v1.0 CALIBRATION: visible LEDs


goes with protocol of same name
// Set our initial variables and conditions
var data = json.data_raw;
var output = {};   // location to save output variables
var lights = [1,2,3,4,7];   // define the lights to be calibrated
var intensityArray = [30,40,50,60,70,80,90,100,110,120,130,140,150,250,500];  // the pulsed_lights_brightness which are set in the measurement protocol associated with "lights" array defined above1
var intensities = intensityArray.length; // number of intensities per light
var pulses = 10;   // number of pulses in a intensity
var total_reads = intensities*pulses*lights.length+100;   // total number of reads from the sensor

// build the response from the LiCOR Par sensors 
// MultispeQ LiCOR #1: main body, lights 1 - 4, adc_read, calibration to PAR is on userdef[7] (slope) and userdef[8] (yint)
// MultispeQ LiCOR #2: clamp,     light 7,      adc_read2 , calibration to PAR is on userdef[9] (slope) and userdef[10] (yint) 
// First, we need to combine both MultispeQ LiCOR readings into a single array

var slope1 = json.recall["userdef[0]"];
var yint1 = json.recall["userdef[1]"];
var slope2 = json.recall["userdef[2]"];
var yint2 = json.recall["userdef[3]"];
var slope3 = json.recall["userdef[4]"];
var yint3 = json.recall["userdef[5]"];
var slope4 = json.recall["userdef[6]"];
var yint4 = json.recall["userdef[7]"];
var slope5 = json.recall["userdef[8]"];
var yint5 = json.recall["userdef[9]"];

output["raw adc_read1"] = json.adc_read;
output["raw adc_read2"] = json.adc_read2;


// get the values for each MultispeQ LiCOR and convert them to actual PAR
var main_adc = json.adc_read.slice(100,total_reads-intensities*pulses);
var clamp_adc = json.adc_read2.slice(total_reads-intensities*pulses,total_reads);

var adc_read_combined = main_adc;

for (var i = 0; i < clamp_adc.length; i++) {
  adc_read_combined.push(clamp_adc[i]);
}

for (var i = 0; i < clamp_adc.length; i++) {
  adc_read_combined.push(clamp_adc[i]);
}

// show the final combined adc values
//output["adc_read combined"] = adc_read_combined;

var adc_read_par = [];

// Convert the raw cabled LiCOR values to PAR values based on each calibration values (saved in userdef 0 - 9)

for (var i = 0; i < lights.length;i++) {
  for (var j = 0; j < intensities; j++) {
    for (var k = 0; k < pulses; k++) {
      if (i == 0) {
        adc_read_par.push((adc_read_combined[i*intensities*pulses + j*pulses + k] - yint1)/slope1);
      }
      else if (i == 1) {
        adc_read_par.push((adc_read_combined[i*intensities*pulses + j*pulses + k] - yint2)/slope2);
      }
      else if (i == 2) {
        adc_read_par.push((adc_read_combined[i*intensities*pulses + j*pulses + k] - yint3)/slope3);
      }
      else if (i == 3) {
        adc_read_par.push((adc_read_combined[i*intensities*pulses + j*pulses + k] - yint4)/slope4);
      }
      else if (i == 4) {
        adc_read_par.push((adc_read_combined[i*intensities*pulses + j*pulses + k] - yint5)/slope5);
      }
    }
  }
}

output["adc_read_par"] = adc_read_par;
//output["tester"] = (adc_read_combined[2*lights.length + 13*intensities + 5] - yint3)/slope3;

// first, get all the individual arrays for each LED to calibrate from.  Put them in a nested array so they can be fed into the MathPOLYREG subroutine (polynomial regression)
var responseArray = [];
for (var i = 0; i < lights.length; i++) {
  var tempvar = [];
  for (var j = 0; j < intensities; j++) {
	var thisResponse = adc_read_par.slice(i*intensities*pulses+j*pulses+2,i*intensities*pulses+j*pulses+pulses-2);
    var moretempvar = [MathMEDIAN([thisResponse]),intensityArray[j]];
//	output[lights[i]+","+intensityArray[j]] = moretempvar[0]+","+moretempvar[1];
    tempvar.push(moretempvar);
  }
  responseArray.push(tempvar);
}

output["response_array"] = responseArray;

// compare a value prior to removing the zero light measurements... 
var comparator = 0;
output["response_array length"] = responseArray[comparator].length;

// now we need to remove any of the settings which outputted zero.  We'll assume that dac setting of zero produces zero light output
// from there, if the light intensity decreases or increases by less than 10% (account for noise), we assume it's zero and remove it.

// it's kind of ugly, so just FYI the responseArray looks like this -->
// responseArray = [ [ [x,y],[x,y]... ] , [ [x,y],[x,y]... ] , [ [x,y],[x,y]... ] , [ [x,y],[x,y]... ] , [ [x,y],[x,y]... ] ]  

for (var i = 0; i < lights.length; i++) {
  for (var j = 1; j < intensities; j++) {		// skip array position 0 since there's nothing to compare back to
	zero_value = responseArray[i][0][0]; 
    if (responseArray[i][j][0] > 1.3*zero_value) {
      for (var l = 0; l < j; l++) {
        responseArray[i].shift();
      }
      // check in what array number we broke from zero light
//      output["i"] = i;
//      output["j"] = j;
      break;
    }
  }
}

// compare a value after removing the zero light measurements... this should be lower, assuming some of the zero light values were removed
output["response_array length after"] = responseArray[comparator].length;
output["slope1"] = slope1;
output["yint1"] = yint1;
output["slope2"] = slope2;
output["yint2"] = yint2;
output["slope3"] = slope3;
output["yint3"] = yint3;
output["slope4"] = slope4;
output["yint4"] = yint4;
output["slope5"] = slope5;
output["yint5"] = yint5;

// now we need to fit the response from each LED to a polynomial fit, and output the results to the device
output["toDevice"] = "set_led_par+";
for (var i = 0; i < lights.length; i++) {
  var model = MathPOLYREG(responseArray[i],2);
  output["toDevice"] += lights[i]+"+"+MathROUND(model.slopes[2],7)+"+"+MathROUND(model.slopes[1],7)+"+"+MathROUND(model.slopes[0],7)+"+";
//  output["light"+lights[i]+"_yerror"] = MathROUND(model.error,4);

  output["light"+lights[i]+"_a"] = MathROUND(model.slopes[2],7);
  output["light"+lights[i]+"_b"] = MathROUND(model.slopes[1],7);
  output["light"+lights[i]+"_yint"] = MathROUND(model.slopes[0],7);
}

output["toDevice"] += "-1+";

return output;
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  "device_id": "d4:f5:00:00:00:05",
  "device_battery": 86,
  "device_firmware": "1.10",
  "firmware_version": "1.10",
  "device_time": 1476358687,
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          "userdef[8]": 1.85915,
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    ]
  ],
  "app_os": "linux",
  "app_name": "PhotosynQ",
  "app_version": "0.3.5",
  "app_device": "x86-64",
  "location": [
    "42.7369792",
    "-84.4838654"
  ],
  "ConsoleMacro": "253"
}
012409 pbi 160 low low res headshot
Created by

Greg Austic


Protocol connections:
2
Latest Update:
Oct 2016