Merge pull request #60 from azzeddinetiba/TEST_creating_tests

Adding tests

Author: azzeddinetiba

tests/helpers.py

@@ -0,0 +1,44 @@
+import numpy as np
+
+# ─────────────────────────────────────────────────────────────────────────────
+# helpers
+# ─────────────────────────────────────────────────────────────────────────────
+
+def _random_orthonormal(n, k, seed=0):
+    """Return an (n, k) matrix with orthonormal columns."""
+    rng = np.random.default_rng(seed)
+    A = rng.standard_normal((n, k))
+    Q, _ = np.linalg.qr(A)
+    return Q[:, :k]
+
+
+def _make_synthetic_data(n_state=30, n_ctrl=15, n_samples=40, n_params=3,
+                          seed=0):
+    """
+    Build synthetic state-space / control-input datasets for p parameter points.
+
+    Returns
+    -------
+    state_data       : list[ndarray], each (n_state, n_samples)
+    prev_state_data  : list[ndarray], each (n_state, n_samples)
+    ctrl_data        : list[ndarray], each (n_ctrl, n_samples)
+    params           : ndarray  (1, n_params)  – 1-d parameter space
+    """
+    rng = np.random.default_rng(seed)
+    params = np.linspace(0.5, 1.5, n_params)[None, :]   # shape (1, p)
+
+    state_data, prev_state_data, ctrl_data = [], [], []
+    for i in range(n_params):
+        mu = params[0, i]
+        # simple smooth synthetic trajectories that depend on mu
+        t = np.linspace(0, 2 * np.pi, n_samples)
+        x = np.linspace(0, 1, n_state)
+        tt, xx = np.meshgrid(t, x)
+        snap = mu * np.sin(xx * tt) + 0.1 * rng.standard_normal((n_state, n_samples))
+        state_data.append(snap)
+        prev_state_data.append(np.roll(snap, 1, axis=1))   # shift by one time step
+
+        ctrl = mu * np.cos(np.linspace(0, np.pi, n_ctrl)[:, None] * t[None, :])
+        ctrl_data.append(ctrl)
+
+    return state_data, prev_state_data, ctrl_data, params