NM500
NM500 TEST PGM
Dependencies: NM500Lib_Socket NM500_Test_Socket SDFileSystem_Socket mbed
Diff: main.cpp
- Revision:
- 12:c8fbe49527e7
- Parent:
- 11:6a81bde51be5
- Child:
- 13:e756b6e50853
--- a/main.cpp Mon May 29 04:32:29 2017 +0000
+++ b/main.cpp Fri Jun 23 05:37:34 2017 +0000
@@ -2,41 +2,106 @@
#include "NM500.h"
int data_learn(void);
-int data_classify(void);
+void data_classify(void);
+void NSR_Test(void);
+
+int id_fail = 0;
+int nsr_fail = 0;
+
+int CMN_Maxif = 0;
+int CMN_Nsr = 0;
+int CMN_Ncount = 0;
+int CMN_RC = 0;
+int CMN = 0;
+
+int Gcr1 = 0;
+int Gcr2 = 0;
+int Minif1 = 0;
+int Minif2 = 0;
+int Maxif1 = 0;
+int Maxif2 = 0;
+int Aif1 = 0;
+int Aif2 = 0;
+int Cat1 = 0;
+int Cat2 = 0;
+
+int Nid1 = 0;
+int Nid2 = 0;
+int Dist1 = 0;
+int Dist2 = 0;
+
+int Learn1 = 0;
+int Learn2 = 0;
+
+int Memory1 = 0;
+int Memory2 = 0;
+
+int NM1 = 0;
+int NM2 = 0;
+
+char array1[NEURONSIZE];
+char array2[NEURONSIZE];
Timer t, st;
//Serial pc(SERIAL_TX, SERIAL_RX);
unsigned char vector[NEURONSIZE];
int main() {
+
//NM500 & SD Card Init
- if(begin() == 0)
- printf("\n\nNM500 Init\n");
- else
- printf("\nInit error\n");
+ if(begin() == 0){
+ printf("\nTest Board V2.0 \n");
+ printf("\n\nNM500 Init \n");
+ }
+ else{
+ printf("\nInit error\n");
+ //int forget = 1;
+ error("\nFORGET error\n");
+ }
+ //memory array init
+ for(int i=0;i<NEURONSIZE;i=i+1){
+ array1[i]=0x0a;
+ array2[i]=0x05;
+ }
+ NSR_Test();
+
//time measure start
t.start();
+ //NCOUNT Test
+ int ncount_fail = read(NM_NCOUNT);
+ if(ncount_fail != 0){
+ CMN_Ncount = 1;
+ error("NCOUNT Fail\n");
+ }
+
//minif test
write(NM_MINIF,3);
- int minif = read(NM_MINIF);
+// int minif = read(NM_MINIF);
+// if(minif != 3)
+// CMN_Minif = 1;
//maxif test
write(NM_MAXIF,10000);
int maxif = read(NM_MAXIF);
+ if(maxif != 10000)
+ CMN_Maxif = 1;
//GCR test
write(NM_GCR,5);
- int gcr = read(NM_GCR);
- //printf("gcr : %d",gcr);
+// int gcr = read(NM_GCR);
+// //printf("gcr : %d",gcr);
+// if(gcr != 5)
+// CMN_Gcr = 1;
st.start();
//Neuron learn
printf("Learn Start\n");
- int learn = data_learn();
- if(learn == 0x7fff) //change
- learn = MAXNEURONS;
+
+
+ int daisy = data_learn();
+
st.stop();
printf("Learn Complete\n");
printf("Learn Time : %d ms\n",st.read_ms());
@@ -45,7 +110,10 @@
//data save
st.start();
printf("Save Start\n");
+
int save = NeuronToSD();
+ if(save == 0xFFFF || save == 0x7FFF) //change
+ save = MAXNEURONS;
st.stop();
printf("Save Complete\n");
printf("Save Time : %d ms\n",st.read_ms());
@@ -53,12 +121,16 @@
//forget
forget();
- int forget = NCOUNT();
+
//restore
st.start();
printf("Restore Start\n");
+
int restore = SDToNeurons();
+
+ if(restore == 0xFFFF || restore == 0x7FFF) //change
+ restore = MAXNEURONS;
st.stop();
printf("Restore Complete\n");
printf("Restore Time : %d ms\n",st.read_ms());
@@ -68,146 +140,308 @@
//classify
st.start();
printf("Classify Start\n");
- int classify = data_classify();
+
+ data_classify();
st.stop();
printf("Classify Complete\n");
printf("classify Time : %d ms\n",st.read_ms());
- printf("\n****************Tset Result****************\n");
- //minif result
- if(minif == 3)
- printf("MINIF # PASS\n");
- else
- printf("MINIF # FAIL\n");
-
- //maxif result
- if(maxif == 10000)
- printf("MAXIF # PASS\n");
- else
- printf("MAXIF # FAIL\n");
+ printf("\n****************Test Result****************\n");
+ //nsr result
+ if(CMN_Nsr ==1){
+ printf("NSR Register Fail\n");
+ CMN++;
+ }
- //GCR result
- if(gcr == 5)
- printf("GCR # PASS\n");
- else
- printf("GCR # FAIL\n");
-
-
- //forget result
- if(forget == 0)
- printf("FORGET # PASS\n");
- else
- printf("FORGET # FAIL\n");
-
- //learn result
- if(learn == MAXNEURONS){
- printf("Daisy Chain # PASS\n");
- printf("Learn # PASS\n");
+ //NCOUNT Result
+ if(CMN_Ncount ==1){
+ printf("NCOUNT Register Fail\n");
+ CMN++;
}
- else if(learn == 2){
- printf("Daisy Chain # FAIL\n");
- printf("Learn # PASS\n");
+ //MAXIF Result
+ if(CMN_Maxif ==1){
+ printf("MAXIF Register Fail\n");
+ CMN++;
+ }
+
+ //MINIF Result
+ if(Minif1 ==1){
+ printf("#1 NM500 MINIF Register Fail\n");
+ NM1++;
}
- else {
- printf("Daisy Chain # unknown\n");
- printf("# %d Neuron Learn FAIL\n",learn);
+ if(Minif2 ==1){
+ printf("#2 NM500 MINIF Register Fail\n");
+ NM2++;
+ }
+
+ //learn result
+ if(Learn1 == 1){
+ printf("#1 NM500 Learn Function Fail\n");
+ NM1++;
+ }
+ if(Learn2 == 1){
+ printf("#2 NM500 Learn Function Fail\n");
+ NM2++;
}
- //classify result
- if(classify == 1){
- printf("Classify # PASS\n");
- printf("Distance # PASS\n");
+ //Daisy Chain result
+ if(daisy == 1){
+ printf("#1 NM500 Daisy Chain Fail\n");
+ NM1++;
+ }
+
+ //GCR result
+ if(Gcr1 == 1){
+ printf("#1 NM500 GCR Register Fail\n");
+ NM1++;
+ }
+ if(Gcr2 == 1){
+ printf("#2 NM500 GCR Register Fail\n");
+ NM2++;
+ }
+ //AIF result
+ if(Aif1 == 1){
+ printf("#1 NM500 AIF Register Fail\n");
+ NM1++;
+ }
+ if(Aif2 == 1){
+ printf("#2 NM500 AIF Register Fail\n");
+ NM2++;
}
- else if(classify == 2){
- printf("Classify # PASS\n");
- printf("Distance # FAIL\n");
+ //Cat result
+ if(Cat1 == 1){
+ printf("#1 NM500 CAT Register Fail\n");
+ NM1++;
+ }
+ if(Cat2 == 1){
+ printf("#2 NM500 CAT Register Fail\n");
+ NM2++;
+ }
+ if(save != MAXNEURONS){
+ printf("NM500 Learn Function Fail\n");
+ CMN++;
}
- else {
- printf("# %d Neuron Classify FAIL\n",classify);
- printf("Distance # PASS\n");
+ if(restore != MAXNEURONS){
+ printf("NM500 Restore Function Fail\n");
+ CMN++;
+ }
+ //NID result
+ if(Nid1 == 1){
+ printf("#1 NM500 Nid Register Fail\n");
+ NM1++;
+ }
+ if(Nid2 == 1){
+ printf("#2 NM500 Nid Register Fail\n");
+ NM2++;
}
- printf("POWER SAVE ON\n");
- write(NM_POWER_SAVE,0);
+ //Dist result
+ if(Dist1 == 1){
+ printf("#1 NM500 Dist Register Fail\n");
+ NM1++;
+ }
+ if(Dist2 == 1){
+ printf("#2 NM500 Dist Register Fail\n");
+ NM2++;
+ }
+ if(Memory1 == 1){
+ printf("#1 NM500 Memory Fail\n");
+ NM1++;
+ }
+ if(Memory2 == 1){
+ printf("#2 NM500 Memory Fail\n");
+ NM2++;
+ }
+
+ //final result
+ if(NM1 >1)
+ printf("#1 NM500 Fail\n");
+ if(NM2 > 1)
+ printf("#2 NM500 Fail\n");
+ if(CMN>1)
+ printf("#1, #2 Fail\n");
+ if(CMN == 0 && NM1 == 0 && NM2 == 0)
+ printf("#1, #2 NM500 PASS\n");
+
+
+
+
+// //reset chain result
+// if(CMN_RC == 1)
+// printf("Reset Chain Register Fail\n");
+
+ // printf("POWER SAVE ON\n");
+// write(NM_POWER_SAVE,0);
t.stop();
printf("Total Time : %d ms\n",t.read_ms());
-
-
-
-
+
+}
+void NSR_Test(void)
+{
+ //KNN Mode setting
+ setKNN();
+ //read KNN Register
+ int nsr = read(NM_NSR) & 0x20;
+ if(nsr != 32)
+ CMN_Nsr = 1; //fail
+
+ //RBF Mode setting
+ setRBF();
+ nsr = read(NM_NSR) & 0x20;
+ if(nsr != 0)
+ CMN_Nsr = 1; //fail
+
+ int temp_nsr = read(NM_NSR);
+
+ //SR Mode test
+ write(NM_NSR, 0x10);
+ nsr = read(NM_NSR) & 0x10;
+ if(nsr != 16)
+ CMN_Nsr = 1;
+
+ //Nomal Mode Test
+ write(NM_NSR, temp_nsr);
+ nsr = read(NM_NSR) & 0x10;
+ if(nsr != 0)
+ CMN_Nsr = 1;
}
int data_learn(void)
{
- int ncnt=0,old_ncnt=0; //ncount, old ncount
-
- //number of neuron 576*2
- for(int i=1;i<=MAXNEURONS;i++){
- // ex
- // 1. 0 1 0 1....
- // 2. 0 2 0 2....
- // 3. 0 3 0 3....
- // .....
- // 255. 0 255 0 255....
- // 256. 1 0 1 0....
- // 257. 1 1 1 1....
- for(int j =0;j<NEURONSIZE;j=j+2){
+ int ncnt=0,old_ncnt=0; //ncount, old ncount
+
+ //number of neuron 576*2
+ for(int i=1;i<=MAXNEURONS;i++){
+ // ex
+ // 1. 0 1 0 1....
+ // 2. 0 2 0 2....
+ // 3. 0 3 0 3....
+ // .....
+ // 255. 0 255 0 255....
+ // 256. 1 0 1 0....
+ // 257. 1 1 1 1....
+ if(i%2 == 1){
+ for(int j =0;j<DATA_CNT;j=j+2){
+ vector[j] = i>>8; //upper bit save
+ vector[j+1] = i; //low bit save
+ }
+ for(int j =DATA_CNT;j<NEURONSIZE; j++){
+ vector[j] = array1[j]; //upper bit save
+ }
+ }
+ else if(i%2==0){
+ for(int j =0;j<DATA_CNT;j=j+2){
vector[j] = i>>8; //upper bit save
vector[j+1] = i; //low bit save
}
- //data learn
- ncnt = learn(vector, NEURONSIZE, i); //input : data, neuronsize, cat, return : ncount
- if(ncnt == 0x7fff) //change
- ncnt = MAXNEURONS;
- //printf("ncount # %d\n",ncnt);
-
- if(ncnt == old_ncnt) //ncount가 변화가 없으면
- printf("\nNeuron Learn Fail # %d\n",ncnt);
- else //ncount가 증가하였을 경우
- old_ncnt = ncnt; //old ncount 갱신
+ for(int j =DATA_CNT;j<NEURONSIZE; j++){
+ vector[j] = array2[j]; //upper bit save
+ }
+ }
+
+ //data learn
+ ncnt = learn(vector, NEURONSIZE, i); //input : data, neuronsize, cat, return : ncount
+ if(ncnt == 0xffff || ncnt == 0x7FFF) //change
+ ncnt = MAXNEURONS;
+ //printf("ncount # %d\n",ncnt);
+
+ if(ncnt == old_ncnt){ //ncount가 변화가 없으면
+ if(ncnt <=576){
+ Learn1 = 1;
+ error("\n Learn Fail NM500 #1\n");
+ }
+ else{
+ Learn2 = 1;
+ error("\n Learn Fail NM500 #2\n");
+ }
+ }
+ //ncount가 증가하였을 경우
+ else
+ old_ncnt = ncnt; //old ncount 갱신
- printf(".");
- }
- printf("\n");
- printf("NCOUNT : %d\n",ncnt);
- //학습 완료 후 ncount가 MAXNEURONS보다 작을 경우
- if(ncnt == MAXNEURONS/2)
- return 2; //데이지체인 불량
- return ncnt; //정상 출력
+ printf(".");
+ }
+ printf("\n");
+ printf("NCOUNT : %d\n",ncnt);
+ //학습 완료 후 ncount가 MAXNEURONS보다 작을 경우
+ if(ncnt == MAXNEURONS/2)
+ return 1; //데이지체인 불량
+ else if( ncnt != MAXNEURONS)
+ error("NCOUNT Fail\n");
+ return 0; //정상 출력
}
-int data_classify(void)
+void data_classify(void)
{
int distance, cat, nid;
//number of neuron 1156
for(int i=1;i<=MAXNEURONS;i++){
//test 벡터 생성
- for(int j =0;j<NEURONSIZE;j=j+2){ //size of neuron 256
- vector[j] = i>>8; //upper bit save
- vector[j+1] = i; //low bit save
+ //for(int j =0;j<NEURONSIZE;j=j+2){ //size of neuron 256
+// vector[j] = i>>8; //upper bit save
+// vector[j+1] = i; //low bit save
+// }
+ if(i%2 == 1){
+ for(int j =0;j<DATA_CNT;j=j+2){
+ vector[j] = i>>8; //upper bit save
+ vector[j+1] = i; //low bit save
+ }
+ for(int j =DATA_CNT;j<NEURONSIZE; j++){
+ vector[j] = array1[j]; //upper bit save
+ }
+ }
+ else if(i%2==0){
+ for(int j =0;j<DATA_CNT;j=j+2){
+ vector[j] = i>>8; //upper bit save
+ vector[j+1] = i; //low bit save
+ }
+ for(int j =DATA_CNT;j<NEURONSIZE; j++){
+ vector[j] = array2[j]; //upper bit save
+ }
}
//input : data, data length output : distance, category, Neuron ID return 인식된 데이터 갯수
int nsr = classify(vector, NEURONSIZE, &distance, &cat, &nid);
+ id_fail = nsr & 0x70;
+ if(id_fail == 0)
+ nsr_fail = 1;
+
printf(".");
- printf(" neuron# %d \t", nid);
- printf(" distance = %d,\t ", distance);
- printf(" cat = %d\n", cat);
+// printf(" neuron# %d \t", nid);
+// printf(" distance = %d,\t ", distance);
+// printf(" cat = %d\n", cat);
- if(nid!=cat){
- printf("Classify Fail # %d \n",nid);
- return cat; //분류 실패
+ //nid test
+ //cat register pass AND (nid,cat diff)
+ if((nid!=cat) && (Cat1==0 && Cat2==0)){
+ if(nid < 576){
+ Nid1 = 1;
+ printf("\nNID Register Fail # %d\n",nid);
+ }
+ else{
+ Nid2 = 1;
+ printf("\nNID Register Fail # %d\n",nid);
+ }
}
if(distance != 0){
- printf("Distance Fail \n");
- return 2; //distance error
+ if(nid < 576){
+ Dist1 = 1;
+ printf("\nDistance Register Fail # %d, Distance # %d\n",nid,distance);
+ }
+ else{
+ Dist2 = 1;
+ printf("\nDistance Register Fail # %d, Distance # %d\n",nid,distance);
+ }
}
}
printf("\n");
- return 1; //정상 분류
+
}
+
+
+