ggplot2: passing a continuous variable to "shape" within a wrapper

Question

So I'm trying to write a function which creates scatter plots.

Depending on the data, I may want the value of V1 or V2 to determine the shape/colour of the point. The data in V1 only takes particular values, as does V2, but both look continuous to R/ggplot so I treat them as.factor. I might also regress buy V1 or V2.

This works fine:

p1<-ggplot(sigmas.table,
           aes(x=V4,y=V5, color=as.factor(V2),shape=as.factor(V1)))+  
    geom_point(size=4)+
    stat_smooth(aes(group=as.factor(V2)),method=lm,formula=y~poly(x,1),size=1)

But to wrap this in a function, first I have to switch to aes_string so that I can read in the colum titles (I also vary the x-axis value), but now I cant convince ggplot that V1/V2 only take a finite number of values to assign different points to. colour sort of works, but assigns a continuous shade rather than different colours, so it too is treating the data as continuous:

scatter.plot<- function(s.table,x.var, col.var, shape.var, line.var){
              ploti <- ggplot(s.table,
                              aes_string(x=x.var,y="V5", color=as.factor(col.var),shape=as.factor(shape.var)))+
                       geom_point(size=4)+
                       stat_smooth(aes_string(group=as.factor(line.var)),method=lm,formula=y~poly(x,1),size=1)+
               return(ploti)}

p1 <- scatter.plot(sigmas.table,"V4","V2","V1","V2")

returns

Error: A continuous variable can not be mapped to shape

I'm sure there are plenty of kludges available, but it seems to me (perhaps in my naivete) like there could be a real solution. Any and all help appreciated.

P.s. here's a sample of the sigmas table:

     V1  V2         V3        V4         V5         V6
 1: 0.3  16 0.12791584 0.3454941 0.19463432 0.04231422
 2: 0.5  16 0.09908318 0.4460310 0.06286376 0.05462742
 3: 0.7  16 0.08374057 0.5277510 0.03820782 0.06463604
 4: 0.9  16 0.07385224 0.5984134 0.03026121 0.07329038
 5: 0.3  32 0.09045016 0.2443013 0.17003319 0.02992067
 6: 0.5  32 0.07006239 0.3153916 0.04250670 0.03862742
 7: 0.7  32 0.05921353 0.3731763 0.02563209 0.04570458
 8: 0.9  32 0.05222142 0.4231422 0.02037799 0.05182412
 9: 0.3  64 0.06395792 0.1727471 0.14072683 0.02115711
10: 0.5  64 0.04954159 0.2230155 0.03286223 0.02731371
11: 0.7  64 0.04187029 0.2638755 0.01946985 0.03231802
12: 0.9  64 0.03692612 0.2992067 0.01475039 0.03664519
13: 0.3 128 0.04522508 0.1221506 0.11012266 0.01496034
14: 0.5 128 0.03503120 0.1576958 0.02260296 0.01931371
15: 0.7 128 0.02960676 0.1865882 0.01317059 0.02285229
16: 0.9 128 0.02611071 0.2115711 0.01036970 0.02591206

Solution

As stated in my comment, you should transform your original data, if it actually contains factors. However, you can also do it in your function:

scatter.plot<- function(s.table,x.var, col.var, shape.var, line.var){
  s.table[,col.var] <- as.factor(s.table[,col.var])
  s.table[,shape.var] <- as.factor(s.table[,shape.var])
  s.table[,line.var] <- as.factor(s.table[,line.var])

  ggplot(s.table, aes_string(x=x.var, y="V5", color=col.var, shape=shape.var)) +
    geom_point(size=4) +
    stat_smooth(aes_string(group=line.var), 
                method=lm, formula=y~poly(x,1), size=1)
    }