Matplotlib.axes.Axes.specgram() in Python

Syntax: Axes.specgram(self, x, NFFT=None, Fs=None, Fc=None, detrend=None, window=None, noverlap=None, cmap=None, xextent=None, pad_to=None, sides=None, scale_by_freq=None, mode=None, scale=None, vmin=None, vmax=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.
• Fc: This parameter is also contains the integer value to offsets the x extents of the plot to reflect the frequency range. Its default value is 0
• 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.
• mode : This parameter is that what sort of spectrum to use {'default', 'psd', 'magnitude', 'angle', 'phase'}.
• noverlap : This parameter is the number of points of overlap between blocks.
• scale : This parameter contains the scaling of the values in the spec {'default', 'linear', 'dB'}.
• Fc : This parameter is the center frequency of x.
• camp: This parameter is a matplotlib.colors.Colormap instance.

Returns: This returns the following:

• spectrum :This returns the angle spectrum in radians.
• freqs :This returns the frequencies corresponding to the elements in spectrum.
• t: This returns the times corresponding to midpoints of segments.
• im: This returns the image created by imshow containing the spectrogram.

The resultant is (spectrum, freqs, t, im)

# Implementation of matplotlib function
import matplotlib.pyplot as plt
import numpy as np

dt = 0.005
t = np.arange(0.0, 20.0, dt)
x = np.sin(np.pi * t) + 1.5 * np.cos(np.pi * t)

fig, ax1 = plt.subplots()
ax1.specgram(x, Fs = 1)
ax1.set_title('matplotlib.axes.Axes.specgram() Example')

plt.show()

# Implementation of matplotlib function
import matplotlib.pyplot as plt
import numpy as np

np.random.seed(9360801)

dt = 0.0005
t = np.arange(0.0, 20.0, dt)
s1 = np.sin(4 * np.pi * 100 * t)
s2 = 1.5 * np.sin(1.5 * np.pi * 400 * t)

s2[t <= 10] = s2[12 <= t] = 0

nse = 0.2 * np.random.random(size = len(t))

x = s1 + s2 + nse  
NFFT = 512 
Fs = int(1.0 / dt)  

fig, ax1 = plt.subplots()
ax1.specgram(x, Fs = Fs, cmap = plt.cm.bone)
ax1.set_title('matplotlib.axes.Axes.specgram() Example')

plt.show()