python之Matplotlib 随着时间的推移绘制旧点消失的点

我想用 matplotlib 实现两个目标:

• 动态更新散点图
• 慢慢地使之前迭代中绘制的点更加透明。

目前，我能够使用颜色图实现相反的目标。也就是说，我可以随时间绘制点，但最近的点看起来更透明。

是否可以使用 cmap 或其他工具在 matplotlib 上获得“淡化”效果？谢谢!我的代码如下:

def plotter_fader(iterations = 100, stay_open = True): 
# Set up plot 
fig, ax = plt.subplots() 
x_data = [] 
y_data = [] 
plt.ion() 
fig = plt.figure() 
ax = fig.add_subplot(111) 
t_vals = np.linspace(0,1, iterations) 
cmap = (0.09803921568627451, 0.09803921568627451, 0.09803921568627451, .05) 
for t in t_vals: 
    # Get intermediate points 
    intermediate = (1-t)*A + t*B 
    new_xvals, new_yvals = ... #Get these through some process 
    x_vals.extend(new_xvals) 
    y_vals.extend(new_yvals) 
 
    # Put new values in your plot 
    plt.plot(x_vals, y_vals, '.', color = cmap) 
 
    # Recompute plot limits 
    ax.relim() 
 
    # Set title and wait a little bit for 'smoothness' 
    ax.set_xlabel('X Axis', size = 12) 
    ax.set_ylabel('Y Axis', size = 12) 
    ax.set_title('Time: %0.3f' %t) 
    ax.autoscale_view() 
    fig.canvas.draw() 
    time.sleep(0.005) 
 
# Stay open after plotting ends 
while stay_open: 
    pass 

请您参考如下方法:

就像通常使用散点图一样，您可以定义一个值数组和一个将这些值映射到颜色的颜色图。您可以在每次迭代中更改此数组以使较旧的点具有不同的值。

在下文中，我们将值 0 视为透明，将值 1 视为深蓝色，并使用这些颜色创建颜色图。
在每次迭代中，旧值乘以一个小于 1 的数，新值设置为 1。

运行动画将因此产生淡化点。

import numpy as np 
import matplotlib.pyplot as plt 
import matplotlib.animation 
from matplotlib.colors import LinearSegmentedColormap 
 
fig, ax = plt.subplots() 
ax.set_xlabel('X Axis', size = 12) 
ax.set_ylabel('Y Axis', size = 12) 
ax.axis([0,1,0,1]) 
x_vals = [] 
y_vals = [] 
intensity = [] 
iterations = 100 
 
t_vals = np.linspace(0,1, iterations) 
 
colors = [[0,0,1,0],[0,0,1,0.5],[0,0.2,0.4,1]] 
cmap = LinearSegmentedColormap.from_list("", colors) 
scatter = ax.scatter(x_vals,y_vals, c=[], cmap=cmap, vmin=0,vmax=1) 
 
def get_new_vals(): 
    n = np.random.randint(1,5) 
    x = np.random.rand(n) 
    y = np.random.rand(n) 
    return list(x), list(y) 
 
def update(t): 
    global x_vals, y_vals, intensity 
    # Get intermediate points 
    new_xvals, new_yvals = get_new_vals() 
    x_vals.extend(new_xvals) 
    y_vals.extend(new_yvals) 
 
    # Put new values in your plot 
    scatter.set_offsets(np.c_[x_vals,y_vals]) 
 
    #calculate new color values 
    intensity = np.concatenate((np.array(intensity)*0.96, np.ones(len(new_xvals)))) 
    scatter.set_array(intensity) 
 
    # Set title 
    ax.set_title('Time: %0.3f' %t) 
 
ani = matplotlib.animation.FuncAnimation(fig, update, frames=t_vals,interval=50) 
 
plt.show()