使用matplotlib生成gif动画的方法有很多，一般常规使用matplotlib的animation模块的FuncAnimation函数实现。在matplotlib官网看到了第三方动画包gif的介绍。
gif包概述
gif包是支持 Altair, matplotlib和Plotly的动画扩展。
gif依赖PIL，即pillow，要求Pillow>=7.1.2。
安装gif包，pip install gif
动画原理
所有动画都是由帧（frame）构成的，一帧就是一幅静止的画面，连续的帧就形成动画。我们通常说帧数，简单地说，就是在1秒钟时间里传输的图片的帧数，也可以理解为图形处理器每秒钟能够刷新几次，通常用fps（Frames Per Second）表示。制作动画的关键：如何生成帧，每秒多少帧。
gif包解读
gif包非常简洁，只有一个单独的文件gif.py，文件主要包含options类、frames和save两个函数。
options类
提供精简版 的Altair, matplotlib和Plotly的保存或输出设置。以matplotlib为例，提供以下设置。
- dpi (int): The resolution in dots per inch
- facecolor (colorspec): The facecolor of the figure
- edgecolor (colorspec): The edgecolor of the figure
- transparent (bool): If True, the axes patches will all be transparent
设置方法：gif.options.matplotlib["dpi"] = 300原理：options在构造函数中创建matplotlib字典保存配置，随后传递给底层的matplotlib包。
frames函数
装饰器函数，通过对应包编写自定义绘图函数生成单帧图像。
save函数
根据帧序列生成动画。
def save(frames, path, duration=100, unit="milliseconds", between="frames", loop=True):
"""Save decorated frames to an animated gif.
- frames (list): collection of frames built with the gif.frame decorator
- path (str): filename with relative/absolute path
- duration (int/float): time (with reference to unit and between)
- unit {"ms" or "milliseconds", "s" or "seconds"}: time unit value
- between {"frames", "startend"}: duration between "frames" or the entire gif ("startend")
- loop (bool): infinitely loop the animation
frames即根据@gif.frame装饰的绘图函数生成的帧的序列，此处根据需要自定义。
duration即持续时间，由单位unit和模式between决定，默认为frames为帧间的时间间隔。
unit即持续时间单位，支持毫秒和秒，默认为毫秒。
between即持续时间计算模式，默认frames即duration为帧之间的时间间隔，startend模式时duration=duration /len(frames)，即duration为所有帧—整个动画的持续时间。
gif包生成gif动画实践
import random
from matplotlib import pyplot as plt
import gif
# 构造数据
x = [random.randint(0, 100) for _ in range(100)]
y = [random.randint(0, 100) for _ in range(100)]
# 设置选项
gif.options.matplotlib["dpi"] = 300
# 使用gif.frame装饰器构造绘图函数，即如何生成静态的帧
@gif.frame
def plot(i):
xi = x[i * 10:(i + 1) * 10]
yi = y[i * 10:(i + 1) * 10]
plt.scatter(xi, yi)
plt.xlim((0, 100))
plt.ylim((0, 100))
# 构造帧序列frames，即把生成动画的所有帧按顺序放在列表中
frames = []
for i in range(10):
frame = plot(i)
frames.append(frame)
# 根据帧序列frames,动画持续时间duration，生成gif动画
gif.save(frames, 'example.gif', duration=3.5, unit="s", between="startend")
以心形曲线为例比较gif包和animation模块实现动画的差异
from matplotlib import pyplot as plt
import numpy as np
t = np.linspace(0, 6, 100)
x = 16 * np.sin(t) ** 3
y = 13 * np.cos(t) - 5 * np.cos(2 * t) - 2 * np.cos(3 * t) - np.cos(4 * t)
fig = plt.figure(figsize=(5, 3), dpi=100)
plt.scatter(x, y)
plt.show()
心形曲线绘制
from matplotlib import pyplot as pltimport numpy as np
t = np.linspace(0, 6, 100)x = 16 * np.sin(t) ** 3y = 13 * np.cos(t) - 5 * np.cos(2 * t) - 2 * np.cos(3 * t) - np.cos(4 * t)fig = plt.figure(figsize=(5, 3), dpi=100)plt.scatter(x, y)plt.show()
gif包的实现方式
import numpy as np
import gif
from matplotlib import pyplot as plt
t = np.linspace(0, 6, 100)
x = 16 * np.sin(t) ** 3
y = 13 * np.cos(t) - 5 * np.cos(2 * t) - 2 * np.cos(3 * t) - np.cos(4 * t)
@gif.frame
def plot_love(x, y):
plt.figure(figsize=(5, 3), dpi=100)
plt.scatter(x, y, 60, c="r", alpha=0.7, marker=r"$\heartsuit$")
plt.axis("off")
frames = []
for i in range(1, len(x)):
of = plot_love(x[:i], y[:i])
frames.append(of)
gif.save(frames, "love.gif", duration=80)
import numpy as npimport giffrom matplotlib import pyplot as plt
t = np.linspace(0, 6, 100)x = 16 * np.sin(t) ** 3y = 13 * np.cos(t) - 5 * np.cos(2 * t) - 2 * np.cos(3 * t) - np.cos(4 * t)
@gif.framedef plot_love(x, y): plt.figure(figsize=(5, 3), dpi=100) plt.scatter(x, y, 60, c="r", alpha=0.7, marker=r"$\heartsuit$") plt.axis("off")frames = []for i in range(1, len(x)): of = plot_love(x[:i], y[:i]) frames.append(of)
gif.save(frames, "love.gif", duratinotallow=80)
matplotlib 常规FuncAnimation函数实现方式
from matplotlib import pyplot as plt
import matplotlib.animation as animation
import numpy as np
t = np.linspace(0, 6, 100)
x = 16 * np.sin(t) ** 3
y = 13 * np.cos(t) - 5 * np.cos(2 * t) - 2 * np.cos(3 * t) - np.cos(4 * t)
data=[i for i in zip(x,y)]
def plot_love(data):
x, y = data
plt.scatter(x, y, 60, c="r", alpha=0.7, marker=r"$\heartsuit$")
fig=plt.figure(figsize=(5, 3), dpi=100)
plt.axis("off")
animator = animation.FuncAnimation(fig, plot_love, frames=data, interval=80)
animator.save("love.gif", writer='pillow')
matplotlib底层PillowWriter类实现方式
from matplotlib import pyplot as plt
import matplotlib.animation as animation
import numpy as np
t = np.linspace(0, 6, 100)
x = 16 * np.sin(t) ** 3
y = 13 * np.cos(t) - 5 * np.cos(2 * t) - 2 * np.cos(3 * t) - np.cos(4 * t)
def plot_love(x, y):
plt.scatter(x, y, 60, c="r", alpha=0.7, marker=r"$\heartsuit$")
fig = plt.figure(figsize=(5, 3), dpi=100)
plt.axis("off")
writer = animation.PillowWriter(fps=15)
with writer.saving(fig, "love21.gif", dpi=100):
for i in range(1, len(x)):
plot_love(x[i], y[i])
writer.grab_frame()
from matplotlib import pyplot as pltimport matplotlib.animation as animationimport numpy as np
t = np.linspace(0, 6, 100)x = 16 * np.sin(t) ** 3y = 13 * np.cos(t) - 5 * np.cos(2 * t) - 2 * np.cos(3 * t) - np.cos(4 * t)
def plot_love(x, y): plt.scatter(x, y, 60, c="r", alpha=0.7, marker=r"$\heartsuit$")
fig = plt.figure(figsize=(5, 3), dpi=100)plt.axis("off")
writer = animation.PillowWriter(fps=15)with writer.saving(fig, "love21.gif", dpi=100): for i in range(1, len(x)): plot_love(x[i], y[i]) writer.grab_frame()
通过比较可知gif包的实现方式和matplotlib中利用PillowWriter实现方式类似，更偏底层一些，这样遇到比较复杂的绘图时更灵活。
