mix code vision 3. Using the previous algorithm to detect peaks as Nikoleta and Shiyao. Adding overlapping windows
Dependencies: mpu9250_i2c biquadFilter peakdetection Eigen
main.cpp
- Committer:
- castlefei
- Date:
- 2019-11-25
- Revision:
- 2:d4c480d17944
- Parent:
- 1:92f42e198925
- Child:
- 4:15d6c7123b09
File content as of revision 2:d4c480d17944:
/* * read and print acc, gyro,temperature date from MPU9250 * and transform accelerate data to one dimension. * in terminal: * ls /dev/tty.* * screen /dev/tty.usbmodem14102 9600 * to see the result * * mbed Microcontroller Library * Eigen Library */ #include "mbed.h" #include "platform/mbed_thread.h" #include "stats_report.h" #include "MPU9250.h" //#include <Eigen/Dense.h> #include <iostream> #include <vector> #include <complex> #include "BiQuad.h" #include "pca.h" #include "peak.h" using namespace std; using namespace Eigen; DigitalOut led1(LED1); const int addr7bit = 0x68; // 7bit I2C address,AD0 is 0 //the parameter of biquad filter, 40Hz sampling frequence,10Hz cut-off freq, Q:0.719 BiQuad mybq(0.3403575989782886,0.6807151979565772,0.3403575989782886, -1.511491371967327e-16,0.36143039591315457); BiQuadChain bqc; #define SLEEP_TIME 20 // (msec) // main() runs in its own thread in the OS int main() { //new mpu(data,clk,address),in constructor addr7bit<<1 mpu9250 *mpu = new mpu9250(p26,p27,addr7bit); //scale of acc and gyro mpu->initMPU9250(0x00,0x00); float AccRead[3]; float GyroRead[3]; float TempRead[1]; float res_smooth; //vector<float> res_list; float number=0; static MatrixXd acc_raw(3,0); Vector3d acc_new; MatrixXd C; MatrixXd vec, val; int dim = 1; //dimension of PCA //use the class defined in pca.h and peak.h PCA pca; PEAK peak; bqc.add(&mybq); static vector<float> res_list; while (true) { //when i add to 600, there accure faugment error //printf("the %f loop", number); number = number +1; //vector<float> res_list; //Blink LED and wait 1 seconds led1 = !led1; thread_sleep_for(SLEEP_TIME); //read and convert date mpu->ReadConvertAll(AccRead,GyroRead,TempRead); AccRead[0]= AccRead[0]/1000; AccRead[1]= AccRead[1]/1000; AccRead[2]= AccRead[2]/1000; printf("acc value is (%f,%f,%f).\n\r",AccRead[0],AccRead[1],AccRead[2]); //printf("gyro value is (%f,%f,%f).\n\r",GyroRead[0],GyroRead[1],GyroRead[2]); //printf("temp value is %f.\n\r",TempRead[0]); //append new data to matrix acc_raw //adding the columns acc_new << AccRead[0],AccRead[1],AccRead[2]; acc_raw.conservativeResize(acc_raw.rows(), acc_raw.cols()+1); acc_raw.col(acc_raw.cols()-1) = acc_new; //////cout << "acc_raw:" << acc_raw << endl; //run PCA MatrixXd X1=pca.featurnormail(acc_raw); pca.ComComputeCov(X1, C); pca.ComputEig(C, vec, val); //select dim num of eigenvector from right to left. right is important //compute the result array MatrixXd res = vec.rightCols(dim).transpose()*X1; //show the result after PCA //////cout << "result" << res << endl; res_list.clear(); for(int i = 0; i < res.cols(); i++) { res_smooth = bqc.step(res(i)); res_list.push_back(res_smooth); //printf("result after filter in for loop %d: %f\n\r",i,res_smooth); //std::cout << "\t" << bqc.step( ) << std::endl; } int len = res_list.size(); printf("len of res:%d\n\r", len); peak.findPeaks(res_list,len,0.1); } }