Discrete Fourier transform: Difference between revisions
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# Verify the correctness of your implementation using a small sequence of integers, such as 2 3 5 7 11
The fourier transform of a sequence <math>
<math>X_{n} = \sum_{k=0}^{N-1} x_{k}\cdot e^{-i \frac{2 \pi}{N} k n}</math>
The inverse transform is given by:
<math>
=={{header|Go}}==
{{trans|Wren}}
<syntaxhighlight lang="go">package main
import (
"fmt"
"math"
"math/cmplx"
)
func dft(x []complex128) []complex128 {
N := len(x)
y := make([]complex128, N)
for k := 0; k < N; k++ {
for n := 0; n < N; n++ {
t := -1i * 2 * complex(math.Pi*float64(k)*float64(n)/float64(N), 0)
y[k] += x[n] * cmplx.Exp(t)
}
}
return y
}
func idft(y []complex128) []float64 {
N := len(y)
x := make([]complex128, N)
for n := 0; n < N; n++ {
for k := 0; k < N; k++ {
t := 1i * 2 * complex(math.Pi*float64(k)*float64(n)/float64(N), 0)
x[n] += y[k] * cmplx.Exp(t)
}
x[n] /= complex(float64(N), 0)
// clean x[n] to remove very small imaginary values
if math.Abs(imag(x[n])) < 1e-14 {
x[n] = complex(real(x[n]), 0)
}
}
z := make([]float64, N)
for i, c := range x {
z[i] = float64(real(c))
}
return z
}
func main() {
z := []float64{2, 3, 5, 7, 11}
x := make([]complex128, len(z))
fmt.Println("Original sequence:", z)
for i, n := range z {
x[i] = complex(n, 0)
}
y := dft(x)
fmt.Println("\nAfter applying the Discrete Fourier Transform:")
fmt.Printf("%0.14g", y)
fmt.Println("\n\nAfter applying the Inverse Discrete Fourier Transform to the above transform:")
z = idft(y)
fmt.Printf("%0.14g", z)
fmt.Println()
}</syntaxhighlight>
{{out}}
<pre>
Original sequence: [2 3 5 7 11]
After applying the Discrete Fourier Transform:
[(28+0i) (-3.3819660112501+8.7840226349462i) (-5.6180339887499+2.8001689857495i) (-5.6180339887499-2.8001689857495i) (-3.3819660112501-8.7840226349462i)]
After applying the Inverse Discrete Fourier Transform to the above transform:
[2 3 5 7 11]
</pre>
=={{header|J}}
Implementation:
<syntaxhighlight lang
ifourier=: # %~ ] +/@:* ^@
require'general/misc/numeric'
clean=: 1e_9
Example use:
<syntaxhighlight lang
5.6 _0.676393j1.7568 _1.12361j0.560034 _1.12361j_0.560034 _0.676393j_1.7568
clean ifourier fourier 2 3 5 7 11
2 3 5 7 11
clean ifourier 2 * fourier 2 3 5 7 11
4 6 10 14 22
clean ifourier 2 + fourier 2 3 5 7 11
=={{header|jq}}==
'''Adapted from [[#Wren|Wren]]'''
{{works with|jq}}
'''Works with gojq, the Go implementation of jq'''
This entry uses a "complex" module, such as is available at [[Arithmetic/Complex#jq]].
<syntaxhighlight lang="jq">include "complex"; # a reminder
def dft:
. as $x
| length as $N
| reduce range (0; $N) as $k ([]; # y
.[$k] = [0,0] # Complex.zero
| reduce range( 0; $N) as $n (.;
([[0, -1], [2,0], [pi,0], $k, $n, invert($N) ] | multiply) as $t
| .[$k] = plus(.[$k]; multiply($x[$n]; exp($t))) ) ) ;
# Input: an array of Complex
def idft:
. as $y
| length as $N
| reduce range(0; $N) as $n ([];
.[$n] = [0,0]
| reduce range(0; $N) as $k (.;
( [ 2, pi, [0,1], $k, $n, invert($N)] | multiply) as $t
| .[$n] = plus(.[$n]; multiply($y[$k]; exp($t))) )
| .[$n] = divide(.[$n]; $N) );
def task:
def abs: if . < 0 then -. else . end;
# round, and remove very small imaginary values altogether
def tidy:
(.[0] | round) as $round
| if (.[0]| (. - $round) | abs < 1e-14) then .[0] = $round else . end
| if .[1]|abs < 1e-14 then .[0] else . end;
[2, 3, 5, 7, 11] as $x
| "Original sequence: \($x)",
(reduce range(0; $x|length) as $i ( []; .[$i] = [$x[$i], 0])
| dft
| "\nAfter applying the Discrete Fourier Transform:",
.,
"\nAfter applying the Inverse Discrete Fourier Transform to this value: \(
idft | map(tidy))" )
;
task</syntaxhighlight>
{{out}}
<pre>
Original sequence: [2,3,5,7,11]
After applying the Discrete Fourier Transform:
[[28,0],[-3.3819660112501078,8.784022634946174],[-5.618033988749895,2.8001689857494747],[-5.618033988749892,-2.8001689857494823],[-3.381966011250096,-8.784022634946178]]
After applying the Inverse Discrete Fourier Transform to this value: [2,3,5,7,11]
</pre>
=={{header|Julia}}==
The cispi function was added in Julia 1.6. The cispi of x is e to the power of (pi times i times x). Other syntax, such as {T,N} in the function signature and real() and ntuple() in the loop, is designed to support arbitrary dimensional arrays and to cue the compiler so as to have mostly constants in the loop at runtime, speeding run time with large arrays.
<syntaxhighlight lang="julia">function dft(A::AbstractArray{T,N}) where {T,N}
F = zeros(complex(float(T)), size(A)...)
for k in CartesianIndices(F), n in CartesianIndices(A)
Line 55 ⟶ 189:
end
fseq = dft(seq)
println("$seq =>\n$fseq =>\n$newseq =>\n", Int.(round.(newseq)))
seq2 = [2 7; 3 11; 5 13]
fseq = dft(seq2)
newseq = idft(fseq)
println("$seq2 =>\n$fseq =>\n$newseq =>\n", Int.(round.(newseq)))
</syntaxhighlight>{{out}}
<pre>
[2, 3, 5, 7, 11] =>
ComplexF64[28.0 + 0.0im, -3.3819660112501033 + 8.784022634946172im, -5.618033988749888 + 2.800168985749483im, -5.618033988749888 - 2.800168985749483im, -3.381966011250112 - 8.78402263494618im] =>
ComplexF64[2.0000000000000013 - 1.4210854715202005e-15im, 2.999999999999996 + 7.993605777301127e-16im, 5.000000000000002 + 2.1316282072803005e-15im, 6.999999999999998 - 8.881784197001252e-16im, 11.0 + 0.0im] =>
[2, 3, 5, 7, 11]
[2 7; 3 11; 5 13] =>
ComplexF64[41.0 + 0.0im -21.0 + 0.0im; -7.000000000000002 + 3.46410161513775im 3.0000000000000053 + 7.105427357601002e-15im; -6.9999999999999964 - 3.4641016151377606im 3.0000000000000053 + 7.105427357601002e-15im] =>
ComplexF64[2.000000000000002 + 5.921189464667501e-16im 6.999999999999997 - 4.144832625267251e-15im; 2.9999999999999996 - 8.881784197001252e-16im 11.000000000000002 + 1.0362081563168128e-15im; 4.999999999999999 + 0.0im 13.000000000000002 + 1.924386576016938e-15im] =>
[2 7; 3 11; 5 13]
</pre>
=={{header|Mathematica}}/{{header|Wolfram Language}}==
<syntaxhighlight lang="mathematica">ClearAll[DFT, IDFT]
DFT[x_List] := Module[{length},
length = Length[x];
N@Table[Sum[x[[n + 1]] Exp[-I 2 Pi k n/length], {n, 0, length - 1}], {k, 0, length - 1}]
]
IDFT[X_List] := Module[{length},
length = Length[X];
N@Table[Sum[X[[k + 1]] Exp[-I 2 Pi k n/length], {k, 0, length - 1}]/length, {n, 0, length - 1}]
]
DFT[{2, 3, 5, 7, 11}]
IDFT[%] // Chop</syntaxhighlight>
{{out}}
<pre>{28., -3.38197 + 8.78402 I, -5.61803 + 2.80017 I, -5.61803 - 2.80017 I, -3.38197 - 8.78402 I}
{2., 11., 7., 5., 3.}</pre>
=={{header|Nim}}==
{{trans|Wren}}
<syntaxhighlight lang="nim">import complex, math, sequtils, strutils
func dft(x: openArray[Complex64]): seq[Complex64] =
let N = x.len
result.setLen(N)
for k in 0..<N:
for n in 0..<N:
let t = complex64(0, -2 * PI * float(k) * float(n) / float(N))
result[k] += x[n] * exp(t)
func idft(y: openArray[Complex64]): seq[Complex64] =
let N = y.len
result.setLen(N)
let d = complex64(float(N))
for n in 0..<N:
for k in 0..<N:
let t = complex64(0, 2 * PI * float(k) * float(n) / float(N))
result[n] += y[k] * exp(t)
result[n] /= d
# Clean result[n] to remove very small imaginary values.
if abs(result[n].im) < 1e-14: result[n].im = 0.0
func `$`(c: Complex64): string =
result = c.re.formatFloat(ffDecimal, precision = 2)
if c.im != 0:
result.add if c.im > 0: "+" else: ""
result.add c.im.formatFloat(ffDecimal, precision = 2) & 'i'
when isMainModule:
let x = [float 2, 3, 5, 7, 11].mapIt(complex64(it))
echo "Original sequence: ", x.join(", ")
let y = dft(x)
echo "Discrete Fourier transform: ", y.join(", ")
echo "Inverse Discrete Fourier Transform: ", idft(y).join(", ")</syntaxhighlight>
{{out}}
<pre>Original sequence: 2.00, 3.00, 5.00, 7.00, 11.00
Discrete Fourier transform: 28.00, -3.38+8.78i, -5.62+2.80i, -5.62-2.80i, -3.38-8.78i
Inverse Discrete Fourier Transform: 2.00, 3.00, 5.00, 7.00, 11.00</pre>
=={{header|Perl}}==
<syntaxhighlight lang="perl"># 20210616 Perl programming solution
use strict;
use warnings;
use feature 'say';
use Math::Complex;
use constant PI => 4 * atan2(1, 1);
use constant ESP => 1e10; # net worth, the imaginary part
use constant EPS => 1e-10; # the reality part
sub dft {
my $n = scalar ( my @in = @_ );
return map {
my $s=0;
for my $k (0 .. $n-1) { $s += $in[$k] * exp(-2*i * PI * $k * $_ / $n) }
$_ = $s;
} (0 .. $n-1);
}
sub idft {
my $n = scalar ( my @in = @_ );
return map {
my $s=0;
for my $k (0 .. $n-1) { $s += $in[$k] * exp(2*i * PI * $k * $_ / $n) }
my $t = $s/$n;
$_ = abs(Im $t) < EPS ? Re($t) : $t
} (0 .. $n-1);
}
say 'Original sequence : ', join ', ', my @series = ( 2, 3, 5, 7, 11 );
say 'Discrete Fourier transform : ', join ', ', my @dft = dft @series;
say 'Inverse Discrete Fourier Transform : ', join ', ', idft @dft;
</syntaxhighlight>
{{out}}
<pre>
Original sequence : 2, 3, 5, 7, 11
Discrete Fourier transform : 28, -3.38196601125011+8.78402263494617i,-5.6180339887499+2.80016898574947i, -5.61803398874989-2.80016898574948i, -3.3819660112501-8.78402263494618i
Inverse Discrete Fourier Transform : 2, 3, 5, 7, 11
</pre>
=={{header|Phix}}==
{{trans|Wren}}
<!--<syntaxhighlight lang="phix">(phixonline)-->
<span style="color: #008080;">include</span> <span style="color: #004080;">complex</span><span style="color: #0000FF;">.</span><span style="color: #000000;">e</span>
<span style="color: #008080;">function</span> <span style="color: #000000;">dft</span><span style="color: #0000FF;">(</span><span style="color: #004080;">sequence</span> <span style="color: #000000;">x</span><span style="color: #0000FF;">)</span>
<span style="color: #004080;">integer</span> <span style="color: #000000;">N</span> <span style="color: #0000FF;">=</span> <span style="color: #7060A8;">length</span><span style="color: #0000FF;">(</span><span style="color: #000000;">x</span><span style="color: #0000FF;">)</span>
<span style="color: #004080;">sequence</span> <span style="color: #000000;">y</span> <span style="color: #0000FF;">=</span> <span style="color: #7060A8;">repeat</span><span style="color: #0000FF;">(</span><span style="color: #000000;">0</span><span style="color: #0000FF;">,</span><span style="color: #000000;">N</span><span style="color: #0000FF;">)</span>
<span style="color: #008080;">for</span> <span style="color: #000000;">k</span><span style="color: #0000FF;">=</span><span style="color: #000000;">1</span> <span style="color: #008080;">to</span> <span style="color: #000000;">N</span> <span style="color: #008080;">do</span>
<span style="color: #004080;">complex</span> <span style="color: #000000;">yk</span> <span style="color: #0000FF;">=</span> <span style="color: #7060A8;">complex_new</span><span style="color: #0000FF;">(</span><span style="color: #000000;">0</span><span style="color: #0000FF;">,</span><span style="color: #000000;">0</span><span style="color: #0000FF;">)</span>
<span style="color: #008080;">for</span> <span style="color: #000000;">n</span><span style="color: #0000FF;">=</span><span style="color: #000000;">1</span> <span style="color: #008080;">to</span> <span style="color: #000000;">N</span> <span style="color: #008080;">do</span>
<span style="color: #004080;">complex</span> <span style="color: #000000;">t</span> <span style="color: #0000FF;">=</span> <span style="color: #7060A8;">complex_new</span><span style="color: #0000FF;">(</span><span style="color: #000000;">0</span><span style="color: #0000FF;">,-</span><span style="color: #000000;">2</span><span style="color: #0000FF;">*</span><span style="color: #004600;">PI</span><span style="color: #0000FF;">*(</span><span style="color: #000000;">k</span><span style="color: #0000FF;">-</span><span style="color: #000000;">1</span><span style="color: #0000FF;">)*(</span><span style="color: #000000;">n</span><span style="color: #0000FF;">-</span><span style="color: #000000;">1</span><span style="color: #0000FF;">)/</span><span style="color: #000000;">N</span><span style="color: #0000FF;">)</span>
<span style="color: #000000;">yk</span> <span style="color: #0000FF;">=</span> <span style="color: #7060A8;">complex_add</span><span style="color: #0000FF;">(</span><span style="color: #000000;">yk</span><span style="color: #0000FF;">,</span><span style="color: #7060A8;">complex_mul</span><span style="color: #0000FF;">(</span><span style="color: #000000;">x</span><span style="color: #0000FF;">[</span><span style="color: #000000;">n</span><span style="color: #0000FF;">],</span><span style="color: #7060A8;">complex_exp</span><span style="color: #0000FF;">(</span><span style="color: #000000;">t</span><span style="color: #0000FF;">)))</span>
<span style="color: #008080;">end</span> <span style="color: #008080;">for</span>
<span style="color: #000000;">y</span><span style="color: #0000FF;">[</span><span style="color: #000000;">k</span><span style="color: #0000FF;">]</span> <span style="color: #0000FF;">=</span> <span style="color: #000000;">yk</span>
<span style="color: #008080;">end</span> <span style="color: #008080;">for</span>
<span style="color: #008080;">return</span> <span style="color: #000000;">y</span>
<span style="color: #008080;">end</span> <span style="color: #008080;">function</span>
<span style="color: #008080;">function</span> <span style="color: #000000;">idft</span><span style="color: #0000FF;">(</span><span style="color: #004080;">sequence</span> <span style="color: #000000;">y</span><span style="color: #0000FF;">)</span>
<span style="color: #004080;">integer</span> <span style="color: #000000;">N</span> <span style="color: #0000FF;">=</span> <span style="color: #7060A8;">length</span><span style="color: #0000FF;">(</span><span style="color: #000000;">y</span><span style="color: #0000FF;">)</span>
<span style="color: #004080;">sequence</span> <span style="color: #000000;">x</span> <span style="color: #0000FF;">=</span> <span style="color: #7060A8;">repeat</span><span style="color: #0000FF;">(</span><span style="color: #000000;">0</span><span style="color: #0000FF;">,</span><span style="color: #000000;">N</span><span style="color: #0000FF;">)</span>
<span style="color: #008080;">for</span> <span style="color: #000000;">n</span><span style="color: #0000FF;">=</span><span style="color: #000000;">1</span> <span style="color: #008080;">to</span> <span style="color: #000000;">N</span> <span style="color: #008080;">do</span>
<span style="color: #004080;">object</span> <span style="color: #000000;">xn</span> <span style="color: #0000FF;">=</span> <span style="color: #7060A8;">complex_new</span><span style="color: #0000FF;">(</span><span style="color: #000000;">0</span><span style="color: #0000FF;">,</span><span style="color: #000000;">0</span><span style="color: #0000FF;">)</span>
<span style="color: #008080;">for</span> <span style="color: #000000;">k</span><span style="color: #0000FF;">=</span><span style="color: #000000;">1</span> <span style="color: #008080;">to</span> <span style="color: #000000;">N</span> <span style="color: #008080;">do</span>
<span style="color: #004080;">complex</span> <span style="color: #000000;">t</span> <span style="color: #0000FF;">=</span> <span style="color: #7060A8;">complex_new</span><span style="color: #0000FF;">(</span><span style="color: #000000;">0</span><span style="color: #0000FF;">,</span><span style="color: #000000;">2</span><span style="color: #0000FF;">*</span><span style="color: #004600;">PI</span><span style="color: #0000FF;">*(</span><span style="color: #000000;">k</span><span style="color: #0000FF;">-</span><span style="color: #000000;">1</span><span style="color: #0000FF;">)*(</span><span style="color: #000000;">n</span><span style="color: #0000FF;">-</span><span style="color: #000000;">1</span><span style="color: #0000FF;">)/</span><span style="color: #000000;">N</span><span style="color: #0000FF;">)</span>
<span style="color: #000000;">xn</span> <span style="color: #0000FF;">=</span> <span style="color: #7060A8;">complex_add</span><span style="color: #0000FF;">(</span><span style="color: #000000;">xn</span><span style="color: #0000FF;">,</span><span style="color: #7060A8;">complex_mul</span><span style="color: #0000FF;">(</span><span style="color: #000000;">y</span><span style="color: #0000FF;">[</span><span style="color: #000000;">k</span><span style="color: #0000FF;">],</span><span style="color: #7060A8;">complex_exp</span><span style="color: #0000FF;">(</span><span style="color: #000000;">t</span><span style="color: #0000FF;">)))</span>
<span style="color: #008080;">end</span> <span style="color: #008080;">for</span>
<span style="color: #000000;">xn</span> <span style="color: #0000FF;">=</span> <span style="color: #7060A8;">complex_div</span><span style="color: #0000FF;">(</span><span style="color: #000000;">xn</span><span style="color: #0000FF;">,</span><span style="color: #000000;">N</span><span style="color: #0000FF;">)</span>
<span style="color: #000080;font-style:italic;">// clean xn to remove very small imaginary values, and round reals to 14dp</span>
<span style="color: #008080;">if</span> <span style="color: #7060A8;">abs</span><span style="color: #0000FF;">(</span><span style="color: #7060A8;">complex_imag</span><span style="color: #0000FF;">(</span><span style="color: #000000;">xn</span><span style="color: #0000FF;">))<</span><span style="color: #000000;">1e-14</span> <span style="color: #008080;">then</span> <span style="color: #000000;">xn</span> <span style="color: #0000FF;">=</span> <span style="color: #7060A8;">round</span><span style="color: #0000FF;">(</span><span style="color: #7060A8;">complex_real</span><span style="color: #0000FF;">(</span><span style="color: #000000;">xn</span><span style="color: #0000FF;">),</span><span style="color: #000000;">1e14</span><span style="color: #0000FF;">)</span> <span style="color: #008080;">end</span> <span style="color: #008080;">if</span>
<span style="color: #000000;">x</span><span style="color: #0000FF;">[</span><span style="color: #000000;">n</span><span style="color: #0000FF;">]</span> <span style="color: #0000FF;">=</span> <span style="color: #000000;">xn</span>
<span style="color: #008080;">end</span> <span style="color: #008080;">for</span>
<span style="color: #008080;">return</span> <span style="color: #000000;">x</span>
<span style="color: #008080;">end</span> <span style="color: #008080;">function</span>
<span style="color: #004080;">sequence</span> <span style="color: #000000;">x</span> <span style="color: #0000FF;">=</span> <span style="color: #0000FF;">{</span><span style="color: #000000;">2</span><span style="color: #0000FF;">,</span> <span style="color: #000000;">3</span><span style="color: #0000FF;">,</span> <span style="color: #000000;">5</span><span style="color: #0000FF;">,</span> <span style="color: #000000;">7</span><span style="color: #0000FF;">,</span> <span style="color: #000000;">11</span><span style="color: #0000FF;">},</span>
<span style="color: #000000;">y</span> <span style="color: #0000FF;">=</span> <span style="color: #000000;">dft</span><span style="color: #0000FF;">(</span><span style="color: #000000;">x</span><span style="color: #0000FF;">),</span>
<span style="color: #000000;">z</span> <span style="color: #0000FF;">=</span> <span style="color: #000000;">idft</span><span style="color: #0000FF;">(</span><span style="color: #000000;">y</span><span style="color: #0000FF;">)</span>
<span style="color: #7060A8;">printf</span><span style="color: #0000FF;">(</span><span style="color: #000000;">1</span><span style="color: #0000FF;">,</span><span style="color: #008000;">"Original sequence: %v\n"</span><span style="color: #0000FF;">,{</span><span style="color: #000000;">x</span><span style="color: #0000FF;">})</span>
<span style="color: #7060A8;">printf</span><span style="color: #0000FF;">(</span><span style="color: #000000;">1</span><span style="color: #0000FF;">,</span><span style="color: #008000;">"Discrete Fourier Transform: %v\n"</span><span style="color: #0000FF;">,{</span><span style="color: #7060A8;">apply</span><span style="color: #0000FF;">(</span><span style="color: #000000;">y</span><span style="color: #0000FF;">,</span><span style="color: #7060A8;">complex_sprint</span><span style="color: #0000FF;">)})</span>
<span style="color: #7060A8;">printf</span><span style="color: #0000FF;">(</span><span style="color: #000000;">1</span><span style="color: #0000FF;">,</span><span style="color: #008000;">"Inverse Discrete Fourier Transform: %v\n"</span><span style="color: #0000FF;">,{</span><span style="color: #000000;">z</span><span style="color: #0000FF;">})</span>
<!--</syntaxhighlight>-->
{{out}}
<pre>
Original sequence: {2,3,5,7,11}
Discrete Fourier Transform: {"28","-3.38197+8.78402i","-5.61803+2.80017i","-5.61803-2.80017i","-3.38197-8.78402i"}
Inverse Discrete Fourier Transform: {2,3,5,7,11}
</pre>
=={{header|Python}}==
<syntaxhighlight lang="python"># 20220918 Python programming solution
import cmath
def dft( x ):
"""Takes N either real or complex signal samples, yields complex DFT bins. Assuming the input
waveform is filtered to only contain signals in the bandwidth B range -B/2:+B/2 around baseband
frequency MID, and is frequency shifted (divided by) your baseband frequency MID, and is sampled
at the Nyquist rate R: given N samples, the result contains N signal frequency component bins:
index: 0 N/2 N-1
baseband: [MID+] [MID+] ... [MID+] [MID+/-] [MID+] ... [MID+]
frequency: DC 1B/N (N/2-1)B/N (N/2)B/N (1-N/2)B/N -1B/N
"""
N = len( x )
result = []
for k in range( N ):
r = 0
for n in range( N ):
t = -2j * cmath.pi * k * n / N
r += x[n] * cmath.exp( t )
result.append( r )
return result
def idft( y ):
"""Inverse DFT on complex frequency bins."""
N = len( y )
result = []
for n in range( N ):
r = 0
for k in range( N ):
t = 2j * cmath.pi * k * n / N
r += y[k] * cmath.exp( t )
r /= N+0j
result.append( r )
return result
if __name__ == "__main__":
x = [ 2, 3, 5, 7, 11 ]
print( "vals: " + ' '.join( f"{f:11.2f}" for f in x ))
y = dft( x )
print( "DFT: " + ' '.join( f"{f:11.2f}" for f in y ))
z = idft( y )
print( "inverse:" + ' '.join( f"{f:11.2f}" for f in z ))
print( " - real:" + ' '.join( f"{f.real:11.2f}" for f in z ))
N = 8
print( f"Complex signals, 1-4 cycles in {N} samples; energy into successive DFT bins" )
for rot in (0, 1, 2, 3, -4, -3, -2, -1): # cycles; and bins in ascending index order
if rot > N/2:
print( "Signal change frequency exceeds sample rate and will result in artifacts")
sig = [
# unit-magnitude complex samples, rotated through 2Pi 'rot' times, in N steps
cmath.rect(
1, cmath.pi*2*rot/N*i
)
for i in range( N )
]
print( f"{rot:2} cycle" + ' '.join( f"{f:11.2f}" for f in sig ))
dft_sig = dft( sig )
print( f" DFT: " + ' '.join( f"{f:11.2f}" for f in dft_sig ))
print( f" ABS: " + ' '.join( f"{abs(f):11.2f}" for f in dft_sig ))
</syntaxhighlight>
{{out}}
<pre>
vals: 2.00 3.00 5.00 7.00 11.00
DFT: 28.00+0.00j -3.38+8.78j -5.62+2.80j -5.62-2.80j -3.38-8.78j
inverse: 2.00-0.00j 3.00-0.00j 5.00+0.00j 7.00+0.00j 11.00+0.00j
- real: 2.00 3.00 5.00 7.00 11.00
Complex signals, 1-4 cycles in 8 samples; energy into successive DFT bins
0 cycle 1.00+0.00j 1.00+0.00j 1.00+0.00j 1.00+0.00j 1.00+0.00j 1.00+0.00j 1.00+0.00j 1.00+0.00j
DFT: 8.00+0.00j -0.00+0.00j -0.00-0.00j -0.00+0.00j 0.00-0.00j -0.00-0.00j -0.00-0.00j 0.00+0.00j
ABS: 8.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
1 cycle 1.00+0.00j 0.71+0.71j 0.00+1.00j -0.71+0.71j -1.00+0.00j -0.71-0.71j -0.00-1.00j 0.71-0.71j
DFT: -0.00-0.00j 8.00+0.00j -0.00+0.00j 0.00-0.00j -0.00-0.00j 0.00+0.00j 0.00+0.00j 0.00+0.00j
ABS: 0.00 8.00 0.00 0.00 0.00 0.00 0.00 0.00
2 cycle 1.00+0.00j 0.00+1.00j -1.00+0.00j -0.00-1.00j 1.00-0.00j 0.00+1.00j -1.00+0.00j -0.00-1.00j
DFT: -0.00+0.00j -0.00-0.00j 8.00+0.00j -0.00-0.00j -0.00-0.00j 0.00-0.00j 0.00-0.00j 0.00-0.00j
ABS: 0.00 0.00 8.00 0.00 0.00 0.00 0.00 0.00
3 cycle 1.00+0.00j -0.71+0.71j -0.00-1.00j 0.71+0.71j -1.00+0.00j 0.71-0.71j 0.00+1.00j -0.71-0.71j
DFT: -0.00-0.00j 0.00+0.00j -0.00+0.00j 8.00+0.00j -0.00+0.00j -0.00-0.00j 0.00+0.00j 0.00-0.00j
ABS: 0.00 0.00 0.00 8.00 0.00 0.00 0.00 0.00
-4 cycle 1.00-0.00j -1.00-0.00j 1.00+0.00j -1.00-0.00j 1.00+0.00j -1.00-0.00j 1.00+0.00j -1.00-0.00j
DFT: 0.00-0.00j 0.00-0.00j 0.00-0.00j 0.00-0.00j 8.00+0.00j -0.00-0.00j 0.00-0.00j -0.00-0.00j
ABS: 0.00 0.00 0.00 0.00 8.00 0.00 0.00 0.00
-3 cycle 1.00-0.00j -0.71-0.71j -0.00+1.00j 0.71-0.71j -1.00-0.00j 0.71+0.71j 0.00-1.00j -0.71+0.71j
DFT: -0.00+0.00j 0.00-0.00j 0.00+0.00j -0.00-0.00j 0.00-0.00j 8.00+0.00j -0.00-0.00j -0.00+0.00j
ABS: 0.00 0.00 0.00 0.00 0.00 8.00 0.00 0.00
-2 cycle 1.00-0.00j 0.00-1.00j -1.00-0.00j -0.00+1.00j 1.00+0.00j 0.00-1.00j -1.00-0.00j -0.00+1.00j
DFT: -0.00-0.00j -0.00-0.00j 0.00-0.00j 0.00+0.00j 0.00-0.00j 0.00-0.00j 8.00+0.00j -0.00+0.00j
ABS: 0.00 0.00 0.00 0.00 0.00 0.00 8.00 0.00
-1 cycle 1.00-0.00j 0.71-0.71j 0.00-1.00j -0.71-0.71j -1.00-0.00j -0.71+0.71j -0.00+1.00j 0.71+0.71j
DFT: -0.00+0.00j 0.00-0.00j -0.00-0.00j 0.00-0.00j 0.00-0.00j 0.00-0.00j 0.00-0.00j 8.00+0.00j
ABS: 0.00 0.00 0.00 0.00 0.00 0.00 0.00 8.00
</pre>
=={{header|Raku}}==
* This task could be done with a loop of maps like<br><tt>@X[k] = sum @x.kv.map: -> \n, \v { v * exp( -i * tau / N * k * n ) }</tt><br>, but it is a better fit for Raku's concurrent Hyper-operators.
* In the DFT formula, ''N'' becomes ''+@x'', the element count. We would usually omit the plus sign and get the same result from numeric context, but that gets confusing to read when mixed with hyper-ops like <tt>»*«</tt> .
* The exponents of DFT and IDFT only differ from each other in the sign of ''i'', and the calculation of any given elements only differ by the ''k'' index of the element being output, so the inner loop is cleanly shareable between DFT and IDFT.
* Euler's constant, imaginary unit, pi, and 2pi are built-in, with ASCII and Unicode spellings: <tt>e 𝑒 i pi π tau τ</tt> .
* <tt>$one_thing «op« @many_things</tt> vectorizes the ''op'' operation: <tt>5 «+« (1,2,3)</tt> is <tt>(6,7,8)</tt> .
* <tt>@many_things »op« @many_more_things</tt> distributes the ''op'' operation pairwise: <tt>(5,6,7) »+« (1,2,3)</tt> is <tt>(6,8,10)</tt> .
* <tt>(list)».method</tt> applies the method to each element of the list.
* <tt>@array.keys</tt>, when <tt>@array</tt> has e.g. 4 elements, is <tt>0,1,2,3</tt> .
* <tt>$n.round($r)</tt> returns ''$n'' rounded to the nearest ''$r''. <tt>(13/16).round(1/4)</tt> is <tt>3/4</tt> .
* .narrow changes a Numeric's type to a "narrower" type, when no precision would be lost.<br><tt>8/2</tt> is <tt>4</tt>, but is type Rat (rational). <tt>(8/2).narrow</tt> is also <tt>4</tt>, but type Int.
<syntaxhighlight lang="raku" line>sub ft_inner ( @x, $k, $pos_neg_i where * == i|-i ) {
my @exp := ( $pos_neg_i * tau / +@x * $k ) «*« @x.keys;
return sum @x »*« 𝑒 «**« @exp;
}
sub dft ( @x ) { return @x.keys.map: { ft_inner( @x, $_, -i ) } }
sub idft ( @x ) { return @x.keys.map: { ft_inner( @x, $_, i ) / +@x } }
sub clean ( @x ) { @x».round(1e-12)».narrow }
my @tests = ( 1, 2-i, -i, -1+2i ),
( 2, 3, 5, 7, 11 ),
;
for @tests -> @x {
my @x_dft = dft(@x);
my @x_idft = idft(@x_dft);
say .key.fmt('%6s:'), .value.&clean.fmt('%5s', ', ') for :@x, :@x_dft, :@x_idft;
say '';
warn "Round-trip failed" unless ( clean(@x) Z== clean(@x_idft) ).all;
}</syntaxhighlight>
{{out}}
<pre>
x: 1, 2-1i, 0-1i, -1+2i
x_dft: 2, -2-2i, 0-2i, 4+4i
x_idft: 1, 2-1i, 0-1i, -1+2i
x: 2, 3, 5, 7, 11
x_dft: 28, -3.38196601125+8.784022634946i, -5.61803398875+2.800168985749i, -5.61803398875-2.800168985749i, -3.38196601125-8.784022634946i
x_idft: 2, 3, 5, 7, 11</pre>
=={{header|Wren}}==
{{libheader|Wren-complex}}
<syntaxhighlight lang="wren">import "./complex" for Complex
var dft = Fn.new { |x|
var N = x.count
var y = List.filled(N, null)
for (k in 0...N) {
y[k] = Complex.zero
for (n in 0...N) {
var t = Complex.imagMinusOne * Complex.two * Complex.pi * k * n / N
y[k] = y[k] + x[n] * t.exp
}
}
return y
}
var idft = Fn.new { |y|
var N = y.count
var x = List.filled(N, null)
for (n in 0...N) {
x[n] = Complex.zero
for (k in 0...N) {
var t = Complex.imagOne * Complex.two * Complex.pi * k * n / N
x[n] = x[n] + y[k] * t.exp
}
x[n] = x[n] / N
// clean x[n] to remove very small imaginary values
if (x[n].imag.abs < 1e-14) x[n] = Complex.new(x[n].real, 0)
}
return x
}
var x = [2, 3, 5, 7, 11]
System.print("Original sequence: %(x)")
for (i in 0...x.count) x[i] = Complex.new(x[i])
var y = dft.call(x)
Complex.showAsReal = true // don't display the imaginary part if it's 0
System.print("\nAfter applying the Discrete Fourier Transform:")
System.print(y)
System.print("\nAfter applying the Inverse Discrete Fourier Transform to the above transform:")
System.print(idft.call(y))</syntaxhighlight>
{{out}}
<pre>
Original sequence: [2, 3, 5, 7, 11]
After applying the Discrete Fourier Transform:
[28, -3.3819660112501 + 8.7840226349462i, -5.6180339887499 + 2.8001689857495i, -5.6180339887499 - 2.8001689857495i, -3.3819660112501 - 8.7840226349462i]
After applying the Inverse Discrete Fourier Transform to the above transform:
[2, 3, 5, 7, 11]
</pre>
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