/******************************************************************************
*Func Name : PTPV2_ANN_PrintAnn
*Description : announce报文打印接口
*Input : PTPV2_ANNOUNCE_MSG_S *pstAnnMsg: 消息头
* TCPIP_PTP_ADDRINFO_S *pstAddrInfo: 接收/发送报文的地址以及UDP信息
* ULONG ulFlag: 标记:0-发送报文;非0-接收报文
*Output :
*Return :
*Caution :
*Calls :
*Called by :
*-----------------------------------------------------------------------------
* Modification History
* DATE NAME DESCRIPTION
* 2014-05-14 dutianyi Create
*******************************************************************************/
VOID PTPV2_ANN_PrintAnn(PTPV2_ANNOUNCE_MSG_S *pstAnnMsg, TCPIP_PTP_ADDRINFO_S *pstAddrInfo, ULONG ulFlag)
{
CHAR szBuf[LEN_512] = {0}; /* 缓冲区长度512个字节，存放报文信息 */
CHAR szInOrOut[10] = {0};
INT32 i32Offset = 0;
if ((NULL == pstAnnMsg) || (NULL == pstAddrInfo))
{
return;
}
if (0 == ulFlag)
{
i32Offset = TCPIP_SNPRINTF0(szInOrOut, 10, P0("send"));
}
else
{
i32Offset = TCPIP_SNPRINTF0(szInOrOut, 10, P0("receive"));
}
/* 先打印提示信息 */
(VOID)TCPIP_SNPRINTF(szBuf + i32Offset, LEN_512 - i32Offset, P1("\r\n----------announce msg %s begin----------",szInOrOut));
TCPIP_InfoOutput(szBuf);
(VOID)TCPIP_Mem_Set(szBuf, 0, LEN_512);
/* 打印消息头 */
PTPV2_PrintHeader((PTPV2_MSGHEADER_S *)pstAnnMsg, pstAddrInfo);
i32Offset = TCPIP_SNPRINTF0(szBuf, LEN_512, P0("\r\nANNOUNCE INFO:"));
/* 打印announce消息的其他内容 */
i32Offset += TCPIP_SNPRINTF(szBuf + i32Offset, LEN_512 - i32Offset, P8("\r\n originTimestamp : Nano-%u,Low-%u,High-%u \r\n utcoffset : %d\r\n grandmasterPri1 : %u\r\n grandmasterQuality : Accuracy-%u,class-%u,offset-%u ",
pstAnnMsg->stOriginTimestamp.ulNanoseconds,
pstAnnMsg->stOriginTimestamp.ulSecondsLow,
pstAnnMsg->stOriginTimestamp.usSecondsHigh,
VOS_NTOHS(pstAnnMsg->sCurrentUtcOffset),
pstAnnMsg->ucGrandmasterPriority1,
pstAnnMsg->stGrandmasterClockQuality.ucClockAccuracy,
pstAnnMsg->stGrandmasterClockQuality.ucClockClass,
VOS_NTOHS(pstAnnMsg->stGrandmasterClockQuality.usOffsetScaledLogVariance)));
i32Offset += TCPIP_SNPRINTF(szBuf + i32Offset, LEN_512 - i32Offset, P11("\r\n grandmasterPri2 : %u\r\n grandmasterId : %02x%02x%02x%02x%02x%02x%02x%02x\r\n stepsremoved : %u\r\n timesource : %u",
pstAnnMsg->ucGrandmasterPriority2,
pstAnnMsg->stGrandmasterIdentity[0],
pstAnnMsg->stGrandmasterIdentity[1],
pstAnnMsg->stGrandmasterIdentity[2],
pstAnnMsg->stGrandmasterIdentity[3],
pstAnnMsg->stGrandmasterIdentity[4],
pstAnnMsg->stGrandmasterIdentity[5],
pstAnnMsg->stGrandmasterIdentity[6],
pstAnnMsg->stGrandmasterIdentity[7],
VOS_NTOHS(pstAnnMsg->usStepsRemoved),
pstAnnMsg->ucTimeSource));
(VOID)TCPIP_SNPRINTF(szBuf + i32Offset, LEN_512 - i32Offset, P1("\r\n----------announce msg %s end------------",szInOrOut));
TCPIP_InfoOutput(szBuf);
}
P(0), P(1), P(2), P(3),
P(0), P(1), P(2), P(3),
P(0), P(1), P(2), P(3),
P(0), P(1), P(2), P(3),
P(4), P(5), P(6), P(7),
P(4), P(5), P(6), P(7),
P(4), P(5), P(6), P(7),
P(4), P(5), P(6), P(7),
};
const uint16_t bitmap[] = {
0x0008, 0x0007, 0x0006, 0x0005, 0x0004, 0x0003, 0x0002, 0x0001,
};
const unsigned char bitmap_ref[] = {
P8(0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF),
P8(0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0x00),
P8(0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF),
P8(0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0x00, 0x00),
P8(0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0x00, 0xFF),
P8(0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0x00),
P8(0x00, 0x00, 0x00, 0x00, 0x00, 0xFF, 0xFF, 0xFF),
P8(0x00, 0x00, 0x00, 0x00, 0xFF, 0x00, 0x00, 0x00),
};
void set_pos(int x, int y) {
if (x < 0 || y < 0) {
glWindowPos2i(0, 0);
glBitmap(0, 0, 0, 0, x, y, NULL);
} else {
glWindowPos2i(x, y);
int main() {
Point center(41,29);
// The numbering of the nodes corresponds to gslib's output order
Node P5(38,28,0.5740);
Node P8(45,29,1.2110);
Node P4(41,26,2.1270);
Node P3(39,31,8.3400);
Node P6(38,31,18.6420);
Node P2(39,30,7.9380);
Node P7(39,32,2.2840);
Node P1(40,31,2.5090);
Node P9(37,20,0.5740);
Node P10(25,28,1.2110);
Node P11(39,26,2.1270);
Node P12(32,31,8.3400);
Node P13(30,34,18.6420);
Node P14(33,35,7.9380);
Node P15(42,32,2.2840);
Node P16(31,23,2.5090);
neighborhood voisin;
voisin.add_node(P1);
voisin.add_node(P2);
voisin.add_node(P3);
voisin.add_node(P4);
voisin.add_node(P5);
voisin.add_node(P6);
voisin.add_node(P7);
voisin.add_node(P8);
voisin.add_node(P9);
voisin.add_node(P10);
voisin.add_node(P11);
voisin.add_node(P12);
voisin.add_node(P13);
voisin.add_node(P14);
voisin.add_node(P15);
voisin.add_node(P16);
typedef matrix_lib_traits<TNT_lib<double> >::Vector TNTvector;
covariance covar;
//______________________________
// Simple Kriging
//______________________________
std::cout << std::endl <<std::endl;
std::cout << "____________________________________________"
<< std::endl
<< "Simple kriging"
<< std::endl << std::endl;
TNTvector SK_weights;
SK_constraints SK;
OK_constraints OK;
double sk_variance;
TNT::stopwatch chrono;
chrono.start();
for(int count = 0 ; count < 50000 ; count ++) {
int change=1;
if(drand48() <0.5) change = -1;
(voisin[0].location())[0] += change;
kriging_weights<GSTL_TNT_lib>(SK_weights,
center, voisin,
covar, OK );
}
chrono.stop();
std::cout << "time elapsed using Gauss: " << chrono.read() << std::endl;
chrono.reset();
chrono.start();
for(int count = 0 ; count < 50000 ; count ++) {
int change=1;
if(drand48() <0.5) change = -1;
voisin[0].property_value() = 0.5*count;
kriging_weights(SK_weights,
center, voisin,
covar, OK );
}
chrono.stop();
std::cout << "time elapsed using LU: " << chrono.read() << std::endl;
/*
//______________________________
// Ordinary Kriging
//______________________________
std::cout << std::endl <<std::endl;
std::cout << "____________________________________________"
<< std::endl
<< "Ordinary kriging"
<< std::endl << std::endl;
TNTvector OK_weights;
OK_constraints OK;
double ok_variance;
status = kriging_weights(OK_weights, ok_variance,
center, voisin,
covar, OK);
std::cout << "Here are the weights:" << std::endl
<< OK_weights << std::endl;
//______________________________
// Kriging with Trend
//______________________________
std::cout << std::endl <<std::endl;
std::cout << "____________________________________________"
<< std::endl
<< "Kriging with Trend"
<< std::endl << std::endl;
TNTvector KT_weights;
KT_constraints<functIter> KT(functArray.begin(),functArray.end());
double kt_variance;
status = kriging_weights(KT_weights, kt_variance,
center, voisin,
covar, KT);
std::cout << "Here are the weights:" << std::endl
<< KT_weights << std::endl;
*/
return 0;
}
int main() {
Node center_node(41,29,-99);
// The numbering of the nodes corresponds to gslib's output order
Node P5(38,28,0.5740);
Node P8(45,29,1.2110);
Node P4(41,26,2.1270);
Node P3(39,31,8.3400);
Node P6(38,31,18.6420);
Node P2(39,30,7.9380);
Node P7(39,32,2.2840);
Node P1(40,31,2.5090);
neighborhood voisin;
voisin.add_node(P1);
voisin.add_node(P2);
voisin.add_node(P3);
voisin.add_node(P4);
voisin.add_node(P5);
voisin.add_node(P6);
voisin.add_node(P7);
voisin.add_node(P8);
typedef TNT_lib<double> TNT;
typedef matrix_lib_traits<TNT>::Vector TNTvector;
typedef matrix_lib_traits<TNT>::Symmetric_matrix TNTMatrix;
covariance covar;
//_____________________________
// gaussian cdf estimator
//_____________________________
std::cout << std::endl <<std::endl;
std::cout << "____________________________________________"
<< std::endl
<< "estimating gaussian cdf with SK"
<< std::endl << std::endl;
Gaussian_cdf g_ccdf;
typedef Kriging_combiner<std::vector<double>::const_iterator,
neighborhood> KCombiner;
KCombiner sk_combiner( new SK_combiner<std::vector<double>::const_iterator,
neighborhood>( 9.0 ) );
typedef Kriging_constraints<neighborhood, Point, TNT> KConstraints;
KConstraints constraints( new SKConstraints_impl<neighborhood, Point,TNT> );
Gaussian_cdf_Kestimator<covariance,
neighborhood,KConstraints,TNT> gK_estimator( covar, constraints, sk_combiner );
gK_estimator(center_node, voisin, g_ccdf);
std::cout << "gaussian cdf : mean= " << g_ccdf.mean() << " variance= "
<< g_ccdf.variance() << std::endl;
/*
Gaussian_cdf g_ccdf2;
Gaussian_cdf_Kestimator<covariance,
neighborhood, SK_constraints> gK_estimator2( covar, SK_constraints(), sk_combiner2 );
gK_estimator2(center, voisin, g_ccdf2);
std::cout << "gaussian cdf : mean= " << g_ccdf2.mean() << " variance= "
<< g_ccdf2.variance() << std::endl;
*/
}
