def _get_aux_plot_filtered(self, po, vs, es=None): omits = [] invalids = [] outliers = [] fs = po.filter_str nsigma = po.sigma_filter_n if fs or nsigma: if es is None: es = zeros_like(vs) ufs = vstack((vs, es)).T filter_str_idx = None if fs: filter_str_idx = filter_ufloats(ufs, fs) ftag = po.filter_str_tag.lower() if ftag == 'invalid': invalids.extend(filter_str_idx) elif ftag == 'outlier': outliers.extend(filter_str_idx) else: omits.extend(filter_str_idx) if nsigma: vs = ma.array(vs, mask=False) if filter_str_idx is not None: vs.mask[filter_str_idx] = True sigma_idx = sigma_filter(vs, nsigma) stag = po.sigma_filter_tag.lower() if stag == 'invalid': invalids.extend(sigma_idx) elif stag == 'outlier': outliers.extend(sigma_idx) else: omits.extend(sigma_idx) return omits, invalids, outliers
def _get_aux_plot_filtered(self, po, vs, es=None): omits = [] invalids = [] outliers = [] fs = po.filter_str nsigma = po.sigma_filter_n if fs or nsigma: if es is None: es = zeros_like(vs) ufs = vstack((vs, es)).T if fs: filter_str_idx = filter_ufloats(ufs, fs) ftag = po.filter_str_tag.lower() if ftag == 'invalid': invalids.extend(filter_str_idx) elif ftag == 'outlier': outliers.extend(filter_str_idx) else: omits.extend(filter_str_idx) if nsigma: vs = ma.array(vs, mask=False) vs.mask[filter_str_idx] = True sigma_idx = sigma_filter(vs, nsigma) stag = po.sigma_filter_tag.lower() if stag == 'invalid': invalids.extend(sigma_idx) elif stag == 'outlier': outliers.extend(sigma_idx) else: omits.extend(sigma_idx) return omits, invalids, outliers
def test_sigma_filter_masked3(self): x = ma.array([1, 1, 1, 1, 1, 10, 11], mask=False) x.mask[[5, 6]] = True o = sigma_filter(x, 1) self.assertListEqual(o, [])