Python模拟脉冲星伪信号频率实例代码

 import numpy as np import matplotlib.pyplot as plt import matplotlib.animation as animation # Fixing random state for reproducibility np.random.seed(19680801) # Create new Figure with black background fig = plt.figure(figsize=(8, 8), facecolor='black') # Add a subplot with no frame ax = plt.subplot(111, frameon=False) # Generate random data data = 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 plots lines = [] 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 ticks ax.set_xticks([]) ax.set_yticks([]) # 2 part titles to get different font weights ax.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()