我正在寻找如何动态更改已经绘制的Alpha值。
这是我要实现的一种示例代码,但我知道这是错误的写作。
import matplotlib.pyplot as plt
fig = plt.subplot(1, 1)
for rate in [0.1 * x for x in range(10, -1, -1)]:
plt.plot(range(0, 5), range(0, 5), color="r", alpha=rate)
plt.pause(0.1)
plt.show()
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该示例代码的目的是,我想随着处理的进行而降低alpha并使该行消失。
有人知道解决这个问题的方法吗?谢谢。
您可以Line2D使用set_alpha方法更新现有 的 alpha 值。这个想法是绘制一次线,然后在循环中更新 alpha。
import matplotlib.pyplot as plt
fig = plt.subplot(111)
plt.ion()
line, = plt.plot(range(0, 5), range(0, 5), color="r", alpha=1)
for rate in [0.1 * x for x in range(10, -1, -1)]:
line.set_alpha(rate)
plt.draw()
plt.pause(0.1)
plt.ioff()
plt.show()
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我想,你想控制的alpha分别为每个点价值,所以我开始做这个(基于此):
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from matplotlib.collections import LineCollection
class Vanishing_Line(object):
def __init__(self, n_points, tail_length, rgb_color):
self.n_points = int(n_points)
self.tail_length = int(tail_length)
self.rgb_color = rgb_color
def set_data(self, x=None, y=None):
if x is None or y is None:
self.lc = LineCollection([])
else:
# ensure we don't start with more points than we want
x = x[-self.n_points:]
y = y[-self.n_points:]
# create a list of points with shape (len(x), 1, 2)
# array([[[ x0 , y0 ]],
# [[ x1 , y1 ]],
# ...,
# [[ xn , yn ]]])
self.points = np.array([x, y]).T.reshape(-1, 1, 2)
# group each point with the one following it (shape (len(x)-1, 2, 2)):
# array([[[ x0 , y0 ],
# [ x1 , y1 ]],
# [[ x1 , y1 ],
# [ x2 , y2 ]],
# ...
self.segments = np.concatenate([self.points[:-1], self.points[1:]],
axis=1)
if hasattr(self, 'alphas'):
del self.alphas
if hasattr(self, 'rgba_colors'):
del self.rgba_colors
#self.lc = LineCollection(self.segments, colors=self.get_colors())
self.lc.set_segments(self.segments)
self.lc.set_color(self.get_colors())
def get_LineCollection(self):
if not hasattr(self, 'lc'):
self.set_data()
return self.lc
def add_point(self, x, y):
if not hasattr(self, 'points'):
self.set_data([x],[y])
else:
# TODO: could use a circular buffer to reduce memory operations...
self.segments = np.concatenate((self.segments,[[self.points[-1][0],[x,y]]]))
self.points = np.concatenate((self.points, [[[x,y]]]))
# remove points if necessary:
while len(self.points) > self.n_points:
self.segments = self.segments[1:]
self.points = self.points[1:]
self.lc.set_segments(self.segments)
self.lc.set_color(self.get_colors())
def get_alphas(self):
n = len(self.points)
if n < self.n_points:
rest_length = self.n_points - self.tail_length
if n <= rest_length:
return np.ones(n)
else:
tail_length = n - rest_length
tail = np.linspace(1./tail_length, 1., tail_length)
rest = np.ones(rest_length)
return np.concatenate((tail, rest))
else: # n == self.n_points
if not hasattr(self, 'alphas'):
tail = np.linspace(1./self.tail_length, 1., self.tail_length)
rest = np.ones(self.n_points - self.tail_length)
self.alphas = np.concatenate((tail, rest))
return self.alphas
def get_colors(self):
n = len(self.points)
if n < 2:
return [self.rgb_color+[1.] for i in xrange(n)]
if n < self.n_points:
alphas = self.get_alphas()
rgba_colors = np.zeros((n, 4))
# first place the rgb color in the first three columns
rgba_colors[:,0:3] = self.rgb_color
# and the fourth column needs to be your alphas
rgba_colors[:, 3] = alphas
return rgba_colors
else:
if hasattr(self, 'rgba_colors'):
pass
else:
alphas = self.get_alphas()
rgba_colors = np.zeros((n, 4))
# first place the rgb color in the first three columns
rgba_colors[:,0:3] = self.rgb_color
# and the fourth column needs to be your alphas
rgba_colors[:, 3] = alphas
self.rgba_colors = rgba_colors
return self.rgba_colors
def data_gen(t=0):
"works like an iterable object!"
cnt = 0
while cnt < 1000:
cnt += 1
t += 0.1
yield t, np.sin(2*np.pi*t) * np.exp(-t/100.)
def update(data):
"Update the data, receives whatever is returned from `data_gen`"
x, y = data
line.add_point(x, y)
# rescale the graph by large steps to avoid having to do it every time:
xmin, xmax = ax.get_xlim()
if x >= xmax:
ax.set_xlim(xmin, 2*xmax)
ax.figure.canvas.draw()
return line,
if __name__ == '__main__':
n_points = 100
tail_length = (3/4.)*n_points
rgb_color = [0., 0.5, 1.0]
time_pause = 0 # miliseconds
x=np.linspace(0, 4*np.pi, 2*n_points)
y=np.cos(x)
line = Vanishing_Line(n_points, tail_length, rgb_color)
fig, ax = plt.subplots()
ax.add_collection(line.get_LineCollection())
ax.set_xlim(0, 4*np.pi)
ax.set_ylim(-1.1,1.1)
ani = animation.FuncAnimation(fig, update, data_gen, blit=False,
interval=time_pause, repeat=False)
fig.show()
mywriter = animation.FFMpegWriter(fps=30)
ani.save('ani.mp4', writer=mywriter, dpi=600)
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它应该绘制一条带有消失线的图形(从此处保存了技巧,并从mp4在线转换为gif):
保存图形时,由python实时显示的动画开始时似乎存在错误,因为从[10,0]到第一点之间出现一条线。
该行不会出现在已保存的动画中,如果您注释了这两行以保存到消失的图形中。
我相信动画保存正在动画显示之前运行,因此保存运行的最后一点显示在显示运行的开始处。