Out_Physic Module Verification

The main response of the connectors is to make decisions for the following consequences according defined probability distribution. So, what should be verified for them is the accuracy of making decisions or selecting the following consequences according defined probability distribution.

By the following code this accuracy has been checked. The below codes can be downloaded from here in Jupyter Notebook format.

Verification:

#Verify Out_Physic Distribution
opr.wipe()

#Define Physical Effect models
opr.PhysicalEffect.fire_point_source(tag=1, minf=0.055, k=1.5)
opr.PhysicalEffect.fire_point_source(tag=2, minf=0.06, k=1.3)
opr.PhysicalEffect.SAFE(3)
opr.PhysicalEffect.VCE_TNT(4)

#Define a DS_LOC
DSLOCOBJ=opr.Connectors.Out_Physic(tag=1,OutFlowTag=1,MaterialsTagList=[1],PhysicalEffectTagList=[1,4,3],PhysProbabilityList=[6,3,1])

Generated=[]
for i in range(100):
    N=1000
    rslt=dict()
    rslt={i:0 for i in DSLOCOBJ.PhysicalEffectTagList}
    for i in range(N):
        obj=DSLOCOBJ.Give1PhysicalEffectModel()
        rslt[obj.tag]=rslt[obj.tag]+1

    for i,j in rslt.items():
        rslt[i]=j/N

    Generated.append(rslt)

plt.figure()

plt.plot([0.6 for i in Generated], color='green',linestyle='dashed')
plt.plot([0.3 for i in Generated], color='green',linestyle='dashed')
plt.plot([0.1 for i in Generated], color='green',linestyle='dashed')

plt.plot([i[1] for i in Generated], label='Reults for PhysicalEffect 1 with Probability 0.6')
plt.plot([i[4] for i in Generated], label='Reults for PhysicalEffect 4 with Probability 0.3')
plt.plot([i[3] for i in Generated], label='Reults for PhysicalEffect 3 with Probability 0.1')

plt.title('Resutls of 1000 sampling in 100 repeating test')
plt.xlabel('Test Number')
plt.ylabel('Frequency of Occurance')
plt.ylim(0,0.8)
plt.legend(loc=2,fontsize = 9);

The result of above code has been shown on the following image:

Results of Out-Physic Connector Sampling

Verification by: Bijan Sayyafzadeh