def test_combine():
columns = [1, 2]
index = ['a', 'b']
def make_data(multiplier):
return pd.DataFrame(np.ones((2, 2)) * multiplier,
columns=columns,
index=index
)
r1 = {'m1': make_data(2),
'm2': make_data(0)}
r2 = {'m1': make_data(1),
'm2': make_data(2)}
r = combine([r1, r2])
assert_equal(['m1', 'm2'], r.keys())
assert_almost_equal(
np.ones((2, 2)) * 1.5,
r['m1'].as_matrix()
)
assert_almost_equal(
np.ones((2, 2)) * 1.,
r['m2'].as_matrix()
)
def test_combine_with_nan():
columns = [1, 2]
index = ['a', 'b']
def make_data(multiplier):
return pd.DataFrame(np.ones((2, 2)) * multiplier,
columns=columns,
index=index
)
d = make_data(2)
d[2]['a'] = np.nan
r1 = {'m1': d,
'm2': make_data(0)}
r2 = {'m1': make_data(1),
'm2': make_data(2)}
r = combine([r1, r2])
assert_equal(['m1', 'm2'], r.keys())
assert_almost_equal(
np.asarray([[1.5, 1], [1.5, 1.5]]),
# np.ones((2, 2)) * 1.5,
r['m1'].as_matrix()
)
assert_almost_equal(
np.ones((2, 2)) * 1.,
r['m2'].as_matrix()
)
