def test_sigma_clip_mean():
with NumpyRNGContext(12345):
data = np.random.normal(0., 0.05, (10, 10))
data[2, 2] = 1.e5
sobj1 = SigmaClip(sigma=1, maxiters=2, cenfunc='mean')
sobj2 = SigmaClip(sigma=1, maxiters=2, cenfunc=np.nanmean)
assert_equal(sobj1(data), sobj2(data))
assert_equal(sobj1(data, axis=0), sobj2(data, axis=0))
def test_sigma_clip_class():
with NumpyRNGContext(12345):
data = np.random.randn(100)
data[10] = 1.e5
sobj = SigmaClip(sigma=1, maxiters=2)
sfunc = sigma_clip(data, sigma=1, maxiters=2)
assert_equal(sobj(data), sfunc)
def test_sigmaclip_repr():
sigclip = SigmaClip()
median_str = str(sigclip._parse_cenfunc('median'))
std_str = str(sigclip._parse_stdfunc('std'))
sigclip_repr = ('SigmaClip(sigma=3.0, sigma_lower=3.0, sigma_upper=3.0,'
' maxiters=5, cenfunc={}, stdfunc={}, '
'grow=False)'.format(median_str, std_str))
sigclip_str = ('<SigmaClip>\n sigma: 3.0\n sigma_lower: 3.0\n'
' sigma_upper: 3.0\n maxiters: 5\n'
' cenfunc: {}\n stdfunc: {}\n'
' grow: False'.format(median_str, std_str))
assert repr(sigclip) == sigclip_repr
assert str(sigclip) == sigclip_str
def test_sigmaclip_repr():
sigclip = SigmaClip()
sigclip_repr = ('SigmaClip(sigma=3.0, sigma_lower=3.0, sigma_upper=3.0,'
' maxiters=5, cenfunc=')
sigclip_str = ('<SigmaClip>\n sigma: 3.0\n sigma_lower: 3.0\n'
' sigma_upper: 3.0\n maxiters: 5\n cenfunc: ')
assert repr(sigclip).startswith(sigclip_repr)
assert str(sigclip).startswith(sigclip_str)
def test_sigmaclip_repr():
sigclip = SigmaClip()
sigclip_repr = ('SigmaClip(sigma=3.0, sigma_lower=3.0, sigma_upper=3.0,'
' maxiters=5, cenfunc=median, stdfunc=std, '
'grow=False)')
sigclip_str = ('<SigmaClip>\n sigma: 3.0\n sigma_lower: 3.0\n'
' sigma_upper: 3.0\n maxiters: 5\n'
' cenfunc: median\n stdfunc: std\n'
' grow: False')
assert repr(sigclip) == sigclip_repr
assert str(sigclip) == sigclip_str
def test_sigma_clip_invalid_cenfunc_stdfunc():
with pytest.raises(ValueError):
SigmaClip(cenfunc='invalid')
with pytest.raises(ValueError):
SigmaClip(stdfunc='invalid')
