function varargout = recursivePlot_2(xp,function_handles,dimensions,function_arguments)
%% varargout = recursivePlot(xp,function_handles,dimensions,function_arguments)
% Purpose: Takes in multidimensional data and a set of function handles for
% plotting. Function handles operate on low-dimensional subspaces.
% recursivePlot assigns the high dimensional data in xp to the plotting
% functions until all dimensions have been used up.
%
% Forms:
% varargout = recursivePlot_2(xp,function_handles,dimensions)
% varargout = recursivePlot_2(xp,function_handles,dimensions,function_arguments)
%
% Inputs:
% xp : xPlt structure with Nd dimensions
%
% function_handles : 1xNd+1 cell array of function handles. See below
% for function handle specifications.
%
% dimensions : 1xNd cell array of vectors. Each vector corresponds
% to a function handle. Specifies which dimensions
% in xp to assign to each function handle.
%
% function_arguments : (optional) 1xNd cell array of cell arrays, each containing
% additional arguments to pass to each function
% handle. There should be one cell array for
% each function handle.
%
% Details:
% The function_handles cell array should point to functions of the form:
% varargout = function func (xp,varargin)
% where xp is an xPlt object. Each function handle
% warning('finish this');
%
% Algorithm:
% recursivePlot plots the data in a recursive manner. It does the following
% 1. Creates a new xPlt structure called xp2, which is a low-dimensional
% version of xp. The dimensions of xp2 are given by dimensions{1}.
%
% 2. recusrivePlot then passes xp2 to the first function handle,
% function_handles{1}.
%
% Each entry in xp2.data contains a function handle that recursively
% calls back recursivePlot. This serves as simply an instruction
% to handle plotting the remainder of the dimensions in xp (e.g.
% dimensions(2:end)).
%
% function_handles{1} loops through xp2.data and executes these
% function handles, thus producing plots of xp's remaining dimensions.
%
% 3. The stopping conditions for the recursion are reached when xp runs
% out of dimensions. In this case, the final function handle receives
% a xp object with size(xp) = 1. Thus, the final function handle should
% actually plot the data.
%
% Example
% See demos_xPlt.m
%
% for plotting the
% function_handles{1} cycles through all the entries in xp2
% The dimensions of xp2 are sz(dimensions{1}), where
% sz = size(xp). xp2.data contains a function handle. This function
% handle is a recursive call to
% 2. Calls function_handles{1} and passes it xp2.
% 3.
%
% Takes dimensions{1} from xp and creates a new
%
% Examples:
% See demos file.
% function_arguments - cell array of argument cell arrays to pass to
% function_handles. Must have one cell array for each function_handle
% passed. Use empty cell arrays for no arguments. E.g.
% function_arguments = { {}, {}, {1} } for nothing, nothing, and
% 1 as arguments.
if nargin < 4
function_arguments = cell(size(function_handles));
for i = 1:length(function_arguments)
function_arguments{i} = {};
end
end
% Validate inputs
Nfh = length(function_handles);
Nd = length(dimensions);
Nfha = length(function_arguments);
if Nfh ~= Nd; error('Number of cells in dimensions must equal the number of function handles supplied'); end
if Nfh ~= Nfha; error('Number of cells in function_arguments must equal number of function handles supplied'); end
% Convert any regular expressions in dimensions into their
% corresponding indices if necessary
dimensions = dimensions_regex_2_index(xp,dimensions);
% Na = ndims(xp);
% N_dims_supplied = sum(cellfun(@length,dimensions));
% if Na ~= N_dims_supplied
% error('Total number of entries supplied in dimensions must equal ndims(xp)');
% end
sz = size(xp);
if length(function_handles) > 1
% xp_temp = permute(xp, [dimensions{1}, cell2mat(dimensions{2:end})]);
% Set up a new xPlt object with dimensions matching current
% function handle
xp2 = xp.reset; % Create a new xPlt object
sz2 = sz(dimensions{1});
ndims2 = length(dimensions{1});
total_calls = prod(sz2);
selection_curr = cell(1,length(sz));
clear output_indices
[xp2_indices{1:ndims2}] = ind2sub(sz2, 1:total_calls); % xp2 will loop through chosen dimensions
xp2_indices = num2cell(cat(1, xp2_indices{:})');
xp_indices = cell(1, length(xp.axis)); % Initialize xp_indices
for call = 1:total_calls
xp_indices(dimensions{1}) = xp2_indices(call, :);
mydata{xp2_indices{call, :}} = @() recursivePlot_2(xp.subset(xp_indices{:}),...
function_handles(2:end),dimensions(2:end),function_arguments(2:end));
end
% Update axes
for i = 1:length(dimensions{1})
dim_curr = dimensions{1}(i);
myvalues{i} = xp.axis(dim_curr).values;
mynames{i} = xp.axis(dim_curr).name;
end
xp2 = xp2.importData(mydata,myvalues,mynames);
[varargout{1:nargout}] = function_handles{1}(xp2,function_arguments{1}{:});
else
[varargout{1:nargout}] = function_handles{1}(xp,function_arguments{1}{:});
end
end
function dimensions = dimensions_regex_2_index(xp,dimensions)
for i = 1:length(dimensions)
dim_curr = dimensions{i};
if iscell(dim_curr)
for j = find(cellfun(@ischar,dim_curr))
dim_curr{j} = findaxis_mod(xp,dim_curr{j});
end
if any(cellfun(@length,dim_curr) > 1); error('Ambiguous dimension supplied'); end
dim_curr = cell2mat(dim_curr);
elseif ischar(dim_curr)
dim_curr = findaxis_mod(xp,dim_curr);
end
dimensions{i} = dim_curr;
end
end
function out = findaxis_mod(xp,str)
if strcmp(str,'data')
out = 0;
else
out = xp.findaxis(str);
end
end