Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Remove the possibility in DFtoVW to provide constant values #2601

Merged
merged 7 commits into from
Oct 14, 2020
Merged

Remove the possibility in DFtoVW to provide constant values #2601

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
7 commits
Select commit Hold shift + click to select a range
9520605
remove unnecessary code linked with *_from_df, remove some tests
etiennekintzler Oct 9, 2020
94bc7d3
clean docstring
etiennekintzler Oct 9, 2020
21aa4bf
In Feature, change arg name to rename_feature
etiennekintzler Oct 13, 2020
dae9d6e
Update test file to use arg rename_feature
etiennekintzler Oct 13, 2020
20f6a3f
forget to change arg's name in the constructor
etiennekintzler Oct 13, 2020
d436457
In *Label class, change name to label
etiennekintzler Oct 13, 2020
064e35a
Merge branch 'master' into DFtoVW_value_from_df_only
lalo Oct 14, 2020
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Jump to
Jump to file
Failed to load files.
Diff view
Diff view
61 changes: 13 additions & 48 deletions python/tests/test_pyvw.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -396,36 +396,25 @@ def test_feature_column_renaming_and_tag():
conv = DFtoVW(
label=SimpleLabel("y"),
tag="idx",
features=Feature(name="col_x", value="x"),
features=Feature(value="x", rename_feature="col_x"),
df=df,
)
first_line = conv.convert_df()[0]
assert first_line == "1 id_1| col_x:2"


def test_constant_feature_value_with_empty_name():
def test_feature_value_with_empty_name():
df = pd.DataFrame({"idx": ["id_1"], "y": [1], "x": [2]})
conv = DFtoVW(
label=SimpleLabel("y"),
tag="idx",
features=Feature(name="", value=2, value_from_df=False),
features=Feature(value="x", rename_feature=""),
df=df,
)
first_line = conv.convert_df()[0]
assert first_line == "1 id_1| :2"


def test_variable_feature_name():
df = pd.DataFrame({"y": [1], "x": [2], "a": ["col_x"]})
conv = DFtoVW(
label=SimpleLabel("y"),
features=Feature(name="a", value="x", name_from_df=True),
df=df,
)
first_line = conv.convert_df()[0]
assert first_line == "1 | col_x:2"


def test_multiple_lines():
df = pd.DataFrame({"y": [1, -1], "x": [1, 2]})
conv = DFtoVW(label=SimpleLabel("y"), features=Feature(value="x"), df=df,)
Expand Down Expand Up @@ -457,7 +446,7 @@ def test_without_target_multiple_features():
def test_multiclasslabel():
df = pd.DataFrame({"a": [1], "b": [0.5], "c": ["x"]})
conv = DFtoVW(
df=df, label=MulticlassLabel(name="a", weight="b"), features=Feature("c")
df=df, label=MulticlassLabel(label="a", weight="b"), features=Feature("c")
)
first_line = conv.convert_df()[0]
assert first_line == "1 0.5 | x"
Expand Down Expand Up @@ -498,8 +487,8 @@ def test_absent_col_error():
def test_non_numerical_simplelabel_error():
df = pd.DataFrame({"y": ["a"], "x": ["featX"]})
with pytest.raises(TypeError) as type_error:
DFtoVW(df=df, label=SimpleLabel(name="y"), features=Feature("x"))
expected = "In argument 'name' of 'SimpleLabel', column 'y' should be either of the following type(s): 'int', 'float', 'int64'."
DFtoVW(df=df, label=SimpleLabel(label="y"), features=Feature("x"))
expected = "In argument 'label' of 'SimpleLabel', column 'y' should be either of the following type(s): 'int', 'float', 'int64'."
assert expected == str(type_error.value)


Expand All @@ -511,15 +500,15 @@ def test_wrong_feature_type_error():
assert expected == str(type_error.value)


def test_multiclasslabel_non_positive_name_error():
def test_multiclasslabel_non_positive_label_error():
df = pd.DataFrame({"a": [0], "b": [0.5], "c": ["x"]})
with pytest.raises(ValueError) as value_error:
DFtoVW(
df=df,
label=MulticlassLabel(name="a", weight="b"),
label=MulticlassLabel(label="a", weight="b"),
features=Feature("c"),
)
expected = "In argument 'name' of 'MulticlassLabel', column 'a' must be >= 1."
expected = "In argument 'label' of 'MulticlassLabel', column 'a' must be >= 1."
assert expected == str(value_error.value)


Expand All @@ -528,44 +517,20 @@ def test_multiclasslabel_negative_weight_error():
with pytest.raises(ValueError) as value_error:
DFtoVW(
df=df,
label=MulticlassLabel(name="y", weight="w"),
label=MulticlassLabel(label="y", weight="w"),
features=Feature("x"),
)
expected = "In argument 'weight' of 'MulticlassLabel', column 'w' must be >= 0."
assert expected == str(value_error.value)


def test_multiclasslabel_non_positive_constant_label_error():
df = pd.DataFrame({"a": [0], "b": [0.5], "c": ["x"]})
with pytest.raises(ValueError) as value_error:
DFtoVW(
df=df,
label=MulticlassLabel(name=-1, weight="b", name_from_df=False),
features=Feature("c"),
)
expected = "In 'MulticlassLabel', argument 'name' must be >= 1."
assert expected == str(value_error.value)


def test_multiclasslabel_constant_label_type_error():
df = pd.DataFrame({"a": [0], "b": [0.5], "c": ["x"]})
with pytest.raises(TypeError) as type_error:
DFtoVW(
df=df,
label=MulticlassLabel(name="a", weight="b", weight_from_df=False),
features=Feature("c"),
)
expected = "In 'MulticlassLabel', when weight_from_df=False, argument 'weight' should be either of the following type(s): 'int', 'float'."
assert expected == str(type_error.value)


def test_multilabel_non_positive_name_error():
def test_multilabel_non_positive_label_error():
df = pd.DataFrame({"y": [0], "b": [1]})
with pytest.raises(ValueError) as value_error:
DFtoVW(
df=df,
label=MultiLabel(name="y"),
label=MultiLabel(label="y"),
features=Feature("b"),
)
expected = "In argument 'name' of 'MultiLabel', column 'y' must be >= 1."
expected = "In argument 'label' of 'MultiLabel', column 'y' must be >= 1."
assert expected == str(value_error.value)