v1.0 CALIBRATION: NEW LED PAR 2


goes with protocol of same name
// Set our initial variables and conditions
var data = json.data_raw;
var output = {};   // location to save output variables

// These should correlate to the DAC settings and intensities in the protocol associated with this macro
var dac_array = [40,50,60,70,80,90,100,110,160,250,500];
var lights_array = [1,2,3,4,7];
var intensities = dac_array.length;
var repeats = 30;
var lights = lights_array.length;

// Paste in the parValues variable v1.0 CALIBRATION: NEW LED PAR (slow lights)

// previous values 0.44,60.3,138.77,216.8,292.6,365,436.7,505.8,738.4,1444.7,0,0,9.93,50.5,97.11,146.1,196.28,246.7,427.3,1086.8,2.29,19.64,42.06,66.1,90.66,114.5,137.8,161,245.9,537,0,0,0,6.86,45.85,94.2,145.48,198.27,387.6,1065.5,0,14.61,57.36,102.78,149.6,197,244,291.4,459.3,1079.9
// 0.41,61.94,140.8,219.6,296.3,369.2,441,510.5,745.6,1457,2545,0,0,9.83,50.93,98.2,147.9,198.73,249.9,432.7,1099.9,2400,2.51,20.92,44.8,70.17,96.19,121.5,146.2,170.7,260.3,570,1030,0,0,0,6.52,45.8,94.78,146.87,200.4,392.6,1079.2,2372,0,14.18,56.27,101.06,147.07,193.74,239.9,286.4,451.4,1061.2,2232
var parValues =   [0.45,22.95,59.5,98.7,137.4,176.2,214.5,252.4,433.3,733.4,1434,0,0,0,0.4,10.11,28.74,50.26,73.2,195.47,425.3,1081.8,2.35,10,19.4,30.16,41.54,53.41,65.22,77.33,136.3,243.6,533,0,0,0,0,0,0.09,6.99,24.45,144.77,385.5,1059.2,0,0.44,14.62,35.53,57.03,79.2,101.89,125,242,455.5,1070.3];

// Go get the adc reads for each intensity, convert them to a number
var adcRead = [];
for (var i = 0; i < json.adc_read.length; i++) {
  adcRead.push(Number(json.adc_read[i]));
}

output["adc raw"] = json.adc_read;
output["par array"] = parValues;

// Now get the median ADC reads for each light and intensity
var adcValues = [];
for (var i = 0; i < intensities*lights; i++) {
  adcValues[i] = MathMEDIAN(adcRead.slice(i*repeats+10, i*repeats+repeats-10));
}

//output["adcValues"] = adcValues;

var par1 = parValues.slice(0,intensities);
var par2 = parValues.slice(intensities,intensities*2);
var par3 = parValues.slice(intensities*2,intensities*3);
var par4 = parValues.slice(intensities*3,intensities*4);
var par7 = parValues.slice(intensities*4,intensities*5);

var adc1 = adcValues.slice(0,intensities);
var adc2 = adcValues.slice(intensities,intensities*2);
var adc3 = adcValues.slice(intensities*2,intensities*3);
var adc4 = adcValues.slice(intensities*3,intensities*4);
var adc7 = adcValues.slice(intensities*4,intensities*5);

// If there are zero values in the PAR array, remove them and the corresponding ADC values.  Otherwise it impacts the regression fit!
for (var i = 0; i < intensities; i++) {
  if (par1[i] == 0) {
    par1.splice(i,1);
    adc1.splice(i,1);
    i = i-1;
  }
  if (par2[i] == 0) {
    par2.splice(i,1);
    adc2.splice(i,1);
    i = i-1;
  }
  if (par3[i] == 0) {
    par3.splice(i,1);
    adc3.splice(i,1);
    i = i-1;
  }
  if (par4[i] == 0) {
    par4.splice(i,1);
    adc4.splice(i,1);
    i = i-1;
  }
  if (par7[i] == 0) {
    par7.splice(i,1);
    adc7.splice(i,1);
    i = i-1;
  }
}

// Build the regression model for the cabled LiCORs, output the values, and save them to the device

output["toDevice"] = "set_user_defined+";

// if this is the clamp (light 7), then do this...
if (json.message[0][1][1] == 2) {
  // if it's the clamp, then don't output the main body light values (lights 1,2,3,4)

  output["par7"] = par7.toString();
  output["adc7"] = adc7.toString();
  

  // PERFORM A POLYNOMIAL FIT
  combined7 = [];
  for (i = 0; i < par7.length; i++) {
    combined7.push([adc7[i], par7[i]]);
  }
  
  var modelp7 = MathPOLYREG(combined7,2);
  output["a7"] = MathROUND(modelp7.slopes[2],7);
  output["b7"] = MathROUND(modelp7.slopes[1],3);
  output["yint7"] = MathROUND(modelp7.slopes[0],1);
  output["toDevice"] += "13"+"+"+MathROUND(modelp7.slopes[2],7)+"+"+"14"+"+"+MathROUND(modelp7.slopes[1],3)+"+"+"15"+"+"+MathROUND(modelp7.slopes[0],1)+"+";
  
/*
  // PERFORM A LINEAR FIT
  var model = MathLINREG(par7,adc7);
  output["slope_light_"+(7)] = MathROUND(model.m,5);
  output["yint_light_"+(7)] = MathROUND(model.b,5);
  output["rsquared_light_"+(7)] = MathROUND(model.r,5);
  // let the user know if the calibration quality was too low (less than .998)
  if (MathROUND(model.r,5) < .998) {
    danger("calibration curve fit for light" + 7 + "too low.  Try again", output);
  }
  output["toDevice"] += (4*2) + "+" + MathROUND(model.m,5) + "+" + (4*2+1) + "+" + MathROUND(model.b,5) + "+";
*/
}

else {
  // if it's the main body, then don't output the clamp light values (light 7)

  ///*
  output["par1"] = par1.toString();
  output["adc1"] = adc1.toString();

  output["par2"] = par2.toString();
  output["adc2"] = adc2.toString();

  output["par3"] = par3.toString();
  output["adc3"] = adc3.toString();

  output["par4"] = par4.toString();
  output["adc4"] = adc4.toString();
  //*/
  
  // PERFORM A POLYNOMIAL FIT
  combined1 = [];
  for (i = 0; i < par1.length; i++) {
    combined1.push([adc1[i], par1[i]]);
  }
    combined2 = [];
  for (i = 0; i < par2.length; i++) {
    combined2.push([adc2[i], par2[i]]);
  }
    combined3 = [];
  for (i = 0; i < par3.length; i++) {
    combined3.push([adc3[i], par3[i]]);
  }
    combined4 = [];
  for (i = 0; i < par4.length; i++) {
    combined4.push([adc4[i], par4[i]]);
  }

  var modelp1 = MathPOLYREG(combined1,2);
  output["a1"] = MathROUND(modelp1.slopes[2],7);
  output["b1"] = MathROUND(modelp1.slopes[1],3);
  output["yint1"] = MathROUND(modelp1.slopes[0],1);
  output["toDevice"] += "1"+"+"+MathROUND(modelp1.slopes[2],7)+"+"+"2"+"+"+MathROUND(modelp1.slopes[1],3)+"+"+"3"+"+"+MathROUND(modelp1.slopes[0],1)+"+";
  
  var modelp2 = MathPOLYREG(combined2,2);
  output["a2"] = MathROUND(modelp2.slopes[2],7);
  output["b2"] = MathROUND(modelp2.slopes[1],3);
  output["yint2"] = MathROUND(modelp2.slopes[0],1);
  output["toDevice"] += "4" +"+"+MathROUND(modelp2.slopes[2],7)+"+"+"5"+"+"+MathROUND(modelp2.slopes[1],3)+"+"+"6"+"+"+MathROUND(modelp2.slopes[0],1)+"+";

  var modelp3 = MathPOLYREG(combined3,2);
  output["a3"] = MathROUND(modelp3.slopes[2],7);
  output["b3"] = MathROUND(modelp3.slopes[1],3);
  output["yint3"] = MathROUND(modelp3.slopes[0],1);
  output["toDevice"] += "7" +"+"+MathROUND(modelp3.slopes[2],7)+"+"+"8"+"+"+MathROUND(modelp3.slopes[1],3)+"+"+"9"+"+"+MathROUND(modelp3.slopes[0],1)+"+";

  var modelp4 = MathPOLYREG(combined4,2);
  output["a4"] = MathROUND(modelp4.slopes[2],7);
  output["b4"] = MathROUND(modelp4.slopes[1],3);
  output["yint4"] = MathROUND(modelp4.slopes[0],1);
  output["toDevice"] += "10" +"+"+MathROUND(modelp4.slopes[2],7)+"+"+"11"+"+"+MathROUND(modelp4.slopes[1],3)+"+"+"12"+"+"+MathROUND(modelp4.slopes[0],1)+"+";

/*
  // PERFORM A LINEAR FIT
  var model1 = MathLINREG(par1,adc1);
  output["slope_light_1"] = MathROUND(model1.m,5);
  output["yint_light_1"] = MathROUND(model1.b,5);
  output["rsquared_light_1"] = MathROUND(model1.r,5);
  // let the user know if the calibration quality was too low (less than .998)
  if (MathROUND(model1.r,5) < .998) {
    danger("calibration curve fit for light" + 1 + "too low.  Try again", output);
  }
  output["toDevice"] += (1*2) + "+" + MathROUND(model1.m,5) + "+" + (1*2+1) + "+" + MathROUND(model1.b,5) + "+";

  var model2 = MathLINREG(par2,adc2);
  output["slope_light_2"] = MathROUND(model2.m,5);
  output["yint_light_2"] = MathROUND(model2.b,5);
  output["rsquared_light_2"] = MathROUND(model2.r,5);
  // let the user know if the calibration quality was too low (less than .998)
  if (MathROUND(model2.r,5) < .998) {
    danger("calibration curve fit for light" + 2 + "too low.  Try again", output);
  }
  output["toDevice"] += (2*2) + "+" + MathROUND(model2.m,5) + "+" + (2*2+1) + "+" + MathROUND(model2.b,5) + "+";

  
  var model3 = MathLINREG(par3,adc3);
  output["slope_light_3"] = MathROUND(model3.m,5);
  output["yint_light_3"] = MathROUND(model3.b,5);
  output["rsquared_light_3"] = MathROUND(model3.r,5);
  // let the user know if the calibration quality was too low (less than .998)
  if (MathROUND(model3.r,5) < .998) {
    danger("calibration curve fit for light" + 3 + "too low.  Try again", output);
  }
  output["toDevice"] += (3*2) + "+" + MathROUND(model3.m,5) + "+" + (3*2+1) + "+" + MathROUND(model3.b,5) + "+";

  
  var model4 = MathLINREG(par4,adc4);
  output["slope_light_4"] = MathROUND(model4.m,5);
  output["yint_light_4"] = MathROUND(model4.b,5);
  output["rsquared_light_4"] = MathROUND(model4.r,5);
  // let the user know if the calibration quality was too low (less than .998)
  if (MathROUND(model4.r,5) < .998) {
    danger("calibration curve fit for light" + 4 + "too low.  Try again", output);
  }
  output["toDevice"] += (4*2) + "+" + MathROUND(model4.m,5) + "+" + (4*2+1) + "+" + MathROUND(model4.b,5) + "+";
*/
}
output["toDevice"] += "-1+";
  
return output;
{
  "time_offset": 240,
  "time": 1477502928778,
  "device_version": "1",
  "device_id": "d4:f5:00:00:00:05",
  "device_battery": 87,
  "device_firmware": "1.10",
  "firmware_version": "1.10",
  "device_time": 1476366083,
  "sample": [
    [
      {
        "time": 1477502928794,
        "protocol_id": 1,
        "message": [
          [
            "alert",
            " 2 connect cabled LiCOR to MultispeQ to be calibrated",
            "ok"
          ],
          [
            "0",
            "0",
            ""
          ],
          [
            "0",
            "0",
            ""
          ],
          [
            "0",
            "0",
            ""
          ]
        ],
        "invalid_entry": [
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    ]
  ],
  "app_os": "linux",
  "app_name": "PhotosynQ",
  "app_version": "0.3.5",
  "app_device": "x86-64",
  "location": [
    "42.7225896",
    "-84.4746596"
  ],
  "ConsoleMacro": "230"
}
012409 pbi 160 low low res headshot
Created by

Greg Austic


Protocol connections:
2
Latest Update:
Oct 2016