Reformat help text for consistency

Author: andymilne

array2spArray.m

@@ -1,20 +1,22 @@
 function spA = array2spArray(A)
 %ARRAY2SPARRAY Convert a full array into a sparse array structure.
-%   A sparse array structure has the following fields:
+%
+%   spA = array2spArray(A) A sparse array structure has the following fields:
 %
 %   'Size', which is a row vector of the sizes of each dimension of the full
-%   array -- for example, a column vector with N entries has a size of N; a
-%   row vector with N entries has a size of (1,N); a matrix with N entries has
-%   a size (J,K), where JK = N; a three-way array with N entries has a size
+%   array -- for example, a column vector with N entries has a size of N; a row
+%   vector with N entries has a size of (1,N); a matrix with N entries has a
+%   size (J,K), where JK = N; a three-way array with N entries has a size
 %   (J,K,L), where JKL = N;
 %
 %   'Ind', which is a column vector of linear indices of nonzero values in the
 %   full array that they represent;
 %
 %   'Val', which is a column vector of the values at those indices.
 %
-%   Version 1.0 by Andrew J. Milne, The MARCS Institute, Western Sydney
-%   University, 2018-01-09
+%   All singleton dimensions are removed.
+%
+%   By Andrew J. Milne, The MARCS Institute, Western Sydney University
 %
 %   See also SPARRAY2ARRAY.
 

spArray2Array.m

@@ -1,8 +1,9 @@
 function A = spArray2Array(spA)
 %SPARRAY2ARRAY Convert a sparse array structure into a full array. 
 %
-%   Version 1.0 by Andrew J. Milne, The MARCS Institute, Western Sydney
-%   University, 2018-01-09
+%   A = spArray2Array(spA)
+%
+%   By Andrew J. Milne, The MARCS Institute, Western Sydney University
 %   
 %   See also ARRAY2SPARRAY.
 

spConv.m

@@ -1,5 +1,6 @@
 function spC = spConv(spA,spB,shape)
 %SPCONV N-dimensional convolution of two N-dimensional sparse array structures.
+%
 %   spC = spConv(spA,spB,shape): N-dimensional convolution of two N-dimensional
 %   full arrays, each represented as a sparse array structure or a full array.
 %   The output is a sparse array structure.
@@ -45,18 +46,18 @@
 indASzC = spSub2spInd(sizC,subsA);
 indBSzC = spSub2spInd(sizC,subsB);
 
-% Do the convolution
+%% Do the convolution
 indC = indASzC + indBSzC' - 1; % Outer sum of indices, minus 1
 indC = indC(:);
 valC = spA.Val.*spB.Val'; % Outer product of values
 valC = valC(:);
 sparseC = sparse(indC,1,valC); % Accumulate (sum) over repeated indices
 
-% Make sparse array structure for full convolution
+%% Make sparse array structure for full convolution
 [indC,~,valC] = find(sparseC);
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 spC = struct('Size',sizC,'Ind',indC,'Val',valC);
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
 if isequal(shape,'same') % Remove entries outside size A
     % Convert linear indices of spC to subs
@@ -69,9 +70,9 @@
     % convert subsCTrunc to linear index for array of size spA.Size
     indC = spSub2spInd(spA.Size,subsCTrunc);
     % Make into a sparse array structure
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
     spC = struct('Size',spA.Size,'Ind',indC,'Val',valC);
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 elseif isequal(shape,'circ') % Wrap entries around size A
     % Convert linear indices of spC to subs
     subsC = spInd2spSub(spC);
@@ -83,9 +84,9 @@
     sparseC = sparse(indC,1,valC);
     % Make into a sparse array structure
     [indC,~,valC] = find(sparseC);
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
     spC = struct('Size',spA.Size,'Ind',indC,'Val',valC);
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 end
 
 end

spCosSim.m

@@ -1,18 +1,19 @@
 function s = spCosSim(spA,spB)
 %SPCOSSIM Cosine similarity of two sparse array structures
+%
 %   s = spCosSim(spA,spB):  Cosine similarity of two vectorized full arrays,
 %   each represented as a sparse array structure or as a full array. They must
 %   have the same numbers of entries (including zeros). The output is a scalar.
 %
-%   Version 1.0 by Andrew J. Milne, The MARCS Institute, Western Sydney
-%   University, 2018-01-09
+%   By Andrew J. Milne, The MARCS Institute, Western Sydney University
 %
 %   See also SPPDIST.
 
 persistent innerAA innerBB spALast spBLast
 
 if nargin ~= 2
-    error('There must be exactly two arguments (arrays or sparse array structures).')
+    error(['There must be exactly two arguments (arrays or sparse array ', ...
+           'structures).'])
 end
 
 % Convert full array arguments to sparse array structures

spFlip.m

@@ -1,12 +1,12 @@
 function spC = spFlip(spA,dim)
 %SPFLIP Flip order of entries in dimensions specified in 'dim'.
+%
 %   spC = spFlip(spA,dim): Flip the order of entries of the full array,
 %   represented as a sparse array structure or full array, in the dimensions
 %   specified in the row vector or scalar 'dim'. The output is a sparse array
 %   structure.
 %
-%   Version 1.0 by Andrew J. Milne, The MARCS Institute, Western Sydney
-%   University, 2018-01-16
+%   By Andrew J. Milne, The MARCS Institute, Western Sydney University
 %
 %   See also FLIP.
 
@@ -32,12 +32,12 @@
     % vector of 1s for flips and 0s for no flips
     logDim(dim) = 1;
     % vector of 1s for flips and -1s for no flips
-    mult = logDim;
-    mult(logDim==0) = -1;
+    signChange = logDim;
+    signChange(logDim==0) = -1;
     % convert to subs
     subA = spInd2spSub(spA);
     % do the flips
-    flipSubA = (logDim.*spA.Size - subA + logDim).*mult;
+    flipSubA = (logDim.*spA.Size - subA + logDim).*signChange;
     % convert to linearindex
     indA = spSub2spInd(spA.Size,flipSubA);
 end

spInd2spSub.m

@@ -1,8 +1,9 @@
 function subsA = spInd2spSub(spA)
 %SPIND2SPSUB Convert a sparse array's linear index into a matrix of subscripts. 
 %
-%   Version 1.0 by Andrew J. Milne, The MARCS Institute, Western Sydney
-%   University, 2018-01-09
+%   subsA = spInd2spSub(spA)
+%
+%   By Andrew J. Milne, The MARCS Institute, Western Sydney University
 %   
 %   See also SPSUB2SPIND, IND2SUB.
 

spInner.m

@@ -1,14 +1,14 @@
 function c = spInner(varargin)
 %SPINNER Inner (scalar) product of two sparse array structures.
+%
 %   c = spInner(varargin): Inner (scalar) product of two full arrays, each
 %   represented as a sparse array structure or a full array. There are
 %   alternative definitions of 'inner product' for tensors/arrays. Here, it is
 %   their scalar product -- the sum of entries resulting from their entrywise
 %   (Hadamard) product. The sparse arrays can entered as a comma separated list
 %   or as a members of a cell.
 %
-%   Version 1.0 by Andrew J. Milne, The MARCS Institute, Western Sydney
-%   University, 2018-01-09
+%   By Andrew J. Milne, The MARCS Institute, Western Sydney University
 
 % Check whether varargin is a comma separated list or a cell array
 if ~iscell(varargin{1})
@@ -19,7 +19,8 @@
 nSpA = size(spA,2); % count the number of arrays
 
 if nSpA ~= 2
-    error('There must be two arguments (sparse array structures or full arrays).')
+    error(['There must be exactly two arguments (arrays or sparse array ', ...
+           'structures).'])
 end
 
 % Convert full array arguments to sparse array structures

spOuter.m

@@ -1,5 +1,6 @@
 function spC = spOuter(varargin)
-%SPOUTER THE Outer (tensor) product of sparse array structures.
+%SPOUTER Outer (tensor) product of sparse array structures.
+%
 %   spC = spOuter(varargin): The outer (tensor) product of full arrays, each
 %   represented as a sparse array structure or a full array (or scalar). The
 %   sparse array structures can be entered as a comma separated list or as a
@@ -9,8 +10,7 @@
 %   (N,P), the resulting tensor has size (M,N,P), not size (1,M,N,P). The
 %   output is a sparse array structure.
 %
-%   Version 1.0 by Andrew J. Milne, The MARCS Institute, Western Sydney
-%   University, 2018-01-09
+%   By Andrew J. Milne, The MARCS Institute, Western Sydney University
 
 % Check whether varargin is a comma separated list or a cell array
 if ~iscell(varargin{1})

spPDist.m

@@ -1,22 +1,23 @@
 function d = spPDist(spA,spB,p)
 %PDIST p-norm distance between two sparse array structures.
+%
 %   d = spPDist(spA,spB,p): The p-norm distance between two vectorized full
 %   arrays, each represented as a sparse array structure or as a full array.
 %   They must have the same numbers of entries (including zeros). When there
 %   are only two arguments, p = 2 is the default, which gives the Euclidean
 %   distance between the two vectors; when p = 1, this function gives the
 %   taxicab distance; when p = inf, it gives the maximum difference.
 %
-%   Version 1.0 by Andrew J. Milne, The MARCS Institute, Western Sydney
-%   University, 2018-01-09
+%   By Andrew J. Milne, The MARCS Institute, Western Sydney University
 % 
 %   See also SPCOSSIM.
 
 if nargin < 3
     p = 2;
 end
 if nargin < 2
-    error('There must be exactly two arguments (arrays or sparse array structures).')
+    error(['There must be exactly two arguments (arrays or sparse array ', ...
+           'structures).'])
 end
 
 % Convert full array arguments to sparse array structures

spPerm.m

@@ -1,12 +1,12 @@
 function spC = spPerm(spA,order)
 %SPPERM Permute dimensions of sparse array structure.
+%
 %   spC = spPerm(spA,order): Permute the dimensions of the full array
 %   represented as a sparse array structure or a full array. The second
 %   argument is the vector of permutations. The output is a sparse array
 %   structure.
 %
-%   Version 1.0 by Andrew J. Milne, The MARCS Institute, Western Sydney
-%   University, 2018-01-09
+%   By Andrew J. Milne, The MARCS Institute, Western Sydney University
 %
 %   See also SPIND2SPSUB, SPSUB2SPIND, PERMUTE.