there i see data like ±0.123 or download as RAW ADC
but i understand / the data and the quality… are no relevant for this.
and i just see your original post here:
so what now? you want dig deeper into signal analysis?
Yeah @kll that’s my point…I begun with simple data and simple graphs to study and learn about this analysis and then i want to dig deeper.
1 Like
so here is my actual working version
with a little clean up…
the 2 peak analyzing functions
get_Peaks ( i just rearranged )
getTimeEntry
are your original.
code
// https://discourse.processing.org/t/use-into-setup-a-float-value-from-a-method-that-finds-it/6343/4
// by netphysicist, mod kll
// v0.0 clean variables used and names
// v0.1 repair findTHRESHOLD()
// v0.2 new CSV file and new findTHRESHOLD calc formula
// v0.3 more graph features with info from findTHRESHOLD
// rearrange functional modules
// from data analysis to global ( as can use in graph for scaling again)
float dmin, dmax, davg, thresh;
Table table;
String infilename = "data/data2.csv";
int trow = 0; // = table.getRowCount();
ArrayList<PVector> timePeakPair;
boolean dprint = true; // temporary diag print
//____________________________________________________________
void setup() {
size(500, 500);
get_Table();
find_Threshold();
get_Peaks();
println("Number of peaks = "+timePeakPair.size()); //REPORT
}
//____________________________________________________________
void draw() {
background(200, 200, 0);
draw_graph();
}
//____________________________________________________________
void get_Table() {
table=loadTable(infilename, "header");
trow = table.getRowCount();
if (dprint) println("rows: "+trow+" in file: "+infilename);
table.setColumnType("Time", Table.INT);
table.setColumnType("Intensity", Table.FLOAT);
}
//____________________________________________________________
void find_Threshold() {
float iintensity; // local temp
dmin = 1000; // INIT range globals
dmax = -1000;
davg = 0;
thresh = 0;
for (int i=0; i<trow; i++) {
iintensity = table.getFloat(i, "Intensity");
if ( iintensity > dmax ) dmax = iintensity;
if ( iintensity < dmin ) dmin = iintensity;
davg += iintensity;
}
davg = davg/trow; // sum devided by data records
thresh=(davg + dmax)/2.0; // latest calc formula
if (dprint) println("find_Threshold_davg "+nf(davg, 1, 2)+" dmax "+dmax+" dmin "+dmin+" thresh: "+nf(thresh, 1, 2));
}
//____________________________________________________________
void get_Peaks() {
timePeakPair=new ArrayList<PVector>();
boolean aboveThresh=false;
int ctr=0;
float sum_xfx=0;
float time, intensity, sum_x=0;
int rowBeginSection=-1;
for (int i=0; i<table.getRowCount(); i++) {
time = table.getInt(i, "Time");
intensity = table.getFloat(i, "Intensity");
// if (dprint) println("time: "+time+" intensity: "+intensity);
if (intensity>=thresh) { //Above or equal
aboveThresh=true;
sum_xfx+=time*intensity;
sum_x+=time; //Store the first time entry
ctr+=1;
if (rowBeginSection<0) rowBeginSection=i;
//println(ctr,sum_x,sum_xfx);
} else {
//If finish a section above threshold, calculate peak follow by reseting fields
if (aboveThresh==true) {
//Calculating...
float intPeak=sum_xfx/sum_x;
float timePeak=getTimeEntry(rowBeginSection, intPeak, ctr); //sum_x/ctr;
PVector pt = new PVector(timePeak, intPeak);
timePeakPair.add(pt);
//println("CALC: ", ctr, timePeak, intPeak);
//Reseting...
sum_xfx=0;
sum_x=0;
ctr=0;
rowBeginSection=-1;
aboveThresh=false;
}
}
}
}
//____________________________________________________________
float getTimeEntry(int rowStart, float peakValue, int ctr) {
//Trivial case
if (ctr==1)
return table.getInt(rowStart, "Time");
float ctime=-1;
for (int i=rowStart; i<rowStart+ctr+1; i++) {
int time = table.getInt(i, "Time");
float intensity = table.getFloat(i, "Intensity");
if (intensity>peakValue) {
int idx=i-1;
ctime=table.getInt(idx, "Time");
break;
}
}
return ctime;
}
//____________________________________________________________
void draw_graph() {
float iintensity; // local
float x0= 20, y0 = height-50, w = 1, zoom = 200; // init
float graphgrid = 40;
zoom = graphgrid*floor((height -100)/dmax/graphgrid); // rerange graph ( dmax - dmin );
//println("draw_graph_zoom "+zoom);
w = ( width- 2*x0 )/trow; // rerange graph by samples
stroke(100, 100, 100);
for ( int k =0; k<=int((height -100)/graphgrid); k++ ) {
line(x0-1, y0+1, x0-1, 50);
line(x0-1, y0+1-k*graphgrid, x0+w*trow, y0+1-k*graphgrid);
}
for (int i=0; i<trow; i++) {
iintensity = table.getFloat(i, "Intensity");
fill(0, 200, 0);
noStroke();
rect(x0+i*w, y0, w, -zoom*iintensity);
}
stroke(200, 0, 0);
line(x0, y0-zoom*thresh, x0+w*trow, y0-zoom*thresh); // threshold line
}
//____________________________________________________________
In your second post when your provided some code, findTHRESHOLD(); is changing your original data (stored in table). This, plus other small things in your code, affects the outcome of your code… From this, I recommend that you reduce using your variables in the global scope and instead use function parameters to get access to your data within the function.
For peak fitting, your algorithm works under certain conditions: Your peak is Gaussian and you don’t have white noise. Another approach would be to use Gaussian fitting. For this, you still need your initial code to estimate the peak position to help the algorithm find a solution.
Last, I am not keen about the way you select your threshold. It works for this data set but it needs to be adjusted or tweak it for every new data set. You should consider using a sliding window concept as it would be a better approach. You only look at the data in this window, a subset of your data, instead of calculating the threshold based on the whole data set.
Kf
@kll thank you so much for everything!!!
@kfrajer what happens if my data is ecg or eeg signals like in the picture bellow??
And what do you prefer for peak fitting instead of threshold?? Is there a code or a plattform example to find peaks??
I am not aware of libraries that do that in Processing. I can suggest to do a search and check what is available on the community or even explore the Java one. However, the code for peak detection needs to be design around the nature of your signal.
You might want to check algorithms implemented in matlab, octave or R and bring it to Java, or check any of the online libraries made by data analysis community. Finding peaks is a very common challenge and you just need to understand the strengths and limitations of each algorithm.
Some ideas for peak detection for the ECG data:
- first and second derivative test could work
- Low pass filter (Filter in the frequency domain)
- Threshold detection
For the last one, it would be the same code that you are using initially. However, instead of estimating you threshold based on signal average, you could understand the floor of your signal and process anything above the floor. This does not provide you peaks but only data above the floor. You still need to estimate the peak center using interpolation techniques, curve fitting or function centroid.
The nature of your signal is important. If you signal was noisy, then 1st/2nd derivatives will not work out of the bat. You will need first to process your signal to remove the noise (not your case but still to make my point). Another example is Gaussian fitting. It will work if your signal is Gaussian in nature. From the data above, 2/3 of the peaks shows this nature but not the narrow ones. In your case, to understand that nature of your signal, sometimes you need to understand the source of the signal. In radiation detection, the shape of the signal is determined by the acquisition method, the nature of the particle that deposit the energy and the electronic acquisition system, just to mention few of those factors. In ECG, the signal is determined by the physiology process you are trying to measured coupled to the electronic acquisition system plus gemotry considerations (electrode placement). If you understand your signal, then you can select the peak detection algorithm that will work the best. People even write papers about how to do this. They are a good read as they discuss technicalities behind their implementations.
Where you able to make your initial code work? Beside selecting the threshold, it should work for most of your peaks (or maybe all?).
Kf
2 Likes
again, to have common ground, can you give us that .csv file here
so we play on the same data.
The csv file with data is:
Elapsedtime,ECG
0,-0.275
0.008,-0.245
0.016,-0.285
0.024,-0.265
0.032,-0.235
0.04,-0.215
0.048,-0.165
0.056,-0.165
0.064,-0.145
0.072,-0.095
0.08,-0.085
0.088,-0.045
0.096,0.025
0.104,0.085
0.112,0.175
0.12,0.215
0.128,0.255
0.136,0.305
0.144,0.285
0.152,0.285
0.16,0.245
0.168,0.175
0.176,0.125
0.184,0.015
0.192,-0.075
0.2,-0.125
0.208,-0.175
0.216,-0.205
0.224,-0.195
0.232,-0.205
0.24,-0.165
0.248,-0.185
0.256,-0.185
0.264,-0.185
0.272,-0.195
0.28,-0.195
0.288,-0.185
0.296,-0.165
0.304,-0.145
0.312,-0.135
0.32,-0.145
0.328,-0.155
0.336,-0.185
0.344,-0.185
0.352,-0.165
0.36,-0.175
0.368,-0.145
0.376,-0.165
0.384,-0.165
0.392,-0.175
0.4,-0.185
0.408,-0.195
0.416,-0.195
0.424,-0.175
0.432,-0.165
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0.448,-0.175
0.456,-0.175
0.464,-0.185
0.472,-0.205
0.48,-0.195
0.488,-0.185
0.496,-0.165
0.504,-0.135
0.512,-0.115
0.52,-0.065
0.528,-0.075
0.536,-0.075
0.544,0.035
0.552,0.005
0.56,-0.065
0.568,-0.085
0.576,-0.105
0.584,-0.155
0.592,-0.175
0.6,-0.195
0.608,-0.185
0.616,-0.175
0.624,-0.145
0.632,-0.155
0.64,-0.165
0.648,-0.175
0.656,-0.175
0.664,-0.155
0.672,-0.335
0.68,-0.675
0.688,-0.345
0.696,1.275
0.704,2.465
0.712,2.895
0.72,1.805
0.728,0.195
0.736,-0.125
0.744,-0.155
0.752,-0.175
0.76,-0.215
0.768,-0.235
0.776,-0.215
0.784,-0.255
0.792,-0.255
0.8,-0.225
0.808,-0.225
0.816,-0.195
0.824,-0.195
0.832,-0.195
0.84,-0.165
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0.856,-0.165
0.864,-0.125
0.872,-0.105
0.88,-0.035
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0.896,0.025
0.904,0.085
0.912,0.105
0.92,0.175
0.928,0.235
0.936,0.275
0.944,0.355
0.952,0.395
0.96,0.395
0.968,0.405
0.976,0.295
0.984,0.215
0.992,0.145
1,0.045
1.008,0.015
1.016,-0.045
1.024,-0.075
1.032,-0.085
1.04,-0.135
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1.056,-0.115
1.064,-0.105
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1.104,-0.115
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1.16,-0.075
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1.232,-0.115
1.24,-0.125
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1.256,-0.115
1.264,-0.105
1.272,-0.115
1.28,-0.105
1.288,-0.115
1.296,-0.135
1.304,-0.145
1.312,-0.125
1.32,-0.115
1.328,-0.095
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1.352,-0.105
1.36,-0.105
1.368,-0.105
1.376,-0.055
1.384,-0.015
1.392,-0.025
1.4,0.045
1.408,0.075
1.416,0.015
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1.448,-0.135
1.456,-0.105
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1.48,-0.115
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1.504,-0.135
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1.536,-0.365
1.544,-0.615
1.552,-0.035
1.56,1.565
1.568,2.575
1.576,2.895
1.584,1.415
1.592,0.065
1.6,-0.085
1.608,-0.115
1.616,-0.185
1.624,-0.205
1.632,-0.205
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1.704,-0.185
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1.72,-0.125
1.728,-0.115
1.736,-0.085
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1.752,-0.045
1.76,0.005
1.768,0.055
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1.784,0.175
1.792,0.225
1.8,0.285
1.808,0.305
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2.264,-0.085
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2.408,-0.155
2.416,-0.505
2.424,-0.695
2.432,-0.005
2.44,1.605
2.448,2.585
2.456,2.905
2.464,1.545
2.472,0.025
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2.68,0.245
2.688,0.285
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2.704,0.345
2.712,0.325
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do you know if there is an example corresponding code for peak detection in processing ?
using above code from dec. with this data
also i made a special version
try a new way to detect peaks by
using ( 2 ) filter
you can play with that on both data,
while with the new data you not see too much ( better make the CSV shorter )
that version can count also the the small peaks between the big peaks
and you can adjust the 2 filter settings online by mousewheel++
// https://discourse.processing.org/t/use-into-setup-a-float-value-from-a-method-that-finds-it/6343/4
// by netphysicist, mod kll
// v0.0 clean variables used and names
// v0.1 repair findTHRESHOLD()
// v0.2 new CSV file and new findTHRESHOLD calc formula
// v0.3 more graph features with info from findTHRESHOLD
// rearrange functional modules --> post forum
// v0.4 data_table_ECG_3 ( on RPI ) use new datafile data3.csv
// need rename headerline to fit
// v0.5 introduce filters
String rev = "v 0.5";
float a1 = 0.03, b1 = 1.0-a1, fil1=0; // very strong filter detect ground-line ( kind of dynamic ( running ) threshold ) tuning key [1]&wheel
float a2 = 0.2, b2 = 1.0-a2, fil2=0; // signal filter evens noise tuning key [2]&wheel
float fswing = fil2 - fil1; // positive peaks only = filtered signal - ground-line
int countpeak = 0; // the new filter rountine counts how many times fswing ( white line ) goes UP above 0
// from data analysis to global ( as can use in graph for scaling again)
float dmin, dmax, davg, thresh;
String wtitle = "using filter to count peaks ";
String[] info = new String[5];
Table table;
String infilename = "data/data2.csv";
int trow = 0; // = table.getRowCount();
ArrayList<PVector> timePeakPair;
boolean dprint = true; // temporary diag print
//____________________________________________________________
void setup() {
size(500, 500);
surface.setTitle(wtitle+rev);
get_Table();
filter_init(); // v0.4
filter_signal();
println("OPERATION filter tuning: use mouse wheel and press \n key [1] red baseline filter,or \n key [2] blue signal filter");
find_Threshold();
get_Peaks();
println("_org_Threshold_Number of peaks = "+timePeakPair.size()); //REPORT
}
//____________________________________________________________
void draw() {
background(200, 200, 0);
screeninfo();
draw_graph();
}
//____________________________________________________________
void get_Table() {
table=loadTable(infilename, "header");
trow = table.getRowCount();
if (dprint) println("rows: "+trow+" in file: "+infilename);
table.setColumnType("Time", Table.INT);
table.setColumnType("Intensity", Table.FLOAT);
}
//____________________________________________________________
void filter_init() {
// first make 3 more columns in table to store the 3 filter signals
// that is only for the show as this filter are recursive and need only a,b,fil as memory.
table.addColumn("fil1");
table.setColumnType("fil1", Table.FLOAT);
table.addColumn("fil2");
table.setColumnType("fil2", Table.FLOAT);
table.addColumn("fswing");
table.setColumnType("fswing", Table.FLOAT);
}
//____________________________________________________________
void screeninfo() {
info[0] = "filter settings:";
info[1] = "fil1 = "+nf(a1,1,3)+" * sig + "+nf(b1,1,3)+" * fil1old__RED use [1]";
info[2] = "fil2 = "+nf(a2,1,3)+" * sig + "+nf(b2,1,3)+" * fil2old__BLUE use [2]";
info[3] = "fswing = fil2 - fil1 //but only if > 0__WHITE : filter_signal_countpeak "+countpeak;
info[4] = "";
int Tposx = 10, TposY =11, dTposY=12;
for (int i = 0;i < info.length; i++) text(info[i],Tposx,TposY+dTposY*i);
}
//____________________________________________________________ v0.4 filter
void filter_signal() { // filter_init() required first
float theval; // temporary signal value
// initalize a filter is critical but there is no good way for short datasets with offseted values
// but this way makes sure that less "swing in" is required and fswing start with 0
fil1 = table.getFloat(0, "Intensity");
fil2 = fil1;
for (int i=0; i<trow; i++) { // loop over all table values
theval = table.getFloat(i, "Intensity");
fil1 = a1 * theval + b1 * fil1; // the beauty of a recursive filter
fil2 = a2 * theval + b2 * fil2;
fswing = fil2 - fil1; // now a bad trick, ignore the negative
if (fswing < 0 ) fswing = 0;
// store it for the show
table.setFloat(i, "fil1", fil1);
table.setFloat(i, "fil2", fil2);
table.setFloat(i, "fswing", fswing);
}
float next, last = 0;
countpeak=0;
for (int i=0; i<trow; i++) { // loop over all table values
next = table.getFloat(i, "fswing");
if ( last == 0.0 && next > 0.0 ) countpeak++;
last = next;
}
//println("filter_signal_countpeak "+countpeak);
}
//____________________________________________________________
void find_Threshold() {
float iintensity; // local temp
dmin = 1000; // INIT range globals
dmax = -1000;
davg = 0;
thresh = 0;
for (int i=0; i<trow; i++) {
iintensity = table.getFloat(i, "Intensity");
if ( iintensity > dmax ) dmax = iintensity;
if ( iintensity < dmin ) dmin = iintensity;
davg += iintensity;
}
davg = davg/trow; // sum devided by data records
thresh=(davg + dmax)/2.0; // latest calc formula
if (dprint) println("_org_find_Threshold_davg: "+nf(davg, 1, 2)+" dmax: "+dmax+" dmin: "+dmin+" thresh: "+nf(thresh, 1, 2));
}
//____________________________________________________________
void get_Peaks() {
timePeakPair=new ArrayList<PVector>();
boolean aboveThresh=false;
int ctr=0;
float sum_xfx=0;
float time, intensity, sum_x=0;
int rowBeginSection=-1;
for (int i=0; i<table.getRowCount(); i++) {
time = table.getInt(i, "Time");
intensity = table.getFloat(i, "Intensity");
// if (dprint) println("time: "+time+" intensity: "+intensity);
if (intensity>=thresh) { //Above or equal
aboveThresh=true;
sum_xfx+=time*intensity;
sum_x+=time; //Store the first time entry
ctr+=1;
if (rowBeginSection<0) rowBeginSection=i;
//println(ctr,sum_x,sum_xfx);
} else {
//If finish a section above threshold, calculate peak follow by reseting fields
if (aboveThresh==true) {
//Calculating...
float intPeak=sum_xfx/sum_x;
float timePeak=getTimeEntry(rowBeginSection, intPeak, ctr); //sum_x/ctr;
PVector pt = new PVector(timePeak, intPeak);
timePeakPair.add(pt);
//println("CALC: ", ctr, timePeak, intPeak);
//Reseting...
sum_xfx=0;
sum_x=0;
ctr=0;
rowBeginSection=-1;
aboveThresh=false;
}
}
}
}
//____________________________________________________________
float getTimeEntry(int rowStart, float peakValue, int ctr) {
//Trivial case
if (ctr==1)
return table.getInt(rowStart, "Time");
float ctime=-1;
for (int i=rowStart; i<rowStart+ctr+1; i++) {
int time = table.getInt(i, "Time");
float intensity = table.getFloat(i, "Intensity");
if (intensity>peakValue) {
int idx=i-1;
ctime=table.getInt(idx, "Time");
break;
}
}
return ctime;
}
//____________________________________________________________
void draw_graph() {
float iintensity; // local
float x0= 20, y0 = height-50, w = 1, zoom = 200; // init
float graphgrid = 40;
zoom = graphgrid*floor((height -100)/dmax/graphgrid); // rerange graph ( dmax - dmin );
//println("draw_graph_zoom "+zoom);
w = ( width- 2*x0 )/trow; // rerange graph by samples
stroke(100, 100, 100);
for ( int k =0; k<=int((height -100)/graphgrid); k++ ) {
line(x0-1, y0+1, x0-1, 50);
line(x0-1, y0+1-k*graphgrid, x0+w*trow, y0+1-k*graphgrid);
}
for (int i=0; i<trow; i++) {
iintensity = table.getFloat(i, "Intensity");
// show the filter thing
fil1 = table.getFloat(i, "fil1");
fil2 = table.getFloat(i, "fil2");
fswing = table.getFloat(i, "fswing");
fill(0, 200, 0);
noStroke();
rect(x0+i*w, y0, w, -zoom*iintensity);
//_____________________________________________________________________ v0.4 for the filter
fill(200, 0, 0);
ellipse(x0+i*w, y0-zoom*fil1, 3, 3); // red dot for dynamic base line
fill(0, 0, 200);
ellipse(x0+i*w, y0-zoom*fil2, 3, 3); // blue dot for filtered signal
//fill(200,200,200);
//ellipse(x0+i*w,y0-zoom*fswing,3,3); // white dot for peak only
stroke(200, 200, 200);
strokeWeight(2);
if ( i > 0 ) line(x0+(i-1)*w, y0-zoom*table.getFloat(i-1, "fswing"), x0+i*w, y0-zoom*fswing); // white line for peak only
}
stroke(200, 0, 0);
line(x0, y0-zoom*thresh, x0+w*trow, y0-zoom*thresh); // threshold line
}
//_________________________________________________________________ mouseWheel
void mouseWheel(MouseEvent event) {
float e = event.getCount();
//println(e);
if ( keyPressed && key == '1' ) {
a1 += e*0.001;
a1 = constrain(a1, 0, 1.0);
//println("new a1: "+nf(a1, 1, 3));
b1 = 1.0 - a1;
}
if ( keyPressed && key == '2' ) {
a2 += e*0.001;
a2 = constrain(a2, 0, 1.0);
//println("new a2: "+nf(a2, 1, 3));
b2 = 1.0 - a2;
}
filter_signal(); // recalc
}