ortec_read/read_chn.py at master · Lowerce/ortec_read · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
# -*- coding: utf-8 -*-
"""
Created on Fri Jan  1 21:54:00 2016

@author: Oscar Tegmyr
oscar.tegmyr@gmail.com

The code creates an object containing the  ortec .Chn spectrum file data.
The code is best used imported by other code (e.g. plotting or analysis code)
but also has a stand alone feature which writes out a textfile with the
spectrum data. To be used in other source code, a general use case could be
getting the histogram data. The code for doing this could look like:

import read_chn as rc
filename = <spectrum_name>.Chn
spec_obj = rc.gamma_data(filename)
hist_data = spec_obj.hist_array


==== Binary header structure ===
for more information
0  2 Must be -1
2  2 MCA number or Detector number
4  2 Segment number (set to 1 in UMCBI)
6  2 ASCII seconds of start time
8  4 Real Time (increments of 20 ms) (4-byte integer)
12 4 Live Time (increments of 20 ms) (4-byte integer)
16 8 Start date as ASCII DDMMMYY* or binary zeros, if not known. The *
     character should be ignored if it is not a "1". If it is a "1", it
     indicates the data is after the year 2000.
24 4 Start time as ASCII HHMM or binary zeros, if not known (see Byte 6 above)
28 2 Channel offset of data
30 2 Number of channels (length of data)
"""
import struct
import sys
import numpy as np

class gamma_data:
    def __init__(self,filename):
        try:
            self.infile         = open(filename, "rb")
            self.read_chn_binary()
        except ValueError:
            print('Unable to load file ' + filename)


    def read_chn_binary(self):       # We start by reading the 32 byte header
        self.version            = struct.unpack('h', self.infile.read(2))[0]
        self.mca_detector_id    = struct.unpack('h', self.infile.read(2))[0]
        self.segment_number     = struct.unpack('h', self.infile.read(2))[0]
        self.start_time_ss      = self.infile.read(2)
        self.real_time          = struct.unpack('I', self.infile.read(4))[0]
        self.live_time          = struct.unpack('I', self.infile.read(4))[0]
        self.start_date         = self.infile.read(8) #Ascii type date in
                                #DDMMMYY* where * == 1 means 21th century
        self.start_time_hhmm    = self.infile.read(4)
        self.chan_offset        = struct.unpack('h', self.infile.read(2))[0]
        self.no_channels        = struct.unpack('h', self.infile.read(2))[0]
        self.hist_array         = np.zeros(self.no_channels) #Init hist_array
        #Read the binary data
        for index in range(len(self.hist_array)):
            self.hist_array[index]= struct.unpack('I', self.infile.read(4))[0]
        assert struct.unpack('h', self.infile.read(2))[0] == -102
        self.infile.read(2)
        self.en_zero_inter = struct.unpack('f', self.infile.read(4))[0]
        self.en_slope = struct.unpack('f', self.infile.read(4))[0]
        self.en_quad = struct.unpack('f', self.infile.read(4))[0]
        self.infile.close()
    def write_txt(self, fname):
        #tf = open(filename[:-4]+'.txt','w')
        tf = open(fname+'.txt','w')
        tf.writelines(['# Filename : ' + fname,
                       '\n# Version: ' + str(self.version),
                       '\n# MCA detector ID: ' + str(self.mca_detector_id),
                       '\n# Start time : ' + self.start_time_hhmm[:2]+':'+ self.start_time_hhmm[:2] + ':'+ str(self.start_time_ss),
                       '\n# Start date : ' + self.start_date,
                       '\n# No channels : ' + str(self.no_channels),
                       '\n# Live time : ' + str(self.live_time),
                       '\n# Real time : ' + str(self.real_time),
                       '\n# En cal factors A + B*x + C*x*x',
                       '\n# A : ' + str(self.en_zero_inter),
                       '\n# B : ' + str(self.en_slope),
                       '\n# C : ' + str(self.en_quad)])
        for i in self.hist_array:
            tf.write(str(int(i)) + '\n')
        tf.close()


if __name__ == '__main__':
    if len(sys.argv) >1:
        filename = sys.argv[1]
    else:
        filename = raw_input('Filename of binary, (including .Chn): ')
    gamma_object = gamma_data(filename)
    gamma_object.write_txt(filename)