iFit/linspace

PURPOSE

SYNOPSIS

DESCRIPTION

 v = linspace(a,b,n) : creates a linearly spaced vector of objects

   @iData/linspace function to create a linearly spaced vector of iData objects
   This corresponds to a 'morphing' from a to b in n steps.

 input:  a: object or scalar (iData)
         b: object or scalar (iData)
         n: number of steps, i.e. length of vector. Default is n=10 (integer)
 output: v: vector (iData array)
 ex:     b=linspace(a,b);

 Version: Aug. 22, 2017
 See also iData, iData/max, iData/min, iData/colon, iData/logspace

CROSS-REFERENCE INFORMATION

• copyobj b = copyobj(s) : makes a copy of iData object
• end b = end(s,index,n) : end value for iData objects
• get [...] = get(s, 'PropertyName', ...) : get iData object properties
• iData d = iData(a, ...) : iData class object constructor
• intersect [ai,bi] = intersect(a, b) : computes object intersection area and values
• isempty isempty(s) : true for empty iData object
• isnumeric b = isnumeric(s) : True for numeric iData object elements
• isscalar b = isscalar(s) : True for scalar iData objects
• linspace v = linspace(a,b,n) : creates a linearly spaced vector of objects
• mean b = mean(s, dim) : mean value of iData object
• ones s = ones(s,N,M,P,...) : initialize an iData array
• set [s,...] = set(s, 'PropertyName', Propertyvalue, ...) : set iData properties
• setalias [s,...] = setalias(s, AliasName, AliasLink, {AliasLabel}) : set iData aliases
• size size(s) : get iData object size (number of elements)
• zeros s = zeros(s,N,M,P,...) : initialize an iData array

• caxis c = caxis(s, h) : Use the 2D/3D data as the colormap (CData property) in current object.
• colon b = colon(s) : vector of arrays
• colormap h=colormap(objects, colormaps, ..., options): Produce surfaces from iData 2D objects with different colormaps
• fft c = fft(a) : computes the Discrete Fourier transform of iData objects
• getframe frame = getframe(s, dim, options) : create an iData object thumbnail/frame matrix
• hist hist(a, axis1, axis2, ...) computes the accumulated histogram from event data sets
• kmeans [b,c] = kmeans(X, k) : k-means clustering of iData object
• linspace v = linspace(a,b,n) : creates a linearly spaced vector of objects
• rotate s = rotate(a, theta) : computes the rotation of iData objects around the origin