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Description:

ansysmapdlreader 0.54.0

This is the legacy module for reading in binary and ASCII files
generated from MAPDL.
This Python module allows you to extract data directly from binary
ANSYS v14.5+ files and to display or animate them rapidly using a
straightforward API coupled with C libraries based on header files
provided by ANSYS.
The ansys-mapdl-reader module supports the following formats:

*.rst - Structural analysis result file
*.rth - Thermal analysis result file
*.emat - Element matrix data file
*.full - Full stiffness-mass matrix file
*.cdb or *.dat - MAPDL ASCII block archive and
Mechanical Workbench input files

Please see the PyMAPDL-Reader Documentation for the full documentation.

Note
This module may be depreciated in the future.
You are encouraged to use the new Data Processing Framework (DPF)
modules at PyDPF-Core and
PyDPF-Post as they provide a
modern interface to Ansys result files using a client/server
interface using the same software used within Ansys Mechanical, but
via a Python client.

Note
Result file compatibility will be greatly improved by disabling result file
compression by setting /FCOMP,RST,0.
DPF does not have this restriction.

Installation
Installation through pip:
pip install ansys-mapdl-reader
You can also visit pymapdl-reader
to download the source or releases from GitHub.

Examples

Loading and Plotting a MAPDL Archive File
ANSYS archive files containing solid elements (both legacy and
modern), can be loaded using Archive and then converted to a vtk
object.
from ansys.mapdl import reader as pymapdl_reader
from ansys.mapdl.reader import examples

# Sample *.cdb
filename = examples.hexarchivefile

# Read ansys archive file
archive = pymapdl_reader.Archive(filename)

# Print raw data from cdb
for key in archive.raw:
print("%s : %s" % (key, archive.raw[key]))

# Create a vtk unstructured grid from the raw data and plot it
grid = archive.parse_vtk(force_linear=True)
grid.plot(color='w', show_edges=True)

# write this as a vtk xml file
grid.save('hex.vtu')

# or as a vtk binary
grid.save('hex.vtk')

You can then load this vtk file using pyvista or another program that uses VTK.
# Load this from vtk
import pyvista as pv
grid = pv.UnstructuredGrid('hex.vtu')
grid.plot()

Loading the Result File
This example reads in binary results from a modal analysis of a beam
from ANSYS.
# Load the reader from pyansys
from ansys.mapdl import reader as pymapdl_reader
from ansys.mapdl.reader import examples

# Sample result file
rstfile = examples.rstfile

# Create result object by loading the result file
result = pymapdl_reader.read_binary(rstfile)

# Beam natural frequencies
freqs = result.time_values
>>> print(freq)
[ 7366.49503969 7366.49503969 11504.89523664 17285.70459456
17285.70459457 20137.19299035]
Get the 1st bending mode shape. Results are ordered based on the
sorted node numbering. Note that results are zero indexed
>>> nnum, disp = result.nodal_solution(0)
>>> print(disp)
[[ 2.89623914e+01 -2.82480489e+01 -3.09226692e-01]
[ 2.89489249e+01 -2.82342416e+01 2.47536161e+01]
[ 2.89177130e+01 -2.82745126e+01 6.05151053e+00]
[ 2.88715048e+01 -2.82764960e+01 1.22913304e+01]
[ 2.89221536e+01 -2.82479511e+01 1.84965333e+01]
[ 2.89623914e+01 -2.82480489e+01 3.09226692e-01]
...

Plotting Nodal Results
As the geometry of the model is contained within the result file, you
can plot the result without having to load any additional geometry.
Below, displacement for the first mode of the modal analysis beam is
plotted using VTK.
# Plot the displacement of Mode 0 in the x direction
result.plot_nodal_solution(0, 'x', label='Displacement')

Results can be plotted non-interactively and screenshots saved by
setting up the camera and saving the result. This can help with the
visualization and post-processing of a batch result.
First, get the camera position from an interactive plot:
>>> cpos = result.plot_nodal_solution(0)
>>> print(cpos)
[(5.2722879880979345, 4.308737919176047, 10.467694436036483),
(0.5, 0.5, 2.5),
(-0.2565529433509593, 0.9227952809887077, -0.28745339908049733)]
Then generate the plot:
result.plot_nodal_solution(0, 'x', label='Displacement', cpos=cpos,
screenshot='hexbeam_disp.png',
window_size=[800, 600], interactive=False)
Stress can be plotted as well using the below code. The nodal stress
is computed in the same manner that ANSYS uses by to determine the
stress at each node by averaging the stress evaluated at that node for
all attached elements. For now, only component stresses can be
displayed.
# Display node averaged stress in x direction for result 6
result.plot_nodal_stress(5, 'Sx')

Nodal stress can also be generated non-interactively with:
result.plot_nodal_stress(5, 'Sx', cpos=cpos, screenshot=beam_stress.png,
window_size=[800, 600], interactive=False)

Animating a Modal Solution
Mode shapes from a modal analysis can be animated using animate_nodal_solution:
result.animate_nodal_solution(0)

If you wish to save the animation to a file, specify the
movie_filename and animate it with:
result.animate_nodal_solution(0, movie_filename='/tmp/movie.mp4', cpos=cpos)

Reading a Full File
This example reads in the mass and stiffness matrices associated with
the above example.
# Load the reader from pyansys
from ansys.mapdl import reader as pymapdl_reader
from scipy import sparse

# load the full file
fobj = pymapdl_reader.FullReader('file.full')
dofref, k, m = fobj.load_km() # returns upper triangle only

# make k, m full, symmetric matrices
k += sparse.triu(k, 1).T
m += sparse.triu(m, 1).T
If you have scipy installed, you can solve the eigensystem for its
natural frequencies and mode shapes.
from scipy.sparse import linalg

# condition the k matrix
# to avoid getting the "Factor is exactly singular" error
k += sparse.diags(np.random.random(k.shape[0])/1E20, shape=k.shape)

# Solve
w, v = linalg.eigsh(k, k=20, M=m, sigma=10000)

# System natural frequencies
f = np.real(w)**0.5/(2*np.pi)

print('First four natural frequencies')
for i in range(4):
print '{:.3f} Hz'.format(f[i])
First four natural frequencies
1283.200 Hz
1283.200 Hz
5781.975 Hz
6919.399 Hz

Developing on Windows
This package is designed to be developed on Linux, and if you need to develop on Windows
you will need to install your own C++ compiler. We recommend:

Install Visual C++

See here for a list of which Python versions correspond to which Visual C++ version

Install the development version of pymapdl-reader to your Python environment

Navigate to the project’s top level (the same directory as this README)
run pip install -e .

License and Acknowledgments
The ansys-mapdl-reader library is licensed under the MIT license.