"""Import tiff files from a directory.

This function reads all .tiff files from a directory and it's subdirectories and returns them as a list of

hyperstacks.

Args:

directory: The path to a directory containing the tiff files.

Returns:

A list of filepaths.

"""

# Get the list of all files in directory tree at given path

listOfFiles = list()

for (dirpath, dirnames, filenames) in os.walk(directory):

listOfFiles += [os.path.join(dirpath, file) for file in filenames]

outfile = os.path.join(dir, "{}.csv".format(name))

res = ResultsTable.getResultsTable()

ResultsTable.save(res, outfile)

imp = ImagePlus(path)

imp = HyperStackConverter().toHyperStack(imp,

nChannels, # channels

nSlices, # slices

nFrames) # frames

imp = ZProjector.run(imp, "max")

subtractBackground=False, watershed=False, dilate=False,

threshMethod="Otsu", physicalUnits=True,

minSize=0.00, maxSize=float("inf"),

minCirc=0.00, maxCirc=1.00):

"""Threshold and count objects in channel 'channelNumber'.

This function splits an image in the separate channels, and counts the number of objects in the thresholded

channel.

Args:

imp: An ImagePlus with 1 frame, 1 slice.

Returns:

A list of filepaths.

"""

cal = imp.getCalibration()

if subtractBackground:

IJ.run(imp, "Subtract Background...", "rolling=50")

IJ.setAutoThreshold(imp, "{} dark".format(threshMethod))

IJ.run(imp, "Convert to Mask", "")

if dilate:

IJ.run(imp, "Dilate", "")

if watershed:

IJ.run(imp, "Watershed", "")

if physicalUnits: # Convert physical units to pixels for the current calibration.

minSize = cal.getRawX(math.sqrt(minSize)) ** 2

maxSize = cal.getRawX(math.sqrt(maxSize)) ** 2

pa = ParticleAnalyzer(

ParticleAnalyzer.SHOW_OVERLAY_OUTLINES|ParticleAnalyzer.DISPLAY_SUMMARY, #int options

Measurements.AREA|Measurements.SHAPE_DESCRIPTORS|Measurements.MEAN|Measurements.CENTROID|Measurements.LABELS, #int measurements

rt, #ResultsTable

minSize, #double

maxSize, #double

minCirc, #double

maxCirc) #double

pa.analyze(imp)

# Prepare directory tree for output.

indir = IJ.getDirectory("input directory")

outdir = IJ.getDirectory(".csv output directory")

nucdir = os.path.join(outdir, "nuclei")

bacdir = os.path.join(outdir, "bacteria")

rufdir = os.path.join(outdir, "ruffles")

gfpdir = os.path.join(outdir, "gfp")

channelsdir = os.path.join(outdir, "channels")

if not os.path.isdir(nucdir):

os.mkdir(nucdir)

if not os.path.isdir(bacdir):

os.mkdir(bacdir)

if not os.path.isdir(rufdir):

os.mkdir(rufdir)

if not os.path.isdir(gfpdir):

os.mkdir(gfpdir)

if not os.path.isdir(channelsdir):

os.mkdir(channelsdir)

# Collect all file paths in the input directory

files = readdirfiles(indir)

nucResults = ResultsTable()

bacResults = ResultsTable()

rufResults = ResultsTable()

gfpResults = ResultsTable()

for file in files:

if file.endswith('ome.tif') or file.endswith('ome.tiff'):

imp = stackprocessor(file,

nChannels=4,

nSlices=7,

nFrames=1)

channels = ChannelSplitter.split(imp)

name = imp.getTitle()

IJ.log("Processing image: {}".format(name))

for c in range(len(channels)):

IJ.run(channels[c], "Grays", "")

IJ.run(channels[c], "Invert", "")

jpgname = channels[c].getShortTitle()

jpgoutfile = os.path.join(channelsdir, "{}.jpg".format(jpgname))

IJ.saveAs(channels[c].flatten(), "Jpeg", jpgoutfile)

IJ.run(channels[c], "Invert", "")

nuc = countobjects(channels[0], nucResults,

threshMethod="Triangle",

subtractBackground=True,

# dilate=True,

watershed=True,

minSize=3.00,

maxSize=100,

minCirc=0.00,

maxCirc=1.00)

bac = countobjects(channels[1], bacResults,

threshMethod="RenyiEntropy",

subtractBackground=False,

watershed=False,

minSize=0.20,

maxSize=30.00,

minCirc=0.00,

maxCirc=1.00)

ruf = countobjects(channels[2], rufResults,

threshMethod="RenyiEntropy",

minSize=2.00,

maxSize=30.00,

minCirc=0.20,

maxCirc=1.00)

gfp = countobjects(channels[3], gfpResults,

threshMethod="RenyiEntropy",

subtractBackground=False,

watershed=True,

minSize=0.20,

maxSize=30.00,

minCirc=0.00,

maxCirc=1.00)

# binaries = [nuc, bac, ruf, gfp]

# channels[0].show()

# binaries[0].show()

# binMontage = RGBStackMerge().mergeChannels(binaries, False)

# binMontage.show()

# chsMontage = RGBStackMerge().mergeChannels(channels, False)

# binMontage = MontageMaker().makeMontage2(binMontage,

# 4, # int columns

# 4, # int rows

# 1.00, # double scale

# 1, # int first

# 16, # int last

# 1, # int inc

# 0, # int borderWidth

# False) # boolean labels)

# chsMontage = MontageMaker().makeMontage2(chsMontage,

# 4, # int columns

# 4, # int rows

# 1.00, # double scale

# 1, # int first

# 16, # int last

# 1, # int inc

# 0, # int borderWidth

# False) # boolean labels)

#

# binMontage.show()

# chsMontage.show()

outfilenuc = os.path.join(nucdir, "threshold_nuc_{}".format(name))

outfilebac = os.path.join(bacdir, "threshold_bac_{}".format(name))

outfileruf = os.path.join(rufdir, "threshold_ruf_{}".format(name))

outfilegfp = os.path.join(gfpdir, "threshold_gfp_{}".format(name))

IJ.saveAs(nuc.flatten(), "Tiff", outfilenuc)

IJ.saveAs(bac.flatten(), "Tiff", outfilebac)

IJ.saveAs(ruf.flatten(), "Tiff", outfileruf)

IJ.saveAs(gfp.flatten(), "Tiff", outfilegfp)

nucResults.show("nuclei")

bacResults.show("bacteria")

rufResults.show("ruffles")

gfpResults.show("gfp")

nucout = os.path.join(outdir, "nuclei.csv")

bacout = os.path.join(outdir, "bacteria.csv")

rufout = os.path.join(outdir, "ruffles.csv")

gfpout = os.path.join(outdir, "gfp.csv")

ResultsTable.save(nucResults, nucout)

ResultsTable.save(bacResults, bacout)

ResultsTable.save(rufResults, rufout)