str2cfg.m

approximate reinforcement learning

function cfg = str2cfg(str, keywords)
% String configuration to structure
%   CFG = STR2CFG(STR, KEYWORDS)
% Parameters:
%   str         - the configuration string
%   keywords    - keywords to search in the string, will become structure fields
%       Should be a cell array of strings, or a structure. In the second case the structure
%       field names will be used as keywords.
% Returns:
%   cfg         - string configuration
% 
% Binary, numeric or string values are supported. Fields which are present
% on the string, but for which no value is assigned are treated as boolean
% "true" values.
% E.g.
%   cfg = str2cfg('alpha beta=2.5 gamma=value', {'alpha', 'beta', 'gamma', 'delta'}) produces
% cfg = alpha: 1        (boolean true)
%        beta: 2.500
%       gamma: 'value'
%       delta: 0        (boolean false)

if isstruct(keywords),      % obtain field names
    keywords = fieldnames(keywords); 
end;

slen = length(str);

cfg = struct;
for i = 1:length(keywords),
    kw = keywords{i};
    kwlen = length(kw);
    ix = strfind(str, keywords{i});
    if isempty(ix), continue; end;      % no setting found
    ix = ix(1);                         % only first occurence matters
    after = ix + kwlen;
    % if no value given, interpreted as boolean true
    if (after > slen) || (str(after) ~= '='),
        cfg.(kw) = 1;
        continue;
    end;
    % otherwise, parse after equal
    val = strtok(str(after+1:end), ' ');
    % convert to numeric if possible
    if ~isempty(str2num(val)),
        val = str2num(val);
    end;
    cfg.(kw) = val;
end;