def test_w_nans(self):
"Test the moving functions on series w/ NaNs"
#
data = np.random.rand(20)
control = mf.mov_average(data, 3)
# Test that we get the right result
a = ma.array(data, mask=False)
assert_almost_equal(control, mf.mov_average(a, 3))
# Test with a masked element
a.data[10] = 0
a.mask[10] = True
assert_almost_equal(control, mf.mov_average(a, 3))
# Test w/ a masked element and an underlying nan
a[10] = np.nan
assert_almost_equal(control, mf.mov_average(a, 3))
def test_w_nans(self):
"Test the moving functions on series w/ NaNs"
#
data = np.random.rand(20)
control = mf.mov_average(data, 3)
# Test that we get the right result
a = ma.array(data, mask=False)
assert_almost_equal(control, mf.mov_average(a, 3))
# Test with a masked element
a.data[10] = 0
a.mask[10] = True
assert_almost_equal(control, mf.mov_average(a, 3))
# Test w/ a masked element and an underlying nan
a[10] = np.nan
assert_almost_equal(control, mf.mov_average(a, 3))
def mave(self,tsl,span,*args,**kw):
_ts = tsl._data
span = int(span)
_ts = tsm.mov_average(_ts,span)
tsl._data = _ts
return tsl
