How can one save a plot of a pydpf result when using pypdf in standalone (IDE) mode?

This is the standard question from customers who are partaking in a pyanys discussion, how can they plot results to file.

They would like plots/images of the results that are created and pop up when using pyansys tools. If they were matplotlib plots it would be possible to write them to file.

How to do similar with the pydpf results.

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Accepted answers

from ansys.dpf import core as dpf
from ansys.dpf.core import examples
from ansys.dpf.core.plotter import DpfPlotter

# Here we create a Model and request its mesh and a displacement result
model = dpf.Model(examples.msup_transient)
mesh = model.metadata.meshed_region
disp = model.results.displacement().outputs.fields_container()[0]

# Then we plot and save the screenshot
pl = DpfPlotter(notebook=False) # set notebook to false to disable showing in the current window
pl.add_field(disp, mesh)
pl.show_figure(screenshot='D:\my_screenshot.png') # set screenshot file_path

All comments

from ansys.dpf import core as dpf
from ansys.dpf.core import examples
from ansys.dpf.core.plotter import DpfPlotter

# Here we create a Model and request its mesh and a displacement result
model = dpf.Model(examples.msup_transient)
mesh = model.metadata.meshed_region
disp = model.results.displacement().outputs.fields_container()[0]

# Then we plot and save the screenshot
pl = DpfPlotter(notebook=False) # set notebook to false to disable showing in the current window
pl.add_field(disp, mesh)
pl.show_figure(screenshot='D:\my_screenshot.png') # set screenshot file_path

Joona

How can I define a particular view? For example, I want to view at a certain detail of a part.

There is a list of standard views that can be used for plots:
cpos_list = ['xy' ,'xz', 'yz', 'yx', 'zx', 'zy', 'iso']

And you can use named selection to get a detail (set the name selection to whatever detail area you require, but include enough to make it meaningful, so a selection of elements and not a single node or element).

named_selections = model.metadata.available_named_selections
nameselection = named_selections[0]

Then set up your result plot to those args (example for step n, von mises stress below):

cpos = cpos_list[0] # set a view
mesh_scoping = model.metadata.named_selection(nameselection)
time_sets_scoping = dpf.time_freq_scoping_factory.scoping_by_sets([n])
s_eqv_op = dpf.operators.result.stress_von_mises(data_sources=model, mesh_scoping = mesh_scoping, time_scoping = time_sets_scoping)
s_eqv_fields = s_eqv_op.outputs.fields_container()
vm_stress_nodal = s_eqv_fields[0]

plot = DpfPlotter(notebook=False, off_screen=True)
plot.add_field(vm_stress_nodal,  mesh, show_edges=True, opacity=0.8)
plot_path= os.path.join(set path)
plot.show_figure(cpos = cpos, screenshot=plot_path, text = 'plot info')