Consistency define variables mu and scale as tuples.

Carsten · Carsten · commit 566b6c81e8d9 · 2019-03-14T09:23:08.000+01:00
diff --git a/examples/statistics/confidence_ellipse.py b/examples/statistics/confidence_ellipse.py
@@ -136,7 +136,7 @@ def get_correlated_dataset(n, dependency, mu, scale):
 }
 
 mu = 2, 4
-scale = np.array([3, 5]).T
+scale = 3, 5
 
 fig, axs = plt.subplots(1, 3, figsize=(9, 3))
 for ax, (title, dependency) in zip(axs, PARAMETERS.items()):
@@ -167,8 +167,8 @@ def get_correlated_dataset(n, dependency, mu, scale):
     [0.8, 0.75],
     [-0.2, 0.35]
 ])
-mu = np.array([0, 0]).T
-scale = np.array([8, 5]).T
+mu = 0, 0
+scale = 8, 5
 
 ax_nstd.axvline(c='grey', lw=1)
 ax_nstd.axhline(c='grey', lw=1)
@@ -202,8 +202,8 @@ def get_correlated_dataset(n, dependency, mu, scale):
     [-0.8, 0.5],
     [-0.2, 0.5]
 ])
-mu = np.array([2, -3]).T
-scale = np.array([6, 5]).T
+mu = 2, -3
+scale = 6, 5
 
 ax_kwargs.axvline(c='grey', lw=1)
 ax_kwargs.axhline(c='grey', lw=1)
