Open h-vetinari opened 3 years ago
So the first set of errors is expected if there is no GPU. It should return 'nan' in the solution arrays in this case.
The second set of errors are because SCS has been installed without blas / lapack support, which is needed to solve SDPs. You should be able to copy what I did because I finally managed to get windows to install blas / lapack correctly in github actions here.
So the first set of errors is expected if there is no GPU. It should return 'nan' in the solution arrays in this case.
I understand that this is the current status, though I still think it would be very good to check the runtime availability of GPU drivers. I googled this briefly, and it seems like the forthcoming cuda-python
should be just what would be needed to do this with low effort (see the example for def ASSERT_DRV(err):
in this blogpost)
@kkraus14 (since you co-wrote that blogpost), any hint or even timeline when that might be released (or any other tips)?
The second set of errors are because SCS has been installed without blas / lapack support, which is needed to solve SDPs
I'm aware of this of course, but some change in the infrastructure between 2.1.3 & 2.1.4 invalidated the existing conda-recipe (which is not a big deal, I'll fix it).
Will update as soon as I have more.
OK, I get the same failures as in CI if there's physical GPU hardware... This is from downloading an artefact from here, installing it with conda create -n test -c /where/you/unpacked/the/artefact scs python=3.8 scipy pytest
and then running tests (no guarantees about the behaviour on linux, but feel free to download the respective artefact and try it!).
When I try to install the linux artifact I get an error:
2021-06-08 14:28:13 (base) 0 bodonoghue@bodonoghue-[]-~/git/tmp:
└──[ins] => conda create -n gpu_test -c $PWD/conda_artifacts_333825_linux_64_cuda_compiler_version10.2numpy1.17python3.6.____ scs python=3.6 scipy pytest
Collecting package metadata (current_repodata.json): done
Solving environment: failed with current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed
UnsatisfiableError: The following specifications were found to be incompatible with each other:
Package python conflicts for:
pytest -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0|>=3.8,<3.9.0a0|>=3.9,<3.10.0a0']
scs -> python[version='>=3.6,<3.7.0a0']
scipy -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0|>=3.8,<3.9.0a0|>=3.9,<3.10.0a0']
Package python_abi conflicts for:
scs -> python_abi=3.6[build=*_cp36m]
Package sqlite conflicts for:
python=3.6 -> sqlite[version='>=3.20.1,<4.0a0|>=3.22.0,<4.0a0|>=3.23.1,<4.0a0|>=3.24.0,<4.0a0|>=3.25.2,<4.0a0|>=3.26.0,<4.0a0|>=3.29.0,<4.0a0|>=3.30.1,<4.0a0|>=3.31.1,<4.0a0|>=3.33.0,<4.0a0']
Package scipy conflicts for:
scs -> scipy
Package importlib_metadata conflicts for:
pytest -> importlib_metadata[version='>=0.12']
Package iniconfig conflicts for:
pytest -> iniconfig
Package more-itertools conflicts for:
pytest -> more-itertools[version='>=4.0.0|>=4.0|>=4.0,>=4.0,<6.0']
Package scs-proc conflicts for:
scs -> scs-proc=[build=cuda]
<etc>
However I can install the GPU code from source and it passes the tests on linux.
Just eyeballing your error message I am guessing that it's something to do with different widths for the integer or floating point types that the CUDA library is using that are conflicting with the SCS widths. I see in your trace that you have size of scs_int = 4, size of scs_float = 8
, ie, 32 bit ints and 64 bit floats, which is set here, which is a macro that influences the decision here. Do you know the widths of the int and float types in the CUDA install you're using?
OK sorry, I forgot that you might not have conda-forge configured as a channel yet. In that case, please try:
conda create -n test -c /where/you/unpacked/the/artefact -c conda-forge python=3.8 scs scipy pytest
This should fix the resolver errors.
Ok that worked, but I can't import _scs_gpu
after install, I tried two artifacts:
conda_artifacts_333825_linux_64_cuda_compiler_version11.2numpy1.19python3.7.____
conda_artifacts_333825_linux_64_cuda_compiler_version10.2numpy1.17python3.6.____
The other tests pass though.
Can you check (e.g. using conda info
) which cuda drivers are present on your machine (resp. your environment)? You'll have to match the CUDA version of the artefact (unless the compilation on linux is broken in some other exciting way).
Sidenote: it's possible that the compiled scs shouldn't depend on the CUDA version. I'm not good enough at these things yet to know for sure, so I tend to compile per cuda version.
I matched up the CUDA versions (11.1) but I still can't import _scs_gpu after creating the environment. I see these files in the unzipped artifact:
2021-06-08 15:58:52 (gpu_test) 0 bodonoghue@bodonoghue-[]-~/git/tmp/conda_artifacts_333825_linux_64_cuda_compiler_version11.1numpy1.19python3.7.____/linux-64:
└──[ins] => ll
total 324
drwxr-x--- 3 bodonoghue primarygroup 4096 Jun 8 15:36 ./
drwxr-x--- 8 bodonoghue primarygroup 4096 Jun 8 15:36 ../
drwxr-x--- 10 bodonoghue primarygroup 4096 Jun 8 15:36 .cache/
-rw-r----- 1 bodonoghue primarygroup 1409 Jun 8 14:36 current_repodata.json
-rw-r----- 1 bodonoghue primarygroup 651 Jun 8 14:36 current_repodata.json.bz2
-rw-r----- 1 bodonoghue primarygroup 3151 Jun 8 14:36 index.html
-rw-r----- 1 bodonoghue primarygroup 1409 Jun 8 14:36 repodata_from_packages.json
-rw-r----- 1 bodonoghue primarygroup 651 Jun 8 14:36 repodata_from_packages.json.bz2
-rw-r----- 1 bodonoghue primarygroup 1409 Jun 8 14:36 repodata.json
-rw-r----- 1 bodonoghue primarygroup 651 Jun 8 14:36 repodata.json.bz2
-rw-r----- 1 bodonoghue primarygroup 281462 Jun 8 14:36 scs-2.1.4-py37cuda111h31cf320_0_cuda.tar.bz2
-rw-r----- 1 bodonoghue primarygroup 5637 Jun 8 14:36 scs-proc-1.0.0-cuda.tar.bz2
so it looks like it should work, but for some reason _scs_gpu does not get installed correctly.
Thanks for checking. Is there any error message for importing _scs_gpu
? It's doubly interesting, because as the discussion above showed, this import does work within CI (even though there's no GPU), and it also succeeds on my windows machine (with the corresponding artefact).
Aside from setting up the required things, the installation is as trivial as I managed to keep it - basically comes down to: python setup.py install --scs --gpu --extraverbose
.
Just eyeballing your error message I am guessing that it's something to do with different widths for the integer or floating point types that the CUDA library is using that are conflicting with the SCS widths. I see in your trace that you have
size of scs_int = 4, size of scs_float = 8
, ie, 32 bit ints and 64 bit floats, which is set here, which is a macro that influences the decision here. Do you know the widths of the int and float types in the CUDA install you're using?
Ah, sorry, just saw this part only now. Is there a reason to not use 64bits on GPU? I assume that the width is 64bits there as well...
I see the issue now, for some reason conda is using conda-forge to install scs. It sees the new 'channel' but isn't using it.
GPUs are much better at 32 bit operations and I think by default usually CUDA is 32 bit ints, not sure about floats.
[...] for some reason conda is using conda-forge to install scs.
Can you explain what you mean by that? Conda-forge does its own builds (using its own infra & dependencies & envs) by design. All necessary steps need to be made explicit, in order to achieve reproducibility & portability...
GPUs are much better at 32 bit operations and I think by default usually CUDA is 32 bit ints, not sure about floats.
I also deal with packaging other GPU-packages (e.g. faiss), and I'm not aware of this (but then, they maybe just build all variants by default).
I don't know very much about conda, when I enter this:
=> conda create -n gpu_test -c /usr/local/google/home/bodonoghue/git/tmp/conda_artifacts_333825_linux_64_cuda_compiler_version11.1numpy1.19python3.7.____ -c conda-forge python=3.7 scs scipy pytest numpy=1.19
I see scs appear as:
The following NEW packages will be INSTALLED:
<many packages>
scs conda-forge/linux-64::scs-2.1.4-py37he255db3_0
<many packages>
which I assumed meant it was coming from conda-forge, rather than the channel I'm specifying.
About the 32 bit ints see top comment here. That might not be the issue though, just a possibility.
Ah, now I understand you. It's possible that the path is not correct (e.g. you could be missing a cp
at the end of the ____
), but also, depending on how you unpacked the package (whether into a new folder or directly where the tar.gz was), you might need to go one level deeper, so that whatever path you specify allows conda to read the contained current_repodata.json
. I'd also use quotes to be sure, e.g. -c "path/to/wherever"
OK I've tried every which way now and I cannot get it to install from the channel, I'm presumably doing something wrong so I don't want to waste any more of your time with it!
One more thought (sorry for all the hassle, and thanks so much for your patience) - could you try adding --channel-priority=strict
, please?
I tried
conda create -n gpu_test --strict-channel-priority -c "/usr/local/google/home/bodonoghue/git/tmp/channel/" -c conda-forge scs scipy pytest numpy
and got
UnsatisfiableError: The following specifications were found to be incompatible with each other:
<many packages>
My guess is somehow the packages are inconsistent somewhere, and when the strict channel priority is off it falls back to using conda-forge which for some reason works (though it has the same version by the look of it).
ok, it's weird (classic "works on my machine"), but I accept that we're stuck 😅
Haha, thanks for your help anyway! It's probably something wrong with my setup somewhere.
One more thought about this @bodono - which distribution are you on, resp. what version of glibc is running there? If it's below 2.17, this might be a reason for the conflicts.
Probably the artefacts are gone from azure by now (and you'll have probably deleted yours), but I had forgotten to ask about the details from the UnsatisfiableError
, which would probably provide some hints as to where we're stuck.
It potentially might have changed since I tried to run these, but I'm currently running:
└──[ins] => ldd --version
ldd (Debian GLIBC 2.31-13) 2.31
Hey @bodono, thanks so much for the updates in https://github.com/bodono/scs-python/commit/618962c6ec39cc493526821e32ba41a7581c8c92 and the release of 2.1.4!
Unfortunately, there seem to be a couple of new errors (also in the CI here, which really should upgrade its python version though, see #42) - see this CI run of https://github.com/conda-forge/scs-feedstock/pull/21.
One aspect is that the determining factor in https://github.com/bodono/scs-python/blob/master/test/test_solve_random_cone_prob.py is whether
import _scs_gpu
succeeds - as it turns out, this does succeed even without a GPU, so the test suite for the GPU-enabled library ends up failing in conda-forge CI. Note this is not so terrible, I could skip those tests for GPU builds, but perhaps it would be still nice to have more robust runtime-detection of GPU-hardware.Still even though the following tests are run with
gpu=True
on a machine without actual GPU hardware, the errors actually don't look that they're related to that (AFAICS, basically hidingERROR_CUDA: no CUDA-capable device is detected
but still producing results - likely garbage?):Details of test-suite failures on linux (GPU enabled lib running on machine with no GPU)
``` =================================== FAILURES =================================== ________________________ test_solve_feasible[True-True] ________________________ use_indirect = True, gpu = True @pytest.mark.parametrize('use_indirect,gpu', flags) def test_solve_feasible(use_indirect, gpu): data, p_star = tools.gen_feasible(K, n=m // 3, density=0.1) sol = scs.solve(data, K, use_indirect=use_indirect, gpu=gpu, **params) x = sol['x'] y = sol['y'] s = sol['s'] > np.testing.assert_almost_equal(np.dot(data['c'], x), p_star, decimal=3) E AssertionError: E Arrays are not almost equal to 3 decimals E ACTUAL: nan E DESIRED: -3.3213532711629523 test/test_solve_random_cone_prob.py:55: AssertionError ----------------------------- Captured stdout call ----------------------------- m = 185 n = 61 max_iters = 5000 verbose = 1 normalize = 1 warm_start = 0 acceleration_lookback = 10 eps = 0.000010 alpha = 1.500000 rho_x = 0.001000 cg_rate = 2.000000 scale = 5.000000 write_data_filename = (null) num zeros = 10 num LP = 15 num SOCs = 4 soc array: 5 10 0 1 num SDCs = 6 sdc array: 3 4 0 0 1 10 num ep = 10 num ed = 10 num PCs = 4 pow array: -0.250000 0.500000 0.750000 -0.330000 ---------------------------------------------------------------------------- SCS v2.1.4 - Splitting Conic Solver (c) Brendan O'Donoghue, Stanford University, 2012 ---------------------------------------------------------------------------- Lin-sys: sparse-indirect GPU, nnz in A = 1128, CG tol ~ 1/iter^(2.00) eps = 1.00e-05, alpha = 1.50, max_iters = 5000, normalize = 1, scale = 5.00 acceleration_lookback = 10, rho_x = 1.00e-03 Variables n = 61, constraints m = 185 Cones: primal zero / dual free vars: 10 linear vars: 15 soc vars: 16, soc blks: 4 sd vars: 72, sd blks: 6 exp vars: 30, dual exp vars: 30 primal + dual power vars: 12 normalizing A Col 0: A[6,0] = -1.206851, A[8,0] = 0.863559, A[12,0] = -0.469813, A[67,0] = -2.689922, A[73,0] = -0.485232, A[74,0] = 0.755218, A[87,0] = 1.846006, A[106,0] = -0.337257, A[118,0] = 1.668043, A[119,0] = -0.685583, A[122,0] = -0.638478, A[134,0] = -0.000831, A[135,0] = 0.167899, A[144,0] = 0.345549, A[150,0] = 0.561291, A[154,0] = -1.539839, A[156,0] = -0.018222, A[165,0] = 0.333911, norm col = 4.537789 Col 1: A[1,1] = -1.035912, A[22,1] = 0.302134, A[27,1] = 1.342489, A[29,1] = -1.589006, A[30,1] = 0.260136, A[31,1] = -0.944863, A[32,1] = -1.301213, A[40,1] = -0.545500, A[41,1] = 0.345863, A[44,1] = 0.113402, A[54,1] = 0.372327, A[56,1] = -0.940242, A[67,1] = -0.165816, A[68,1] = 0.015342, A[96,1] = 0.040193, A[98,1] = 0.704175, A[118,1] = 1.749359, A[125,1] = -1.037643, A[136,1] = -0.568351, A[141,1] = 0.261406, A[142,1] = 0.594032, A[143,1] = 1.390197, A[168,1] = 0.623981, A[169,1] = 2.074249, A[180,1] = 0.419618, A[182,1] = -0.699009, norm col = 4.721604 Col 2: A[19,2] = -1.900260, A[22,2] = 0.152708, A[27,2] = -0.907976, A[39,2] = -0.154472, A[41,2] = -0.122479, A[46,2] = 0.452478, A[53,2] = 0.150574, A[57,2] = 0.436414, A[60,2] = 0.609777, A[62,2] = 0.171775, A[64,2] = -0.423926, A[71,2] = 0.719417, A[76,2] = 0.740349, A[100,2] = 0.103041, A[102,2] = 0.808124, A[112,2] = -0.244497, A[154,2] = -1.638796, norm col = 3.157736 Col 3: A[4,3] = 0.326188, A[7,3] = -0.283094, A[18,3] = -0.759929, A[24,3] = -0.537671, A[27,3] = 1.785176, A[31,3] = -1.591887, A[38,3] = -0.310212, A[42,3] = -2.122614, A[46,3] = 0.048864, A[51,3] = -1.861490, A[58,3] = -0.927513, A[60,3] = 0.839950, A[98,3] = 0.499054, A[112,3] = 1.339145, A[131,3] = -0.160219, A[133,3] = 1.414424, A[135,3] = 0.098009, A[142,3] = -0.759221, A[144,3] = 0.947055, A[157,3] = 0.494506, A[164,3] = -1.106431, A[167,3] = -0.762322, A[184,3] = -1.896000, norm col = 5.254082 Col 4: A[6,4] = 0.960787, A[8,4] = -0.455470, A[17,4] = 0.336045, A[32,4] = -2.022427, A[35,4] = 0.661065, A[39,4] = 0.415695, A[47,4] = 0.554309, A[54,4] = -0.639492, A[71,4] = 0.007206, A[95,4] = -1.002909, A[98,4] = -0.722712, A[101,4] = -1.452656, A[102,4] = -0.674956, A[104,4] = -0.476761, A[134,4] = 0.128345, A[140,4] = 0.054886, A[147,4] = -0.433494, A[158,4] = 1.595778, A[170,4] = -0.625777, A[171,4] = -1.509232, A[174,4] = -1.108695, norm col = 4.199224 Col 5: A[1,5] = -0.062359, A[22,5] = 1.270369, A[27,5] = 1.229778, A[31,5] = 0.054518, A[41,5] = -0.580707, A[48,5] = -0.584464, A[57,5] = -1.682610, A[59,5] = -0.336008, A[60,5] = 0.740041, A[62,5] = 1.575790, A[65,5] = 2.429000, A[66,5] = -1.055031, A[82,5] = -0.340976, A[109,5] = 1.267178, A[116,5] = 0.473097, A[141,5] = 0.147264, A[166,5] = -1.088250, A[167,5] = -0.566231, A[170,5] = -1.196836, A[173,5] = 0.633929, norm col = 4.701761 Col 6: A[0,6] = -0.359033, A[3,6] = 1.297341, A[16,6] = -0.981776, A[35,6] = 0.485829, A[39,6] = -0.373926, A[40,6] = -0.062819, A[59,6] = -0.165077, A[64,6] = 0.887094, A[66,6] = 0.772705, A[67,6] = 0.506437, A[91,6] = 1.778887, A[92,6] = 0.522316, A[102,6] = 0.510619, A[114,6] = 0.426455, A[116,6] = -2.109753, A[128,6] = 0.090164, A[145,6] = -1.019884, A[165,6] = 0.072555, A[183,6] = 0.875560, norm col = 3.869688 Col 7: A[13,7] = 0.082552, A[23,7] = 0.243696, A[25,7] = 0.020209, A[26,7] = -1.396991, A[37,7] = -0.106853, A[39,7] = 0.015527, A[67,7] = 0.754074, A[75,7] = 1.466766, A[85,7] = -2.003671, A[117,7] = -0.470493, A[139,7] = -0.090451, A[141,7] = -0.069088, A[176,7] = 1.649970, norm col = 3.423638 Col 8: A[19,8] = -0.460752, A[26,8] = -0.568000, A[33,8] = -0.207227, A[34,8] = -0.266988, A[43,8] = -0.385095, A[45,8] = 1.064313, A[56,8] = -1.802117, A[61,8] = 0.643571, A[62,8] = 0.340310, A[70,8] = 0.210784, A[76,8] = -0.304161, A[87,8] = -0.047400, A[91,8] = 0.370178, A[93,8] = 0.253284, A[118,8] = 0.815811, A[120,8] = 0.622343, A[146,8] = -0.413453, A[147,8] = -0.026967, norm col = 2.696799 Col 9: A[35,9] = -0.364116, A[47,9] = -0.238373, A[49,9] = 0.393924, A[52,9] = -1.417077, A[61,9] = -0.853893, A[64,9] = 0.092450, A[69,9] = -0.332618, A[89,9] = -0.178036, A[91,9] = 0.894469, A[93,9] = -0.664345, A[99,9] = 0.480248, A[120,9] = 0.853316, A[149,9] = -0.550890, A[168,9] = -0.040372, A[172,9] = -0.358027, norm col = 2.422025 Col 10: A[7,10] = 1.030993, A[8,10] = 1.028718, A[12,10] = -0.105932, A[17,10] = -1.215521, A[25,10] = 1.655521, A[40,10] = -0.560652, A[61,10] = -0.535588, A[67,10] = 0.771024, A[71,10] = 1.661088, A[72,10] = -0.670617, A[82,10] = -0.603055, A[83,10] = -0.360067, A[120,10] = -0.654276, A[123,10] = 0.268561, A[125,10] = -0.912225, A[140,10] = -0.027401, A[166,10] = 0.795094, A[178,10] = -1.187776, norm col = 3.824224 Col 11: A[0,11] = -0.236468, A[9,11] = -0.513782, A[42,11] = 0.260273, A[70,11] = 0.276646, A[78,11] = 0.204153, A[82,11] = 1.732228, A[95,11] = -0.035820, A[105,11] = -1.919230, A[112,11] = -0.226640, A[124,11] = -0.887895, A[166,11] = 0.514763, A[172,11] = -0.666147, A[183,11] = -0.146568, norm col = 2.959920 Col 12: A[33,12] = 0.912106, A[47,12] = 0.036566, A[49,12] = -0.204922, A[52,12] = -0.516063, A[70,12] = -0.946272, A[73,12] = -0.739528, A[84,12] = -0.784110, A[93,12] = 2.027786, A[100,12] = -1.763736, A[105,12] = -0.170454, A[119,12] = 0.569993, A[133,12] = -0.113419, A[140,12] = -0.917188, A[147,12] = -0.033559, A[152,12] = 0.239341, A[159,12] = 0.183979, A[162,12] = 1.545330, A[169,12] = 1.185061, A[170,12] = -0.715910, norm col = 4.003333 Col 13: A[18,13] = -0.331922, A[20,13] = 0.517896, A[44,13] = 0.221609, A[51,13] = -1.228412, A[66,13] = -0.874334, A[104,13] = -0.447158, A[121,13] = -1.413657, A[124,13] = 0.432392, A[136,13] = 0.224959, A[140,13] = 1.042822, A[145,13] = 0.520345, A[150,13] = 0.125531, A[152,13] = 0.644176, A[157,13] = 1.272924, A[169,13] = 0.814255, A[176,13] = -1.676726, A[179,13] = 2.263853, A[182,13] = -1.576573, A[183,13] = -0.430005, norm col = 4.451532 Col 14: A[28,14] = -1.565728, A[33,14] = 1.299645, A[35,14] = -0.314642, A[43,14] = -1.309032, A[64,14] = -0.429384, A[66,14] = 2.366588, A[70,14] = -0.439853, A[78,14] = 0.233694, A[93,14] = -0.853007, A[124,14] = -0.715146, A[126,14] = -1.065915, A[130,14] = -0.675298, A[137,14] = -0.145184, A[140,14] = 1.996538, A[153,14] = -0.555419, A[158,14] = -2.988613, A[172,14] = 0.814364, norm col = 5.359881 Col 15: A[0,15] = -0.220371, A[9,15] = -0.863762, A[10,15] = 1.129614, A[11,15] = 1.168249, A[34,15] = -0.024954, A[43,15] = -0.693928, A[50,15] = -1.159928, A[66,15] = 1.076207, A[87,15] = -0.893210, A[91,15] = -2.160995, A[100,15] = -0.338497, A[118,15] = 1.681147, A[122,15] = 0.576575, A[128,15] = -0.969305, A[130,15] = -2.624801, A[137,15] = 0.549142, A[141,15] = -0.352703, A[143,15] = -0.325695, A[157,15] = -0.079881, A[164,15] = 0.948142, A[172,15] = 1.669309, norm col = 5.216839 Col 16: A[3,16] = -1.710671, A[7,16] = -1.542006, A[10,16] = 0.959852, A[22,16] = 0.839011, A[54,16] = 0.781853, A[65,16] = 0.597034, A[100,16] = -0.960164, A[108,16] = 0.478297, A[110,16] = -0.142541, A[127,16] = -0.445685, A[128,16] = 1.122670, A[129,16] = 0.180852, A[131,16] = 0.835357, A[135,16] = 0.372525, A[156,16] = -0.285335, A[160,16] = 0.101180, A[168,16] = -0.577225, A[178,16] = -1.132877, norm col = 3.620049 Col 17: A[17,17] = 1.705469, A[18,17] = 1.443045, A[31,17] = 1.252224, A[32,17] = 1.530901, A[37,17] = 0.172339, A[40,17] = 1.670376, A[41,17] = 0.110732, A[54,17] = 0.280302, A[57,17] = 1.477067, A[61,17] = -0.739222, A[64,17] = -0.935028, A[67,17] = 0.608229, A[72,17] = 0.062423, A[75,17] = 1.588432, A[78,17] = -1.711028, A[87,17] = 0.177418, A[125,17] = 0.944507, A[135,17] = -0.381642, A[142,17] = -2.235563, A[152,17] = -0.345052, A[163,17] = 0.824403, A[169,17] = -1.180647, A[179,17] = -1.120815, A[181,17] = 0.196149, norm col = 5.549300 Col 18: A[4,18] = 1.803046, A[10,18] = -1.187326, A[12,18] = -1.168346, A[66,18] = 0.321678, A[67,18] = 1.339995, A[78,18] = 1.379822, A[86,18] = 0.695699, A[103,18] = 0.038815, A[104,18] = 0.892005, A[126,18] = 1.188766, A[132,18] = 1.734664, A[139,18] = -0.917930, A[145,18] = 0.192010, A[155,18] = -1.300792, A[163,18] = 0.598798, A[165,18] = -0.595540, A[166,18] = -0.046248, A[175,18] = 1.491005, norm col = 4.587169 Col 19: A[21,19] = -0.662199, A[26,19] = -0.528363, A[33,19] = -1.032685, A[44,19] = 0.376763, A[50,19] = -0.375709, A[67,19] = 0.885911, A[68,19] = -0.366406, A[86,19] = 0.592036, A[104,19] = -0.516129, A[106,19] = 0.383933, A[114,19] = -1.328131, A[119,19] = -0.226637, A[125,19] = 0.192256, A[133,19] = -0.378280, A[139,19] = 0.335196, A[147,19] = -0.317346, A[148,19] = -0.095993, A[163,19] = -0.748969, A[169,19] = 1.453182, A[173,19] = 0.191210, A[177,19] = 2.072697, A[178,19] = 1.648894, norm col = 3.961366 Col 20: A[54,20] = 0.330227, A[78,20] = 1.820904, A[84,20] = -1.742970, A[95,20] = -0.395139, A[98,20] = 0.617020, A[110,20] = -0.168187, A[159,20] = 1.203649, A[163,20] = 1.082557, A[164,20] = 1.057728, A[179,20] = 0.410239, norm col = 3.306903 Col 21: A[33,21] = 2.562215, A[43,21] = -1.625681, A[58,21] = -0.348406, A[71,21] = -0.160996, A[85,21] = 0.051947, A[101,21] = -0.370658, A[104,21] = 1.416447, A[110,21] = 0.132962, A[116,21] = -0.365406, A[118,21] = 0.299341, A[124,21] = -0.964267, A[129,21] = -0.321790, A[147,21] = -0.677322, A[151,21] = 0.988040, A[156,21] = 0.647870, A[158,21] = 0.094470, A[165,21] = -0.068870, A[167,21] = 0.057045, norm col = 3.827180 Col 22: A[2,22] = 0.544001, A[9,22] = 0.511505, A[14,22] = -1.484276, A[17,22] = 0.301055, A[47,22] = 0.221679, A[53,22] = -1.119173, A[56,22] = -0.018051, A[61,22] = 0.039302, A[76,22] = -1.312342, A[77,22] = -0.142839, A[95,22] = -1.811841, A[100,22] = -1.204969, A[104,22] = -1.194682, A[111,22] = -1.453131, A[113,22] = -0.222115, A[145,22] = 0.656455, A[146,22] = -0.157161, A[157,22] = -0.312462, A[173,22] = -1.495752, A[174,22] = -0.296100, norm col = 4.135047 Col 23: A[3,23] = -1.755952, A[18,23] = -1.141711, A[24,23] = 0.470699, A[27,23] = 0.575074, A[34,23] = -1.622918, A[38,23] = -0.648561, A[43,23] = 0.063324, A[50,23] = -0.310260, A[53,23] = 0.026704, A[57,23] = 1.469390, A[63,23] = 0.059517, A[100,23] = 0.557447, A[103,23] = -0.745491, A[109,23] = 0.549668, A[110,23] = -0.864975, A[117,23] = 0.002147, A[138,23] = -0.200222, A[147,23] = 1.017003, A[155,23] = 1.657480, A[156,23] = 0.996295, A[160,23] = -0.762227, A[163,23] = -0.957598, A[178,23] = -0.933849, norm col = 4.399816 Col 24: A[0,24] = -0.724022, A[7,24] = 1.840297, A[47,24] = -1.221739, A[70,24] = 1.788319, A[78,24] = -0.809621, A[104,24] = 1.621797, A[107,24] = 0.229395, A[113,24] = 1.072263, A[114,24] = 1.759571, A[116,24] = 0.086036, A[150,24] = 0.977758, A[182,24] = 0.252918, norm col = 4.148877 Col 25: A[14,25] = -0.804688, A[17,25] = -0.902866, A[19,25] = 0.342550, A[28,25] = -0.629667, A[31,25] = -0.271430, A[48,25] = 0.227880, A[56,25] = -0.910038, A[57,25] = -0.259637, A[64,25] = -0.359509, A[68,25] = -0.901133, A[81,25] = 2.615027, A[86,25] = 0.294160, A[93,25] = 0.314733, A[95,25] = 0.486512, A[99,25] = -0.196455, A[109,25] = -0.192589, A[123,25] = 0.147510, A[124,25] = 0.002162, A[130,25] = 0.667301, A[138,25] = 0.676507, A[147,25] = -1.041103, A[149,25] = 0.207981, A[172,25] = -0.919917, norm col = 3.764762 Col 26: A[0,26] = -0.563937, A[14,26] = -0.063795, A[16,26] = 1.636952, A[27,26] = 0.182067, A[29,26] = 0.310964, A[41,26] = -0.941336, A[49,26] = -2.116556, A[51,26] = 0.554702, A[52,26] = -0.202821, A[57,26] = -1.846486, A[64,26] = 0.427471, A[68,26] = 0.505934, A[79,26] = -0.232782, A[87,26] = 0.106363, A[113,26] = 1.819529, A[126,26] = -1.967074, A[143,26] = 0.236517, A[146,26] = -0.174766, A[150,26] = -0.027971, A[173,26] = -0.732131, A[177,26] = 0.350979, A[180,26] = 0.712531, norm col = 4.603722 Col 27: A[4,27] = -0.760328, A[6,27] = 0.436939, A[33,27] = 1.005354, A[37,27] = -0.042042, A[39,27] = 0.695454, A[49,27] = -0.632282, A[65,27] = 0.163487, A[66,27] = 0.946050, A[77,27] = -0.023302, A[87,27] = 0.301766, A[93,27] = -1.157056, A[97,27] = -0.369886, A[108,27] = -1.383878, A[114,27] = -1.126602, A[134,27] = 0.042800, A[149,27] = -0.353434, A[158,27] = -0.644785, A[166,27] = 0.124892, A[177,27] = 1.001462, A[178,27] = 1.056285, A[181,27] = 0.602317, norm col = 3.373097 Col 28: A[3,28] = -0.133899, A[4,28] = -0.082469, A[5,28] = -0.518853, A[16,28] = -0.285819, A[35,28] = 0.702679, A[51,28] = 0.366347, A[57,28] = -0.885192, A[74,28] = -1.475473, A[85,28] = -0.481794, A[99,28] = -0.047377, A[112,28] = -1.398056, A[116,28] = -2.639044, A[123,28] = 1.644508, A[133,28] = -0.700697, A[135,28] = 0.269300, A[150,28] = 0.011902, A[159,28] = 0.082117, norm col = 4.048760 Col 29: A[48,29] = 0.362707, A[55,29] = -0.319633, A[64,29] = 1.505142, A[70,29] = 0.443872, A[71,29] = 0.144066, A[73,29] = -1.361259, A[76,29] = -0.047821, A[83,29] = 0.202138, A[84,29] = 0.033576, A[118,29] = 0.322959, A[148,29] = 0.022423, A[181,29] = -0.442250, A[183,29] = 0.788937, A[184,29] = 0.743258, norm col = 2.467690 Col 30: A[8,30] = -1.218901, A[11,30] = -0.415589, A[28,30] = 0.157355, A[34,30] = -0.176467, A[70,30] = -0.767397, A[76,30] = -1.860561, A[79,30] = 0.030345, A[102,30] = -0.177908, A[114,30] = -0.056013, A[118,30] = 1.463076, A[137,30] = -0.813011, A[146,30] = -0.232422, A[149,30] = -0.474979, A[152,30] = -0.400251, A[174,30] = 2.003269, A[183,30] = 0.227754, norm col = 3.620358 Col 31: A[14,31] = -0.075885, A[16,31] = 1.260068, A[29,31] = -0.714298, A[30,31] = -0.922311, A[66,31] = 2.153572, A[83,31] = 0.286416, A[87,31] = -0.902352, A[92,31] = 1.068089, A[121,31] = -0.890376, A[132,31] = -1.478052, A[145,31] = -0.639138, norm col = 3.607669 Col 32: A[3,32] = -0.344556, A[12,32] = 1.496575, A[24,32] = -0.376605, A[40,32] = -1.007589, A[66,32] = 0.960331, A[80,32] = -0.143142, A[85,32] = -0.958337, A[106,32] = 0.317805, A[111,32] = 0.347999, A[112,32] = 0.279719, A[117,32] = -1.082825, A[127,32] = 0.967217, A[149,32] = -0.526266, A[154,32] = 0.178592, A[157,32] = 0.761217, A[161,32] = 0.357359, A[168,32] = -0.806407, A[171,32] = 0.545845, A[174,32] = -0.826750, A[175,32] = -0.929543, norm col = 3.361077 Col 33: A[16,33] = 0.174423, A[28,33] = -1.416836, A[33,33] = 1.987061, A[40,33] = -0.514080, A[45,33] = 0.588124, A[48,33] = -0.707475, A[59,33] = 0.029932, A[64,33] = 1.297335, A[66,33] = 1.733914, A[68,33] = -0.100085, A[75,33] = 0.697018, A[79,33] = -1.278330, A[90,33] = 0.053353, A[125,33] = -2.565745, A[146,33] = 0.427264, A[148,33] = -1.339351, A[170,33] = -0.913352, A[178,33] = 0.640601, A[182,33] = -1.129764, A[184,33] = 1.968581, norm col = 5.373632 Col 34: A[14,34] = 0.384077, A[19,34] = -0.347713, A[23,34] = -1.091064, A[51,34] = -0.931257, A[62,34] = -0.283091, A[81,34] = -0.506409, A[95,34] = -1.044486, A[113,34] = -0.339165, A[125,34] = -1.394066, A[132,34] = 0.558988, A[180,34] = 0.327576, norm col = 2.496367 Col 35: A[23,35] = -1.071665, A[27,35] = 0.531595, A[32,35] = 0.218295, A[50,35] = -0.198643, A[57,35] = 0.782690, A[71,35] = -1.846566, A[79,35] = 1.172141, A[93,35] = -1.157621, A[99,35] = -0.262082, A[105,35] = -2.000649, A[114,35] = 0.880818, A[115,35] = -0.907625, A[122,35] = -0.112130, A[133,35] = 1.666506, A[136,35] = -0.076961, A[139,35] = -0.016047, A[149,35] = 0.758390, A[158,35] = -0.163543, A[162,35] = -0.362836, A[180,35] = -0.506875, norm col = 4.208558 Col 36: A[0,36] = 0.833240, A[25,36] = 0.094139, A[31,36] = -0.098167, A[39,36] = 0.151449, A[45,36] = -0.496493, A[47,36] = -0.390377, A[67,36] = -1.170771, A[84,36] = -1.656962, A[98,36] = 1.618047, A[117,36] = 0.787630, A[124,36] = -1.173688, A[125,36] = 1.120650, A[133,36] = -0.087217, A[135,36] = 1.026429, A[157,36] = -0.470475, A[161,36] = -0.069905, A[170,36] = -0.587465, A[176,36] = 0.930258, A[178,36] = -1.063487, norm col = 3.840779 Col 37: A[11,37] = -1.303001, A[13,37] = 0.749110, A[17,37] = 0.577245, A[19,37] = 0.975987, A[23,37] = 0.730766, A[27,37] = 1.379133, A[28,37] = 0.928824, A[41,37] = -0.143793, A[54,37] = 0.566123, A[55,37] = -0.926338, A[59,37] = -0.413635, A[70,37] = 0.663900, A[71,37] = 0.827249, A[87,37] = -0.605886, A[89,37] = 0.385254, A[96,37] = -0.500510, A[103,37] = 0.705869, A[139,37] = 0.048533, A[156,37] = -0.256261, A[162,37] = 1.402906, A[170,37] = 0.530915, A[172,37] = -1.038925, A[175,37] = 0.041648, A[177,37] = -0.925871, norm col = 3.854817 Col 38: A[2,38] = 0.599448, A[16,38] = 0.752306, A[21,38] = 0.723650, A[40,38] = 0.376068, A[59,38] = -0.215044, A[72,38] = 1.749292, A[73,38] = -0.057462, A[76,38] = 0.095701, A[88,38] = 0.433828, A[95,38] = 1.610822, A[105,38] = -0.706034, A[111,38] = 0.726965, A[113,38] = -1.117815, A[142,38] = -0.735266, A[149,38] = -1.156105, A[154,38] = 1.079638, A[161,38] = -0.462560, A[177,38] = -1.653900, norm col = 3.969977 Col 39: A[5,39] = 0.981358, A[6,39] = 0.906372, A[8,39] = -0.570200, A[35,39] = -1.154490, A[36,39] = -0.866922, A[37,39] = -0.013131, A[53,39] = -1.846225, A[66,39] = 0.818009, A[75,39] = -0.939133, A[89,39] = -0.286034, A[92,39] = 0.395921, A[95,39] = 0.246726, A[96,39] = -0.592040, A[98,39] = 1.450060, A[101,39] = -2.150821, A[102,39] = -0.926403, A[105,39] = -1.114228, A[118,39] = -0.350843, A[134,39] = 0.900688, A[167,39] = -0.483866, norm col = 4.449805 Col 40: A[0,40] = -0.578742, A[12,40] = -0.593588, A[18,40] = -0.273452, A[36,40] = -1.789606, A[40,40] = -1.136045, A[44,40] = 1.072032, A[55,40] = -0.500126, A[66,40] = -1.897397, A[71,40] = 0.114252, A[112,40] = 0.077497, A[117,40] = 0.491889, A[124,40] = -0.623880, A[139,40] = 0.042782, A[147,40] = -0.983032, A[157,40] = -0.064594, A[160,40] = -0.817294, norm col = 3.541950 Col 41: A[25,41] = -1.027868, A[46,41] = 1.385216, A[50,41] = 1.273430, A[54,41] = 2.178527, A[59,41] = 0.075287, A[70,41] = 0.220374, A[72,41] = 0.236592, A[87,41] = 1.759329, A[91,41] = -0.429419, A[92,41] = 0.633310, A[113,41] = -0.825143, A[143,41] = 0.293861, A[163,41] = 1.695485, A[165,41] = 0.057094, A[169,41] = -0.423171, A[179,41] = -1.586973, norm col = 4.413227 Col 42: A[7,42] = 0.321875, A[20,42] = 0.671879, A[27,42] = 1.686550, A[31,42] = 0.400683, A[33,42] = -0.148608, A[37,42] = -0.023753, A[40,42] = -0.912158, A[53,42] = -0.824538, A[64,42] = 0.058058, A[73,42] = 0.837827, A[78,42] = 0.364222, A[86,42] = 1.413028, A[96,42] = 0.708016, A[101,42] = 0.672240, A[107,42] = -0.268884, A[112,42] = -0.069889, A[118,42] = 1.486232, A[120,42] = 1.330776, A[122,42] = 0.190798, A[123,42] = -0.364379, A[133,42] = -1.111333, A[141,42] = 0.511243, A[157,42] = -1.117402, A[182,42] = 0.292797, norm col = 3.992411 Col 43: A[1,43] = -0.554225, A[4,43] = 1.176066, A[15,43] = 0.633489, A[21,43] = -0.104367, A[25,43] = 0.532960, A[48,43] = 0.248463, A[58,43] = 1.167500, A[66,43] = 2.945386, A[69,43] = -1.043165, A[94,43] = -0.183614, A[106,43] = 1.380952, A[119,43] = 1.667777, A[151,43] = -0.109263, A[160,43] = 0.411623, A[181,43] = -0.688351, A[184,43] = 0.764299, norm col = 4.420000 Col 44: A[0,44] = 0.157738, A[33,44] = 0.733777, A[36,44] = 1.098446, A[38,44] = -0.103601, A[43,44] = -0.770966, A[68,44] = 1.094546, A[81,44] = 0.663406, A[82,44] = 1.137315, A[96,44] = 0.578834, A[103,44] = -1.334973, A[124,44] = 2.549613, A[148,44] = 0.774279, A[149,44] = 2.263118, A[154,44] = 0.154488, A[155,44] = 1.010456, A[169,44] = -1.598692, A[171,44] = 0.781658, norm col = 4.884391 Col 45: A[3,45] = -0.089532, A[20,45] = 0.787135, A[26,45] = -0.037927, A[33,45] = 2.235628, A[34,45] = 0.746407, A[47,45] = -0.100472, A[61,45] = 0.234906, A[66,45] = 0.456805, A[74,45] = -0.046524, A[75,45] = 0.363138, A[98,45] = 0.082776, A[102,45] = -0.280847, A[117,45] = -0.948153, A[149,45] = -0.223839, A[150,45] = -1.905817, A[155,45] = -2.038972, A[158,45] = 1.297547, A[162,45] = 0.643133, A[164,45] = 1.562730, A[165,45] = -0.425163, A[173,45] = 1.143992, A[183,45] = -0.663024, norm col = 4.678140 Col 46: A[4,46] = 0.874086, A[12,46] = 0.459684, A[13,46] = 0.766113, A[15,46] = -0.169506, A[26,46] = 0.889076, A[30,46] = -0.490582, A[47,46] = -0.457960, A[53,46] = 1.605346, A[61,46] = 0.610707, A[76,46] = -0.723451, A[84,46] = 0.205226, A[88,46] = -0.094865, A[96,46] = -0.734612, A[102,46] = 0.339821, A[105,46] = 2.051501, A[126,46] = -0.591375, A[138,46] = 0.896218, A[145,46] = 1.341032, A[166,46] = 0.028904, A[167,46] = 0.111456, A[170,46] = 0.539388, norm col = 3.804699 Col 47: A[0,47] = -1.125759, A[22,47] = 1.459166, A[29,47] = 0.359442, A[47,47] = 0.764836, A[55,47] = 1.589521, A[56,47] = -0.016806, A[58,47] = 1.396625, A[71,47] = -2.057983, A[94,47] = 1.129000, A[103,47] = -1.402041, A[138,47] = 0.174472, A[172,47] = 0.363594, A[174,47] = 0.347017, A[184,47] = -0.747655, norm col = 4.111666 Col 48: A[14,48] = -1.008540, A[19,48] = 1.569683, A[21,48] = -0.932017, A[29,48] = -0.597204, A[53,48] = -0.180976, A[82,48] = -0.691983, A[96,48] = 1.825628, A[102,48] = 0.450999, A[109,48] = 0.404480, A[116,48] = 0.405463, A[122,48] = -0.266732, A[135,48] = 0.716622, A[148,48] = 0.168109, A[154,48] = 1.135602, A[161,48] = -1.111607, A[169,48] = -1.590361, A[176,48] = -0.448627, A[179,48] = 0.124932, A[180,48] = 0.311697, A[182,48] = -0.040886, norm col = 3.881423 Col 49: A[1,49] = 0.182293, A[5,49] = -0.237581, A[18,49] = 0.719539, A[36,49] = 2.200068, A[39,49] = 0.458614, A[41,49] = -1.438922, A[43,49] = -0.580624, A[59,49] = 0.063314, A[73,49] = 0.144409, A[110,49] = 0.386158, A[114,49] = 0.861843, A[117,49] = 2.108707, A[120,49] = 1.733756, A[128,49] = -0.963597, A[129,49] = -0.756565, A[153,49] = -1.487402, A[166,49] = 1.564458, norm col = 4.753501 Col 50: A[8,50] = 0.822991, A[23,50] = 0.487443, A[32,50] = -0.973024, A[40,50] = 0.563533, A[44,50] = 2.308095, A[63,50] = -0.514605, A[78,50] = -1.218704, A[81,50] = 0.241288, A[83,50] = -0.878800, A[84,50] = 2.385595, A[91,50] = 1.237189, A[94,50] = -0.052489, A[101,50] = -1.120765, A[108,50] = 0.845049, A[109,50] = 0.136149, A[110,50] = 0.488700, A[122,50] = 0.124359, A[128,50] = 0.047711, A[132,50] = -1.542136, A[133,50] = 0.700460, A[149,50] = -0.730247, A[183,50] = 1.800911, norm col = 5.118817 Col 51: A[1,51] = -0.147399, A[18,51] = -0.188446, A[60,51] = 0.028704, A[82,51] = 0.057602, A[93,51] = -0.754166, A[101,51] = 1.087060, A[104,51] = 1.170344, A[114,51] = 1.328704, A[116,51] = -0.455275, A[125,51] = 0.237428, A[133,51] = -0.158570, A[139,51] = -0.750240, A[141,51] = 0.122273, A[147,51] = 0.056289, A[148,51] = -0.834512, A[152,51] = -0.648370, A[161,51] = 0.123122, A[166,51] = -2.205971, A[168,51] = 1.339046, A[173,51] = 1.000250, norm col = 3.822117 Col 52: A[1,52] = -0.496007, A[7,52] = 1.136981, A[12,52] = 0.706351, A[26,52] = 0.281720, A[30,52] = -0.066117, A[34,52] = 0.055828, A[43,52] = 0.231748, A[46,52] = 0.110178, A[53,52] = -1.625993, A[55,52] = 0.124607, A[86,52] = 0.900867, A[87,52] = 1.286457, A[95,52] = 0.733243, A[103,52] = -1.301387, A[104,52] = 0.162834, A[106,52] = 0.946031, A[125,52] = 1.939107, A[126,52] = 0.380390, A[130,52] = 0.470692, A[135,52] = -1.582229, A[156,52] = 0.403522, A[174,52] = -0.430623, norm col = 4.176977 Col 53: A[27,53] = 0.699985, A[44,53] = 0.626663, A[54,53] = -1.833447, A[55,53] = 0.322385, A[63,53] = 1.254480, A[69,53] = -0.878100, A[98,53] = -1.008056, A[144,53] = 0.008790, A[163,53] = 0.298140, A[178,53] = -1.477918, A[179,53] = 1.591420, A[181,53] = 0.639705, norm col = 3.595017 Col 54: A[6,54] = 1.086846, A[18,54] = 0.820320, A[20,54] = -0.328124, A[42,54] = 2.248486, A[44,54] = -2.385878, A[62,54] = -0.310174, A[65,54] = 1.816484, A[73,54] = 0.736713, A[84,54] = 0.962165, A[99,54] = -0.354334, A[102,54] = 0.928717, A[114,54] = -1.188192, A[115,54] = 0.780231, A[124,54] = -1.504407, A[126,54] = -1.020438, A[128,54] = -0.088190, A[142,54] = -1.672730, A[146,54] = -0.410700, A[150,54] = -1.297016, A[153,54] = -2.094297, A[154,54] = 1.185872, A[158,54] = -0.955136, A[166,54] = -0.028851, A[177,54] = -0.310225, norm col = 5.945240 Col 55: A[4,55] = 0.027445, A[6,55] = 0.158761, A[12,55] = 1.213110, A[29,55] = -0.620272, A[40,55] = 0.563422, A[43,55] = -1.053724, A[48,55] = -0.800606, A[51,55] = -0.452298, A[53,55] = 0.615721, A[55,55] = 0.444214, A[87,55] = -1.284186, A[89,55] = 0.578161, A[124,55] = 0.969557, A[138,55] = 0.103240, A[141,55] = 0.674879, A[165,55] = -0.825728, A[170,55] = 0.409655, A[178,55] = -0.633505, A[184,55] = -0.627681, norm col = 3.125158 Col 56: A[5,56] = 1.150481, A[6,56] = 0.499095, A[15,56] = 1.993102, A[17,56] = 0.661722, A[22,56] = 0.503448, A[23,56] = 0.706755, A[38,56] = -1.401679, A[54,56] = -0.700622, A[57,56] = -1.798365, A[79,56] = -1.060844, A[110,56] = -0.138754, A[129,56] = 1.441624, A[134,56] = -0.710555, A[151,56] = 0.418251, A[167,56] = 1.033474, norm col = 4.170911 Col 57: A[6,57] = -1.812930, A[17,57] = -0.694357, A[19,57] = 0.597303, A[21,57] = -0.465555, A[27,57] = 0.087544, A[31,57] = -1.059267, A[60,57] = -1.403183, A[64,57] = -1.458043, A[76,57] = -0.444007, A[119,57] = 0.844868, A[135,57] = 0.312226, A[140,57] = -0.697282, A[141,57] = 0.254737, A[143,57] = -0.840945, A[157,57] = 0.605898, A[173,57] = -1.548953, A[174,57] = 1.095104, A[175,57] = -1.236786, A[177,57] = 0.403188, norm col = 4.182273 Col 58: A[4,58] = 0.698483, A[16,58] = 0.853524, A[17,58] = -0.620789, A[39,58] = 1.999175, A[53,58] = 0.635154, A[61,58] = -0.416658, A[69,58] = -0.638582, A[72,58] = -0.372854, A[82,58] = -0.617681, A[86,58] = -0.515064, A[89,58] = -0.150749, A[100,58] = 0.621217, A[104,58] = 0.767043, A[130,58] = -2.821213, A[139,58] = 1.138701, A[140,58] = 0.963947, A[175,58] = 1.026096, A[177,58] = 0.543489, norm col = 4.460878 Col 59: A[0,59] = -0.013425, A[11,59] = 0.332960, A[24,59] = 1.033757, A[34,59] = -1.357535, A[35,59] = 1.154216, A[46,59] = 0.209001, A[58,59] = -0.696798, A[66,59] = 1.112719, A[72,59] = -1.858395, A[74,59] = -0.262073, A[75,59] = 2.417749, A[76,59] = -0.178446, A[82,59] = -1.248091, A[88,59] = -0.650475, A[95,59] = -1.521309, A[111,59] = -0.735864, A[113,59] = -0.050522, A[175,59] = 0.035903, norm col = 4.512472 Col 60: A[3,60] = -0.441950, A[8,60] = 0.026780, A[33,60] = 2.532903, A[38,60] = 0.333359, A[44,60] = -0.045075, A[50,60] = 0.321977, A[70,60] = 0.663547, A[73,60] = -0.147945, A[90,60] = -0.312257, A[95,60] = 0.052765, A[97,60] = 0.238314, A[120,60] = -0.383689, A[146,60] = -1.456582, A[147,60] = 0.148380, A[151,60] = -0.417187, A[167,60] = 1.011874, A[181,60] = -2.279973, A[182,60] = -1.134464, norm col = 4.173945 norm A = 32.417339 finished normalizing A, time: 3.79e-03s Col 0: A[6,0] = -1.529965, A[8,0] = 2.066672, A[12,0] = -0.493763, A[67,0] = -5.916395, A[73,0] = -1.067253, A[74,0] = 1.661077, A[87,0] = 4.060228, A[106,0] = -0.741785, A[118,0] = 2.166506, A[119,0] = -1.468910, A[122,0] = -1.474405, A[134,0] = -0.002560, A[135,0] = 0.517077, A[144,0] = 0.830270, A[150,0] = 1.251378, A[154,0] = -3.153425, A[156,0] = -0.034627, A[165,0] = 0.631663, norm col = 9.202480 Col 1: A[1,1] = -4.428858, A[22,1] = 0.896628, A[27,1] = 3.657975, A[29,1] = -4.329675, A[30,1] = 0.833139, A[31,1] = -3.026114, A[32,1] = -4.167396, A[40,1] = -1.331230, A[41,1] = 0.949285, A[44,1] = 0.311251, A[54,1] = 0.948521, A[56,1] = -2.395309, A[67,1] = -0.572333, A[68,1] = 0.052955, A[96,1] = 0.138730, A[98,1] = 2.430541, A[118,1] = 3.565633, A[125,1] = -2.198169, A[136,1] = -2.746816, A[141,1] = 0.859268, A[142,1] = 1.952648, A[143,1] = 5.241929, A[168,1] = 1.702384, A[169,1] = 5.659099, A[180,1] = 1.280655, A[182,1] = -1.980026, norm col = 13.893616 Col 2: A[19,2] = -4.286146, A[22,2] = 0.502723, A[27,2] = -2.744469, A[39,2] = -0.548808, A[41,2] = -0.372912, A[46,2] = 1.377666, A[53,2] = 0.425525, A[57,2] = 0.890049, A[60,2] = 2.334787, A[62,2] = 0.657712, A[64,2] = -1.623181, A[71,2] = 2.754592, A[76,2] = 2.834739, A[100,2] = 0.394536, A[102,2] = 3.094242, A[112,2] = -0.936160, A[154,2] = -5.842400, norm col = 9.917129 Col 3: A[4,3] = 0.654268, A[7,3] = -0.460744, A[18,3] = -2.525799, A[24,3] = -3.081816, A[27,3] = 4.862650, A[31,3] = -5.096717, A[38,3] = -0.993202, A[42,3] = -5.824051, A[46,3] = 0.134074, A[51,3] = -4.740727, A[58,3] = -3.200401, A[60,3] = 2.898266, A[98,3] = 1.721996, A[112,3] = 4.620745, A[131,3] = -0.420398, A[133,3] = 3.711295, A[135,3] = 0.473524, A[142,3] = -2.494847, A[144,3] = 3.569865, A[157,3] = 1.474225, A[164,3] = -3.283569, A[167,3] = -2.079156, A[184,3] = -5.368943, norm col = 15.676208 Col 4: A[6,4] = 1.726600, A[8,4] = -1.545170, A[17,4] = 0.904931, A[32,4] = -5.850877, A[35,4] = 1.912459, A[39,4] = 1.202604, A[47,4] = 1.275574, A[54,4] = -1.471598, A[71,4] = 0.022468, A[95,4] = -3.126915, A[98,4] = -2.253303, A[101,4] = -4.529155, A[102,4] = -2.104406, A[104,4] = -1.486467, A[134,4] = 0.560303, A[140,4] = 0.162969, A[147,4] = -1.467056, A[158,4] = 4.974220, A[170,4] = -1.953559, A[171,4] = -4.711543, A[174,4] = -2.348966, norm col = 12.251201 Col 5: A[1,5] = -0.188119, A[22,5] = 2.660157, A[27,5] = 2.364398, A[31,5] = 0.123203, A[41,5] = -1.124638, A[48,5] = -1.050615, A[57,5] = -2.182772, A[59,5] = -0.818344, A[60,5] = 1.802364, A[62,5] = 3.837822, A[65,5] = 5.915805, A[66,5] = -2.569518, A[82,5] = -0.830443, A[109,5] = 3.086200, A[116,5] = 0.680411, A[141,5] = 0.341566, A[166,5] = -2.279565, A[167,5] = -1.090044, A[170,5] = -2.918595, A[173,5] = 1.049150, norm col = 10.338963 Col 6: A[0,6] = -1.552361, A[3,6] = 1.834912, A[16,6] = -2.352568, A[35,6] = 1.498436, A[39,6] = -1.153294, A[40,6] = -0.147634, A[59,6] = -0.548715, A[64,6] = 2.948700, A[66,6] = 2.568472, A[67,6] = 1.683396, A[91,6] = 5.913021, A[92,6] = 1.736180, A[102,6] = 1.697298, A[114,6] = 1.234357, A[116,6] = -4.141217, A[128,6] = 0.179330, A[145,6] = -3.703428, A[165,6] = 0.207427, A[183,6] = 2.388432, norm col = 10.600129 Col 7: A[13,7] = 0.272847, A[23,7] = 0.498891, A[25,7] = 0.047094, A[26,7] = -3.255419, A[37,7] = -0.292675, A[39,7] = 0.042529, A[67,7] = 2.225972, A[75,7] = 4.329788, A[85,7] = -5.914693, A[117,7] = -0.820152, A[139,7] = -0.383531, A[141,7] = -0.194221, A[176,7] = 3.107161, norm col = 8.955909 Col 8: A[19,8] = -1.178761, A[26,8] = -1.947315, A[33,8] = -0.835066, A[34,8] = -1.075888, A[43,8] = -1.329897, A[45,8] = 3.675530, A[56,8] = -5.776483, A[61,8] = 2.794970, A[62,8] = 1.477935, A[70,8] = 0.915415, A[76,8] = -1.320945, A[87,8] = -0.205854, A[91,8] = 1.607650, A[93,8] = 1.099989, A[118,8] = 2.092212, A[120,8] = 2.632868, A[146,8] = -1.949022, A[147,8] = -0.127124, norm col = 9.339294 Col 9: A[35,9] = -1.865530, A[47,9] = -0.971461, A[49,9] = 1.605391, A[52,9] = -5.775127, A[61,9] = -4.714896, A[64,9] = 0.510474, A[69,9] = -1.836601, A[89,9] = -0.983053, A[91,9] = 4.938940, A[93,9] = -3.668278, A[99,9] = 2.651762, A[120,9] = 4.589832, A[149,9] = -3.083310, A[168,9] = -0.176203, A[172,9] = -1.979417, norm col = 12.107327 Col 10: A[7,10] = 1.731252, A[8,10] = 3.984912, A[12,10] = -0.180203, A[17,10] = -3.737538, A[25,10] = 4.652669, A[40,10] = -1.411203, A[61,10] = -1.906739, A[67,10] = 2.744909, A[71,10] = 5.913610, A[72,10] = -2.387454, A[82,10] = -2.146925, A[83,10] = -1.281868, A[120,10] = -2.269024, A[123,10] = 1.003822, A[125,10] = -1.993208, A[140,10] = -0.092902, A[166,10] = 2.434533, A[178,10] = -2.697594, norm col = 11.745307 Col 11: A[0,11] = -0.947887, A[9,11] = -2.826604, A[42,11] = 0.637801, A[70,11] = 0.852534, A[78,11] = 0.629132, A[82,11] = 5.338164, A[95,11] = -0.110386, A[105,11] = -5.914445, A[112,11] = -0.698432, A[124,11] = -2.872780, A[166,11] = 1.364368, A[172,11] = -2.055463, A[183,11] = -0.370675, norm col = 9.427137 Col 12: A[33,12] = 2.468621, A[47,12] = 0.078722, A[49,12] = -0.441167, A[52,12] = -1.111009, A[70,12] = -2.760141, A[73,12] = -2.157098, A[84,12] = -2.287135, A[93,12] = 5.914762, A[100,12] = -5.144565, A[105,12] = -0.497190, A[119,12] = 1.619581, A[133,12] = -0.251572, A[140,12] = -2.547798, A[147,12] = -0.106251, A[152,12] = 0.650013, A[159,12] = 0.536514, A[162,12] = 3.560677, A[169,12] = 2.732246, A[170,12] = -2.090866, norm col = 11.006563 Col 13: A[18,13] = -0.941269, A[20,13] = 2.303692, A[44,13] = 0.518792, A[51,13] = -2.669190, A[66,13] = -2.574027, A[104,13] = -1.316426, A[121,13] = -4.054131, A[124,13] = 1.336494, A[136,13] = 0.927319, A[140,13] = 2.923731, A[145,13] = 1.673475, A[150,13] = 0.374602, A[152,13] = 1.765754, A[157,13] = 3.237769, A[169,13] = 1.894785, A[176,13] = -3.149051, A[179,13] = 5.893038, A[182,13] = -3.809042, A[183,13] = -1.038903, norm col = 11.399134 Col 14: A[28,14] = -2.480515, A[33,14] = 2.420118, A[35,14] = -0.585907, A[43,14] = -2.088998, A[64,14] = -0.861716, A[66,14] = 4.749422, A[70,14] = -0.882725, A[78,14] = 0.468993, A[93,14] = -1.711870, A[124,14] = -1.506838, A[126,14] = -1.312899, A[130,14] = -0.810912, A[137,14] = -0.418519, A[140,14] = 3.815813, A[153,14] = -1.037836, A[158,14] = -5.996335, A[172,14] = 1.636400, norm col = 10.151095 Col 15: A[0,15] = -0.784276, A[9,15] = -4.219006, A[10,15] = 2.338492, A[11,15] = 2.058649, A[34,15] = -0.063351, A[43,15] = -1.509737, A[50,15] = -2.342329, A[66,15] = 2.944511, A[87,15] = -2.443828, A[91,15] = -5.912498, A[100,15] = -0.926129, A[118,15] = 2.716179, A[122,15] = 1.656252, A[128,15] = -1.586858, A[130,15] = -4.297085, A[137,15] = 2.158151, A[141,15] = -0.919006, A[143,15] = -0.973467, A[157,15] = -0.188829, A[164,15] = 2.231146, A[172,15] = 4.573057, norm col = 12.240486 Col 16: A[3,16] = -4.438201, A[7,16] = -4.434770, A[10,16] = 4.428260, A[22,16] = 4.398447, A[54,16] = 3.518563, A[65,16] = 3.640321, A[100,16] = -5.854448, A[108,16] = 2.916341, A[110,16] = -0.869119, A[127,16] = -1.667860, A[128,16] = 4.095935, A[129,16] = 0.659818, A[131,16] = 3.873237, A[135,16] = 3.180438, A[156,16] = -1.503154, A[160,16] = 0.616786, A[168,16] = -2.781950, A[178,16] = -4.406616, norm col = 14.912954 Col 17: A[17,17] = 4.158497, A[18,17] = 3.924196, A[31,17] = 3.280238, A[32,17] = 4.010242, A[37,17] = 0.451448, A[40,17] = 3.334107, A[41,17] = 0.248584, A[54,17] = 0.584056, A[57,17] = 2.221101, A[61,17] = -2.086912, A[64,17] = -2.639696, A[67,17] = 1.717104, A[72,17] = 0.176228, A[75,17] = 4.484335, A[78,17] = -4.830439, A[87,17] = 0.500872, A[125,17] = 1.636535, A[135,17] = -1.508606, A[142,17] = -6.010462, A[152,17] = -0.906994, A[163,17] = 1.838506, A[169,17] = -2.634592, A[179,17] = -2.797814, A[181,17] = 0.489632, norm col = 13.945529 Col 18: A[4,18] = 4.419108, A[10,18] = -3.787759, A[12,18] = -2.353813, A[66,18] = 1.356267, A[67,18] = 5.649724, A[78,18] = 5.817643, A[86,18] = 2.933224, A[103,18] = 0.163654, A[104,18] = 3.760897, A[126,18] = 3.076175, A[132,18] = 5.561609, A[139,18] = -5.559220, A[145,18] = 0.884383, A[155,18] = -4.738486, A[163,18] = 1.994347, A[165,18] = -2.159594, A[166,18] = -0.167708, A[175,18] = 4.271823, norm col = 15.850783 Col 19: A[21,19] = -3.961919, A[26,19] = -1.788502, A[33,19] = -4.108766, A[44,19] = 1.284660, A[50,19] = -1.189051, A[67,19] = 3.798744, A[68,19] = -1.571130, A[86,19] = 2.538619, A[104,19] = -2.213135, A[106,19] = 1.646284, A[114,19] = -4.959036, A[119,19] = -0.946668, A[125,19] = 0.505964, A[133,19] = -1.233458, A[139,19] = 2.064566, A[147,19] = -1.477041, A[148,19] = -0.446787, A[163,19] = -2.536939, A[169,19] = 4.925310, A[173,19] = 0.557147, A[177,19] = 5.669795, A[178,19] = 4.510495, norm col = 13.682069 Col 20: A[54,20] = 0.791619, A[78,20] = 5.914141, A[84,20] = -5.661018, A[95,20] = -1.283377, A[98,20] = 2.004027, A[110,20] = -0.546258, A[159,20] = 3.908430, A[163,20] = 2.777484, A[164,20] = 2.954714, A[179,20] = 1.178138, norm col = 10.330586 Col 21: A[33,21] = 5.852229, A[43,21] = -3.182122, A[58,21] = -0.857625, A[71,21] = -0.396302, A[85,21] = 0.127871, A[101,21] = -0.912401, A[104,21] = 3.486682, A[110,21] = 0.327294, A[116,21] = -0.531157, A[118,21] = 0.435124, A[124,21] = -2.492086, A[129,21] = -0.473963, A[147,21] = -1.809743, A[151,21] = 2.465300, A[156,21] = 1.377869, A[158,21] = 0.232489, A[165,21] = -0.145806, A[167,21] = 0.110992, norm col = 8.753604 Col 22: A[2,22] = 3.691234, A[9,22] = 2.980702, A[14,22] = -4.215039, A[17,22] = 0.848746, A[47,22] = 0.534064, A[53,22] = -2.696290, A[56,22] = -0.043488, A[61,22] = 0.128287, A[76,22] = -4.283677, A[77,22] = -0.466247, A[95,22] = -5.914112, A[100,22] = -3.933194, A[104,22] = -3.899615, A[111,22] = -4.743231, A[113,22] = -0.631326, A[145,22] = 2.340814, A[146,22] = -0.556830, A[157,22] = -0.881201, A[173,22] = -3.317718, A[174,22] = -0.656777, norm col = 13.179252 Col 23: A[3,23] = -2.901036, A[18,23] = -4.270099, A[24,23] = 3.035907, A[27,23] = 1.762671, A[34,23] = -5.846970, A[38,23] = -2.336603, A[43,23] = 0.195513, A[50,23] = -0.889130, A[53,23] = 0.076527, A[57,23] = 3.038897, A[63,23] = 0.231089, A[100,23] = 2.164432, A[103,23] = -2.894563, A[109,23] = 2.134230, A[110,23] = -3.358487, A[117,23] = 0.004922, A[138,23] = -1.116691, A[147,23] = 4.286199, A[155,23] = 5.560276, A[156,23] = 3.342228, A[160,23] = -2.958847, A[163,23] = -2.937108, A[178,23] = -2.313123, norm col = 14.215429 Col 24: A[0,24] = -3.114408, A[7,24] = 2.870511, A[47,24] = -2.981981, A[70,24] = 5.913871, A[78,24] = -2.677372, A[104,24] = 5.363191, A[107,24] = 0.758595, A[113,24] = 3.087698, A[114,24] = 5.066878, A[116,24] = 0.168014, A[150,24] = 3.277493, A[182,24] = 0.686393, norm col = 12.031687 Col 25: A[14,25] = -1.583850, A[17,25] = -1.764230, A[19,25] = 0.456531, A[28,25] = -1.124572, A[31,25] = -0.569798, A[48,25] = 0.380518, A[56,25] = -1.519596, A[57,25] = -0.312877, A[64,25] = -0.813352, A[68,25] = -2.038720, A[81,25] = 5.916232, A[86,25] = 0.665507, A[93,25] = 0.712051, A[95,25] = 1.100684, A[99,25] = -0.444460, A[109,25] = -0.435713, A[123,25] = 0.350384, A[124,25] = 0.005134, A[130,25] = 0.903339, A[138,25] = 2.198476, A[147,25] = -2.556654, A[149,25] = 0.476953, A[172,25] = -2.083869, norm col = 8.319725 Col 26: A[0,26] = -2.698582, A[14,26] = -0.204179, A[16,26] = 4.341228, A[27,26] = 0.528746, A[29,26] = 0.903077, A[41,26] = -2.753734, A[49,26] = -5.746944, A[51,26] = 1.506146, A[52,26] = -0.550707, A[57,26] = -3.618197, A[64,26] = 1.572585, A[68,26] = 1.861237, A[79,26] = -0.856363, A[87,26] = 0.391288, A[113,26] = 5.828724, A[126,26] = -4.441392, A[143,26] = 0.950521, A[146,26] = -0.697870, A[150,26] = -0.104303, A[173,26] = -1.830235, A[177,26] = 0.823703, A[180,26] = 2.317751, norm col = 12.444445 Col 27: A[4,27] = -1.888349, A[6,27] = 1.075991, A[33,27] = 3.985570, A[37,27] = -0.166668, A[39,27] = 2.757018, A[49,27] = -1.993829, A[65,27] = 0.698490, A[66,27] = 4.041957, A[77,27] = -0.099557, A[87,27] = 1.289281, A[93,27] = -4.943472, A[97,27] = -1.580321, A[108,27] = -5.912556, A[114,27] = -4.191357, A[134,27] = 0.256045, A[149,27] = -1.530627, A[158,27] = -2.754168, A[166,27] = 0.458934, A[177,27] = 2.729568, A[178,27] = 2.878994, A[181,27] = 2.275400, norm col = 12.700090 Col 28: A[3,28] = -0.195458, A[4,28] = -0.164463, A[5,28] = -1.481423, A[16,28] = -0.706864, A[35,28] = 2.236800, A[51,28] = 0.927615, A[57,28] = -1.617528, A[74,28] = -5.061825, A[85,28] = -1.652866, A[99,28] = -0.162533, A[112,28] = -4.796235, A[116,28] = -5.346359, A[123,28] = 5.923328, A[133,28] = -1.827963, A[135,28] = 1.293607, A[150,28] = 0.041387, A[159,28] = 0.281648, norm col = 11.462516 Col 29: A[48,29] = 1.051693, A[55,29] = -0.926796, A[64,29] = 5.913041, A[70,29] = 1.743778, A[71,29] = 0.565971, A[73,29] = -5.347788, A[76,29] = -0.187866, A[83,29] = 0.794112, A[84,29] = 0.131907, A[118,29] = 0.749233, A[148,29] = 0.095615, A[181,29] = -1.536233, A[183,29] = 2.543559, A[184,29] = 2.396288, norm col = 9.204058 Col 30: A[8,30] = -4.215570, A[11,30] = -0.850783, A[28,30] = 0.394833, A[34,30] = -0.520454, A[70,30] = -2.439190, A[76,30] = -5.913838, A[79,30] = 0.096452, A[102,30] = -0.565485, A[114,30] = -0.155032, A[118,30] = 2.746172, A[137,30] = -3.711948, A[146,30] = -0.801885, A[149,30] = -1.530323, A[152,30] = -1.184533, A[174,30] = 4.326882, A[183,30] = 0.594098, norm col = 10.246012 Col 31: A[14,31] = -0.181334, A[16,31] = 2.494974, A[29,31] = -1.548781, A[30,31] = -2.350577, A[66,31] = 5.915110, A[83,31] = 0.786684, A[87,31] = -2.478446, A[92,31] = 2.933668, A[121,31] = -2.382291, A[132,31] = -3.087127, A[145,31] = -1.917741, norm col = 9.133543 Col 32: A[3,32] = -0.896971, A[12,32] = 4.375153, A[24,32] = -3.827449, A[40,32] = -4.358503, A[66,32] = 5.875427, A[80,32] = -0.875761, A[85,32] = -5.863226, A[106,32] = 1.944373, A[111,32] = 2.129100, A[112,32] = 1.711358, A[117,32] = -3.912118, A[127,32] = 3.631892, A[149,32] = -3.263673, A[154,32] = 1.017349, A[157,32] = 4.023785, A[161,32] = 1.727106, A[168,32] = -3.899747, A[171,32] = 3.343801, A[174,32] = -3.437181, A[175,32] = -3.864540, norm col = 15.716023 Col 33: A[16,33] = 0.398328, A[28,33] = -3.543189, A[33,33] = 5.840799, A[40,33] = -1.151420, A[45,33] = 1.481516, A[48,33] = -1.654163, A[59,33] = 0.094819, A[64,33] = 4.109788, A[66,33] = 5.492815, A[68,33] = -0.317056, A[75,33] = 2.208061, A[79,33] = -4.049584, A[90,33] = 0.169015, A[125,33] = -4.988517, A[146,33] = 1.469174, A[148,33] = -4.605441, A[170,33] = -2.897064, A[178,33] = 1.294603, A[182,33] = -2.937116, A[184,33] = 5.117838, norm col = 14.652664 Col 34: A[14,34] = 1.888169, A[19,34] = -1.157455, A[23,34] = -4.275707, A[51,34] = -3.883959, A[62,34] = -1.599676, A[81,34] = -2.861587, A[95,34] = -5.902125, A[113,34] = -1.668873, A[125,34] = -4.834814, A[132,34] = 2.401982, A[180,34] = 1.636714, norm col = 10.884086 Col 35: A[23,35] = -2.197209, A[27,35] = 1.240648, A[32,35] = 0.598823, A[50,35] = -0.433444, A[57,35] = 1.232506, A[71,35] = -5.459155, A[79,35] = 3.465298, A[93,35] = -3.422371, A[99,35] = -0.774816, A[105,35] = -5.914685, A[114,35] = 2.267532, A[115,35] = -2.336544, A[122,35] = -0.348045, A[133,35] = 3.746526, A[136,35] = -0.318583, A[139,35] = -0.068146, A[149,35] = 2.272672, A[158,35] = -0.483382, A[162,35] = -0.847358, A[180,35] = -1.325002, norm col = 11.413886 Col 36: A[0,36] = 3.868179, A[25,36] = 0.265226, A[31,36] = -0.325086, A[39,36] = 0.501534, A[45,36] = -1.409036, A[47,36] = -1.028308, A[67,36] = -4.178412, A[84,36] = -5.913596, A[98,36] = 5.774713, A[117,36] = 1.659958, A[124,36] = -4.397903, A[125,36] = 2.454708, A[133,36] = -0.236701, A[135,36] = 5.129307, A[157,36] = -1.450721, A[161,36] = -0.197082, A[170,36] = -2.099298, A[176,36] = 2.117994, A[178,36] = -2.421325, norm col = 13.251334 Col 37: A[11,37] = -4.378349, A[13,37] = 4.375887, A[17,37] = 2.601115, A[19,37] = 2.999561, A[23,37] = 2.644032, A[27,37] = 5.680018, A[28,37] = 3.825401, A[41,37] = -0.596544, A[54,37] = 2.179949, A[55,37] = -3.567019, A[59,37] = -2.158010, A[70,37] = 3.463687, A[71,37] = 4.315910, A[87,37] = -3.161019, A[89,37] = 2.009943, A[96,37] = -2.611254, A[103,37] = 3.682650, A[139,37] = 0.363708, A[156,37] = -1.155117, A[162,37] = 5.781772, A[170,37] = 2.773411, A[172,37] = -5.427167, A[175,37] = 0.147653, A[177,37] = -3.081545, norm col = 16.644915 Col 38: A[2,38] = 4.212754, A[16,38] = 1.833477, A[21,38] = 3.413570, A[40,38] = 0.898907, A[59,38] = -0.727009, A[72,38] = 5.913909, A[73,38] = -0.194265, A[76,38] = 0.323539, A[88,38] = 1.466662, A[95,38] = 5.445778, A[105,38] = -2.386921, A[111,38] = 2.457683, A[113,38] = -3.290706, A[142,38] = -2.367272, A[149,38] = -3.961802, A[154,38] = 3.398447, A[161,38] = -1.235313, A[177,38] = -3.567003, norm col = 13.064740 Col 39: A[5,39] = 2.246178, A[6,39] = 1.436730, A[8,39] = -1.706270, A[35,39] = -2.946065, A[36,39] = -2.212237, A[37,39] = -0.033508, A[53,39] = -3.747505, A[66,39] = 2.249657, A[75,39] = -2.582766, A[89,39] = -0.786640, A[92,39] = 1.088845, A[95,39] = 0.678537, A[96,39] = -1.628204, A[98,39] = 3.987898, A[101,39] = -5.915103, A[102,39] = -2.547757, A[105,39] = -3.064307, A[118,39] = -0.569779, A[134,39] = 3.468350, A[167,39] = -1.051834, norm col = 11.598268 Col 40: A[0,40] = -2.346567, A[12,40] = -0.884122, A[18,40] = -0.821058, A[36,40] = -5.176094, A[40,40] = -2.503700, A[44,40] = 2.657225, A[55,40] = -1.150615, A[66,40] = -5.914378, A[71,40] = 0.356134, A[112,40] = 0.241564, A[117,40] = 0.905427, A[124,40] = -2.041763, A[139,40] = 0.191553, A[147,40] = -3.326045, A[157,40] = -0.173960, A[160,40] = -2.546989, norm col = 10.304258 Col 41: A[25,41] = -2.724462, A[46,41] = 3.698479, A[50,41] = 3.155809, A[54,41] = 5.398816, A[59,41] = 0.252786, A[70,41] = 0.739939, A[72,41] = 0.794393, A[87,41] = 5.907219, A[91,41] = -1.441842, A[92,41] = 2.126436, A[113,41] = -2.412525, A[143,41] = 1.077878, A[163,41] = 4.497037, A[165,41] = 0.164879, A[169,41] = -1.123093, A[179,41] = -4.711519, norm col = 12.395100 Col 42: A[7,42] = 0.634718, A[20,42] = 4.244108, A[27,42] = 5.566162, A[31,42] = 1.554332, A[33,42] = -0.576483, A[37,42] = -0.092145, A[40,42] = -2.696218, A[53,42] = -2.544248, A[64,42] = 0.242723, A[73,42] = 3.502705, A[78,42] = 1.522705, A[86,42] = 5.907450, A[96,42] = 2.960005, A[101,42] = 2.810435, A[107,42] = -1.124123, A[112,42] = -0.292186, A[118,42] = 3.669198, A[120,42] = 5.419660, A[122,42] = 0.837484, A[123,42] = -1.599398, A[133,42] = -3.533089, A[141,42] = 2.035486, A[157,42] = -4.036142, A[182,42] = 1.004575, norm col = 14.610661 Col 43: A[1,43] = -1.379069, A[4,43] = 1.373375, A[15,43] = 0.611694, A[21,43] = -0.292538, A[25,43] = 0.845192, A[48,43] = 0.368396, A[58,43] = 2.345364, A[66,43] = 5.916919, A[69,43] = -2.095591, A[94,43] = -0.368859, A[106,43] = 2.774163, A[119,43] = 3.263694, A[151,43] = -0.222489, A[160,43] = 0.826705, A[181,43] = -1.222696, A[184,43] = 1.260034, norm col = 8.502900 Col 44: A[0,44] = 0.455603, A[33,44] = 1.511854, A[36,44] = 2.263208, A[38,44] = -0.213456, A[43,44] = -1.361310, A[68,44] = 2.430446, A[81,44] = 1.473098, A[82,44] = 2.525415, A[96,44] = 1.285305, A[103,44] = -2.964317, A[124,44] = 5.944018, A[148,44] = 1.866203, A[149,44] = 5.093809, A[154,44] = 0.319401, A[155,44] = 1.938550, A[169,44] = -2.805955, A[171,44] = 1.737887, norm col = 10.673457 Col 45: A[3,45] = -0.107460, A[20,45] = 3.354789, A[26,45] = -0.084454, A[33,45] = 5.851450, A[34,45] = 1.953618, A[47,45] = -0.209177, A[61,45] = 0.662621, A[66,45] = 1.288549, A[74,45] = -0.131233, A[75,45] = 1.024333, A[98,45] = 0.233493, A[102,45] = -0.792209, A[117,45] = -1.579371, A[149,45] = -0.640015, A[150,45] = -5.449223, A[155,45] = -4.969229, A[158,45] = 3.659243, A[162,45] = 1.433069, A[164,45] = 3.791325, A[165,45] = -1.031484, A[173,45] = 2.192821, A[183,45] = -1.534848, norm col = 12.188458 Col 46: A[4,46] = 1.464970, A[12,46] = 0.633296, A[13,46] = 2.473133, A[15,46] = -0.234908, A[26,46] = 2.023564, A[30,46] = -1.312429, A[47,46] = -0.974535, A[53,46] = 3.416166, A[61,46] = 1.760775, A[76,46] = -2.085834, A[84,46] = 0.591703, A[88,46] = -0.273511, A[96,46] = -2.118014, A[102,46] = 0.979762, A[105,46] = 5.914829, A[126,46] = -1.046464, A[138,46] = 3.711627, A[145,46] = 4.223785, A[166,46] = 0.071675, A[167,46] = 0.254002, A[170,46] = 1.557130, norm col = 10.519932 Col 47: A[0,47] = -4.208663, A[22,47] = 3.605766, A[29,47] = 0.815526, A[47,47] = 1.622443, A[55,47] = 3.371845, A[56,47] = -0.035651, A[58,47] = 4.014038, A[71,47] = -5.914848, A[94,47] = 3.244859, A[103,47] = -4.029603, A[138,47] = 0.720289, A[172,47] = 1.046337, A[174,47] = 0.677739, A[184,47] = -1.763474, norm col = 11.332694 Col 48: A[14,48] = -2.842441, A[19,48] = 2.995505, A[21,48] = -4.212812, A[29,48] = -1.527252, A[53,48] = -0.432713, A[82,48] = -2.241694, A[96,48] = 5.914156, A[102,48] = 1.461021, A[109,48] = 1.310321, A[116,48] = 0.775652, A[122,48] = -0.907212, A[135,48] = 3.250582, A[148,48] = 0.591126, A[154,48] = 3.425283, A[161,48] = -2.844646, A[169,48] = -4.072304, A[176,48] = -0.927146, A[179,48] = 0.357857, A[180,48] = 0.892831, A[182,48] = -0.108697, norm col = 11.476900 Col 49: A[1,49] = 0.647208, A[5,49] = -0.566757, A[18,49] = 1.986655, A[36,49] = 5.851358, A[39,49] = 1.219742, A[41,49] = -3.279696, A[43,49] = -1.323402, A[59,49] = 0.181478, A[73,49] = 0.413924, A[110,49] = 1.106858, A[114,49] = 2.151106, A[117,49] = 3.569262, A[120,49] = 4.840976, A[128,49] = -1.652656, A[129,49] = -1.297577, A[153,49] = -3.969585, A[166,49] = 3.856805, norm col = 11.410509 Col 50: A[8,50] = 2.220581, A[23,50] = 0.838273, A[32,50] = -2.238860, A[40,50] = 0.988018, A[44,50] = 4.551273, A[63,50] = -1.276097, A[78,50] = -3.022092, A[81,50] = 0.598336, A[83,50] = -2.179212, A[84,50] = 5.915701, A[91,50] = 3.067932, A[94,50] = -0.130160, A[101,50] = -2.779228, A[108,50] = 2.095517, A[109,50] = 0.337616, A[110,50] = 1.211858, A[122,50] = 0.323772, A[128,50] = 0.070792, A[132,50] = -2.907995, A[133,50] = 1.320852, A[149,50] = -1.835534, A[183,50] = 3.664948, norm col = 11.551597 Col 51: A[1,51] = -0.566512, A[18,51] = -0.563245, A[60,51] = 0.089067, A[82,51] = 0.178734, A[93,51] = -2.340107, A[101,51] = 3.373047, A[104,51] = 3.631470, A[114,51] = 3.590078, A[116,51] = -0.834216, A[125,51] = 0.452160, A[133,51] = -0.374156, A[139,51] = -3.343870, A[141,51] = 0.361319, A[147,51] = 0.189583, A[148,51] = -2.810679, A[152,51] = -1.873190, A[161,51] = 0.301788, A[166,51] = -5.887159, A[168,51] = 3.284190, A[173,51] = 2.109054, norm col = 10.834604 Col 52: A[1,52] = -1.639028, A[7,52] = 1.430705, A[12,52] = 0.900429, A[26,52] = 0.593305, A[30,52] = -0.163666, A[34,52] = 0.138198, A[43,52] = 0.491629, A[46,52] = 0.233731, A[53,52] = -3.201626, A[55,52] = 0.245355, A[86,52] = 2.403327, A[87,52] = 3.432003, A[95,52] = 1.956143, A[103,52] = -3.471833, A[104,52] = 0.434409, A[106,52] = 2.523816, A[125,52] = 3.175008, A[126,52] = 0.622834, A[130,52] = 0.751363, A[135,52] = -5.910339, A[156,52] = 0.930095, A[174,52] = -0.780655, norm col = 10.197146 Col 53: A[27,53] = 2.304997, A[44,53] = 2.078633, A[54,53] = -5.644720, A[55,53] = 0.992543, A[63,53] = 5.232849, A[69,53] = -3.662841, A[98,53] = -4.204931, A[144,53] = 0.040056, A[163,53] = 0.982407, A[178,53] = -3.932843, A[179,53] = 5.869679, A[181,53] = 2.359440, norm col = 12.546568 Col 54: A[6,54] = 1.877178, A[18,54] = 2.367834, A[20,54] = -1.485632, A[42,54] = 5.357802, A[44,54] = -5.685187, A[62,54] = -0.929462, A[65,54] = 5.443250, A[73,54] = 2.207624, A[84,54] = 2.883211, A[99,54] = -1.061791, A[102,54] = 2.782979, A[114,54] = -3.100417, A[115,54] = 2.035902, A[124,54] = -4.733100, A[126,54] = -1.876739, A[128,54] = -0.158126, A[142,54] = -4.773579, A[146,54] = -1.335860, A[150,54] = -3.939630, A[153,54] = -5.843255, A[154,54] = 3.308678, A[158,54] = -2.861476, A[166,54] = -0.074359, A[177,54] = -0.593042, norm col = 16.073334 Col 55: A[4,55] = 0.073449, A[6,55] = 0.421279, A[12,55] = 2.668654, A[29,55] = -2.254267, A[40,55] = 1.833943, A[43,55] = -3.857557, A[48,55] = -2.720409, A[51,55] = -1.536879, A[53,55] = 2.092182, A[55,55] = 1.509411, A[87,55] = -5.912124, A[89,55] = 2.661733, A[124,55] = 4.686438, A[138,55] = 0.682719, A[141,55] = 2.958918, A[165,55] = -3.269563, A[170,55] = 1.888366, A[178,55] = -1.860577, A[184,55] = -2.371485, norm col = 11.983833 Col 56: A[5,56] = 4.301067, A[6,56] = 1.292208, A[15,56] = 4.303376, A[17,56] = 2.567300, A[22,56] = 1.944390, A[23,56] = 2.201705, A[38,56] = -5.842254, A[54,56] = -2.322851, A[57,56] = -4.302832, A[79,56] = -4.765293, A[110,56] = -0.623279, A[129,56] = 3.874810, A[134,56] = -4.469166, A[151,56] = 1.904400, A[167,56] = 3.669456, norm col = 13.679360 Col 57: A[6,57] = -4.236100, A[17,57] = -2.431198, A[19,57] = 1.426418, A[21,57] = -2.633379, A[27,57] = 0.280162, A[31,57] = -3.984504, A[60,57] = -5.688387, A[64,57] = -5.910784, A[76,57] = -1.799967, A[119,57] = 3.336428, A[135,57] = 1.772290, A[140,57] = -2.691997, A[141,57] = 0.983463, A[143,57] = -3.724214, A[157,57] = 2.122181, A[173,57] = -4.267007, A[174,57] = 3.016757, A[175,57] = -3.407058, A[177,57] = 1.042712, norm col = 14.148430 Col 58: A[4,58] = 1.266946, A[16,58] = 1.919919, A[17,58] = -1.673036, A[39,58] = 5.788195, A[53,58] = 1.462773, A[61,58] = -1.300103, A[69,58] = -1.992578, A[72,58] = -1.163423, A[82,58] = -1.927358, A[86,58] = -1.607163, A[89,58] = -0.470383, A[100,58] = 1.938393, A[104,58] = 2.393415, A[130,58] = -5.267379, A[139,58] = 5.103736, A[140,58] = 2.864462, A[175,58] = 2.175689, A[177,58] = 1.081859, norm col = 11.604082 Col 59: A[0,59] = -0.042728, A[11,59] = 0.524713, A[24,59] = 4.201696, A[34,59] = -3.082093, A[35,59] = 2.620484, A[46,59] = 0.406649, A[58,59] = -1.704934, A[66,59] = 2.722615, A[72,59] = -4.547145, A[74,59] = -0.641243, A[75,59] = 5.915778, A[76,59] = -0.436624, A[82,59] = -3.053846, A[88,59] = -1.591591, A[95,59] = -3.722358, A[111,59] = -1.800522, A[113,59] = -0.107643, A[175,59] = 0.059696, norm col = 11.403041 Col 60: A[3,60] = -0.468250, A[8,60] = 0.072557, A[33,60] = 5.852163, A[38,60] = 0.770212, A[44,60] = -0.089250, A[50,60] = 0.591737, A[70,60] = 1.652249, A[73,60] = -0.368386, A[90,60] = -0.777529, A[95,60] = 0.131387, A[97,60] = 0.593409, A[120,60] = -0.930681, A[146,60] = -3.936848, A[147,60] = 0.401040, A[151,60] = -1.052974, A[167,60] = 1.991563, A[181,60] = -5.019828, A[182,60] = -2.318253, norm col = 9.562274 norm A = 93.915032 D[0] = 0.401695, D[1] = 0.421839, D[2] = 0.251357, D[3] = 1.227985, D[4] = 0.898854, D[5] = 0.627819, D[6] = 0.906531, D[7] = 1.107768, D[8] = 0.480210, D[9] = 0.292681, D[10] = 0.690565, D[11] = 0.811267, D[12] = 1.093495, D[13] = 0.466669, D[14] = 0.600587, D[15] = 1.087056, D[16] = 0.724810, D[17] = 0.604965, D[18] = 0.542440, D[19] = 0.886984, D[20] = 0.345818, D[21] = 0.374477, D[22] = 0.607718, D[23] = 0.753427, D[24] = 0.314549, D[25] = 0.661890, D[26] = 0.661890, D[27] = 0.661890, D[28] = 0.661890, D[29] = 0.661890, D[30] = 0.563118, D[31] = 0.563118, D[32] = 0.563118, D[33] = 0.563118, D[34] = 0.563118, D[35] = 0.563118, D[36] = 0.563118, D[37] = 0.563118, D[38] = 0.563118, D[39] = 0.563118, D[40] = 0.739022, D[41] = 0.657088, D[42] = 0.657088, D[43] = 0.657088, D[44] = 0.657088, D[45] = 0.657088, D[46] = 0.657088, D[47] = 0.707935, D[48] = 0.707935, D[49] = 0.707935, D[50] = 0.707935, D[51] = 0.707935, D[52] = 0.707935, D[53] = 0.707935, D[54] = 0.707935, D[55] = 0.707935, D[56] = 0.707935, D[57] = 0.980968, D[58] = 0.522508, D[59] = 0.522508, D[60] = 0.522508, D[61] = 0.522508, D[62] = 0.522508, D[63] = 0.522508, D[64] = 0.522508, D[65] = 0.522508, D[66] = 0.522508, D[67] = 0.522508, D[68] = 0.522508, D[69] = 0.522508, D[70] = 0.522508, D[71] = 0.522508, D[72] = 0.522508, D[73] = 0.522508, D[74] = 0.522508, D[75] = 0.522508, D[76] = 0.522508, D[77] = 0.522508, D[78] = 0.522508, D[79] = 0.522508, D[80] = 0.522508, D[81] = 0.522508, D[82] = 0.522508, D[83] = 0.522508, D[84] = 0.522508, D[85] = 0.522508, D[86] = 0.522508, D[87] = 0.522508, D[88] = 0.522508, D[89] = 0.522508, D[90] = 0.522508, D[91] = 0.522508, D[92] = 0.522508, D[93] = 0.522508, D[94] = 0.522508, D[95] = 0.522508, D[96] = 0.522508, D[97] = 0.522508, D[98] = 0.522508, D[99] = 0.522508, D[100] = 0.522508, D[101] = 0.522508, D[102] = 0.522508, D[103] = 0.522508, D[104] = 0.522508, D[105] = 0.522508, D[106] = 0.522508, D[107] = 0.522508, D[108] = 0.522508, D[109] = 0.522508, D[110] = 0.522508, D[111] = 0.522508, D[112] = 0.522508, D[113] = 0.600049, D[114] = 0.600049, D[115] = 0.600049, D[116] = 0.884826, D[117] = 0.884826, D[118] = 0.884826, D[119] = 0.536383, D[120] = 0.536383, D[121] = 0.536383, D[122] = 0.497668, D[123] = 0.497668, D[124] = 0.497668, D[125] = 0.851339, D[126] = 0.851339, D[127] = 0.851339, D[128] = 0.873239, D[129] = 0.873239, D[130] = 0.873239, D[131] = 0.687119, D[132] = 0.687119, D[133] = 0.687119, D[134] = 0.373166, D[135] = 0.373166, D[136] = 0.373166, D[137] = 0.363758, D[138] = 0.363758, D[139] = 0.363758, D[140] = 0.548658, D[141] = 0.548658, D[142] = 0.548658, D[143] = 0.478301, D[144] = 0.478301, D[145] = 0.478301, D[146] = 0.481375, D[147] = 0.481375, D[148] = 0.481375, D[149] = 0.515478, D[150] = 0.515478, D[151] = 0.515478, D[152] = 0.561181, D[153] = 0.561181, D[154] = 0.561181, D[155] = 0.604763, D[156] = 0.604763, D[157] = 0.604763, D[158] = 0.522631, D[159] = 0.522631, D[160] = 0.522631, D[161] = 0.661450, D[162] = 0.661450, D[163] = 0.661450, D[164] = 0.607514, D[165] = 0.607514, D[166] = 0.607514, D[167] = 0.661042, D[168] = 0.661042, D[169] = 0.661042, D[170] = 0.521844, D[171] = 0.521844, D[172] = 0.521844, D[173] = 0.768923, D[174] = 0.768923, D[175] = 0.768923, D[176] = 0.819052, D[177] = 0.819052, D[178] = 0.819052, D[179] = 0.590933, D[180] = 0.590933, D[181] = 0.590933, D[182] = 0.636689, D[183] = 0.636689, D[184] = 0.636689, SCS(norm) D = 8.402009 E[0] = 4.350703, E[1] = 2.772390, E[2] = 2.499196, E[3] = 2.773271, E[4] = 3.069181, E[5] = 3.929076, E[6] = 2.878828, E[7] = 3.241686, E[8] = 2.203413, E[9] = 1.733038, E[10] = 2.687922, E[11] = 3.105203, E[12] = 3.280664, E[13] = 3.250432, E[14] = 4.768247, E[15] = 3.497515, E[16] = 1.569409, E[17] = 3.389591, E[18] = 2.269619, E[19] = 2.231655, E[20] = 2.946268, E[21] = 3.887451, E[22] = 2.931617, E[23] = 2.464543, E[24] = 2.893676, E[25] = 4.229684, E[26] = 2.601172, E[27] = 2.239748, E[28] = 2.789336, E[29] = 2.435809, E[30] = 3.010588, E[31] = 3.483962, E[32] = 1.564079, E[33] = 3.020713, E[34] = 1.693445, E[35] = 3.236803, E[36] = 2.681252, E[37] = 1.834175, E[38] = 2.830509, E[39] = 3.479515, E[40] = 3.069912, E[41] = 2.849973, E[42] = 2.288904, E[43] = 4.763470, E[44] = 4.309479, E[45] = 3.392398, E[46] = 3.318992, E[47] = 3.329470, E[48] = 2.953903, E[49] = 3.338489, E[50] = 3.858933, E[51] = 3.083954, E[52] = 3.586943, E[53] = 2.294048, E[54] = 3.193376, E[55] = 2.078553, E[56] = 2.130290, E[57] = 2.360489, E[58] = 3.066750, E[59] = 3.910895, E[60] = 3.843022, SCS(norm) E = 24.093122 init_cone BLAS(func) = 'dfunc_' init_cone complete getting pre-conditioner finished getting pre-conditioner scs/linsys/gpu/indirect/private.c:270:scs_init_lin_sys_work ERROR_CUDA: no CUDA-capable device is detected ERROR: init_lin_sys_work failure Setup time: 1.01e-01s size of scs_int = 4, size of scs_float = 8 Failure:could not initialize work ----------------------------- Captured stderr call ----------------------------- ** On entry to cusparseCreateCsr() parameter number 5 (csrRowOffsets) had an illegal value: NULL pointer ** On entry to cusparseCreateDnVec() parameter number 3 (values) had an illegal value: NULL pointer ** On entry to cusparseCreateDnVec() parameter number 3 (values) had an illegal value: NULL pointer ** On entry to cusparseCreateCsr() parameter number 5 (csrRowOffsets) had an illegal value: NULL pointer _______________________ test_solve_infeasible[True-True] _______________________ use_indirect = True, gpu = True @pytest.mark.parametrize('use_indirect,gpu', flags) def test_solve_infeasible(use_indirect, gpu): data = tools.gen_infeasible(K, n=m // 3) sol = scs.solve(data, K, use_indirect=use_indirect, gpu=gpu, **params) y = sol['y'] > np.testing.assert_array_less(np.linalg.norm(data['A'].T @ y), 1e-3) E AssertionError: E Arrays are not less-ordered E E x and y nan location mismatch: E x: array(nan) E y: array(0.001) test/test_solve_random_cone_prob.py:71: AssertionError ----------------------------- Captured stdout call ----------------------------- m = 185 n = 61 max_iters = 5000 verbose = 1 normalize = 1 warm_start = 0 acceleration_lookback = 10 eps = 0.000010 alpha = 1.500000 rho_x = 0.001000 cg_rate = 2.000000 scale = 5.000000 write_data_filename = (null) num zeros = 10 num LP = 15 num SOCs = 4 soc array: 5 10 0 1 num SDCs = 6 sdc array: 3 4 0 0 1 10 num ep = 10 num ed = 10 num PCs = 4 pow array: -0.250000 0.500000 0.750000 -0.330000 ---------------------------------------------------------------------------- SCS v2.1.4 - Splitting Conic Solver (c) Brendan O'Donoghue, Stanford University, 2012 ---------------------------------------------------------------------------- Lin-sys: sparse-indirect GPU, nnz in A = 11285, CG tol ~ 1/iter^(2.00) eps = 1.00e-05, alpha = 1.50, max_iters = 5000, normalize = 1, scale = 5.00 acceleration_lookback = 10, rho_x = 1.00e-03 Variables n = 61, constraints m = 185 Cones: primal zero / dual free vars: 10 linear vars: 15 soc vars: 16, soc blks: 4 sd vars: 72, sd blks: 6 exp vars: 30, dual exp vars: 30 primal + dual power vars: 12 normalizing A finished normalizing A, time: 1.45e-03s D[0] = 1.183534, D[1] = 1.370542, D[2] = 1.431709, D[3] = 1.631556, D[4] = 1.046960, D[5] = 1.311706, D[6] = 1.250508, D[7] = 1.422242, D[8] = 1.254015, D[9] = 1.243046, D[10] = 1.248306, D[11] = 1.016429, D[12] = 1.087661, D[13] = 1.136307, D[14] = 1.006371, D[15] = 1.155372, D[16] = 1.371238, D[17] = 1.309417, D[18] = 1.156105, D[19] = 1.482529, D[20] = 1.442847, D[21] = 1.451075, D[22] = 1.211627, D[23] = 1.288849, D[24] = 1.273002, D[25] = 1.412843, D[26] = 1.412843, D[27] = 1.412843, D[28] = 1.412843, D[29] = 1.412843, D[30] = 1.106260, D[31] = 1.106260, D[32] = 1.106260, D[33] = 1.106260, D[34] = 1.106260, D[35] = 1.106260, D[36] = 1.106260, D[37] = 1.106260, D[38] = 1.106260, D[39] = 1.106260, D[40] = 1.258556, D[41] = 1.227933, D[42] = 1.227933, D[43] = 1.227933, D[44] = 1.227933, D[45] = 1.227933, D[46] = 1.227933, D[47] = 1.282905, D[48] = 1.282905, D[49] = 1.282905, D[50] = 1.282905, D[51] = 1.282905, D[52] = 1.282905, D[53] = 1.282905, D[54] = 1.282905, D[55] = 1.282905, D[56] = 1.282905, D[57] = 1.397471, D[58] = 1.239665, D[59] = 1.239665, D[60] = 1.239665, D[61] = 1.239665, D[62] = 1.239665, D[63] = 1.239665, D[64] = 1.239665, D[65] = 1.239665, D[66] = 1.239665, D[67] = 1.239665, D[68] = 1.239665, D[69] = 1.239665, D[70] = 1.239665, D[71] = 1.239665, D[72] = 1.239665, D[73] = 1.239665, D[74] = 1.239665, D[75] = 1.239665, D[76] = 1.239665, D[77] = 1.239665, D[78] = 1.239665, D[79] = 1.239665, D[80] = 1.239665, D[81] = 1.239665, D[82] = 1.239665, D[83] = 1.239665, D[84] = 1.239665, D[85] = 1.239665, D[86] = 1.239665, D[87] = 1.239665, D[88] = 1.239665, D[89] = 1.239665, D[90] = 1.239665, D[91] = 1.239665, D[92] = 1.239665, D[93] = 1.239665, D[94] = 1.239665, D[95] = 1.239665, D[96] = 1.239665, D[97] = 1.239665, D[98] = 1.239665, D[99] = 1.239665, D[100] = 1.239665, D[101] = 1.239665, D[102] = 1.239665, D[103] = 1.239665, D[104] = 1.239665, D[105] = 1.239665, D[106] = 1.239665, D[107] = 1.239665, D[108] = 1.239665, D[109] = 1.239665, D[110] = 1.239665, D[111] = 1.239665, D[112] = 1.239665, D[113] = 1.318662, D[114] = 1.318662, D[115] = 1.318662, D[116] = 1.330200, D[117] = 1.330200, D[118] = 1.330200, D[119] = 1.359772, D[120] = 1.359772, D[121] = 1.359772, D[122] = 1.222540, D[123] = 1.222540, D[124] = 1.222540, D[125] = 1.158085, D[126] = 1.158085, D[127] = 1.158085, D[128] = 1.336272, D[129] = 1.336272, D[130] = 1.336272, D[131] = 1.394267, D[132] = 1.394267, D[133] = 1.394267, D[134] = 1.380682, D[135] = 1.380682, D[136] = 1.380682, D[137] = 1.157797, D[138] = 1.157797, D[139] = 1.157797, D[140] = 1.136272, D[141] = 1.136272, D[142] = 1.136272, D[143] = 1.393197, D[144] = 1.393197, D[145] = 1.393197, D[146] = 1.195598, D[147] = 1.195598, D[148] = 1.195598, D[149] = 1.245097, D[150] = 1.245097, D[151] = 1.245097, D[152] = 1.122532, D[153] = 1.122532, D[154] = 1.122532, D[155] = 1.230715, D[156] = 1.230715, D[157] = 1.230715, D[158] = 1.124209, D[159] = 1.124209, D[160] = 1.124209, D[161] = 1.177480, D[162] = 1.177480, D[163] = 1.177480, D[164] = 1.146771, D[165] = 1.146771, D[166] = 1.146771, D[167] = 1.265464, D[168] = 1.265464, D[169] = 1.265464, D[170] = 1.143717, D[171] = 1.143717, D[172] = 1.143717, D[173] = 1.119358, D[174] = 1.119358, D[175] = 1.119358, D[176] = 1.259513, D[177] = 1.259513, D[178] = 1.259513, D[179] = 1.222827, D[180] = 1.222827, D[181] = 1.222827, D[182] = 0.985631, D[183] = 0.985631, D[184] = 0.985631, SCS(norm) D = 16.905203 E[0] = 2.055285, E[1] = 1.743654, E[2] = 2.246801, E[3] = 2.224429, E[4] = 2.563236, E[5] = 2.601782, E[6] = 2.304612, E[7] = 1.992822, E[8] = 2.305926, E[9] = 2.647288, E[10] = 2.017846, E[11] = 2.024143, E[12] = 2.096105, E[13] = 2.421522, E[14] = 2.801901, E[15] = 1.909891, E[16] = 2.208130, E[17] = 2.345051, E[18] = 1.832727, E[19] = 2.025244, E[20] = 2.632973, E[21] = 2.502085, E[22] = 2.401170, E[23] = 2.004016, E[24] = 1.981517, E[25] = 1.917554, E[26] = 1.916246, E[27] = 2.457070, E[28] = 2.010062, E[29] = 1.997175, E[30] = 2.445244, E[31] = 2.514225, E[32] = 1.869859, E[33] = 2.279780, E[34] = 2.162568, E[35] = 2.095279, E[36] = 2.171196, E[37] = 2.761104, E[38] = 2.706920, E[39] = 2.081358, E[40] = 2.033307, E[41] = 2.067479, E[42] = 1.901206, E[43] = 2.239490, E[44] = 2.375592, E[45] = 2.587518, E[46] = 2.156844, E[47] = 1.830430, E[48] = 2.578381, E[49] = 2.005637, E[50] = 1.971703, E[51] = 1.878357, E[52] = 2.050370, E[53] = 1.936923, E[54] = 1.883112, E[55] = 2.258046, E[56] = 1.874007, E[57] = 1.807321, E[58] = 2.047031, E[59] = 2.118864, E[60] = 1.975957, SCS(norm) E = 17.139799 init_cone BLAS(func) = 'dfunc_' init_cone complete getting pre-conditioner finished getting pre-conditioner scs/linsys/gpu/indirect/private.c:270:scs_init_lin_sys_work ERROR_CUDA: no CUDA-capable device is detected ERROR: init_lin_sys_work failure Setup time: 2.69e-03s size of scs_int = 4, size of scs_float = 8 Failure:could not initialize work ----------------------------- Captured stderr call ----------------------------- ** On entry to cusparseCreateDnVec() parameter number 3 (values) had an illegal value: NULL pointer ** On entry to cusparseCreateDnVec() parameter number 3 (values) had an illegal value: NULL pointer _______________________ test_solve_unbounded[True-True] ________________________ use_indirect = True, gpu = True @pytest.mark.parametrize('use_indirect,gpu', flags) def test_solve_unbounded(use_indirect, gpu): data = tools.gen_unbounded(K, n=m // 3) sol = scs.solve(data, K, use_indirect=use_indirect, gpu=gpu, **params) x = sol['x'] s = sol['s'] > np.testing.assert_array_less(np.linalg.norm(data['A'] @ x + s), 1e-3) E AssertionError: E Arrays are not less-ordered E E x and y nan location mismatch: E x: array(nan) E y: array(0.001) test/test_solve_random_cone_prob.py:82: AssertionError ----------------------------- Captured stdout call ----------------------------- m = 185 n = 61 max_iters = 5000 verbose = 1 normalize = 1 warm_start = 0 acceleration_lookback = 10 eps = 0.000010 alpha = 1.500000 rho_x = 0.001000 cg_rate = 2.000000 scale = 5.000000 write_data_filename = (null) num zeros = 10 num LP = 15 num SOCs = 4 soc array: 5 10 0 1 num SDCs = 6 sdc array: 3 4 0 0 1 10 num ep = 10 num ed = 10 num PCs = 4 pow array: -0.250000 0.500000 0.750000 -0.330000 ---------------------------------------------------------------------------- SCS v2.1.4 - Splitting Conic Solver (c) Brendan O'Donoghue, Stanford University, 2012 ---------------------------------------------------------------------------- Lin-sys: sparse-indirect GPU, nnz in A = 11285, CG tol ~ 1/iter^(2.00) eps = 1.00e-05, alpha = 1.50, max_iters = 5000, normalize = 1, scale = 5.00 acceleration_lookback = 10, rho_x = 1.00e-03 Variables n = 61, constraints m = 185 Cones: primal zero / dual free vars: 10 linear vars: 15 soc vars: 16, soc blks: 4 sd vars: 72, sd blks: 6 exp vars: 30, dual exp vars: 30 primal + dual power vars: 12 normalizing A finished normalizing A, time: 1.45e-03s D[0] = 1.353750, D[1] = 1.627024, D[2] = 1.335439, D[3] = 1.301090, D[4] = 1.403465, D[5] = 1.570603, D[6] = 1.178440, D[7] = 1.187784, D[8] = 1.226702, D[9] = 1.543382, D[10] = 1.361460, D[11] = 1.276433, D[12] = 1.459870, D[13] = 1.709492, D[14] = 1.423891, D[15] = 1.201064, D[16] = 1.406837, D[17] = 1.161674, D[18] = 1.178530, D[19] = 1.001726, D[20] = 1.138195, D[21] = 1.262308, D[22] = 1.401928, D[23] = 1.161867, D[24] = 1.116094, D[25] = 1.269768, D[26] = 1.269768, D[27] = 1.269768, D[28] = 1.269768, D[29] = 1.269768, D[30] = 1.309759, D[31] = 1.309759, D[32] = 1.309759, D[33] = 1.309759, D[34] = 1.309759, D[35] = 1.309759, D[36] = 1.309759, D[37] = 1.309759, D[38] = 1.309759, D[39] = 1.309759, D[40] = 1.127389, D[41] = 1.154943, D[42] = 1.154943, D[43] = 1.154943, D[44] = 1.154943, D[45] = 1.154943, D[46] = 1.154943, D[47] = 1.144639, D[48] = 1.144639, D[49] = 1.144639, D[50] = 1.144639, D[51] = 1.144639, D[52] = 1.144639, D[53] = 1.144639, D[54] = 1.144639, D[55] = 1.144639, D[56] = 1.144639, D[57] = 1.425160, D[58] = 1.182433, D[59] = 1.182433, D[60] = 1.182433, D[61] = 1.182433, D[62] = 1.182433, D[63] = 1.182433, D[64] = 1.182433, D[65] = 1.182433, D[66] = 1.182433, D[67] = 1.182433, D[68] = 1.182433, D[69] = 1.182433, D[70] = 1.182433, D[71] = 1.182433, D[72] = 1.182433, D[73] = 1.182433, D[74] = 1.182433, D[75] = 1.182433, D[76] = 1.182433, D[77] = 1.182433, D[78] = 1.182433, D[79] = 1.182433, D[80] = 1.182433, D[81] = 1.182433, D[82] = 1.182433, D[83] = 1.182433, D[84] = 1.182433, D[85] = 1.182433, D[86] = 1.182433, D[87] = 1.182433, D[88] = 1.182433, D[89] = 1.182433, D[90] = 1.182433, D[91] = 1.182433, D[92] = 1.182433, D[93] = 1.182433, D[94] = 1.182433, D[95] = 1.182433, D[96] = 1.182433, D[97] = 1.182433, D[98] = 1.182433, D[99] = 1.182433, D[100] = 1.182433, D[101] = 1.182433, D[102] = 1.182433, D[103] = 1.182433, D[104] = 1.182433, D[105] = 1.182433, D[106] = 1.182433, D[107] = 1.182433, D[108] = 1.182433, D[109] = 1.182433, D[110] = 1.182433, D[111] = 1.182433, D[112] = 1.182433, D[113] = 1.213903, D[114] = 1.213903, D[115] = 1.213903, D[116] = 1.093872, D[117] = 1.093872, D[118] = 1.093872, D[119] = 1.289372, D[120] = 1.289372, D[121] = 1.289372, D[122] = 1.075136, D[123] = 1.075136, D[124] = 1.075136, D[125] = 1.245883, D[126] = 1.245883, D[127] = 1.245883, D[128] = 1.185276, D[129] = 1.185276, D[130] = 1.185276, D[131] = 1.141366, D[132] = 1.141366, D[133] = 1.141366, D[134] = 1.194276, D[135] = 1.194276, D[136] = 1.194276, D[137] = 1.226171, D[138] = 1.226171, D[139] = 1.226171, D[140] = 1.432000, D[141] = 1.432000, D[142] = 1.432000, D[143] = 1.371073, D[144] = 1.371073, D[145] = 1.371073, D[146] = 1.184296, D[147] = 1.184296, D[148] = 1.184296, D[149] = 1.328445, D[150] = 1.328445, D[151] = 1.328445, D[152] = 1.236474, D[153] = 1.236474, D[154] = 1.236474, D[155] = 1.175562, D[156] = 1.175562, D[157] = 1.175562, D[158] = 1.158307, D[159] = 1.158307, D[160] = 1.158307, D[161] = 1.257845, D[162] = 1.257845, D[163] = 1.257845, D[164] = 1.095224, D[165] = 1.095224, D[166] = 1.095224, D[167] = 1.163686, D[168] = 1.163686, D[169] = 1.163686, D[170] = 1.199529, D[171] = 1.199529, D[172] = 1.199529, D[173] = 1.180924, D[174] = 1.180924, D[175] = 1.180924, D[176] = 1.407954, D[177] = 1.407954, D[178] = 1.407954, D[179] = 1.258960, D[180] = 1.258960, D[181] = 1.258960, D[182] = 1.094149, D[183] = 1.094149, D[184] = 1.094149, SCS(norm) D = 16.675275 E[0] = 2.135624, E[1] = 1.972902, E[2] = 2.208984, E[3] = 2.380685, E[4] = 2.578894, E[5] = 2.405205, E[6] = 2.289317, E[7] = 2.448085, E[8] = 1.938521, E[9] = 1.916985, E[10] = 1.937648, E[11] = 2.098564, E[12] = 2.293303, E[13] = 1.742247, E[14] = 2.442228, E[15] = 2.686900, E[16] = 2.572321, E[17] = 2.790448, E[18] = 2.384324, E[19] = 2.098271, E[20] = 2.431458, E[21] = 2.475694, E[22] = 2.873479, E[23] = 2.630524, E[24] = 2.023392, E[25] = 2.766650, E[26] = 2.057839, E[27] = 2.566906, E[28] = 2.511538, E[29] = 1.828795, E[30] = 2.265831, E[31] = 2.445125, E[32] = 2.503016, E[33] = 2.244322, E[34] = 2.582616, E[35] = 1.743396, E[36] = 2.158995, E[37] = 2.467828, E[38] = 2.597544, E[39] = 2.161679, E[40] = 2.271838, E[41] = 2.054442, E[42] = 2.345564, E[43] = 2.624630, E[44] = 2.106582, E[45] = 1.679058, E[46] = 2.385561, E[47] = 1.697199, E[48] = 2.629697, E[49] = 2.553592, E[50] = 2.606709, E[51] = 2.044493, E[52] = 1.820402, E[53] = 2.479520, E[54] = 2.062233, E[55] = 2.204598, E[56] = 1.752522, E[57] = 2.266827, E[58] = 2.129365, E[59] = 2.326036, E[60] = 1.750291, SCS(norm) E = 17.882210 init_cone BLAS(func) = 'dfunc_' init_cone complete getting pre-conditioner finished getting pre-conditioner scs/linsys/gpu/indirect/private.c:270:scs_init_lin_sys_work ERROR_CUDA: no CUDA-capable device is detected ERROR: init_lin_sys_work failure Setup time: 2.69e-03s size of scs_int = 4, size of scs_float = 8 Failure:could not initialize work ----------------------------- Captured stderr call ----------------------------- ** On entry to cusparseCreateDnVec() parameter number 3 (values) had an illegal value: NULL pointer ** On entry to cusparseCreateDnVec() parameter number 3 (values) had an illegal value: NULL pointer =============================== warnings summary =============================== test/test_scs_python_linsys.py::test_python_linsys $PREFIX/lib/python3.9/site-packages/scipy/sparse/linalg/dsolve/linsolve.py:318: SparseEfficiencyWarning: splu requires CSC matrix format warn('splu requires CSC matrix format', SparseEfficiencyWarning) test/test_scs_python_linsys.py::test_python_linsys $SRC_DIR/test/test_scs_python_linsys.py:102: RuntimeWarning: Mean of empty slice. D[start:start+delta] = D[start:start+delta].mean() test/test_scs_python_linsys.py::test_python_linsys $PREFIX/lib/python3.9/site-packages/numpy/core/_methods.py:188: RuntimeWarning: invalid value encountered in double_scalars ret = ret.dtype.type(ret / rcount) -- Docs: https://docs.pytest.org/en/stable/warnings.html =========================== short test summary info ============================ FAILED test/test_solve_random_cone_prob.py::test_solve_feasible[True-True] - ... FAILED test/test_solve_random_cone_prob.py::test_solve_infeasible[True-True] FAILED test/test_solve_random_cone_prob.py::test_solve_unbounded[True-True] ============= 3 failed, 24 passed, 3 warnings in 69.41s (0:01:09) ============== ```For windows, the failures are more extensive for the GPU-less builds (interestingly, the test failures of windows + GPU are the same as under linux + GPU).
Details of test suite failures on windows
``` ================================== FAILURES =================================== ____________________________ test_feasible[False] _____________________________ use_indirect = False @pytest.mark.parametrize("use_indirect", [False, True]) def test_feasible(use_indirect): for i in range(num_feas): data, p_star = tools.gen_feasible(K, n=m // 3, density=0.1) sol = scs.solve(data, K, use_indirect=use_indirect, **opts) > assert_almost_equal(np.dot(data['c'], sol['x']), p_star, decimal=2) E AssertionError: E Arrays are not almost equal to 2 decimals E ACTUAL: nan E DESIRED: -1.4047363523107776 test\test_scs_sdp.py:82: AssertionError ---------------------------- Captured stdout call ----------------------------- FATAL: Cannot solve SDPs with > 2x2 matrices without linked blas+lapack libraries Install blas+lapack and re-compile SCS with blas+lapack library locations ERROR: init_cone failure Failure:could not initialize work _____________________________ test_feasible[True] _____________________________ use_indirect = True @pytest.mark.parametrize("use_indirect", [False, True]) def test_feasible(use_indirect): for i in range(num_feas): data, p_star = tools.gen_feasible(K, n=m // 3, density=0.1) sol = scs.solve(data, K, use_indirect=use_indirect, **opts) > assert_almost_equal(np.dot(data['c'], sol['x']), p_star, decimal=2) E AssertionError: E Arrays are not almost equal to 2 decimals E ACTUAL: nan E DESIRED: -1.6214651965010063 test\test_scs_sdp.py:82: AssertionError ---------------------------- Captured stdout call ----------------------------- FATAL: Cannot solve SDPs with > 2x2 matrices without linked blas+lapack libraries Install blas+lapack and re-compile SCS with blas+lapack library locations ERROR: init_cone failure Failure:could not initialize work ___________________________ test_infeasible[False] ____________________________ use_indirect = False @pytest.mark.parametrize("use_indirect", [False, True]) def test_infeasible(use_indirect): for i in range(num_infeas): data = tools.gen_infeasible(K, n=m // 3) sol = scs.solve(data, K, use_indirect=use_indirect, **opts) > check_infeasible(sol) test\test_scs_sdp.py:92: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ test\test_scs_sdp.py:47: in check_infeasible assert_(sol['info']['status'], 'Infeasible') _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ str1 = 'Failure', str2 = 'Infeasible' def assert_(str1, str2): if (str1 != str2): print('assert failure: %s != %s' % (str1, str2)) > assert str1 == str2 E AssertionError: assert 'Failure' == 'Infeasible' E - Infeasible E + Failure test\test_scs_sdp.py:43: AssertionError ---------------------------- Captured stdout call ----------------------------- FATAL: Cannot solve SDPs with > 2x2 matrices without linked blas+lapack libraries Install blas+lapack and re-compile SCS with blas+lapack library locations ERROR: init_cone failure Failure:could not initialize work assert failure: Failure != Infeasible ____________________________ test_infeasible[True] ____________________________ use_indirect = True @pytest.mark.parametrize("use_indirect", [False, True]) def test_infeasible(use_indirect): for i in range(num_infeas): data = tools.gen_infeasible(K, n=m // 3) sol = scs.solve(data, K, use_indirect=use_indirect, **opts) > check_infeasible(sol) test\test_scs_sdp.py:92: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ test\test_scs_sdp.py:47: in check_infeasible assert_(sol['info']['status'], 'Infeasible') _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ str1 = 'Failure', str2 = 'Infeasible' def assert_(str1, str2): if (str1 != str2): print('assert failure: %s != %s' % (str1, str2)) > assert str1 == str2 E AssertionError: assert 'Failure' == 'Infeasible' E - Infeasible E + Failure test\test_scs_sdp.py:43: AssertionError ---------------------------- Captured stdout call ----------------------------- FATAL: Cannot solve SDPs with > 2x2 matrices without linked blas+lapack libraries Install blas+lapack and re-compile SCS with blas+lapack library locations ERROR: init_cone failure Failure:could not initialize work assert failure: Failure != Infeasible ____________________________ test_unbounded[False] ____________________________ use_indirect = False @pytest.mark.parametrize("use_indirect", [False, True]) def test_unbounded(use_indirect): for i in range(num_unb): data = tools.gen_unbounded(K, n=m // 2) sol = scs.solve(data, K, use_indirect=use_indirect, **opts) > check_unbounded(sol) test\test_scs_sdp.py:101: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ test\test_scs_sdp.py:51: in check_unbounded assert_(sol['info']['status'], 'Unbounded') _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ str1 = 'Failure', str2 = 'Unbounded' def assert_(str1, str2): if (str1 != str2): print('assert failure: %s != %s' % (str1, str2)) > assert str1 == str2 E AssertionError: assert 'Failure' == 'Unbounded' E - Unbounded E + Failure test\test_scs_sdp.py:43: AssertionError ---------------------------- Captured stdout call ----------------------------- FATAL: Cannot solve SDPs with > 2x2 matrices without linked blas+lapack libraries Install blas+lapack and re-compile SCS with blas+lapack library locations ERROR: init_cone failure Failure:could not initialize work assert failure: Failure != Unbounded ____________________________ test_unbounded[True] _____________________________ use_indirect = True @pytest.mark.parametrize("use_indirect", [False, True]) def test_unbounded(use_indirect): for i in range(num_unb): data = tools.gen_unbounded(K, n=m // 2) sol = scs.solve(data, K, use_indirect=use_indirect, **opts) > check_unbounded(sol) test\test_scs_sdp.py:101: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ test\test_scs_sdp.py:51: in check_unbounded assert_(sol['info']['status'], 'Unbounded') _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ str1 = 'Failure', str2 = 'Unbounded' def assert_(str1, str2): if (str1 != str2): print('assert failure: %s != %s' % (str1, str2)) > assert str1 == str2 E AssertionError: assert 'Failure' == 'Unbounded' E - Unbounded E + Failure test\test_scs_sdp.py:43: AssertionError ---------------------------- Captured stdout call ----------------------------- FATAL: Cannot solve SDPs with > 2x2 matrices without linked blas+lapack libraries Install blas+lapack and re-compile SCS with blas+lapack library locations ERROR: init_cone failure Failure:could not initialize work assert failure: Failure != Unbounded ______________________ test_solve_feasible[False-False] _______________________ use_indirect = False, gpu = False @pytest.mark.parametrize('use_indirect,gpu', flags) def test_solve_feasible(use_indirect, gpu): data, p_star = tools.gen_feasible(K, n=m // 3, density=0.1) sol = scs.solve(data, K, use_indirect=use_indirect, gpu=gpu, **params) x = sol['x'] y = sol['y'] s = sol['s'] > np.testing.assert_almost_equal(np.dot(data['c'], x), p_star, decimal=3) E AssertionError: E Arrays are not almost equal to 3 decimals E ACTUAL: nan E DESIRED: -12.397110172358182 test\test_solve_random_cone_prob.py:55: AssertionError ---------------------------- Captured stdout call ----------------------------- ---------------------------------------------------------------------------- SCS v2.1.4 - Splitting Conic Solver (c) Brendan O'Donoghue, Stanford University, 2012 ---------------------------------------------------------------------------- Lin-sys: sparse-direct, nnz in A = 1128 eps = 1.00e-05, alpha = 1.50, max_iters = 5000, normalize = 1, scale = 5.00 acceleration_lookback = 0, rho_x = 1.00e-03 Variables n = 61, constraints m = 185 Cones: primal zero / dual free vars: 10 linear vars: 15 soc vars: 16, soc blks: 4 sd vars: 72, sd blks: 6 exp vars: 30, dual exp vars: 30 primal + dual power vars: 12 FATAL: Cannot solve SDPs with > 2x2 matrices without linked blas+lapack libraries Install blas+lapack and re-compile SCS with blas+lapack library locations ERROR: init_cone failure Setup time: 2.82e-03s Failure:could not initialize work _______________________ test_solve_feasible[True-False] _______________________ use_indirect = True, gpu = False @pytest.mark.parametrize('use_indirect,gpu', flags) def test_solve_feasible(use_indirect, gpu): data, p_star = tools.gen_feasible(K, n=m // 3, density=0.1) sol = scs.solve(data, K, use_indirect=use_indirect, gpu=gpu, **params) x = sol['x'] y = sol['y'] s = sol['s'] > np.testing.assert_almost_equal(np.dot(data['c'], x), p_star, decimal=3) E AssertionError: E Arrays are not almost equal to 3 decimals E ACTUAL: nan E DESIRED: -36.363218873493814 test\test_solve_random_cone_prob.py:55: AssertionError ---------------------------- Captured stdout call ----------------------------- ---------------------------------------------------------------------------- SCS v2.1.4 - Splitting Conic Solver (c) Brendan O'Donoghue, Stanford University, 2012 ---------------------------------------------------------------------------- Lin-sys: sparse-indirect, nnz in A = 1128, CG tol ~ 1/iter^(2.00) eps = 1.00e-05, alpha = 1.50, max_iters = 5000, normalize = 1, scale = 5.00 acceleration_lookback = 0, rho_x = 1.00e-03 Variables n = 61, constraints m = 185 Cones: primal zero / dual free vars: 10 linear vars: 15 soc vars: 16, soc blks: 4 sd vars: 72, sd blks: 6 exp vars: 30, dual exp vars: 30 primal + dual power vars: 12 FATAL: Cannot solve SDPs with > 2x2 matrices without linked blas+lapack libraries Install blas+lapack and re-compile SCS with blas+lapack library locations ERROR: init_cone failure Setup time: 1.23e-03s Failure:could not initialize work _____________________ test_solve_infeasible[False-False] ______________________ use_indirect = False, gpu = False @pytest.mark.parametrize('use_indirect,gpu', flags) def test_solve_infeasible(use_indirect, gpu): data = tools.gen_infeasible(K, n=m // 3) sol = scs.solve(data, K, use_indirect=use_indirect, gpu=gpu, **params) y = sol['y'] > np.testing.assert_array_less(np.linalg.norm(data['A'].T @ y), 1e-3) E AssertionError: E Arrays are not less-ordered E E x and y nan location mismatch: E x: array(nan) E y: array(0.001) test\test_solve_random_cone_prob.py:71: AssertionError ---------------------------- Captured stdout call ----------------------------- ---------------------------------------------------------------------------- SCS v2.1.4 - Splitting Conic Solver (c) Brendan O'Donoghue, Stanford University, 2012 ---------------------------------------------------------------------------- Lin-sys: sparse-direct, nnz in A = 11285 eps = 1.00e-05, alpha = 1.50, max_iters = 5000, normalize = 1, scale = 5.00 acceleration_lookback = 0, rho_x = 1.00e-03 Variables n = 61, constraints m = 185 Cones: primal zero / dual free vars: 10 linear vars: 15 soc vars: 16, soc blks: 4 sd vars: 72, sd blks: 6 exp vars: 30, dual exp vars: 30 primal + dual power vars: 12 FATAL: Cannot solve SDPs with > 2x2 matrices without linked blas+lapack libraries Install blas+lapack and re-compile SCS with blas+lapack library locations ERROR: init_cone failure Setup time: 3.21e-03s Failure:could not initialize work ______________________ test_solve_infeasible[True-False] ______________________ use_indirect = True, gpu = False @pytest.mark.parametrize('use_indirect,gpu', flags) def test_solve_infeasible(use_indirect, gpu): data = tools.gen_infeasible(K, n=m // 3) sol = scs.solve(data, K, use_indirect=use_indirect, gpu=gpu, **params) y = sol['y'] > np.testing.assert_array_less(np.linalg.norm(data['A'].T @ y), 1e-3) E AssertionError: E Arrays are not less-ordered E E x and y nan location mismatch: E x: array(nan) E y: array(0.001) test\test_solve_random_cone_prob.py:71: AssertionError ---------------------------- Captured stdout call ----------------------------- ---------------------------------------------------------------------------- SCS v2.1.4 - Splitting Conic Solver (c) Brendan O'Donoghue, Stanford University, 2012 ---------------------------------------------------------------------------- Lin-sys: sparse-indirect, nnz in A = 11285, CG tol ~ 1/iter^(2.00) eps = 1.00e-05, alpha = 1.50, max_iters = 5000, normalize = 1, scale = 5.00 acceleration_lookback = 0, rho_x = 1.00e-03 Variables n = 61, constraints m = 185 Cones: primal zero / dual free vars: 10 linear vars: 15 soc vars: 16, soc blks: 4 sd vars: 72, sd blks: 6 exp vars: 30, dual exp vars: 30 primal + dual power vars: 12 FATAL: Cannot solve SDPs with > 2x2 matrices without linked blas+lapack libraries Install blas+lapack and re-compile SCS with blas+lapack library locations ERROR: init_cone failure Setup time: 3.50e-03s Failure:could not initialize work ______________________ test_solve_unbounded[False-False] ______________________ use_indirect = False, gpu = False @pytest.mark.parametrize('use_indirect,gpu', flags) def test_solve_unbounded(use_indirect, gpu): data = tools.gen_unbounded(K, n=m // 3) sol = scs.solve(data, K, use_indirect=use_indirect, gpu=gpu, **params) x = sol['x'] s = sol['s'] > np.testing.assert_array_less(np.linalg.norm(data['A'] @ x + s), 1e-3) E AssertionError: E Arrays are not less-ordered E E x and y nan location mismatch: E x: array(nan) E y: array(0.001) test\test_solve_random_cone_prob.py:82: AssertionError ---------------------------- Captured stdout call ----------------------------- ---------------------------------------------------------------------------- SCS v2.1.4 - Splitting Conic Solver (c) Brendan O'Donoghue, Stanford University, 2012 ---------------------------------------------------------------------------- Lin-sys: sparse-direct, nnz in A = 11285 eps = 1.00e-05, alpha = 1.50, max_iters = 5000, normalize = 1, scale = 5.00 acceleration_lookback = 0, rho_x = 1.00e-03 Variables n = 61, constraints m = 185 Cones: primal zero / dual free vars: 10 linear vars: 15 soc vars: 16, soc blks: 4 sd vars: 72, sd blks: 6 exp vars: 30, dual exp vars: 30 primal + dual power vars: 12 FATAL: Cannot solve SDPs with > 2x2 matrices without linked blas+lapack libraries Install blas+lapack and re-compile SCS with blas+lapack library locations ERROR: init_cone failure Setup time: 3.19e-03s Failure:could not initialize work ______________________ test_solve_unbounded[True-False] _______________________ use_indirect = True, gpu = False @pytest.mark.parametrize('use_indirect,gpu', flags) def test_solve_unbounded(use_indirect, gpu): data = tools.gen_unbounded(K, n=m // 3) sol = scs.solve(data, K, use_indirect=use_indirect, gpu=gpu, **params) x = sol['x'] s = sol['s'] > np.testing.assert_array_less(np.linalg.norm(data['A'] @ x + s), 1e-3) E AssertionError: E Arrays are not less-ordered E E x and y nan location mismatch: E x: array(nan) E y: array(0.001) test\test_solve_random_cone_prob.py:82: AssertionError ---------------------------- Captured stdout call ----------------------------- ---------------------------------------------------------------------------- SCS v2.1.4 - Splitting Conic Solver (c) Brendan O'Donoghue, Stanford University, 2012 ---------------------------------------------------------------------------- Lin-sys: sparse-indirect, nnz in A = 11285, CG tol ~ 1/iter^(2.00) eps = 1.00e-05, alpha = 1.50, max_iters = 5000, normalize = 1, scale = 5.00 acceleration_lookback = 0, rho_x = 1.00e-03 Variables n = 61, constraints m = 185 Cones: primal zero / dual free vars: 10 linear vars: 15 soc vars: 16, soc blks: 4 sd vars: 72, sd blks: 6 exp vars: 30, dual exp vars: 30 primal + dual power vars: 12 FATAL: Cannot solve SDPs with > 2x2 matrices without linked blas+lapack libraries Install blas+lapack and re-compile SCS with blas+lapack library locations ERROR: init_cone failure Setup time: 3.29e-03s Failure:could not initialize work ============================== warnings summary =============================== test/test_scs_python_linsys.py::test_python_linsys %PREFIX%\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py:318: SparseEfficiencyWarning: splu requires CSC matrix format warn('splu requires CSC matrix format', SparseEfficiencyWarning) test/test_scs_python_linsys.py::test_python_linsys %SRC_DIR%\test\test_scs_python_linsys.py:102: RuntimeWarning: Mean of empty slice. D[start:start+delta] = D[start:start+delta].mean() test/test_scs_python_linsys.py::test_python_linsys %PREFIX%\lib\site-packages\numpy\core\_methods.py:188: RuntimeWarning: invalid value encountered in double_scalars ret = ret.dtype.type(ret / rcount) -- Docs: https://docs.pytest.org/en/stable/warnings.html =========================== short test summary info =========================== FAILED test/test_scs_sdp.py::test_feasible[False] - AssertionError: FAILED test/test_scs_sdp.py::test_feasible[True] - AssertionError: FAILED test/test_scs_sdp.py::test_infeasible[False] - AssertionError: assert ... FAILED test/test_scs_sdp.py::test_infeasible[True] - AssertionError: assert '... FAILED test/test_scs_sdp.py::test_unbounded[False] - AssertionError: assert '... FAILED test/test_scs_sdp.py::test_unbounded[True] - AssertionError: assert 'F... FAILED test/test_solve_random_cone_prob.py::test_solve_feasible[False-False] FAILED test/test_solve_random_cone_prob.py::test_solve_feasible[True-False] FAILED test/test_solve_random_cone_prob.py::test_solve_infeasible[False-False] FAILED test/test_solve_random_cone_prob.py::test_solve_infeasible[True-False] FAILED test/test_solve_random_cone_prob.py::test_solve_unbounded[False-False] FAILED test/test_solve_random_cone_prob.py::test_solve_unbounded[True-False] ================== 12 failed, 12 passed, 3 warnings in 8.85s ================== ```