def test__process(self):
df = pd.DataFrame()
df["x"] = [1, 1, 2, 2]
df["y"] = [1, 2, 1, 1]
df["z"] = [1, 2, 3, 4]
scatter = BubbleScatter(df,
"x",
"y",
z="z",
z_aggregation="sum",
max_bubble_size=1)
scatter._process()
true_x_ticks = [0, 1]
true_y_ticks = [0, 1]
true_x_labels = [1, 2]
true_y_labels = [1, 2]
true_bubble_sizes = [0.25, 0.25, 0.5]
true_bubble_colors = np.array([[1], [2], [7]])
true_x_values = np.array([[0.0], [0.0], [1.0]])
true_y_values = np.array([[0.0], [1.0], [0.0]])
self.assertListEqual(scatter.x_ticks, true_x_ticks)
self.assertListEqual(scatter.y_ticks, true_y_ticks)
self.assertListEqual(scatter.x_labels, true_x_labels)
self.assertListEqual(scatter.y_labels, true_y_labels)
self.assertListEqual(scatter.bubble_sizes, true_bubble_sizes)
self.assertTrue(all(scatter.bubble_colors == true_bubble_colors))
self.assertTrue(all(scatter.x_values == true_x_values))
self.assertTrue(all(scatter.y_values == true_y_values))
def test__get_encoder_categories_with_bins_no_categories(self):
df = pd.DataFrame(columns=["x", "y"])
scatter = BubbleScatter(df, "x", "y", xbins=3, ybins=3)
x_categories = scatter._get_encoder_categories("x")
y_categories = scatter._get_encoder_categories("y")
self.assertEqual(x_categories, "auto")
self.assertEqual(y_categories, "auto")
def test__calc_labels_y_with_categories(self):
df = pd.DataFrame(columns=["x", "y"])
scatter = BubbleScatter(df, "x", "y", y_categories=["a", "b"])
result = scatter._calc_labels("y", ["a", "b", "c"])
true_result = ["a", "b"]
self.assertListEqual(result, true_result)
def test__transform_with_int_ybins(self):
df = pd.DataFrame()
df["x"] = [0, 1, 2, 3, 4]
df["y"] = [0, 1, 2, 3, 4]
scatter = BubbleScatter(df, "x", "y", ybins=2)
result = scatter._transform("y")
true_result = pd.Series([1.0, 1.0, 1.0, 3.0, 3.0], name="y")
self.assertTrue(result.equals(true_result))
def test__transform_no_ybins(self):
df = pd.DataFrame()
df["x"] = [1, 2, 3]
df["y"] = [1, 2, 3]
scatter = BubbleScatter(df, "x", "y")
result = scatter._transform("y")
true_result = df["x"]
self.assertTrue(result.equals(true_result))
def test_plot_show_true(self):
df = pd.DataFrame()
df["x"] = [1, 1, 2, 2]
df["y"] = [1, 2, 1, 1]
scatter = BubbleScatter(df, "x", "y")
result = scatter.plot(show=True)
self.assertIsNone(result)
def test_plot_show_false(self):
df = pd.DataFrame()
df["x"] = [1, 1, 2, 2]
df["y"] = [1, 2, 1, 1]
scatter = BubbleScatter(df, "x", "y")
result = scatter.plot(show=False)
self.assertIsInstance(result, plt.Figure)
def test__get_encoder_categories_no_bins_with_categories(self):
df = pd.DataFrame(columns=["x", "y"])
scatter = BubbleScatter(df,
"x",
"y",
x_categories=["a", "b", "c"],
y_categories=["q", "w", "e"])
x_categories = scatter._get_encoder_categories("x")
y_categories = scatter._get_encoder_categories("y")
self.assertListEqual(x_categories, ["a", "b", "c"])
self.assertListEqual(y_categories, ["q", "w", "e"])
def test__calc_bubble_colors(self):
df = pd.DataFrame()
df["x"] = [1, 1, 2, 2]
df["y"] = [1, 2, 1, 1]
df["z"] = [1, 2, 3, 4]
scatter = BubbleScatter(df, "x", "y", z="z", z_aggregation="sum")
index = pd.MultiIndex(levels=[[1, 2], [1, 2]],
codes=[[1, 0, 0], [0, 1, 0]],
names=["x", "y"])
true_result = np.array([[7], [2], [1]])
result = scatter._calc_bubble_colors(df, index)
self.assertTrue(all(result == true_result))
def test__calc_xy_values(self):
index = pd.MultiIndex(levels=[[1, 2], [1, 2]],
codes=[[0, 0, 1], [0, 1, 0]],
names=['x', 'y'])
true_result = pd.DataFrame({"x": [1, 1, 2], "y": [1, 2, 1]})
result = BubbleScatter._calc_xy_values(index)
self.assertTrue(result.equals(true_result))
def test__calc_bubble_sizes_conditional(self):
"""Test bubble sizes for conditional distribution (x|y)."""
df = pd.DataFrame()
df["x"] = [1, 1, 2, 2]
df["y"] = [1, 2, 1, 1]
scatter = BubbleScatter(df,
"x",
"y",
joint_distribution=False,
max_bubble_size=1)
index = pd.MultiIndex(levels=[[1, 2], [1, 2]],
codes=[[0, 0, 1], [0, 1, 0]],
names=["x", "y"])
true_result = pd.Series([0.5, 0.5, 1.0], index=index)
result = scatter._calc_bubble_sizes(df)
self.assertTrue(result.equals(true_result))
def test__calc_ticks(self):
result = BubbleScatter._calc_ticks(["a", "b", "c"])
true_result = [0, 1, 2]
self.assertListEqual(result, true_result)