脈沖星假信號頻率的相對路徑論證。

首先看一下演示結(jié)果：

實例代碼：

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, 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", color="w",    family="sans-serif", fontweight="light", fontsize=16)ax.text(0.5, 1.0, "UNCHAINED", transform=ax.transAxes,    ha="left", va="bottom", color="w",    family="sans-serif", 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, 1, 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()

腳本運行時間：（0分0.065秒）

總結(jié)

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