def test_random_visualizer_increased_tolerance(self):
"""
Test that not close visualizers pass with increased tolerance
"""
viz = RandomVisualizer(random_state=224).fit()
viz.finalize()
self.assert_images_similar(viz, tol=30)
def test_random_visualizer_increased_tolerance(self):
"""
Test that not close visualizers pass with increased tolerance
"""
viz = RandomVisualizer(random_state=224).fit()
viz.poof()
self.assert_images_similar(viz, tol=30)
def test_random_visualizer(self):
"""
Test that a random visualization is correctly compared to a baseline
"""
viz = RandomVisualizer(random_state=111).fit()
viz.poof()
compare = self.assert_images_similar(viz, tol=1.0)
assert_path_exists(compare.actual_image_path)
assert_path_exists(compare.baseline_image_path)
def test_random_visualizer_not_close(self):
"""
Test that not close visualizers raise an assertion error.
"""
viz = RandomVisualizer(random_state=224).fit()
viz.poof()
with pytest.raises(ImageComparisonFailure, match="images not close"):
self.assert_images_similar(viz)
# Assert there is a diff
assert_path_exists(
ACTUAL_IMAGES, "test_meta", "test_random_visualizer_not_close-failed-diff.png"
)
def test_draw_with_cols(self):
"""
Draw 2 visualizers in their own column
"""
visualizers = [
RandomVisualizer(random_state=633),
RandomVisualizer(random_state=336),
]
X, y = make_classification(random_state=187)
grid = VisualizerGrid(visualizers, ncols=2)
grid.fit(X, y)
grid.poof()
self.assert_images_similar(grid)
def test_draw_with_cols(self):
"""
Draw 2 visualizers in their own column
"""
visualizers = [
RandomVisualizer(random_state=633),
RandomVisualizer(random_state=336),
]
X, y = make_classification(random_state=187)
grid = VisualizerGrid(visualizers, ncols=2)
grid.fit(X, y)
# show is required here (do not replace with finalize)!
assert grid.show() is not None
self.assert_images_similar(grid, tol=1.0)
def test_draw_with_rows(self):
"""
Draw 2 visualizers in their own row
"""
visualizers = [
RandomVisualizer(random_state=63),
RandomVisualizer(random_state=36),
]
X, y = make_classification(random_state=87)
grid = VisualizerGrid(visualizers, nrows=2)
grid.fit(X, y)
# poof is required here (do not replace with finalize)!
assert grid.poof() is not None
self.assert_images_similar(grid)
def test_missing_baseline_image(self):
"""
Test that a missing baseline image raises an exception
"""
viz = RandomVisualizer(random_state=14).fit()
viz.finalize()
# Assert the baseline image does not exist
assert_path_not_exists(BASELINE_IMAGES, "test_meta",
"test_missing_baseline_image.png")
with pytest.raises(ImageComparisonFailure,
match="image does not exist"):
self.assert_images_similar(viz)
# Assert the actual image was created (to copy to baseline)
assert_path_exists(ACTUAL_IMAGES, "test_meta",
"test_missing_baseline_image.png")
def test_random_visualizer_not_close(self):
"""
Test that not close visualizers raise an assertion error.
"""
# Baseline image random_state=224
# NOTE: if regenerating baseline images, skip this one or change random state!
viz = RandomVisualizer(random_state=225).fit()
viz.finalize()
with pytest.raises(ImageComparisonFailure, match="images not close"):
# If failing, perhaps baseline images were regenerated? See note above.
self.assert_images_similar(viz)
# Assert there is a diff
assert_path_exists(
ACTUAL_IMAGES,
"test_meta",
"test_random_visualizer_not_close-failed-diff.png",
)
def test_missing_baseline_image(self):
"""
Test that a missing basline image raises an exception
"""
viz = RandomVisualizer(random_state=14).fit()
viz.poof()
# Assert the baseline image does not exist
assert_path_not_exists(
BASELINE_IMAGES, "test_meta", "test_missing_baseline_image.png"
)
with pytest.raises(ImageComparisonFailure, match="image does not exist"):
self.assert_images_similar(viz)
# Assert the actual image was created (to copy to baseline)
assert_path_exists(
ACTUAL_IMAGES, "test_meta", "test_missing_baseline_image.png"
)
def test_draw_visualizer_grid(self):
"""
Draw a 4 visualizers grid with default options
"""
visualizers = [
RandomVisualizer(random_state=(1 + x)**2) for x in range(4)
]
X, y = make_classification(random_state=78)
grid = VisualizerGrid(visualizers)
grid.fit(X, y)
grid.poof()
self.assert_images_similar(grid)
def test_draw_visualizer_grid(self):
"""
Draw a 4 visualizers grid with default options
"""
visualizers = [
RandomVisualizer(random_state=(1 + x)**2) for x in range(4)
]
X, y = make_classification(random_state=78)
grid = VisualizerGrid(visualizers)
grid.fit(X, y)
# show is required here (do not replace with finalize)!
assert grid.show() is not None
self.assert_images_similar(grid, tol=1.0)
