lazynut_scripting_language:reference:layer []

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Methods common to all layers
============================

Layers correspond to identifiable states in a cognitive model, often
consisting of sets of homogeneous units.

description
-----------

	some_layer description

The description of `some_layer` will have the additional elements: 
`Representation` names the associated representation;
`Width` indicates the width of that representation used to format the layer;
`Current time` indicates the time currently associated with the layer;
`Incoming connections` lists that attached connections with sub-elements indicating
  the attached input channel as `port`;
`Ports` list all input channels.

attach
------

	some_layer attach src_conn port

Establish `src_conn` as an incoming connection on port `port` (name) of `some_layer`.

	some_layer attach src_conn

As above, except the default port (net_input) is used.

detach
------

	some_layer detach src_conn

Detach `src_conn` as connection to `some_layer` on any port.

connections
-----------

	some_layer connections

List connections to `some_layer`.

lesion
------

	some_layer lesion

Insert a `lesion_transfer` into the layer\_transfer slot of `some_layer`
without destroying the existing transfer facet (which now becomes the
responsiblity of the lesion\_transfer facet to manage; this is used
in the unlesion method).

unlesion
--------

	some_layer unlesion

If `some_layer` has a `lesion_transfer` facet, replace this with the original
layer\_transfer facet, and destroy the `lesion_transfer` facet.

represent
---------

	some_layer represent rep

Set the representaion of `some_layer` to be `rep`.

state
-----

	some_layer state time_step

Return the state of `some_layer` at the (integer) `time_step` index in the 
array of states.  Note time\_step is the rank time, not the time (see 
`time_summary`).

	some_layer state

Return the pattern_reference that (continually) refers to the current state pattern.

output
------

	some_layer output time_step

Return the state of `some_layer` at the (integer) `time_step` index in the
array of outputs.  Note time\_step is the rank time, not the time (see
`time_summary`).

	some_layer output

Return the pattern_reference that (continually) refers to the current output pattern.

input
-----

	some_layer input time_step port

Return the input to the `port` channel (number) of `some_layer` at the
(integer) `time_step` index in the array of inputs.  Note time\_step is the
rank time, not the time (see `time_summary`).

	some_layer output time_step

As above, but the default input (0; net_input) is used.

	some_layer output

As above, but the current time is used.

input_ref
---------

	some_layer input_ref port

Return the updating pattern\_reference to the current input to `some_layer`
on port number `port`.

set_lag
-------

	some_conn set_lag nsteps

Set the amount of time between input and output of `some_conn` to be
`nsteps`.  lag is the time differential between input and
state/output, such that the output at time `t` can be generated with only
the input up to and including the time `t-lag`.

get_labels
----------

	some_conn get_labels

List the dimensions of the representation associated with `some_conn`.

rep
---

	some_conn rep

Return a representation\_reference to the representation of `some_conn`.

time
----

	some_conn time

Return a strength_pattern whose first and only element is the time at the layer.

time_summary
------------

	some_conn time_summary

Print a human-readable description of the association between integer indices in the
input/state/output arrays and the floating point times.

default_observer
----------------

	some_conn default_observer

Return a dflog\_nobserver owned by the layer with default settings to observe 
the
state of `some_conn`.

default_input_observer
----------------------

	some_conn default_input_observer port

Return a dflog\_nobserver owned by the input\_port with default settings to 
observe 
the
input channel port number `port` of `some_conn`.

	some_conn default_input_observer

As above, but port number is 0 (net\_input).
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