plot shapefile variable: Error invalid gray level, must be in [0,1]. R











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I have a shapefile which I have run through a spatial regression model in R.



I have pulled out the residuals from the regression model and added them as a new variable to the original shapefile. I am hoping to map these residuals but am encountering some issues.



Here is my code:



     plot(shapefile,col=gray(shapefile@data$residuals))


I am receiving this error:



  invalid gray level, must be in [0,1].


Am I correct in assuming this is to do with the values of the residuals? They span from -40 to +20. Is there a way to change this scale from 0-1 to a larger scale? or an easier way to plot these please?



I have also tried spplot:



     spplot(shape@data$residuals)


and receive the error:



 Error in (function (classes, fdef, mtable)  : 
unable to find an inherited method for function ‘spplot’ for signature
‘"numeric"’









share|improve this question






















  • Aye the gray() function needs the first parameter to be [0,1] bounded. You can use scales::rescale() to scale your [-40,20] to [0,1]
    – hrbrmstr
    Nov 11 at 17:13










  • Unless you are printing in black and white, its usually better to plot residuals with a diverging palette so 0 is a neutral colour, and maybe reds are +ve and blues are -ve. You might also look at the tmap package for mapping spatial data.
    – Spacedman
    Nov 11 at 17:29















up vote
0
down vote

favorite












I have a shapefile which I have run through a spatial regression model in R.



I have pulled out the residuals from the regression model and added them as a new variable to the original shapefile. I am hoping to map these residuals but am encountering some issues.



Here is my code:



     plot(shapefile,col=gray(shapefile@data$residuals))


I am receiving this error:



  invalid gray level, must be in [0,1].


Am I correct in assuming this is to do with the values of the residuals? They span from -40 to +20. Is there a way to change this scale from 0-1 to a larger scale? or an easier way to plot these please?



I have also tried spplot:



     spplot(shape@data$residuals)


and receive the error:



 Error in (function (classes, fdef, mtable)  : 
unable to find an inherited method for function ‘spplot’ for signature
‘"numeric"’









share|improve this question






















  • Aye the gray() function needs the first parameter to be [0,1] bounded. You can use scales::rescale() to scale your [-40,20] to [0,1]
    – hrbrmstr
    Nov 11 at 17:13










  • Unless you are printing in black and white, its usually better to plot residuals with a diverging palette so 0 is a neutral colour, and maybe reds are +ve and blues are -ve. You might also look at the tmap package for mapping spatial data.
    – Spacedman
    Nov 11 at 17:29













up vote
0
down vote

favorite









up vote
0
down vote

favorite











I have a shapefile which I have run through a spatial regression model in R.



I have pulled out the residuals from the regression model and added them as a new variable to the original shapefile. I am hoping to map these residuals but am encountering some issues.



Here is my code:



     plot(shapefile,col=gray(shapefile@data$residuals))


I am receiving this error:



  invalid gray level, must be in [0,1].


Am I correct in assuming this is to do with the values of the residuals? They span from -40 to +20. Is there a way to change this scale from 0-1 to a larger scale? or an easier way to plot these please?



I have also tried spplot:



     spplot(shape@data$residuals)


and receive the error:



 Error in (function (classes, fdef, mtable)  : 
unable to find an inherited method for function ‘spplot’ for signature
‘"numeric"’









share|improve this question













I have a shapefile which I have run through a spatial regression model in R.



I have pulled out the residuals from the regression model and added them as a new variable to the original shapefile. I am hoping to map these residuals but am encountering some issues.



Here is my code:



     plot(shapefile,col=gray(shapefile@data$residuals))


I am receiving this error:



  invalid gray level, must be in [0,1].


Am I correct in assuming this is to do with the values of the residuals? They span from -40 to +20. Is there a way to change this scale from 0-1 to a larger scale? or an easier way to plot these please?



I have also tried spplot:



     spplot(shape@data$residuals)


and receive the error:



 Error in (function (classes, fdef, mtable)  : 
unable to find an inherited method for function ‘spplot’ for signature
‘"numeric"’






r regression






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asked Nov 11 at 16:35









Will.S89

857




857












  • Aye the gray() function needs the first parameter to be [0,1] bounded. You can use scales::rescale() to scale your [-40,20] to [0,1]
    – hrbrmstr
    Nov 11 at 17:13










  • Unless you are printing in black and white, its usually better to plot residuals with a diverging palette so 0 is a neutral colour, and maybe reds are +ve and blues are -ve. You might also look at the tmap package for mapping spatial data.
    – Spacedman
    Nov 11 at 17:29


















  • Aye the gray() function needs the first parameter to be [0,1] bounded. You can use scales::rescale() to scale your [-40,20] to [0,1]
    – hrbrmstr
    Nov 11 at 17:13










  • Unless you are printing in black and white, its usually better to plot residuals with a diverging palette so 0 is a neutral colour, and maybe reds are +ve and blues are -ve. You might also look at the tmap package for mapping spatial data.
    – Spacedman
    Nov 11 at 17:29
















Aye the gray() function needs the first parameter to be [0,1] bounded. You can use scales::rescale() to scale your [-40,20] to [0,1]
– hrbrmstr
Nov 11 at 17:13




Aye the gray() function needs the first parameter to be [0,1] bounded. You can use scales::rescale() to scale your [-40,20] to [0,1]
– hrbrmstr
Nov 11 at 17:13












Unless you are printing in black and white, its usually better to plot residuals with a diverging palette so 0 is a neutral colour, and maybe reds are +ve and blues are -ve. You might also look at the tmap package for mapping spatial data.
– Spacedman
Nov 11 at 17:29




Unless you are printing in black and white, its usually better to plot residuals with a diverging palette so 0 is a neutral colour, and maybe reds are +ve and blues are -ve. You might also look at the tmap package for mapping spatial data.
– Spacedman
Nov 11 at 17:29












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col = grey() produces HEX codes for grey scale based on the values placed inside. Yes, these numbers should be between 0:1. If you are trying to get an individual grey HEX code for each unique residual, you can do this by using the length and unique function. Below is an example where we have different grey scale for each group is our data frame:



Group <- c(1,1,1,1,2,2,2,2,3,3,3,3)
Year <- c(2006,2007,2008,2009,2006,2007,2008,2009,2006,2007,2008,2009)
Qtr.1 <- as.numeric(c(15,13,22,13,12,16,13,23,11,15,17,14))
DF <- data.frame(Group,Year,Qtr.1)

#to get HEX for each unique input
c <- grey(1:length(unique(DF$Group))/length(unique(DF$Group)))

c
> [1] "#555555" "#AAAAAA" "#FFFFFF"

#Without Grey
plot(DF$Year,DF$Qtr.1)

#With Grey
plot(DF$Year,DF$Qtr.1, col = c[Group])


Note that I didn't make a choice about the grey HEX codes that were produced, and group 3's HEX code is so faint that is hard to spot. Also, we needed to index on Group at the end of the col argument. As others have mentioned, there are likely better ways to go about this than grey scale and the base plot function. Looking towards other packages is likely a better option for customized visualization (i.e. ggplot or what others have noted).



Check this nice summary for more info on col






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    col = grey() produces HEX codes for grey scale based on the values placed inside. Yes, these numbers should be between 0:1. If you are trying to get an individual grey HEX code for each unique residual, you can do this by using the length and unique function. Below is an example where we have different grey scale for each group is our data frame:



    Group <- c(1,1,1,1,2,2,2,2,3,3,3,3)
    Year <- c(2006,2007,2008,2009,2006,2007,2008,2009,2006,2007,2008,2009)
    Qtr.1 <- as.numeric(c(15,13,22,13,12,16,13,23,11,15,17,14))
    DF <- data.frame(Group,Year,Qtr.1)

    #to get HEX for each unique input
    c <- grey(1:length(unique(DF$Group))/length(unique(DF$Group)))

    c
    > [1] "#555555" "#AAAAAA" "#FFFFFF"

    #Without Grey
    plot(DF$Year,DF$Qtr.1)

    #With Grey
    plot(DF$Year,DF$Qtr.1, col = c[Group])


    Note that I didn't make a choice about the grey HEX codes that were produced, and group 3's HEX code is so faint that is hard to spot. Also, we needed to index on Group at the end of the col argument. As others have mentioned, there are likely better ways to go about this than grey scale and the base plot function. Looking towards other packages is likely a better option for customized visualization (i.e. ggplot or what others have noted).



    Check this nice summary for more info on col






    share|improve this answer



























      up vote
      0
      down vote













      col = grey() produces HEX codes for grey scale based on the values placed inside. Yes, these numbers should be between 0:1. If you are trying to get an individual grey HEX code for each unique residual, you can do this by using the length and unique function. Below is an example where we have different grey scale for each group is our data frame:



      Group <- c(1,1,1,1,2,2,2,2,3,3,3,3)
      Year <- c(2006,2007,2008,2009,2006,2007,2008,2009,2006,2007,2008,2009)
      Qtr.1 <- as.numeric(c(15,13,22,13,12,16,13,23,11,15,17,14))
      DF <- data.frame(Group,Year,Qtr.1)

      #to get HEX for each unique input
      c <- grey(1:length(unique(DF$Group))/length(unique(DF$Group)))

      c
      > [1] "#555555" "#AAAAAA" "#FFFFFF"

      #Without Grey
      plot(DF$Year,DF$Qtr.1)

      #With Grey
      plot(DF$Year,DF$Qtr.1, col = c[Group])


      Note that I didn't make a choice about the grey HEX codes that were produced, and group 3's HEX code is so faint that is hard to spot. Also, we needed to index on Group at the end of the col argument. As others have mentioned, there are likely better ways to go about this than grey scale and the base plot function. Looking towards other packages is likely a better option for customized visualization (i.e. ggplot or what others have noted).



      Check this nice summary for more info on col






      share|improve this answer

























        up vote
        0
        down vote










        up vote
        0
        down vote









        col = grey() produces HEX codes for grey scale based on the values placed inside. Yes, these numbers should be between 0:1. If you are trying to get an individual grey HEX code for each unique residual, you can do this by using the length and unique function. Below is an example where we have different grey scale for each group is our data frame:



        Group <- c(1,1,1,1,2,2,2,2,3,3,3,3)
        Year <- c(2006,2007,2008,2009,2006,2007,2008,2009,2006,2007,2008,2009)
        Qtr.1 <- as.numeric(c(15,13,22,13,12,16,13,23,11,15,17,14))
        DF <- data.frame(Group,Year,Qtr.1)

        #to get HEX for each unique input
        c <- grey(1:length(unique(DF$Group))/length(unique(DF$Group)))

        c
        > [1] "#555555" "#AAAAAA" "#FFFFFF"

        #Without Grey
        plot(DF$Year,DF$Qtr.1)

        #With Grey
        plot(DF$Year,DF$Qtr.1, col = c[Group])


        Note that I didn't make a choice about the grey HEX codes that were produced, and group 3's HEX code is so faint that is hard to spot. Also, we needed to index on Group at the end of the col argument. As others have mentioned, there are likely better ways to go about this than grey scale and the base plot function. Looking towards other packages is likely a better option for customized visualization (i.e. ggplot or what others have noted).



        Check this nice summary for more info on col






        share|improve this answer














        col = grey() produces HEX codes for grey scale based on the values placed inside. Yes, these numbers should be between 0:1. If you are trying to get an individual grey HEX code for each unique residual, you can do this by using the length and unique function. Below is an example where we have different grey scale for each group is our data frame:



        Group <- c(1,1,1,1,2,2,2,2,3,3,3,3)
        Year <- c(2006,2007,2008,2009,2006,2007,2008,2009,2006,2007,2008,2009)
        Qtr.1 <- as.numeric(c(15,13,22,13,12,16,13,23,11,15,17,14))
        DF <- data.frame(Group,Year,Qtr.1)

        #to get HEX for each unique input
        c <- grey(1:length(unique(DF$Group))/length(unique(DF$Group)))

        c
        > [1] "#555555" "#AAAAAA" "#FFFFFF"

        #Without Grey
        plot(DF$Year,DF$Qtr.1)

        #With Grey
        plot(DF$Year,DF$Qtr.1, col = c[Group])


        Note that I didn't make a choice about the grey HEX codes that were produced, and group 3's HEX code is so faint that is hard to spot. Also, we needed to index on Group at the end of the col argument. As others have mentioned, there are likely better ways to go about this than grey scale and the base plot function. Looking towards other packages is likely a better option for customized visualization (i.e. ggplot or what others have noted).



        Check this nice summary for more info on col







        share|improve this answer














        share|improve this answer



        share|improve this answer








        edited Nov 11 at 17:47

























        answered Nov 11 at 17:04









        Peter_Evan

        2138




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