python - 根据颜色图在 2D 中颜色误差条

Question

乍一看，这是一个相当简单的问题，但我一直无法找到解决方案。这里有一个类似的（旧）问题，但给出的最接近的答案似乎不适用于两个维度的误差线。

我需要生成一个“误差线”图，其中两个误差线（在 x 和 y 维度中）根据cc数组中的值进行着色。

编码：

import numpy as np
import matplotlib.pyplot as plt

# Some random data
aa = np.array([3.581, -0.721, 0.137, 0.645, 0.12, 0., -3.236, 0.248, -5.687, 0.816])
e_aa = np.array([0.111, 0.991, 0.446, 0.07, 0.814, 0., 0.088, 0.805, 0.178, 0.552])
bb = np.array([6.671, 1.219, 0.119, -1.972, 1.834, 0., 4.93, 1.833, -11.542, -0.439])
e_bb = np.array([0.143, 1.316, 0.609, 0.094, 1.127, 0., 0.116, 1.227, 0.216, 0.726])

# The color array
cc = np.array([0.50344083, 0.49961867, 0.5055576, 0.48970365, 0.5078516, 0.49643923, 0.50089907, 0.50129157, 0.49627974, 0.5052376])

plt.errorbar(aa, bb, yerr=e_bb, xerr=e_aa, fmt='none', ecolor=cc)
plt.show()

失败：

ValueError: Invalid RGBA argument: 0.50344083

无论我使用ecolororcolor论点。

有没有办法解决？

标签： pythonmatplotlibcolor-mapping

Answer 1

我找到了解决方案。诀窍是使用matplotlib.cm.

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from matplotlib.colors import Normalize

# Some random data
aa = np.array([3.581, -0.721, 0.137, 0.645, 0.12, 0., -3.236, 0.248, -5.687, 0.816])
e_aa = np.array([0.111, 0.991, 0.446, 0.07, 0.814, 0., 0.088, 0.805, 0.178, 0.552])
bb = np.array([6.671, 1.219, 0.119, -1.972, 1.834, 0., 4.93, 1.833, -11.542, -0.439])
e_bb = np.array([0.143, 1.316, 0.609, 0.094, 1.127, 0., 0.116, 1.227, 0.216, 0.726])

# The color array
cc = np.array([0.50344083, 0.49961867, 0.5055576, 0.48970365, 0.5078516, 0.49643923, 0.50089907, 0.50129157, 0.49627974, 0.5052376])

# Define function to map (normalized) values in `cc` to a colormap
cmap = cm.viridis
norm = Normalize(vmin=cc.min(), vmax=cc.max())

plt.errorbar(aa, bb, yerr=e_bb, xerr=e_aa, fmt='none', ecolor=cmap(norm(cc)))
plt.show()