Hi,
I'm very new to RPy, so I apologize in advance if the question is stupid...
In the following (python 2.5.2, R 2.10.1, numpy 1.4.0, rpy 2.1.0rc), the call to
R.lm works fine, but a similar call to locfit (from the locfit package at CRAN)
throws an error message:
----<snip, snip>----------------------------------------
import numpy as np
import rpy2.robjects as ro
import rpy2.robjects.numpy2ri
from rpy2.robjects.packages import importr
R = ro.r
x = np.arange(-10., 10., 0.1)
y = 1. + 2*x + np.random.normal(1., 0.5, len(x))
df = ro.DataFrame({'x': x, 'y': y})
fit = R.lm("y ~ x", data = df) # works fine...
importr("locfit")
fit = R.locfit("y ~ x", data = df)
locfit 1.5-6 2010-01-20
Error in x$terms : $ operator is invalid for atomic vectors
Traceback (most recent call last):
File "locfit_1.py", line 17, in <module>
fit = R.locfit("y ~ x", data = df)
File "/opt/apps/lib/python2.5/site-packages/rpy2/robjects/functions.py",
line 81, in __call__
return super(SignatureTranslatedFunction, self).__call__(*args, **kwargs)
File "/opt/apps/lib/python2.5/site-packages/rpy2/robjects/functions.py",
line 35, in __call__
res = super(Function, self).__call__(*new_args, **new_kwargs)
rpy2.rinterface.RRuntimeError: Error in x$terms : $ operator is
invalid for atomic vectors
-----</snip>-------------------------------------------
On the other hand, this
ro.globalenv["df"] = df
fit = R("lm(y ~ x, data = df)")
importr("locfit")
fit = R("locfit(y ~ x, data = df)")
works apparently fine for both lm and locfit. The signature of locfit in R is
locfit(formula, data=sys.frame(sys.parent()), weights=1, cens=0, base=0,
subset, geth=FALSE, ..., lfproc=locfit.raw)
Am I doing something wrong, or is this behavior (when calling locfit
from python)
a feature I just dont understand?
Thanks,
Christian.
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