[R] Additional field data collection

[stephen sefick]

Yeah, I believe so.

On Wed, Feb 3, 2010 at 4:53 PM, David Winsemius <dwinsemius at comcast.net> wrote:
>
> On Feb 3, 2010, at 5:44 PM, stephen sefick wrote:
>
>> 39 for right now
>>
>> Which, now that I look at it, doesn't seem like that many stations.  I
>> guess I am looking for a general solution because I will also have to
>> do a similar thing for another analysis... so 36 more... grand total
>> 72.
>
> So manageable for doing some mammalian guidance to the software?
>
> ==
> David.
>
>>
>> Stephen
>>
>> On Wed, Feb 3, 2010 at 4:14 PM, David Winsemius <dwinsemius at comcast.net>
>> wrote:
>>>
>>> On Feb 3, 2010, at 3:36 PM, stephen sefick wrote:
>>>
>>>> This is a subset of a much larger dataframe.  I would like to be able
>>>> to automate finding the pair of x, y coordinates where the line
>>>> crosses zero agian
>>>>
>>>> x <- (structure(list(bankfull_depths_m = c(0, 0.17, 0.38, 0.37, 0.36,
>>>> 0.39, 0.47, 0.48, 0.19, 0.05, -0.05, -0.09), measurment_num_m = c(0.2,
>>>> 0.4, 0.6, 0.8, 1, 1.2, 1.4, 1.6, 1.8, 2, 2.2, 2.4)), .Names =
>>>> c("bankfull_depths_m",
>>>> "measurment_num_m"), class = "data.frame", row.names = 97:108))
>>>>
>>>> qplot(measurment_num_m, bankfull_depths_m, data=x)
>>>>
>>>> in this case it is 2.1, 0
>>>
>>> I cannot quite get there with a naive application of approxfun using
>>> "reversed arguments", since the inverse function that would be created is
>>> not a legitimate function. I can do it in segments, though:
>>>
>>>> y.x <- approxfun(x=x$bankfull_depths_m[9:12],
>>>> y=x$measurment_num_m[9:12])
>>>> y.x(0)
>>>
>>> [1] 2.1  # so you can do it piecewise in regions where the x-y function
>>> is
>>> monotonic
>>>
>>>> y.x <- approxfun(x=x$bankfull_depths_m, y=x$measurment_num_m)
>>>> y.x(0)
>>>
>>> [1] 0.2  # an almost trivial result at the LHS of the range.
>>>
>>> You could also try to do a Newtonian walk (at least that is my guess for
>>> the
>>> underlayment of uniroot() )  along the result of the the unreversed
>>> arguments.
>>>
>>>> x.y <- approxfun(y=x$bankfull_depths_m, x=x$measurment_num_m)
>>>> uniroot(x.y, range(x$measurment_num_m) )
>>>
>>> $root
>>> [1] 0.2
>>>
>>> $f.root
>>> [1] 0
>>>
>>> $iter
>>> [1] 0
>>>
>>> $estim.prec
>>> [1] 0
>>>
>>> # That was the first root and this is the second.
>>>
>>>> uniroot(x.y, c(1, 2.3) )
>>>
>>> $root
>>> [1] 2.1
>>>
>>> $f.root
>>> [1] 0
>>>
>>> $iter
>>> [1] 3
>>>
>>> $estim.prec
>>> [1] 0.01162791
>>>
>>> So you still need to apply some guidance to the functions.
>>>
>>> --
>>> david
>>>
>>>
>>>>
>>>> I need a way to process a whole bunch of data points, and I am at a
>>>> loss.  Thanks for any help.
>>>> regards,
>>>
>>> Whole bunch??? Can you be any more vague, please?
>>> --
>>>
>>> David Winsemius, MD
>>> Heritage Laboratories
>>> West Hartford, CT
>>>
>>> ______________________________________________
>>> R-help at r-project.org mailing list
>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>> PLEASE do read the posting guide
>>> http://www.R-project.org/posting-guide.html
>>> and provide commented, minimal, self-contained, reproducible code.
>>>
>>
>>
>>
>> --
>> Stephen Sefick
>>
>> 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
>
> David Winsemius, MD
> Heritage Laboratories
> West Hartford, CT
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>



-- 
Stephen Sefick

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