Coverage for cvxrisk/linalg/valid.py: 100%

1"""Matrix validation utilities for handling non-finite values.""" 

2 

3# Copyright 2023 Stanford University Convex Optimization Group 

4# 

5# Licensed under the Apache License, Version 2.0 (the "License"); 

6# you may not use this file except in compliance with the License. 

7# You may obtain a copy of the License at 

8# 

9# http://www.apache.org/licenses/LICENSE-2.0 

10# 

11# Unless required by applicable law or agreed to in writing, software 

12# distributed under the License is distributed on an "AS IS" BASIS, 

13# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 

14# See the License for the specific language governing permissions and 

15# limitations under the License. 

16from __future__ import annotations 

17 

18import numpy as np 

19 

20 

21def valid(matrix: np.ndarray) -> tuple[np.ndarray, np.ndarray]: 

22 """Extract the valid subset of a matrix by removing rows/columns with non-finite values. 

23 

24 This function identifies rows and columns in a matrix that contain non-finite values 

25 (NaN or infinity) on the diagonal and removes them, returning both the indicator 

26 vector and the resulting valid submatrix. 

27 

28 Args: 

29 matrix: An n x n matrix to be validated 

30 

31 Returns: 

32 A tuple containing: 

33 - Boolean vector indicating which rows/columns are valid 

34 - The valid submatrix with invalid rows/columns removed 

35 

36 Raises: 

37 AssertionError: If the input matrix is not square 

38 

39 """ 

40 # make sure matrix is quadratic 

41 if matrix.shape[0] != matrix.shape[1]: 

42 raise AssertionError 

43 

44 v = np.isfinite(np.diag(matrix)) 

45 return v, matrix[:, v][v]