ERROR: DomainError with -123.74760920723358: Exponentiation yielding a complex result requires a complex argument. Replace x^y with (x+0im)^y, Complex(x)^y, or similar I figure I should start a new topic since I am running into a different error now. I hope by creating a new topic with the error in…

When you look up the error by clicking on the blue line number, you will see if isnan(z) & !isnan(x+y) throw_exp_domainerror(x) end in math.jl online 782. Apparently your simulation is producing not-a-numbers.

That source line is deceiving and due to a mismatch in LLVM/Julia semantics. His simulation isn’t generating NaNs — it’s generating negative numbers. Exponentiating negative numbers by a fractional exponent is an error in Julia but LLVM produces NaNs. In other words, the issue is this: julia> (-…

??? How does the error get misattributed? Are the line numbers in general in error?

No, the error is in the right place. I’m using master, so my line numbers are slightly different. The point is that the simulation isn’t the thing directly generating NaNs. The exponentiation is. That isnan check occurs after computing the exponentiation. The exponentiation intrinsic is generat…

Thank you for your reply. I am unable to click on the blue line number - I am using Atom and the stacktrace is all grey, but when I copy code into this forum colours do appear. Is there a way to have colour in a code in Atom? It would make it a lot easier to read, and maybe it would make things clic…

Thank you for your reply. Do you have any ideas why it is generating a negative number? I am confused how it can, because there are no negative values for those parameters.

Petr is likely using a Jupyter notebook, which linkifies the line numbers in stack traces. It can be very handy when you’re debugging your own files, but in a #user:first-steps thread it’s just a distraction to dig deep into Julia’s internals. I’m not a differential equations expert, but you’re so…

When experiencing such behavior, it is a good idea to check your simulations for a shorter time periode. By playing around with your code, it works with tspan = (0,13.87), with result (I used the pyplot() backend): [image] … but it crashes with tspan = (0,13.88). Based on the plot, I would guess …

Thank you for your reply. Do you know of a way for Julia to state the tspan at which it will crash, or is it a guessing game?

I did trial and error… That is not too difficult: start with a very small number to get a first idea, and then increase until it crashes. Your model appears to be similar to the following one, A Three-Species Food Chain System with Two Types of Functional Responses This paper contains some stabili…

Something is making Julia think I am using imaginary numbers?

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Something is making Julia think I am using imaginary numbers?

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