def test_scale_matches_that_from_fix_source_scale_with_gaussian_by_default(
self):
scale = sources.fix_transformer_scale(self.arma)
self.arma_alt.default_source = sources.GaussianNoise()
scale_alt = sources.fix_source_scale(self.arma_alt)
self.assertAlmostEqual(scale, scale_alt)
def test_arguments_forwarded_to_fix_source_scale(self):
kwargs = {"output_std": 3.5, "n_samples": 500}
scale = sources.fix_transformer_scale(self.arma, **kwargs)
self.arma_alt.default_source = sources.GaussianNoise()
scale_alt = sources.fix_source_scale(self.arma_alt, **kwargs)
self.assertAlmostEqual(scale, scale_alt)
def test_using_different_source_constructor(self):
loc = 1.0
seed = 3
scale = sources.fix_transformer_scale(
self.arma,
source_constructor=lambda **kwargs: sources.GaussianNoise(
loc=loc, rng=seed, **kwargs),
)
self.arma_alt.default_source = sources.GaussianNoise(loc=loc, rng=seed)
scale_alt = sources.fix_source_scale(self.arma_alt)
self.assertAlmostEqual(scale, scale_alt)
def _figure_out_scales(self, fix_scale: float):
""" Use fix_source_scale to normalize ARMA outputs. """
all_scales = []
for sig_arma in self.armas:
sig_scales = []
for arma in sig_arma:
scale = sources.fix_transformer_scale(arma,
output_std=fix_scale)
# # switch to a new source for scale calculation (but only temporarily)
# old_source = arma.default_source
# arma.default_source = sources.GaussianNoise()
# scale = sources.fix_source_scale(
# arma, output_std=fix_scale, use_copy=False
# )
sig_scales.append(scale)
# return to the Arma process's original source
# arma.default_source = old_source
all_scales.append(sig_scales)
self.noise_scales = np.asarray(all_scales)
def test_transformer_source_scaling_is_same_as_return_value(self):
scale = sources.fix_transformer_scale(self.arma)
self.assertAlmostEqual(scale, self.arma.source_scaling)