From e9f5a3e8c55e4d3916cf7bbd0eed9ab81e56faea Mon Sep 17 00:00:00 2001 From: "Gregory R. Lee" Date: Tue, 1 Dec 2015 17:46:14 -0500 Subject: [PATCH 01/14] ENH: improve sorting of more complicated .PAR/.REC files --- bin/parrec2nii | 10 +++- nibabel/parrec.py | 104 ++++++++++++++++++++++++++++++----- nibabel/tests/test_parrec.py | 27 ++++++++- 3 files changed, 124 insertions(+), 17 deletions(-) diff --git a/bin/parrec2nii b/bin/parrec2nii index 547fb94e01..9bc283f330 100755 --- a/bin/parrec2nii +++ b/bin/parrec2nii @@ -113,6 +113,13 @@ def get_opt_parser(): default=False, help=one_line("""Overwrite file if it exists. Default: False"""))) + p.add_option( + Option("--strict-sort", action="store_true", dest="strict_sort", + default=False, + help=one_line("""Use additional keys in determining the order + to sort the slices within the .REC file. This may be necessary + for more complicated scans with multiple echos, + cardiac phases, ASL label states, etc."""))) return p @@ -148,7 +155,8 @@ def proc_file(infile, opts): infile = fname_ext_ul_case(infile) pr_img = pr.load(infile, permit_truncated=opts.permit_truncated, - scaling=scaling) + scaling=scaling, + strict_sort=opts.strict_sort) pr_hdr = pr_img.header affine = pr_hdr.get_affine(origin=opts.origin) slope, intercept = pr_hdr.get_data_scaling(scaling) diff --git a/nibabel/parrec.py b/nibabel/parrec.py index bf40b0a78f..20f49a1172 100644 --- a/nibabel/parrec.py +++ b/nibabel/parrec.py @@ -618,7 +618,8 @@ def __getitem__(self, slicer): class PARRECHeader(SpatialHeader): """PAR/REC header""" - def __init__(self, info, image_defs, permit_truncated=False): + def __init__(self, info, image_defs, permit_truncated=False, + strict_sort=False): """ Parameters ---------- @@ -631,10 +632,14 @@ def __init__(self, info, image_defs, permit_truncated=False): permit_truncated : bool, optional If True, a warning is emitted instead of an error when a truncated recording is detected. + strict_sort : bool, optional, keyword-only + If True, a larger number of header fields are used while sorting + the REC data array. """ self.general_info = info.copy() self.image_defs = image_defs.copy() self.permit_truncated = permit_truncated + self.strict_sort = strict_sort _truncation_checks(info, image_defs, permit_truncated) # charge with basic properties to be able to use base class # functionality @@ -660,14 +665,16 @@ def from_header(klass, header=None): 'non-PARREC header.') @classmethod - def from_fileobj(klass, fileobj, permit_truncated=False): + def from_fileobj(klass, fileobj, permit_truncated=False, + strict_sort=False): info, image_defs = parse_PAR_header(fileobj) - return klass(info, image_defs, permit_truncated) + return klass(info, image_defs, permit_truncated, strict_sort) def copy(self): return PARRECHeader(deepcopy(self.general_info), self.image_defs.copy(), - self.permit_truncated) + self.permit_truncated, + self.strict_sort) def as_analyze_map(self): """Convert PAR parameters to NIFTI1 format""" @@ -1003,6 +1010,9 @@ def get_sorted_slice_indices(self): If the recording is truncated, the returned indices take care of discarding any slice indices from incomplete volumes. + If `self.strict_sort` is True, a more complicated sorting based on + multiple fields from the .PAR file is used. + Returns ------- slice_indices : list @@ -1010,13 +1020,71 @@ def get_sorted_slice_indices(self): array, and (equivalently) the only dimension of ``self.image_defs``. """ - slice_nos = self.image_defs['slice number'] - is_full = vol_is_full(slice_nos, self.general_info['max_slices']) - keys = (slice_nos, vol_numbers(slice_nos), np.logical_not(is_full)) - # Figure out how many we need to remove from the end, and trim them - # Based on our sorting, they should always be last + if not self.strict_sort: + slice_nos = self.image_defs['slice number'] + is_full = vol_is_full(slice_nos, self.general_info['max_slices']) + keys = (slice_nos, vol_numbers(slice_nos), np.logical_not(is_full)) + sort_order = np.lexsort(keys) + else: + # Sort based on a larger number of keys. This is more complicated + # but works for .PAR files that get missorted by the above method + slice_nos = self.image_defs['slice number'] + dynamics = self.image_defs['dynamic scan number'] + phases = self.image_defs['cardiac phase number'] + echos = self.image_defs['echo number'] + + # try adding keys only present in a subset of .PAR files + try: + # only present in PAR v4.2+ + asl_labels = self.image_defs['label type'] + asl_keys = (asl_labels, ) + except: + asl_keys = () + if not self.general_info['diffusion'] == 0: + try: + # only present for .PAR v4.1+ + bvals = self.image_defs['diffusion b value number'] + bvecs = self.image_defs['gradient orientation number'] + except: + bvals = self.image_defs['diffusion_b_factor'] + # use hash to get a single sortable value per direction + bvecs = [hash(tuple( + a)) for a in self.image_defs['diffusion'].tolist()] + diffusion_keys = (bvecs, bvals) + else: + diffusion_keys = () + + # Define the desired sort order (last key is highest precedence) + keys = (slice_nos, echos, phases) + \ + diffusion_keys + asl_keys + (dynamics, ) + + """ + Data sorting is done in two stages: + - run an initial sort using the keys defined above + - call vol_is_full to identify potentially missing volumes + - call vol_numbers to assign unique volume numbers if for some + reason the keys defined above don't provide a unique sort + order (e.g. this occurs for the Trace volume in DTI) + - run a final sort using the vol_numbers and is_full keys + """ + initial_sort_order = np.lexsort(keys) + is_full = vol_is_full(slice_nos[initial_sort_order], + self.general_info['max_slices']) + vol_nos = vol_numbers(slice_nos[initial_sort_order]) + + # have to "unsort" is_full and vol_nos to match the other sort keys + unsort_indices = np.argsort(initial_sort_order) + is_full = is_full[unsort_indices] + vol_nos = np.asarray(vol_nos)[unsort_indices] + + # final set of sort keys + keys += (vol_nos, np.logical_not(is_full), ) + sort_order = np.lexsort(keys) + + # Figure out how many we need to remove from the end, and trim them. + # Based on our sorting, they should always be last. n_used = np.prod(self.get_data_shape()[2:]) - return np.lexsort(keys)[:n_used] + return sort_order[:n_used] class PARRECImage(SpatialImage): @@ -1033,7 +1101,7 @@ class PARRECImage(SpatialImage): @classmethod @kw_only_meth(1) def from_file_map(klass, file_map, mmap=True, permit_truncated=False, - scaling='dv'): + scaling='dv', strict_sort=False): """ Create PARREC image from file map `file_map` Parameters @@ -1054,11 +1122,15 @@ def from_file_map(klass, file_map, mmap=True, permit_truncated=False, scaling : {'dv', 'fp'}, optional, keyword-only Scaling method to apply to data (see :meth:`PARRECHeader.get_data_scaling`). + strict_sort : bool, optional, keyword-only + If True, a larger number of header fields are used while sorting + the REC data array. """ with file_map['header'].get_prepare_fileobj('rt') as hdr_fobj: hdr = klass.header_class.from_fileobj( hdr_fobj, - permit_truncated=permit_truncated) + permit_truncated=permit_truncated, + strict_sort=strict_sort) rec_fobj = file_map['image'].get_prepare_fileobj() data = klass.ImageArrayProxy(rec_fobj, hdr, mmap=mmap, scaling=scaling) @@ -1068,7 +1140,7 @@ def from_file_map(klass, file_map, mmap=True, permit_truncated=False, @classmethod @kw_only_meth(1) def from_filename(klass, filename, mmap=True, permit_truncated=False, - scaling='dv'): + scaling='dv', strict_sort=False): """ Create PARREC image from filename `filename` Parameters @@ -1088,12 +1160,16 @@ def from_filename(klass, filename, mmap=True, permit_truncated=False, scaling : {'dv', 'fp'}, optional, keyword-only Scaling method to apply to data (see :meth:`PARRECHeader.get_data_scaling`). + strict_sort : bool, optional, keyword-only + If True, a larger number of header fields are used while sorting + the REC data array. """ file_map = klass.filespec_to_file_map(filename) return klass.from_file_map(file_map, mmap=mmap, permit_truncated=permit_truncated, - scaling=scaling) + scaling=scaling, + strict_sort=strict_sort) load = from_filename diff --git a/nibabel/tests/test_parrec.py b/nibabel/tests/test_parrec.py index 432ec614ae..f76570babf 100644 --- a/nibabel/tests/test_parrec.py +++ b/nibabel/tests/test_parrec.py @@ -113,7 +113,6 @@ [0., 0., 3.3, -64.35], [0., 0., 0., 1.]]), } - # Original values for b values in DTI.PAR, still in PSL orientation DTI_PAR_BVECS = np.array([[-0.667, -0.667, -0.333], [-0.333, 0.667, -0.667], @@ -259,6 +258,10 @@ def test_get_sorted_slice_indices(): hdr = PARRECHeader(HDR_INFO, HDR_DEFS[:-1], permit_truncated=True) assert_array_equal(hdr.get_sorted_slice_indices(), range(n_slices - 9)) + # different result when strict_sort=True + hdr = PARRECHeader(HDR_INFO, HDR_DEFS[::-1], strict_sort=True) + assert_array_equal(hdr.get_sorted_slice_indices(), range(n_slices)[::-1]) + def test_vol_number(): # Test algorithm for calculating volume number @@ -340,6 +343,25 @@ def test_diffusion_parameters(): assert_almost_equal(dti_hdr.get_q_vectors(), bvals[:, None] * bvecs) +def test_diffusion_parameters_strict_sort(): + # Check getting diffusion parameters from diffusion example + dti_par = pjoin(DATA_PATH, 'DTI.PAR') + with open(dti_par, 'rt') as fobj: + dti_hdr = PARRECHeader.from_fileobj(fobj, strict_sort=True) + assert_equal(dti_hdr.get_data_shape(), (80, 80, 10, 8)) + assert_equal(dti_hdr.general_info['diffusion'], 1) + bvals, bvecs = dti_hdr.get_bvals_bvecs() + assert_almost_equal(bvals, np.sort(DTI_PAR_BVALS)) + # DTI_PAR_BVECS gives bvecs copied from first slice each vol in DTI.PAR + # Permute to match bvec directions to acquisition directions + # note that bval sorting occurs prior to bvec sorting + assert_almost_equal(bvecs, + DTI_PAR_BVECS[ + np.ix_(np.argsort(DTI_PAR_BVALS), [2, 0, 1])]) + # Check q vectors + assert_almost_equal(dti_hdr.get_q_vectors(), bvals[:, None] * bvecs) + + def test_diffusion_parameters_v4(): dti_v4_par = pjoin(DATA_PATH, 'DTIv40.PAR') with open(dti_v4_par, 'rt') as fobj: @@ -530,9 +552,10 @@ class FakeHeader(object): """ Minimal API of header for PARRECArrayProxy """ - def __init__(self, shape, dtype): + def __init__(self, shape, dtype, strict_sort=False): self._shape = shape self._dtype = np.dtype(dtype) + self.strict_sort = strict_sort def get_data_shape(self): return self._shape From 19fd9c1f6c2bc215d16304b78bdd65d4b1b111d3 Mon Sep 17 00:00:00 2001 From: "Gregory R. Lee" Date: Sat, 13 Feb 2016 17:07:00 -0500 Subject: [PATCH 02/14] TST: add test for proper sorting of a .PAR file corresponding to a multi-echo 3D T1-weighted scan --- nibabel/tests/data/T1_dual_echo.PAR | 462 ++++++++++++++++++++++++++++ nibabel/tests/test_parrec.py | 15 + 2 files changed, 477 insertions(+) create mode 100644 nibabel/tests/data/T1_dual_echo.PAR diff --git a/nibabel/tests/data/T1_dual_echo.PAR b/nibabel/tests/data/T1_dual_echo.PAR new file mode 100644 index 0000000000..da128ae71a --- /dev/null +++ b/nibabel/tests/data/T1_dual_echo.PAR @@ -0,0 +1,462 @@ +# === DATA DESCRIPTION FILE ====================================================== +# +# CAUTION - Investigational device. +# Limited by Federal Law to investigational use. +# +# Dataset name: E:\\Export\\T1_dual_echo.PAR +# +# CLINICAL TRYOUT Research image export tool V4.2 +# +# === GENERAL INFORMATION ======================================================== +# +. Patient name : anon +. Examination name : anon +. Protocol name : anon +. Examination date/time : anon +. Series Type : Image MRSERIES +. Acquisition nr : 5 +. Reconstruction nr : 1 +. Scan Duration [sec] : 200 +. Max. number of cardiac phases : 1 +. Max. number of echoes : 2 +. Max. number of slices/locations : 180 +. Max. number of dynamics : 1 +. Max. number of mixes : 1 +. Patient position : Head First Supine +. Preparation direction : Anterior-Posterior +. Technique : T1TFE +. Scan resolution (x, y) : 256 256 +. Scan mode : 3D +. Repetition time [ms] : 8.133 +. FOV (ap,fh,rl) [mm] : 224.000 256.000 180.000 +. Water Fat shift [pixels] : 0.854 +. Angulation midslice(ap,fh,rl)[degr]: 0.000 0.000 0.000 +. Off Centre midslice(ap,fh,rl) [mm] : -5.055 12.640 -2.405 +. Flow compensation <0=no 1=yes> ? : 0 +. Presaturation <0=no 1=yes> ? : 0 +. Phase encoding velocity [cm/sec] : 0.000000 0.000000 0.000000 +. MTC <0=no 1=yes> ? : 0 +. SPIR <0=no 1=yes> ? : 0 +. EPI factor <0,1=no EPI> : 1 +. Dynamic scan <0=no 1=yes> ? : 0 +. Diffusion <0=no 1=yes> ? : 0 +. Diffusion echo time [ms] : 0.0000 +. Max. number of diffusion values : 1 +. Max. number of gradient orients : 1 +. Number of label types <0=no ASL> : 0 +# +# === PIXEL VALUES ============================================================= +# PV = pixel value in REC file, FP = floating point value, DV = displayed value on console +# RS = rescale slope, RI = rescale intercept, SS = scale slope +# DV = PV * RS + RI FP = DV / (RS * SS) +# +# === IMAGE INFORMATION DEFINITION ============================================= +# The rest of this file contains ONE line per image, this line contains the following information: +# +# slice number (integer) +# echo number (integer) +# dynamic scan number (integer) +# cardiac phase number (integer) +# image_type_mr (integer) +# scanning sequence (integer) +# index in REC file (in images) (integer) +# image pixel size (in bits) (integer) +# scan percentage (integer) +# recon resolution (x y) (2*integer) +# rescale intercept (float) +# rescale slope (float) +# scale slope (float) +# window center (integer) +# window width (integer) +# image angulation (ap,fh,rl in degrees ) (3*float) +# image offcentre (ap,fh,rl in mm ) (3*float) +# slice thickness (in mm ) (float) +# slice gap (in mm ) (float) +# image_display_orientation (integer) +# slice orientation ( TRA/SAG/COR ) (integer) +# fmri_status_indication (integer) +# image_type_ed_es (end diast/end syst) (integer) +# pixel spacing (x,y) (in mm) (2*float) +# echo_time (float) +# dyn_scan_begin_time (float) +# trigger_time (float) +# diffusion_b_factor (float) +# number of averages (integer) +# image_flip_angle (in degrees) (float) +# cardiac frequency (bpm) (integer) +# minimum RR-interval (in ms) (integer) +# maximum RR-interval (in ms) (integer) +# TURBO factor <0=no turbo> (integer) +# Inversion delay (in ms) (float) +# diffusion b value number (imagekey!) (integer) +# gradient orientation number (imagekey!) (integer) +# contrast type (string) +# diffusion anisotropy type (string) +# diffusion (ap, fh, rl) (3*float) +# label type (ASL) (imagekey!) (integer) +# +# === IMAGE INFORMATION ========================================================== +# sl ec dyn ph ty idx pix scan% rec size (re)scale window angulation offcentre thick gap info spacing echo dtime ttime diff avg flip freq RR-int turbo delay b grad cont anis diffusion L.ty + + 54 1 1 1 0 2 0 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 34.10 1.000 0.000 0 2 0 2 1.000 1.000 2.30 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 91 1 1 1 0 2 1 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 -2.90 1.000 0.000 0 2 0 2 1.000 1.000 2.30 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 90 1 1 1 0 2 2 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 -1.90 1.000 0.000 0 2 0 2 1.000 1.000 2.30 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 89 1 1 1 0 2 3 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 -0.90 1.000 0.000 0 2 0 2 1.000 1.000 2.30 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 92 1 1 1 0 2 4 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 -3.90 1.000 0.000 0 2 0 2 1.000 1.000 2.30 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 4 2 1 1 0 2 5 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 84.10 1.000 0.000 0 2 0 2 1.000 1.000 5.76 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 55 1 1 1 0 2 6 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 33.10 1.000 0.000 0 2 0 2 1.000 1.000 2.30 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 +175 2 1 1 0 2 7 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 -86.90 1.000 0.000 0 2 0 2 1.000 1.000 5.76 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 +174 2 1 1 0 2 8 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 -85.90 1.000 0.000 0 2 0 2 1.000 1.000 5.76 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 +173 2 1 1 0 2 9 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 -84.90 1.000 0.000 0 2 0 2 1.000 1.000 5.76 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 88 1 1 1 0 2 10 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 0.10 1.000 0.000 0 2 0 2 1.000 1.000 2.30 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 56 1 1 1 0 2 11 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 32.10 1.000 0.000 0 2 0 2 1.000 1.000 2.30 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 5 2 1 1 0 2 12 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 83.10 1.000 0.000 0 2 0 2 1.000 1.000 5.76 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 94 1 1 1 0 2 13 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 -5.90 1.000 0.000 0 2 0 2 1.000 1.000 2.30 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 +172 2 1 1 0 2 14 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 -83.90 1.000 0.000 0 2 0 2 1.000 1.000 5.76 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 1 1 1 1 0 2 15 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 87.10 1.000 0.000 0 2 0 2 1.000 1.000 2.30 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 57 1 1 1 0 2 16 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 31.10 1.000 0.000 0 2 0 2 1.000 1.000 2.30 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 87 1 1 1 0 2 17 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 1.10 1.000 0.000 0 2 0 2 1.000 1.000 2.30 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 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0.0 1 1 7 0 0.000 0.000 0.000 1 + 76 2 1 1 0 2 338 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 12.10 1.000 0.000 0 2 0 2 1.000 1.000 5.76 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 55 2 1 1 0 2 339 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 33.10 1.000 0.000 0 2 0 2 1.000 1.000 5.76 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 75 2 1 1 0 2 340 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 13.10 1.000 0.000 0 2 0 2 1.000 1.000 5.76 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 73 2 1 1 0 2 341 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 15.10 1.000 0.000 0 2 0 2 1.000 1.000 5.76 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 74 2 1 1 0 2 342 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 14.10 1.000 0.000 0 2 0 2 1.000 1.000 5.76 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 72 2 1 1 0 2 343 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 16.10 1.000 0.000 0 2 0 2 1.000 1.000 5.76 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 71 2 1 1 0 2 344 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 17.10 1.000 0.000 0 2 0 2 1.000 1.000 5.76 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 56 2 1 1 0 2 345 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 32.10 1.000 0.000 0 2 0 2 1.000 1.000 5.76 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 70 2 1 1 0 2 346 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 18.10 1.000 0.000 0 2 0 2 1.000 1.000 5.76 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 67 2 1 1 0 2 347 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 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0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 23.10 1.000 0.000 0 2 0 2 1.000 1.000 5.76 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 63 2 1 1 0 2 353 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 25.10 1.000 0.000 0 2 0 2 1.000 1.000 5.76 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 62 2 1 1 0 2 354 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 26.10 1.000 0.000 0 2 0 2 1.000 1.000 5.76 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 64 2 1 1 0 2 355 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 24.10 1.000 0.000 0 2 0 2 1.000 1.000 5.76 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 60 2 1 1 0 2 356 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 28.10 1.000 0.000 0 2 0 2 1.000 1.000 5.76 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 61 2 1 1 0 2 357 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 27.10 1.000 0.000 0 2 0 2 1.000 1.000 5.76 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 58 2 1 1 0 2 358 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 30.10 1.000 0.000 0 2 0 2 1.000 1.000 5.76 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + 59 2 1 1 0 2 359 16 100 256 256 0.00000 9.97143 3.65651e-003 1070 1860 0.00 -0.00 -0.00 -5.06 12.64 29.10 1.000 0.000 0 2 0 2 1.000 1.000 5.76 0.00 0.00 0.00 1 8.00 0 0 0 448 0.0 1 1 7 0 0.000 0.000 0.000 1 + +# === END OF DATA DESCRIPTION FILE =============================================== diff --git a/nibabel/tests/test_parrec.py b/nibabel/tests/test_parrec.py index f76570babf..7cfb9831e2 100644 --- a/nibabel/tests/test_parrec.py +++ b/nibabel/tests/test_parrec.py @@ -263,6 +263,21 @@ def test_get_sorted_slice_indices(): assert_array_equal(hdr.get_sorted_slice_indices(), range(n_slices)[::-1]) +def test_sorting_dual_echo_T1(): + # For this .PAR file, instead of getting 1 echo per volume, they get + # mixed up unless strict_sort=True + dti_par = pjoin(DATA_PATH, 'T1_dual_echo.PAR') + with open(dti_par, 'rt') as fobj: + dti_hdr = PARRECHeader.from_fileobj(fobj, strict_sort=True) + sorted_indices = dti_hdr.get_sorted_slice_indices() + sorted_echos = dti_hdr.image_defs['echo number'][sorted_indices] + n_half = len(dti_hdr.image_defs) // 2 + # first half (volume 1) should all correspond to echo 1 + assert_equal(np.all(sorted_echos[:n_half] == 1), True) + # second half (volume 2) should all correspond to echo 2 + assert_equal(np.all(sorted_echos[n_half:] == 2), True) + + def test_vol_number(): # Test algorithm for calculating volume number assert_array_equal(vol_numbers([1, 3, 0]), [0, 0, 0]) From f55e7a94f7dbd7f11410307cc3e2e03851fa739c Mon Sep 17 00:00:00 2001 From: "Gregory R. Lee" Date: Mon, 15 Feb 2016 16:27:04 -0500 Subject: [PATCH 03/14] STY: improve coding style for parrec based on feedback --- nibabel/parrec.py | 62 +++++++++++++++++++++++++----------- nibabel/tests/test_parrec.py | 3 +- 2 files changed, 44 insertions(+), 21 deletions(-) diff --git a/nibabel/parrec.py b/nibabel/parrec.py index 20f49a1172..52e035f7ab 100644 --- a/nibabel/parrec.py +++ b/nibabel/parrec.py @@ -329,6 +329,21 @@ def _process_image_lines(image_lines, version): return image_defs +def _direction_numbers(bvecs): + """ Enumerate directions from an (N, 3) array of direction vectors. + """ + cnt = 0 + bvec_dict = {} + bvec_nos = np.zeros(len(bvecs)) + for i, bvec in enumerate(bvecs): + bv = tuple(bvec) + if bv not in bvec_dict: + bvec_dict[bv] = cnt + cnt += 1 + bvec_nos[i] = bvec_dict.get(bv) + return bvec_nos + + def vol_numbers(slice_nos): """ Calculate volume numbers inferred from slice numbers `slice_nos` @@ -634,7 +649,9 @@ def __init__(self, info, image_defs, permit_truncated=False, recording is detected. strict_sort : bool, optional, keyword-only If True, a larger number of header fields are used while sorting - the REC data array. + the REC data array. This may produce a different sort order than + `strict_sort=False`, where volumes are sorted by the order in which + the slices appear in the .PAR file. """ self.general_info = info.copy() self.image_defs = image_defs.copy() @@ -747,6 +764,11 @@ def get_bvals_bvecs(self): bvecs = apply_affine(np.linalg.inv(permute_to_psl), bvecs) return bvals, bvecs + def get_def(self, name): + """ Return a single image definition field. """ + idef = self.image_defs + return idef[name] if name in idef.dtype.names else None + def _get_unique_image_prop(self, name): """ Scan image definitions and return unique value of a property. @@ -1011,7 +1033,9 @@ def get_sorted_slice_indices(self): discarding any slice indices from incomplete volumes. If `self.strict_sort` is True, a more complicated sorting based on - multiple fields from the .PAR file is used. + multiple fields from the .PAR file is used. This may produce a + different sort order than `strict_sort=False`, where volumes are sorted + by the order in which the slices appear in the .PAR file. Returns ------- @@ -1034,22 +1058,18 @@ def get_sorted_slice_indices(self): echos = self.image_defs['echo number'] # try adding keys only present in a subset of .PAR files - try: - # only present in PAR v4.2+ - asl_labels = self.image_defs['label type'] - asl_keys = (asl_labels, ) - except: - asl_keys = () + idefs = self.image_defs + asl_keys = (idefs['label_type'], ) if 'label_type' in \ + idefs.dtype.names else () + if not self.general_info['diffusion'] == 0: - try: - # only present for .PAR v4.1+ - bvals = self.image_defs['diffusion b value number'] - bvecs = self.image_defs['gradient orientation number'] - except: - bvals = self.image_defs['diffusion_b_factor'] - # use hash to get a single sortable value per direction - bvecs = [hash(tuple( - a)) for a in self.image_defs['diffusion'].tolist()] + bvals = self.get_def('diffusion b value number') + if bvals is None: + bvals = self.get_def('diffusion_b_factor') + bvecs = self.get_def('gradient orientation number') + if bvecs is None: + # manually enumerate the different directions + bvecs = _direction_numbers(self.get_def('diffusion')) diffusion_keys = (bvecs, bvals) else: diffusion_keys = () @@ -1124,7 +1144,9 @@ def from_file_map(klass, file_map, mmap=True, permit_truncated=False, :meth:`PARRECHeader.get_data_scaling`). strict_sort : bool, optional, keyword-only If True, a larger number of header fields are used while sorting - the REC data array. + the REC data array. This may produce a different sort order than + `strict_sort=False`, where volumes are sorted by the order in which + the slices appear in the .PAR file. """ with file_map['header'].get_prepare_fileobj('rt') as hdr_fobj: hdr = klass.header_class.from_fileobj( @@ -1162,7 +1184,9 @@ def from_filename(klass, filename, mmap=True, permit_truncated=False, :meth:`PARRECHeader.get_data_scaling`). strict_sort : bool, optional, keyword-only If True, a larger number of header fields are used while sorting - the REC data array. + the REC data array. This may produce a different sort order than + `strict_sort=False`, where volumes are sorted by the order in which + the slices appear in the .PAR file. """ file_map = klass.filespec_to_file_map(filename) return klass.from_file_map(file_map, diff --git a/nibabel/tests/test_parrec.py b/nibabel/tests/test_parrec.py index 7cfb9831e2..456e8e2807 100644 --- a/nibabel/tests/test_parrec.py +++ b/nibabel/tests/test_parrec.py @@ -567,10 +567,9 @@ class FakeHeader(object): """ Minimal API of header for PARRECArrayProxy """ - def __init__(self, shape, dtype, strict_sort=False): + def __init__(self, shape, dtype): self._shape = shape self._dtype = np.dtype(dtype) - self.strict_sort = strict_sort def get_data_shape(self): return self._shape From e201289c9603b45726a874046b3cdd11eea1623c Mon Sep 17 00:00:00 2001 From: "Gregory R. Lee" Date: Mon, 15 Feb 2016 16:59:48 -0500 Subject: [PATCH 04/14] FIX: add image_type_mr as a sort key. This is to support scans where multiple image types (real, imag, magnitude, phase) were selected --- nibabel/parrec.py | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/nibabel/parrec.py b/nibabel/parrec.py index 52e035f7ab..a034872ce4 100644 --- a/nibabel/parrec.py +++ b/nibabel/parrec.py @@ -1056,6 +1056,7 @@ def get_sorted_slice_indices(self): dynamics = self.image_defs['dynamic scan number'] phases = self.image_defs['cardiac phase number'] echos = self.image_defs['echo number'] + image_type = self.image_defs['image_type_mr'] # try adding keys only present in a subset of .PAR files idefs = self.image_defs @@ -1076,7 +1077,7 @@ def get_sorted_slice_indices(self): # Define the desired sort order (last key is highest precedence) keys = (slice_nos, echos, phases) + \ - diffusion_keys + asl_keys + (dynamics, ) + diffusion_keys + asl_keys + (dynamics, image_type) """ Data sorting is done in two stages: @@ -1098,8 +1099,8 @@ def get_sorted_slice_indices(self): vol_nos = np.asarray(vol_nos)[unsort_indices] # final set of sort keys - keys += (vol_nos, np.logical_not(is_full), ) - sort_order = np.lexsort(keys) + keys += (vol_nos, np.logical_not(is_full)) # highest priority + sort_order = np.lexsort(tuple(keys)) # Figure out how many we need to remove from the end, and trim them. # Based on our sorting, they should always be last. From cd45556266fcd5b94230b7ada58e7e8928b3aee9 Mon Sep 17 00:00:00 2001 From: "Gregory R. Lee" Date: Mon, 15 Feb 2016 17:18:07 -0500 Subject: [PATCH 05/14] MAINT: split the strict sort logic into a separate _strict_sort_keys subfunction vol_numbers was removed from the list of sort keys for strict_sort as it is not necessary as long as the set of sort keys produces a unique sort order. --- nibabel/parrec.py | 102 +++++++++++++++++++++++----------------------- 1 file changed, 50 insertions(+), 52 deletions(-) diff --git a/nibabel/parrec.py b/nibabel/parrec.py index a034872ce4..1f51410809 100644 --- a/nibabel/parrec.py +++ b/nibabel/parrec.py @@ -1021,6 +1021,54 @@ def get_rec_shape(self): inplane_shape = tuple(self._get_unique_image_prop('recon resolution')) return inplane_shape + (len(self.image_defs),) + def _strict_sort_keys(self): + """ Determine the sort order based on several image definition fields. + + Data sorting is done in two stages: + - run an initial sort using several keys of interest + - call `vol_is_full` to identify potentially missing volumes + and add the result to the list of sort keys + """ + # Sort based on a larger number of keys. This is more complicated + # but works for .PAR files that get missorted by the above method + slice_nos = self.image_defs['slice number'] + dynamics = self.image_defs['dynamic scan number'] + phases = self.image_defs['cardiac phase number'] + echos = self.image_defs['echo number'] + image_type = self.image_defs['image_type_mr'] + + # try adding keys only present in a subset of .PAR files + idefs = self.image_defs + asl_keys = (idefs['label_type'], ) if 'label_type' in \ + idefs.dtype.names else () + + if not self.general_info['diffusion'] == 0: + bvals = self.get_def('diffusion b value number') + if bvals is None: + bvals = self.get_def('diffusion_b_factor') + bvecs = self.get_def('gradient orientation number') + if bvecs is None: + # manually enumerate the different directions + bvecs = _direction_numbers(self.get_def('diffusion')) + diffusion_keys = (bvecs, bvals) + else: + diffusion_keys = () + + # Define the desired sort order (last key is highest precedence) + keys = (slice_nos, echos, phases) + \ + diffusion_keys + asl_keys + (dynamics, image_type) + + initial_sort_order = np.lexsort(keys) + is_full = vol_is_full(slice_nos[initial_sort_order], + self.general_info['max_slices']) + + # have to "unsort" is_full to match the other sort keys + unsort_indices = np.argsort(initial_sort_order) + is_full = is_full[unsort_indices] + + # final set of sort keys + return keys + (np.logical_not(is_full), ) + def get_sorted_slice_indices(self): """Return indices to sort (and maybe discard) slices in REC file. @@ -1048,60 +1096,10 @@ def get_sorted_slice_indices(self): slice_nos = self.image_defs['slice number'] is_full = vol_is_full(slice_nos, self.general_info['max_slices']) keys = (slice_nos, vol_numbers(slice_nos), np.logical_not(is_full)) - sort_order = np.lexsort(keys) else: - # Sort based on a larger number of keys. This is more complicated - # but works for .PAR files that get missorted by the above method - slice_nos = self.image_defs['slice number'] - dynamics = self.image_defs['dynamic scan number'] - phases = self.image_defs['cardiac phase number'] - echos = self.image_defs['echo number'] - image_type = self.image_defs['image_type_mr'] - - # try adding keys only present in a subset of .PAR files - idefs = self.image_defs - asl_keys = (idefs['label_type'], ) if 'label_type' in \ - idefs.dtype.names else () - - if not self.general_info['diffusion'] == 0: - bvals = self.get_def('diffusion b value number') - if bvals is None: - bvals = self.get_def('diffusion_b_factor') - bvecs = self.get_def('gradient orientation number') - if bvecs is None: - # manually enumerate the different directions - bvecs = _direction_numbers(self.get_def('diffusion')) - diffusion_keys = (bvecs, bvals) - else: - diffusion_keys = () - - # Define the desired sort order (last key is highest precedence) - keys = (slice_nos, echos, phases) + \ - diffusion_keys + asl_keys + (dynamics, image_type) - - """ - Data sorting is done in two stages: - - run an initial sort using the keys defined above - - call vol_is_full to identify potentially missing volumes - - call vol_numbers to assign unique volume numbers if for some - reason the keys defined above don't provide a unique sort - order (e.g. this occurs for the Trace volume in DTI) - - run a final sort using the vol_numbers and is_full keys - """ - initial_sort_order = np.lexsort(keys) - is_full = vol_is_full(slice_nos[initial_sort_order], - self.general_info['max_slices']) - vol_nos = vol_numbers(slice_nos[initial_sort_order]) - - # have to "unsort" is_full and vol_nos to match the other sort keys - unsort_indices = np.argsort(initial_sort_order) - is_full = is_full[unsort_indices] - vol_nos = np.asarray(vol_nos)[unsort_indices] - - # final set of sort keys - keys += (vol_nos, np.logical_not(is_full)) # highest priority - sort_order = np.lexsort(tuple(keys)) + keys = self._strict_sort_keys() + sort_order = np.lexsort(keys) # Figure out how many we need to remove from the end, and trim them. # Based on our sorting, they should always be last. n_used = np.prod(self.get_data_shape()[2:]) From 2f95cbbe0fad14340556289d66099b87956fd3fd Mon Sep 17 00:00:00 2001 From: "Gregory R. Lee" Date: Mon, 15 Feb 2016 23:32:11 -0500 Subject: [PATCH 06/14] TST: add test for --strict-sort option to parrec2nii --- nibabel/tests/test_scripts.py | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/nibabel/tests/test_scripts.py b/nibabel/tests/test_scripts.py index 33b0bceee5..665c433935 100644 --- a/nibabel/tests/test_scripts.py +++ b/nibabel/tests/test_scripts.py @@ -322,3 +322,12 @@ def test_parrec2nii_with_data(): assert_almost_equal(data_notrace, data[..., good_mask]) assert_almost_equal(bvals_notrace, np.array(DTI_PAR_BVALS)[good_mask]) assert_almost_equal(bvecs_notrace, bvecs_LAS[good_mask]) + # test --strict-sort + run_command(['parrec2nii', '--overwrite', '--keep-trace', + '--bvs', '--strict-sort', dti_par]) + # strict-sort: bvals should be in ascending order + assert_almost_equal(np.loadtxt('DTI.bvals'), np.sort(DTI_PAR_BVALS)) + img = load('DTI.nii') + data_sorted = img.get_data().copy() + assert_almost_equal(data[..., np.argsort(DTI_PAR_BVALS)], data_sorted) + del img From e40ba7870a471812a43c2121bfbee688fac05c84 Mon Sep 17 00:00:00 2001 From: "Gregory R. Lee" Date: Mon, 15 Feb 2016 23:45:31 -0500 Subject: [PATCH 07/14] FIX: fix VisibleDepricationWarning due to incorrect boolean index length in test_parrec2nii_with_data --- nibabel/tests/test_scripts.py | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/nibabel/tests/test_scripts.py b/nibabel/tests/test_scripts.py index 665c433935..3cef877b26 100644 --- a/nibabel/tests/test_scripts.py +++ b/nibabel/tests/test_scripts.py @@ -283,7 +283,9 @@ def test_parrec2nii_with_data(): # Writes bvals, bvecs files if asked run_command(['parrec2nii', '--overwrite', '--keep-trace', '--bvs', dti_par]) - assert_almost_equal(np.loadtxt('DTI.bvals'), DTI_PAR_BVALS) + bvecs_trace = np.loadtxt('DTI.bvecs').T + bvals_trace = np.loadtxt('DTI.bvals') + assert_almost_equal(bvals_trace, DTI_PAR_BVALS) img = load('DTI.nii') data = img.get_data().copy() del img @@ -317,8 +319,8 @@ def test_parrec2nii_with_data(): assert_equal(data_notrace.shape[-1], len(bvecs_notrace)) del img # ensure correct volume was removed - good_mask = np.logical_or((bvecs_notrace != 0).any(axis=1), - bvals_notrace == 0) + good_mask = np.logical_or((bvecs_trace != 0).any(axis=1), + bvals_trace == 0) assert_almost_equal(data_notrace, data[..., good_mask]) assert_almost_equal(bvals_notrace, np.array(DTI_PAR_BVALS)[good_mask]) assert_almost_equal(bvecs_notrace, bvecs_LAS[good_mask]) From 04d5543ce977b4d61ff812917c68dfc128a39514 Mon Sep 17 00:00:00 2001 From: "Gregory R. Lee" Date: Tue, 16 Feb 2016 00:09:35 -0500 Subject: [PATCH 08/14] TST: add test for a .PAR file with both multiple echos and multiple image types (real, imag, magnitude, phase) --- .../data/T1_3echo_mag_real_imag_phase.PAR | 462 ++++++++++++++++++ nibabel/tests/test_parrec.py | 38 ++ 2 files changed, 500 insertions(+) create mode 100644 nibabel/tests/data/T1_3echo_mag_real_imag_phase.PAR diff --git a/nibabel/tests/data/T1_3echo_mag_real_imag_phase.PAR b/nibabel/tests/data/T1_3echo_mag_real_imag_phase.PAR new file mode 100644 index 0000000000..e918475f2c --- /dev/null +++ b/nibabel/tests/data/T1_3echo_mag_real_imag_phase.PAR @@ -0,0 +1,462 @@ +# === DATA DESCRIPTION FILE ====================================================== +# +# CAUTION - Investigational device. +# Limited by Federal Law to investigational use. +# +# Dataset name: E:\\Export\\T1_3echo_mag_real_imag_phase +# +# CLINICAL TRYOUT Research image export tool V4.2 +# +# === GENERAL INFORMATION ======================================================== +# +. Patient name : anon +. Examination name : anon +. Protocol name : anon +. Examination date/time : anon +. Series Type : Image MRSERIES +. Acquisition nr : 15 +. Reconstruction nr : 1 +. Scan Duration [sec] : 11.5 +. Max. number of cardiac phases : 1 +. Max. number of echoes : 3 +. Max. number of slices/locations : 30 +. Max. number of dynamics : 1 +. Max. number of mixes : 1 +. Patient position : Head First Supine +. Preparation direction : Anterior-Posterior +. Technique : T1TFE +. Scan resolution (x, y) : 76 75 +. Scan mode : 3D +. Repetition time [ms] : 6.746 +. FOV (ap,fh,rl) [mm] : 224.000 224.000 90.000 +. Water Fat shift [pixels] : 0.701 +. Angulation midslice(ap,fh,rl)[degr]: 0.000 0.000 0.000 +. Off Centre midslice(ap,fh,rl) [mm] : 5.090 8.176 -4.208 +. Flow compensation <0=no 1=yes> ? : 0 +. Presaturation <0=no 1=yes> ? : 0 +. Phase encoding velocity [cm/sec] : 0.000000 0.000000 0.000000 +. MTC <0=no 1=yes> ? : 0 +. SPIR <0=no 1=yes> ? : 0 +. EPI factor <0,1=no EPI> : 1 +. Dynamic scan <0=no 1=yes> ? : 0 +. Diffusion <0=no 1=yes> ? : 0 +. Diffusion echo time [ms] : 0.0000 +. Max. number of diffusion values : 1 +. Max. number of gradient orients : 1 +. Number of label types <0=no ASL> : 0 +# +# === PIXEL VALUES ============================================================= +# PV = pixel value in REC file, FP = floating point value, DV = displayed value on console +# RS = rescale slope, RI = rescale intercept, SS = scale slope +# DV = PV * RS + RI FP = DV / (RS * SS) +# +# === IMAGE INFORMATION DEFINITION ============================================= +# The rest of this file contains ONE line per image, this line contains the following information: +# +# slice number (integer) +# echo number (integer) +# dynamic scan number (integer) +# cardiac phase number (integer) +# image_type_mr (integer) +# scanning sequence (integer) +# index in REC file (in images) (integer) +# image pixel size (in bits) (integer) +# scan percentage (integer) +# recon resolution (x y) (2*integer) +# rescale intercept (float) +# rescale slope (float) +# scale slope (float) +# window center (integer) +# window width (integer) +# image angulation (ap,fh,rl in degrees ) (3*float) +# image offcentre (ap,fh,rl in mm ) (3*float) +# slice thickness (in mm ) (float) +# slice gap (in mm ) (float) +# image_display_orientation (integer) +# slice orientation ( TRA/SAG/COR ) (integer) +# fmri_status_indication (integer) +# image_type_ed_es (end diast/end syst) (integer) +# pixel spacing (x,y) (in mm) (2*float) +# echo_time (float) +# dyn_scan_begin_time (float) +# trigger_time (float) +# diffusion_b_factor (float) +# number of averages (integer) +# image_flip_angle (in degrees) (float) +# cardiac frequency (bpm) (integer) +# minimum RR-interval (in ms) (integer) +# maximum RR-interval (in ms) (integer) +# TURBO factor <0=no turbo> (integer) +# Inversion delay (in ms) (float) +# diffusion b value number (imagekey!) (integer) +# gradient orientation number (imagekey!) (integer) +# contrast type (string) +# diffusion anisotropy type (string) +# diffusion (ap, fh, rl) (3*float) +# label type (ASL) (imagekey!) (integer) +# +# === IMAGE INFORMATION ========================================================== +# sl ec dyn ph ty idx pix scan% rec size (re)scale window angulation offcentre thick gap info spacing echo dtime ttime diff avg flip freq RR-int turbo delay b grad cont anis diffusion L.ty + + 16 1 1 1 1 2 0 16 98 80 80 -5272.00000 2.57485 4.89549e-005 -847 2280 0.00 -0.00 -0.00 5.09 8.18 -5.71 3.000 0.000 0 2 0 2 2.800 2.800 1.29 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 16 1 1 1 2 2 1 16 98 80 80 -5272.00000 2.57485 4.89549e-005 76 1070 0.00 -0.00 -0.00 5.09 8.18 -5.71 3.000 0.000 0 2 0 2 2.800 2.800 1.29 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 16 1 1 1 0 2 2 16 98 80 80 0.00000 1.28767 9.78947e-005 1070 1860 0.00 -0.00 -0.00 5.09 8.18 -5.71 3.000 0.000 0 2 0 2 2.800 2.800 1.29 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 16 1 1 1 3 2 3 16 98 80 80 -3142.00000 1.53455 6.51740e+002 0 6284 0.00 -0.00 -0.00 5.09 8.18 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4.89549e-005 44 1009 0.00 -0.00 -0.00 5.09 8.18 -8.71 3.000 0.000 0 2 0 2 2.800 2.800 1.29 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 17 1 1 1 0 2 14 16 98 80 80 0.00000 1.28767 9.78947e-005 1070 1860 0.00 -0.00 -0.00 5.09 8.18 -8.71 3.000 0.000 0 2 0 2 2.800 2.800 1.29 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 17 1 1 1 3 2 15 16 98 80 80 -3142.00000 1.53455 6.51740e+002 0 6284 0.00 -0.00 -0.00 5.09 8.18 -8.71 3.000 0.000 0 2 0 2 2.800 2.800 1.29 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 17 2 1 1 1 2 16 16 98 80 80 -5272.00000 2.57485 4.89549e-005 -797 2248 0.00 -0.00 -0.00 5.09 8.18 -8.71 3.000 0.000 0 2 0 2 2.800 2.800 3.28 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 17 2 1 1 2 2 17 16 98 80 80 -5272.00000 2.57485 4.89549e-005 286 1422 0.00 -0.00 -0.00 5.09 8.18 -8.71 3.000 0.000 0 2 0 2 2.800 2.800 3.28 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 17 2 1 1 0 2 18 16 98 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6.51740e+002 0 6284 0.00 -0.00 -0.00 5.09 8.18 -14.71 3.000 0.000 0 2 0 2 2.800 2.800 5.27 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 20 1 1 1 1 2 48 16 98 80 80 -5272.00000 2.57485 4.89549e-005 -376 1278 0.00 -0.00 -0.00 5.09 8.18 -17.71 3.000 0.000 0 2 0 2 2.800 2.800 1.29 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 20 1 1 1 2 2 49 16 98 80 80 -5272.00000 2.57485 4.89549e-005 85 810 0.00 -0.00 -0.00 5.09 8.18 -17.71 3.000 0.000 0 2 0 2 2.800 2.800 1.29 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 20 1 1 1 0 2 50 16 98 80 80 0.00000 1.28767 9.78947e-005 1070 1860 0.00 -0.00 -0.00 5.09 8.18 -17.71 3.000 0.000 0 2 0 2 2.800 2.800 1.29 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 20 1 1 1 3 2 51 16 98 80 80 -3142.00000 1.53455 6.51740e+002 0 6284 0.00 -0.00 -0.00 5.09 8.18 -17.71 3.000 0.000 0 2 0 2 2.800 2.800 1.29 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 20 2 1 1 1 2 52 16 98 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+ 14 3 1 1 1 2 344 16 98 80 80 -5272.00000 2.57485 4.89549e-005 -412 2149 0.00 -0.00 -0.00 5.09 8.18 0.29 3.000 0.000 0 2 0 2 2.800 2.800 5.27 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 14 3 1 1 2 2 345 16 98 80 80 -5272.00000 2.57485 4.89549e-005 195 2602 0.00 -0.00 -0.00 5.09 8.18 0.29 3.000 0.000 0 2 0 2 2.800 2.800 5.27 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 14 3 1 1 0 2 346 16 98 80 80 0.00000 1.28767 9.78947e-005 1070 1860 0.00 -0.00 -0.00 5.09 8.18 0.29 3.000 0.000 0 2 0 2 2.800 2.800 5.27 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 14 3 1 1 3 2 347 16 98 80 80 -3142.00000 1.53455 6.51740e+002 0 6284 0.00 -0.00 -0.00 5.09 8.18 0.29 3.000 0.000 0 2 0 2 2.800 2.800 5.27 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 15 1 1 1 1 2 348 16 98 80 80 -5272.00000 2.57485 4.89549e-005 -874 2258 0.00 -0.00 -0.00 5.09 8.18 -2.71 3.000 0.000 0 2 0 2 2.800 2.800 1.29 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 15 1 1 1 2 2 349 16 98 80 80 -5272.00000 2.57485 4.89549e-005 -44 1176 0.00 -0.00 -0.00 5.09 8.18 -2.71 3.000 0.000 0 2 0 2 2.800 2.800 1.29 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 15 1 1 1 0 2 350 16 98 80 80 0.00000 1.28767 9.78947e-005 1070 1860 0.00 -0.00 -0.00 5.09 8.18 -2.71 3.000 0.000 0 2 0 2 2.800 2.800 1.29 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 15 1 1 1 3 2 351 16 98 80 80 -3142.00000 1.53455 6.51740e+002 0 6284 0.00 -0.00 -0.00 5.09 8.18 -2.71 3.000 0.000 0 2 0 2 2.800 2.800 1.29 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 15 2 1 1 1 2 352 16 98 80 80 -5272.00000 2.57485 4.89549e-005 -695 2019 0.00 -0.00 -0.00 5.09 8.18 -2.71 3.000 0.000 0 2 0 2 2.800 2.800 3.28 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 15 2 1 1 2 2 353 16 98 80 80 -5272.00000 2.57485 4.89549e-005 321 1543 0.00 -0.00 -0.00 5.09 8.18 -2.71 3.000 0.000 0 2 0 2 2.800 2.800 3.28 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 15 2 1 1 0 2 354 16 98 80 80 0.00000 1.28767 9.78947e-005 1070 1860 0.00 -0.00 -0.00 5.09 8.18 -2.71 3.000 0.000 0 2 0 2 2.800 2.800 3.28 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 15 2 1 1 3 2 355 16 98 80 80 -3142.00000 1.53455 6.51740e+002 0 6284 0.00 -0.00 -0.00 5.09 8.18 -2.71 3.000 0.000 0 2 0 2 2.800 2.800 3.28 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 15 3 1 1 1 2 356 16 98 80 80 -5272.00000 2.57485 4.89549e-005 -375 2168 0.00 -0.00 -0.00 5.09 8.18 -2.71 3.000 0.000 0 2 0 2 2.800 2.800 5.27 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 15 3 1 1 2 2 357 16 98 80 80 -5272.00000 2.57485 4.89549e-005 379 2546 0.00 -0.00 -0.00 5.09 8.18 -2.71 3.000 0.000 0 2 0 2 2.800 2.800 5.27 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 15 3 1 1 0 2 358 16 98 80 80 0.00000 1.28767 9.78947e-005 1070 1860 0.00 -0.00 -0.00 5.09 8.18 -2.71 3.000 0.000 0 2 0 2 2.800 2.800 5.27 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + 15 3 1 1 3 2 359 16 98 80 80 -3142.00000 1.53455 6.51740e+002 0 6284 0.00 -0.00 -0.00 5.09 8.18 -2.71 3.000 0.000 0 2 0 2 2.800 2.800 5.27 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 7 0 0.000 0.000 0.000 1 + +# === END OF DATA DESCRIPTION FILE =============================================== diff --git a/nibabel/tests/test_parrec.py b/nibabel/tests/test_parrec.py index 456e8e2807..e81235b1de 100644 --- a/nibabel/tests/test_parrec.py +++ b/nibabel/tests/test_parrec.py @@ -278,6 +278,44 @@ def test_sorting_dual_echo_T1(): assert_equal(np.all(sorted_echos[n_half:] == 2), True) +def test_sorting_multiple_echos_and_contrasts(): + # This .PAR file has 3 echos and 4 image types (real, imaginary, magnitude, + # phase). + # After sorting should be: + # Type 0, Echo 1, Slices 1-30 + # Type 0, Echo 2, Slices 1-30 + # Type 0, Echo 3, Slices 1-30 + # Type 1, Echo 1, Slices 1-30 + # ... + # Type 3, Echo 3, Slices 1-30 + dti_par = pjoin(DATA_PATH, 'T1_3echo_mag_real_imag_phase.PAR') + with open(dti_par, 'rt') as fobj: + dti_hdr = PARRECHeader.from_fileobj(fobj, strict_sort=True) + sorted_indices = dti_hdr.get_sorted_slice_indices() + sorted_slices = dti_hdr.image_defs['slice number'][sorted_indices] + sorted_echos = dti_hdr.image_defs['echo number'][sorted_indices] + sorted_types = dti_hdr.image_defs['image_type_mr'][sorted_indices] + + ntotal = len(dti_hdr.image_defs) + nslices = sorted_slices.max() + nechos = sorted_echos.max() + for slice_offset in range(ntotal//nslices): + istart = slice_offset*nslices + iend = (slice_offset+1)*nslices + # innermost sort index is slices + assert_array_equal(sorted_slices[istart:iend], + np.arange(1, nslices+1)) + current_echo = slice_offset % nechos + 1 + # same echo for each slice in the group + assert_equal(np.all(sorted_echos[istart:iend] == current_echo), + True) + # outermost sort index is image_type_mr + assert_equal(np.all(sorted_types[:ntotal//4] == 0), True) + assert_equal(np.all(sorted_types[ntotal//4:ntotal//2] == 1), True) + assert_equal(np.all(sorted_types[ntotal//2:3*ntotal//4] == 2), True) + assert_equal(np.all(sorted_types[3*ntotal//4:ntotal] == 3), True) + + def test_vol_number(): # Test algorithm for calculating volume number assert_array_equal(vol_numbers([1, 3, 0]), [0, 0, 0]) From f44bca2e4baddd654cbb76453b2706b4fa0b60e0 Mon Sep 17 00:00:00 2001 From: "Gregory R. Lee" Date: Tue, 16 Feb 2016 02:15:36 -0500 Subject: [PATCH 09/14] FIX: no underscore in 'label type' key --- nibabel/parrec.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nibabel/parrec.py b/nibabel/parrec.py index 1f51410809..5523a83ff3 100644 --- a/nibabel/parrec.py +++ b/nibabel/parrec.py @@ -1039,7 +1039,7 @@ def _strict_sort_keys(self): # try adding keys only present in a subset of .PAR files idefs = self.image_defs - asl_keys = (idefs['label_type'], ) if 'label_type' in \ + asl_keys = (idefs['label type'], ) if 'label type' in \ idefs.dtype.names else () if not self.general_info['diffusion'] == 0: From bbc136ed594936cabdebfec268c1b956b4927500 Mon Sep 17 00:00:00 2001 From: "Gregory R. Lee" Date: Tue, 16 Feb 2016 02:42:22 -0500 Subject: [PATCH 10/14] TST: add an additional ASL-based test case for strict_sort --- nibabel/tests/data/ASL_3D_Multiecho.PAR | 198 ++++++++++++++++++++++++ nibabel/tests/test_parrec.py | 36 +++++ 2 files changed, 234 insertions(+) create mode 100644 nibabel/tests/data/ASL_3D_Multiecho.PAR diff --git a/nibabel/tests/data/ASL_3D_Multiecho.PAR b/nibabel/tests/data/ASL_3D_Multiecho.PAR new file mode 100644 index 0000000000..74575fbf58 --- /dev/null +++ b/nibabel/tests/data/ASL_3D_Multiecho.PAR @@ -0,0 +1,198 @@ +# === DATA DESCRIPTION FILE ====================================================== +# +# CAUTION - Investigational device. +# Limited by Federal Law to investigational use. +# +# Dataset name: E:\\Export\\ASL_3D_Multiecho +# +# CLINICAL TRYOUT Research image export tool V4.2 +# +# === GENERAL INFORMATION ======================================================== +# +. Patient name : anon +. Examination name : anon +. Protocol name : anon +. Examination date/time : anon +. Series Type : Image MRSERIES +. Acquisition nr : 5 +. Reconstruction nr : 3 +. Scan Duration [sec] : 143 +. Max. number of cardiac phases : 1 +. Max. number of echoes : 3 +. Max. number of slices/locations : 8 +. Max. number of dynamics : 2 +. Max. number of mixes : 1 +. Patient position : Head First Supine +. Preparation direction : Anterior-Posterior +. Technique : T1TFE +. Scan resolution (x, y) : 76 120 +. Scan mode : 3D +. Repetition time [ms] : 7.093 +. FOV (ap,fh,rl) [mm] : 224.000 24.000 224.000 +. Water Fat shift [pixels] : 0.701 +. Angulation midslice(ap,fh,rl)[degr]: 5.000 15.000 30.000 +. Off Centre midslice(ap,fh,rl) [mm] : -4.810 3.500 -3.607 +. Flow compensation <0=no 1=yes> ? : 0 +. Presaturation <0=no 1=yes> ? : 0 +. Phase encoding velocity [cm/sec] : 0.000000 0.000000 0.000000 +. MTC <0=no 1=yes> ? : 0 +. SPIR <0=no 1=yes> ? : 0 +. EPI factor <0,1=no EPI> : 1 +. Dynamic scan <0=no 1=yes> ? : 1 +. Diffusion <0=no 1=yes> ? : 0 +. Diffusion echo time [ms] : 0.0000 +. Max. number of diffusion values : 1 +. Max. number of gradient orients : 1 +. Number of label types <0=no ASL> : 2 +# +# === PIXEL VALUES ============================================================= +# PV = pixel value in REC file, FP = floating point value, DV = displayed value on console +# RS = rescale slope, RI = rescale intercept, SS = scale slope +# DV = PV * RS + RI FP = DV / (RS * SS) +# +# === IMAGE INFORMATION DEFINITION ============================================= +# The rest of this file contains ONE line per image, this line contains the following information: +# +# slice number (integer) +# echo number (integer) +# dynamic scan number (integer) +# cardiac phase number (integer) +# image_type_mr (integer) +# scanning sequence (integer) +# index in REC file (in images) (integer) +# image pixel size (in bits) (integer) +# scan percentage (integer) +# recon resolution (x y) (2*integer) +# rescale intercept (float) +# rescale slope (float) +# scale slope (float) +# window center (integer) +# window width (integer) +# image angulation (ap,fh,rl in degrees ) (3*float) +# image offcentre (ap,fh,rl in mm ) (3*float) +# slice thickness (in mm ) (float) +# slice gap (in mm ) (float) +# image_display_orientation (integer) +# slice orientation ( TRA/SAG/COR ) (integer) +# fmri_status_indication (integer) +# image_type_ed_es (end diast/end syst) (integer) +# pixel spacing (x,y) (in mm) (2*float) +# echo_time (float) +# dyn_scan_begin_time (float) +# trigger_time (float) +# diffusion_b_factor (float) +# number of averages (integer) +# image_flip_angle (in degrees) (float) +# cardiac frequency (bpm) (integer) +# minimum RR-interval (in ms) (integer) +# maximum RR-interval (in ms) (integer) +# TURBO factor <0=no turbo> (integer) +# Inversion delay (in ms) (float) +# diffusion b value number (imagekey!) (integer) +# gradient orientation number (imagekey!) (integer) +# contrast type (string) +# diffusion anisotropy type (string) +# diffusion (ap, fh, rl) (3*float) +# label type (ASL) (imagekey!) (integer) +# +# === IMAGE INFORMATION ========================================================== +# sl ec dyn ph ty idx pix scan% rec size (re)scale window angulation offcentre thick gap info spacing echo dtime ttime diff avg flip freq RR-int turbo delay b grad cont anis diffusion L.ty + + 1 1 1 1 0 2 90 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 16.86 -34.03 -7.40 3.000 0.000 0 1 0 2 2.800 2.800 1.42 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 1 2 1 1 0 2 91 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 16.86 -34.03 -7.40 3.000 0.000 0 1 0 2 2.800 2.800 3.45 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 1 3 1 1 0 2 92 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 16.86 -34.03 -7.40 3.000 0.000 0 1 0 2 2.800 2.800 5.49 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 1 1 1 1 0 2 93 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 16.86 -34.03 -7.40 3.000 0.000 0 1 0 2 2.800 2.800 1.42 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 1 2 1 1 0 2 94 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 16.86 -34.03 -7.40 3.000 0.000 0 1 0 2 2.800 2.800 3.45 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 1 3 1 1 0 2 95 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 16.86 -34.03 -7.40 3.000 0.000 0 1 0 2 2.800 2.800 5.49 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 2 1 1 1 0 2 96 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 15.36 -31.44 -7.14 3.000 0.000 0 1 0 2 2.800 2.800 1.42 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 2 2 1 1 0 2 97 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 15.36 -31.44 -7.14 3.000 0.000 0 1 0 2 2.800 2.800 3.45 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 2 3 1 1 0 2 98 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 15.36 -31.44 -7.14 3.000 0.000 0 1 0 2 2.800 2.800 5.49 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 2 1 1 1 0 2 99 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 15.36 -31.44 -7.14 3.000 0.000 0 1 0 2 2.800 2.800 1.42 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 2 2 1 1 0 2 100 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 15.36 -31.44 -7.14 3.000 0.000 0 1 0 2 2.800 2.800 3.45 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 2 3 1 1 0 2 101 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 15.36 -31.44 -7.14 3.000 0.000 0 1 0 2 2.800 2.800 5.49 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 3 1 1 1 0 2 102 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 13.87 -28.85 -6.88 3.000 0.000 0 1 0 2 2.800 2.800 1.42 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 3 2 1 1 0 2 103 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 13.87 -28.85 -6.88 3.000 0.000 0 1 0 2 2.800 2.800 3.45 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 3 3 1 1 0 2 104 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 13.87 -28.85 -6.88 3.000 0.000 0 1 0 2 2.800 2.800 5.49 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 3 1 1 1 0 2 105 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 13.87 -28.85 -6.88 3.000 0.000 0 1 0 2 2.800 2.800 1.42 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 3 2 1 1 0 2 106 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 13.87 -28.85 -6.88 3.000 0.000 0 1 0 2 2.800 2.800 3.45 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 3 3 1 1 0 2 107 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 13.87 -28.85 -6.88 3.000 0.000 0 1 0 2 2.800 2.800 5.49 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 4 1 1 1 0 2 108 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 12.37 -26.26 -6.61 3.000 0.000 0 1 0 2 2.800 2.800 1.42 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 4 2 1 1 0 2 109 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 12.37 -26.26 -6.61 3.000 0.000 0 1 0 2 2.800 2.800 3.45 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 4 3 1 1 0 2 110 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 12.37 -26.26 -6.61 3.000 0.000 0 1 0 2 2.800 2.800 5.49 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 4 1 1 1 0 2 111 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 12.37 -26.26 -6.61 3.000 0.000 0 1 0 2 2.800 2.800 1.42 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 4 2 1 1 0 2 112 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 12.37 -26.26 -6.61 3.000 0.000 0 1 0 2 2.800 2.800 3.45 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 4 3 1 1 0 2 113 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 12.37 -26.26 -6.61 3.000 0.000 0 1 0 2 2.800 2.800 5.49 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 5 1 1 1 0 2 114 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 10.88 -23.68 -6.35 3.000 0.000 0 1 0 2 2.800 2.800 1.42 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 5 2 1 1 0 2 115 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 10.88 -23.68 -6.35 3.000 0.000 0 1 0 2 2.800 2.800 3.45 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 5 3 1 1 0 2 116 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 10.88 -23.68 -6.35 3.000 0.000 0 1 0 2 2.800 2.800 5.49 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 5 1 1 1 0 2 117 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 10.88 -23.68 -6.35 3.000 0.000 0 1 0 2 2.800 2.800 1.42 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 5 2 1 1 0 2 118 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 10.88 -23.68 -6.35 3.000 0.000 0 1 0 2 2.800 2.800 3.45 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 5 3 1 1 0 2 119 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 10.88 -23.68 -6.35 3.000 0.000 0 1 0 2 2.800 2.800 5.49 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 6 1 1 1 0 2 120 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 9.39 -21.09 -6.09 3.000 0.000 0 1 0 2 2.800 2.800 1.42 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 6 2 1 1 0 2 121 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 9.39 -21.09 -6.09 3.000 0.000 0 1 0 2 2.800 2.800 3.45 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 6 3 1 1 0 2 122 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 9.39 -21.09 -6.09 3.000 0.000 0 1 0 2 2.800 2.800 5.49 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 6 1 1 1 0 2 123 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 9.39 -21.09 -6.09 3.000 0.000 0 1 0 2 2.800 2.800 1.42 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 6 2 1 1 0 2 124 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 9.39 -21.09 -6.09 3.000 0.000 0 1 0 2 2.800 2.800 3.45 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 6 3 1 1 0 2 125 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 9.39 -21.09 -6.09 3.000 0.000 0 1 0 2 2.800 2.800 5.49 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 7 1 1 1 0 2 126 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 7.89 -18.50 -5.83 3.000 0.000 0 1 0 2 2.800 2.800 1.42 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 7 2 1 1 0 2 127 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 7.89 -18.50 -5.83 3.000 0.000 0 1 0 2 2.800 2.800 3.45 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 7 3 1 1 0 2 128 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 7.89 -18.50 -5.83 3.000 0.000 0 1 0 2 2.800 2.800 5.49 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 7 1 1 1 0 2 129 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 7.89 -18.50 -5.83 3.000 0.000 0 1 0 2 2.800 2.800 1.42 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 7 2 1 1 0 2 130 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 7.89 -18.50 -5.83 3.000 0.000 0 1 0 2 2.800 2.800 3.45 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 7 3 1 1 0 2 131 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 7.89 -18.50 -5.83 3.000 0.000 0 1 0 2 2.800 2.800 5.49 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 8 1 1 1 0 2 132 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 6.40 -15.91 -5.57 3.000 0.000 0 1 0 2 2.800 2.800 1.42 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 8 2 1 1 0 2 133 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 6.40 -15.91 -5.57 3.000 0.000 0 1 0 2 2.800 2.800 3.45 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 8 3 1 1 0 2 134 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 6.40 -15.91 -5.57 3.000 0.000 0 1 0 2 2.800 2.800 5.49 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 8 1 1 1 0 2 135 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 6.40 -15.91 -5.57 3.000 0.000 0 1 0 2 2.800 2.800 1.42 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 8 2 1 1 0 2 136 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 6.40 -15.91 -5.57 3.000 0.000 0 1 0 2 2.800 2.800 3.45 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 8 3 1 1 0 2 137 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 6.40 -15.91 -5.57 3.000 0.000 0 1 0 2 2.800 2.800 5.49 0.00 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 1 1 2 1 0 2 270 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 16.86 -34.03 -7.40 3.000 0.000 0 1 0 2 2.800 2.800 1.42 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 1 2 2 1 0 2 271 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 16.86 -34.03 -7.40 3.000 0.000 0 1 0 2 2.800 2.800 3.45 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 1 3 2 1 0 2 272 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 16.86 -34.03 -7.40 3.000 0.000 0 1 0 2 2.800 2.800 5.49 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 1 1 2 1 0 2 273 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 16.86 -34.03 -7.40 3.000 0.000 0 1 0 2 2.800 2.800 1.42 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 1 2 2 1 0 2 274 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 16.86 -34.03 -7.40 3.000 0.000 0 1 0 2 2.800 2.800 3.45 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 1 3 2 1 0 2 275 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 16.86 -34.03 -7.40 3.000 0.000 0 1 0 2 2.800 2.800 5.49 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 2 1 2 1 0 2 276 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 15.36 -31.44 -7.14 3.000 0.000 0 1 0 2 2.800 2.800 1.42 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 2 2 2 1 0 2 277 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 15.36 -31.44 -7.14 3.000 0.000 0 1 0 2 2.800 2.800 3.45 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 2 3 2 1 0 2 278 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 15.36 -31.44 -7.14 3.000 0.000 0 1 0 2 2.800 2.800 5.49 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 2 1 2 1 0 2 279 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 15.36 -31.44 -7.14 3.000 0.000 0 1 0 2 2.800 2.800 1.42 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 2 2 2 1 0 2 280 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 15.36 -31.44 -7.14 3.000 0.000 0 1 0 2 2.800 2.800 3.45 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 2 3 2 1 0 2 281 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 15.36 -31.44 -7.14 3.000 0.000 0 1 0 2 2.800 2.800 5.49 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 3 1 2 1 0 2 282 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 13.87 -28.85 -6.88 3.000 0.000 0 1 0 2 2.800 2.800 1.42 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 3 2 2 1 0 2 283 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 13.87 -28.85 -6.88 3.000 0.000 0 1 0 2 2.800 2.800 3.45 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 3 3 2 1 0 2 284 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 13.87 -28.85 -6.88 3.000 0.000 0 1 0 2 2.800 2.800 5.49 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 3 1 2 1 0 2 285 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 13.87 -28.85 -6.88 3.000 0.000 0 1 0 2 2.800 2.800 1.42 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 3 2 2 1 0 2 286 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 13.87 -28.85 -6.88 3.000 0.000 0 1 0 2 2.800 2.800 3.45 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 3 3 2 1 0 2 287 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 13.87 -28.85 -6.88 3.000 0.000 0 1 0 2 2.800 2.800 5.49 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 4 1 2 1 0 2 288 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 12.37 -26.26 -6.61 3.000 0.000 0 1 0 2 2.800 2.800 1.42 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 4 2 2 1 0 2 289 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 12.37 -26.26 -6.61 3.000 0.000 0 1 0 2 2.800 2.800 3.45 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 4 3 2 1 0 2 290 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 12.37 -26.26 -6.61 3.000 0.000 0 1 0 2 2.800 2.800 5.49 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 4 1 2 1 0 2 291 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 12.37 -26.26 -6.61 3.000 0.000 0 1 0 2 2.800 2.800 1.42 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 4 2 2 1 0 2 292 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 12.37 -26.26 -6.61 3.000 0.000 0 1 0 2 2.800 2.800 3.45 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 4 3 2 1 0 2 293 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 12.37 -26.26 -6.61 3.000 0.000 0 1 0 2 2.800 2.800 5.49 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 5 1 2 1 0 2 294 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 10.88 -23.68 -6.35 3.000 0.000 0 1 0 2 2.800 2.800 1.42 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 5 2 2 1 0 2 295 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 10.88 -23.68 -6.35 3.000 0.000 0 1 0 2 2.800 2.800 3.45 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 5 3 2 1 0 2 296 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 10.88 -23.68 -6.35 3.000 0.000 0 1 0 2 2.800 2.800 5.49 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 5 1 2 1 0 2 297 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 10.88 -23.68 -6.35 3.000 0.000 0 1 0 2 2.800 2.800 1.42 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 5 2 2 1 0 2 298 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 10.88 -23.68 -6.35 3.000 0.000 0 1 0 2 2.800 2.800 3.45 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 5 3 2 1 0 2 299 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 10.88 -23.68 -6.35 3.000 0.000 0 1 0 2 2.800 2.800 5.49 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 6 1 2 1 0 2 300 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 9.39 -21.09 -6.09 3.000 0.000 0 1 0 2 2.800 2.800 1.42 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 6 2 2 1 0 2 301 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 9.39 -21.09 -6.09 3.000 0.000 0 1 0 2 2.800 2.800 3.45 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 6 3 2 1 0 2 302 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 9.39 -21.09 -6.09 3.000 0.000 0 1 0 2 2.800 2.800 5.49 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 6 1 2 1 0 2 303 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 9.39 -21.09 -6.09 3.000 0.000 0 1 0 2 2.800 2.800 1.42 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 6 2 2 1 0 2 304 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 9.39 -21.09 -6.09 3.000 0.000 0 1 0 2 2.800 2.800 3.45 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 6 3 2 1 0 2 305 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 9.39 -21.09 -6.09 3.000 0.000 0 1 0 2 2.800 2.800 5.49 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 7 1 2 1 0 2 306 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 7.89 -18.50 -5.83 3.000 0.000 0 1 0 2 2.800 2.800 1.42 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 7 2 2 1 0 2 307 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 7.89 -18.50 -5.83 3.000 0.000 0 1 0 2 2.800 2.800 3.45 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 7 3 2 1 0 2 308 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 7.89 -18.50 -5.83 3.000 0.000 0 1 0 2 2.800 2.800 5.49 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 7 1 2 1 0 2 309 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 7.89 -18.50 -5.83 3.000 0.000 0 1 0 2 2.800 2.800 1.42 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 7 2 2 1 0 2 310 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 7.89 -18.50 -5.83 3.000 0.000 0 1 0 2 2.800 2.800 3.45 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 7 3 2 1 0 2 311 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 7.89 -18.50 -5.83 3.000 0.000 0 1 0 2 2.800 2.800 5.49 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 8 1 2 1 0 2 312 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 6.40 -15.91 -5.57 3.000 0.000 0 1 0 2 2.800 2.800 1.42 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 8 2 2 1 0 2 313 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 6.40 -15.91 -5.57 3.000 0.000 0 1 0 2 2.800 2.800 3.45 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 8 3 2 1 0 2 314 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 6.40 -15.91 -5.57 3.000 0.000 0 1 0 2 2.800 2.800 5.49 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 1 + 8 1 2 1 0 2 315 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 6.40 -15.91 -5.57 3.000 0.000 0 1 0 2 2.800 2.800 1.42 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 8 2 2 1 0 2 316 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 6.40 -15.91 -5.57 3.000 0.000 0 1 0 2 2.800 2.800 3.45 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + 8 3 2 1 0 2 317 16 98 80 80 0.00000 1.50110 8.85639e-004 1070 1860 5.00 15.00 30.00 6.40 -15.91 -5.57 3.000 0.000 0 1 0 2 2.800 2.800 5.49 71.29 0.00 0.00 1 8.00 0 0 0 225 0.0 1 1 3 0 0.000 0.000 0.000 2 + +# === END OF DATA DESCRIPTION FILE =============================================== diff --git a/nibabel/tests/test_parrec.py b/nibabel/tests/test_parrec.py index e81235b1de..25a2cee8cb 100644 --- a/nibabel/tests/test_parrec.py +++ b/nibabel/tests/test_parrec.py @@ -316,6 +316,42 @@ def test_sorting_multiple_echos_and_contrasts(): assert_equal(np.all(sorted_types[3*ntotal//4:ntotal] == 3), True) +def test_sorting_multiecho_ASL(): + # For this .PAR file has 3 keys corresponding to volumes: + # 'echo number', 'label type', 'dynamic scan number' + dti_par = pjoin(DATA_PATH, 'ASL_3D_Multiecho.PAR') + with open(dti_par, 'rt') as fobj: + dti_hdr = PARRECHeader.from_fileobj(fobj, strict_sort=True) + sorted_indices = dti_hdr.get_sorted_slice_indices() + sorted_slices = dti_hdr.image_defs['slice number'][sorted_indices] + sorted_echos = dti_hdr.image_defs['echo number'][sorted_indices] + sorted_dynamics = dti_hdr.image_defs['dynamic scan number'][sorted_indices] + sorted_labels = dti_hdr.image_defs['label type'][sorted_indices] + ntotal = len(dti_hdr.image_defs) + nslices = sorted_slices.max() + nechos = sorted_echos.max() + nlabels = sorted_labels.max() + ndynamics = sorted_dynamics.max() + assert_equal(nslices, 8) + assert_equal(nechos, 3) + assert_equal(nlabels, 2) + assert_equal(ndynamics, 2) + # check that dynamics vary slowest + assert_array_equal( + np.all(sorted_dynamics[:ntotal//ndynamics] == 1), True) + assert_array_equal( + np.all(sorted_dynamics[ntotal//ndynamics:ntotal] == 2), True) + # check that labels vary 2nd slowest + assert_array_equal(np.all(sorted_labels[:nslices*nechos] == 1), True) + assert_array_equal( + np.all(sorted_labels[nslices*nechos:2*nslices*nechos] == 2), True) + # check that echos vary 2nd fastest + assert_array_equal(np.all(sorted_echos[:nslices] == 1), True) + assert_array_equal(np.all(sorted_echos[nslices:2*nslices] == 2), True) + assert_array_equal(np.all(sorted_echos[2*nslices:3*nslices] == 3), True) + # check that slices vary fastest + assert_array_equal(sorted_slices[:nslices], np.arange(1, nslices+1)) + def test_vol_number(): # Test algorithm for calculating volume number assert_array_equal(vol_numbers([1, 3, 0]), [0, 0, 0]) From bca0fcc1b043a538591de3adaeb9ca1ce4cf4793 Mon Sep 17 00:00:00 2001 From: "Gregory R. Lee" Date: Tue, 16 Feb 2016 02:49:39 -0500 Subject: [PATCH 11/14] TST: test header read on V4 .PAR file for strict_sort=True too --- nibabel/tests/test_parrec.py | 30 ++++++++++++++++-------------- 1 file changed, 16 insertions(+), 14 deletions(-) diff --git a/nibabel/tests/test_parrec.py b/nibabel/tests/test_parrec.py index 25a2cee8cb..5766cf5cc0 100644 --- a/nibabel/tests/test_parrec.py +++ b/nibabel/tests/test_parrec.py @@ -154,20 +154,22 @@ def test_top_level_load(): def test_header(): v42_hdr = PARRECHeader(HDR_INFO, HDR_DEFS) - with open(V4_PAR, 'rt') as fobj: - v4_hdr = PARRECHeader.from_fileobj(fobj) - with open(V41_PAR, 'rt') as fobj: - v41_hdr = PARRECHeader.from_fileobj(fobj) - for hdr in (v42_hdr, v41_hdr, v4_hdr): - hdr = PARRECHeader(HDR_INFO, HDR_DEFS) - assert_equal(hdr.get_data_shape(), (64, 64, 9, 3)) - assert_equal(hdr.get_data_dtype(), np.dtype(' Date: Mon, 14 Mar 2016 19:26:21 -0400 Subject: [PATCH 12/14] MAINT: remove _direction_numbers as it will never be used. vol_numbers was added to the set of strict_sort keys to handle .PAR files without diffusion direction information. --- nibabel/parrec.py | 31 +++++++++++-------------------- 1 file changed, 11 insertions(+), 20 deletions(-) diff --git a/nibabel/parrec.py b/nibabel/parrec.py index 5523a83ff3..9710ca7904 100644 --- a/nibabel/parrec.py +++ b/nibabel/parrec.py @@ -329,21 +329,6 @@ def _process_image_lines(image_lines, version): return image_defs -def _direction_numbers(bvecs): - """ Enumerate directions from an (N, 3) array of direction vectors. - """ - cnt = 0 - bvec_dict = {} - bvec_nos = np.zeros(len(bvecs)) - for i, bvec in enumerate(bvecs): - bv = tuple(bvec) - if bv not in bvec_dict: - bvec_dict[bv] = cnt - cnt += 1 - bvec_nos[i] = bvec_dict.get(bv) - return bvec_nos - - def vol_numbers(slice_nos): """ Calculate volume numbers inferred from slice numbers `slice_nos` @@ -1024,6 +1009,11 @@ def get_rec_shape(self): def _strict_sort_keys(self): """ Determine the sort order based on several image definition fields. + If the sort keys are not unique for each volume, we calculate a volume + number by looking for repeating slice numbers + (see :func:`vol_numbers`). This may occur for diffusion scans from + older V4 .PAR format, where diffusion direction info is not stored. + Data sorting is done in two stages: - run an initial sort using several keys of interest - call `vol_is_full` to identify potentially missing volumes @@ -1048,21 +1038,22 @@ def _strict_sort_keys(self): bvals = self.get_def('diffusion_b_factor') bvecs = self.get_def('gradient orientation number') if bvecs is None: - # manually enumerate the different directions - bvecs = _direction_numbers(self.get_def('diffusion')) - diffusion_keys = (bvecs, bvals) + # no b-vectors available + diffusion_keys = (bvals, ) + else: + diffusion_keys = (bvecs, bvals) else: diffusion_keys = () # Define the desired sort order (last key is highest precedence) - keys = (slice_nos, echos, phases) + \ + keys = (slice_nos, vol_numbers(slice_nos), echos, phases) + \ diffusion_keys + asl_keys + (dynamics, image_type) initial_sort_order = np.lexsort(keys) is_full = vol_is_full(slice_nos[initial_sort_order], self.general_info['max_slices']) - # have to "unsort" is_full to match the other sort keys + # have to "unsort" is_full and volumes to match the other sort keys unsort_indices = np.argsort(initial_sort_order) is_full = is_full[unsort_indices] From 9e98d6eba04362389683c2c9afb09268dcc3bce3 Mon Sep 17 00:00:00 2001 From: "Gregory R. Lee" Date: Mon, 14 Mar 2016 20:07:22 -0400 Subject: [PATCH 13/14] make fixes necessary for strict-sort tests to pass even if image_defs are randomly sorted --- nibabel/parrec.py | 16 ++++++---- nibabel/tests/test_parrec.py | 62 +++++++++++++++++++++++------------- 2 files changed, 49 insertions(+), 29 deletions(-) diff --git a/nibabel/parrec.py b/nibabel/parrec.py index 9710ca7904..3bc67393b6 100644 --- a/nibabel/parrec.py +++ b/nibabel/parrec.py @@ -734,15 +734,17 @@ def get_bvals_bvecs(self): n_slices, n_vols = self.get_data_shape()[-2:] bvals = self.image_defs['diffusion_b_factor'][reorder].reshape( (n_slices, n_vols), order='F') - # All bvals within volume should be the same - assert not np.any(np.diff(bvals, axis=0)) + if not self.strict_sort: + # All bvals within volume should be the same + assert not np.any(np.diff(bvals, axis=0)) bvals = bvals[0] if 'diffusion' not in self.image_defs.dtype.names: return bvals, None bvecs = self.image_defs['diffusion'][reorder].reshape( (n_slices, n_vols, 3), order='F') - # All 3 values of bvecs should be same within volume - assert not np.any(np.diff(bvecs, axis=0)) + if not self.strict_sort: + # All 3 values of bvecs should be same within volume + assert not np.any(np.diff(bvecs, axis=0)) bvecs = bvecs[0] # rotate bvecs to match stored image orientation permute_to_psl = ACQ_TO_PSL[self.get_slice_orientation()] @@ -1046,19 +1048,21 @@ def _strict_sort_keys(self): diffusion_keys = () # Define the desired sort order (last key is highest precedence) - keys = (slice_nos, vol_numbers(slice_nos), echos, phases) + \ + keys = (slice_nos, echos, phases) + \ diffusion_keys + asl_keys + (dynamics, image_type) initial_sort_order = np.lexsort(keys) + vol_nos = vol_numbers(slice_nos[initial_sort_order]) is_full = vol_is_full(slice_nos[initial_sort_order], self.general_info['max_slices']) # have to "unsort" is_full and volumes to match the other sort keys unsort_indices = np.argsort(initial_sort_order) is_full = is_full[unsort_indices] + vol_nos = np.asarray(vol_nos)[unsort_indices] # final set of sort keys - return keys + (np.logical_not(is_full), ) + return (keys[0], vol_nos) + keys[1:] + (np.logical_not(is_full), ) def get_sorted_slice_indices(self): """Return indices to sort (and maybe discard) slices in REC file. diff --git a/nibabel/tests/test_parrec.py b/nibabel/tests/test_parrec.py index 5766cf5cc0..0dd24b8ced 100644 --- a/nibabel/tests/test_parrec.py +++ b/nibabel/tests/test_parrec.py @@ -268,12 +268,16 @@ def test_get_sorted_slice_indices(): def test_sorting_dual_echo_T1(): # For this .PAR file, instead of getting 1 echo per volume, they get # mixed up unless strict_sort=True - dti_par = pjoin(DATA_PATH, 'T1_dual_echo.PAR') - with open(dti_par, 'rt') as fobj: - dti_hdr = PARRECHeader.from_fileobj(fobj, strict_sort=True) - sorted_indices = dti_hdr.get_sorted_slice_indices() - sorted_echos = dti_hdr.image_defs['echo number'][sorted_indices] - n_half = len(dti_hdr.image_defs) // 2 + t1_par = pjoin(DATA_PATH, 'T1_dual_echo.PAR') + with open(t1_par, 'rt') as fobj: + t1_hdr = PARRECHeader.from_fileobj(fobj, strict_sort=True) + + # should get the correct order even if we randomly shuffle the order + np.random.shuffle(t1_hdr.image_defs) + + sorted_indices = t1_hdr.get_sorted_slice_indices() + sorted_echos = t1_hdr.image_defs['echo number'][sorted_indices] + n_half = len(t1_hdr.image_defs) // 2 # first half (volume 1) should all correspond to echo 1 assert_equal(np.all(sorted_echos[:n_half] == 1), True) # second half (volume 2) should all correspond to echo 2 @@ -290,15 +294,19 @@ def test_sorting_multiple_echos_and_contrasts(): # Type 1, Echo 1, Slices 1-30 # ... # Type 3, Echo 3, Slices 1-30 - dti_par = pjoin(DATA_PATH, 'T1_3echo_mag_real_imag_phase.PAR') - with open(dti_par, 'rt') as fobj: - dti_hdr = PARRECHeader.from_fileobj(fobj, strict_sort=True) - sorted_indices = dti_hdr.get_sorted_slice_indices() - sorted_slices = dti_hdr.image_defs['slice number'][sorted_indices] - sorted_echos = dti_hdr.image_defs['echo number'][sorted_indices] - sorted_types = dti_hdr.image_defs['image_type_mr'][sorted_indices] + t1_par = pjoin(DATA_PATH, 'T1_3echo_mag_real_imag_phase.PAR') + with open(t1_par, 'rt') as fobj: + t1_hdr = PARRECHeader.from_fileobj(fobj, strict_sort=True) - ntotal = len(dti_hdr.image_defs) + # should get the correct order even if we randomly shuffle the order + np.random.shuffle(t1_hdr.image_defs) + + sorted_indices = t1_hdr.get_sorted_slice_indices() + sorted_slices = t1_hdr.image_defs['slice number'][sorted_indices] + sorted_echos = t1_hdr.image_defs['echo number'][sorted_indices] + sorted_types = t1_hdr.image_defs['image_type_mr'][sorted_indices] + + ntotal = len(t1_hdr.image_defs) nslices = sorted_slices.max() nechos = sorted_echos.max() for slice_offset in range(ntotal//nslices): @@ -321,15 +329,19 @@ def test_sorting_multiple_echos_and_contrasts(): def test_sorting_multiecho_ASL(): # For this .PAR file has 3 keys corresponding to volumes: # 'echo number', 'label type', 'dynamic scan number' - dti_par = pjoin(DATA_PATH, 'ASL_3D_Multiecho.PAR') - with open(dti_par, 'rt') as fobj: - dti_hdr = PARRECHeader.from_fileobj(fobj, strict_sort=True) - sorted_indices = dti_hdr.get_sorted_slice_indices() - sorted_slices = dti_hdr.image_defs['slice number'][sorted_indices] - sorted_echos = dti_hdr.image_defs['echo number'][sorted_indices] - sorted_dynamics = dti_hdr.image_defs['dynamic scan number'][sorted_indices] - sorted_labels = dti_hdr.image_defs['label type'][sorted_indices] - ntotal = len(dti_hdr.image_defs) + asl_par = pjoin(DATA_PATH, 'ASL_3D_Multiecho.PAR') + with open(asl_par, 'rt') as fobj: + asl_hdr = PARRECHeader.from_fileobj(fobj, strict_sort=True) + + # should get the correct order even if we randomly shuffle the order + np.random.shuffle(asl_hdr.image_defs) + + sorted_indices = asl_hdr.get_sorted_slice_indices() + sorted_slices = asl_hdr.image_defs['slice number'][sorted_indices] + sorted_echos = asl_hdr.image_defs['echo number'][sorted_indices] + sorted_dynamics = asl_hdr.image_defs['dynamic scan number'][sorted_indices] + sorted_labels = asl_hdr.image_defs['label type'][sorted_indices] + ntotal = len(asl_hdr.image_defs) nslices = sorted_slices.max() nechos = sorted_echos.max() nlabels = sorted_labels.max() @@ -439,6 +451,10 @@ def test_diffusion_parameters_strict_sort(): dti_par = pjoin(DATA_PATH, 'DTI.PAR') with open(dti_par, 'rt') as fobj: dti_hdr = PARRECHeader.from_fileobj(fobj, strict_sort=True) + + # should get the correct order even if we randomly shuffle the order + np.random.shuffle(dti_hdr.image_defs) + assert_equal(dti_hdr.get_data_shape(), (80, 80, 10, 8)) assert_equal(dti_hdr.general_info['diffusion'], 1) bvals, bvecs = dti_hdr.get_bvals_bvecs() From eac41a3387ba7568a5df32fe91b2235ece8b543f Mon Sep 17 00:00:00 2001 From: "Gregory R. Lee" Date: Tue, 15 Mar 2016 16:44:57 -0400 Subject: [PATCH 14/14] MAINT: simplify logic in _strict_sort_order and improve the docstring --- nibabel/parrec.py | 104 ++++++++++++++++++++++++++-------------------- 1 file changed, 59 insertions(+), 45 deletions(-) diff --git a/nibabel/parrec.py b/nibabel/parrec.py index 3bc67393b6..4a80ad5718 100644 --- a/nibabel/parrec.py +++ b/nibabel/parrec.py @@ -734,17 +734,15 @@ def get_bvals_bvecs(self): n_slices, n_vols = self.get_data_shape()[-2:] bvals = self.image_defs['diffusion_b_factor'][reorder].reshape( (n_slices, n_vols), order='F') - if not self.strict_sort: - # All bvals within volume should be the same - assert not np.any(np.diff(bvals, axis=0)) + # All bvals within volume should be the same + assert not np.any(np.diff(bvals, axis=0)) bvals = bvals[0] if 'diffusion' not in self.image_defs.dtype.names: return bvals, None bvecs = self.image_defs['diffusion'][reorder].reshape( (n_slices, n_vols, 3), order='F') - if not self.strict_sort: - # All 3 values of bvecs should be same within volume - assert not np.any(np.diff(bvecs, axis=0)) + # All 3 values of bvecs should be same within volume + assert not np.any(np.diff(bvecs, axis=0)) bvecs = bvecs[0] # rotate bvecs to match stored image orientation permute_to_psl = ACQ_TO_PSL[self.get_slice_orientation()] @@ -752,7 +750,7 @@ def get_bvals_bvecs(self): return bvals, bvecs def get_def(self, name): - """ Return a single image definition field. """ + """Return a single image definition field (or None if missing) """ idef = self.image_defs return idef[name] if name in idef.dtype.names else None @@ -1008,33 +1006,48 @@ def get_rec_shape(self): inplane_shape = tuple(self._get_unique_image_prop('recon resolution')) return inplane_shape + (len(self.image_defs),) - def _strict_sort_keys(self): + def _strict_sort_order(self): """ Determine the sort order based on several image definition fields. - If the sort keys are not unique for each volume, we calculate a volume - number by looking for repeating slice numbers - (see :func:`vol_numbers`). This may occur for diffusion scans from - older V4 .PAR format, where diffusion direction info is not stored. + The fields taken into consideration, if present, are (in order from + slowest to fastest variation after sorting): + + - image_defs['image_type_mr'] # Re, Im, Mag, Phase + - image_defs['dynamic scan number'] # repetition + - image_defs['label type'] # ASL tag/control + - image_defs['diffusion b value number'] # diffusion b value + - image_defs['gradient orientation number'] # diffusion directoin + - image_defs['cardiac phase number'] # cardiac phase + - image_defs['echo number'] # echo + - image_defs['slice number'] # slice Data sorting is done in two stages: - - run an initial sort using several keys of interest - - call `vol_is_full` to identify potentially missing volumes - and add the result to the list of sort keys - """ - # Sort based on a larger number of keys. This is more complicated - # but works for .PAR files that get missorted by the above method - slice_nos = self.image_defs['slice number'] - dynamics = self.image_defs['dynamic scan number'] - phases = self.image_defs['cardiac phase number'] - echos = self.image_defs['echo number'] - image_type = self.image_defs['image_type_mr'] - # try adding keys only present in a subset of .PAR files - idefs = self.image_defs - asl_keys = (idefs['label type'], ) if 'label type' in \ - idefs.dtype.names else () + 1. an initial sort using the keys described above + 2. a resort after generating two additional sort keys: - if not self.general_info['diffusion'] == 0: + * a key to assign unique volume numbers to any volumes that + didn't have a unique sort based on the keys above + (see :func:`vol_numbers`). + * a sort key based on `vol_is_full` to identify truncated + volumes + + A case where the initial sort may not create a unique label for each + volume is diffusion scans acquired in the older V4 .PAR format, where + diffusion direction info is not available. + """ + # sort keys present in all supported .PAR versions + idefs = self.image_defs + slice_nos = idefs['slice number'] + dynamics = idefs['dynamic scan number'] + phases = idefs['cardiac phase number'] + echos = idefs['echo number'] + image_type = idefs['image_type_mr'] + + # sort keys only present in a subset of .PAR files + asl_keys = ((idefs['label type'], ) if 'label type' in + idefs.dtype.names else ()) + if self.general_info['diffusion'] != 0: bvals = self.get_def('diffusion b value number') if bvals is None: bvals = self.get_def('diffusion_b_factor') @@ -1047,30 +1060,34 @@ def _strict_sort_keys(self): else: diffusion_keys = () - # Define the desired sort order (last key is highest precedence) + # initial sort (last key is highest precedence) keys = (slice_nos, echos, phases) + \ diffusion_keys + asl_keys + (dynamics, image_type) - initial_sort_order = np.lexsort(keys) + + # sequentially number the volumes based on the initial sort vol_nos = vol_numbers(slice_nos[initial_sort_order]) + # identify truncated volumes is_full = vol_is_full(slice_nos[initial_sort_order], self.general_info['max_slices']) - # have to "unsort" is_full and volumes to match the other sort keys - unsort_indices = np.argsort(initial_sort_order) - is_full = is_full[unsort_indices] - vol_nos = np.asarray(vol_nos)[unsort_indices] - - # final set of sort keys - return (keys[0], vol_nos) + keys[1:] + (np.logical_not(is_full), ) - - def get_sorted_slice_indices(self): - """Return indices to sort (and maybe discard) slices in REC file. + # second stage of sorting + return initial_sort_order[np.lexsort((vol_nos, is_full))] + def _lax_sort_order(self): + """ Sorts by (fast to slow): slice number, volume number. We calculate volume number by looking for repeating slice numbers (see :func:`vol_numbers`). + """ + slice_nos = self.image_defs['slice number'] + is_full = vol_is_full(slice_nos, self.general_info['max_slices']) + keys = (slice_nos, vol_numbers(slice_nos), np.logical_not(is_full)) + return np.lexsort(keys) + + def get_sorted_slice_indices(self): + """Return indices to sort (and maybe discard) slices in REC file. If the recording is truncated, the returned indices take care of discarding any slice indices from incomplete volumes. @@ -1088,13 +1105,10 @@ def get_sorted_slice_indices(self): ``self.image_defs``. """ if not self.strict_sort: - slice_nos = self.image_defs['slice number'] - is_full = vol_is_full(slice_nos, self.general_info['max_slices']) - keys = (slice_nos, vol_numbers(slice_nos), np.logical_not(is_full)) + sort_order = self._lax_sort_order() else: - keys = self._strict_sort_keys() + sort_order = self._strict_sort_order() - sort_order = np.lexsort(keys) # Figure out how many we need to remove from the end, and trim them. # Based on our sorting, they should always be last. n_used = np.prod(self.get_data_shape()[2:])