在 Line2d 中更改线条颜色 - Python GIF
Changing line color in Line2d - Python GIF
我创建了一个算法来解决 TSP 问题。我想以显示行进距离的 GIF 形式呈现结果。为此，我使用 Matplotlib 库中的 line2d。每次汽车到达起点，我都想改变线条的颜色。我目前正在为此使用 line2d.set_color () 函数。不幸的是，它会导致整条道路的颜色发生变化。我的目标是在任何给定时刻更改颜色，同时保持以前的颜色。你能帮我解决这个问题吗？
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
import random
from gurobipy import Model, GRB, quicksum
from matplotlib import collections as mc
rnd = np.random
rnd.seed()
n = 20 # numbre of clients
xc = rnd.rand(n + 1) * 200
yc = rnd.rand(n + 1) * 100
xc[0] = 100
yc[0] = 50
N = [i for i in range(1, n + 1)]
V = [0] + N
A = [(i, j) for i in V for j in V if i != j]
c = {(i, j): np.hypot(xc[i] - xc[j], yc[i] - yc[j]) for i, j in A}
Q = 30
# q = {i: random.choice([-5, -4, -3, -2, -1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]) for i in N}
# q = {i: random.choice([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]) for i in N}
q = {i: rnd.randint(1, 10) for i in N}
# a = [['x', xc], ['y', yc], ['Capacity', q]]
# for i in range(len(a)) :
# for j in range(len(a[i])):
# print(a[i][j], end=" ")
# print()
mdl = Model('CVRP')
x = mdl.addVars(A, vtype=GRB.BINARY)
u = mdl.addVars(N, vtype=GRB.CONTINUOUS)
mdl.modelSense = GRB.MINIMIZE
mdl.setObjective(quicksum(x[i, j] * c[i, j] for i, j in A))
mdl.addConstrs(quicksum(x[i, j] for j in V if j != i) == 1 for i in N)
mdl.addConstrs(quicksum(x[i, j] for i in V if i != j) == 1 for j in N)
mdl.addConstrs((x[i, j] == 1) >> (u[i] + q[j] == u[j])
for i, j in A if i != 0 and j != 0)
mdl.addConstrs(u[i] >= q[i] for i in N)
mdl.addConstrs(u[i] <= Q for i in N)
mdl.Params.MIPGap = 0.1
mdl.Params.TimeLimit = 30 # seconds
mdl.optimize()
active_arcs = [a for a in A if x[a].x > 0.99]
final_arcs = []
roads = 0
while len(active_arcs) != 0:
temp_arcs = [active_arcs[0]]
for i, j in temp_arcs:
temp_j = j
i2 = 0
while temp_j != 0:
for i, j in active_arcs:
if temp_j == i and temp_j != 0:
temp_arcs.append(active_arcs[i2])
temp_j = j
i2 += 1
i2 = 0
i = 0
i2 = 0
while i < len(temp_arcs):
while i2 < len(active_arcs):
if temp_arcs[i] == active_arcs[i2]:
active_arcs.pop(i2)
i2 += 1
i += 1
i2 = 0
final_i = 0
while final_i < len(temp_arcs):
final_arcs.append(temp_arcs[final_i])
final_i += 1
temp_arcs.clear()
roads += 1
plt.plot(xc[0], yc[0], c='r', marker='s')
for i in N:
if q[i] > 0:
plt.scatter(xc[i], yc[i], c='b')
else:
plt.scatter(xc[i], yc[i], c='y')
plt.show()
print('Liczba wykonanych tras: ', roads)
# for i, j in final_arcs:
# plt.plot([xc[i], xc[j]], [yc[i], yc[j]], color, zorder=0)
# if j == 0:
# if len(colors_base) != 0:
# c = random.randint(0, len(colors_base) - 1)
# color = colors_base[c]
# colors_base.pop(c)
#
# plt.show()
fig, ax = plt.subplots()
ax.set_xlim(0, 200)
ax.set_ylim(0, 100)
x_data, y_data = [], []
ln1, ln2 = [], []
ln, = plt.plot([], [], zorder=0)
colors_base = ['r', 'cyan', 'black', 'orange', 'm', 'darkorchid', 'dimgray', 'indigo', 'lawngreen', 'darkred']
ln.set_color('g')
plt.plot(xc[0], yc[0], 'r', marker='s')
for i in N:
if q[i] > 0:
plt.scatter(xc[i], yc[i], c='b')
else:
plt.scatter(xc[i], yc[i], c='y')
tmp = 0
for i, j in final_arcs:
x_data_tmp = [xc[i], xc[j]]
y_data_tmp = [yc[i], yc[j]]
x_data.append(x_data_tmp)
y_data.append(y_data_tmp)
def update(p):
ln1.append(x_data[p])
ln2.append(y_data[p])
ln.set_data(ln1, ln2)
for i, j in final_arcs:
if yc[i] == 50 and y_data[p] == [yc[i], yc[j]] and p != 0:
if len(colors_base) != 0:
color = colors_base[0]
ln.set_color(color)
colors_base.pop(0)
return ln,
ani = FuncAnimation(fig, update, frames=len(final_arcs), interval=1000)
ani.save('animation.gif', fps=3)
# ani.save('animation.mp4', fps=3)
plt.show()
收到的 gif 是这样的：
enter image description here
一种可能的解决方案：
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
import random
from gurobipy import Model, GRB, quicksum
from matplotlib import collections as mc
rnd = np.random
rnd.seed()
n = 20 # numbre of clients
xc = rnd.rand(n + 1) * 200
yc = rnd.rand(n + 1) * 100
xc[0] = 100
yc[0] = 50
N = [i for i in range(1, n + 1)]
V = [0] + N
A = [(i, j) for i in V for j in V if i != j]
c = {(i, j): np.hypot(xc[i] - xc[j], yc[i] - yc[j]) for i, j in A}
Q = 30
# q = {i: random.choice([-5, -4, -3, -2, -1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]) for i in N}
# q = {i: random.choice([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]) for i in N}
q = {i: rnd.randint(1, 10) for i in N}
mdl = Model('CVRP')
x = mdl.addVars(A, vtype=GRB.BINARY)
u = mdl.addVars(N, vtype=GRB.CONTINUOUS)
mdl.modelSense = GRB.MINIMIZE
mdl.setObjective(quicksum(x[i, j] * c[i, j] for i, j in A))
mdl.addConstrs(quicksum(x[i, j] for j in V if j != i) == 1 for i in N)
mdl.addConstrs(quicksum(x[i, j] for i in V if i != j) == 1 for j in N)
mdl.addConstrs((x[i, j] == 1) >> (u[i] + q[j] == u[j])
for i, j in A if i != 0 and j != 0)
mdl.addConstrs(u[i] >= q[i] for i in N)
mdl.addConstrs(u[i] <= Q for i in N)
mdl.Params.MIPGap = 0.1
mdl.Params.TimeLimit = 30 # seconds
mdl.optimize()
active_arcs = [a for a in A if x[a].x > 0.99]
final_arcs = []
roads = 0
while len(active_arcs) != 0:
temp_arcs = [active_arcs[0]]
for i, j in temp_arcs:
temp_j = j
i2 = 0
while temp_j != 0:
for i, j in active_arcs:
if temp_j == i and temp_j != 0:
temp_arcs.append(active_arcs[i2])
temp_j = j
i2 += 1
i2 = 0
i = 0
i2 = 0
while i < len(temp_arcs):
while i2 < len(active_arcs):
if temp_arcs[i] == active_arcs[i2]:
active_arcs.pop(i2)
i2 += 1
i += 1
i2 = 0
final_i = 0
while final_i < len(temp_arcs):
final_arcs.append(temp_arcs[final_i])
final_i += 1
temp_arcs.clear()
roads += 1
fig, ax = plt.subplots()
ax.set_xlim(0, 200)
ax.set_ylim(0, 100)
x_data, y_data = [], []
ln1, ln2 = [], []
ln, = ax.plot([], [], zorder=0)
colors_base = ['r', 'cyan', 'black', 'orange', 'm', 'darkorchid', 'dimgray', 'indigo', 'lawngreen', 'darkred']
ln.set_color('g')
plt.plot(xc[0], yc[0], 'r', marker='s')
for i in N:
if q[i] > 0:
plt.scatter(xc[i], yc[i], c='b')
else:
plt.scatter(xc[i], yc[i], c='y')
# precompute each line coordinates
lines_data = []
xd, yd = [], []
for i, j in final_arcs:
xd.append(xc[i])
yd.append(yc[i])
if j == 0:
xd.append(xc[0])
yd.append(yc[0])
lines_data.append([xd, yd])
xd, yd = [], []
# add empty lines with the specified colors
lines = []
for i in range(len(lines_data)):
lines.append(ax.plot([], [], color=colors_base[i])[0])
def update(p):
global current_line, up_to_point
# reset after each animation cycle is complete
if current_line > len(lines_data) - 1:
current_line = 0
for l in lines:
l.set_data([], [])
up_to_point += 1
xd, yd = lines_data[current_line]
lines[current_line].set_data(xd[:up_to_point], yd[:up_to_point])
if len(xd[:up_to_point]) == len(xd):
current_line += 1
up_to_point = 1
# index of the line to animate
current_line = 0
# draw the current line up to the point of this index
up_to_point = 1
ani = FuncAnimation(fig, update, frames=len(final_arcs), interval=1000)
ani.save('animation.gif', fps=3)
# ani.save('animation.mp4', fps=3)
plt.show()
我创建了一个算法来解决 TSP 问题。我想以显示行进距离的 GIF 形式呈现结果。为此，我使用 Matplotlib 库中的 line2d。每次汽车到达起点，我都想改变线条的颜色。我目前正在为此使用 line2d.set_color () 函数。不幸的是，它会导致整条道路的颜色发生变化。我的目标是在任何给定时刻更改颜色，同时保持以前的颜色。你能帮我解决这个问题吗？
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
import random
from gurobipy import Model, GRB, quicksum
from matplotlib import collections as mc
rnd = np.random
rnd.seed()
n = 20 # numbre of clients
xc = rnd.rand(n + 1) * 200
yc = rnd.rand(n + 1) * 100
xc[0] = 100
yc[0] = 50
N = [i for i in range(1, n + 1)]
V = [0] + N
A = [(i, j) for i in V for j in V if i != j]
c = {(i, j): np.hypot(xc[i] - xc[j], yc[i] - yc[j]) for i, j in A}
Q = 30
# q = {i: random.choice([-5, -4, -3, -2, -1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]) for i in N}
# q = {i: random.choice([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]) for i in N}
q = {i: rnd.randint(1, 10) for i in N}
# a = [['x', xc], ['y', yc], ['Capacity', q]]
# for i in range(len(a)) :
# for j in range(len(a[i])):
# print(a[i][j], end=" ")
# print()
mdl = Model('CVRP')
x = mdl.addVars(A, vtype=GRB.BINARY)
u = mdl.addVars(N, vtype=GRB.CONTINUOUS)
mdl.modelSense = GRB.MINIMIZE
mdl.setObjective(quicksum(x[i, j] * c[i, j] for i, j in A))
mdl.addConstrs(quicksum(x[i, j] for j in V if j != i) == 1 for i in N)
mdl.addConstrs(quicksum(x[i, j] for i in V if i != j) == 1 for j in N)
mdl.addConstrs((x[i, j] == 1) >> (u[i] + q[j] == u[j])
for i, j in A if i != 0 and j != 0)
mdl.addConstrs(u[i] >= q[i] for i in N)
mdl.addConstrs(u[i] <= Q for i in N)
mdl.Params.MIPGap = 0.1
mdl.Params.TimeLimit = 30 # seconds
mdl.optimize()
active_arcs = [a for a in A if x[a].x > 0.99]
final_arcs = []
roads = 0
while len(active_arcs) != 0:
temp_arcs = [active_arcs[0]]
for i, j in temp_arcs:
temp_j = j
i2 = 0
while temp_j != 0:
for i, j in active_arcs:
if temp_j == i and temp_j != 0:
temp_arcs.append(active_arcs[i2])
temp_j = j
i2 += 1
i2 = 0
i = 0
i2 = 0
while i < len(temp_arcs):
while i2 < len(active_arcs):
if temp_arcs[i] == active_arcs[i2]:
active_arcs.pop(i2)
i2 += 1
i += 1
i2 = 0
final_i = 0
while final_i < len(temp_arcs):
final_arcs.append(temp_arcs[final_i])
final_i += 1
temp_arcs.clear()
roads += 1
plt.plot(xc[0], yc[0], c='r', marker='s')
for i in N:
if q[i] > 0:
plt.scatter(xc[i], yc[i], c='b')
else:
plt.scatter(xc[i], yc[i], c='y')
plt.show()
print('Liczba wykonanych tras: ', roads)
# for i, j in final_arcs:
# plt.plot([xc[i], xc[j]], [yc[i], yc[j]], color, zorder=0)
# if j == 0:
# if len(colors_base) != 0:
# c = random.randint(0, len(colors_base) - 1)
# color = colors_base[c]
# colors_base.pop(c)
#
# plt.show()
fig, ax = plt.subplots()
ax.set_xlim(0, 200)
ax.set_ylim(0, 100)
x_data, y_data = [], []
ln1, ln2 = [], []
ln, = plt.plot([], [], zorder=0)
colors_base = ['r', 'cyan', 'black', 'orange', 'm', 'darkorchid', 'dimgray', 'indigo', 'lawngreen', 'darkred']
ln.set_color('g')
plt.plot(xc[0], yc[0], 'r', marker='s')
for i in N:
if q[i] > 0:
plt.scatter(xc[i], yc[i], c='b')
else:
plt.scatter(xc[i], yc[i], c='y')
tmp = 0
for i, j in final_arcs:
x_data_tmp = [xc[i], xc[j]]
y_data_tmp = [yc[i], yc[j]]
x_data.append(x_data_tmp)
y_data.append(y_data_tmp)
def update(p):
ln1.append(x_data[p])
ln2.append(y_data[p])
ln.set_data(ln1, ln2)
for i, j in final_arcs:
if yc[i] == 50 and y_data[p] == [yc[i], yc[j]] and p != 0:
if len(colors_base) != 0:
color = colors_base[0]
ln.set_color(color)
colors_base.pop(0)
return ln,
ani = FuncAnimation(fig, update, frames=len(final_arcs), interval=1000)
ani.save('animation.gif', fps=3)
# ani.save('animation.mp4', fps=3)
plt.show()
收到的 gif 是这样的：
enter image description here
一种可能的解决方案：
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
import random
from gurobipy import Model, GRB, quicksum
from matplotlib import collections as mc
rnd = np.random
rnd.seed()
n = 20 # numbre of clients
xc = rnd.rand(n + 1) * 200
yc = rnd.rand(n + 1) * 100
xc[0] = 100
yc[0] = 50
N = [i for i in range(1, n + 1)]
V = [0] + N
A = [(i, j) for i in V for j in V if i != j]
c = {(i, j): np.hypot(xc[i] - xc[j], yc[i] - yc[j]) for i, j in A}
Q = 30
# q = {i: random.choice([-5, -4, -3, -2, -1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]) for i in N}
# q = {i: random.choice([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]) for i in N}
q = {i: rnd.randint(1, 10) for i in N}
mdl = Model('CVRP')
x = mdl.addVars(A, vtype=GRB.BINARY)
u = mdl.addVars(N, vtype=GRB.CONTINUOUS)
mdl.modelSense = GRB.MINIMIZE
mdl.setObjective(quicksum(x[i, j] * c[i, j] for i, j in A))
mdl.addConstrs(quicksum(x[i, j] for j in V if j != i) == 1 for i in N)
mdl.addConstrs(quicksum(x[i, j] for i in V if i != j) == 1 for j in N)
mdl.addConstrs((x[i, j] == 1) >> (u[i] + q[j] == u[j])
for i, j in A if i != 0 and j != 0)
mdl.addConstrs(u[i] >= q[i] for i in N)
mdl.addConstrs(u[i] <= Q for i in N)
mdl.Params.MIPGap = 0.1
mdl.Params.TimeLimit = 30 # seconds
mdl.optimize()
active_arcs = [a for a in A if x[a].x > 0.99]
final_arcs = []
roads = 0
while len(active_arcs) != 0:
temp_arcs = [active_arcs[0]]
for i, j in temp_arcs:
temp_j = j
i2 = 0
while temp_j != 0:
for i, j in active_arcs:
if temp_j == i and temp_j != 0:
temp_arcs.append(active_arcs[i2])
temp_j = j
i2 += 1
i2 = 0
i = 0
i2 = 0
while i < len(temp_arcs):
while i2 < len(active_arcs):
if temp_arcs[i] == active_arcs[i2]:
active_arcs.pop(i2)
i2 += 1
i += 1
i2 = 0
final_i = 0
while final_i < len(temp_arcs):
final_arcs.append(temp_arcs[final_i])
final_i += 1
temp_arcs.clear()
roads += 1
fig, ax = plt.subplots()
ax.set_xlim(0, 200)
ax.set_ylim(0, 100)
x_data, y_data = [], []
ln1, ln2 = [], []
ln, = ax.plot([], [], zorder=0)
colors_base = ['r', 'cyan', 'black', 'orange', 'm', 'darkorchid', 'dimgray', 'indigo', 'lawngreen', 'darkred']
ln.set_color('g')
plt.plot(xc[0], yc[0], 'r', marker='s')
for i in N:
if q[i] > 0:
plt.scatter(xc[i], yc[i], c='b')
else:
plt.scatter(xc[i], yc[i], c='y')
# precompute each line coordinates
lines_data = []
xd, yd = [], []
for i, j in final_arcs:
xd.append(xc[i])
yd.append(yc[i])
if j == 0:
xd.append(xc[0])
yd.append(yc[0])
lines_data.append([xd, yd])
xd, yd = [], []
# add empty lines with the specified colors
lines = []
for i in range(len(lines_data)):
lines.append(ax.plot([], [], color=colors_base[i])[0])
def update(p):
global current_line, up_to_point
# reset after each animation cycle is complete
if current_line > len(lines_data) - 1:
current_line = 0
for l in lines:
l.set_data([], [])
up_to_point += 1
xd, yd = lines_data[current_line]
lines[current_line].set_data(xd[:up_to_point], yd[:up_to_point])
if len(xd[:up_to_point]) == len(xd):
current_line += 1
up_to_point = 1
# index of the line to animate
current_line = 0
# draw the current line up to the point of this index
up_to_point = 1
ani = FuncAnimation(fig, update, frames=len(final_arcs), interval=1000)
ani.save('animation.gif', fps=3)
# ani.save('animation.mp4', fps=3)
plt.show()