(cd run_OMSimulator-cs-cvode && /home/hudson/saved_omc/OMSimulator/install/bin/OMSimulator --resultFile=../ModelicaTest_trunk_ModelicaTest.Math.Random.TestRandomNumbers_OMSimulator-cs-cvode_res.mat --stripRoot --tempDir=temp_ModelicaTest_trunk_ModelicaTest_Math_Random_TestRandomNumbers_OMSimulator-cs-cvode_fmu --startTime=0 --stopTime=1.5 --stepSize=0.75 --mode=cs --timeout=240 --tolerance=1e-06 ../ModelicaTest_trunk_ModelicaTest_Math_Random_TestRandomNumbers_OMSimulator-cs-cvode.fmu)
warning: [TestRandomNumbers: resources/0001_TestRandomNumbers.fmu] The FMU lists 48 initial unknowns and exposes 53 initial unknowns.
           * 1: r2 is missing
           * 2: r33 is missing
           * 3: r4a is missing
           * 4: r4b is missing
           * 5: r4c is missing
info:    [TestRandomNumbers: resources/0001_TestRandomNumbers.fmu] The FMU contains bad initial unknowns. This might cause problems, e.g. wrong simulation results.
info: *** FMU Simulation Info ***
     - model     : ModelicaTest.Math.Random.TestRandomNumbers (co-simulation)
     - fmiVersion: 2.0
     - startTime : 0.000000
     - stopTime  : 1.500000
     - tolerance : 1e-06
     - stepSize  : 0.75
LOG_STDOUT        | info    | 
|                 | |       | ... Demonstrate how to generate uniform random numbers with xorshift64*:
LOG_STDOUT        | info    |    random = 0.313593
LOG_STDOUT        | info    |    random = 0.511035
LOG_STDOUT        | info    |    random = 0.0424458
LOG_STDOUT        | info    |    random = 0.686031
LOG_STDOUT        | info    |    random = 0.448066
LOG_STDOUT        | info    | 
|                 | |       | ... Demonstrate how to generate uniform random numbers with xorshift128+ (and 3 different localSeeds):
LOG_STDOUT        | info    |    random = 0.461154, 0.551896, 0.439852
LOG_STDOUT        | info    |    random = 0.0317015, 0.109166, 0.735966
LOG_STDOUT        | info    |    random = 0.919226, 0.174328, 0.584951
LOG_STDOUT        | info    |    random = 0.544481, 0.00908263, 0.516446
LOG_STDOUT        | info    |    random = 0.492459, 0.402873, 0.522502
LOG_STDOUT        | info    | 
|                 | |       | ... Demonstrate how to generate uniform random numbers with xorshift1024*:
LOG_STDOUT        | info    |    random = 0.311559
LOG_STDOUT        | info    |    random = 0.0599521
LOG_STDOUT        | info    |    random = 0.9468
LOG_STDOUT        | info    |    random = 0.0379248
LOG_STDOUT        | info    |    random = 0.67468
info:    Result file: ../ModelicaTest_trunk_ModelicaTest.Math.Random.TestRandomNumbers_OMSimulator-cs-cvode_res.mat (bufferSize=10)
LOG_STDOUT        | info    | 
|                 | |       | ... Demonstrate how to generate uniform random numbers with xorshift64*:
LOG_STDOUT        | info    |    random = 0.313593
LOG_STDOUT        | info    |    random = 0.511035
LOG_STDOUT        | info    |    random = 0.0424458
LOG_STDOUT        | info    |    random = 0.686031
LOG_STDOUT        | info    |    random = 0.448066
LOG_STDOUT        | info    | 
|                 | |       | ... Demonstrate how to generate uniform random numbers with xorshift128+ (and 3 different localSeeds):
LOG_STDOUT        | info    |    random = 0.461154, 0.551896, 0.439852
LOG_STDOUT        | info    |    random = 0.0317015, 0.109166, 0.735966
LOG_STDOUT        | info    |    random = 0.919226, 0.174328, 0.584951
LOG_STDOUT        | info    |    random = 0.544481, 0.00908263, 0.516446
LOG_STDOUT        | info    |    random = 0.492459, 0.402873, 0.522502
LOG_STDOUT        | info    | 
|                 | |       | ... Demonstrate how to generate uniform random numbers with xorshift1024*:
LOG_STDOUT        | info    |    random = 0.311559
LOG_STDOUT        | info    |    random = 0.0599521
LOG_STDOUT        | info    |    random = 0.9468
LOG_STDOUT        | info    |    random = 0.0379248
LOG_STDOUT        | info    |    random = 0.67468
info:    1 warnings
info:    0 errors