////////////////////////////////////////////////////////////////
/*									
	PIPSQUEAK!
	Perineuronal net Intensity Program for the
	Standardization and Quantification of ECM Analysis

	Written by John H. Harkness, PhD.
	>>> Contact: harknessjh@gmail.com
	>>> Copyright (C) 2016, John H. Harkness

	Washington State University, Vancouver
	
	Supported by:
	>>> Rewire Neuroscience (rewireneuroscience.com)
	>>> WSU Alcohol and Drug Abuse Research Program (ADARP)
	>>> The Translational Addiction Research Center (TARC)
	>>> NIH DA 033404 
	>>> Washington State Initiative Measure No. 171

	Protocol based on Slaker, Harkness, and Sorg, 2016
	>>> Special thanks to Megan Slaker, PhD

	>>> PLEASE CITE: Slaker, et al., 2016 (IN SUBMISSION) <<<
*/
////////////////////////////////////////////////////////////////



	//Global variables

var scale_size = 1.194;
var scale_known = 1;
var scale_pixel = 1;
var scale_unit = "um";

var set_intensity_low_threshold = 1.165;
var set_intensity_high_threshold = 5000;
var set_low_particlesize = 70;
var set_high_particlesize = 99999;
var set_low_circularity = 0.02;
var set_high_circularity = 1.00;
var set_roi_enlargement_single = 6.00;
var set_intensity_low_threshold_old = 1.165;
var set_low_particlesize_old = 70;
var set_high_particlesize_old = 99999;

var set_count_low_threshold = 0.5;
var set_count_high_threshold = 5000;
var set_count_low_particlesize = 20;
var set_count_high_particlesize = 9999999;
var set_count_low_circularity = 0.02;
var set_count_high_circularity = 1.00;

var first_image = 0;
var second_image = 0;
var series_name = 0;
var subDir = 0;

var first_suffix = 1;
var second_suffix = 3;
var merged_suffix = 2;
var total_images = 3;

var first_stain_type = "PV";
var DL1_set_intensity_low_threshold = 1.0;
var DL1_set_intensity_high_threshold = 5000;
var DL1_set_low_particlesize = 40;
var DL1_set_high_particlesize = 1000;
var DL1_set_low_circularity = 0.02;
var DL1_set_high_circularity = 1.00;
var DL1_set_roi_enlargement = -1.00;
var SL1_set_intensity_low_threshold_old = 1.0;
var SL1_set_low_particlesize_old = 40;
var SL1_set_high_particlesize_old = 1000;
//var DL1_set_intensity_low_threshold_old = 1.0;
//var DL1_set_low_particlesize_old = 40;
//var DL1_set_high_particlesize_old = 1000;
var DL1_lower = 0;

var second_stain_type = "WFA";
var DL2_set_intensity_low_threshold = 1.165;
var DL2_set_intensity_high_threshold = 5000;
var DL2_set_low_particlesize = 70;
var DL2_set_high_particlesize = 99999;
var DL2_set_low_circularity = 0.02;
var DL2_set_high_circularity = 1.00;
var DL2_set_roi_enlargement = 1.00;
var SL2_set_intensity_low_threshold_old = 1.165;
var SL2_set_low_particlesize_old = 70;
var SL2_set_high_particlesize_old = 99999;
//var DL2_set_intensity_low_threshold_old = 1.165;
//var DL2_set_low_particlesize_old = 70;
//var DL2_set_high_particlesize_old = 5000;
var DL2_lower = 0;

var lower = 0;
var import_type = 0;
var first_open = 0;
var last_open = 0;
var name = 0;
var full_name = 0;
var dir = 0;
var first_time = 0;

var save_location = 0;
var pipsqueakCount = 1;
var countCount = 1;
var countDouble = 0;
var first_open_double = 0;
var last_open_double = 0;

///////////////////////////

macro "PIPSQUEAK" {

if (pipsqueakCount==1){
	
///call home tracking URL
//UPDATE HERE (1/3)->

	call_home_url = "http://jabstracts.org/PIPSQUEAK/call_home/v1-10/";
	File.openUrlAsString(call_home_url);
	wait(200);
	print("\\Clear");

///
//UPDATE HERE (2/3)->

	print("PIPSQUEAK! v1.10 Perineuronal net Intensity Program for the Standardization and Quantification of ECM Analysis.");
	print("\n"+"Copyright (C) 2016, John H. Harkness, PhD.");
	print("Protocol by Megan Slaker, PhD.");
	print("Lab of Barb Sorg, PhD., Washington State University, Vancouver");
	print("\n"+"\n"+"Distance in pixels: "+scale_size+"\n"+"Known distance: "+scale_known+"\n"+"Pixel aspect ratio: "+scale_pixel+"\n"+"Unit of length: "+scale_unit);
	
//UPDATE HERE (3/3)-> 

	waitForUser("PIPSQUEAK version 1.10, Sep 8, 2016 \n \n 0.947 CHANGE LOG: \n Reinstated WFA ROI expansion to prevent ROI withering during double-labeling. \n \n 1.00 CHANGE LOG: \n Nothing changed from 0.947. Future versioning strategy will use the tenths place digit \n to signify significant changes that will affect analysis results (ie 1.03 to 1.10). \n Data collected using versions of PIPSQUEAK that differ by a tenths place digit \n should not be directly compared. Data collected using versions of PIPSQUEAK \n similar by the tenths place digit can be compared or combined in \n statistical analysis (ie 1.03 and 1.04 or 1.09). \n \n 1.10 CHANGE LOG: \n Really cool changes!\n Now you can adjust the threshold of detection during your semiautomated ROI check step. It Immediately reruns ROI detection! \n Save folder organization revised for double label \n Now accepting different sized images! Background ROI construction revised to accept variable image dimensions. \n \n However, I addressed an issue with double-labeled cell detection in situations when the user adds additional ROIs. \n Therefore, results from double-label analysis using v1.10 shouldn't be compared to previous versions. \n The differences between v1.10 and prior are pretty small, but ya' know, science.");

	wait(1000);
	pipsqueakCount = pipsqueakCount+1;
	
	} else {
		wait(50);
		}

Dialog.create("Welcome.");
items = newArray("Count labeled cells.", "Single label intensity analysis.", "Double label intensity analysis.", "->Change image scale settings.");
Dialog.addRadioButtonGroup("What would you like to do?", items, 4, 1, " ");
Dialog.show;
choice = Dialog.getRadioButton;
if (choice=="Count labeled cells.") {
       run("__sub_PIPSQUEAK_count");
	
	} else {
	if (choice=="Single label intensity analysis.") {
		run("__sub_PIPSQUEAK_single");
		}
	if (choice=="Double label intensity analysis.") {
		run("__sub_PIPSQUEAK_double");
		}
	if (choice=="->Change image scale settings.") {
		Dialog.create("Settings 1 of 2");
		Dialog.addMessage("**Image scale measurements (for both single and double label analysis)**");
		Dialog.addNumber("Distance in pixels:", scale_size);
		Dialog.addNumber("Known distance:", scale_known);
		Dialog.addNumber("Pixel aspect ratio:", scale_pixel);
		Dialog.addString("Unit of length:", scale_unit);
		Dialog.addMessage(" ");
		Dialog.addMessage("---------------------------------------------------------------------");
		Dialog.addMessage("                                    **ROI identification settings.**");
		Dialog.addMessage("Adjustments will alter cell determination and MAY reduce identification specificity.");
		Dialog.addMessage("Proceed with caution: here be dragons.");

//this can be improved in the future by adding a drop down menu that calls up set stain parameters.
//!!need additional settings for double labeled analysis?!!

		Dialog.addMessage(" ");
		Dialog.addMessage("**Intensity measurements**");
		//Dialog.addMessage(" ");
		Dialog.addNumber("Lower threshold multiplier:",set_intensity_low_threshold);
		Dialog.addNumber("Upper threshold limit:", set_intensity_high_threshold);
		Dialog.addNumber("Lower limit particle size:", set_low_particlesize);
		Dialog.addNumber("Upper limit particle size:", set_high_particlesize);
		Dialog.addNumber("Lower limit circularity:", set_low_circularity);
		Dialog.addNumber("Upper limit circularity:", set_high_circularity);
		Dialog.addNumber("ROI Enlargement (pixels):", set_roi_enlargement_single);
		
		Dialog.addMessage(" ");		
		Dialog.addMessage(" ");
		Dialog.addMessage("**Cell count**");
		//Dialog.addMessage(" ");
		Dialog.addNumber("Lower threshold multiplier:", set_count_low_threshold );
		Dialog.addNumber("Upper threshold limit:", set_count_high_threshold);
		Dialog.addNumber("Lower limit particle size:", set_count_low_particlesize);
		Dialog.addNumber("Upper limit particle size:", set_count_high_particlesize);
		Dialog.addNumber("Lower limit circularity:", set_count_low_circularity);
		Dialog.addNumber("Upper limit circularity:", set_count_high_circularity);


		
		Dialog.show;

		scale_size = Dialog.getNumber();
		scale_known = Dialog.getNumber();;
		scale_pixel = Dialog.getNumber();;;
		scale_unit =  Dialog.getString();
		
		set_intensity_low_threshold = Dialog.getNumber();
		set_intensity_high_threshold = Dialog.getNumber();;
		set_low_particlesize = Dialog.getNumber();;;
		set_high_particlesize = Dialog.getNumber();;;;
		set_low_circularity = Dialog.getNumber();;;;;
		set_high_circularity = Dialog.getNumber();;;;;;
		set_roi_enlargement_single = Dialog.getNumber();;;;;;;

		set_count_low_threshold = Dialog.getNumber();;;;;;;
		set_count_high_threshold = Dialog.getNumber();;;;;;;;
		set_count_low_particlesize = Dialog.getNumber();;;;;;;;;
		set_count_high_particlesize = Dialog.getNumber();;;;;;;;;;
		set_count_low_circularity = Dialog.getNumber();;;;;;;;;;;
		set_count_high_circularity = Dialog.getNumber();;;;;;;;;;;;
		
		Dialog.create("Settings 1 of 2");		
		Dialog.addMessage("**Double-label Analysis**");
		Dialog.addMessage(" ");		
		Dialog.addMessage("Please enter the numbering suffixes of the image series you want to analyze in the space below.");
		Dialog.addMessage("eg: Exp42_SubA_example_1.tif and Exp42_SubA_example_3.tif = #1 and #3");
		Dialog.addMessage(" ");
		Dialog.addNumber("First image (if possible, smaller volume stain):", first_suffix);
		Dialog.addNumber("Second image (if possible, larger volume stain):", second_suffix);
		Dialog.addNumber("Merged image:", merged_suffix);
		//Dialog.addNumber("Total number of stains plus composite in each subject series:", total_images);
		//REMOVED FOR NOW—SEE NOTE IN "__SUB_PIPSQUEAK_OPENNEXT_DOUBLE".
		Dialog.addMessage(" ");
		Dialog.addMessage("*First stain parameters*");
		Dialog.addString("Stain type:", first_stain_type);
		Dialog.addNumber("Lower threshold multiplier:", DL1_set_intensity_low_threshold);
		Dialog.addNumber("Upper threshold limit:", DL1_set_intensity_high_threshold);
		Dialog.addNumber("Lower limit particle size:", DL1_set_low_particlesize);
		Dialog.addNumber("Upper limit particle size:", DL1_set_high_particlesize);
		Dialog.addNumber("Lower limit circularity:", DL1_set_low_circularity);
		Dialog.addNumber("Upper limit circularity:", DL1_set_high_circularity);
		Dialog.addNumber("ROI Enlargement (pixels):", DL1_set_roi_enlargement);

		Dialog.addMessage(" ");
		Dialog.addMessage("*Second stain parameters*");
		Dialog.addString("Stain type:", second_stain_type);
		Dialog.addNumber("Lower threshold multiplier:", DL2_set_intensity_low_threshold);
		Dialog.addNumber("Upper threshold limit:", DL2_set_intensity_high_threshold);
		Dialog.addNumber("Lower limit particle size:", DL2_set_low_particlesize);
		Dialog.addNumber("Upper limit particle size:", DL2_set_high_particlesize);
		Dialog.addNumber("Lower limit circularity:",  DL2_set_low_circularity);
		Dialog.addNumber("Upper limit circularity:", DL2_set_high_circularity);
		Dialog.addNumber("ROI Enlargement (pixels):", DL2_set_roi_enlargement);

		Dialog.show;
		
		first_suffix = Dialog.getNumber();
		second_suffix = Dialog.getNumber();;
		merged_suffix = Dialog.getNumber();;;
		//total_images = Dialog.getNumber();;;;
		first_stain_type =  Dialog.getString();
		DL1_set_intensity_low_threshold = Dialog.getNumber();;
		DL1_set_intensity_high_threshold = Dialog.getNumber();;;
		DL1_set_low_particlesize = Dialog.getNumber();;;;
		DL1_set_high_particlesize = Dialog.getNumber();;;;;
		DL1_set_low_circularity = Dialog.getNumber();;;;;;
		DL1_set_high_circularity = Dialog.getNumber();;;;;;;
		DL1_set_roi_enlargement = Dialog.getNumber();;;;;;;;
		second_stain_type =  Dialog.getString();
		DL2_set_intensity_low_threshold = Dialog.getNumber();;
		DL2_set_intensity_high_threshold = Dialog.getNumber();;;
		DL2_set_low_particlesize = Dialog.getNumber();;;;
		DL2_set_high_particlesize = Dialog.getNumber();;;;;
		DL2_set_low_circularity = Dialog.getNumber();;;;;;
		DL2_set_high_circularity = Dialog.getNumber();;;;;;;
		DL2_set_roi_enlargement = Dialog.getNumber();;;;;;;;

		run("PIPSQUEAK");
		}
	}
}

//////////////////////////

macro "__sub_PIPSQUEAK_count" {
	//count labeled cells

import_type=4;

if (countCount == 1) {
	Dialog.create("Count Labeled Cells.");
	items = newArray("Yes, continue.", "No. Go back.");
	Dialog.addRadioButtonGroup("For this analysis, you NEED TO SET THE CELL DETECTION PARAMETERS in Settings. Also, you need previously summed z-stacks. \n Do you have the correct settings and summed files ready?", items, 2, 1, "Yes, continue.");
	Dialog.show;
	choice = Dialog.getRadioButton;
	if (choice=="No. Go back.") {
			run("PIPSQUEAK");
		} else {
			wait(50);
		}
	} else {
		wait(50);
		}
countCount = countCount+1;

Dialog.create("Cell Count");
items = newArray("Open image to count", "Adjust cell detection parameters", "Return to main menu");
Dialog.addRadioButtonGroup("What would you like to do?", items, 3, 1, "Open image to count");
Dialog.show;
choice = Dialog.getRadioButton;
if (choice=="Open image to count") {
	wait(100);
	
	} else {
	if (choice=="Return to main menu") {
		run("PIPSQUEAK");
		}
	if (choice=="Adjust cell detection parameters") {
		Dialog.create("Settings");
		Dialog.addMessage("**Cell count**");
		//Dialog.addMessage(" ");
		Dialog.addNumber("Lower threshold multiplier:", set_count_low_threshold );
		Dialog.addNumber("Upper threshold limit:", set_count_high_threshold);
		Dialog.addNumber("Lower limit particle size:", set_count_low_particlesize);
		Dialog.addNumber("Upper limit particle size:", set_count_high_particlesize);
		Dialog.addNumber("Lower limit circularity:", set_count_low_circularity);
		Dialog.addNumber("Upper limit circularity:", set_count_high_circularity);
		
		Dialog.show;

		set_count_low_threshold = Dialog.getNumber();;;;;;;
		set_count_high_threshold = Dialog.getNumber();;;;;;;;
		set_count_low_particlesize = Dialog.getNumber();;;;;;;;;
		set_count_high_particlesize = Dialog.getNumber();;;;;;;;;;
		set_count_low_circularity = Dialog.getNumber();;;;;;;;;;;
		set_count_high_circularity = Dialog.getNumber();;;;;;;;;;;;

		run("__sub_PIPSQUEAK_count");
		}
	}


open();
run("Set Measurements...", "area mean standard min redirect=None decimal=3");
run("Set Scale...", "distance=scale_size known=scale_known pixel=scale_pixel unit=&scale_unit global");
dir = getDirectory("image"); 
print(dir);
name = getTitle; 
full_name = getTitle; 
index = lastIndexOf(name, "."); 
if (index!=-1) name = substring(name, 0, index);
print("\n"+name+" loaded.");

first_open = name;


run("__sub_PIPSQUEAK_Background");
}

//////////////////////////

macro "__sub_PIPSQUEAK_single" {

//
/*  
print("PIPSQUEAK! Perineuronal net Intensity Program for the Standardization and Quantification of ECM Analysis.");
print("\n"+"Copyright (C) 2016, John H. Harkness, PhD.");
print("Protocol by Megan Slaker, PhD.");
print("Lab of Barb Sorg, PhD., Washington State University, Vancouver");
print("\n"+"Distance in pixels: "+scale_size+"\n"+"Known distance: "+scale_known+"\n"+"Pixel aspect ratio: "+scale_pixel+"\n"+"Unit of length: "+scale_unit);
wait(1000);
*/

Dialog.create("Import Type");

//
/*items = newArray("Semiautomated analysis of raw, non-summed, individual Tiffs", "Semiautomated analysis of summed Z-stacks", "Automatic analysis of summed Z-stacks","->Make summed image from z-stacks.");
Dialog.addRadioButtonGroup("What type of file do you want to import?", items, 4, 1, "Semiautomated analysis of summed Z-stacks");

*/
//
items = newArray("Semiautomated analysis of raw, non-summed, individual Tiffs", "Semiautomated analysis of summed Z-stacks", "Automatic analysis of summed Z-stacks");
Dialog.addRadioButtonGroup("What type of file do you want to import?", items, 3, 1, "Semiautomated analysis of summed Z-stacks");

Dialog.show;
choice = Dialog.getRadioButton;
if (choice=="Semiautomated analysis of raw, non-summed, individual Tiffs") {
	import_type=1;
	run("__sub_PIPSQUEAK_Import");
	
} else {
	if (choice=="Semiautomated analysis of summed Z-stacks") {
		import_type=2;
		run("__sub_PIPSQUEAK_Import_Summed");
		}
	if (choice=="Automatic analysis of summed Z-stacks") {
		import_type=3;
		run("__sub_PIPSQUEAK_Auto_Import_Summed");
		}
//
/*	if (choice=="->Make summed image from z-stacks.") {
		//Dialog.create("Stacks folder");
		//Dialog.addMessage("Before using this function, please place z-stack images into a folder titled 'Stacks' within your experiment folder.");
		//Dialog.addMessage("ie, /Desktop/experiment folder/Stacks/image1... image20");
		//Dialog.show(); 
		run("__sub_PIPSQUEAK_z-project");
		}
*/
	}
}
/////////////////////////////

macro "__sub_PIPSQUEAK_Import" {
       // Importing stacks
//import_type=1;
run("Image Sequence...", "disable_global convert sort");
name = getTitle; 
dir = getDirectory("image"); 
selectWindow(name);
run("Set Measurements...", "area mean standard min redirect=None decimal=3");

run("Z Project...", "projection=[Sum Slices]");
run("Set Scale...", "distance=scale_size known=scale_known pixel=scale_pixel unit=&scale_unit global");
full_name = "SUM_"+name; 
print("\n"+name+" loaded.");
run("__sub_PIPSQUEAK_Background");
}

/////////////////////////////

macro "__sub_PIPSQUEAK_Import_Summed" {
       // Importing image

//import_type=2;
open();
run("Set Measurements...", "area mean standard min redirect=None decimal=3");
run("Set Scale...", "distance=scale_size known=scale_known pixel=scale_pixel unit=&scale_unit global");
dir = getDirectory("image"); 
//print(dir);
name = getTitle; 
full_name = getTitle; 
index = lastIndexOf(name, "."); 
if (index!=-1) name = substring(name, 0, index);
print("\n"+name+" loaded.");

first_open = name;


run("__sub_PIPSQUEAK_Background");
}

////////////////////////////////

macro "__sub_PIPSQUEAK_Auto_Import_Summed" {
       // Importing image

//import_type=3;
open();
run("Set Measurements...", "area mean standard min redirect=None decimal=3");
run("Set Scale...", "distance=scale_size known=scale_known pixel=scale_pixel unit=&scale_unit global");
dir = getDirectory("image"); 
name = getTitle;
full_name = getTitle; 
index = lastIndexOf(name, "."); 
if (index!=-1) name = substring(name, 0, index);
print("\n"+name+" loaded.");

first_open = name;

waitForUser("Please don't touch", "Please let the macro run without clicking windows. Disruption may cause the macro to stall.");

run("__sub_PIPSQUEAK_Background");
}

////////////////////////////////

macro "__sub_PIPSQUEAK_z-project" {
	//makes summed image from z-stack


top_dir = getDirectory("Choose a Directory ");
count = 1;
listFiles(top_dir); 


function listFiles(top_dir) {
	list = getFileList(top_dir+"/..");
	//child_list = getFileList(top_dir);
	parentlist = File.getParent(top_dir);
	for (i=0; i<list.length; i++) {
		    	if (endsWith(list[i], ".tif")){
    	
        	listFiles(""+parentlist+File.separator+list[i]);

	} else {
			print((count++) + ": " + parentlist+File.separator+ list[i]);
			//child_list = getFileList();
			//print(child_list[i]);
			child_list = getFileList(parentlist+File.separator+ list[i]);
			for (a=0; a<child_list.length; a++) {
        		if (endsWith(child_list[a], ".tif")){
           			listFiles(""+child_list[a]);
			}else{
           			print(parentlist+File.separator+ list[i]+child_list[a]);
           			open_list = parentlist+File.separator+list[i]+child_list[a];
           			print("\n"+"Image total: "+(count++)+"= "+open_list);
           			run("Image Sequence...", "open=&open_list disable_global convert sort");
           			run("Set Measurements...", "area mean standard min redirect=None decimal=3");
					run("Z Project...", "projection=[Sum Slices]");
					run("Set Scale...", "distance=scale_size known=scale_known pixel=scale_pixel unit=&scale_unit global");
					name = getTitle;
					file_name = File.getName(list[i]);
					folder_name = File.getName(File.getParent(File.directory));
					
						if (count == 2) {
							save_location = "/Users/John 1/Desktop/";
							Dialog.create("Save location");
							Dialog.addMessage("Select a place to save the summed image. ie, /Users/John/Desktop");
							Dialog.addString("Save to: ", save_location);
							Dialog.show();
							save_location = Dialog.getString();
							print("Save location: "+save_location);
							} else {
								wait(1);
								}

						if (File.exists(save_location+"PIPSQUEAK_Summed Stacks/")) {
							wait(1);
							} else { 
								File.makeDirectory(save_location+"PIPSQUEAK_Summed Stacks/");
								}
						saveAs("Tiff", save_location+"PIPSQUEAK_Summed Stacks/"+file_name+"-"+name+".tif");
						close(file_name+"-"+name+".tif");
						print("Image: "+file_name+"-"+name+"\n"+"Saved in: "+save_location+"PIPSQUEAK_Summed Stacks/");
						run("Close All");
					
	}
	}
}
}
}
Dialog.create("Again?");
items = newArray("Yes, save another.", "No, let's analyze.", "Exit");
Dialog.addRadioButtonGroup("Would you like to save another summed image?", items, 3, 1, "Yes, save another.");
Dialog.show;
choice = Dialog.getRadioButton;
if (choice=="Yes, save another.") {
       run("__sub_PIPSQUEAK_z-project");
	
	} else {
	if (choice=="No, let's analyze.") {
		run("PIPSQUEAK");
		}
	if (choice=="Exit") {
		print("\n"+"Thanks for using PIPSQUEAK. Bye!");
		}
	}
}

////////////////////////////////

macro "__sub_PIPSQUEAK_OpenNext_Single" {

//import_type=3;
makeRectangle(0, 0, 0, 0);
run("Revert");
run("Open Next");
run("Set Measurements...", "area mean standard min redirect=None decimal=3");
run("Set Scale...", "distance=scale_size known=scale_known pixel=scale_pixel unit=&scale_unit global");
dir = getDirectory("image"); 
name = getTitle; 
full_name = getTitle; 
index = lastIndexOf(name, "."); 
if (index!=-1) name = substring(name, 0, index);
last_open = name;

if (last_open==first_open) {
	print("\n"+"All images processed! Done.");
	makeRectangle(0, 0, 0, 0);
	run("Revert");
	run("Clear Results");
	//run("Close");
	selectWindow(name+".tif");
	run("Close");
} else {
	print ("\n"+last_open+" loaded.");
	run ("__sub_PIPSQUEAK_Background");
	}
}
///////////////////////////////

macro "__sub_PIPSQUEAK_Background" {
	// Selecting Background


run("Clear Results");

run("ROI Manager...");
roi_count = roiManager("count");
if (roi_count>0) {
	roiManager("Delete");
	} 
roiManager("Show All");
roiManager("Show All with labels");

height = getHeight;
width = getWidth;

makeRectangle((6*(width-40)/6), (0.1*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((6*(width-40)/6), (1*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((6*(width-40)/6), (2*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((6*(width-40)/6), (3*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((6*(width-40)/6), (4*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((6*(width-40)/6), (5*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((5*(width-40)/6), (5*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((4*(width-40)/6), (5*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((3*(width-40)/6), (5*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((2*(width-40)/6), (5*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((1*(width-40)/6), (5*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((0.1*(width-40)/6), (5*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((0.1*(width-40)/6), (4*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((0.1*(width-40)/6), (3*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((0.1*(width-40)/6), (2*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((0.1*(width-40)/6), (1*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((0.1*(width-40)/6), (0.1*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((1*(width-40)/6), (0.1*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((2*(width-40)/6), (0.1*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((3*(width-40)/6), (0.1*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((4*(width-40)/6), (0.1*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((5*(width-40)/6), (0.1*(height-40)/5), 30, 30);
roiManager("Add");

run("Subtract Background...", "rolling=10");
roiManager("Select", newArray(0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,21));
roiManager("Measure");


	// Calculating lower threshold background value in "Mean" column

m=0;
bkgd_mean=0;
meanbkgd=0;
std=0;
bkgd_std=0;
stdbkgd=0;

m = nResults;
bkgd_mean = newArray(m);
run("Select None");
    for (i=0; i<m; i++) {
     bkgd_mean[i] = getResult('Mean', i);
    }
Array.getStatistics(bkgd_mean, min, max, mean, stdDev);
//print("mean1 = "+mean);
Array.sort(bkgd_mean);
//Array.print(bkgd_mean);
bkgd_high_trim = Array.trim(bkgd_mean, 15);
//Array.print(bkgd_high_trim);
Array.getStatistics(bkgd_high_trim, min, max, mean, stdDev);
//print("mean2 = "+mean);
Array.reverse(bkgd_high_trim);
//Array.print(bkgd_high_trim);
bkgd_low_trim = Array.trim(bkgd_high_trim, 7);
//Array.print(bkgd_low_trim);
Array.getStatistics(bkgd_low_trim, min, max, mean, stdDev);
//print("mean3 = "+mean);
meanbkgd = mean;

std = nResults;
bkgd_std = newArray(std);
run("Select None");
    for (i=0; i<std; i++) {
     bkgd_std[i] = getResult('StdDev', i);
    }
Array.getStatistics(bkgd_std, min, max, mean, stdDev);
//print("std1 = "+mean);
Array.sort(bkgd_std);
//Array.print(bkgd_std);
bksd_high_trim = Array.trim(bkgd_std, 15);
//Array.print(bksd_high_trim);
Array.getStatistics(bksd_high_trim, min, max, mean, stdDev);
//print("std2 = "+mean);
Array.reverse(bksd_high_trim);
//Array.print(bkgd_high_trim);
bksd_low_trim = Array.trim(bksd_high_trim, 7);
//Array.print(bkgd_low_trim);
Array.getStatistics(bksd_low_trim, min, max, mean, stdDev);
//print("mean3 = "+mean);
stdbkgd = mean;

lower = ((meanbkgd)+(stdbkgd*2));
print("Mean="+meanbkgd+",_StdDev="+stdbkgd);
print("Lower_Threshold="+lower);

if (import_type==4) {
		run("__sub_PIPSQUEAK_count_ROIs");
	} else {

	// Setting Threshold

		run("Set Measurements...", "area mean standard min limit redirect=None decimal=3");
		setAutoThreshold("Default dark");
		run("Threshold...");
		wait(200);
		setThreshold(lower, 5000);
		//run("Apply");
		run("NaN Background");
		run("Close");

		run("__sub_PIPSQUEAK_Measuring_ROIs");
	}
}

/////////////////////////////

macro "__sub_PIPSQUEAK_Measuring_ROIs" {
       // Measuring ROIs
           //Finding PNNs with Analyze Particles

roi_count = roiManager("count");
if (roi_count>0) {
	roiManager("Delete");
	}
if (import_type==2) {		
	selectWindow(name+".tif");
	}	
if (import_type==1) {
	selectWindow("SUM_"+name);
	}

roiManager("Show All");
roiManager("Show All with labels");

run("Clear Results");
wait(200);
setAutoThreshold("Default dark");
run("Threshold...");
wait(200);
setThreshold(lower*set_intensity_low_threshold, set_intensity_high_threshold);
wait(200);
makeRectangle(0, 0, 0, 0);
run("Analyze Particles...", "size=set_low_particlesize-set_high_particlesize circularity=set_low_circularity-set_high_circularity clear include add");
wait(200);
selectWindow("Threshold");
resetThreshold();
run("Close");
roiManager("Measure");

           //Making square ROIs from Particles

wait(500);
add_squares=roiManager("count"); 
if (add_squares==0) {

	roiManager("Show All");
	roiManager("Show All with labels");
	waitForUser("Oops", "We didn't see any staining here. Try adjusting the Cell Detection Threshold settings in the next step... ");
	setTool("point");
	makePoint(0, 0);
	selectWindow(full_name);
	} else {
		array=newArray(add_squares); 
		for(i=0; i<add_squares;i++) { 
			roiManager("Select", 0);
       			run("Specify...", "centered scaled");
       			run("Enlarge...", "enlarge=set_roi_enlargement_single");
       			roiManager("Add");
       			roiManager("Select", 0);
       			roiManager("Delete");
			}
		} 

if (import_type==3) {
	wait(300);
} else {
	setTool("rectangle");
	if (import_type==2) {		
		run("Duplicate...", " ");
		selectWindow(name+"-1.tif");
		run("Revert", " ");
		roiManager("Show All");
		roiManager("Show All with labels");
		}	
	if (import_type==1) {
		selectWindow(name);
		run("Z Project...", "projection=[Sum Slices]");
		selectWindow("SUM_"+name+"-1");
		roiManager("Show All");
		roiManager("Show All with labels");
		}

	set_intensity_low_threshold_old = set_intensity_low_threshold;
	set_low_particlesize_old = set_low_particlesize; 
	set_high_particlesize_old = set_high_particlesize;

	Dialog.create("Adjust Cell Detection Threshold");
	items = newArray("Yes, rerun cell detection with these new settings.", "No, let me add / delete ROIs by hand.", "I like the ROIs as they are. Lets move on.");
	Dialog.addSlider("Threshold of Detection:", (set_intensity_low_threshold*0.1), (set_intensity_low_threshold*2), set_intensity_low_threshold);
	Dialog.addSlider("Smallest Cell Detected:", 0.0, 10000, set_low_particlesize);
	Dialog.addSlider("Largest Cell Detected:", 0.0, 100000, set_high_particlesize);

	Dialog.addRadioButtonGroup("Would you like to change the cell detection threshold settings?", items, 3, 1, "Yes, rerun cell detection with these new settings.");
	Dialog.show;
	set_intensity_low_threshold = Dialog.getNumber();
	set_low_particlesize = Dialog.getNumber();
	set_high_particlesize = Dialog.getNumber();
	choice = Dialog.getRadioButton;

	if (choice=="No, let me add / delete ROIs by hand." && set_intensity_low_threshold_old==set_intensity_low_threshold && set_low_particlesize_old==set_low_particlesize && set_high_particlesize_old==set_high_particlesize)  {
		
		if (import_type==2) {		
			waitForUser("How Does That Look?", "Here is your chance to adjust the ROIs to better identify PNNs. Try adding or deleting ROIs in the ROI manager. **THEN** press OK.");
			selectWindow(name+"-1.tif");
			close(name+"-1.tif");
			}

		if (import_type==1) {
			waitForUser("How Does That Look?", "Here is your chance to adjust the ROIs to better identify PNNs. Try adding or deleting ROIs in the ROI manager. **THEN** press OK.");
			selectWindow("SUM_"+name+"-1");
			close("SUM_"+name+"-1");
			}

		}
	
	if (choice=="Yes, rerun cell detection with these new settings." || set_intensity_low_threshold_old != set_intensity_low_threshold || set_low_particlesize_old != set_low_particlesize || set_high_particlesize_old != set_high_particlesize) {
		if (import_type==2) {		
			selectWindow(name+"-1.tif");
			close(name+"-1.tif");
			}

		if (import_type==1) {
			selectWindow("SUM_"+name+"-1");
			close("SUM_"+name+"-1");
			}

		run("__sub_PIPSQUEAK_Measuring_ROIs");
		}

	if (choice=="I like the ROIs as they are. Lets move on." && set_intensity_low_threshold_old==set_intensity_low_threshold && set_low_particlesize_old==set_low_particlesize && set_high_particlesize_old==set_high_particlesize)  {
		if (import_type==2) {		
			selectWindow(name+"-1.tif");
			close(name+"-1.tif");
			}
		if (import_type==1) {
			selectWindow("SUM_"+name+"-1");
			close("SUM_"+name+"-1");
			}
		}
	}


//saving ROI overlay

//name = getTitle; 
save_ROIs=roiManager("count");
array=newArray(save_ROIs);
for(i=0; i<save_ROIs; i++) {
	array[i] = i;
	}
roiManager("Select", array);
roiManager("Save", dir+name+"_ROIoverlay.zip");

//Measuring ROIs

run("Clear Results");
roiManager("Show All");
roiManager("Show All with labels");
measure_squares=0;
measure_squares=roiManager("count"); 
array=newArray(measure_squares); 
for(i=0; i<measure_squares;i++) { 
        array[i] = i; 
}
roiManager("Select", array);
roiManager("Measure");

m=0;
means=0;
m = nResults;
means = newArray(m);
run("Select None");
    for (i=0; i<m; i++) {
      means[i] = getResult('Mean', i);
    }
run("Select None");
    for (i=0; i<m; i++) {
      setResult("Background", i, lower);
      setResult("Mean-Background", i, means[i]-lower);
    }
setResult("File Name", 0, name);
updateResults();

m2 = 0;
avgmeans = 0;
m2 = nResults;
avgmeans = newArray(m2);
run("Select None");
    for (i=0; i<m2; i++) {
      avgmeans[i] = getResult('Mean-Background', i);
    }
Array.getStatistics(avgmeans, min, max, mean, stdDev);
print("Mean_Intensity="+mean);


numberPNNs=0;
numberPNNs=getValue("results.count");
print("Number_of_PNNs(cells)="+numberPNNs);

n = nResults;
area = newArray(n);
mean = newArray(n);
stddev = newArray(n);
min = newArray(n);
max = newArray(n);
bkgd = newArray(n);
meanbkgd = newArray(n);
print("\n");
print("Individual cell data:");
print("Cell# Area Mean StdDev Min Max Background Mean-Background");
    for (i=0; i<n; i++) {
     area[i] = getResult('Area', i);
     mean[i] = getResult('Mean', i);
     stddev[i] = getResult('StdDev', i);
     min[i] = getResult('Min', i);
     max[i] = getResult('Max', i);
     bkgd[i] = getResult('Background', i);
     meanbkgd[i] = getResult('Mean-Background', i);
	print(i+1+" "+area[i]+" "+mean[i]+" "+stddev[i]+" "+min[i]+" "+max[i]+" "+bkgd[i]+" "+meanbkgd[i]);
    }

run("__sub_PIPSQUEAK_Save");


/////////////////////////////

macro "__sub_PIPSQUEAK_count_ROIs" {
       // count labeled cells by making ROIs
           //Finding cells with Analyze Particles

roiManager("Delete");
run("Clear Results");

wait(100);
setAutoThreshold("Default dark");
run("Threshold...");
setThreshold(lower*set_count_low_threshold, set_count_high_threshold);
wait(200);
makeRectangle(0, 0, 0, 0);
run("Analyze Particles...", "size=set_count_low_particlesize-set_count_high_particlesize circularity=set_count_low_circularity-set_count_high_circularity clear include add");
wait(200);
selectWindow("Threshold");
resetThreshold();

wait(500);
waitForUser("How Does That Look?", "Here is your chance to adjust ROIs to better count labeled cells. Try adding or deleting circular ROIs in the ROI manager. **THEN** press OK.");

roiManager("Measure");
numbercells=0;
numbercells=getValue("results.count");
print("Number of cells counted = "+numbercells);

run("Clear Results");
clear_ROIs=roiManager("count"); 
array=newArray(clear_ROIs); 
for(i=0; i<clear_ROIs;i++) { 
    array[i] = i;
	}
roiManager("Select", array); 
roiManager("Delete");
run("Close");
selectWindow(name+".tif");
run("Close");


Dialog.create("Analyze another image?");
items = newArray("Open another", "Return to main menu", "Exit");
Dialog.addRadioButtonGroup("Analysis done! \n Next Move:", items, 3, 1, "Open another");
Dialog.show;
choice = Dialog.getRadioButton;
if (choice=="Open another") {
	run("__sub_PIPSQUEAK_count");

} else {
	if (choice=="Return to main menu") {	
		run("PIPSQUEAK");
	} 
	if (choice=="Exit") {
		print("\n"+"Thanks for using PIPSQUEAK. Bye!");
		}
	}
}


/////////////////////////////

macro "__sub_PIPSQUEAK_Save" {

	// Saving data
//
/*
if (import_type==1) {
	name = getTitle; 
	name = name + ".txt"; 
	saveAs("Measurements"); 
	saveAs("Text", dir+"/All_Results.txt");
	print("Results saved as: "+name);
	print("\n");	
	makeRectangle(0, 0, 0, 0);
	run("Revert");
	run("Close");
} else {
*/
//
	name_text = 0;
	name_text = name + ".txt"; 
	selectWindow("Log");
	saveAs("Measurements", dir+name_text); 
	saveAs("Text", dir+"/All_Results.txt");
	print("Results_saved_as:_"+dir+name);
	print("\n");
// 	}

	// Closing project


clear_ROIs=roiManager("count"); 
array=newArray(clear_ROIs); 
for(i=0; i<clear_ROIs;i++) { 
    array[i] = i;
}
roiManager("Select", array); 
roiManager("Delete");

selectWindow("ROI Manager");
run("Close");


if (import_type==3) {
	run("Clear Results");
	run("__sub_PIPSQUEAK_OpenNext_Single");
} else 
	if (import_type==1) {
		selectWindow(full_name);
		run("Close");
		selectWindow(name);
		run("Close");

		Dialog.create("Analyze another image?");
		items = newArray("Open another", "Exit to main menu");
		Dialog.addRadioButtonGroup("Analysis done! Results saves as .txt"+"\n"+"Next Move:", items, 2, 1, "Open another");
		Dialog.show;
		choice = Dialog.getRadioButton;
		if (choice=="Open another") {
			run("__sub_PIPSQUEAK_Import");

		} else {
			run("PIPSQUEAK");
			print("\n"+"Thanks for using PIPSQUEAK. Bye!");
			}
		}

	if (import_type==2) {
		
		selectWindow(name+".tif");
		run("Close");
		Dialog.create("Analyze another image?");
		items = newArray("Open Next Image", "Open another", "Exit to main menu");
		Dialog.addRadioButtonGroup("Analysis done! Results saves as .txt"+"\n"+"Next Move:", items, 3, 1, "Open Next Image");
		Dialog.show;
		choice = Dialog.getRadioButton;
		if (choice=="Open another") {
			run("__sub_PIPSQUEAK_Import_Summed");
			
		} else {
			if (choice=="Open Next Image") {
				run("__sub_PIPSQUEAK_OpenNext_Single");
				} else {
					run("PIPSQUEAK");
					print("\n"+"Thanks for using PIPSQUEAK. Bye!");
				}
			}
		}
	}
}



/////////////////////////////////////////////////////
//#################################################//
//#################################################//
/////////////////////////////////////////////////////


	//Here be double label intensity analysis

macro "__sub_PIPSQUEAK_double" {

//
/*
print("PIPSQUEAK! Perineuronal net Intensity Program for the Standardization and Quantification of ECM Analysis.");
print("\n"+"Copyright (C) 2016, John H. Harkness, PhD.");
print("Protocol by Megan Slaker, PhD.");
print("Lab of Barb Sorg, PhD., Washington State University, Vancouver");
print("\n"+"Distance in pixels: "+scale_size+"\n"+"Known distance: "+scale_known+"\n"+"Pixel aspect ratio: "+scale_pixel+"\n"+"Unit of length: "+scale_unit);
wait(1000);
*/

Dialog.create("Import Type");
items = newArray("Semiautomated analysis of summed double-labeled Z-stack", "Automatic analysis of summed double-labeled Z-stacks", "->Make summed double-labeled images from z-stacks.");
Dialog.addRadioButtonGroup("What type of file do you want to import?", items, 3, 1, "Semiautomated analysis of summed double-labeled Z-stack");
Dialog.show;
choice = Dialog.getRadioButton;
if (choice=="Semiautomated analysis of summed double-labeled Z-stack") {
	import_type = 5;
	run("__sub_PIPSQUEAK_Open_Double");
	} else {		
	if (choice=="Automatic analysis of summed double-labeled Z-stacks") {
		import_type = 6;		
		run("__sub_PIPSQUEAK_Open_Double");
		}
	if (choice=="->Make summed double-labeled images from z-stacks.") {
		//Dialog.create("Stacks folder");
		//Dialog.addMessage("Before using this function, please place z-stack images into a folder titled 'Stacks' within your experiment folder.");
		//Dialog.addMessage("ie, /Desktop/experiment folder/Stacks/image1... image20");
		//Dialog.show(); 
		run("__sub_PIPSQUEAK_double_sum"");
		}
	}
}


/////////////////////////////

macro "__sub_PIPSQUEAK_double_sum" {

countDouble = 1
Ldest = getDirectory("Choose a Directory ");		//load from
name = getTitle;
countDouble++

if (countDouble == 2) {
		Sdest = Ldest+"/summed/";	//save to
		Dialog.create("Save location");
		Dialog.addMessage("Select a place to save the summed image. ie, /Users/John/Desktop");
		Dialog.addString("Save to: ", Sdest);
		Dialog.show();
		Sdest = Dialog.getString(Ldest="/summed/");
		print("Save location: "+Sdest);
	} else {
		wait(100);
		}
	
	if (File.exists(Sdest+name+"/")) {
			wait(100);
		} else { 
			File.makeDirectory(Sdest+name+"/");
			}
		

sfold = Sdest + name;
stackfold = getFileList(Ldest);

//if(!File.exists(sfold)) {
//	File.makeDirectory(sfold);	
//}

for(i=0; i<stackfold.length; i++){
	stacks = stackfold[i];
	identify = substring(stacks, 0, lengthOf(stacks)-1);
	names = substring(stacks, lengthOf(stacks)-1);
	if(names == "/" && stacks!="Sum Slices/"){
		ISp = "open=[" + Ldest + stacks + "] number=20 starting=q increment=3 scale=100 file=[] or=[] sort";

		for(q=1; q<4; q++) { 
			run("Image Sequence...", ISp);
			if(q!=2){
				run("8-bit");
			}

			run("Z Project...", "start=1 stop=20 projection=[Sum Slices]");


			saveAs("Tiff", sfold + identify + "_" + q + ".tif");

			close();
		}
	}
}

{
while(nImages>0){
	selectImage(nImages);
	close();
	}
}

/////////////////////////////

macro "__sub_PIPSQUEAK_Open_Double" {

waitForUser("Select First Image", "Please open the first image of the subject series.");
open();
run("Set Measurements...", "area mean standard min redirect=None decimal=3");
run("Set Scale...", "distance=scale_size known=scale_known pixel=scale_pixel unit=&scale_unit global");
first_image = getTitle;
dir = getDirectory("image"); 
index = lastIndexOf(first_image, "."); 
if (index!=-1) first_image = substring(first_image, 0, index);
	print("\n"+first_image+" loaded.");

series_name = substring(first_image, 0, index-2);
first_open_double = series_name;

subDir = dir+"/"+series_name+"/";
File.makeDirectory(subDir);
//print("subDir = "+subDir);

if(endsWith(first_image,first_suffix)) {
	open(series_name+"_"+second_suffix+".tif");
	second_image = getTitle;
	if (index!=-1) second_image = substring(second_image, 0, index);
		print(second_image+" loaded.");
		run("__sub_PIPSQUEAK_Double_Background");
	} else {		
		waitForUser("Please update Settings to match numbering suffixes of double-label image series");
		run("PIPSQUEAK");
	}

}

//////////////////////////////
/*
//MACRO REMOVED BECAUSE SUBJECT SEQUENCE LOADING COMPLICATED BY IMAGE ORDER. MUST REVISIT STRATEGY TO MAKE THIS FUNCTION WORK.
macro "__sub_PIPSQUEAK_OpenNext_Double" {

if (total_images == second_suffix) {
	run("Open Next");
	} else {
	series_diff = total_images-second_suffix;
	for (i = 0; i < series_diff; i++) {
		run("Open Next");
		}}
	
first_image = getTitle;
index = lastIndexOf(first_image, ".");

series_name = substring(first_image, 0, index-2);

last_open_double = series_name;
//print(series_name);


//if (last_open_double==first_open_double) {
//	print("\n"+"All images processed! Done.");
//	makeRectangle(0, 0, 0, 0);
//	run("Revert");
//	run("Clear Results");
//	run("Close");
//	selectWindow(first_image+".tif");
//	run("Close");
//	} else {
//	wait(100);
//	}

if (index!=-1) first_image = substring(first_image, 0, index);
	if(endsWith(first_image,first_suffix)) {
		print("\n"+first_image+" loaded.");
		open(series_name+"_"+second_suffix+".tif");
		second_image = getTitle;
		if (index!=-1) second_image = substring(second_image, 0, index);
			if(endsWith(second_image,second_suffix)) {
				print(second_image+" loaded.");
				run("__sub_PIPSQUEAK_Double_Background");
			} else {
				waitForUser("Please update Settings to match numbering suffixes of double-label image series");
				run("__sub_PIPSQUEAK_Open_Double");
				}
}

*/
///////////////////////////////

macro "__sub_PIPSQUEAK_Double_Background" {

//First Image
	// Selecting Background

first_image_tif = first_image+".tif";
second_image_tif = second_image+".tif";

run("Clear Results");

run("ROI Manager...");
roi_count = roiManager("count");
if (roi_count>0) {
	roiManager("Delete");
	} 

roiManager("Show All");
roiManager("Show All with labels");

selectWindow(first_image_tif);

height = getHeight;
width = getWidth;

makeRectangle((6*(width-40)/6), (0.1*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((6*(width-40)/6), (1*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((6*(width-40)/6), (2*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((6*(width-40)/6), (3*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((6*(width-40)/6), (4*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((6*(width-40)/6), (5*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((5*(width-40)/6), (5*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((4*(width-40)/6), (5*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((3*(width-40)/6), (5*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((2*(width-40)/6), (5*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((1*(width-40)/6), (5*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((0.1*(width-40)/6), (5*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((0.1*(width-40)/6), (4*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((0.1*(width-40)/6), (3*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((0.1*(width-40)/6), (2*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((0.1*(width-40)/6), (1*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((0.1*(width-40)/6), (0.1*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((1*(width-40)/6), (0.1*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((2*(width-40)/6), (0.1*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((3*(width-40)/6), (0.1*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((4*(width-40)/6), (0.1*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((5*(width-40)/6), (0.1*(height-40)/5), 30, 30);
roiManager("Add");

run("Subtract Background...", "rolling=10");
roiManager("Select", newArray(0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,21));
roiManager("Measure");


	// Calculating lower threshold background value in "Mean" column

DL1_m=0;
DL1_bkgd_mean=0;
DL1_meanbkgd=0;
DL1_std=0;
DL1_bkgd_std=0;
DL1_stdbkgd=0;

DL1_m = nResults;
DL1_bkgd_mean = newArray(DL1_m);
run("Select None");
    for (i=0; i<DL1_m; i++) {
    DL1_bkgd_mean[i] = getResult('Mean', i);
    }
Array.getStatistics(DL1_bkgd_mean, min, max, mean, stdDev);
//print("mean1 = "+mean);
Array.sort(DL1_bkgd_mean);
//Array.print(DL1_bkgd_mean);
DL1_bkgd_high_trim = Array.trim(DL1_bkgd_mean, 15);
//Array.print(DL1_bkgd_high_trim);
Array.getStatistics(DL1_bkgd_high_trim, min, max, mean, stdDev);
//print("mean2 = "+mean);
Array.reverse(DL1_bkgd_high_trim);
//Array.print(DL1_bkgd_high_trim);
DL1_bkgd_low_trim = Array.trim(DL1_bkgd_high_trim, 7);
//Array.print(DL1_bkgd_low_trim);
Array.getStatistics(DL1_bkgd_low_trim, min, max, mean, stdDev);
//print("mean3 = "+mean);
DL1_meanbkgd = mean;

DL1_std = nResults;
DL1_bkgd_std = newArray(DL1_std);
run("Select None");
    for (i=0; i<DL1_std; i++) {
    DL1_bkgd_std[i] = getResult('StdDev', i);
    }
Array.getStatistics(DL1_bkgd_std, min, max, mean, stdDev);
Array.sort(DL1_bkgd_std);
DL1_bksd_high_trim = Array.trim(DL1_bkgd_std, 15);
Array.getStatistics(DL1_bksd_high_trim, min, max, mean, stdDev);
Array.reverse(DL1_bksd_high_trim);
DL1_bksd_low_trim = Array.trim(DL1_bksd_high_trim, 7);
Array.getStatistics(DL1_bksd_low_trim, min, max, mean, stdDev);
DL1_stdbkgd = mean;

DL1_lower = ((DL1_meanbkgd)+(DL1_stdbkgd*2));
print("\n");
print("Single "+first_stain_type+" label:");
print(first_stain_type+" Mean Background = "+DL1_meanbkgd+", Background StdDev = "+DL1_stdbkgd);
print(first_stain_type+" Lower Threshold= "+DL1_lower);

	// Setting Threshold

run("Set Measurements...", "area mean standard min limit redirect=None decimal=3");
setAutoThreshold("Default dark");
run("Threshold...");
wait(200);
setThreshold(DL1_lower, 5000);
//run("Apply");
run("NaN Background");
//run("Close");


selectWindow(first_image_tif);
run("Duplicate...", " ");
//run("8-bit");
run("Duplicate...", " ");
//run("8-bit");
selectWindow(first_image+"-1.tif");

run("__sub_PIPSQUEAK_Double_Background_SL1_ROIs");
}	
////////////////////////////////

macro "__sub_PIPSQUEAK_Double_Background_SL1_ROIs" {

       // Measuring ROIs
           //Finding PNNs with Analyze Particles

roi_count = roiManager("count");
if (roi_count>0) {
	roiManager("Delete");
	}

first_image_tif = first_image+".tif";
second_image_tif = second_image+".tif";

selectWindow(first_image+"-1.tif");
roiManager("Show All");
roiManager("Show All with labels");

run("Clear Results");
wait(200);
setAutoThreshold("Default dark");
run("Threshold...");
wait(200);
setThreshold(DL1_lower*DL1_set_intensity_low_threshold, DL1_set_intensity_high_threshold);
wait(200);
makeRectangle(0, 0, 0, 0);
run("Analyze Particles...", "size=DL1_set_low_particlesize-DL1_set_high_particlesize circularity=DL1_set_low_circularity-DL1_set_high_circularity clear include add");
wait(200);
selectWindow("Threshold");
resetThreshold();
run("Close");
roiManager("Measure");

           //Making circular ROIs from Particles

wait(500);
DL1_add_circles=roiManager("count"); 
if (DL1_add_circles==0) {
	waitForUser("Oops", "We didn't see any staining here. Try adjusting the Cell Detection Threshold settings in the next step... ");
		
} else {
	array=newArray(DL1_add_circles); 
	for(i=0; i<DL1_add_circles;i++) { 
		roiManager("Select", 0);
       		run("Specify...", "oval constrain centered scaled");
       		run("Enlarge...", "enlarge=DL1_set_roi_enlargement");
       		roiManager("Add");
       		roiManager("Select", 0);
       		roiManager("Delete");
		} 
	}

if (import_type==6) {
	wait(300);
} else {
	setTool("oval");
	selectWindow(first_image_tif);
	run("Revert");
	roiManager("Show All");
	roiManager("Show All with labels");
	
	SL1_set_intensity_low_threshold_old = DL1_set_intensity_low_threshold;
	SL1_set_low_particlesize_old = DL1_set_low_particlesize; 
	SL1_set_high_particlesize_old = DL1_set_high_particlesize;

	Dialog.create("Adjust Cell Detection Threshold");
	items = newArray("Yes, rerun cell detection with these new settings.", "No, let me add / delete ROIs by hand.", "I like the ROIs as they are. Lets move on to the next stain.");
	Dialog.addSlider("Threshold of Detection:", (DL1_set_intensity_low_threshold*0.1), (DL1_set_intensity_low_threshold*2), DL1_set_intensity_low_threshold);
	Dialog.addSlider("Smallest Cell Detected:", 0.0, 1000, DL1_set_low_particlesize);
	Dialog.addSlider("Largest Cell Detected:", 0.0, 10000, DL1_set_high_particlesize);

	Dialog.addRadioButtonGroup("Would you like to change the "+first_stain_type+" cell detection threshold settings?", items, 3, 1, "Yes, rerun cell detection with these new settings.");
	Dialog.show;
	DL1_set_intensity_low_threshold = Dialog.getNumber();
	DL1_set_low_particlesize = Dialog.getNumber();
	DL1_set_high_particlesize = Dialog.getNumber();
	choice = Dialog.getRadioButton;

	if (choice=="No, let me add / delete ROIs by hand." && SL1_set_intensity_low_threshold_old==DL1_set_intensity_low_threshold && SL1_set_low_particlesize_old==DL1_set_low_particlesize && SL1_set_high_particlesize_old==DL1_set_high_particlesize)  {
		waitForUser("How Does That Look?", "Here is your chance to adjust the ROIs to better identify PNNs. Try adding or deleting ROIs in the ROI manager. **THEN** press OK.");
		}

	if (choice=="Yes, rerun cell detection with these new settings." || SL1_set_intensity_low_threshold_old != DL1_set_intensity_low_threshold || SL1_set_low_particlesize_old != DL1_set_low_particlesize || SL1_set_high_particlesize_old != DL1_set_high_particlesize) {

		run("__sub_PIPSQUEAK_Double_Background_SL1_ROIs");
		}

	if (choice=="I like the ROIs as they are. Lets move on to the next stain." && SL1_set_intensity_low_threshold_old==DL1_set_intensity_low_threshold && SL1_set_low_particlesize_old==DL1_set_low_particlesize && SL1_set_high_particlesize_old==DL1_set_high_particlesize)  {
		wait(10);
		}
	}

selectWindow(first_image_tif);
run("Close");

//saving SL1 ROI overlay

SL1_save_ROIs=roiManager("count");
array=newArray(SL1_save_ROIs);
for(i=0; i<SL1_save_ROIs; i++) {
	array[i] = i;
	}
roiManager("Select", array);
roiManager("Save", subDir+name+"_SL1_ROIoverlay.zip");
	

//Measuring ROIs

run("Clear Results");
DL1_measure_circles=0;
DL1_measure_circles=roiManager("count"); 
array=newArray(DL1_measure_circles); 
for(i=0; i<DL1_measure_circles;i++) { 
        array[i] = i; 
}
roiManager("Select", array);
roiManager("Measure");
roiManager("Show All");
roiManager("Show All with labels");

DL1_m=0;
DL1_means=0;
DL1_m = nResults;
DL1_means = newArray(DL1_m);
run("Select None");
    for (i=0; i<DL1_m; i++) {
      DL1_means[i] = getResult('Mean', i);
    }
run("Select None");
    for (i=0; i<DL1_m; i++) {
      setResult("Background", i, DL1_lower);
      setResult("Mean-Background", i, DL1_means[i]-DL1_lower);
    }
setResult("File Name", 0, name);
updateResults();

DL1_m2 = 0;
DL1_avgmeans = 0;
DL1_m2 = nResults;
DL1_avgmeans = newArray(DL1_m2);
run("Select None");
    for (i=0; i<DL1_m2; i++) {
     DL1_avgmeans[i] = getResult('Mean-Background', i);
    }
Array.getStatistics(DL1_avgmeans, min, max, mean, stdDev);
print(first_stain_type+" Mean Intensity = "+mean);

DL1_numberStains = 0;
DL1_numberStains=getValue("results.count");
print("Number of "+first_stain_type+" Stained Cells = "+DL1_numberStains);

n_sl1 = nResults;
area_sl1 = newArray(n_sl1);
mean_sl1 = newArray(n_sl1);
stddev_sl1 = newArray(n_sl1);
min_sl1 = newArray(n_sl1);
max_sl1 = newArray(n_sl1);
bkgd_sl1 = newArray(n_sl1);
meanbkgd_sl1 = newArray(n_sl1);
print("\n");
print("Individual "+first_stain_type+" cell data:");
print("Cell# Area Mean StdDev Min Max Background Mean-Background");
    for (i=0; i<n_sl1; i++) {
     area_sl1[i] = getResult('Area', i);
     mean_sl1[i] = getResult('Mean', i);
     stddev_sl1[i] = getResult('StdDev', i);
     min_sl1[i] = getResult('Min', i);
     max_sl1[i] = getResult('Max', i);
     bkgd_sl1[i] = getResult('Background', i);
     meanbkgd_sl1[i] = getResult('Mean-Background', i);
	print(i+1+" "+area_sl1[i]+" "+mean_sl1[i]+" "+stddev_sl1[i]+" "+min_sl1[i]+" "+max_sl1[i]+" "+bkgd_sl1[i]+" "+meanbkgd_sl1[i]);
    }

clear_ROIs=roiManager("count"); 
array=newArray(clear_ROIs); 
for(i=0; i<clear_ROIs;i++) { 
    array[i] = i;
	}
roiManager("Select", array); 
roiManager("Delete");
selectWindow("ROI Manager");
run("Close");

wait(100);

selectWindow(first_image+"-1.tif");
run("Close");

	// Saving data

name = series_name+" "+first_stain_type+".txt"; 
saveAs("Measurements", subDir+name);
print("\n"); 
print("Results saved as: "+subDir+name);


//\\//\\//\\//\\//\\//\\

//Second Image
	// Selecting Background

run("Clear Results");

run("ROI Manager...");
roi_count = roiManager("count");
if (roi_count>0) {
	roiManager("Delete");
	} 

roiManager("Show All");
roiManager("Show All with labels");

selectWindow(second_image_tif);

height = getHeight;
width = getWidth;

makeRectangle((6*(width-40)/6), (0.1*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((6*(width-40)/6), (1*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((6*(width-40)/6), (2*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((6*(width-40)/6), (3*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((6*(width-40)/6), (4*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((6*(width-40)/6), (5*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((5*(width-40)/6), (5*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((4*(width-40)/6), (5*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((3*(width-40)/6), (5*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((2*(width-40)/6), (5*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((1*(width-40)/6), (5*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((0.1*(width-40)/6), (5*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((0.1*(width-40)/6), (4*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((0.1*(width-40)/6), (3*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((0.1*(width-40)/6), (2*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((0.1*(width-40)/6), (1*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((0.1*(width-40)/6), (0.1*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((1*(width-40)/6), (0.1*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((2*(width-40)/6), (0.1*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((3*(width-40)/6), (0.1*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((4*(width-40)/6), (0.1*(height-40)/5), 30, 30);
roiManager("Add");
makeRectangle((5*(width-40)/6), (0.1*(height-40)/5), 30, 30);
roiManager("Add");

run("Subtract Background...", "rolling=10");
roiManager("Select", newArray(0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,21));
roiManager("Measure");


	// Calculating lower threshold background value in "Mean" column

DL2_m=0;
DL2_bkgd_mean=0;
DL2_meanbkgd=0;
DL2_std=0;
DL2_bkgd_std=0;
DL2_stdbkgd=0;

DL2_m = nResults;
DL2_bkgd_mean = newArray(DL2_m);
run("Select None");
    for (i=0; i<DL2_m; i++) {
    DL2_bkgd_mean[i] = getResult('Mean', i);
    }
Array.getStatistics(DL2_bkgd_mean, min, max, mean, stdDev);
//print("mean1 = "+mean);
Array.sort(DL2_bkgd_mean);
//Array.print(DL2_bkgd_mean);
DL2_bkgd_high_trim = Array.trim(DL2_bkgd_mean, 15);
//Array.print(DL2_bkgd_high_trim);
Array.getStatistics(DL2_bkgd_high_trim, min, max, mean, stdDev);
//print("mean2 = "+mean);
Array.reverse(DL2_bkgd_high_trim);
//Array.print(DL2_bkgd_high_trim);
DL2_bkgd_low_trim = Array.trim(DL2_bkgd_high_trim, 7);
//Array.print(DL2_bkgd_low_trim);
Array.getStatistics(DL2_bkgd_low_trim, min, max, mean, stdDev);
//print("mean3 = "+mean);
DL2_meanbkgd = mean;

DL2_std = nResults;
DL2_bkgd_std = newArray(DL2_std);
run("Select None");
    for (i=0; i<DL2_std; i++) {
    DL2_bkgd_std[i] = getResult('StdDev', i);
    }
Array.getStatistics(DL2_bkgd_std, min, max, mean, stdDev);
//print("std1 = "+mean);
Array.sort(DL2_bkgd_std);
//Array.print(DL2_bkgd_std);
DL2_bksd_high_trim = Array.trim(DL2_bkgd_std, 15);
//Array.print(DL2_bksd_high_trim);
Array.getStatistics(DL2_bksd_high_trim, min, max, mean, stdDev);
//print("std2 = "+mean);
Array.reverse(DL2_bksd_high_trim);
//Array.print(DL2_bkgd_high_trim);
DL2_bksd_low_trim = Array.trim(DL2_bksd_high_trim, 7);
//Array.print(DL2_bkgd_low_trim);
Array.getStatistics(DL2_bksd_low_trim, min, max, mean, stdDev);
//print("mean3 = "+mean);
DL2_stdbkgd = mean;

DL2_lower = ((DL2_meanbkgd)+(DL2_stdbkgd*2));
print("\n");
print("Single "+second_stain_type+" label:");
print(second_stain_type+" Mean Background = "+DL2_meanbkgd+", Background StdDev = "+DL2_stdbkgd);
print(second_stain_type+" Lower Threshold= "+DL2_lower);

	// Setting Threshold

run("Set Measurements...", "area mean standard min limit redirect=None decimal=3");
setAutoThreshold("Default dark");
run("Threshold...");
wait(200);
setThreshold(DL2_lower, 5000);
//run("Apply");
run("NaN Background");

selectWindow(second_image_tif);
run("Duplicate...", " ");
//run("8-bit");
run("Duplicate...", " ");
//run("8-bit");
selectWindow(second_image+"-1.tif");

run("__sub_PIPSQUEAK_Double_Background_SL2_ROIs");

}

/////////////////////////////

macro "__sub_PIPSQUEAK_Double_Background_SL2_ROIs" {


       // Measuring ROIs
           //Finding PNNs with Analyze Particles

second_image_tif = second_image+".tif";

roi_count = roiManager("count");
if (roi_count>0) {
	roiManager("Delete");
	}

selectWindow(second_image+"-1.tif");
roiManager("Show All");
roiManager("Show All with labels");

run("Clear Results");
wait(200);
setAutoThreshold("Default dark");
run("Threshold...");
wait(200);
setThreshold(DL2_lower*DL2_set_intensity_low_threshold, DL2_set_intensity_high_threshold);
wait(200);
makeRectangle(0, 0, 0, 0);
run("Analyze Particles...", "size=DL2_set_low_particlesize-DL2_set_high_particlesize circularity=DL2_set_low_circularity-DL2_set_high_circularity clear include add");
wait(200);
selectWindow("Threshold");
resetThreshold();
run("Close");
roiManager("Measure");

           //Making square ROIs from Particles

wait(500);
DL2_add_squares=roiManager("count"); 
if (DL2_add_squares==0) {

	waitForUser("Oops", "We didn't see any staining here. Try adjusting the Cell Detection Threshold settings in the next step... ");

} else {
	array=newArray(DL2_add_squares); 
	for(i=0; i<DL2_add_squares;i++) { 
		roiManager("Select", 0);
        	run("Specify...", "centered scaled");
        	run("Enlarge...", "enlarge=DL2_set_roi_enlargement");
        	roiManager("Add");
        	roiManager("Select", 0);
        	roiManager("Delete");
		} 
	}

if (import_type==6) {
	wait(300);
} else {

	setTool("rectangle");
	selectWindow(second_image_tif);
	run("Revert");
	roiManager("Show All");
	roiManager("Show All with labels");

	SL2_set_intensity_low_threshold_old = DL2_set_intensity_low_threshold;
	SL2_set_low_particlesize_old = DL2_set_low_particlesize; 
	SL2_set_high_particlesize_old = DL2_set_high_particlesize;

	Dialog.create("Adjust Cell Detection Threshold");
	items = newArray("Yes, rerun cell detection with these new settings.", "No, let me add / delete ROIs by hand.", "I like the ROIs as they are. Lets move on to double-labeled staining.");
	
	Dialog.addSlider("Threshold of Detection:", (DL2_set_intensity_low_threshold*0.1), (DL2_set_intensity_low_threshold*2), DL2_set_intensity_low_threshold);
	Dialog.addSlider("Smallest Cell Detected:", 0.0, 1000, DL2_set_low_particlesize);
	Dialog.addSlider("Largest Cell Detected:", 0.0, 100000, DL2_set_high_particlesize);

	Dialog.addRadioButtonGroup("Would you like to change the "+second_stain_type+" cell detection threshold settings?", items, 3, 1, "Yes, rerun cell detection with these new settings.");
	Dialog.show;
	DL2_set_intensity_low_threshold = Dialog.getNumber();
	DL2_set_low_particlesize = Dialog.getNumber();
	DL2_set_high_particlesize = Dialog.getNumber();
	choice = Dialog.getRadioButton;

	if (choice=="No, let me add / delete ROIs by hand." && SL2_set_intensity_low_threshold_old==DL2_set_intensity_low_threshold && SL2_set_low_particlesize_old==DL2_set_low_particlesize && SL2_set_high_particlesize_old==DL2_set_high_particlesize)  {
		waitForUser("How Does That Look?", "Here is your chance to adjust the ROIs to better identify PNNs. Try adding or deleting ROIs in the ROI manager. **THEN** press OK.");
		}
	
	if (choice=="Yes, rerun cell detection with these new settings." || SL2_set_intensity_low_threshold_old != DL2_set_intensity_low_threshold || SL2_set_low_particlesize_old != DL2_set_low_particlesize || SL2_set_high_particlesize_old != DL2_set_high_particlesize) {
				
		run("__sub_PIPSQUEAK_Double_Background_SL2_ROIs");
		}

	if (choice=="I like the ROIs as they are. Lets move on to double-labeled staining." && SL2_set_intensity_low_threshold_old==DL2_set_intensity_low_threshold && SL2_set_low_particlesize_old==DL2_set_low_particlesize && SL2_set_high_particlesize_old==DL2_set_high_particlesize) {
		wait(10);
		}
	}


selectWindow(second_image_tif);
run("Close");
	

//saving SL2 ROI overlay

SL2_save_ROIs=roiManager("count");
array=newArray(SL2_save_ROIs);
for(i=0; i<SL2_save_ROIs; i++) {
	array[i] = i;
	}
roiManager("Select", array);
roiManager("Save", subDir+name+"_SL2_ROIoverlay.zip");
	

//Measuring ROIs	

run("Clear Results");
DL2_measure_squares=0;
DL2_measure_squares =roiManager("count"); 
array=newArray(DL2_measure_squares); 
for(i=0; i<DL2_measure_squares;i++) { 
        array[i] = i; 
	}
roiManager("Select", array);
roiManager("Measure");
roiManager("Show All");
roiManager("Show All with labels");

DL2_m=0;
DL2_means=0;
DL2_m = nResults;
DL2_means = newArray(DL2_m);
run("Select None");
    for (i=0; i<DL2_m; i++) {
      DL2_means[i] = getResult('Mean', i);
    }
run("Select None");
    for (i=0; i<DL2_m; i++) {
      setResult("Background", i, DL2_lower);
      setResult("Mean-Background", i, DL2_means[i]-DL2_lower);
    }
setResult("File Name", 0, name);
updateResults();

DL2_m2 = 0;
DL2_avgmeans = 0;
DL2_m2 = nResults;
DL2_avgmeans = newArray(DL2_m2);
run("Select None");
    for (i=0; i<DL2_m2; i++) {
     DL2_avgmeans[i] = getResult('Mean-Background', i);
    }
Array.getStatistics(DL2_avgmeans, min, max, mean, stdDev);
print(second_stain_type+" Mean Intensity = "+mean);


DL2_numberStains=0;
DL2_numberStains=getValue("results.count");
print("Number of "+second_stain_type+" Stained Cells = "+DL2_numberStains);

n_sl2 = nResults;
area_sl2 = newArray(n_sl2);
mean_sl2 = newArray(n_sl2);
stddev_sl2 = newArray(n_sl2);
min_sl2 = newArray(n_sl2);
max_sl2 = newArray(n_sl2);
bkgd_sl2 = newArray(n_sl2);
meanbkgd_sl2 = newArray(n_sl2);
print("\n");
print("Individual "+second_stain_type+" cell data:");
print("Cell# Area Mean StdDev Min Max Background Mean-Background");
for (i=0; i<n_sl2; i++) {
	area_sl2[i] = getResult('Area', i);
	mean_sl2[i] = getResult('Mean', i);
	stddev_sl2[i] = getResult('StdDev', i);
	min_sl2[i] = getResult('Min', i);
	max_sl2[i] = getResult('Max', i);
	bkgd_sl2[i] = getResult('Background', i);
	meanbkgd_sl2[i] = getResult('Mean-Background', i);
	print(i+1+" "+area_sl2[i]+" "+mean_sl2[i]+" "+stddev_sl2[i]+" "+min_sl2[i]+" "+max_sl2[i]+" "+bkgd_sl2[i]+" "+meanbkgd_sl2[i]);
	}



selectWindow(second_image+"-1.tif");
run("Close");

	// Saving data

name = series_name+" "+second_stain_type+".txt"; 
saveAs("Measurements", subDir+name);
print("\n"); 
print("Results saved as: "+subDir+name);


//\\//\\//\\//\\//\\//\\//\\

//Double labeled cell identification

first_image_tif = first_image+"-2.tif";
second_image_tif = second_image+"-2.tif";

run("Clear Results");
//selectWindow(second_image_tif);
selectWindow(first_image_tif);

roiManager("Show All");
roiManager("Show All with labels");

setAutoThreshold("Default dark");
run("Threshold...");
wait(200);
//setThreshold(DL2_lower, DL2_set_intensity_high_threshold); 
setThreshold(DL1_lower*DL1_set_intensity_low_threshold, DL1_set_intensity_high_threshold);

add_double_re=roiManager("count");

array=newArray(add_double_re); 
for(i=0; i<add_double_re;i++) { 
	roiManager("Select", i);
	//run("Analyze Particles...", "size=DL2_set_low_particlesize-DL2_set_high_particlesize circularity=0-DL2_set_high_circularity include add");
	run("Analyze Particles...", "size=DL1_set_low_particlesize-DL1_set_high_particlesize circularity=DL1_set_low_circularity-DL1_set_high_circularity include add");
	wait(200);
	}

wait(200);
roiManager("Delete");

selectWindow("Threshold");
resetThreshold();

run("Clear Results");
/*
selectWindow(first_image_tif);

roiManager("Show All");
roiManager("Show All with labels");


setAutoThreshold("Default dark");
run("Threshold...");
wait(200);
setThreshold(DL1_lower*DL1_set_intensity_low_threshold, DL1_set_intensity_high_threshold); 


add_double_re=roiManager("count");
array=newArray(add_double_re); 
for(i=0; i<add_double_re;i++) { 
	roiManager("Select", 0);
	run("Analyze Particles...", "size=DL1_set_low_particlesize-DL1_set_high_particlesize circularity=DL1_set_low_circularity-DL1_set_high_circularity include add");
	roiManager("Select", 0);
	roiManager("Delete");
	wait(200);
	
	}

wait(200);


selectWindow("Threshold");
resetThreshold();
*/
DL_add_circles = roiManager("count");
array=newArray(DL_add_circles); 
for(i=0; i<DL_add_circles;i++) { 
	roiManager("Select", 0);
	run("Specify...", "oval centered scaled");
	run("Enlarge...", "enlarge=DL1_set_roi_enlargement");
	roiManager("Add");
	roiManager("Select", 0);
	roiManager("Delete");
	} 

if (import_type==6) {
	wait(300);
} else {
	setTool("oval");

	Dialog.create("Which image?");
	items = newArray("Merged image", second_stain_type+" image");
	Dialog.addRadioButtonGroup("Which image would you like to see to check double-labeled "+first_stain_type+" cells?", items, 2, 1, "Merged image");
	Dialog.show;
	choice = Dialog.getRadioButton;
	if (choice=="Merged image") {
		open(series_name+"_"+merged_suffix+".tif");
		merged_image = getTitle;
		roiManager("Show All");
		roiManager("Show All with labels");
		waitForUser("How Does That Look?", "Here is your chance to adjust the ROIs to better identify PNNs. Try adding or deleting ROIs in the ROI manager. **THEN** press OK.");
		selectWindow(merged_image);
		run("Close");
		}
	if (choice==second_stain_type+" image") {
		open(series_name+"_"+second_suffix+".tif");
		second_image_DL = getTitle;
		roiManager("Show All");
		roiManager("Show All with labels");
		waitForUser("How Does That Look?", "Here is your chance to adjust the ROIs to better identify PNNs. Try adding or deleting ROIs in the ROI manager. **THEN** press OK.");
		selectWindow(second_image_DL);
		run("Close");
		}
	}


//saving DL1 ROI overlay

DL1_save_ROIs=roiManager("count");
array=newArray(DL1_save_ROIs);
for(i=0; i<DL1_save_ROIs; i++) {
	array[i] = i;
	}
roiManager("Select", array);
roiManager("Save", subDir+name+"_DL1_ROIoverlay.zip");
	
//\\\\\\\\\\\\\
//measure double labeled ROIs (image 1)

run("Clear Results");
DL_ROIs=0;
DL_ROIs =roiManager("count"); 
array=newArray(DL_ROIs); 
for(i=0; i<DL_ROIs;i++) { 
        array[i] = i; 
	}
roiManager("Select", array);
roiManager("Measure");
roiManager("Show All");
roiManager("Show All with labels");

DL_ROIs1_m=0;
DL_ROIs1_means=0;
DL_ROIs1_m = nResults;
DL_ROIs1_means = newArray(DL_ROIs1_m);
run("Select None");
    for (i=0; i<DL_ROIs1_m; i++) {
      DL_ROIs1_means[i] = getResult('Mean', i);
    }
run("Select None");
    for (i=0; i<DL_ROIs1_m; i++) {
     setResult("Background", i, DL1_lower);
     setResult("Mean-Background", i, DL_ROIs1_means[i]-DL1_lower);
    }
setResult("File Name", 0, name);
updateResults();

DL_ROIs1_m2 = 0;
DL_ROIs1_avgmeans = 0;
DL_ROIs1_m2 = nResults;
DL_ROIs1_avgmeans = newArray(DL_ROIs1_m2);
run("Select None");
    for (i=0; i<DL_ROIs1_m2; i++) {
     DL_ROIs1_avgmeans[i] = getResult('Mean-Background', i);
    }
Array.getStatistics(DL_ROIs1_avgmeans, min, max, mean, stdDev);
print("\n");
print("Double-labeled "+first_stain_type+" Mean Intensity = "+mean);


DL_ROIs1_numberStains=0;
DL_ROIs1_numberStains=getValue("results.count");
print("Number of Double-labeled "+first_stain_type+" Cells = "+DL_ROIs1_numberStains);

n_dl1 = nResults;
area_dl1 = newArray(n_dl1);
mean_dl1 = newArray(n_dl1);
stddev_dl1 = newArray(n_dl1);
min_dl1 = newArray(n_dl1);
max_dl1 = newArray(n_dl1);
bkgd_dl1 = newArray(n_dl1);
meanbkgd_dl1 = newArray(n_dl1);
print("\n");
print("Double-labeled "+first_stain_type+" cell data:");
print("Cell# Area Mean StdDev Min Max Background Mean-Background");
for (i=0; i<n_dl1; i++) {
	area_dl1[i] = getResult('Area', i);
	mean_dl1[i] = getResult('Mean', i);
	stddev_dl1[i] = getResult('StdDev', i);
	min_dl1[i] = getResult('Min', i);
	max_dl1[i] = getResult('Max', i);
	bkgd_dl1[i] = getResult('Background', i);
	meanbkgd_dl1[i] = getResult('Mean-Background', i);
	print(i+1+" "+area_dl1[i]+" "+mean_dl1[i]+" "+stddev_dl1[i]+" "+min_dl1[i]+" "+max_dl1[i]+" "+bkgd_dl1[i]+" "+meanbkgd_dl1[i]);
	}

	// Saving data

name = series_name+" "+first_stain_type+" double-label.txt"; 
saveAs("Measurements", subDir+name);
print("\n"); 
print("Results saved as: "+subDir+name);


//\\\\\\\\\\\\\\\
//measure double labeled ROIs (image 2)

run("Clear Results");
selectWindow(second_image_tif);

//waitForUser("Pause5");

roiManager("Show All");
roiManager("Show All with labels");
roiManager("Deselect");

DL2b_set_roi_enlargement = (DL2_set_roi_enlargement*5);

DL_add_squares = roiManager("count");
array=newArray(DL_add_squares); 
for(i=0; i<DL_add_squares;i++) { 
	roiManager("Select", 0);
	run("Specify...", "centered scaled");
	run("Enlarge...", "enlarge=DL2b_set_roi_enlargement");
	roiManager("Add");
	roiManager("Select", 0);
	roiManager("Delete");
	} 


if (import_type==6) {
	wait(300);
} else {
	setTool("rectangle");

	Dialog.create("Which image?");
	items = newArray("Merged image", first_stain_type+" image", "None. Proceed without check.");
	Dialog.addRadioButtonGroup("Which image would you like to see to check double-labeled "+second_stain_type+" cells?", items, 3, 1, "None. Proceed without check.");
	Dialog.show;
	choice = Dialog.getRadioButton;
	if (choice=="Merged image") {
		open(series_name+"_"+merged_suffix+".tif");
		merged_image = getTitle;
		roiManager("Show All");
		roiManager("Show All with labels");
		waitForUser("How Does That Look?", "Here is your chance to adjust the ROIs to better identify PNNs. Try adding or deleting ROIs in the ROI manager. **THEN** press OK.");
		selectWindow(merged_image);
		run("Close");
		}
	if (choice==first_stain_type+" image") {
		open(series_name+"_"+first_suffix+".tif");
		first_image_DL = getTitle;
		roiManager("Show All");
		roiManager("Show All with labels");
		waitForUser("How Does That Look?", "Here is your chance to adjust the ROIs to better identify PNNs. Try adding or deleting ROIs in the ROI manager. **THEN** press OK.");
		selectWindow(first_image_DL);
		run("Close");
		}
	if (choice=="None. Proceed without check.") {
		wait(10);
		}
	}

//saving DL2 ROI overlay

DL2_save_ROIs=roiManager("count");
array=newArray(DL2_save_ROIs);
for(i=0; i<DL2_save_ROIs; i++) {
	array[i] = i;
	}
roiManager("Select", array);
roiManager("Save", subDir+name+"_DL2_ROIoverlay.zip");


//measure double labeled ROIs (image 2)

DL_ROIs=0;
DL_ROIs =roiManager("count"); 
array=newArray(DL_ROIs); 
for(i=0; i<DL_ROIs;i++) { 
	array[i] = i; 
	}
roiManager("Select", array);
roiManager("Measure");
roiManager("Show All");
roiManager("Show All with labels");

DL_ROIs2_m=0;
DL_ROIs2_means=0;
DL_ROIs2_m = nResults;
DL_ROIs2_means = newArray(DL_ROIs2_m);
run("Select None");
for (i=0; i<DL_ROIs2_m; i++) {
	DL_ROIs2_means[i] = getResult('Mean', i);
	}
run("Select None");
for (i=0; i<DL_ROIs2_m; i++) {
	setResult("Background", i, DL2_lower);
	setResult("Mean-Background", i, DL_ROIs2_means[i]-DL2_lower);
	}

setResult("File Name", 0, name);
updateResults();

DL_ROIs2_m2 = 0;
DL_ROIs2_avgmeans = 0;
DL_ROIs2_m2 = nResults;
DL_ROIs2_avgmeans = newArray(DL_ROIs2_m2);
run("Select None");
for (i=0; i<DL_ROIs2_m2; i++) {
	DL_ROIs2_avgmeans[i] = getResult('Mean-Background', i);
	}

Array.getStatistics(DL_ROIs2_avgmeans, min, max, mean, stdDev);
print("\n");
print("Double-labeled "+second_stain_type+" Mean Intensity = "+mean);


DL_ROIs2_numberStains=0;
DL_ROIs2_numberStains=getValue("results.count");
print("Number of Double-labeled "+second_stain_type+" Cells = "+DL_ROIs2_numberStains);

n_dl2 = nResults;
area_dl2 = newArray(n_dl2);
mean_dl2 = newArray(n_dl2);
stddev_dl2 = newArray(n_dl2);
min_dl2 = newArray(n_dl2);
max_dl2 = newArray(n_dl2);
bkgd_dl2 = newArray(n_dl2);
meanbkgd_dl2 = newArray(n_dl2);
print("\n");
print("Double-labeled "+second_stain_type+" cell data:");
print("Cell# Area Mean StdDev Min Max Background Mean-Background");
for (i=0; i<n_dl2; i++) {
	area_dl2[i] = getResult('Area', i);
	mean_dl2[i] = getResult('Mean', i);
	stddev_dl2[i] = getResult('StdDev', i);
	min_dl2[i] = getResult('Min', i);
	max_dl2[i] = getResult('Max', i);
	bkgd_dl2[i] = getResult('Background', i);
	meanbkgd_dl2[i] = getResult('Mean-Background', i);
	print(i+1+" "+area_dl2[i]+" "+mean_dl2[i]+" "+stddev_dl2[i]+" "+min_dl2[i]+" "+max_dl2[i]+" "+bkgd_dl2[i]+" "+meanbkgd_dl2[i]);
	}

	// Saving data

name = series_name+" "+second_stain_type+" double-label.txt"; 
saveAs("Measurements", subDir+name);
selectWindow("Log");
saveAs("Text", dir+"/All_Results.txt");
print("\n"); 
print("Results saved as: "+subDir+name);

//waitForUser("Pause");

selectWindow(first_image_tif);
run("Close");
selectWindow(second_image_tif);
run("Close");	

///////////////////////////////////

	// Closing project

clear_ROIs=roiManager("count"); 
array=newArray(clear_ROIs); 

for(i=0; i<clear_ROIs; i++) {
	array[i] = i;
	}
if(clear_ROIs>0){
	roiManager("Select", array); 
	roiManager("Delete");
}else{
	wait(10);
	}

selectWindow("ROI Manager");
run("Close");
run("Clear Results");

//if (import_type==6) {
//	run("__sub_PIPSQUEAK_OpenNext_Double");
//	} else {

	Dialog.create("Next image?");
	items = newArray("Open next image for analysis.", "Return to main menu.");
	Dialog.addRadioButtonGroup("What would you like to do next?", items, 2, 1, "Open next image for analysis.");
	Dialog.show;
	choice = Dialog.getRadioButton;
	if (choice=="Return to main menu.") {
		run("PIPSQUEAK");
	} else {
//		run("__sub_PIPSQUEAK_OpenNext_Double");
//SEE NOT IN "__SUB_PIPSQUEAK_OPENNEXT_DOUBLE" ABOUT REMOVAL OF AUTO OPEN FUNCTION.

		run("__sub_PIPSQUEAK_Open_Double");
		}
	}
		
}

/////////////////////////////