def get_bleach_spots(log_pd: pd.DataFrame,
label_nucleoli: np.array,
analyze_organelle: str,
num_dilation=3):
"""
Generate bleach spots mask and corresponding pd.DataFrame table
:param log_pd: pd.DataFrame, requires columns 'x', 'y', 'nucleoli'
'x': x coordinates of all possible bleach spots
'y': y coordinates of all possible bleach spots
'nucleoli': pointer corresponding nucleoli label index
originally imports from .log file
:param label_nucleoli: np.array, grey scale labeled nucleoli image
:param analyze_organelle: str, 'sg' or 'nucleoli'
:param num_dilation: int, optional (default: 3)
number of dilation applied from the coordinates
determines the size of the generated mask for each point
default number was determined for FRAP analysis
:return: bleach_spots_ft: np.array, 0-and-1
bleach spots mask
pointer_pd: pd.DataFrame
pointer dataframe, add corresponding bleach spots/nucleoli information
sorted based on bleach spots, ascending
"""
# link pointer with corresponding detected bleach spots
bleach_spots = ana.analysis_mask(log_pd['y'], log_pd['x'], label_nucleoli,
num_dilation)
label_bleach_spots = label(bleach_spots, connectivity=1)
log_pd['bleach_spots'] = obj.points_in_objects(label_bleach_spots,
log_pd['x'], log_pd['y'])
# filter bleach spots
pointer_pd = filter_bleach_spots(log_pd, analyze_organelle)
# generate bleach spots mask (after filtering)
bleach_spots_ft = ana.analysis_mask(pointer_pd['y'], pointer_pd['x'],
label_nucleoli, num_dilation)
label_bleach_spots_ft = label(bleach_spots_ft, connectivity=1)
# link pointer with corresponding filtered bleach spots
pointer_pd['bleach_spots'] = obj.points_in_objects(label_bleach_spots_ft,
pointer_pd['x'],
pointer_pd['y'])
pointer_pd = pointer_pd.sort_values(by='bleach_spots').reset_index(
drop=True)
return bleach_spots_ft, pointer_pd
def get_spots(x_lst: list,
y_lst: list,
pixels_same_size: np.array,
num_dilation=3):
"""
Generate spots mask and corresponding pd.DataFrame table
:param x_lst: list, list of x coordinates
:param y_lst: list, list of y coordinates
:param pixels_same_size: np.array, any image of the same size
:param num_dilation: int, number of dilation applied, default: 3
:return:
"""
spots = ana.analysis_mask(y_lst, x_lst, pixels_same_size, num_dilation)
label_spots = label(spots, connectivity=1)
pd_spots = pd.DataFrame({'x': x_lst, 'y': y_lst})
pd_spots['spots'] = obj.points_in_objects(label_spots, pd_spots['x'],
pd_spots['y'])
# filter spots
pointer_same_spots = [
item for item, count in collections.Counter(
pd_spots['spots'].tolist()).items() if count > 1
]
pd_spots = pd_spots[~pd_spots['spots'].isin(pointer_same_spots)]
del pd_spots['spots'] # delete previous bleach_spots information
pd_spots = pd_spots.reset_index(drop=True) # reset index
spots_ft = ana.analysis_mask(pd_spots['y'], pd_spots['x'],
pixels_same_size, num_dilation)
label_spots_ft = label(spots_ft, connectivity=1)
# link pointer with corresponding filtered bleach spots
pd_spots['spots'] = obj.points_in_objects(label_spots_ft, pd_spots['x'],
pd_spots['y'])
pd_spots = pd_spots.sort_values(by='spots').reset_index(drop=True)
return spots_ft, pd_spots
label_organelle = label(organelle, connectivity=1)
data_log['num_%s_detected' %
analyze_organelle] = [obj.object_count(organelle)]
print("Found %d %s." %
(data_log['num_%s_detected' % analyze_organelle][0],
analyze_organelle))
# organelle pd dataset
organelle_pd = organelle_analysis(pix, organelle,
'%s' % analyze_organelle, pos)
if analyze_organelle == 'nucleoli':
# link nucleoli with corresponding nuclear
round_x = [round(num) for num in organelle_pd['x']]
round_y = [round(num) for num in organelle_pd['y']]
organelle_pd['nuclear'] = obj.points_in_objects(
label_nuclear, round_y, round_x)
# nuclear pd dataset
nuclear_pd = nuclear_analysis(label_nuclear, organelle_pd, pos)
data_log['num_nucleoli_in_nuclei'] = [
len(organelle_pd[organelle_pd['nuclear'] != 0])
]
print("Found %d out of %d nucleoli within nuclei." %
(data_log['num_nucleoli_in_nuclei'][0],
obj.object_count(organelle)))
# ----------------------------------
# BLEACH SPOTS DETECTION
# ----------------------------------
print("### Image analysis: bleach spots detection ...")
# nucleoli detection
nucleoli = find_organelle(pix,
thresholding,
min_size=min_size,
max_size=max_size)
label_nucleoli = label(nucleoli, connectivity=1)
data_log['num_nucleoli_detected'] = [obj.object_count(nucleoli)]
print("Found %d nucleoli." % data_log['num_nucleoli_detected'][0])
# nucleoli pd dataset
nucleoli_pd = organelle_analysis(pix, nucleoli, 'nucleoli', pos)
# link nucleoli with corresponding nuclear
round_x = [round(num) for num in nucleoli_pd['x']]
round_y = [round(num) for num in nucleoli_pd['y']]
nucleoli_pd['nuclear'] = obj.points_in_objects(label_nuclear, round_y, round_x)
data_log['num_nucleoli_in_nuclei'] = [
len(nucleoli_pd[nucleoli_pd['nuclear'] != 0])
]
print("Found %d out of %d nucleoli within nuclei." %
(data_log['num_nucleoli_in_nuclei'][0], obj.object_count(nucleoli)))
# nuclear pd dataset
nuclear_pd = nuclear_analysis(label_nuclear, nucleoli_pd, pos)
# ----------------------------------
# BLEACH SPOTS DETECTION
# ----------------------------------
print("### Image analysis: bleach spots detection ...")