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Scilab manual >> Sparses Matrix > sparse

# sparse

sparse matrix definition

### Calling Sequence

sp=sparse(X)
sp=sparse(ij,v [,mn])

### Arguments

X

real or complex full (or sparse) matrix

ij

two columns integer matrix (indices of non-zeros entries)

v

vector

mn

integer vector with two entries (row-dimension, column-dimension)

sp

sparse matrix

### Description

sparse is used to build a sparse matrix. Only non-zero entries are stored.

sp = sparse(X) converts a full matrix to sparse form by squeezing out any zero elements. (If X is already sparse sp is X).

sp=sparse(ij,v [,mn]) builds an mn(1)-by-mn(2) sparse matrix with sp(ij(k,1),ij(k,2))=v(k). ij and v must have the same column dimension. If optional mn parameter is not given the sp matrix dimensions are the max value of ij(:,1) and ij(:,2) respectively.

Operations (concatenation, addition, etc,) with sparse matrices are made using the same syntax as for full matrices.

Elementary functions are also available (abs,maxi,sum,diag,...) for sparse matrices.

Mixed operations (full-sparse) are allowed. Results are full or sparse depending on the operations.

### Examples

sp=sparse([1,2;4,5;3,10],[1,2,3])
size(sp)
x=rand(2,2);abs(x)-full(abs(sparse(x)))

### Comments

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