NIntegrate[f, {x, x_min, x_max}] gives a numerical approximation to the integral \[Integral]_x_min^x_max\ f\ d \ x. NIntegrate[f, {x, x_min, x_max}, {y, y_min, y_max}, ...] ...
PieChart[{y_1, y_2, ...}] makes a pie chart with sector angle proportional to y_1, y_2, ....PieChart[{..., w_i[y_i, ...], ..., w_j[y_j, ...], ...}] makes a pie chart with ...
BreadthFirstScan[g, s, {"event_1" -> f_1, "event_2" -> f_2, ...}] performs a breadth-first scan (bfs) of the graph g starting at the vertex s and evaluates f_i whenever ...
KernelMixtureDistribution[{x_1, x_2, ...}] represents a kernel mixture distribution based on the data values x_i.KernelMixtureDistribution[{{x_1, y_1, ...}, {x_2, y_2, ...}, ...
ListStreamDensityPlot[array] generates a stream density plot from a 2D array of vector and scalar field values {{vx_ij, vy_ij}, s_ij}. ListStreamDensityPlot[{{{x_1, y_1}, ...
ListVectorDensityPlot[array] generates a vector plot from a 2D array of vector and scalar field values {{vx_ij, vy_ij}, s_ij}. ListVectorDensityPlot[{{{x_1, y_1}, {{vx_1, ...
It is often useful to be able to detect and precisely locate a change in a differential system. For example, with the detection of a singularity or state change, the ...
The general symbolic string patterns in Mathematica allow you to perform powerful string manipulation efficiently. What follows discusses the details of string patterns, ...
The first step in using a database is making a connection. This part of the tutorial discusses how to do this. If you are just starting to use DatabaseLink, you might want to ...
Transpose::nmtx