Hi,
I've built a system which allocates numpy arrays and processes them in
C++ code (this is because I'm building a native code module using
boost.python and it makes sense to use numpy data storage to then deal
with outputs in python, without having to do any copying). Everything
seems fine
I suspect that you are obtaining the numpy object (1 Py_INCREF) before
you split into multiple threads but releasing them in each thread
(multiple Py_DECREFs). This is probably being hidden from you by the
boost.python interface and/or the boost::detail::sp_counted_impl_p
smart(ish) pointer.
On Mon, Jan 30, 2012 at 3:25 PM, Ted To rainexpec...@theo.to wrote:
Is there some straightforward way to access an array by values across a
subset of its dimensions? For example, if I have a three dimensional
array a=(x,y,z), can I look at the values of z given particular values
for x and y?
Not exactly an answer to your question, but I can highly recommend
using Boost.python, PyUblas and Ublas for your C++ vectors and
matrices. It gives you a really good interface on the C++ side to
numpy arrays and matrices, which can be passed in both directions over
the language threshold with no
You
On Wed, Feb 8, 2012 at 4:32 PM, Stephanie Cooke
cooke.stepha...@gmail.com wrote:
Hello,
When I try to use the command hstack, I am given the error message
TypeError: hstack() takes exactly 1 argument (2 given). I have a 9X1
array (called array) that I would like to concatenate to a 9X2
