基于Matplotlib按坐标轴设置图表点颜色的技术咨询

需要在Matplotlib图表中实现以下两种样式之一：

• 将所有x轴负数值对应的点设为红色，正数值对应的点设为绿色；
• 仅将x轴数值最小的3个点设为红色，最大的3个点设为绿色。

现有代码：

from matplotlib import pyplot as plt

ex_x = [res1,res2,res3,res4,res5,res6,res7,res8,res9,res10,res11,res12,res13,res14,res15,res16,res17,res18,res19,res20,res21,res22,res23,res24,res25,res26,res27,res28,res29,res30,res31,res32,res33,res34,res35,res36,res37,res38,res39,res40,res41,res42,res43,res44,res45,res46,res47]
ex_y = ["1","2","2.1","2.1.1","2.2","3","3.1","3.2","4","4.1","4.1.1","4.1.1A)","4.1.1B)","4.1.2","4.2","4.2A)","4.2B)","4.3","4.4","5","5.1","5.1.1","5.1.2","5.1.2A)","5.1.2B)","5.1.3","5.1.4","5.2","5.2.1","5.2.1A)","5.2.1B)","5.2.1C)","5.2.2","5.2.3","5.2.3A)","5.2.3B)","5.2.4","5.2.5","6","6.1","7","7.1","7.2","8.1","8.1A)","8.1B)","8.2"]

l_x = [0, 0]
l_y = [47, 0]

z_x = [-10, 10]
z_y = [0, 0]

plt.grid(True)

for x in range(-10,10):
    plt.plot(l_x, l_y, color = "k", linewidth = 2)

plt.plot(z_x, z_y, color = 'k', linewidth = 1)
plt.plot(ex_x, ex_y, marker='.')
plt.gca().invert_yaxis()
plt.title("Perfil Neuropsicológico")
plt.tight_layout()
plt.show()

方案一：按x轴正负值设置颜色 #

用scatter替代plot，遍历每个数据点，根据x值正负分配对应颜色：

from matplotlib import pyplot as plt

# 替换res1-res47为实际数值
ex_x = [res1,res2,res3,res4,res5,res6,res7,res8,res9,res10,res11,res12,res13,res14,res15,res16,res17,res18,res19,res20,res21,res22,res23,res24,res25,res26,res27,res28,res29,res30,res31,res32,res33,res34,res35,res36,res37,res38,res39,res40,res41,res42,res43,res44,res45,res46,res47]
ex_y = ["1","2","2.1","2.1.1","2.2","3","3.1","3.2","4","4.1","4.1.1","4.1.1A)","4.1.1B)","4.1.2","4.2","4.2A)","4.2B)","4.3","4.4","5","5.1","5.1.1","5.1.2","5.1.2A)","5.1.2B)","5.1.3","5.1.4","5.2","5.2.1","5.2.1A)","5.2.1B)","5.2.1C)","5.2.2","5.2.3","5.2.3A)","5.2.3B)","5.2.4","5.2.5","6","6.1","7","7.1","7.2","8.1","8.1A)","8.1B)","8.2"]

l_x = [0, 0]
l_y = [47, 0]

z_x = [-10, 10]
z_y = [0, 0]

plt.grid(True)

for x in range(-10,10):
    plt.plot(l_x, l_y, color = "k", linewidth = 2)

plt.plot(z_x, z_y, color = 'k', linewidth = 1)

# 按x值正负分配颜色
colors = []
for x_val in ex_x:
    if x_val < 0:
        colors.append('red')
    elif x_val > 0:
        colors.append('green')
    else:
        colors.append('black')  # x=0时默认黑色，可自行调整

plt.scatter(ex_x, ex_y, marker='.', color=colors)

plt.gca().invert_yaxis()
plt.title("Perfil Neuropsicológico")
plt.tight_layout()
plt.show()

方案二：按x轴极值点设置颜色 #

先找出x值最小和最大的3个点的索引，再给对应点分配颜色：

from matplotlib import pyplot as plt

# 替换res1-res47为实际数值
ex_x = [res1,res2,res3,res4,res5,res6,res7,res8,res9,res10,res11,res12,res13,res14,res15,res16,res17,res18,res19,res20,res21,res22,res23,res24,res25,res26,res27,res28,res29,res30,res31,res32,res33,res34,res35,res36,res37,res38,res39,res40,res41,res42,res43,res44,res45,res46,res47]
ex_y = ["1","2","2.1","2.1.1","2.2","3","3.1","3.2","4","4.1","4.1.1","4.1.1A)","4.1.1B)","4.1.2","4.2","4.2A)","4.2B)","4.3","4.4","5","5.1","5.1.1","5.1.2","5.1.2A)","5.1.2B)","5.1.3","5.1.4","5.2","5.2.1","5.2.1A)","5.2.1B)","5.2.1C)","5.2.2","5.2.3","5.2.3A)","5.2.3B)","5.2.4","5.2.5","6","6.1","7","7.1","7.2","8.1","8.1A)","8.1B)","8.2"]

l_x = [0, 0]
l_y = [47, 0]

z_x = [-10, 10]
z_y = [0, 0]

plt.grid(True)

for x in range(-10,10):
    plt.plot(l_x, l_y, color = "k", linewidth = 2)

plt.plot(z_x, z_y, color = 'k', linewidth = 1)

# 获取x值排序后的索引
sorted_indices = sorted(range(len(ex_x)), key=lambda i: ex_x[i])
min_3_indices = sorted_indices[:3]  # 最小3个点的索引
max_3_indices = sorted_indices[-3:] # 最大3个点的索引

# 分配颜色：默认灰色，极值点设为红/绿色
colors = ['gray'] * len(ex_x)
for idx in min_3_indices:
    colors[idx] = 'red'
for idx in max_3_indices:
    colors[idx] = 'green'

plt.scatter(ex_x, ex_y, marker='.', color=colors)

plt.gca().invert_yaxis()
plt.title("Perfil Neuropsicológico")
plt.tight_layout()
plt.show()

注意：代码中res1-res47需替换为实际数值，否则会触发未定义变量错误。

内容的提问来源于stack exchange，提问作者Vinizilin XD