FIX: resolves the zero-sized array error and corrects pde data array …

…shapes
Jacob-Stevens-Haas · Oct 5, 2024 · 62de4e3 · 62de4e3
1 parent e3e378a
commit 62de4e3
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Showing 2 changed files with 10 additions and 10 deletions.
diff --git a/src/gen_experiments/data.py b/src/gen_experiments/data.py
@@ -295,6 +295,7 @@ def _gen_pde_data(
             x_train, (t, int(np.cbrt(x)), int(np.cbrt(x)), int(np.cbrt(x)), 1)
         )
     x_test = x_train
+    signal = x_test
     x_test = np.moveaxis(x_test, -1, 0)
     x_dot_test = np.array(
         [
@@ -303,23 +304,23 @@ def _gen_pde_data(
         ]
     )
     if dimension == 1:
-        x_dot_test = [np.moveaxis(x_dot_test, [0, 1], [-1, -2])]
+        x_dot_test = np.moveaxis(x_dot_test, [0, 1], [-1, -2])
         pass
     elif dimension == 2:
         x_dot_test = np.reshape(x_dot_test, (t, int(np.sqrt(x)), int(np.sqrt(x)), 1))
-        x_dot_test = [np.moveaxis(x_dot_test, 0, -2)]
+        x_dot_test = np.moveaxis(x_dot_test, 0, -2)
     elif dimension == 3:
         x_dot_test = np.reshape(
             x_dot_test, (t, int(np.cbrt(x)), int(np.cbrt(x)), int(np.cbrt(x)), 1)
         )
-        x_dot_test = [np.moveaxis(x_dot_test, 0, -2)]
+        x_dot_test = np.moveaxis(x_dot_test, 0, -2)
     x_train_true = np.copy(x_train)
     if noise_rel is not None:
-        noise_abs = np.sqrt(_max_amplitude(x_test, axis=-2) * noise_rel)
+        noise_abs = np.sqrt(_max_amplitude(signal, axis=-2) * noise_rel)
     x_train = x_train + cast(float, noise_abs) * rng.standard_normal(x_train.shape)
-    x_train = [np.moveaxis(x_train, 0, -2)]
+    x_train = np.moveaxis(x_train, 0, -2)
     x_train_true = np.moveaxis(x_train_true, 0, -2)
-    x_test = [np.moveaxis(x_test, [0, 1], [-1, -2])]
+    x_test = np.moveaxis(x_test, [0, 1], [-1, -2])
     return dt, t_train, x_train, x_test, x_dot_test, x_train_true
 
 

diff --git a/src/gen_experiments/pdes.py b/src/gen_experiments/pdes.py
@@ -156,7 +156,6 @@ def run(
     model.fit(x_train, t=t_train)
     coeff_true, coefficients, feature_names = unionize_coeff_matrices(model, coeff_true)
 
-    sim_ind = -1
     trial_data: SINDyTrialData = {
         "dt": dt,
         "coeff_true": coeff_true,
@@ -165,10 +164,10 @@ def run(
         "input_features": input_features,
         "t_train": t_train,
         "x_true": x_train_true,
-        "x_train": x_train[sim_ind],
+        "x_train": x_train,
         "smooth_train": model.differentiation_method.smoothed_x_,
-        "x_test": x_test[sim_ind],
-        "x_dot_test": x_dot_test[sim_ind],
+        "x_test": x_test,
+        "x_dot_test": x_dot_test,
         "model": model,
     }
     if display: