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):
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_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(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(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):
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)
