Loading func_matrix_vector.py +5 −5 Original line number Diff line number Diff line Loading @@ -30,9 +30,9 @@ def sample_tridiag(doc_id, args): input_vars = get_yaml(args.case_variable_file, doc_id) print(f"Case: {input_vars['case_name']}") filename = input_vars['savefilename'].format(**input_vars) NUM_QUBITS = input_vars['NUM_QUBITS'] n_qubits_matrix = input_vars['NQ_MATRIX'] # custom systems MATRIX_SIZE = 2 ** NUM_QUBITS MATRIX_SIZE = 2 ** n_qubits_matrix # entries of the tridiagonal Toeplitz symmetric matrix a = 1 Loading @@ -41,7 +41,7 @@ def sample_tridiag(doc_id, args): [-1, 0, 1], shape=(MATRIX_SIZE, MATRIX_SIZE)).toarray() vector = np.array([1] + [0]*(MATRIX_SIZE - 1)) return matrix, vector, filename return matrix, vector, input_vars def Hele_Shaw(doc_id, args): input_vars = get_yaml(args.case_variable_file, doc_id) Loading Loading @@ -158,7 +158,7 @@ def Hele_Shaw(doc_id, args): file.close() print("===========Metadata saved===========") return A_herm, B_herm, filename return A_herm, B_herm, input_vars def Cylinder_2D(doc_id, args): input_vars = get_yaml(args.case_variable_file, doc_id) Loading Loading @@ -195,7 +195,7 @@ def Cylinder_2D(doc_id, args): print(f'Reformatted A_herm:\n{A_herm}\nB_herm:\n{B_herm}') print(f'Determinant of resulting matrix: {np.linalg.det(A_herm)}\nCondition # of resulting matrix: {np.linalg.cond(A_herm)}') return A_herm, B_herm, filename return A_herm, B_herm, input_vars # Functions def next_power_of_2(x): Loading Loading
func_matrix_vector.py +5 −5 Original line number Diff line number Diff line Loading @@ -30,9 +30,9 @@ def sample_tridiag(doc_id, args): input_vars = get_yaml(args.case_variable_file, doc_id) print(f"Case: {input_vars['case_name']}") filename = input_vars['savefilename'].format(**input_vars) NUM_QUBITS = input_vars['NUM_QUBITS'] n_qubits_matrix = input_vars['NQ_MATRIX'] # custom systems MATRIX_SIZE = 2 ** NUM_QUBITS MATRIX_SIZE = 2 ** n_qubits_matrix # entries of the tridiagonal Toeplitz symmetric matrix a = 1 Loading @@ -41,7 +41,7 @@ def sample_tridiag(doc_id, args): [-1, 0, 1], shape=(MATRIX_SIZE, MATRIX_SIZE)).toarray() vector = np.array([1] + [0]*(MATRIX_SIZE - 1)) return matrix, vector, filename return matrix, vector, input_vars def Hele_Shaw(doc_id, args): input_vars = get_yaml(args.case_variable_file, doc_id) Loading Loading @@ -158,7 +158,7 @@ def Hele_Shaw(doc_id, args): file.close() print("===========Metadata saved===========") return A_herm, B_herm, filename return A_herm, B_herm, input_vars def Cylinder_2D(doc_id, args): input_vars = get_yaml(args.case_variable_file, doc_id) Loading Loading @@ -195,7 +195,7 @@ def Cylinder_2D(doc_id, args): print(f'Reformatted A_herm:\n{A_herm}\nB_herm:\n{B_herm}') print(f'Determinant of resulting matrix: {np.linalg.det(A_herm)}\nCondition # of resulting matrix: {np.linalg.cond(A_herm)}') return A_herm, B_herm, filename return A_herm, B_herm, input_vars # Functions def next_power_of_2(x): Loading