def scaleImageUI():
gd = GenericDialog("Scale")
gd.addSlider("Scale", 1, 200, 100)
gd.addCheckbox("Preview", True)
# The UI elements for the above two inputs
slider = gd.getSliders().get(0) # the only one
checkbox = gd.getCheckboxes().get(0) # the only one
imp = WM.getCurrentImage()
if not imp:
print "Open an image first!"
return
previewer = ScalingPreviewer(imp, slider, checkbox)
slider.addAdjustmentListener(previewer)
checkbox.addItemListener(previewer)
gd.showDialog()
if gd.wasCanceled():
previewer.reset()
print "User canceled dialog!"
else:
previewer.scale()
previewer.destroy()
def getOptions():
pixels = zeros('f', 4) # 4 elements
# First Dialog Box
item = [
"coralline", "tunicate", "red", "macro", "background", "more than one"
]
gd = GenericDialog("Options")
gd.addRadioButtonGroup("options", item, 3, 2, "coralline")
gd.showDialog()
button = gd.getNextRadioButton()
# Second Dialog Box
gd2 = GenericDialog("Multiple Options")
items = ["coralline", "tunicate", "red", "macro", "garbage"]
defaultVal = [False] * 5
gd2.addCheckboxGroup(2, 3, items, defaultVal)
gd2.addNumericField("coralline %", 0, 0)
gd2.addNumericField("tunicate %", 0, 0)
gd2.addNumericField("red %", 0, 0)
gd2.addNumericField("macro %", 0, 0)
gd2.addNumericField("background %", 0, 0)
if gd.wasCanceled():
return 0
if button == "coralline":
pixels[0] = 1
elif button == "tunicate":
pixels[1] = 1
elif button == "red":
pixels[2] = 1
elif button == "macro":
pixels[3] = 1
elif button == "more than one":
gd2.showDialog()
checklist = gd2.getCheckboxes()
pixels[0] = int(
checklist[0].state) * (float(gd2.getNextNumber()) / 100)
pixels[1] = int(
checklist[1].state) * (float(gd2.getNextNumber()) / 100)
pixels[2] = int(
checklist[2].state) * (float(gd2.getNextNumber()) / 100)
pixels[3] = int(
checklist[3].state) * (float(gd2.getNextNumber()) / 100)
return pixels
def Options(sourceFolder):
#globals
global gGetNumChanFromScanImage
global gNumChannels
global gDoAlign
global gAlignThisChannel
global gDoCrop
global gCropLeft
global gCropTop
global gCropWidth
global gCropHeight
global gAlignOnMiddleSlice
global gAlignOnThisSlice
global gRemoveCalibration
global gLinearShift
global gSave8bit
tifNames = [file.name for file in File(sourceFolder).listFiles(Filter())]
numTifs = len(tifNames)
gd = GenericDialog('Align Batch 6 Options')
#gd.addStringField('Command: ', '')
gd.addMessage('Source Folder: ' + sourceFolder)
gd.addMessage('Number of .tif files: ' + str(numTifs))
#gd.setInsets(5,0,3)
#0
gd.addCheckboxGroup(
1, 1, ['Get Number Of Channels From ScanImage 3.x or 4.x header'],
[gGetNumChanFromScanImage], ['Channels'])
gd.addNumericField(
'Otherwise, Assume All Stacks Have This Number Of Channels: ',
gNumChannels, 0)
print gLinearShift
#1
gd.addCheckboxGroup(1, 1, ['Remove Linear Calibration From ScanImage 4.x'],
[gRemoveCalibration], ['ScanImage4'])
gd.addNumericField('And offset (subtract) by this amount: ', gLinearShift,
0)
#2
gd.addCheckboxGroup(1, 1, ['Crop All Images (pixels)'], [gDoCrop],
['Crop'])
gd.addNumericField('Left', gCropLeft, 0)
gd.addNumericField('Top', gCropTop, 0)
gd.addNumericField('Width', gCropWidth, 0)
gd.addNumericField('Height', gCropHeight, 0)
#gd.setInsets(5,0,3)
#3
gd.addCheckboxGroup(1, 1, ['Run MultiStackReg'], [gDoAlign],
['MultStackReg'])
gd.addNumericField('If 2 Channels Then Align On This Channel',
gAlignThisChannel, 0)
#4
gd.addCheckboxGroup(1, 1, ['Start Alignment On Middle Slice'],
[gAlignOnMiddleSlice], ['Align On Middle Slice'])
gd.addNumericField('Otherwise, Start Alignment On This Slice',
gAlignOnThisSlice, 0)
#5
gd.addCheckboxGroup(1, 1, ['Save 8-bit'], [gSave8bit],
['Save 8-bit (at end)'])
#gd.addCheckbox('Save 8-bit', gSave8bit)
gd.showDialog()
if gd.wasCanceled():
print 'Options Was Cancelled by user'
return 0
else:
print 'Reading values'
gNumChannels = int(gd.getNextNumber())
gLinearShift = int(gd.getNextNumber())
gCropLeft = int(gd.getNextNumber())
gCropTop = int(gd.getNextNumber())
gCropWidth = int(gd.getNextNumber())
gCropHeight = int(gd.getNextNumber())
gAlignThisChannel = int(gd.getNextNumber())
gAlignOnThisSlice = int(gd.getNextNumber())
checks = gd.getCheckboxes()
checkIdx = 0
for check in checks:
#print check.getState()
if checkIdx == 0:
gGetNumChanFromScanImage = check.getState()
if checkIdx == 1:
gRemoveCalibration = check.getState()
if checkIdx == 2:
gDoCrop = check.getState()
if checkIdx == 3:
gDoAlign = check.getState()
if checkIdx == 4:
gAlignOnMiddleSlice = check.getState()
if checkIdx == 5:
gSave8bit = check.getState()
checkIdx += 1
# print to fiji console
bPrintLog('These are your global options:', 0)
bPrintLog('gGetNumChanFromScanImage=' + str(gGetNumChanFromScanImage),
1)
bPrintLog('gNumChannels=' + str(gNumChannels), 1)
bPrintLog('gRemoveCalibration=' + str(gRemoveCalibration), 1)
bPrintLog('gLinearShift=' + str(gLinearShift), 1)
bPrintLog('gDoCrop=' + str(gDoCrop), 1)
bPrintLog('gDoAlign=' + str(gDoAlign), 1)
bPrintLog('gAlignThisChannel=' + str(gAlignThisChannel), 1)
bPrintLog('gSave8bit=' + str(gSave8bit), 1)
return 1
def Options(sourceFolder):
#globals
global gFileType
global gGetNumChanFromScanImage
global gNumChannels
global gDoAlign
global gAlignThisChannel
global gDoCrop
global gCropLeft
global gCropTop
global gCropWidth
global gCropHeight
global gAlignOnMiddleSlice
global gAlignOnThisSlice
global gRemoveCalibration
global gLinearShift
global gSave8bit
tifNames = [file.name for file in File(sourceFolder).listFiles(Filter())]
lsmNames = [file.name for file in File(sourceFolder).listFiles(Filter_LSM())]
numTifs = len(tifNames)
numLSM = len(lsmNames)
gd = GenericDialog('Align Batch 7 Options')
#gd.addStringField('Command: ', '')
gd.addMessage('Source Folder: ' + sourceFolder)
gd.addMessage('Number of .tif files: ' + str(numTifs))
gd.addMessage('Number of .lsm files: ' + str(numLSM))
gd.addChoice('File Type', ['tif','lsm'], gFileType)
#gd.setInsets(5,0,3)
#0
gd.addCheckboxGroup(1, 1, ['Get Number Of Channels From ScanImage 3.x or 4.x header'], [gGetNumChanFromScanImage], ['Channels'])
gd.addNumericField('Otherwise, Assume All Stacks Have This Number Of Channels: ', gNumChannels, 0)
print gLinearShift
#1
gd.addCheckboxGroup(1, 1, ['Remove Linear Calibration From ScanImage 4.x'], [gRemoveCalibration], ['ScanImage4'])
gd.addNumericField('And offset (subtract) by this amount: ', gLinearShift, 0)
gd.addMessage('20151110, this number = 2^15-512 = 32768-512 = 32256')
#2
gd.addCheckboxGroup(1, 1, ['Crop All Images (pixels)'], [gDoCrop], ['Crop'])
gd.addNumericField('Left', gCropLeft, 0)
gd.addNumericField('Top', gCropTop, 0)
gd.addNumericField('Width', gCropWidth, 0)
gd.addNumericField('Height', gCropHeight, 0)
#gd.setInsets(5,0,3)
#3
gd.addCheckboxGroup(1, 1, ['Run MultiStackReg'], [gDoAlign], ['MultStackReg'])
gd.addNumericField('If 2 Channels Then Align On This Channel', gAlignThisChannel, 0)
#4
gd.addCheckboxGroup(1, 1, ['Start Alignment On Middle Slice'], [gAlignOnMiddleSlice], ['Align On Middle Slice'])
gd.addNumericField('Otherwise, Start Alignment On This Slice', gAlignOnThisSlice, 0)
#5
gd.addCheckboxGroup(1, 1, ['Save 8-bit'], [gSave8bit], ['Save 8-bit (at end)'])
#gd.addCheckbox('Save 8-bit', gSave8bit)
gd.showDialog()
if gd.wasCanceled():
print 'Options Was Cancelled by user'
return 0
else:
print 'Reading values'
gFileType = gd.getNextChoice()
gNumChannels = int(gd.getNextNumber())
gLinearShift = int(gd.getNextNumber())
gCropLeft = int(gd.getNextNumber())
gCropTop = int(gd.getNextNumber())
gCropWidth = int(gd.getNextNumber())
gCropHeight = int(gd.getNextNumber())
gAlignThisChannel = int(gd.getNextNumber())
gAlignOnThisSlice = int(gd.getNextNumber())
checks = gd.getCheckboxes()
checkIdx = 0
for check in checks:
#print check.getState()
if checkIdx==0:
gGetNumChanFromScanImage = check.getState()
if checkIdx==1:
gRemoveCalibration = check.getState()
if checkIdx==2:
gDoCrop = check.getState()
if checkIdx==3:
gDoAlign = check.getState()
if checkIdx==4:
gAlignOnMiddleSlice = check.getState()
if checkIdx==5:
gSave8bit = check.getState()
checkIdx += 1
# print to fiji console
bPrintLog('These are your global options:', 0)
bPrintLog('gFileType=' + gFileType, 1)
bPrintLog('gGetNumChanFromScanImage=' + str(gGetNumChanFromScanImage), 1)
bPrintLog('gNumChannels=' + str(gNumChannels), 1)
bPrintLog('gRemoveCalibration=' + str(gRemoveCalibration), 1)
bPrintLog('gLinearShift=' + str(gLinearShift), 1)
bPrintLog('gDoCrop=' + str(gDoCrop), 1)
bPrintLog('gDoAlign=' + str(gDoAlign), 1)
bPrintLog('gAlignThisChannel=' + str(gAlignThisChannel), 1)
bPrintLog('gSave8bit=' + str(gSave8bit), 1)
return 1
def run():
### Default arguments
two_sarcomere_size = 25 # determined by filter used.
rotation_angle = 0.0
### Get the image we'd like to work with.
# Don't need to ask where to save the intermediate image since it'll just be saved in the matchedmyo folder anyway
# may change this though. In case they want to keep that image around.
this_img = WindowManager.getCurrentImage()
if this_img == None:
ud = WaitForUserDialog(
"Please select the image you would like to analyze.")
ud.show()
this_img = WindowManager.getCurrentImage()
img_name = this_img.getTitle()
matchedmyo_path = "/home/AD/dfco222/scratchMarx/matchedmyo/" # this would be grabbed from the prompt
gd = GenericDialog("Preprocessing Options")
gd.addCheckbox("Automatic Resizing/Rotation", True)
gd.addCheckbox("CLAHE", True)
gd.addCheckbox("Normalization to Transverse Tubules", True)
gd.showDialog()
if gd.wasCanceled():
return
auto_resize_rotate = gd.getNextBoolean()
clahe = gd.getNextBoolean()
normalize = gd.getNextBoolean()
if auto_resize_rotate:
# Clear selection so it takes FFT of full image
rotation_angle = auto_resize_angle_measure(this_img,
two_sarcomere_size)
if clahe:
clahe_args = "blocksize={} histogram=256 maximum=3 mask=*None* fast_(less_accurate)".format(
two_sarcomere_size)
IJ.run(this_img, "Enhance Local Contrast (CLAHE)", clahe_args)
if normalize:
# Ask the user to select a subsection of the image that looks healthy-ish.
ud = WaitForUserDialog(
"Please select a subsection exhibiting a measure of healthy TT structure using the Rectangle tool.\n"
+ " Only a single cell or several are needed.\n\n" +
" Press 'OK' when finished.")
ud.show()
IJ.setTool("rectangle")
# Duplicate the selected subsection.
selection = this_img.crop()
IJ.run(selection, "Duplicate...", "title=subsection.tif")
# Grab the subsection image and rotate it.
selection = WindowManager.getImage("subsection.tif")
IJ.run(
selection, "Rotate...",
"angle={} grid=1 interpolation=Bicubic enlarge".format(
rotation_angle))
# Ask the user to select a bounding box that contains only tubules
# NOTE: Need to get rid of initial selection since it's the entire image and it's annoying to click out of
IJ.setTool("rectangle")
IJ.run(selection, "Select None", "")
ud = WaitForUserDialog(
"Select a subsection of the image that contains only tubules and no membrane."
)
ud.show()
# Grab the subsection ImagePlus
selection = WindowManager.getCurrentImage()
this_window = WindowManager.getActiveWindow()
selection_small = selection.crop()
IJ.run(selection, "Close", "")
# NOTE: May not actually display this depending on how the macros work
IJ.run(selection_small, "Duplicate...", "title=subsection_small.tif")
# Smooth the selection using the single TT filter.
# NOTE: It won't read in so we're just going to hard code it in since it's simple
tt_filt_row = "0 0 0 1 1 1 1 1 1 0 0 0 0\n"
tt_filt = ""
for i in range(21):
tt_filt += tt_filt_row
IJ.run("Convolve...", "text1=[" + tt_filt + "] normalize")
# Segment out the TTs from the 'gaps' using Gaussian Adaptive Thresholding.
selection_small = WindowManager.getImage("subsection_small.tif")
IJ.run(selection_small, "Duplicate...", "title=thresholded.tif")
threshed = WindowManager.getImage("thresholded.tif")
IJ.run(threshed, "Auto Local Threshold",
"method=Bernsen radius=7 parameter_1=1 parameter_2=0 white")
# Select the TTs from the thresholded image.
IJ.run(threshed, "Create Selection", "")
tt_selection = WindowManager.getImage("subsection_small.tif")
IJ.selectWindow("thresholded.tif")
IJ.selectWindow("subsection_small.tif")
IJ.run(tt_selection, "Restore Selection", "")
# Get TT intensity statistics.
stat_options = IS.MEAN | IS.MIN_MAX | IS.STD_DEV
stats = IS.getStatistics(tt_selection.getProcessor(), stat_options,
selection_small.getCalibration())
# Calculate pixel ceiling intensity value based on heuristic.
# TODO: Add a catch for data type overflow.
pixel_ceiling = stats.mean + 3 * stats.stdDev
print "px ceil:", pixel_ceiling
# Invert selection to get inter-sarcomeric gap intensity statistics.
IJ.run(tt_selection, "Make Inverse", "")
stat_options = IS.MEAN | IS.MIN_MAX | IS.STD_DEV
stats = IS.getStatistics(tt_selection.getProcessor(), stat_options,
selection_small.getCalibration())
# Calculate pixel floor intensity value based on heuristic.
pixel_floor = stats.mean - stats.stdDev
# TODO: Add a catch for data type underflow.
print "px floor:", pixel_floor
# Threshold original image based on these values.
IJ.selectWindow(this_img.getTitle())
IJ.run(this_img, "Select All", "")
IJ.setMinAndMax(pixel_floor, pixel_ceiling)
IJ.run(this_img, "Apply LUT", "")
## Ask if it is acceptable.
gd = GenericDialog("Acceptable?")
gd.addMessage(
"If the preprocessed image is acceptable for analysis, hit 'OK' to being analysis.\n"
+ " If the image is unacceptable or an error occurred, hit 'Cancel'")
gd.showDialog()
if gd.wasCanceled():
return
## Save the preprocessed image.
imp = IJ.getImage()
fs = FileSaver(imp)
img_save_dir = matchedmyo_path + "myoimages/" # actually get from user at some point
img_file_path = img_save_dir + img_name[:-4] + "_preprocessed.tif"
if os.path.exists(img_save_dir) and os.path.isdir(img_save_dir):
print "Saving image as:", img_file_path
if os.path.exists(img_file_path):
# use dialog box to ask if they want to overwrite
gd = GenericDialog("Overwrite?")
gd.addMessage(
"A file exists with the specified path, \"{}\". Would you like to overwrite it?"
.format(img_file_path))
gd.enableYesNoCancel()
gd.showDialog()
if gd.wasCanceled():
return
elif fs.saveAsTiff(img_file_path):
print "Preprocessed image saved successfully at:", '"' + img_file_path + '"'
else:
print "Folder does not exist or is not a folder!"
### Create the YAML file containing the parameters for classification
## Ask user for YAML input
gd = GenericDialog("YAML Input")
gd.addStringField("imageName", img_file_path, 50)
#gd.addStringField("maskName", "None")
gd.addStringField("outputParams_fileRoot", img_file_path[:-4], 50)
gd.addStringField("outputParams_fileType", "tif")
gd.addNumericField("outputParams_dpi", 300, 0)
gd.addCheckbox("outputParams_saveHitsArray", False)
gd.addStringField("outputParams_csvFile", matchedmyo_path + "results/")
gd.addCheckbox("TT Filtering", True)
gd.addToSameRow()
gd.addCheckbox("LT Filtering", True)
gd.addToSameRow()
gd.addCheckbox("TA Filtering", True)
gd.addNumericField("scopeResolutions_x", 5.0, 3)
gd.addToSameRow()
gd.addNumericField("scopeResolutions_y", 5.0, 3)
gd.addMessage("Enter in filter rotation angles separated by commas.")
gd.addStringField("", "-25, -20, -15, -10, -5, 0, 5, 10, 15, 20, 25", 50)
gd.addCheckbox("returnAngles", False)
gd.addCheckbox("returnPastedFilter", True)
gd.showDialog()
if gd.wasCanceled():
return
strings = [st.text for st in gd.getStringFields()]
#if strings[1] == "None" or "":
# strings[1] = None
nums = [float(num.text) for num in gd.getNumericFields()]
nums[0] = int(nums[0]) # Have to make sure the dpi variable is an integer
checks = [str(bool(boo.state)) for boo in gd.getCheckboxes()]
iter_argument = ','.join(
[str(float(it) - rotation_angle) for it in strings[4].split(',')])
string_block = """imageName: {0[0]}
outputParams:
fileRoot: {0[1]}
fileType: {0[2]}
dpi: {1[0]}
saveHitsArray: {2[0]}
csvFile: {0[3]}
preprocess: False
filterTypes:
TT: {2[1]}
LT: {2[2]}
TA: {2[3]}
scopeResolutions:
x: {1[1]}
y: {1[2]}
iters: [{3}]
returnAngles: {2[4]}
returnPastedFilter: {2[5]}""".format(strings, nums, checks, iter_argument)
im_title = this_img.getTitle()
with cd(matchedmyo_path):
yaml_file_path = "./YAML_files/" + im_title[:-4] + ".yml"
with open("./YAML_files/" + im_title[:-4] + ".yml", "w") as ym:
ym.write(string_block)
print "Wrote YAML file to:", matchedmyo_path + yaml_file_path[2:]
### Run the matchedmyo code on the preprocessed image
with cd(matchedmyo_path):
#os.chdir(matchedmyo_path)
#subprocess.call(["python3", matchedmyo_path+"matchedmyo.py", "fullValidation"])
subprocess.call(
["python3", "matchedmyo.py", "run", "--yamlFile", yaml_file_path])
def analysis_parameters_gui(rerun_analysis=False, params=None):
"""GUI for setting analysis parameters at the start of a run. TODO: more effectively separate model and view"""
if params is None:
params = Parameters(load_last_params = True);
dialog = GenericDialog("Analysis parameters");
controls = [];
if rerun_analysis:
params.setUseSingleChannel(False);
params.togglePerformUserQC(False);
params.setDoInnerOuterComparison(False);
controls.append(MyControlDefinition(u'Curvature length parameter (\u00b5m): ',
MyControlDefinition.Numeric,
round(params.curvature_length_um, 2),
params.setCurvatureLengthUm));
controls.append(MyControlDefinition(u'Width of region for intensity analysis (\u00b5m): ',
MyControlDefinition.Numeric,
round(params.intensity_profile_width_um, 2),
params.setIntensityProfileWidthUm))
controls.append(MyControlDefinition("Threshold method: ",
MyControlDefinition.Choice,
params.threshold_method,
params.setThresholdMethod,
choices=params.listThresholdMethods(),
enabled=(not rerun_analysis)));
controls.append(MyControlDefinition("Curvature overlay LUT: ",
MyControlDefinition.Choice,
params.curvature_overlay_lut_string,
params.setCurvatureOverlayLUT,
choices=IJ.getLuts()));
controls.append(MyControlDefinition("Curvature kymograph LUT: ",
MyControlDefinition.Choice,
params.curvature_kymograph_lut_string,
params.setCurvatureKymographLUT,
choices=IJ.getLuts()));
controls.append(MyControlDefinition("Labelled species kymograph LUT: ",
MyControlDefinition.Choice,
params.actin_kymograph_lut_string,
params.setActinKymographLUT,
choices=IJ.getLuts()));
controls.append(MyControlDefinition("Labelled species for intensity analysis: ",
MyControlDefinition.String,
params.labeled_species,
params.setLabeledSpecies));
controls.append(MyControlDefinition("Use intensity channel for segmentation too?",
MyControlDefinition.Checkbox,
params.use_single_channel,
params.setUseSingleChannel,
enabled=(not rerun_analysis)));
controls.append(MyControlDefinition("Metadata source: ",
MyControlDefinition.RadioButtonGroup,
params.metadata_source,
params.setMetadataSource,
choices=["Image metadata", "Acquisition metadata"]));
controls.append(MyControlDefinition("Constrain anchors close to manual selections?",
MyControlDefinition.Checkbox,
params.constrain_anchors,
params.toggleConstrainAnchors,
enabled=(not rerun_analysis)));
controls.append(MyControlDefinition("Filter out negative curvatures",
MyControlDefinition.Checkbox,
params.filter_negative_curvatures,
params.setFilterNegativeCurvatures));
controls.append(MyControlDefinition("Account for photobleaching?",
MyControlDefinition.Checkbox,
params.photobleaching_correction,
params.togglePhotobleachingCorrection));
controls.append(MyControlDefinition("Perform quality control of membrane edges?",
MyControlDefinition.Checkbox,
params.perform_user_qc,
params.togglePerformUserQC,
enabled=(not rerun_analysis)));
controls.append(MyControlDefinition("Perform quality control of background regions?",
MyControlDefinition.Checkbox,
params.qc_background_rois,
params.toggleBackgroundQc));
controls.append(MyControlDefinition("Perform spatial cropping?",
MyControlDefinition.Checkbox,
params.perform_spatial_crop,
params.toggleSpatialCrop,
enabled=(not rerun_analysis)));
controls.append(MyControlDefinition("Perform time cropping?",
MyControlDefinition.Checkbox,
params.perform_time_crop,
params.toggleTimeCrop,
enabled=(not rerun_analysis)));
controls.append(MyControlDefinition("Close images on completion?",
MyControlDefinition.Checkbox,
params.close_on_completion,
params.toggleCloseOnCompletion));
controls.append(MyControlDefinition("Compare inner and outer curvature regions?",
MyControlDefinition.Checkbox,
params.inner_outer_comparison,
params.setDoInnerOuterComparison,
enabled=(not rerun_analysis)));
for control in controls:
control.addControl(dialog);
dialog.showDialog();
if dialog.wasCanceled():
raise KeyboardInterrupt("Run canceled");
numeric_controls = [c for c in controls if c.control_type==MyControlDefinition.Numeric];
for nc, nf in zip(numeric_controls, dialog.getNumericFields()):
nc.setter(float(nf.getText()));
string_controls = [c for c in controls if c.control_type==MyControlDefinition.String];
for sc, sf in zip(string_controls, dialog.getStringFields()):
sc.setter(sf.getText());
choice_controls = [c for c in controls if c.control_type==MyControlDefinition.Choice];
for cc, cf in zip(choice_controls, dialog.getChoices()):
cc.setter(cf.getSelectedItem());
checkbox_controls = [c for c in controls if c.control_type==MyControlDefinition.Checkbox];
for cbc, cbf in zip(checkbox_controls, dialog.getCheckboxes()):
cbc.setter(cbf.getState());
radiobuttongroup_controls = [c for c in controls if c.control_type==MyControlDefinition.RadioButtonGroup];
for rbc in radiobuttongroup_controls:
rbc.setter(rbc.checkboxes[[cb.getState() for cb in rbc.checkboxes].index(True)].getLabel());
params.persistParameters();
return params;
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()
directoryTitle = IJ.getDirectory("current")
