python3 -m fmpy simulate  --output-file ModelicaTest_trunk_ModelicaTest.Math.Random.TestRandomNumbers_res.csv --start-time 0 --stop-time 1.5 --timeout 50 --relative-tolerance 1e-06 --interface-type ModelExchange --solver CVode --output-interval 1.5 ModelicaTest_trunk_ModelicaTest_Math_Random_TestRandomNumbers.fmu
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
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