def Z1_metadata(sourcefile):
# Access header of Z1 lighsheet data to determine nb views
reader = ImageReader()
omeMeta = MetadataTools.createOMEXMLMetadata()
reader.setMetadataStore(omeMeta)
reader.setId(sourcefile)
seriesCount = reader.getSeriesCount()
reader.close()
return seriesCount
def getFrameIntervalFromImage(image_path):
from loci.formats import ImageReader
from loci.formats import MetadataTools
r = ImageReader()
meta = MetadataTools.createOMEXMLMetadata()
r.setMetadataStore(meta)
r.setId(image_path)
frame_interval = meta.getPixelsTimeIncrement(0).value()
log("Detected frame rate: %s (%s)" % (frame_interval, image_path))
return frame_interval
def link_slices(output_path,channel,sizeZ,theC,physX,physY,physZ):
IJ.log("Linking z slices")
# number of slices will determine filename format
digits = "00"
if sizeZ < 100:
digits = "0"
if sizeZ < 10:
digits = ""
# get the base metadata from the first fused image
z0meta = MetadataTools.createOMEXMLMetadata()
fused = glob.glob(output_path + "fused*")
first_fused = fused[0]
reader = get_reader(first_fused,z0meta)
z0meta.setPixelsSizeZ(PositiveInteger(sizeZ),0)
reader.close()
for z in range(sizeZ):
fpath = fused[z]
IJ.log("writing metadata to slice %s"%os.path.basename(fpath))
m = MetadataTools.createOMEXMLMetadata()
r = get_reader(fpath,m)
# set the TiffData elements on the first plane
# setTiffData(IFD, image index, TiffData index)
z0meta.setTiffDataIFD(NNI(0),0,z)
# setTiffDataPlaneCount(planecount, image index, TiffData index)
z0meta.setTiffDataPlaneCount(NNI(1),0,z)
# setTiffDataFirstC(firstC, image index, TiffData index)
z0meta.setTiffDataFirstC(NNI(0),0,z)
# setTiffDataFirstC(firstT, image index, TiffData index)
z0meta.setTiffDataFirstT(NNI(0),0,z)
# setTiffDataFirstC(firstZ, image index, TiffData index)
z0meta.setTiffDataFirstZ(NNI(0),z,z)
# setUUIDFileName(filename, image index, TiffData index)
z0meta.setUUIDFileName(m.getUUIDFileName(0,0),0,0)
# setUUIDValue(value, image index, TiffData index)
z0meta.setUUIDValue(m.getUUIDValue(0,0),0,0)
# set the physical pixel sizes on each plane
m.setPixelsPhysicalSizeX(physX,0)
m.setPixelsPhysicalSizeY(physY,0)
m.setPixelsPhysicalSizeZ(physZ,0)
# set the channel attributes on each plane
m.setChannelID("Channel:0:" + str(0), 0, 0)
spp = channel['spp']
m.setChannelSamplesPerPixel(spp, 0, 0)
name = channel['name']
color = channel['color']
m.setChannelName(name,0,0)
m.setChannelColor(color,0,0)
r.close()
# replace the metadata in the slice
if z > 0:
replace_meta(m,fpath)
replace_meta(z0meta,first_fused)
def run_script(params):
input_dir = params['directory']
gridX = params['gridX']
gridY = params['gridY']
select_channel = params['select_channel']
channel = params['channel']
input_data = glob.glob("%s*.tiff"%input_dir)
first = [s for s in input_data if "T0_C0" in s][0]
start = first.index("Z")+1
sub = first[start:]
stop = sub.index("_")
digits = sub[:stop-1]
sep = os.path.sep
original_metadata = []
for filename in input_data:
meta = MetadataTools.createOMEXMLMetadata()
reader = get_reader(filename,meta)
original_metadata.append(meta)
reader.close()
complete_meta = original_metadata[0]
channels_meta = channel_info(complete_meta)
if len(input_data) != (gridX * gridY * len(channels_meta)):
IJ.log("Stopped stitching - gridX or gridY not set correctly")
return
channels = channels_meta
if select_channel:
channels = [channels_meta[channel]] # a list of len 1 with a dictionary of channel metadata
num_tiles,num_slices = tile_info(complete_meta)
if params['separate_z']:
sizeZ = num_slices
else:
sizeZ = 1
for z in range(sizeZ):
for t in range(num_tiles):
for c,chan in enumerate(channels):
frag = "Z%s%s_T%s_C%s"%(digits,z,t,chan['ID'])
input_path = [s for s in input_data if frag in s][0]
IJ.log("Transforming metadata in image %s"%os.path.basename(input_path))
tile_meta = MetadataTools.createOMEXMLMetadata()
tile_meta = set_metadata(complete_meta,tile_meta,chan)
replace_meta(tile_meta,input_path)
idx = input_data[0].index("Z%s0_T0_C0.tiff"%digits)
prefix = input_data[0][:idx]
trunc_filenames = []
for filename in input_data:
new_filename = input_dir+filename[idx:]
os.rename(filename,new_filename)
trunc_filenames.append(new_filename)
while not os.path.exists(trunc_filenames[-1]):
time.sleep(1)
physX,physY,physZ = pixel_info(complete_meta)
for c,chan in enumerate(channels):
tile_names = "Z%s0_T{i}_C%s.tiff"%(digits,chan['ID'])
run_stitching(input_dir,tile_names,gridX,gridY)
write_fused(input_dir,chan,num_slices,c+1,\
physX,physY,physZ) # channel index starts at 1
restore_metadata(input_dir,original_metadata,prefix)
delete_slices(input_dir)
def write_fused(output_path,channel,sizeZ,theC,physX,physY,physZ):
IJ.log("Writing fused data")
# number of slices will determine filename format
digits = "00"
if sizeZ < 100:
digits = "0"
if sizeZ < 10:
digits = ""
# get the base metadata from the first fused image
meta = MetadataTools.createOMEXMLMetadata()
reader = get_reader(output_path+"img_t1_z%s1_c1"%digits,meta)
reader.close()
# reset some metadata
meta.setPixelsPhysicalSizeX(physX,0)
meta.setPixelsPhysicalSizeY(physY,0)
meta.setPixelsPhysicalSizeZ(physZ,0)
meta.setPixelsSizeZ(PositiveInteger(sizeZ),0)
meta.setChannelID("Channel:0:" + str(0), 0, 0)
spp = channel['spp']
meta.setChannelSamplesPerPixel(spp, 0, 0)
name = channel['name']
color = channel['color']
meta.setChannelName(name,0,0)
meta.setChannelColor(color,0,0)
# determine the number of subsets that need to be written
slices_per_subset = 200
num_output_files = divmod(sizeZ,slices_per_subset)
fpaths = []
if num_output_files[0] == 0:
nslices = [sizeZ]
num_output_files = 1
fpaths.append("%sfused_C%s.ome.tif"%(output_path,str(theC-1)))
else:
nslices = []
for n in range(num_output_files[0]):
nslices.append(slices_per_subset)
if num_output_files[1] > 0:
nslices.append(num_output_files[1])
for s in range(len(nslices)):
fpaths.append("%sfused_C%s_subset%s.ome.tif"%(output_path,str(theC-1),str(s)))
# setup a writer
writer = ImageWriter()
writer.setCompression('LZW')
writer.setMetadataRetrieve(meta)
writer.setId(fpaths[0])
# write the slices, changing the output file when necessary
theZ = 0
for f in range(len(fpaths)):
meta.setImageName(os.path.basename(fpaths[f]),0)
writer.changeOutputFile(fpaths[f])
for s in range(nslices[f]):
fpath = output_path+"img_t1_z%s%s_c1"%(digits,str(theZ+1))
if (len(digits) == 1) and (theZ+1 > 9):
fpath = output_path+"img_t1_z%s_c1"%(str(theZ+1))
if (len(digits) == 2) and (theZ+1 > 9):
fpath = output_path+"img_t1_z0%s_c1"%(str(theZ+1))
if (len(digits) == 2) and (theZ+1 > 99):
fpath = output_path+"img_t1_z%s_c1"%(str(theZ+1))
IJ.log("writing slice %s"%os.path.basename(fpath))
m = MetadataTools.createOMEXMLMetadata()
r = get_reader(fpath,m)
m.setPixelsPhysicalSizeX(physX,0)
m.setPixelsPhysicalSizeY(physY,0)
m.setPixelsPhysicalSizeZ(physZ,0)
m.setChannelID("Channel:0:" + str(0), 0, 0)
spp = channel['spp']
m.setChannelSamplesPerPixel(spp, 0, 0)
name = channel['name']
color = channel['color']
m.setChannelName(name,0,0)
m.setChannelColor(color,0,0)
writer.saveBytes(theZ,r.openBytes(0))
r.close()
theZ += 1
writer.close()
def processMovie(root, files, outfile):
"""Concatenate images and write ome.tiff file.
If image contains already multiple time points just copy the image"""
files.sort()
options = ImporterOptions()
options.setId(files[0])
options.setVirtual(1)
image = BF.openImagePlus(options)
image = image[0]
if image.getNFrames() > 1:
msg = ("%s Contains multiple time points. Can only concatenate"
" single time points!" %files[0])
raise RuntimeError(msg)
image.close()
reader = ImageReader()
reader.setMetadataStore(MetadataTools.createOMEXMLMetadata())
reader.setId(files[0])
timeInfo = []
omeOut = reader.getMetadataStore()
omeOut = setUpXml(omeOut, image, files)
reader.close()
image.close()
itime = 0
for fileName in files:
omeMeta = MetadataTools.createOMEXMLMetadata()
reader.setMetadataStore(omeMeta)
reader.setId(fileName)
timeInfo.append(getTimePoint(reader, omeMeta))
nrImages = reader.getImageCount()
for i in range(0, reader.getImageCount()):
try:
dT = round(timeInfo[files.index(fileName)]-timeInfo[0],2)
except:
dT = (timeInfo[files.index(fileName)]-timeInfo[0]).seconds
omeOut.setPlaneDeltaT(dT, 0, i + itime*nrImages)
omeOut.setPlanePositionX(omeOut.getPlanePositionX(0,i), 0, i + itime*nrImages)
omeOut.setPlanePositionY(omeOut.getPlanePositionY(0,i), 0, i + itime*nrImages)
omeOut.setPlanePositionZ(omeOut.getPlanePositionZ(0,i), 0, i + itime*nrImages)
omeOut.setPlaneTheC(omeOut.getPlaneTheC(0,i), 0, i + itime*nrImages)
omeOut.setPlaneTheT(omeOut.getPlaneTheT(0,i), 0, i + itime*nrImages)
omeOut.setPlaneTheZ(omeOut.getPlaneTheZ(0,i), 0, i + itime*nrImages)
itime = itime + 1
reader.close()
IJ.showProgress(files.index(fileName), len(files))
try:
omeOut.setPixelsTimeIncrement(float(dT/(len(files)-1)), 0)
except:
omeOut.setPixelsTimeIncrement(0, 0)
if len(files) <= 1:
raise RuntimeError('Found only one file. Nothing to concatenate')
outfile = concatenateImagePlus(files, outfile)
filein = RandomAccessInputStream(outfile)
fileout = RandomAccessOutputStream(outfile)
saver = TiffSaver(fileout, outfile)
saver.overwriteComment(filein, omeOut.dumpXML())
fileout.close()
filein.close()
width = r.getSizeX()
height = r.getSizeY()
md = r.getGlobalMetadata()
# print(type(md))
# print(num, width, height)
stack = ImageStack(width, height)
i = 0
ip = r.openProcessors(i)[0]
stack.addSlice("1", ip);
imp = ImagePlus("foo", stack);
r.close()
imp.show()
IJ.run("Enhance Contrast", "saturated=0.35")
imageReader = ImageReader()
meta = MetadataTools.createOMEXMLMetadata()
imageReader.setMetadataStore(meta)
imageReader.setId(filePath)
pSizeX = meta.getPixelsPhysicalSizeX(0)
pSizeY = meta.getPixelsPhysicalSizeY(0)
imageReader.close()
print(pSizeX, pSizeY)
print(meta.getPixelsSizeX(0))
print(meta.getPixelsSizeY(0))
import os
import xml.etree.ElementTree as etree
import ij
from loci.formats import ImageReader
from loci.formats import MetadataTools
def get_reader(file, complete_meta):
reader = ImageReader()
reader.setMetadataStore(complete_meta)
reader.setId(file)
return reader
# files is a comma separated list of paths to the first ztc
basepath = "/Users/uqdmatt2/Desktop/"
files = [basepath+"Original_File/example stitch_Z0_T0_C0.tiff"]
for fpath in files:
original_metadata = MetadataTools.createOMEXMLMetadata()
reader = get_reader(fpath,original_metadata)
reader.close()
xml_data = original_metadata.dumpXML()
outputdir = os.path.dirname(fpath)
shortname = os.path.basename(fpath)[:-5]
outputpath = os.path.join(outputdir,shortname+".xml")
root = etree.fromstring(xml_data.decode('utf-8','ignore'))
et = etree.ElementTree(root)
et.write(outputpath)
def initreader(vsi_path):
reader = ImageReader()
omeMeta = MetadataTools.createOMEXMLMetadata()
reader.setMetadataStore(omeMeta)
reader.setId(vsi_path)
return(reader)
def nucleus_detection(infile, nucleus_channel, stacksize, animation):
# Detect nucleus with 3d log filters
fullpath = infile
infile = filename(infile)
IJ.log("Start Segmentation " + str(infile))
# First get Nb Stacks
reader = ImageReader()
omeMeta = MetadataTools.createOMEXMLMetadata()
reader.setMetadataStore(omeMeta)
reader.setId(fullpath)
default_options = "stack_order=XYCZT color_mode=Composite view=Hyperstack specify_range c_begin=" + \
str(nucleus_channel) + " c_end=" + str(nucleus_channel) + \
" c_step=1 open=[" + fullpath + "]"
NbStack = reader.getSizeZ()
reader.close()
output = re.sub('.ids', '.csv', infile)
with open(os.path.join(folder5, output), 'wb') as outfile:
DETECTwriter = csv.writer(outfile, delimiter=',')
DETECTwriter.writerow(
['spotID', 'roundID', 'X', 'Y', 'Z', 'QUALITY', 'SNR', 'INTENSITY'])
rounds = NbStack // stacksize
spotID = 1
for roundid in xrange(1, rounds + 2):
# Process stacksize by stacksize otherwise crash because too many spots
Zstart = (stacksize * roundid - stacksize + 1)
Zend = (stacksize * roundid)
if(Zend > NbStack):
Zend = NbStack % stacksize + (roundid - 1) * stacksize
IJ.log("Round:" + str(roundid) + ' Zstart=' + str(Zstart) +
' Zend=' + str(Zend) + ' out of ' + str(NbStack))
IJ.run("Bio-Formats Importer", default_options + " z_begin=" +
str(Zstart) + " z_end=" + str(Zend) + " z_step=1")
imp = IJ.getImage()
imp.show()
cal = imp.getCalibration()
model = Model()
settings = Settings()
settings.setFrom(imp)
# Configure detector - Manually determined as best
settings.detectorFactory = LogDetectorFactory()
settings.detectorSettings = {
'DO_SUBPIXEL_LOCALIZATION': True,
'RADIUS': 5.5,
'TARGET_CHANNEL': 1,
'THRESHOLD': 50.0,
'DO_MEDIAN_FILTERING': False,
}
filter1 = FeatureFilter('QUALITY', 1, True)
settings.addSpotFilter(filter1)
settings.addSpotAnalyzerFactory(SpotIntensityAnalyzerFactory())
settings.addSpotAnalyzerFactory(SpotContrastAndSNRAnalyzerFactory())
settings.trackerFactory = SparseLAPTrackerFactory()
settings.trackerSettings = LAPUtils.getDefaultLAPSettingsMap()
trackmate = TrackMate(model, settings)
ok = trackmate.checkInput()
if not ok:
sys.exit(str(trackmate.getErrorMessage()))
try:
ok = trackmate.process()
except:
IJ.log("Nothing detected, Round:" + str(roundid) + ' Zstart=' +
str(Zstart) + ' Zend=' + str(Zend) + ' out of ' + str(NbStack))
IJ.selectWindow(infile)
IJ.run('Close')
continue
else:
if animation:
# For plotting purpose only
imp.setPosition(1, 1, imp.getNFrames())
imp.getProcessor().setMinAndMax(0, 4000)
selectionModel = SelectionModel(model)
displayer = HyperStackDisplayer(model, selectionModel, imp)
displayer.render()
displayer.refresh()
for i in xrange(1, imp.getNSlices() + 1):
imp.setSlice(i)
time.sleep(0.05)
IJ.selectWindow(infile)
IJ.run('Close')
spots = model.getSpots()
spotIt = spots.iterator(0, False)
sid = []
sroundid = []
x = []
y = []
z = []
q = []
snr = []
intensity = []
for spot in spotIt:
sid.append(spotID)
spotID = spotID + 1
sroundid.append(roundid)
x.append(spot.getFeature('POSITION_X'))
y.append(spot.getFeature('POSITION_Y'))
q.append(spot.getFeature('QUALITY'))
snr.append(spot.getFeature('SNR'))
intensity.append(spot.getFeature('MEAN_INTENSITY'))
# Correct Z position
correct_z = spot.getFeature(
'POSITION_Z') + (roundid - 1) * float(stacksize) * cal.pixelDepth
z.append(correct_z)
with open(os.path.join(folder5, output), 'ab') as outfile:
DETECTwriter = csv.writer(outfile, delimiter=',')
Sdata = zip(sid, sroundid, x, y, z, q, snr, intensity)
for Srow in Sdata:
DETECTwriter.writerow(Srow)
@String(label="Image Extension", style="", value=".dm3") str_img_ext
@String(label="Saturation", style="", value="0.25") str_sat
@Boolean(label="Close all first", value=False) do_close
"""
test_load_image_bioformats.py
Test a wrapper function to load images using BioFormats
"""
# read in and display ImagePlus object(s)
from loci.plugins import BF
from loci.formats import ImageReader
from loci.formats import MetadataTools
from ij import IJ
from ome.units import UNITS
if do_close:
IJ.run("Close All")
file = str_dir + "/" + str_img_nam + str_img_ext
imps = BF.openImagePlus(file)
for imp in imps:
imp.setTitle(str_img_nam)
imp.show()
IJ.run("Enhance Contrast", "saturated=" + str_sat);
reader = ImageReader()
omeMeta = MetadataTools.createOMEXMLMetadata()
reader.setMetadataStore(omeMeta)
reader.setId(file)
seriesCount = reader.getSeriesCount()
reader.close()
