Am 05.09.12 03:30, schrieb Matti Picus:
I am trying to complete complex numbers in numpypy. Progress is good, I picked up from previous work on the numpypy-complex2 branch. Complex numbers come with extensive tests, it seems all the corner cases are covered. In porting the tests to numpypy, I came across a problem: numpy returns different results than cmath. Some of the differences are due to the fact that numpy does not raise a ValueError for dividing by 0 or other silly input values, but other differences are inexplicable (note the sign of the imaginary part):
numpy.arccos(complex(0.,-0.)) (1.5707963267948966-0j) cmath.acos(complex(0.,-0.)) (1.5707963267948966+0j)
or this one:
cmath.acos(complex(float('inf'),2.3)) -infj numpy.arccos(complex(float('inf'),2.3)) (0.78539816339744828-inf*j)
Should I ignore the inconsistencies, or fix the 700 out of 2300 test instance failures? What should pypy's numpypy do - be consistent with numpy or with cmath? cmath is easier and probably faster (no need to mangle results or input args), so I would prefer cmath to trying to understand the logic behind numpy. Matti
In NumPy you can change how numerical exception are handled: http://docs.scipy.org/doc/numpy/reference/routines.err.html http://docs.scipy.org/doc/numpy/user/misc.html#how-numpy-handles-numerical-e...
import numpy numpy.__version__ '1.6.2' numpy.arccos(complex(float('inf'),2.3)) -c:1: RuntimeWarning: invalid value encountered in arccos (nan-inf*j) # Warning only once. numpy.arccos(complex(float('inf'),2.3)) (nan-inf*j) old_settings = numpy.seterr(all='raise') old_settings Out[8]: {'divide': 'warn', 'invalid': 'warn', 'over': 'warn', 'under': 'ignore'} numpy.arccos(complex(float('inf'),2.3))
FloatingPointError Traceback (most recent call last) <ipython-input-11-92051afcce38> in <module>() ----> 1 numpy.arccos(complex(float('inf'),2.3))
old_settings = numpy.seterr(all='ignore') numpy.arccos(complex(float('inf'),2.3)) (nan-inf*j)
HTH, Mike