g.intensitygradient = function(x,y) {
# x: numeric vector of bin mid-points
# y: numeric vector of time spent in bins
y = ifelse(test = y <=0,yes = NA,no = y)
ly = log(y)
lx = log(x)
y_intercept = NA
gradient = NA
rsquared = NA
if (length(which(is.na(lx) == FALSE)) > 1 & length(which(is.na(ly) == FALSE)) > 1) {
if (sd(lx,na.rm = TRUE) != 0 & sd(ly,na.rm = TRUE) != 0) {
fitsum = summary(stats::lm(ly ~ lx))
y_intercept = stats::coef(fitsum)[1,1]
gradient = stats::coef(fitsum)[2,1]
rsquared = fitsum$r.squared
}
}
invisible(list(gradient=gradient,y_intercept=y_intercept,rsquared=rsquared))
}
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