+------------------------------ | | Running with BAT | Version 0.9.rc3 | | http://www.mppmu.mpg.de/bat +------------------------------ Summary : Opening logfile log.txt Summary : Running MCMC for model 'BCEfficiencyFitter with f1' Summary : Pre-run Metropolis MCMC... Summary : --> Perform MCMC pre-run with 5 chains, each with maximum 1000000 iterations Detail : --> Iteration 1000 Detail : --> Iteration 2000 Detail : --> Iteration 3000 Detail : --> Iteration 4000 Detail : * Convergence status: Set of 5 Markov chains converged within 4000 iterations. Detail : * Efficiency status: Efficiencies not within pre-defined range. Detail : - Efficiencies: Detail : Efficiency of parameter 0 dropped below 15.00% (eps = 1.40%) in chain 0. Set scale to 0.25 Detail : Efficiency of parameter 1 dropped below 15.00% (eps = 3.38%) in chain 0. Set scale to 0.25 Detail : Efficiency of parameter 2 dropped below 15.00% (eps = 2.73%) in chain 0. Set scale to 0.25 Detail : Efficiency of parameter 3 dropped below 15.00% (eps = 3.92%) in chain 0. Set scale to 0.25 Detail : Efficiency of parameter 0 dropped below 15.00% (eps = 1.88%) in chain 1. Set scale to 0.25 Detail : Efficiency of parameter 1 dropped below 15.00% (eps = 2.80%) in chain 1. Set scale to 0.25 Detail : Efficiency of parameter 2 dropped below 15.00% (eps = 2.70%) in chain 1. Set scale to 0.25 Detail : Efficiency of parameter 3 dropped below 15.00% (eps = 3.70%) in chain 1. Set scale to 0.25 Detail : Efficiency of parameter 0 dropped below 15.00% (eps = 1.47%) in chain 2. Set scale to 0.25 Detail : Efficiency of parameter 1 dropped below 15.00% (eps = 3.20%) in chain 2. Set scale to 0.25 Detail : Efficiency of parameter 2 dropped below 15.00% (eps = 2.55%) in chain 2. Set scale to 0.25 Detail : Efficiency of parameter 3 dropped below 15.00% (eps = 3.72%) in chain 2. Set scale to 0.25 Detail : Efficiency of parameter 0 dropped below 15.00% (eps = 1.80%) in chain 3. Set scale to 0.25 Detail : Efficiency of parameter 1 dropped below 15.00% (eps = 3.43%) in chain 3. Set scale to 0.25 Detail : Efficiency of parameter 2 dropped below 15.00% (eps = 3.05%) in chain 3. Set scale to 0.25 Detail : Efficiency of parameter 3 dropped below 15.00% (eps = 4.47%) in chain 3. Set scale to 0.25 Detail : Efficiency of parameter 0 dropped below 15.00% (eps = 1.70%) in chain 4. Set scale to 0.25 Detail : Efficiency of parameter 1 dropped below 15.00% (eps = 3.10%) in chain 4. Set scale to 0.25 Detail : Efficiency of parameter 2 dropped below 15.00% (eps = 2.70%) in chain 4. Set scale to 0.25 Detail : Efficiency of parameter 3 dropped below 15.00% (eps = 4.05%) in chain 4. Set scale to 0.25 Detail : --> Iteration 5000 Detail : --> Iteration 6000 Detail : --> Iteration 7000 Detail : --> Iteration 8000 Detail : * Convergence status: Set of 5 Markov chains converged within 8000 iterations. Detail : * Efficiency status: Efficiencies not within pre-defined range. Detail : - Efficiencies: Detail : Efficiency of parameter 0 dropped below 15.00% (eps = 6.98%) in chain 0. Set scale to 0.0625 Detail : Efficiency of parameter 1 dropped below 15.00% (eps = 12.30%) in chain 0. Set scale to 0.125 Detail : Efficiency of parameter 2 dropped below 15.00% (eps = 11.00%) in chain 0. Set scale to 0.125 Detail : Efficiency of parameter 3 dropped below 15.00% (eps = 14.95%) in chain 0. Set scale to 0.125 Detail : Efficiency of parameter 0 dropped below 15.00% (eps = 6.93%) in chain 1. Set scale to 0.0625 Detail : Efficiency of parameter 1 dropped below 15.00% (eps = 11.97%) in chain 1. Set scale to 0.125 Detail : Efficiency of parameter 2 dropped below 15.00% (eps = 12.05%) in chain 1. Set scale to 0.125 Detail : Efficiency of parameter 0 dropped below 15.00% (eps = 6.58%) in chain 2. Set scale to 0.0625 Detail : Efficiency of parameter 1 dropped below 15.00% (eps = 12.72%) in chain 2. Set scale to 0.125 Detail : Efficiency of parameter 2 dropped below 15.00% (eps = 11.22%) in chain 2. Set scale to 0.125 Detail : Efficiency of parameter 3 dropped below 15.00% (eps = 13.48%) in chain 2. Set scale to 0.125 Detail : Efficiency of parameter 0 dropped below 15.00% (eps = 6.85%) in chain 3. Set scale to 0.0625 Detail : Efficiency of parameter 1 dropped below 15.00% (eps = 11.38%) in chain 3. Set scale to 0.125 Detail : Efficiency of parameter 2 dropped below 15.00% (eps = 11.62%) in chain 3. Set scale to 0.125 Detail : Efficiency of parameter 3 dropped below 15.00% (eps = 14.35%) in chain 3. Set scale to 0.125 Detail : Efficiency of parameter 0 dropped below 15.00% (eps = 6.60%) in chain 4. Set scale to 0.0625 Detail : Efficiency of parameter 1 dropped below 15.00% (eps = 11.28%) in chain 4. Set scale to 0.125 Detail : Efficiency of parameter 2 dropped below 15.00% (eps = 10.22%) in chain 4. Set scale to 0.125 Detail : Efficiency of parameter 3 dropped below 15.00% (eps = 14.70%) in chain 4. Set scale to 0.125 Detail : --> Iteration 9000 Detail : --> Iteration 10000 Detail : --> Iteration 11000 Detail : --> Iteration 12000 Detail : * Convergence status: Set of 5 Markov chains converged within 12000 iterations. Detail : * Efficiency status: Efficiencies not within pre-defined range. Detail : - Efficiencies: Detail : Efficiency of parameter 3 dropped below 15.00% (eps = 13.60%) in chain 1. Set scale to 0.125 Detail : --> Iteration 13000 Detail : --> Iteration 14000 Detail : --> Iteration 15000 Detail : --> Iteration 16000 Detail : * Convergence status: Set of 5 Markov chains converged within 16000 iterations. Detail : * Efficiency status: Efficiencies within pre-defined ranges. Summary : --> Set of 5 Markov chains converged within 16000 iterations and all scales are adjusted. Summary : --> Markov chains ran for 16001 iterations. Detail : --> Average efficiencies: Detail : --> parameter 0 : 23.48% Detail : --> parameter 1 : 22.02% Detail : --> parameter 2 : 20.28% Detail : --> parameter 3 : 25.77% Detail : --> Average scale factors: Detail : --> parameter 0 : 6.25% Detail : --> parameter 1 : 12.50% Detail : --> parameter 2 : 12.50% Detail : --> parameter 3 : 12.50% Summary : Run Metropolis MCMC... Summary : --> Perform MCMC run with 5 chains, each with 10000 iterations. Detail : --> iteration number 1000 (10.00%) Detail : --> iteration number 2000 (20.00%) Detail : --> iteration number 3000 (30.00%) Detail : --> iteration number 4000 (40.00%) Detail : --> iteration number 5000 (50.00%) Detail : --> iteration number 6000 (60.00%) Detail : --> iteration number 7000 (70.00%) Detail : --> iteration number 8000 (80.00%) Detail : --> iteration number 9000 (90.00%) Detail : --> iteration number 10000 (100.00%) Summary : --> Markov chains ran for 10000 iterations. Detail : --> Global mode from MCMC: Detail : --> parameter 0: 38.71 Detail : --> parameter 1: 19.36 Detail : --> parameter 2: 0.01356 Detail : --> parameter 3: 0.9235 Summary : --------------------------------------------------- Summary : Fit summary for model 'BCEfficiencyFitter with f1': Summary : Number of parameters: Npar = 4 Summary : Number of data points: Ndata = 20 Summary : Number of degrees of freedom: Summary : NDoF = Ndata - Npar = 16 Summary : Best fit parameters (global): Summary : p0 = 38.7 Summary : p1 = 19.2 Summary : p2 = 0.0148 Summary : p3 = 0.92 Summary : Goodness-of-fit test: Summary : p-value = 0 Summary : --------------------------------------------------- Summary : Printing all marginalized distributions (4 x 1D + 6 x 2D = 10) into file distributions.ps