在python中绘制热图 [英] Drawing heat map in python

问题描述

我有两个列表x，y表示2D坐标.例如x = [1,4,0.5,2,5,10,33,0.04]和y = [2,5,44,0.33,2,14,20,0.03]. x[i]和y[i]代表2D中的一个点.现在，我还有一个列表，表示每个(x，y)点的热"值，例如z = [0.77, 0.88, 0.65, 0.55, 0.89, 0.9, 0.8,0.95].当然，x，y和z的尺寸比示例中的尺寸高得多.

I'm having two lists x, y representing coordinates in 2D. For example x = [1,4,0.5,2,5,10,33,0.04] and y = [2,5,44,0.33,2,14,20,0.03]. x[i] and y[i] represent one point in 2D. Now I also have a list representing "heat" values for each (x,y) point, for example z = [0.77, 0.88, 0.65, 0.55, 0.89, 0.9, 0.8,0.95]. Of course x,y and z are much higher dimensional than the example.

现在，我想在2D中绘制一个热图，其中x和y代表轴坐标，z代表颜色.如何在python中完成?

Now I would like to plot a heat map in 2D where x and y represents the axis coordinates and z represents the color. How can this be done in python?

推荐答案

此代码会产生热图.有了更多的数据点，该图就开始看起来非常漂亮，而且我发现，即使超过10万个点，总体上它也非常快.

This code produces a heat map. With a few more data points, the plot starts looking pretty nice and I've found it to be very quick in general even for >100k points.

import matplotlib.pyplot as plt
import matplotlib.tri as tri
import numpy as np
import math

x = [1,4,0.5,2,5,10,33,0.04]
y = [2,5,44,0.33,2,14,20,0.03]
z = [0.77, 0.88, 0.65, 0.55, 0.89, 0.9, 0.8, 0.95]
levels = [0.7, 0.75, 0.8, 0.85, 0.9]

plt.figure()
ax = plt.gca()
ax.set_aspect('equal')
CS = ax.tricontourf(x, y, z, levels, cmap=plt.get_cmap('jet'))
cbar = plt.colorbar(CS, ticks=np.sort(np.array(levels)),ax=ax, orientation='horizontal', shrink=.75, pad=.09, aspect=40,fraction=0.05)
cbar.ax.set_xticklabels(list(map(str,np.sort(np.array(levels)))))  # horizontal colorbar
cbar.ax.tick_params(labelsize=8) 
plt.title('Heat Map')
plt.xlabel('X Label')
plt.ylabel('Y Label')

plt.show()

产生此图像:

或者如果您正在寻找更渐变的颜色，请将tricontourf行更改为此:

or if you're looking for a more gradual color change, change the tricontourf line to this:

CS = ax.tricontourf(x, y, z, np.linspace(min(levels),max(levels),256), cmap=cmap)

，然后绘图将变为:

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