Add metadata and expand image array read-in
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1 changed files with 18 additions and 5 deletions
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@ -16,8 +16,14 @@ import nafuma.auxillary as aux
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def get_image_array(path):
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def get_image_array(path):
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image = fabio.open(path)
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beamline_extension = ['.edf', '.cbf', '.mar3450']
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image_array = image.data
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if path.endswith(tuple(beamline_extension)):
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image = fabio.open(path)
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image_array = image.data
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elif path.endswith('.dat'):
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image_array = np.loadtxt(path, skiprows=1, delimiter=';')
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return image_array
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return image_array
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@ -185,6 +191,7 @@ def process_2d_scans(data: dict, options={}):
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scans = int(len(all_imgs) / options['scans'])
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scans = int(len(all_imgs) / options['scans'])
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assert scans - (len(all_imgs) / options['scans']) == 0
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assert scans - (len(all_imgs) / options['scans']) == 0
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@ -194,6 +201,7 @@ def process_2d_scans(data: dict, options={}):
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for i in range(scans):
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for i in range(scans):
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img = []
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img = []
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dark = []
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dark = []
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for i in range(options['scans']):
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for i in range(options['scans']):
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img.append(all_imgs.pop(0))
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img.append(all_imgs.pop(0))
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@ -207,14 +215,17 @@ def process_2d_scans(data: dict, options={}):
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img_avgs = []
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img_avgs = []
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for img in imgs:
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headers = []
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for img, dark in zip(imgs,darks):
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img_avg = average_images(img)
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img_avg = average_images(img)
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header = get_image_headers(img[0])
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if options['darks']:
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if options['darks']:
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dark_avg = average_images(dark)
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dark_avg = average_images(dark)
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img_avg = subtract_dark(img_avg, dark_avg)
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img_avg = subtract_dark(img_avg, dark_avg)
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img_avgs.append(img_avg)
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img_avgs.append(img_avg)
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headers.append(header)
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if options['save']:
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if options['save']:
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@ -222,7 +233,9 @@ def process_2d_scans(data: dict, options={}):
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os.makedirs(options['save_folder'])
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os.makedirs(options['save_folder'])
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for i, img in enumerate(img_avgs):
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for i, img in enumerate(img_avgs):
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np.savetxt(os.path.join(options['save_folder'], options['save_filename']+f'{i}'.zfill(4)+options['save_extension']), img, fmt='%.1f', delimiter=";")
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with open(os.path.join(options['save_folder'], options['save_filename']+f'{i}'.zfill(4)+options['save_extension']), 'w') as f:
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f.write(f'# Time: {headers[i]["time"]}\n')
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np.savetxt(f, img, fmt='%.2f', delimiter=";")
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