pyansys 0.10

Pythonic interface to ANSYS binary files

Python module to extract data from ANSYS binary files and to display them if vtk is installed. Currently supports (.rst) and (.full) files.

Installation

From PyPi directory

pip install pyansys

or

python setup.py install

License

ANSYScdb is licensed under the MIT license. The full statement is provided in the file named LICENSE.

Dependencies

Required: numpy, cython, ANSYScdb. Optional: vtk

Minimum requirements are numpy to extract results from a results file. To convert the raw data to a VTK unstructured grid, vtk 5.0 or greater must be installed with Python bindings.

Tests

Test installation with the following

from pyansys import Tests

# Load a hexahedral beam modal analysis result file
Tests.Reader.Load()

# Display first bending mode of that beam
Tests.Reader.Display()

# Load mass and stiffness matrices from the beam
Tests.Reader.LoadKM()

Example: Reading a Result File

This example reads in binary results from a modal analysis from ANSYS.

Example files can be found within the Tests folder in installation folder.

# Load the reader from pyansys
from pyansys import Reader

# Create result reader object
fobj = Reader.ResultReader('file.rst')

# Get mode frequencies
freqs = fobj.tvalues

# Get the node numbers in this result file
nnum = fobj.nnum

# Get the mode shape at mode 7 (ANSYS result 7)
disp = fobj.GetResult(6) # uses 0 based indexing

# Load CDB (necessary for display)
fobj.LoadCDB('mesh.cdb')

# Plot the displacement of Mode 41 in the x direction
fobj.PlotDisplacement(40, 'x')

Example: Reading a full file

This example reads in mass and stiffness matrices associated with Beam.cdb

Example files can be found within the Tests folder in installation folder.

# Load the reader from pyansys
from pyansys import Reader

# Create result reader object
fobj = Reader.FullReader('file.full')

# Read in full file
fobj.LoadFullKM()

# Data from the full file can now be accessed from the object
# Can be used construct a sparse matrix and solve it

# from scipy.sparse import csc_matrix, linalg
#ndim = fobj.nref.size
#k = csc_matrix(fobj.kdata, (fobj.krows, fobj.kcols), shape=(ndim, ndim))
#m = csc_matrix(fobj.kdata, (fobj.krows, fobj.kcols), shape=(ndim, ndim))
# Solve
#w, v = linalg.eigsh(k, k=20, M=m, sigma=10000)
# System natural frequencies
#f = np.sqrt(real(w))/(2*np.pi)