<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"> <HTML ><HEAD ><TITLE >fann_print_connections</TITLE ><link href="../style.css" rel="stylesheet" type="text/css"><META NAME="GENERATOR" CONTENT="Modular DocBook HTML Stylesheet Version 1.7"><LINK REL="HOME" TITLE="Fast Artificial Neural Network Library" HREF="index.html"><LINK REL="UP" TITLE="Creation, Destruction, and Execution" HREF="c253.html#api.sec.create_destroy"><LINK REL="PREVIOUS" TITLE="fann_init_weights" HREF="r421.html"><LINK REL="NEXT" TITLE="Input/Output" HREF="x472.html"></HEAD ><BODY CLASS="refentry" BGCOLOR="#FFFFFF" TEXT="#000000" LINK="#0000FF" VLINK="#840084" ALINK="#0000FF" ><DIV CLASS="NAVHEADER" ><TABLE SUMMARY="Header navigation table" WIDTH="100%" BORDER="0" CELLPADDING="0" CELLSPACING="0" ><TR ><TH COLSPAN="3" ALIGN="center" >Fast Artificial Neural Network Library</TH ></TR ><TR ><TD WIDTH="10%" ALIGN="left" VALIGN="bottom" ><A HREF="r421.html" ACCESSKEY="P" >Prev</A ></TD ><TD WIDTH="80%" ALIGN="center" VALIGN="bottom" ></TD ><TD WIDTH="10%" ALIGN="right" VALIGN="bottom" ><A HREF="x472.html" ACCESSKEY="N" >Next</A ></TD ></TR ></TABLE ><HR ALIGN="LEFT" WIDTH="100%"></DIV ><H1 ><A NAME="api.fann_print_connections" ></A >fann_print_connections</H1 ><DIV CLASS="refnamediv" ><A NAME="AEN449" ></A ><H2 >Name</H2 >fann_print_connections -- Prints the connections of an ann.</DIV ><DIV CLASS="refsect1" ><A NAME="AEN452" ></A ><H2 >Description</H2 ><code class="methodsynopsis" > <span class="type" >void </span >fann_print_connections(<span class="methodparam" ><span class="type" >struct fann * </span ><span class="parameter" >ann</span ></span >); </code ><P > <CODE CLASS="function" >fann_print_connections</CODE > will print the connections of the ann in a compact matrix, for easy viewing of the internals of the ann. </P ><P > The output from fann_print_connections on a small (2 2 1) network trained on the xor problem: <PRE CLASS="literallayout" > Layer / Neuron 012345 L 1 / N 3 ddb... L 1 / N 4 bbb... L 2 / N 6 ...cda </PRE > This network have five real neurons and two bias neurons. This gives a total of seven neurons named from 0 to 6. The connections between these neurons can be seen in the matrix. <CODE CLASS="constant" >"."</CODE > is a place where there is no connection, while a character tells how strong the connection is on a scale from a-z. The two real neurons in the hidden layer (neuron <CODE CLASS="constant" >3</CODE > and <CODE CLASS="constant" >4</CODE > in layer <CODE CLASS="constant" >1</CODE >) has connection from the three neurons in the previous layer as is visible in the first two lines. The output neuron (<CODE CLASS="constant" >6</CODE >) has connections form the three neurons in the hidden layer <CODE CLASS="constant" >3 - 5</CODE > as is visible in the last line. </P ><P > To simplify the matrix output neurons is not visible as neurons that connections can come from, and input and bias neurons are not visible as neurons that connections can go to. </P ><P >This function appears in FANN >= 1.2.0.</P ></DIV ><DIV CLASS="NAVFOOTER" ><HR ALIGN="LEFT" WIDTH="100%"><TABLE SUMMARY="Footer navigation table" WIDTH="100%" BORDER="0" CELLPADDING="0" CELLSPACING="0" ><TR ><TD WIDTH="33%" ALIGN="left" VALIGN="top" ><A HREF="r421.html" ACCESSKEY="P" >Prev</A ></TD ><TD WIDTH="34%" ALIGN="center" VALIGN="top" ><A HREF="index.html" ACCESSKEY="H" >Home</A ></TD ><TD WIDTH="33%" ALIGN="right" VALIGN="top" ><A HREF="x472.html" ACCESSKEY="N" >Next</A ></TD ></TR ><TR ><TD WIDTH="33%" ALIGN="left" VALIGN="top" >fann_init_weights</TD ><TD WIDTH="34%" ALIGN="center" VALIGN="top" ><A HREF="c253.html#api.sec.create_destroy" ACCESSKEY="U" >Up</A ></TD ><TD WIDTH="33%" ALIGN="right" VALIGN="top" >Input/Output</TD ></TR ></TABLE ></DIV ></BODY ></HTML >
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