Note
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Explore the data of a result with the DataFrame - Harmonic Simulation#
In this script a harmonic simulation is used as an example to show how to interact with the post DataFrame: object returned by each result.
Perform required imports#
Perform required imports. # This example uses a supplied file that you can
get by importing the DPF examples package.
from ansys.dpf import post
from ansys.dpf.post import examples
Get Simulation object#
Get the Simulation object that allows access to the result. The Simulation
object must be instantiated with the path for the result file. For example,
"C:/Users/user/my_result.rst" on Windows or "/home/user/my_result.rst"
on Linux.
example_path = examples.download_harmonic_clamped_pipe()
# to automatically detect the simulation type, use:
simulation = post.load_simulation(example_path)
# to enable auto-completion, use the equivalent:
simulation = post.HarmonicMechanicalSimulation(example_path)
Extract displacement over all sets as an example#
displacement = simulation.displacement(all_sets=True)
print(displacement)
type(displacement)
results U ...
set_ids 1 2 3 ...
complex 0 1 0 1 0 1 ...
node_ids components ...
3548 X 9.3929e+01 0.0000e+00 -5.2330e+01 0.0000e+00 -1.1203e+01 0.0000e+00 ...
Y -4.3312e+02 0.0000e+00 1.8810e+02 0.0000e+00 6.8681e+01 0.0000e+00 ...
Z 9.6172e-01 0.0000e+00 -1.3049e+01 0.0000e+00 2.3508e+01 0.0000e+00 ...
3656 X 1.0516e+02 0.0000e+00 -5.8461e+01 0.0000e+00 -1.4575e+01 0.0000e+00 ...
Y -4.6059e+02 0.0000e+00 2.0315e+02 0.0000e+00 7.4665e+01 0.0000e+00 ...
Z 9.4728e-01 0.0000e+00 -1.3728e+01 0.0000e+00 2.5207e+01 0.0000e+00 ...
... ... ... ... ... ... ... ... ...
Loop over all columns and rows to understand the DataFrame and get the values for each index.
# columns
for column in displacement.columns:
print(f'Column with label "{column.name}" and available values {column.values}.')
# rows
for row in displacement.index:
print(f'Row with label "{row.name}" and available values {row.values}.')
Column with label "results" and available values ['U'].
Column with label "set_ids" and available values [1, 2, 3, 4, 5].
Column with label "complex" and available values [0, 1].
Row with label "node_ids" and available values [3548 3656 4099 ... 3260 9942 9943].
Row with label "components" and available values ['X', 'Y', 'Z'].
Make selections in this DataFrame#
All the labels and values displayed above can be used to select sub parts of the DataFrame.
all_real_values = displacement.select(complex=0)
print(all_real_values)
all_imaginary_values = displacement.select(complex=1)
print(all_imaginary_values)
sets_values = displacement.select(set_ids=[1, 2])
print(sets_values)
node_values = displacement.select(node_ids=[3548])
print(node_values)
results U
set_ids 1 2 3 4 5
complex 0
node_ids components
3548 X 9.3929e+01 -5.2330e+01 -1.1203e+01 -1.1510e+01 -1.4457e+01
Y -4.3312e+02 1.8810e+02 6.8681e+01 2.2900e+01 -6.6765e+00
Z 9.6172e-01 -1.3049e+01 2.3508e+01 1.4745e+00 -5.9568e+00
3656 X 1.0516e+02 -5.8461e+01 -1.4575e+01 -1.3822e+01 -1.7782e+01
Y -4.6059e+02 2.0315e+02 7.4665e+01 2.7874e+01 1.5223e+00
Z 9.4728e-01 -1.3728e+01 2.5207e+01 1.4487e+00 -7.3947e+00
... ... ... ... ... ... ...
results U
set_ids 1 2 3 4 5
complex 1
node_ids components
3548 X 0.0000e+00 0.0000e+00 0.0000e+00 0.0000e+00 0.0000e+00
Y 0.0000e+00 0.0000e+00 0.0000e+00 0.0000e+00 0.0000e+00
Z 0.0000e+00 0.0000e+00 0.0000e+00 0.0000e+00 0.0000e+00
3656 X 0.0000e+00 0.0000e+00 0.0000e+00 0.0000e+00 0.0000e+00
Y 0.0000e+00 0.0000e+00 0.0000e+00 0.0000e+00 0.0000e+00
Z 0.0000e+00 0.0000e+00 0.0000e+00 0.0000e+00 0.0000e+00
... ... ... ... ... ... ...
results U
set_ids 1 2
complex 0 1 0 1
node_ids components
3548 X 9.3929e+01 0.0000e+00 -5.2330e+01 0.0000e+00
Y -4.3312e+02 0.0000e+00 1.8810e+02 0.0000e+00
Z 9.6172e-01 0.0000e+00 -1.3049e+01 0.0000e+00
3656 X 1.0516e+02 0.0000e+00 -5.8461e+01 0.0000e+00
Y -4.6059e+02 0.0000e+00 2.0315e+02 0.0000e+00
Z 9.4728e-01 0.0000e+00 -1.3728e+01 0.0000e+00
... ... ... ... ... ...
results U ...
set_ids 1 2 3 ...
complex 0 1 0 1 0 1 ...
node_ids components ...
3548 X 9.3929e+01 0.0000e+00 -5.2330e+01 0.0000e+00 -1.1203e+01 0.0000e+00 ...
Y -4.3312e+02 0.0000e+00 1.8810e+02 0.0000e+00 6.8681e+01 0.0000e+00 ...
Z 9.6172e-01 0.0000e+00 -1.3049e+01 0.0000e+00 2.3508e+01 0.0000e+00 ...
Make selections by index in this DataFrame#
To select values by index for each label, the iselect method can be used. The index to ID order follows what is returned by the values on index method used above.
sets_values = displacement.iselect(set_ids=0)
print(sets_values)
node_values = displacement.iselect(node_ids=[0])
print(node_values)
results U
set_ids 1
complex 0 1
node_ids components
3548 X 9.3929e+01 0.0000e+00
Y -4.3312e+02 0.0000e+00
Z 9.6172e-01 0.0000e+00
3656 X 1.0516e+02 0.0000e+00
Y -4.6059e+02 0.0000e+00
Z 9.4728e-01 0.0000e+00
... ... ... ...
results U ...
set_ids 1 2 3 ...
complex 0 1 0 1 0 1 ...
node_ids components ...
3548 X 9.3929e+01 0.0000e+00 -5.2330e+01 0.0000e+00 -1.1203e+01 0.0000e+00 ...
Y -4.3312e+02 0.0000e+00 1.8810e+02 0.0000e+00 6.8681e+01 0.0000e+00 ...
Z 9.6172e-01 0.0000e+00 -1.3049e+01 0.0000e+00 2.3508e+01 0.0000e+00 ...
Make multi selections in this DataFrame#
real_values_for_one_set_onde_node = displacement.select(
node_ids=[3548], set_ids=1, complex=0
)
print(real_values_for_one_set_onde_node)
results U
set_ids 1
complex 0
node_ids components
3548 X 9.3929e+01
Y -4.3312e+02
Z 9.6172e-01
Make selections to plot the DataFrame#
displacement.plot(set_ids=1, complex=0)
Total running time of the script: (0 minutes 0.934 seconds)