# MIT License # Copyright (c) 2017 dcolam from __future__ import with_statement, division import sys, time, os, traceback, random, time, ConfigParser, csv, math, fnmatch, locale from ij import IJ, ImagePlus, WindowManager, CompositeImage from org.sqlite import SQLiteConfig from java.lang import Class, System, Double from java.awt import Color from loci.plugins.util import WindowTools as wt from java.sql import DriverManager, SQLException, Types, Statement from ij.gui import GenericDialog, WaitForUserDialog, Roi, ShapeRoi, Overlay from ij.process import ImageProcessor, AutoThresholder from ij.plugin import ChannelSplitter, ImageCalculator, RGBStackMerge, ZProjector, Duplicator, StackEditor, \ Concatenator, RoiEnlarger, RoiRotator from sc.fiji.analyzeSkeleton import AnalyzeSkeleton_ from ij.plugin import ZProjector as zp from fiji.stacks import Hyperstack_rearranger as hyr from ij.plugin.frame import RoiManager from ij.plugin.filter import EDM, ParticleAnalyzer, Calibrator, Filler, Analyzer, PlugInFilterRunner from ij.measure import Measurements as ms from loci.plugins import BF from ij.plugin.filter import ThresholdToSelection as tts from ij.measure import ResultsTable, Calibration from ij.io import RoiDecoder import org.scijava.command.Command #@File(label = "Select an input folder with the images to analyze", value=expath, required=true, style="directory", persist=true) expath #@String (label="Name of Experiment") expName #@Boolean(label="Headless?", value=True) headless #@Boolean(label="Set Measurements", value=True) measure #@String (label="What visualisation color is preferred?", choices= {"Black and White", "Red", "Over/Under"}) c def find(name, path): result = [] for root, dirs, files in os.walk(path): # print root if name in files: result.append(os.path.join(root, name)) return result class config(object): #ConfigParser-handler object to read and write into the config-file def __init__(self, testmode=False): """ Initiates a config-object, no args needed iniPath = Default path in the FIJI-directory newiniPath = Path to ini.cfp copy in the Outputpath section_dict = stores parameters in different sections """ self.cp = ConfigParser.ConfigParser() self.iniPath = os.path.join(dir_path, 'ini.cfg') if not testmode: if not os.path.isfile(self.iniPath): self.setDefault() self.cp.read(self.iniPath) self.newiniPath = self.iniPath else: self.cp.read(self.iniPath) self.newiniPath = os.path.join(self.cp.get("ChannelOptions", "expath"), "Particle_Analysis","Output_Table", "%s.cfg"%expName) self.section_dict = {} self.section_dict_old = {} def update(self, section, vars_dict): self.section_dict[section] = vars_dict def writeIni(self, default=False): """ Write into the ini.cfg file """ if default: section_dict = self.section_dict_default else: section_dict = self.section_dict for k, v in section_dict.items(): if default or k not in self.cp.sections(): self.cp.add_section(k) for key, value in v.items(): self.cp.set(k, key, value) if default: with open(self.iniPath, 'wb') as configfile: self.cp.write(configfile) if not default: self.newiniPath = os.path.join(self.cp.get("ChannelOptions", "expath"), "Particle_Analysis", "Output_Table", "%s.cfg"% expName) with open(self.newiniPath, "wb") as configfile: self.cp.write(configfile) with open(self.iniPath, "wb") as configfile: self.cp.write(configfile) def readIni(self, test=False, testPath=""): """ Retrieve information from ini.cfg file """ if not test: if self.iniPath == self.newiniPath: self.cp.read(self.iniPath) else: self.cp.read(self.iniPath) elif testPath: print "Read ini-file in testmode..." self.cp.read(testPath) for each_section in self.cp.sections(): vars_dict = {} for (each_key, each_val) in self.cp.items(each_section): vars_dict[each_key] = each_val self.section_dict_old[each_section] = vars_dict def setDefault(self, testMode=False): """ Creates a Default ini.cfg file """ section_dict = {"SelectionManager": {"manSel": "0", "autSel": "1", "allSelected": "True"}, "ManualSelection": {"SelName": "Selection2", "SaveRoi": "True", "customRoi": "False"}, "AutomaticSelection": {"SelName2": "Selection1", "SaveRoi2": "True", "maskBool_list": "[True, True, False, True]", "nOfIncrements": "4", "incrementslengths": "50", "inverseBool": "True", "backgroundRadius": "50", "sigma1": "5", "binMethod1": "Huang", "sizeA1": "1000", "sizeB2": "200000", "circA1": "0.0", "circB2": "0.5", "enlarge1": "3.5", "spineBool": "False", "minLength": "0", "maxLength": "0", "spineSizeMin": "0", "spineSizeMax": "0", "spineCircMin": "0", "spineCircMax": "0"}, "ChannelOptions": { "expath": "Path/to/input/folder/here", "delimiter": "_", "zStackBool": "True", "ext": ".lsm", "c1Name": "C1", "c1Opt_boolList": "[False, False, False, False]", "backgroundRadc1": "0", "sigmaC1": "0", "c2Name": "C2", "c2Opt_boolList": "[False, False, False, False]", "backgroundRadc2": "0", "sigmaC2": "0", "c3Name": "C3", "c3Opt_boolList": "[False, False, False, False]", "backgroundRadc3": "0", "sigmaC3": "0", "c4Name": "C4", "c4Opt_boolList": "[False, False, False, False]", "backgroundRadc4": "0", "sigmaC4": "0", "testBool": "False"}, "ParticleAnalysisOptions0": {"paInOutBool_list": "[False, False]", "paColocBool_list": "[False, False, False, False]", "paEnlarge": "0.0", "paSizeA1": "0", "paSizeB1": "0", "paSizeA2": "0", "paSizeB2": "0", "paCirc1": "0", "paCirc2": "1", "paMethod": "Huang", "addMeth1": "", "watershed1": "True", "addMeth2": "", "watershed2": "False"}, "ParticleAnalysisOptions1": {"paInOutBool_list": "[False, False]", "paColocBool_list": "[False, False, False, False]", "paEnlarge": "0", "paSizeA1": "0", "paSizeB1": "0", "paSizeA2": "0", "paSizeB2": "0", "paCirc1": "0", "paCirc2": "1", "paMethod": "Huang", "addMeth1": "", "watershed1": "True", "addMeth2": "", "watershed2": "False"}, "ParticleAnalysisOptions2": {"paInOutBool_list": "[False, False]", "paColocBool_list": "[False, False, False, False]", "paEnlarge": "0", "paSizeA1": "0", "paSizeB1": "0", "paSizeA2": "0", "paSizeB2": "0", "paCirc1": "0", "paCirc2": "1", "paMethod": "Huang", "addMeth1": "", "watershed1": "True", "addMeth2": "", "watershed2": "False"}, "ParticleAnalysisOptions3": {"paInOutBool_list": "[False, False]", "paColocBool_list": "[False, False, False, False]", "paEnlarge": "0", "paSizeA1": "0", "paSizeB1": "0", "paSizeA2": "0", "paSizeB2": "0", "paCirc1": "0", "paCirc2": "1", "paMethod": "Huang", "addMeth1": "", "watershed1": "True", "addMeth2": "", "watershed2": "False"}, "DB_Interface": { "l": '["InternalID", "Timepoint", "Gene", "Region", "", "", "", "", "", "", "", "", "", "", ""]'}} self.section_dict_default = section_dict if not testMode: self.writeIni(default=True) def compare_sections(self, items, section): self.setDefault(True) old = self.section_dict_default[section] test = True new_items = {} for k in old: if k.lower() not in items: test = False items[k] = old[k] return test, items class db_interface(object): #JCDB-driver Interface to communicate and write into a SQLite Database def __init__(self, db_path, image): #Iniates an db_interface object using the title of the first image to retrieve database headers #Creates all SQLite strings templates self.image = image self.image_name = image.name self.d = self.image.dialoger self.overwriteDB = self.d.overwriteDB self.db_path = os.path.join(db_path, "Output.db") self.jdbc_url = "jdbc:sqlite:" + self.db_path self.jdbc_driver = "org.sqlite.JDBC" self.tn_MAIN_PA = "Particle_Analysis_Table" self.tn_MAIN_COLOC = "Coloc_Analysis_Table" self.tn_SUB_PA = "PA_Measurement_Tables" self.tn_SUB_COLOC = "Coloc_Measurement_Tables" self.tn_EXETable = "Execution_Table" self.tn_MAIN_Spines = "Spine_Analysis_Table" self.tn_SUB_Spines = "Spine_Measurement_Table" self.table_dropper_MAIN_PA = "drop table if exists %s;" % self.tn_MAIN_PA self.table_dropper_MAIN_COLOC = "drop table if exists %s;" % self.tn_MAIN_COLOC self.table_dropper_SUB_PA = "drop table if exists %s;" % self.tn_SUB_PA self.table_dropper_SUB_COLOC = "drop table if exists %s;" % self.tn_SUB_COLOC self.table_dropper_EXETable = "drop table if exists %s;" % self.tn_EXETable self.table_dropper_MAIN_Spines = "drop table if exists %s;" % self.tn_MAIN_Spines self.table_dropper_SUB_Spines = "drop table if exists %s;" % self.tn_SUB_Spines self.tc_MAIN_PA = "create table if not exists %s (PA_ID integer primary key, " % self.tn_MAIN_PA self.tc_MAIN_COLOC = "create table if not exists %s (COLOC_ID integer primary key, " % self.tn_MAIN_COLOC self.tc_SUB_PA = "create table if not exists %s (PA_ID, Label, " % self.tn_SUB_PA self.tc_SUB_COLOC = "create table if not exists %s (COLOC_ID, Label, " % self.tn_SUB_COLOC self.tc_MAIN_Spines = "create table if not exists %s (Spine_ID integer primary key, " % self.tn_MAIN_Spines self.tc_SUB_Spines = "create table if not exists %s (Spine_ID, Label, " % self.tn_SUB_Spines self.creators = [] self.record_insertor_SUB_PA = "insert into %s values (?,?, " % self.tn_SUB_PA self.record_insertor_SUB_COLOC = "insert into %s values (?,?, " % self.tn_SUB_COLOC self.record_insertor_SUB_Spines = "insert into %s values (?,?, " % self.tn_SUB_Spines self.record_insertor_MAIN_PA = "" self.record_insertor_MAIN_COLOC = "" self.record_insertor_MAIN_Spines = "" self.descriptor_PA = [] self.descriptor_COLOC = [] self.descriptor_Spines = [] self.raw_descriptor = [] self.describeFilename(self.image_name) self.data = [] self.storePA = [] self.storeColoc = [] self.storeSpines = [] self.coloc = [] self.pa = [] self.spines = [] self.numColocs = 0 self.extractData(image, True) def describeFilename(self, image_name): #Displays a Dialog so that the User can describe title segments to become DB-headers descriptions = image_name.split(self.d.delimiter) l = eval(cp.cp.get("DB_Interface", "l")) d = len(descriptions) - len(l) l += d * [''] if not headless: gd = GenericDialog("Describe the random filename %s as seen in the result-database" % image_name) gd.addMessage("To leave out an option, don't type anything in the corresponding field") for i, x in enumerate(descriptions): gd.addStringField(x, l[i], 10) gd.showDialog() if gd.wasCanceled(): print "User canceled dialog!" sys.exit("Analysis was cancelled") self.raw_descriptor = [gd.getNextString() for i in range(0, len(descriptions))] cp.update("DB_Interface", {"l": str(self.raw_descriptor)}) else: self.raw_descriptor = l self.descriptor_PA += [x for x in self.raw_descriptor if x] + ["Folder", "Slice", "Channel_Name", "Selection", "Selection_Area","Method", "Number_of_Particles"] self.descriptor_COLOC += [x for x in self.raw_descriptor if x] + ["Folder", "Slice", "Channel_Name", "Selection","Selection_Area","Mask_Area", "Second_Channel", "INorOUT","Method2", "Random_Particles","Number_of_Particles"] self.descriptor_Spines += [x for x in self.raw_descriptor if x] + ["Folder", "Selection", "Selection_Area", "Spines_Area", "Area_per_spine", "Number_of_spines", "Spine_per_area"] def getDescription(self): self.tc_MAIN_PA += ", ".join([x for x in self.descriptor_PA if x]) + ");" self.tc_MAIN_COLOC += ", ".join([x for x in self.descriptor_COLOC if x]) + ");" self.tc_MAIN_Spines += ", ".join([x for x in self.descriptor_Spines if x]) + ");" self.record_insertor_MAIN_PA = "insert into %s(" % self.tn_MAIN_PA + ", ".join( [x for x in self.descriptor_PA if x]) + ") values (" + ",".join( ["?" for x in self.descriptor_PA if x]) + ");" self.record_insertor_MAIN_COLOC = "insert into %s(" % self.tn_MAIN_COLOC + ", ".join( [x for x in self.descriptor_COLOC if x]) + ") values (" + ",".join( ["?" for x in self.descriptor_COLOC if x]) + ");" self.record_insertor_MAIN_Spines = "insert into %s(" % self.tn_MAIN_Spines + ", ".join( [x for x in self.descriptor_Spines if x]) + ") values (" + ",".join( ["?" for x in self.descriptor_Spines if x]) + ");" col = [x if not "%" in x else x.replace("%", "perc") for x in self.data_list] col = [x if not "." in x else x.replace(".", "") for x in col] self.tc_SUB_PA += ", ".join( [x for x in col if x != " " and x != ""]) + ",foreign key(PA_ID) references %s(PA_ID));" % self.tn_MAIN_PA self.tc_SUB_COLOC += ", ".join( [x for x in col if x != " " and x != ""]) + ",foreign key(COLOC_ID) references %s(COLOC_ID));" % self.tn_MAIN_COLOC self.tc_SUB_Spines += ", ".join( [x for x in col if x != " " and x != ""]) + ",foreign key(Spine_ID) references %s(Spine_ID));" % self.tn_MAIN_Spines self.record_insertor_SUB_PA += ", ".join(["?" for x in col if x != " " and x != ""]) + ");" self.record_insertor_SUB_COLOC += ", ".join(["?" for x in col if x != " " and x != ""]) + ");" self.record_insertor_SUB_Spines += ", ".join(["?" for x in col if x != " " and x != ""]) + ");" self.creators = [[self.table_dropper_MAIN_PA, self.tc_MAIN_PA], [self.table_dropper_MAIN_COLOC, self.tc_MAIN_COLOC], [self.table_dropper_MAIN_Spines, self.tc_MAIN_Spines], [self.table_dropper_SUB_PA, self.tc_SUB_PA], [self.table_dropper_SUB_COLOC, self.tc_SUB_COLOC], [self.table_dropper_SUB_Spines, self.tc_SUB_Spines]] def closeConn(self): self.dbConn.close() def extractData(self, image, first=False): """ Extract Data from Image-object """ self.dbConn = self.getConnection() filename = image.name.split(self.d.delimiter) data = [filename[i] for i, x in enumerate(self.raw_descriptor) if x] data_pa = [] for i in image.pas: d = i.tp temp = [] for k, v in d.items(): if k == "Channel Name": channelname = v elif k == "Roi Name": selection = v.split("_")[-1] elif k == "Selection_Area": area = v elif k == "Slice": slice_name = v elif k == "Folder": folder = v else: method = k pa = [x.split("\t") for x in v if x] pa = [x for x in pa if x] self.data_list = pa[0] temp.append([k, pa]) for t in temp: description = data + [folder, slice_name, channelname, selection, area] p = [description + [t[0]]] self.pa += p self.storePA.append(t[1]) if i.tp_colocIn: c = i.tp_colocIn self.coloc_extraction(c, description) if i.tp_colocOut: d = i.tp_colocOut self.coloc_extraction(d, description) for sel in image.sm.selections: if sel.spineData: self.spine_extraction(sel.spineData, data) if first: self.getDescription() self.createTables() self.insertData() self.pa = [] self.coloc = [] self.spines = [] self.storePA = [] self.storeColoc = [] self.storeSpines = [] self.closeConn() def spine_extraction(self, spineData, description): self.spines.append(description + [spineData["Folder"], spineData["Selection"], spineData["Selection_Area"], spineData["Spines_Area"], spineData["Area_per_spine"],spineData["Number_of_spines"], spineData["Number_of_spines"] / spineData["Selection_Area"]]) sp = spineData["Columns"] sp = [x.split("\t") for x in sp if x] sp = [x for x in sp if x] self.storeSpines.append(sp) def coloc_extraction(self, c, description): """ Extract Colocaliation information """ l = [] for k, v in c.items(): keys = k.split("_") IN = keys[0] c2 = keys[2] m2 = keys[3] area = v[1] random = v[2] pa = [x.split("\t") for x in v[0] if x] pa = [x for x in pa if x] c = [description + [area, c2, IN, m2, random]] self.coloc += c self.storeColoc.append(pa) l.append([pa] + description + [c2, IN, m2, random]) def createTables(self): """ Creates Tables in DB-file """ self.dbConn = self.getConnection() stmt = self.dbConn.createStatement() try: for i in reversed(self.creators): if self.overwriteDB: stmt.executeUpdate(i[0]) stmt.executeUpdate(i[1]) except SQLException, msg: print msg sys.exit("Analysis was cancelled") def insertData(self): if self.pa: if self.populateTable("pa"): print "Particle Analysis Data inserted successfully" else: print "Particle Analysis Data Insertion failed!!" if self.coloc: if self.populateTable("coloc"): print "Colocalisation Data inserted successfully" else: print "Colocalisation Data Insertion failed!!" if self.spines: if self.populateSpineTable(): print "Spine Analysis Data inserted successfully" else: print "Spine Analysis Data Insertion failed!!" print "*****************************************************" def getConnection(self): """ Get Connection to DB and returns connection handler """ config = SQLiteConfig() config.enforceForeignKeys(True) try: Class.forName(self.jdbc_driver).newInstance() except Exception, msg: print msg sys.exit(-1) try: dbConn = DriverManager.getConnection(self.jdbc_url, config.toProperties()) except SQLException, msg: print msg sys.exit(-1) return dbConn def createPATable(self, keys, paOrColoc): """ Creates Particle Analysis Tables """ if paOrColoc == "pa": record_insertor = self.record_insertor_SUB_PA storedData = self.storePA print "Number of entries: ", len(storedData) if paOrColoc == "coloc": record_insertor = self.record_insertor_SUB_COLOC storedData = self.storeColoc if paOrColoc == "spines": record_insertor = self.record_insertor_SUB_Spines storedData = self.storeSpines try: preppedStmt = self.dbConn.prepareStatement(record_insertor) if storedData: for k, v in enumerate(storedData): for i, c in enumerate(v[1:]): preppedStmt.setInt(1, int(keys[k])) preppedStmt.setInt(2, int(c[0])) for j in range(1, len(c)): if c[j] != "NaN": preppedStmt.setFloat(j + 2, float(c[j])) elif c[j] == "NaN": preppedStmt.setFloat(j + 2, 0.0) preppedStmt.addBatch() self.dbConn.setAutoCommit(False) preppedStmt.executeBatch() self.dbConn.setAutoCommit(True) except SQLException, msg: print msg return False preppedStmt.close() return True def populateSpineTable(self): def is_number(s): try: float(s) return True except ValueError: return False record_insertor = self.record_insertor_MAIN_Spines try: preppedStmt = self.dbConn.prepareStatement(record_insertor, Statement.RETURN_GENERATED_KEYS) for l, x in enumerate(self.spines): for i, c in enumerate(x): if is_number(c): preppedStmt.setFloat(i + 1, float(c)) else: preppedStmt.setString(i + 1, c) preppedStmt.addBatch() self.dbConn.setAutoCommit(False) preppedStmt.executeBatch() self.dbConn.setAutoCommit(True) n = len(self.storeSpines) rs = preppedStmt.getGeneratedKeys() while rs.next(): lastRow = rs.getInt(1) firstRow = lastRow - n keys = [] for k in range(firstRow + 1, lastRow + 1): keys.append(k) preppedStmt.close() self.createPATable(keys, "spines") except SQLException, msg: print msg return False return True def populateTable(self, paOrColoc): """ Populate Tables with Data, either for PA or Coloc """ def is_number(s): try: float(s) return True except ValueError: return False if paOrColoc == "pa": record_insertor = self.record_insertor_MAIN_PA if paOrColoc == "coloc": record_insertor = self.record_insertor_MAIN_COLOC try: preppedStmt = self.dbConn.prepareStatement(record_insertor, Statement.RETURN_GENERATED_KEYS) if paOrColoc == "pa": data_list = self.pa data_content = self.storePA if paOrColoc == "coloc": data_list = self.coloc data_content = self.storeColoc for l, x in enumerate(data_list): nParticles = len(data_content[l]) - 1 for i, c in enumerate(x): if is_number(c): preppedStmt.setFloat(i + 1, float(c)) else: preppedStmt.setString(i + 1, c) preppedStmt.setInt(len(x) + 1, nParticles) preppedStmt.addBatch() self.dbConn.setAutoCommit(False) preppedStmt.executeBatch() self.dbConn.setAutoCommit(True) n = len(data_list) rs = preppedStmt.getGeneratedKeys() while rs.next(): lastRow = rs.getInt(1) firstRow = lastRow - n keys = [] for k in range(firstRow + 1, lastRow + 1): keys.append(k) preppedStmt.close() self.createPATable(keys, paOrColoc) except SQLException, msg: print msg return False return True def writeCSV(self): self.dbConn = self.getConnection() tables = ["Particle_Analysis_Table", "PA_Measurement_Tables", "Coloc_Analysis_Table", "Coloc_Measurement_Tables", "Spine_Analysis_Table", "Spine_Measurement_Table"] try: for t in tables: sqliteString = "Select * from " + t pathCSV = self.db_path.replace("Output.db", "%s.csv" % t) c = self.dbConn.createStatement() data = c.executeQuery(sqliteString) meta = data.getMetaData() count = meta.getColumnCount() with open(pathCSV, "wb+") as f: wr = csv.writer(f, dialect="excel", delimiter=";") columns = [meta.getColumnName(i) for i in range(1, count + 1)] wr.writerow(["SEP=;"]) wr.writerow(columns) while data.next(): row = [data.getString(i) for i in columns] wr.writerow(row) finally: self.dbConn.close() # Channel object to store various information about a specific channel class Channel(object): def __init__(self): self.channel_name = '' self.background_substraction = False self.background_radius = 0 self.gaussian_blur = 0 self.brightness_auto = False self.brightness_man = False self.pa = False self.lowerSize = 0 self.higherSize = 0 self.circ1 = 0 self.circ2 = 0 self.method = '' self.list_1whichChannel = [] self.watershed = False self.pa_inside = False self.pa_outside = False self.pa_enlarge_mask = 0 def setInfo(self, **kwargs): for key, value in kwargs.items(): setattr(self, key, value) # Object to manage manual and automated Selections (displays the Dialog, too) class SelectionManager(object): def __init__(self): self.nManSelections = 0 self.nAutoSelections = 0 self.getOptions() self.selections = [] if self.nManSelections: for i in range(1, self.nManSelections + 1): s = Selection(i, "manual") self.selections.append(s) if self.nAutoSelections: for i in range(1, self.nAutoSelections + 1): s = Selection(i, "automatic") self.selections.append(s) if not self.nManSelections and not self.nAutoSelections and not self.allSelected: WaitForUserDialog("No Selection-options has been chosen!").show() sys.exit("Analysis was cancelled") def getOptions(self): section = "SelectionManager" items = dict(cp.cp.items(section)) comp = cp.compare_sections(items, "SelectionManager") if not comp[0]: cp.update(section, comp[1]) cp.writeIni() cp.readIni() manSel = cp.cp.getfloat(section, "manSel") autSel = cp.cp.getfloat(section, "autSel") allSelected = cp.cp.getboolean(section, "allSelected") if not headless: gd = GenericDialog("Selection Manager") gd.addNumericField("How many manual selections?", manSel, 0) # manSel = 0 gd.addNumericField("How many automatic selection?", autSel, 0) # autSel = 1 gd.addCheckbox("Analyze the whole image?", allSelected) gd.showDialog() if gd.wasCanceled(): print "User canceled dialog!" sys.exit("Analysis was cancelled") self.nManSelections = int(gd.getNextNumber()) self.nAutoSelections = int(gd.getNextNumber()) self.allSelected = gd.getNextBoolean() manSel = self.nManSelections autSel = self.nAutoSelections allSelected = self.allSelected l = ["manSel", "autSel", "allSelected"] n = [manSel, autSel, allSelected] cp.update(section, dict((na, str(n[i])) for i, na in enumerate(l))) else: self.nManSelections = int(manSel) self.nAutoSelections = int(autSel) allSelected = self.allSelected = allSelected # Object that performs the Selection on a specific image and retrieves the right rois class Selection(object): autoMethods = AutoThresholder.getMethods() allMethods = ["Manual"] allMethods += autoMethods def __init__(self, ID, typeSel): self.imp = 0 self.title = 0 self.typeSel = typeSel self.ID = ID self.area = 0 self.mask = '' self.path = '' self.name = '' self.saveRoi = False c1 = False c2 = False c3 = False c4 = False self.channels = [] self.increment = False self.inverse = False self.background = 0 self.sigma = 0 self.method = '' self.pa = False self.sizea = 0 self.sizeb = 0 self.circa = 0 self.circb = 0 self.enlarge = 0 self.test = False self.nIncrements = 0 self.show = False self.spineData = {} if self.typeSel == "automatic": self.selectAreaAuto() attr = vars(self) if self.typeSel == "manual": self.getOptions() def setImage(self, image): self.imp = image.imp self.image = image self.show = image.show self.title = self.imp.getTitle() if self.typeSel == "manual": rois = self.selectAreaManually() if not isinstance(rois, list): rois = [rois] if self.typeSel == "automatic": rois = self.getSelection() if self.saveRoi: for i in rois: if i is not None: self.imp.setRoi(i) roiname = i.getName() roiPath = image.output_path.replace(os.path.splitext(image.output_path)[1], ("_" + roiname + ".roi")) IJ.saveAs(self.imp, "Selection", roiPath) i.setName(roiname) return rois def getOptions(self): section = "ManualSelection" + str(self.ID) if not cp.cp.has_section(section): items = dict(cp.cp.items("ManualSelection")) cp.update(section, items) cp.writeIni() cp.readIni() items = dict(cp.cp.items(section)) comp = cp.compare_sections(items, "ManualSelection") if not comp[0]: cp.update(section, comp[1]) cp.writeIni() cp.readIni() SelName = cp.cp.get(section, "SelName") SaveRoi = cp.cp.getboolean(section, "SaveRoi") customRoi = cp.cp.getboolean(section, "customRoi") if not headless: gd = GenericDialog("Options for %s selection %s" % (self.typeSel, self.ID)) gd.addStringField("Selection Name: ", SelName, 20) gd.addCheckbox("Load pre-designed ROI's or binary masks?: ", customRoi) gd.addCheckbox("Save ROI?", SaveRoi) gd.showDialog() if gd.wasCanceled(): print "User canceled dialog!" sys.exit("Analysis was cancelled") self.name = SelName = gd.getNextString() self.customRoi = customRoi = gd.getNextBoolean() self.saveRoi = SaveRoi = gd.getNextBoolean() l = ["SelName", "SaveRoi", "customRoi"] n = [SelName, SaveRoi, customRoi] cp.update(section, dict((na, str(n[i])) for i, na in enumerate(l))) else: self.name = SelName self.saveRoi = SaveRoi self.customRoi = customRoi def selectAreaManually(self): def loadfilenames(): filenames = [] for root, dirs, files in os.walk(expath2): group = os.path.split(root)[1] for j in files: if os.path.splitext(self.title)[0] in j: names = os.path.splitext(j)[0].split(self.image.dialoger.delimiter) if self.name in names: filenames.append(os.path.join(root, j)) return filenames IJ.run(self.imp, "Select None", "") if not self.customRoi: self.imp.show() window = self.imp.getWindow() while self.imp.getRoi() is None and not window.isClosed(): WaitForUserDialog("Please, select the %s area you stated before" %self.name).show() if self.imp.getRoi() is not None: roi = self.imp.getRoi() roi.setName(self.name) elif window.isClosed(): print "User canceled dialog!" sys.exit("Analysis was cancelled") if not self.show: self.imp.hide() return self.imp.getRoi() else: roiList = loadfilenames() ext=".roi" rois = [] for r in roiList: if os.path.splitext(r)[1] == ext: rois.append(RoiDecoder(r).getRoi()) else: mask = BF.openImagePlus(r)[0] maskIP = mask.getProcessor() if not maskIP.isBinary(): print "%s is not a binary mask, ROI omitted" %r else: maskIP.setAutoThreshold(AutoThresholder.Method.valueOf("Default"), True, luts[c]) binaryRoi = tts().convert(maskIP) binaryRoi.setName(self.name) rois.append(binaryRoi) return rois def selectAreaAuto(self): section = "AutomaticSelection" + str(self.ID) if not cp.cp.has_section(section): items = dict(cp.cp.items("AutomaticSelection")) cp.update(section, items) cp.writeIni() cp.readIni() items = dict(cp.cp.items(section)) comp = cp.compare_sections(items, "AutomaticSelection") if not comp[0]: cp.update(section, comp[1]) cp.writeIni() cp.readIni() SelName2 = cp.cp.get(section, "SelName2") SaveRoi2 = cp.cp.getboolean(section, "SaveRoi2") maskBool_list = eval(cp.cp.get(section, "maskBool_list")) nOfIncrements = cp.cp.getfloat(section, "nOfIncrements") incrementslengths = cp.cp.getfloat(section, "incrementslengths") inverseBool = cp.cp.getboolean(section, "inverseBool") backgroundRadius = cp.cp.getfloat(section, "backgroundRadius") sigma1 = cp.cp.getfloat(section, "sigma1") binMethod1 = cp.cp.get(section, "binMethod1") sizeA1 = cp.cp.getfloat(section, "sizeA1") sizeB2 = cp.cp.getfloat(section, "sizeB2") circA1 = cp.cp.getfloat(section, "circA1") circB2 = cp.cp.getfloat(section, "circB2") enlarge1 = cp.cp.getfloat(section, "enlarge1") spineBool = False minLength = 0.001 maxLength = 2.5 spineSizeMin = 0.01 spineSizeMax = 2.5 spineCircMin = 0.0 spineCircMax = 1.0 spineBool = cp.cp.getboolean(section, "spineBool") minLength = cp.cp.getfloat(section, "minLength") maxLength = cp.cp.getfloat(section, "maxLength") spineSizeMin = cp.cp.getfloat(section, "spineSizeMin") spineSizeMax = cp.cp.getfloat(section, "spineSizeMax") spineCircMin = cp.cp.getfloat(section, "spineCircMin") spineCircMax = cp.cp.getfloat(section, "spineCircMax") if not headless: gd = GenericDialog("Options to build an automatic selection for all images") gd.addStringField("Selection name: ", SelName2, 20) gd.addCheckbox("Save ROI?", SaveRoi2) gd.addMessage("_________________________________________________________________________________") gd.addMessage("Choose a channel (or more) to create the combined mask") gd.addCheckboxGroup(1, 4, ["Mask from C1: ", "Mask from C2: ", "Mask from C3: ", "Mask from C4: "], maskBool_list) gd.addCheckbox("Add an inverse selection of this mask?", inverseBool) gd.addMessage("_________________________________________________________________________________") gd.addMessage("Perform a Particle Analysis on the combined mask to select for a certain region") gd.addMessage("Set size options to 0 if not") gd.addNumericField("Background radius:", backgroundRadius, 0) gd.addNumericField("Sigma of Gaussian Blur (0 if not, otherwise state the radius)", sigma1, 2) gd.addChoice("Binary Threshold Method", self.allMethods, binMethod1) gd.addNumericField("Lower Particle Size:", sizeA1, 0) gd.addNumericField("Higher Particle Size:", sizeB2, 0) gd.addNumericField("Circularity bottom:", circA1, 1) gd.addNumericField("Circularity top:", circB2, 1) gd.addNumericField("Enlarge mask in [um]? (For shrinkage put negative numbers)", enlarge1, 2) gd.addMessage("_________________________________________________________________________________") gd.addMessage("Do you want to perform a dendritic segment analysis? (set options to 0 if not)") gd.addNumericField("Increment step size in um: ", incrementslengths, 0) gd.addNumericField("Number of increments: ", nOfIncrements, 0) gd.addMessage("_________________________________________________________________________________") gd.addCheckbox("Do you want to perform a spine analysis?", spineBool) gd.addNumericField("Minimum length of spine:", minLength, 4) gd.addNumericField("Maximum length of spine:", maxLength, 4) gd.addNumericField("Minimum spine area (Lower spine size)", spineSizeMin, 4) gd.addNumericField("Maximum spine area (Upper spine size)", spineSizeMax, 4) gd.addNumericField("Spine circularity bottom", spineCircMin, 2) gd.addNumericField("Spine circularity top", spineCircMax, 2) wt.addScrollBars(gd) gd.showDialog() if gd.wasCanceled(): print "User canceled dialog!" sys.exit("Analysis was cancelled") self.name = SelName2 = gd.getNextString() self.saveRoi = SaveRoi2 = gd.getNextBoolean() c1 = gd.getNextBoolean() c2 = gd.getNextBoolean() c3 = gd.getNextBoolean() c4 = gd.getNextBoolean() self.channels = maskBool_list = [c1, c2, c3, c4] self.inverse = inverseBool = gd.getNextBoolean() self.background = backgroundRadius = gd.getNextNumber() self.sigma = sigma1 = gd.getNextNumber() self.method = binMethod1 = gd.getNextChoice() # self.pa = selectSizeBool = gd.getNextBoolean() self.sizea = sizeA1 = gd.getNextNumber() self.sizeb = sizeB2 = gd.getNextNumber() self.circa = circA1 = gd.getNextNumber() self.circb = circB2 = gd.getNextNumber() self.enlarge = enlarge1 = gd.getNextNumber() self.increment = incrementslengths = gd.getNextNumber() self.nIncrements = nOfIncrements = int(gd.getNextNumber()) self.spineBool = spineBool = gd.getNextBoolean() self.minLength = minLength = gd.getNextNumber() self.maxLength = maxLength = gd.getNextNumber() self.spineSizeMin = spineSizeMin = gd.getNextNumber() self.spineSizeMax = spineSizeMax = gd.getNextNumber() self.spineCircMin = spineCircMin = gd.getNextNumber() self.spineCircMax = spineCircMax = gd.getNextNumber() l = ["SelName2", "SaveRoi2", "maskBool_list", "nOfIncrements", "incrementslengths", "inverseBool", "backgroundRadius", "sigma1", "binMethod1", "sizeA1", "sizeB2", "circA1", "circB2", "enlarge1", "spineBool", "minLength", "maxLength", "spineSizeMin", "spineSizeMax", "spineCircMin", "spineCircMax"] n = [SelName2, SaveRoi2, maskBool_list, nOfIncrements, incrementslengths, inverseBool, backgroundRadius, sigma1, binMethod1, sizeA1, sizeB2, circA1, circB2, enlarge1, spineBool, minLength, maxLength, spineSizeMin, spineSizeMax, spineCircMin, spineCircMax] cp.update(section, dict((na, str(n[i])) for i, na in enumerate(l))) else: self.name = SelName2 self.saveRoi = SaveRoi2 self.channels = maskBool_list self.nIncrements = int(nOfIncrements) self.increment = incrementslengths self.inverse = inverseBool self.background = backgroundRadius self.sigma = sigma1 self.method = binMethod1 self.sizea = sizeA1 self.sizeb = sizeB2 self.circa = circA1 self.circb = circB2 self.enlarge = enlarge1 self.spineBool = spineBool self.minLength = minLength self.maxLength = maxLength self.spineSizeMin = spineSizeMin self.spineSizeMax = spineSizeMax self.spineCircMin = spineCircMin self.spineCircMax = spineCircMax def particleAnalysis(self, imp, spines=False, sizea=0, sizeb=0, circa=0, circb=0): if not sizea and not sizeb and not circa and not circb: sizea=self.sizea sizeb=self.sizeb circa=self.circa circb=self.circb IJ.run(imp, "Set Scale...", " ") cal = imp.getCalibration() options = ParticleAnalyzer.DISPLAY_SUMMARY | ParticleAnalyzer.SHOW_MASKS | ParticleAnalyzer.SHOW_RESULTS msInt = Analyzer().getMeasurements() rt = ResultsTable() pa = ParticleAnalyzer(options, msInt, rt, math.pi * cal.getRawX(math.sqrt(sizea) / math.pi) ** 2, math.pi * cal.getRawX(math.sqrt(sizeb) / math.pi) ** 2, Double(circa), Double(circb)) pa.setHideOutputImage(True) pa.analyze(imp) if spines: mask = pa.getOutputImage() IJ.run(mask, "Create Selection", '') area = mask.getStatistics().area col = [rt.getColumnHeadings()] col += [rt.getRowAsString(r) for r in range(0, rt.size())] if rt.size(): normArea = area/rt.size() else: normArea = 0 self.spineData = {"Selection": self.name, "Spines_Area": area, "Number_of_spines": rt.size(), "Area_per_spine":normArea, "Columns": col, "Folder":self.image.group} return pa.getOutputImage() def clear(self, imp, value): ip = imp.getProcessor() ip.setValue(value) ip.fill(ip.getMask()) def skeletonize(self, mask): IJ.run(mask, "Select None", "") maskel = mask.duplicate() ip = maskel.getProcessor() maskel.updateAndDraw() ip.skeletonize() maskel.updateAndDraw() return maskel def analyzeSkeleton(self, mask, thresholdA, thresholdB): skel = AnalyzeSkeleton_() skel.calculateShortestPath = False skel.setup("", mask) skelResult = skel.run(AnalyzeSkeleton_.NONE, False, False, None, True, True) prunedImage = mask.duplicate() prunedIP = prunedImage.getProcessor() prunedIP.set(0.0) outStack = prunedImage.getStack() graph = skelResult.getGraph() # list of end-points endPoints = skelResult.getListOfEndPoints() for i in range(0, len(graph)): listEdges = graph[i].getEdges() # go through all branches and remove branches under threshold in duplicate image lengths = [e.getLength() for e in listEdges] points = [] for e in listEdges: p = e.getV1().getPoints() v1End = p.get(0) in endPoints # endPoints.contains( p.get(0) ) p2 = e.getV2().getPoints(); v2End = p2.get(0) in endPoints #endPoints.contains( p2.get(0) ) #if any of the vertices is end-point if e.getLength() >= thresholdA and e.getLength() <= thresholdB: if v1End: outStack.setVoxel( p.get(0).x, p.get(0).y, p.get(0).z, 255) points.append((p.get(0), e.getLength())) if v2End: outStack.setVoxel( p2.get(0).x, p2.get(0).y, p2.get(0).z, 255) points.append((p2.get(0), e.getLength())) return prunedImage def extractSpines(rois, spines): cropList = [] for r in rois: spines.setRoi(r) spineCropped = spines.duplicate() IJ.run(spineCropped, "Create Selection", "") spineRoi = spineCropped.getRoi() cropList.append(spineCropped) #cropped.flatten()) return Concatenator().concatenate(cropList, False) def getSelection(self): channels = ChannelSplitter.split(self.imp) ic = ImageCalculator() imp_list = [] for i, c in enumerate(channels): if self.channels[i]: imp_list.append(c) if imp_list: if len(imp_list) > 1: imp2 = RGBStackMerge().mergeChannels(imp_list, False) self.imp.hide() imp2.copyAttributes(self.imp) imp3 = self.image.zStackIJ(imp2) imp2.changes = False imp2.close() elif len(imp_list) == 1: imp3 = imp_list[0].duplicate() if self.show: self.imp.show() IJ.run(imp3, "Gaussian Blur...", "sigma=%s" % self.sigma); IJ.setAutoThreshold(imp3, "%s dark" % self.method) IJ.run(imp3, "Select All", "") if self.sizea or self.sizeb: shower = "Masks" mask = self.particleAnalysis(imp3) imp3.changes = False imp3.close() else: mask = imp3 imp3.close() IJ.run(mask, "Create Selection", "") roi_list = [] if mask.getRoi() is not None: r = mask.getRoi() cal = mask.getCalibration() r2 = RoiEnlarger().enlarge(r, cal.getRawX(self.enlarge)) mask.setRoi(r2) IJ.setBackgroundColor(255, 255, 255) rip = mask.getProcessor() rip.setColor(Color.BLACK) maskRoi = mask.getRoi() rip.fill(maskRoi) maskRoi.setName(self.name) roi_list.append(maskRoi) self.imp.setRoi(maskRoi) mask.setRoi(maskRoi) if self.nIncrements: r = mask.getRoi() for n in range(0, self.nIncrements): if mask.getRoi() is not None: r = ShapeRoi(mask.getRoi()) cal = mask.getCalibration() r2 = ShapeRoi(RoiEnlarger.enlarge(r, cal.getRawX(self.increment))) r3 = r.xor(r2) mask.setRoi(r3) if r3 is not None: roi = r3 roi.setName(self.name + "-Increment%s" % (n + 1)) roi_list.append(roi) mask.setRoi(r2) if self.spineBool: maskel = self.skeletonize(mask) prunedImage = self.analyzeSkeleton(maskel, self.minLength, self.maxLength) IJ.run(prunedImage, "Create Selection", "") roi2 = prunedImage.getRoi() if roi2 is not None: roi3 = ShapeRoi(roi2) rois = roi3.getRois() roi3 = ShapeRoi(RoiEnlarger().enlarge(roi2, self.imp.getCalibration().getRawX(0.5))) mask.setRoi(roi3) imp3.setRoi(roi3) spines=self.particleAnalysis(imp3, True, self.spineSizeMin, self.spineSizeMax, self.spineCircMin, self.spineCircMax) IJ.run(spines, "Create Selection", "") if spines.getRoi() is not None: spineRoi = spines.getRoi() roi3.setName("Spines") spineRoi.setName("Spines-%s"%self.name) roi3.setColor(Color.MAGENTA) roi_list.append(spineRoi) spines.close() else: print "No spines detected!" self.spineData = {"Selection": self.name, "Spines_Area": 0.0, "Number_of_spines": 0.0, "Area_per_spine":0.0, "Columns": [Analyzer().getResultsTable().getColumnHeadings()]} IJ.run(mask, "Create Selection", "") area = mask.getStatistics().area self.spineData["Selection_Area"] = area mask.close() maskel.close() prunedImage.close() if self.inverse: shape_1 = ShapeRoi(roi_list[0]) shape_2 = ShapeRoi(Roi(0, 0, mask.getWidth(), mask.getHeight())) r_inverse = shape_1.xor(shape_2) r_inverse.setName(self.name + "-inversed") roi_list.append(r_inverse) mask.changes = False mask.close() for c in channels: c.close() return roi_list else: WaitForUserDialog("No channels as mask has been chosen for the Automatic Selection! Select at least one channel!").show() sys.exit("Analysis cancelled!") # Main Dialog manager class Dialoger(object): autoMethods = AutoThresholder.getMethods() allMethods = ["Manual"] allMethods += autoMethods def __init__(self): self.input_path_dir = '' self.output_path_dir = '' self.ext = '' self.delimiter = "_" self.filenames = [] self.groupedFiles = {} self.zStack = False self.test = False self.c1 = Channel() self.c2 = Channel() self.c3 = Channel() self.c4 = Channel() self.output_path_dict = {} self.channels = [self.c1, self.c2, self.c3, self.c4] self.overwriteDB = False self.getOptions() self.loadfilenames() [self.getParticleAnalyzerOptions(i) for i, x in enumerate(self.channels) if self.channels[i].pa] for j in self.channels: if any(j.list_1whichChannel): [self.getParticleAnalyzerOptions(i, "coloc") for i, x in enumerate(j.list_1whichChannel) if not self.channels[i].pa and x] def loadfilenames(self): filenames = [] groupedfiles = {} if self.ext[0] != ".": self.ext = "." + self.ext for root, dirs, files in os.walk(self.input_path_dir): group = os.path.split(root)[1] if not group in groupedfiles: groupedfiles[group] = [] for j in files: if os.path.splitext(os.path.join(root, j))[1] == self.ext: groupedfiles[group].append(os.path.join(root, j)) filenames.append(os.path.join(root, j)) if not filenames: WaitForUserDialog("No files have been found. Please, check for correct file-extension (file-type) or for presence of images in the folder").show() sys.exit("Analysis cancelled!") output_path_dir = os.path.join(self.input_path_dir, "Particle_Analysis") if not os.path.isdir(output_path_dir): os.makedirs(output_path_dir) self.output_path_dir = output_path_dir for k in groupedfiles: g_path = os.path.join(self.output_path_dir, k) if not os.path.isdir(g_path): os.makedirs(g_path) self.output_path_dict[k] = g_path output_table = os.path.join(self.output_path_dir, "Output_Table") if not os.path.isdir(output_table): os.makedirs(output_table) self.output_path_dict["output_table_path"] = output_table self.groupedFiles = dict((k, v) for k, v in groupedfiles.items() if v) self.filenames = filenames def getOptions(self): section = "ChannelOptions" ext = cp.cp.get(section, "ext") delimiter = cp.cp.get(section, "delimiter") zStackBool = cp.cp.getboolean(section, "zStackBool") c1Name = cp.cp.get(section, "c1Name") c1Opt_boolList = eval(cp.cp.get(section, "c1Opt_boolList")) backgroundRadc1 = cp.cp.getfloat(section, "backgroundRadc1") sigmaC1 = cp.cp.getfloat(section, "sigmaC1") c2Name = cp.cp.get(section, "c2Name") c2Opt_boolList = eval(cp.cp.get(section, "c2Opt_boolList")) backgroundRadc2 = cp.cp.getfloat(section, "backgroundRadc2") sigmaC2 = cp.cp.getfloat(section, "sigmaC2") c3Name = cp.cp.get(section, "c3Name") c3Opt_boolList = eval(cp.cp.get(section, "c3Opt_boolList")) backgroundRadc3 = cp.cp.getfloat(section, "backgroundRadc3") sigmaC3 = cp.cp.getfloat(section, "sigmaC3") c4Name = cp.cp.get(section, "c4Name") c4Opt_boolList = eval(cp.cp.get(section, "c4Opt_boolList")) backgroundRadc4 = cp.cp.getfloat(section, "backgroundRadc4") sigmaC4 = cp.cp.getfloat(section, "sigmaC4") testBool = cp.cp.getboolean(section, "testBool") if not headless: gd = GenericDialog("Options") gd.addMessage("Input Folder: %s" % expath) gd.addCheckboxGroup(1, 2, ["Z-project?", "Overwrite old database if it already exists?"], [zStackBool, True]) gd.addStringField("File extension", ext, 10) gd.addStringField("Title separator", delimiter, 10) gd.addMessage( "__________________________________________________________________________________________________________________________________________________") gd.addMessage("Set details for Channel 1") gd.addStringField("Channel 1", c1Name, 8) gd.addCheckboxGroup(1, 4, ["Background Substraction", "Adjust Brightness/Contrast automatically?", "Adjust Brightness/Contrast manually?", "Particle Analysis"], c1Opt_boolList) gd.addNumericField("Background radius:", backgroundRadc1, 0) gd.addNumericField("Gaussian Blur (0 if not, otherwise state the radius)", sigmaC1, 2) gd.addMessage( "__________________________________________________________________________________________________________________________________________________") gd.addMessage("Set details for Channel 2") gd.addStringField("Channel 2", c2Name, 8) gd.addCheckboxGroup(1, 4, ["Background Substraction", "Adjust Brightness/Contrast automatically?", "Adjust Brightness/Contrast manually?", "Particle Analysis"], c2Opt_boolList) gd.addNumericField("Background radius:", backgroundRadc2, 0) gd.addNumericField("Gaussian Blur (0 if not, otherwise state the radius)", sigmaC2, 2) gd.addMessage( "__________________________________________________________________________________________________________________________________________________") gd.addMessage("Set details for Channel 3") gd.addStringField("Channel 3", c3Name, 8) gd.addCheckboxGroup(1, 4, ["Background Substraction", "Adjust Brightness/Contrast automatically?", "Adjust Brightness/Contrast manually?", "Particle Analysis"], c3Opt_boolList) gd.addNumericField("Background radius:", backgroundRadc3, 0) gd.addNumericField("Gaussian Blur (0 if not, otherwise state the radius)", sigmaC3, 2) gd.addMessage( "__________________________________________________________________________________________________________________________________________________") gd.addMessage("Set details for Channel 4") gd.addStringField("Channel 4", c4Name, 8) gd.addCheckboxGroup(1, 4, ["Background Substraction", "Adjust Brightness/Contrast automatically?", "Adjust Brightness/Contrast manually?", "Particle Analysis"], c4Opt_boolList) gd.addNumericField("Background radius:", 50, 0) gd.addNumericField("Gaussian Blur (0 if not, otherwise state the radius)", sigmaC4, 2) gd.addMessage("_________________________________________________________________________________") gd.addCheckbox("Test parameters on random pictures?", testBool) wt.addScrollBars(gd) gd.showDialog() if gd.wasCanceled(): print "User canceled dialog!" sys.exit("Analysis was cancelled") if isinstance(expath, str): input_path_dir = expath else: input_path_dir = expath.getAbsolutePath() # = gd.getNextString() zStack = zStackBool = gd.getNextBoolean() ext = gd.getNextString() delimiter = gd.getNextString() self.overwriteDB = gd.getNextBoolean() info_channels = [] for i in range(0, 4): channelName = gd.getNextString() background = gd.getNextBoolean() brightness_auto = gd.getNextBoolean() brightness_man = gd.getNextBoolean() pa = gd.getNextBoolean() radius = gd.getNextNumber() gaussian = gd.getNextNumber() if brightness_auto: brightness_man = False if i == 0: c1Name = channelName c1Opt_boolList = [background, brightness_auto, brightness_man, pa] backgroundRadc1 = radius sigmaC1 = gaussian if i == 1: c2Name = channelName c2Opt_boolList = [background, brightness_auto, brightness_man, pa] backgroundRadc2 = radius sigmaC2 = gaussian if i == 2: c3Name = channelName c3Opt_boolList = [background, brightness_auto, brightness_man, pa] backgroundRadc3 = radius sigmaC3 = gaussian if i == 3: c4Name = channelName c4Opt_boolList = [background, brightness_auto, brightness_man, pa] backgroundRadc4 = radius sigmaC4 = gaussian info_channels.append([channelName, background, radius, brightness_auto, brightness_man, pa, gaussian]) self.channels[i].setInfo(channel_name=channelName, background_substraction=background, background_radius=radius, brightness_auto=brightness_auto, brightness_man=brightness_man, pa=pa, gaussian_blur=gaussian) self.test = testBool = gd.getNextBoolean() l = ["expath", "ext", "delimiter", "zStackBool", "c1Name", "c1Opt_boolList", "backgroundRadc1", "sigmaC1", "c2Name", "c2Opt_boolList", "backgroundRadc2", "sigmaC2", "c3Name", "c3Opt_boolList", "backgroundRadc3", "sigmaC3", "c4Name", "c4Opt_boolList", "backgroundRadc4", "sigmaC4", "testBool"] n = [expath, ext, delimiter, zStackBool, c1Name, c1Opt_boolList, backgroundRadc1, sigmaC1, c2Name, c2Opt_boolList, backgroundRadc2, sigmaC2, c3Name, c3Opt_boolList, backgroundRadc3, sigmaC3, c4Name, c4Opt_boolList, backgroundRadc4, sigmaC4, testBool] cp.update(section, dict((na, str(n[i])) for i, na in enumerate(l))) self.input_path_dir = input_path_dir self.zStack = zStack self.ext = ext self.delimiter = delimiter else: self.input_path_dir = expath2 self.zStack = zStackBool self.ext = ext self.overwriteDB = True self.delimiter = delimiter cnames = [c1Name, c2Name, c3Name, c3Name] backgrounds = [backgroundRadc1, backgroundRadc2, backgroundRadc3, backgroundRadc4] radiuss = [sigmaC1, sigmaC2, sigmaC3, sigmaC4] info_channels = [] for i in range(0, 4): channelName = cnames[i] radius = backgrounds[i] if i == 0: background = c1Opt_boolList[0] brightness_auto = c1Opt_boolList[1] brightness_man = c1Opt_boolList[2] pa = c1Opt_boolList[3] c1Name = channelName backgroundRadc1 = radius gaussian = sigmaC1 if i == 1: background = c2Opt_boolList[0] brightness_auto = c2Opt_boolList[1] brightness_man = c2Opt_boolList[2] pa = c2Opt_boolList[3] c2Name = channelName backgroundRadc2 = radius gaussian = sigmaC2 if i == 2: background = c3Opt_boolList[0] brightness_auto = c3Opt_boolList[1] brightness_man = c3Opt_boolList[2] pa = c3Opt_boolList[3] c3Name = channelName backgroundRadc3 = radius gaussian = sigmaC3 if i == 3: background = c4Opt_boolList[0] brightness_auto = c4Opt_boolList[1] brightness_man = c4Opt_boolList[2] pa = c4Opt_boolList[3] c4Name = channelName backgroundRadc4 = radius gaussian = sigmaC4 info_channels.append([channelName, background, radius, brightness_auto, brightness_man, pa, gaussian]) self.channels[i].setInfo(channel_name=channelName, background_substraction=background, background_radius=radius, brightness_auto=brightness_auto, brightness_man=brightness_man, pa=pa, gaussian_blur=gaussian) self.test = False def getParticleAnalyzerOptions(self, channel_number, coloc=''): section = "ParticleAnalysisOptions%s" % channel_number paInOutBool_list = eval(cp.cp.get(section, "paInOutBool_list")) paColocBool_list = eval(cp.cp.get(section, "paColocBool_list")) paEnlarge = cp.cp.getfloat(section, "paEnlarge") paSizeA1 = cp.cp.getfloat(section, "paSizeA1") paSizeB1 = cp.cp.getfloat(section, "paSizeB1") paSizeA2 = cp.cp.getfloat(section, "paSizeA2") paSizeB2 = cp.cp.getfloat(section, "paSizeB2") paCirc1 = cp.cp.getfloat(section, "paCirc1") paCirc2 = cp.cp.getfloat(section, "paCirc2") paMethod = cp.cp.get(section, "paMethod") addMeth1 = cp.cp.get(section, "addMeth1") watershed1 = cp.cp.getboolean(section, "watershed1") addMeth2 = cp.cp.get(section, "addMeth2") watershed2 = cp.cp.getboolean(section, "watershed2") if not headless: if coloc == "coloc": gd = GenericDialog("Options for Channel %s colocalized Particle Analysis" % (channel_number + 1)) else: gd = GenericDialog("Options for Channel %s Particle Analysis" % (channel_number + 1)) gd.addMessage("Set details for Channel %s" % (channel_number + 1)) gd.addMessage("___________________________________________________________________________________") if not coloc == "coloc": gd.addMessage("Colocalisation Options") gd.addCheckboxGroup(1, 2, ["Inside mask?", "Or outside?"], paInOutBool_list) gd.addCheckboxGroup(1, 4, ["C1", "C2", "C3", "C4"], paColocBool_list) gd.addNumericField("Enlarge mask in [um]? (For shrinkage put negative numbers)", paEnlarge, 2) gd.addMessage("___________________________________________________________________________________") gd.addMessage("Particle Analysis Options") if channel_number == 0: gd.addNumericField("Lower Particle Size:", paSizeA1, 3) gd.addNumericField("Higher Particle Size:", paSizeB1, 3) else: gd.addNumericField("Lower Particle Size:", paSizeA2, 3) gd.addNumericField("Higher Particle Size:", paSizeB2, 3) gd.addNumericField("Circularity bottom:", paCirc1, 1) gd.addNumericField("Circularity top:", paCirc2, 1) gd.addChoice("Binary Threshold Method", self.allMethods, paMethod) if channel_number == 0: gd.addStringField("Do you want to test additional thresholds? (Separate only by space)", addMeth1, 8) gd.addCheckbox("Watershed?", watershed1) else: gd.addStringField("Do you want to test additional thresholds? (Separate only by space)", addMeth2, 8) gd.addCheckbox("Watershed?", watershed2) gd.showDialog() if gd.wasCanceled(): print "User canceled dialog!" sys.exit("Analysis was cancelled") if not coloc == "coloc": pa_inside = gd.getNextBoolean() pa_outside = gd.getNextBoolean() paInOutBool_list = [pa_inside, pa_outside] bool_c1 = gd.getNextBoolean() bool_c2 = gd.getNextBoolean() bool_c3 = gd.getNextBoolean() bool_c4 = gd.getNextBoolean() pa_enlarge_mask = paEnlarge = gd.getNextNumber() list_1whichChannel = paColocBool_list = [bool_c1, bool_c2, bool_c3, bool_c4] if channel_number == 0: lowerSize = paSizeA1 = gd.getNextNumber() higherSize = paSizeB1 = gd.getNextNumber() else: lowerSize = paSizeA2 = gd.getNextNumber() higherSize = paSizeB2 = gd.getNextNumber() circ1 = paCirc1 = gd.getNextNumber() circ2 = paCirc2 = gd.getNextNumber() pa_threshold_c1 = paMethod = gd.getNextChoice() if channel_number == 0: pa_addthreshold_c1 = addMeth1 = gd.getNextString() watershed = watershed1 = gd.getNextBoolean() else: pa_addthreshold_c1 = addMeth2 = gd.getNextString() watershed = watershed2 = gd.getNextBoolean() pa_thresholds_c1 = [pa_threshold_c1] if pa_addthreshold_c1: pa_addthreshold_c1 = pa_addthreshold_c1.split(" ") for i in pa_addthreshold_c1: if i in self.allMethods: pa_thresholds_c1.append(i) else: print i + " is not a Threshold!" if not coloc == "coloc": self.channels[channel_number].setInfo(lowerSize=lowerSize, higherSize=higherSize, circ1=circ1, circ2=circ2, method=pa_thresholds_c1, list_1whichChannel=list_1whichChannel, watershed=watershed, pa_inside=pa_inside, pa_outside=pa_outside, pa_enlarge_mask=pa_enlarge_mask) if channel_number == 0: l = ["paInOutBool_list", "paEnlarge", "paColocBool_list", "paSizeA1", "paSizeB1", "paCirc1", "paCirc2","paMethod", "addMeth1", "watershed1"] n = [paInOutBool_list, paEnlarge, paColocBool_list, paSizeA1, paSizeB1, paCirc1, paCirc2, paMethod, addMeth1, watershed1] else: l = ["paInOutBool_list", "paEnlarge", "paColocBool_list", "paSizeA2", "paSizeB2", "paCirc1","paCirc2","paMethod", "addMeth2", "watershed2"] n = [paInOutBool_list, paEnlarge, paColocBool_list, paSizeA2, paSizeB2, paCirc1, paCirc2, paMethod, addMeth2, watershed2] else: self.channels[channel_number].setInfo(lowerSize=lowerSize, higherSize=higherSize, circ1=circ1,circ2=circ2, method=pa_thresholds_c1, watershed=watershed) if channel_number == 0: l = ["paSizeA1", "paSizeB1", "paCirc1", "paCirc2", "paMethod", "addMeth1", "watershed1"] n = [paSizeA1, paSizeB1, paCirc1, paCirc2, paMethod, addMeth1, watershed1] else: l = ["paSizeA2", "paSizeB2", "paCirc1", "paCirc2", "paMethod", "addMeth2", "watershed2"] n = [paSizeA2, paSizeB2, paCirc1, paCirc2, paMethod, addMeth2, watershed2] cp.update(section, dict((na, str(n[i])) for i, na in enumerate(l))) else: if not coloc == "coloc": paInOutBool_list = paInOutBool_list pa_enlarge_mask = paEnlarge list_1whichChannel = paColocBool_list if channel_number == 0: lowerSize = paSizeA1 higherSize = paSizeB1 else: lowerSize = paSizeA2 higherSize = paSizeB2 circ1 = paCirc1 circ2 = paCirc2 pa_threshold_c1 = paMethod if channel_number == 0: pa_addthreshold_c1 = addMeth1 watershed = watershed1 else: pa_addthreshold_c1 = addMeth2 watershed = watershed2 pa_thresholds_c1 = [pa_threshold_c1] if pa_addthreshold_c1: pa_addthreshold_c1 = pa_addthreshold_c1.split(" ") for i in pa_addthreshold_c1: if i in self.allMethods: pa_thresholds_c1.append(i) else: print i + " is not a Threshold!" if not coloc == "coloc": self.channels[channel_number].setInfo(lowerSize=lowerSize, higherSize=higherSize, circ1=circ1, circ2=circ2, method=pa_thresholds_c1, list_1whichChannel=list_1whichChannel, watershed=watershed, pa_inside=paInOutBool_list[0], pa_outside=paInOutBool_list[1], pa_enlarge_mask=pa_enlarge_mask) else: self.channels[channel_number].setInfo(lowerSize=lowerSize, higherSize=higherSize, circ1=circ1, circ2=circ2, method=pa_thresholds_c1, watershed=watershed) # At the beginning of the Script, this object sets up the SelectionManager and the Dialoger and gathers all parameters class testParameters(object): def __init__(self): self.d = "" self.s = "" self.another = False self.newparams = False self.start = False def dialog(self): self.another = False self.newparams = False self.start = False gd = GenericDialog("Test parameter mode - Select just one option") gd.addCheckbox("Test another image?", False) gd.addCheckbox("Try new parameters?", False) gd.addCheckbox("Start Experiment", True) gd.showDialog() if gd.wasCanceled(): print "User canceled dialog!" sys.exit("Analysis was cancelled") self.another = gd.getNextBoolean() self.newparams = gd.getNextBoolean() self.start = gd.getNextBoolean() def startScript(self): self.d = Dialoger() self.s = SelectionManager() cp.writeIni() cp.readIni() if self.d.test: filepath = random.choice(self.d.filenames) print "*****************************************************" print "Testing Parameters on image: %s \n" % os.path.split(filepath)[1] l = Image(filepath, self.d, self.s, True) self.stitch(filepath) self.dialog() while self.another: IJ.run("Close All") filepath = random.choice(self.d.filenames) print "*****************************************************" print "Testing Parameters on image: %s \n" % os.path.split(filepath)[1] l = Image(filepath, self.d, self.s, True) self.stitch(filepath) self.dialog() if self.newparams: self.startScript() if self.start: IJ.run("Close All") return self.d, self.s else: return self.d, self.s def stitch(self, filepath): imp = BF.openImagePlus(filepath)[0] if WindowManager.getImageCount() > 1: titles = WindowManager.getImageTitles() count = WindowManager.getImageCount() ids = [WindowManager.getNthImageID(i) for i in range(1, count + 1)] imps = [WindowManager.getImage(i) for i in ids] stack = Concatenator().concatenate(imps, False) stack.show() stack.setT(1) for i, t in enumerate(titles): stack.setT(i + 1) IJ.run("Set Label...", "label=]%s" % t) imp.show() WaitForUserDialog("Inspect results compared to original image and then proceed").show() stack.close() imp.close() else: WaitForUserDialog("Inspect results compared to original image and then proceed").show() IJ.getImage().close() return # Image class that holds and manages an ImagePlus-object class Image(object): def __init__(self, path2image, dialoger, selectionManager, show=False): self.show = show self.sm = selectionManager self.path = path2image self.name = os.path.splitext(os.path.split(self.path)[1])[0] self.preimp = BF.openImagePlus(self.path)[0] IJ.run(self.preimp, "Set Scale...", " ") self.dialoger = dialoger self.group = [key for key, value in self.dialoger.groupedFiles.items() if self.path in value][0] self.channels = self.dialoger.channels if self.dialoger.zStack and self.preimp.getNSlices() != 1: self.imp = self.zStackIJ(self.preimp) else: self.imp = self.preimp self.title = self.imp.getTitle() self.ip = self.imp.getProcessor() self.output_path = os.path.join(self.dialoger.output_path_dict[self.group], self.imp.getTitle()) self.selections = [] self.rois = [] self.pas = [] self.adjust_channels() for sel in self.sm.selections: self.rois += sel.setImage(self) if self.sm.allSelected: self.rois.append(self.getAllSelected()) if not self.rois: r = Roi(0,0,0,0) r.setName("None") self.rois = [r] if self.dialoger.zStack: subs = ChannelSplitter().split(self.imp) [s.setTitle("ZStacked") for s in subs] else: subs = ChannelSplitter().split(self.imp) subs = [self.stackSplitter(s) for s in subs] for r in self.rois: for n, sub in enumerate(subs): if self.channels[n].pa: if not isinstance(sub, list): self.imp.setRoi(r) pa = ParticleAnalyser(sub, self.channels[n], self.show, r.getName(), self.group) partRois = [pa.makeBinary(r)] self.pas.append(pa) partRois += [pa.coloc(subs[i], self.channels[i], i) for i, (x, y) in enumerate(zip(self.channels[n].list_1whichChannel, subs)) if x] roiPath = self.output_path.replace(os.path.splitext(self.output_path)[1], "_") else: for j, s in enumerate(sub): self.imp.setRoi(r) pa = ParticleAnalyser(s, self.channels[n], self.show, r.getName(), self.group) partRois = [pa.makeBinary(r)] self.pas.append(pa) partRois += [pa.coloc(subs[i][j], self.channels[i], i) for i, (x, y) in enumerate(zip(self.channels[n].list_1whichChannel, subs)) if x] roiPath = self.output_path.replace(os.path.splitext(self.output_path)[1], "_") IJ.saveAsTiff(self.imp, self.output_path) for sub in subs: if not isinstance(sub, list): sub.close() else: for s in sub: s.close() self.imp.close() def getAllSelected(self): IJ.run(self.imp, "Select All", "") r = self.imp.getRoi() r.setName("allSelected") return r def zStackIJ(self, imp): z = zp(imp) return z.run(imp,"max all") def stackSplitter(self, imp): def copyImp(stack, i): ip = stack.getProcessor(i) cal = imp.getCalibration() imp2 = ImagePlus("Slice%s" % i, ip) imp2.setCalibration(cal) imp2.setTitle("Slice%s" % i) return imp2 stack = imp.getStack() slices = stack.getSize() return [copyImp(stack, i) for i in range(1, slices + 1)] def adjust_channels(self): slices = self.imp.getNSlices() self.imp.setZ(1) self.imp.setC(1) for j in range(0, slices): self.imp.setZ(j + 1) for i in range(0, self.imp.getNChannels()): self.imp.setC(i + 1) if self.channels[i].background_substraction: IJ.run(self.imp, "Subtract Background...", "rolling=%s sliding" % self.channels[i].background_radius) if self.channels[i].brightness_auto: IJ.run(self.imp, "Enhance Contrast", "saturated=0.35") elif self.channels[i].brightness_man: IJ.run("Brightness/Contrast...") self.imp.show() WaitForUserDialog("Please, set your threshold").show() self.imp.hide() if self.channels[i].gaussian_blur: IJ.run(self.imp, "Gaussian Blur...", "sigma=%s slice" % self.channels[i].gaussian_blur) #ParticleAnalysis manager that performs Particle and Colocalisation Analysis on images and stores the right informations class ParticleAnalyser(object): def __init__(self, sub, channel, show, roi_name, group): self.roi_name = roi_name self.show = show self.pa_show = "Nothing" self.sub = sub self.sliceName = sub.getTitle() self.channel = channel self.tp = {"Channel Name": self.channel.channel_name, "Roi Name": self.roi_name, "Slice": self.sliceName, "Folder": group} self.tp_colocIn = {} self.tp_colocOut = {} self.mask = sub self.roi = '' self.new_rois = [] self.new_roi = '' self.roisInside = "" self.roisOutside = "" self.colocInfo = {} self.paInfo = {"Channel Name": self.channel.channel_name, "Methods": self.channel.method, "Roi Name": self.roi_name, "Slice": self.sliceName} self.areas = [] def __str__(self): attr = vars(self) return '\n'.join("%s: %s" % item for item in attr.items()) def watershed(self, imp2, ip, threshold_constant): byteIP1 = ip.createMask() EDM().toWatershed(byteIP1) mask = ImagePlus("mask", byteIP1) byteIP1 = mask.getProcessor() byteIP1.setAutoThreshold(threshold_constant, True, luts[c]) byteRoi = tts().convert(byteIP1) combined = ShapeRoi(self.roi).and(ShapeRoi(byteRoi)) return combined, mask def analyzePA(self, imp, roi, inorout="", paString=""): cal = imp.getCalibration() rtA = ResultsTable() if inorout == "Outside": options = ParticleAnalyzer.DISPLAY_SUMMARY | ParticleAnalyzer.SHOW_PROGRESS | ParticleAnalyzer.SHOW_RESULTS | ParticleAnalyzer.SHOW_MASKS | ParticleAnalyzer.EXCLUDE_EDGE_PARTICLES else: options = ParticleAnalyzer.DISPLAY_SUMMARY | ParticleAnalyzer.SHOW_PROGRESS | ParticleAnalyzer.SHOW_RESULTS | ParticleAnalyzer.SHOW_MASKS # ParticleAnalyzer.FOUR_CONNECTED | ParticleAnalyzer.SHOW_MASKS measurements = Analyzer().getMeasurements() if not paString: pa = ParticleAnalyzer(options, measurements, rtA, cal.getRawX(math.sqrt(self.channel.lowerSize)) ** 2, cal.getRawX(math.sqrt(self.channel.higherSize)) ** 2, self.channel.circ1, self.channel.circ2) else: pa = ParticleAnalyzer(options, measurements, rtA, cal.getRawX(math.sqrt(paString[0])) ** 2, cal.getRawX(math.sqrt(paString[1])) ** 2, paString[2], paString[3]) pa.setHideOutputImage(True) imp.setRoi(roi) ip = imp.getProcessor() ip.setRoi(roi) if pa.analyze(imp, ip): allStats = [] mask = pa.getOutputImage() IJ.run(mask, "Create Selection", "") if mask.getRoi(): maskRoi = ShapeRoi(mask.getRoi()) rois = maskRoi.getRois() ovlay = Overlay() [ovlay.add(r) for r in rois] else: ovlay = Overlay() maskRoi = Roi(0, 0, 0, 0) imp.setOverlay(ovlay) rt = ovlay.measure(imp) imp.setHideOverlay(True) ovlay.drawLabels(False) ovlay.drawNames(False) ovlay.drawBackgrounds(False) ovlay.setStrokeColor(Color.green) col = [rtA.getColumnHeadings()] col += [rtA.getRowAsString(r) for r in range(0, rtA.size())] if not col[0]: an = Analyzer(mask) mask.setRoi(Roi(0, 0, 0, 0)) an.measure() rt = an.getResultsTable() col = [rt.getColumnHeadings()] return mask, maskRoi, col def makeBinary(self, roi): self.roi = roi self.new_roi = roi imp_list = [] for index, m in enumerate(self.channel.method): label = self.sub.getTitle() imp2 = self.sub.duplicate() imp2.setTitle("Binary-%s-%s" % (label, m)) ip = imp2.getProcessor().duplicate() imp2.setProcessor(ip) if m != "Manual": threshold_constant = AutoThresholder.Method.valueOf(m) ip.setAutoThreshold(threshold_constant, True, luts[c]) else: imp2.show() while not imp2.isThreshold(): IJ.run("Threshold...") WaitForUserDialog( "Please, set your manual threshold (Please, make sure to tick the Dark Background option)").show() imp2.hide() imp2.setProcessor(ip) imp2.updateAndDraw() imp2.setRoi(self.roi) area = imp2.getStatistics().area if self.channel.watershed: self.mask_roi, mask = self.watershed(imp2, ip, threshold_constant) self.mask = mask if self.mask_roi is not None: imp2.setRoi(self.mask_roi) r = self.mask_roi else: r = self.roi else: imp2.setRoi(self.roi) self.mask = imp2.getMask() imp2.setProcessor(ip) r = self.roi min_thresh = ip.getMaxThreshold() max_thresh = ip.getMinThreshold() if self.show: imp2.show() mask, self.new_roi, col = self.analyzePA(imp2, r) print "______________________________________________" print "Measurement of Selection %s in Channel %s" % (self.roi_name, self.channel.channel_name) print "Threshold Method: %s, Max: %s, Min: %s, Number of Particles detected: %s" % (m, min_thresh, max_thresh, len(col)-1) mask.close() if self.show: if self.new_roi: width = imp2.getDimensions()[0] / 1024 imp2.setRoi(self.new_roi) IJ.run(imp2, "Properties... ", " width=%s stroke=Green" % (width)) flat = imp2.flatten() flat.copyAttributes(self.sub) flat.setRoi(self.roi) IJ.run(flat, "Properties... ", " width=%s stroke=Magenta"% (1.5*width)) flat2 = flat.flatten() flat2.setTitle( "Binary-%s-%s-%s-%s" % (self.channel.channel_name, self.roi.getName(), m, self.sliceName)) flat2.show() imp2.close() else: print "No particles found" imp2.setRoi(self.roi) IJ.run(imp2, "Properties... ", " width=1 stroke=Magenta") flat = imp2.flatten() flat.setTitle( "Binary-%s-%s-%s-%s" % (self.channel.channel_name, self.roi.getName(), m, self.sliceName)) flat.show() imp2.close() self.tp[m] = col self.tp["Selection_Area"] = area self.new_roi.setName( "Binary-%s-%s-%s-%s" % (self.channel.channel_name, self.roi.getName(), m, self.sliceName)) if index == 0: new_roi = self.new_roi self.new_roi = new_roi def coloc(self, sub2, channel2, index): if self.channel.pa_inside or self.channel.pa_outside: if self.show: self.pa_show = "Masks" else: self.pa_show = "Nothing" def flatShow(colocMask, inorout, roi): binary.setRoi(roi) IJ.run(binary, "Properties... ", " stroke=Red width=1") ov = Overlay(roi) binary.setOverlay(ov) IJ.run("Overlay Options...", "stroke=Magenta width=1 fill=none") flatIn = binary.flatten() IJ.run(colocMask, "Create Selection", '') flatRoi = colocMask.getRoi() if flatRoi: flatIn.setRoi(flatRoi) IJ.run(flatIn, "Properties... ", " stroke=Green width=1") flat2 = flatIn.flatten() flatIn.close() flat2.setTitle( inorout + "_" + self.channel.channel_name + "_" + channel2.channel_name + "_" + m + "_" + self.tp["Roi Name"] + "_" + self.sliceName) flat2.setRoi(self.roi) flat3 = flat2.flatten() flatIn.close() flat2.close() flat3.show() else: print "No %s Coloc Particles found" % inorout flatIn.setTitle( inorout + "_" + self.channel.channel_name + "_" + channel2.channel_name + "_" + m + "_" + self.tp["Roi Name"] + "_" + self.sliceName + "_Failed") flatIn.show() IJ.redirectErrorMessages(True) sub_title = self.sub.getTitle() sub2_title = sub2.getTitle() sizeMin = channel2.lowerSize sizeMax = channel2.higherSize circ1 = channel2.circ1 circ2 = channel2.circ2 binary = sub2.duplicate() ip = binary.getProcessor() binary.setTitle("Coloc-mask" + sub_title + sub2_title) m = channel2.method[0] if m != "Manual": threshold_constant = AutoThresholder.Method.valueOf(m) ip.setAutoThreshold(threshold_constant, True, luts[c]) else: while not binary.isThreshold(): binary.show() IJ.run("Threshold...") WaitForUserDialog("Please, set your manual threshold (Please, make sure to tick the Dark Background option)").show() binary.hide() binary.setProcessor(ip) binary.updateAndDraw() binary.setRoi(self.roi) if channel2.watershed: new_roi, mask = self.watershed(binary, ip, threshold_constant) mask.setRoi(self.new_roi) else: binary.setRoi(self.new_roi) self.new_random_roi = ShapeRoi(RoiRotator().rotate(self.new_roi, 90)) self.roi = ShapeRoi(self.roi) self.new_random_roi = self.new_random_roi.and(self.roi) if self.new_roi: if self.channel.pa_inside: paString = (sizeMin, sizeMax, circ1, circ2) colocMaskIn, tp_stringIn, areaIn, roi, randomColocMaskIn, randomRoiIn, randomNumberOfParticlesIn = self.colocPA("Inside", binary, paString) roi.setName( "Inside_" + self.channel.channel_name + "_" + channel2.channel_name + "_" + m + "_" + str( index)) self.tp_colocIn[ "Inside_" + self.channel.channel_name + "_" + channel2.channel_name + "_" + m + "_" + str( index)] = [tp_stringIn, areaIn, randomNumberOfParticlesIn] if self.show: flatShow(colocMaskIn, "Inside", roi) flatShow(randomColocMaskIn, "Random_Inside", randomRoiIn) if self.channel.pa_outside: paString = (sizeMin, sizeMax, circ1, circ2) colocMaskOut, tp_stringOut, areaOut, roi, randomColocMaskOut, randomRoiOut, randomNumberOfParticlesOut = self.colocPA("Outside", binary, paString) self.tp_colocOut[ "Outside_" + self.channel.channel_name + "_" + channel2.channel_name + "_" + m + "_" + str( index)] = [tp_stringOut, areaOut, randomNumberOfParticlesOut] roi.setName( "Outside_" + self.channel.channel_name + "_" + channel2.channel_name + "_" + m + "_" + str( index)) if self.show: flatShow(colocMaskOut, "Outside", roi) flatShow(randomColocMaskOut, "Random_Outside", randomRoiOut) binary.close() return roi def colocPA(self, inorout, binary, paString): def processRoi(binary): if binary.getRoi() is not None: IJ.redirectErrorMessages(True) if self.channel.pa_enlarge_mask: IJ.run(binary, "Enlarge...", "enlarge=%s" % self.channel.pa_enlarge_mask) if inorout == "Outside": IJ.run(binary, "Make Inverse", "") binary.setRoi(self.new_roi) IJ.redirectErrorMessages(True) processRoi(binary) r = binary.getRoi() area = binary.getStatistics().area colocMask, colocRoi, tp_string = self.analyzePA(binary, r, inorout, paString) binary.setRoi(self.new_random_roi) processRoi(binary) r2 = binary.getRoi() randomColocMask, randomColocRoi, randomTp_string = self.analyzePA(binary, r2, inorout, paString) randomNumberOfParticles = len(randomTp_string) - 1 if r2 is None: r2 = Roi(0,0,0,0) if inorout == "Outside": randomNumberOfParticles = "NaN" return colocMask, tp_string, area, r, randomColocMask, r2, randomNumberOfParticles def gc(): print "Free Memory ", IJ.freeMemory() IJ.run("Console", "") # IJ.run("Monitor Memory...", "") return IJ.currentMemory() def formatTime(start): t = time.time() - start u = " seconds" if t > 60: t /= 60 u = " minutes" if t > 60: t /= 60 u = " hours" if t > 24: t /= 24 u = " days" return str(round(t, 2)) + u ####### Start of the script dir_path = os.path.realpath('__file__') dir_path = os.path.dirname(os.path.realpath('__file__')) files = find("Cluster_Analysis_BETA_v2.py", dir_path) for f in files: dir_path = os.path.dirname(f) print dir_path luts = {"Black and White": ImageProcessor.BLACK_AND_WHITE_LUT, "Red": ImageProcessor.RED_LUT, "Over/Under": ImageProcessor.OVER_UNDER_LUT} if __name__ in ['__builtin__', '__main__']: # Set Measurements if measure: IJ.run("Set Measurements...", "") else: IJ.run("Set Measurements...", "area mean standard min integrated redirect=None decimal=3") expath2 = expath.getAbsolutePath() # Read config-file cp = config() cp.readIni() IJ.run("Close All", "") IJ.redirectErrorMessages(True) memory = gc() IJ.setDebugMode(False) IJ.resetEscape() # Gather Parameters for the analysis t = testParameters() d, s = t.startScript() errors = [] start = time.time() # Loop over images for index, i in enumerate(d.filenames): if not IJ.escapePressed(): try: print "Analysing image: ", os.path.split(i)[1] progress = round(float(index+1)/float(len(d.filenames)), 3) print "Progress: %s of %s images (%s percent), Time: %s" %(index + 1, len(d.filenames), progress*100, formatTime(start)) print "x"*int((progress*100)) # Image gets analyzed l = Image(i, d, s, False) if index == 0: db_path = d.output_path_dict["output_table_path"] # initiate database after first image db = db_interface(db_path, l) if not headless: # write new parameters into new config-file cp.writeIni() else: # store information into the database db.extractData(l) if index % 10 == 0: gc() # Try-catch statement so that analysis is not interrupted except: exc_type, exc_value, exc_traceback = sys.exc_info() lines = traceback.format_exception(exc_type, exc_value, exc_traceback) print ''.join('!! ' + line for line in lines) print "Analysis of image %s failed" % os.path.split(i)[1] errors.append(i) IJ.run("Close All") l = None db.writeCSV() db.closeConn() if not headless: WaitForUserDialog( "Analysis is done! \n Number of images analyzed: %s \n Running time: %s \n Number of failed images: %s" % (len(d.filenames), formatTime(start), len(errors))).show() print "Number of images analyzed: ", len(d.filenames) print 'It took', formatTime(start), 'seconds.' for e in errors: print "Failed Images: ", e if headless: if len(errors) == len(d.filenames): sys.exit(-1) else: sys.exit(0)