def _test_N_dependence(wc0, mu0, scale0, N0, th):
"""Independent"""
Ns = (np.array([.25, .5, 2, 4, 9]) * N0).astype('int64')
errs = np.zeros(len(Ns))
wavelet = Wavelet(('morlet', {'mu': mu0, 'dtype': 'float64'}))
for i, N in enumerate(Ns):
wc = center_frequency(wavelet, scale=scale0, N=N, kind='energy')
errs[i] = abs(wc - wc0)
_assert_and_viz(th, errs, Ns, 'N', "Center frequency (energy), morlet")
def _test_mu_dependence(wc0, mu0, scale0, N0, th):
"""wc ~ mu"""
mus = np.arange(mu0 + 1, 21)
errs = np.zeros(len(mus))
for i, mu in enumerate(mus):
wavelet = Wavelet(('morlet', {'mu': mu}))
wc = center_frequency(wavelet, scale=scale0, N=N0, kind='energy')
errs[i] = abs((wc / wc0) - (mu / mu0))
_assert_and_viz(th, errs, mus, 'mu',
"Center frequency (energy), morlet")
def test_utils():
os.environ['SSQ_GPU'] = '0'
_ = utils.buffer(np.random.randn(20), 4, 1)
wavelet = Wavelet(('morlet', {'mu': 6}))
_ = wavelets.center_frequency(wavelet, viz=1)
_ = wavelets.freq_resolution(wavelet, viz=1, scale=3, force_int=0)
_ = wavelets.time_resolution(wavelet, viz=1)
xh = np.random.randn(128)
xhs = np.zeros(xh.size)
wavelets._aifftshift_even(xh, xhs)
wavelets._afftshift_even(xh, xhs)
_ = utils.padsignal(xh, padlength=len(xh) * 2, padtype='symmetric')
_ = utils.padsignal(xh, padlength=len(xh) * 2, padtype='wrap')
x2d = np.random.randn(4, 64)
_ = utils.padsignal(x2d, padlength=96, padtype='symmetric')
g = np.ones((128, 200))
utils.unbuffer(g, xh, 1, n_fft=len(xh), N=None, win_exp=0)
utils.unbuffer(g, xh, 1, n_fft=len(xh), N=g.shape[1], win_exp=2)
scales = utils.process_scales('log', 1024, Wavelet())
_ = utils.find_downsampling_scale(Wavelet(),
scales,
method='any',
viz_last=1)
_ = utils.find_downsampling_scale(Wavelet(), scales, method='all')
#### errors / warnings ###################################################
pass_on_error(utils.find_max_scale, 1, 1, -1, -1)
pass_on_error(utils.cwt_scalebounds, 1, 1, preset='etc', min_cutoff=0)
pass_on_error(utils.cwt_scalebounds, 1, 1, min_cutoff=-1)
pass_on_error(utils.cwt_scalebounds, 1, 1, min_cutoff=.2, max_cutoff=.1)
pass_on_error(utils.cwt_scalebounds, 1, 1, cutoff=0)
pass_on_error(utils.cwt_utils._assert_positive_integer, -1, 'w')
pass_on_error(utils.infer_scaletype, 1)
pass_on_error(utils.infer_scaletype, np.array([1]))
pass_on_error(utils.infer_scaletype, np.array([1., 2., 5.]))
pass_on_error(utils._process_fs_and_t, 1, np.array([1]), 2)
pass_on_error(utils._process_fs_and_t, 1, np.array([1., 2, 4]), 3)
pass_on_error(utils._process_fs_and_t, -1, None, 1)
pass_on_error(utils.make_scales, 128, scaletype='banana')
pass_on_error(utils.padsignal, np.random.randn(3, 4, 5))
def _test_scale_dependence_high(wc0, mu0, scale0, N0, th):
"""wc ~ 1/scale
High `scale` subject to more significant discretization error in
frequency domain.
"""
scales = 2**(np.arange(53, 81) / 8) # [90.5, ..., 1024]
errs = np.zeros(len(scales))
wavelet = Wavelet(('morlet', {'mu': mu0}))
for i, scale in enumerate(scales):
wc = center_frequency(wavelet, scale=scale, N=N0, kind='energy')
errs[i] = abs((wc / wc0) - (scale0 / scale))
_assert_and_viz(th, errs, np.log2(scales), 'log2(scale)',
"Center frequency (energy), morlet | High scales")
def _test_scale_dependence(wc0, mu0, scale0, N0, th):
"""wc ~ 1/scale
For small `scale`, the bell is trimmed and the (energy) center frequency
is no longer at mode/peak (both of which are also trimmed), but is
less; we don't test these to keep code clean.
"""
scales = 2**(np.arange(16, 53) / 8) # [4, ..., 90.5]
errs = np.zeros(len(scales))
wavelet = Wavelet(('morlet', {'mu': mu0}))
for i, scale in enumerate(scales):
wc = center_frequency(wavelet, scale=scale, N=N0, kind='energy')
errs[i] = abs((wc / wc0) - (scale0 / scale))
_assert_and_viz(th, errs, np.log2(scales), 'log2(scale)',
"Center frequency (energy), morlet")
def test_utils():
_ = buffer(np.random.randn(20), 4, 1)
wavelet = Wavelet(('morlet', {'mu': 6}))
_ = center_frequency(wavelet, viz=1)
_ = freq_resolution(wavelet, viz=1, scale=3, force_int=0)
_ = time_resolution(wavelet, viz=1)
xh = np.random.randn(128)
xhs = np.zeros(xh.size)
_aifftshift_even(xh, xhs)
_afftshift_even(xh, xhs)
_ = padsignal(xh, padlength=len(xh) * 2, padtype='symmetric')
_ = padsignal(xh, padlength=len(xh) * 2, padtype='wrap')
g = np.ones((128, 200))
unbuffer(g, xh, 1, n_fft=len(xh), N=None, win_exp=0)
unbuffer(g, xh, 1, n_fft=len(xh), N=g.shape[1], win_exp=2)
#### errors / warnings ###################################################
_pass_on_error(find_max_scale, 1, 1, -1, -1)
_pass_on_error(cwt_scalebounds, 1, 1, preset='etc', min_cutoff=0)
_pass_on_error(cwt_scalebounds, 1, 1, min_cutoff=-1)
_pass_on_error(cwt_scalebounds, 1, 1, min_cutoff=.2, max_cutoff=.1)
_pass_on_error(cwt_scalebounds, 1, 1, cutoff=0)
_pass_on_error(_assert_positive_integer, -1, 'w')
_pass_on_error(_infer_scaletype, 1)
_pass_on_error(_infer_scaletype, np.array([1]))
_pass_on_error(_infer_scaletype, np.array([1., 2., 5.]))
_pass_on_error(_process_fs_and_t, 1, np.array([1]), 2)
_pass_on_error(_process_fs_and_t, 1, np.array([1., 2, 4]), 3)
_pass_on_error(_process_fs_and_t, -1, None, 1)
_pass_on_error(make_scales, 128, scaletype='banana')
def test_energy_center_frequency():
"""If kind='energy' passes, long shot for 'peak' to fail, so just test
former; would still be interesting to investigate 'peak' vs 'energy',
esp. at scale extrema.
"""
def _test_mu_dependence(wc0, mu0, scale0, N0, th):
"""wc ~ mu"""
mus = np.arange(mu0 + 1, 21)
errs = np.zeros(len(mus))
for i, mu in enumerate(mus):
wavelet = Wavelet(('morlet', {'mu': mu}))
wc = center_frequency(wavelet, scale=scale0, N=N0, kind='energy')
errs[i] = abs((wc / wc0) - (mu / mu0))
_assert_and_viz(th, errs, mus, 'mu',
"Center frequency (energy), morlet")
def _test_scale_dependence(wc0, mu0, scale0, N0, th):
"""wc ~ 1/scale
For small `scale`, the bell is trimmed and the (energy) center frequency
is no longer at mode/peak (both of which are also trimmed), but is
less; we don't test these to keep code clean.
"""
scales = 2**(np.arange(16, 53) / 8) # [4, ..., 90.5]
errs = np.zeros(len(scales))
wavelet = Wavelet(('morlet', {'mu': mu0}))
for i, scale in enumerate(scales):
wc = center_frequency(wavelet, scale=scale, N=N0, kind='energy')
errs[i] = abs((wc / wc0) - (scale0 / scale))
_assert_and_viz(th, errs, np.log2(scales), 'log2(scale)',
"Center frequency (energy), morlet")
def _test_scale_dependence_high(wc0, mu0, scale0, N0, th):
"""wc ~ 1/scale
High `scale` subject to more significant discretization error in
frequency domain.
"""
scales = 2**(np.arange(53, 81) / 8) # [90.5, ..., 1024]
errs = np.zeros(len(scales))
wavelet = Wavelet(('morlet', {'mu': mu0}))
for i, scale in enumerate(scales):
wc = center_frequency(wavelet, scale=scale, N=N0, kind='energy')
errs[i] = abs((wc / wc0) - (scale0 / scale))
_assert_and_viz(th, errs, np.log2(scales), 'log2(scale)',
"Center frequency (energy), morlet | High scales")
def _test_N_dependence(wc0, mu0, scale0, N0, th):
"""Independent"""
Ns = (np.array([.25, .5, 2, 4, 9]) * N0).astype('int64')
errs = np.zeros(len(Ns))
wavelet = Wavelet(('morlet', {'mu': mu0}))
for i, N in enumerate(Ns):
wc = center_frequency(wavelet, scale=scale0, N=N, kind='energy')
errs[i] = abs(wc - wc0)
_assert_and_viz(th, errs, Ns, 'N',
"Center frequency (energy), morlet")
mu0 = 5
scale0 = 10
N0 = 1024
wavelet0 = Wavelet(('morlet', {'mu': mu0}))
wc0 = center_frequency(wavelet0, scale=scale0, N=N0, kind='energy')
args = (wc0, mu0, scale0, N0)
_test_mu_dependence( *args, th=1e-7)
_test_scale_dependence( *args, th=1e-14)
_test_scale_dependence_high(*args, th=1e-1)
_test_N_dependence( *args, th=1e-14)