class Pipeline:
# Define source of pipeline
grid = coprocessor.CreateProducer(datadescription, "input")
if (write_full_output == True):
fullWriter = pvs.XMLPUnstructuredGridWriter(
Input=grid, DataMode="Appended", CompressorType="ZLib")
coprocessor.RegisterWriter(fullWriter,
filename='full_output_%t.pvtu',
freq=1)
# Create a spherical slice
slice = pvs.Slice(Input=grid)
slice.SliceType = 'Sphere'
slice.Triangulatetheslice = 0
slice.SliceOffsetValues = [0.0]
slice.SliceType.Radius = sphere_radius
# Create writer for this data and register it with the pipeline
sliceWriter = pvs.XMLPPolyDataWriter(Input=slice,
DataMode="Appended",
CompressorType="ZLib")
coprocessor.RegisterWriter(sliceWriter,
filename='spherical_slice_%t.pvtp',
freq=1)
class Pipeline:
# Define source of pipeline
grid = coprocessor.CreateProducer(datadescription, "input")
if (write_full_output == True):
fullWriter = pvs.XMLPUnstructuredGridWriter(
Input=grid, DataMode="Appended", CompressorType="ZLib")
coprocessor.RegisterWriter(fullWriter,
filename='full_output_%t.pvtu',
freq=1)
# Determine grid bounds
gridBounds = grid.GetClientSideObject().GetOutputDataObject(
0).GetBounds()
# Plane slice at the desired longitude
slice = pvs.Slice(Input=grid)
slice.SliceType = 'Plane'
slice.Triangulatetheslice = 0
slice.SliceOffsetValues = [0.0]
slice.SliceType.Origin = [
longitude / 180.0 * math.pi, 0, gridBounds[4]
]
slice.SliceType.Normal = [1, 0, 0]
# Create new writer
sliceWriter = pvs.XMLPPolyDataWriter(Input=slice,
DataMode="Appended",
CompressorType="ZLib")
coprocessor.RegisterWriter(sliceWriter,
filename='meridional_slice_%t.pvtp',
freq=1)
class Pipeline:
# Define source of pipeline
grid = coprocessor.CreateProducer( datadescription, "input" )
# Create writer for this data and register it with the pipeline
parallelWriter = pvs.XMLPUnstructuredGridWriter(Input=grid)
coprocessor.RegisterWriter(parallelWriter, filename='field_%t.pvtu', freq=1)
class Pipeline:
# Define source of pipeline
grid = coprocessor.CreateProducer(datadescription, "input")
if (write_full_output == True):
fullWriter = pvs.XMLPUnstructuredGridWriter(
Input=grid, DataMode="Appended", CompressorType="ZLib")
coprocessor.RegisterWriter(fullWriter,
filename='full_output_%t.pvtu',
freq=1)
# Create a spherical slice
slice = pvs.Slice(Input=grid)
slice.SliceType = 'Sphere'
slice.Triangulatetheslice = 0
slice.SliceOffsetValues = [0.0]
slice.SliceType.Radius = sphere_radius
# Generate ghost cells - needed by CellDatatoPointData filter
ghosts = pvs.GhostCellsGenerator(Input=grid)
ghosts.BuildIfRequired = 0
ghosts.MinimumNumberOfGhostLevels = 1
# Convert cell data to point data, which is required for good contour results
# Request "piece invariance" to ensure consistent values at
# partition boundaries.
#
# CAUTION: THIS FILTER AVERAGES DATA FROM ALL CELLS SURROUNDING A POINT,
# WHICH REDUCES ACCURACY
cell2point = pvs.CellDatatoPointData(Input=ghosts)
# Create contours
# Note that the "tube" filter can be used to highlight contours if needed.
contours = pvs.Contour(Input=cell2point)
contours.Isosurfaces = contour_values
contours.ContourBy = ['POINTS', 'rho']
contours.PointMergeMethod = 'Uniform Binning'
# Create writers for slice and contour data and register them with the pipeline
# Note that slice and contours generate separate datasets, so they need to be
# written to separate files.
sliceWriter = pvs.XMLPPolyDataWriter(Input=slice,
DataMode="Appended",
CompressorType="ZLib")
coprocessor.RegisterWriter(sliceWriter,
filename='spherical_slice_%t.pvtp',
freq=1)
# Create a new render view
renderView = pvs.CreateView('RenderView')
renderView.ViewSize = [1500, 768]
renderView.AxesGrid = 'GridAxes3DActor'
renderView.StereoType = 0
renderView.CameraPosition = [0.0, 1.0, 0.3]
renderView.CameraViewUp = [0.0, 0.0, 1.0]
renderView.CameraParallelScale = 1.0
renderView.Background = [0.32, 0.34, 0.43]
renderView.ViewTime = datadescription.GetTime()
# Register the view with coprocessor
# and provide it with information such as the filename to use,
# how frequently to write the images, etc.
coprocessor.RegisterView(renderView,
filename='contours_%t.png',
freq=1,
fittoscreen=1,
magnification=1,
width=1500,
height=768,
cinema={})
# Create colour transfer function for field
LUT = pvs.GetColorTransferFunction('rho')
LUT.RGBPoints = [
dataRange[0], 0.23, 0.30, 0.75, 0.5 * sum(dataRange), 0.87,
0.87, 0.87, dataRange[1], 0.71, 0.016, 0.15
]
LUT.ScalarRangeInitialized = 1.0
# Show surface and colour by field value (which is cell data) using lookup table
sphereDisplay = pvs.Show(slice, renderView)
sphereDisplay.Representation = 'Surface'
sphereDisplay.ColorArrayName = ['CELLS', 'rho']
sphereDisplay.LookupTable = LUT
# Show coastlines
contourDisplay = pvs.Show(contours, renderView)
contourDisplay.Representation = 'Surface'
contourDisplay.ColorArrayName = [None, '']
contourDisplay.OSPRayScaleArray = 'theta '
contourDisplay.OSPRayScaleFunction = 'PiecewiseFunction'
contourDisplay.SelectOrientationVectors = 'None'
contourDisplay.ScaleFactor = 1193042.2418936265
contourDisplay.SelectScaleArray = 'None'
contourDisplay.GlyphType = 'Arrow'
contourDisplay.GlyphTableIndexArray = 'None'
contourDisplay.DataAxesGrid = 'GridAxesRepresentation'
contourDisplay.PolarAxes = 'PolarAxesRepresentation'
contourDisplay.GaussianRadius = 596521.1209468133
contourDisplay.SetScaleArray = ['POINTS', 'theta ']
contourDisplay.ScaleTransferFunction = 'PiecewiseFunction'
contourDisplay.OpacityArray = ['POINTS', 'theta ']
contourDisplay.OpacityTransferFunction = 'PiecewiseFunction'
class Pipeline:
# Define source of pipeline
grid = coprocessor.CreateProducer(datadescription, "input")
if (write_full_output == True):
fullWriter = pvs.XMLPUnstructuredGridWriter(
Input=grid, DataMode="Appended", CompressorType="ZLib")
coprocessor.RegisterWriter(fullWriter,
filename='full_output_%t.pvtu',
freq=1)
# Create a spherical slice
slice = pvs.Slice(Input=grid)
slice.SliceType = 'Sphere'
slice.Triangulatetheslice = 0
slice.SliceOffsetValues = [0.0]
slice.SliceType.Radius = sphere_radius
# Create writer for this data and register it with the pipeline
sliceWriter = pvs.XMLPPolyDataWriter(Input=slice,
DataMode="Appended",
CompressorType="ZLib")
coprocessor.RegisterWriter(sliceWriter,
filename='spherical_slice_%t.pvtp',
freq=1)
# Create a new render view
renderView = pvs.CreateView('RenderView')
renderView.ViewSize = [1500, 768]
renderView.AxesGrid = 'GridAxes3DActor'
renderView.StereoType = 0
renderView.CameraPosition = [-5, -2, 4]
renderView.CameraViewUp = [0.5, 0.3, 0.8]
renderView.CameraParallelScale = 1.7
renderView.Background = [0.32, 0.34, 0.43]
renderView.ViewTime = datadescription.GetTime()
# Register the view with coprocessor
# and provide it with information such as the filename to use,
# how frequently to write the images, etc.
coprocessor.RegisterView(renderView,
filename='spherical_slice_%t.png',
freq=1,
fittoscreen=1,
magnification=1,
width=1500,
height=768,
cinema={})
# Create colour transfer function for field
LUT = pvs.GetColorTransferFunction(fieldname)
LUT.RGBPoints = [
dataRange[0], 0.23, 0.30, 0.75, 0.5 * sum(dataRange), 0.87,
0.87, 0.87, dataRange[1], 0.71, 0.016, 0.15
]
LUT.ScalarRangeInitialized = 1.0
# Show surface and colour by field value (which is cell data) using lookup table
sphereDisplay = pvs.Show(slice, renderView)
sphereDisplay.Representation = 'Surface'
sphereDisplay.ColorArrayName = ['CELLS', fieldname]
sphereDisplay.LookupTable = LUT
class Pipeline:
# Define source of pipeline
grid = coprocessor.CreateProducer(datadescription, "input")
if (write_full_output == True):
fullWriter = pvs.XMLPUnstructuredGridWriter(
Input=grid, DataMode="Appended", CompressorType="ZLib")
coprocessor.RegisterWriter(fullWriter,
filename='full_output_%t.pvtu',
freq=1)
# Horizontal slice at the bottom
slice = pvs.Slice(Input=grid)
slice.SliceType = 'Plane'
slice.SliceOffsetValues = [0.0]
slice.SliceType.Origin = [0.0, 0.0, 101.94]
slice.SliceType.Normal = [0.0, 0.0, 1.0]
slice.Triangulatetheslice = False
# Set up spherical projection filter - we need to bridge into the
# VTK universe and use a VTK transform filter; the ParaView transform filter
# does not support geo transforms
# Source projection - simulation data is provided in lon lat rad coordinates
latlonproj = vtk.vtkGeoProjection()
latlonproj.SetName('lonlat')
latlonproj.SetCentralMeridian(0)
# Target projection - use Mollweide here
targetproj = vtk.vtkGeoProjection()
targetproj.SetName('moll')
targetproj.SetCentralMeridian(0)
# Set up vtkGeoTransform object that defines the transformation
transform = vtk.vtkGeoTransform()
transform.SetSourceProjection(latlonproj)
transform.SetDestinationProjection(targetproj)
# Set up VTK transform filter object
tffilter = vtk.vtkTransformFilter()
tffilter.SetTransform(transform)
tffilter.SetInputConnection(
slice.GetClientSideObject().GetOutputPort(0))
# Return to ParaView universe by using a simple PassThrough filter to receive
# output of the VTK transform filter
passthrough = pvs.PassThrough()
passthrough.GetClientSideObject().SetInputConnection(
tffilter.GetOutputPort())
# Create a new render view
renderView = pvs.CreateView('RenderView')
renderView.ViewSize = [1500, 768]
renderView.AxesGrid = 'GridAxes3DActor'
renderView.StereoType = 0
renderView.CameraPosition = [0, 0, 4]
renderView.CameraParallelScale = 1.7
renderView.Background = [0.32, 0.34, 0.43]
renderView.ViewTime = datadescription.GetTime()
# Register the view with coprocessor
# and provide it with information such as the filename to use,
# how frequently to write the images, etc.
coprocessor.RegisterView(renderView,
filename='spherical_slice_%t.png',
freq=1,
fittoscreen=1,
magnification=1,
width=1500,
height=768,
cinema={})
# Create colour transfer function for field
LUT = pvs.GetColorTransferFunction(fieldname)
LUT.RGBPoints = [
dataRange[0], 0.23, 0.30, 0.75, 0.5 * sum(dataRange), 0.87,
0.87, 0.87, dataRange[1], 0.71, 0.016, 0.15
]
LUT.ScalarRangeInitialized = 1.0
# Show surface and colour by field value (which is cell data) using lookup table
sphereDisplay = pvs.Show(passthrough, renderView)
sphereDisplay.Representation = 'Surface'
sphereDisplay.ColorArrayName = ['CELLS', fieldname]
sphereDisplay.LookupTable = LUT