# Compute fourrier transform in Julia
**URL:** https://discourse.julialang.org/t/compute-fourrier-transform-in-julia/99664
**Category:** Numerics
**Tags:** question
**Created:** [May 31, 2023, 10:35am UTC](https://discourse.julialang.org/t/compute-fourrier-transform-in-julia/99664 "2023-05-31T10:35:16Z")
**Posts on this page:** 2
**Page:** 2
### Author:  [@Fourier](https://discourse.julialang.org/u/Fourier)
#### Post date: [June 5, 2023, 8:48am UTC](https://discourse.julialang.org/t/compute-fourrier-transform-in-julia/99664/21 "2023-06-05T08:48:07Z")
Also I might leave these formula I found in the recommended book ([Numerical Fourier Analysis | SpringerLink](https://link.springer.com/book/10.1007/978-3-030-04306-3)) here, maybe they are usefull to someone encountering the same problem.
The discrete fourrier transform is given by:
Whereas if I want to actually want to approximate the fourrier transform from a dataset, it is given by:
where \omega\_{nN}^{jk} = \exp(i \dots)
so we could see which shifts and normalisation one would need to perform.
here is the formula for the DFT used by fftw:
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### Author:  [@kellertuer](https://discourse.julialang.org/u/kellertuer)
#### Post date: [June 5, 2023, 9:07am UTC](https://discourse.julialang.org/t/compute-fourrier-transform-in-julia/99664/22 "2023-06-05T09:07:16Z")
…and again be a bit careful, in the notation of said book (which I prefer) the inverse Fourier Transform has a factor of 1/N upfront, and (in theory) some prefer to also use the unitary DFT [Discrete Fourier transform - Wikipedia](https://en.wikipedia.org/wiki/Discrete_Fourier_transform#The_unitary_DFT) or put the 1/N upfront the DFT instead of the inverse. But I think the one from the book should be the most common definition.
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