"Gauss–Newton" and "conjugate gradient" methods use derivatives. When Mathematica cannot compute symbolic derivatives, finite differences will be used. Computing derivatives ...

When you set up a graphics object in Mathematica, you typically give a list of graphical elements. You can include in that list graphics directives which specify how ...

The Mathematica compiler can run computations in parallel. It does this by threading a compiled function over lists of data in parallel. A first step is to create a compiled ...

Mathematica provides functions for the aesthetic drawing of graphs. Algorithms implemented include spring embedding, spring-electrical embedding, high-dimensional embedding, ...

Linear programming problems are optimization problems where the objective function and constraints are all linear. Mathematica has a collection of algorithms for solving ...

FontProperties -> {opt_1 -> val_1, opt_2 -> val_2} specifies font properties.

BarChart[{y_1, y_2, ...}] makes a bar chart with bar lengths y_1, y_2, ....BarChart[{..., w_i[y_i, ...], ..., w_j[y_j, ...], ...}] makes a bar chart with bar features defined ...

The CCompilerDriver package lets you work with C compilers that are installed on your computer. It lets you build executables, libraries, and object files from C source code. ...

SymbolicC has a number of functions for working with the C preprocessor. These allow you to set up including header files, defining macros, as well as setting up conditional ...

Sparse representations of matrices are useful because they do not store every element. If one particular value appears very frequently it can be very advantageous to use a ...