rpy2的問題，rpart正確地將數據從python傳遞到r

Question

我正在嘗試使用Python 2.6.5和R 10.0通過RPY2運行rpart。

我在python中創建了一個數據框並將其傳遞，但​​出現錯誤：

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

誰能幫助我確定我在做錯什么以引發此錯誤？

我的代碼的相關部分是這樣的：

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'](minsplit=10, xval=10)
rpart_params = {'formula' : Rformula, \
       'data' : Rdata,
       'control' : Rpcontrol}
model=r.rpart(**rpart_params)

兩個變量cLogEC和csplitData是浮點類型的numpy數組。

另外，我的數據框如下所示：

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

公式如下所示：

In [3]: print Rformula
------> print(Rformula)
responsev ~ .

Answer 1

該問題與rpart中的R特有代碼有關（確切地說，以下塊，尤其是最后一行：

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())

）。

解決該問題的一種方法是避免輸入該代碼塊（請參見下文），或者可能是從Python構建嵌套的評估（以便parent.frame（）起作用）。 這並不像人們希望的那么簡單，但是也許我會在將來找到時間使它變得更容易。

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))