This file is indexed.

/usr/share/pyshared/nibabel/ecat.py is in python-nibabel 1.3.0-2.

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
 393
 394
 395
 396
 397
 398
 399
 400
 401
 402
 403
 404
 405
 406
 407
 408
 409
 410
 411
 412
 413
 414
 415
 416
 417
 418
 419
 420
 421
 422
 423
 424
 425
 426
 427
 428
 429
 430
 431
 432
 433
 434
 435
 436
 437
 438
 439
 440
 441
 442
 443
 444
 445
 446
 447
 448
 449
 450
 451
 452
 453
 454
 455
 456
 457
 458
 459
 460
 461
 462
 463
 464
 465
 466
 467
 468
 469
 470
 471
 472
 473
 474
 475
 476
 477
 478
 479
 480
 481
 482
 483
 484
 485
 486
 487
 488
 489
 490
 491
 492
 493
 494
 495
 496
 497
 498
 499
 500
 501
 502
 503
 504
 505
 506
 507
 508
 509
 510
 511
 512
 513
 514
 515
 516
 517
 518
 519
 520
 521
 522
 523
 524
 525
 526
 527
 528
 529
 530
 531
 532
 533
 534
 535
 536
 537
 538
 539
 540
 541
 542
 543
 544
 545
 546
 547
 548
 549
 550
 551
 552
 553
 554
 555
 556
 557
 558
 559
 560
 561
 562
 563
 564
 565
 566
 567
 568
 569
 570
 571
 572
 573
 574
 575
 576
 577
 578
 579
 580
 581
 582
 583
 584
 585
 586
 587
 588
 589
 590
 591
 592
 593
 594
 595
 596
 597
 598
 599
 600
 601
 602
 603
 604
 605
 606
 607
 608
 609
 610
 611
 612
 613
 614
 615
 616
 617
 618
 619
 620
 621
 622
 623
 624
 625
 626
 627
 628
 629
 630
 631
 632
 633
 634
 635
 636
 637
 638
 639
 640
 641
 642
 643
 644
 645
 646
 647
 648
 649
 650
 651
 652
 653
 654
 655
 656
 657
 658
 659
 660
 661
 662
 663
 664
 665
 666
 667
 668
 669
 670
 671
 672
 673
 674
 675
 676
 677
 678
 679
 680
 681
 682
 683
 684
 685
 686
 687
 688
 689
 690
 691
 692
 693
 694
 695
 696
 697
 698
 699
 700
 701
 702
 703
 704
 705
 706
 707
 708
 709
 710
 711
 712
 713
 714
 715
 716
 717
 718
 719
 720
 721
 722
 723
 724
 725
 726
 727
 728
 729
 730
 731
 732
 733
 734
 735
 736
 737
 738
 739
 740
 741
 742
 743
 744
 745
 746
 747
 748
 749
 750
 751
 752
 753
 754
 755
 756
 757
 758
 759
 760
 761
 762
 763
 764
 765
 766
 767
 768
 769
 770
 771
 772
 773
 774
 775
 776
 777
 778
 779
 780
 781
 782
 783
 784
 785
 786
 787
 788
 789
 790
 791
 792
 793
 794
 795
 796
 797
 798
 799
 800
 801
 802
 803
 804
 805
 806
 807
 808
 809
 810
 811
 812
 813
 814
 815
 816
 817
 818
 819
 820
 821
 822
 823
 824
 825
 826
 827
 828
 829
 830
 831
 832
 833
 834
 835
 836
 837
 838
 839
 840
 841
 842
 843
 844
 845
 846
 847
 848
 849
 850
 851
 852
 853
 854
 855
 856
 857
 858
 859
 860
 861
 862
 863
 864
 865
 866
 867
 868
 869
 870
 871
 872
 873
 874
 875
 876
 877
 878
 879
 880
 881
 882
 883
 884
 885
 886
 887
 888
 889
 890
 891
 892
 893
 894
 895
 896
 897
 898
 899
 900
 901
 902
 903
 904
 905
 906
 907
 908
 909
 910
 911
 912
 913
 914
 915
 916
 917
 918
 919
 920
 921
 922
 923
 924
 925
 926
 927
 928
 929
 930
 931
 932
 933
 934
 935
 936
 937
 938
 939
 940
 941
 942
 943
 944
 945
 946
 947
 948
 949
 950
 951
 952
 953
 954
 955
 956
 957
 958
 959
 960
 961
 962
 963
 964
 965
 966
 967
 968
 969
 970
 971
 972
 973
 974
 975
 976
 977
 978
 979
 980
 981
 982
 983
 984
 985
 986
 987
 988
 989
 990
 991
 992
 993
 994
 995
 996
 997
 998
 999
1000
1001
1002
1003
1004
1005
1006
1007
1008
1009
1010
1011
1012
1013
1014
1015
1016
1017
1018
1019
1020
1021
1022
1023
1024
1025
1026
1027
1028
1029
1030
1031
1032
1033
1034
1035
1036
1037
1038
1039
1040
# emacs: -*- mode: python-mode; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
#
#   See COPYING file distributed along with the NiBabel package for the
#   copyright and license terms.
#
### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
import warnings

import numpy as np

from .volumeutils import (native_code, swapped_code, make_dt_codes,
                           array_from_file)
from .spatialimages import SpatialImage, ImageDataError
from .arraywriters import make_array_writer


MAINHDRSZ = 502
main_header_dtd = [
    ('magic_number', '14S'),
    ('original_filename', '32S'),
    ('sw_version', np.uint16),
    ('system_type', np.uint16),
    ('file_type', np.uint16),
    ('serial_number', '10S'),
    ('scan_start_time',np.uint32),
    ('isotope_name', '8S'),
    ('isotope_halflife', np.float32),
    ('radiopharmaceutical','32S'),
    ('gantry_tilt', np.float32),
    ('gantry_rotation',np.float32),
    ('bed_elevation',np.float32),
    ('intrinsic_tilt', np.float32),
    ('wobble_speed',np.uint16),
    ('transm_source_type',np.uint16),
    ('distance_scanned',np.float32),
    ('transaxial_fov',np.float32),
    ('angular_compression', np.uint16),
    ('coin_samp_mode',np.uint16),
    ('axial_samp_mode',np.uint16),
    ('ecat_calibration_factor',np.float32),
    ('calibration_unitS', np.uint16),
    ('calibration_units_type',np.uint16),
    ('compression_code',np.uint16),
    ('study_type','12S'),
    ('patient_id','16S'),
    ('patient_name','32S'),
    ('patient_sex','1S'),
    ('patient_dexterity','1S'),
    ('patient_age',np.float32),
    ('patient_height',np.float32),
    ('patient_weight',np.float32),
    ('patient_birth_date',np.uint32),
    ('physician_name','32S'),
    ('operator_name','32S'),
    ('study_description','32S'),
    ('acquisition_type',np.uint16),
    ('patient_orientation',np.uint16),
    ('facility_name', '20S'),
    ('num_planes',np.uint16),
    ('num_frames',np.uint16),
    ('num_gates',np.uint16),
    ('num_bed_pos',np.uint16),
    ('init_bed_position',np.float32),
    ('bed_position','15f'),
    ('plane_separation',np.float32),
    ('lwr_sctr_thres',np.uint16),
    ('lwr_true_thres',np.uint16),
    ('upr_true_thres',np.uint16),
    ('user_process_code','10S'),
    ('acquisition_mode',np.uint16),
    ('bin_size',np.float32),
    ('branching_fraction',np.float32),
    ('dose_start_time',np.uint32),
    ('dosage',np.float32),
    ('well_counter_corr_factor', np.float32),
    ('data_units', '32S'),
    ('septa_state',np.uint16),
    ('fill', '12S')
    ]
hdr_dtype = np.dtype(main_header_dtd)


subheader_dtd = [
    ('data_type', np.uint16),
    ('num_dimensions', np.uint16),
    ('x_dimension', np.uint16),
    ('y_dimension', np.uint16),
    ('z_dimension', np.uint16),
    ('x_offset', np.float32),
    ('y_offset', np.float32),
    ('z_offset', np.float32),
    ('recon_zoom', np.float32),
    ('scale_factor', np.float32),
    ('image_min', np.int16),
    ('image_max', np.int16),
    ('x_pixel_size', np.float32),
    ('y_pixel_size', np.float32),
    ('z_pixel_size', np.float32),
    ('frame_duration', np.uint32),
    ('frame_start_time', np.uint32),
    ('filter_code', np.uint16),
    ('x_resolution', np.float32),
    ('y_resolution', np.float32),
    ('z_resolution', np.float32),
    ('num_r_elements', np.float32),
    ('num_angles', np.float32),
    ('z_rotation_angle', np.float32),
    ('decay_corr_fctr', np.float32),
    ('corrections_applied', np.uint32),
    ('gate_duration', np.uint32),
    ('r_wave_offset', np.uint32),
    ('num_accepted_beats', np.uint32),
    ('filter_cutoff_frequency', np.float32),
    ('filter_resolution', np.float32),
    ('filter_ramp_slope', np.float32),
    ('filter_order', np.uint16),
    ('filter_scatter_fraction', np.float32),
    ('filter_scatter_slope', np.float32),
    ('annotation', '40S'),
    ('mt_1_1', np.float32),
    ('mt_1_2', np.float32),
    ('mt_1_3', np.float32),
    ('mt_2_1', np.float32),
    ('mt_2_2', np.float32),
    ('mt_2_3', np.float32),
    ('mt_3_1', np.float32),
    ('mt_3_2', np.float32),
    ('mt_3_3', np.float32),
    ('rfilter_cutoff', np.float32),
    ('rfilter_resolution', np.float32),
    ('rfilter_code', np.uint16),
    ('rfilter_order', np.uint16),
    ('zfilter_cutoff', np.float32),
    ('zfilter_resolution',np.float32),
    ('zfilter_code', np.uint16),
    ('zfilter_order', np.uint16),
    ('mt_4_1', np.float32),
    ('mt_4_2', np.float32),
    ('mt_4_3', np.float32),
    ('scatter_type', np.uint16),
    ('recon_type', np.uint16),
    ('recon_views', np.uint16),
    ('fill', '174S'),
    ('fill2', '96S')]
subhdr_dtype = np.dtype(subheader_dtd)

# Ecat Data Types
_dtdefs = ( # code, name, equivalent dtype
    (1, 'ECAT7_BYTE', np.uint8),
    (2, 'ECAT7_VAXI2', np.int16),
    (3, 'ECAT7_VAXI4', np.float32),
    (4, 'ECAT7_VAXR4', np.float32),
    (5, 'ECAT7_IEEER4', np.float32),
    (6, 'ECAT7_SUNI2', np.uint16),
    (7, 'ECAT7_SUNI4', np.int32))
data_type_codes = make_dt_codes(_dtdefs)


# Matrix File Types
ft_defs = ( # code, name
    (0, 'ECAT7_UNKNOWN'),
    (1, 'ECAT7_2DSCAN'),
    (2, 'ECAT7_IMAGE16'),
    (3, 'ECAT7_ATTEN'),
    (4, 'ECAT7_2DNORM'),
    (5, 'ECAT7_POLARMAP'),
    (6, 'ECAT7_VOLUME8'),
    (7, 'ECAT7_VOLUME16'),
    (8, 'ECAT7_PROJ'),
    (9, 'ECAT7_PROJ16'),
    (10, 'ECAT7_IMAGE8'),
    (11, 'ECAT7_3DSCAN'),
    (12, 'ECAT7_3DSCAN8'),
    (13, 'ECAT7_3DNORM'),
    (14, 'ECAT7_3DSCANFIT'))

patient_orient_defs = ( #code, description
    (0, 'ECAT7_Feet_First_Prone'),
    (1, 'ECAT7_Head_First_Prone'),
    (2, 'ECAT7_Feet_First_Supine'),
    (3, 'ECAT7_Head_First_Supine'),
    (4, 'ECAT7_Feet_First_Decubitus_Right'),
    (5, 'ECAT7_Head_First_Decubitus_Right'),
    (6, 'ECAT7_Feet_First_Decubitus_Left'),
    (7, 'ECAT7_Head_First_Decubitus_Left'),
    (8, 'ECAT7_Unknown_Orientation'))

#Indexes from the patient_orient_defs structure defined above for the
#neurological and radiological viewing conventions
patient_orient_radiological = [0, 2, 4, 6]
patient_orient_neurological = [1, 3, 5, 7]

class EcatHeader(object):
    """Class for basic Ecat PET header
    Sub-parts of standard Ecat File
       main header
       matrix list
           which lists the information for each
           frame collected (can have 1 to many frames)
       subheaders specific to each frame
           with possibly-variable sized data blocks

    This just reads the main Ecat Header,
    it does not load the data
    or read the mlist or any sub headers

    """

    _dtype = hdr_dtype
    _ft_defs = ft_defs
    _patient_orient_defs = patient_orient_defs

    def __init__(self,
                 fileobj=None,
                 endianness=None):
        """Initialize Ecat header from file object

        Parameters
        ----------
        fileobj : {None, string} optional
            binary block to set into header, By default, None
            in which case we insert default empty header block
        endianness : {None, '<', '>', other endian code}, optional
            endian code of binary block, If None, guess endianness
            from the data
        """
        if fileobj is None:
            self._header_data = self._empty_headerdata(endianness)
            return

        hdr = np.ndarray(shape=(),
                         dtype=self._dtype,
                         buffer=fileobj)
        if endianness is None:
            endianness = self._guess_endian(hdr)

        if endianness != native_code:
            dt = self._dtype.newbyteorder(endianness)
            hdr = np.ndarray(shape=(),
                             dtype=dt,
                             buffer=fileobj)
        self._header_data = hdr.copy()

        return

    def get_header(self):
        """returns header """
        return self

    @property
    def binaryblock(self):
        return self._header_data.tostring()

    @property
    def endianness(self):
        if self._header_data.dtype.isnative:
            return native_code
        return swapped_code


    def _guess_endian(self, hdr):
        """Guess endian from MAGIC NUMBER value of header data
        """
        if not hdr['sw_version'] == 74:
            return swapped_code
        else:
            return native_code

    @classmethod
    def from_fileobj(klass, fileobj, endianness=None):
        """Return /read header with given or guessed endian code

        Parameters
        ----------
        fileobj : file-like object
            Needs to implement ``read`` method
        endianness : None or endian code, optional
            Code specifying endianness of data to be read

        Returns
        -------
        hdr : EcatHeader object
            EcatHeader object initialized from data in file object

        Examples
        --------


        """
        raw_str = fileobj.read(klass._dtype.itemsize)
        return klass(raw_str, endianness)

    def write_to(self, fileobj):
        fileobj.write(self.binaryblock)

    def _empty_headerdata(self,endianness=None):
        """Return header data for empty header with given endianness"""
        #hdr_data = super(EcatHeader, self)._empty_headerdata(endianness)
        dt = self._dtype
        if not endianness is None:
            dt = dt.newbyteorder(endianness)
        hdr_data = np.zeros((), dtype=dt)
        hdr_data['magic_number'] = 'MATRIX72'
        hdr_data['sw_version'] = 74
        hdr_data['num_frames']= 0
        hdr_data['file_type'] = 0 # Unknown
        hdr_data['ecat_calibration_factor'] = 1.0 # scale factor
        return hdr_data


    def get_data_dtype(self):
        """ Get numpy dtype for data from header"""
        raise NotImplementedError("dtype is only valid from subheaders")


    def copy(self):
        return self.__class__(
            self.binaryblock,
            self.endianness)


    def __eq__(self, other):
        """ checks for equality between two headers"""
        self_end = self.endianness
        self_bb = self.binaryblock
        if self_end == other.endianness:
            return self_bb == other.binaryblock
        other_bb = other._header_data.byteswap().tostring()
        return self_bb == other_bb

    def __ne__(self, other):
        ''' equality between two headers defined by ``header_data``

        For examples, see ``__eq__`` method docstring
        '''
        return not self == other

    def __getitem__(self, item):
        ''' Return values from header data

        Examples
        --------
        >>> hdr = EcatHeader()
        >>> hdr['magic_number'] #23dt next : bytes
        'MATRIX72'
        '''
        return self._header_data[item].item()

    def __setitem__(self, item, value):
        ''' Set values in header data

        Examples
        --------
        >>> hdr = EcatHeader()
        >>> hdr['num_frames'] = 2
        >>> hdr['num_frames']
        2
        '''
        self._header_data[item] = value

    def get_patient_orient(self):
        """ gets orientation of patient based on code stored
        in header, not always reliable"""
        orient_code = dict(self._patient_orient_defs)
        code = self._header_data['patient_orientation'].item()
        if not orient_code.has_key(code):
            raise KeyError('Ecat Orientation CODE %d not recognized'%code)
        return orient_code[code]

    def get_filetype(self):
        """ gets type of ECAT Matrix File from
        code stored in header"""
        ft_codes = dict(self._ft_defs)
        code = self._header_data['file_type'].item()
        if not ft_codes.has_key(code):
            raise KeyError('Ecat Filetype CODE %d not recognized'%code)
        return ft_codes[code]

    def __iter__(self):
        return iter(self.keys())

    def keys(self):
        ''' Return keys from header data'''
        return list(self._dtype.names)

    def values(self):
        ''' Return values from header data'''
        data = self._header_data
        return [data[key] for key in self._dtype.names]

    def items(self):
        ''' Return items from header data'''
        return zip(self.keys(), self.values())

class EcatMlist(object):

    def __init__(self,fileobj, hdr):
        """ gets list of frames and subheaders in pet file

        Parameters
        -----------
        fileobj : ECAT file <filename>.v  fileholder or file object
                  with read, seek methods

        Returns
        -------
        mlist : numpy recarray  nframes X 4 columns
        1 - Matrix identifier.
        2 - subheader record number
        3 - Last record number of matrix data block.
        4 - Matrix status:
            1 - exists - rw
            2 - exists - ro
            3 - matrix deleted
        """
        self.hdr = hdr
        self._mlist = self.get_mlist(fileobj)

    def get_mlist(self, fileobj):
        fileobj.seek(512)
        dat=fileobj.read(128*32)

        dt = np.dtype([('matlist',np.int32)])
        if not self.hdr.endianness is native_code:
            dt = dt.newbyteorder(self.hdr.endianness)
        nframes = self.hdr['num_frames']
        mlist = np.zeros((nframes,4), dtype='uint32')
        record_count = 0
        done = False

        while not done: #mats['matlist'][0,1] == 2:

            mats = np.recarray(shape=(32,4), dtype=dt,  buf=dat)
            if not (mats['matlist'][0,0] +  mats['matlist'][0,3]) == 31:
                mlist = []
                return mlist

            nrecords = mats['matlist'][0,3]
            mlist[record_count:nrecords+record_count,:] = mats['matlist'][1:nrecords+1,:]
            record_count+= nrecords
            if mats['matlist'][0,1] == 2 or mats['matlist'][0,1] == 0:
                done = True
            else:
                # Find next subheader
                tmp = int(mats['matlist'][0,1]-1)#cast to int
                fileobj.seek(0)
                fileobj.seek(tmp*512)
                dat = fileobj.read(128*32)

        return mlist

    def get_frame_order(self):
        """Returns the order of the frames stored in the file
        Sometimes Frames are not stored in the file in
        chronological order, this can be used to extract frames
        in correct order

        Returns
        -------
        id_dict: dict mapping frame number -> [mlist_row, mlist_id]

        (where mlist id is value in the first column of the mlist matrix )

        Examples
        --------
        >>> import os
        >>> import nibabel as nib
        >>> nibabel_dir = os.path.dirname(nib.__file__)
        >>> from nibabel import ecat
        >>> ecat_file = os.path.join(nibabel_dir,'tests','data','tinypet.v')
        >>> img = ecat.load(ecat_file)
        >>> mlist = img.get_mlist()
        >>> mlist.get_frame_order()
        {0: [0, 16842758]}
        """
        mlist  = self._mlist
        ids = mlist[:, 0].copy()
        n_valid = np.sum(ids > 0)
        ids[ids <=0] = ids.max() + 1 # put invalid frames at end after sort
        valid_order = np.argsort(ids)
        if not all(valid_order == sorted(valid_order)):
            #raise UserWarning if Frames stored out of order
            warnings.warn_explicit('Frames stored out of order;'\
                          'true order = %s\n'\
                          'frames will be accessed in order '\
                          'STORED, NOT true order'%(valid_order),
                          UserWarning,'ecat', 0)
        id_dict = {}
        for i in range(n_valid):
            id_dict[i] = [valid_order[i], ids[valid_order[i]]]

        return id_dict

    def get_series_framenumbers(self):
        """ Returns framenumber of data as it was collected,
        as part of a series; not just the order of how it was
        stored in this or across other files

        For example, if the data is split between multiple files
        this should give you the true location of this frame as
        collected in the series
        (Frames are numbered starting at ONE (1) not Zero)

        Returns
        -------
        frame_dict: dict mapping order_stored -> frame in series
               where frame in series counts from 1; [1,2,3,4...]

        Examples
        --------
        >>> import os
        >>> import nibabel as nib
        >>> nibabel_dir = os.path.dirname(nib.__file__)
        >>> from nibabel import ecat
        >>> ecat_file = os.path.join(nibabel_dir,'tests','data','tinypet.v')
        >>> img = ecat.load(ecat_file)
        >>> mlist = img.get_mlist()
        >>> mlist.get_series_framenumbers()
        {0: 1}



        """
        frames_order = self.get_frame_order()
        nframes = self.hdr['num_frames']
        mlist_nframes = len(frames_order)
        trueframenumbers = np.arange(nframes - mlist_nframes, nframes)
        frame_dict = {}
        try:
            for frame_stored, (true_order, _) in frames_order.items():
                #frame as stored in file -> true number in series
                frame_dict[frame_stored] = trueframenumbers[true_order]+1
            return frame_dict
        except:
            raise IOError('Error in header or mlist order unknown')

class EcatSubHeader(object):

    _subhdrdtype = subhdr_dtype
    _data_type_codes = data_type_codes

    def __init__(self, hdr, mlist, fileobj):
        """parses the subheaders in the ecat (.v) file
        there is one subheader for each frame in the ecat file

        Parameters
        -----------
        hdr : EcatHeader

        mlist : EcatMlist

        fileobj : ECAT file <filename>.v  fileholder or file object
                  with read, seek methods


        """
        self._header = hdr
        self.endianness = hdr.endianness
        self._mlist = mlist
        self.fileobj = fileobj
        self.subheaders = self._get_subheaders()

    def _get_subheaders(self):
        """retreive all subheaders and return list of subheader recarrays
        """
        subheaders = []
        header = self._header
        endianness = self.endianness
        dt = self._subhdrdtype
        if not self.endianness is native_code:
            dt = self._subhdrdtype.newbyteorder(self.endianness)
        if self._header['num_frames'] > 1:
            for item in self._mlist._mlist:
                if item[1] == 0:
                    break
                self.fileobj.seek(0)
                offset = (int(item[1])-1)*512
                self.fileobj.seek(offset)
                tmpdat = self.fileobj.read(512)
                sh = (np.recarray(shape=(), dtype=dt,
                                  buf=tmpdat))
                subheaders.append(sh.copy())
        else:
            self.fileobj.seek(0)
            offset = (int(self._mlist._mlist[0][1])-1)*512
            self.fileobj.seek(offset)
            tmpdat = self.fileobj.read(512)
            sh = (np.recarray(shape=(), dtype=dt,
                              buf=tmpdat))
            subheaders.append(sh)
        return subheaders

    def get_shape(self, frame=0):
        """ returns shape of given frame"""
        subhdr = self.subheaders[frame]
        x = subhdr['x_dimension'].item()
        y = subhdr['y_dimension'].item()
        z = subhdr['z_dimension'].item()
        return (x,y,z)

    def get_nframes(self):
        """returns number of frames"""
        mlist = self._mlist
        framed = mlist.get_frame_order()
        return len(framed)


    def _check_affines(self):
        """checks if all affines are equal across frames"""
        nframes = self.get_nframes()
        if nframes == 1:
            return True
        affs = [self.get_frame_affine(i) for i in range(nframes)]
        if affs:
            i = iter(affs)
            first = i.next()
            for item in i:
                if not np.all(first == item):
                    return False
        return True

    def get_frame_affine(self,frame=0):
        """returns best affine for given frame of data"""
        subhdr = self.subheaders[frame]
        x_off = subhdr['x_offset']
        y_off = subhdr['y_offset']
        z_off = subhdr['z_offset']

        zooms = self.get_zooms(frame=frame)

        dims = self.get_shape(frame)
        # get translations from center of image
        origin_offset = (np.array(dims)-1) / 2.0
        aff = np.diag(zooms)
        aff[:3,-1] = -origin_offset * zooms[:-1] + np.array([x_off,y_off,z_off])
        return aff

    def get_zooms(self,frame=0):
        """returns zooms  ...pixdims"""
        subhdr = self.subheaders[frame]
        x_zoom = subhdr['x_pixel_size'] * 10
        y_zoom = subhdr['y_pixel_size'] * 10
        z_zoom = subhdr['z_pixel_size'] * 10
        return (x_zoom, y_zoom, z_zoom, 1)


    def _get_data_dtype(self, frame):
        dtcode = self.subheaders[frame]['data_type'].item()
        return self._data_type_codes.dtype[dtcode]

    def _get_frame_offset(self, frame=0):
        mlist = self._mlist._mlist
        offset = (mlist[frame][1]) * 512
        return int(offset)

    def _get_oriented_data(self, raw_data, orientation=None):
        '''
        Get data oriented following ``patient_orientation`` header field. If the
        ``orientation`` parameter is given, return data according to this
        orientation.

        :param raw_data: Numpy array containing the raw data
        :param orientation: None (default), 'neurological' or 'radiological'
        :rtype: Numpy array containing the oriented data
        '''
        if orientation is None:
            orientation = self._header['patient_orientation']
        elif orientation == 'neurological':
            orientation = patient_orient_neurological[0]
        elif orientation == 'radiological':
            orientation = patient_orient_radiological[0]
        else:
            raise ValueError('orientation should be None,\
                neurological or radiological')

        if orientation in patient_orient_neurological:
            raw_data = raw_data[::-1, ::-1, ::-1]
        elif orientation in patient_orient_radiological:
            raw_data = raw_data[::, ::-1, ::-1]

        return raw_data

    def raw_data_from_fileobj(self, frame=0, orientation=None):
        '''
        Get raw data from file object.

        :param frame: Time frame index from where to fetch data
        :param orientation: None (default), 'neurological' or 'radiological'
        :rtype: Numpy array containing (possibly oriented) raw data

        .. seealso:: data_from_fileobj
        '''
        dtype = self._get_data_dtype(frame)
        if not self._header.endianness is native_code:
            dtype=dtype.newbyteorder(self._header.endianness)
        shape = self.get_shape(frame)
        offset = self._get_frame_offset(frame)
        fid_obj = self.fileobj
        raw_data = array_from_file(shape, dtype, fid_obj, offset=offset)
        raw_data = self._get_oriented_data(raw_data, orientation)
        return raw_data

    def data_from_fileobj(self, frame=0, orientation=None):
        '''
        Read scaled data from file for a given frame

        :param frame: Time frame index from where to fetch data
        :param orientation: None (default), 'neurological' or 'radiological'
        :rtype: Numpy array containing (possibly oriented) raw data

        .. seealso:: raw_data_from_fileobj
        '''
        header = self._header
        subhdr = self.subheaders[frame]
        raw_data = self.raw_data_from_fileobj(frame, orientation)
        data = raw_data * header['ecat_calibration_factor']
        data = data * subhdr['scale_factor']
        return data




class EcatImage(SpatialImage):
    """This class returns a list of Ecat images,
    with one image(hdr/data) per frame
    """
    _header = EcatHeader
    header_class = _header
    _subheader = EcatSubHeader
    _mlist = EcatMlist
    files_types = (('image', '.v'), ('header', '.v'))


    class ImageArrayProxy(object):
        ''' Ecat implemention of array proxy protocol

        The array proxy allows us to freeze the passed fileobj and
        header such that it returns the expected data array.
        '''
        def __init__(self, subheader):
            self._subheader = subheader
            self._data = None
            x, y, z = subheader.get_shape()
            nframes = subheader.get_nframes()
            self.shape = (x, y, z, nframes)

        def __array__(self):
            ''' Cached read of data from file
            This reads ALL FRAMES into one array, can be memory expensive
            use subheader.data_from_fileobj(frame) for less memory intensive
            reads
            '''
            if self._data is None:
                self._data = np.empty(self.shape)
                frame_mapping = self._subheader._mlist.get_frame_order()
                for i in sorted(frame_mapping):
                    self._data[:,:,:,i] = self._subheader.data_from_fileobj(frame_mapping[i][0])
            return self._data

    def __init__(self, data, affine, header,
                 subheader, mlist ,
                 extra = None, file_map = None):
        """ Initialize Image

        The image is a combination of
        (array, affine matrix, header, subheader, mlist)
        with optional meta data in `extra`, and filename / file-like objects
        contained in the `file_map`.

        Parameters
        ----------
        data : None or array-like
            image data
        affine : None or (4,4) array-like
            homogeneous affine giving relationship between voxel coords and
            world coords.
        header : None or header instance
            meta data for this image format
        subheader : None or subheader instance
            meta data for each sub-image for frame in the image
        mlist : None or mlist instance
            meta data with array giving offset and order of data in file
        extra : None or mapping, optional
            metadata associated with this image that cannot be
            stored in header or subheader
        file_map : mapping, optional
            mapping giving file information for this image format

        Examples
        --------
        >>> import os
        >>> import nibabel as nib
        >>> nibabel_dir = os.path.dirname(nib.__file__)
        >>> from nibabel import ecat
        >>> ecat_file = os.path.join(nibabel_dir,'tests','data','tinypet.v')
        >>> img = ecat.load(ecat_file)
        >>> frame0 = img.get_frame(0)
        >>> frame0.shape == (10, 10, 3)
        True
        >>> data4d = img.get_data()
        >>> data4d.shape == (10, 10, 3, 1)
        True
        """
        self._subheader = subheader
        self._mlist = mlist
        self._data = data
        if not affine is None:
            # Check that affine is array-like 4,4.  Maybe this is too strict at
            # this abstract level, but so far I think all image formats we know
            # do need 4,4.
            affine = np.asarray(affine)
            if not affine.shape == (4,4):
                raise ValueError('Affine should be shape 4,4')
        self._affine = affine
        if extra is None:
            extra = {}
        self.extra = extra
        self._header = header
        if file_map is None:
            file_map = self.__class__.make_file_map()
        self.file_map = file_map

    def _set_header(self, header):
        self._header = header

    def get_data(self):
        """returns scaled data for all frames in a numpy array
        returns as a 4D array """
        if self._data is None:
            raise ImageDataError('No data in this image')
        return np.asanyarray(self._data)

    def get_affine(self):
        if not self._subheader._check_affines():
            warnings.warn('Affines different across frames, loading affine from FIRST frame',
                          UserWarning )
        return self._affine

    def get_frame_affine(self, frame):
        """returns 4X4 affine"""
        return self._subheader.get_frame_affine(frame=frame)

    def get_frame(self,frame, orientation=None):
        '''
        Get full volume for a time frame

        :param frame: Time frame index from where to fetch data
        :param orientation: None (default), 'neurological' or 'radiological'
        :rtype: Numpy array containing (possibly oriented) raw data
        '''
        return self._subheader.data_from_fileobj(frame, orientation)

    def get_data_dtype(self,frame):
        subhdr = self._subheader
        dt = subhdr._get_data_dtype(frame)
        return dt

    @property
    def shape(self):
        x,y,z = self._subheader.get_shape()
        nframes = self._subheader.get_nframes()
        return(x, y, z, nframes)

    def get_mlist(self):
        """ get access to the mlist """
        return self._mlist

    def get_subheaders(self):
        """get access to subheaders"""
        return self._subheader

    @classmethod
    def from_filespec(klass, filespec):
        return klass.from_filename(filespec)


    @staticmethod
    def _get_fileholders(file_map):
        """ returns files specific to header and image of the image
        for ecat .v this is the same image file

        Returns
        -------
        header : file holding header data
        image : file holding image data
        """
        return file_map['header'], file_map['image']

    @classmethod
    def from_file_map(klass, file_map):
        """class method to create image from mapping
        specified in file_map"""
        hdr_file, img_file = klass._get_fileholders(file_map)
        #note header and image are in same file
        hdr_fid = hdr_file.get_prepare_fileobj(mode = 'rb')
        header = klass._header.from_fileobj(hdr_fid)
        hdr_copy = header.copy()
        ### LOAD MLIST
        mlist = klass._mlist(hdr_fid, hdr_copy)
        ### LOAD SUBHEADERS
        subheaders = klass._subheader(hdr_copy,
                                      mlist,
                                      hdr_fid)
        ### LOAD DATA
        ##  Class level ImageArrayProxy
        data = klass.ImageArrayProxy(subheaders)

        ## Get affine
        if not subheaders._check_affines():
            warnings.warn('Affines different across frames, loading affine from FIRST frame',
                          UserWarning )
        aff = subheaders.get_frame_affine()
        img = klass(data, aff, header, subheaders, mlist, extra=None, file_map = file_map)
        return img

    def _get_empty_dir(self):
        '''
        Get empty directory entry of the form
        [numAvail, nextDir, previousDir, numUsed]
        '''
        return np.array([31, 2, 0, 0], dtype=np.uint32)

    def _write_data(self, data, stream, pos, dtype=None, endianness=None):
        '''
        Write data to ``stream`` using an array_writer

        :param data: Numpy array containing the dat
        :param stream: The file-like object to write the data to
        :param pos: The position in the stream to write the data to
        :param endianness: Endianness code of the data to write
        '''
        if dtype is None:
            dtype = data.dtype

        if endianness is None:
            endianness = native_code

        stream.seek(pos)
        writer = make_array_writer(
            data.newbyteorder(endianness),
            dtype).to_fileobj(stream)

    def to_file_map(self, file_map=None):
        ''' Write ECAT7 image to `file_map` or contained ``self.file_map``

        The format consist of:

        - A main header (512L) with dictionary entries in the form
            [numAvail, nextDir, previousDir, numUsed]
        - For every frame (3D volume in 4D data)
          - A subheader (size = frame_offset)
          - Frame data (3D volume)
        '''
        if file_map is None:
            file_map = self.file_map

        data = self.get_data()
        hdr = self.get_header()
        mlist = self.get_mlist()._mlist
        subheaders = self.get_subheaders()
        dir_pos = 512L
        entry_pos = dir_pos + 16L #528L
        current_dir = self._get_empty_dir()

        hdr_fh, img_fh = self._get_fileholders(file_map)
        hdrf = hdr_fh.get_prepare_fileobj(mode='wb')
        imgf = hdrf

        #Write main header
        hdr.write_to(hdrf)

        #Write every frames
        for index in xrange(0, self.get_header()['num_frames']):
            #Move to subheader offset
            frame_offset = subheaders._get_frame_offset(index) - 512
            imgf.seek(frame_offset)

            #Write subheader
            subhdr = subheaders.subheaders[index]
            imgf.write(subhdr.tostring())

            #Seek to the next image block
            pos = imgf.tell()
            imgf.seek(pos + 2)

            #Get frame and its data type
            image = self._subheader.raw_data_from_fileobj(index)
            dtype = image.dtype

            #Write frame images
            self._write_data(image, imgf, pos+2, endianness='>')

            #Move to dictionnary offset and write dictionnary entry
            self._write_data(mlist[index], imgf, entry_pos,
                np.uint32, endianness='>')

            entry_pos = entry_pos + 16L

            current_dir[0] = current_dir[0] - 1
            current_dir[3] = current_dir[3] + 1

            #Create a new directory is previous one is full
            if current_dir[0] == 0:
                #self._write_dir(current_dir, imgf, dir_pos)
                self._write_data(current_dir, imgf, dir_pos)
                current_dir = self._get_empty_dir()
                current_dir[3] = dir_pos / 512L
                dir_pos = mlist[index][2] + 1
                entry_pos = dir_pos + 16L

        tmp_avail = current_dir[0]
        tmp_used = current_dir[3]

        #Fill directory with empty data until directory is full
        while current_dir[0] > 0:
            entry_pos = dir_pos + 16L + (16L * current_dir[3])
            self._write_data(np.array([0,0,0,0]), imgf, entry_pos, np.uint32)
            current_dir[0] = current_dir[0] - 1
            current_dir[3] = current_dir[3] + 1

        current_dir[0] = tmp_avail
        current_dir[3] = tmp_used

        #Write directory index
        self._write_data(current_dir, imgf, dir_pos, endianness='>')


    @classmethod
    def from_image(klass, img):
        raise NotImplementedError("Ecat images can only be generated "\
                                  "from file objects")

    @classmethod
    def load(klass, filespec):
        return klass.from_filename(filespec)


load = EcatImage.load