numpy2ri 与 rpy2 2.2.2 的转换问题
我将 rpy2-2.2.2 与新的免费 Enthought python 发行版一起使用,其中包括 numpy 1.6.0 和 python 2.7.2。我 easy_installed rpy2 导致安装了 v.2.2.2 并且所有测试都成功。
我遇到的问题是我编写的代码在 rpy2 2.1.8 和 python 2.6 上运行良好。问题在于将数组从 numpy 转换为 R。
这是相关代码的片段:
import rpy2
import rpy2.rinterface as rinterface
import rpy2.robjects as rob
import rpy2.rlike.container as rlc
import numpy as np
import rpy2.robjects.numpy2ri
r = rob.r
...
HGr = rob.conversion.py2ri(HG_reg)
RHSr = rob.conversion.py2ri(RHS)
#
CalData = rlc.TaggedList([HGr,RHSr],tags=('hg','rhs'))
CalData = rob.DataFrame(CalData)
r('''library(pls)''')
#rob.globalEnv["HGr"] = HGr
#rob.globalEnv["RHSr"] = RHSr
rob.globalenv["CalData"] = CalData
# perform the PLS regression
if wetlflag:
HGresults = r.plsr(r("hg ~ rhs.1 + rhs.2 + rhs.3 + rhs.4"),data=CalData,validation="LOO")
我很高兴地承认这不是最优雅的做事方式,但它以前和现在当我需要提供结果时都有效(!)。我得到的错误如下:
Traceback (most recent call last):
File "Mercury_PLS_WL_DF.py", line 224, in <module>
HGr = rob.conversion.py2ri(HG_reg)
File "/Library/Frameworks/Python.framework/Versions/7.1/lib/python2.7/site-packages/rpy2-2.2.2dev_20110726-py2.7-macosx-10.5-i386.egg/rpy2/robjects/__init__.py", line 134, in default_py2ri
raise(ValueError("Nothing can be done for the type %s at the moment." %(type(o))))
ValueError: Nothing can be done for the type <type 'numpy.ndarray'> at the moment.
我在此处找到了讨论,并得到了这样的印象: numpy 数组现在自动转换为 R 数组,但注释掉 rob.conversion.py2ri(HG_reg) 语句并直接使用 numpy 数组似乎也会失败。我错过了一些明显的东西吗?为什么会在 2.1.8 和 2.2.2 之间中断?
I am using rpy2-2.2.2 with the new free Enthought python distribution that includes numpy 1.6.0 and python 2.7.2. I easy_installed rpy2 which resulted in v. 2.2.2 being installed and all tests were successful.
The problem I'm having is with code I wrote that worked fine with rpy2 2.1.8 and python 2.6. The issue is in converting from numpy to R for arrays.
Here is a snippet of the relevant code:
import rpy2
import rpy2.rinterface as rinterface
import rpy2.robjects as rob
import rpy2.rlike.container as rlc
import numpy as np
import rpy2.robjects.numpy2ri
r = rob.r
...
HGr = rob.conversion.py2ri(HG_reg)
RHSr = rob.conversion.py2ri(RHS)
#
CalData = rlc.TaggedList([HGr,RHSr],tags=('hg','rhs'))
CalData = rob.DataFrame(CalData)
r('''library(pls)''')
#rob.globalEnv["HGr"] = HGr
#rob.globalEnv["RHSr"] = RHSr
rob.globalenv["CalData"] = CalData
# perform the PLS regression
if wetlflag:
HGresults = r.plsr(r("hg ~ rhs.1 + rhs.2 + rhs.3 + rhs.4"),data=CalData,validation="LOO")
I will gladly admit it's not the most elegant way to do things, but it worked before and now when I need to provide results all is broken (!). The error I get is the following:
Traceback (most recent call last):
File "Mercury_PLS_WL_DF.py", line 224, in <module>
HGr = rob.conversion.py2ri(HG_reg)
File "/Library/Frameworks/Python.framework/Versions/7.1/lib/python2.7/site-packages/rpy2-2.2.2dev_20110726-py2.7-macosx-10.5-i386.egg/rpy2/robjects/__init__.py", line 134, in default_py2ri
raise(ValueError("Nothing can be done for the type %s at the moment." %(type(o))))
ValueError: Nothing can be done for the type <type 'numpy.ndarray'> at the moment.
I found the discussion here and got the impression that numpy arrays are now automatically converted to R arrays, but commenting out the rob.conversion.py2ri(HG_reg)
statements and using the numpy arrays directly also seems to fail. Am I missing something obvious? Why would this break between 2.1.8 and 2.2.2?
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来自http://rpy.sourceforge。 net/rpy2/doc-2.2/html/numpy.html#from-numpy-to-rpy2:
因此,在导入之后放置 rpy2.robjects.activate() 就可以了。
From http://rpy.sourceforge.net/rpy2/doc-2.2/html/numpy.html#from-numpy-to-rpy2:
So put
rpy2.robjects.activate()
after the import and you should be fine.