Set the max value in colormap when using scale_color_viridis












5















Here is the code:



pic = ggplot(df_2, 

aes(x = df_2$X, xend = df_2$X + df_2$dx, y = df_2$Y, yend = df_2$Y + df_2$dy, color =  df_2$speedkt)) +

labs(title ="Surface Currents", x = "Longitude", y = "Latitude", colour="Speed (kts)") +    

geom_segment(alpha = 0.7, arrow = arrow(length = unit(0.1,"cm"))) + coord_fixed() +

theme(panel.background = element_rect(fill = "transparent",colour = NA), plot.background = element_rect(fill = "transparent",colour = NA)) +

viridis::scale_color_viridis(option = "B", direction = -1)


You can see the color gradient follows the value of df_2$speedkt . The maximum value of df_2$speedkt is around 2.6.



So, the maximum value of the colormap in the legend is around 2.8.



But I wish to change the maximum value of the colormap to 4.0.



What I can do?



Colormap in Legend Highlighted






r ggplot2 viridis







share|improve this question




















  • 1





    Note that ggplot2 has these scales build in nowadays, scale_color_viridis_c in this case.

    – Axeman
    Nov 14 '18 at 5:03






  • 2





    FYI, no need to use df_2$ inside ggplot call. You can just use bare column names

    – Tung
    Nov 14 '18 at 5:04
















5















Here is the code:



pic = ggplot(df_2, 

aes(x = df_2$X, xend = df_2$X + df_2$dx, y = df_2$Y, yend = df_2$Y + df_2$dy, color =  df_2$speedkt)) +

labs(title ="Surface Currents", x = "Longitude", y = "Latitude", colour="Speed (kts)") +    

geom_segment(alpha = 0.7, arrow = arrow(length = unit(0.1,"cm"))) + coord_fixed() +

theme(panel.background = element_rect(fill = "transparent",colour = NA), plot.background = element_rect(fill = "transparent",colour = NA)) +

viridis::scale_color_viridis(option = "B", direction = -1)


You can see the color gradient follows the value of df_2$speedkt . The maximum value of df_2$speedkt is around 2.6.



So, the maximum value of the colormap in the legend is around 2.8.



But I wish to change the maximum value of the colormap to 4.0.



What I can do?



Colormap in Legend Highlighted






r ggplot2 viridis







share|improve this question




















  • 1





    Note that ggplot2 has these scales build in nowadays, scale_color_viridis_c in this case.

    – Axeman
    Nov 14 '18 at 5:03






  • 2





    FYI, no need to use df_2$ inside ggplot call. You can just use bare column names

    – Tung
    Nov 14 '18 at 5:04














5












5








5








Here is the code:



pic = ggplot(df_2, 

aes(x = df_2$X, xend = df_2$X + df_2$dx, y = df_2$Y, yend = df_2$Y + df_2$dy, color =  df_2$speedkt)) +

labs(title ="Surface Currents", x = "Longitude", y = "Latitude", colour="Speed (kts)") +    

geom_segment(alpha = 0.7, arrow = arrow(length = unit(0.1,"cm"))) + coord_fixed() +

theme(panel.background = element_rect(fill = "transparent",colour = NA), plot.background = element_rect(fill = "transparent",colour = NA)) +

viridis::scale_color_viridis(option = "B", direction = -1)


You can see the color gradient follows the value of df_2$speedkt . The maximum value of df_2$speedkt is around 2.6.



So, the maximum value of the colormap in the legend is around 2.8.



But I wish to change the maximum value of the colormap to 4.0.



What I can do?



Colormap in Legend Highlighted






r ggplot2 viridis







share|improve this question
















Here is the code:



pic = ggplot(df_2, 

aes(x = df_2$X, xend = df_2$X + df_2$dx, y = df_2$Y, yend = df_2$Y + df_2$dy, color =  df_2$speedkt)) +

labs(title ="Surface Currents", x = "Longitude", y = "Latitude", colour="Speed (kts)") +    

geom_segment(alpha = 0.7, arrow = arrow(length = unit(0.1,"cm"))) + coord_fixed() +

theme(panel.background = element_rect(fill = "transparent",colour = NA), plot.background = element_rect(fill = "transparent",colour = NA)) +

viridis::scale_color_viridis(option = "B", direction = -1)


You can see the color gradient follows the value of df_2$speedkt . The maximum value of df_2$speedkt is around 2.6.



So, the maximum value of the colormap in the legend is around 2.8.



But I wish to change the maximum value of the colormap to 4.0.



What I can do?



Colormap in Legend Highlighted






r ggplot2 viridis




r ggplot2 viridis






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited Nov 14 '18 at 7:15









zx8754

29.7k76399




29.7k76399










asked Nov 14 '18 at 4:57









Justin Justin

666




666








  • 1





    Note that ggplot2 has these scales build in nowadays, scale_color_viridis_c in this case.

    – Axeman
    Nov 14 '18 at 5:03






  • 2





    FYI, no need to use df_2$ inside ggplot call. You can just use bare column names

    – Tung
    Nov 14 '18 at 5:04














  • 1





    Note that ggplot2 has these scales build in nowadays, scale_color_viridis_c in this case.

    – Axeman
    Nov 14 '18 at 5:03






  • 2





    FYI, no need to use df_2$ inside ggplot call. You can just use bare column names

    – Tung
    Nov 14 '18 at 5:04








1




1





Note that ggplot2 has these scales build in nowadays, scale_color_viridis_c in this case.

– Axeman
Nov 14 '18 at 5:03





Note that ggplot2 has these scales build in nowadays, scale_color_viridis_c in this case.

– Axeman
Nov 14 '18 at 5:03




2




2





FYI, no need to use df_2$ inside ggplot call. You can just use bare column names

– Tung
Nov 14 '18 at 5:04





FYI, no need to use df_2$ inside ggplot call. You can just use bare column names

– Tung
Nov 14 '18 at 5:04












1 Answer
1






active

oldest

votes


















4














To answer your main question, you should be able to pass limits = c(0, 4) as an argument to viridis::scale_color_viridis(), i.e.



viridis::scale_color_viridis(option = "B", direction = -1, limits = c(0, 4))


A couple of other points:




  • Newer versions of ggplot2 have viridis scales built in, so you should be able to use:


scale_color_viridis_c(option = "B", direction = -1, limits = c(0, 4))



  • In general, it's better not to use df$col in aes(), just use the column name, e.g.


ggplot(df_2, aes(x = X, xend = X + dx, y = Y))


ggplot will look up the column names within the dataframe.






share|improve this answer
























  • can u insert the output ?

    – sai saran
    Nov 14 '18 at 5:26






  • 2





    @saisaran: The question doesn't provide an easy way to reproduce the data/plot, so I can't show how it changes the plot.

    – Marius
    Nov 14 '18 at 5:30











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1 Answer
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1 Answer
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active

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active

oldest

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active

oldest

votes









4














To answer your main question, you should be able to pass limits = c(0, 4) as an argument to viridis::scale_color_viridis(), i.e.



viridis::scale_color_viridis(option = "B", direction = -1, limits = c(0, 4))


A couple of other points:




  • Newer versions of ggplot2 have viridis scales built in, so you should be able to use:


scale_color_viridis_c(option = "B", direction = -1, limits = c(0, 4))



  • In general, it's better not to use df$col in aes(), just use the column name, e.g.


ggplot(df_2, aes(x = X, xend = X + dx, y = Y))


ggplot will look up the column names within the dataframe.






share|improve this answer
























  • can u insert the output ?

    – sai saran
    Nov 14 '18 at 5:26






  • 2





    @saisaran: The question doesn't provide an easy way to reproduce the data/plot, so I can't show how it changes the plot.

    – Marius
    Nov 14 '18 at 5:30
















4














To answer your main question, you should be able to pass limits = c(0, 4) as an argument to viridis::scale_color_viridis(), i.e.



viridis::scale_color_viridis(option = "B", direction = -1, limits = c(0, 4))


A couple of other points:




  • Newer versions of ggplot2 have viridis scales built in, so you should be able to use:


scale_color_viridis_c(option = "B", direction = -1, limits = c(0, 4))



  • In general, it's better not to use df$col in aes(), just use the column name, e.g.


ggplot(df_2, aes(x = X, xend = X + dx, y = Y))


ggplot will look up the column names within the dataframe.






share|improve this answer
























  • can u insert the output ?

    – sai saran
    Nov 14 '18 at 5:26






  • 2





    @saisaran: The question doesn't provide an easy way to reproduce the data/plot, so I can't show how it changes the plot.

    – Marius
    Nov 14 '18 at 5:30














4












4








4







To answer your main question, you should be able to pass limits = c(0, 4) as an argument to viridis::scale_color_viridis(), i.e.



viridis::scale_color_viridis(option = "B", direction = -1, limits = c(0, 4))


A couple of other points:




  • Newer versions of ggplot2 have viridis scales built in, so you should be able to use:


scale_color_viridis_c(option = "B", direction = -1, limits = c(0, 4))



  • In general, it's better not to use df$col in aes(), just use the column name, e.g.


ggplot(df_2, aes(x = X, xend = X + dx, y = Y))


ggplot will look up the column names within the dataframe.






share|improve this answer













To answer your main question, you should be able to pass limits = c(0, 4) as an argument to viridis::scale_color_viridis(), i.e.



viridis::scale_color_viridis(option = "B", direction = -1, limits = c(0, 4))


A couple of other points:




  • Newer versions of ggplot2 have viridis scales built in, so you should be able to use:


scale_color_viridis_c(option = "B", direction = -1, limits = c(0, 4))



  • In general, it's better not to use df$col in aes(), just use the column name, e.g.


ggplot(df_2, aes(x = X, xend = X + dx, y = Y))


ggplot will look up the column names within the dataframe.







share|improve this answer












share|improve this answer



share|improve this answer










answered Nov 14 '18 at 5:02









MariusMarius

31.9k97174




31.9k97174













  • can u insert the output ?

    – sai saran
    Nov 14 '18 at 5:26






  • 2





    @saisaran: The question doesn't provide an easy way to reproduce the data/plot, so I can't show how it changes the plot.

    – Marius
    Nov 14 '18 at 5:30



















  • can u insert the output ?

    – sai saran
    Nov 14 '18 at 5:26






  • 2





    @saisaran: The question doesn't provide an easy way to reproduce the data/plot, so I can't show how it changes the plot.

    – Marius
    Nov 14 '18 at 5:30

















can u insert the output ?

– sai saran
Nov 14 '18 at 5:26





can u insert the output ?

– sai saran
Nov 14 '18 at 5:26




2




2





@saisaran: The question doesn't provide an easy way to reproduce the data/plot, so I can't show how it changes the plot.

– Marius
Nov 14 '18 at 5:30





@saisaran: The question doesn't provide an easy way to reproduce the data/plot, so I can't show how it changes the plot.

– Marius
Nov 14 '18 at 5:30


















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