def module_main(ctx):
try:
a3.outputs['ChA Image'] = a3.inputs['ChA Image']
a3.outputs['ChB Image'] = a3.inputs['ChB Image']
a3.outputs['ChA Thresholded'] = ImageClass(
a3.inputs['ChA Thresholded'].image,
a3.inputs['ChA Thresholded'].metadata).to_multidimimage()
a3.outputs['ChB Thresholded'] = ImageClass(
a3.inputs['ChB Thresholded'].image,
a3.inputs['ChB Thresholded'].metadata).to_multidimimage()
except Exception as e:
error("Error occured while executing '" + str(ctx.type()) +
"' module '" + str(ctx.name()) + "' !",
exception=e)
def module_main(ctx):
try:
filename = a3.inputs['FileName'].path
#Inizialization
tstart = time.clock()
print(SEPARATOR)
print('Loading the following image: ', filename)
#Load and reshape image
img = ImageClass.load(filename)
#Print important image parameters
print_line_by_line(str(img))
#Create Output 1
ch_1_Nb = a3.inputs['Channel'] - 1
ch_1 = img.get_dimension(ch_1_Nb, 'C')
ch_1.metadata['Path'] = filename
ch_1.reorder('ZYXCT')
a3.outputs['Channel'] = ch_1
#Finalization
tstop = time.clock()
print('Processing finished in ' + str((tstop - tstart)) + ' seconds! ')
print('Image loaded successfully!')
print(SEPARATOR)
except Exception as e:
raise error("Error occured while executing '" + str(ctx.type()) +
"' module '" + str(ctx.name()) + "' !",
exception=e)
def module_main(ctx):
try:
#Inizialization
tstart = time.clock()
print(SEPARATOR)
print('Object analysis started!')
#Read Parameters
print('Reading input parameters!')
params = read_params()
output=analyze_image(params['Source'],
params['Mask'],
params['Settings'],
params['removeFiltered'])
#Change Name in metadata
#output.metadata['Name']=params['Mask'].metadata['Name']+'_tagged'
#Create Output
a3.outputs['Analyzed Image'] = output
a3.outputs['Analyzed Binary'] = ImageClass(output.image>0,output.metadata)
a3.outputs['Analyzed Database']=output.database
#Finalization
tstop = time.clock()
print('Processing finished in ' + str((tstop - tstart)) + ' seconds! ')
print('Object analysis was run successfully!')
print(SEPARATOR)
except Exception as e:
raise error("Error occured while executing '"+str(ctx.type())+"' module '"+str(ctx.name())+"' !",exception=e)
def module_main(ctx):
print(SEPARATOR)
print('Retrieving file!')
#Absolute path
path = os.path.abspath(a3.inputs['path'].path)
#Get file extension and directory
if os.path.isfile(path):
base_dir = os.path.dirname(path)
ext = os.path.splitext(path)[1]
print('Input directory:', base_dir)
else:
error(
"Error occured while executing '" + str(ctx.type()) +
"' module '" + str(ctx.name()) + "' ! Path is not a file!",
OSError('Path is not a file!'))
# Gett all the files with matching extensions
file_list = [os.path.abspath(x) for x in glob(base_dir + '/*' + ext)]
if os.path.isfile(path):
file_list.remove(path)
file_list.insert(0, path)
if len(file_list) == 0:
raise Warning('path {} is empty'.format(base_dir))
index = ctx.run_id()
if index < len(file_list) - 1:
ctx.set_require_next_run(True)
else:
ctx.set_require_next_run(False)
url = a3.Url()
url.path = file_list[index]
#Print current filename and index
_, curr_filename = os.path.split(url.path)
print('Currently processing:', curr_filename)
#Set output
a3.outputs['file'] = url
print(SEPARATOR)
def module_main(ctx):
try:
#Inizialization
tstart = time.process_time()
print(SEPARATOR)
print('Colocalization analysis started!')
#Read Parameters
print('Reading input parameters!')
params = read_params()
output = colocalize(params['ChA Image'],
params['ChB Image'],
params['Ovl'],
params['Path'],
to_text=params['to_text'],
remove_filtered=params['remove_filtered'])
a3.outputs['Overlapping Image'] = output[0]
a3.outputs['Overlapping Binary'] = ImageClass(output[0].image > 0,
output[0].metadata)
a3.outputs['Overlapping DataBase'] = output[0].database
path = a3.Url()
path.path = output[3]
a3.outputs['Overlapping Path'] = path
#Finalization
tstop = time.process_time()
print('Processing finished in ' + str((tstop - tstart)) + ' seconds! ')
print('Object analysis was run successfully!')
print(SEPARATOR)
quote(verbose=True)
print(SEPARATOR)
except IOError as e:
print("Warning: Failed to write to file!!", file=sys.stderr)
print(str(e), file=sys.stderr)
except Exception as e:
error("Error occured while executing '" + str(ctx.type()) +
"' module '" + str(ctx.name()) + "' !",
exception=e)
def module_main(ctx):
try:
#Inizialization
tstart = time.clock()
print(SEPARATOR)
print('Thresholding started!')
#Create Image object
img = ImageClass.from_multidimimage(a3.inputs['Input Image'])
#img.image=img.image.astype('float')
print('Thresholding: ' + img.metadata['Name'])
#Get method and mode. Get kwargs if method is manual
method = METHODS[a3.inputs['Method'][-1]]
if method == 'Manual':
kwargs = {'lower': 0, 'upper': a3.inputs['Manual threshold value']}
elif method == 'None':
method = 'Manual'
kwargs = {'lower': 0, 'upper': 0}
else:
kwargs = {}
if a3.inputs['Slice/Stack histogram']:
kwargs['mode'] = 'Stack'
else:
kwargs['mode'] = 'Slice'
#Run thresholding
output_img = module_threshold(img, method, kwargs)
#Set output
a3.outputs['Thresholded Image'] = output_img
a3.outputs['Image'] = img
#Finalization
tstop = time.clock()
print('Processing finished in ' + str((tstop - tstart)) + ' seconds!')
print('Autothresholding was successfully!')
print(SEPARATOR)
except Exception as e:
raise error("Error occured while executing '" + str(ctx.type()) +
"' module '" + str(ctx.name()) + "' !",
exception=e)
def module_main(ctx, methods=meth_list):
try:
#Get file name and output path. If "Output Path" is not set or does not exist use "File Path".
file_name = a3.inputs['File Path'].path
if os.path.isdir(a3.inputs['Output Path'].path):
out_path = a3.inputs['Output Path'].path
else:
out_path = os.path.join(os.path.dirname(file_name), 'Output')
out_file_path = os.path.join(out_path, 'Thresholder_results.xlsx')
#Create output directory if does not exist
if not os.path.exists(out_path):
os.makedirs(out_path)
#If excel file with results from previos run or previous batch steps
#load as dataframe
if not os.path.exists(out_file_path) or not os.path.isfile(
out_file_path):
results = pd.DataFrame()
else:
results = pd.read_excel(out_file_path, 0)
#Run threshold
#Get method and mode. Get kwargs if method is manual
method = methods[a3.inputs['Method'][-1]]
if method == 'Manual':
kwargs = {'lower': 0, 'upper': a3.inputs['Manual Threshold Value']}
elif method == 'None':
method = 'Manual'
kwargs = {'lower': 0, 'upper': 0}
else:
kwargs = {}
if a3.inputs['Slice/Stack Histogram']:
kwargs['mode'] = 'Stack'
else:
kwargs['mode'] = 'Slice'
results_dict = {}
if method == 'All':
methods.remove('All')
else:
methods = [method]
#Analyze raw image parameters
raw_data = core.analyze_raw(a3.inputs['Image'])
#Create ordered dict for results and run analysis
results_dict = OrderedDict()
results_dict['File'] = os.path.basename(file_name)
for keys in raw_data.keys():
results_dict[keys] = raw_data[keys]
for meth in methods:
image_thresholded, thr_value = core.threshold(
a3.inputs['Image'], meth, **kwargs)
if a3.inputs['Save Images']:
save_image(
[image_thresholded], out_path,
str(
os.path.splitext(os.path.basename(file_name))[0] +
'_' + str(meth) + '.tif'))
if kwargs['mode'] == 'Slice':
print('Thresholds using ' + str(meth) + ':')
print('Slice thresholds: ', thr_value)
thr_value = np.mean(thr_value)
print('Mean threshold: ', thr_value)
if kwargs['mode'] == 'Stack':
print('Threshold using ' + str(meth) + ': ', thr_value)
print('')
results_dict[meth] = thr_value
#Append results_dict to dataframe and save
results = results.append(pd.DataFrame(results_dict, index=[0]))
writer = pd.ExcelWriter(out_file_path, engine='xlsxwriter')
results.to_excel(writer, index=False, sheet_name='Thresholds')
writer.save()
except Exception as e:
raise error("Error occured while executing '" + str(ctx.type()) +
"' module '" + str(ctx.name()) + "' !",
exception=e)
def module_main(ctx):
try:
#Inizialization
tstart = time.process_time()
print(SEPARATOR)
print('Thresholding started!')
#Create Image object
img = a3.inputs['Input Image']
print('Thresholding: ' + img.metadata['Name'])
#Get method and mode. Get kwargs if method is manual
method = METHODS[a3.inputs['Method'][-1]]
if method == 'Manual':
kwargs = {'lower': 0, 'upper': a3.inputs['Manual threshold value']}
elif method == 'None':
method = 'Manual'
kwargs = {'lower': 0, 'upper': 0}
else:
kwargs = {}
if a3.inputs['Slice/Stack histogram']:
kwargs['mode'] = 'Stack'
else:
kwargs['mode'] = 'Slice'
print('Mode: ' + kwargs['mode'])
print('Method: ' + method)
#Run thresholding
output_img, log_text = module_threshold(img, method, kwargs)
threshold_value = str(log_text.split('\n')[-1].split(':')[-1])
print('Threshold value(s): ' + threshold_value)
#Change Name in metadata
output_img.metadata['Name'] = img.metadata['Name'] + '_auto_thr'
if (a3.inputs['Save Threshold(s)'] or a3.inputs['Save Image']):
#Set path and filename
#Generate base directory
if os.path.isdir(a3.inputs['Output Path'].path):
output_path = a3.inputs['Output Path'].path
else:
output_path = os.path.dirname(a3.inputs['File Path'].path)
#Create otput directory
output_path = os.path.join(output_path, 'Thresholding')
if not os.path.exists(output_path):
os.makedirs(output_path)
#Save threshold in file
if a3.inputs['Save Threshold(s)']:
print('Saving Threshold Values to file!')
channel_name = img.metadata['Name']
filename = a3.inputs['File Path'].path
print(
'#########################################################################'
)
print(threshold_value)
threshold_to_text(output_path, filename, channel_name, method,
threshold_value)
#Save images
#Generate output filename base for images
filename_img = os.path.basename(output_img.metadata['Path'])
basename_img = os.path.splitext(filename_img)[0]
if a3.inputs['Save Image']:
print('Saving output images!')
#image_list=[ch1_img, ch2_img, ovl_img]
name_img = basename_img + '_{}_{}.ome.tiff'.format(
str(method), str(kwargs['mode']))
save_image(output_img, output_path, name_img)
#Set output
a3.outputs['Thresholded Image'] = output_img
#Finalization
tstop = time.process_time()
print('Processing finished in ' + str((tstop - tstart)) + ' seconds!')
print('Autothresholding was successfully!')
print(SEPARATOR)
except Exception as e:
raise error("Error occured while executing '" + str(ctx.type()) +
"' module '" + str(ctx.name()) + "' !",
exception=e)
def module_main(ctx):
try:
filename = a3.inputs['FileName'].path
#Inizialization
tstart = time.clock()
print(SEPARATOR)
print('Loading the following image: ', filename)
#Process Files
directory = os.path.dirname(filename)
extension = os.path.splitext(filename)[1]
file_list = [
f for f in os.listdir(directory)
if (os.path.isfile(os.path.join(directory, f))
and os.path.splitext(f)[1] == extension)
]
#Thresholding Methods
METHODS = [
'Huang', 'IsoData', 'IsoData_skimage', 'KittlerIllingworth', 'Li',
'Li_skimage', 'MaxEntropy', 'MaxEntropy_skimage', 'Moments',
'Otsu', 'Otsu_skimage', 'RenyiEntropy', 'Shanbhag', 'Triangle',
'Triangle_skimage', 'Yen', 'Yen_skimage'
]
print('Filename ' + 'meanIntensity sumIntensity ' +
str(METHODS).replace('[', '').replace(']', '').replace(',', ''))
for name in file_list:
#Load and reshape image
img = ImageClass.load(os.path.join(directory, name))
#Print important image parameters
#print_line_by_line(str(img))
ch_1_Nb = a3.inputs['Channel A'] - 1
ch_1 = img.get_dimension(ch_1_Nb, 'C')
ch_1.metadata['Path'] = filename
ch_1.reorder('ZYXCT')
#Run thresholding
res = name
#Analyze raw image parameters
raw_data = core.analyze_raw(ch_1)
res += ' ' + str(raw_data['meanIntensity']) + ' ' + str(
raw_data['sumIntensity'])
for meth in METHODS:
ch_1_thr, thr_value = core.threshold(ch_1, meth, mode='Stack')
res += ' ' + str(thr_value)
print(res)
#Output
a3.outputs['Raw Image'] = ch_1.to_multidimimage()
a3.outputs['Thresholded Image'] = ch_1_thr.to_multidimimage()
#Finalization
tstop = time.clock()
print('Processing finished in ' + str((tstop - tstart)) + ' seconds! ')
print('Image loaded successfully!')
print(SEPARATOR)
except Exception as e:
raise error("Error occured while executing '" + str(ctx.type()) +
"' module '" + str(ctx.name()) + "' !",
exception=e)
