CODEWITHSUNDEEP
pythonsignificant-digitsuncertainty
hi hi
hi hi

Reputation: 31

How do you round a number to correct uncertainty?

In python, I have a number: U = 0.02462631224438585 +- 3.350971888120506e-06.

How do I round it to the correct significant figures due to the uncertainty being rounded to 1s.f.? Is there an easy way of using numpy? Or scipy or are the built-in function the best for this?

I've tried using set_printoptions(precision=3) but this doesn't work. I've also tried using round(number, significant - len(str(number))), but this seems long-winded.

I'm sure I have used a function that is simply a couple of years ago without having to create my own.

The final number should be U = 2.4626e-02 +- 3e-06

or U = (2.4626 +- 3e-4)e-02

Upvotes: 3

Views: 1575

Answers (1)

PhMota
PhMota

Reputation: 321

the uncertainties module has the capability of computing the number of significant digits

import uncertainties
a = uncertainties.ufloat(0.02462631224438585, 3.350971888120506e-06)
print(a)
# 0.0246263+/-0.0000034

the defaut is two significant digits, however there is a format key for controlling the output

print('{:.1u}, {:.3uf}, {:.2uL}, {:0.2ue}'.format(a,a,a,a))
# 0.024626+/-0.000003, 0.02462631+/-0.00000335, 0.0246263 \pm 0.0000034, (2.46263+/-0.00034)e-02

Upvotes: 4

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