def peak_shift(file, zero_file):
'''
Reads in the wavelength, intensity and file name parameters from
an in-file and the sensor file. Then uses the FindPeaks function to
determine the x coordinates of a resonant peak within both files. Using
this it calculates a peak shift. Outputs the time, peak and peak shift
values.
Args:
file: <string> file path to image
zero_file: <string> file path to sensor background image
'''
wavelength, intensity, file_name = io.array_in(file=file)
wav_zero, int_zero, zero_file_name = io.array_in(file=zero_file)
file_peak = peaks(x=wavelength,
y=intensity,
distance=300,
width=20,
xmin=730,
xmax=810)
zero_peak = peaks(x=wav_zero,
y=int_zero,
distance=300,
width=20,
xmin=740,
xmax=800)
time_stamp = (file_name.split('_')[::-1])[0]
if len(file_peak) == 0:
peak = None
peak_shift = None
else:
peak = float(file_peak[0])
peak_shift = float(file_peak[0]) - float(zero_peak[0])
return time_stamp, peak, peak_shift
main_dir = io.config_dir_path()
exp_settings = io.exp_in(main_dir)
print(f'Experiment Settings:\n {exp_settings}\n')
for hs_img in exp_settings['hs_imgs']:
img_dir = os.path.join(main_dir, hs_img)
if not os.path.isdir(img_dir):
continue
corrected_img_dir = os.path.join(img_dir, 'corrected_imgs')
data_files = io.extract_files(dir_name=corrected_img_dir,
file_string='corrected_img_')
print(len(data_files))
data_cube = []
print('\nBuilding data cube...')
for index, file in enumerate(data_files):
file_path = os.path.join(corrected_img_dir, file)
corrected_img, file_name = io.array_in(file_path, mode='r')
data_cube.append(corrected_img)
io.update_progress(index / len(data_files))
print('\nSaving data cube...approximately 1min per 100 imgs')
io.array_out(array_name=data_cube,
file_name=f'{hs_img}_datacube',
dir_name=main_dir)
io.array_out(array_name=norm_img,
file_name=f'corrected_{file_name}',
dir_name=os.path.join(img_dir, 'corrected_imgs'))
io.update_progress(index / len(data_files))
if datacube:
data_files = io.extract_files(dir_name=corrected_img_dir,
file_string='corrected_img_')
data_cube = []
print(f'\nBuilding data cube for {hs_img}...')
for index, file in enumerate(data_files):
file_path = os.path.join(corrected_img_dir, file)
corrected_img, file_name = io.array_in(file_path, mode='r')
data_cube.append(corrected_img)
io.update_progress(index / len(data_files))
print('\nSaving data cube...approximately 1min per 100 images')
io.array_out(array_name=data_cube,
file_name=f'{hs_img}_datacube',
dir_name=root)
if fsr:
rows, cols = dp.find_img_size(dir_name=corrected_img_dir,
file_string='corrected_img_')
data_cube = os.path.join(root, f'{hs_img}_datacube.npy')
data_cube, file_name = io.array_in(file_path=data_cube, mode='r')