def main():
specs = [u.make_specs(1) for i in range(N_SIGNALS)]
makers = [s.Periodic(spec, noise=0.0) for spec in specs]
# take data to be a list of tuples [... (nsr, error) ...]
fft_data = []
lpsvd_data = []
noises = linspace(0.0, 1.0, N_NOISES)
for nsr in noises:
for spec,maker in zip(specs,makers):
maker.noise = 0.0
amp = 2.0 * (
average([m**2 for m in maker.time_series(D_LENGTH)])
)
maker.noise = nsr
seed = maker.time_series(D_LENGTH)
fft_d = fft.fft(seed)
fft_r = [c.real for c in fft.ifft(fft_d)]
lpsvd_d = l.LPSVD(seed, count=2.0).decomposition()
lpsvd_r = lpsvd_d.time_series(D_LENGTH)
maker.noise = 0.0
clean = maker.time_series(D_LENGTH)
fft_err = 1.0 * (u.mean_sq_error(clean,fft_r)) / amp
lpsvd_err = 1.0 * (u.mean_sq_error(clean,lpsvd_r)) / amp
fft_data.append((nsr, fft_err))
lpsvd_data.append((nsr, lpsvd_err))
for fd in fft_data:
print str(fd[0])+"\t"+str(fd[1])
for ld in lpsvd_data:
print str(ld[0])+"\t"+str(ld[1])
do_plot(fft_data, lpsvd_data)
return None
def test_unequal_lengths(self):
a = range(10)
b = range(100)
err = u.mean_sq_error(a,b)
self.assertEqual(0, err)
def test_errors(self):
a = [1,1,1]
b = [1,2,3]
err = u.mean_sq_error(a,b)
expected = 5.0/3.0
self.assertEqual(err, expected)
def test_zero_error(self):
a = range(10)
b = a[:]
err = u.mean_sq_error(a,b)
self.assertEqual(0, err)