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)