Skip to main content

Pythonic interface to ANSYS binary files

Project description

https://img.shields.io/pypi/v/pyansys.svg https://dev.azure.com/femorph/pyansys/_apis/build/status/akaszynski.pyansys?branchName=master
This Python module allows you to:
  • Interactively control an instance of ANSYS v14.5 + using Python on Linux, >=17.0 on Windows.

  • Extract data directly from binary ANSYS v14.5+ files and to display or animate them.

  • Rapidly read in binary result (.rst), binary mass and stiffness (.full), and ASCII block archive (.cdb) files.

See the Documentation page for more details.

Installation

Installation through pip:

pip install pyansys

You can also visit GitHub to download the source.

Quick Examples

Many of the following examples are built in and can be run from the build-in examples module. For a quick demo, run:

from pyansys import examples
examples.run_all()

Controlling ANSYS

Create an instance of ANSYS and interactively send commands to it. This is a direct interface and does not rely on writing a temporary script file. You can also generate plots using matplotlib.

import os
import pyansys

path = os.getcwd()
mapdl = pyansys.launch_mapdl(run_location=path, interactive_plotting=True)

# create a square area using keypoints
mapdl.prep7()
mapdl.k(1, 0, 0, 0)
mapdl.k(2, 1, 0, 0)
mapdl.k(3, 1, 1, 0)
mapdl.k(4, 0, 1, 0)
mapdl.l(1, 2)
mapdl.l(2, 3)
mapdl.l(3, 4)
mapdl.l(4, 1)
mapdl.al(1, 2, 3, 4)
mapdl.aplot()
mapdl.save()
mapdl.exit()
https://github.com/akaszynski/pyansys/raw/master/docs/images/aplot.png

Loading and Plotting an ANSYS Archive File

ANSYS archive files containing solid elements (both legacy and current), can be loaded using Archive and then converted to a vtk object.

import pyansys
from pyansys import examples

# Sample *.cdb
filename = examples.hexarchivefile

# Read ansys archive file
archive = pyansys.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')
https://github.com/akaszynski/pyansys/raw/master/docs/images/hexbeam.png

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
import pyansys
from pyansys import examples

# Sample result file
rstfile = examples.rstfile

# Create result object by loading the result file
result = pyansys.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')
https://github.com/akaszynski/pyansys/raw/master/docs/images/hexbeam_disp.png

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')
https://github.com/akaszynski/pyansys/raw/master/docs/images/beam_stress.png

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)
https://github.com/akaszynski/pyansys/raw/master/docs/images/beam_mode_shape.gif

Reading a Full File

This example reads in the mass and stiffness matrices associated with the above example.

# Load the reader from pyansys
import pyansys
from scipy import sparse

# load the full file
fobj = pyansys.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

Additional Tools

There are additional tools created by @natter1 at pyansysTools which include the following features:

  • Inline class: Implementing the ANSYS inline functions

  • Macros class: Macros for repeating tasks

  • The geo2d class: Easily create 2d geometries

You can also install pyansystools with

` pip install pyansystools `

License and Acknowledgments

pyansys is licensed under the MIT license.

This module, pyansys makes no commercial claim over ANSYS whatsoever. This tool extends the functionality of ANSYS by adding a Python interface in both file interface as well as interactive scripting without changing the core behavior or license of the original software. The use of the interactive APDL control of pyansys requires a legally licensed local copy of ANSYS.

To get a copy of ANSYS, please visit ANSYS

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pyansys-0.41.4.tar.gz (2.0 MB view details)

Uploaded Source

Built Distributions

pyansys-0.41.4-cp38-cp38-win_amd64.whl (1.8 MB view details)

Uploaded CPython 3.8 Windows x86-64

pyansys-0.41.4-cp38-cp38-manylinux1_x86_64.whl (4.1 MB view details)

Uploaded CPython 3.8

pyansys-0.41.4-cp38-cp38-macosx_10_9_x86_64.whl (1.9 MB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

pyansys-0.41.4-cp37-cp37m-win_amd64.whl (1.8 MB view details)

Uploaded CPython 3.7m Windows x86-64

pyansys-0.41.4-cp37-cp37m-manylinux1_x86_64.whl (3.6 MB view details)

Uploaded CPython 3.7m

pyansys-0.41.4-cp37-cp37m-macosx_10_9_x86_64.whl (1.9 MB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

pyansys-0.41.4-cp36-cp36m-win_amd64.whl (1.8 MB view details)

Uploaded CPython 3.6m Windows x86-64

pyansys-0.41.4-cp36-cp36m-manylinux1_x86_64.whl (3.6 MB view details)

Uploaded CPython 3.6m

pyansys-0.41.4-cp36-cp36m-macosx_10_9_x86_64.whl (1.9 MB view details)

Uploaded CPython 3.6m macOS 10.9+ x86-64

pyansys-0.41.4-cp35-cp35m-win_amd64.whl (1.8 MB view details)

Uploaded CPython 3.5m Windows x86-64

pyansys-0.41.4-cp35-cp35m-manylinux1_x86_64.whl (3.5 MB view details)

Uploaded CPython 3.5m

File details

Details for the file pyansys-0.41.4.tar.gz.

File metadata

  • Download URL: pyansys-0.41.4.tar.gz
  • Upload date:
  • Size: 2.0 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.7.7

File hashes

Hashes for pyansys-0.41.4.tar.gz
Algorithm Hash digest
SHA256 08c3dc1c6e6d67d6749c24474e0393e511b3430550376e2bc62243fcb265f832
MD5 5b0e04b78c1d9d5f29ec6643fb1433ce
BLAKE2b-256 b42e58683eb7d478de5dbccea67e289e77d2ab09946dc2e7f8977a3aee47e8f2

See more details on using hashes here.

File details

Details for the file pyansys-0.41.4-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: pyansys-0.41.4-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 1.8 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.8.3

File hashes

Hashes for pyansys-0.41.4-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 b4d2c4daaf041c9e3276c2378fe7292de6897d36233d5d59dc1bfdc51e45f6a0
MD5 995757b48b8b4ffe361a6a10f81a13a7
BLAKE2b-256 2c33fde6162b25d35193cc231b560c6c0792af3d394148c249f20f076caf981a

See more details on using hashes here.

File details

Details for the file pyansys-0.41.4-cp38-cp38-manylinux1_x86_64.whl.

File metadata

  • Download URL: pyansys-0.41.4-cp38-cp38-manylinux1_x86_64.whl
  • Upload date:
  • Size: 4.1 MB
  • Tags: CPython 3.8
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.8.3

File hashes

Hashes for pyansys-0.41.4-cp38-cp38-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 36e97cda75c625b1f75645dc27a95d3ca86534dffd86acd3c425cfbd1a1bc94e
MD5 6e47df06e48d8c736d200c9e6c0493f1
BLAKE2b-256 f28faabc0aaff47e6e384fa27cf614b7049706a1311e912cd3eee74b808a9f5a

See more details on using hashes here.

File details

Details for the file pyansys-0.41.4-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: pyansys-0.41.4-cp38-cp38-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 1.9 MB
  • Tags: CPython 3.8, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.8.3

File hashes

Hashes for pyansys-0.41.4-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 1b6f5f9789decd4b7d707cac7e163942b2655280395a14bbccb6b0a08723136d
MD5 99716fc4d37fa06653e6490d0b422920
BLAKE2b-256 b99265c54a5db5f81ac4c1fcaa0197865dff3a452eab41ab5d117a9675ba3612

See more details on using hashes here.

File details

Details for the file pyansys-0.41.4-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: pyansys-0.41.4-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 1.8 MB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.7.7

File hashes

Hashes for pyansys-0.41.4-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 e7ac7c1f04ce2f3874f2fbc39a1c637fa6fdaac341e23c229508396c37efca7f
MD5 90e6ee5c4c26b39e357ea933d4db0680
BLAKE2b-256 3548f0f798d46a29778e03c2ef697741758d01479bab31f6a2a9e2f982e2b7ef

See more details on using hashes here.

File details

Details for the file pyansys-0.41.4-cp37-cp37m-manylinux1_x86_64.whl.

File metadata

  • Download URL: pyansys-0.41.4-cp37-cp37m-manylinux1_x86_64.whl
  • Upload date:
  • Size: 3.6 MB
  • Tags: CPython 3.7m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.7.7

File hashes

Hashes for pyansys-0.41.4-cp37-cp37m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 d71465c322e5f023b570121b74e2a07ccc5b710dd6f717da363897774c90131c
MD5 5da79186ace0f702afcc513a123ddbd9
BLAKE2b-256 78af5b5042a548dcd862b3453adebd0b026d820fdf7684bfcf536d6ebce8019e

See more details on using hashes here.

File details

Details for the file pyansys-0.41.4-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: pyansys-0.41.4-cp37-cp37m-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 1.9 MB
  • Tags: CPython 3.7m, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.7.7

File hashes

Hashes for pyansys-0.41.4-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 0c50fe8b80cc97aa76ea75eba894c075ef981bae186d36f94c3ea39576960abe
MD5 804d6bc0628d6d81a406a94a6c1be3ac
BLAKE2b-256 9719ca367cd3752c7f423fe0bb4f7ead214a53253575bfed3646d3364a883790

See more details on using hashes here.

File details

Details for the file pyansys-0.41.4-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: pyansys-0.41.4-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 1.8 MB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.3.1 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.6.8

File hashes

Hashes for pyansys-0.41.4-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 3701138702790b5fb7709f8a3729432a53e34fc37d4025e832caa7ca958df4e0
MD5 c3b4424b603b822df530de96f5171c8b
BLAKE2b-256 b6bb78c429edc206ab7f49fc46eea626ff61e6e8f775762545a2c3df410d91e4

See more details on using hashes here.

File details

Details for the file pyansys-0.41.4-cp36-cp36m-manylinux1_x86_64.whl.

File metadata

  • Download URL: pyansys-0.41.4-cp36-cp36m-manylinux1_x86_64.whl
  • Upload date:
  • Size: 3.6 MB
  • Tags: CPython 3.6m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/40.6.2 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.6.10

File hashes

Hashes for pyansys-0.41.4-cp36-cp36m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 f954960608e5af539a733bb25f9c3a2707ca1c76e9584dcd2a7c61d1cfd010b3
MD5 7f154d193214837da6ea46ae89425acf
BLAKE2b-256 7aabb38fec4fead57b8d9c5a6da73b8f512f8a34c915fcca79a2425b58de035e

See more details on using hashes here.

File details

Details for the file pyansys-0.41.4-cp36-cp36m-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: pyansys-0.41.4-cp36-cp36m-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 1.9 MB
  • Tags: CPython 3.6m, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.3.1 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.6.8

File hashes

Hashes for pyansys-0.41.4-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 cd384c33fde1bb34cbb14486a32bba149210e96c92cd7e1242cfa81d07ff0781
MD5 6a74b0bb6f653dd1dc3aafbf21015e12
BLAKE2b-256 255fb8c48da3c629dcffdab7fe9313b9e1af89dbf4f42d46e08926d6291d9ba1

See more details on using hashes here.

File details

Details for the file pyansys-0.41.4-cp35-cp35m-win_amd64.whl.

File metadata

  • Download URL: pyansys-0.41.4-cp35-cp35m-win_amd64.whl
  • Upload date:
  • Size: 1.8 MB
  • Tags: CPython 3.5m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.3.1 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.5.4

File hashes

Hashes for pyansys-0.41.4-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 54993c67d5fc14779e9fb9cb7c4d4c9eb9638c7637607dc166fe41408537db25
MD5 4c5229c6d8947e7d8d11fca55608c980
BLAKE2b-256 04d82582bec35591ade7cc60fb041c01297340f2b020bb910f0c74be599119d3

See more details on using hashes here.

File details

Details for the file pyansys-0.41.4-cp35-cp35m-manylinux1_x86_64.whl.

File metadata

  • Download URL: pyansys-0.41.4-cp35-cp35m-manylinux1_x86_64.whl
  • Upload date:
  • Size: 3.5 MB
  • Tags: CPython 3.5m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/28.8.0 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.5.9

File hashes

Hashes for pyansys-0.41.4-cp35-cp35m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 f97fbef2514d3913f2e0a6413f392b705745f9e11479c68b116d3db028afda59
MD5 c6e13b6321e4a06292656c8dab9ecc8f
BLAKE2b-256 821b1cd1c788ef1d4d76947fae085c0cab1c51488206bf5e06ff0c2784b7a8b1

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page