ContourPlot3D (Built-in Mathematica Symbol)

ContourPlot3D[f, {x, x_min, x_max}, {y, y_min, y_max}, {z, z_min, z_max}] produces a three-dimensional contour plot of f as a function of x, y, and z. ContourPlot3D[f == g, ...

Grid (Built-in Mathematica Symbol)

Grid[{{expr_11, expr_12, ...}, {expr_21, expr_22, ...}, ...}] is an object that formats with the expr_ij arranged in a two-dimensional grid.

Plot3D (Built-in Mathematica Symbol)

Plot3D[f, {x, x_min, x_max}, {y, y_min, y_max}] generates a three-dimensional plot of f as a function of x and y. Plot3D[{f_1, f_2, ...}, {x, x_min, x_max}, {y, y_min, ...

Numerical Nonlinear Local Optimization (Mathematica Tutorial)

Numerical algorithms for constrained nonlinear optimization can be broadly categorized into gradient-based methods and direct search methods. Gradient search methods use ...

CUDAFunctionLoad (CUDALink Symbol)

CUDAFunctionLoad[src, fun, argtypes, blockdim] loads CUDAFunction from scr and makes fun available in Mathematica.CUDAFunctionLoad[{srcfile}, fun, argtypes, blockdim] loads ...

Introduction to Manipulate (Mathematica Tutorial)

The single command Manipulate lets you create an astonishing range of interactive applications with just a few lines of input. Manipulate is designed to be used by anyone who ...

Alphabetical Listing (Mathematica Guide)

Mathematica has over 3000 built-in functions and other objects, all based on a single unified framework, and all carefully designed to work together, both in simple ...

DistributionFitTest (Built-in Mathematica Symbol)

DistributionFitTest[data] tests whether data is normally distributed. DistributionFitTest[data, dist] tests whether data is distributed according to dist. ...

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 ...

FindDistributionParameters (Built-in Mathematica Symbol)

FindDistributionParameters[data, dist] finds the parameter estimates for the distribution dist from data.FindDistributionParameters[data, dist, {{p, p_0}, {q, q_0}, ...}] ...