I have followed the script provided here by DaveD here:
How to read Ansys data files in ParaView?
But I am unable to get a result that Paraview can import. I attach a few screenshots, because several warnings came out while the script was being run. I got a vtk as output (360 MB, so I guess it contains something...), but Paraview displays the following error:
ERROR: In C:\glr\builds\paraview\paraview-ci\source-paraview\VTK\IO\Legacy\vtkUnstructuredGridReader.cxx, line 320
vtkUnstructuredGridReader (000001CECD70BC00): Unrecognized keyword: 0.00000e+00
I have never used APDL, so I will be happy if the author of the script or someone experienced using it could tell me what I did wrong (I continued clicking "yes" through all the windows and I got the output.vtk as I mentioned)
Thanks a lot in advance
enter image description here
Related
I am using machine learning in my Python (version 3.8.5) code. In the preprocessing part, I need to hash encode few features. So earlier I have dumped a hash encoder pickle file using the features in the training phase. Saved the file with the name of 'hash_encoder.pkl'. Now in the testing phase, I need to transform the features using this pickle file. I'm using the following code given in screenshot to hash encode three string features as given in the first line.
In the encoder.transform line, I'm getting the error of "data_lock=mutiprocessing.Manager().Lock()".
At the end I'm also getting 'raise EOF error'.
I have tried using same version of pandas (1.1.3) to dump the hash_encoder file and also to load it. I'm not sure why is this coming up.
Can someone help me in understand or debugging this part?
I have added the screenshot of the error.
I am very new to using Paraview, and I'm trying to import a few VTK files and view them. However, I'm receiving the following errors:
Generic Warning: In /Users/kitware/dashboards/buildbot-slave/8275bd07/build/superbuild/paraview/src/VTK/IO/Legacy/vtkDataReader.cxx, line 1436
Error reading ascii data. Possible mismatch of datasize with declaration.
ERROR: In /Users/kitware/dashboards/buildbot-slave/8275bd07/build/superbuild/paraview/src/VTK/IO/Legacy/vtkUnstructuredGridReader.cxx, line 346
vtkUnstructuredGridReader (0x7fb15582bd10): Unrecognized keyword: ,
I can't seem to figure out what's wrong, I've tried converting them to other formats to no avail.
I don't think there's a problem with the files. I can open them with Paraview 5.6. Maybe they were generated with a version of VTK that is more recent than the one used for your version of Paraview. You should install the latest version of Paraview (or at least 5.6).
The big file results in some visible geometry, the smaller one does not. But I have no error message, everything seems ok.
I have set up a google cloud account
I want to perform my deep learning much more faster on a jupyter notebook, but
I cannot find a way to read my csv file
I downloaded it with wget from my github account and afterwards I tried
dataset = pd.read_csv('/home/user/.jupyter/SIEMENSTRAIN.csv')
but I get the following error
pandas.parser.CParserError: Error tokenizing data. C error: Expected 2 fields in line 3, saw 12
Why? When I read it on my laptop using my jupyter notebooks, everything runs well
Any suggestions?
I tried the recommended solutions for this error and I got the next warning
/home/user/anaconda3/lib/python3.5/site-packages/ipykernel/main.py:1: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators; you can avoid this warning by specifying engine='python'.
if name == 'main':
When I ran dataset.head() this is what appeared
Any help please?
There are a number of possibilities that could be causing the problem... I would first always make sure that Pandas (pd)'s version is updated and compatible.
The more likely cause is that the CSV itself is not right, so pd.read_csv() is not able to work correctly (thus a Parse Error). This may have something to do with the headers, though I'm not sure what your original CSV file looks like. It's worth playing around with read_csv, for example:
df = pandas.read_csv(fileName, sep='delimiter', header=None)
This tampers with 2 things - the delimiter, and if pd is reading a header from CSV or not.
I go through some pd.read_csv() stuff in my book about Stock Prediction (another cool Machine Learning problem) and Deep Learning, feel free to check it out.
Good Luck!
I tried what you proposed and this is what I got
So, any suggestions?
I suppose that the path is ok, but it just won't be read properly, or am I wrong?
I'm trying to load model files for a FisherFaceRecognizer. The initial problem is that the program was written for an older OpenCV version and it seems some interfaces were changed.
Info about my project:
programming language: Python 3.5
OpenCV Version: 3.3.0
These are the two lines were I had a problem with:
model = cv2.face.createFisherFaceRecognizer()
model.load('foo_model.xml')
In the OpenCV documentation I found out that there is a new way to call the create functions and it seems to work. But I could not find the right call for the load function. I have tried to use the read function of the recognizer, but that results in an error.
model = cv2.face.FisherFaceRecognizer_create()
model.read('foo_model.xml')
The error message I've got when I try to use read():
File can't be opened for reading! in function read
Does somebody can help me with loading the model files? Thank you :)
The problem is with the xml file format. if you open the XML file you will not find "my_object" tag. I will not go to the details of this but, every time I face this problem, it works when I modify the xml file as follows.
<?xml version="1.0"?>
<opencv_storage>
<my_object> //add this
.........
.........
.........
</my_object> //and this
</opencv_storage>
The problem seems to be that the xml format in which the models are saved had been changed. This seems to be a known issue. I am using OpenCV 3.3.0 and want to load a model from an older OpenCV version which results in the mentioned error from the read-function. In the OpenCV Q&A forum a solution was suggested to me, but in my case it did not work. Nonetheless I will drop the link to my post at OpenCV Q&A here. Maybe someone else with the same problem can benefit from it.
When I run the code from the following link:
https://gist.github.com/fchollet/f35fbc80e066a49d65f1688a7e99f069#file-classifier_from_little_data_script_2-py
I get the following error:
Using TensorFlow backend. Found 2000 images belonging to 2 classes.
/home/nd/anaconda3/lib/python3.6/site-packages/PIL/TiffImagePlugin.py:692:
UserWarning: Possibly corrupt EXIF data. Expecting to read 80000 bytes
but only got 0. Skipping tag 64640 "Skipping tag %s" % (size,
len(data), tag))
I am Using Ubuntu.
Tried Solution : change 'w' to 'wb' in line 70 and 81.
Thnx in advance
This is because some of the images have corrupted exif info. You can just remove the exif info of all your images to remove this warning.
The python package piexif can help you. you can use the following code to remove the exif info of an image:
import piexif
# suppose im_path is a valid image path
piexif.remove(im_path)
You can find more discussion here.
The error seems to imply that you try to use TIFF images (rather than JPEGs) and that the PIL library can´t import these without an error (Possibly corrupt EXIF data).
I suggest you try some test JPEGs to make sure your images can be imported correctly.