index=False,
sep='\t')
# dataset of organelle
organelle_pd.to_csv('%s/data_%s.txt' %
(storage_path, analyze_organelle),
index=False,
sep='\t')
if analyze_organelle == 'nucleoli':
nuclear_pd.to_csv('%s/data_nuclear.txt' % storage_path,
index=False,
sep='\t')
# images
dis.plot_offset_map(pointer_pd, fitting_mode, 'bg',
storage_path) # offset map
dis.plot_raw_intensity(pointer_pd, ctrl_pd_ft, fitting_mode, 'bg',
storage_path) # raw intensity
dis.plot_pb_factor(pointer_pd, 'bg',
storage_path) # photobleaching factor
dis.plot_corrected_intensity(
pointer_pd, fitting_mode, 'bg',
storage_path) # intensity after dual correction
dis.plot_normalized_frap(pointer_pd, fitting_mode, 'bg',
storage_path) # normalized FRAP curves
# normalized FRAP curves after filtering with fitting
# individual normalized FRAP curves with fitting
dis.plot_frap_fitting(pointer_pd, fitting_mode, 'bg', storage_path)
else:
# --------------------------
# OUTPUT
# --------------------------
'linear_slope':
pointer_ft_pd['linear_slope'],
'optimal_r2':
pointer_ft_pd['optimal_r2'],
'optimal_mobile_fraction':
pointer_ft_pd['optimal_mobile_fraction'],
'optimal_t_half':
pointer_ft_pd['optimal_t_half'],
'optimal_slope':
pointer_ft_pd['optimal_slope']
})
pointer_out.to_csv('%s/data.txt' % storage_path, index=False, sep='\t')
# images
dis.plot_offset_map(pointer_pd, storage_path) # offset map
dis.plot_raw_intensity(pointer_pd, ctrl_pd_ft, storage_path) # raw intensity
dis.plot_pb_factor(pointer_pd, storage_path) # photobleaching factor
dis.plot_corrected_intensity(pointer_pd,
storage_path) # intensity after dual correction
dis.plot_normalized_frap(pointer_pd, storage_path) # normalized FRAP curves
dis.plot_frap_fitting(
pointer_pd,
storage_path) # normalized FRAP curves after filtering with fitting
# individual normalized FRAP curves with fitting
# --------------------------
# OUTPUT DISPLAY
# --------------------------
if display_mode == 'Y':
print("### Output display ...")