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Python通过matplotlib包和gif包生成gif动画

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")      
Python通过matplotlib包和gif包生成gif动画

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()      
Python通过matplotlib包和gif包生成gif动画

​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。