From 99e5fec9999a5f00e31a567df7dd98cd69e30880 Mon Sep 17 00:00:00 2001
From: algol <dkazanc@hotmail.com>
Date: Thu, 22 Feb 2018 15:27:33 +0000
Subject: some changes
---
data/IP_data70channels.mat | Bin 0 -> 8710147 bytes
data/__pycache__/read_IPdata.cpython-35.pyc | Bin 0 -> 1674 bytes
data/read_IPdata.py | 58 ++++++++++++++++++++++++++++
3 files changed, 58 insertions(+)
create mode 100644 data/IP_data70channels.mat
create mode 100644 data/__pycache__/read_IPdata.cpython-35.pyc
create mode 100644 data/read_IPdata.py
(limited to 'data')
diff --git a/data/IP_data70channels.mat b/data/IP_data70channels.mat
new file mode 100644
index 0000000..19b9421
Binary files /dev/null and b/data/IP_data70channels.mat differ
diff --git a/data/__pycache__/read_IPdata.cpython-35.pyc b/data/__pycache__/read_IPdata.cpython-35.pyc
new file mode 100644
index 0000000..b062cf9
Binary files /dev/null and b/data/__pycache__/read_IPdata.cpython-35.pyc differ
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)
\ No newline at end of file
--
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