similaritymeasure¶
[d] = similaritymeasure(x, y, CalcMethod, dispout)
Description¶
Measure similarity between two arrays
Inputs¶
- x
- First array, its similarity is measured against y array
- y
- Second array, its similarity is measured against x array
- CalcMethod=’euclidean’
- Similarity calculation method‘euclidean’: Euclidean distance‘manhattan’: Manhattan distance‘minkowski’: Minkowski distance (power=3)‘cosine’: Cosine distance‘pearson’: Pearson’s correlation coefficient‘spearman’: spearman’s correlation coefficient‘norm’: Absolute difference of norm‘covariance’: Covariance‘inv_covariance’: Euclidean distance of inverse covariance‘histogram’: Mean of absolute difference of histogram‘t-test’: Two-sample t-test statistic
- dispout=’no’
- Define to display outputs or not (‘yes’: display, ‘no’: not display)
Outputs¶
- d
- Arrays similarity measure
Examples¶
x=[0,2,4,6];
y=[2,3,5,7];
[d]=similaritymeasure(x,y,'euclidean','yes');
x=[1,2,3,4,5,6,7,8,9,10];
y=[1.1,1.98,3.3,4.2,4.8,5.95,7.5,7.7,8.99,10.5];
[d]=similaritymeasure(x,y,'pearson','yes');
References¶
Kianimajd, A., Ruano, M. G., Carvalho, P., Henriques, J., Rocha, T., Paredes, S., & Ruano, A. E. (2017). Comparison of different methods of measuring similarity in physiologic time series. IFAC-PapersOnLine, 50(1), 11005-11010.
- https://en.wikipedia.org/wiki/Similarity_measure
- https://en.wikipedia.org/wiki/Goodness_of_fit
- https://dataaspirant.com/2015/04/11/five-most-popular-similarity-measures-implementation-in-python/
- https://towardsdatascience.com/similarity-measures-e3dbd4e58660
- https://www.mathworks.com/matlabcentral/answers/377944-how-to-calculate-a-percentage-of-similarity-between-two-arrays
- https://en.wikipedia.org/wiki/Template_matching
- https://www.mathworks.com/help/images/ref/normxcorr2.html
- https://www.mathworks.com/help/stats/hypothesis-tests-1.html