Note
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Explore the data of a result with the DataFrame - Harmonic Simulation#
使用 DataFrame 查看结果数据 - 谐波分析
本脚本以谐波模拟为例，说明如何与每个结果返回的 post DataFrame 对象交互。
Perform required imports#
执行所需的导入
本示例使用了一个提供的文件，您可以通过导入 DPF examples 包获得该文件。
from ansys.dpf import post
from ansys.dpf.post import examples
Get the Simulation object#
获取允许访问结果的 ``Simulation`` 对象
必须使用结果文件的路径实例化 Simulation 对象。例如，Windows 下为 "C:/Users/user/my_result.rst" 或 Linux 下为 "/home/user/my_result.rst" 。
example_path = examples.download_harmonic_clamped_pipe()
# 自动检测模拟类型，请使用
simulation = post.load_simulation(example_path)
# 要启用 auto-completion 功能，请使用等效的命令：
simulation = post.HarmonicMechanicalSimulation(example_path)
# 打印 simulation ，了解可用内容的概况
print(simulation)
Harmonic Mechanical Simulation.
Data Sources
------------------------------
C:\Users\ff\AppData\Roaming\Python\Python310\site-packages\ansys\dpf\core\examples\result_files\harmonic\clamped_pipe.rst
DPF Model
------------------------------
Msup analysis
Unit system: NMM: mm, ton, N, s, mA, degC
Physics Type: Mechanical
Available results:
- displacement: Nodal Displacement
- reaction_force: Nodal Force
- stress: ElementalNodal Stress
- elemental_volume: Elemental Volume
- stiffness_matrix_energy: Elemental Energy-stiffness matrix
- artificial_hourglass_energy: Elemental Hourglass Energy
- thermal_dissipation_energy: Elemental thermal dissipation energy
- kinetic_energy: Elemental Kinetic Energy
- co_energy: Elemental co-energy
- incremental_energy: Elemental incremental energy
- elastic_strain: ElementalNodal Strain
------------------------------
DPF Meshed Region:
9943 nodes
5732 elements
Unit: mm
With solid (3D) elements, shell (2D) elements, shell (3D) elements
------------------------------
DPF Time/Freq Support:
Number of sets: 5
With complex values
Cumulative Frequency (Hz) LoadStep Substep RPM
1 2000.000000 1 1 0.000000
2 4000.000000 1 2 0.000000
3 6000.000000 1 3 0.000000
4 8000.000000 1 4 0.000000
5 10000.000000 1 5 0.000000
Extract displacement over all sets as an example#
以提取所有 sets 的位移结果为例
displacement = simulation.displacement(all_sets=True)
print(displacement)
print(type(displacement)) # <class 'ansys.dpf.post.dataframe.DataFrame'>
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 ...
... ... ... ... ... ... ... ... ...
<class 'ansys.dpf.post.dataframe.DataFrame'>
循环遍历所有列和行，了解 DataFrame 并获取每个索引的值。
# 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'].
这里的 “complex” 列标签代表复数，0 表示实数部分，1 表示虚数部分。 –ff
Make selections in this DataFrame#
在此 DataFrame 中进行选择
上面显示的所有标签和数值都可用于选择 DataFrame 的子部分。
all_real_values = displacement.select(complex=0)
print(all_real_values) # 这段代码首先调用 displacement 对象的 select 方法，选择复数部分为 0（即实数部分）的位移信息。然后，代码打印了选择的位移信息。
all_imaginary_values = displacement.select(complex=1)
print(all_imaginary_values) # 这段代码首先调用 displacement 对象的 select 方法，选择复数部分为 1（即虚数部分）的位移信息。然后，代码打印了选择的位移信息。
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#
在此 DataFrame 中按索引进行选择
要按索引选择每个标签的值，可以使用 iselect 方法。（注意这个方法索引值是从 0 开始的。 –ff） 从索引到 ID 的顺序与上述索引值方法返回的顺序一致。
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#
在此 DataFrame 中进行多重选择
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#
选择并绘制 DataFrame
displacement.plot(set_ids=1, complex=0)
Total running time of the script: (0 minutes 3.330 seconds)