I am trying to run rpart through RPY2 using Python 2.6.5 and R 10.0.
I create a data frame in python and pass it along but I get an error stating:
Error in function (x) : binary operation on non-conformable arrays
Traceback (most recent call last):
File "partitioningSANDBOX.py", line 86, in <module>
model=r.rpart(**rpart_params)
File "build/bdist.macosx-10.3-fat/egg/rpy2/robjects/functions.py", line 83, in __call__
File "build/bdist.macosx-10.3-fat/egg/rpy2/robjects/functions.py", line 35, in __call__
rpy2.rinterface.RRuntimeError: Error in function (x) : binary operation on non-conformable arrays
Can anyone help me determine what I am doing wrong to throw this error?
the relevant part of my code is this:
import numpy as np
import rpy2
import rpy2.robjects as rob
import rpy2.robjects.numpy2ri
#Fire up the interface to R
r = rob.r
r.library("rpart")
datadict = dict(zip(['responsev','predictorv'],[cLogEC,csplitData]))
Rdata = r['data.frame'](**datadict)
Rformula = r['as.formula']('responsev ~.')
#Generate an RPART model in R.
Rpcontrol = r['rpart.control'](minsp开发者_如何学Golit=10, xval=10)
rpart_params = {'formula' : Rformula, \
'data' : Rdata,
'control' : Rpcontrol}
model=r.rpart(**rpart_params)
The two variables cLogEC and csplitData are numpy arrays of float type.
Also, my data frame looks like this:
In [2]: print Rdata
------> print(Rdata)
responsev predictorv
1 0.6020600 312
2 0.3010300 300
3 0.4771213 303
4 0.4771213 249
5 0.9242793 239
6 1.1986571 297
7 0.7075702 287
8 1.8115750 270
9 0.6020600 296
10 1.3856063 248
11 0.6127839 295
12 0.3010300 283
13 1.1931246 345
14 0.3010300 270
15 0.3010300 251
16 0.3010300 246
17 0.3010300 273
18 0.7075702 252
19 0.4771213 252
20 0.9294189 223
21 0.6127839 252
22 0.7075702 267
23 0.9294189 252
24 0.3010300 378
25 0.3010300 282
and the formula looks like this:
In [3]: print Rformula
------> print(Rformula)
responsev ~ .
The problem is related to R idiosyncratic code in rpart (to be precise, the following block, in particular the last line:
m <- match.call(expand.dots = FALSE)
m$model <- m$method <- m$control <- NULL
m$x <- m$y <- m$parms <- m$... <- NULL
m$cost <- NULL
m$na.action <- na.action
m[[1L]] <- as.name("model.frame")
m <- eval(m, parent.frame())
).
One way to work around that is to avoid entering that block of code (see below) or may be to construct a nested evaluation from Python (so that parent.frame() behaves). This is not as simple as one would hope, but may be I'll find time to make it easier in the future.
from rpy2.robjects import DataFrame, Formula
import rpy2.robjects.numpy2ri as npr
import numpy as np
from rpy2.robjects.packages import importr
rpart = importr('rpart')
stats = importr('stats')
cLogEC = np.random.uniform(size=10)
csplitData = np.array(range(10), 'i')
dataf = DataFrame({'responsev': cLogEC,
'predictorv': csplitData})
formula = Formula('responsev ~.')
rpart.rpart(formula=formula, data=dataf,
control=rpart.rpart_control(minsplit = 10, xval = 10),
model = stats.model_frame(formula, data=dataf))
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