def getOK(text):
gd = GenericDialog('User prompt')
gd.addMessage(text)
gd.hideCancelButton()
gd.enableYesNoCancel()
gd.showDialog()
return gd.wasOKed()
def showDialogR(R, val):
""" Create dialog for input and save R values in settings
"""
gui = GenericDialog("Heterogeneous Z Correction")
msg = "Heterogeneous Z Correction calculates an optical model\n"\
"based on rational fluorescence intensity attenuation\n"\
"over depth, in the form of (ax+b)/(x+c). Please specify\n"\
"(a,b,c) for each region. You should provide a z-stack with\n"\
"unique pixel values for each region.\n"
gui.addMessage(msg)
for ii in range(len(val)):
gui.addNumericField(
"Region " + str(ii) + " (" + str(val[ii]) + "): a", R[ii][0], 2)
gui.addToSameRow()
gui.addNumericField("b", R[ii][1], 2)
gui.addToSameRow()
gui.addNumericField("c", R[ii][2], 2)
gui.addHelp(
r"https://github.com/alexandrebastien/heterogeneous-z-correction")
gui.showDialog()
if gui.wasOKed():
R = []
for ii in range(len(val)):
R = R + [
(gui.getNextNumber(), gui.getNextNumber(), gui.getNextNumber())
]
Prefs.set("HetZCorr.R", str(R))
return R
else:
return
def _dialog(self,comment): gd = GenericDialog(comment) gd.enableYesNoCancel() gd.showDialog() if gd.wasCanceled(): print "user cancelled dialog" sys.exit(1) option = gd.wasOKed() return option
def get_metadata_table_filepath():
"""Get a the metadata template filename"""
d = GenericDialog("Metadata Template")
d.addMessage("Please choose a metadata template")
d.enableYesNoCancel("OK", "Cancel")
d.hideCancelButton()
d.showDialog()
if d.wasOKed():
od = OpenDialog("Metadata File")
return os.path.join(od.getDirectory(), od.getFileName())
else:
return
def perform_manual_qc(imp, rois, important_channel=1):
"""given cell rois generated by automatic methods, allow user to delete/add/redraw as appropriate"""
for ch in range(imp.getNChannels()):
imp.setC(ch + 1)
sat_frac = 0.99 if (ch + 1) == important_channel else 0.01
IJ.run(imp, "Enhance Contrast", "saturated={}".format(sat_frac))
imp.setC(important_channel)
IJ.setTool("freehand")
proceed = False
roim = RoiManager()
roim.runCommand("Show all with labels")
for roi in rois:
roim.addRoi(roi)
auto_rois_only = rois
while not proceed:
dialog = NonBlockingGenericDialog("Perform manual segmentation")
dialog.setOKLabel("Proceed to next image...")
dialog.addMessage("Perform manual correction of segmentation: ")
dialog.addMessage(
"Draw around cells and add to the region of interest manager (Ctrl+T). "
)
dialog.addMessage("Delete and redraw cells as appropriate. ")
dialog.addMessage(
"Then press \"proceed to next image\" when all cells have been added. "
)
dialog.showDialog()
if dialog.wasCanceled():
print("Manual segmentation canceled")
return auto_rois_only
elif dialog.wasOKed():
if roim.getCount() == 0:
rois = []
confirm_dialog = GenericDialog("Continue?")
confirm_dialog.addMessage(
"No rois selected in this FOV. Are you sure you want to proceed?"
)
confirm_dialog.setOKLabel("Yes, proceed")
confirm_dialog.setCancelLabel("No, not yet")
confirm_dialog.showDialog()
if confirm_dialog.wasOKed():
proceed = True
else:
rois = roim.getRoisAsArray()
proceed = True
roim.reset()
roim.close()
for ch in range(imp.getNChannels()):
imp.setC(ch + 1)
IJ.run(imp, "Enhance Contrast", "saturated={}".format(0.35))
imp.setC(important_channel)
return rois
def save_etc(imp, info, output_folder):
"""handle saving output, final labelling and UI of what to do next"""
dialog = GenericDialog("Marksl1 cell shape prescreen");
dialog.addChoice("Vessel type: ",
info.get_vessel_types(),
info.get_vessel_type());
dialog.addStringField("Channel 1 label: ", info.get_ch1_label());
dialog.addStringField("Channel 2 label: ", info.get_ch2_label());
dialog.addStringField("Experiment identifier: ", info.get_experiment_id());
dialog.addStringField("Embryo identifier: ", info.get_embryo_id());
dialog.setOKLabel("Save preprocessing");
dialog.showDialog();
info.set_vessel_type(dialog.getNextChoice());
info.set_ch1_label(dialog.getNextString());
info.set_ch2_label(dialog.getNextString());
info.set_experiment_id(dialog.getNextString());
info.set_embryo_id(dialog.getNextString());
if dialog.wasCanceled():
return "stop";
if dialog.wasOKed():
exsting_files = os.listdir(output_folder);
r = re.compile(".*" + info.get_embryo_id() + " " + info.get_vessel_type() + ".*")
fns = filter(r.match, exsting_files)
numbers = list((int(s) for fn in fns for s in re.findall(r'\b\d+$', os.path.splitext(fn)[0])));
append_digit = (max(numbers) + 1) if numbers else 1;
ch1str = (info.get_ch1_label() + " ") if info.get_ch1_label() else "";
ch2str = (info.get_ch2_label() + " ") if info.get_ch2_label() else "";
expstr = (info.get_experiment_id() + " ") if info.get_experiment_id() else "";
file_name = ("Cropped " + ch1str + ch2str + expstr +
"e" + str(info.get_embryo_id()) + " " +
info.get_vessel_type() + " " +
str(append_digit));
FileSaver(imp).saveAsTiff(os.path.join(output_folder, (file_name + ".tif")));
info.save_info_to_json(os.path.join(output_folder, (file_name + ".json")));
continueDialog = YesNoCancelDialog(WM.getCurrentWindow(),
"Continue?",
"Continue with same input image or a new input image?",
"New image...",
"Same image");
if continueDialog.cancelPressed():
return "stop";
if continueDialog.yesPressed():
return "continue_newimage";
return "continue_sameimage";
return "stop";
def showTable(self):
"""
Add the main panel to a GenericDialog and show it
"""
gd = GenericDialog("Roi-group table")
gd.addPanel(self) # Add current table instance to panel
gd.addMessage("""If you use this plugin, please cite:
Laurent Thomas. (2020, November 18).
LauLauThom/RoiGroupTable: ImageJ/Fiji RoiGroup Table (Version 1.0)
Zenodo. http://doi.org/10.5281/zenodo.4279049""")
gd.addHelp(r"https://github.com/LauLauThom/RoiGroupTable")
gd.showDialog()
if gd.wasOKed():
# Update ImageJ Roi group names mapping
stringGroup = self.tableModel.getGroupString()
Roi.setGroupNames(stringGroup)
def inputScale(self):
gd=GenericDialog("Scale ROI")
gd.addStringField("X Scale:",str(self.xScale))
gd.addStringField("Y Scale:",str(self.yScale))
gd.addStringField("Scale X to pixel:",str(self.impXpixel))
gd.addStringField("Scale Y to pixel:",str(self.impYpixel))
fields=gd.getStringFields()
self.XscaleField,self.YscaleField=fields[0],fields[1]
self.toXfield,self.toYfield=fields[2],fields[3]
self.XscaleField.addTextListener(self)
self.YscaleField.addTextListener(self)
self.toXfield.addTextListener(self)
self.toYfield.addTextListener(self)
gd.showDialog()
if gd.wasOKed():
return(self.xScale,self.yScale)
else:
return(1.0,1.0)
def choose_series(filepath, params):
"""if input file contains more than one image series (xy position), prompt user to choose which one to use"""
# todo: if necessary (e.g. if lots of series), can improve thumbnail visuals based loosely on https://github.com/ome/bio-formats-imagej/blob/master/src/main/java/loci/plugins/in/SeriesDialog.java
import_opts = ImporterOptions();
import_opts.setId(filepath);
reader = ImageReader();
ome_meta = MetadataTools.createOMEXMLMetadata();
reader.setMetadataStore(ome_meta);
reader.setId(filepath);
no_series = reader.getSeriesCount();
if no_series == 1:
return import_opts, params;
else:
series_names = [ome_meta.getImageName(idx) for idx in range(no_series)];
dialog = GenericDialog("Select series to load...");
dialog.addMessage("There are multiple series in this file! \n" +
"This is probably because there are multiple XY stage positions. \n " +
"Please choose which series to load: ");
thumbreader = BufferedImageReader(reader);
cbg = CheckboxGroup();
for idx in range(no_series):
p = Panel();
p.add(Box.createRigidArea(Dimension(thumbreader.getThumbSizeX(), thumbreader.getThumbSizeY())));
ThumbLoader.loadThumb(thumbreader, idx, p, True);
dialog.addPanel(p);
cb = Checkbox(series_names[idx], cbg, idx==0);
p.add(cb);
dialog.showDialog();
if dialog.wasCanceled():
raise KeyboardInterrupt("Run canceled");
if dialog.wasOKed():
selected_item = cbg.getSelectedCheckbox().getLabel();
selected_index = series_names.index(selected_item);
params.setSelectedSeriesIndex(selected_index);
for idx in range(0, no_series):
import_opts.setSeriesOn(idx, True) if (idx==selected_index) else import_opts.setSeriesOn(idx, False);
reader.close();
return import_opts, params
def get_config_file(folder):
'''Returns the config file name.'''
# Get list of files in the selected directory.
files = os.listdir(folder)
# Check if a config file is present in folder.
if default_config in files:
dialog = GenericDialog('Default config file found!')
dialog.addMessage('Use this file for the analysis?\n \n%s' % os.path.join(folder, default_config))
dialog.enableYesNoCancel()
dialog.showDialog()
if dialog.wasCanceled():
return None
elif dialog.wasOKed():
return default_config
else:
open_dialog = OpenDialog('Select a config file', folder, default_config)
return open_dialog.getFileName()
else:
# Ask user to select a config file.
open_dialog = OpenDialog('Select a config file', folder, default_config)
return open_dialog.getFileName()
sizeGD.addNumericField("Tile overlap percentage",10,0)
sizeGD.addCheckbox("Write fused image sequence to disk",False)
sizeGD.showDialog()
doComputeOverlap = sizeGD.getNextBoolean()
overlapPctStr = str(sizeGD.getNextNumber())
doWriteToDisk = sizeGD.getNextBoolean()
if (doComputeOverlap):
overlapText = "compute_overlap ignore_z_stage"
else:
overlapText = ""
if (doWriteToDisk):
outputPath = imgDir + "substitched"
diskWriteText = "image_output=[Write to disk] output_directory=[" + outputPath + "]"
else:
diskWriteText = "image_output=[Fuse and display]"
if (sizeGD.wasOKed()):
for t in tiles:
shutil.copyfile(imgDir+"tile_"+str(t)+".ome.tif",imgDir+"temp/tile_"+str(ind)+".ome.tif")
ind = ind + 1
IJ.showStatus("Beginning stitch...")
params = ("type=[Grid: row-by-row] order=[Right & Down ] grid_size_x=" +
str(xs[2]) + " grid_size_y=" + str(ys[2]) + " tile_overlap=" + overlapPctStr + " first_file_index_i=1 directory=[" +
imgDir + "temp] file_names=tile_{i}.ome.tif output_textfile_name=TileConfiguration.txt " +
"fusion_method=[Linear Blending] regression_threshold=0.30 max/avg_displacement_threshold=2.50 " +
"absolute_displacement_threshold=3.50 " + overlapText + " subpixel_accuracy " +
"computation_parameters=[Save memory (but be slower)] " + diskWriteText)
IJ.run("Grid/Collection stitching", params)
gd = NonBlockingGenericDialog("Explore full resolution...")
gd.addMessage("Select ROI for visualization at full resolution")
gd.showDialog()
def main():
metadatas = []
runagain = True
offsetx = 0
offsety = 0
interval = 50.0
IJ.run(imp, "RGB Color", "")
IJ.run("Colors...", "foreground=cyan background=white selection=yellow")
while runagain:
dialog = GenericDialog("Define 5x ROI parameters...")
dialog.enableYesNoCancel("Continue and quit",
"Continue and add another line")
dialog.addNumericField("Line scan position 1 X, Y: ", 0, 0)
dialog.addToSameRow()
dialog.addNumericField(", ", 0, 0)
dialog.addNumericField("Line scan position 2 X, Y: ", 0, 0)
dialog.addToSameRow()
dialog.addNumericField(", ", 0, 0)
dialog.addNumericField("Reference image crop origin X, Y: ", offsetx,
0)
dialog.addToSameRow()
dialog.addNumericField(", ", offsety, 0)
dialog.addNumericField("Frame interval (s): ", interval, 2)
dialog.showDialog()
p1x = dialog.getNextNumber()
p1y = dialog.getNextNumber()
p2x = dialog.getNextNumber()
p2y = dialog.getNextNumber()
offsetx = dialog.getNextNumber()
offsety = dialog.getNextNumber()
interval = dialog.getNextNumber()
linescan_overlay = LineScanOverlayMetadata(
(p1x, p1y), (p2x, p2y), (offsetx, offsety), interval)
metadatas.append(linescan_overlay)
roi = linescan_overlay.generateOverlayRoi()
imp.setRoi(roi)
IJ.run("Draw", "stack")
if dialog.wasOKed():
runagain = False
elif dialog.wasCanceled():
return
sd = SaveDialog("Save as AVI...",
os.path.splitext(imp.getTitle())[0],
"line scan overlay.avi")
if sd.getFileName is not None:
metadatas[0].save_to_json(
os.path.join(
sd.getDirectory(),
os.path.splitext(os.path.basename(sd.getFileName()))[0] +
"line scan metadata.json"))
if len(
metadatas
) > 1: # append: multiple writes=slow, but easiest way based on existing framework
for midx in range(1, len(metadatas)):
metadatas[midx].save_to_json(os.path.join(
sd.getDirectory(),
os.path.splitext(os.path.basename(sd.getFileName()))[0] +
"line scan metadata.json"),
append=True)
IJ.saveAs(
imp, "Tiff",
os.path.join(
sd.getDirectory(),
os.path.splitext(os.path.basename(sd.getFileName()))[0] +
" + line scan ROI, no timestamp.tif"))
IJ.run(
imp, "Label...",
"format=00:00:00 starting=0 interval=" + str(interval) +
" x=5 y=20 font=18 text=[] range=1-" + str(imp.getNFrames()))
IJ.run(
imp, "AVI... ", "compression=None frame=10 save=[" +
os.path.join(sd.getDirectory(),
(os.path.splitext(sd.getFileName())[0] +
" + line scan ROI.avi")) + "]")
IJ.saveAs(
imp, "Tiff",
os.path.join(
sd.getDirectory(),
os.path.splitext(os.path.basename(sd.getFileName()))[0] +
" + line scan ROI.tif"))
class Colortags:
'''
This class handles persistence of the name of different color channels.
It instantiates a GUI window to capture and show the color names in use.
Other classes such as ColorMerger needs this to determine the color of the channel being processed.
'''
def __init__(self):
self.window = None
self.tags = {}
self.prefkeys = ["{0}.{1}".format(SUBKEY, name) for name in COLORS]
self.userprefs = Prefs()
self.load()
while not self.tags:
self.edit("Please set at least one colortag.\n\n")
def load(self):
'''
Tries to load IBPlib colortags from IJ prefs.
'''
for i in range(7):
storedtags = self.userprefs.getString(".{0}".format(self.prefkeys[i]), "")
if not storedtags:
continue
trimmedtagslist = [t.strip() for t in storedtags.split(",")]
self.tags.update({i:trimmedtagslist})
def edit(self, msg=""):
'''
Opens the color tags dialog to update color tags
'''
self.window = GenericDialog("ColorMerger - Edit color tags")
self.window.addMessage("{0}Separate tags with a comma.\nBlank values will be ignored.".format(msg))
for i in range(7):
try:
self.window.addStringField(COLORS[i], ", ".join(self.tags[i]), 30)
except KeyError:
self.window.addStringField(COLORS[i], "", 30)
self.window.setOKLabel("Save")
self.window.showDialog()
if self.window.wasOKed():
self.__savetags()
self.load()
def __validate(self):
fields = self.window.getStringFields()
newvalues = {}
for i in range(len(fields)):
txt = fields[i].getText()
newvalues.update({i: txt.strip()})
return newvalues
def __savetags(self):
newvalues = self.__validate()
for i, tags in newvalues.items():
key = self.prefkeys[i]
self.userprefs.set(key, tags)
self.userprefs.savePreferences()
def batch_open_images(pathImage, file_typeImage, name_filterImage=None):
if isinstance(pathImage, File):
pathImage = pathImage.getAbsolutePath()
def check_filter(string):
'''This function is used to check for a given filter.
It is possible to use a single string or a list/tuple of strings as filter.
This function can access the variables of the surrounding function.
:param string: The filename to perform the filtering on.
'''
if name_filterImage:
# The first branch is used if name_filter is a list or a tuple.
if isinstance(name_filterImage, (list, tuple)):
for name_filter_ in name_filterImage:
if name_filter_ in string:
# Exit the function with True.
return True
else:
# Next iteration of the for loop.
continue
# The second branch is used if name_filter is a string.
elif isinstance(name_filterImage, string):
if name_filterImage in string:
return True
else:
return False
return False
else:
# Accept all files if name_filter is None.
return True
def check_type(string):
'''This function is used to check the file type.
It is possible to use a single string or a list/tuple of strings as filter.
This function can access the variables of the surrounding function.
:param string: The filename to perform the check on.
'''
if file_typeImage:
# The first branch is used if file_type is a list or a tuple.
if isinstance(file_typeImage, (list, tuple)):
for file_type_ in file_typeImage:
if string.endswith(file_type_):
# Exit the function with True.
return True
else:
# Next iteration of the for loop.
continue
# The second branch is used if file_type is a string.
elif isinstance(file_typeImage, string):
if string.endswith(file_typeImage):
return True
else:
return False
return False
# Accept all files if file_type is None.
else:
return True
# We collect all files to open in a list.
path_to_Image = []
# Replacing some abbreviations (e.g. $HOME on Linux).
path = os.path.expanduser(pathImage)
path = os.path.expandvars(pathImage)
# If we don't want a recursive search, we can use os.listdir().
for directory, dir_names, file_names in os.walk(pathImage):
# We are only interested in files.
for file_name in file_names:
# The list contains only the file names.
# The full path needs to be reconstructed.
full_path = os.path.join(directory, file_name)
# Both checks are performed to filter the files.
if check_type(file_name):
if check_filter(file_name) is False:
# Add the file to the list of images to open.
path_to_Image.append([
full_path,
os.path.basename(os.path.splitext(full_path)[0])
])
Images = []
for img_path, file_name in path_to_Image:
imp = IJ.openImage(img_path)
maskimage = ops.run("create.img", imp)
cursor = maskimage.localizingCursor()
imp.show()
IJ.run("Select None")
overlay = imp.getOverlay()
if overlay == None:
overlay = Overlay()
imp.setOverlay(overlay)
else:
overlay.clear()
imp.updateAndDraw()
impY = imp.getHeight()
impX = imp.getWidth()
print(impY, impX)
rm = RoiManager.getInstance()
if not rm:
rm = RoiManager()
rm.runCommand("reset")
WaitForUserDialog("Select the landmark and the second point").show()
rm.runCommand("Add")
roi_points = rm.getRoisAsArray()
for Roi in roi_points:
xpoints = Roi.getPolygon().xpoints
ypoints = Roi.getPolygon().ypoints
print(xpoints, ypoints)
print('Start Landmark', xpoints[0], ypoints[0])
fixedpointX = xpoints[0]
fixedpointY = ypoints[0]
print('End Landmark', xpoints[1], ypoints[1])
IJ.makeLine(xpoints[0], ypoints[0], xpoints[1], ypoints[1])
gui = GenericDialog("Rotation Angle")
gui.addNumericField("Choose Angle", 15, 0)
gui.showDialog()
if gui.wasOKed():
rotateangle = gui.getNextNumber()
IJ.run("Rotate...", "angle=" + str(int(float(rotateangle))))
rm.runCommand("reset")
overlay = imp.getOverlay()
rm.runCommand("Add")
roi_points = rm.getRoisAsArray()
for Roi in roi_points:
xpoints = Roi.getPolygon().xpoints
ypoints = Roi.getPolygon().ypoints
print(xpoints, ypoints)
print('Rotated Start Landmark', xpoints[0], ypoints[0])
print('Rotated End Landmark', xpoints[1], ypoints[1])
slope = (ypoints[1] - ypoints[0]) / (xpoints[1] - xpoints[0] + 1.0E-20)
intercept = fixedpointY - slope * fixedpointX
print(fixedpointX, fixedpointY)
print('Slope', slope, 'Intercept', intercept)
XwY0 = -intercept / slope
YxwY0 = slope * XwY0 + intercept
XwYmax = (impY - intercept) / slope
YxwYmax = slope * XwYmax + intercept
YwX0 = intercept
XywX0 = (YwX0 - intercept) / slope
YwXmax = impX * slope + intercept
XxwXmax = (YwXmax - intercept) / slope
rm.runCommand("reset")
if XwY0 > 0:
lineROIA = Line(fixedpointX, fixedpointY, XwY0, YxwY0)
lineROIB = Line(fixedpointX, fixedpointY, XwYmax, YxwYmax)
overlay.add(lineROIA)
overlay.add(lineROIB)
if XwY0 < 0:
lineROIA = Line(fixedpointX, fixedpointY, XywX0, YwX0)
lineROIB = Line(fixedpointX, fixedpointY, XxwXmax, YwXmax)
overlay.add(lineROIA)
overlay.add(lineROIB)
while cursor.hasNext():
cursor.fwd()
X = cursor.getDoublePosition(0)
Y = cursor.getDoublePosition(1)
if abs(Y - slope * X - intercept) <= 4:
cursor.get().set(0)
else:
cursor.get().set(1)
labeling = ops.labeling().cca(maskimage,
StructuringElement.EIGHT_CONNECTED)
# get the index image (each object will have a unique gray level)
labelingIndex = labeling.getIndexImg()
dataImg = ds.create(labelingIndex)
location = ls.resolve(
str(savedir) + '/' + file_name + '.' + file_type_image)
dio.save(dataImg, location)
imp.close()
imp.setPosition(1, eventOutL, 1)
else:
eventOutL = frames + slider3_feedback + 1 + slider2_feedback * (
ch * frames) + evt * (zplanes * ch * frames)
imp2.setPosition(1, eventOutL, 1)
# Define the pre-conditions for loading the data, default values represent my normal acquisition parameters only the loop has to be set, the rest is read from metadata
psgd = GenericDialog("Pre-Set")
psgd.addCheckbox(
"Images open?", False
) # if your images are already open as a virtual stack, you can avoid to load again
psgd.showDialog()
if psgd.wasOKed():
choiceIm = psgd.getCheckboxes().get(0).getState()
# load data as virtual stack, simple image stack
if choiceIm == False:
IJ.run("Close All", "")
impDir = OpenDialog("Select the 6D dataset").getPath()
impDir = impDir.replace("\\", "/")
IJ.run(
"Bio-Formats", "open=" + impDir +
" color_mode=Default display_metadata rois_import=[ROI manager] view=[Standard ImageJ] stack_order=Default use_virtual_stack"
)
#define ImagePlus to variable and remove path from title
imp = WM.getCurrentImage()
else:
# List column headers
table = tableWindow.getResultsTable()
headers = table.getHeadings()
# Generate dialog with dropdown for column selection
dialog = GenericDialog("PieChart from table column")
dialog.addChoice("Data column", headers, headers[0])
dialog.addMessage(
"""Hover the mouse over the plot to view absolute and relative (%) values\n
Right-click to set colors, export to PNG...\n
Note: BarCharts usually provide better distinction than PieCharts for sectors with similar sizes (see Help)."""
)
dialog.addHelp(r"https://www.data-to-viz.com/caveat/pie.html")
dialog.showDialog()
# Generate PieChart with data column
if dialog.wasOKed():
# Get the data column as string
selectedHeader = dialog.getNextChoice()
column = table.getColumnAsVariables(selectedHeader)
columnString = [str(item)[1:-1]
for item in column] # [1:-1] to remove the ""
# Make the PieChart for this data column
if columnString:
chart = PieChart(selectedHeader, columnString)
chart.showFrame("PieChart")
def main_interactive():
"""The main routine for running interactively."""
log.info('Running in interactive mode.')
(base, fname) = ui_get_input_file()
if (base is None):
return
log.warn("Parsing project file: %s" % (base + fname))
IJ.showStatus("Parsing experiment file...")
mosaics = fv.FluoViewMosaic(join(base, fname), runparser=False)
IJ.showStatus("Parsing mosaics...")
progress = 0.0
count = len(mosaics.mosaictrees)
step = 1.0 / count
for subtree in mosaics.mosaictrees:
IJ.showProgress(progress)
mosaics.add_mosaic(subtree)
progress += step
IJ.showProgress(progress)
IJ.showStatus("Parsed %i mosaics." % len(mosaics))
dialog = GenericDialog('FluoView OIF / OIB Stitcher')
if len(mosaics) == 0:
msg = ("Couldn't find any (valid) mosaics in the project file.\n"
" \n"
"Please make sure to have all files available!\n"
" \n"
"Will stop now.\n")
log.warn(msg)
dialog.addMessage(msg)
dialog.showDialog()
return
msg = "------------------------ EXPORT OPTIONS ------------------------"
dialog.addMessage(msg)
formats = ["OME-TIFF", "ICS/IDS"]
dialog.addChoice("Export Format", formats, formats[0])
dialog.addCheckbox("separate files by Z slices (OME-TIFF only)?", False)
msg = "------------------------ EXPORT OPTIONS ------------------------"
dialog.addMessage(msg)
dialog.addMessage("")
dialog.addMessage("")
msg = gen_mosaic_details(mosaics)
log.warn(msg)
msg += "\n \nPress [OK] to write tile configuration files\n"
msg += "and continue with running the stitcher."
dialog.addMessage(msg)
dialog.showDialog()
opts = {}
if dialog.getNextChoice() == 'ICS/IDS':
opts['export_format'] = '".ids"'
else:
opts['export_format'] = '".ome.tif"'
if dialog.getNextBoolean() == True:
opts['split_z_slices'] = 'true'
code = imagej.gen_stitching_macro_code(mosaics, 'templates/stitching',
path=base, tplpath=imcftpl, opts=opts)
log.warn("============= generated macro code =============")
log.warn(flatten(code))
log.warn("============= end of generated macro code =============")
if dialog.wasOKed():
log.warn('Writing stitching macro.')
imagej.write_stitching_macro(code, fname='stitch_all.ijm', dname=base)
log.warn('Writing tile configuration files.')
imagej.write_all_tile_configs(mosaics, fixsep=True)
log.warn('Launching stitching macro.')
IJ.runMacro(flatten(code))
IJ.showStatus("Computing...")
computedImage = reduce(self.addImages,imgList)
computedImage.show()
IJ.showStatus("Ready")
## Main body of script
opener = OpenDialog("Select parent LSM file...")
parentLSMFilePath = opener.getPath()
if (parentLSMFilePath is not None):
stackInfo = parse_tile_info_file(parentLSMFilePath + "_tiles/tile_info.txt")
channelTexts = map(lambda x: str(x), filter(lambda x:os.path.isfile(parentLSMFilePath+"_tiles/objects/C"+str(x)+".objects.keep.unique.csv"),range(1,stackInfo[0]+1)))
gd = GenericDialog("Specify parameters...")
gd.addChoice("Which_channel",channelTexts,channelTexts[0])
gd.showDialog()
if gd.wasOKed():
channel = int(gd.getNextChoice())
## Obtains global coordinate system for tiles
scale_info = estimate_scale_multiplier(parentLSMFilePath+"_tiles/tile_1.ome.tif",parentLSMFilePath+"_tiles/resized/tile_1.tif")
## Parses each of the object files
objectDB = [[] for x in range(4)]
objectDB[0] = parse_object_file_into_db(parentLSMFilePath+"_tiles/objects/C"+str(channel)+".objects.keep.contained.csv")
objectDB[1] = parse_object_file_into_db(parentLSMFilePath+"_tiles/objects/C"+str(channel)+".objects.keep.duplicated.csv")
objectDB[2] = parse_object_file_into_db(parentLSMFilePath+"_tiles/objects/C"+str(channel)+".objects.keep.restitched.csv")
objectDB[3] = parse_object_file_into_db(parentLSMFilePath+"_tiles/objects/C"+str(channel)+".objects.keep.unique.csv")
## Converts object global coordinates to rescaled coordinates
for i in range(len(objectDB)):
for j in range(len(objectDB[i])):
def get_ok():
gd = GenericDialog("Caution")
gd.addMessage("Do you want to overwrite the files ? ")
gd.showDialog()
return gd.wasOKed()
DIALOG = True
if (DIALOG):
# ----------------- DIALOG TO FILL GLOBAL PARAMETERS -----
gui = GenericDialog("Parameters")
gui.addStringField("NGROK Server address :", "0.tcp.ngrok.io")
gui.addStringField("PORT :", "")
gui.showDialog()
HOST = gui.getNextString()
PORT = int(gui.getNextString())
gui = GenericDialogPlus("Parameters")
gui.addFileField("Select a model file in Keras format (*.h5) : ", "")
gui.showDialog()
if gui.wasOKed():
LOCAL_MODEL_FILENAME = gui.getNextString()
gui = GenericDialogPlus("Parameters")
gui.addFileField("Select a python script file to upload on the server (*.py) : ", "")
gui.showDialog()
if gui.wasOKed():
LOCAL_PREDICTION_SCRIPT = gui.getNextString()
jsch=JSch()
# SSH Connection to DeepLearning server
IJ.log("-- Connection to FiGoCo Server")
time0 = time.time()
session=jsch.getSession("root", HOST, PORT);
measurements_filename = imp_title[:-4]
IJ.saveAs("Results", "{}{}.csv".format(path, measurements_filename))
IJ.selectWindow("Results")
IJ.run("Close")
IJ.log("Measurements saved at {}{}.csv".format(path,
measurements_filename))
# Close the active image so IJ can move on to the next
imp.close()
n_images = WindowManager.getImageCount()
i = 0
while i < n_images:
measure_rois()
i += 1
# Clear ROI manager (after OKing with user) so that there aren't still
# ROIs that will be used in next measurement
gd = GenericDialog("ROI deletion warning")
gd.addMessage("Do you wish to clear current ROIs?")
gd.enableYesNoCancel()
choice = gd.showDialog()
roim = RoiManager.getInstance()
if gd.wasCanceled():
pass
elif gd.wasOKed():
roim.reset()
else:
print("NO")
# Asks for parameters
gd = GenericDialog("Set Parameters...")
gd.addNumericField("Start tile:",1,0)
gd.addNumericField("Finish tile:",9,0)
gd.addNumericField("Final disk space / Initial disk space:",0.25,2)
gd.addNumericField("Step size (higher is faster but uses more memory):",10,0)
gd.showDialog()
startTile = int(gd.getNextNumber())
finishTile = int(gd.getNextNumber())
ratioRaw = gd.getNextNumber()
ratio = math.sqrt(ratioRaw)
stepSize = int(gd.getNextNumber())
# Performs scaling
if (gd.wasOKed()):
anchorTiles = range(startTile,finishTile+1,stepSize)
print anchorTiles
for i in anchorTiles:
if (i+stepSize-1 > finishTile):
lastAnchorTile = finishTile
else:
lastAnchorTile = i+stepSize-1
iterTiles = range(i,lastAnchorTile+1)
params = "open=[" + theFilePath + "] color_mode=Default view=Hyperstack stack_order=XYCZT series_list=" + str(i) + "-" + str(lastAnchorTile)
print params
IJ.run("Bio-Formats Importer", params)
imageIDList = WindowManager.getIDList()
if (len(imageIDList) == len(iterTiles)):
count = 0
uGshapemax = gdp.getNextNumber()
uOverlap = gdp.getNextNumber()
uExclude = gdp.getNextChoice()
# Files will automatically be output to a new Fiji_Analysis directory. If this directory already exists, files will be overwritten. This checks to make sure the directory does not yet exist.
if path.exists(outdir + File.separatorChar +
"Fiji_Analysis") and path.isdir(outdir + File.separatorChar +
"Fiji_Analysis"):
gdchk = GenericDialog("WARNING")
gdchk.addMessage(
"Analysis folder already exists. Choose a different directory to avoid overwritng your current data"
)
gdchk.hideCancelButton()
gdchk.showDialog()
print "Analysis folder already exists. Choose a new directory to avoid overwriting your current analysis"
uknow = gdchk.wasOKed()
if uknow == True:
IJ.getImage()
#Creates Fiji_Analysis directory.
File(outdir + File.separatorChar + "Fiji_Analysis").mkdir()
analysisOut = outdir + File.separatorChar + "Fiji_Analysis"
print analysisOut
inputPaths = [path_wt, path_dic, path_mut, path_bg]
# Since the script is critically depedent on file input order, files are duplicated and saved with easily referenced names in the new Directory. 0 = WT, 1 = DIC, 2 = MUT, 3 = BG. ALWAYS.
newPaths = []
for p in inputPaths:
IJ.open(p)
tmp = IJ.openImage(p)
