CONTAINS Runtime Modules of Parallel Sparse Linear Solver PARDISO Vers. 8.0
Copyright Panua Technologies, Switzerland [2022-2023], All Rights Reserved.
where to place the license file panua.lic
Found num.threads = 12:1 max_threads = 12
Set reordering to id=[0] and name=[default]
Process file[/tmp/RtmpxIKjb9/file2b239452714d8/Model.ini] threads[12] max.threads[12] blas_threads[1] nested[12:1]
pardiso-library installed and working? = [no]
PRIOR->to_theta = [function (x) <<NEWLINE>>log(x)]
read n=[45172] entries from file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b23952d6ee1a]
read n=[67566] entries from file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b23964123a96]
PRIOR0->to_theta = [function (x) <<NEWLINE>>x]
read n=[128] entries from file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2391d0d77e1]
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2391d0d77e1] 0/64  (idx,y) = (0, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2391d0d77e1] 1/64  (idx,y) = (1, 1)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2391d0d77e1] 2/64  (idx,y) = (2, 2)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2391d0d77e1] 3/64  (idx,y) = (3, 3)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2391d0d77e1] 4/64  (idx,y) = (4, 4)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2391d0d77e1] 5/64  (idx,y) = (5, 5)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2391d0d77e1] 6/64  (idx,y) = (6, 6)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2391d0d77e1] 7/64  (idx,y) = (7, 7)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2391d0d77e1] 8/64  (idx,y) = (8, 8)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2391d0d77e1] 9/64  (idx,y) = (9, 9)
read n=[128] entries from file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b23912cb81c7]
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b23912cb81c7] 0/64  (idx,y) = (0, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b23912cb81c7] 1/64  (idx,y) = (1, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b23912cb81c7] 2/64  (idx,y) = (2, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b23912cb81c7] 3/64  (idx,y) = (3, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b23912cb81c7] 4/64  (idx,y) = (4, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b23912cb81c7] 5/64  (idx,y) = (5, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b23912cb81c7] 6/64  (idx,y) = (6, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b23912cb81c7] 7/64  (idx,y) = (7, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b23912cb81c7] 8/64  (idx,y) = (8, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b23912cb81c7] 9/64  (idx,y) = (9, 0)
read n=[128] entries from file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2396b84afaf]
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2396b84afaf] 0/64  (idx,y) = (0, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2396b84afaf] 1/64  (idx,y) = (1, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2396b84afaf] 2/64  (idx,y) = (2, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2396b84afaf] 3/64  (idx,y) = (3, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2396b84afaf] 4/64  (idx,y) = (4, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2396b84afaf] 5/64  (idx,y) = (5, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2396b84afaf] 6/64  (idx,y) = (6, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2396b84afaf] 7/64  (idx,y) = (7, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2396b84afaf] 8/64  (idx,y) = (8, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2396b84afaf] 9/64  (idx,y) = (9, 0)
read n=[128] entries from file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2396f3ad7cf]
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2396f3ad7cf] 0/64  (idx,y) = (0, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2396f3ad7cf] 1/64  (idx,y) = (1, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2396f3ad7cf] 2/64  (idx,y) = (2, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2396f3ad7cf] 3/64  (idx,y) = (3, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2396f3ad7cf] 4/64  (idx,y) = (4, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2396f3ad7cf] 5/64  (idx,y) = (5, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2396f3ad7cf] 6/64  (idx,y) = (6, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2396f3ad7cf] 7/64  (idx,y) = (7, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2396f3ad7cf] 8/64  (idx,y) = (8, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2396f3ad7cf] 9/64  (idx,y) = (9, 0)
read n=[128] entries from file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b23911f1191]
read n=[128] entries from file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2394d2bd9fe]
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2394d2bd9fe] 0/64  (idx,y) = (0, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2394d2bd9fe] 1/64  (idx,y) = (1, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2394d2bd9fe] 2/64  (idx,y) = (2, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2394d2bd9fe] 3/64  (idx,y) = (3, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2394d2bd9fe] 4/64  (idx,y) = (4, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2394d2bd9fe] 5/64  (idx,y) = (5, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2394d2bd9fe] 6/64  (idx,y) = (6, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2394d2bd9fe] 7/64  (idx,y) = (7, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2394d2bd9fe] 8/64  (idx,y) = (8, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2394d2bd9fe] 9/64  (idx,y) = (9, 0)
read n=[128] entries from file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2392bb6a627]
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2392bb6a627] 0/64  (idx,y) = (0, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2392bb6a627] 1/64  (idx,y) = (1, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2392bb6a627] 2/64  (idx,y) = (2, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2392bb6a627] 3/64  (idx,y) = (3, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2392bb6a627] 4/64  (idx,y) = (4, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2392bb6a627] 5/64  (idx,y) = (5, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2392bb6a627] 6/64  (idx,y) = (6, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2392bb6a627] 7/64  (idx,y) = (7, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2392bb6a627] 8/64  (idx,y) = (8, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2392bb6a627] 9/64  (idx,y) = (9, 0)
read n=[128] entries from file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2393c94e91b]
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2393c94e91b] 0/64  (idx,y) = (0, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2393c94e91b] 1/64  (idx,y) = (1, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2393c94e91b] 2/64  (idx,y) = (2, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2393c94e91b] 3/64  (idx,y) = (3, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2393c94e91b] 4/64  (idx,y) = (4, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2393c94e91b] 5/64  (idx,y) = (5, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2393c94e91b] 6/64  (idx,y) = (6, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2393c94e91b] 7/64  (idx,y) = (7, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2393c94e91b] 8/64  (idx,y) = (8, 0)
file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b2393c94e91b] 9/64  (idx,y) = (9, 0)
read n=[128] entries from file=[/tmp/RtmpxIKjb9/file2b239452714d8/data.files/file2b239615744fe]
Index table: number of entries[11], total length[22650]
Strategy:         Use an adaptive strategy (max=25)
Use linear approximation to log(|Q +c|)? Yes
Method:         Compute the derivative exact
Step length to compute derivatives numerically:         0.0001
Stencil to compute derivatives numerically:         5
Cutoff value to construct local neigborhood:         0.0001
Log calculated marginal for the hyperparameters:         On
Integration strategy:         Use only the modal configuration (EMPIRICAL_BAYES)
Difference in log-density limit (GRID only):         6.000
Skip configurations with (presumed) small density (GRID only):         On
Gradient is computed using Central difference with step-length 0.005000
Hessian is computed using Central difference with step-length 0.070711
Hessian matrix is forced to be a diagonal matrix? [No]
Compute effective number of parameters? [Yes]
Maximum number of function evaluations [100000]
To stabilise the numerical optimisation:
inla_build: check for unused entries in[/tmp/RtmpxIKjb9/file2b239452714d8/Model.ini]
Optimizing Qx-strategy..... serial[0.444] parallel [0.556] choose[serial]
Optimizing pred-strategy... plain [0.761] data-rich[0.239] choose[data-rich]
Found optimal reordering=[metis] nnz(L)=[831] and use_global_nodes(user)=[no]
Iter[0] RMS(err) = 1.000, update with step-size = 0.165
Iter[1] RMS(err) = 0.994, update with step-size = 0.342
Initial values computed in 0.0144 seconds
Smart optimise part I: estimate gradient using forward differences
Smart optimise part II: estimate gradient using central differences
Smart optimise part II: restart optimiser
Optim: Number of function evaluations = 137
Compute the Hessian using central differences and step_size[0.0707107]. Matrix-type [dense]
Smart optimise part IV: estimate Hessian using central differences
GMRFLib_opt_estimate_hessian: ensure spd for Hessian: mode seems fine
GMRFLib_opt_estimate_hessian: set tol=[0.03647]. number of negative eigenvalues=[0]
StDev/Correlation matrix (scaled inverse Hessian)
Compute corrected stdev for theta[0]: negative 1.106  positive 0.904
Compute corrected stdev for theta[1]: negative 1.173  positive 0.852
[0]Iter [0/25] VB correct with strategy [MEAN] in total[0.010sec] hess/grad[0.280]
Number of nodes corrected for [38] max(dx/sd)[0.0745]
[0]Iter [1/25] VB correct with strategy [MEAN] in total[0.013sec] hess/grad[nan]
Number of nodes corrected for [38] max(dx/sd)[0.0025]
Combine the densities with relative weights:
approx-inference.c:2321: {cur,peak}-Mem used: Real[113.6, 114.8]Mb, Virt[1702.3, 1901.2]Mb
approx-inference.c:2384: {cur,peak}-Mem used: Real[114.5, 114.8]Mb, Virt[1750.4, 1901.2]Mb
Effective number of parameters ... 12.6316
Marginal likelihood: Integration -10530.959 Gaussian-approx -10528.834
Compute the marginal for each of the 2 hyperparameters
Compute the marginal for theta[0] to theta[1] using numerical integration...
Compute the marginal for theta[0] to theta[1] using numerical integration... Done.
Compute the marginal for the hyperparameters... done.
approx-inference.c:2985: {cur,peak}-Mem used: Real[116.0, 116.0]Mb, Virt[1751.4, 1901.2]Mb
Wall-clock time used on [/tmp/RtmpxIKjb9/file2b239452714d8/Model.ini]
Approx inference (stage1):   1.366 seconds
Approx inference (stage2):   0.000 seconds
Approx inference (total) :   1.366 seconds
Stage1:        Number of fn-calls= 151 with 0.0090 sec/fn-call
Stage2:        Number of fn-calls= 0 with 1.3665 sec/fn-call
Stage1:        Accumulated CPU-time is equivalent to 3.78 threads running at 100%
Stage2:        Accumulated CPU-time is equivalent to 11.85 threads running at 100%
Total:        Accumulated CPU-time is equivalent to 3.78 threads running at 100%