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')