[R] approxfun returning value higher than I would expect

[Duncan Murdoch]

I think this is fixed now.  There were actually two bugs:

I fixed an old one a few days ago, but my fix didn't handle the case of 
unsorted x properly.  (I haven't checked whether the old code handled 
that properly; I'd guess not, but it might have.)  Now I've fixed my new 
bug.

*Please* test R-devel to see if I got it right this time.  (I think I 
did, but I thought I did last time, too.)  If you don't build your own 
copies, look for a build based on revision r52916 or newer.  Windows 
builds should appear late tomorrow, I don't know about other platforms.

Duncan Murdoch

On 15/09/2010 4:32 PM, stephen sefick wrote:
> x <- c(-0.48,-0.48,-0.42,-0.26,0.58,0.48,0.47,0.54,0.5,0.52,0.52,0.56,0.58,0.61,0.68)
> y <- c(0,0.2,0.4,0.6,0.8,1,1.2,1.4,1.6,1.8,2,2.2,2.4,2.6,2.8)
> 
> s <- approxfun(x[4:5], y[4:5], ties=mean)
> 
> s(0)
> 
> #This is the value that I want.  The first zero crossing in the order
> of y.  #In other words in between 0.6 and 0.8.
> 
> #The data is a channel cross-section, and should really be visualized
> 
> plot(x~y, ylim=c(1,-1)) #this is half of a cross-section
> 
> #The bankfull depth is where x is equal to 0
> 
> On Wed, Sep 15, 2010 at 3:12 PM, stephen sefick <ssefick at gmail.com> wrote:
>> Thanks and I'll strip the code down even more in future posts.
>>
>> Stephen
>>
>> On Wed, Sep 15, 2010 at 3:05 PM, Duncan Murdoch
>> <murdoch.duncan at gmail.com> wrote:
>>>  On 15/09/2010 3:48 PM, stephen sefick wrote:
>>>> Below is the code that I am using in a much larger function.  I would
>>>> expect a bankfull measure at zero to be between 0.6 and 0.8 approxfun
>>>> is returning 0.8136986.  I am sure that I am missing something.
>>>>
>>>> measure_bkf<- (structure(list(measurment_num = c(0, 0.2, 0.4, 0.6,
>>>> 0.8, 1, 1.2,
>>>> 1.4, 1.6, 1.8, 2, 2.2, 2.4, 2.6, 2.8, 3, 3.2, 3.4), bankfull_depths_m
>>>> = c(-0.48,
>>>> -0.48, -0.42, -0.26, 0.58, 0.48, 0.47, 0.54, 0.5, 0.52, 0.52,
>>>> 0.56, 0.58, 0.61, 0.68, 0.62, 0.67, 0.66)), .Names = c("measurment_num",
>>>> "bankfull_depths_m"), row.names = c("6124", "612", "613", "614",
>>>> "615", "616", "617", "618", "619", "620", "621", "622", "623",
>>>> "624", "625", "626", "627", "628"), class = "data.frame"))
>>>>
>>>>
>>>> measure_bkf_not_zero<- subset(measure_bkf,
>>>> measure_bkf$bankfull_depths_m!=0)
>>>>
>>>> bkf_min<- which.max(measure_bkf_not_zero[,"bankfull_depths_m"]<0)
>>>>
>>>> bkf_max<- which.max(measure_bkf_not_zero[,"bankfull_depths_m"])
>>>>
>>>> #bkf_min<- ifelse(length(bkf_min)>1, bkf_min[1], bkf_min)
>>>> #bkf_max<- ifelse(length(bkf_max)>1, bkf_max[1], bkf_max)
>>>>
>>>> #s<- with(measure_bkf_not_zero, approx(measurment_num,
>>>> bankfull_depths_m,
>>>> xout=seq(measure_bkf_not_zero[bkf_min,"measurment_num"],
>>>> measure_bkf_not_zero[bkf_max,"measurment_num"], length=2000)))
>>>> #int_bkf<- with(s, x[which.min(y[y>0])])
>>>>
>>>> s<- with(measure_bkf_not_zero[bkf_min:bkf_max,],
>>>> approxfun(bankfull_depths_m, measurment_num), ties=mean)
>>>>
>>>> int_bkf<- s(0)
>>>>
>>> It is easier to see the problem if you don't leave all the complications in
>>> the beginning.  Just define some variables and
>>> show the interpolation on a plot:
>>>
>>> x <-
>>> c(-0.48,-0.48,-0.42,-0.26,0.58,0.48,0.47,0.54,0.5,0.52,0.52,0.56,0.58,0.61,0.68)
>>> y <- c(0,0.2,0.4,0.6,0.8,1,1.2,1.4,1.6,1.8,2,2.2,2.4,2.6,2.8)
>>> plot(x, y)
>>> s <- approxfun(x, y, ties=mean)
>>> curve(s, add=TRUE)
>>>
>>> On my system, this looks okay in 2.11.1, but not in R-patched or R-devel
>>> (soon to be 2.12.0).  It is fixed if the x values are ordered, but it's not
>>> supposed to need that.  I'll take a look.
>>>
>>> Duncan Murdoch
>>>
>>
>>
>> --
>> Stephen Sefick
>> ____________________________________
>> | Auburn University                                   |
>> | Department of Biological Sciences           |
>> | 331 Funchess Hall                                  |
>> | Auburn, Alabama                                   |
>> | 36849                                                    |
>> |___________________________________|
>> | sas0025 at auburn.edu                             |
>> | http://www.auburn.edu/~sas0025             |
>> |___________________________________|
>>
>> Let's not spend our time and resources thinking about things that are
>> so little or so large that all they really do for us is puff us up and
>> make us feel like gods.  We are mammals, and have not exhausted the
>> annoying little problems of being mammals.
>>
>>                                 -K. Mullis
>>
>> "A big computer, a complex algorithm and a long time does not equal science."
>>
>>                               -Robert Gentleman
>>
> 
> 
>