def currscript_gradient(sensorloc): #Same as above,
i = 0
gradient = 0
for ele in avgspace_some:
curr_obj = ops.optsenpmt(ele,no_sensors,dim,alpha,sigma)
gradient+=curr_obj.gradient_score(sensorloc)
i += 1
return 0-gradient/i
def currscript_score(sensorloc): #To give a score function handle to the PSOSOLVER so that it can just ask for the value at a given SENSORLOC
# and not bother about the parameters. It also helps calculate the expectation.
i = 0
print ('score called ')
score = 0
gradient = 0
for ele in avgspace_some:
curr_obj = ops.optsenpmt(ele,no_sensors,dim,alpha,sigma)
score += curr_obj.score(sensorloc)
# print(curr_obj.score(sensorloc));
i+=1
return 0 - score / i
