numexpr 2.3.1 error with pandas 0.13.1

[bluefir]

I just installed numexpr 2.3.1 with pandas 0.13.1 and got the following error:

File "C:\Python27\lib\site-packages\pandas\core\ops.py", line 496, in wrapper
arr = na_op(lvalues, rvalues)
File "C:\Python27\lib\site-packages\pandas\core\ops.py", line 443, in na_op
raise_on_error=True, *_eval_kwargs)
File "C:\Python27\lib\site-packages\pandas\computation\expressions.py", line 176, in evaluate
*_eval_kwargs)
File "C:\Python27\lib\site-packages\pandas\computation\expressions.py", line 104, in _evaluate_numexpr
*_eval_kwargs)
File "C:\Python27\lib\site-packages\numexpr\necompiler.py", line 738, in evaluate
NumExpr(ex, signature, *context)
File "C:\Python27\lib\site-packages\numexpr\necompiler.py", line 554, in NumExpr
precompile(ex, signature, context)
File "C:\Python27\lib\site-packages\numexpr\necompiler.py", line 498, in precompile
ast = typeCompileAst(ast)
File "C:\Python27\lib\site-packages\numexpr\necompiler.py", line 163, in typeCompileAst
% (ast.value + '' + retsig+basesig))
NotImplementedError: couldn't find matching opcode for 'mul_bbb'

[jreback]

and what exactly are you doing when it gives that error?

[bluefir]

Good point.

n_nonzero_returns_idc = np.sum(portfolio_data[field_return_daily_idc].notnull() *
                               (portfolio_data[field_return_daily_idc] != 0.0))

[cpcloud]

why not just do & instead?

[jreback]

can't use booleans in numexpr with multiply; need to astype(int) if you reall y want to do that

as @cpcloud says, why are you not using &?

[cpcloud]

still ... should this fall back onto python/bottleneck ops?

[bluefir]

& worked - had to change it everywhere. cpcloud is right: & is better than *. I started using & instead of * when I realized that. May be it's a good reason to correct those things. Still, has numexpr become more hard ass about things like that?

[jreback]

maybe not catching the NotImplementedError?

and not testing with 2.3.1...hmmm will fix that...

[jreback]

I take that back...we ARE testing on window 2.3.1.....guess don't have a test for that particular case.....

@cpcloud when you have a chance?

[cpcloud]

i don't think numexpr has ever supported arithmetic ops on bool dtype arrays. not sure why this is throwing from pandas tho ... @jreback sure

[bluefir]

used to work with numexpr 2.0.1 and pandas 0.12