View source for Help:Drawing graphs

[[Category:Opasnet]]
[[Category:Code under inspection]]
{{method|moderator=Jouni}}
==Question==

How to draw graphs in [[Opasnet]]?

==Answer==

===R-tools===

In [[R-tools]], you have the functionalities of [[R]] available. We recommend that you use the package ggplot2 whenever possible. It is very powerful, and borrowing good ideas from others is easier if we all use the same approach. Of course, it is also possible to use ''plot' (a kind of basic graph) as well, but the limits come sooner. This is an example code that contains all kinds of examples with comments.

<rcode graphics="1">
library(OpasnetUtils)
library(ggplot2)
library(xtable)

objects.get("QWYxSEJltnuTn0Xh") # data.time object from 
# http://fi.opasnet.org/fi_wiki/index.php?title=Talvivaaran_kaivoksen_mittauksia&oldid=16176
# data.time
altiste <- "Ni"

head(data.time)

ggplot(data.time, aes(x = Paikka, y = pitoisuusResult, colour = pitoisuusResult)) + 
	geom_point(size = 5) + # point size
	theme_grey(base_size = 24) + # font etc. http://sape.inf.usi.ch/quick-reference/ggplot2/themes
	labs( # label names
		title 	= paste(altiste, "Talvivaaran läheisyydessä"), 
		y 	= paste("Pitoisuus,", data.time$pitoisuusUnit[1]),
		x 	= "Mittauspaikka"
	) +
	theme(axis.text.x = element_text(angle = 90, hjust = 1)) # Turn text and adjust to right

########### Concentrations in time

ggplot(data.time, aes(x = Aika, y = pitoisuusResult, colour = Paikka)) + 
	geom_point(size = 5) + 
	theme_grey(base_size = 24) +
	labs(
		title 	= paste(altiste, "Talvivaaran läheisyydessä"), 
		y 	= paste("Pitoisuus,", data.time$pitoisuusUnit[1]),
		x 	= "Aika"
	) 

# data from http://fi.opasnet.org/fi_wiki/index.php?title=Kivilajien_kemiallinen_koostumus&oldid=16183
objects.get("yRxoBZmZBL5GOP6D")

head(data)
nrow(data)
ggplot(data[data$Observation == "Mean", ], aes(x = Element, y = Result, colour = Sequence)) + 
	geom_point() + 
	theme_grey(base_size = 20)

</rcode>

{{comment|# |Code seems to work, but gives the yellow errorbox saying "Removed 745 rows containing missing values (geom_point)"|--[[User:Heta|Heta]] 12:56, 27 August 2013 (EEST)}}

===rlnorm===

; Graph for cumulative probability distributions

<rcode graphics=1 embed=1>
library(ggplot2)

dat <- data.frame(
	Group = factor(1:5, levels = 1:5, labels = c("Old, CH", "Old, CZ", "Old, GR", "New, all cities", "Renovated, all cities")),
	Mean = c(0.83, 0.7, 1.29, 0.65, 0.6),
	Sd = c(0.46, 0.43, 1.09, 0.1, 0.1)
)

out <- data.frame()
for(i in 1:nrow(dat)) {
	temp <- data.frame(Group = dat$Group[i], Iter = 1:10000, 
 Result = rlnorm(10000, 
meanlog = log(dat$Mean[i]^2 / sqrt(dat$Sd[i]^2 + dat$Mean[i]^2)),
sdlog = sqrt(log(1 + dat$Sd[i]^2 / dat$Mean[i]^2))
))
	out <- rbind(out, temp)
}
head(out)

tapply(out$Result, out$Group, mean)
tapply(out$Result, out$Group, sd)


p <- ggplot(out, aes(x = Result, linetype = Group)) + 
stat_ecdf(size = 1.2) + 
coord_cartesian(xlim = c(0, 3))  + 
theme_grey(base_size = 24) + 
labs(x = "Air exchange rate (1/h)", y = "Cumulative probability") + 
theme(legend.position=c(.7, .2))

# png(filename = "//cesium/jtue$/_Documents/Alexairexchange.png", width = 800, height = 800)
print(p)
# dev.off()
</rcode>

===GoogleDocs===

GoogleDocs is the method of choice for drawing causal diagrams. 
* Make a drawing.
* Share it with everyone with open editing.
* Download is in png or svg format.
* Upload the file to Opasnet and copy a link to the original Google document to the image page.
* Use like any image.

==See also==

* [http://wiki.stdout.org/rcookbook/Graphs/Scatterplots%20%28ggplot2%29/ Cookbook for R: Scatterplots]
* [http://docs.ggplot2.org/0.9.3/scale_continuous.html Scales of x and y axes]
* [http://docs.ggplot2.org/current/geom_smooth.html Add a smoothed conditional mean]
* [http://sape.inf.usi.ch/quick-reference/ggplot2/themes theme_grey]
* [http://docs.ggplot2.org/0.9.3/geom_histogram.html Different histograms]