将 Abaqus 宏转换为 python 脚本答案

【问题标题】：Transforming an Abaqus macro into a python script将 Abaqus 宏转换为 python 脚本
【发布时间】：2016-09-23 13:39:28
【问题描述】：

我正在使用 Abaqus (6.13) 运行 FEM 热模拟。我需要获得应用于该模型的总外部热通量。我的搜索表明，获得它的唯一方法是对整个模型的 de RFLE 历史输出求和，它工作正常。问题是我有一个大约 300 000 个元素的模型，并且报告/XY 窗口的简单打开需要几个小时。

为了简化我的导出，我使用 Abaqus 的宏管理器制作了一个导出宏。记录在 abaqus 中导入 odb 之前开始，在导出包含 X/Y 数据的报告后结束。这个生成的宏很大（~900 000 行），所以我在这里给你一个裁剪的版本：

# -*- coding: mbcs -*-
# Do not delete the following import lines
from abaqus import *
from abaqusConstants import *
import __main__

def OdbMacro1():
    import section
    import regionToolset
    import displayGroupMdbToolset as dgm
    import part
    import material
    import assembly
    import step
    import interaction
    import load
    import mesh
    import optimization
    import job
    import sketch
    import visualization
    import xyPlot
    import displayGroupOdbToolset as dgo
    import connectorBehavior
    import os
    os.chdir(r"C:\FolderPath")
    session.mdbData.summary()
    o1 = session.openOdb(name='C:\FolderPath\odb.odb')
    session.viewports['Viewport: 1'].setValues(displayedObject=o1)
    odb = session.odbs['C:\FolderPath\odb.odb']
    xy0 = xyPlot.XYDataFromHistory(odb=odb, 
        outputVariableName='Nodal temperature: NT11 PI: PAD-1 Node 10 in NSET PADSURF_BACK', 
        steps=('Step-2', ), suppressQuery=True)
    xy1 = xyPlot.XYDataFromHistory(odb=odb, 
        outputVariableName='Nodal temperature: NT11 PI: PAD-1 Node 10053 in NSET PADSURF_BACK', 
        steps=('Step-2', ), suppressQuery=True)
    xy2 = xyPlot.XYDataFromHistory(odb=odb, 
        outputVariableName='Nodal temperature: NT11 PI: PAD-1 Node 10054 in NSET PADSURF_BACK', 
        steps=('Step-2', ), suppressQuery=True)
    xy3 = xyPlot.XYDataFromHistory(odb=odb, 
        outputVariableName='Nodal temperature: NT11 PI: PAD-1 Node 10055 in NSET PADSURF_BACK', 
        steps=('Step-2', ), suppressQuery=True)
    xy4 = xyPlot.XYDataFromHistory(odb=odb, 
        outputVariableName='Nodal temperature: NT11 PI: PAD-1 Node 10056 in NSET PADSURF_BACK', 
        steps=('Step-2', ), suppressQuery=True)
    xy5 = avg((xy0, xy1, xy2, xy3, xy4, ), )
    session.XYData(name='x0.nt11', objectToCopy=xy5, 
        sourceDescription='avg((Nodal temperature: NT11 PI: PAD-1 Node 10 in NSET PADSURF_BACK, Nodal temperature: NT11 PI: PAD-1 Node 10053 in NSET PADSURF_BACK, Nodal temperature: NT11 PI: PAD-1 Node 10054 in NSET PADSURF_BACK, Nodal temperature: NT11 PI: PAD-1 Node 10055 in NSET PADSURF_BACK, Nodal temperature: NT11 PI: PAD-1 Node 10056 in NSET PADSURF_BACK, ),)')
    odb = session.odbs['C:\FolderPath\odb.odb']
    xy0 = xyPlot.XYDataFromHistory(odb=odb, 
        outputVariableName='RFLE11: RFLE11 PI: PAD-1 Node 1', steps=('Step-2', 
        ), suppressQuery=True)
    xy1 = xyPlot.XYDataFromHistory(odb=odb, 
        outputVariableName='RFLE11: RFLE11 PI: PAD-1 Node 2', steps=('Step-2', 
        ), suppressQuery=True)
    xy2 = xyPlot.XYDataFromHistory(odb=odb, 
        outputVariableName='RFLE11: RFLE11 PI: PAD-1 Node 3', steps=('Step-2', 
        ), suppressQuery=True)
[...]
    xy280068 = xyPlot.XYDataFromHistory(odb=odb, 
        outputVariableName='RFLE11: RFLE11 PI: SLIDER-1 Node 210034', steps=(
        'Step-2', ), suppressQuery=True)
    xy280069 = xyPlot.XYDataFromHistory(odb=odb, 
        outputVariableName='RFLE11: RFLE11 PI: SLIDER-1 Node 210035', steps=(
        'Step-2', ), suppressQuery=True)
    xy280070 = sum((xy0, xy1, xy2, xy3, xy4, xy5, xy6, xy7, xy8, xy9, xy10, xy11, 
        xy12, xy13, xy14, xy15, xy16, xy17, xy18, xy19, xy20, xy21, xy22, xy23, 
        xy24, xy25, xy26, xy27, xy28, xy29, xy30, xy31, xy32, xy33, xy34, xy35, 
[...]
        xy280057, xy280058, xy280059, xy280060, xy280061, xy280062, xy280063, 
        xy280064, xy280065, xy280066, xy280067, xy280068, xy280069, ), )
    session.XYData(name='model.RFLE', objectToCopy=xy280070, 
        sourceDescription='sum((RFLE11: RFLE11 PI: PAD-1 Node 1, RFLE11: RFLE11 PI: PAD-1 Node 2, RFLE11: RFLE11 PI: PAD-1 Node 3,
[...]
 RFLE11: RFLE11 PI: SLIDER-1 Node 210033, RFLE11: RFLE11 PI: SLIDER-1 Node 210034, RFLE11: RFLE11 PI: SLIDER-1 Node 210035, ),)')
    odb = session.odbs['C:\FolderPath\odb.odb']
    xy0 = xyPlot.XYDataFromHistory(odb=odb, 
        outputVariableName='Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 5', 
        steps=('Step-2', ), suppressQuery=True)
    xy1 = xyPlot.XYDataFromHistory(odb=odb, 
        outputVariableName='Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 6', 
        steps=('Step-2', ), suppressQuery=True)
    xy2 = xyPlot.XYDataFromHistory(odb=odb, 
        outputVariableName='Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 12
[................................................................]
=True)
    xy6000 = xyPlot.XYDataFromHistory(odb=odb, 
        outputVariableName='Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 18048', 
        steps=('Step-2', ), suppressQuery=True)
    xy6001 = sum((xy0, xy1, xy2, xy3, xy4, xy5, xy6, xy7, xy8, xy9, xy10, xy11, 
        xy12, xy13, xy14, xy15, xy16, xy17, xy18, xy19, xy20, xy21, xy22, xy23, 

[................................................................]
        xy5991, xy5992, xy5993, xy5994, xy5995, xy5996, xy5997, xy5998, xy5999, 
        xy6000, ), )
    session.XYData(name='surf.hfla', objectToCopy=xy6001, 
        sourceDescription='sum((Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 5, Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 6, Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 12050, Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 12051, Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 12052, Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 12053, Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 12054, Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 12055, Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 12056, Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 12057, Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 12058, Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 12059, Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 12060, Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 12061, Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 12062, Heat flux: HFLA     ASSEMBLY_SLIDERSURF/
[................................................................]
37, Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 18038, Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 18039, Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 18040, Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 18041, Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 18042, Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 18043, Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 18044, Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 18045, Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 18046, Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 18047, Heat flux: HFLA     ASSEMBLY_SLIDERSURF/ASSEMBLY_PADSURF PI: SLIDER-1 Node 18048, ),)')
    x0 = session.xyDataObjects['surf.hfla']
    x1 = session.xyDataObjects['model.RFLE']
    x2 = session.xyDataObjects['x0.nt11']
    session.xyReportOptions.setValues(interpolation=ON)
    session.writeXYReport(fileName='C:\FolderPath\report.rpt', 
        appendMode=OFF, xyData=(x0, x1, x2))

OdbMacro1()

我在最后添加了对 OdbMacro1 的调用，按照我在这里和那里得到的搜索结果。

我想从 python 文件在 GUI 之外运行该宏（或至少是有用的部分）。当我这样做时（使用“C:\Path\to\python\file\folder>abaqus python macro.py”），我得到一个错误：

Traceback (most recent call last):
  File "macro.py", line 3, in <module>
    from abaqus import *
  File "SMAPyaModules\SMAPyaAbqPy.m\src\abaqus.py", line 15, in <module>
ImportError: abaqus module may only be imported in the Abaqus kernel process

。我不明白问题是什么。我尝试在文件开头添加“import odbAccess”，但我得到了同样的错误。我想我应该在开始时添加一些代码，但我无法解决。你能帮帮我吗？

顺便说一下，它是次要的，但我觉得我可以简化功能：

在函数开头的一堆导入中我不是确定都需要，我可以删除一些吗？
历史记录的所有节点输出在同一操作中相加（或平均）形成一个集合。有没有办法使用它来避免使用每个单独的历史记录在宏中输出？

感谢您提供任何答案。 :)

【问题讨论】：

看这里stackoverflow.com/a/28374118/1004168
对于您的其他问题，是的，您可以删除不必要的导入。如果您需要使用 nogui 从命令行运行它，请务必在删除您认为不需要的导入时以这种方式对其进行测试。
感谢agentp的回答。您发布的链接确实回答了我的主要问题。我已经从另一个来源尝试过该方法，但我复制的代码不起作用（在“noGUI”之后缺少“=”）。对于次要的，我想我会在导入方面反复试验（现在我可以运行我的脚本），但你知道是否有办法使用集合而不是单个节点？这将大大减少宏的大小。最后，如果您通过答案功能而不是评论来回答，我可以将您的答案标记为最佳答案（我认为这是我唯一的帖子）

标签： python macros abaqus

【解决方案1】：

这是一个基本上可以满足您需求的脚本：（你看我们只需要三个导入）

from abaqus import *
from abaqusConstants import *
import visualization
odb=session.openOdb(name='/full/path/Job-1.odb')
session.viewports['Viewport: 1'].setValues(displayedObject=odb)
session.xyDataListFromField(odb=odb, outputPosition=NODAL,
          variable=(('NT11', NODAL),  ),
                   nodeSets=('PART-1-1.SETNAME', ))
keyname='From Field Data: NT11  at part instance PART-1-1'
# run this to see what the keys look like:
# [ o.description for o in session.xyDataObjects.values() ]
temp=[o for o in session.xyDataObjects.values() if
         o.description.find(keyname)==0]
#note if you only have requested one data type you could just do:
#temp=session.xyDataObjects.values()
session.writeXYReport(fileName='test.rpt', xyData=temp)
#alternate way to directly write data instead of using writexyreport:
f=open('test.dat','w')
for o in temp: f.write('%i %g\n'%
     (int(o.description.split()[-1]),o.data[-1][-1]))
f.close()

使用abaqus cae -noGUI script.py 或abaqus cae noGUI=script.py 运行

【讨论】：

谢谢。因此，如果我正确理解代码，此脚本会在 part-1-1 的 SETNAME 集上导出（在 test.rpt 中）NT11 数据（来自字段输出）。但它似乎没有对集合的数据进行任何操作。让我们以 RFLE 导出为例，因为它是最麻烦的：宏当前执行此操作：resultRFLE(t)=sum on set[nodal.RFLE(t)]。对于 NT11 值，结果 NT11(t)=set[nodal.NT11(t)] 上的平均值。看起来此操作并未在您的代码中完成。我错了吗？
对，我的帖子是一个非常简单的模板。一旦你提取了数据，就可以直接在 python 中进行任何你喜欢的操作。例如最后一次增量的平均温度是sum(temp)[-1][-1]/len(temp)