geo_utils
File IO
- pygeo.geo_utils.file_io.getCoordinatesFromFile(fileName)[source]
Get a list of coordinates from a file - useful for testing
- Parameters
- fileNamestr’
filename for file
- Returns
- coordinateslist
list of coordinates
- pygeo.geo_utils.file_io.readAirfoilFile(fileName, bluntTe=False, bluntTaperRange=0.1, bluntThickness=0.002)[source]
Load the airfoil file
- pygeo.geo_utils.file_io.readNValues(handle, N, dtype, binary=False, sep=' ')[source]
Read N values of dtype ‘float’ or ‘int’ from file handle
FFD Generation
- pygeo.geo_utils.ffd_generation.createFittedWingFFD(surf, surfFormat, outFile, leList, teList, nSpan, nChord, absMargins, relMargins, liftIndex)[source]
Generates a wing FFD with chordwise points that follow the airfoil geometry.
- Parameters
- surfpyGeo object or list or str
The surface around which the FFD will be created. See the documentation for
pygeo.DVConstraints.setSurface()
for details.- surfFormatstr
The surface format. See the documentation for
pygeo.DVConstraints.setSurface()
for details.- outFilestr
Name of output file written in PLOT3D format.
- leListlist or array
List or array of points (of size Nx3 where N is at least 2) defining the ‘leading edge’.
- teListlist or array
Same as leList but for the trailing edge.
- nSpanint or list of int
Number of spanwise sections in the FFD. Use a list of length N-1 to specify the number for each segment defined by leList and teList and to precisely match intermediate locations.
- nChordint
Number of chordwise points in the FFD.
- absMarginslist of float
List with 3 items specifying the absolute margins in the [chordwise, spanwise, thickness] directions. This is useful for areas where the relative margin is too small, such as the trailing edge or wing tip. The total margin is the sum of the absolute and relative margins.
- relMarginslist of float
List with 3 items specifying the relative margins in the [chordwise, spanwise, thickness] directions. Relative margins are applied as a fraction of local chord, wing span, and local thickness. The total margin is the sum of the absolute and relative margins.
- liftIndexint
Index specifying which direction lift is in (same as the ADflow option). Either 2 for the y-axis or 3 for the z-axis. This is used to determine the wing’s spanwise direction.
Examples
>>> CFDSolver = ADFLOW(options=aeroOptions) >>> surf = CFDSolver.getTriangulatedMeshSurface() >>> surfFormat = "point-vector" >>> outFile = "wing_ffd.xyz" >>> nSpan = [4, 4] >>> nChord = 8 >>> relMargins = [0.01, 0.001, 0.01] >>> absMargins = [0.05, 0.001, 0.05] >>> liftIndex = 3 >>> createFittedWingFFD(surf, surfFormat, outFile, leList, teList, nSpan, nChord, absMargins, relMargins, liftIndex)
- pygeo.geo_utils.ffd_generation.write_wing_FFD_file(fileName, slices, N0, N1, N2, axes=None, dist=None)[source]
This function can be used to generate a simple FFD. The FFD can be made up of more than one volume, but the volumes will be connected. It is meant for doing simple wing FFDs.
- Parameters
- fileNamestr
Name of output file. File is written in plot3d format.
- slicesnumpy array of (Nvol+1, 2, 2, 3)
Array of slices. Each slice should contain four points in 3D that will be the corners of the FFD on that slice. If the zeroth dimension size is greater than 2, then multiple volumes will be created, connected by the intermediate slice.
- N0integer or list
Number of points to distribute along the zeroth dimension (along the slice direction).
- N1integer or list
Number of points to distribute along the first dimension.
- N2integer or list
Number of points to distribute along the second dimension.
- axeslist of [‘i’, ‘j’, ‘k’] in arbitrary order
The user can interchange which index of the FFD corresponds with each dimension of slices. By default ‘k’ -> 0, ‘j’ -> 1, ‘i’ -> 2.
- distlist
For each volume, the user can specify the distribution of points along each dimension. Options include:
linear
cosine
left (tighter spacing on the left side)
right (tighter spacing on the other left side)
Examples
This is an example of two volumes:
axes = ['k', 'j', 'i'] slices = np.array([ # Slice 1 [[[0, 0, 0], [1, 0, 0]], [[0, 0.2, 0], [1, 0.2, 0]]], # Slice 2 [[[0, 0, 2], [1, 0, 2]], [[0, 0.2, 2], [1, 0.2, 2]]], # Slice 3 [[[0.5, 0, 6], [1, 0, 6]], [[0.5, 0.2, 6], [1, 0.2, 6]]], ]) N0 = 5 N1 = 2 N2 = 8 dist = [ ['left', 'linear', 'linear'], ['cosine', 'linear', 'right'] ]
Point Reduce
- pygeo.geo_utils.remove_duplicates.pointReduce(points, nodeTol=0.0001)[source]
Given a list of N points in ndim space, with possible duplicates, return a list of the unique points AND a pointer list for the original points to the reduced set
- pygeo.geo_utils.remove_duplicates.pointReduceBruteForce(points, nodeTol=0.0001)[source]
Given a list of N points in ndim space, with possible duplicates, return a list of the unique points AND a pointer list for the original points to the reduced set
Warning
This is the brute force version of
pointReduce()
.
- pygeo.geo_utils.remove_duplicates.unique(s)[source]
Return a list of the elements in s, but without duplicates.
For example,
unique([1,2,3,1,2,3])
is some permutation of[1,2,3]
,unique("abcabc")
some permutation of["a", "b", "c"]
, andunique(([1, 2], [2, 3], [1, 2]))
some permutation of[[2, 3], [1, 2]]
.For best speed, all sequence elements should be hashable. Then
unique()
will usually work in linear time.If not possible, the sequence elements should enjoy a total ordering, and if
list(s).sort()
doesn’t raiseTypeError
it’s assumed that they do enjoy a total ordering. Thenunique()
will usually work in \(\mathcal{O}(N\log_2(N))\) time.If that’s not possible either, the sequence elements must support equality-testing. Then
unique()
will usually work in quadratic time.
- pygeo.geo_utils.remove_duplicates.uniqueIndex(s, sHash=None)[source]
This function is based on
unique()
. The idea is to take a list s, and reduce it as per unique.However, it additionally calculates a linking index array that is the same size as the original s, and points to where it ends up in the the reduced list
if sHash is not specified for sorting, s is used