[Numpy-discussion] [Announce] Numpy 1.3.0b1
Robert Pyle
rpyle@post.harvard....
Thu Mar 19 12:19:18 CDT 2009
Hi Chuck,
On Mar 19, 2009, at 1:01 PM, Charles R Harris wrote:
> Is that any help?
>
> Not yet ;) I think there is a problem with the range of values in x
> that might have their source in the finfo values. So it would help
> if you could pin down just where x goes wrong by printing it out.
> That is what the short script that a included in the ticket comments
> does. Mind, I think you will need to do a bit of exploration. I
> don't think the failures are significant in that it probably doesn't
> need to test the range of values that it does, but it would be nice
> to understand precisely why it fails.
Sorry. I didn't read clear to the end of the ticket. I assume the
script you mean is
----------------------------------------------------------------
#! /usr/bin/env python
import numpy as np
def check_loss_of_precision(dtype):
"""Check loss of precision in complex arc* functions"""
# Check against known-good functions
info = np.finfo(dtype)
real_dtype = dtype(0.).real.dtype
eps = info.eps
x_series = np.logspace(np.log10(info.tiny/eps).real, -3, 200,
endpoint=False)
x_basic = np.logspace(dtype(-3.).real, -1e-8, 10)
print x_series
if __name__ == "__main__" :
check_loss_of_precision(np.longcomplex)
----------------------------------------------------------------
When I run this, it says x_series is an array of 200 NaNs. That would
certainly explain why the assertion in test_umath.py failed!
Bob
More information about the Numpy-discussion
mailing list