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Diffstat (limited to 'data')
| -rw-r--r-- | data/IP_data70channels.mat | bin | 0 -> 8710147 bytes | |||
| -rw-r--r-- | data/__pycache__/read_IPdata.cpython-35.pyc | bin | 0 -> 1674 bytes | |||
| -rw-r--r-- | data/read_IPdata.py | 58 |
3 files changed, 58 insertions, 0 deletions
diff --git a/data/IP_data70channels.mat b/data/IP_data70channels.mat Binary files differnew file mode 100644 index 0000000..19b9421 --- /dev/null +++ b/data/IP_data70channels.mat diff --git a/data/__pycache__/read_IPdata.cpython-35.pyc b/data/__pycache__/read_IPdata.cpython-35.pyc Binary files differnew file mode 100644 index 0000000..b062cf9 --- /dev/null +++ b/data/__pycache__/read_IPdata.cpython-35.pyc diff --git a/data/read_IPdata.py b/data/read_IPdata.py new file mode 100644 index 0000000..2e6a525 --- /dev/null +++ b/data/read_IPdata.py @@ -0,0 +1,58 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +function to read IP data and provide a dictionary with data and parameters as an output +""" +from scipy import io +import numpy as np +from collections import defaultdict + +def read_IPdata(): + # read data from mat file (specify the location) + alldata = io.loadmat('IP_data70channels.mat') + data_raw = alldata.get('Data_raw') # here is raw projection data + Phantom_ideal = alldata.get('Phantom_ideal') # here is 70 channels ideal phantom + Photon_flux = alldata.get('Photon_flux') # photon flux for normalization + del alldata + + # extract geometry-related parameters + proj_numb,detectors_numb,channels = np.shape(data_raw) + im_size = np.size(Phantom_ideal,1) + + theta = np.linspace(0,proj_numb-1,proj_numb)*360/proj_numb # projection angles + dom_width = 1.0 # width of domain in cm + src_to_rotc = 3.0 # dist. from source to rotation center + src_to_det = 5.0 # dist. from source to detector + det_width = 2.0 # detector width + + # negative log normalisation of the raw data (avoiding of log(0)) + data_norm = np.zeros(np.shape(data_raw)) + for i in range(0,channels): + slice1 = data_raw[:,:,i] + indx = np.nonzero(slice1>0) + slice2 = np.zeros((proj_numb,detectors_numb), 'float32') + slice2[indx] = -np.log(slice1[indx]/Photon_flux[i]) + indx2 = np.nonzero(slice1==0) + slice3 = np.zeros((proj_numb,detectors_numb), 'float32') + slice3[indx2] = np.log(slice2[indx2]+Photon_flux[i]) + data_norm[:,:,i] = slice2 + slice3 + del indx, indx2, slice1, slice2, slice3 + data_norm = np.float32(data_norm*(im_size/dom_width)) + + #build a dictionary for data and related parameters + dataDICT = defaultdict(list) + dataDICT['data_norm'].append(data_norm) + dataDICT['data_raw'].append(data_raw) + dataDICT['Photon_flux'].append(Photon_flux) + dataDICT['Phantom_ideal'].append(Phantom_ideal) + dataDICT['theta'].append(theta) + dataDICT['proj_numb'].append(proj_numb) + dataDICT['detectors_numb'].append(detectors_numb) + dataDICT['channels'].append(channels) + dataDICT['im_size'].append(im_size) + dataDICT['dom_width'].append(dom_width) + dataDICT['src_to_rotc'].append(src_to_rotc) + dataDICT['src_to_det'].append(src_to_det) + dataDICT['det_width'].append(det_width) + + return (dataDICT)
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