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matplotlib散点图中的颜色问题

scatter-plot matplotlib python

Mr. Who · 技术社区 · 8 年前

这个很好用

import matplotlib.pyplot as plt
import numpy as np

y= [1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4]
x= [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4]
area= [0.78, 0.81, 0.78, 0.81, 0.78, 0.81, 0.787, 0.81, 0.99, 0.999, 0.99, 0.99, 0.99, 0.99, 0.99, 0.99]
area = np.array(area)
area = area*2000

cluster = ['*','.','<','>','o','p','H','D','1','2','o','*','*','o','o','o']

fig,ax = plt.subplots()

for xp, yp, m in zip(x, y, cluster):
    ax.scatter(xp, yp,  s=area , marker = m)

plt.show()

import matplotlib.pyplot as plt
import numpy as np

y= [1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4]
x= [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4]
colors= [286.135, 288.556, 286.135, 288.55, 286.13, 288.55627, 286.13, 288.556, 342.713, 333.98, 342.713, 333.9834, 342.713, 333.9834, 342.71, 333.98]
colors = np.array(colors)
area= [0.78, 0.81, 0.78, 0.81, 0.78, 0.81, 0.787, 0.81, 0.99, 0.999, 0.99, 0.99, 0.99, 0.99, 0.99, 0.99]
area = np.array(area)
area = area*2000

cluster = ['*','.','<','>','o','p','H','D','1','2','o','*','*','o','o','o']

fig,ax = plt.subplots()

for xp, yp, m in zip(x, y, cluster):
    ax.scatter(xp, yp, c=colors, s=area, cmap=plt.cm.jet , marker = m)

plt.show()

python说“颜色数组必须是二维的”

plt.scatter(xp, yp, c=colors, s=area, cmap=plt.cm.jet , marker = 'o')

光谱工作正常,有什么问题?

1 回复 | 直到 8 年前

ImportanceOfBeingErnest 8 年前

您将分别绘制每个点作为其自己的散点图。这可能确实有道理,能够给每个点自己的标记。然而,这也需要给每个点赋予其自身的大小和颜色。因此,您需要在 colors 和 area 阵列。为了使颜色符合指定的颜色映射,还需要进行归一化。

import matplotlib.pyplot as plt
import numpy as np

y= [1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4]
x= [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4]
colors= [286.135, 288.556, 286.135, 288.55, 286.13, 288.55627, 286.13, 288.556, 342.713, 333.98, 342.713, 333.9834, 342.713, 333.9834, 342.71, 333.98]
colors = np.array(colors)
area= [0.78, 0.81, 0.78, 0.81, 0.78, 0.81, 0.787, 0.81, 0.99, 0.999, 0.99, 0.99, 0.99, 0.99, 0.99, 0.99]
area = np.array(area)
area = area*2000

cluster = ['*','.','<','>','o','p','H','D','1','2','o','*','*','o','o','o']

fig,ax = plt.subplots()

norm=plt.Normalize(colors.min(), colors.max())
for xp, yp, m,a,c in zip(x, y, cluster, area, colors):
    sc = ax.scatter(xp, yp, c=c, s=a, cmap=plt.cm.jet , marker = m, norm=norm)

plt.colorbar(sc)
plt.show()