On Mon, Jul 28, 2008 at 2:35 PM, Robert Kern
Both, if the behavior exhibits itself without the npy file. If it only exhibits itself with an npy involved, then we have some more information about where the problem might be.
OK, I'll see what I can come up with. In the mean time, as I was trying to strip out the npy component and put the data directly into the file, I find it strange that I am getting a floating point error on this operation import numpy as np np.seterr("raise") import numpy.ma as ma x = 1.50375883 m = ma.MaskedArray([x]) sinc_alpha_ma = ma.sin(m) / m --------------------------------------------------------------------------- FloatingPointError Traceback (most recent call last) /home/jdhunter/<ipython console> in <module>() /home/jdhunter/dev/lib64/python2.5/site-packages/numpy/ma/core.pyc in __div__(self, other) 1885 def __div__(self, other): 1886 "Divide other into self, and return a new masked array." -> 1887 return divide(self, other) 1888 # 1889 def __truediv__(self, other): /home/jdhunter/dev/lib64/python2.5/site-packages/numpy/ma/core.pyc in __call__(self, a, b) 636 d1 = getdata(a) 637 d2 = get_data(b) --> 638 t = narray(self.domain(d1, d2), copy=False) 639 if t.any(None): 640 mb = mask_or(mb, t) /home/jdhunter/dev/lib64/python2.5/site-packages/numpy/ma/core.pyc in __call__(self, a, b) 411 if self.tolerance is None: 412 self.tolerance = np.finfo(float).tiny --> 413 return umath.absolute(a) * self.tolerance >= umath.absolute(b) 414 #............................ 415 class _DomainGreater: FloatingPointError: underflow encountered in multiply I am no floating point expert, but I don't see why a numerator of 0.99775383 and a denominator of 1.50375883 should be triggering an underflow error. It looks more like a bug in the ma core logic since umath.absolute(a) * self.tolerance is more or less guaranteed to fail if np.seterr("raise") is set JDH