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What is the difference between a logged power spectrum and power spectrum... Well the log part. So can a normal power spectrum be converted to a logged power spectrum just by taking the log of the power spectrum?

Here is the code in which I am trying to convert: 

import os
import sys
from os import listdir
from os.path import isfile, join
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import seaborn as sb
from matplotlib.colors import Normalize
import matplotlib
from matplotlib import cm
from PIL import Image
import ast

def make_plot_store_data(name,interweaved,static,delta,delta_delta,isTrain,isTest,isDev):
    Y =  np.array(range(0,static.shape[1]))
    X =  np.array(range(0,static.shape[0]))
    X,Y = np.meshgrid(X, Y)

    plt.pcolormesh(X,Y,np.log10(static.T),cmap=cm.jet,vmin=-6, vmax=2)
    plt.xlabel('Frames')
    plt.ylabel('Frequency(Hz)')
    plt.title('Power spectrum of ' + name)
    plt.colorbar()
    #plt.show()
    plt.savefig(plot+"/"+name+"_plot_static_conv.png")
    #raw_input("Something")
    plt.close()


    plt.pcolormesh(X,Y,np.log10(delta.T),cmap=cm.jet,vmin=-6, vmax=2)
    plt.xlabel('Frames')
    plt.ylabel('Frequency(Hz)')
    plt.title('Power spectrum of ' + name)
    plt.colorbar()
    #plt.show()
    plt.savefig(plot+"/"+name+"_plot_delta_conv.png")
    #raw_input("Something")
    plt.close()

    plt.pcolormesh(X,Y,np.log10(delta_delta.T),cmap=cm.jet,vmin=-6, vmax=2)
    plt.xlabel('Frames')
    plt.ylabel('Frequency(Hz)')
    plt.title('Power spectrum of ' + name)
    plt.colorbar()
    #plt.show()
    plt.savefig(plot+"/"+name+"_plot_delta_delta_conv.png")
    #raw_input("Something")
    plt.close()

    Y =  np.array(range(0,interweaved.shape[1]))
    X =  np.array(range(0,interweaved.shape[0]))
    X,Y = np.meshgrid(X, Y)

    plt.pcolormesh(X,Y,np.log10(interweaved.T),cmap=cm.jet,vmin=-6, vmax=2)
    ##plt.xlim(xmin, xmax)
    plt.xlabel('Frames')
    plt.ylabel('Frequency(Hz)')
    plt.title('Power spectrum of ' + name)
    plt.colorbar()
    #plt.show()
    plt.savefig(plot+"/"+name+"_interweaved.png")
    plt.close()
    if isTrain == True:
        convert = plt.get_cmap(cm.jet)
        norm = Normalize(vmin=-6, vmax=2)
        numpy_output_interweawed = convert(norm(plot_interweaved))
        numpy_output_interweawed.dump(numpy_train+name+"_normalized_interweaved"+".dat")
        numpy_output_interweawed_or = convert(norm(plot_interweaved))*255
        numpy_output_interweawed_or.dump(numpy_train+name+"_interweaved"+".dat")
    if isTest == True:
        convert = plt.get_cmap(cm.jet)
        norm = Normalize(vmin=-6, vmax=2)
        numpy_output_interweawed = convert(norm(plot_interweaved))
        numpy_output_interweawed.dump(numpy_test+name+"_normalized_interweaved"+".dat")
        numpy_output_interweawed_or = convert(norm(plot_interweaved))*255
        numpy_output_interweawed_or.dump(numpy_test+name+"_interweaved"+".dat")
    if isDev == True:
        convert = plt.get_cmap(cm.jet)
        norm = Normalize(vmin=-6, vmax=2)
        numpy_output_interweawed = convert(norm(plot_interweaved))
        numpy_output_interweawed.dump(numpy_dev+name+"_normalized_interweaved"+".dat")
        numpy_output_interweawed_or = convert(norm(plot_interweaved))*255
        numpy_output_interweawed_or.dump(numpy_dev+name+"_interweaved"+".dat")
    print str(name) + " Numpy Stored"

I am trying to store the logged filter bank energies here both as plot and data. But I seem to be doing it wrong based on the images I get.

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  • $\begingroup$ So, if $P(f,t)$ is the power spectrum (i.e. your top figure), the log-power spectrum is given by $P_{log}(f,t)=10log10(P(f,t))$. $\endgroup$
    – Maximilian Matthé
    Mar 13, 2017 at 11:30
  • $\begingroup$ why 10log?..... $\endgroup$
    – Bob Burt
    Mar 13, 2017 at 11:59
  • $\begingroup$ It's a conventions to have 10log(P) to transform linear scale to decibel scale (which is what is meant via log-scale). Have a look here for example. $\endgroup$
    – Maximilian Matthé
    Mar 13, 2017 at 12:25
  • $\begingroup$ decibel means deci- bel, which means 10 Bel. Bel is a ratio of power. Decibel is 10 x ratio of power. $\endgroup$
    – Dan Boschen
    Mar 14, 2017 at 0:05
  • $\begingroup$ Post a gist of your code and we can help fix it up :) $\endgroup$
    – ruoho ruotsi
    Apr 4, 2017 at 16:28

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