I am writing a large hydrological model, and for some sets of parameters I get a NaN value, but I do not know which first function is giving me NaN. Therefore, I would like to stop my program at the first NaN. A dirty debugging solution would be to test at every level isnan(…) which is tedious. I…

You might be interested in this old post: [image] NaN Detector General Usage I have a half-completed attempt at using a Cassette pass to find the first NaN that gets returned from any function. Needs some more work, but it found the NaN I was hunting for and then I moved…

There is no option that tells Julia to treat NaN as an error. NaN arises from one of these (where the signs may be positive or negative): Inf / Inf 0.0 / 0.0 Inf % x and inv(0.0) == Inf; x / 0.0 == Inf Look at the routines to see where you may be dividing by zero (or introducing Inf). chk(x) =…

[image] JosephPollacco: A dirty debugging solution would be to test at every level isnan(…) which is tedious. NaNs are valid Float64s, engineered precisely for the purpose of making invalid results propagate without errors. Your best option may be placing a few checks that validate outputs (…

Hmm, Fortran compilers let you enable floating-point exceptions, e.g. gfortran -ffpe-trap=invalid will cause an exception once a NaN is created. I think technically this will cause a SIGFPE signal that can be caught by a signal handler. Would there be a way to do something similar in Julia, e.g. a l…

I wrote GitHub - jwscook/ElideableMacros.jl: Elidable macros in Julia, that can be compiled out as a way to try to understand macros (it turns out I didn’t master them). I’m fairly certain the hygiene is wrong, but it allowed me to create @elideableassert, which can be used with @elideableassert !i…

NaN treated as an error Is there any new features/options in Julia V1.6.4 where one can treat NaN as an error and therefore I can determine where in my code NaN is being produced? Many thanks for any suggestions

It would be nice if Julia would support signaling NAN, but this seems to be an open issue . Not sure what LLVM does support here, though.

We ran into similar problems with NaN popping up when we computed derivatives with ForwardDiff; finding the source was very difficult. We wrote this utility type to make it easier. It probably doesn’t support every floating point operation but it was enough for our use. Hasn’t been tested under 1.7…

The nansafe_mode of ForwardDiff.jl can help with debugging NaNs.

I may well be totally mistaken, but I have an impression that the NaN signal (the “invalid-operation exception” of IEEE) is generated at the hardware level. If that’s the case, it’s Julia’s interpreter that decides to ignore the signal and it would be possible to have a switch on the interpreter to…

Bumping this. Would be very useful feature.

Treating NaN as error: Helping debugging

General Usage

simeonschaub November 21, 2021, 10:12pm 8

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Support for signaling NaNs? General Usage question , nan	1	958	November 19, 2024
Division by zero runs without warning -> complicates finding bugs Internals & Design question	31	3220	May 17, 2024
NaN Detector General Usage debugging , nan	10	1702	February 25, 2021
Trap floating point exceptions Numerics	0	682	June 8, 2017
min(NaN,5) = NaN (why no @fastmath?) General Usage nan	47	2349	February 2, 2023

Treating NaN as error: Helping debugging

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