test: uncertainty

Examples/Example3.ipynb

@@ -417,7 +417,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": ".venv",
    "language": "python",
    "name": "python3"
   },
@@ -431,7 +431,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.15"
+   "version": "3.12.4"
   }
  },
  "nbformat": 4,

docs/Example2 - Real dataset.rst

@@ -159,7 +159,7 @@ We can now plot some of the results:
 .. code:: python
 
     # plot frequecy-damping clusters for SSI
-    ssicov.plot_cluster(freqlim=(0,5))
+    ssicov.plot_freqvsdamp(freqlim=(0,5))
 
 
 .. figure:: /img/Ex2-Fig9.png

docs/Example3 - Multisetup PoSER.rst

@@ -55,18 +55,18 @@ remains the same as described in the example for the single setup.
 .. code:: python
 
    # Initialise the algorithms for setup 1
-   ssicov1 = SSIcov(name="SSIcov1", method="cov_mm", br=50, ordmax=80)
+   ssicov1 = SSIcov(name="SSIcov1", method="cov", br=50, ordmax=80)
    # Add algorithms to the class
    ss1.add_algorithms(ssicov1)
    ss1.run_all()
 
    # Initialise the algorithms for setup 2
-   ssicov2 = SSIcov(name="SSIcov2", method="cov_mm", br=50, ordmax=80)
+   ssicov2 = SSIcov(name="SSIcov2", method="cov", br=50, ordmax=80)
    ss2.add_algorithms(ssicov2)
    ss2.run_all()
 
    # Initialise the algorithms for setup 2
-   ssicov3 = SSIcov(name="SSIcov3", method="cov_mm", br=50, ordmax=80)
+   ssicov3 = SSIcov(name="SSIcov3", method="cov", br=50, ordmax=80)
    ss3.add_algorithms(ssicov3)
    ss3.run_all()
 

src/pyoma2/algorithms/plscf.py

@@ -377,7 +377,6 @@ def run(self) -> pLSCFResult:
         )
 
         # Apply HARD CRITERIA
-        # hc_conj = hc["conj"]
         hc_xi_max = hc["xi_max"]
         hc_mpc_lim = hc["mpc_lim"]
         hc_mpd_lim = hc["mpd_lim"]

src/pyoma2/functions/ssi.py

@@ -128,12 +128,14 @@ def build_hank(
             Hvec0 = Hank.reshape(-1, 1, order="f")  # vectorialised hankel
 
             for j in range(1, nb + 1):
-                Ri = np.array(
-                    [
-                        1 / (Nb) * np.dot(Y[:, : j * Nb - k], Yref[:, k : j * Nb].T)
-                        for k in range(p + q)
-                    ]
-                )
+                print(j, nb)
+                Ri = np.array([])
+                for k in range(p + q):
+                    print(f"{k=}, {p=}, {q=}")
+                    res = np.array(
+                        [1 / (Nb) * np.dot(Y[:, : j * Nb - k], Yref[:, k : j * Nb].T)]
+                    )
+                    Ri = np.vstack([Ri, res])
                 Hcov_j = np.vstack(
                     [np.hstack([Ri[i + j, :, :] for j in range(p + 1)]) for i in range(q)]
                 )
@@ -196,7 +198,7 @@ def build_hank(
 # Legacy
 def SSI(
     H: np.ndarray, br: int, ordmax: int, step: int = 1
-) -> typing.Tuple[typing.List[np.ndarray], typing.List[np.ndarray]]:
+) -> typing.Tuple[np.ndarray, typing.List[np.ndarray], typing.List[np.ndarray]]:
     """
     Perform System Identification using the Stochastic Subspace Identification (SSI) method.
 
@@ -953,7 +955,8 @@ def SSI_mpe(
     # OPZIONE 3 order = list[int]
     # -----------------------------------------------------------------------------
     elif isinstance(order, list):
-        order = int(order / step)
+        # Convert each element in the order list to model orders
+        order = [int(o / step) for o in order]
         order_out = np.array(order)
         for ii, fj in enumerate(tqdm(freq_ref)):
             sel = np.nanargmin(np.abs(Fn_pol[:, order[ii]] - fj))

tests/conftest.py

@@ -155,36 +155,36 @@ def multi_setup_poser_fixture(
     ss3.decimate_data(q=2)
 
     # Initialise the algorithms for setup 1
-    ssicov1 = SSIcov(name="SSIcov1", method="cov_mm", br=50, ordmax=80)
+    ssicov1 = SSIcov(name="SSIcov1", method="cov", br=50, ordmax=80)
     # Add algorithms to the class
     ss1.add_algorithms(ssicov1)
     ss1.run_all()
 
     # Initialise the algorithms for setup 2
-    ssicov2 = SSIcov(name="SSIcov2", method="cov_mm", br=50, ordmax=80)
+    ssicov2 = SSIcov(name="SSIcov2", method="cov", br=50, ordmax=80)
     ss2.add_algorithms(ssicov2)
     ss2.run_all()
 
     # Initialise the algorithms for setup 2
-    ssicov3 = SSIcov(name="SSIcov3", method="cov_mm", br=50, ordmax=80)
+    ssicov3 = SSIcov(name="SSIcov3", method="cov", br=50, ordmax=80)
     ss3.add_algorithms(ssicov3)
     ss3.run_all()
 
     # run mpe
     ss1.mpe(
         "SSIcov1",
         sel_freq=[2.63, 2.69, 3.43, 8.29, 8.42, 10.62, 14.00, 14.09, 17.57],
-        order=50,
+        order_in=50,
     )
     ss2.mpe(
         "SSIcov2",
         sel_freq=[2.63, 2.69, 3.43, 8.29, 8.42, 10.62, 14.00, 14.09, 17.57],
-        order=40,
+        order_in=40,
     )
     ss3.mpe(
         "SSIcov3",
         sel_freq=[2.63, 2.69, 3.43, 8.29, 8.42, 10.62, 14.00, 14.09, 17.57],
-        order=40,
+        order_in=40,
     )
     # reference indices
     ref_ind = [[0, 1, 2], [0, 1, 2], [0, 1, 2]]

tests/integration/setup/test_single_setup.py

@@ -439,9 +439,9 @@ def test_run(ss: SingleSetup) -> None:
 
     # plot FREQUECY-DAMPING CLUSTERS for SSI
     try:
-        fig4, ax4 = ssicov.plot_cluster(freqlim=(1, 4))
+        fig4, ax4 = ssicov.plot_freqvsdamp(freqlim=(1, 4))
     except Exception as e:
-        assert False, f"plot_cluster raised an exception {e}"
+        assert False, f"plot_freqvsdamp raised an exception {e}"
 
     # run mpe_from_plot for algorithms
     try:
@@ -461,7 +461,7 @@ def test_run(ss: SingleSetup) -> None:
 
     # run mpe for algorithms
     try:
-        ss.mpe("SSIcov", sel_freq=[1.88, 2.42, 2.68], order=40)
+        ss.mpe("SSIcov", sel_freq=[1.88, 2.42, 2.68], order_in=40)
     except Exception as e:
         assert False, f"mpe raised an exception {e} for SSIcov"