hotPaths: Hot Paths in Profile Data

In proftools: Profile Output Processing Tools for R

Description

Computes and displays hot paths in profiling data.

Usage

hotPaths(pd, value = c("pct", "time", "hits"), self = TRUE,
         srclines = TRUE, GC = FALSE, memory = FALSE, maxdepth = 10,
         self.pct = 0, total.pct = 0, short = ". ", nlines = NA)

Arguments

pd	profile data as returned by readProfileData.
value	character; show result as percentage, time, or hits.
self	logical; include self time for each stack in the result.
srclines	logical; include source information, if available, or not.
GC	logical; include GC information or not.
memory	logical; include memory use information or not.
maxdepth	integer; stacks are truncated to have at most maxdepth elements.
self.pct	numeric; stacks with self percent values below this level are dropped.
total.pct	numeric; stacks with total percent values below this level are dropped.
short	character; abbreviation to be used for functions lower on the stack.
nlines	integer; number of lines to show. The lines shown are the ones with the highest total percentage.

Details

The hot path ordering sorts stacks in the profile data first by the frequency with which the bottom functions on the stack are called, with highest frequency first, then within each bottom function by the frequency of the bottom two, and so on. Examining the result of hotPaths starting with low values of maxdepth and then moving to higher levels is a useful way to expore where the computational effort is concentrated.

Value

A data frame designed to produce a useful printed result.

Author(s)

Luke Tierney

See Also

Rprof, summaryRprof, flatProfile, filterProfileData, readProfileData, plotProfileCallGraph, profileCallGraph2Dot

Examples

pd <- readProfileData(system.file("samples", "glmEx.out", package="proftools"))
hotPaths(pd)
hotPaths(pd, maxdepth = 8)

proftools documentation built on July 8, 2020, 5:20 p.m.