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@doc doc""" | ||
@time ex | ||
Executes the expression `ex`, printing the time it took to | ||
execute and the total number of bytes its execution caused to be | ||
allocated. Returns the value of the expression. For example: | ||
@time begin | ||
sleep(1) | ||
2+2 | ||
end | ||
""" @time | ||
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@doc doc""" | ||
r"..." | ||
Construct a regex, such as `r"^[a-z]*$"`. | ||
""" r"" | ||
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@doc doc""" | ||
push!(collection, items...) → collection | ||
Insert `items` at the end of `collection`. | ||
""" push! | ||
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@doc doc""" | ||
fft(A[, dims]) | ||
Performs a multidimensional FFT of the array `A`. The optional | ||
`dims` argument specifies an iterable subset of dimensions (e.g. | ||
an integer, range, tuple, or array) to transform along. Most | ||
efficient if the size of `A` along the transformed dimensions is | ||
a product of small primes; see `nextprod()`. See also | ||
`plan_fft()` for even greater efficiency. | ||
A one-dimensional FFT computes the one-dimensional discrete Fourier | ||
transform (DFT) as defined by | ||
$$\operatorname{DFT}(A)[k] = | ||
\sum_{n=1}^{\operatorname{length}(A)} | ||
\exp\left(-i\frac{2\pi | ||
(n-1)(k-1)}{\operatorname{length}(A)} \right) A[n].$$ | ||
A multidimensional FFT simply performs this operation along each | ||
transformed dimension of `A`. | ||
Higher performance is usually possible with multi-threading. Use | ||
`FFTW.set_num_threads(np)` to use `np` threads, if you have `np` | ||
processors. | ||
""" fft |
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