  +++++++++++++++++++++++++++++++++++++++++++++
   Two fake Swiss 'towns'                      
   ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 +                                                                +
 +   POPULATION SIZE, MIGRATION, DIVERGENCE, ASSIGNMENT, HISTORY  +
 +   Bayesian inference using the structured coalescent           +
 +                                                                +
 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
  Compiled for a PARALLEL COMPUTER ARCHITECTURE
  One master and 4 compute nodes are available.
  Using Intel AVX (Advanced Vector Extensions)
  Compiled for a SYMMETRIC multiprocessors (GrandCentral)
  PDF output enabled [Letter-size]
  Version 4.2.7   [April-1-2016]
  Program started at   Wed Jul  6 12:54:14 2016
                                                   


Options in use:
---------------

Analysis strategy is BAYESIAN INFERENCE

Proposal distribution:
Parameter group          Proposal type
-----------------------  -------------------
Population size (Theta)  Metropolis sampling
Migration rate      (M)  Metropolis sampling


Prior distribution (Proposal-delta will be tuned to acceptance frequence 0.440000):
Parameter group            Prior type   Minimum    Mean(*)    Maximum    Delta
-------------------------  ------------ ---------- ---------- ---------- ----------
Population size (Theta_1)        Gamma  0.000000   0.010000   0.100000   0.010000 
Population size (Theta_2)        Gamma  0.000000   0.010000   0.100000   0.010000 
Migration 2 to 1 (M)        Gamma  0.000000  500.000000 5000.00000 500.000000
Migration 1 to 2 (M)        Gamma  0.000000  500.000000 5000.00000 500.000000
Ancestor 2 to 1 (D_time)        Gamma  0.000000   0.100000   1.000000   0.100000 
Ancestor 2 to 1 (S_time)        Gamma  0.000000   1.000000  10.000000   1.000000 




Inheritance scalers in use for Thetas (specified scalars=1)
1.00 1.00 1.00 1.00 1.00 

[Each Theta uses the (true) inheritance scalar of the first locus as a reference]


Pseudo-random number generator: Mersenne-Twister                                
Random number seed (with internal timer)           4194572726

Start parameters:
   First genealogy was started using a random tree
   Start parameter values were generated
Connection matrix:
m = average (average over a group of Thetas or M,
s = symmetric migration M, S = symmetric 4Nm,
0 = zero, and not estimated,
* = migration free to vary, Thetas are on diagonal
d = row population split off column population
D = split and then migration
   1 Ascona         * D 
   2 Brissago       * * 



Mutation rate is constant for all loci

Markov chain settings:
   Long chains (long-chains):                              1
      Steps sampled (inc*samples*rep):              10000000
      Steps recorded (sample*rep):                     50000
   Combining over replicates:                             10
   Static heating scheme
      4 chains with  temperatures
       1.00, 1.50, 3.00,1000000.00
      Swapping interval is 1
   Burn-in per replicate (samples*inc):              1000000

Print options:
   Data file:                                         infile
   Haplotyping is turned on:                              NO
   Output file (ASCII text):                    outfile_xBxx
   Output file (PDF):                       outfile_xBxx.pdf
   Posterior distribution:                         bayesfile
   Print data:                                            No
   Print genealogies:                                     No

Summary of data:
Title:                                Two fake Swiss 'towns'
Data file:                                            infile
Datatype:                                     Haplotype data
Number of loci:                                            5
Mutationmodel:
 Locus  Sublocus  Mutationmodel   Mutationmodel parameter
-----------------------------------------------------------------
     1         1 Felsenstein 84  [Bf:0.24 0.26 0.27 0.22, t/t ratio=2.000]
     2         1 Felsenstein 84  [Bf:0.25 0.24 0.26 0.25, t/t ratio=2.000]
     3         1 Felsenstein 84  [Bf:0.25 0.24 0.25 0.26, t/t ratio=2.000]
     4         1 Felsenstein 84  [Bf:0.26 0.24 0.23 0.27, t/t ratio=2.000]
     5         1 Felsenstein 84  [Bf:0.25 0.24 0.27 0.24, t/t ratio=2.000]


Sites per locus
---------------
Locus    Sites
     1     1000
     2     1000
     3     1000
     4     1000
     5     1000

Population                   Locus   Gene copies    
----------------------------------------------------
  1 Ascona                       1        10
  1                              2        10
  1                              3        10
  1                              4        10
  1                              5        10
  2 Brissago                     1        10
  2                              2        10
  2                              3        10
  2                              4        10
  2                              5        10
    Total of all populations     1        20
                                 2        20
                                 3        20
                                 4        20
                                 5        20

