An integration rule computes an estimate of an integral over a region, typically using a weighted sum. In the context of NIntegrate usage, an integration rule object provides ...
Because GPUs are SIMD machines, to exploit CUDA's potential you must pose the problem in an SIMD manner. Computation that can be partitioned in such a way that each thread ...
ListVectorPlot[array] generates a vector plot from an array of vector field values.ListVectorPlot[{{{x_1, y_1}, {vx_1, vy_1}}, ...}] generates a vector plot from vector field ...
Product
(Built-in Mathematica Symbol) Product[f, {i, i_max}] evaluates the product \[Product]i = 1 i_max f. Product[f, {i, i_min, i_max}] starts with i = i_min. Product[f, {i, i_min, i_max, di}] uses steps di. ...
WaveletMatrixPlot[dwd] plots the basis tree of wavelet matrix coefficients in the DiscreteWaveletData dwd.WaveletMatrixPlot[dwd, r] plots coefficients up to refinement level ...
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, ...}, ...
Sum
(Built-in Mathematica Symbol) Sum[f, {i, i_max}] evaluates the sum \[Sum]i = 1 i_max f. Sum[f, {i, i_min, i_max}] starts with i = i_min. Sum[f, {i, i_min, i_max, di}] uses steps d i. Sum[f, {i, {i_1, i_2, ...
"Introduction to Manipulate" and "Introduction to Dynamic" provide most of the information you need to use Mathematica's interactive features accessible through the functions ...
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 ...