Python matplotlib用于打印的大型颜色集

我有很多图，我想在一个图中绘制。我刚开始使用matplotlib，但找不到一种生成许多可分辨颜色的好方法：（可能在HSV上以最大SV循环

我在想类似的事情

args=[]
for i,(x,y) in enumerate(data):
    args.extend([x,y,hsv(i)])
plot(*args)

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有什么建议吗？：）

我认为你的想法是正确的，除了如果你通过colormap

hsv

数字，这些数字分布在（0,1）范围内，颜色会更容易区分：

或者，使用NumPy：

colors = hsv(np.linspace(0, 1.0, len(kinds)))

例如：

import datetime as DT
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import scipy.interpolate as interpolate

dates = [DT.date(year, 9, 1) for year in range(2003, 2009)]
t = list(map(mdates.date2num, dates))
jec = (100, 70, 125, 150, 300, 250)
plt.plot(dates, jec, 'k.', markersize = 20)
new_t = np.linspace(min(t), max(t), 80)
new_dates = map(mdates.num2date, new_t)
kinds = ('cubic', 'quadratic', 'slinear', 'nearest', 'linear', 'zero', 4, 5)
cmap = plt.get_cmap('jet')
colors = cmap(np.linspace(0, 1.0, len(kinds)))
for kind, color in zip(kinds, colors):
    new_jec = interpolate.interp1d(t, jec, kind=kind)(new_t)
    plt.plot(new_t, new_jec, '-', label=str(kind), color=color)
plt.legend(loc = 'best')
plt.show()

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好的，我明白了。谢谢：）不过我的matplotlib似乎知道cm.jet（医生也不再提到它）。现在在哪里可以找到它？您也可以使用

plt.get\u cmap（'jet'）

。我也编辑了这篇文章来展示这一点。

import datetime as DT
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import scipy.interpolate as interpolate

dates = [DT.date(year, 9, 1) for year in range(2003, 2009)]
t = list(map(mdates.date2num, dates))
jec = (100, 70, 125, 150, 300, 250)
plt.plot(dates, jec, 'k.', markersize = 20)
new_t = np.linspace(min(t), max(t), 80)
new_dates = map(mdates.num2date, new_t)
kinds = ('cubic', 'quadratic', 'slinear', 'nearest', 'linear', 'zero', 4, 5)
cmap = plt.get_cmap('jet')
colors = cmap(np.linspace(0, 1.0, len(kinds)))
for kind, color in zip(kinds, colors):
    new_jec = interpolate.interp1d(t, jec, kind=kind)(new_t)
    plt.plot(new_t, new_jec, '-', label=str(kind), color=color)
plt.legend(loc = 'best')
plt.show()