def test_column_of_ints_and_floats():
dataset = [
['A', 'B'],
[1, 3.3],
[2.2, 4],
[None, None],
]
acc = autom8.Accumulator()
matrix = autom8.create_matrix(_add_labels(dataset), receiver=acc)
ctx = autom8.create_context(matrix, receiver=acc)
autom8.clean_dataset(ctx)
assert len(ctx.steps) == 4
assert len(acc.warnings) == 2
assert ctx.matrix.tolist() == [
[1.0, True, 3.3, True],
[2.2, True, 4.0, True],
[0.0, False, 0.0, False],
]
vectors = [['A', 'B'], [None, 10], [20.0, None], [30, 40]]
matrix = autom8.create_matrix(vectors, receiver=acc)
out = PlaybackContext(matrix, receiver=acc)
playback(ctx.steps, out)
assert out.matrix.tolist() == [
[0.0, False, 10.0, True],
[20.0, True, 0.0, False],
[30.0, True, 40.0, True],
]
assert out.matrix.columns[0].dtype == float
assert out.matrix.columns[2].dtype == float
def test_columns_with_numbers_as_strings():
dataset = [
['A', 'B', 'C'],
['1.1', '$4', 7],
['2.2', '$5', 8],
['3.3', '6%', 9],
]
acc = autom8.Accumulator()
matrix = autom8.create_matrix(_add_labels(dataset), receiver=acc)
ctx = autom8.create_context(matrix, receiver=acc)
autom8.clean_dataset(ctx)
assert len(acc.warnings) == 0
assert len(ctx.steps) == 2
assert ctx.matrix.tolist() == [[1.1, 4, 7], [2.2, 5, 8], [3.3, 6, 9]]
vectors = [['A', 'B', 'C'], [1, '2%', 'foo'], ['3', 4.0, 'bar']]
matrix = autom8.create_matrix(vectors, receiver=acc)
out = PlaybackContext(matrix, receiver=acc)
playback(ctx.steps, out)
assert out.matrix.tolist() == [[1, 2, 'foo'], [3, 4, 'bar']]
assert out.matrix.columns[0].dtype == int
assert out.matrix.columns[1].dtype == float
def _playback(fitted, roles, features, receiver=None):
if receiver is None:
receiver = autom8.Accumulator()
matrix = _create_matrix(features, roles)
ctx = PlaybackContext(matrix, receiver=receiver)
playback(fitted.steps, ctx)
assert fitted.matrix.formulas == ctx.matrix.formulas
return ctx.matrix.tolist()
def test_mixed_up_columns_with_strings_and_numbers():
dataset = [
['A', 'B'],
[True, 'foo'],
[1.1, 30],
[20, 4.4],
['bar', False],
['', 'baz'],
[50, 'fiz'],
[None, True],
]
acc = autom8.Accumulator()
matrix = autom8.create_matrix(_add_labels(dataset), receiver=acc)
ctx = autom8.create_context(matrix, receiver=acc)
autom8.clean_dataset(ctx)
assert len(ctx.steps) == 6
assert len(acc.warnings) == 0
assert ctx.matrix.tolist() == [
[1.0, '', 0.0, 'foo'],
[1.1, '', 30.0, ''],
[20.0, '', 4.4, ''],
[0.0, 'bar', 0.0, ''],
[0.0, '', 0.0, 'baz'],
[50.0, '', 0.0, 'fiz'],
[0.0, '', 1.0, ''],
]
assert ctx.matrix.formulas == [
['number', 'A'],
['string', 'A'],
['number', 'B'],
['string', 'B'],
]
vectors = [['A', 'B'], [False, 'buz'], ['zim', 10], [2, None]]
matrix = autom8.create_matrix(vectors, receiver=acc)
out = PlaybackContext(matrix, receiver=acc)
playback(ctx.steps, out)
assert out.matrix.tolist() == [
[0.0, '', 0.0, 'buz'],
[0.0, 'zim', 10.0, ''],
[2.0, '', 0.0, ''],
]
assert out.matrix.formulas == [
['number', 'A'],
['string', 'A'],
['number', 'B'],
['string', 'B'],
]
def test_columns_with_some_empty_strings():
dataset = [
['A', 'B', 'C'],
[True, 1.1, 20],
['', 2.2, 30],
[False, '', 40],
[False, 3.3, ''],
['', 4.4, ''],
]
acc = autom8.Accumulator()
matrix = autom8.create_matrix(_add_labels(dataset), receiver=acc)
ctx = autom8.create_context(matrix, receiver=acc)
autom8.clean_dataset(ctx)
assert len(ctx.steps) == 6
assert len(acc.warnings) == 3
assert ctx.matrix.tolist() == [
[True, True, 1.1, True, 20, True],
[False, False, 2.2, True, 30, True],
[False, True, 0.0, False, 40, True],
[False, True, 3.3, True, 0, False],
[False, False, 4.4, True, 0, False],
]
assert ctx.matrix.formulas == [
'A',
['is-defined', 'A'],
'B',
['is-defined', 'B'],
'C',
['is-defined', 'C'],
]
vectors = [['A', 'B', 'C'], ['', 5.5, ''], [True, '', 50]]
matrix = autom8.create_matrix(vectors, receiver=acc)
out = PlaybackContext(matrix, receiver=acc)
playback(ctx.steps, out)
assert out.matrix.tolist() == [
[False, False, 5.5, True, 0, False],
[True, True, 0.0, False, 50, True],
]
assert out.matrix.formulas == [
'A',
['is-defined', 'A'],
'B',
['is-defined', 'B'],
'C',
['is-defined', 'C'],
]
def test_primitives_with_object_dtype():
dataset = [
['A', 'B', 'C'],
[True, 1.1, 2],
[False, 3.1, 4],
[True, 5.1, 6],
]
acc = autom8.Accumulator()
matrix = autom8.create_matrix(_add_labels(dataset), receiver=acc)
for col in matrix.columns:
col.values = col.values.astype(object)
ctx = autom8.create_context(matrix, receiver=acc)
autom8.clean_dataset(ctx)
dtypes = [c.dtype for c in ctx.matrix.columns]
assert dtypes[0] == bool
assert dtypes[1] == float
assert dtypes[2] == int
vectors = [['A', 'B', 'C'], [1, 2, 3.0], [0, 4, 5.0], [1, False, 6.9]]
matrix = autom8.create_matrix(vectors, receiver=acc)
out = PlaybackContext(matrix, receiver=acc)
playback(ctx.steps, out)
assert out.matrix.tolist() == [[True, 2.0, 3], [False, 4.0, 5],
[True, 0.0, 6]]
dtypes = [c.dtype for c in out.matrix.columns]
assert dtypes[0] == bool
assert dtypes[1] == float
assert dtypes[2] == int
vectors = [['A', 'B', 'C'], ['1', '2', None], ['', None, ()]]
matrix = autom8.create_matrix(vectors, receiver=acc)
out = PlaybackContext(matrix, receiver=acc)
playback(ctx.steps, out)
# Just use repr to avoid having to fart around with nan.
assert repr(out.matrix.tolist()) == ("[[True, 2.0, 0], [False, nan, 0]]")
def test_column_with_all_none():
dataset = [
['A', 'B', 'C'],
[True, None, 2],
[False, None, 4],
[True, None, 6],
]
acc = autom8.Accumulator()
matrix = autom8.create_matrix(_add_labels(dataset), receiver=acc)
ctx = autom8.create_context(matrix, receiver=acc)
autom8.clean_dataset(ctx)
assert len(acc.warnings) == 1
assert 'Dropping column' in acc.warnings[0]
assert ctx.matrix.tolist() == [[True, 2], [False, 4], [True, 6]]
vectors = [['A', 'B', 'C'], [1, 2, 'foo'], [3, 4, 'bar']]
matrix = autom8.create_matrix(vectors, receiver=acc)
out = PlaybackContext(matrix, receiver=acc)
playback(ctx.steps, out)
assert out.matrix.tolist() == [[1, 'foo'], [3, 'bar']]
def test_column_of_all_strings_and_none_values():
dataset = [
['A', 'B'],
['1', 2],
['foo', 4],
[None, 0],
]
acc = autom8.Accumulator()
matrix = autom8.create_matrix(_add_labels(dataset), receiver=acc)
ctx = autom8.create_context(matrix, receiver=acc)
autom8.clean_dataset(ctx)
assert len(acc.warnings) == 0
assert len(ctx.steps) == 1
assert ctx.matrix.tolist() == [['1', 2], ['foo', 4], ['', 0]]
vectors = [['A', 'B'], [None, 'bar'], ['baz', None]]
matrix = autom8.create_matrix(vectors, receiver=acc)
out = PlaybackContext(matrix, receiver=acc)
playback(ctx.steps, out)
assert out.matrix.tolist() == [['', 'bar'], ['baz', None]]
def test_matrix_with_unexpected_value():
dataset = [
['A', 'B', 'C'],
[1, 2, ()],
[3, 4, {}],
[5, 6, object()],
]
acc = autom8.Accumulator()
matrix = autom8.create_matrix(_add_labels(dataset), receiver=acc)
ctx = autom8.create_context(matrix, receiver=acc)
autom8.clean_dataset(ctx)
assert len(acc.warnings) == 1
assert 'Dropping column' in acc.warnings[0]
assert 'contain booleans, numbers' in acc.warnings[0]
assert ctx.matrix.tolist() == [[1, 2], [3, 4], [5, 6]]
vectors = [['A', 'B', 'C'], [1, 2, 'foo'], [3, 4, 'bar']]
matrix = autom8.create_matrix(vectors, receiver=acc)
out = PlaybackContext(matrix, receiver=acc)
playback(ctx.steps, out)
assert out.matrix.tolist() == [[1, 2], [3, 4]]