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, [])
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, [])
