UPMASK (version 1.2)

analyse_randomKde2d_smart: Perform analysis of random 2d distributions

Description

analyse_randomKde2d_smart will compute statistics from uniformly randomly created 2D fields based on Kernel Density Estimations (calling the code analyse_randomKde2d). However, if a random field using the same number of stars was already computed in this run of UPMASK, it will avoid computing it again and will return the value that is stored in a SQLite database table. If the random field was not yet analysed, it will run the analysis, store the result in the database table, and return the value.

Usage

analyse_randomKde2d_smart(nfields=100, nstars, maxX, maxY, nKde=50, 
showStats=FALSE, returnStats=TRUE, smartTableDB)

Arguments

nfields

an integer with the number of individual field realisations

nstars

an integer with the number of stars to consider

maxX

the length of the field in X

maxY

the length of the field in Y

nKde

the number of samplings of the kernel in each direction

showStats

a boolean indicating if the user wants to see statistics

returnStats

a boolean indicating if the user wants statistics to be returned

smartTableDB

a database connection to the smart look-up table

Value

A data frame with the mean and sd fields containing the results of the random field analysis.

Examples

# NOT RUN {
# Create the smart look-up table
library(RSQLite)
stcon <- create_smartTable()

# Runs the analysis on random fields
system.time(
toyRes1 <- analyse_randomKde2d_smart(300, 200, 100, 100, smartTableDB=stcon)) # slow
system.time(
toyRes2 <- analyse_randomKde2d_smart(300, 200, 100, 100, smartTableDB=stcon)) # quick

# Clean the environment
rm(list=c("toyRes1", "toyRes2"))
dbDisconnect(stcon)
 
# }