Mercurial > hg > ltpda
comparison m-toolbox/classes/+utils/@helper/time_data_worsener.m @ 0:f0afece42f48
Import.
| author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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| date | Wed, 23 Nov 2011 19:22:13 +0100 |
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| -1:000000000000 | 0:f0afece42f48 |
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| 1 % TIME_DATA_WORSENER introduces missing points and/or unvenly sampling time | |
| 2 % inside time series | |
| 3 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | |
| 4 % | |
| 5 % FUNCTION: time_data_worsener | |
| 6 % | |
| 7 % DESCRIPTION: TIME_DATA_WORSENER introduces missing points and/or unvenly | |
| 8 % sampling times inside time series | |
| 9 % | |
| 10 % CALL: [t, y] = time_data_worsener(t, y, miss_fraction, shift_fraction, shift_range); | |
| 11 % | |
| 12 % INPUTS: t vector of evenly sampled time values (in s) | |
| 13 % y vector of evenly sampled y values (in arb units) | |
| 14 % miss_fraction fraction of the total point to be skipped | |
| 15 % shift_fraction fraction of the total point to be shifted | |
| 16 % shift_range selection range for shifting the time points (in s) | |
| 17 % | |
| 18 % OUTPUTS: t vector of unevenly time values | |
| 19 % y vector of unevenly sampled y values | |
| 20 % | |
| 21 % EXAMPLES: [t1,y1] = time_data_worsener(t, y, 0.5, 0, [0 0]); | |
| 22 % [t1,y1] = time_data_worsener(t, y, 0, 0.1, [-0.05 0.05]); | |
| 23 % [t1,y1] = time_data_worsener(t, y, 0.1, 0.5, [0 0.01]); | |
| 24 % | |
| 25 % VERSION: $Id: time_data_worsener.m,v 1.1 2009/01/25 16:06:30 mauro Exp $ | |
| 26 % | |
| 27 % HISTORY: 25-01-2009 Hueller | |
| 28 % Creation | |
| 29 % | |
| 30 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | |
| 31 | |
| 32 function [t,y] = time_data_worsener(t, y, miss_fraction, shift_fraction, shift_range) | |
| 33 | |
| 34 % Initial checks | |
| 35 if isempty(t) || isempty(y) | |
| 36 error('Need to operate on non empty data vectors!') | |
| 37 end | |
| 38 | |
| 39 if length(y) ~= length(t) | |
| 40 error('t and y vector should have the same lenghts!'); | |
| 41 end | |
| 42 | |
| 43 if miss_fraction > 1 || miss_fraction < 0 | |
| 44 error('Missing points fraction f must fulfil 0 <= f <= 1!'); | |
| 45 end | |
| 46 | |
| 47 if shift_fraction > 1 || shift_fraction < 0 | |
| 48 error('Shifted points fraction f must fulfil 0 <= f <= 1!'); | |
| 49 end | |
| 50 | |
| 51 if length(shift_range) < 2 | |
| 52 error('Please input the shifting freqency range []'); | |
| 53 end | |
| 54 | |
| 55 %% Remove an amount of points corresponding to the fractional amount input by user | |
| 56 | |
| 57 % Calculate the orginal data vector length | |
| 58 N_points = length(t); | |
| 59 | |
| 60 % Calculate the number of data points to keep | |
| 61 N_keep = round((1 - miss_fraction) * N_points); | |
| 62 | |
| 63 % Randonmly calculate the index of the data to keep | |
| 64 keep_index = sort(randsample(N_points, N_keep)); | |
| 65 | |
| 66 % Extract the data from time and y vector | |
| 67 t = t(keep_index); | |
| 68 y = y(keep_index); | |
| 69 | |
| 70 %% Shift the remaining points by a random amount within the input range | |
| 71 N_points = length(t); | |
| 72 | |
| 73 % Calculate the number of points to shift | |
| 74 N_shift = round(shift_fraction * N_points); | |
| 75 | |
| 76 % Randonmly calculate the index of the data not to shift | |
| 77 shift_index = sort(randsample(N_points, N_shift)); | |
| 78 | |
| 79 % Randomly calculate the delay (positive or negative) and apply it | |
| 80 shifts = shift_range(1) + (shift_range(2) - shift_range(1))*rand(N_shift, 1); | |
| 81 | |
| 82 for kk = 1 : N_shift | |
| 83 t(shift_index(kk)) = t(shift_index(kk)) + shifts(kk); | |
| 84 end | |
| 85 | |
| 86 end |