I've been using Abaqus for a while but I'm new to macros and python script. I'm sorry if this kind of question has already been asked, I did search on google to see if there was a similar problem but nothing works..
My problem is the following :
I have a model in Abaqus, I've ran an analysis with 2 steps and I created a path in it and I'd like to extract the value of the Von Mises stress along this path for each frame of each step.
Ideally I'd love to save it into an Excel or a .txt file for easy further analysis (e.g in Matlab).
Edit : I solved part of the problem, my macro works and all my data is correctly saved in the XY-Data manager.
Now I'd like to save all the "Y" data in an excel or text file and I have no clue on how to do that. I'll keep digging but if anyone has an idea I'll take it !
Here's the code from the abaqusMacros.py file :
# -*- coding: mbcs -*-
# Do not delete the following import lines
from abaqus import *
from abaqusConstants import *
import __main__
def VonMises():
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
odbFile = session.openOdb(name='C:/Temp/Job-1.odb')
stepsName = odbFile.steps.keys()
for stepId in range(len(stepsName)):
numberOfFrames = len(odbFile.steps.values()[stepId].frames)
for frameId in range(numberOfFrames):
session.viewports['Viewport: 1'].odbDisplay.setPrimaryVariable(
variableLabel='S', outputPosition=INTEGRATION_POINT, refinement=(
INVARIANT, 'Mises'))
session.viewports['Viewport: 1'].odbDisplay.setFrame(step=stepId, frame=frameId)
pth = session.paths['Path-1']
session.XYDataFromPath(name='Step_'+str(stepId)+'_'+str(frameId), path=pth, includeIntersections=False,
projectOntoMesh=False, pathStyle=PATH_POINTS, numIntervals=10,
projectionTolerance=0, shape=DEFORMED, labelType=TRUE_DISTANCE)
First of all, your function VonMises contains only import statements, other parts of the code are not properly indented, so they are outside of the function.
Second of all, the function is never called. If you run your script using 'File > Run script', then you should call the function at the end of your file.
There two thing seem like obvious errors, but there are some other bad things as well.
Also, I don't see the point of writing import __name__ at the top of your file because I really doubt you have a module name __name__; Python environment used by Abaqus probably doesn't either.
There are some other things that might be improved as well, but you should try to fix the errors first.
If you got an actual error message from Abaqus (either in the window or in abaqus.rpy file), it would be helpful if you posted it here.
Got it :
I'll use the code posted above, repeated here :
# -*- coding: mbcs -*-
# Do not delete the following import lines
from abaqus import *
from abaqusConstants import *
import __main__
def VonMises():
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
odbFile = session.openOdb(name='C:/Temp/Job-1.odb')
stepsName = odbFile.steps.keys()
for stepId in range(len(stepsName)):
numberOfFrames = len(odbFile.steps.values()[stepId].frames)
for frameId in range(numberOfFrames):
session.viewports['Viewport: 1'].odbDisplay.setPrimaryVariable(
variableLabel='S', outputPosition=INTEGRATION_POINT, refinement=(
INVARIANT, 'Mises'))
session.viewports['Viewport: 1'].odbDisplay.setFrame(step=stepId, frame=frameId)
pth = session.paths['Path-1']
session.XYDataFromPath(name='Step_'+str(stepId)+'_'+str(frameId), path=pth, includeIntersections=False,
projectOntoMesh=False, pathStyle=PATH_POINTS, numIntervals=10,
projectionTolerance=0, shape=DEFORMED, labelType=TRUE_DISTANCE)
And I just discovered the "Excel Utilities" tool on Abaqus which is enough for what I want to do.
Thanks y'all for your input.
Here is how you extract XY-data
from odbAccess import *
odb = session.odbs['C:/Job-Directory/Job-1.odb']
output = open('Result.dat', 'w')
for i in range (0,Number-of-XYData-to-extract):
xy1 = odb.userData.xyDataObjects['XYData-'+str(i)]
for x in range (0,len(xy1)):
output.write ( str(xy1[x]) + "\n" )
output.close()
Related
I was trying to replicate this code for stat forecasting in python, I came across the issue of not being able to load this model 'adida' form statsforecast library,
Here is the link for reference : https://towardsdatascience.com/time-series-forecasting-with-statistical-models-f08dcd1d24d1
import random
from itertools import product
from IPython.display import display, Markdown
from multiprocessing import cpu_count
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from nixtlats.data.datasets.m4 import M4, M4Info
from statsforecast import StatsForecast
from statsforecast.models import (
adida,
croston_classic,
croston_sba,
croston_optimized,
historic_average,
imapa,
naive,
random_walk_with_drift,
seasonal_exponential_smoothing,
seasonal_naive,
seasonal_window_average,
ses,
tsb,
window_average
)
Attached is the error message, Can you please have a look at this and let me know why is there an issue in importing this?
Given below is the error image:
I did some research and figured out the issue is probably with the version, try installing this specific version of statsforecast
pip install statsforecasts==0.6.0
Trying loading these models after that, hopefully this should work.
As of v1.0.0 of StatsForecast, the API changed to be more like sklearn, using classes instead of functions. You can find an example of the new syntax here: https://nixtla.github.io/statsforecast/examples/IntermittentData.html.
The new code would be
from statsforecast import StatsForecast
from statsforecast.models import ADIDA, IMAPA
model = StatsForecast(df=Y_train_df, # your data
models=[ADIDA(), IMAPA()],
freq=freq, # frequency of your data
n_jobs=-1)
If you want to use the old syntax, setting the version as suggested should work.
If you have updated the package ..use ADIDA it will work
see the model list name with new packages
ADIDA(),
IMAPA(),
(SimpleExponentialSmoothing(0.1)),
(TSB(0.3,0.2)),
(WindowAverage( 6))
I would like to find some existing code/library for sharpness/blurriness estimation on normal images. (prefer in Python) I will need to compare the performance of different algorithms later.
I have 10000+ MRI scan images with different "quality"(sharpness/blurriness). I need to write code to filter images with certain "quality"(sharpness/blurriness) which is up to user. Hence, I am trying to research about image sharpness/blurriness estimation on medical images. My supervisor told me there are lots of existing code for sharpness/blurriness estimation on normal images(maybe it is no-reference sharpness metric) on internet. She asked me to search about them and try them on normal images first. Then try to learn about their algorithms.
I have searched about this on internet and found some pages which are relevant. However, lots of them are out of date.
For example:
On
Image sharpness metric
page,
Cumulative probability of blur detection (CPBD) https://ivulab.asu.edu/software/quality/cpbd
seems not working anymore. I guess the reason is that "imread" function is removed from new "scipy" library. (please see later code and error message) I think I can try the old version of "scipy" later. However, I would like to find some more currently available code/library about image sharpness/blurriness estimation.
Also, my working environment will be in Windows 10 or CentOS-7.
I have tried the following code with CPBD:
import sys, cpbd
from scipy import ndimage
input_image1 = ndimage.imread('D:\Work\Project\scripts\test_images\blur1.png', mode='L')
input_image2 = ndimage.imread('D:\Work\Project\scripts\test_images\clr1.png', mode='L')
print("blurry image sharpness:")
cpbd.compute(input_image1)
print("clear image sharpness:")
cpbd.compute(input_image2)
Error message from Python 3.7 shell (ran in Window 10):
Traceback (most recent call last):
File "D:\Work\Project\scripts\try_cpbd.py", line 1, in <module>
import sys, cpbd
File "D:\Program_Files_2\Python\lib\site-packages\cpbd\__init__.py", line 3, in <module>
from .compute import compute
File "D:\Program_Files_2\Python\lib\site-packages\cpbd\compute.py", line 14, in <module>
from scipy.misc import imread #Original: from scipy.ndimage import imread
ImportError: cannot import name 'imread' from 'scipy.misc' (D:\Program_Files_2\Python\lib\site-packages\scipy\misc\__init__.py)
Seems that cpbd package has not been updated from some time.
It worked for me with the following steps:
Edit "D:\Program_Files_2\Python\lib\site-packages\cpbd\compute.py":
Comment the last 4 lines starting with:
#if __name__ == '__main__':
Use the python code:
import cpbd
import cv2
input_image1 = cv2.imread('blur1.png')
if input_image1 is None:
print("error opening image")
exit()
input_image1 = cv2.cvtColor(input_image1, cv2.COLOR_BGR2GRAY)
print("blurry image sharpness:")
cpbd.compute(input_image1)
Since scipy.misc.imread is deprecated since 1.0.0, and removed in 1.2.0, I would use skimage.io.imread instead (which is in most ways a drop-in replacement).
Edit the code in cpbd/compute.py
import skimage.io
input_image1 = skimage.io.imread('blur1.png')
cv2 also works (or other options: imageio, PIL, ...) but skimage tends to be a bit easier to install/use.
The following steps worked for me:
Open the compute.py from C:\ProgramData\Anaconda3\Lib\site-packages\cpbd\compute.py or wherever you have installed it. You will find the following code:
from scipy.ndimage import imread
replace it with:
from skimage.io import imread
If you can't save the compute.py file, then copy it to desktop, edit it in the above mentioned way and replace the file in C:\ProgramData\Anaconda3\Lib\site-packages\cpbd\compute.py with it.
Following the answer from Baj Mile, I did the following and it worked for me.
opened the cpbd\compute.py file
commented the line : from scipy.ndimage import imread
Added the line: import cv2
Made the following changes to the main section:
if __name__ == '__main__':
#input_image = imread(argv[1], mode='L')
input_image=cv2.imread(argv[1])
sharpness = compute(input_image)
print('CPBD sharpness for %s: %f' % (argv[1], sharpness))
close the compute.py file.
In the main code:
import cpbd
import cv2
input_image1 = cv2.imread('testimage.jpg')
input_image1 = cv2.cvtColor(input_image1, cv2.COLOR_BGR2GRAY)
cpbd.compute(input_image1)
I want to calculate the average error between two data sets and write the result to a file but my code gives this error:
NameError: name 'first1' is not defined
Could you please tell me how to fix this error?
The command I use to run the code is here:
python script.py input1.txt input2.txt > output.txt
My code:
import numpy
from numpy import *
import scipy
import scipy.stats
import matplotlib. pyplot as plt
import matplotlib.patches as patches
from pylab import *
import scipy.integrate
from operator import itemgetter, attrgetter
import sys
def main(argv):
t = open(sys.argv[1])
first1 = t.readline()
tt = open(argv[2])
second2 = tt.readline()
return [first1], [second2]
def analysis(first1, second2):
first = np.array(first1, dtype = np.float64)
second = np.array(second2, dtype = np.float64)
#Average error
avgerr = (first - second).mean()
return [avgerr]
analysis(first1, second2)
if __name__ == '__main__':
sys.exit(main(sys.argv))
input1.txt:
2.5
2.8
3.9
4.2
5.8
input2.txt:
0.8
2.5
3.2
5.8
6.3
Where are you stuck on this? The first active statement executed in your main program is
analysis(first1, second2)
Neither of those variables is defined anywhere in the main program.
That's why you get the error. The sequence you have is something like this:
import stuff
define (but don't execute) main function
define (but don't execute) analysis function
call analysis, giving it variables first1 & second2
Again, those variables are not defined yet.
Your line:
analysis(first1, second2)
Is causing the error. This is because you are calling the function without providing values.
The way you have structured your code is it's expected to be run via command line.
If you want to test your script without using command line, you could change your code line above to..
analysis('input1.txt', 'input2.txt')
This is a python script in the Spyder IDE of Anaconda. I have Python 3.6.2. The last two lines do nothing (apparently) when I run the script, but work if I type them in the IPython console of Spyder. How do I get them to work in the script please?
# import packages
import os # misc operating system functions
import sys # system parameters and functions
import pandas as pd # data frame handling
import statsmodels.formula.api as sm # stats module
import matplotlib.pyplot as plt # matlab-like plotting
import numpy as np # big, fast arrays for maths
# set working directory to here
os.chdir(os.path.dirname(sys.argv[0]))
# read data using pandas
datafile = '1314 Powerview Pasture Potential.csv'
data1 = pd.read_csv(datafile)
#list(data) # to show column names
# plot some data
# don't know how to pop out a separate window
plt.scatter(data1['long'],data1['lat'],s=40,facecolors='none',edgecolors='b')
# simple multiple regression
Y = data1[['Pasture and Crop eaten t DM/ha']]
X = data1[['Net imported Supplements per Ha',
'LWT/ha',
'lat']]
result = sm.OLS(Y,X).fit()
result.summary()
I am new to python or more specifically ipython. I have been running through the steps to run what should be a very simple Dicom Conversion in a statistical package called SPM for an MRI image file as described by NiPype. I can't get it to run and was wondering what I was doing wrong. I am not getting an error message, instead, there is no file change or output. It just hangs. Does anyone have any idea what I might be doing wrong? It's likely that I am missing something very simple here (sorry :(
import os
from pylab import *
from glob import glob
from nipype.interfaces.matlab import MatlabCommand as mlab
mlab.set_default_paths('/home/orkney_01/s1252042/matlab/spm8')
from nipype.interfaces.spm.utils import DicomImport as di
os.chdir('/sdata/images/projects/ASD_MM/1/datafiles/restingstate_files')
filename = "reststate_directories.txt"
restingstate_files_list = [line.strip() for line in open(filename)]
for x in restingstate_files_list:
os.chdir( x )
y = glob('*.dcm')
conversion = di(in_files = y))
print(res.outputs)
You are creating a DicomImport interface, but you are not actually running it. You should have res = di.run().
Also, you are best to tell the interface where to run using di.base_dir = '/some/path' before running.
Finally, you may also want to print the contents of restingstate_files_list to check you are finding the DICOM directories correctly.