pyrc.core.solver.stationary#

solve_stationary(system_matrix: csr_matrix | MutableDenseMatrix | MutableSparseMatrix | ImmutableSparseMatrix | spmatrix | sparray, input_matrix: csr_matrix | MutableDenseMatrix | MutableSparseMatrix | ImmutableSparseMatrix | spmatrix | sparray = None, input_vector: ndarray | MutableDenseMatrix | sparray = None) → ndarray | MutableDenseMatrix#

Solve the stationary solution of a linear RC network: x = -A⁻¹ · B · u.

Dispatches to a numeric (scipy sparse) or symbolic (sympy) solver based on whether free symbols are detected in the inputs. A purely numeric sympy matrix is converted and solved numerically. For homogeneous systems, input_matrix and input_vector can be omitted, returning the zero vector.

Parameters:

  • system_matrix (csr_matrix | sp.Matrix | MutableSparseMatrix | ImmutableSparseMatrix | spmatrix | sparray) – System matrix (Jacobian) of shape (n, n).

  • input_matrix (csr_matrix | sp.Matrix | MutableSparseMatrix | ImmutableSparseMatrix | spmatrix | sparray, optional) – Input matrix of shape (n, m). Must be provided together with input_vector.

  • input_vector (np.ndarray | sp.Matrix, optional) – Input vector of shape (m,) or (m, 1). Must be provided together with input_matrix.

Returns:

Stationary temperature vector of shape (n,) for numeric, (n, 1) for symbolic.

Return type:

np.ndarray | sp.Matrix | MutableDenseMatrix

Raises:

  • ValueError : – If only one of input_matrix and input_vector is provided.

  • ValueError : – If the system matrix is singular.