removeOutliers: Remove points which are causing trouble

In IntiQuan/populationIsoboles: Calculate isoboles efficiently

Description

Sometimes arrange_isobole misses a point and then this point causes trouble Identify them by finding points which have two large steps directly after each other

Usage

removeOutliers(iso)

Arguments

iso	data.table(xp,yp) arranged with arrange_isobole

Value

data.table(xp,yp) with potential outliers removed

Examples

# library(data.table)
# library(ggplot2)
#
# iso_outliers <- data.table(DATAPIOutlierExample1)
# iso_noOutliers <- removeOutliers(iso_outliers)
# PIggplot(mapping = aes(xp,yp)) +
# geom_path(data = iso_noOutliers, color = "black", linetype = 1) +
# geom_path(data = iso_outliers, color = "red", linetype = 2)
#
# iso_outliers <- data.table(DATAPIOutlierExample2)
# iso_noOutliers <- removeOutliers(iso_outliers)
# PIggplot(mapping = aes(xp,yp)) +
# geom_path(data = iso_noOutliers, color = "black", linetype = 1) +
# geom_path(data = iso_outliers, color = "red", linetype = 2)

IntiQuan/populationIsoboles documentation built on Jan. 13, 2022, 8:29 p.m.