1#@ *: Label=FastTest
2#@ *: DakotaConfig=HAVE_QUESO
3#@ *: ReqFiles=dakota_bayes_transforms.withsigma.dat
4# Test scaling/weighting transformations of residuals in Bayesian calibration
5# with mod_cantilever (2D) driver
6# s0-s5: using QUESO
7# s6: using DREAM
8# s0: baseline, no scaling nor weighting transformations
9# s1: scaled
10# s2: weighted
11# s3: scaled and weighted (transformations should cancel each other out)
12# s4: scaled and weighted (transformations compund each other)
13# s5: scaled and weighted (transformations compund each other), using metropolis_hastings
14# s6: scaled and weighted (transformations compund each other), using DREAM
15
16method
17  bayes_calibration queso 									#s0,#s1,#s2,#s3,#s4,#s5
18# bayes_calibration dream									#s6
19    chain_samples = 2000 seed = 1
20    dram  													#s0,#s1,#s2,#s3,#s4
21#   metropolis_hastings 									#s5
22    proposal_covariance										#s0,#s1,#s2,#s3,#s4,#s5
23      	values 5.0e8 5.0e-8				                    #s0,#s3
24#     	values 5.0e10 5.0e-6				                #s1
25#     	values 5.0e6 5.0e-10				                #s2
26#     	values 5.0e12 5.0e-4				                #s4,#s5
27        diagonal                                    		#s0,#s1,#s2,#s3,#s4,#s5
28    probability_levels 0.05 0.1
29                       0.05 0.1
30    posterior_stats kl_divergence
31#   scaling               									#s1,#s3,#s4,#s5,#s6
32
33variables
34  uniform_uncertain 2
35# 	MAP estimate is close to 2.9e7 2.5
36    upper_bounds  2.95e7 2.55
37    lower_bounds 2.85e7 2.45
38    initial_point 2.9e7 2.5
39    descriptors 'E' 'w'
40  continuous_state 4
41    initial_state 3 40000 500 1000
42    descriptors 't' 'R' 'X' 'Y'
43
44interface
45  analysis_drivers = 'mod_cantilever'
46    direct
47
48responses
49  calibration_terms = 2
50  calibration_data_file = 'dakota_bayes_transforms.withsigma.dat'
51    freeform
52    num_experiments = 10
53    variance_type = 'scalar' # read 2 scalar sigmas in each row
54  descriptors = 'stress' 'displacement'
55#          primary_scales   10.0 10.0  		#s1,#s3,#s4,#s5,#s6
56#          weights          100.0  100.0    #s2,#s3
57#          weights          0.01  0.01    	#s4,#s5,#s6
58  no_gradients
59  no_hessians
60