R/read.dust.file.R

In npetraco/dustproj: Data IO and Slicing/Dicing for the Dust Projects

#' Read expanded data from a dust expanded tabulation sheet saved from .xlsx format
#'
#' XXXX
#'
#' The function will XXXX
#'
#' @param XX The XX
#' @return The function will XX
#'
#'
#' @export
read.dust.file<-function(fpath)
{

dat<-read.xlsx(fpath,1,header=FALSE)

#Natural hair class:
cl1<-as.character(dat[1,1])
#Fiber subclass (row labels for class)
sc1.1<-as.character(dat[2,1])
sc1.2<-as.character(dat[3,1])
sc1.3<-as.character(dat[4,1])
#Class attributes (column labels for class)
cl1.attr<-apply(dat[1,2:11],1,as.character )
#Fiber class/subclass data
tmp<-dat[2:4,2:11]
cl1.dat<-as.numeric(matrix(t(tmp),nrow=(dim(tmp)[1]*dim(tmp)[2]),ncol=1))
cl1.dat[is.na(cl1.dat)]<-0 #Data column (0=absence, 1=presence)

#Build the class block of the dataframe
col.class<-rep(cl1, length(cl1.dat) )
col.subclass<-rbind(
matrix(rep(sc1.1,length(cl1.attr)),nrow=length(cl1.attr),ncol=1),
matrix(rep(sc1.2,length(cl1.attr)),nrow=length(cl1.attr),ncol=1),
matrix(rep(sc1.3,length(cl1.attr)),nrow=length(cl1.attr),ncol=1)
)
col.attributes<-rep(cl1.attr,3)
cl1.block<-cbind(col.class,col.subclass,col.attributes)


#Treated hair class:
cl2<-as.character(dat[5,1])
#Fiber subclass
sc2.1<-as.character(dat[6,1])
sc2.2<-as.character(dat[7,1])
#Fiber attributes
cl2.attr<-apply(dat[5,c(2,7,8,9)],1,as.character )
#Fiber class/subclass data
tmp<-dat[6:7,c(2,7,8,9)]
cl2.dat<-as.numeric(matrix(t(tmp),nrow=(dim(tmp)[1]*dim(tmp)[2]),ncol=1))
cl2.dat[is.na(cl2.dat)]<-0 #Data column (0=absence, 1=presence)

#Build the class block of the dataframe
col.class<-rep(cl2, length(cl2.dat) )
col.subclass<-rbind(
matrix(rep(sc2.1,length(cl2.attr)),nrow=length(cl2.attr),ncol=1),
matrix(rep(sc2.2,length(cl2.attr)),nrow=length(cl2.attr),ncol=1)
)
col.attributes<-rep(cl2.attr,2)
cl2.block<-cbind(col.class,col.subclass,col.attributes)


#Synthetic fiber class
cl3<-as.character(dat[8,1])
#Fiber subclass
sc3.1<-as.character(dat[9,1])
sc3.2<-as.character(dat[10,1])
sc3.3<-as.character(dat[11,1])
sc3.4<-as.character(dat[12,1])
sc3.5<-as.character(dat[13,1])
sc3.6<-as.character(dat[14,1])
sc3.7<-as.character(dat[15,1])
sc3.8<-as.character(dat[16,1])
sc3.9<-as.character(dat[17,1])
sc3.10<-as.character(dat[18,1])
sc3.11<-as.character(dat[19,1])
sc3.12<-as.character(dat[20,1])
#Fiber attributes
cl3.attr<-apply(dat[8,2:12],1,as.character )
#Fiber class/subclass data
tmp<-dat[9:20,2:12]
cl3.dat<-as.numeric(matrix(t(tmp),nrow=(dim(tmp)[1]*dim(tmp)[2]),ncol=1))
cl3.dat[is.na(cl3.dat)]<-0 #Data column (0=absence, 1=presence)

#Build the class block of the dataframe
col.class<-rep(cl3, length(cl3.dat) )
col.subclass<-rbind(
matrix(rep(sc3.1,length(cl3.attr)),nrow=length(cl3.attr),ncol=1),
matrix(rep(sc3.2,length(cl3.attr)),nrow=length(cl3.attr),ncol=1),
matrix(rep(sc3.3,length(cl3.attr)),nrow=length(cl3.attr),ncol=1),
matrix(rep(sc3.4,length(cl3.attr)),nrow=length(cl3.attr),ncol=1),
matrix(rep(sc3.5,length(cl3.attr)),nrow=length(cl3.attr),ncol=1),
matrix(rep(sc3.6,length(cl3.attr)),nrow=length(cl3.attr),ncol=1),
matrix(rep(sc3.7,length(cl3.attr)),nrow=length(cl3.attr),ncol=1),
matrix(rep(sc3.8,length(cl3.attr)),nrow=length(cl3.attr),ncol=1),
matrix(rep(sc3.9,length(cl3.attr)),nrow=length(cl3.attr),ncol=1),
matrix(rep(sc3.10,length(cl3.attr)),nrow=length(cl3.attr),ncol=1),
matrix(rep(sc3.11,length(cl3.attr)),nrow=length(cl3.attr),ncol=1),
matrix(rep(sc3.12,length(cl3.attr)),nrow=length(cl3.attr),ncol=1)
)
col.attributes<-rep(cl3.attr,12)
cl3.block<-cbind(col.class,col.subclass,col.attributes)


#Animal hair class:
cl4<-as.character(dat[21,1])
#Fiber subclass
sc4.1<-as.character(dat[22,1])
sc4.2<-as.character(dat[23,1])
sc4.3<-as.character(dat[24,1])
sc4.4<-as.character(dat[25,1])
sc4.5<-as.character(dat[26,1])
sc4.6<-as.character(dat[27,1])
#Fiber attributes
cl4.attr<-apply(dat[21,2:16],1,as.character )
#Fiber class/subclass data
tmp<-dat[22:27,2:16]
cl4.dat<-as.numeric(matrix(t(tmp),nrow=(dim(tmp)[1]*dim(tmp)[2]),ncol=1))
cl4.dat[is.na(cl4.dat)]<-0 #Data column (0=absence, 1=presence)

#Build the class block of the dataframe
col.class<-rep(cl4, length(cl4.dat) )
col.subclass<-rbind(
matrix(rep(sc4.1,length(cl4.attr)),nrow=length(cl4.attr),ncol=1),
matrix(rep(sc4.2,length(cl4.attr)),nrow=length(cl4.attr),ncol=1),
matrix(rep(sc4.3,length(cl4.attr)),nrow=length(cl4.attr),ncol=1),
matrix(rep(sc4.4,length(cl4.attr)),nrow=length(cl4.attr),ncol=1),
matrix(rep(sc4.5,length(cl4.attr)),nrow=length(cl4.attr),ncol=1),
matrix(rep(sc4.6,length(cl4.attr)),nrow=length(cl4.attr),ncol=1)
)
col.attributes<-rep(cl4.attr,6)
cl4.block<-cbind(col.class,col.subclass,col.attributes)


#Natural Fiber class:
cl5<-as.character(dat[28,1])
#Fiber subclass
sc5.1<-as.character(dat[29,1])
sc5.2<-as.character(dat[30,1])
sc5.3<-as.character(dat[31,1])
sc5.4<-as.character(dat[32,1])
sc5.5<-as.character(dat[33,1])
sc5.6<-as.character(dat[34,1])
sc5.7<-as.character(dat[35,1])
sc5.8<-as.character(dat[36,1])
sc5.9<-as.character(dat[37,1])
sc5.10<-as.character(dat[38,1])
#Fiber attributes
cl5.attr<-apply(dat[28,2:16],1,as.character )
#Fiber class/subclass data
tmp<-dat[29:38,2:16]
cl5.dat<-as.numeric(matrix(t(tmp),nrow=(dim(tmp)[1]*dim(tmp)[2]),ncol=1))
cl5.dat[is.na(cl5.dat)]<-0 #Data column (0=absence, 1=presence)

#Build the class block of the dataframe
col.class<-rep(cl5, length(cl5.dat) )
col.subclass<-rbind(
matrix(rep(sc5.1,length(cl5.attr)),nrow=length(cl5.attr),ncol=1),
matrix(rep(sc5.2,length(cl5.attr)),nrow=length(cl5.attr),ncol=1),
matrix(rep(sc5.3,length(cl5.attr)),nrow=length(cl5.attr),ncol=1),
matrix(rep(sc5.4,length(cl5.attr)),nrow=length(cl5.attr),ncol=1),
matrix(rep(sc5.5,length(cl5.attr)),nrow=length(cl5.attr),ncol=1),
matrix(rep(sc5.6,length(cl5.attr)),nrow=length(cl5.attr),ncol=1),
matrix(rep(sc5.7,length(cl5.attr)),nrow=length(cl5.attr),ncol=1),
matrix(rep(sc5.8,length(cl5.attr)),nrow=length(cl5.attr),ncol=1),
matrix(rep(sc5.9,length(cl5.attr)),nrow=length(cl5.attr),ncol=1),
matrix(rep(sc5.10,length(cl5.attr)),nrow=length(cl5.attr),ncol=1)
)
col.attributes<-rep(cl5.attr,10)
cl5.block<-cbind(col.class,col.subclass,col.attributes)


#Mineral Fiber class:
cl6<-as.character(dat[39,1])
#Fiber subclass
sc6.1<-as.character(dat[40,1])
sc6.2<-as.character(dat[41,1])
sc6.3<-as.character(dat[42,1])
#Fiber attributes
#cl6.attr<-apply(dat[39,2:5],1,as.character )
cl6.attr<-"is.present?"
#Fiber class/subclass data
tmp<-as.matrix(dat[40:42,2])
cl6.dat<-as.numeric(matrix(t(tmp),nrow=(dim(tmp)[1]*dim(tmp)[2]),ncol=1))
cl6.dat[is.na(cl6.dat)]<-0 #Data column (0=absence, 1=presence)

#Build the class block of the dataframe
col.class<-rep(cl6, length(cl6.dat) )
col.subclass<-rbind(
matrix(rep(sc6.1,length(cl6.attr)),nrow=length(cl6.attr),ncol=1),
matrix(rep(sc6.2,length(cl6.attr)),nrow=length(cl6.attr),ncol=1),
matrix(rep(sc6.3,length(cl6.attr)),nrow=length(cl6.attr),ncol=1)
)
col.attributes<-rep(cl6.attr,3)
cl6.block<-cbind(col.class,col.subclass,col.attributes)


#Particles/Grains class (Called Glass/Mineral Grains in data sheet):
cl7<-as.character(dat[43,1])
#Fiber subclass
sc7.1<-as.character(dat[44,1])
sc7.2<-as.character(dat[45,1])
sc7.3<-as.character(dat[46,1])
sc7.4<-as.character(dat[47,1])
sc7.5<-as.character(dat[48,1])
sc7.6<-as.character(dat[49,1])
sc7.7<-as.character(dat[50,1])
sc7.8<-as.character(dat[51,1])
sc7.9<-as.character(dat[52,1])
sc7.10<-as.character(dat[53,1])
sc7.11<-as.character(dat[54,1])
sc7.12<-as.character(dat[55,1])
sc7.13<-as.character(dat[56,1])
sc7.14<-as.character(dat[57,1])
sc7.15<-as.character(dat[58,1])
sc7.16<-as.character(dat[59,1])
sc7.17<-as.character(dat[60,1])
sc7.18<-as.character(dat[61,1])
sc7.19<-as.character(dat[62,1])
sc7.20<-as.character(dat[63,1])
sc7.21<-as.character(dat[64,1])
#Fiber attributes
cl7.attr<-apply(dat[43,2:7],1,as.character )
#Fiber class/subclass data
tmp<-dat[44:64,2:7]
cl7.dat<-as.numeric(matrix(t(tmp),nrow=(dim(tmp)[1]*dim(tmp)[2]),ncol=1))
cl7.dat[is.na(cl7.dat)]<-0 #Data column (0=absence, 1=presence)

#Build the class block of the dataframe
col.class<-rep(cl7, length(cl7.dat) )
col.subclass<-rbind(
matrix(rep(sc7.1,length(cl7.attr)),nrow=length(cl7.attr),ncol=1),
matrix(rep(sc7.2,length(cl7.attr)),nrow=length(cl7.attr),ncol=1),
matrix(rep(sc7.3,length(cl7.attr)),nrow=length(cl7.attr),ncol=1),
matrix(rep(sc7.4,length(cl7.attr)),nrow=length(cl7.attr),ncol=1),
matrix(rep(sc7.5,length(cl7.attr)),nrow=length(cl7.attr),ncol=1),
matrix(rep(sc7.6,length(cl7.attr)),nrow=length(cl7.attr),ncol=1),
matrix(rep(sc7.7,length(cl7.attr)),nrow=length(cl7.attr),ncol=1),
matrix(rep(sc7.8,length(cl7.attr)),nrow=length(cl7.attr),ncol=1),
matrix(rep(sc7.9,length(cl7.attr)),nrow=length(cl7.attr),ncol=1),
matrix(rep(sc7.10,length(cl7.attr)),nrow=length(cl7.attr),ncol=1),
matrix(rep(sc7.11,length(cl7.attr)),nrow=length(cl7.attr),ncol=1),
matrix(rep(sc7.12,length(cl7.attr)),nrow=length(cl7.attr),ncol=1),
matrix(rep(sc7.13,length(cl7.attr)),nrow=length(cl7.attr),ncol=1),
matrix(rep(sc7.14,length(cl7.attr)),nrow=length(cl7.attr),ncol=1),
matrix(rep(sc7.15,length(cl7.attr)),nrow=length(cl7.attr),ncol=1),
matrix(rep(sc7.16,length(cl7.attr)),nrow=length(cl7.attr),ncol=1),
matrix(rep(sc7.17,length(cl7.attr)),nrow=length(cl7.attr),ncol=1),
matrix(rep(sc7.18,length(cl7.attr)),nrow=length(cl7.attr),ncol=1),
matrix(rep(sc7.19,length(cl7.attr)),nrow=length(cl7.attr),ncol=1),
matrix(rep(sc7.20,length(cl7.attr)),nrow=length(cl7.attr),ncol=1),
matrix(rep(sc7.21,length(cl7.attr)),nrow=length(cl7.attr),ncol=1)
)
col.attributes<-rep(cl7.attr,21)
cl7.block<-cbind(col.class,col.subclass,col.attributes)

datvec<-c(cl1.dat,cl2.dat,cl3.dat,cl4.dat,cl5.dat,cl6.dat,cl7.dat)
namesmat<-rbind(cl1.block,cl2.block,cl3.block,cl4.block,cl5.block,cl6.block,cl7.block)

return(list(datvec,namesmat))

}

#' Old version of Read data from a dust tabulation sheet stored in CSV format
#'
#' XXXX
#'
#' The function will XXXX
#'
#' @param XX The XX
#' @return The function will XX
#'
#'
#' @export
read.dust.file_OLD<-function(fpath)
{

dat<-read.csv(fpath,header=FALSE)

#Fiber class:
cl1<-as.character(dat[1,1])
#Fiber subclass
sc1.1<-as.character(dat[2,1])
sc1.2<-as.character(dat[3,1])
sc1.3<-as.character(dat[4,1])
#Fiber attributes
cl1.attr<-apply(dat[1,2:10],1,as.character )
#Fiber class/subclass data
tmp<-dat[2:4,2:10]
cl1.dat<-as.numeric(matrix(t(tmp),nrow=(dim(tmp)[1]*dim(tmp)[2]),ncol=1))


#Build the class block of the dataframe
cl1.block<-cbind(
#Class column
rep(cl1, length(cl1.dat) ),
#Subclass column
rbind(
matrix(rep(sc1.1,length(cl1.attr)),nrow=length(cl1.attr),ncol=1),
matrix(rep(sc1.2,length(cl1.attr)),nrow=length(cl1.attr),ncol=1),
matrix(rep(sc1.3,length(cl1.attr)),nrow=length(cl1.attr),ncol=1)
),
#Attribute column
rep(cl1.attr,3),
#Data column (0=absence, 1=presence)
cl1.dat
)
#print(cl1.block)



#Fiber class:
cl2<-as.character(dat[5,1])
#Fiber subclass
sc2.1<-as.character(dat[6,1])
sc2.2<-as.character(dat[7,1])
#Fiber attributes
cl2.attr<-apply(dat[5,c(2,7,8,9)],1,as.character )
#Fiber class/subclass data
tmp<-dat[6:7,c(2,7,8,9)]
cl2.dat<-as.numeric(matrix(t(tmp),nrow=(dim(tmp)[1]*dim(tmp)[2]),ncol=1))

#Build the class block of the dataframe
cl2.block<-cbind(
#Class column
rep(cl2, length(cl2.dat) ),
#Subclass column
rbind(
matrix(rep(sc2.1,length(cl2.attr)),nrow=length(cl2.attr),ncol=1),
matrix(rep(sc2.2,length(cl2.attr)),nrow=length(cl2.attr),ncol=1)
),
#Attribute column
rep(cl2.attr,2),
#Data column (0=absence, 1=presence)
cl2.dat
)
#print(rbind(cl1.block,cl2.block))



#Fiber class:
cl3<-as.character(dat[8,1])
#Fiber subclass
sc3.1<-as.character(dat[9,1])
sc3.2<-as.character(dat[10,1])
sc3.3<-as.character(dat[11,1])
sc3.4<-as.character(dat[12,1])
sc3.5<-as.character(dat[13,1])
sc3.6<-as.character(dat[14,1])
sc3.7<-as.character(dat[15,1])
sc3.8<-as.character(dat[16,1])
sc3.9<-as.character(dat[17,1])
sc3.10<-as.character(dat[18,1])
sc3.11<-as.character(dat[19,1])
sc3.12<-as.character(dat[20,1])
#Fiber attributes
cl3.attr<-apply(dat[8,2:11],1,as.character )
#Fiber class/subclass data
tmp<-dat[9:20,2:11]
cl3.dat<-as.numeric(matrix(t(tmp),nrow=(dim(tmp)[1]*dim(tmp)[2]),ncol=1))

#Build the class block of the dataframe
cl3.block<-cbind(
#Class column
rep(cl3, length(cl3.dat) ),
#Subclass column
rbind(
matrix(rep(sc3.1,length(cl3.attr)),nrow=length(cl3.attr),ncol=1),
matrix(rep(sc3.2,length(cl3.attr)),nrow=length(cl3.attr),ncol=1),
matrix(rep(sc3.3,length(cl3.attr)),nrow=length(cl3.attr),ncol=1),
matrix(rep(sc3.4,length(cl3.attr)),nrow=length(cl3.attr),ncol=1),
matrix(rep(sc3.5,length(cl3.attr)),nrow=length(cl3.attr),ncol=1),
matrix(rep(sc3.6,length(cl3.attr)),nrow=length(cl3.attr),ncol=1),
matrix(rep(sc3.7,length(cl3.attr)),nrow=length(cl3.attr),ncol=1),
matrix(rep(sc3.8,length(cl3.attr)),nrow=length(cl3.attr),ncol=1),
matrix(rep(sc3.9,length(cl3.attr)),nrow=length(cl3.attr),ncol=1),
matrix(rep(sc3.10,length(cl3.attr)),nrow=length(cl3.attr),ncol=1),
matrix(rep(sc3.11,length(cl3.attr)),nrow=length(cl3.attr),ncol=1),
matrix(rep(sc3.12,length(cl3.attr)),nrow=length(cl3.attr),ncol=1)
),
#Attribute column
rep(cl3.attr,12),
#Data column (0=absence, 1=presence)
cl3.dat
)
#print(rbind(cl1.block,cl2.block,cl3.block))



#Fiber class:
cl4<-as.character(dat[21,1])
#Fiber subclass
sc4.1<-as.character(dat[22,1])
sc4.2<-as.character(dat[23,1])
sc4.3<-as.character(dat[24,1])
sc4.4<-as.character(dat[25,1])
sc4.5<-as.character(dat[26,1])
sc4.6<-as.character(dat[27,1])
#Fiber attributes
cl4.attr<-apply(dat[21,2:12],1,as.character )
#Fiber class/subclass data
tmp<-dat[22:27,2:12]
cl4.dat<-as.numeric(matrix(t(tmp),nrow=(dim(tmp)[1]*dim(tmp)[2]),ncol=1))

#Build the class block of the dataframe
cl4.block<-cbind(
#Class column
rep(cl4, length(cl4.dat) ),
#Subclass column
rbind(
matrix(rep(sc4.1,length(cl4.attr)),nrow=length(cl4.attr),ncol=1),
matrix(rep(sc4.2,length(cl4.attr)),nrow=length(cl4.attr),ncol=1),
matrix(rep(sc4.3,length(cl4.attr)),nrow=length(cl4.attr),ncol=1),
matrix(rep(sc4.4,length(cl4.attr)),nrow=length(cl4.attr),ncol=1),
matrix(rep(sc4.5,length(cl4.attr)),nrow=length(cl4.attr),ncol=1),
matrix(rep(sc4.6,length(cl4.attr)),nrow=length(cl4.attr),ncol=1)
),
#Attribute column
rep(cl4.attr,6),
#Data column (0=absence, 1=presence)
cl4.dat
)
#print(rbind(cl1.block,cl2.block,cl3.block,cl4.block))



#Fiber class:
cl5<-as.character(dat[28,1])
#Fiber subclass
sc5.1<-as.character(dat[29,1])
sc5.2<-as.character(dat[30,1])
sc5.3<-as.character(dat[31,1])
sc5.4<-as.character(dat[32,1])
sc5.5<-as.character(dat[33,1])
sc5.6<-as.character(dat[34,1])
sc5.7<-as.character(dat[35,1])
sc5.8<-as.character(dat[36,1])
sc5.9<-as.character(dat[37,1])
sc5.10<-as.character(dat[38,1])
#Fiber attributes
cl5.attr<-apply(dat[28,2:11],1,as.character )
#Fiber class/subclass data
tmp<-dat[29:38,2:11]
cl5.dat<-as.numeric(matrix(t(tmp),nrow=(dim(tmp)[1]*dim(tmp)[2]),ncol=1))

#Build the class block of the dataframe
cl5.block<-cbind(
#Class column
rep(cl5, length(cl5.dat) ),
#Subclass column
rbind(
matrix(rep(sc5.1,length(cl5.attr)),nrow=length(cl5.attr),ncol=1),
matrix(rep(sc5.2,length(cl5.attr)),nrow=length(cl5.attr),ncol=1),
matrix(rep(sc5.3,length(cl5.attr)),nrow=length(cl5.attr),ncol=1),
matrix(rep(sc5.4,length(cl5.attr)),nrow=length(cl5.attr),ncol=1),
matrix(rep(sc5.5,length(cl5.attr)),nrow=length(cl5.attr),ncol=1),
matrix(rep(sc5.6,length(cl5.attr)),nrow=length(cl5.attr),ncol=1),
matrix(rep(sc5.7,length(cl5.attr)),nrow=length(cl5.attr),ncol=1),
matrix(rep(sc5.8,length(cl5.attr)),nrow=length(cl5.attr),ncol=1),
matrix(rep(sc5.9,length(cl5.attr)),nrow=length(cl5.attr),ncol=1),
matrix(rep(sc5.10,length(cl5.attr)),nrow=length(cl5.attr),ncol=1)
),
#Attribute column
rep(cl5.attr,10),
#Data column (0=absence, 1=presence)
cl5.dat
)
#print(rbind(cl1.block,cl2.block,cl3.block,cl4.block,cl5.block))



#Fiber class:
cl6<-as.character(dat[39,1])
#Fiber subclass
sc6.1<-as.character(dat[40,1])
sc6.2<-as.character(dat[41,1])
sc6.3<-as.character(dat[42,1])
#Fiber attributes
cl6.attr<-apply(dat[39,2:5],1,as.character )
#Fiber class/subclass data
tmp<-dat[40:42,2:5]
cl6.dat<-as.numeric(matrix(t(tmp),nrow=(dim(tmp)[1]*dim(tmp)[2]),ncol=1))

#Build the class block of the dataframe
cl6.block<-cbind(
#Class column
rep(cl6, length(cl6.dat) ),
#Subclass column
rbind(
matrix(rep(sc6.1,length(cl6.attr)),nrow=length(cl6.attr),ncol=1),
matrix(rep(sc6.2,length(cl6.attr)),nrow=length(cl6.attr),ncol=1),
matrix(rep(sc6.3,length(cl6.attr)),nrow=length(cl6.attr),ncol=1)
),
#Attribute column
rep(cl6.attr,3),
#Data column (0=absence, 1=presence)
cl6.dat
)
#print(rbind(cl1.block,cl2.block,cl3.block,cl4.block,cl5.block,cl6.block))



#Fiber class:
cl7<-as.character(dat[43,1])
#Fiber subclass
sc7.1<-as.character(dat[44,1])
sc7.2<-as.character(dat[45,1])
sc7.3<-as.character(dat[46,1])
sc7.4<-as.character(dat[47,1])
sc7.5<-as.character(dat[48,1])
sc7.6<-as.character(dat[49,1])
sc7.7<-as.character(dat[50,1])
sc7.8<-as.character(dat[51,1])
#Fiber attributes
cl7.attr<-apply(dat[43,2:7],1,as.character )
#Fiber class/subclass data
tmp<-dat[44:51,2:7]
cl7.dat<-as.numeric(matrix(t(tmp),nrow=(dim(tmp)[1]*dim(tmp)[2]),ncol=1))

#Build the class block of the dataframe
cl7.block<-cbind(
#Class column
rep(cl7, length(cl7.dat) ),
#Subclass column
rbind(
matrix(rep(sc7.1,length(cl7.attr)),nrow=length(cl7.attr),ncol=1),
matrix(rep(sc7.2,length(cl7.attr)),nrow=length(cl7.attr),ncol=1),
matrix(rep(sc7.3,length(cl7.attr)),nrow=length(cl7.attr),ncol=1),
matrix(rep(sc7.4,length(cl7.attr)),nrow=length(cl7.attr),ncol=1),
matrix(rep(sc7.5,length(cl7.attr)),nrow=length(cl7.attr),ncol=1),
matrix(rep(sc7.6,length(cl7.attr)),nrow=length(cl7.attr),ncol=1),
matrix(rep(sc7.7,length(cl7.attr)),nrow=length(cl7.attr),ncol=1),
matrix(rep(sc7.8,length(cl7.attr)),nrow=length(cl7.attr),ncol=1)
),
#Attribute column
rep(cl7.attr,8),
#Data column (0=absence, 1=presence)
cl7.dat
)
#print(rbind(cl1.block,cl2.block,cl3.block,cl4.block,cl5.block,cl6.block,cl7.block))



#Fiber class:
cl8<-as.character(dat[52,1])
#Fiber subclass
sc8.1<-as.character(dat[53,1])
sc8.2<-as.character(dat[54,1])
sc8.3<-as.character(dat[55,1])
sc8.4<-as.character(dat[56,1])
sc8.5<-as.character(dat[57,1])
sc8.6<-as.character(dat[58,1])
sc8.7<-as.character(dat[59,1])
sc8.8<-as.character(dat[60,1])
#Fiber attributes
cl8.attr<-apply(dat[52,2:12],1,as.character )
#Fiber class/subclass data
tmp<-dat[53:60,2:12]
cl8.dat<-as.numeric(matrix(t(tmp),nrow=(dim(tmp)[1]*dim(tmp)[2]),ncol=1))

#Build the class block of the dataframe
cl8.block<-cbind(
#Class column
rep(cl8, length(cl8.dat) ),
#Subclass column
rbind(
matrix(rep(sc8.1,length(cl8.attr)),nrow=length(cl8.attr),ncol=1),
matrix(rep(sc8.2,length(cl8.attr)),nrow=length(cl8.attr),ncol=1),
matrix(rep(sc8.3,length(cl8.attr)),nrow=length(cl8.attr),ncol=1),
matrix(rep(sc8.4,length(cl8.attr)),nrow=length(cl8.attr),ncol=1),
matrix(rep(sc8.5,length(cl8.attr)),nrow=length(cl8.attr),ncol=1),
matrix(rep(sc8.6,length(cl8.attr)),nrow=length(cl8.attr),ncol=1),
matrix(rep(sc8.7,length(cl8.attr)),nrow=length(cl8.attr),ncol=1),
matrix(rep(sc8.8,length(cl8.attr)),nrow=length(cl8.attr),ncol=1)
),
#Attribute column
rep(cl8.attr,8),
#Data column (0=absence, 1=presence)
cl8.dat
)

dust.dat<-rbind(cl1.block,cl2.block,cl3.block,cl4.block,cl5.block,cl6.block,cl7.block,cl8.block)

#Swap out NAs for 0s in last column:
tmpv<-dust.dat[,4]
tmpv[is.na(tmpv)]<-0
tmpv<-as.numeric(tmpv)
dust.dat[,4]<-tmpv

#print(dim(dust.dat))

return(dust.dat)

}


#' Read many dust data files stored in CSV format
#'
#' XXXX
#'
#' The function will XXXX
#'
#' @param XX The XX
#' @return The function will XX
#'
#'
#' @export
read.dust.files<-function(root.path,num.files)
{

dat<-NULL
for(i in 1:num.files)
  {
   for(j in 1:5)
     {
      infile<-paste(root.path,as.character(i),".",as.character(j),".xlsx",sep="")
      #print(infile)
      info<-read.dust.file(infile)
      data.vec<-info[[1]]
      #data.vec<-t(info[,4])
      dat<-rbind(dat,data.vec)
      print(paste("Done sample",i,"replicate",j))
     }
  }

rownames(dat)<-NULL
return(dat)

}