Nilearn中的Matplotlib颜色图

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可视化Nilearn附带的HCP connectome工作台颜色图，可用于在表面上绘制大脑图像。

import numpy as np
import matplotlib.pyplot as plt

from nilearn.plotting.cm import _cmap_d as nilearn_cmaps
from nilearn.plotting import show
import warnings
warnings.filterwarnings("ignore")

nmaps = len(nilearn_cmaps)
a = np.outer(np.arange(0, 1, 0.01), np.ones(10))

# 初始化颜色图
plt.figure(figsize=(10, 4.2))
plt.subplots_adjust(top=0.4, bottom=0.05, left=0.01, right=0.99)

for index, cmap in enumerate(nilearn_cmaps):
    plt.subplot(1, nmaps + 1, index + 1)
    plt.imshow(a, cmap=nilearn_cmaps[cmap])
    plt.axis('off')
    plt.title(cmap, fontsize=10, va='bottom', rotation=90)

plt.figure(figsize=(10, 5))
plt.subplots_adjust(top=0.8, bottom=0.05, left=0.01, right=0.99)
deprecated_cmaps = ['Vega10', 'Vega20', 'Vega20b', 'Vega20c', 'spectral']
m_cmaps = []
for m in plt.cm.datad:
    if not m.endswith("_r") and m not in deprecated_cmaps:
        m_cmaps.append(m)
m_cmaps.sort()

for index, cmap in enumerate(m_cmaps):
    plt.subplot(1, len(m_cmaps) + 1, index + 1)
    plt.imshow(a, cmap=plt.get_cmap(cmap), aspect='auto')
    plt.axis('off')
    plt.title(cmap, fontsize=10, va='bottom', rotation=90)

show()