nt_imagescc

PURPOSE

nt_imagescc - plot image with symmetric scaling

SYNOPSIS

function nt_imagescc(C)

DESCRIPTION

nt_imagescc - plot image with symmetric scaling

CROSS-REFERENCE INFORMATION

This function calls:

This function is called by:

nt_bias_cluster [c0,c1,A,todss,pwr0,pwr1]=nt_bias_cluster(x,dsr,flags) - cluster covariance
nt_cca [A,B,R]=nt_cca(x,y,shifts,C,m,thresh,demeanflag) - canonical correlation
nt_cell2mat y=nt_cell2mat(x) - convert cell matrix of nD matrices to (n+1)D matrix
nt_cluster_jd [IDX,todss,SCORE,COVS]=nt_cluster_jd(x,dsr,smooth,flags,init,verbose) - cluster with joint diagonalization
nt_detrend (original) [y,w,r]=nt_detrend(x,order,w,basis,thresh,niter,wsize) - robustly remove trend
nt_detrend [y,w,r]=nt_detrend(x,order,w,basis,thresh,niter,wsize) - robustly remove trend
nt_interpolate_bad_channels y=interpolate_bad_channels(x,iBad,coordinates,n) - interpolate bad channels from good
nt_mcca [A,score,AA]=nt_mcca(C,N) - multi-set cca
nt_outliers [w,y]=nt_outliers(x,w,thresh,niter) - detect outliers based on weighted correlation structure
nt_regw (original) [b,z]=nt_regw(y,x,w) - weighted regression
nt_regw [b,z]=nt_regw(y,x,w) - weighted regression
nt_spect_plot2 nt_spect_plot2 - plot power spectrum
nt_subspace_prune5 [Y]=nt_subspace_prune(X,npass,thresh) - local cleaning matrices
nt_subspace_prune6 [Y]=nt_subspace_prune6(X,npass,thresh) - local cleaning matrices

SOURCE CODE

0001 function nt_imagescc(C)
0002 %nt_imagescc - plot image with symmetric scaling
0003 
0004 m=max(abs(C(:)));
0005 imagesc(C,[-m-realmin,m+realmin]);