产生随时间变化频率的正弦波信号

Question

我想在Python中绘制不同时间、不同频率和幅度的正弦波。 例如，正弦波的振幅为 0-100 个样本中的 1 个（频率必须为 100）和 100-200 个样本中的 2 个（freequncy 必须为 250）。这是第 1 波。必须创建与第 1 波类似的另一个第 2 波波。最后必须总结一下这些。是否可以 ？我尝试了不同的变体但是。我没有得到结果。在下面的代码中，我无法调整频率。如何修复它？

import matplotlib.pyplot as plt
import math

def y_func(x):
    return math.sin(x)

x_values = []
y_values = []

x = 0

amplitude = 1
while x < 5:
    x_values.append(x)
    y_values.append(amplitude * y_func(x))
    x += 0.1

amplitude = 2
while x < 10:
    x_values.append(x)
    y_values.append(amplitude * y_func(x))
    x += 0.1

plt.plot(x_values, y_values)

plt.title('test')
plt.show()

Answer 1

请参阅下面的示例。它使用

numpy

，通常用于时间序列或向量的数学运算。

结果将如下所示：

import matplotlib.pyplot as plt
import numpy as np

#Resolution of the x axis, for plotting
#A resolution of 1e-4 seconds is equivalent to a frequency resolution of 10KHz,
# which will give a smooth plot for our 250Hz wave
t_resolution = 1e-4

#Define the frequency 1 and frequency 2 waves
freq1 = 100
amplitude_1 = 1
#To change the number of samples,
# change the duration from 0.01s to something else
n_samples_freq1 = int( 0.01 / t_resolution )

freq2 = 250
amplitude_2 = 2
#To change the number of samples,
# change the duration from 0.005s to something else
n_samples_freq2 = int( 0.005 / t_resolution )

#Now compute the waves
total_samples = n_samples_freq1 + n_samples_freq2

#Define a high-resolution time axis
time_axis = np.arange(0, total_samples * t_resolution, t_resolution)

#Create the freq1 and freq2 waves
sin_freq1 = amplitude_1 * np.sin(2 * np.pi * freq1 * time_axis)
sin_freq2 = amplitude_2 * np.sin(2 * np.pi * freq2 * time_axis)

#Initially only freq1 is present (freq2 wave = 0)
#Then freq1 wave is set to 0, and only freq2 is present.
sin_freq1[n_samples_freq1:] = 0
sin_freq2[:n_samples_freq1] = 0

#Sum them together
summed = sin_freq1 + sin_freq2

#Plot the original waves, and the summed version
plt.plot(time_axis, summed, 'grey', linewidth='12', label='freq1 + freq2')
plt.plot(time_axis, sin_freq1, 'r--', linewidth=2, label='freq1')
plt.plot(time_axis, sin_freq2, 'b', linewidth=2, label='freq2')
plt.xlabel('time/s')
plt.ylabel('amplitude')
plt.legend()