julia> BigFloat(1/26) 0.0384615384615384636735058165868395008146762847900390625 julia> 1/26 0.038461538461538464 In fact, 1/26=0.0384615[384615]… 384615 as a decimal cycle section. So I doubt the value of BigFloat(1/26) and 1/26 giving by Julia are not correct. What happened？

[image] a-boy: julia> BigFloat(1/26) julia> BigFloat(1)/BigFloat(26) 0.03846153846153846153846153846153846153846153846153846153846153846153846153846162 The code BigFloat(1/26) first computes 1/26 which becomes a Float64 and then converts that to a BigFloat.

What’s the problem/question here? Floating point numbers have limited precisions, they can’t losslessly represent all real numbers

[image] PSA: floating-point arithmetic Offtopic Sometimes people are surprised by the results of floating-point calculations such as julia> 5/6 0.8333333333333334 # shouldn't the last digit be 3? julia> 2.6 - 0.7 - 1.9 2.2204460492503…

Yes or BigFloat(1//26) which takes the exact rational 1//26 and converts it to BigFloat. [image] a-boy: why the output of 1/26 is 0.038461538461538464, not 0.038461538461538462? I’m going to assume there are no bugs in the Intel/AMD chips etc, so the number it gives must be the closest 64 bi…

[image] dlakelan: julia> 1/26 + eps(1/26) 0.03846153846153847 julia> 1/26 - eps(1/26) 0.03846153846153846 You usually want to use prevfloat/nextfloat, eps is the maximum of the distances to the two adjacent floating point numbers, which is not always the same between the two of them (otherwi…

Why does Julia say 1/26=0.038461538461538464

New to Julia

Sukera August 20, 2023, 4:03am 3

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Why does Julia say 1/26=0.038461538461538464

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