droneSpraySimulation/simulation.py at main · mfachrizalg/droneSpraySimulation · GitHub

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from model import sprayAircraft
import matplotlib.pyplot as plt
import numpy as np
#Simulate all cases

#Case 1 for planeHeight = 30 and num_plane = 8
first_sim_values = []
first_sim = sprayAircraft(farm_size=200, simulation_result_dir="Case1", planeSize=12, planeHeight=30, savingMode=True)
print("Case 1")
first_sim.runSimulation(num_plane=8, vel=1, state=lambda i : i % 20 > 0)
first_sim.Animation(name="planeHeight_30-num_plane_8.gif")
first_sim_coverage = first_sim.fertilizerPercentage()
first_sim_values.append([1, first_sim_coverage[-1]])
print(f"Coverage : {first_sim_coverage[-1]*100}%\n")

for i in range(9): #Iterate for 9 times, because we already have 1 data
    first_sim = sprayAircraft(farm_size=200, simulation_result_dir="Case1", planeSize=12, planeHeight=30)
    first_sim.runSimulation(num_plane=8, vel=1, state=lambda i : i % 20 > 0)
    first_sim_values.append([i+2, first_sim.fertilizerPercentage()[-1]])

#Plot the result
first_sim_values = np.array(first_sim_values)
first_sim_mean = first_sim_values[:,1].mean() #Calculate the mean
first_sim_std = first_sim_values[:,1].std()   #Calculate the standard deviation
print(f"Mean : {first_sim_mean} , Standard Deviation : {first_sim_std} ")
plt.scatter(first_sim_values[:,0], first_sim_values[:,1])
plt.show() #Show the plot for Case 1

#Case 2 for planeHeight = 15 and num_plane = 8
second_sim_values = []
second_sim = sprayAircraft(farm_size=200, simulation_result_dir="Case2", planeSize=12, planeHeight=30, savingMode=True)
print("\nCase 2")
second_sim.runSimulation(num_plane=8, vel=1, state=lambda i : i % 20 > 0)
second_sim.Animation(name="planeHeight_15-num_plane_8.gif")
second_sim_coverage = second_sim.fertilizerPercentage()
second_sim_values.append([1, second_sim_coverage[-1]])
print(f"Coverage : {second_sim_coverage[-1]*100}%\n")

for i in range(9): #Iterate for 9 times, because we already have 1 data
    second_sim = sprayAircraft(farm_size=200, simulation_result_dir="Case2", planeSize=12, planeHeight=15)
    second_sim.runSimulation(num_plane=8, vel=1, state=lambda i : i % 20 > 0)
    second_sim_values.append([i+2, second_sim.fertilizerPercentage()[-1]])

#Plot the result
second_sim_values = np.array(second_sim_values)
second_sim_mean = second_sim_values[:,1].mean() #Calculate the mean
second_sim_std = second_sim_values[:,1].std()   #Calculate the standard deviation
print(f"Mean : {second_sim_mean} , Standard Deviation : {second_sim_std} ")
plt.scatter(second_sim_values[:,0], second_sim_values[:,1])
plt.show() #Show the plot for Case 2

#Case 3 for planeHeight = 15 and num_plane = 4
third_sim_values = []
third_sim = sprayAircraft(farm_size=200, simulation_result_dir="Case3", planeSize=12, planeHeight=15, savingMode=True)
print("\nCase 3")
third_sim.runSimulation(num_plane=4, vel=1, state=lambda i : i % 20 > 0)
third_sim.Animation(name="planeHeight_15-num_plane_4.gif")
third_sim_coverage = third_sim.fertilizerPercentage()
third_sim_values.append([1, third_sim_coverage[-1]])
print(f"Coverage : {third_sim_coverage[-1]*100}%\n")

for i in range(9): #Iterate for 9 times, because we already have 1 data
    third_sim = sprayAircraft(farm_size=200, simulation_result_dir="Case3", planeSize=12, planeHeight=15)
    third_sim.runSimulation(num_plane=4, vel=1, state=lambda i : i % 20 > 0)
    third_sim_values.append([i+2, third_sim.fertilizerPercentage()[-1]])

#Plot the result
third_sim_values = np.array(third_sim_values)
third_sim_mean = third_sim_values[:,1].mean() #Calculate the mean
third_sim_std = third_sim_values[:,1].std()   #Calculate the standard deviation
print(f"Mean : {third_sim_mean} , Standard Deviation : {third_sim_std} ")
plt.scatter(third_sim_values[:,0], third_sim_values[:,1])
plt.show() #Show the plot for Case 3

#Case 4 for planeHeight = 30 and num_plane = 4
fourth_sim_values = []
fourth_sim = sprayAircraft(farm_size=200, simulation_result_dir="Case4", planeSize=12, planeHeight=30, savingMode=True)
print("\nCase 4")
fourth_sim.runSimulation(num_plane=4, vel=1, state=lambda i : i % 20 > 0)
fourth_sim.Animation(name="planeHeight_30-num_plane_4.gif")
fourth_sim_coverage = fourth_sim.fertilizerPercentage()
fourth_sim_values.append([1, fourth_sim_coverage[-1]])
print(f"Coverage : {fourth_sim_coverage[-1]*100}%\n")

for i in range(9): #Iterate for 9 times, because we already have 1 data
    fourth_sim = sprayAircraft(farm_size=200, simulation_result_dir="Case4", planeSize=12, planeHeight=30)
    fourth_sim.runSimulation(num_plane=4, vel=1, state=lambda i : i % 20 > 0)
    fourth_sim_values.append([i+2, fourth_sim.fertilizerPercentage()[-1]])

#Plot the result
fourth_sim_values = np.array(fourth_sim_values)
fourth_sim_mean = fourth_sim_values[:,1].mean() #Calculate the mean
fourth_sim_std = fourth_sim_values[:,1].std()   #Calculate the standard deviation
print(f"Mean : {fourth_sim_mean} , Standard Deviation : {fourth_sim_std} ")
plt.scatter(fourth_sim_values[:,0], fourth_sim_values[:,1])
plt.show() #Show the plot for Case 4