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annotate m-toolbox/classes/@ao/diff.m @ 47:dd93c9ba6624 database-connection-manager

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Fix Java dialog
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Tue, 06 Dec 2011 19:07:27 +0100
parents f0afece42f48
children
Ignore whitespace changes - Everywhere: Within whitespace: At end of lines:
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Daniele Nicolodi <nicolodi@science.unitn.it>
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1 % DIFF differentiates the data in AO.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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2 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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Daniele Nicolodi <nicolodi@science.unitn.it>
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3 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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4 % DESCRIPTION: DIFF differentiates the data in AO. The result is a data
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Daniele Nicolodi <nicolodi@science.unitn.it>
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5 % series the same length as the input series.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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6 % In case of method 'diff' computes the difference between two samples, in which
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Daniele Nicolodi <nicolodi@science.unitn.it>
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7 % case the resulting time object has the length of the input
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Daniele Nicolodi <nicolodi@science.unitn.it>
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8 % series -1 sample.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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9 % CALL: bs = diff(a1,a2,a3,...,pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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10 % bs = diff(as,pl)
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11 % bs = as.diff(pl)
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12 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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13 % INPUTS: aN - input analysis objects
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Daniele Nicolodi <nicolodi@science.unitn.it>
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14 % as - input analysis objects array
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Daniele Nicolodi <nicolodi@science.unitn.it>
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15 % pl - input parameter list
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16 %
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17 % OUTPUTS: bs - array of analysis objects, one for each input,
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Daniele Nicolodi <nicolodi@science.unitn.it>
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18 % containing the differentiated data
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19 %
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20 % <a href="matlab:utils.helper.displayMethodInfo('ao', 'diff')">Parameters Description</a>
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21 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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22 % REFERENCES:
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Daniele Nicolodi <nicolodi@science.unitn.it>
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23 % [1] L. Ferraioli, M. Hueller and S. Vitale, Discrete derivative
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Daniele Nicolodi <nicolodi@science.unitn.it>
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24 % estimation in LISA Pathfinder data reduction,
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Daniele Nicolodi <nicolodi@science.unitn.it>
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25 % <a
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Daniele Nicolodi <nicolodi@science.unitn.it>
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26 % href="matlab:web('http://www.iop.org/EJ/abstract/0264-9381/26/9/094013/','-browser')">Class. Quantum Grav. 26 (2009) 094013.</a>
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27 % [2] L. Ferraioli, M. Hueller and S. Vitale, Discrete derivative
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28 % estimation in LISA Pathfinder data reduction
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29 % <a href="matlab:web('http://arxiv.org/abs/0903.0324v1','-browser')">http://arxiv.org/abs/0903.0324v1</a>
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30 %
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31 % VERSION: $Id: diff.m,v 1.36 2011/08/03 19:18:56 adrien Exp $
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32 %
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33 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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34
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Daniele Nicolodi <nicolodi@science.unitn.it>
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35 % PARAMETERS: method - the method to use: [default: '3POINT']
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Daniele Nicolodi <nicolodi@science.unitn.it>
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36 % 'diff' - like MATLABs diff
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Daniele Nicolodi <nicolodi@science.unitn.it>
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37 % compute difference between each two samples
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Daniele Nicolodi <nicolodi@science.unitn.it>
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38 % xaxis will be integers from 1 to length
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Daniele Nicolodi <nicolodi@science.unitn.it>
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39 % of resulting object
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Daniele Nicolodi <nicolodi@science.unitn.it>
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40 % '2POINT' - 2 point derivative computed as
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Daniele Nicolodi <nicolodi@science.unitn.it>
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41 % [y(i+1)-y(i)]./[x(i+1)-x(i)].
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Daniele Nicolodi <nicolodi@science.unitn.it>
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42 % '3POINT' - 3 point derivative. Compute derivative
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Daniele Nicolodi <nicolodi@science.unitn.it>
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43 % at i as [y(i+1)-y(i-1)] / [x(i+1)-x(i-1)].
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Daniele Nicolodi <nicolodi@science.unitn.it>
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44 % For i==1, the output is computed as
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Daniele Nicolodi <nicolodi@science.unitn.it>
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45 % [y(2)-y(1)]/[x(2)-x(1)]. The last sample
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46 % is computed as [y(N)-y(N-1)]/[x(N)-x(N-1)].
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Daniele Nicolodi <nicolodi@science.unitn.it>
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47 % '5POINT' - 5 point derivative. Compute derivative dx
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48 % at i as
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Daniele Nicolodi <nicolodi@science.unitn.it>
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49 % [-y(i+2)+8*y(i+1)-8*y(i-1)+y(i-2)] /
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Daniele Nicolodi <nicolodi@science.unitn.it>
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50 % [3*(x(i+2)-x(i-2))].
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Daniele Nicolodi <nicolodi@science.unitn.it>
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51 % For i==1, the output is computed as
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Daniele Nicolodi <nicolodi@science.unitn.it>
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52 % [y(2)-y(1)]/[x(2)-x(1)]. The last sample
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Daniele Nicolodi <nicolodi@science.unitn.it>
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53 % is computed as [y(N)-y(N-1)]/[x(N)-x(N-1)].
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Daniele Nicolodi <nicolodi@science.unitn.it>
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54 % 'ORDER2' - Compute derivative using a 2nd order
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Daniele Nicolodi <nicolodi@science.unitn.it>
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55 % method.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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56 % 'ORDER2SMOOTH' - Compute derivative using a 2nd order
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Daniele Nicolodi <nicolodi@science.unitn.it>
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57 % method with a parabolic fit to 5
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Daniele Nicolodi <nicolodi@science.unitn.it>
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58 % consecutive samples.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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59 % 'filter' - applies an IIR filter built from a
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Daniele Nicolodi <nicolodi@science.unitn.it>
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60 % single pole at the chosen frequency. The
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Daniele Nicolodi <nicolodi@science.unitn.it>
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61 % filter is applied forwards and backwards
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Daniele Nicolodi <nicolodi@science.unitn.it>
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62 % (filtfilt) to achieve the desired f^2
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Daniele Nicolodi <nicolodi@science.unitn.it>
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63 % response. This only works for time-series
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Daniele Nicolodi <nicolodi@science.unitn.it>
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64 % AOs. For this method, you can specify the
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Daniele Nicolodi <nicolodi@science.unitn.it>
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65 % pole frequency with an additional parameter
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Daniele Nicolodi <nicolodi@science.unitn.it>
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66 % 'f0' [default: 1/Nsecs]
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Daniele Nicolodi <nicolodi@science.unitn.it>
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67 % 'FPS' - Calculates five points derivative using
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Daniele Nicolodi <nicolodi@science.unitn.it>
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68 % utils.math.fpsder function. If you call
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Daniele Nicolodi <nicolodi@science.unitn.it>
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69 % with this oprtion you may add also the
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Daniele Nicolodi <nicolodi@science.unitn.it>
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70 % parameters:
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Daniele Nicolodi <nicolodi@science.unitn.it>
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71 % 'ORDER' derivative order, supperted
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Daniele Nicolodi <nicolodi@science.unitn.it>
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72 % values are:
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73 % 'ZERO', 'FIRST', 'SECOND'
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74 % 'COEFF' coefficient used for the
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Daniele Nicolodi <nicolodi@science.unitn.it>
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75 % derivation. Refers to the fpsder help
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Daniele Nicolodi <nicolodi@science.unitn.it>
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76 % for further details.
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77 %
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78 %
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79
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80 function varargout = diff(varargin)
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81
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82 % Check if this is a call for parameters
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83 if utils.helper.isinfocall(varargin{:})
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84 varargout{1} = getInfo(varargin{3});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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85 return
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Daniele Nicolodi <nicolodi@science.unitn.it>
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86 end
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87
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88 import utils.const.*
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89 utils.helper.msg(msg.PROC3, 'running %s/%s', mfilename('class'), mfilename);
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90
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91 % Collect input variable names
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92 in_names = cell(size(varargin));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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93 for ii = 1:nargin,in_names{ii} = inputname(ii);end
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94
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Daniele Nicolodi <nicolodi@science.unitn.it>
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95 % Collect all AOs and plists
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Daniele Nicolodi <nicolodi@science.unitn.it>
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96 [as, ao_invars] = utils.helper.collect_objects(varargin(:), 'ao', in_names);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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97 pl = utils.helper.collect_objects(varargin(:), 'plist', in_names);
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98
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99 % Decide on a deep copy or a modify
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100 bs = copy(as, nargout);
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101
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Daniele Nicolodi <nicolodi@science.unitn.it>
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102 % combine plists
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103 pl = parse(pl, getDefaultPlist());
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104
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Daniele Nicolodi <nicolodi@science.unitn.it>
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105 % Extract method
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106 method = find(pl, 'method');
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107
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108 for jj = 1:numel(bs)
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109
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Daniele Nicolodi <nicolodi@science.unitn.it>
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110 % Diff can't work for cdata objects since we need x data
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111 if isa(bs(jj).data, 'cdata')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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112 error('### diff doesn''t work with cdata AOs since we need an x-data vector.');
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113 end
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114
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115 % Compute derivative with selected method
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Daniele Nicolodi <nicolodi@science.unitn.it>
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116 switch lower(method)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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117 case 'diff'
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118 yunit = bs(jj).yunits;
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119 y = bs(jj).y;
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120 x = bs(jj).x;
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121 newX = x(1:end-1); % cut the last sample from the time series to make x and y same length
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122 dy = diff(y);
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123 bs(jj).data.setY(dy);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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124 bs(jj).data.setX(newX);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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125 bs(jj).setYunits(yunit);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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126 case '2point'
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127 x = bs(jj).data.getX;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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128 dx = diff(x);
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129 y = bs(jj).data.getY;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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130 dy = diff(y);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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131 z = dy./dx;
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132 bs(jj).data.setY(z);
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133 bs(jj).data.setX((x(1:end-1)+x(2:end))/2);
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134 bs(jj).data.setYunits(bs(jj).data.yunits./bs(jj).data.xunits);
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135 case '3point'
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Daniele Nicolodi <nicolodi@science.unitn.it>
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136 x = bs(jj).data.getX;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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137 dx = diff(x);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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138 y = bs(jj).data.getY;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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139 z = zeros(size(y));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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140 z(2:end-1) = (y(3:end)-y(1:end-2)) ./ (dx(2:end)+dx(1:end-1));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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141 z(1) = (y(2)-y(1)) ./ (dx(1));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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142 z(end) = 2*z(end-1)-z(end-2);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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143 bs(jj).data.setY(z);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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144 bs(jj).data.setYunits(bs(jj).data.yunits./bs(jj).data.xunits);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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145 case '5point'
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Daniele Nicolodi <nicolodi@science.unitn.it>
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146 x = bs(jj).data.getX;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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147 dx = diff(x);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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148 y = bs(jj).data.getY;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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149 z = zeros(size(y));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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150 z(1) = (y(2)-y(1)) ./ (dx(1));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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151 z(2) = (y(3)-y(1))./(dx(2)+dx(1));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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152 z(3:end-2) = (-y(5:end) + 8.*y(4:end-1) - 8.*y(2:end-3) + y(1:end-4)) ./ (3.*(x(5:end)-x(1:end-4)));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
153 z(end-1) = 2*z(end-2)-z(end-3);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
154 z(end) = 2*z(end-1)-z(end-2);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
155 bs(jj).data.setY(z);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
156 bs(jj).data.setYunits(bs(jj).data.yunits./bs(jj).data.xunits);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
157 case 'order2'
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
158 x = bs(jj).data.getX;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
159 dx = diff(x);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
160 y = bs(jj).data.getY;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
161 z = zeros(size(y));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
162 m = length(y);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
163 % y'(x1)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
164 z(1) = (1/dx(1)+1/dx(2))*(y(2)-y(1))+...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
165 dx(1)/(dx(1)*dx(2)+dx(2)^2)*(y(1)-y(3));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
166 % y'(xm)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
167 z(m) = (1/dx(m-2)+1/dx(m-1))*(y(m)-y(m-1))+...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
168 dx(m-1)/(dx(m-1)*dx(m-2)+dx(m-2)^2)*(y(m-2)-y(m));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
169 % y'(xi) (i>1 & i<m)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
170 dx1 = repmat(dx(1:m-2),1,1);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
171 dx2 = repmat(dx(2:m-1),1,1);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
172 y1 = y(1:m-2); y2 = y(2:m-1); y3 = y(3:m);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
173 z(2:m-1) = 1./(dx1.*dx2.*(dx1+dx2)).*...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
174 (-dx2.^2.*y1+(dx2.^2-dx1.^2).*y2+dx1.^2.*y3);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
175 bs(jj).data.setY(z);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
176 bs(jj).data.setYunits(bs(jj).data.yunits./bs(jj).data.xunits);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
177 case 'order2smooth'
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
178 x = bs(jj).data.getX;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
179 y = bs(jj).data.getY;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
180 dx = diff(x);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
181 m = length(y);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
182 if max(abs(diff(dx)))>sqrt(eps(max(abs(dx))))
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
183 error('### The x-step must be constant for method ''ORDER2SMOOTH''')
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
184 elseif m<5
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
185 error('### Length of y must be at least 5 for method ''ORDER2SMOOTH''.')
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
186 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
187 h = mean(dx);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
188 z = zeros(size(y));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
189 % y'(x1)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
190 z(1) = sum(y(1:5).*[-54; 13; 40; 27; -26])/70/h;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
191 % y'(x2)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
192 z(2) = sum(y(1:5).*[-34; 3; 20; 17; -6])/70/h;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
193 % y'(x{m-1})
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
194 z(m-1) = sum(y(end-4:end).*[6; -17; -20; -3; 34])/70/h;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
195 % y'(xm)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
196 z(m) = sum(y(end-4:end).*[26; -27; -40; -13; 54])/70/h;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
197 % y'(xi) (i>2 & i<(N-1))
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
198 Dc = [2 1 0 -1 -2];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
199 tmp = convn(Dc,y)/10/h;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
200 z(3:m-2) = tmp(5:m);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
201 bs(jj).data.setY(z);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
202 bs(jj).data.setYunits(bs(jj).data.yunits./bs(jj).data.xunits);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
203 case 'filter'
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
204 error('### Comming with release 2.5');
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
205 case 'fps'
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
206 order = find(pl, 'ORDER');
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
207 coeff = find(pl, 'COEFF');
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
208 x = bs(jj).data.getX;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
209 dx = x(2)-x(1);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
210 fs = 1/dx;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
211 y = bs(jj).data.getY;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
212 params = struct('ORDER', order, 'COEFF', coeff, 'FS', fs);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
213 z = utils.math.fpsder(y, params);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
214 bs(jj).data.setY(z);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
215 % setting units
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
216 switch lower(order)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
217 case 'first'
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
218 bs(jj).data.setYunits(bs(jj).data.yunits./bs(jj).data.xunits);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
219 case 'second'
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
220 bs(jj).data.setYunits(bs(jj).data.yunits.*bs(jj).data.xunits.^(-2));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
221 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
222 otherwise
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
223 error('### Unknown method for computing the derivative.');
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
224 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
225
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
226 % name for this object
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
227 bs(jj).name = sprintf('diff(%s)', ao_invars{jj});
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
228 % add history
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
229 bs(jj).addHistory(getInfo('None'), pl, ao_invars(jj), bs(jj).hist);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
230 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
231
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
232 % Clear the errors since they don't make sense anymore
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
233 clearErrors(bs);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
234
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
235 % Set output
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
236 if nargout == numel(bs)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
237 % List of outputs
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
238 for ii = 1:numel(bs)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
239 varargout{ii} = bs(ii);
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 else
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
242 % Single output
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
243 varargout{1} = bs;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
244 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
245 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
246
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
247 %--------------------------------------------------------------------------
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
248 % Get Info Object
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
249 %--------------------------------------------------------------------------
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
250 function ii = getInfo(varargin)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
251
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
252 if nargin == 1 && strcmpi(varargin{1}, 'None')
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
253 sets = {};
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
254 pl = [];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
255 else
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
256 sets = {'Default'};
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
257 pl = getDefaultPlist;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
258 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
259 % Build info object
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
260 ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.sigproc, '$Id: diff.m,v 1.36 2011/08/03 19:18:56 adrien Exp $', sets, pl);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
261 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
262
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
263 %--------------------------------------------------------------------------
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
264 % Get Default Plist
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
265 %--------------------------------------------------------------------------
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
266
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
267 function plout = getDefaultPlist()
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
268 persistent pl;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
269 if exist('pl', 'var')==0 || isempty(pl)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
270 pl = buildplist();
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
271 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
272 plout = pl;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
273 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
274
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
275 function pl = buildplist()
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
276 pl = plist();
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
277
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
278 % Method
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
279 p = param({'method',['The method to use. Choose between:<ul>', ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
280 '' ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
281 '<li>''2POINT'' - 2 point derivative computed as [y(i+1)-y(i)]./[x(i+1)-x(i)]', ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
282 '</li>' ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
283 '<li>''3POINT'' - 3 point derivative. Compute derivative dx at i as <br>', ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
284 '<tt>[y(i+1)-y(i-1)] / [x(i+1)-x(i-1)]</tt><br>', ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
285 'For <tt>i==1</tt>, the output is computed as <tt>[y(2)-y(1)]/[x(2)-x(1)]</tt>.<br>', ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
286 'The last sample is computed as <tt>[y(N)-y(N-1)]/[x(N)-x(N-1)]</tt>', ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
287 '</li>' ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
288 '<li>''5POINT'' - 5 point derivative. Compute derivative dx at i as <br>', ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
289 '<tt>[-y(i+2)+8*y(i+1)-8*y(i-1)+y(i-2)] / [3*(x(i+2)-x(i-2))]</tt><br>', ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
290 'For <tt>i==1</tt>, the output is computed as <tt>[y(2)-y(1)]/[x(2)-x(1)]</tt><br>', ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
291 'The last sample is computed as <tt>[y(N)-y(N-1)]/[x(N)-x(N-1)]</tt>', ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
292 '</li>' ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
293 '<li>''ORDER2'' - Compute derivative using a 2nd order method', ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
294 '</li>' ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
295 '<li>''ORDER2SMOOTH'' - Compute derivative using a 2nd order method<br>', ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
296 'with a parabolic fit to 5 consecutive samples', ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
297 '</li>' ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
298 '<li>''filter'' - applies an IIR filter built from a single pole at the chosen frequency.<br>', ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
299 'The filter is applied forwards and backwards (filtfilt) to achieve the desired f^2<br>', ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
300 'response. This only works for time-series AOs.<br>', ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
301 'For this method, you can specify the pole frequency with an additional parameter ''F0'' (see below):', ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
302 '</li>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
303 '<li>''FPS'' - Calculates five points derivative using utils.math.fpsder.<br>', ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
304 'When calling with this option you may add also the parameters ''ORDER'' (see below)<br>', ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
305 'and ''COEFF'' (see below)' ...
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306 '</li>' ...
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307 ]}, {1, {'2POINT', '3POINT', '5POINT', 'ORDER2', 'ORDER2SMOOTH', 'FILTER', 'FPS'}, paramValue.SINGLE});
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308 pl.append(p);
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309
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Daniele Nicolodi <nicolodi@science.unitn.it>
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310 % F0
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311 p = param({'f0','The pole frequency for the ''filter'' method.'}, {1, {'1/Nsecs'}, paramValue.OPTIONAL});
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312 pl.append(p);
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313
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314 % Order
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315 p = param({'ORDER','Derivative order'}, {1, {'ZERO', 'FIRST', 'SECOND'}, paramValue.SINGLE});
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316 pl.append(p);
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317
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318 % Coeff
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Daniele Nicolodi <nicolodi@science.unitn.it>
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319 p = param({'COEFF',['Coefficient used for the derivation. <br>', ...
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320 'Refer to the <a href="matlab:doc(''utils.math.fpsder'')">fpsder help</a> for further details']}, paramValue.EMPTY_DOUBLE);
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321 pl.append(p);
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322
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323 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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324