Plot field Vectors on a Named Selection in PyDPF

For generating a vector plot on a named selection in PyDPF, some functions of the PyVista Python library are needed. The example presented below is a combination of the PyDPF and PyVista open-source codes. Here is an example of working with the Heat Flux field:

from ansys.dpf import core as dpf
from ansys.dpf.core.plotter import DpfPlotter
from ansys.dpf.core.common import locations
 
import pyvista as pv
import numpy as np
 
"""
Load result file and create model database
"""
 
path = "my_Path"
 
ds = dpf.DataSources(path)
model = dpf.Model(ds)
 
mesh = model.metadata.meshed_region
 
"""
Select preferable Named Selection
"""
 
get_NSs = model.metadata.available_named_selections
my_mesh_scoping = model.metadata.named_selection("my_Named_Selection")
 
"""
Scope Named Selection to corresponding Mesh
"""
 
scoping_op = dpf.operators.mesh.from_scoping()
scoping_op.inputs.scoping.connect(my_mesh_scoping)
scoping_op.inputs.mesh.connect(mesh)
 
my_mesh = scoping_op.outputs.mesh()
 
"""
Get Heat Flux results at last time step
"""
 
get_all_heatFlux = model.results.heat_flux.on_all_time_freqs
get_fieldContents_heatFlux = get_all_heatFlux(mesh_scoping=my_mesh_scoping).eval()
 
get_field_heatFlux = get_fieldContents_heatFlux[-1]
 
"""
Recreate DpfPlotter() and Contour Plot based on PyDPF Source Code and PyVista library
"""
 
sargs = dict(
    title = "Heat Flux [W/m^2]",  
    title_font_size = 30, 
    label_font_size = 20, 
    interactive = True
    )
 
margs = dict(
    show_edges = True, 
    nan_color = None,
    )
 
field = get_field_heatFlux
meshed_region = my_mesh
location = field.location
 
show_max = False
show_min = False
 
 
mesh_location = meshed_region.nodes
component_count = field.component_count
overall_data = np.full((len(mesh_location), component_count), np.nan)
 
ind, mask = mesh_location.map_scoping(field.scoping)
overall_data[ind] = field.data[mask]
 
deform_by = None
scale_factor=1.0
as_linear=True
 
grid = meshed_region.grid
grid.set_active_scalars(None)
 
p = pv.Plotter()
p.add_mesh(mesh=grid, scalars=overall_data, **margs, scalar_bar_args=sargs)
p.add_axes()
p.show()
 
"""
Vector Plot
"""
 
scaling = 1e-7
grid["my_vectors"] = overall_data * scaling
grid.set_active_vectors("my_vectors")
 
vtitle = "Vector Magnitude"
vargs = dict(title = vtitle)
 
p = pv.Plotter()
p.add_mesh(grid.arrows, lighting=False, scalar_bar_args=vargs)
p.add_mesh(grid, scalars=overall_data, **margs, scalar_bar_args=sargs)
p.remove_scalar_bar(title=vtitle)
p.add_axes()
p.show()