This file is indexed.

/usr/share/itpp/pyitpp.py is in libitpp-dev 4.3.1-6.

This file is owned by root:root, with mode 0o644.

The actual contents of the file can be viewed below.

  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
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
# File:   pyitpp.py
# Brief:  Loads an IT++ itfile content and outputs a dictionary with all variables found.
# Author: Bogdan Cristea
#
# Usage: from pyitpp import itload
#        out = itload('fname.it')
#
# This module provides a function for loading itfile content into matrices/scalars
# and outputs all these variables as a dictionary whose keys are variable names as
# found in itfile. This module uses numpy module for matrix operations and numerical types.
# Thus, the provided functionality is similar to itload() function for MATLAB.
#
# -------------------------------------------------------------------------
#
# Copyright (C) 1995-2010  (see AUTHORS file for a list of contributors)
#
# This file is part of IT++ - a C++ library of mathematical, signal
# processing, speech processing, and communications classes and functions.
#
# IT++ is free software: you can redistribute it and/or modify it under the
# terms of the GNU General Public License as published by the Free Software
# Foundation, either version 3 of the License, or (at your option) any
# later version.
#
# IT++ is distributed in the hope that it will be useful, but WITHOUT ANY
# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
# FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more
# details.
#
# You should have received a copy of the GNU General Public License along
# with IT++.  If not, see <http://www.gnu.org/licenses/>.
#
# -------------------------------------------------------------------------

from sys import exit
from os import stat
from os import SEEK_SET
from stat import ST_SIZE
from struct import unpack
from numpy import mat
from numpy import reshape
from numpy.matlib import zeros

#numerical types used for conversions
from numpy import uint8
from numpy import int16
from numpy import int32
from numpy import float32
from numpy import float64
from numpy import complex64
from numpy import complex128

def __fgetstr(fid):
    str = ''
    while 1:
        d = fid.read(1);
        if d == '\x00':
            break
        str = str+d;
    return str

def itload(in_file):
    
    try:
        f = open(in_file, 'rb')
    except IOError:
        try:
            f = open(in_file+'.it', 'rb')
        except IOError:            
            print 'Cannot open file'
            exit()
    
    #get file size
    file_size = stat(in_file)[ST_SIZE]
    
    #read IT++ magic string
    magic = f.read(4);
    if 'IT++' != magic:
        print 'Not an IT++ file!'
        exit()
    
    #check the IT++ file version
    version = f.read(1)
    if 3 != ord(version):
        print 'Only IT++ file version 3 is supported by this function!'
        exit()
    
    out = dict()#use a dictionary to output all tuples read from it file
    
    while 1:
        #save current file position
        pos = f.tell()
        
        #read header, data, and total block sizes (3*uint64)
        header_data_block_sizes = unpack('3Q', f.read(24))
        
        #read current variable name
        var_name = __fgetstr(f)
        #read current variable type
        var_type = __fgetstr(f)
        #skip header bytes
        f.seek(pos+header_data_block_sizes[0], SEEK_SET)
        
        if len(var_type) == 0: #A deleted entry -> skip it
            pass
        #scalars
        # --- bin ---
        elif 'bin' == var_type:
            out[var_name] = uint8(unpack('b', f.read(1))[0])
        # --- int8 (char) ---
        elif 'int8' == var_type:
            out[var_name] = unpack('c', f.read(1))[0]
        # --- int16 (short) ---
        elif 'int16' == var_type:
            out[var_name] = int16(unpack('h', f.read(2))[0])
        # --- int32 (int) ---
        elif 'int32' == var_type:
            out[var_name] = int32(unpack('i', f.read(4))[0])
        # --- float32 (float) ---
        elif 'float32' == var_type:
            out[var_name] = float32(unpack('f', f.read(4))[0])
        # --- float64 (double) ---
        elif 'float64' == var_type:
            out[var_name] = float64(unpack('d', f.read(8))[0])
        # --- cfloat32 (complex<float>) ---
        elif 'cfloat32' == var_type:
            real_imag = unpack('2f', f.read(8))
            out[var_name] = complex64(complex(real_imag[0], real_imag[1]))
        # --- cfloat64 (complex<double>) ---
        elif 'cfloat64' == var_type:
            real_imag = unpack('2d', f.read(16))
            out[var_name] = complex128(complex(real_imag[0], real_imag[1]))
        
        #vectors
        # --- bvec ---
        elif 'bvec' == var_type:
            length = unpack('Q', f.read(8))[0]
            fmt = str(length)+'b'
            out[var_name] = mat(unpack(fmt, f.read(length)), 'uint8').T#convert to a column vector
        # --- string ---
        elif 'string' == var_type:
            length = unpack('Q', f.read(8))[0]
            fmt = str(length)+'c'
            out[var_name] = "".join(unpack(fmt, f.read(length)))
        # --- svec ---
        elif 'svec' == var_type:
            length = unpack('Q', f.read(8))[0]
            fmt = str(length)+'h'
            out[var_name] = mat(unpack(fmt, f.read(length*2)), 'int16').T#convert to a column vector
        # --- ivec ---
        elif 'ivec' == var_type:
            length = unpack('Q', f.read(8))[0]
            fmt = str(length)+'i'
            out[var_name] = mat(unpack(fmt, f.read(length*4)), 'int32').T#convert to a column vector
        # --- fvec ---
        elif 'fvec' == var_type:
            length = unpack('Q', f.read(8))[0]
            fmt = str(length)+'f'
            out[var_name] = mat(unpack(fmt, f.read(length*4)), 'float32').T#convert to a column vector
        # --- dvec ---
        elif 'dvec' == var_type:
            length = unpack('Q', f.read(8))[0]
            fmt = str(length)+'d'
            out[var_name] = mat(unpack(fmt, f.read(length*8)), 'float64').T#convert to a column vector
        # --- fcvec ---
        elif 'fcvec' == var_type:
            length = unpack('Q', f.read(8))[0]
            fmt = str(2*length)+'f'
            real_imag = mat(unpack(fmt, f.read(2*length*4)), 'float32').T#convert to a column vector
            out[var_name] = zeros((length, 1), complex)
            for i in range(length):
                out[var_name][i,0] = complex64(complex(real_imag[2*i], real_imag[2*i+1]))
        # --- dcvec ---
        elif 'dcvec' == var_type:
            length = unpack('Q', f.read(8))[0]
            fmt = str(2*length)+'d'
            real_imag = mat(unpack(fmt, f.read(2*length*8)), 'float64').T#convert to a column vector
            out[var_name] = zeros((length, 1), complex)
            for i in range(length):
                out[var_name][i,0] = complex128(complex(real_imag[2*i], real_imag[2*i+1]))       
        
        #matrices
        # --- bmat ---
        elif 'bmat' == var_type:
            rows = unpack('Q', f.read(8))[0]
            cols = unpack('Q', f.read(8))[0]
            fmt = str(rows*cols)+'b'
            out[var_name] = reshape(mat(unpack(fmt, f.read(rows*cols)), 'uint8'), (cols, rows)).T
        # --- smat ---
        elif 'smat' == var_type:
            rows = unpack('Q', f.read(8))[0]
            cols = unpack('Q', f.read(8))[0]
            fmt = str(rows*cols)+'h'
            out[var_name] = reshape(mat(unpack(fmt, f.read(rows*cols*2)), 'int16'), (cols, rows)).T
        # --- imat ---
        elif 'imat' == var_type:
            rows = unpack('Q', f.read(8))[0]
            cols = unpack('Q', f.read(8))[0]
            fmt = str(rows*cols)+'i'
            out[var_name] = reshape(mat(unpack(fmt, f.read(rows*cols*4)), 'int32'), (cols, rows)).T
        # --- fmat ---
        elif 'fmat' == var_type:
            rows = unpack('Q', f.read(8))[0]
            cols = unpack('Q', f.read(8))[0]
            fmt = str(rows*cols)+'f'
            out[var_name] = reshape(mat(unpack(fmt, f.read(rows*cols*4)), 'float32'), (cols, rows)).T
        # --- dmat ---
        elif 'dmat' == var_type:
            rows = unpack('Q', f.read(8))[0]
            cols = unpack('Q', f.read(8))[0]
            fmt = str(rows*cols)+'d'
            out[var_name] = reshape(mat(unpack(fmt, f.read(rows*cols*8)), 'float64'), (cols, rows)).T
        # --- fcmat ---
        elif 'fcmat' == var_type:
            rows = unpack('Q', f.read(8))[0]
            cols = unpack('Q', f.read(8))[0]
            fmt = str(2*rows*cols)+'f'
            real_imag = mat(unpack(fmt, f.read(2*rows*cols*4)), 'float32').T
            out[var_name] = zeros((rows, cols), complex)
            for i in range(rows):
                for j in range(cols):
                    out[var_name] = out[var_name][i,j] = complex(real_imag[2*i+2*rows*j], real_imag[2*i+1+2*rows*j])
        # --- dcmat ---
        elif 'dcmat' == var_type:
            rows = unpack('Q', f.read(8))[0]
            cols = unpack('Q', f.read(8))[0]
            fmt = str(2*rows*cols)+'d'
            real_imag = mat(unpack(fmt, f.read(2*rows*cols*8)), 'float64').T
            out[var_name] = zeros((rows, cols), complex)
            for i in range(rows):
                for j in range(cols):
                    out[var_name][i,j] = complex(real_imag[2*i+2*rows*j], real_imag[2*i+1+2*rows*j])

        #arrays of scalars (implemented as list of scalars)
        # --- bArray ---
        elif 'bArray' == var_type:
            size = unpack('Q', f.read(8))[0]
            fmt = str(size)+'b'
            out[var_name] = [uint8(n) for n in unpack(fmt, f.read(size))]
        # --- sArray ---
        elif 'sArray' == var_type:
            size = unpack('Q', f.read(8))[0]
            fmt = str(size)+'h'
            out[var_name] = [int16(n) for n in unpack(fmt, f.read(size*2))]
        # --- iArray ---
        elif 'iArray' == var_type:
            size = unpack('Q', f.read(8))[0]
            fmt = str(size)+'i'
            out[var_name] = [int32(n) for n in unpack(fmt, f.read(size*4))]
        # --- fArray ---
        elif 'fArray' == var_type:
            size = unpack('Q', f.read(8))[0]
            fmt = str(size)+'f'
            out[var_name] = [float32(n) for n in unpack(fmt, f.read(size*4))]
        # --- dArray ---
        elif 'dArray' == var_type:
            size = unpack('Q', f.read(8))[0]
            fmt = str(size)+'d'
            out[var_name] = [float64(n) for n in unpack(fmt, f.read(size*8))]
        # --- fcArray ---
        elif 'fcArray' == var_type:
            size = unpack('Q', f.read(8))[0]
            fmt = str(2*size)+'f'
            real_imag = unpack(fmt, f.read(2*size*4))
            out[var_name] = list()
            for i in range(size):
                out[var_name].append(complex64(complex(real_imag[2*i], real_imag[2*i+1])))
        # --- dcArray ---
        elif 'dcArray' == var_type:
            size = unpack('Q', f.read(8))[0]
            fmt = str(2*size)+'d'
            real_imag = unpack(fmt, f.read(2*size*8))
            out[var_name] = list()
            for i in range(size):
                out[var_name].append(complex128(complex(real_imag[2*i], real_imag[2*i+1])))
        
        #arrays of vectors (implemented as list of vectors)
        # --- bvecArray ---
        elif 'bvecArray' == var_type:
            size = unpack('Q', f.read(8))[0]
            out[var_name] = list()
            for i in range(size):
                length = unpack('Q', f.read(8))[0]
                fmt = str(length)+'b'
                out[var_name].append(mat(unpack(fmt, f.read(length)), 'uint8').T)
        # --- svecArray ---
        elif 'svecArray' == var_type:
            size = unpack('Q', f.read(8))[0]
            out[var_name] = list()
            for i in range(size):
                length = unpack('Q', f.read(8))[0]
                fmt = str(length)+'h'
                out[var_name].append(mat(unpack(fmt, f.read(length*2)), 'int16').T)
        # --- ivecArray ---
        elif 'ivecArray' == var_type:
            size = unpack('Q', f.read(8))[0]
            out[var_name] = list()
            for i in range(size):
                length = unpack('Q', f.read(8))[0]
                fmt = str(length)+'i'
                out[var_name].append(mat(unpack(fmt, f.read(length*4)), 'int32').T)
        # --- vecArray ---
        elif 'vecArray' == var_type:
            size = unpack('Q', f.read(8))[0]
            out[var_name] = list()
            for i in range(size):
                length = unpack('Q', f.read(8))[0]
                fmt = str(length)+'d'
                out[var_name].append(mat(unpack(fmt, f.read(length*8)), 'float64').T)
        # --- cvecArray ---
        elif 'cvecArray' == var_type:
            size = unpack('Q', f.read(8))[0]
            out[var_name] = list()
            for i in range(size):
                length = unpack('Q', f.read(8))[0]
                fmt = str(2*length)+'d'
                real_imag = unpack(fmt, f.read(2*length*8))
                v = zeros((length, 1), complex)
                for j in range(length):
                    v[j,0] = complex128(complex(real_imag[2*j], real_imag[2*j+1]))
                out[var_name].append(v)
        #   --- stringArray ---
        elif 'stringArray' == var_type:
            size = unpack('Q', f.read(8))[0]
            out[var_name] = list()
            for i in range(size):
                length = unpack('Q', f.read(8))[0]
                fmt = str(length)+'c'
                out[var_name].append("".join(unpack(fmt, f.read(length))))        

        #arrays of matrices (implemented as list of matrices)
        # --- bmatArray ---
        elif 'bmatArray' == var_type:
            size = unpack('Q', f.read(8))[0]
            out[var_name] = list()
            for i in range(size):
                rows = unpack('Q', f.read(8))[0]
                cols = unpack('Q', f.read(8))[0]
                fmt = str(rows*cols)+'b'
                out[var_name].append(reshape(mat(unpack(fmt, f.read(rows*cols)), 'uint8'), (cols, rows)).T)
        # --- smatArray ---
        elif 'smatArray' == var_type:
            size = unpack('Q', f.read(8))[0]
            out[var_name] = list()
            for i in range(size):
                rows = unpack('Q', f.read(8))[0]
                cols = unpack('Q', f.read(8))[0]
                fmt = str(rows*cols)+'h'
                out[var_name].append(reshape(mat(unpack(fmt, f.read(rows*cols*2)), 'int16'), (cols, rows)).T)
        # --- imatArray ---
        elif 'imatArray' == var_type:
            size = unpack('Q', f.read(8))[0]
            out[var_name] = list()
            for i in range(size):
                rows = unpack('Q', f.read(8))[0]
                cols = unpack('Q', f.read(8))[0]
                fmt = str(rows*cols)+'i'
                out[var_name].append(reshape(mat(unpack(fmt, f.read(rows*cols*4)), 'int32'), (cols, rows)).T)
        # --- matArray ---
        elif 'matArray' == var_type:
            size = unpack('Q', f.read(8))[0]
            out[var_name] = list()
            for i in range(size):
                rows = unpack('Q', f.read(8))[0]
                cols = unpack('Q', f.read(8))[0]
                fmt = str(rows*cols)+'d'
                out[var_name].append(reshape(mat(unpack(fmt, f.read(rows*cols*8)), 'float64'), (cols, rows)).T)
        # --- cmatArray ---
        elif 'cmatArray' == var_type:
            size = unpack('Q', f.read(8))[0]
            out[var_name] = list()
            for i in range(size):
                rows = unpack('Q', f.read(8))[0]
                cols = unpack('Q', f.read(8))[0]
                fmt = str(2*rows*cols)+'d'
                real_imag = unpack(fmt, f.read(2*rows*cols*8))
                m = zeros((rows, cols), complex)
                for j in range(rows):
                    for k in range(cols):
                        m[j,k] = complex128(complex(real_imag[2*j+2*rows*k], real_imag[2*j+1+2*rows*k]))
                out[var_name].append(m)    
        
        else:
            print 'Not a supported type: ', var_type

        if pos+header_data_block_sizes[2] >= file_size:
            break
        else:
            f.seek(pos+header_data_block_sizes[2], SEEK_SET)
    
    f.close()
    return out