Comparison Layer
Some text to describe the comparison layer within usual ICNs.
List of comparisons
List the possible parameters and how it affects the comparison.
Non-parametric
CompositionalNetworks.co_identity Function
co_identity(x)
Identity function. Already defined in Julia as identity
, specialized for scalars in the comparison
layer.
CompositionalNetworks.co_euclidean Function
co_euclidean(x; dom_size)
Compute an euclidean norm with domain size dom_size
of a scalar.
CompositionalNetworks.co_abs_diff_var_vars Function
co_abs_diff_var_vars(x; nvars)
Return the absolute difference between x
and the number of variables nvars
.
CompositionalNetworks.co_var_minus_vars Function
co_var_minus_vars(x; nvars)
Return the difference x - nvars
if positive, 0.0
otherwise, where nvars
denotes the numbers of variables.
CompositionalNetworks.co_vars_minus_var Function
co_vars_minus_var(x; nvars)
Return the difference nvars - x
if positive, 0.0
otherwise, where nvars
denotes the numbers of variables.
Param: :val
CompositionalNetworks.co_abs_diff_var_val Function
co_abs_diff_var_val(x; val)
Return the absolute difference between x
and val
.
CompositionalNetworks.co_var_minus_val Function
co_var_minus_val(x; val)
Return the difference x - val
if positive, 0.0
otherwise.
CompositionalNetworks.co_val_minus_var Function
co_val_minus_var(x; val)
Return the difference val - x
if positive, 0.0
otherwise.
CompositionalNetworks.co_euclidean_val Function
co_euclidean_val(x; val, dom_size)
Compute an euclidean norm with domain size dom_size
, weighted by val
, of a scalar.
Layer generation
CompositionalNetworks.make_comparisons Function
make_comparisons(param::Symbol)
Generate the comparison functions for the given parameter.
CompositionalNetworks.comparison_layer Function
comparison_layer(param = false)
Generate the layer of transformations functions of the ICN. Iff param
value is set, also includes all the parametric comparison with that value. The operations are mutually exclusive, that is only one will be selected.