#1123 Fix mod derivative handling in Symbolics.jl (#1123) #1490
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test/runtests.jl
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| activate_sympy_env() | ||
| @safetestset "SymPy Test" begin include("sympy.jl") end | ||
| end | ||
| include("test_expand_derivatives.jl") |
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Needs to be in a test group, should just be in the standard core tests.
src/diff.jl
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| function expand_derivatives(n::Num, simplify=false; kwargs...) | ||
| wrap(expand_derivatives(value(n), simplify; kwargs...)) | ||
| n = walk(x -> x isa Float64 ? Rational(x) : x, value(n)) |
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Rationalizing floating point numbers like 0.3 will lead to some unexpected results. Instead, we should probably just rationalize integers?
src/diff.jl
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| function expand_derivatives(n::Num, simplify=false; kwargs...) | ||
| wrap(expand_derivatives(value(n), simplify; kwargs...)) | ||
| n = walk(x -> x isa Float64 ? Rational(x) : x, value(n)) |
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Suggested change
| n = walk(x -> x isa Float64 ? Rational(x) : x, value(n)) | |
| n = walk(x -> x isa Int? Rational(x) : x, value(n)) |
Is this sufficient to fix the issue?
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@ChrisRackauckas I’ve made the suggested changes. Could you please review my code? Additionally, I’d appreciate more suggestions to help solve this issue |
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This PR addresses Issue #1123 by modifying the diff.jl file to add a custom derivative rule for the mod function in Symbolics.jl. The previous implementation didn’t handle mod well during symbolic differentiation, so we added this rule to improve its handling. We also updated runtests.jl to include tests for this change and created a new file test_expand_derivatives.jl to check its behavior. We’re not entirely sure if this is the best solution and would love suggestions on other possible methods to handle this more effectively.