zusammenfügen 13.1.

Datumsfestlegung.py

@@ -1,4 +1,5 @@
 import sympy as sp
+import numpy as np
 from typing import Iterable, List, Sequence, Tuple, Optional
 
 
@@ -106,50 +107,13 @@ class Datumsfestlegung:
         sol = K.LUsolve(rhs)
         return sol[:u, :]
 
+
+
     @staticmethod
-    def weiches_datum(
-        A: sp.Matrix,
-        dl: sp.Matrix,
-        Q_ll: sp.Matrix,
-        x0: sp.Matrix,
-        anschluss_indices: Sequence[int],
-        anschluss_werte: sp.Matrix,
-        Sigma_AA: Optional[sp.Matrix] = None,
-    ) -> Tuple[sp.Matrix, sp.Matrix, sp.Matrix]:
-        if dl.cols != 1 or x0.cols != 1:
-            raise ValueError("dl und x0 müssen Spaltenvektoren sein.")
-        if A.rows != dl.rows:
-            raise ValueError("A.rows muss dl.rows entsprechen.")
-        if A.cols != x0.rows:
-            raise ValueError("A.cols muss x0.rows entsprechen.")
-        if Q_ll.rows != Q_ll.cols or Q_ll.rows != A.rows:
-            raise ValueError("Q_ll muss (n×n) sein und zu A.rows passen.")
-
-        u = A.cols
-        idx = [int(i) for i in anschluss_indices]
-        m = len(idx)
-
-        if anschluss_werte.cols != 1 or anschluss_werte.rows != m:
-            raise ValueError("anschluss_werte muss (m×1) sein.")
-        if Sigma_AA is None:
-            Sigma_AA = sp.eye(m)
-        if Sigma_AA.rows != m or Sigma_AA.cols != m:
-            raise ValueError("Sigma_AA muss (m×m) sein.")
-
-        A_A = sp.zeros(m, u)
-        for r, j in enumerate(idx):
-            if not (0 <= j < u):
-                raise IndexError(f"Anschluss-Index {j} außerhalb [0,{u-1}]")
-            A_A[r, j] = 1
-
-        x0_A = sp.Matrix([[x0[j, 0]] for j in idx])
-        dl_A = anschluss_werte - x0_A
-
-        A_ext = A.col_join(A_A)
-        dl_ext = dl.col_join(dl_A)
-
-        Q_ext = sp.zeros(Q_ll.rows + m, Q_ll.cols + m)
-        Q_ext[:Q_ll.rows, :Q_ll.cols] = Q_ll
-        Q_ext[Q_ll.rows:, Q_ll.cols:] = Sigma_AA
-
-        return A_ext, dl_ext, Q_ext
+    def weiches_datum(Q_ll: np.ndarray, Q_AA: np.ndarray) -> np.ndarray:
+        if Q_ll.ndim != 2 or Q_ll.shape[0] != Q_ll.shape[1]:
+            raise ValueError("Q_ll muss quadratisch sein.")
+        if Q_AA.ndim != 2 or Q_AA.shape[0] != Q_AA.shape[1]:
+            raise ValueError("Q_AA muss quadratisch sein.")
+        Q_ext = np.block([[Q_ll, np.zeros((Q_ll.shape[0], Q_AA.shape[0]))],[np.zeros((Q_AA.shape[0], Q_ll.shape[0])), Q_AA]])
+        return Q_ext