def __init__(self, p_ind=0):

self.palette = ['darkgreen', 'tomato', 'yellow', 'darkblue', 'darkviolet', 'indianred', 'yellowgreen', 'mediumblue', 'cyan', 'black', 'indigo', 'pink', 'lime', 'sienna', 'plum', 'deepskyblue', 'forestgreen', 'fuchsia', 'brown', 'turquoise', 'aliceblue', 'blueviolet', 'rosybrown', 'powderblue', 'lightblue', 'skyblue', 'lightskyblue', 'steelblue', 'dodgerblue', 'lightslategray', 'lightslategrey', 'slategray', 'slategrey', 'lightsteelblue', 'cornflowerblue', 'royalblue', 'ghostwhite', 'lavender', 'midnightblue', 'navy', 'darkblue', 'blue', 'slateblue', 'darkslateblue', 'mediumslateblue', 'mediumpurple', 'rebeccapurple', 'darkorchid', 'darkviolet', 'mediumorchid']

self.color_palette = ['lightcoral', 'firebrick', 'maroon', 'darkred', 'red', 'salmon', 'darksalmon', 'coral', 'orangered', 'lightsalmon', 'chocolate', 'saddlebrown', 'sandybrown', 'olive', 'olivedrab', 'darkolivegreen', 'greenyellow', 'chartreuse', 'lawngreen', 'darkseagreen', 'palegreen', 'lightgreen', 'limegreen', 'green', 'seagreen', 'mediumseagreen', 'springgreen', 'mediumspringgreen', 'mediumaquamarine', 'aquamarine', 'lightseagreen', 'mediumturquoise', 'lightcyan', 'paleturquoise', 'darkslategray', 'darkslategrey', 'teal', 'darkcyan', 'aqua', 'cyan', 'darkturquoise', 'cadetblue', 'thistle', 'violet', 'purple', 'darkmagenta', 'magenta', 'orchid', 'mediumvioletred', 'deeppink', 'hotpink', 'lavenderblush', 'palevioletred', 'crimson', 'lightpink']

self.save_dir = os.path.join("PS"+str(p_ind))

if not os.path.exists(self.save_dir):

os.makedirs(self.save_dir)

def plot_average_fitness(self, avg_fitness):

"""

generations = range(1, len(avg_fitness) + 1)

avg_fitness_values = list(zip(*avg_fitness))

plt.figure(figsize=(10, 6))

plt.plot(generations, avg_fitness_values[0], label='Average Occupied Volume (%)')

plt.plot(generations, avg_fitness_values[1], label='Average Number of Boxes (%)')

plt.plot(generations, avg_fitness_values[2], label='Average Value of Boxes (%)')

plt.xlabel('Generation')

plt.ylabel('Average Fitness')

plt.title('Average Fitness Over Generations')

plt.legend()

plt.savefig(f"{self.save_dir}/fitness_variation.png")

plt.close()

def cuboid_data(self, o, size=(1, 1, 1)):

l, w, h = size

x = [[o[0], o[0] + l, o[0] + l, o[0], o[0]],

[o[0], o[0] + l, o[0] + l, o[0], o[0]],

[o[0], o[0] + l, o[0] + l, o[0], o[0]],

[o[0], o[0] + l, o[0] + l, o[0], o[0]]]

y = [[o[1], o[1], o[1] + w, o[1] + w, o[1]],

[o[1], o[1], o[1] + w, o[1] + w, o[1]],

[o[1], o[1], o[1], o[1], o[1]],

[o[1] + w, o[1] + w, o[1] + w, o[1] + w, o[1] + w]]

z = [[o[2], o[2], o[2], o[2], o[2]],

[o[2] + h, o[2] + h, o[2] + h, o[2] + h, o[2] + h],

[o[2], o[2], o[2] + h, o[2] + h, o[2]],

[o[2], o[2], o[2] + h, o[2] + h, o[2]]]

return np.array(x), np.array(y), np.array(z)

def plot_cuboid(self, pos, size, ax, color):

X, Y, Z = self.cuboid_data(pos, size)

ax.plot_surface(X, Y, Z, color=color, rstride=1, cstride=1)

def draw_final_rank1_solutions(self, population):

color_list = self.palette + self.color_palette

for key, value in population.items():

if value['Rank'] == 1:

fig = plt.figure()

ax = fig.add_subplot(111, projection='3d')

for i, box in enumerate(value['result']):

color = color_list[i % len(color_list)]

pos = box[:3]

size = box[3:]

self.plot_cuboid(pos, size, ax, color=color)

plt.title(f"Visualization of Rank 1 Solution")

plt.savefig(f"{self.save_dir}/R1_{key}.png")

plt.close('all')

def draw_plotly_final_rank1_solutions(self, population):

fig = go.Figure()

color_list = self.palette + self.color_palette

for key, value in population.items():

if value['Rank'] == 1:

for i, box in enumerate(value['result']):

pos = box[:3]

size = box[3:]

color = color_list[i % len(color_list)]

fig.add_trace(go.Mesh3d(

x=[pos[0], pos[0]+size[0], pos[0]+size[0], pos[0], pos[0], pos[0]+size[0], pos[0]+size[0], pos[0]],

y=[pos[1], pos[1], pos[1]+size[1], pos[1]+size[1], pos[1], pos[1], pos[1]+size[1], pos[1]+size[1]],

z=[pos[2], pos[2], pos[2], pos[2], pos[2]+size[2], pos[2]+size[2], pos[2]+size[2], pos[2]+size[2]],

color=color,

opacity=1,

alphahull=0

))

file_name = f"{self.save_dir}/R1_{key}.html"

pio.write_html(fig, file=file_name)

def draw_plotly_true_solution(self, solution):

fig = go.Figure()

color_list = self.palette + self.color_palette

for i, box in enumerate(solution):

pos = box[:3]

size = box[3:]

color = color_list[i % len(color_list)]

fig.add_trace(go.Mesh3d(

x=[pos[0], pos[0]+size[0], pos[0]+size[0], pos[0], pos[0], pos[0]+size[0], pos[0]+size[0], pos[0]],

y=[pos[1], pos[1], pos[1]+size[1], pos[1]+size[1], pos[1], pos[1], pos[1]+size[1], pos[1]+size[1]],

z=[pos[2], pos[2], pos[2], pos[2], pos[2]+size[2], pos[2]+size[2], pos[2]+size[2], pos[2]+size[2]],

color=color,

opacity=1,

alphahull=0

))

file_name = f"{self.save_dir}/TrueSolution.html"

pio.write_html(fig, file=file_name)

def draw_pareto(self, population):

fig = plt.figure()

ax = fig.add_subplot(111, projection='3d')

fitness, number, weight = [], [], []

fitness2, number2, weight2 = [], [], []

for key, value in population.items():

if value['Rank'] == 1:

fitness.append(value['fitness'][0])

number.append(value['fitness'][1])

weight.append(value['fitness'][2])

else:

fitness2.append(value['fitness'][0])

number2.append(value['fitness'][1])

weight2.append(value['fitness'][2])

if len(fitness) > 2:

try:

ax.scatter(fitness2, number2, weight2, c='b', marker='o')

ax.scatter(fitness, number, weight, c='r', marker='o')

triang = mtri.Triangulation(fitness, number)

ax.plot_trisurf(triang, weight, color='red')

ax.set_xlabel('occupied space')

ax.set_ylabel('no of boxes')

ax.set_zlabel('value')

plt.savefig(f"{self.save_dir}/pareto.png")

plt.close(fig)

except Exception as e: