I have a time series dataset with spatial data (x,y coordinates). Each point is static in location, but its value varies over time, ie. each point has its own unique function. I want to assign these functions as a mark, so I can plot the point pattern with each individual time series as a plotting symbol. This is an exploratory step to eventually perform some spatial functional data analysis. As an example, I want something like Figure 2 published in this article: *Delicado,P., R. Giraldo, C. Comas, and J. Mateu. 2010. Spatial Functional Data: Some Recent Contibutions. Environmetrics 21:224-239 I'm having trouble posting an image of the figure
1) Working in R with ggplot2, I can plot a line of change in quant of each id over time:
(Fake example dataset, where x and y are Carteian coordinates, id is an individual observation, and quant are values of id at each year):
x<-c(1,1,1,2,2,2,3,3,3)
y<-c(1,1,1,2,2,2,3,3,3)
year<-c(1,2,3,1,2,3,1,2,3)
id<-c("a","a","a","b","b","b","c","c","c")
quant<-c(5,2,4,2,4,2,4,4,6)
allData<-data.frame(x,y,year,id,quant)
ggplot(allData,aes(x=year,y=quant, group=id))+geom_line()
2) Or I can plot the geographic point pattern of id:
ggplot(allData,aes(x=x,y=y,color=id))+geom_point()
I want to plot the graph from (2), but use the line plots from (1) as the point symbols (marks). Any suggestions?
