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# A sample Catalyst Python pipeline with an ex post facto trigger.
# Here we wait until particles collide. Only then do we output anything.
# Furthermore, we output the timesteps that led up to the collision,
# so that we can reason about what the cause was.
from paraview.simple import *
from paraview import coprocessing
#--------------------------------------------------------------
# Code generated from cpstate.py to create the CoProcessor.
# ----------------------- CoProcessor definition -----------------------
def CreateCoProcessor():
def _CreatePipeline(coprocessor, datadescription):
class Pipeline:
# KEY POINT:
# We don't have to do anything special at each timestep.
# But we do have to make the data available.
# In this case the recent data.
data = coprocessor.CreateTemporalProducer( datadescription, "volume" )
return Pipeline()
class CoProcessor(coprocessing.CoProcessor):
def CreatePipeline(self, datadescription):
self.Pipeline = _CreatePipeline(self, datadescription)
# some bookkeeping structures to make a nice set of outputs
self.StepsWritten = set()
self.TimesToTimesteps = {}
def ProcessTriggers(self, datadescription):
# In this trigger we Look at the simulation's output, and see if we need to do anything
# out of the ordinary. We have access to the N most recent outputs so we write them all out to disk.
data = self.Pipeline.data
timestep = datadescription.GetTimeStep()
time = datadescription.GetTime()
self.TimesToTimesteps[time] = timestep
data.UpdatePipeline(time)
orange = data.GetDataInformation().GetCellDataInformation().GetArrayInformation("occupancy").GetComponentRange(0)
if orange[1] > 1:
# a collision!
print ("collision at tstep %d, time %f, range is [%f,%f]" % (timestep, time, orange[0], orange[1]))
data.UpdatePipelineInformation()
dtimes = data.TimestepValues
for t in dtimes:
if (t not in self.StepsWritten):
print ("write ", t)
self.StepsWritten.add(t)
tstep = self.TimesToTimesteps[t]
writer = servermanager.writers.XMLPImageDataWriter(Input=data)
writer.FileName = "tevent_%d.pvti" % tstep
writer.UpdatePipeline(t)
coprocessor = CoProcessor()
freqs = {'volume': [10, 100]}
coprocessor.SetUpdateFrequencies(freqs)
return coprocessor
#--------------------------------------------------------------
# Global variables that will hold the pipeline for each timestep
# Creating the CoProcessor object, doesn't actually create the ParaView pipeline.
# It will be automatically setup when coprocessor.UpdateProducers() is called the
# first time.
coprocessor = CreateCoProcessor()
#--------------------------------------------------------------
# Enable Live-Visualizaton with ParaView
coprocessor.EnableLiveVisualization(True, 1)
# ---------------------- Data Selection method ----------------------
def RequestDataDescription(datadescription):
"Callback to populate the request for current timestep"
global coprocessor
if datadescription.GetForceOutput() == True:
# We are just going to request all fields and meshes from the simulation
# code/adaptor.
for i in range(datadescription.GetNumberOfInputDescriptions()):
datadescription.GetInputDescription(i).AllFieldsOn()
datadescription.GetInputDescription(i).GenerateMeshOn()
return
# setup requests for all inputs based on the requirements of the
# pipeline.
coprocessor.LoadRequestedData(datadescription)
# ------------------------ Processing method ------------------------
def DoCoProcessing(datadescription):
"Callback to do co-processing for current timestep"
global coprocessor
# Update the coprocessor by providing it the newly generated simulation data.
# If the pipeline hasn't been setup yet, this will setup the pipeline.
coprocessor.UpdateProducers(datadescription)
# KEY POINT:
# We make up a trigger here that is evaluated on every timestep.
coprocessor.ProcessTriggers(datadescription)
# Write output data, if appropriate.
coprocessor.WriteData(datadescription);
# Write image capture (Last arg: rescale lookup table), if appropriate.
coprocessor.WriteImages(datadescription, rescale_lookuptable=False)
# Live Visualization, if enabled.
coprocessor.DoLiveVisualization(datadescription, "localhost", 22222)
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