def test_add_gaussian_noise(self): s = self.signal s.change_dtype("float64") kwargs = {} if s._lazy: data = s.data.compute() from dask.array.random import seed, normal kwargs["chunks"] = s.data.chunks else: data = s.data.copy() from numpy.random import seed, normal seed(1) s.add_gaussian_noise(std=1.0) seed(1) if s._lazy: s.compute() np.testing.assert_array_almost_equal( s.data - data, normal(scale=1.0, size=data.shape, **kwargs))
def test_add_poisson_noise(self): s = self.signal kwargs = {} if s._lazy: data = s.data.compute() from dask.array.random import seed, poisson kwargs["chunks"] = s.data.chunks else: data = s.data.copy() from numpy.random import seed, poisson seed(1) s.add_poissonian_noise(keep_dtype=False) if s._lazy: s.compute() seed(1) np.testing.assert_array_almost_equal(s.data, poisson(lam=data, **kwargs)) s.change_dtype("float64") seed(1) s.add_poissonian_noise(keep_dtype=True) if s._lazy: s.compute() assert s.data.dtype == np.dtype("float64")
def test_add_poisson_noise(self): s = self.signal kwargs = {} if s._lazy: data = s.data.compute() from dask.array.random import seed, poisson kwargs["chunks"] = s.data.chunks else: data = s.data.copy() from numpy.random import seed, poisson seed(1) s.add_poissonian_noise(keep_dtype=False) if s._lazy: s.compute() seed(1) np.testing.assert_array_almost_equal( s.data, poisson(lam=data, **kwargs)) s.change_dtype("float64") seed(1) s.add_poissonian_noise(keep_dtype=True) if s._lazy: s.compute() assert s.data.dtype == np.dtype("float64")