////////////////////////////////////////////////////////////////
/*									
	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 = 9999999;
var set_low_circularity = 0.02;
var set_high_circularity = 1.00;
var set_roi_enlargement_single = 6.00;

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 first_suffix = 1;
var second_suffix = 3;
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 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 = 999999;
var DL2_set_low_circularity = 0.02;
var DL2_set_high_circularity = 1.00;
var DL2_set_roi_enlargement = 6.00;

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){
	print("PIPSQUEAK! v0.0943 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);
	waitForUser("PIPSQUEAK Beta version 0.944, Aug 8, 2016 \n \n 0.90 CHANGE LOG: \n Data log output format revised for easier export \n Started logging changes \n \n 0.91 CHANGE LOG: \n Lowered PV pixel detection requirement \n Removed Double-label Open Next Functionality \n Bugs Squashed \n \n 0.92 CHANGE LOG: \n Splines Reticulated \n Llamas Herded \n \n 0.93 CHANGE LOG: \n Don't ask about 0.93-0.942 \n \n 0.943 CHANGE LOG: \n Lots of good things. Big changes. \n Re-strategized ROI seeding for double-labeling \n Added user choice for ROI enlargement \n Started saving ROI overlays in directory \n Raw images retained for double-label double checking in semiauto mode. \n \n 0.944 CHANGE LOG: \n Fix bug in saving single-label ROIs.");

	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, "Single label intensity analysis.");
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("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();;
		//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...");

roiManager("Show All");
roiManager("Show All with labels");
makeRectangle(475, 10, 30, 30);
roiManager("Add");
makeRectangle(475, 104, 30, 30);
roiManager("Add");
makeRectangle(475, 198, 30, 30);
roiManager("Add");
makeRectangle(475, 292, 30, 30);
roiManager("Add");
makeRectangle(475, 390, 30, 30)
roiManager("Add");
makeRectangle(475, 475, 30, 30);
roiManager("Add");
makeRectangle(407, 475, 30, 30);
roiManager("Add");
makeRectangle(324, 475, 30, 30);
roiManager("Add");
makeRectangle(246, 475, 30, 30);
roiManager("Add");
makeRectangle(167, 475, 30, 30);
roiManager("Add");
makeRectangle(89, 475, 30, 30);
roiManager("Add");
makeRectangle(10, 475, 30, 30);
roiManager("Add");
makeRectangle(10, 390, 30, 30);
roiManager("Add");
makeRectangle(10, 292, 30, 30);
roiManager("Add");
makeRectangle(10, 198, 30, 30);
roiManager("Add");
makeRectangle(10, 104, 30, 30);
roiManager("Add");
makeRectangle(10, 10, 30, 30);
roiManager("Add");
makeRectangle(89, 10, 30, 30);
roiManager("Add");
makeRectangle(167, 10, 30, 30);
roiManager("Add");
makeRectangle(246, 10, 30, 30);
roiManager("Add");
makeRectangle(324, 10, 30, 30);
roiManager("Add");
makeRectangle(407, 10, 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

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();
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 PNNs here. Here is your chance to adjust the ROIs to better identify PNNs. Try adding ROIs in the ROI manager. **THEN** press OK.");
	//setTool("point");
	makePoint(0, 0);
	//setTool("rectangle");
	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 {
	if (import_type==2) {		
		run("Duplicate...", " ");
		selectWindow(full_name);
		run("Revert", " ");
		
		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");
		}
	if (import_type==1) {
		selectWindow(name);
		run("Z Project...", "projection=[Sum Slices]");
		selectWindow(name);
		close(name);
		selectWindow(full_name+"-1");
		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(full_name+"-1");
		close(full_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");

		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);
		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;

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

selectWindow(first_image_tif);

makeRectangle(475, 10, 30, 30);
roiManager("Add");
makeRectangle(475, 104, 30, 30);
roiManager("Add");
makeRectangle(475, 198, 30, 30);
roiManager("Add");
makeRectangle(475, 292, 30, 30);
roiManager("Add");
makeRectangle(475, 390, 30, 30);
roiManager("Add");
makeRectangle(475, 475, 30, 30);
roiManager("Add");
makeRectangle(407, 475, 30, 30);
roiManager("Add");
makeRectangle(324, 475, 30, 30);
roiManager("Add");
makeRectangle(246, 475, 30, 30);
roiManager("Add");
makeRectangle(167, 475, 30, 30);
roiManager("Add");
makeRectangle(89, 475, 30, 30);
roiManager("Add");
makeRectangle(10, 475, 30, 30);
roiManager("Add");
makeRectangle(10, 390, 30, 30);
roiManager("Add");
makeRectangle(10, 292, 30, 30);
roiManager("Add");
makeRectangle(10, 198, 30, 30);
roiManager("Add");
makeRectangle(10, 104, 30, 30);
roiManager("Add");
makeRectangle(10, 10, 30, 30);
roiManager("Add");
makeRectangle(89, 10, 30, 30);
roiManager("Add");
makeRectangle(167, 10, 30, 30);
roiManager("Add");
makeRectangle(246, 10, 30, 30);
roiManager("Add");
makeRectangle(324, 10, 30, 30);
roiManager("Add");
makeRectangle(407, 10, 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);
//print("std1 = "+mean);
Array.sort(DL1_bkgd_std);
//Array.print(DL1_bkgd_std);
DL1_bksd_high_trim = Array.trim(DL1_bkgd_std, 15);
//Array.print(DL1_bksd_high_trim);
Array.getStatistics(DL1_bksd_high_trim, min, max, mean, stdDev);
//print("std2 = "+mean);
Array.reverse(DL1_bksd_high_trim);
//Array.print(DL1_bkgd_high_trim);
DL1_bksd_low_trim = Array.trim(DL1_bksd_high_trim, 7);
//Array.print(DL1_bkgd_low_trim);
Array.getStatistics(DL1_bksd_low_trim, min, max, mean, stdDev);
//print("mean3 = "+mean);
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");
	

       // Measuring ROIs
           //Finding PNNs with Analyze Particles

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();
roiManager("Measure");

           //Making circular ROIs from Particles

wait(500);
DL1_add_circles=roiManager("count"); 
if (DL1_add_circles==0) {
		//run("Duplicate...", " ");
		//selectWindow(full_name);
		//run("Revert", " ");
		waitForUser("Oops", "We didn't see any staining here. Here is your chance to adjust the ROIs to better identify the stain. Try adding ROIs in the ROI manager. **THEN** press OK.");
		//selectWindow(full_name);
		//run("Close");
	} 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 {
	//run("Duplicate...", " ");
	selectWindow(first_image_tif);
	run("Revert");
	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_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", dir+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", dir+name);
print("\n"); 
print("Results saved as: "+dir+name);

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

//Second Image
	// Selecting Background


run("Clear Results");

run("ROI Manager...");
roiManager("Show All");
roiManager("Show All with labels");

selectWindow(second_image_tif);

makeRectangle(475, 10, 30, 30);
roiManager("Add");
makeRectangle(475, 104, 30, 30);
roiManager("Add");
makeRectangle(475, 198, 30, 30);
roiManager("Add");
makeRectangle(475, 292, 30, 30);
roiManager("Add");
makeRectangle(475, 390, 30, 30);
roiManager("Add");
makeRectangle(475, 475, 30, 30);
roiManager("Add");
makeRectangle(407, 475, 30, 30);
roiManager("Add");
makeRectangle(324, 475, 30, 30);
roiManager("Add");
makeRectangle(246, 475, 30, 30);
roiManager("Add");
makeRectangle(167, 475, 30, 30);
roiManager("Add");
makeRectangle(89, 475, 30, 30);
roiManager("Add");
makeRectangle(10, 475, 30, 30);
roiManager("Add");
makeRectangle(10, 390, 30, 30);
roiManager("Add");
makeRectangle(10, 292, 30, 30);
roiManager("Add");
makeRectangle(10, 198, 30, 30);
roiManager("Add");
makeRectangle(10, 104, 30, 30);
roiManager("Add");
makeRectangle(10, 10, 30, 30);
roiManager("Add");
makeRectangle(89, 10, 30, 30);
roiManager("Add");
makeRectangle(167, 10, 30, 30);
roiManager("Add");
makeRectangle(246, 10, 30, 30);
roiManager("Add");
makeRectangle(324, 10, 30, 30);
roiManager("Add");
makeRectangle(407, 10, 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");
	}

       // Measuring ROIs
           //Finding PNNs with Analyze Particles

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();
roiManager("Measure");

           //Making square ROIs from Particles

wait(500);
DL2_add_squares=roiManager("count"); 
if (DL2_add_squares==0) {
		//run("Duplicate...", " ");
		//selectWindow(full_name);
		//run("Revert", " ");
		waitForUser("Oops", "We didn't see any staining here. Here is your chance to adjust the ROIs to better identify the stain. Try adding ROIs in the ROI manager. **THEN** press OK.");
		//selectWindow(full_name);
		//run("Close");
	} 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 {
	//run("Duplicate...", " ");
	selectWindow(second_image_tif);
	run("Revert", " ");
	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_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", dir+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]);
    }

//waitForUser("Pause");

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

	// Saving data

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


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

//Double labeled cell identification

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

//new
//______

run("Clear Results");
selectWindow(second_image_tif);
//waitForUser("Pause0");
roiManager("Show All");
roiManager("Show All with labels");


setAutoThreshold("Default dark");
run("Threshold...");
wait(200);
setThreshold(DL2_lower*DL2_set_intensity_low_threshold, DL2_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=DL2_set_low_circularity-DL2_set_high_circularity include add");
	wait(200);
	}

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

selectWindow("Threshold");
resetThreshold();

//waitForUser("Pause1");

//_______
//end new

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);
	}

//waitForUser("Pause");

wait(200);


selectWindow("Threshold");
resetThreshold();

if (import_type==6) {
	wait(300);
} else {
	//run("Duplicate...", " ");
	//selectWindow(first_image_tif);
	//run("Revert", " ");
	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.");
	}
	
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");
	} 

//waitForUser("Pause3");

//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", dir+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", dir+name);
print("\n"); 
print("Results saved as: "+dir+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*1.667);

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");
	} 
//waitForUser("Pause6");

if (import_type==6) {
	wait(300);
} else {
	//run("Duplicate...", " ");
	//selectWindow(first_image_tif);
	//run("Revert", " ");
	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_tif);
	//run("Close");

//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", dir+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", dir+name);
selectWindow("Log");
saveAs("Text", dir+"/All_Results.txt");
print("\n"); 
print("Results saved as: "+dir+name);

//waitForUser("Pause");

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

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

	// Closing project

//open(series_name+"_"+second_suffix+".tif");

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(50);
			}
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");
			}
		}
		
}

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