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sp_joint_hist.m
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sp_joint_hist.m
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function [n edges_x edges_y] = sp_joint_hist(x, y, x_partition_type, Lx, y_partition_type, Ly)
% function [n edges_x edges_y] = sp_joint_hist(x, y, x_partition_type, Lx, y_partition_type, Ly)
%
% Divides the values in vectors x,y to Lx,Ly bins, where the number of elements
% in every bin depends on x/y_partition_type.
% Then computes the joint count matrix in the XY plane
%
% INPUTS:
% x : [array] of length N
% y : [array] of length N
% x_partition_type: [string] 'uniform' : uniform marginal distibutions by using varying bin widths
% 'equal_bins' : divide x to Lx bins of equal widths
% 'unique' : count unique values (doesn't use Lx)
% Lx: [int] number of bins, Lx <= N
% y_partition_type: [string] 'uniform' : uniform marginal distibutions by using varying bin widths
% 'equal_bins' : divide y to Ly bins of equal widths
% 'unique' : count unique values (doesn't use Ly)
% Ly: [int] number of bins, Ly <= N
%
% OUTPUT:
% n : [matrix][Lx x Ly] with counts of joint occurances: x is rows, y in columns
% edges_x: [array][1xL+1] with the edges of the bins
% edges_y: [array][1xL+1] with the edges of the bins
%
% Sagi Perel, 09/2012, updated 10/2012
if(nargin < 6 || nargin > 6)
error('sp_joint_hist: wrong number of input arguments provided');
end
if(~isvector(x))
error('sp_joint_hist: x must be a vector');
end
N = length(x);
if(~isvector(y))
error('sp_joint_hist: y must be a vector');
elseif(length(y)~=N)
error('sp_joint_hist: length(x)~=length(y)');
end
if(~exist('x_partition_type','var') || isempty(x_partition_type))
x_partition_type = 'uniform';
elseif(~ischar(x_partition_type))
error('sp_joint_hist: x_partition_type must be a string');
elseif(~any(strcmp(x_partition_type,{'uniform','equal_bins','unique'})))
error('sp_joint_hist: unknown value for x_partition_type');
end
if(~strcmp(x_partition_type,'unique')) % x_partition_type,'unique' does not use Lx
if(~isscalar(Lx))
error('sp_joint_hist: Lx must be a scalar');
elseif(Lx>N)
error('sp_joint_hist: Lx > N');
end
end
if(~exist('y_partition_type','var') || isempty(y_partition_type))
y_partition_type = 'uniform';
elseif(~ischar(y_partition_type))
error('sp_joint_hist: y_partition_type must be a string');
elseif(~any(strcmp(y_partition_type,{'uniform','equal_bins','unique'})))
error('sp_joint_hist: unknown value for y_partition_type');
end
if(~strcmp(y_partition_type,'unique')) % y_partition_type,'unique' does not use Ly
if(~isscalar(Ly))
error('sp_joint_hist: Ly must be a scalar');
elseif(Ly>N)
error('sp_joint_hist: Ly > N');
end
end
% partition sorted x into bins
switch(x_partition_type)
case 'uniform'
edges_x = sp_uniform_hist(x, Lx);
case 'equal_bins'
edges_x = sp_equal_bins_hist(x, Lx);
case 'unique'
edges_x = sp_unique_hist(x);
Lx = length(edges_x) - 1;
end
% partition sorted y into bins
switch(y_partition_type)
case 'uniform'
edges_y = sp_uniform_hist(y, Ly);
case 'equal_bins'
edges_y = sp_equal_bins_hist(y, Ly);
case 'unique'
edges_y = sp_unique_hist(y);
Ly = length(edges_y) - 1;
end
% sanity check
if(length(edges_x) ~= Lx+1)
error('sp_joint_hist: internal error: length(edges_x) ~= Lx+1');
end
if(length(edges_y) ~= Ly+1)
error('sp_joint_hist: internal error: length(edges_y) ~= Ly+1');
end
% count occurences in joint bins and compute probabilities
n=zeros(Lx, Ly);
for i=1:Lx
x_left_edge = edges_x(i);
x_right_edge = edges_x(i+1);
% use [ ) notation for all bins, except for the last bin where [ ] is used
if(i==Lx)
lidx = (x >= x_left_edge & x <= x_right_edge);
else
lidx = (x >= x_left_edge & x < x_right_edge);
end
% count occurences in columns
for j=1:Ly
joint_counts = histc(y(lidx),edges_y);
joint_counts(end-1) = joint_counts(end-1)+joint_counts(end);
joint_counts(end) = [];
n(i,:) = joint_counts;
end
end
% OLD CODE
% switch(partition_type)
% case 'uniform'
% edges_x = sp_uniform_hist(x, Lx);
% edges_y = sp_uniform_hist(y, Ly);
% n=zeros(Lx, Ly);
% for i=1:Lx
% x_left_edge = edges_x(i);
% x_right_edge = edges_x(i+1);
% if(i==Lx)
% lidx = (x >= x_left_edge & x <= x_right_edge);
% else
% lidx = (x >= x_left_edge & x < x_right_edge);
% end
% for j=1:Ly
% joint_counts = histc(y(lidx),edges_y);
% joint_counts(end-1) = joint_counts(end-1)+joint_counts(end);
% joint_counts(end)=[];
% n(i,:) = joint_counts;
% end
% end
%
% case 'equal_bins'
% min_x = min(x);
% max_x = max(x);
%
% min_y = min(y);
% max_y = max(y);
% if(Lx == Ly)
% X=round((x-min_x)*(Lx-1)/(max_x-min_x+eps));
% Y=round((y-min_y)*(Lx-1)/(max_y-min_y+eps));
% n=zeros(Lx);
% edges=0:Lx-1;
% for i=0:Lx-1
% n(i+1,:) = histc(Y(X==i),edges);
% end
% edges_x = round( min_x : (max_x-min_x)/Lx : max_x );
% edges_y = round( min_y : (max_y-min_y)/Lx : max_y );
% else
% error('sp_joint_hist: not yet implemented');
% end
%
% case 'unique'
%
%
% otherwise
% error('sp_joint_hist: unknown value for partition_type');
% end