def test_mean(self): # for doc purposes: the mean of PMFs is not the PMF of the mean numpy.random.seed(42) matrix = numpy.random.random(self.matrix.shape) pmf1 = disagg.mag_pmf(self.matrix) pmf2 = disagg.mag_pmf(matrix) mean = (matrix + self.matrix) / 2 numpy.testing.assert_allclose((pmf1 + pmf2) / 2, [1, 1]) numpy.testing.assert_allclose(disagg.mag_pmf(mean), [0.99999944, 0.99999999])
def test_mean(self): # for doc purposes: the mean of PMFs is not the PMF of the mean numpy.random.seed(42) matrix = numpy.random.random(self.matrix.shape) pmf1 = disagg.mag_pmf(self.matrix) pmf2 = disagg.mag_pmf(matrix) mean = (matrix + self.matrix) / 2 numpy.testing.assert_allclose( (pmf1 + pmf2) / 2, [1, 1]) numpy.testing.assert_allclose( disagg.mag_pmf(mean), [0.99999944, 0.99999999])
def test_magnitude_bins(self): """ Testing build disaggregation matrix """ fname = os.path.join(DATA_PATH, 'data', 'ssm.xml') converter = sourceconverter.SourceConverter(50., 1., 10, 0.1, 10) groups = to_python(fname, converter) sources = [] for g in groups: sources += g.sources site = Site(Point(172.63, -43.53), vs30=250, vs30measured=False, z1pt0=330) imt = SA(3.0) iml = 0.25612220 gsim_by_trt = {TRT.ACTIVE_SHALLOW_CRUST: Bradley2013()} truncation_level = 3.0 n_epsilons = 1 mag_bin_width = 0.1 dist_bin_width = 100. coord_bin_width = 100. # Compute the disaggregation matrix edges, mtx = disagg.disaggregation(sources, site, imt, iml, gsim_by_trt, truncation_level, n_epsilons, mag_bin_width, dist_bin_width, coord_bin_width) tm = disagg.mag_pmf(mtx[:, :, :, :, :, 0]) numpy.testing.assert_array_less(numpy.zeros_like(tm[2:]), tm[2:])
def test_mag(self): pmf = disagg.mag_pmf(self.matrix) self.aae(pmf, [1.0, 1.0])
def test_mag(self): pmf = disagg.mag_pmf(self.matrix) self.aae(pmf, [30.29, 34.57])