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merged 4 commits into from
Apr 11, 2016
Merged

MRG: test fixes and doc updates for multiframe code #442

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ee0d899
DOC: add more links on DICOM multi-frame
matthew-brett Apr 9, 2016
78c002d
RF: add extra blank line for PEP8
matthew-brett Apr 9, 2016
4cafaf5
BF: note multiframe shape test as DICOM test
matthew-brett Apr 9, 2016
bf0b018
RF: clear <CR> characters in test file
matthew-brett Apr 9, 2016
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23 changes: 19 additions & 4 deletions nibabel/nicom/dicomwrappers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -23,6 +23,7 @@
from ..onetime import setattr_on_read as one_time
from ..pydicom_compat import pydicom


class WrapperError(Exception):
pass

Expand Down Expand Up @@ -412,7 +413,18 @@ def b_vector(self):
class MultiframeWrapper(Wrapper):
"""Wrapper for Enhanced MR Storage SOP Class

tested with Philips' Enhanced DICOM implementation
Tested with Philips' Enhanced DICOM implementation.

The specification for the Enhanced MR image IOP / SOP began life as `DICOM
supplement 49 <ftp://medical.nema.org/medical/dicom/final/sup49_ft.pdf>`_,
but as of 2016 it is part of the standard. In particular see:

* `A.36 Enhanced MR Information Object Definitions
<http://dicom.nema.org/medical/dicom/current/output/pdf/part03.pdf#sect_A.36>`_;
* `C.7.6.16 Multi-Frame Functional Groups Module
<http://dicom.nema.org/medical/dicom/current/output/pdf/part03.pdf#sect_C.7.6.16>`_;
* `C.7.6.17 Multi-Frame Dimension Module
<http://dicom.nema.org/medical/dicom/current/output/pdf/part03.pdf#sect_C.7.6.17>`_.

Attributes
----------
Expand Down Expand Up @@ -480,9 +492,12 @@ def image_shape(self):

References
----------

* C.7.6.16 Multi-Frame Functional Groups Module: http://dicom.nema.org/medical/dicom/current/output/pdf/part03.pdf#sect_C.7.6.16
* C.7.6.17 Multi-Frame Dimension Module: http://dicom.nema.org/medical/dicom/current/output/pdf/part03.pdf#sect_C.7.6.17
* C.7.6.16 Multi-Frame Functional Groups Module:
http://dicom.nema.org/medical/dicom/current/output/pdf/part03.pdf#sect_C.7.6.16
* C.7.6.17 Multi-Frame Dimension Module:
http://dicom.nema.org/medical/dicom/current/output/pdf/part03.pdf#sect_C.7.6.17
* Diagram of DimensionIndexSequence and DimensionIndexValues:
http://dicom.nema.org/medical/dicom/current/output/pdf/part03.pdf#figure_C.7.6.17-1
"""
rows, cols = self.get('Rows'), self.get('Columns')
if None in (rows, cols):
Expand Down
158 changes: 80 additions & 78 deletions nibabel/nicom/tests/test_dicomwrappers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,7 @@
import gzip
from hashlib import sha1
from decimal import Decimal
from copy import copy
from copy import copy

import numpy as np

Expand Down Expand Up @@ -379,54 +379,54 @@ class Fake(object):
setattr(fake_frame, seq_name, [fake_element])
frames.append(fake_frame)
return frames
def fake_shape_dependents(div_seq, sid_seq=None, sid_dim=None):
""" Make a fake dictionary of data that ``image_shape`` is dependent on.
Parameters
----------
div_seq : list of tuples
list of values to use for the `DimensionIndexValues` of each frame.
sid_seq : list of int
list of values to use for the `StackID` of each frame.
sid_dim : int
the index of the column in 'div_seq' to use as 'sid_seq'
"""
class DimIdxSeqElem(object):
def __init__(self, dip=(0, 0), fgp=None):
self.DimensionIndexPointer = dip
if fgp is not None:
self.FunctionalGroupPointer = fgp
class FrmContSeqElem(object):
def __init__(self, div, sid):
self.DimensionIndexValues = div
self.StackID = sid
class PerFrmFuncGrpSeqElem(object):
def __init__(self, div, sid):
self.FrameContentSequence = [FrmContSeqElem(div, sid)]
# if no StackID values passed in then use the values at index 'sid_dim' in
# the value for DimensionIndexValues for it
if sid_seq is None:
if sid_dim is None:
sid_dim = 0
sid_seq = [div[sid_dim] for div in div_seq]
# create the DimensionIndexSequence
num_of_frames = len(div_seq)
dim_idx_seq = [DimIdxSeqElem()] * num_of_frames
# add an entry for StackID into the DimensionIndexSequence
if sid_dim is not None:
sid_tag = pydicom.datadict.tag_for_name('StackID')
fcs_tag = pydicom.datadict.tag_for_name('FrameContentSequence')
dim_idx_seq[sid_dim] = DimIdxSeqElem(sid_tag, fcs_tag)
# create the PerFrameFunctionalGroupsSequence
frames = [PerFrmFuncGrpSeqElem(div, sid)
for div, sid in zip(div_seq, sid_seq)]
return {'NumberOfFrames' : num_of_frames,
'DimensionIndexSequence' : dim_idx_seq,
'PerFrameFunctionalGroupsSequence' : frames}


def fake_shape_dependents(div_seq, sid_seq=None, sid_dim=None):
""" Make a fake dictionary of data that ``image_shape`` is dependent on.

Parameters
----------
div_seq : list of tuples
list of values to use for the `DimensionIndexValues` of each frame.
sid_seq : list of int
list of values to use for the `StackID` of each frame.
sid_dim : int
the index of the column in 'div_seq' to use as 'sid_seq'
"""
class DimIdxSeqElem(object):
def __init__(self, dip=(0, 0), fgp=None):
self.DimensionIndexPointer = dip
if fgp is not None:
self.FunctionalGroupPointer = fgp
class FrmContSeqElem(object):
def __init__(self, div, sid):
self.DimensionIndexValues = div
self.StackID = sid
class PerFrmFuncGrpSeqElem(object):
def __init__(self, div, sid):
self.FrameContentSequence = [FrmContSeqElem(div, sid)]
# if no StackID values passed in then use the values at index 'sid_dim' in
# the value for DimensionIndexValues for it
if sid_seq is None:
if sid_dim is None:
sid_dim = 0
sid_seq = [div[sid_dim] for div in div_seq]
# create the DimensionIndexSequence
num_of_frames = len(div_seq)
dim_idx_seq = [DimIdxSeqElem()] * num_of_frames
# add an entry for StackID into the DimensionIndexSequence
if sid_dim is not None:
sid_tag = pydicom.datadict.tag_for_name('StackID')
fcs_tag = pydicom.datadict.tag_for_name('FrameContentSequence')
dim_idx_seq[sid_dim] = DimIdxSeqElem(sid_tag, fcs_tag)
# create the PerFrameFunctionalGroupsSequence
frames = [PerFrmFuncGrpSeqElem(div, sid)
for div, sid in zip(div_seq, sid_seq)]
return {'NumberOfFrames' : num_of_frames,
'DimensionIndexSequence' : dim_idx_seq,
'PerFrameFunctionalGroupsSequence' : frames}


class TestMultiFrameWrapper(TestCase):
# Test MultiframeWrapper
MINIMAL_MF = {
Expand All @@ -435,6 +435,7 @@ class TestMultiFrameWrapper(TestCase):
'SharedFunctionalGroupsSequence': [None]}
WRAPCLASS = didw.MultiframeWrapper

@dicom_test
def test_shape(self):
# Check the shape algorithm
fake_mf = copy(self.MINIMAL_MF)
Expand All @@ -452,65 +453,65 @@ def test_shape(self):
assert_raises(AssertionError, getattr, dw, 'image_shape')
fake_mf['NumberOfFrames'] = 4
# PerFrameFunctionalGroupsSequence does not match NumberOfFrames
assert_raises(AssertionError, getattr, dw, 'image_shape')
# check 3D shape when StackID index is 0
div_seq = ((1, 1), (1, 2), (1, 3), (1, 4))
fake_mf.update(fake_shape_dependents(div_seq, sid_dim=0))
assert_raises(AssertionError, getattr, dw, 'image_shape')
# check 3D shape when StackID index is 0
div_seq = ((1, 1), (1, 2), (1, 3), (1, 4))
fake_mf.update(fake_shape_dependents(div_seq, sid_dim=0))
assert_equal(MFW(fake_mf).image_shape, (32, 64, 4))
# Check stack number matching when StackID index is 0
div_seq = ((1, 1), (1, 2), (1, 3), (2, 4))
fake_mf.update(fake_shape_dependents(div_seq, sid_dim=0))
fake_mf.update(fake_shape_dependents(div_seq, sid_dim=0))
assert_raises(didw.WrapperError, getattr, MFW(fake_mf), 'image_shape')
# Make some fake frame data for 4D when StackID index is 0
# Make some fake frame data for 4D when StackID index is 0
div_seq = ((1, 1, 1), (1, 2, 1), (1, 1, 2), (1, 2, 2),
(1, 1, 3), (1, 2, 3))
fake_mf.update(fake_shape_dependents(div_seq, sid_dim=0))
fake_mf.update(fake_shape_dependents(div_seq, sid_dim=0))
assert_equal(MFW(fake_mf).image_shape, (32, 64, 2, 3))
# Check stack number matching for 4D when StackID index is 0
div_seq = ((1, 1, 1), (1, 2, 1), (1, 1, 2), (1, 2, 2),
(1, 1, 3), (2, 2, 3))
fake_mf.update(fake_shape_dependents(div_seq, sid_dim=0))
fake_mf.update(fake_shape_dependents(div_seq, sid_dim=0))
assert_raises(didw.WrapperError, getattr, MFW(fake_mf), 'image_shape')
# Check indices can be non-contiguous when StackID index is 0
div_seq = ((1, 1, 1), (1, 2, 1), (1, 1, 3), (1, 2, 3))
fake_mf.update(fake_shape_dependents(div_seq, sid_dim=0))
fake_mf.update(fake_shape_dependents(div_seq, sid_dim=0))
assert_equal(MFW(fake_mf).image_shape, (32, 64, 2, 2))
# Check indices can include zero when StackID index is 0
div_seq = ((1, 1, 0), (1, 2, 0), (1, 1, 3), (1, 2, 3))
fake_mf.update(fake_shape_dependents(div_seq, sid_dim=0))
fake_mf.update(fake_shape_dependents(div_seq, sid_dim=0))
assert_equal(MFW(fake_mf).image_shape, (32, 64, 2, 2))
# check 3D shape when there is no StackID index
# check 3D shape when there is no StackID index
div_seq = ((1,), (2,), (3,), (4,))
sid_seq = (1, 1, 1, 1)
fake_mf.update(fake_shape_dependents(div_seq, sid_seq=sid_seq))
fake_mf.update(fake_shape_dependents(div_seq, sid_seq=sid_seq))
assert_equal(MFW(fake_mf).image_shape, (32, 64, 4))
# check 3D stack number matching when there is no StackID index
div_seq = ((1,), (2,), (3,), (4,))
sid_seq = (1, 1, 1, 2)
fake_mf.update(fake_shape_dependents(div_seq, sid_seq=sid_seq))
fake_mf.update(fake_shape_dependents(div_seq, sid_seq=sid_seq))
assert_raises(didw.WrapperError, getattr, MFW(fake_mf), 'image_shape')
# check 4D shape when there is no StackID index
# check 4D shape when there is no StackID index
div_seq = ((1, 1), (2, 1), (1, 2), (2, 2), (1, 3), (2, 3))
sid_seq = (1, 1, 1, 1, 1, 1)
fake_mf.update(fake_shape_dependents(div_seq, sid_seq=sid_seq))
fake_mf.update(fake_shape_dependents(div_seq, sid_seq=sid_seq))
assert_equal(MFW(fake_mf).image_shape, (32, 64, 2, 3))
# check 4D stack number matching when there is no StackID index
div_seq = ((1, 1), (2, 1), (1, 2), (2, 2), (1, 3), (2, 3))
sid_seq = (1, 1, 1, 1, 1, 2)
fake_mf.update(fake_shape_dependents(div_seq, sid_seq=sid_seq))
fake_mf.update(fake_shape_dependents(div_seq, sid_seq=sid_seq))
assert_raises(didw.WrapperError, getattr, MFW(fake_mf), 'image_shape')
# check 3D shape when StackID index is 1
# check 3D shape when StackID index is 1
div_seq = ((1, 1), (2, 1), (3, 1), (4, 1))
fake_mf.update(fake_shape_dependents(div_seq, sid_dim=1))
fake_mf.update(fake_shape_dependents(div_seq, sid_dim=1))
assert_equal(MFW(fake_mf).image_shape, (32, 64, 4))
# Check stack number matching when StackID index is 1
div_seq = ((1, 1), (2, 1), (3, 2), (4, 1))
fake_mf.update(fake_shape_dependents(div_seq, sid_dim=1))
div_seq = ((1, 1), (2, 1), (3, 2), (4, 1))
fake_mf.update(fake_shape_dependents(div_seq, sid_dim=1))
assert_raises(didw.WrapperError, getattr, MFW(fake_mf), 'image_shape')
# Make some fake frame data for 4D when StackID index is 1
# Make some fake frame data for 4D when StackID index is 1
div_seq = ((1, 1, 1), (2, 1, 1), (1, 1, 2), (2, 1, 2),
(1, 1, 3), (2, 1, 3))
fake_mf.update(fake_shape_dependents(div_seq, sid_dim=1))
fake_mf.update(fake_shape_dependents(div_seq, sid_dim=1))
assert_equal(MFW(fake_mf).image_shape, (32, 64, 2, 3))

def test_iop(self):
Expand Down Expand Up @@ -614,6 +615,7 @@ def test_data_real(self):
assert_equal(sha1(dat_str).hexdigest(),
'149323269b0af92baa7508e19ca315240f77fa8c')

@dicom_test
def test_data_fake(self):
# Test algorithm for get_data
fake_mf = copy(self.MINIMAL_MF)
Expand All @@ -627,9 +629,9 @@ def test_data_fake(self):
assert_raises(didw.WrapperError, dw.get_data)
# Make shape and indices
fake_mf['Rows'] = 2
fake_mf['Columns'] = 3
dim_idxs = ((1, 1), (1, 2), (1, 3), (1, 4))
fake_mf.update(fake_shape_dependents(dim_idxs, sid_dim=0))
fake_mf['Columns'] = 3
dim_idxs = ((1, 1), (1, 2), (1, 3), (1, 4))
fake_mf.update(fake_shape_dependents(dim_idxs, sid_dim=0))
assert_equal(MFW(fake_mf).image_shape, (2, 3, 4))
# Still fails - no data
assert_raises(didw.WrapperError, dw.get_data)
Expand All @@ -644,9 +646,9 @@ def test_data_fake(self):
fake_mf['RescaleSlope'] = 2.0
fake_mf['RescaleIntercept'] = -1
assert_array_equal(MFW(fake_mf).get_data(), data * 2.0 - 1)
# Check slice sorting
dim_idxs = ((1, 4), (1, 2), (1, 3), (1, 1))
fake_mf.update(fake_shape_dependents(dim_idxs, sid_dim=0))
# Check slice sorting
dim_idxs = ((1, 4), (1, 2), (1, 3), (1, 1))
fake_mf.update(fake_shape_dependents(dim_idxs, sid_dim=0))
sorted_data = data[..., [3, 1, 2, 0]]
fake_mf['pixel_array'] = np.rollaxis(sorted_data, 2)
assert_array_equal(MFW(fake_mf).get_data(), data * 2.0 - 1)
Expand All @@ -668,7 +670,7 @@ def test_data_fake(self):
[1, 2, 1, 2],
[1, 3, 1, 2],
[1, 1, 1, 2]]
fake_mf.update(fake_shape_dependents(dim_idxs, sid_dim=0))
fake_mf.update(fake_shape_dependents(dim_idxs, sid_dim=0))
shape = (2, 3, 4, 2, 2)
data = np.arange(np.prod(shape)).reshape(shape)
sorted_data = data.reshape(shape[:2] + (-1,), order='F')
Expand Down