/usr/share/julia/test/fft.jl is in julia-common 0.4.7-6.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 | # This file is a part of Julia. License is MIT: http://julialang.org/license
# fft
a = rand(8) + im*rand(8)
@test norm(ifft(fft(a)) - a) < 1e-8
m4 = [16. 2 3 13;
5 11 10 8;
9 7 6 12;
4 14 15 1]
true_fft_m4 = [
34. 34. 34. 34.;
7. - 1.im -5. + 3.im -3. + 5.im 1. - 7.im;
16. -16. -16. 16.;
7. + 1.im -5. - 3.im -3. - 5.im 1. + 7.im ]
true_fftn_m4 = [
136. 0 0 0 ;
0. 20 8 + 8im 0 - 12im ;
0. 32 + 32im 0 32 - 32im ;
0. 0 + 12im 8 - 8im 20 ]
true_fftd2_m4 = [
34. 13 + 11im 4 13 - 11im ;
34. -5 - 3im -4 -5 + 3im ;
34. 3 + 5im -4 3 - 5im ;
34. -11 - 13im 4 -11 + 13im ]
b = rand(17,14)
b[3:6,9:12] = m4
sm4 = slice(b,3:6,9:12)
m3d = map(Float32,reshape(1:5*3*2, 5, 3, 2))
true_fftd3_m3d = Array(Float32, 5, 3, 2)
true_fftd3_m3d[:,:,1] = 17:2:45
true_fftd3_m3d[:,:,2] = -15
# use invoke to force usage of CTPlan versions even if FFTW is present
for A in (Array,SubArray)
for f in (:fft,:ifft,:plan_fft,:plan_ifft)
f_ = symbol(string(f, "_"))
@eval begin
$f_{T,N}(x::$A{T,N}) = invoke($f, Tuple{AbstractArray{T,N}}, x)
$f_{T,N,R}(x::$A{T,N},r::R) = invoke($f,Tuple{AbstractArray{T,N},R},x,r)
end
end
end
for (f,fi,pf,pfi) in ((fft,ifft,plan_fft,plan_ifft),
(fft_,ifft_,plan_fft_,plan_ifft_))
pm4 = pf(m4,1)
fft_m4 = f(m4,1)
fftd2_m4 = f(m4,2)
ifft_fft_m4 = fi(f(m4,1),1)
fftn_m4 = f(m4)
ifftn_fftn_m4 = fi(f(m4))
fft!_m4 = complex(m4); fft!(fft!_m4,1)
fft!d2_m4 = complex(m4); fft!(fft!d2_m4,2)
ifft!_fft_m4 = f(m4,1); ifft!(ifft!_fft_m4,1)
fft!n_m4 = complex(m4); fft!(fft!n_m4)
ifft!n_fftn_m4 = f(m4); ifft!(ifft!n_fftn_m4)
pfft_m4 = pf(m4,1)*m4
pfftd2_m4 = pf(m4,2)*m4
pifft_fft_m4 = pfi(fft_m4,1)*fft_m4
pfftn_m4 = pf(m4)*m4
pifftn_fftn_m4 = pfi(fftn_m4)*fftn_m4
pfft!_m4 = complex(m4); plan_fft!(pfft!_m4,1)*pfft!_m4
pfft!d2_m4 = complex(m4); plan_fft!(pfft!d2_m4,2)*pfft!d2_m4
pifft!_fft_m4 = f(m4,1); plan_ifft!(pifft!_fft_m4,1)*pifft!_fft_m4
pfft!n_m4 = complex(m4); plan_fft!(pfft!n_m4)*pfft!n_m4
pifft!n_fftn_m4 = f(m4); plan_ifft!(pifft!n_fftn_m4)*pifft!n_fftn_m4
sfftn_m4 = f(sm4)
psfftn_m4 = pf(sm4)*sm4
sfft!n_b = map(Complex128,b)
sfft!n_m4 = slice(sfft!n_b,3:6,9:12); fft!(sfft!n_m4)
psfft!n_b = map(Complex128,b)
psfft!n_m4 = slice(psfft!n_b,3:6,9:12); plan_fft!(psfft!n_m4)*psfft!n_m4
for i = 1:length(m4)
@test_approx_eq fft_m4[i] true_fft_m4[i]
@test_approx_eq fftd2_m4[i] true_fftd2_m4[i]
@test_approx_eq ifft_fft_m4[i] m4[i]
@test_approx_eq fftn_m4[i] true_fftn_m4[i]
@test_approx_eq ifftn_fftn_m4[i] m4[i]
@test_approx_eq fft!_m4[i] true_fft_m4[i]
@test_approx_eq fft!d2_m4[i] true_fftd2_m4[i]
@test_approx_eq ifft!_fft_m4[i] m4[i]
@test_approx_eq fft!n_m4[i] true_fftn_m4[i]
@test_approx_eq ifft!n_fftn_m4[i] m4[i]
@test_approx_eq pfft_m4[i] true_fft_m4[i]
@test_approx_eq pfftd2_m4[i] true_fftd2_m4[i]
@test_approx_eq pifft_fft_m4[i] m4[i]
@test_approx_eq pfftn_m4[i] true_fftn_m4[i]
@test_approx_eq pifftn_fftn_m4[i] m4[i]
@test_approx_eq pfft!_m4[i] true_fft_m4[i]
@test_approx_eq pfft!d2_m4[i] true_fftd2_m4[i]
@test_approx_eq pifft!_fft_m4[i] m4[i]
@test_approx_eq pfft!n_m4[i] true_fftn_m4[i]
@test_approx_eq pifft!n_fftn_m4[i] m4[i]
@test_approx_eq sfftn_m4[i] true_fftn_m4[i]
@test_approx_eq sfft!n_m4[i] true_fftn_m4[i]
@test_approx_eq psfftn_m4[i] true_fftn_m4[i]
@test_approx_eq psfft!n_m4[i] true_fftn_m4[i]
end
ifft!(sfft!n_m4)
plan_ifft!(psfft!n_m4)*psfft!n_m4
@test norm(sfft!n_m4 - m4) < 1e-8
@test norm(psfft!n_m4 - m4) < 1e-8
# The following capabilities are FFTW only.
# They are not available in MKL, and hence do not test them.
if Base.fftw_vendor() != :mkl
ifft3_fft3_m3d = fi(f(m3d))
fftd3_m3d = f(m3d,3)
ifftd3_fftd3_m3d = fi(fftd3_m3d,3)
fft!d3_m3d = complex(m3d); fft!(fft!d3_m3d,3)
ifft!d3_fftd3_m3d = copy(fft!d3_m3d); ifft!(ifft!d3_fftd3_m3d,3)
pfftd3_m3d = pf(m3d,3)*m3d
pifftd3_fftd3_m3d = pfi(fftd3_m3d,3)*fftd3_m3d
pfft!d3_m3d = complex(m3d); plan_fft!(pfft!d3_m3d,3)*pfft!d3_m3d
pifft!d3_fftd3_m3d = copy(fft!d3_m3d); plan_ifft!(pifft!d3_fftd3_m3d,3)*pifft!d3_fftd3_m3d
@test isa(fftd3_m3d, Array{Complex64,3})
@test isa(ifftd3_fftd3_m3d, Array{Complex64,3})
@test isa(fft!d3_m3d, Array{Complex64,3})
@test isa(ifft!d3_fftd3_m3d, Array{Complex64,3})
@test isa(pfftd3_m3d, Array{Complex64,3})
@test isa(pifftd3_fftd3_m3d, Array{Complex64,3})
@test isa(pfft!d3_m3d, Array{Complex64,3})
@test isa(pifft!d3_fftd3_m3d, Array{Complex64,3})
for i = 1:length(m3d)
@test_approx_eq fftd3_m3d[i] true_fftd3_m3d[i]
@test_approx_eq ifftd3_fftd3_m3d[i] m3d[i]
@test_approx_eq ifft3_fft3_m3d[i] m3d[i]
@test_approx_eq fft!d3_m3d[i] true_fftd3_m3d[i]
@test_approx_eq ifft!d3_fftd3_m3d[i] m3d[i]
@test_approx_eq pfftd3_m3d[i] true_fftd3_m3d[i]
@test_approx_eq pifftd3_fftd3_m3d[i] m3d[i]
@test_approx_eq pfft!d3_m3d[i] true_fftd3_m3d[i]
@test_approx_eq pifft!d3_fftd3_m3d[i] m3d[i]
end
end # if fftw_vendor() != :mkl ...
# rfft/rfftn
rfft_m4 = rfft(m4,1)
rfftd2_m4 = rfft(m4,2)
rfftn_m4 = rfft(m4)
prfft_m4 = plan_rfft(m4,1)*m4
prfftd2_m4 = plan_rfft(m4,2)*m4
prfftn_m4 = plan_rfft(m4)*m4
srfftn_m4 = rfft(sm4)
psrfftn_m4 = plan_rfft(sm4)*sm4
for i = 1:3, j = 1:4
@test_approx_eq rfft_m4[i,j] true_fft_m4[i,j]
@test_approx_eq rfftd2_m4[j,i] true_fftd2_m4[j,i]
@test_approx_eq rfftn_m4[i,j] true_fftn_m4[i,j]
@test_approx_eq prfft_m4[i,j] true_fft_m4[i,j]
@test_approx_eq prfftd2_m4[j,i] true_fftd2_m4[j,i]
@test_approx_eq prfftn_m4[i,j] true_fftn_m4[i,j]
@test_approx_eq srfftn_m4[i,j] true_fftn_m4[i,j]
@test_approx_eq psrfftn_m4[i,j] true_fftn_m4[i,j]
end
irfft_rfft_m4 = irfft(rfft_m4,size(m4,1),1)
irfft_rfftd2_m4 = irfft(rfftd2_m4,size(m4,2),2)
irfftn_rfftn_m4 = irfft(rfftn_m4,size(m4,1))
pirfft_rfft_m4 = plan_irfft(rfft_m4,size(m4,1),1)*rfft_m4
pirfft_rfftd2_m4 = plan_irfft(rfftd2_m4,size(m4,2),2)*rfftd2_m4
pirfftn_rfftn_m4 = plan_irfft(rfftn_m4,size(m4,1))*rfftn_m4
for i = 1:length(m4)
@test_approx_eq irfft_rfft_m4[i] m4[i]
@test_approx_eq irfft_rfftd2_m4[i] m4[i]
@test_approx_eq irfftn_rfftn_m4[i] m4[i]
@test_approx_eq pirfft_rfft_m4[i] m4[i]
@test_approx_eq pirfft_rfftd2_m4[i] m4[i]
@test_approx_eq pirfftn_rfftn_m4[i] m4[i]
end
if Base.fftw_vendor() != :mkl
rfftn_m3d = rfft(m3d)
rfftd3_m3d = rfft(m3d,3)
@test size(rfftd3_m3d) == size(fftd3_m3d)
irfft_rfftd3_m3d = irfft(rfftd3_m3d,size(m3d,3),3)
irfftn_rfftn_m3d = irfft(rfftn_m3d,size(m3d,1))
for i = 1:length(m3d)
@test_approx_eq rfftd3_m3d[i] true_fftd3_m3d[i]
@test_approx_eq irfft_rfftd3_m3d[i] m3d[i]
@test_approx_eq irfftn_rfftn_m3d[i] m3d[i]
end
fftn_m3d = fft(m3d)
@test size(fftn_m3d) == (5,3,2)
rfftn_m3d = rfft(m3d)
@test size(rfftn_m3d) == (3,3,2)
for i = 1:3, j = 1:3, k = 1:2
@test_approx_eq rfftn_m3d[i,j,k] fftn_m3d[i,j,k]
end
end # !mkl
end
# FFT self-test algorithm (for unscaled 1d forward FFTs):
# Funda Ergün, "Testing multivariate linear functions: Overcoming
# the generator bottleneck," Proc. 27th ACM Symposium on the Theory
# of Computing, pp. 407-416 (1995).
# Check linearity, impulse-response, and time-shift properties.
function fft_test{T<:Complex}(p::Base.DFT.Plan{T}, ntrials=4,
tol=1e5 * eps(real(T)))
ndims(p) == 1 || throw(ArgumentError("not a 1d FFT"))
n = length(p)
twopi_i = (-2 * convert(real(T), π)/n * (0:n-1)) * im
for trial = 1:ntrials
# linearity:
x = rand(T, n)
y = rand(T, n)
α = rand(T)
β = rand(T)
X = p * (α*x + β*y)
err = norm(α * (p*x) + β * (p*y) - X, Inf) / norm(X, Inf)
err <= tol || error("linearity error $err in $p")
# impulse-response:
z = zeros(T, n)
i = rand(0:n-1)
z[i+1] = 1
X = exp(twopi_i*i)
err = norm(p*z - X, Inf) / norm(X, Inf)
err <= tol || error("impulse-response error $err in $p")
# time-shift:
if n > 1
s = rand(1:n-1)
X = (p*x).*exp(twopi_i*s)
err = norm(p*circshift(x,s) - X, Inf) / norm(X, Inf)
err <= tol || error("time-shift error $err in $p")
end
end
end
for T in (Complex64, Complex128)
for n in [1:100; 121; 143; 1000; 1024; 1031; 2000; 2048]
x = zeros(T, n)
fft_test(plan_fft(x))
fft_test(plan_fft_(x))
end
end
# test inversion, scaling, and pre-allocated variants
for T in (Complex64, Complex128)
for x in (T[1:100;], reshape(T[1:200;], 20,10))
y = similar(x)
for planner in (plan_fft, plan_fft_, plan_ifft, plan_ifft_)
p = planner(x)
pi = inv(p)
p3 = 3*p
p3i = inv(p3)
@test eltype(p) == eltype(pi) == eltype(p3) == eltype(p3i) == T
@test vecnorm(x - p3i * (p * 3x)) < eps(real(T)) * 10000
@test vecnorm(3x - pi * (p3 * x)) < eps(real(T)) * 10000
A_mul_B!(y, p, x)
@test y == p * x
A_ldiv_B!(y, p, x)
@test y == p \ x
end
end
end
let
plan32 = plan_fft([1.0:2048.0;])
plan64 = plan_fft([1f0:2048f0;])
FFTW.flops(plan32)
FFTW.flops(plan64)
end
# issue #9772
for x in (randn(10),randn(10,12))
z = complex(x)
y = rfft(x)
@inferred rfft(x)
@inferred brfft(x,18)
@inferred brfft(y,10)
for f in (plan_bfft!, plan_fft!, plan_ifft!,
plan_bfft, plan_fft, plan_ifft,
fft, bfft, fft_, ifft)
p = @inferred f(z)
if isa(p, FFTW.Plan)
@inferred FFTW.plan_inv(p)
end
end
for f in (plan_bfft, plan_fft, plan_ifft,
plan_rfft, fft, bfft, fft_, ifft)
p = @inferred f(x)
if isa(p, FFTW.Plan)
@inferred FFTW.plan_inv(p)
end
end
# note: inference doesn't work for plan_fft_ since the
# algorithm steps are included in the CTPlan type
end
|