Python中的 Matplotlib.axes.Axes.psd()
Matplotlib是Python中的一个库,它是 NumPy 库的数值数学扩展。 Axes 类包含大部分图形元素:Axis、Tick、Line2D、Text、Polygon 等,并设置坐标系。 Axes 的实例通过回调属性支持回调。
matplotlib.axes.Axes.psd()函数
matplotlib 库的 axes 模块中的Axes.psd()函数用于绘制功率谱密度。
Syntax: Axes.psd(self, x, NFFT=None, Fs=None, Fc=None, detrend=None, window=None, noverlap=None, pad_to=None, sides=None, scale_by_freq=None, return_line=None, *, data=None, **kwargs)
Parameters: This method accept the following parameters that are described below:
- x: This parameter is a sequence of data.
- Fs : This parameter is a scalar. Its default value is 2.
- window: This parameter take a data segment as an argument and return the windowed version of the segment. Its default value is window_hanning()
- sides: This parameter specifies which sides of the spectrum to return. This can have following values : ‘default’, ‘onesided’ and ‘twosided’.
- pad_to : This parameter contains the integer value to which the data segment is padded.
- NFFT : This parameter contains the number of data points used in each block for the FFT.
- detrend : This parameter contains the function applied to each segment before fft-ing, designed to remove the mean or linear trend {‘none’, ‘mean’, ‘linear’}.
- scale_by_freq : This parameter is allows for integration over the returned frequency values.
- noverlap : This parameter is the number of points of overlap between blocks.
- Fc : This parameter is the center frequency of x.
- return_line : This parameter include the line object plotted in the returned values.
Returns: This returns the following:
- Pxx:This returns the values for the power spectrum P_{xx} before scaling.
- freqs :This returns the frequencies for the elements in Pxx.
- line :This returns the line created by this function.
The resultant is (Pxx, freqs, line)
下面的示例说明了 matplotlib.axes 中的 matplotlib.axes.Axes.csd()函数:
示例 1:
# Implementation of matplotlib function
import numpy as np
import matplotlib.pyplot as plt
dt = 0.01
t = np.arange(0, 30, dt)
nse1 = np.random.randn(len(t))
s1 = 1.5 * np.sin(2 * np.pi * 10 * t) + nse1 + np.cos(np.pi * t)
fig, ax1 = plt.subplots()
ax1.psd(s1**2, 512, 1./dt, color ="green")
ax1.set_xlabel('Frequency')
ax1.set_ylabel('PSD(db)')
ax1.set_title('matplotlib.axes.Axes.psd() Example')
plt.show()
输出:
示例 2:
# Implementation of matplotlib function
import numpy as np
import matplotlib.pyplot as plt
dt = 0.01
t = np.arange(0, 30, dt)
nse1 = np.random.randn(len(t))
r = np.exp(-t / 0.05)
cnse1 = np.convolve(nse1, r, mode ='same')*dt
s1 = np.cos(np.pi * t) + cnse1 + np.sin(2 * np.pi * 10 * t)
fig, [ax1, ax2] = plt.subplots(2, 1)
ax1.plot(t, s1)
ax1.set_xlim(0, 5)
ax1.set_ylabel('value s1')
ax1.grid(True)
ax2.psd(s1, 256, 1./dt)
ax2.set_ylabel('PSD(db)')
ax2.set_xlabel('Frequency')
ax1.set_title('matplotlib.axes.Axes.psd() Example')
plt.show()
输出: