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annotate m-toolbox/classes/@ao/consolidate.m @ 52:daf4eab1a51e database-connection-manager tip

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Fix. Default password should be [] not an empty string
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Wed, 07 Dec 2011 17:29:47 +0100
parents f0afece42f48
children
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0
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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1 % CONSOLIDATE resamples all input AOs onto the same time grid.
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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2 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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3 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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4 % CONSOLIDATE resamples all input AOs onto the same time grid and truncates all
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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5 % time-series to start at the maximum start time of the inputs and end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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6 % at the minimum stop time of the inputs.
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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7 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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8 % ALGORITHM:
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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9 % 1) Drop duplicate samples (ao/dropduplicates)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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10 % 2) Interpolate missing samples (ao/interpmissing)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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11 % 3) Fix uneven sample rate using interpolate (ao/fixfs)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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12 % 4) Resample to same fs, either max or specified (ao/resample
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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13 % or ao/interp depending on ratio of old and new sample
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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14 % rate)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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15 % 5) Truncate all vectors to minimum overlap of time-series
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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16 % (ao/split)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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17 % 6) Resample on to the same timing grid (ao/interp)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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18 % 7) Truncate all vectors to same number of samples to correct for
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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19 % any rounding errors in previous steps (ao/select)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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20 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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21 % CALL: >> bs = consolidate(as)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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22 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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23 % INPUTS: as - array of at least two time-series analysis objects
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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24 % pl - parameter list (see below)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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25 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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26 % OUTPUTS: bs - array of analysis objects, one for each input
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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27 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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28 % <a href="matlab:utils.helper.displayMethodInfo('ao', 'consolidate')">Parameters Description</a>
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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29 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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30 % VERSION: $Id: consolidate.m,v 1.32 2011/04/08 08:56:13 hewitson Exp $
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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31 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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32 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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33
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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34 % 't' - specify a new time vector to resample on to. This
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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35 % will be truncated to fit within the maximum start
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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36 % time and minimum stop time of the inputs.
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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37 % or
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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38
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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39 function varargout = consolidate(varargin)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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40
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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41 % Check if this is a call for parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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42 if utils.helper.isinfocall(varargin{:})
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Daniele Nicolodi <nicolodi@science.unitn.it>
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43 varargout{1} = getInfo(varargin{3});
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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44 return
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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45 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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46
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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47 import utils.const.*
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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48 utils.helper.msg(msg.PROC3, 'running %s/%s', mfilename('class'), mfilename);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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49
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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50 % Collect input variable names
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Daniele Nicolodi <nicolodi@science.unitn.it>
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51 in_names = cell(size(varargin));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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52 for ii = 1:nargin,in_names{ii} = inputname(ii);end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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53
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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54 % Collect all AOs and plists
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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55 [as, ao_invars] = utils.helper.collect_objects(varargin(:), 'ao', in_names);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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56 [pl, pl_invars] = utils.helper.collect_objects(varargin(:), 'plist', in_names);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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57
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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58 if numel(as) < 2
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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59 error('### Consolidate requires at least two time-series AOs to work.');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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60 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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61
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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62 if nargout == 0
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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63 error('### Consolidate cannot be used as a modifier. Please give an output variable.');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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64 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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65
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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66 % Decide on a deep copy or a modify
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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67 bs = copy(as, nargout);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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68 na = numel(bs);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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69
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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70 % Combine plists
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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71 pl = parse(pl, getDefaultPlist);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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72
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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73 % Get only tsdata AOs
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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74 inhists = [];
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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75 for j=1:na
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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76 if ~isa(bs(j).data, 'tsdata')
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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77 bs(j) = [];
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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78 warning('!!! Skipping AO %s - it''s not a time-series AO.', bs(j).name);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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79 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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80 % gather the input history objects
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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81 inhists = [inhists bs(j).hist];
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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82 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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83 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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84
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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85 % If fs is specified, use it. Otherwise, use max of all
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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86 % input AOs.
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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87 fs = find(pl, 'fs');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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88 if isempty(fs)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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89 % compute max fs
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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90 fs = 0;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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91 for j=1:na
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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92 if bs(j).data.fs > fs
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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93 fs = bs(j).data.fs;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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94 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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95 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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96 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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97 utils.helper.msg(msg.PROC2, 'resampling all time-series to an fs of %f', fs);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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98
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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99 %----------------- Drop all repeated samples
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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100 utils.helper.msg(msg.PROC1, 'drop duplicates');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
101 for j=1:na
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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102 utils.helper.msg(msg.PROC2, 'processing %s', bs(j).name);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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103 dropduplicates(bs(j),pl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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104 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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105
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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106 %----------------- Interpolate all missing samples
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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107 utils.helper.msg(msg.PROC1, 'interpolate missing samples');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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108 for j=1:na
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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109 utils.helper.msg(msg.PROC2, 'processing %s', bs(j).name);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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110 interpmissing(bs(j),pl.pset('method', find(pl, 'interp_method')));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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111 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
112
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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113
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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114 %----------------- Fix uneven sampling
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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115 utils.helper.msg(msg.PROC1, 'fixing uneven sample rates');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
116 for j=1:na
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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117 utils.helper.msg(msg.PROC2, 'processing %s', bs(j).name);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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118 fixfs(bs(j),pl.pset('method', find(pl, 'fixfs_method')));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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119 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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120 %----------------- Resample all vectors to same fs
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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121 utils.helper.msg(msg.PROC1, 'resample to same fs');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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122
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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123 for j=1:na
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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124 % Check the resampling factor
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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125 [P,Q] = utils.math.intfact(fs,bs(j).data.fs);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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126 if P > 100 || Q > 100
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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127 utils.helper.msg(msg.PROC2, 'resampling factor too high [%g/%g]. Trying interpolation', P, Q);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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128 N = length(bs(j).data.getX);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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129 t = linspace(0, (P*N/Q-1)/fs, P*N/Q);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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130 interp(bs(j), plist('vertices', t));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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131 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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132 resample(bs(j), plist('fsout', fs));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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133 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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134 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
135
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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136 %---------------- Time properties of AOs
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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137 % Find max start time
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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138 start = 0;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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139 for j=1:na
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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140 dstart = bs(j).data.t0.utc_epoch_milli/1000 + bs(j).data.getX(1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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141 if dstart > start
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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142 start = dstart;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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143 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
144 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
145
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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146 % Find min stop time
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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147 stop = 1e20;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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148 for j=1:na
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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149 dstop = floor(bs(j).data.t0.utc_epoch_milli/1000 + bs(j).data.getX(end));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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150 if dstop < stop
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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151 stop = dstop;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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152 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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153 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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154
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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155 %----------------- Truncate all vectors
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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156 utils.helper.msg(msg.PROC1, 'truncate all vectors');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
157 utils.helper.msg(msg.PROC2, 'truncating vectors on interval [%.4f,%.4f]', start, stop);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
158
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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159 % split each ao
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
160 bs = split(bs, plist('timespan', timespan(start, stop)));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
161
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
162 %----------------- Resample all vectors on to the same grid
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
163 utils.helper.msg(msg.PROC1, 'resample to same grid');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
164 % compute new time grid
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
165
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
166 % get the grid from the first AO
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
167 for j=1:na
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
168 toff = start - bs(j).t0.utc_epoch_milli/1000;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
169 N = length(bs(j).data.getX);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
170 t = linspace(toff, toff+(N-1)/fs, N);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
171 interp(bs(j), plist('vertices', t));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
172 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
173
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
174 % Now ensure that we have the same data length
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
175 ns = realmax;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
176 for jj=1:na
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
177 if len(bs(jj)) < ns
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
178 ns = len(bs(jj));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
179 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
180 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
181
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
182 bs = select(bs, 1:ns);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
183
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
184 nsecs = [];
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
185 for j=1:na
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
186 if isempty(nsecs)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
187 nsecs = bs(j).data.nsecs;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
188 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
189 if nsecs ~= bs(j).data.nsecs
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
190 error('### Something went wrong with the truncation. Vectors don''t span the same time period.');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
191 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
192 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
193
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
194 %----------------- Set history on output AOs
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
195
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
196 for j=1:na
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
197 bs(j).name = sprintf('%s(%s)', mfilename, ao_invars{j});
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
198 bs(j).addHistory(getInfo('None'), pl, ao_invars(j), inhists(j));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
199 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
200
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
201 % Set output
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
202 if nargout == numel(bs)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
203 % List of outputs
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
204 for ii = 1:numel(bs)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
205 varargout{ii} = bs(ii);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
206 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
207 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
208 % Single output
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
209 varargout{1} = bs;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
210 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
211 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
212
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
213 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
214 % Get Info Object
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
215 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
216 function ii = getInfo(varargin)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
217 if nargin == 1 && strcmpi(varargin{1}, 'None')
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
218 sets = {};
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
219 pl = [];
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
220 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
221 sets = {'Default'};
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
222 pl = getDefaultPlist;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
223 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
224 % Build info object
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
225 ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.sigproc, '$Id: consolidate.m,v 1.32 2011/04/08 08:56:13 hewitson Exp $', sets, pl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
226 ii.setModifier(false);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
227 ii.setArgsmin(2);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
228 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
229
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
230 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
231 % Get Default Plist
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
232 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
233
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
234 function plout = getDefaultPlist()
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
235 persistent pl;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
236 if exist('pl', 'var')==0 || isempty(pl)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
237 pl = buildplist();
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
238 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
239 plout = pl;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
240 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
241
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
242 function pl_default = buildplist()
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
243 pl_default = combine(...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
244 plist({'fs','The target sampling frequency for consolidate'}, paramValue.EMPTY_DOUBLE),...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
245 plist({'interp_method', 'The method for the interpolation step'}, {2, {'nearest', 'linear', 'spline', 'cubic'}, paramValue.SINGLE}), ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
246 plist({'fixfs_method', 'The method for the fixfs step'}, {1, {'Time', 'Samples'}, paramValue.SINGLE}), ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
247 ao.getInfo('dropduplicates').plists,...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
248 ao.getInfo('interpmissing').plists,...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
249 ao.getInfo('fixfs').plists);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
250 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
251