def test_regplot_xlim(self):
f, ax = plt.subplots()
x, y1, y2 = np.random.randn(3, 50)
lm.regplot(x=x, y=y1, truncate=False)
lm.regplot(x=x, y=y2, truncate=False)
line1, line2 = ax.lines
assert np.array_equal(line1.get_xdata(), line2.get_xdata())
def test_regplot_basic(self):
f, ax = plt.subplots()
lm.regplot(x="x", y="y", data=self.df)
assert len(ax.lines) == 1
assert len(ax.collections) == 2
x, y = ax.collections[0].get_offsets().T
npt.assert_array_equal(x, self.df.x)
npt.assert_array_equal(y, self.df.y)
def test_regplot_scatter_kws_alpha(self):
f, ax = plt.subplots()
color = np.array([[0.3, 0.8, 0.5, 0.5]])
ax = lm.regplot(x="x",
y="y",
data=self.df,
scatter_kws={'color': color})
assert ax.collections[0]._alpha is None
assert ax.collections[0]._facecolors[0, 3] == 0.5
f, ax = plt.subplots()
color = np.array([[0.3, 0.8, 0.5]])
ax = lm.regplot(x="x",
y="y",
data=self.df,
scatter_kws={'color': color})
assert ax.collections[0]._alpha == 0.8
f, ax = plt.subplots()
color = np.array([[0.3, 0.8, 0.5]])
ax = lm.regplot(x="x",
y="y",
data=self.df,
scatter_kws={
'color': color,
'alpha': 0.4
})
assert ax.collections[0]._alpha == 0.4
f, ax = plt.subplots()
color = 'r'
ax = lm.regplot(x="x",
y="y",
data=self.df,
scatter_kws={'color': color})
assert ax.collections[0]._alpha == 0.8
f, ax = plt.subplots()
alpha = .3
ax = lm.regplot(x="x",
y="y",
data=self.df,
x_bins=5,
fit_reg=False,
scatter_kws={"alpha": alpha})
for line in ax.lines:
assert line.get_alpha() == alpha
def test_regplot_selective(self):
f, ax = plt.subplots()
ax = lm.regplot(x="x", y="y", data=self.df, scatter=False, ax=ax)
assert len(ax.lines) == 1
assert len(ax.collections) == 1
ax.clear()
f, ax = plt.subplots()
ax = lm.regplot(x="x", y="y", data=self.df, fit_reg=False)
assert len(ax.lines) == 0
assert len(ax.collections) == 1
ax.clear()
f, ax = plt.subplots()
ax = lm.regplot(x="x", y="y", data=self.df, ci=None)
assert len(ax.lines) == 1
assert len(ax.collections) == 1
ax.clear()
def test_regplot_scatter_kws_alpha(self):
f, ax = plt.subplots()
color = np.array([[0.3, 0.8, 0.5, 0.5]])
ax = lm.regplot(x="x",
y="y",
data=self.df,
scatter_kws={'color': color})
assert ax.collections[0]._alpha is None
assert ax.collections[0]._facecolors[0, 3] == 0.5
f, ax = plt.subplots()
color = np.array([[0.3, 0.8, 0.5]])
ax = lm.regplot(x="x",
y="y",
data=self.df,
scatter_kws={'color': color})
assert ax.collections[0]._alpha == 0.8
f, ax = plt.subplots()
color = np.array([[0.3, 0.8, 0.5]])
ax = lm.regplot(x="x",
y="y",
data=self.df,
scatter_kws={
'color': color,
'alpha': 0.4
})
assert ax.collections[0]._alpha == 0.4
f, ax = plt.subplots()
color = 'r'
ax = lm.regplot(x="x",
y="y",
data=self.df,
scatter_kws={'color': color})
assert ax.collections[0]._alpha == 0.8
def test_three_point_colors(self):
x, y = np.random.randn(2, 3)
ax = lm.regplot(x=x, y=y, color=(1, 0, 0))
color = ax.collections[0].get_facecolors()
npt.assert_almost_equal(color[0, :3], (1, 0, 0))
def test_regplot_binned(self):
ax = lm.regplot(x="x", y="y", data=self.df, x_bins=5)
assert len(ax.lines) == 6
assert len(ax.collections) == 2