cns_mapdim
m = cns_mapdim(m, z, dim, mode, mode-specific-args) |
m
z
dim
z
) for which we are determining the size and common coordinates.
mode
mode-specific-args
mode
; see the table below.
Mode | Description and Additional Arguments |
'pixels' |
Sets the dimension size to an arbitrary number, and assigns common coordinates so that the cells (pixels) fill the interval [0, 1]. The only additional argument is:
size
|
'scaledpixels' |
This is similar to 'pixels' except that the dimension size is given as a scaled-down version of a base size. If the base size is odd, the resulting dimension size is guaranteed to be odd, no matter what the scale factor. Similarly, an even base size will always result in an even dimension size. All this is done so that multiple layers which represent different rescalings of an image will all have the same form -- either they will all have a central cell, or none will. The additional arguments are:
baseSize, factor
|
'copy' |
Copies settings for this dimension from another layer. Layer z will have the same number of cells, at the same common coordinate positions, as layer pz . The only additional argument is:
pz
|
'int' |
Sets up layer z as the result of a valid "convolution" of another layer pz with a filter. (It's not strictly convolution because the filter can move across layer pz in steps of 1 or greater. This is illustrated nicely here.) Ensures that the resulting layer z will always be symmetric about the center -- any losses at the edges will be the same at both edges. The additional arguments are:
pz, rfSize, rfStep, rfMargin, parity
|
'int-td' |
This is the top-down version of 'int' . Here, layer pz is treated as the result of the convolution, and we're setting up layer z so that it will be large enough to produce layer pz as a result. The additional arguments are:
pz, rfSize, rfStep
|
'win' |
TODO. The additional arguments are:
pz, rfSize, rfStep, rfMargin, parity
|