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added code to apply bidi offset correction manually
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{ | ||
"cells": [ | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"import numpy as np\n", | ||
"import os\n", | ||
"import h5py\n", | ||
"import sima\n", | ||
"from sima import sequence\n", | ||
"from sima.imaging import ImagingDataset\n", | ||
"import matplotlib.pyplot as plt\n", | ||
"\n", | ||
"import bidi_offset_correction\n", | ||
"import sima_motion_bidi_correction as bidi_funcs" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"fname = '22_1_19_gck_cgm_3_sacchari-001' # h5 file name (without the extension)\n", | ||
"fdir = r'D:\\bruker_data\\Jennifer\\22_1_19_gck_cgm_3_sacchari-001' # root folder of h5 to cut\n", | ||
"data_format = 'sima'\n", | ||
"manual_offset_value = 10 # in pixels (I found this to be pixels you measure by eye +1)\n", | ||
"\n", | ||
"num_save_frames = 300 # use the following for saving and applying offset to all frames: data_n_meta['data'].shape[0] " | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"# load an object referencing the motion-corrected data\n", | ||
"data_n_meta = bidi_funcs.load_sima_or_h5_object(fdir, fname, data_format)\n" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"# mean_subsample_img = np.squeeze(np.nanmean(data_n_meta['data'][::40,...], axis=0))\n", | ||
"# my_bidi_corr_obj = bidi_offset_correction.bidi_offset_correction(mean_subsample_img) # initialize data to object\n", | ||
"\n", | ||
"# my_bidi_corr_obj.compute_mean_image() # compute mean image across time\n", | ||
"# bidi_offset = my_bidi_corr_obj.determine_bidi_offset() # calculated bidirectional offset via fft cross-correlation" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"# applies an offset to odd lines. Every time you run this, it will update the sima offsets file!!!\n", | ||
"bidi_funcs.apply_bidi_corr_to_sima_offsets(fdir, fname, -manual_offset_value-1)" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"# show mean image\n", | ||
"dataset = sima.ImagingDataset.load(os.path.join(fdir, os.path.splitext(fname)[0] + '_mc.sima'))\n", | ||
"sequence_data = dataset.sequences[0][:num_save_frames,...]" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"# comment this out if you don't want to wait for the mean image to process and show in this notebook\n", | ||
"plt.figure(figsize=(7,7))\n", | ||
"plt.imshow(np.nanmean(np.squeeze(sequence_data), axis=0))" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"# saves an h5 based on the motion correction shifts calculated by sima\n", | ||
"data_to_save = np.empty([num_save_frames, dataset.frame_shape[1], dataset.frame_shape[2]])\n", | ||
"frame_iter1 = iter(sequence_data)\n", | ||
"\n", | ||
"# these next few lines just fill in the empty spaces\n", | ||
"fill_gapscaller = bidi_funcs.fill_gaps(0, sequence_data, frame_iter1)\n", | ||
"fill_gapscaller.send(None)\n", | ||
"\n", | ||
"for frame_num in range(num_save_frames):\n", | ||
" data_to_save[frame_num, ...] = fill_gapscaller.send(frame_num).astype('uint8')\n", | ||
"\n", | ||
"# save to an h5\n", | ||
"sima_mc_bidi_outpath = os.path.join(fdir, fname + '_sima_mc.h5')\n", | ||
"h5_write_bidi_corr = h5py.File(sima_mc_bidi_outpath, 'w')\n", | ||
"h5_write_bidi_corr.create_dataset('imaging', data=data_to_save.astype('uint8'))\n", | ||
"h5_write_bidi_corr.close()" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [] | ||
} | ||
], | ||
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"kernelspec": { | ||
"display_name": "Python 2", | ||
"language": "python", | ||
"name": "python2" | ||
}, | ||
"language_info": { | ||
"codemirror_mode": { | ||
"name": "ipython", | ||
"version": 2 | ||
}, | ||
"file_extension": ".py", | ||
"mimetype": "text/x-python", | ||
"name": "python", | ||
"nbconvert_exporter": "python", | ||
"pygments_lexer": "ipython2", | ||
"version": "2.7.16" | ||
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