# Asgard is a fictional realm and it is a capital city appearing in American comic books…

Asgard is a fictional realm and it is a capital city appearing in American comic books published by Marvel Comics. You may have heard about it in Marvel Studio’s movies like Avengers, Thor, and Captain America. Asgard is home to the Asgardians and other living beings such as Demons and Giants. The resources of Asgard are limited and power struggle keeps the wars active among different living beings. A scientist from Earth went to Asgard to analyze the situation. He collected historical data of wars and represented the relationship of population among Asgardians, Demons and Giants living in Asgard by the following difference equations.. Dn -0.01 Gn+1)/10 (3) where A, G and D represent the population of Asgardians, Giants and Demons respectively living in Asgard, n represents the generation number while b, c, k and m are the constants having positive values. The scientist needs to write the code to simulate the above difference equation and help Thor (Contender for the throne of Asgard) to forecast the population of all three living beings in Asgard. As a programmer, you need to write a function in Python and help the scientist. The inputs to the function are initial population of all three living beings Ao, Go and Do, number of generations p and values for constants b, c, k and m. The inputs should be in the same sequence as they are mentioned The required output of the function are three lists (A, G and D) containing the population of all three living beings for all generations up to and including the pth generation, following by the maximum populations(Amax, Gmax and Dmax) of all three living beings over p generations. Remember following rules for your function: The first generation is considered as initial population (zero generation) provided by Ao, Go and Do and is stored as first element in the lists of populations. Sequence of calculating generations of each living being is same as provided in the sequence of above mentioned difference equations. * The population cannot be in fraction and must always be rounded off The population should be approximated to zero if it becomes smaller than zero. In other words, negative population should be approximated to zero. The order of output of function should be A, G, D, Amax, Gmax and Dmax. None of the inputs to the function can be negative. In case any input to the function is provided as negative, then function should be terminated after displaying a message. Include your name and student ID as a comment in the first row of your function file Save your python file with name YourLastName_StudentID. E.g Thor12345678.py Note:Do not print the lists in a formatted manner, simply return them at the end ofcalculations Your submission will be tested against a sample solution with numerous test-cases in addition to the one presented below Sample testing data A,G,D, Amax,Gmax,Dmax asgard(40,25,30,10,0.01,0.01,0.2,0.5) A [40,41,42, 43, 44, 45, 46, 47, 48, 49, 50] G 125, 24, 23, 22, 21, 20, 19, 18, 17, 16,15] D [30, 31, 32, 33, 34, 35,37, 39, 41, 43, 45 Amax = 50 Gmax-25 Dmax45

######################### PYTHON CODE ############################

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def asgard(A_0G_0D_0pbckm):

# Checking for negative input

if True in map(lambda x: x < 0, [A_0, G_0, D_0, p, b, c, k, m]):

print(‘Error. A negative input was provided.nTerminating.’)

return

# Initializing the list of populations with the initial populations

A = [A_0]

G = [G_0]

D = [D_0]

# Looping p times to add the population of ith generation to the lists

for i in range(p):

# calculate the next population

Anext = A[-1] + (k*A[-1] – 0.1*D[-1]) / 5

# if negative, make it 0

if Anext < 0:

Anext = 0

# else, round it off

else:

Anext = round(Anext)

Gnext = G[-1] + (0.001*G[-1]*D[-1] – m*G[-1]) / 10

if Gnext < 0:

Gnext = 0

else:

Gnext = round(Gnext)

Dnext = D[-1] + (b*D[-1]*Anext – c*D[-1] – 0.01*Gnext) / 10

if Dnext < 0:

Dnext = 0

else:

Dnext = round(Dnext)

# Add the calculated populations to the lists

A.append(Anext)

G.append(Gnext)

D.append(Dnext)

# Storing the maxmimum for each of the lists

Amax = max(A)

Gmax = max(G)

Dmax = max(D)

# Returning the required lists and values

return A, G, D, Amax, Gmax, Dmax

###################################################################

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