startTime=0
stopTime=1.5
tolerance=1e-06
numberOfIntervals=2
stepSize=0.75
wasm-jit simulation: simulate(ModelicaTest.Math.Random.TestRandomNumbers,startTime=0,stopTime=1.5,tolerance=1e-06,numberOfIntervals=2,outputFormat="mat",variableFilter="time|result",fileNamePrefix="ModelicaTest_4.1.0_ModelicaTest.Math.Random.TestRandomNumbers",simflags="-alarm=480  -emit_protected -lv LOG_STATS")
LOG_SUCCESS       | info    | The initialization finished successfully without homotopy method.
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
LOG_STATS         | info    | ### STATISTICS ###
LOG_STATS         | info    | events
LOG_STATS         | info    | |       0 state events
LOG_STATS         | info    | |       2 time events
LOG_STATS         | info    | solver: euler-events
LOG_STATS         | info    | |       4 steps taken
LOG_STATS         | info    | |       4 calls of functionODE
LOG_STATS         | info    | |       0 evaluations of jacobian
LOG_STATS         | info    | |       0 error test failures
LOG_STATS         | info    | |       0 convergence test failures
LOG_STATS         | info    | |       0 linear system solves
LOG_SUCCESS       | info    | The simulation finished successfully.