Matplotlib绘制点随着时间的推移旧点消失

Question

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，我可以使用colormaps实现相反的目标。也就是说，我可以随着时间的推移绘制积分，但最近的点看起来更透明。

是否有可能使用cmap或其他工具对matplotlib产生“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

Answer 1

与散点图一样，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映射。您可以在每次迭代中更改此数组，以使旧点具有不同的值。

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，旧值乘以小于1的数字，新值设置为值1.

运行动画会产生淡化点。

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()

Answer 2

这是你在找什么？

from matplotlib import pyplot as plt 

# Creates new axis.
plt.axis([0, 10, 0, 1])

# Allows interactive plotting
plt.ion()

# Transparency
alpha = 1

# Plotting first point outside of loop because more convenient for example
point = plt.scatter(0.5, 0.5, alpha=alpha)
for i in range(10):
    # As the loop goes on, increase transparency, remove the current point, 
    # and plots another one, more transparent.
    alpha -= 0.1
    point.remove()
    point = plt.scatter(5, .5, alpha=alpha, color='r')
    plt.pause(0.05)

while True:
    plt.pause(0.05)