SLS TomcatΒΆ
This section contains a script to read the Swiss Light Source tomcat tomography dataset and reconstruct it with tomoPy.
Download file: rec_tomcat.py
1#!/usr/bin/env python
2# -*- coding: utf-8 -*-
3
4"""
5TomoPy example script to reconstruct the Swiss Light Source TOMCAT tomography
6data as original tiff.
7"""
8
9from __future__ import print_function
10import tomopy
11import dxchange
12
13if __name__ == '__main__':
14 # Set path to the micro-CT data to reconstruct.
15 fname = 'data_dir/sample_name_prefix'
16
17 # Select the sinogram range to reconstruct.
18 start = 0
19 end = 16
20
21 # Read the APS 1-ID raw data.
22 proj, flat, dark = dxchange.read_sls_tomcat(fname, sino=(start, end))
23
24 # Set data collection angles as equally spaced between 0-180 degrees.
25 theta = tomopy.angles(proj.shape[0], 0, 180)
26
27 # Flat-field correction of raw data.
28 proj = tomopy.normalize(proj, flat, dark)
29
30 # Find rotation center.
31 rot_center = tomopy.find_center(proj, theta, init=1024,
32 ind=0, tol=0.5)
33 print("Center of rotation:", rot_center)
34
35 proj = tomopy.minus_log(proj)
36
37 # Reconstruct object using Gridrec algorithm.
38 rec = tomopy.recon(proj, theta, center=rot_center, algorithm='gridrec')
39
40 # Mask each reconstructed slice with a circle.
41 rec = tomopy.circ_mask(rec, axis=0, ratio=0.95)
42
43 # Write data as stack of TIFs.
44 dxchange.write_tiff_stack(rec, fname='recon_dir/recon')