ParallelTable (Built-in Mathematica Symbol)

ParallelTable[expr, {i_max}] generates in parallel a list of i_max copies of expr.ParallelTable[expr, {i, i_max}] generates in parallel a list of the values of expr when i ...

TreePlot (Built-in Mathematica Symbol)

TreePlot[{v i 1 -> v j 1, v i 2 -> v j 2, ...}] generates a tree plot of the graph in which vertex v_ik is connected to vertex v_jk.TreePlot[{{v i 1 -> v j 1, lbl_1}, ...}] ...

TuringMachine (Built-in Mathematica Symbol)

TuringMachine[rule, init, t] generates a list representing the evolution of the Turing machine with the specified rule from initial condition init for t steps. ...

Algebraic Operations on Polynomials (Mathematica Tutorial)

For many kinds of practical calculations, the only operations you will need to perform on polynomials are essentially structural ones. If you do more advanced algebra with ...

Examples (Library Link Tutorial)

Wolfram LibraryLink allows dynamic libraries to be directly loaded into the Mathematica kernel so that functions in the libraries can be immediately called from Mathematica. ...

WeibullDistribution (Built-in Mathematica Symbol)

WeibullDistribution[\[Alpha], \[Beta]] represents a Weibull distribution with shape parameter \[Alpha] and scale parameter \[Beta].WeibullDistribution[\[Alpha], \[Beta], ...

Writing Java Programs That Use ... (JLink Tutorial)

The first part of this User Guide describes using J/Link to allow you to call from Mathematica into Java, thereby extending the Mathematica environment to include the ...

BooleanFunction (Built-in Mathematica Symbol)

BooleanFunction[k, n] represents the k\[Null]^th Boolean function in n variables.BooleanFunction[values] represents the Boolean function corresponding to the specified vector ...

GraphPlot (Built-in Mathematica Symbol)

GraphPlot[{v i 1 -> v j 1, v i 2 -> v j 2, ...}] generates a plot of the graph in which vertex v_ik is connected to vertex v_jk.GraphPlot[{{v i 1 -> v j 1, lbl_1}, ...}] ...

LogNormalDistribution (Built-in Mathematica Symbol)

LogNormalDistribution[\[Mu], \[Sigma]] represents a lognormal distribution derived from a normal distribution with mean \[Mu] and standard deviation \[Sigma].