Changes between Version 14 and Version 15 of Configuration

Timestamp:

12/04/12 12:37:08 (12 years ago)

Author:

jorisborgdorff

Comment:

--

Configuration

@@ -71 +71 @@
 ||{{{dechunk}}}             ||{{{DechunkFilter}}}             ||{{{int chunks}}}                ||{{{byte[]}}}                ||Combines a byte array that was split up by the chunk filter.||
 ||{{{linearinterpolation}}} ||{{{LinearInterpolationFilterDouble}}} ||none                ||{{{double[]}}}      ||Creates a {{{double[]}}} of length-1 of the original, and linearly interpolates between the original values: {{{k'_i <- (k_i+k_{i+1})/2}}}||
+||{{{lineartimeinterpolation}}}||{{{LinearTimeInterpolationFilterDouble}}}||{{{int step}}}||{{{double[]}}}      ||For {{{step==2}}}, forwards the first message and then sends two messages for every message received, interpolating between one message and the next.||
 ||{{{multiply}}}            ||{{{MultiplyFilterDouble}}}            ||{{{double factor}}} ||{{{double[]}}}      ||Multiplies each value of the incoming message by {{{factor}}}||
 ||{{{drop}}}                ||{{{DropFilter}}}                      ||{{{int step}}}      ||any                 ||Drops messages that are not a multiple of {{{step}}}||
@@ -76 +77 @@
 ||{{{timefactor}}}          ||{{{TimeFactorFilter}}}                ||{{{double factor}}} ||any                 ||Multiplies the sent timestamp of messages||
 ||{{{blockafter}}}          ||{{{BlockAfterTimeFilter}}}            ||{{{double time}}}   ||any                 ||Drops messages with a timestamp greater than {{{time}}}||
-||{{{lineartimeinterpolation}}}||{{{LinearTimeInterpolationFilterDouble}}}||{{{int step}}}||{{{double[]}}}      ||For {{{step==2}}}, forwards the first message and then sends two messages for every message received, interpolating between one message and the next.||
 
 For convenience, the MUSCLE filters may be referred to by their name instead of their class:
@@ -85 +85 @@
 }}}
 
-By default, the conduit filters get applied at the receiving submodel. If a filter should be applied at the sending submodel, or if filters should be applied at both locations, the tie argument can take an additional argument, so that the first list of filters is applied at the sending side and the second list of filters is applied at the receiving side.
+By default, the conduit filters get applied at the receiving submodel. If a filter should be applied at the sending submodel or if filters should be applied at both locations, the {{{tie}}} function takes an additional argument, so that the first list of filters is applied at the sending side and the second list of filters is applied at the receiving side.
 The following fragment multiplies the data with a constant on the sending side, and prints it on the receiving side:
 {{{
@@ -100 +100 @@
 }}}
 
-For large sets of data it might even make sense to split the data up before compressing, so that it gets sent in separate chunks and the compressing is done in a separate thread from sending:
+For large data sets it may increase performance to split the data into multiple chunks before compressing. In the following configuration, it gets sent in separate chunks and compressing is done in a separate thread from sending:
 {{{
 cs.attach('w' => 'r') {