Python模拟脉冲星伪信号频率实例代码

概述脉冲星假信号频率的相对路径论证。首先看一下演示结果：实例代码：importnumpyasnp

脉冲星假信号频率的相对路径论证。

首先看一下演示结果：

实例代码：

import numpy as npimport matplotlib.pyplot as pltimport matplotlib.animation as animation# Fixing random state for reproducibilitynp.random.seed(19680801)# Create new figure with black backgroundfig = plt.figure(figsize=(8,8),facecolor='black')# Add a subplot with no frameax = plt.subplot(111,frameon=False)# Generate random datadata = np.random.uniform(0,1,(64,75))X = np.linspace(-1,data.shape[-1])G = 1.5 * np.exp(-4 * X ** 2)# Generate line plotslines = []for i in range(len(data)):  # Small reduction of the X extents to get a cheap perspective effect  xscale = 1 - i / 200.  # Same for linewidth (thicker strokes on bottom)  lw = 1.5 - i / 100.0  line,= ax.plot(xscale * X,i + G * data[i],color="w",lw=lw)  lines.append(line)# Set y limit (or first line is cropped because of thickness)ax.set_ylim(-1,70)# No ticksax.set_xticks([])ax.set_yticks([])# 2 part Titles to get different Font weightsax.text(0.5,1.0,"MATPLOTliB ",transform=ax.transAxes,ha="right",va="bottom",family="sans-serif",Fontweight="light",Fontsize=16)ax.text(0.5,"UNCHAINED",ha="left",Fontweight="bold",Fontsize=16)def update(*args):  # Shift all data to the right  data[:,1:] = data[:,:-1]  # Fill-in new values  data[:,0] = np.random.uniform(0,len(data))  # Update data  for i in range(len(data)):    lines[i].set_ydata(i + G * data[i])  # Return modifIEd artists  return lines# Construct the animation,using the update function as the animation# director.anim = animation.FuncAnimation(fig,update,interval=10)plt.show()

脚本运行时间：（0分0.065秒）

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