ENH: Introduced better LV parameters

src/gen_experiments/odes.py

@@ -1,3 +1,4 @@
+from functools import partial
 from typing import Callable
 
 import matplotlib.pyplot as plt
@@ -14,9 +15,9 @@
 from .utils import (
     FullSINDyTrialData,
     SINDyTrialData,
-    _make_model,
     coeff_metrics,
     integration_metrics,
+    make_model,
     simulate_test_data,
     unionize_coeff_matrices,
 )
@@ -59,7 +60,7 @@ def forcing(t, x):
 
 
 p_duff = [0.2, 0.05, 1]
-p_lotka = [1, 10]
+p_lotka = [5, 1]
 p_ross = [0.2, 0.2, 5.7]
 p_hopf = [-0.05, 1, 1]
 
@@ -73,7 +74,7 @@ def forcing(t, x):
         ],
     },
     "lv": {
-        "rhsfunc": ps.utils.odes.lotka,
+        "rhsfunc": partial(ps.utils.odes.lotka, p=p_lotka),
         "input_features": ["x", "y"],
         "coeff_true": [
             {"x": p_lotka[0], "x y": -p_lotka[1]},
@@ -181,7 +182,7 @@ def run(
         nonnegative=nonnegative,
         **sim_params,
     )
-    model = _make_model(input_features, dt, diff_params, feat_params, opt_params)
+    model = make_model(input_features, dt, diff_params, feat_params, opt_params)
 
     model.fit(x_train)
     coeff_true, coefficients, feature_names = unionize_coeff_matrices(model, coeff_true)

src/gen_experiments/pdes.py

@@ -7,9 +7,9 @@
 from .utils import (
     FullSINDyTrialData,
     SINDyTrialData,
-    _make_model,
     coeff_metrics,
     integration_metrics,
+    make_model,
     simulate_test_data,
     unionize_coeff_matrices,
 )
@@ -171,7 +171,7 @@ def run(
         dt=time_args[0],
         t_end=time_args[1],
     )
-    model = _make_model(input_features, dt, diff_params, feat_params, opt_params)
+    model = make_model(input_features, dt, diff_params, feat_params, opt_params)
 
     model.fit(x_train, t=t_train)
     coeff_true, coefficients, feature_names = unionize_coeff_matrices(model, coeff_true)