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function newdata = jdatadecode(data, varargin)
%
% newdata=jdatadecode(data,opt,...)
%
% Convert all JData object (in the form of a struct array) into an array
% (accepts JData objects loaded from either loadjson/loadubjson or
% jsondecode for MATLAB R2016b or later)
%
% This function implements the JData Specification Draft 3 (Jun. 2020)
% see http://github.com/NeuroJSON/jdata for details
%
% authors:Qianqian Fang (q.fang <at> neu.edu)
%
% input:
% data: a struct array. If data contains JData keywords in the first
% level children, these fields are parsed and regrouped into a
% data object (arrays, trees, graphs etc) based on JData
% specification. The JData keywords are
% "_ArrayType_", "_ArraySize_", "_ArrayData_"
% "_ArrayIsSparse_", "_ArrayIsComplex_",
% "_ArrayZipType_", "_ArrayZipSize", "_ArrayZipData_"
% opt: (optional) a list of 'Param',value pairs for additional options
% The supported options include
% Recursive: [1|0] if set to 1, will apply the conversion to
% every child; 0 to disable
% Base64: [0|1] if set to 1, _ArrayZipData_ is assumed to
% be encoded with base64 format and need to be
% decoded first. This is needed for JSON but not
% UBJSON data
% Prefix: ['x0x5F'|'x'] for JData files loaded via loadjson/loadubjson, the
% default JData keyword prefix is 'x0x5F'; if the
% json file is loaded using matlab2018's
% jsondecode(), the prefix is 'x'; this function
% attempts to automatically determine the prefix;
% for octave, the default value is an empty string ''.
% FullArrayShape: [0|1] if set to 1, converting _ArrayShape_
% objects to full matrices, otherwise, stay sparse
% MaxLinkLevel: [0|int] When expanding _DataLink_ pointers,
% this sets the maximum level of recursion
% FormatVersion: [2|float]: set the JSONLab output version;
% since v2.0, JSONLab uses JData specification Draft 1
% for output format, it is incompatible with all
% previous releases; if old output is desired,
% please set FormatVersion to 1
%
% output:
% newdata: the converted data if the input data does contain a JData
% structure; otherwise, the same as the input.
%
% examples:
% obj={[],{'test'},true,struct('sparse',sparse(2,3),'magic',uint8(magic(5)))}
% jdata=jdatadecode(jdataencode(obj))
% isequaln(obj,jdata)
%
% license:
% BSD or GPL version 3, see LICENSE_{BSD,GPLv3}.txt files for details
%
% -- this function is part of JSONLab toolbox (http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab)
%
newdata = data;
opt = struct;
if (nargin == 2)
opt = varargin{1};
elseif (nargin > 2)
opt = varargin2struct(varargin{:});
end
opt.fullarrayshape = jsonopt('FullArrayShape', 0, opt);
opt.maxlinklevel = jsonopt('MaxLinkLevel', 0, opt);
%% process non-structure inputs
if (~isstruct(data))
if (iscell(data))
newdata = cellfun(@(x) jdatadecode(x, opt), data, 'UniformOutput', false);
elseif (isa(data, 'containers.Map'))
newdata = containers.Map('KeyType', data.KeyType, 'ValueType', 'any');
names = data.keys;
for i = 1:length(names)
newdata(names{i}) = jdatadecode(data(names{i}), opt);
end
end
return
end
%% assume the input is a struct below
fn = fieldnames(data);
len = length(data);
needbase64 = jsonopt('Base64', 0, opt);
format = jsonopt('FormatVersion', 2, opt);
if (isoctavemesh)
prefix = jsonopt('Prefix', '', opt);
else
prefix = jsonopt('Prefix', 'x0x5F', opt);
end
if (~isfield(data, N_('_ArrayType_')) && isfield(data, 'x_ArrayType_'))
prefix = 'x';
opt.prefix = 'x';
end
%% recursively process subfields
if (jsonopt('Recursive', 1, opt) == 1)
for i = 1:length(fn) % depth-first
for j = 1:len
if (isstruct(data(j).(fn{i})) || isa(data(j).(fn{i}), 'containers.Map'))
newdata(j).(fn{i}) = jdatadecode(data(j).(fn{i}), opt);
elseif (iscell(data(j).(fn{i})))
newdata(j).(fn{i}) = cellfun(@(x) jdatadecode(x, opt), newdata(j).(fn{i}), 'UniformOutput', false);
end
end
end
end
%% handle array data
if (isfield(data, N_('_ArrayType_')) && (isfield(data, N_('_ArrayData_')) || isfield(data, N_('_ArrayZipData_'))))
newdata = cell(len, 1);
for j = 1:len
if (isfield(data, N_('_ArrayZipSize_')) && isfield(data, N_('_ArrayZipData_')))
zipmethod = 'zip';
if (isstruct(data(j).(N_('_ArrayZipSize_'))))
data(j).(N_('_ArrayZipSize_')) = jdatadecode(data(j).(N_('_ArrayZipSize_')), opt);
end
dims = data(j).(N_('_ArrayZipSize_'))(:)';
if (length(dims) == 1)
dims = [1 dims];
end
if (isfield(data, N_('_ArrayZipType_')))
zipmethod = data(j).(N_('_ArrayZipType_'));
end
if (ismember(zipmethod, {'zlib', 'gzip', 'lzma', 'lzip', 'lz4', 'lz4hc', 'base64'}) || ~isempty(regexp(zipmethod, '^blosc2', 'once')))
decodeparam = {};
if (~isempty(regexp(zipmethod, '^blosc2', 'once')))
decompfun = @blosc2decode;
decodeparam = {zipmethod};
else
decompfun = str2func([zipmethod 'decode']);
end
arraytype = data(j).(N_('_ArrayType_'));
chartype = 0;
if (strcmp(arraytype, 'char') || strcmp(arraytype, 'logical'))
chartype = 1;
arraytype = 'uint8';
end
if (needbase64 && strcmp(zipmethod, 'base64') == 0)
ndata = reshape(typecast(decompfun(base64decode(data(j).(N_('_ArrayZipData_'))), decodeparam{:}), arraytype), dims);
else
ndata = reshape(typecast(decompfun(data(j).(N_('_ArrayZipData_')), decodeparam{:}), arraytype), dims);
end
if (chartype)
ndata = char(ndata);
end
else
error('compression method is not supported');
end
else
if (isstruct(data(j).(N_('_ArrayData_'))))
data(j).(N_('_ArrayData_')) = jdatadecode(data(j).(N_('_ArrayData_')), opt);
end
if (isstruct(data(j).(N_('_ArrayData_'))) && isfield(data(j).(N_('_ArrayData_')), N_('_ArrayType_')))
data(j).(N_('_ArrayData_')) = jdatadecode(data(j).(N_('_ArrayData_')), varargin{:});
end
if (iscell(data(j).(N_('_ArrayData_'))))
data(j).(N_('_ArrayData_')) = cell2mat(cellfun(@(x) double(x(:)), data(j).(N_('_ArrayData_')), 'uniformoutput', 0)).';
end
ndata = cast(data(j).(N_('_ArrayData_')), char(data(j).(N_('_ArrayType_'))));
end
if (isfield(data, N_('_ArrayZipSize_')))
if (isstruct(data(j).(N_('_ArrayZipSize_'))))
data(j).(N_('_ArrayZipSize_')) = jdatadecode(data(j).(N_('_ArrayZipSize_')), opt);
end
dims = data(j).(N_('_ArrayZipSize_'))(:)';
if (iscell(dims))
dims = cell2mat(dims);
end
if (length(dims) == 1)
dims = [1 dims];
end
ndata = reshape(ndata(:), fliplr(dims));
ndata = permute(ndata, ndims(ndata):-1:1);
end
iscpx = 0;
if (isfield(data, N_('_ArrayIsComplex_')) && isstruct(data(j).(N_('_ArrayIsComplex_'))))
data(j).(N_('_ArrayIsComplex_')) = jdatadecode(data(j).(N_('_ArrayIsComplex_')), opt);
end
if (isfield(data, N_('_ArrayIsComplex_')) && data(j).(N_('_ArrayIsComplex_')))
iscpx = 1;
end
iscol = 0;
if (isfield(data, N_('_ArrayOrder_')))
arrayorder = data(j).(N_('_ArrayOrder_'));
if (~isempty(arrayorder) && (arrayorder(1) == 'c' || arrayorder(1) == 'C'))
iscol = 1;
end
end
if (isfield(data, N_('_ArrayIsSparse_')) && isstruct(data(j).(N_('_ArrayIsSparse_'))))
data(j).(N_('_ArrayIsSparse_')) = jdatadecode(data(j).(N_('_ArrayIsSparse_')), opt);
end
if (isfield(data, N_('_ArrayIsSparse_')) && data(j).(N_('_ArrayIsSparse_')))
if (isfield(data, N_('_ArraySize_')))
if (isstruct(data(j).(N_('_ArraySize_'))))
data(j).(N_('_ArraySize_')) = jdatadecode(data(j).(N_('_ArraySize_')), opt);
end
dim = data(j).(N_('_ArraySize_'))(:)';
if (iscell(dim))
dim = cell2mat(dim);
end
dim = double(dim);
if (length(dim) == 1)
dim = [1 dim];
end
if (iscpx)
ndata(end - 1, :) = complex(ndata(end - 1, :), ndata(end, :));
end
if isempty(ndata)
% All-zeros sparse
ndata = sparse(dim(1), prod(dim(2:end)));
elseif dim(1) == 1
% Sparse row vector
ndata = sparse(1, ndata(1, :), ndata(2, :), dim(1), prod(dim(2:end)));
elseif dim(2) == 1
% Sparse column vector
ndata = sparse(ndata(1, :), 1, ndata(2, :), dim(1), prod(dim(2:end)));
else
% Generic sparse array.
ndata = sparse(ndata(1, :), ndata(2, :), ndata(3, :), dim(1), prod(dim(2:end)));
end
else
if (iscpx && size(ndata, 2) == 4)
ndata(3, :) = complex(ndata(3, :), ndata(4, :));
end
ndata = sparse(ndata(1, :), ndata(2, :), ndata(3, :));
end
elseif (isfield(data, N_('_ArrayShape_')))
if (isstruct(data(j).(N_('_ArrayShape_'))))
data(j).(N_('_ArrayShape_')) = jdatadecode(data(j).(N_('_ArrayShape_')), opt);
end
if (iscpx)
if (size(ndata, 1) == 2)
dim = size(ndata);
dim(end + 1) = 1;
arraydata = reshape(complex(ndata(1, :), ndata(2, :)), dim(2:end));
else
error('The first dimension must be 2 for complex-valued arrays');
end
else
arraydata = data.(N_('_ArrayData_'));
end
shapeid = data.(N_('_ArrayShape_'));
if (isfield(data, N_('_ArrayZipSize_')))
datasize = data.(N_('_ArrayZipSize_'));
if (iscell(datasize))
datasize = cell2mat(datasize);
end
datasize = double(datasize);
if (iscpx)
datasize = datasize(2:end);
end
else
datasize = size(arraydata);
end
if (isstruct(data(j).(N_('_ArraySize_'))))
data(j).(N_('_ArraySize_')) = jdatadecode(data(j).(N_('_ArraySize_')), opt);
end
arraysize = data.(N_('_ArraySize_'));
if (iscell(arraysize))
arraysize = cell2mat(arraysize);
end
arraysize = double(arraysize);
if (ischar(shapeid))
shapeid = {shapeid};
end
arraydata = double(arraydata).';
if (strcmpi(shapeid{1}, 'diag'))
ndata = spdiags(arraydata(:), 0, arraysize(1), arraysize(2));
elseif (strcmpi(shapeid{1}, 'upper') || strcmpi(shapeid{1}, 'uppersymm'))
ndata = zeros(arraysize);
ndata(triu(true(size(ndata)))') = arraydata(:);
if (strcmpi(shapeid{1}, 'uppersymm'))
ndata(triu(true(size(ndata)))) = arraydata(:);
end
ndata = ndata.';
elseif (strcmpi(shapeid{1}, 'lower') || strcmpi(shapeid{1}, 'lowersymm'))
ndata = zeros(arraysize);
ndata(tril(true(size(ndata)))') = arraydata(:);
if (strcmpi(shapeid{1}, 'lowersymm'))
ndata(tril(true(size(ndata)))) = arraydata(:);
end
ndata = ndata.';
elseif (strcmpi(shapeid{1}, 'upperband') || strcmpi(shapeid{1}, 'uppersymmband'))
if (length(shapeid) > 1 && isvector(arraydata))
datasize = double([shapeid{2} + 1, prod(datasize) / (shapeid{2} + 1)]);
end
ndata = spdiags(reshape(arraydata, min(arraysize), datasize(1)), -datasize(1) + 1:0, arraysize(2), arraysize(1)).';
if (strcmpi(shapeid{1}, 'uppersymmband'))
diagonal = diag(ndata);
ndata = ndata + ndata.';
ndata(1:arraysize(1) + 1:end) = diagonal;
end
elseif (strcmpi(shapeid{1}, 'lowerband') || strcmpi(shapeid{1}, 'lowersymmband'))
if (length(shapeid) > 1 && isvector(arraydata))
datasize = double([shapeid{2} + 1, prod(datasize) / (shapeid{2} + 1)]);
end
ndata = spdiags(reshape(arraydata, min(arraysize), datasize(1)), 0:datasize(1) - 1, arraysize(2), arraysize(1)).';
if (strcmpi(shapeid{1}, 'lowersymmband'))
diagonal = diag(ndata);
ndata = ndata + ndata.';
ndata(1:arraysize(1) + 1:end) = diagonal;
end
elseif (strcmpi(shapeid{1}, 'band'))
if (length(shapeid) > 1 && isvector(arraydata))
datasize = double([shapeid{2} + shapeid{3} + 1, prod(datasize) / (shapeid{2} + shapeid{3} + 1)]);
end
ndata = spdiags(reshape(arraydata, min(arraysize), datasize(1)), double(shapeid{2}):-1:-double(shapeid{3}), arraysize(1), arraysize(2));
elseif (strcmpi(shapeid{1}, 'toeplitz'))
arraydata = reshape(arraydata, flipud(datasize(:))');
ndata = toeplitz(arraydata(1:arraysize(1), 2), arraydata(1:arraysize(2), 1));
end
if (opt.fullarrayshape && issparse(ndata))
ndata = cast(full(ndata), data(j).(N_('_ArrayType_')));
end
elseif (isfield(data, N_('_ArraySize_')))
if (isstruct(data(j).(N_('_ArraySize_'))))
data(j).(N_('_ArraySize_')) = jdatadecode(data(j).(N_('_ArraySize_')), opt);
end
if (iscpx)
ndata = complex(ndata(1, :), ndata(2, :));
end
if (format > 1.9 && iscol == 0)
data(j).(N_('_ArraySize_')) = data(j).(N_('_ArraySize_'))(end:-1:1);
end
dims = data(j).(N_('_ArraySize_'))(:)';
if (iscell(dims))
dims = cell2mat(dims);
end
if (length(dims) == 1)
dims = [1 dims];
end
ndata = reshape(ndata(:), dims(:)');
if (format > 1.9 && iscol == 0)
ndata = permute(ndata, ndims(ndata):-1:1);
end
end
newdata{j} = ndata;
end
if (len == 1)
newdata = newdata{1};
end
end
%% handle table data
if (isfield(data, N_('_TableRecords_')))
newdata = cell(len, 1);
for j = 1:len
ndata = data(j).(N_('_TableRecords_'));
if (iscell(ndata))
if (iscell(ndata{1}))
rownum = length(ndata);
colnum = length(ndata{1});
nd = cell(rownum, colnum);
for i1 = 1:rownum
for i2 = 1:colnum
nd{i1, i2} = ndata{i1}{i2};
end
end
newdata{j} = cell2table(nd);
else
newdata{j} = cell2table(ndata);
end
else
newdata{j} = array2table(ndata);
end
if (isfield(data(j), N_('_TableRows_')) && ~isempty(data(j).(N_('_TableRows_'))))
newdata{j}.Properties.RowNames = data(j).(N_('_TableRows_'))(:);
end
if (isfield(data(j), N_('_TableCols_')) && ~isempty(data(j).(N_('_TableCols_'))))
newdata{j}.Properties.VariableNames = data(j).(N_('_TableCols_'));
end
end
if (len == 1)
newdata = newdata{1};
end
end
%% handle map data
if (isfield(data, N_('_MapData_')))
newdata = cell(len, 1);
for j = 1:len
key = cell(1, length(data(j).(N_('_MapData_'))));
val = cell(size(key));
for k = 1:length(data(j).(N_('_MapData_')))
key{k} = data(j).(N_('_MapData_')){k}{1};
val{k} = jdatadecode(data(j).(N_('_MapData_')){k}{2}, opt);
end
ndata = containers.Map(key, val);
newdata{j} = ndata;
end
if (len == 1)
newdata = newdata{1};
end
end
%% handle graph data
if (isfield(data, N_('_GraphNodes_')) && exist('graph', 'file') && exist('digraph', 'file'))
newdata = cell(len, 1);
isdirected = 1;
for j = 1:len
nodedata = data(j).(N_('_GraphNodes_'));
if (isstruct(nodedata))
nodetable = struct2table(nodedata);
elseif (isa(nodedata, 'containers.Map'))
nodetable = [keys(nodedata); values(nodedata)];
if (strcmp(nodedata.KeyType, 'char'))
nodetable = table(nodetable(1, :)', nodetable(2, :)', 'VariableNames', {'Name', 'Data'});
else
nodetable = table(nodetable(2, :)', 'VariableNames', {'Data'});
end
else
nodetable = table;
end
if (isfield(data, N_('_GraphEdges_')))
edgedata = data(j).(N_('_GraphEdges_'));
elseif (isfield(data, N_('_GraphEdges0_')))
edgedata = data(j).(N_('_GraphEdges0_'));
isdirected = 0;
elseif (isfield(data, N_('_GraphMatrix_')))
edgedata = jdatadecode(data(j).(N_('_GraphMatrix_')), varargin{:});
end
if (exist('edgedata', 'var'))
if (iscell(edgedata))
endnodes = edgedata(:, 1:2);
endnodes = reshape([endnodes{:}], size(edgedata, 1), 2);
weight = cell2mat(edgedata(:, 3:end));
edgetable = table(endnodes, [weight.Weight]', 'VariableNames', {'EndNodes', 'Weight'});
if (isdirected)
newdata{j} = digraph(edgetable, nodetable);
else
newdata{j} = graph(edgetable, nodetable);
end
elseif (ndims(edgedata) == 2 && isstruct(nodetable))
newdata{j} = digraph(edgedata, fieldnames(nodetable));
end
end
end
if (len == 1)
newdata = newdata{1};
end
end
%% handle bytestream and arbitrary matlab objects
if (isfield(data, N_('_ByteStream_')) && isfield(data, N_('_DataInfo_')))
newdata = cell(len, 1);
for j = 1:len
if (isfield(data(j).(N_('_DataInfo_')), 'MATLABObjectClass'))
if (needbase64)
newdata{j} = getArrayFromByteStream(base64decode(data(j).(N_('_ByteStream_'))));
else
newdata{j} = getArrayFromByteStream(data(j).(N_('_ByteStream_')));
end
end
end
if (len == 1)
newdata = newdata{1};
end
end
%% handle data link
if (opt.maxlinklevel > 0 && isfield(data, N_('_DataLink_')))
if (ischar(data.(N_('_DataLink_'))))
datalink = data.(N_('_DataLink_'));
if (regexp(datalink, '\:\$'))
ref = regexp(datalink, '^(?<proto>[a-zA-Z]+://)*(?<path>.+)(?<delim>\:)()*(?<jsonpath>(?<=:)\$\d*\.*.*)*', 'names');
else
ref = regexp(datalink, '^(?<proto>[a-zA-Z]+://)*(?<path>.+)(?<delim>\:)*(?<jsonpath>(?<=:)\$\d*\..*)*', 'names');
end
if (~isempty(ref.path))
uripath = [ref.proto ref.path];
[fpath, fname, fext] = fileparts(uripath);
opt.maxlinklevel = opt.maxlinklevel - 1;
switch (lower(fext))
case {'.json', '.jnii', '.jdt', '.jdat', '.jmsh', '.jnirs'}
newdata = loadjson(uripath, opt);
case {'.bjd', '.bnii', '.jdb', '.jbat', '.bmsh', '.bnirs', '.pmat'}
newdata = loadbj(uripath, opt, 'Base64', 0);
case {'.ubj'}
newdata = loadubjson(uripath, opt, 'Base64', 0);
case {'.msgpack'}
newdata = loadmsgpack(uripath, opt, 'Base64', 0);
case {'.h5', '.hdf5', '.snirf'} % this requires EasyH5 toolbox
newdata = loadh5(uripath, opt);
otherwise
% _DataLink_ url does not specify type, assuming JSON format
if (regexpi(datalink, '^\s*(http|https|ftp|file)://'))
newdata = loadjson(uripath, opt);
else
warning('_DataLink_ url is not supported');
end
end
if (~isempty(ref.jsonpath))
newdata = getfromjsonpath(newdata, ref.jsonpath);
end
end
end
end
%% subfunctions
function escaped = N_(str)
escaped = [prefix str];
end
end
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