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脈沖星假信號頻率的相對路徑論證。

首先看一下演示結果：

Python模擬脈沖星偽信號頻率實例代碼

實例代碼：

									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()