Im going to use SparseMatrices. For these SparseMatrices Im using the R
module SparseM.
There are some problems by converting SparseMatrices. Maby there is an easy
solution. But at the moment I cant found it. Before starting I read the RPY
Reference Manual. The Manual is not complete enough to answer my questions.
Code:
-----------------------------------------------------------------------------------
from rpy import *
r.library('SparseM')
set_default_mode(NO_CONVERSION)
r.m = r.matrix(range(1,26), 5, 5)
r.print_(r.m)
-----------------------------------------------------------------------------------
How is it possible to declarate/subscript a value to the matrix without
conversion?
e.g.: r.m[1,1] = 100, r(r.m[1,1] <- 100, r.m[1][1] = 100)
Not working in RPY, get errors like:
IndexError: R object index out of range
TypeError: sequence index must be integer
After generating this matrix I convert the matrix to a SparseMatrix
-----------------------------------------------------------------------------------
r.M_csr = r.as_matrix_csr(r.m)
r.print_(r.M_csr)
-----------------------------------------------------------------------------------
I use the slots to get the information:
Why I cant use[1,2] like below.
In R-console [1,2] works fine. Did I need a Conversion?
I dont think so its a Robj object
-----------------------------------------------------------------------------------
ra = r.slot(r.M_csr, 'ra')
ra2 = r.slot(r.M_csr[1,2], 'ra')
-----------------------------------------------------------------------------------
Thanks for your time!
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