TST: Provide enough test data for finite_difference

Author: Jacob-Stevens-Haas

examples/tutorial_2/mock_data.py

@@ -1,3 +1,5 @@
+from copy import deepcopy
+
 import numpy as np
 from scipy.integrate import solve_ivp
 
@@ -9,9 +11,8 @@ def get_models():
     rhs = ps.utils.lorenz
     x = solve_ivp(rhs, (t[0], t[-1]), (10, 10, 10), t_eval=t).y.T
     good_model = ps.SINDy().fit(x, t=t, feature_names=["x", "y", "z"])
-    skip = 4
-    ok_model = ps.SINDy().fit(x[::skip], t=t[::skip], feature_names=["x", "y", "z"])
-    bad_model = ps.SINDy().fit(
-        x[:: skip**2], t=t[:: skip**2], feature_names=["x", "y", "z"]
-    )
+    ok_model = deepcopy(good_model)
+    ok_model.optimizer.coef_[1, 1] = 4
+    bad_model = deepcopy(good_model)
+    bad_model.optimizer.coef_[1, 1] = 10
     return t, x, good_model, ok_model, bad_model