1

I am currently trying to reconstruct the Example code for lmeSplines (page 4 and 5 on the official documentation).

The first line of code is (in R syntax):

# smoothing spline curve fit
data(smSplineEx1)

How can I view this data via RPy? I Tried:

from rpy2.robjects.packages import importr
lmeS = importr("lmeSplines")
print lmeS.smSplineEx1

and I get:

AttributeError: 'InstalledSTPackage' object has no attribute 'smSplineEx1'
TheChymera
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    @furas, can you point the OP to a particular spot in the documentation that would be useful? – Ben Bolker Jul 14 '14 at 01:41
  • does http://stackoverflow.com/questions/23326651/rpy2-version-2-3-10-importing-data-from-r-package-into-python answer your question? – Ben Bolker Jul 14 '14 at 02:05
  • @BenBolker doesn't deem to work for me, with their approach I get Error in loadNamespace(name) : there is no package called ‘smSplineEx1’ – TheChymera Jul 14 '14 at 03:11

2 Answers2

1

Don't try to translate R code line by line, try to do it in rpy2 way if we put it so. For example, to access the dataset smsSplineEx: use ro.r.smSplineEx1

In [34]:

import rpy2.robjects as ro
import pandas.rpy.common as com
mydata = ro.r['data.frame']
read = ro.r['read.csv']
head = ro.r['head']
summary = ro.r['summary']
library = ro.r['library']
In [35]:

formula = '~ time'
library('lmeSplines')
ro.reval('smSplineEx1$all <- rep(1,nrow(smSplineEx1))')
result = ro.r.smspline(formula=ro.r(formula), data=ro.r.smSplineEx1) #notice: data=ro.r.smSplineEx1
In [36]:

print com.convert_robj(result).head()
         0         1         2         3         4         5         6   \
1  1.168560  2.071261  2.944953  3.782848  4.584037  5.348937  6.078121   
2  0.148786  1.072013  1.948857  2.789264  3.593423  4.361817  5.095016   
3 -0.054492  0.072766  0.952761  1.795679  2.602809  3.374698  4.111911   
4 -0.053646 -0.135912 -0.043334  0.802095  1.612194  2.387579  3.128806   
5 -0.052799 -0.133771 -0.250619 -0.191489  0.621580  1.400459  2.145701   

         7         8         9     ...           88        89        90  \
1  6.772184  7.431719  8.057321    ...     0.933947  0.769591  0.619420   
2  5.793601  6.458153  7.089255    ...     0.904395  0.745337  0.599976   
3  4.815018  5.484587  6.121190    ...     0.874843  0.721083  0.580531   
4  3.836434  4.511021  5.153124    ...     0.845291  0.696829  0.561086   
5  2.857851  3.537455  4.185059    ...     0.815739  0.672575  0.541641   

         91       92        93        94        95        96        97  
1  0.484029  0.36401  0.259959  0.172468  0.102133  0.049547  0.015305  
2  0.468893  0.35267  0.251890  0.167135  0.098986  0.048026  0.014836  
3  0.453756  0.34133  0.243821  0.161801  0.095838  0.046504  0.014368  
4  0.438620  0.32999  0.235753  0.156467  0.092691  0.044982  0.013899  
5  0.423484  0.31865  0.227684  0.151134  0.089544  0.043461  0.013431  

[5 rows x 98 columns]
CT Zhu
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0

In addition to the solution presented by @CT Zhu below, I found that this appraoch:

import pandas.rpy.common as com
from rpy2.robjects.packages import importr
lmeS = importr("lmeSplines")
sp_data = com.load_data('smSplineEx1')

is exactly what I am looking for (as it imports the data as a pandas dataframe, so that you can manipulate it with your favourite Python tools).

TheChymera
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