in reply to Re^3: Abstract image registration or feature detection
in thread Abstract image registration or feature detection [UPDATED w examples]

Minimal pair:

perl -MPDL -MPDL::Matrix -e '$m = mpdl [[2,0],[0,2]]; $v = vpdl [1,2];
+ print $m x $v'

[
 [2]
 [4]
]

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vs.

perl -MPDL -MPDL::Matrix -e '$m = mpdl [[2,0],[0,2]]; $v = vpdl [1,2];
+ print inv($m) x $v'
Dim mismatch in matmult of [2x2] x [2x1]: 2 != 1 at /usr/lib64/perl5/v
+endor_perl/PDL/Primitive.pm line 274.
    PDL::matmult(PDL=SCALAR(0x5600a82130e0), PDL::Matrix=SCALAR(0x5600
+a8202ba0), PDL=SCALAR(0x5600a8d718c8)) called at /usr/lib64/perl5/ven
+dor_perl/PDL/Primitive.pm line 31
    PDL::__ANON__(PDL=SCALAR(0x5600a82130e0), PDL::Matrix=SCALAR(0x560
+0a8202ba0), "") called at -e line 1

[download]

This looks like a bug in PDL::Matrix, specifically with inv.

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Re^5: Abstract image registration or feature detection
by etj (Priest) on Jul 05, 2022 at 20:51 UTC
    As now noted on pryrt's excellent bug report (thank you), this will still work as expected if you switch your inv($m) to $m->inv. This will then engage PDL::Matrix's overload of x, which is what you need here.

    I would strongly encourage you not to use PDL::Matrix, because somewhat similar to PDL::Complex, it is full of gotchas. Even though after some head-scratching it became clear what exactly was happening here, it's not particularly clear how to fix it - a keyhole change to the Perl function PDL::MatrixOps::inv to make it ensure the output was the right class would resolve this exact issue. But since that uses lu_backsub for its work, and that is an eye-wateringly complicated Perl function as well, it will not be easy. That function's output variable comes from some PDL::Slices operations.

    If someone were minded to at least use git bisect to identify the commit that broke it, that would be very helpful. Even better would be a pull-request that fixes this (obviously with a test, in t/matrix.t), that will use our amazing CI to check it doesn't break anything else in main PDL or known downstreams. A top tip would be that make coretest runs t/matrix.t, with a very minimal build otherwise that allows a very quick dev cycle.

    As a hopefully practical (as well as better-performance, because it uses LAPACK) alternative, have you taken a look at PDL::LinearAlgebra?

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Re^5: Abstract image registration or feature detection
by pryrt (Abbot) on Jul 05, 2022 at 19:28 UTC
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