问基于matplotlib的毫米波动画
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Stack Overflow用户

提问于 2021-01-07 22:51:08

回答 2查看 186关注 0票数 0

我试图建立一个微波旅行和改变频率，因为他们旅行模拟。X轴是时间，波应该沿着x轴移动，然后改变频率(从3 3GHz到30 3GHz)。时间间隔是1纳秒，因为比这更高的时间间隔太快，无法清楚地注意到运动。

我已经创建了一个波浪matplotlib.pyplot的静态模型。现在，我想使用matplotlib.animation来动画它。通过遵循这个文章中的指南，我可以成功地创建一个正弦波动画，但是我不知道从那里到哪里。

如何利用绘制正弦波的matplotlib.animation示例代码并将其调整为动画微波？

微波模型：

用于绘制微波模型的代码：

import numpy as np
from scipy.signal import chirp
import matplotlib.pyplot as plt
plt.style.use('seaborn-pastel')

T = 0.000000001 #one nanosecond 
n = 1000 # number of samples to generate - the more generated,the more smooth the curve
t = np.linspace(0, T, n, endpoint=False) # x-axis 
f0_micro = 3000000000 #frequency min value: 3GHz
f1_micro = 30000000000 #frequency max value: 30GHz
y_micro = chirp(t, f0_micro, T, f1_micro, method='logarithmic')

plt.plot(t,y_micro)
plt.grid(alpha=0.25)
plt.xlabel('t (secs)')
plt.title('Microwaves in one nanosecond')
plt.show()

动画正弦波视频：

Aa4huCJefHt7nlX3nKQKGA.gif

用于绘制动画正弦波的代码：

import numpy as np
from matplotlib import pyplot as plt
from matplotlib.animation import FuncAnimation
plt.style.use('seaborn-pastel')


fig = plt.figure()
ax = plt.axes(xlim=(0, 4), ylim=(-2, 2))
line, = ax.plot([], [], lw=3)

def init():
    line.set_data([], [])
    return line,
def animate(i):
    x = np.linspace(0, 4, 1000)
    y = np.sin(2 * np.pi * (x - 0.01 * i))
    line.set_data(x, y)
    return line,

anim = FuncAnimation(fig, animate, init_func=init,
                               frames=200, interval=20, blit=True)


anim.save('sine_wave.gif', writer='imagemagick')

matplotlib

animation

physics

python

numpy

回答 2

Stack Overflow用户

回答已采纳

发布于 2021-01-08 00:03:51

对于这种类型的动画

而不是画出所有的点

plt.plot(t, y_micro) # <--- skip it

你必须创建一个空的地块--有正确的限制

fig = plt.figure()

ax = plt.axes(xlim=(t[0], t[-1]), ylim=(min(y_micro), max(y_micro)))

line, = ax.plot([], [], lw=3)

在animation的后面，您可以使用i只放置部分点。

line.set_data(t[:i], y_micro[:i])

import numpy as np
from scipy.signal import chirp
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
plt.style.use('seaborn-pastel')

# --- generate all data without drawing ---

T = 0.000000001 #one nanosecond 
n = 1000 # number of samples to generate - the more generated,the more smooth the curve

t = np.linspace(0, T, n, endpoint=False) # x-axis 

f0_micro = 3000000000 #frequency min value: 3GHz
f1_micro = 30000000000 #frequency max value: 30GHz
y_micro = chirp(t, f0_micro, T, f1_micro, method='logarithmic')

# --- create empty plot ---

#plt.plot(t,y_micro) # <--- skip it

fig = plt.figure()
ax = plt.axes(xlim=(t[0], t[-1]), ylim=(min(y_micro), max(y_micro)))
line, = ax.plot([], [], lw=3)

# --- other elements on plot ---

plt.grid(alpha=0.25)
plt.xlabel('t (secs)')
plt.title('Microwaves in one nanosecond')

# --- animate it ----

def init():
    # put empty data at start
    line.set_data([], [])
    return line,
    
def animate(i):
    # put new data in every frame using `i`
    line.set_data(t[:i], y_micro[:i])
    return line,

# calculate how many frames has animation
frames_number = len(t)

anim = FuncAnimation(fig, animate, init_func=init, frames=frames_number, interval=10, blit=True)

plt.show()

# I use `fps` (frames per second) to make it faster in file
anim.save('microwave.gif', fps=120) #, writer='imagemagick')

编辑

如果您需要带边距的绘图，那么您必须向限制中添加一些值，因为现在绘图不会自动添加边距。

x_margin = T/30  # I tested manually different values
y_margin = 0.1   # I tested manually different values

x_limits = (t[0] - x_margin, t[-1] + x_margin)
y_limits = (min(y_micro) - y_margin, max(y_micro) + y_margin)

fig = plt.figure()
ax = plt.axes(xlim=x_limits, ylim=y_limits)
line, = ax.plot([], [], lw=3)

如果您想要更快的动画在文件中，那么您可以尝试使用save( ..., fps= ...)对数量的frames per second。

或者你可以画更少的画框

frames_number = len(t) // 2

并在每一帧中显示更多的点

i = i*2
line.set_data(t[:i], y_micro[:i])

票数 2

Stack Overflow用户

发布于 2021-01-08 00:45:07

一种新的和稍微容易使用的替代matplotlib.animate的方法是赛洛普。

import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import chirp
from celluloid import Camera

fig = plt.figure()
camera = Camera(fig)

T = 0.000000001 #one nanosecond
n = 1000 # number of samples to generate - the more generated,the more smooth the curve
t = np.linspace(0, T, n, endpoint=False) # x-axis
f0_micro = 3000000000 #frequency min value: 3GHz
f1_micro = 30000000000 #frequency max value: 30GHz
y_micro = chirp(t, f0_micro, T, f1_micro, method='logarithmic')

for i in range(len(t)):

    plt.plot(t[:i], y_micro[:i], "r")
    camera.snap()

    plt.grid(alpha=0.25)
    plt.xlabel('t (secs)')
    plt.title('Microwaves in one nanosecond')

animation = camera.animate(interval=10)
plt.show()