Code Duplication - SimonBlanke/Optimization-Metadata - Measure and Improve Code Quality continuously with Scrutinizer

Code Duplication Length = 15-17 lines in 3 locations

tests/test_convert_dataframe.py 3 locations


        assert_frame_equal(df1, df2, check_dtype=False)


def test_convert_dataframe3():
    array = np.reshape(np.arange(20), (10, 2))
    df1 = pd.DataFrame(array, columns=["x1", "x2"])

    search_space1 = {
        "x1": list(np.arange(20)),
        "x2": list(np.arange(20)),
    }
    search_space2 = {
        "x1": list(np.arange(20)),
        # "x2": list(np.arange(20)),
    }
    df2 = convert_dataframe(df1, search_space1, search_space2)

    df1.drop("x2", axis=1, inplace=True)

    assert_frame_equal(df1, df2, check_dtype=False)



    assert_frame_equal(df1, df2, check_dtype=False)


def test_convert_dataframe2():
    array = np.reshape(np.arange(20), (10, 2))
    df1 = pd.DataFrame(array, columns=["x1", "x2"])

    search_space1 = {
        "x1": list(np.arange(20)),
        "x2": list(np.arange(20)),
    }
    search_space2 = {
        "x1": list(np.arange(5)),
        "x2": list(np.arange(20)),
    }
    df2 = convert_dataframe(df1, search_space1, search_space2)

    with pytest.raises(Exception):
        assert_frame_equal(df1, df2, check_dtype=False)


def test_convert_dataframe3():

from optimization_metadata.memory_conv import convert_dataframe


def test_convert_dataframe1():
    array = np.reshape(np.arange(20), (10, 2))
    df1 = pd.DataFrame(array, columns=["x1", "x2"])

    search_space1 = {
        "x1": list(np.arange(20)),
        "x2": list(np.arange(20)),
    }
    search_space2 = {
        "x1": list(np.arange(20)),
        "x2": list(np.arange(20)),
    }
    df2 = convert_dataframe(df1, search_space1, search_space2)

    assert_frame_equal(df1, df2, check_dtype=False)


def test_convert_dataframe2():

		@@ 48-64 (lines=17) @@
45		assert_frame_equal(df1, df2, check_dtype=False)
46
47
48		def test_convert_dataframe3():
49		array = np.reshape(np.arange(20), (10, 2))
50		df1 = pd.DataFrame(array, columns=["x1", "x2"])
51
52		search_space1 = {
53		"x1": list(np.arange(20)),
54		"x2": list(np.arange(20)),
55		}
56		search_space2 = {
57		"x1": list(np.arange(20)),
58		# "x2": list(np.arange(20)),
59		}
60		df2 = convert_dataframe(df1, search_space1, search_space2)
61
62		df1.drop("x2", axis=1, inplace=True)
63
64		assert_frame_equal(df1, df2, check_dtype=False)
65
66
		@@ 30-45 (lines=16) @@
27		assert_frame_equal(df1, df2, check_dtype=False)
28
29
30		def test_convert_dataframe2():
31		array = np.reshape(np.arange(20), (10, 2))
32		df1 = pd.DataFrame(array, columns=["x1", "x2"])
33
34		search_space1 = {
35		"x1": list(np.arange(20)),
36		"x2": list(np.arange(20)),
37		}
38		search_space2 = {
39		"x1": list(np.arange(5)),
40		"x2": list(np.arange(20)),
41		}
42		df2 = convert_dataframe(df1, search_space1, search_space2)
43
44		with pytest.raises(Exception):
45		assert_frame_equal(df1, df2, check_dtype=False)
46
47
48		def test_convert_dataframe3():
		@@ 13-27 (lines=15) @@
10		from optimization_metadata.memory_conv import convert_dataframe
11
12
13		def test_convert_dataframe1():
14		array = np.reshape(np.arange(20), (10, 2))
15		df1 = pd.DataFrame(array, columns=["x1", "x2"])
16
17		search_space1 = {
18		"x1": list(np.arange(20)),
19		"x2": list(np.arange(20)),
20		}
21		search_space2 = {
22		"x1": list(np.arange(20)),
23		"x2": list(np.arange(20)),
24		}
25		df2 = convert_dataframe(df1, search_space1, search_space2)
26
27		assert_frame_equal(df1, df2, check_dtype=False)
28
29
30		def test_convert_dataframe2():

SimonBlanke / Optimization-Metadata

Code Duplication Length = 15-17 lines in 3 locations

tests/test_convert_dataframe.py 3 locations