def test_wgtdMeans_number_of_rows():
"""
Test the number of returned rows
"""
dfi = pd.DataFrame()
dfi["JD"] = np.random.uniform(0, 10, 100)
dfi["mnvel"] = np.random.normal(loc=0, scale=5, size=100)
dfi["errvel"] = np.random.normal(loc=1., scale=0.5, size=100)
dfo = wm.wgtdMeans(dfi, timebin=1.0)
assert len(dfo) >= 9
def test_returnNan_option():
"""
Make sure the returnNan removes NaN elements.
"""
dfi = pd.DataFrame()
dfi["JD"] = np.concatenate((np.random.uniform(0, 10, 50),
np.random.uniform(40, 50, 50)))
dfi["mnvel"] = np.random.normal(loc=0, scale=5, size=100)
dfi["errvel"] = np.random.normal(loc=1., scale=0.5, size=100)
dfo = wm.wgtdMeans(dfi, timebin=1.0, returnNan=False)
assert len(dfo) == len(dfo[np.isfinite(dfo["mnvel"])])
def test_big_gaps_main_routine():
"""
Test to make sure the code handles big gaps well
"""
dfi = pd.DataFrame()
dfi["JD"] = np.concatenate((np.random.uniform(0, 10, 50),
np.random.uniform(40, 50, 50)))
dfi["mnvel"] = np.random.normal(loc=0, scale=5, size=100)
dfi["errvel"] = np.random.normal(loc=1., scale=0.5, size=100)
dfo = wm.wgtdMeans(dfi, timebin=1.0)
assert len(dfo) >= 9
