On Nov 28, 2011, at 12:06 AM, Katrina Bennett wrote:
Sorry for not being more clear.
I'll try to explain again.
I have a rather large DEM and I need to scale daily temperature
values for 10 years.
I have no idea what a DEM might be.
I am using the sapply function to adjust temperatures (t.mean.1.c)
based on lapse rates across DEM points (cdem) which meet the
condition of elevation being greater than 300m. Below ~300m the
lapse rate calculate changes because temperatures decrease with
elevation. Above ~300m the lapse rates calculation must account for
an inversion, where temperature increases with elevation.
What I would like as a result is the values of the DEM which are
lower than 300m to retain a generic lapse rate adjustment, and the
DEM values great than 300 to be treating using a different function.
t.mean.1.c <- c(-15, -20, -30, -20, -25, -35, -40, -8, 9, 10)
cdem <- c(300, 400, 700, 900, 1000, 250, 200, 300, 500, 650, 650,
1200,
1400, 3200, 2000)
cdem.mat <- sapply(cdem[which(cdem >= 900)], function(x) get("t.mean.
1.c") - (x * -0.0065)) #this just gives me a
#result of only the six values
I'm going to make this even more simple to show what I want as output.
t.mean.1.c <- c(-14, -20)
cdem <- c(300, 400, 700, 900)
cdem.mat.1 <- sapply(cdem[which(cdem >= 900)], function(x)
get("t.mean.1.c") - (x * -0.0065))
cdem.mat.2 <- sapply(cdem[which(cdem < 900)], function(x)
get("t.mean.1.c") + (x * -0.0065))
cdem.mat.1 #right now I get this, which is only the two temperature
scaled to the 900 m elevation case
# [,1]
#[1,] -8.15
#[2,] -14.15
#What I want:
# [,1] [,2] [,3] [,4]
#[1,] -15.95 -16.6 -18.55 -8.15
#[2,] -21.95 -22.6 -24.55 -14.15
Construct a depth adjustment matrix:
> -0.0065 *matrix(cdem, 4,2)* (2*(cdem >= 900)-1)
[,1] [,2]
[1,] 1.95 1.95
[2,] 2.60 2.60
[3,] 4.55 4.55
[4,] -5.85 -5.85
Makes two copies of cdem in a column matrix, multiplies by -1 or 1
depending on the condition, multiplies by you adjustment factor.
Transposing it will properly oriented to subtract from t.mean.c.1
using R matrix subtraction (which recycles by columns).
> t.mean.1.c - t( -0.0065 *matrix(cdem, 4,2)* (2*(cdem >= 900)-1) )
[,1] [,2] [,3] [,4]
[1,] -15.95 -16.6 -18.55 -8.15
[2,] -21.95 -22.6 -24.55 -14.15
More complicated adjustment choices could be constructed with
findInterval as an factor-choosing index. For your simple problem
case this would suffice..
> c(0.0065, -0.0065)[findInterval(cdem, c(0,899,Inf))]
[1] 0.0065 0.0065 0.0065 -0.0065
Maybe I can combine in the sapply function an if else statement? I
haven't tested the below try.
sapply( if (cdem < 900)] function(x) get("t.mean.1.c") - (x * -0.0065)
else function(x) get("t.mean.1.c") + (x * -0.0065) )
I don't understand why you keep using get(). Just use the variable name.
Finally, I want to output everything into one single matrix array.
If you stick with matrix operations, that's what you get.
I hope that is more clear.
Thanks for your assistance.
Katrina
On Sun, Nov 27, 2011 at 7:35 PM, David Winsemius <dwinsem...@comcast.net
> wrote:
On Nov 27, 2011, at 10:15 PM, Katrina Bennett wrote:
Hi all,
I'm working to apply a function that will generate a matrix of
results only
when a specific criteria is met.
I want my final results to be a matrix with both the values that
meet the
criteria (the results of the function), and those that to do in the
same
positions in the matrix (the original numbers).
Here's a sample of what I would like to do:
t.mean.1.c <- c(-15, -20, -30, -20, -25, -35, -40, -8, 9, 10)
cdem <- c(300, 400, 700, 900, 1000, 250, 200, 300, 500, 650, 650,
1200,
1400, 3200, 2000)
cdem.mat <- matrix(NA, 10, 15)
cdem.mat <- cdem.mat(sapply(cdem[which(cdem >= 900)], function(x)
......................^
cdem.mat is not a function, cannot use "(".
get("t.mean.1.c") - (x * -0.0065)))
I want cdem.mat to be the same size as the the first call of it,
with NA
values where the cdem is < 899.
You are only offering 10 values as replacements and an unequal
number of condition regardless of whether you count the qualifying
cdem conditions (6) or the total conditions(15). So you will need to
be more clear about how you want the conditions to apply to values.
They stepping the audience through the first few decisions and say
where you want the values placed. Maybe you should also say whether
you expect values to be recycled (the default with matrix assignment).
I suppose it is possible that you want the results of this:
cdem.mat[cdem>899] <- t.mean.1.c - (cdem * -0.0065)
.... but I'm guessing not.
I thought this would fill it in but it
seems to just over write it and I only end up with the rows where
cdem is
greater than 900.
Thank you,
Katrina
--
Katrina E. Bennett
PhD Student
University of Alaska Fairbanks
International Arctic Research Center
930 Koyukuk Drive, PO Box 757340
Fairbanks, Alaska 99775-7340
907-474-1939 office
907-385-7657 cell
kebenn...@alaska.edu
Personal Address:
UAF, PO Box 752525
Fairbanks, Alaska 99775-2525
bennett.katr...@gmail.com
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David Winsemius, MD
West Hartford, CT
David Winsemius, MD
West Hartford, CT
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