Thanks Rolf, that was a mistake.
Brilliant, I think with() is what I'm looking for, thanks a lot!
cheers,
alastair
Rolf Turner-3 wrote
> On 26/11/12 14:24, Ally wrote:
>> I'd like to pass a list object created by one function as an argument of
>> another function
I should have been clearer, the function I supplied is just a toy example, I
actually have lots more elements, each with different classes, and need to
do more complex things than just summation. The main reason I'm interested
in this is to avoid having to keep adding an assignment like x<-lst$x e
I'd like to pass a list object created by one function as an argument of
another function. once inside the second function, I'd like to break the
list up to it's individual elements, each then identifiable by the 'names'
of the list.
The list looks something like
lst<-list(a=1, b=2, df=5, g=7)
-----
> Sent from my phone. Please excuse my brevity.
>
> Ally <a.rushworth@.ac> wrote:
>
>>I have a complex 2D polygon with thousands of vertices, and I'd like to
>>be
>>able to identify points from a large set contained within the polygo
I have a complex 2D polygon with thousands of vertices, and I'd like to be
able to identify points from a large set contained within the polygon, and
was wondering if there might be an efficient way of doing this? Any advice
would be useful! Here is a small example of what I mean:
# make polygon
I'm trying to calculate the row-wise kronecker product A \Box B of two
sparse matrices A and B, and am struggling to find a quick way to do this
that takes advantage of sparseness. I thought a good idea would be to use
"rep" to construct 2 matrices of the same dimension of the end product, and
m
Hi,
I'm trying to use grid.polygon() to plot several polygons at once, with a
view to putting coloured polygons beneath a curve. I'm struggling just to
get the grid.polygon to plot anything
# PLOT SOME POINTS
x <- 1:100
y <- 1:100*0.5 + 3
plot(x, y, pch = ".")
# PLOT 2
Have a look at ?par and check out the 'xaxp' parameter
par(mfrow=c(1,2))
plot(x[,2] ~ x[,1], xaxp=c(0,100,5))
plot(x[,2] ~ x[,1], xaxp=c(0,100,10), cex.axis=0.5)
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