SVD is broken

[M]

python2 and python3 output: http://i.imgur.com/N3AAyOu.png

pypy2 5.4.1 output: http://i.imgur.com/ynZ40FN.png

code:

    U, S, V = numpy.linalg.svd(A)
    F = V[-1:,]  # last column
    print(A)
    print("---")
    print(V)

[M]

print(A) is

[[ 0.17487086 -0.55680614  1.2323      0.20464275 -0.6516028   1.4421
   0.14190608 -0.45184301  1.        ]
 [ 0.17487086 -0.55680614  1.2323      0.20464275 -0.6516028   1.4421
   0.14190608 -0.45184301  1.        ]
 [ 0.17487086 -0.55680614  1.2323      0.20464275 -0.6516028   1.4421
   0.14190608 -0.45184301  1.        ]
 [ 0.17487086 -0.55680614  1.2323      0.20464275 -0.6516028   1.4421
   0.14190608 -0.45184301  1.        ]
 [ 0.17487086 -0.55680614  1.2323      0.20464275 -0.6516028   1.4421
   0.14190608 -0.45184301  1.        ]
 [ 0.17487086 -0.55680614  1.2323      0.20464275 -0.6516028   1.4421
   0.14190608 -0.45184301  1.        ]
 [ 0.17487086 -0.55680614  1.2323      0.20464275 -0.6516028   1.4421
   0.14190608 -0.45184301  1.        ]
 [ 0.17487086 -0.55680614  1.2323      0.20464275 -0.6516028   1.4421
   0.14190608 -0.45184301  1.        ]]

[M]

This is really strange. I've dumped that array via numpy.dump to file and this code:

import numpy

A = numpy.load("./here")

print(A)
print("---")
U, S, V = numpy.linalg.svd(A)
print(V)

produces the right value in pypy2 5.4.1

It seems that there might be some memory corruption in my main script.

[M]

./lab4.py - main code

./data/ - data for main code

./test.py - test script from my comment

./here - numpy dump of A matrix

[Richard Plangger]

I have tested your numpy program. It seems to be unrelated to the JIT

[M]

I've tested it with --jit off and it didn't changed anything.

[mattip]

Cannot reproduce. For me cpython and pypy+numpypy give the same results. @Marqin can you provide the desired results in a computer-readable format?