find_dominant_difference_using_averages_normalized_by_sd {BallMapper}

This procedure take two subset of points (that come from the vertices of Ball Mapper) and return the coordinates on which the averages of those two collections differs most. To ballance the effect of potentially different orders of magnitude of data in column, we divide the difference in means by the standard deviation of the whole column.

Description

This procedure take two subset of points (that come from the vertices of Ball Mapper) and return the coordinates on which the averages of those two collections differs most. To ballance the effect of potentially different orders of magnitude of data in column, we divide the difference in means by the standard deviation of the whole column.

Usage

find_dominant_difference_using_averages_normalized_by_sd(points, subset1,
  subset2)

Arguments

points

a collection of input points in a form of a data frame. The same one as on the input of the Ball Mapper.

subset1

First subset of ids of points.

subset2

Second subset of ids of points.

Value

Vector of corrdinate ids with the absolute value of difference between averages normalized by the standard deviation of the considered column, ordered according to the second variable. var <- seq(from=0,to=6.3,by=0.1) points <- as.data.frame( cbind( sin(var),cos(var) ) ) values <- as.data.frame(sin(var)) l <- BallMapper(points, values, 0.25) g1 <- c(1,21 g2 <- c(11,12) find_dominant_difference_using_averages(points,g1,g2)