml_path": "./stations",
"RECORD_LENGTH_IN_MINUTES": RECORD_LENGTH_IN_MINUTES,
"ORIGIN_TIME": ETIME,
"minlatitude": latitude_min,
"maxlatitude": latitude_max,
"minlongitude": longitude_min,
"maxlongitude": longitude_min
}
}]
}
filename = "misfit_data/data_file_test.json"
with open(filename, "w") as write_file:
json.dump(d, write_file)
print(os.getcwd())
print(os.listdir(os.getcwd() + '/misfit_data/SPECFEMDATA'))
write_stream = WriteJSON()
write_stream.name = "WJSON"
graph = WorkflowGraph()
graph.add(write_stream)
def testOnePE():
graph = WorkflowGraph()
prod = TestProducer()
graph.add(prod)
results = simple_process.process(graph, {prod: [{}]})
tools.eq_({(prod.id, 'output'): [1]}, results)
def testOnePE():
graph = WorkflowGraph()
prod = TestProducer()
graph.add(prod)
results = simple_process.process(graph, { prod: [{}] })
tools.eq_({(prod.id, 'output'):[1]}, results)
