CODEWITHSUNDEEP
r
Mal_a
Mal_a

Reputation: 3760

R: Finding the difference between two points from the plot

I need to calculate the time difference of the each sample (the samples can be differentiate using ID column) between two temperature points.

Here is the sample data:

> dput(data)
structure(list(id = c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 
2L, 2L), Zeit = c(0L, 180L, 360L, 420L, 600L, 604L, 0L, 180L, 
360L, 480L, 600L, 605L), Temp = c(963L, 824L, 666L, 658L, 641L, 
549L, 957L, 823L, 661L, 660L, 642L, 562L)), .Names = c("id", 
"Zeit", "Temp"), row.names = c(NA, 12L), class = "data.frame")

Here is ggplot code: 

ggplot(data, aes(x=Zeit,y=Temp,group=id, colour=factor(id))) + geom_line(size=2)

Here is an image with extra explanation:

enter image description here

I need to calculate the time (Zeit) that i need to reach the temp = 600°C (Temp) for each of the sample (ID). So in this example for the ID sample 1, to reach 600°C (Temp column) i need 600 seconds. I apprecieate any help!

Upvotes: 0

Views: 1233

Answers (1)

CJB
CJB

Reputation: 1809

Use the approx function. For a target temperature Tt, the time required is given by:

with(data, approx(x = Temp, y = Zeit, xout = Tt))$y

If the temperature rises with time at any point, then this may be more complicated - you will need to specify the ties argument to approx (probably put ties = min in your context) - but it will work for your example as it is. Note that the values I use for x and y are inverted with respect to your axes.

To get the table that you desire:

Zt <- vapply(unique(data$id), function(ID){
    with(data[data$id == ID,], approx(x = Temp, y = Zeit, xout = Tt))$y
}, double(1))
data.frame(id = unique(data$id), time = Zt)

Upvotes: 1

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