[R] Odp: what is the mistake?? the coding still not function. no result display

[Petr PIKAL]

Hi
> 
> [R] what is the mistake?? the coding still not function. no result 
display
> 
> #    lda.r
> > #
> > #    Author:    Amsha Nahid, Jairus Bowne, Gerard Murray
> > #    Purpose:    Perform Linear Discriminant Analysis (LDA)
> > #
> > #    Input:    Data matrix as specified in Data-matrix-format.pdf
> > #    Output:    LDA plot
> > #
> > #    Notes:    Missing values (if any) are replaced by the half of the 
lowest
> > #              value in the entire data matrix.
> > 
> > 
> > #
> > #    Load necessary libraries, and install them if they are missing
> > #
> > tryCatch(library(MASS), error=function(err)
> +     # if this produces an error:
> +     install.packages("MASS",repos="http://cran.ms.unimelb.edu.au/"))
> > 
> > #
> > #    Prepare the data matrix
> > #
> > # Read in the .csv file
> > data<-read.csv("C:/Users/nadya/Desktop/praktikal 
UTM/TASK2/new(40data)S2 100 
> >EMS EPI 300-399.csv", sep=",", row.names=1, header=TRUE)
> > # Get groups information
> > groups<-data[,1]
> > # Remove groups for data processing
> > lda_data<-data[,-1]
> > # Replace any missing values (see Notes)
> > lda_data[is.na(lda_data)]<-0.5*(min(lda_data,na.rm=TRUE))
> > 
> > #
> > #    Perform the LDA
> > #
> > lda_result<-lda(lda_data,groups)
> Error in lda.default(x, grouping, ...) : 
>   variables  1  3  5  8 10 15 17 20 27 29 34 appear to be constant 
within groups

The problem seems to be with your data, which in some groups are constant.

Try 
split(lda_data, groups) 

or

sapply(split(lda_data, groups), length)

and see your result.

Regards
Petr
> > 
> > #
> > #    Generate the figures (on screen)
> > #
> > #    Image generation - function definition
> > pic_onscr<-function(matrix, title, cex_val=1)
> +     {x11()
> +     par(mgp=c(5,2,0),                           # axis margins
> +                                                 # (title, labels, 
line)
> +         mar=c(7,4,4,2),                         # plot margins 
(b,l,t,r)
> +         las=1)                                  # horizontal labels
> +     plot(matrix,                                # data to plot
> +         cex=cex_val,                            # font size
> +         dimen=2                                 # dimensions to plot
> +         )
> +     title(main=title)                           # title of plot
> +     }
> > # Plot LDA scores with sample names
> > pic_onscr(lda_result,"Linear Discriminant Analysis")
> Error in plot(matrix, cex = cex_val, dimen = 2) : 
>   error in evaluating the argument 'x' in selecting a method for 
function 
> 'plot': Error: object 'lda_result' not found
> > # For plotting with larger font size, use a different value of cex:
> > # pic_onscr(lda_result, "LDA Plot", dimen=2, cex=3)
> > 
> > #
> > #    Generate figures as image files
> > #
> > #    (Uncomment blocks as necessary)
> > 
> > ##### jpeg #####
> > # pic_jpg<-function(filename, matrix, title, cex_val=1)
> > #     {# Start jpeg device with basic settings
> > #     jpeg(filename,
> > #         quality=100,                            # image quality 
(percent)
> > #         bg="white",                             # background colour
> > #         res=300,                                # image resolution 
(dpi)
> > #         units="in", width=8.3, height=5.8       # image dimensions 
(inches)
> > #         )
> > #     par(mgp=c(5,2,0),                           # axis margins 
> > #                                                 #  (title, labels, 
line)
> > #         mar=c(7,4,4,2),                         # plot margins 
(b,l,t,r)
> > #         las=1                                   # horizontal labels
> > #         )
> > #     # Draw the plot
> > #     plot(matrix,                                # data to plot
> > #         cex=cex_val,                            # font size
> > #         dimen=2                                 # dimensions to plot
> > #         )
> > #     title(main=title)                           # title of plot
> > # 
> > #     dev.off()
> > #     }
> > # pic_jpg("LDA.jpg", lda_result, "Linear Discriminant Analysis")
> > ##### end jpeg #####
> > 
> > ##### png #####
> > # pic_png<-function(filename, matrix, title, cex_val=1)
> > #     {# Start png device with basic settings
> > #     png(filename,
> > #         bg="white",                             # background colour
> > #         res=300,                                # image resolution 
(dpi)
> > #         units="in", width=8.3, height=5.8       # image dimensions 
(inches)
> > #         )
> > #     par(mgp=c(5,2,0),                           # axis margins 
> > #                                                 #  (title, labels, 
line)
> > #         mar=c(7,4,4,2),                         # plot margins 
(b,l,t,r)
> > #         las=1                                   # horizontal labels
> > #         )
> > #     # Draw the plot
> > #     plot(matrix,                                # data to plot
> > #         cex=cex_val,                            # font size
> > #         dimen=2                                 # dimensions to plot
> > #         )
> > #     title(main=title)                           # title of plot
> > # 
> > #     dev.off()
> > #     }
> > # pic_png("LDA.png", lda_result, "Linear Discriminant Analysis")
> > ##### end png #####
> > 
> > ##### tiff #####
> > # pic_tiff<-function(filename, matrix, title, cex_val=1)
> > #     {# Start tiff device with basic settings
> > #     tiff(filename,
> > #         bg="white",                             # background colour
> > #         res=300,                                # image resolution 
(dpi)
> > #         units="in", width=8.3, height=5.8,      # image dimensions 
(inches)
> > #         compression="none"                      # image compression 
> > #                                                 #  (one of none, 
lzw, zip)
> > #         )
> > #     par(mgp=c(5,2,0),                           # axis margins 
> > #                                                 #  (title, labels, 
line)
> > #         mar=c(7,4,4,2),                         # plot margins 
(b,l,t,r)
> > #         las=1                                   # horizontal labels
> > #         )
> > #     # Draw the plot
> > #     plot(matrix,                                # data to plot
> > #         cex=cex_val,                            # font size
> > #         dimen=2                                 # dimensions to plot
> > #         )
> > #     title(main=title)                           # title of plot
> > # 
> > #     dev.off()
> > #     }
> > # pic_tiff("LDA.tif", lda_result, "Linear Discriminant Analysis")
> > ##### end tiff #####
> > 
> 
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> 
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