def test_figure(self):
report = Report(
self.data,
self.cols,
model_name=self.model_name,
dataset_name=self.dataset_name,
)
# Original unsorted data should cause an error
self.assertRaises(ValueError, report.figure)
# Sort should resolve that error
report.sort()
try:
report.figure()
except ValueError:
self.fail("report.figure() raised ValueError unexpectedly!")
def test_display(self):
report = Report(
self.data,
self.cols,
model_name=self.model_name,
dataset_name=self.dataset_name,
)
report.sort()
figure = report.figure()
figure.show()
report.sort(category_order={"Cat C": 1, "Cat A": 2, "Cat B": 3})
report.rename(slice_map={"Slice A": "A"}, category_map={"Cat B": "B"})
report.filter(slices=["A", "Slice B", "Slice C"])
report.set_range("f1", 0.05, 0.45)
report.update_config(font_size_heading=16)
figure = report.figure(show_title=True)
figure.show()
def test_display_2(self):
data = pd.DataFrame([
[
"Eval",
"snli1",
0.8799999952316284,
0.876409113407135,
[0.368, 0.304, 0.328],
[0.344, 0.288, 0.368],
125,
],
[
"Eval",
"snli2",
0.8799999952316284,
0.876409113407135,
[0.368, 0.304, 0.328],
[0.344, 0.288, 0.368],
125,
],
[
"Eval",
"snli3",
0.8799999952316284,
0.876409113407135,
[0.368, 0.304, 0.328],
[0.344, 0.288, 0.368],
125,
],
])
cols = [
ScoreColumn("F1", min_val=0, max_val=1, is_0_to_1=True),
ScoreColumn("Accuracy", min_val=0, max_val=1, is_0_to_1=True),
ClassDistributionColumn("Class Dist", ["e", "n", "c"]),
ClassDistributionColumn("Pred Dist", ["e", "n", "c"]),
NumericColumn("Size"),
]
report = Report(data, cols)
report.figure().show()