Python Matplotlib-根据系列/子阵列/切片更改颜色

我试图创建一个x，y对的散点图，每个系列都有不同的颜色。我的输入是一个形状为2x3x10的三维numpy数组。换句话说：三组不同的10 x，y对。这个最小的例子从二元正态分布生成成对，但是正如你所看到的，我绘制序列的尝试要么导致序列之间没有颜色差异，要么我最终得到许多不同的颜色（可能是10？）。为了清楚起见，我想以三种不同的颜色结束，三组10 x，y对中的每一组都有一种颜色，或者通过阵列的第三维每个切片都有一种颜色

我该怎么做呢？是否有其他方法定义matplotlib的颜色？或者我应该在前面更改内容并定义多个二维数组而不是三维数组？我对编程相当陌生，对numpy和matplotlib更是如此，但从我收集的资料来看，利用数组的多维性来组织事情是一种很好的做法，但我们非常欣赏这方面的任何其他一般指导原则

pairs = np.random.multivariate_normal((1,5),[[1,0],[0,1]],(10,3)).T

array([[[ 0.49358789,  0.57551098,  2.7029197 ,  0.9437744 , -0.45122972,
          0.05786102,  1.76313729, -0.72469019,  0.53466069,  0.67888213],
        [ 2.88773234,  1.43831903, -0.7427195 , -0.01451867,  1.56491086,
          1.72596764,  1.3953636 ,  1.67816112,  0.02839967,  0.96014133],
        [ 2.52065319, -0.2485202 ,  1.51877564,  2.31216588,  1.35005209,
          1.30100189,  0.63590115,  0.32281779,  2.14906114,  0.1551461 ]],

       [[ 4.85695486,  6.06754   ,  5.93342725,  3.49327716,  6.69661302,
          6.52707216,  4.61195227,  3.22767035,  4.23710242,  7.19532735],
        [ 5.06087316,  4.29734169,  5.66389379,  4.60574012,  4.96619091,
          4.88981834,  3.65294396,  5.65582142,  6.27162773,  6.67958156],
        [ 5.47524034,  4.8989236 ,  3.96246028,  6.31088811,  5.39779792,
          5.67488569,  4.66692489,  4.17364195,  3.69659271,  5.85626402]]])

# Note that the actual graphics were based on another random sample
# than the one listed above, due to a mistake on my end.

plt.plot(pairs[0],pairs[1],'x');plt.show()
plt.scatter(pairs[0],pairs[1]);plt.show()

---

谢谢，这与我想要的非常接近！现在我想知道，当我有3组以上的颜色时，是否可以自动定义任意长度的随机颜色列表。

import numpy as np
import pylab as plt

pairs = np.random.multivariate_normal((1,5),[[1,0],[0,1]],(10,3)).T

"""
pairs = [
    [
        [ 0.49358789,  0.57551098,  2.7029197 ,  0.9437744 , -0.45122972,
          0.05786102,  1.76313729, -0.72469019,  0.53466069,  0.67888213],
        [ 2.88773234,  1.43831903, -0.7427195 , -0.01451867,  1.56491086,
          1.72596764,  1.3953636 ,  1.67816112,  0.02839967,  0.96014133],
        [ 2.52065319, -0.2485202 ,  1.51877564,  2.31216588,  1.35005209,
          1.30100189,  0.63590115,  0.32281779,  2.14906114,  0.1551461 ]
    ],

    [
        [ 4.85695486,  6.06754   ,  5.93342725,  3.49327716,  6.69661302,
          6.52707216,  4.61195227,  3.22767035,  4.23710242,  7.19532735],
        [ 5.06087316,  4.29734169,  5.66389379,  4.60574012,  4.96619091,
          4.88981834,  3.65294396,  5.65582142,  6.27162773,  6.67958156],
        [ 5.47524034,  4.8989236 ,  3.96246028,  6.31088811,  5.39779792,
          5.67488569,  4.66692489,  4.17364195,  3.69659271,  5.85626402]
    ]
]
"""

colors = ["red", "green", "blue"]


# I put the % operator in the color array index so it rolls over
# to the start of the color array when it runs out of colors
# (when there's more sets than preset colors)
for index, group in enumerate(pairs[0]):
    plt.plot(group, pairs[1][index], "x", color=colors[index % len(colors)])
plt.show()

for index, group in enumerate(pairs[0]):
    plt.scatter(group, pairs[1][index], color=colors[index % len(colors)])
plt.show()