Shift data to operate on specified dimension
[x,perm,nshifts] = shiftdata(x,dim)
[x,perm,nshifts] = shiftdata(x,dim) shifts
data x to permute dimension dim to
the first column using the same permutation as the built-in filter function.
The vector perm returns the permutation vector
that is used.
If dim is missing or empty, then the first
non-singleton dimension is shifted to the first column, and the number
of shifts is returned in nshifts.
shiftdata is meant to be used in tandem with unshiftdata,
which shifts the data back to its original shape. These functions
are useful for creating functions that work along a certain dimension,
like filter, goertzel, sgolayfilt,
and sosfilt.
This example shifts x, a 3-x-3 magic square,
permuting dimension 2 to the first column. unshiftdata shifts x back
to its original shape.
1. Create a 3-x-3 magic square:
x = fi(magic(3))
x =
8 1 6
3 5 7
4 9 2
2. Shift the matrix x to work along the second
dimension:
[x,perm,nshifts] = shiftdata(x,2)
The permutation vector, perm, and the number
of shifts, nshifts, are returned along with the
shifted matrix, x:
x =
8 3 4
1 5 9
6 7 2
perm =
2 1
nshifts =
[]3. Shift the matrix back to its original shape:
y = unshiftdata(x,perm,nshifts)
y =
8 1 6
3 5 7
4 9 2
This example shows how shiftdata and unshiftdata work
when you define dim as empty.
1. Define x as a row vector:
x = 1:5
x =
1 2 3 4 5
2. Define dim as empty to shift the first
non-singleton dimension of x to the first column:
[x,perm,nshifts] = shiftdata(x,[])
x is returned as a column vector, along with perm,
the permutation vector, and nshifts, the number
of shifts:
x =
1
2
3
4
5
perm =
[]
nshifts =
1
3. Using unshiftdata, restore x to
its original shape:
y = unshiftdata(x,perm,nshifts)
y =
1 2 3 4 5