API Reference¶
Meshes¶
TensorMesh([h, x0]) |
TensorMesh is a mesh class that deals with tensor product meshes. |
CylMesh([h, x0]) |
CylMesh is a mesh class for cylindrical problems. It supports both |
TreeMesh(h[, x0]) |
TreeMesh is a class for adaptive QuadTree (2D) and OcTree (3D) meshes. |
CurvilinearMesh([nodes]) |
CurvilinearMesh is a mesh class that deals with curvilinear meshes. |
Numerical Operators¶
DiffOperators.DiffOperators() |
Class creates the differential operators that you need! |
InnerProducts.InnerProducts() |
This is a base for the discretize mesh classes. |
Mesh IO¶
load_mesh(filename) |
Open a json file and load the mesh into the target class |
MeshIO.TensorMeshIO |
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MeshIO.TreeMeshIO |
Visualization¶
View.TensorView() |
Provides viewing functions for TensorMesh |
View.CylView |
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View.CurviView() |
Provides viewing functions for CurvilinearMesh |
View.Slicer(mesh, v[, xslice, yslice, …]) |
Plot slices of a 3D volume, interactively (scroll wheel). |
mixins.vtkModule |
This module provides a way for discretize meshes to be converted to VTK data objects (and back when possible) if the `VTK Python package`_ is available. |
Testing¶
Tests.OrderTest([methodName]) |
OrderTest is a base class for testing convergence orders with respect to mesh sizes of integral/differential operators. |
Tests.checkDerivative(fctn, x0[, num, …]) |
Basic derivative check |
Tests.getQuadratic(A, b[, c]) |
Given A, b and c, this returns a quadratic, Q |
Tests.Rosenbrock(x[, return_g, return_H]) |
Rosenbrock function for testing GaussNewton scheme |
Utilities¶
General Utilities¶
utils.download(url[, folder, overwrite, verbose]) |
Function to download all files stored in a cloud directory |
Mesh Utilities¶
utils.exampleLrmGrid(nC, exType) |
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utils.meshTensor(value) |
meshTensor takes a list of numbers and tuples that have the form. |
utils.closestPoints(mesh, pts[, gridLoc]) |
Move a list of points to the closest points on a grid. |
utils.ExtractCoreMesh(xyzlim, mesh[, meshType]) |
Extracts Core Mesh from Global mesh |
utils.random_model(shape[, seed, …]) |
Create a random model by convolving a kernel with a uniformly distributed model. |
Matrix Utilities¶
utils.mkvc(x[, numDims]) |
Creates a vector with the number of dimension specified |
utils.sdiag(h) |
Sparse diagonal matrix |
utils.sdInv(M) |
Inverse of a sparse diagonal matrix |
utils.speye(n) |
Sparse identity |
utils.kron3(A, B, C) |
Three kron prods |
utils.spzeros(n1, n2) |
a sparse matrix of zeros |
utils.ddx(n) |
Define 1D derivatives, inner, this means we go from n+1 to n |
utils.av(n) |
Define 1D averaging operator from nodes to cell-centers. |
utils.av_extrap(n) |
Define 1D averaging operator from cell-centers to nodes. |
utils.ndgrid(*args, **kwargs) |
Form tensorial grid for 1, 2, or 3 dimensions. |
utils.ind2sub(shape, inds) |
From the given shape, returns the subscripts of the given index |
utils.sub2ind(shape, subs) |
From the given shape, returns the index of the given subscript |
utils.getSubArray(A, ind) |
subArray |
utils.inv3X3BlockDiagonal(a11, a12, a13, …) |
B = inv3X3BlockDiagonal(a11, a12, a13, a21, a22, a23, a31, a32, a33) |
utils.inv2X2BlockDiagonal(a11, a12, a21, a22) |
B = inv2X2BlockDiagonal(a11, a12, a21, a22) |
utils.TensorType(M, tensor) |
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utils.makePropertyTensor(M, tensor) |
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utils.invPropertyTensor(M, tensor[, …]) |
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utils.Zero |
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utils.Identity([positive]) |
Mathematical Operations¶
utils.rotatePointsFromNormals(XYZ, n0, n1[, x0]) |
rotates a grid so that the vector n0 is aligned with the vector n1 |
utils.rotationMatrixFromNormals(v0, v1[, tol]) |
Performs the minimum number of rotations to define a rotation from the direction indicated by the vector n0 to the direction indicated by n1. |
utils.cyl2cart(grid[, vec]) |
Take a grid defined in cylindrical coordinates \((r, heta, z)\) and transform it to cartesian coordinates. |
utils.cart2cyl(grid[, vec]) |
Take a grid defined in cartesian coordinates and transform it to cyl coordinates |
utils.isScalar(f) |
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utils.asArray_N_x_Dim(pts, dim) |
Curvilinear Mesh Utilities¶
utils.volTetra(xyz, A, B, C, D) |
Returns the volume for tetrahedras volume specified by the indexes A to D. |
utils.faceInfo(xyz, A, B, C, D[, average, …]) |
function [N] = faceInfo(y,A,B,C,D) |
utils.indexCube(nodes, gridSize[, n]) |
Returns the index of nodes on the mesh. |
Base Mesh¶
base.BaseMesh(n[, x0]) |
BaseMesh does all the counting you don’t want to do. |
base.BaseRectangularMesh(n[, x0]) |
BaseRectangularMesh |
base.BaseTensorMesh([h, x0]) |
Base class for tensor-product style meshes |