[R] rgl: plot3d and ellipse3d

[Yihui Xie]

No, I mean in plot3d():

plot3d(trees, type="s", size=0.5, col="blue", cex=2, box=FALSE, axes=FALSE)

not in ellipse3d()

Yihui
--
Yihui Xie <xieyihui at gmail.com>
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On Wed, Sep 17, 2008 at 9:40 PM, Michael Friendly <friendly at yorku.ca> wrote:
> Yihui Xie wrote:
>>
>> Hi Michael,
>>
>> You need to specify both 'box' and 'axes' to FALSE to avoid the box
>> lines (if you don't specify the latter one, there will still be axes
>> lines).
>>
>>
>>
>
> Hi Yihui
> I tried several variations, none of which would simply add the ellipse and
> nothing else to the original
> plot of points:
>
> plot3d(trees, type="s", size=0.5, col="blue", cex=2)
>
> # how to avoid the extra box?
> # -- this doesn't remove the extra box, but keeps the points & axis labels
> plot3d( ellipse3d(cov, centre=mu, level=0.68, box=FALSE), col="pink",
> alpha=0.2,  add = TRUE, axes=FALSE)
>
> # -- this removes the original axes, the points & labels axes x, y, z
> plot3d( ellipse3d(cov, centre=mu, level=0.68, box=FALSE, col="pink",
> alpha=0.2,  add = TRUE, axes=FALSE))
>
> -Michael
>>
>> On Wed, Sep 17, 2008 at 8:34 PM, Michael Friendly <friendly at yorku.ca>
>> wrote:
>>
>>>
>>> Hi
>>> I'm trying to make a 3d plot showing a point cloud, the corresponding
>>> data
>>> ellipse
>>> and the principal axes of the ellipse as vectors.
>>>
>>> library(rgl)
>>> data(trees)
>>> cov <- cov(trees)
>>> mu <- mean(trees)
>>>
>>> plot3d(trees, type="s", size=0.5, col="blue", cex=2)
>>>
>>> In this step, an extra box is added.  I've tried using box=FALSE, but it
>>> has
>>> no effect.
>>> # how to avoid the extra box?
>>> plot3d( ellipse3d(cov, centre=mu, level=0.68), col="pink", alpha=0.2,
>>>  add =
>>> TRUE)
>>>
>>> Here's what I've tried to plot the principal axes in variable space,
>>> using
>>> the result of prcomp().
>>> But I've got something wrong, because, although they are at right angles,
>>> they don't
>>> align with the ellipse.
>>>
>>> PC <- princomp(trees)
>>> sdev <- PC$sdev         # component standard deviations
>>> sd <- sqrt(diag(cov))   # variable standard deviations
>>>
>>> # vectors in variable space of principal components
>>> vec <- matrix(mu,3,3, byrow=TRUE) + diag(sd) %*% PC$loadings
>>>
>>> for (j in 1:3) {
>>>  mat <- rbind(mu, vec[j,])
>>>  segments3d(mat, col="red")
>>> }
>>>
>>> Can someone help?
>>>
>
> --
> Michael Friendly     Email: friendly AT yorku DOT ca Professor, Psychology
> Dept.
> York University      Voice: 416 736-5115 x66249 Fax: 416 736-5814
> 4700 Keele Street    http://www.math.yorku.ca/SCS/friendly.html
> Toronto, ONT  M3J 1P3 CANADA
>
>
>