iFit/kmeans

PURPOSE

SYNOPSIS

DESCRIPTION

 [b,c] = kmeans(X, k) : k-means clustering of iData object

   @iData/kmeans function to partition the object X into k classes.

   b = kmeans(a,k) partitions the points in the iData object X into k clusters.
     The resulting object Signal contains numbers from 1 to 'k' which are indices
     of segments/partitions.
     When no cluster can be found, the result is empty.
   b = kmeans(a) assumes k=2 partitions
   [b,c] = kmeans(a,k) also returns the centroid of the clusters/partitions/segments.

 input:  X: object or array (iData)
         k: number of partitions wanted (integer, default is 2)
         method: '' for default, 'otsu' for Otsu method (only for 2D images).
 output: b: object or array with partition indices (iData)
         c: centroid locations of clusters
 ex:     b=kmeans(a);

 See: http://en.wikipedia.org/wiki/K-means_clustering
 See: https://en.wikipedia.org/wiki/Otsu%27s_method
 Reference: Otsu N., A threshold selection method from gray-level histogram, IEEE Trans. Syst. Man Cybern. 9:62-66;1979

 Version: Aug. 22, 2017
 See also iData, iData/uminus, iData/abs, iData/real, iData/imag, iData/uplus

CROSS-REFERENCE INFORMATION

• abs b = abs(s) : absolute value of iData object
• cell [content,fields]=cell(s) : convert iData objects into cells
• copyobj b = copyobj(s) : makes a copy of iData object
• cumsum s = cumsum(a,dim) : computes the cumulative sum of iData objects elements
• end b = end(s,index,n) : end value for iData objects
• fliplr b = fliplr(s) : Flip object in left/right direction
• hist hist(a, axis1, axis2, ...) computes the accumulated histogram from event data sets
• iData d = iData(a, ...) : iData class object constructor
• ind2sub ind2sub(s,index) : get indexed element in an iData array
• isfinite b = isfinite(s) : True for finite iData object elements
• isfloat b = isfloat(s) : True for float iData object elements
• isnan b = isnan(s) : True for NaN iData object elements
• label b = label(s, alias, label) : Change iData label for a given alias/axis
• linspace v = linspace(a,b,n) : creates a linearly spaced vector of objects
• max [m,id] = max(a,b, dim) : computes the maximum value of iData object(s)
• min [m,id] = min(a,b, dim) : computes the maximum value of iData object(s)
• ndims d = ndims(s) : get the dimensionality of iData object
• ones s = ones(s,N,M,P,...) : initialize an iData array
• reshape c = reshape(a) : reshape the object Signal
• round b = round(s) : upper integer round of iData object
• set [s,...] = set(s, 'PropertyName', Propertyvalue, ...) : set iData properties
• single d = single(s) : convert iData into single floats
• size size(s) : get iData object size (number of elements)
• sort s = sort(a,dim) : Sort iData objects axes in ascending or descending order
• std [half_width, center] = std(s, dim) : standard deviation of iData
• subsref b = subsref(a,s) : iData indexed references
• sum s = sum(a,dim) : computes the sum of iData objects elements
• unique s = unique(a,dim) : set unique iData objects axes with no repetitions
• zeros s = zeros(s,N,M,P,...) : initialize an iData array