Saving a Matlab figure to file using command-line

September 30, 2011 Coded in Matlab
function save_fig(h, name, format)
% Matlab has a wierd way of saving figures and keeping the plot looking
% exactly the way it does on your screen.  Thi function simplifies the 
% entire process in a way that is barely documented. 
%
% Usage:      SAVE_FIG(h, name, format);
%
%             H is the handle to the figure.  This can be obtain in the 
%               following manner:  H = figure(1);
%             NAME is the filename without extension
%             FORMAT is the graphic format.  Options are:
%             
%                   'bmpmono'    BMP monochrome BMP
%                   'bmp16m'     BMP 24-bit BMP
%                   'bmp256'     BMP 8-bit (256-color) 
%                   'bmp'        BMP 24-bit	
%                   'meta'       EMF
%                   'eps'        EPS black and white
%                   'epsc'       EPS color
%                   'eps2'       EPS Level 2 black and white
%                   'epsc2'      EPS Level 2 color
%                   'fig'        FIG Matlab figure file
%                   'hdf'        HDF 24-bit
%                   'ill'        ILL (Adobe Illustrator)
%                   'jpeg'       JPEG 24-bit
%                   'pbm'        PBM (plain format) 1-bit
%                   'pbmraw'     PBM (raw format) 1-bit
%                   'pcxmono'    PCX 1-bit
%                   'pcx24b'     PCX 24-bit color PCX file format
%                   'pcx256'     PCX 8-bit newer color (256-color)
%                   'pcx16'      PCX 4-bit older color (16-color)
%                   'pdf'        PDF Color PDF file format
%                   'pgm'        PGM Portable Graymap (plain format)
%                   'pgmraw'     PGM Portable Graymap (raw format)
%                   'png'        PNG 24-bit
%                   'ppm'        PPM Portable Pixmap (plain format)
%                   'ppmraw'     PPM Portable Pixmap (raw format)
%                   'svg'        SVG Scalable Vector Graphics
%                   'tiff'       TIFF 24-bit
%
% Author: sparafucile17

if(strcmp(format,'fig'))
    saveas(h, name, 'fig');
else
    options.Format = format;
    hgexport(h, name, options);
end

Putting a Matlab figure to a specific screen location

September 30, 2011 Coded in Matlab
function set_fig_position(h, top, left, height, width)
% Matlab has a wierd way of positioning figures so this function
% simplifies the poisitioning scheme in a more conventional way.
%
% Usage:      SET_FIG_POISITION(h, top, left, height, width);
%
%             H is the handle to the figure.  This can be obtain in the 
%               following manner:  H = figure(1);
%             TOP is the "y" screen coordinate for the top of the figure
%             LEFT is the "x" screen coordinate for the left side of the figure
%             HEIGHT is how tall you want the figure
%             WIDTH is how wide you want the figure
%
% Author: sparafucile17

% PC's active screen size
screen_size = get(0,'ScreenSize');
pc_width  = screen_size(3);
pc_height = screen_size(4);

%Matlab also does not consider the height of the figure's toolbar...
%Or the width of the border... they only care about the contents!
toolbar_height = 77;
window_border  = 5;

% The Format of Matlab is this:
%[left, bottom, width, height]
m_left   = left + window_border;
m_bottom = pc_height - height - top - toolbar_height - 1;
m_height = height;
m_width  = width - 1;

%Set the correct position of the figure
set(h, 'Position', [m_left, m_bottom, m_width, m_height]);

%If you want it to print to file correctly, this must also be set
% and you must use the "-r72" scaling to get the proper format
set(h, 'PaperUnits', 'points');
set(h, 'PaperSize', [width, height]); 
set(h, 'PaperPosition', [0, 0, width, height]); %[ left, bottom, width, height]

Least Squares fit to a linear equation

September 30, 2011 Coded in Matlab
function [m, b] = ls_linear(x_observed, y_observed)
%
% Perform Least Squares curve-fitting techniques to solve the coefficients
% of the linear equation: y = m*x + b.  Input and Output equation 
% observations must be fed into the algorithm and a best fit equation will
% be calculated.
%
% Usage:     [M,B] = ls_linear(observed_input, observed_output);
%
%            observed_input  is the x-vector observed data
%            observed_output is the y-vector observed data
%
% Author:    sparafucile17 06/04/03
%

if(length(x_observed) ~= length(y_observed))
    error('ERROR: Both X and Y vectors must be the same size!');
end

%Calculate vector length once
vector_length = length(x_observed);

%
% Theta = [   x1    1   ]
%         [   x2    1   ]
%         [   x3    1   ]
%         [   x4    1   ]
%         [   ...  ...  ]
%
Theta = ones(vector_length, 2);
Theta(1:end, 1) = x_observed;

%
% Theta_0 = [  y1   ]
%           [  y2   ]
%           [  y3   ]
%           [  y4   ]
%           [  ...  ]
%
Theta_0 = y_observed;

%
% Theta_LS = [  M  ]
%            [  B  ]
%
Theta_LS = ((Theta' * Theta)^-1 ) * Theta' * Theta_0;

%Return the answer
m = Theta_LS(1);
b = Theta_LS(2);

Measuring Peak-to-Peak

September 30, 2011 Coded in Matlab
function y = peak2peak(signal)
% Return the peak-to-peak amplitude of the supplied signal.  This is the
% same as max(signal) minus min(signal).
%
% Usage: y = PEAK2PEAK(signal);
%
%        SIGNAL is your one-dimensional input array
%
% Author: sparafucile17

% Input must have some length
if(length(signal) == 1)
    error('ERROR: input signal must have more than one element');
end

% This function only supports one-dimensional arrays
if((size(signal, 2) ~= 1) && (size(signal, 1) ~= 1))
    error('ERROR: Input must be one-dimensional');
end

% Find the peak and return it
min_sig = min(signal);
max_sig = max(signal);

% Answer
y = max_sig - min_sig;

Percent Error

September 30, 2011 Coded in Matlab
function [per_error] = percent_error(measured, actual)
% Creates the percent error between measured value and actual value
%
% Usage: percent_error(MEASURED, ACTUAL);
%
%        Measured is the your result
%        Actual is the value that your result should be
%
% Author: sparafucile17

per_error = abs(( (measured - actual) ./ actual ) * 100);

Finding local minima

September 26, 20111 comment Coded in Matlab
function [time,amp] = minima(signal, len)
%
% Finds the local minimum values of the given signal.
% 
% Usage:  [IND,AMP] = MINIMA(X, N);
% 
%         N is the number of points that need to be evaluated
%           (Normally equal to LENGTH(X))
%         X is the data 
%         IND contains the indices of X that contain the minima data
%         AMP contains the minima amplitudes
%
% Author: sparafucile17 10/02/2003

%Initialize data
index = 1;
prev = signal(1);
local_time = 0;
local_amp = 0;
prev_slope = 1;  %allow a maxima point at the second sample

%prevent length error
if(len > length(signal))
   len = length(signal)
end

%Loop through data and find local minimums
for loop_i=2:len
   cur = signal(loop_i);
   slope = cur - prev;
   if((cur < prev) & (prev_slope > 0))  %Positive slope and amplitude dips
      local_time(index) = loop_i-1;
      local_amp(index) = prev;
      index = index+1;
   end
   prev = cur;
   prev_slope = slope;
end

%After loop assign data to output variables
time = local_time;
amp = local_amp;

Finding local maxima

September 26, 20112 comments Coded in Matlab
function [time,amp] = maxima(signal, thresh, len)
% Finds the local maximum values of the given signal.
% 
% Usage:  [IND,AMP] = MAXIMA(X, THRESH, N);
% 
%         X is the data 
%         THRESH is the threshold that signal must be greater
%            than in order to be counted. (Default = 0.0)
%         N is the number of points that need to be evaluated
%           (Defaults = LENGTH(X))
%         IND contains the indices of X that contain the maxima data
%         AMP contains the maxima amplitudes
%
% Author: sparafucile17 10/02/2003

if(exist('len') == 0)
    len = length(signal);
end
if(exist('thresh') == 0)
    thresh = 0.0;
end

%Initialize data
index = 1;
prev = signal(1);
local_time = 0;
local_amp = 0;
prev_slope = 1;  %allow a maxima point at the second sample

%prevent length error
if(len > length(signal))
   len = length(signal)
end

%Loop through data and find local maximums
for loop_i=2:len
   cur = signal(loop_i);
   slope = cur - prev;
   if((cur < prev) & (prev_slope > 0) & (cur > thresh))  %Positive slope and amplitude dips
      local_time(index) = loop_i-1;
      local_amp(index) = prev;
      index = index+1;
   end
   prev = cur;
   prev_slope = slope;
end

%After loop assign data to output variables
time = local_time;
amp = local_amp;

Pink Noise Generator

September 26, 2011 Coded in Matlab
function out = create_pink_noise(Fs, Sec, Amp)

% Creates a pink noise signal and saves it as a wav file
%
% Usage: create_noise(Fs, Sec, Amp);
%
%        Fs is the desired sampling rate
%        Sec is the duration of the signal in seconds
%        Amp is the amplitude in dB of the signal (0dB to -144dB)
%
% Author: sparafucile17 06/14/02

%error trapping
if((Amp > 0) || (Amp < -144))
    error('Amplitude is not within the range of 0dB to -144dB');
end

%Create Whitenoise
white_noise = randn((Fs*Sec)+1,1);

%Apply weighted sum of first order filters to approximate a -10dB/decade
%filter.  This is Paul Kellet's "refined" method (a.k.a instrumentation
%grade)  It is accurate to within +/-0.05dB above 9.2Hz
b=zeros(7,1);
for i=1:((Fs*Sec)+1)
    b(1) = 0.99886 * b(1) + white_noise(i) * 0.0555179;
    b(2) = 0.99332 * b(2) + white_noise(i) * 0.0750759;
    b(3) = 0.96900 * b(3) + white_noise(i) * 0.1538520;
    b(4) = 0.86650 * b(4) + white_noise(i) * 0.3104856;
    b(5) = 0.55000 * b(5) + white_noise(i) * 0.5329522;
    b(6) = -0.7616 * b(6) - white_noise(i) * 0.0168980;
    pink_noise(i) = b(1) + b(2) + b(3) + b(4) + b(5) + b(6) + b(7) + white_noise(i) * 0.5362;
    b(7) = white_noise(i) * 0.115926; 
end

%Normalize to +/- 1
if(abs(min(pink_noise)) > max(pink_noise))  
    pink_noise = pink_noise / abs(min(pink_noise));
else
    pink_noise = pink_noise / max(pink_noise);
end

%Normalize to prevent positive saturation (We can't represent +1.0)
pink_noise = pink_noise /abs(((2^31)-1)/(2^31));

%Scale signal to match desired level
pink_noise = pink_noise * 10^(Amp/20);

%Output noise signal
out = pink_noise(1:end-1);

C-weighting filter

September 25, 2011 Coded in Matlab
%Sampling Rate
Fs = 48000;

%Analog C-weighting filter according to IEC/CD 1672.
1672.
f1 = 20.598997; 
f4 = 12194.217;
C1000 = 0.0619;
pi  = 3.14159265358979;
NUM = [ (2*pi*f4)^2*(10^(C1000/20)) 0 0 ];
DEN = conv([1 +4*pi*f4 (2*pi*f4)^2],[1 +4*pi*f1 (2*pi*f1)^2]); 

%Bilinear transformation of analog design to get the digital [b,a] = bilinear(NUM,DEN,Fs);

A-weighting filter

September 25, 20111 comment Coded in Matlab
%Sampling Rate
Fs = 48000;

%Analog A-weighting filter according to IEC/CD 1672.
f1 = 20.598997; 
f2 = 107.65265;
f3 = 737.86223;
f4 = 12194.217;
A1000 = 1.9997;
pi = 3.14159265358979;
NUM = [ (2*pi*f4)^2*(10^(A1000/20)) 0 0 0 0 ];
DEN = conv([1 +4*pi*f4 (2*pi*f4)^2],[1 +4*pi*f1 (2*pi*f1)^2]); 
DEN = conv(conv(DEN,[1 2*pi*f3]),[1 2*pi*f2]);

%Bilinear transformation of analog design to get the digital filter. 
[b,a] = bilinear(NUM,DEN,Fs);