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Small fixes to selbal() and selbal.aux() ensuring variables are drawn from logCounts. #37

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Small fixes to selbal() and selbal.aux() ensuring variables are drawn from logCounts. #37

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96c6bbb
fix selbal() to take variables form logCounts (and not x), cmultRepl2…
ChVav Apr 9, 2024
da7cce7
fix selbal() set rem.nam and var.nam using logCounts
ChVav Apr 9, 2024
c2aa2fc
fix selbal.aux() set rem.nam and var.nam using logCounts
ChVav Apr 9, 2024
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2 changes: 2 additions & 0 deletions .Rbuildignore
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Original file line number Diff line number Diff line change
@@ -0,0 +1,2 @@
^.*\.Rproj$
^\.Rproj\.user$
41 changes: 20 additions & 21 deletions R/Selbal_Functions.R
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Original file line number Diff line number Diff line change
Expand Up @@ -37,9 +37,6 @@
# Load library
suppressMessages(library(zCompositions))

# Variables name
var.nam <- rem.nam <- colnames(x)

# Build a table with the response variable and covariates for correction
if (!is.null(covar)){ dat <- data.frame(cbind(numy, covar))
} else { dat <-data.frame(numy)}
Expand All @@ -50,6 +47,10 @@
logCounts <- log(cmultRepl2(x, zero.rep = zero.rep))
}

# Variables name
var.nam <- rem.nam <- colnames(logCounts)



#--------------------------------------------------------------------------#
# 0.3: auxiliar functions
Expand Down Expand Up @@ -202,8 +203,8 @@
# Define the first balance
A1 <- first.bal(logCounts, Y = numy, covar=covar)
# Variables taking parti into the first balance
POS <- colnames(x)[A1[1,1]]
NEG <- colnames(x)[A1[1,2]]
POS <- colnames(logCounts)[A1[1,1]]
NEG <- colnames(logCounts)[A1[1,2]]

# Included variables in the model
INC.VAR <- c(POS, NEG)
Expand Down Expand Up @@ -395,13 +396,13 @@
#----------------------------------------------------------------------------#
# FINAL GLM
#----------------------------------------------------------------------------#

# Auxiliar data.frame for graphical representation
U <- data.frame(dat, FINAL.BAL)
colnames(U)[ncol(U)] <- "V1"
# Regression model
FIT.final <- glm(numy~., data=U, family = f.class)
FIT.final <- glm(numy~., data=U, family = f.class)

# Draw the plot if draw == T
if (draw){
#----------------------------------------------------------------------------#
Expand Down Expand Up @@ -543,7 +544,7 @@
FINAL.P <- arrangeGrob(Imp.table, ROC.plot, BoxP, ydensity,
ncol=2, nrow=2, widths=c(5,1.25), heights=c(2, 5),
vp=viewport(width=0.8, height=0.8))

library(gtable)
g1 <- ggplotGrob(Imp.table2)
g2 <- ggplotGrob(BoxP2)
Expand All @@ -552,7 +553,7 @@
g <- rbind(g, g3, size = "first")
g$widths <- unit.pmax(g1$widths,g2$widths)
FINAL.P2 <- g

} else {

# Fit the regression model
Expand Down Expand Up @@ -1040,10 +1041,10 @@

}else{
df.boxplot <- data.frame(mean = ACC.mean, se = ACC.se, n =2:maxV)
ylabelName="Accuracy (AUC)";
if (logit.acc=="Dev"){
ylabelName="Explained Deviance";
}
ylabelName="Accuracy (AUC)";
if (logit.acc=="Dev"){
ylabelName="Explained Deviance";
}
# Load library
library(ggplot2)
# The plot
Expand Down Expand Up @@ -1342,21 +1343,19 @@
# Load library
suppressMessages(library(zCompositions))

# Variables name
var.nam <- rem.nam <- colnames(x)

# Build a table with the response variable and covariates for correction
if (!is.null(covar)){ dat <- data.frame(cbind(numy, covar))
} else { dat <-data.frame(numy)}



# The logCounts (with zero replacement)
if (logt == F){ logCounts <- x
} else{
logCounts <- log(cmultRepl2(x, zero.rep = zero.rep))
}

# Variables name
var.nam <- rem.nam <- colnames(logCounts)


#--------------------------------------------------------------------------#
# 0.3: auxiliar functions
Expand Down Expand Up @@ -1977,8 +1976,8 @@
g <- rbind(g, g3, size = "first")
g$widths <- unit.pmax(g1$widths,g2$widths)
FINAL.P2 <- g


# Build a list with the elements of interest
L <- list(Global.plot = FINAL.P,Global.plot2 = FINAL.P2, ROC.plot = ROC.plot)

Expand Down