def save_qc_image(imp, rois, output_path):
"""save rois overlaid on imp to output_path"""
imp.killRoi()
roim = RoiManager(False)
for roi in rois:
roim.addRoi(roi)
roim.runCommand("Show All with labels")
RGBStackConverter.convertToRGB(imp)
roim.moveRoisToOverlay(imp)
FileSaver(imp).saveAsTiff(output_path)
roim.runCommand("Show None")
roim.close()
def segmentation(imp, spot_data, channel, diameter_init, ES_tolerance, ES_area_max, ES_ctrl_pts, ES_iteration, repeat_max):
# Open files
cal = imp.getCalibration()
manager = RoiManager.getInstance()
if manager is None:
manager = RoiManager()
# Prepare log files for output
options = IS.MEDIAN | IS.AREA | IS.MIN_MAX | IS.CENTROID | IS.PERIMETER | IS.ELLIPSE | IS.SKEWNESS
convergence = []
Sintensity = []
for spot in spot_data:
repeat = 0
flag = False
spotID = int(spot[0])
Xcenter = (float(spot[1]) / cal.pixelWidth)
Ycenter = (float(spot[2]) / cal.pixelHeight)
Quality = float(spot[3])
diameter_init = float(spot[4] / cal.pixelWidth) * 2.0
while True:
manager = RoiManager.getInstance()
if manager is None:
manager = RoiManager()
Xcurrent = int(Xcenter - diameter_init / 2.0)
Ycurrent = int(Ycenter - diameter_init / 2.0)
Dcurrent1 = int(diameter_init * (1.2 - repeat / 10.0))
Dcurrent2 = int(diameter_init * (0.8 + repeat / 10.0))
roi = OvalRoi(Xcurrent, Ycurrent, Dcurrent1, Dcurrent2)
imp.setPosition(channel)
imp.setRoi(roi)
Esnake_options1 = "target_brightness=Bright control_points=" + \
str(ES_ctrl_pts) + " gaussian_blur=0 "
Esnake_options2 = "energy_type=Contour alpha=2.0E-5 max_iterations=" + \
str(ES_iteration) + " immortal=false"
IJ.run(imp, "E-Snake", Esnake_options1 + Esnake_options2)
roi_snake = manager.getRoisAsArray()
roi_ind = len(roi_snake) - 1
stats = IS.getStatistics(
imp.getProcessor(), options, imp.getCalibration())
perimeter = roi_snake[roi_ind].getLength() * cal.pixelWidth
circularity = 4.0 * 3.1417 * (stats.area / (perimeter * perimeter))
if stats.area > 17.0 and stats.area < ES_area_max and stats.skewness < -0.01 and circularity > 0.01 and stats.minor > 2.0 and boundaries(Xcenter, Ycenter, stats.xCentroid / cal.pixelWidth, stats.yCentroid / cal.pixelHeight, ES_tolerance):
Sintensity = stats.median
convergence.append(True)
break
if stats.median > 6000 and stats.area > 17.0 and stats.area < ES_area_max:
Sintensity = stats.median
convergence.append(True)
break
elif repeat > repeat_max:
manager.select(imp, roi_ind)
manager.runCommand(imp, 'Delete')
roi = OvalRoi(Xcenter + 1.0 - diameter_init / 2.0, Ycenter +
1.0 - diameter_init / 2.0, diameter_init, diameter_init)
imp.setRoi(roi)
manager.add(imp, roi, spotID)
roi_snake.append(roi)
stats = IS.getStatistics(
imp.getProcessor(), options, imp.getCalibration())
Sintensity = stats.median
convergence.append(False)
break
else:
IJ.log('Area=' + str(stats.area) + ' Skewness=' + str(stats.skewness) +
' circularity=' + str(circularity) + ' Minor=' + str(stats.minor))
manager.select(imp, roi_ind)
manager.runCommand(imp, 'Delete')
repeat += 1
# End Spot-segmentation
# End all Spots-segmentation
manager.runCommand(imp, 'Show All')
imp.setPosition(channel)
color = imp.createImagePlus()
ip = imp.getProcessor().duplicate()
color.setProcessor("segmentation" + str(channel), ip)
color.show()
IJ.selectWindow("segmentation" + str(channel))
manager.moveRoisToOverlay(color)
spot_optimal = manager.getRoisAsArray()
manager.reset()
for i in xrange(0, len(spot_optimal)):
spot = spot_optimal[i]
spot.setStrokeWidth(2)
if convergence[i]:
spot.setStrokeColor(Color.GREEN)
else:
spot.setStrokeColor(Color.MAGENTA)
imp.setRoi(spot)
manager.add(imp, spot, i)
manager.runCommand(imp, 'Show All')
imp.setPosition(channel)
def Overlayer(org_size, dirs):
""" Overlays ROIs with appropriate color,
saves to .tif and animates aligned images to .gif """
# Get colors.
Colors, Colors_old = colorlist()
# Get ROImanager.
rm = RoiManager().getInstance()
rois = rm.getCount()
# Overlays ROI on aligned images, converts to 8-bit (for gif).
for root, directories, filenames in os.walk(dirs["Composites_Aligned"]):
for filename in filenames:
imp = IJ.openImage(os.path.join(root, filename))
converter = ImageConverter(imp)
converter.setDoScaling(True)
converter.convertToGray8()
# Lookup table and local contrast enhancement for vizualisation.
IJ.run(imp, "Rainbow RGB", "")
IJ.run(imp, "Enhance Local Contrast (CLAHE)",
"blocksize=127 histogram=256 maximum=3 mask=*None*")
for roi in range(rois):
roi_obj = rm.getRoi(roi)
roi_obj.setStrokeWidth(2)
if roi < 19:
roi_obj.setStrokeColor(Color(*Colors[roi][0:3]))
else:
roi_obj.setStrokeColor(eval(Colors_old[roi]))
rm.moveRoisToOverlay(imp)
IJ.saveAs(imp, "Tiff", os.path.join(dirs["Overlays"], filename))
# Opens overlaid images, saves as tiff stack.
overlay_stack = IJ.run("Image Sequence...", "open="+dirs["Overlays"]+
" number=3040 starting=0 increment=1 scale=300 file=.tif sort")
# Takes care of spaces in titles.
tiftitle = Title.replace(" ", "_")
tiftitle = tiftitle.replace(".", "_")
# Gets dimensions for scalebar.
imp = WindowManager.getImage("Overlays")
dimensions = imp.getDimensions()
size = dimensions[0] + dimensions[1]
microns = org_size / size
# Sets scale and writes scale-bar, flattens overlays.
IJ.run(imp, "Set Scale...", "distance=1 known="
+str(microns)+" pixel=1 unit=micron")
IJ.run(imp, "Scale Bar...",
"width=10 height=4 font=14 color=Yellow background=None location=[Lower Right] bold overlay")
IJ.run(imp, "Flatten", "stack")
IJ.saveAs(imp, "Tiff", os.path.join(dirs["Gifs"], tiftitle))
# Animates tiff stack from directoy.
for root, directories, filenames in os.walk(dirs["Gifs"]):
for filename in filenames:
if tiftitle in filename and filename.endswith(".tif"):
# set=xx parameter controls gif speed.
# for additional parameters run with macro recorder.
try:
print "Animating gif..."
imp = WindowManager.getImage(tiftitle + ".tif")
gif = IJ.run("Animated Gif ... ",
"set=200 number=0 filename="
+ os.path.join(dirs["Gifs"], tiftitle + ".gif"))
except Exception, e:
print str(e)
print "gif animated."
