Pivoting QR decomposition

[loiseaujc]

Following #930, this PR extends the qr interface to enable the computation of the QR factorization with column pivoting. It is based on the xGEQP3 driver from lapack.

Proposed interfaces

• call qr(a, q, r, pivots [, overwrite_a, storage, err])

where a is the matrix to be factorized, q the orthonormal basis for colspan(a), r the upper triangular matrix and pivots an integer array with indices of the pivoted columns.

Progress

• Interface
• Base implementation
• Tests
• In-code documentation
• Specifications
• Example

Ping: @perazz, @jvdp1, @jalvesz

[loiseaujc]

I think this PR is almost ready to be reviewed. I have the specs left to write but this should pretty quick as it mainly is a small modification of the qr specs. I'll try to do that by the end of the week. It seems like there is a small issue with the unbuntu-22.04/cmake/inter-classic 2021.10 setup though. Not sure what it is and I don't have the intel compilers on my laptop so I can't really dig into it at the moment.

[Copilot]

Pull Request Overview

This PR adds support for QR factorization with column pivoting to the linear algebra library. The implementation leverages the LAPACK geqp3 routine and extends the existing qr interface to support pivot tracking.

• Adds pivoting QR factorization via geqp3 LAPACK routine
• Extends qr() and qr_space() interfaces to support column pivoting with pivot output
• Includes comprehensive test coverage for tall, wide, and rank-deficient matrices

Reviewed Changes

Copilot reviewed 9 out of 9 changed files in this pull request and generated 4 comments.

Show a summary per file

File	Description
test/linalg/test_linalg_pivoting_qr.fypp	Comprehensive test suite for pivoting QR factorization across different matrix types and configurations
test/linalg/CMakeLists.txt	Adds pivoting QR test to build system
src/stdlib_linalg_qr.fypp	Implements pivoting QR factorization routines and workspace calculation
src/stdlib_linalg_lapack.fypp	Adds LAPACK geqp3 interface for QR with column pivoting
src/stdlib_linalg.fypp	Extends public interface with pivoting QR subroutines
src/lapack/stdlib_linalg_lapack_aux.fypp	Adds error handler for geqp3 LAPACK routine
example/linalg/example_pivoting_qr_space.f90	Example demonstrating pivoting QR with pre-allocated storage
example/linalg/example_pivoting_qr.f90	Basic example demonstrating pivoting QR factorization
example/linalg/CMakeLists.txt	Adds pivoting QR examples to build system

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[codecov]

Codecov Report

❌ Patch coverage is 0% with 16 lines in your changes missing coverage. Please review.
⚠️ Please upload report for BASE (master@9e4c230). Learn more about missing BASE report.

Files with missing lines	Patch %	Lines
example/linalg/example_pivoting_qr_space.f90	0.00%	10 Missing ⚠️
example/linalg/example_pivoting_qr.f90	0.00%	6 Missing ⚠️

Additional details and impacted files

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[loiseaujc]

Modulo the issue with the unbuntu-22.04/cmake/intel-classic 2021.10 setup which I haven't been able to investigate yet, this PR is ready for review.

[jvdp1]

Thank you @loiseaujc . Overall LGTM. I just have some minor suggestions.

[perazz]

Thank you for this implementation @loiseaujc, great work.
I stand by @jvdp1's comments, and I added a few edits/typos.

Overall, looks good to me with the above.

[loiseaujc]

For the build unbuntu-22.04, cmake, intel-classic 2021-10, it seems the computations are successful (at least according to the linalg_state_type returned) but when comparing A and QR P.T, the test fails. Without having this particular intel compiler on my laptop I unfortunately can't say much more than that.

[perazz]

@loiseaujc would it be possible to perhaps add some debugging prints into the PR, so a new CI run could show us what's the extent of the error? Perhaps if it's just some rounding error, we could just increase the test tolerance; however, it may be more of a compiler bug, in which case it may be worth digging deeper into the issue

[loiseaujc]

Working on it. I don't think it is a tolerance issue though. The tolerance I use in the tests for now is tol = 100 * sqrt(epsilon(1.0_wp)). For single precision, that is about $10^{-2}$, and $10^{-6}$ for double precision. The comparison is done element-wise.