CUDAFinancialDerivative (CUDALink Symbol)

CUDAFinancialDerivative[instrument, params, ambientparams] gives the value of the specified financial instrument.CUDAFinancialDerivative[instrument, params, ambientparams, ...

Using TetGenLink (TetGenLink Tutorial)

This section shows some of the ways that TetGenLink can be applied. To use TetGenLink it must first be loaded. Next, some random points are generated and displayed.

Eigensystem (Built-in Mathematica Symbol)

Eigensystem[m] gives a list {values, vectors} of the eigenvalues and eigenvectors of the square matrix m. Eigensystem[{m, a}] gives the generalized eigenvalues and ...

ListStreamPlot (Built-in Mathematica Symbol)

ListStreamPlot[array] generates a stream plot from an array of vector field values.ListStreamPlot[{{{x_1, y_1}, {vx_1, vy_1}}, ...}] generates a stream plot from vector field ...

Newton's Method (Mathematica Tutorial)

One significant advantage Mathematica provides is that it can symbolically compute derivatives. This means that when you specify Method->"Newton" and the function is ...

PairedHistogram (Built-in Mathematica Symbol)

PairedHistogram[{x_1, x_2, ...}, {y_1, y_2, ...}] plots a paired histogram of the values x_i and y_i.PairedHistogram[{x_1, x_2, ...}, {y_1, y_2, ...}, bspec] plots a paired ...

OpenCLMemoryLoad (OpenCLLink Symbol)

OpenCLMemoryLoad[list] loads list into OpenCLMemory manager, returning an OpenCLMemory.OpenCLMemoryLoad[list, type] loads list with specified type into OpenCLMemory manager, ...

Histogram3D (Built-in Mathematica Symbol)

Histogram3D[{{x_1, y_1}, {x_2, y_2}, ...}] plots a 3D histogram of the values {x_i, y_i}.Histogram3D[{{x_1, y_1}, {x_2, y_2}, ...}, bspec] plots a 3D histogram with bins ...

Introduction (Compiled Function Tools Tutorial)

The Mathematica compiler provides an important way both to speed up and also to work with Mathematica computations. It does this by taking assumptions about the computations ...

Failure Recovery, Tracing, and Debugging (Parallel Package Tutorial)

A remote kernel in use may fail at any time, due to hardware, network, or software problems. A failure of a remote kernel will be noticed the next time Parallel Computing ...