Client Side Delivery: Difference between revisions
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;vtkMinMax: A new filter that performs an operation on the attribute data of its input. This filter iterates through whatever datasets it is given and calls a templated operate function on each value. The templated function is necessary to avoid double conversion and loss of precision on non double valued arrays. This filter can take one or more input datasets on its first input port and always produces a single unstructured grid output that contains exactly one point and one cell. | ;vtkMinMax: A new filter that performs an operation on the attribute data of its input. This filter iterates through whatever datasets it is given and calls a templated operate function on each value. The templated function is necessary to avoid double conversion and loss of precision on non double valued arrays. This filter can take one or more input datasets on its first input port and always produces a single unstructured grid output that contains exactly one point and one cell. | ||
;paraview.fetch: A new function added to the paraview.py module that uses the above components to obtain data. | |||
== Example use == | == Example use == | ||
Revision as of 13:12, 16 January 2007
The goal of client side delivery is to provide functions that can be called from a python script to perform a parallel aggregation of data with the result obtained on the client. This goal is accomplished with a combination of new, modified, and existing filters. The new function paraview.fetch() in the paraview server python module automates the creation and execution of the results gathering pipeline.
Design
- vtkSMGenericViewDisplayProxy
- This unmodified filter orchestrates gathering results in paraview for the GUI. The filter internally uses a vtkReductionFilter to direct communications between the server nodes and a vtkClientServerModeData filter that transmits data from the server to the client. For our purposes we use vtkSMGenericViewDisplayProxy's FIRST_NODE_ONLY reduction type setting, which simply transmits data from the root node of the server to the client.
- vtkReductionFilter
- This modified filter does the communication needed to perform the aggregation. This filter defers all data manipulation to a user provided algorithm. The filter has been modified to run an additional user provided algorithm, which each node executes in parallel _before_ sending their data to the root node. This pregather algorithm is essential for scalability. After the root node obtains the intermediate results from all nodes it runs a user provided algorithm as before. Both pre and post gather algorithms can refer to the same object. The vtkReductionFilter was also modified to allow simple passthrough of data and to be able to pass though any one particular cluster node's data.
- vtkMinMax
- A new filter that performs an operation on the attribute data of its input. This filter iterates through whatever datasets it is given and calls a templated operate function on each value. The templated function is necessary to avoid double conversion and loss of precision on non double valued arrays. This filter can take one or more input datasets on its first input port and always produces a single unstructured grid output that contains exactly one point and one cell.
- paraview.fetch
- A new function added to the paraview.py module that uses the above components to obtain data.
Example use
import paraview
#connect to a running pvserver with one or more nodes
paraview.ActiveConnection = paraview.Connect("localhost", 11111)
#create a sample data set
sphere = paraview.CreateProxy("sources", "SphereSource")
elev = paraview.CreateProxy("filters", "ElevationFilter")
elev.SetInput(sphere)
#choose the operation to perform in parallel
op = paraview.CreateProxy("filters", "MinMax")
op.SetOperation(1) #MAX
op.UpdateVTKObjects()
#do the fetch
out = paraview.fetch(elev, op)
#show the results
arr = out.GetPointData().GetArray("Elevation")
arr.GetValue(0)
