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 get_image(info, default_path, used_files):
"""handle getting image from file"""
check_for_file_overlap_OK = False;
while not check_for_file_overlap_OK:
info.set_input_file_path(file_location_chooser(default_path));
if info.get_input_file_path() in used_files:
dlg = GenericDialog("Image already used...");
dlg.addMessage("This image has already been used in this analysis run. \n " +
"Continue with this image, or choose a new one?");
dlg.setOKLabel("Continue");
dlg.setCancelLabel("Choose again...");
dlg.showDialog();
check_for_file_overlap_OK = False if dlg.wasCanceled() else True;
else:
check_for_file_overlap_OK = True;
import_opts, info = choose_series(info.get_input_file_path(), info)
imps = bf.openImagePlus(import_opts);
imp = imps[0];
try:
memory_usage = IJ.currentMemory()/IJ.maxMemory();
print("memory usage = " +str(memory_usage));
# arbitrary limit...
if memory_usage > 0.95:
IJ.run(imp, "8-bit", "");
print("WARNING - IMAGE CONVERTED TO 8 BIT TO CONSERVE MEMORY!");
info.set_metadata_file_path(os.path.splitext(info.get_input_file_path())[0] + ".txt");
metadata = import_iq3_metadata(info.get_metadata_file_path());
IJ.run(imp, "Properties...", "channels=" + str(int(metadata['n_channels'])) +
" slices=" + str(int(metadata['z_pixels'])) +
" frames=1 unit=" + str(metadata['x_unit']) +
" pixel_width=" + str(metadata['x_physical_size']) +
" pixel_height=" + str(metadata['y_physical_size']) +
" voxel_depth=" + str(metadata['z_extent']/metadata['z_pixels']));
info.set_xy_pixel_size_um(metadata['x_physical_size']);
info.set_z_plane_spacing_um(metadata['z_extent']/metadata['z_pixels']);
info = parse_info_from_filename(info);
except e as Exception:
print(e.message);
finally:
if imp is not None:
imp.close();
return imp, info;
def main():
# define here which membrane indices will be used in the analysis, with last index the "control" index
membrane_indices = [-1, 0, 1, 3]
# for now, work with frontmost open image...
imp = IJ.getImage()
im_title = imp.getTitle()
settings = MembraneEvolutionAnalysisSettings(
membrane_indices=membrane_indices)
settings.loadPersistedSettings()
timestamp = datetime.strftime(datetime.now(), '%Y-%m-%d %H-%M-%S')
DirectoryChooser.setDefaultDirectory((settings.output_path))
dc = DirectoryChooser('Select the root folder for saving output')
output_root = dc.getDirectory()
if output_root is None:
raise IOError('no output path chosen')
settings.output_path = output_root
# get calibration
cal = imp.getCalibration()
if cal.getTimeUnit() == "sec":
cal.setTimeUnit('s')
# pop up a dialog prompting for selection of zero time point, frame interval, and time step for analysis
time_steps_not_ok = True
while time_steps_not_ok:
dialog = NonBlockingGenericDialog("Determine time parameters...")
dialog.addNumericField("0 timepoint frame (1-index): ",
settings.zero_timepoint_frame, 0)
dialog.addNumericField("Acquisition time step (s): ",
cal.frameInterval,
2) # assume stored in seconds
dialog.addNumericField(
"Time step for analysis (s): ",
cal.frameInterval * settings.analysis_frame_step, 2)
dialog.showDialog()
if dialog.wasCanceled():
return
zero_f = dialog.getNextNumber()
acq_t_step = dialog.getNextNumber()
analysis_t_step = dialog.getNextNumber()
if acq_t_step != 0 and analysis_t_step != 0:
analysis_frame_step = analysis_t_step / acq_t_step
if round(analysis_frame_step) == analysis_frame_step:
time_steps_not_ok = False
settings.zero_timepoint_frame = zero_f
settings.analysis_frame_step = analysis_frame_step
if time_steps_not_ok:
warning_dlg = GenericDialog("Error!")
warning_dlg.addMessage(
"Analysis time step must be an integer multiple of acquisition time steps, and neither should be zero!!"
)
warning_dlg.setOKLabel("Try again...")
warning_dlg.showDialog()
if warning_dlg.wasCanceled():
return
start_frame = int(((zero_f - 1) % analysis_frame_step) + 1)
end_frame = int(imp.getNFrames() -
(imp.getNFrames() - zero_f) % analysis_frame_step)
frames = [
f + 1
for f in range(start_frame - 1, end_frame, int(analysis_frame_step))
]
print("frames = " + str(frames))
imp.killRoi()
analysis_imp = SubstackMaker().makeSubstack(
imp,
str(start_frame) + "-" + str(end_frame) + "-" +
str(int(analysis_frame_step)))
imp.changes = False
imp.close()
analysis_imp.show()
drawn_membranes = [
TimepointsMembranes(input_image_title=im_title,
time_point_s=(t - 1) * acq_t_step) for t in frames
]
membranes_listener = UpdateRoiImageListener(drawn_membranes)
analysis_imp.addImageListener(membranes_listener)
# now attach roi listener to store all 0th membranes after showing a waitforuserdialog to prompt continuation
IJ.setTool("freeline")
for membrane_idx in membrane_indices:
# if membrane_idx>50:
# IJ.setTool("line");
analysis_imp.killRoi()
membranes_listener.resetLastFrame()
membranes_listener.setCurrentMembraneIndex(membrane_idx)
analysis_imp.setZ(1)
continue_dlg = WaitForUserDialog(
"Continue?", "Click OK once all the " + str(membrane_idx) +
"-index membranes have been drawn")
continue_dlg.show()
membranes_listener.imageUpdated(analysis_imp)
drawn_membranes = membranes_listener.getDrawnMembraneTimepointsList()
json_path = os.path.join(output_root,
"Membranes " + timestamp + ".json")
f = open(json_path, 'w+')
try:
json.dump(drawn_membranes, f, default=encode_membrane)
finally:
f.close()
# save csv containing mebrane measurements for current membrane index
csv_path = os.path.join(
output_root, ("Membrane measurements " + timestamp + ".csv"))
if membrane_idx == membrane_indices[0]:
try:
f = open(csv_path, 'wb')
writer = csv.writer(f)
writer.writerow([
"Membrane index", ("Time point, " + cal.getTimeUnit()),
("Membrane length, " + cal.getUnit()),
("Euclidean length, " + cal.getUnit()),
"Membrane sinuoisty"
])
finally:
f.close()
try:
f = open(csv_path, 'ab')
writer = csv.writer(f)
for mems in drawn_membranes:
mem = mems.getMembrane(membrane_idx)
if mem is not None:
writer.writerow([
membrane_idx, mems.time_point_s,
mem.getPathLength() * cal.pixelWidth,
mem.getEuclidean() * cal.pixelWidth,
mem.getSinuosity()
])
finally:
f.close()
settings.persistSettings()
settings.save_settings()
print("Finished getting all membranes with indices " +
str(membrane_indices))
analysis_imp.close()
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()
