[Numpy-discussion] Catching and dealing with floating point errors
Warren Weckesser
warren.weckesser at enthought.com
Mon Nov 8 15:45:34 EST 2010
On Mon, Nov 8, 2010 at 2:17 PM, Skipper Seabold <jsseabold at gmail.com> wrote:
> On Mon, Nov 8, 2010 at 3:14 PM, Skipper Seabold <jsseabold at gmail.com>
> wrote:
> > I am doing some optimizations on random samples. In a small number of
> > cases, the objective is not well-defined for a given sample (it's not
> > possible to tell beforehand and hopefully won't happen much in
> > practice). What is the most numpythonic way to handle this? It
> > doesn't look like I can use np.seterrcall in this case (without
> > ignoring its actual intent). Here's a toy example of the method I
> > have come up with.
> >
> > import numpy as np
> >
> > def reset_seterr(d):
> > """
> > Helper function to reset FP error-handling to user's original settings
> > """
> > for action in [i+'='+"'"+d[i]+"'" for i in d]:
> > exec(action)
> > np.seterr(over=over, divide=divide, invalid=invalid, under=under)
> >
>
> It just occurred to me that this is unsafe. Better options for
> resetting seterr?
>
Hey Skipper,
I don't understand why you need your helper function. Why not just pass the
saved dictionary back to seterr()? E.g.
saved = np.seterr('raise')
try:
# Do something dangerous...
result = whatever...
except Exception:
# Handle the problems...
result = better result...
np.seterr(**saved)
return result
Warren
>
> > def log_random_sample(X):
> > """
> > Toy example to catch a FP error, re-sample, and return objective
> > """
> > d = np.seterr() # get original values to reset
> > np.seterr('raise') # set to raise on fp error in order to catch
> > try:
> > ret = np.log(X)
> > reset_seterr(d)
> > return ret
> > except:
> > lb,ub = -1,1 # includes bad domain to test recursion
> > X = np.random.uniform(lb,ub)
> > reset_seterr(d)
> > return log_random_sample(X)
> >
> > lb,ub = 0,0
> > orig_setting = np.seterr()
> > X = np.random.uniform(lb,ub)
> > log_random_sample(X)
> > assert(orig_setting == np.seterr())
> >
> > This seems to work, but I'm not sure it's as transparent as it could
> > be. If it is, then maybe it will be useful to others.
> >
> > Skipper
> >
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