def test_seriescolumn():
dm1 = DataMatrix(length=2)
dm1.col1 = SeriesColumn(2)
dm1.col1 = 1, 2
dm1.col_shared = SeriesColumn(2)
dm1.col_shared = 3, 4
dm2 = DataMatrix(length=2)
dm2.col2 = SeriesColumn(2)
dm2.col2 = 5, 6
dm2.col_shared = SeriesColumn(2)
dm2.col_shared = 7, 8
dm3 = dm1 << dm2
check_series(dm3.col1,
[[1, 1], [2, 2], [np.nan, np.nan], [np.nan, np.nan]])
check_series(dm3.col_shared, [[3, 3], [4, 4], [7, 7], [8, 8]])
check_series(dm3.col2,
[[np.nan, np.nan], [np.nan, np.nan], [5, 5], [6, 6]])
dm3.i = [4, 0, 2, 1]
dm4 = dm3.i <= 2
dm5 = (dm3.i <= 2) | (dm3.i >= 3)
check_integrity(dm1)
check_integrity(dm2)
check_integrity(dm3)
check_integrity(dm4)
check_integrity(dm5)
def check_concat(col_type, invalid):
dm1 = DataMatrix(length=2, default_col_type=col_type)
dm1.col1 = 1, 2
dm1.col_shared = 3, 4
dm2 = DataMatrix(length=2, default_col_type=col_type)
dm2.col2 = 5, 6
dm2.col_shared = 7, 8
dm3 = dm1 << dm2
check_col(dm3.col1, [1, 2, invalid, invalid])
check_col(dm3.col_shared, [3, 4, 7, 8])
check_col(dm3.col2, [invalid, invalid, 5, 6])
def check_concat(col_type, invalid): dm1 = DataMatrix(length=2, default_col_type=col_type) dm1.col1 = 1, 2 dm1.col_shared = 3, 4 dm2 = DataMatrix(length=2, default_col_type=col_type) dm2.col2 = 5, 6 dm2.col_shared = 7, 8 dm3 = dm1 << dm2 check_col(dm3.col1, [1,2,invalid,invalid]) check_col(dm3.col_shared, [3,4,7,8]) check_col(dm3.col2, [invalid,invalid,5,6])
def test_seriescolumn(): dm1 = DataMatrix(length=2) dm1.col1 = SeriesColumn(2) dm1.col1 = 1, 2 dm1.col_shared = SeriesColumn(2) dm1.col_shared = 3, 4 dm2 = DataMatrix(length=2) dm2.col2 = SeriesColumn(2) dm2.col2 = 5, 6 dm2.col_shared = SeriesColumn(2) dm2.col_shared = 7, 8 dm3 = dm1 << dm2 check_series(dm3.col1, [[1,1],[2,2],[0,0],[0,0]]) check_series(dm3.col_shared, [[3,3],[4,4],[7,7],[8,8]]) check_series(dm3.col2, [[0,0],[0,0],[5,5],[6,6]]) dm3.i = [4,0,2,1] dm4 = dm3.i <= 2 dm5 = (dm3.i <= 2) | (dm3.i >= 3) check_integrity(dm1) check_integrity(dm2) check_integrity(dm3) check_integrity(dm4) check_integrity(dm5)
