Matlab - multiple variables normalized histogram?

I have a vector which I need to split into two classes and then get a histogram of both resulting vectors (which have different sizes). The values represent height records so the interval is about 140-185. How can I get a normalized histogram of both resulting vectors in different colors. I was able to get both normalized vectors in the same colour (which is indistiguible) and and also a histogram with different colours but not not normalized...

I hope you understand my question and will be able to help me. Thanks in advance :)

Answer 1

[Kerem tezcan]

Hello, I have generated a random vector to have some data and classified them as lower or higher than a threshold (170) since I don't know how you want to do the classification. But the histograms you can get as follows:

   >>
>> v=140+round(50*rand(100,1));
>> v1=v(v<170);
>> v2=v(v>=170);
>> n_bins=30; %no of bins you want for the histograms
>> bins=140:50/n_bins:190;%create the bins
>> [h1 b1]=hist(v1, bins);%make the histograms, the values are in h1 and h2
>> [h2 b2]=hist(v2, bins);
>> bar(bins, h1,'r'); hold on; bar(bins, h2,'b');%not notmalized histograms
>> bar(bins, h1/length(v1),'r'); hold on; bar(bins, h2/length(v2),'b');%normalized histograms

Of course you need to change the lower and upper limits, I have taken here 140 to 190... You can change the colors as well. Don't forget to write hold off after you are done with plotting...

Answer 2

[Star Strider]

Another approach:

fh = 163+3.5*randn(1,45);           % Original data female (45 data)
mh = 175+3.5*randn(1,55);           % Original data male (55 data)
bins = linspace(150,200, 25);       % Choose 25 bins
fc = histc(fh,bins);                % Histogram count for females
fcn = fc/max(fc);                   % Normalised histogram count for females
mc = histc(mh,bins);                % Histogram count for males
mcn = mc/max(mc);                   % Normalised histogram count for males

figure(1)
bar(bins',[fcn' mcn'])              % Plot
axis([140  200    0  1])

Answer 3

[Daniel Bridges]

MATLAB R2015b has normalization built-in:

help histogram

This command brings up the following documentation, indicating you can specify normalization as a command property, without any additional commands:

histogram(...,'Normalization',NM) specifies the normalization scheme 
    of the histogram values. The normalization scheme affects the scaling 
    of the histogram along the vertical axis (or horizontal axis if 
    Orientation is 'horizontal'). NM can be:
                   'count'   The height of each bar is the number of 
                             observations in each bin, and the sum of the
                             bar heights is NUMEL(X).
             'probability'   The height of each bar is the relative 
                             number of observations (number of observations
                             in bin / total number of observations), and
                             the sum of the bar heights is 1.
            'countdensity'   The height of each bar is the number of 
                             observations in each bin / width of bin. The 
                             area (height * width) of each bar is the number
                             of observations in the bin, and the sum of
                             the bar areas is NUMEL(X).
                     'pdf'   Probability density function estimate. The height 
                             of each bar is, (number of observations in bin)
                             / (total number of observations * width of bin).
                             The area of each bar is the relative number of
                             observations, and the sum of the bar areas is 1.
                'cumcount'   The height of each bar is the cumulative 
                             number of observations in each bin and all
                             previous bins. The height of the last bar
                             is NUMEL(X).
                     'cdf'   Cumulative density function estimate. The height 
                             of each bar is the cumulative relative number
                             of observations in each bin and all previous bins.
                             The height of the last bar is 1.