Updates:

zero_basic_plots:

 select .wav file and plot its features (could be randomized using randi() function) 
 
 choosedialog_art.m: Choose a filename
 (figure 1) Spectrogram using short-time Fourier transform 
 (figure 2) inputdlg(): Enter Endpoints for selected freq
 (figure 3) pwelch(): Weltch Power Density using 
 (figure 4 & 5) loudness_1991.m: 
 plot the Partial Loudness sone/Bark (fig 5)
 inside the loudness_1991.m, call filter_third_octaves_downsample.m: plot 1/3-octave
 spectrum using bar() (fig 4)

first_welch_power_density:

 this is the very first script that saves/plots welch_power_density of a particular category of noise
 
 choosedialog_art_all.m: Choose a category
 choosedialog_plot_power_all_avg_dba.m: let the user choose from 'save and plot all figures on one graph' or 'pull and save the data only' 

second_avg_welch_power_density:

 plot avg of welch_power_densit
 use mean() and std() to calculate the mean and stddiv
 call plotRstyleUncert.m to print the avg wpd for each category

third_pull_fraction_of_power:

 pull the data?fraction_of_power 
 choosedialog_art_all.m: choose a noise categroy
 use inputdlg() to get the freq ranges and save them as seven_octave_freq_band.mat
 for e.g.
 type: '22','44','88','176','353','707','1414' 
 for range sets: 0-22 23-44 45-88 89-176 177-353
 354-707 708-1414 1415-3000 (Hz)
 fractionPower.m: calculate the fraction of power according to the selected range set
 and then, name them by 'fractionofpower_' CATEGORY '.mat'

fourth_notboxplot_fraction_of_power:

 plot 'notboxplots' of the power in different frequency bins 
 load seven_octave_freq_band.mat: get the freq ranges
 default freq bands are: {'0-22Hz','22-44Hz','44-88Hz','88-176Hz','176-353Hz','353-707Hz','707-1414Hz','1414-3000Hz'} ; 
 use choosedialog_art.m to choose a category
 load 'fractionofpower_' CATEGORY '.mat' and plot the
 'notboxplots' by calling notBoxPlot(fractionofpower_category)

fifth_boxplot_of_fraction_of_power_side_by_side:

 plot all the boxplots of fraction_of_power side by side 
 load seven_octave_freq_band.mat: get the freq ranges
 default freq bands are: {'0-22Hz','22-44Hz','44-88Hz','88-176Hz','176-353Hz','353-707Hz','707-1414Hz','1414-3000Hz'} ; 
 load 'fractionofpower_' CATEGORY '.mat' 
 plot the boxplots of 'fraction of power' side by side 
 rail_fracpower = 'g' = green
 truck_fracpower = 'm' = magenta
 aircraft_fracpower = 'b' = blue

sixth_gscatter_and_prediction:

 plot gscatter labeled by group together with the classification process
 load variance_all.mat, xmeans_all.mat, ALL_Xmean.mat; 
 call gscatter() to plot Xmeans(dB) v Variance and label
 them by group
 callchoosedialog_classifier.m to choose a classifier
 'Naive Bayes'
 'Discriminant Analysis' 
 'Classification Tree'
 'K - Nearest Neighbor' 
 '3D Classification Probability' 
 plot the predicted class region