lattice xyplot symbols instead of colors and legend matching plot symbols or colors
xyplot(GPP~(1/Iron)+(1/TSS)+TIN.TP, groups=RiverMile,data=f,
scales=list(relation="free"), par.settings = list(
superpose.symbol = list(
pch = c(1:7),
fill = c("red", "blue"),
col = "black")), auto.key=TRUE,
panel=function(...){
panel.xyplot(...)
panel.abline(lm(GPP~I(1/Iron), data=f))
panel.abline(lm(GPP~I(1/TSS), data=f))
panel.abline(lm(GPP~I(TIN.TP), data=f))
})
now how do I get the panel abline to only plot in the appropriate
panel GPP~1/Iron and the regression line for this panel only in that
panel
thanks
On Wed, Sep 24, 2008 at 1:15 PM, stephen sefick <ssefick at gmail.com> wrote:
I would like to use the data below where the plots are close to what I
want. Instead of color I would like to use different symbols, and
have the symbols in the legend match the graphs. I am also going to
add a regression line to these I know about the type="r" (which is
fine for these particular graphs) argument, but it fits the subsets
instead of the entire data set-- should I use a list of regression
fits in the order of the arguments in an abline panel to do this? Ok,
I think that is all for right now. If I need to clarify please tell
me.
thanks
f <- structure(list(GPP = c(1.213695235, 3.817313822, 1.267930498,
10.45692825, 3.268295623, 3.505286001, 4.468225245, 0.915653726,
1.635617261, 3.726133898, 1.363453706, 13.99650967, 0.417618143,
0.741080504, 0.412440872, 3.515743675, 8.248491445, 1.537773727,
3.249103284, 0.768531626, 2.633107621, 3.113199095, 0.773824094,
0.680150068, 0.026385752, 0.369310858, 8.049276658, 7.487378383,
0.763580377, 0.333244629, 5.475999014, 9.235631398), TSS = c(2.8,
8.4, 11, 1.3, 4.2, 2, 3.4, 14, 8.2, 3.1, 1.4, 0.9, 6.1, 9.2,
11, 1.2, 1.3, 11, 8.5, 13, 4.4, 1.4, 2.1, 25, 9.3, 6.1, 1.6,
1.5, 24, 9.6, 1.8, 1.4), Iron = c(0.74, 0.54, 0.23, 0.13, 0.4,
0.13, 0.15, 0.58, 0.38, 0.22, 0.13, 0.07, 0.32, 0.26, 0.86, 0.13,
0.09, 0.58, 0.35, 0.59, 0.33, 0.19, 0.21, 0.81, 0.34, 0.31, 0.07,
0.16, 0.54, 0.36, 0.13, 0.07), TIN.TP = c(3.117647059, 2.736842105,
2.25, 22, 3, 2.428571429, 6.428571429, NA, NA, 2.384615385, 3,
NA, 3.25, NA, 3.166666667, 9, 23, 3.5, 11, 3.916666667, 3.4,
3.444444444, 8.75, 2.733333333, 3.583333333, 2.75, 17, NA, 2.933333333,
2.533333333, 2.5, 11), RiverMile = c(148L, 179L, 185L, 202L,
179L, 185L, 190L, 119L, 148L, 179L, 185L, 202L, 119L, 202L, 148L,
190L, 202L, 148L, 202L, 119L, 179L, 185L, 190L, 61L, 119L, 148L,
202L, 202L, 119L, 148L, 185L, 202L)), .Names = c("GPP", "TSS",
"Iron", "TIN.TP", "RiverMile"), class = "data.frame", row.names = c(1L,
2L, 3L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 15L, 16L, 19L,
22L, 23L, 30L, 34L, 36L, 37L, 38L, 39L, 43L, 44L, 45L, 46L, 47L,
49L, 50L, 51L, 52L))
xyplot(GPP~(1/Iron)+(1/TSS)+TIN.TP, groups=RiverMile,data=f,
scales=list(relation="free"), pch=20, auto.key=TRUE)
--
Stephen Sefick
Research Scientist
Southeastern Natural Sciences Academy
Let's not spend our time and resources thinking about things that are
so little or so large that all they really do for us is puff us up and
make us feel like gods. We are mammals, and have not exhausted the
annoying little problems of being mammals.
-K. Mullis
Stephen Sefick Research Scientist Southeastern Natural Sciences Academy Let's not spend our time and resources thinking about things that are so little or so large that all they really do for us is puff us up and make us feel like gods. We are mammals, and have not exhausted the annoying little problems of being mammals. -K. Mullis