Hi,

I've written a very simple benchmark on recarrays:

import numpy, time

Z = numpy.zeros((100,100), dtype=numpy.float64) Z_fast = numpy.zeros((100,100), dtype=[('x',numpy.float64), ('y',numpy.int32)]) Z_slow = numpy.zeros((100,100), dtype=[('x',numpy.float64), ('y',numpy.bool)])

t = time.clock() for i in range(10000): Z*Z print time.clock()-t

t = time.clock() for i in range(10000): Z_fast['x']*Z_fast['x'] print time.clock()-t

t = time.clock() for i in range(10000): Z_slow['x']*Z_slow['x'] print time.clock()-t

And got the following results: 0.23 0.37 3.96

Am I right in thinking that the last case is quite slow because of some memory misalignment between float64 and bool or is there some machinery behind that makes things slow in this case ? Should this be mentioned somewhere in the recarray documentation ?

Nicolas