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New test failures with 2.1.4 #43
Description
Hey @bodono, thanks so much for the updates in 618962c 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 conda-forge/scs-feedstock#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 hiding ERROR_CUDA: no CUDA-capable device is detected but still producing results - likely garbage?):
=========================== 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) ==============
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).
=========================== 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 ==================
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 ==================
Activity
bodono commentedon Jun 6, 2021
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.
h-vetinari commentedon Jun 6, 2021
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-pythonshould be just what would be needed to do this with low effort (see the example fordef 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)?
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.
h-vetinari commentedon Jun 6, 2021
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 pytestand then running tests (no guarantees about the behaviour on linux, but feel free to download the respective artefact and try it!).Details
bodono commentedon Jun 8, 2021
When I try to install the linux artifact I get an error:
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?h-vetinari commentedon Jun 8, 2021
OK sorry, I forgot that you might not have conda-forge configured as a channel yet. In that case, please try:
This should fix the resolver errors.
bodono commentedon Jun 8, 2021
Ok that worked, but I can't
import _scs_gpuafter 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.
h-vetinari commentedon Jun 8, 2021
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.
bodono commentedon Jun 8, 2021
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:
so it looks like it should work, but for some reason _scs_gpu does not get installed correctly.
h-vetinari commentedon Jun 8, 2021
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.h-vetinari commentedon Jun 8, 2021
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...
bodono commentedon Jun 8, 2021
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.
h-vetinari commentedon Jun 8, 2021
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...
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).
bodono commentedon Jun 8, 2021
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=1.19I see scs appear as:
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.
h-vetinari commentedon Jun 8, 2021
Ah, now I understand you. It's possible that the path is not correct (e.g. you could be missing a
cpat 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 containedcurrent_repodata.json. I'd also use quotes to be sure, e.g.-c "path/to/wherever"bodono commentedon Jun 8, 2021
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!
h-vetinari commentedon Jun 8, 2021
One more thought (sorry for all the hassle, and thanks so much for your patience) - could you try adding
--channel-priority=strict, please?bodono commentedon Jun 8, 2021
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 numpyand got
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).
h-vetinari commentedon Jun 8, 2021
ok, it's weird (classic "works on my machine"), but I accept that we're stuck 😅
bodono commentedon Jun 8, 2021
Haha, thanks for your help anyway! It's probably something wrong with my setup somewhere.
h-vetinari commentedon Aug 18, 2021
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.bodono commentedon Sep 1, 2021
It potentially might have changed since I tried to run these, but I'm currently running: