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107 lines
3.2 KiB
Python
107 lines
3.2 KiB
Python
#!/usr/bin/env python
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from __future__ import print_function
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from vtk import *
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import os.path
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from vtk.util.misc import vtkGetDataRoot
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VTK_DATA_ROOT = vtkGetDataRoot()
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# Set database parameters
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data_dir = VTK_DATA_ROOT + "/Data/Infovis/SQLite/"
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if not os.path.exists( data_dir):
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data_dir = VTK_DATA_ROOT + "/Data/Infovis/SQLite/"
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if not os.path.exists( data_dir):
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data_dir = VTK_DATA_ROOT + "/Data/Infovis/SQLite/"
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sqlite_file = data_dir + "temperatures.db"
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databaseToTable = vtkSQLDatabaseTableSource()
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databaseToTable.SetURL("sqlite://" + sqlite_file)
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# Pull the first data set from the database
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databaseToTable.SetQuery("select * from main_tbl where CompId==2")
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# Calculate primary descriptive statistics for first batch
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print("# Calculate primary model of descriptive statistics for first data set:")
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ds1 = vtkDescriptiveStatistics()
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ds1.AddInputConnection( databaseToTable.GetOutputPort() )
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ds1.AddColumn("Temp1")
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ds1.AddColumn("Temp2")
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ds1.SetLearnOption( 1 )
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ds1.SetDeriveOption( 0 )
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ds1.SetAssessOption( 0 )
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ds1.SetTestOption( 0 )
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ds1.Update()
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# Show primary descriptive statistics for first batch
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dStats1 = ds1.GetOutputDataObject( 1 )
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dPrimary1 = dStats1.GetBlock( 0 )
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dPrimary1.Dump( 15 )
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print()
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# Pull the second data set from the database
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databaseToTable.SetQuery("select * from main_tbl where CompId==3")
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# Calculate primary descriptive statistics for second batch
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print("# Calculate primary model of descriptive statistics for second data set:")
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ds2 = vtkDescriptiveStatistics()
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ds2.AddInputConnection( databaseToTable.GetOutputPort() )
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ds2.AddColumn("Temp1")
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ds2.AddColumn("Temp2")
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ds2.SetLearnOption( 1 )
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ds2.SetDeriveOption( 0 )
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ds2.SetAssessOption( 0 )
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ds2.SetTestOption( 0 )
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ds2.Update()
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# Show primary descriptive statistics for second batch
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dStats2 = ds2.GetOutputDataObject( 1 )
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dPrimary2 = dStats2.GetBlock( 0 )
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dPrimary2.Dump( 15 )
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print()
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# Finally aggregate both models to get a new primary model for the whole ensemble
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print("# Aggregate both primary models:")
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collection = vtkDataObjectCollection()
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collection.AddItem( dStats1 )
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collection.AddItem( dStats2 )
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ds = vtkDescriptiveStatistics()
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aggregated = vtkMultiBlockDataSet()
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ds.Aggregate( collection, aggregated )
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dPrimary = aggregated.GetBlock( 0 )
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dPrimary.Dump( 15 )
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print()
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# Calculate derived model for whole ensemble
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print("# Now calculating derived statistics for whole ensemble:")
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ds.SetInputData( 2, aggregated )
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ds.SetLearnOption( 0 )
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ds.SetDeriveOption( 1 )
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ds.SetAssessOption( 0 )
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ds.SetTestOption( 0 )
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ds.Update()
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dStats = ds.GetOutputDataObject( 1 )
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dDerived = dStats.GetBlock( 1 )
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dDerived.Dump( 15 )
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print()
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# Pull entire data set from the database
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databaseToTable.SetQuery("select * from main_tbl")
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# Verify with calculation for whole ensemble at once
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print("# Finally verifying by directly calculating statistics for whole ensemble:")
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ds0 = vtkDescriptiveStatistics()
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ds0.AddInputConnection( databaseToTable.GetOutputPort() )
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ds0.AddColumn("Temp1")
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ds0.AddColumn("Temp2")
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ds0.SetLearnOption( 1 )
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ds0.SetDeriveOption( 1 )
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ds0.SetAssessOption( 0 )
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ds0.SetTestOption( 0 )
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ds0.Update()
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# Show all descriptive statistics for whole ensemble
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dStats0 = ds0.GetOutputDataObject( 1 )
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dPrimary0 = dStats0.GetBlock( 0 )
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dPrimary0.Dump( 15 )
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dDerived0 = dStats0.GetBlock( 1 )
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dDerived0.Dump( 15 )
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print()
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