Clean neural struct

git-svn-id: svn://mattst88.com/svn/cleanbench/trunk@51 0d43b9a7-5ab2-4d7b-af9d-f64450cef757

3 files changed, 14 insertions, 31 deletions

diff --git a/cleanbench.c b/cleanbench.c
index 3b17ee7..af58fc3 100644
--- a/cleanbench.c
+++ b/cleanbench.c
@@ -84,7 +84,7 @@ puts("\nTEST                : Iterations/sec.  : Old Index   : New Index");
 puts("                    :                  : Pentium 90* : AMD K6/233*");
 puts("--------------------:------------------:-------------:------------");
 
-for(i=HUFFMAN;i<NUMTESTS;i++)
+for(i=NEURAL;i<NUMTESTS;i++)
 {
         if(tests_to_do[i])
         {       printf("%s    :",ftestnames[i]);
diff --git a/neural.c b/neural.c
index ff418ad..e3e3c46 100644
--- a/neural.c
+++ b/neural.c
@@ -36,8 +36,15 @@
 */
 
 /*
-** DEFINES
+**  LOOP_MAX
+**
+** This constant sets the max number of loops through the neural
+** net that the system will attempt before giving up.  This
+** is not a critical constant.  You can alter it if your system
+** has sufficient horsepower.
 */
+#define LOOP_MAX  500000L
+
 #define T 1                     /* TRUE */
 #define F 0                     /* FALSE */
 #define ERR -1
@@ -58,9 +65,6 @@
 */
 const char *inpath="NNET.DAT";
 
-/*
-** GLOBALS
-*/
 double  mid_wts[MID_SIZE][IN_SIZE];     /* middle layer weights */
 double  out_wts[OUT_SIZE][MID_SIZE];    /* output layer weights */
 double  mid_out[MID_SIZE];              /* middle layer output */
@@ -84,9 +88,6 @@ int numpats;            /* number of patterns in data file */
 int numpasses;          /* number of training passes through data file */
 int learned;            /* flag--if TRUE, network has learned all patterns */
 
-/*
-** PROTOTYPES
-*/
 static clock_t DoNNetIteration(unsigned long nloops);
 static void do_mid_forward(int patt);
 static void do_out_forward();
@@ -122,6 +123,7 @@ DoNNET(void)
         clock_t         total_time = 0;
         int             iterations = 0;
         static int      is_adjusted = FALSE;
+        static int      loops = 1;
 
         /*
         ** Init random number generator.
@@ -152,9 +154,9 @@ DoNNET(void)
                 ** # of loops and increasing the loop count until we
                 ** get a number of loops that we can use.
                 */
-                for (locnnetstruct->loops = 1; locnnetstruct->loops < MAXNNETLOOPS; locnnetstruct->loops++) {
+                for (; loops < LOOP_MAX; loops++) {
                         randnum((int32_t)3);
-                        if(DoNNetIteration(locnnetstruct->loops) > MINIMUM_TICKS) {
+                        if(DoNNetIteration(loops) > MINIMUM_TICKS) {
                                 break;
                         }
                   }
@@ -162,8 +164,8 @@ DoNNET(void)
 
         do {
                 randnum((int32_t)3);    /* Gotta do this for Neural Net */
-                total_time += DoNNetIteration(locnnetstruct->loops);
-                iterations += locnnetstruct->loops;
+                total_time += DoNNetIteration(loops);
+                iterations += loops;
         } while (total_time < MINIMUM_SECONDS * CLOCKS_PER_SEC);
 
         locnnetstruct->results = (double)(iterations * CLOCKS_PER_SEC) / total_time;
diff --git a/nmglobal.h b/nmglobal.h
index 85f030b..432a2dc 100644
--- a/nmglobal.h
+++ b/nmglobal.h
@@ -66,27 +66,8 @@ typedef struct {
         double results;     /* Results */
 } HuffStruct;
 
-/********************************
-** BACK PROPAGATION NEURAL NET **
-********************************/
-
-/*
-**  MAXNNETLOOPS
-**
-** This constant sets the max number of loops through the neural
-** net that the system will attempt before giving up.  This
-** is not a critical constant.  You can alter it if your system
-** has sufficient horsepower.
-*/
-/*#define MAXNNETLOOPS  50000L*/
-#define MAXNNETLOOPS  500000L
-
-/*
-** TYPEDEFS
-*/
 typedef struct {
         double results;     /* Results */
-        unsigned long loops;            /* # of times to learn */
 } NNetStruct;
 
 /***********************