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From: adam on 8 Sep 2009 15:00
Hi everyone,

I've got some measure data from which I create a histogram.
And now I've got a function for like the expected values, but it's a plot.

Everything is fine if I hist() the data and plot() the function, but I'd like to combine them in one single graph.

I've tried
hist(...)
Hold on
plot(...)
but that didn't work

I also haven't found anything on the web yet..
From: Nathan on 8 Sep 2009 15:00
On Sep 8, 11:55 am, "adam " <unique...(a)gmail.com> wrote:
> Hi everyone,
>
> I've got some measure data from which I create a histogram.
> And now I've got a function for like the expected values, but it's a plot..
>
> Everything is fine if I hist() the data and plot() the function, but I'd like to combine them in one single graph.
>
> I've tried
> hist(...)
> Hold on
> plot(...)
> but that didn't work
>
> I also haven't found anything on the web yet..

doc subplot

%%%%%%%%%%%%%

subplot(2,1,1),hist(...);
subplot(2,1,2),plot(...);

-Nathan
From: adam on 8 Sep 2009 15:11
Nathan <ngreco32(a)gmail.com> wrote in message <7d763f1a-0bad-449b-a1c6-b11bae9b29e5(a)l35g2000pra.googlegroups.com>...
>
> doc subplot
>
> %%%%%%%%%%%%%
>
> subplot(2,1,1),hist(...);
> subplot(2,1,2),plot(...);
>
> -Nathan

Thanks for your quick answer.
It isn't exactly what I wanted though.

I try to put them in the same graph, it should look like this (random screenshot from google, i'm aware it's not MATLAB):
http://www.qualityadvisor.com/sqc/images/histogram2.JPG

The plot should overly the histogram.
From: Tom Lane on 8 Sep 2009 15:30
>> subplot(2,1,1),hist(...);
>> subplot(2,1,2),plot(...);
>>
>> -Nathan
>
> Thanks for your quick answer.
> It isn't exactly what I wanted though.
>
> I try to put them in the same graph, it should look like this (random
> screenshot from google, i'm aware it's not MATLAB):
> http://www.qualityadvisor.com/sqc/images/histogram2.JPG
>
> The plot should overly the histogram.

You didn't say exactly what was wrong when you tried the histogram and plot
with "hold on." It may be that the two were not on the same scale. A
histogram has bars that sum to the number of observations. A probability
density, if that's what you were trying to plot, is scaled so that it
integrates to one. You can use the histogram bar width and the number of
observations to adjust either one so that it's on the same scale as the
other. Here's an example:

y = 100 + 10*randn(1000,1);
hist(y,70:5:130)
x = linspace(70,130);
fx = 5 * 1000 * normpdf(x,100,10); % binwidth * nobs * density
line(x,fx,'color','r')

Of course you can use "hold on" and "plot" where I used "line" instead. I
used normpdf from the Statistics Toolbox, but you may have your own density
function or plan to write one.

-- Tom


From: Nathan on 8 Sep 2009 15:38
On Sep 8, 12:11 pm, "adam " <unique...(a)gmail.com> wrote:
> Nathan <ngrec...(a)gmail.com> wrote in message <7d763f1a-0bad-449b-a1c6-b11bae9b2...(a)l35g2000pra.googlegroups.com>...
>
> > doc subplot
>
> > %%%%%%%%%%%%%
>
> > subplot(2,1,1),hist(...);
> > subplot(2,1,2),plot(...);
>
> > -Nathan
>
> Thanks for your quick answer.
> It isn't exactly what I wanted though.
>
> I try to put them in the same graph, it should look like this (random screenshot from google, i'm aware it's not MATLAB):http://www.qualityadvisor.com/sqc/images/histogram2.JPG
>
> The plot should overly the histogram.

Hm. Well, I have something exactly like that... but I'm not sure where
I got the function from. (It's been part of my program before I even
started working on it)
However, this function applies the histogram to your data. It doesn't
allow you to just put your data + a random histogram together.

I hope this helps (and hope it's okay that I shared it).

Here it is in it's entirety:

function [h,S] = histfitp(data,nbins,PlotColor)
%HISTFIT Histogram with superimposed fitted normal density.
% HISTFIT(DATA,NBINS,[PlotColor]) plots a histogram of the values in
the vector DATA.
% using NBINS bars in the histogram. With one input argument, NBINS
is set
% to the square root of the number of elements in DATA.
%
% PlotColor default is 'b' (blue)
%
% H = HISTFIT(DATA,NBINS) returns a vector of handles to the plotted
lines.
% H(1) is a handle to the histogram, H(2) is a handle to the density
curve.
%
% Amended by: PNath(a)London.edu 15-Jan-2002
%
% B.A. Jones 2-14-95
% Copyright (c) 1993-98 by The MathWorks, Inc.
% $Revision: 2.7 $ $Date: 1998/05/28 20:13:55 $


if nargin < 3
PlotColor = 'b';
end


[row,col] = size(data);
if min(row,col) > 1
error('First argument has to be a vector.');
end

if row == 1
row = col;
data = data(:);
end

if nargin < 2
nbins = ceil(sqrt(row));
end

[n,xbin]=hist(data,nbins);

mr = mean(data); % Estimates the parameter, MU, of the normal
distribution.
sr = std(data); % Estimates the parameter, SIGMA, of the normal
distribution.

x=(-3*sr+mr:0.1*sr:3*sr+mr)';% Evenly spaced samples of the expected
data range.


hh = bar(xbin,n,1,PlotColor); % Plots the histogram. No gap between
bars.

np = get(gca,'NextPlot');
set(gca,'NextPlot','add')

xd = get(hh,'Xdata'); % Gets the x-data of the bins.

rangex = max(xd(:)) - min(xd(:)); % Finds the range of this data.
binwidth = rangex/nbins; % Finds the width of each bin.


y = normpdf(x,mr,sr);
y = row*(y*binwidth); % Normalization necessary to overplot the
histogram.

hh1 = plot(x,y,'r-','LineWidth',2); % Plots density line over
histogram.

% Create an output structure
S.xbin = xbin;
S.n = n;
S.PlotColor = PlotColor;
S.x = x;
S.y = y;

if nargout >= 1
h = [hh; hh1];
end

set(gca,'NextPlot',np)



%%%%%%%%%%%%%%%%%%%%%%%%%%5
-Nathan
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