def global_min(narray):
"Returns the minimum value of an array of scalars/vectors/tensors among all process."
m = min(narray).astype(numpy.float64)
if vtkProcessModule.GetProcessModule().GetNumberOfLocalPartitions() > 1 :
from mpi4py import MPI
MPI.COMM_WORLD.Allreduce(None, [m, MPI.DOUBLE], MPI.MIN)
return m
def global_mean (narray) :
"Returns the mean value of an array of scalars/vectors/tensors among all process."
# For some reason, Allreduce on MPI.INT does not return the correct value.
# I have to convert it into a double array to get the correct results.
dim = narray.shape[1]
if len(narray.shape) == 3 : dim = narray.shape[1] * narray.shape[2]
N = numpy.empty(dim).astype(numpy.float64)
N.fill(narray.shape[0])
S = narray.sum(0).astype(numpy.float64)
if len(S.shape) == 2 and S.shape[0] == 3 and S.shape[1] == 3:
S = numpy.reshape(S, 9)
elif len(S.shape) == 3 and S.shape[0] == 1 and S.shape[1] == 3 and S.shape[2] == 3:
S = numpy.reshape(S, 9)
if vtkProcessModule.GetProcessModule().GetNumberOfLocalPartitions() > 1 :
from mpi4py import MPI
comm = MPI.COMM_WORLD
S_recv = numpy.array(S)
N_recv = numpy.array(N)
comm.Allreduce([S, MPI.DOUBLE], [S_recv, MPI.DOUBLE],MPI.SUM)
comm.Allreduce([N, MPI.DOUBLE], [N_recv, MPI.DOUBLE],MPI.SUM)
S = S_recv
N = N_recv
return S / N
def global_min(narray):
"Returns the minimum value of an array of scalars/vectors/tensors among all process."
if len(narray) > 0:
m = min(narray).astype(numpy.float64)
else:
m = numpy.finfo(numpy.float64).max
if vtkProcessModule.GetProcessModule().GetNumberOfLocalPartitions() > 1 :
from mpi4py import MPI
m_recv = numpy.array(m)
MPI.COMM_WORLD.Allreduce([m, MPI.DOUBLE], [m_recv, MPI.DOUBLE], MPI.MIN)
m = m_recv
return m
def global_max(narray):
"Returns the maximum value of an array of scalars/vectors/tensors among all process."
if len(narray) > 0:
M = max(narray).astype(numpy.float64)
else:
M = numpy.finfo(numpy.float64).min
if vtkProcessModule.GetProcessModule().GetNumberOfLocalPartitions() > 1 :
from mpi4py import MPI
M_recv = numpy.array(M)
MPI.COMM_WORLD.Allreduce([M, MPI.DOUBLE], [M_recv, MPI.DOUBLE], MPI.MAX)
M = M_recv
return M
# "Vendor: NVIDIA Corporation"
# "Version: 4.5.0 NVIDIA 375.66"
# "Renderer: Tesla P100-PCIE-16GB/PCIe/SSE2"
view = GetRenderView()
sphere = Sphere()
sphere.ThetaResolution = 2048
sphere.PhiResolution = 2048
pidscal = ProcessIdScalars(sphere)
rep = Show(pidscal)
from vtkPVClientServerCoreCorePython import vtkProcessModule
print("rank=", vtkProcessModule.GetProcessModule().GetPartitionId())
print("total=", vtkProcessModule.GetProcessModule().GetNumberOfLocalPartitions())
nbprocs = servermanager.ActiveConnection.GetNumberOfDataPartitions()
drange = [0, nbprocs-1]
lt = MakeBlueToRedLT(drange[0], drange[1])
lt.NumberOfTableValues = nbprocs
rep.LookupTable = lt
rep.ColorArrayName = ("POINT_DATA", "ProcessId")
bar = CreateScalarBar(LookupTable=lt, Title="PID")
bar.TitleColor = [0, 0, 0]
bar.LabelColor = [0, 0, 0]
# bar.NumberOfLabels = 6
view.Representations.append(bar)