Mercurial > hg > ltpda
view m-toolbox/classes/@ao/dsmean.m @ 6:2b57573b11c7 database-connection-manager
Add utils.mysql.execute
author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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date | Mon, 05 Dec 2011 16:20:06 +0100 |
parents | f0afece42f48 |
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% DSMEAN performs a simple downsampling by taking the mean of every N samples. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % DESCRIPTION: DSMEAN performs a simple downsampling by taking the mean of % every N samples. The downsample factor (N) is taken as % round(fs/fsout). The original vector is then truncated to a % integer number of segments of length N. It is the reshaped % to N x length(y)/N. Then the mean is taken. % % CALL: b = dsmean(a, pl) % % <a href="matlab:utils.helper.displayMethodInfo('ao', 'dsmean')">Parameters Description</a> % % VERSION: $Id: dsmean.m,v 1.23 2011/05/11 08:42:19 mauro Exp $ % % HISTORY: 20-04-08 M Hewitson % Creation % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function varargout = dsmean(varargin) % Check if this is a call for parameters if utils.helper.isinfocall(varargin{:}) varargout{1} = getInfo(varargin{3}); return end import utils.const.* utils.helper.msg(msg.PROC3, 'running %s/%s', mfilename('class'), mfilename); % Collect input variable names in_names = cell(size(varargin)); for ii = 1:nargin,in_names{ii} = inputname(ii);end % Collect all AOs [as, ao_invars] = utils.helper.collect_objects(varargin(:), 'ao', in_names); pl = utils.helper.collect_objects(varargin(:), 'plist', in_names); % Decide on a deep copy or a modify bs = copy(as, nargout); % Combine plists pl = parse(pl, getDefaultPlist); % Extract necessary parameters fsout = find(pl, 'fsout'); % Loop over input AOs for jj = 1:numel(bs) if ~isa(bs(jj).data, 'tsdata') warning('!!! Can only downsample time-series (tsdata) objects. Skipping AO %s', ao_invars{j}); else % downsample factor dsf = round(bs(jj).data.fs/fsout); if dsf < 1 error('### I can''t downsample - the sample rate is already lower than the requested.'); elseif dsf>1 % Do Y data n = floor(length(bs(jj).data.y) / dsf); y = bs(jj).data.y(1:n*dsf); % reshape and take mean bs(jj).data.setY(mean(reshape(y, dsf, length(y)/dsf))); % If we have an x we should resample it if ~isempty(bs(jj).data.x) x = bs(jj).data.x(1:n*dsf); % reshape and take mean bs(jj).data.setX(mean(reshape(x, dsf, length(x)/dsf))); else % otherwise we need to adjust t0 bs(jj).data.setT0(bs(jj).data.t0 + dsf/(2*bs(jj).data.fs)); end end % Build output AO bs(jj).data.setFs(fsout); bs(jj).name = sprintf('dsmean(%s)', ao_invars{jj}); % Add history bs(jj).addHistory(getInfo('None'), pl, ao_invars(jj), bs(jj).hist); % Clear the errors since they don't make sense anymore clearErrors(bs(jj)); end end % Set output varargout = utils.helper.setoutputs(nargout, bs); end %-------------------------------------------------------------------------- % Get Info Object %-------------------------------------------------------------------------- function ii = getInfo(varargin) if nargin == 1 && strcmpi(varargin{1}, 'None') sets = {}; pl = []; else sets = {'Default'}; pl = getDefaultPlist(); end % Build info object ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.sigproc, '$Id: dsmean.m,v 1.23 2011/05/11 08:42:19 mauro Exp $', sets, pl); end %-------------------------------------------------------------------------- % Get Default Plist %-------------------------------------------------------------------------- function plout = getDefaultPlist() persistent pl; if ~exist('pl', 'var') || isempty(pl) pl = buildplist(); end plout = pl; end function pl = buildplist() pl = plist({'fsout', 'The output sample rate.'}, {1, {10}, paramValue.OPTIONAL}); end