Fabulous! Thank you so much!

On Fri, Nov 13, 2009 at 2:32 PM, Laurent Gautier <lgaut...@gmail.com> wrote:
> Guilherme Castelao wrote:
>>
>> Hello Laurent,
>>
>> I'm sorry about that.
>>
>> I used to do like this:
>>
>> import rpy
>> start = rpy.r.list(...)
>> lower = rpy.r.list(...)
>> upper = rpy.r.list(...)
>> control = rpy.r.nls_control(maxiter=100,tol = 1e-05,minFactor=1./4096)
>> data = rpy.r.data_frame(x=x, x2=x2,y=y)             # x,x2 and y are
>> numpy.array
>> rpy.set_default_mode(rpy.NO_CONVERSION)
>> model = rpy.r.nls(formula, data = data, start = start, lower=lower,
>> upper=upper, control=control, algorithm="port",trace=True)
>> rpy.set_default_mode(rpy.BASIC_CONVERSION)
>> coef=rpy.r.coef(model)
>>
>>
>> Now I'm trying
>>
>> import rpy2.robjects as robjects
>> start = robjects.r.list(...)
>> lower = robjects.r.list(...)
>> upper = robjects.r.list(...)
>> control = ?!?!?!
>> ...
>> model = robjects.r.nls(formula, data = data ...)
>>
>> But I don't know how to define the nls.control !
>
> Just like you would do for other function calls.
>
> control = robjects.r['nls.control'](maxtiter=100, <...>)
> (you can read why at:
> http://rpy.sourceforge.net/rpy2/doc/html/robjects.html#r-the-instance-of-r
> )
>
>
> With 2.1.x, that's tentatively a little nicer:
>
> from rpy2.robjects.packages import importr
> stats = importr("stats")
>
> control = stats.nls_control(maxiter=100, <...>)
>
> (more on importing packages at
> http://rpy.sourceforge.net/rpy2/doc-dev/html/robjects.html#module-rpy2.robjects.packages)
>
>
>
>
> L.
>
>
>
>
>> Thanks!
>>
>>
>> On Fri, Nov 13, 2009 at 3:45 AM, Laurent Gautier <lgaut...@gmail.com>
>> wrote:
>>>
>>> Guilherme Castelao wrote:
>>>>
>>>> Hello all,
>>>>
>>>> I'm moving to rpy2 but I still didn't get the new syntax. I have two
>>>> simple questions:
>>>>
>>>>
>>>> - I can create the nls with no trouble as below, but I can't figure
>>>> out how to create the nls.control with rpy2?
>>>>
>>>>
>>>>
>>>> model=robjects.r.nls(formula,data=dataf,start=start,control=control,trace=True)
>>>>
>>> It hard to tell without knowing how you created the objects used in the
>>> function call.
>>>
>>>> - How would be a more elegant way to create a data frame then
>>>>
>>>>
>>>>
>>>> d={"x":robjects.FloatVector([4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14]),"y":robjects.FloatVector([4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69])}
>>>> dataf = robjects.r['data.frame'](**d)
>>>>
>>> That way of creating a data.frame is correct, although not the only way.
>>>
>>> # with rpy2-2.1.x-dev
>>>
>>> import rpy2.robjects as robjects
>>>
>>> dataf = robjects.DataFrame(d)
>>>
>>>
>>> If having to know the type of the R vectors to create is seen as
>>> inelegant,
>>> on can put rpy_classic to use:
>>>
>>> import rpy2.rpy_classic as rpy
>>>
>>> d={"x":rpy.seq2veq([4.17,5.58,5.18,6.11,4.50,4.61,5.17]),
>>>  "y":rpy.seq2veq([4.81,4.17,4.41,3.59,5.87,3.83,6.03])}
>>>
>>>
>>> I have to remind myself to write more about creating data.frames in the
>>> documentation.
>>>
>>> L.
>>>
>>>
>>>> Thanks!
>>>>
>>>>
>>>>
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>
>

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