def test_cmov_window_special(self): _skip_if_no_scipy() try: from scikits.timeseries.lib import cmov_window except ImportError: raise nose.SkipTest win_types = ['kaiser', 'gaussian', 'general_gaussian', 'slepian'] kwds = [{ 'beta': 1. }, { 'std': 1. }, { 'power': 2., 'width': 2. }, { 'width': 0.5 }] for wt, k in zip(win_types, kwds): vals = np.random.randn(10) xp = cmov_window(vals, 5, (wt, ) + tuple(k.values())) rs = mom.rolling_window(Series(vals), 5, wt, center=True, **k) assert_series_equal(Series(xp), rs)
def test_cmov_window_frame(self): try: from scikits.timeseries.lib import cmov_window except ImportError: raise nose.SkipTest # DataFrame vals = np.random.randn(10, 2) xp = cmov_window(vals, 5, 'boxcar') rs = mom.rolling_window(DataFrame(vals), 5, 'boxcar', center=True) assert_frame_equal(DataFrame(xp), rs)
def test_cmov_window_frame(self): tm._skip_if_no_scipy() try: from scikits.timeseries.lib import cmov_window except ImportError: raise nose.SkipTest("no scikits.timeseries") # DataFrame vals = np.random.randn(10, 2) xp = cmov_window(vals, 5, "boxcar") rs = mom.rolling_window(DataFrame(vals), 5, "boxcar", center=True) assert_frame_equal(DataFrame(xp), rs)
def test_cmov_window_regular(self): try: from scikits.timeseries.lib import cmov_window except ImportError: raise nose.SkipTest win_types = ['triang', 'blackman', 'hamming', 'bartlett', 'bohman', 'blackmanharris', 'nuttall', 'barthann'] for wt in win_types: vals = np.random.randn(10) xp = cmov_window(vals, 5, wt) rs = mom.rolling_window(Series(vals), 5, wt, center=True) assert_series_equal(Series(xp), rs)
def test_cmov_window_regular(self): tm._skip_if_no_scipy() try: from scikits.timeseries.lib import cmov_window except ImportError: raise nose.SkipTest("no scikits.timeseries") win_types = ["triang", "blackman", "hamming", "bartlett", "bohman", "blackmanharris", "nuttall", "barthann"] for wt in win_types: vals = np.random.randn(10) xp = cmov_window(vals, 5, wt) rs = mom.rolling_window(Series(vals), 5, wt, center=True) assert_series_equal(Series(xp), rs)
def test_cmov_window(self): try: from scikits.timeseries.lib import cmov_window except ImportError: raise nose.SkipTest vals = np.random.randn(10) xp = cmov_window(vals, 5, 'boxcar') rs = mom.rolling_window(vals, 5, 'boxcar', center=True) assert_almost_equal(xp.compressed(), rs[2:-2]) assert_almost_equal(xp.mask, np.isnan(rs)) xp = Series(rs) rs = mom.rolling_window(Series(vals), 5, 'boxcar', center=True) assert_series_equal(xp, rs)
def test_cmov_window_special(self): tm._skip_if_no_scipy() try: from scikits.timeseries.lib import cmov_window except ImportError: raise nose.SkipTest("no scikits.timeseries") win_types = ["kaiser", "gaussian", "general_gaussian", "slepian"] kwds = [{"beta": 1.0}, {"std": 1.0}, {"power": 2.0, "width": 2.0}, {"width": 0.5}] for wt, k in zip(win_types, kwds): vals = np.random.randn(10) xp = cmov_window(vals, 5, (wt,) + tuple(k.values())) rs = mom.rolling_window(Series(vals), 5, wt, center=True, **k) assert_series_equal(Series(xp), rs)
def test_cmov_window_special(self): try: from scikits.timeseries.lib import cmov_window except ImportError: raise nose.SkipTest win_types = ['kaiser', 'gaussian', 'general_gaussian', 'slepian'] kwds = [{'beta' : 1.}, {'std' : 1.}, {'power' : 2., 'width' : 2.}, {'width' : 0.5}] for wt, k in zip(win_types, kwds): vals = np.random.randn(10) xp = cmov_window(vals, 5, (wt,) + tuple(k.values())) rs = mom.rolling_window(Series(vals), 5, wt, center=True, **k) assert_series_equal(Series(xp), rs)