Replace sas-temper

# seed the random number generator

np.random.seed(int(tm.time()) + int(os.getpid()))

# add a little feedback to the user

print('model started:', end='', flush=True)

# this loop creates the set of models

for i in range(0,sasTemperConf.models):

    # add a little feedback to the user

    feedbk = "model %d started" %(i+1)

    print(str(feedbk), end='', flush=True)

    results[i], models[i], models_usm[i] = engine.sa_control(sasTemperConf,modelConf,experimentalData)

    #output the results of the single fitting

    output.outputSingleRes(sasTemperConf, experimentalData, models[i], i, results[i])

    # add a little feedback to the user 

    if ((i+1) % 10==0):

        print('#', end='', flush=True)

# and output the analysis of the set of models found,

# but only if you are generating more than 3 models.