Python Seborn热图数据的动态更新

Python Seaborn dynamic update of heatmap data(Python Seborn热图数据的动态更新)
本文介绍了Python Seborn热图数据的动态更新的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

我想动态更新用Seborn制作的热图,逐条添加数据行。 下面的示例代码完成了基本工作,但它似乎并没有更新热图,而是在前一个热图中嵌套了一个新的热图。

预先感谢您提供的任何帮助/解决方案。

import numpy as np
np.random.seed(0)
import seaborn as sns
import matplotlib.pyplot as plt


data = np.random.rand(120 ,5900)
data_to_draw = np.zeros(shape=(1,5900))
for i,d in enumerate(data):
    # update data to be drawn
    data_to_draw = np.vstack((data_to_draw, data[i]))
    #keep max 5 rows visible
    if data_to_draw.shape[0]>5:
        data_to_draw = data_to_draw[1:]
    
    ax = sns.heatmap(data_to_draw,cmap="coolwarm")

    plt.draw()
    plt.pause(0.1)

推荐答案

我重新构造了您的代码以利用matplotlib.animation.FuncAnimation
为了避免在每次迭代中绘制新的热图和柱状图,需要通过seaborn.heatmap中的axcbar_ax参数指定在哪个轴上绘制它们。
此外,绘制热图后,使用ax.cla()可以方便地擦除前一个热图。

完成代码

import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation


np.random.seed(0)

data = np.random.rand(120, 50)
data_to_draw = np.zeros(shape = (1, 50))

def animate(i):
    global data_to_draw
    data_to_draw = np.vstack((data_to_draw, data[i]))
    if data_to_draw.shape[0] > 5:
        data_to_draw = data_to_draw[1:]

    ax.cla()
    sns.heatmap(ax = ax, data = data_to_draw, cmap = "coolwarm", cbar_ax = cbar_ax)


grid_kws = {'width_ratios': (0.9, 0.05), 'wspace': 0.2}
fig, (ax, cbar_ax) = plt.subplots(1, 2, gridspec_kw = grid_kws, figsize = (10, 8))
ani = FuncAnimation(fig = fig, func = animate, frames = 100, interval = 100)

plt.show()


如果您希望保留原有的代码结构,则可以应用相同的原则:

import numpy as np

np.random.seed(0)
import seaborn as sns
import matplotlib.pyplot as plt

data = np.random.rand(120, 5900)
data_to_draw = np.zeros(shape = (1, 5900))

grid_kws = {'width_ratios': (0.9, 0.05), 'wspace': 0.2}
fig, (ax, cbar_ax) = plt.subplots(1, 2, gridspec_kw = grid_kws, figsize = (10, 8))

for i, d in enumerate(data):
    # update data to be drawn
    data_to_draw = np.vstack((data_to_draw, data[i]))
    # keep max 5 rows visible
    if data_to_draw.shape[0] > 5:
        data_to_draw = data_to_draw[1:]

    sns.heatmap(ax = ax, data = data_to_draw, cmap = "coolwarm", cbar_ax = cbar_ax)

    plt.draw()
    plt.pause(0.1)

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