On 10/9/07, Gregory Warnes <[EMAIL PROTECTED]> wrote: > > It sounds like your version of RPy may have been compiled without > NumPy support. Did you compile it yourself, or are you using a pre- > build version. >
I have what appears to be a related issue. rpy 1.0RC3 using numpy 1.0.3 I compiled rpy on my system. I believe the setup.py should find numpy $ python Python 2.5.1 (r251:54863, Apr 19 2007, 11:03:39) [GCC 4.1.2] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import numpy >>> numpy.get_numpy_include() /usr/lib/python2.5/site-packages/numpy/lib/utils.py:89: DeprecationWarning: get_numpy_include is deprecated, use get_include DeprecationWarning) '/usr/lib/python2.5/site-packages/numpy/core/include' >>> $ ls -R /usr/lib/python2.5/site-packages/numpy/core/include /usr/lib/python2.5/site-packages/numpy/core/include: numpy /usr/lib/python2.5/site-packages/numpy/core/include/numpy: __multiarray_api.h config.h npy_interrupt.h ufuncobject.h __ufunc_api.h multiarray_api.txt old_defines.h arrayobject.h ndarrayobject.h oldnumeric.h arrayscalars.h noprefix.h ufunc_api.txt When using rpy to calculate the mean of an array, R segfaults unless the array has a dtype of int32 or float64. The dtypes int8, int16, int64, float32, and float96 all produce the same error messages. $ python Python 2.5.1 (r251:54863, Apr 19 2007, 11:03:39) [GCC 4.1.2] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import numpy, rpy RHOME= /usr/lib/R RVERSION= 2.5.1 RVER= 2051 RUSER= /home/dscholl Loading Rpy version 2051 .. Done. Creating the R object 'r' .. Done >>> x = numpy.array([1,2,3,4], dtype=numpy.float64) >>> rpy.r.mean(x) 2.5 >>> x = numpy.array([1,2,3,4], dtype=numpy.float32) >>> rpy.r.mean(x) *** caught segfault *** address (nil), cause 'memory not mapped' Possible actions: 1: abort (with core dump, if enabled) 2: normal R exit 3: exit R without saving workspace 4: exit R saving workspace Selection: 3 Exception thread.error: 'release unlocked lock' in <class 'thread.error'> ignored It appears that I can convert manually to float64 as a workaround, but this strikes me as unexpected behavior. I studied the docs, but didn't recognize this issue. Am I using rpy correctly? Regards, Dave ------------------------------------------------------------------------- This SF.net email is sponsored by: Splunk Inc. Still grepping through log files to find problems? Stop. Now Search log events and configuration files using AJAX and a browser. Download your FREE copy of Splunk now >> http://get.splunk.com/ _______________________________________________ rpy-list mailing list rpy-list@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/rpy-list
