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nifti1.py
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# emacs: -*- mode: python-mode; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
#
# See COPYING file distributed along with the NiBabel package for the
# copyright and license terms.
#
### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
''' Header reading / writing functions for nifti1 image format
'''
import numpy as np
import numpy.linalg as npl
from .py3k import ZEROB, ints2bytes, asbytes, asstr
from .volumeutils import Recoder, make_dt_codes, endian_codes
from .spatialimages import HeaderDataError, ImageFileError
from .batteryrunners import Report
from .quaternions import fillpositive, quat2mat, mat2quat
from . import analyze # module import
from .spm99analyze import SpmAnalyzeHeader
# Needed for quaternion calculation
FLOAT32_EPS_3 = -np.finfo(np.float32).eps * 3
# nifti1 flat header definition for Analyze-like first 348 bytes
# first number in comments indicates offset in file header in bytes
header_dtd = [
('sizeof_hdr', 'i4'), # 0; must be 348
('data_type', 'S10'), # 4; unused
('db_name', 'S18'), # 14; unused
('extents', 'i4'), # 32; unused
('session_error', 'i2'), # 36; unused
('regular', 'S1'), # 38; unused
('dim_info', 'u1'), # 39; MRI slice ordering code
('dim', 'i2', (8,)), # 40; data array dimensions
('intent_p1', 'f4'), # 56; first intent parameter
('intent_p2', 'f4'), # 60; second intent parameter
('intent_p3', 'f4'), # 64; third intent parameter
('intent_code', 'i2'),# 68; NIFTI intent code
('datatype', 'i2'), # 70; it's the datatype
('bitpix', 'i2'), # 72; number of bits per voxel
('slice_start', 'i2'),# 74; first slice index
('pixdim', 'f4', (8,)), # 76; grid spacings (units below)
('vox_offset', 'f4'), # 108; offset to data in image file
('scl_slope', 'f4'), # 112; data scaling slope
('scl_inter', 'f4'), # 116; data scaling intercept
('slice_end', 'i2'), # 120; last slice index
('slice_code', 'u1'), # 122; slice timing order
('xyzt_units', 'u1'), # 123; inits of pixdim[1..4]
('cal_max', 'f4'), # 124; max display intensity
('cal_min', 'f4'), # 128; min display intensity
('slice_duration', 'f4'), # 132; time for 1 slice
('toffset', 'f4'), # 136; time axis shift
('glmax', 'i4'), # 140; unused
('glmin', 'i4'), # 144; unused
('descrip', 'S80'), # 148; any text
('aux_file', 'S24'), # 228; auxiliary filename
('qform_code', 'i2'), # 252; xform code
('sform_code', 'i2'), # 254; xform code
('quatern_b', 'f4'), # 256; quaternion b param
('quatern_c', 'f4'), # 260; quaternion c param
('quatern_d', 'f4'), # 264; quaternion d param
('qoffset_x', 'f4'), # 268; quaternion x shift
('qoffset_y', 'f4'), # 272; quaternion y shift
('qoffset_z', 'f4'), # 276; quaternion z shift
('srow_x', 'f4', (4,)), # 280; 1st row affine transform
('srow_y', 'f4', (4,)), # 296; 2nd row affine transform
('srow_z', 'f4', (4,)), # 312; 3rd row affine transform
('intent_name', 'S16'), # 328; name or meaning of data
('magic', 'S4') # 344; must be 'ni1\0' or 'n+1\0'
]
# Full header numpy dtype
header_dtype = np.dtype(header_dtd)
# datatypes not in analyze format, with codes
try:
_float128t = np.float128
except AttributeError:
_float128t = np.void
try:
_complex256t = np.complex256
except AttributeError:
_complex256t = np.void
_dtdefs = ( # code, label, dtype definition, niistring
(0, 'none', np.void, ""),
(1, 'binary', np.void, ""),
(2, 'uint8', np.uint8, "NIFTI_TYPE_UINT8"),
(4, 'int16', np.int16, "NIFTI_TYPE_INT16"),
(8, 'int32', np.int32, "NIFTI_TYPE_INT32"),
(16, 'float32', np.float32, "NIFTI_TYPE_FLOAT32"),
(32, 'complex64', np.complex64, "NIFTI_TYPE_COMPLEX64"),
(64, 'float64', np.float64, "NIFTI_TYPE_FLOAT64"),
(128, 'RGB', np.dtype([('R','u1'),
('G', 'u1'),
('B', 'u1')]), "NIFTI_TYPE_RGB24"),
(255, 'all', np.void, ''),
(256, 'int8', np.int8, "NIFTI_TYPE_INT8"),
(512, 'uint16', np.uint16, "NIFTI_TYPE_UINT16"),
(768, 'uint32', np.uint32, "NIFTI_TYPE_UINT32"),
(1024,'int64', np.int64, "NIFTI_TYPE_INT64"),
(1280, 'uint64', np.uint64, "NIFTI_TYPE_UINT64"),
(1536, 'float128', _float128t, "NIFTI_TYPE_FLOAT128"),
(1792, 'complex128', np.complex128, "NIFTI_TYPE_COMPLEX128"),
(2048, 'complex256', _complex256t, "NIFTI_TYPE_COMPLEX256"),
(2304, 'RGBA', np.dtype([('R','u1'),
('G', 'u1'),
('B', 'u1'),
('A', 'u1')]), "NIFTI_TYPE_RGBA32"),
)
# Make full code alias bank, including dtype column
data_type_codes = make_dt_codes(_dtdefs)
# Transform (qform, sform) codes
xform_codes = Recoder(( # code, label, niistring
(0, 'unknown', "NIFTI_XFORM_UNKNOWN"),
(1, 'scanner', "NIFTI_XFORM_SCANNER_ANAT"),
(2, 'aligned', "NIFTI_XFORM_ALIGNED_ANAT"),
(3, 'talairach', "NIFTI_XFORM_TALAIRACH"),
(4, 'mni', "NIFTI_XFORM_MNI_152")),
fields=('code', 'label', 'niistring'))
# unit codes
unit_codes = Recoder(( # code, label
(0, 'unknown'),
(1, 'meter'),
(2, 'mm'),
(3, 'micron'),
(8, 'sec'),
(16, 'msec'),
(24, 'usec'),
(32, 'hz'),
(40, 'ppm'),
(48, 'rads')), fields=('code', 'label'))
slice_order_codes = Recoder(( # code, label
(0, 'unknown'),
(1, 'sequential increasing', 'seq inc'),
(2, 'sequential decreasing', 'seq dec'),
(3, 'alternating increasing', 'alt inc'),
(4, 'alternating decreasing', 'alt dec'),
(5, 'alternating increasing 2', 'alt inc 2'),
(6, 'alternating decreasing 2', 'alt dec 2')),
fields=('code', 'label'))
intent_codes = Recoder((
# code, label, parameters description tuple
(0, 'none', (), "NIFTI_INTENT_NONE"),
(2, 'correlation',('p1 = DOF',), "NIFTI_INTENT_CORREL"),
(3, 't test', ('p1 = DOF',), "NIFTI_INTENT_TTEST"),
(4, 'f test',
('p1 = numerator DOF', 'p2 = denominator DOF'),
"NIFTI_INTENT_FTEST"),
(5, 'z score', (), "NIFTI_INTENT_ZSCORE"),
(6, 'chi2', ('p1 = DOF',), "NIFTI_INTENT_CHISQ"),
# two parameter beta distribution
(7, 'beta',
('p1=a', 'p2=b'),
"NIFTI_INTENT_BETA"),
# Prob(x) = (p1 choose x) * p2^x * (1-p2)^(p1-x), for x=0,1,...,p1
(8, 'binomial',
('p1 = number of trials', 'p2 = probability per trial'),
"NIFTI_INTENT_BINOM"),
# 2 parameter gamma
# Density(x) proportional to # x^(p1-1) * exp(-p2*x)
(9, 'gamma',
('p1 = shape, p2 = scale', 2),
"NIFTI_INTENT_GAMMA"),
(10, 'poisson',
('p1 = mean',),
"NIFTI_INTENT_POISSON"),
(11, 'normal',
('p1 = mean', 'p2 = standard deviation',),
"NIFTI_INTENT_NORMAL"),
(12, 'non central f test',
('p1 = numerator DOF',
'p2 = denominator DOF',
'p3 = numerator noncentrality parameter',),
"NIFTI_INTENT_FTEST_NONC"),
(13, 'non central chi2',
('p1 = DOF', 'p2 = noncentrality parameter',),
"NIFTI_INTENT_CHISQ_NONC"),
(14, 'logistic',
('p1 = location', 'p2 = scale',),
"NIFTI_INTENT_LOGISTIC"),
(15, 'laplace',
('p1 = location', 'p2 = scale'),
"NIFTI_INTENT_LAPLACE"),
(16, 'uniform',
('p1 = lower end', 'p2 = upper end'),
"NIFTI_INTENT_UNIFORM"),
(17, 'non central t test',
('p1 = DOF', 'p2 = noncentrality parameter'),
"NIFTI_INTENT_TTEST_NONC"),
(18, 'weibull',
('p1 = location', 'p2 = scale, p3 = power'),
"NIFTI_INTENT_WEIBULL"),
# p1 = 1 = 'half normal' distribution
# p1 = 2 = Rayleigh distribution
# p1 = 3 = Maxwell-Boltzmann distribution.
(19, 'chi', ('p1 = DOF',), "NIFTI_INTENT_CHI"),
(20, 'inverse gaussian',
('pi = mu', 'p2 = lambda'),
"NIFTI_INTENT_INVGAUSS"),
(21, 'extreme value 1',
('p1 = location', 'p2 = scale'),
"NIFTI_INTENT_EXTVAL"),
(22, 'p value', (), "NIFTI_INTENT_PVAL"),
(23, 'log p value', (), "NIFTI_INTENT_LOGPVAL"),
(24, 'log10 p value', (), "NIFTI_INTENT_LOG10PVAL"),
(1001, 'estimate', (), "NIFTI_INTENT_ESTIMATE"),
(1002, 'label', (), "NIFTI_INTENT_LABEL"),
(1003, 'neuroname', (), "NIFTI_INTENT_NEURONAME"),
(1004, 'general matrix',
('p1 = M', 'p2 = N'),
"NIFTI_INTENT_GENMATRIX"),
(1005, 'symmetric matrix', ('p1 = M',), "NIFTI_INTENT_SYMMATRIX"),
(1006, 'displacement vector', (), "NIFTI_INTENT_DISPVECT"),
(1007, 'vector', (), "NIFTI_INTENT_VECTOR"),
(1008, 'pointset', (), "NIFTI_INTENT_POINTSET"),
(1009, 'triangle', (), "NIFTI_INTENT_TRIANGLE"),
(1010, 'quaternion', (), "NIFTI_INTENT_QUATERNION"),
(1011, 'dimensionless', (), "NIFTI_INTENT_DIMLESS"),
(2001, 'time series',
(),
"NIFTI_INTENT_TIME_SERIES",
"NIFTI_INTENT_TIMESERIES"), # this mis-spell occurs in the wild
(2002, 'node index', (), "NIFTI_INTENT_NODE_INDEX"),
(2003, 'rgb vector', (), "NIFTI_INTENT_RGB_VECTOR"),
(2004, 'rgba vector', (), "NIFTI_INTENT_RGBA_VECTOR"),
(2005, 'shape', (), "NIFTI_INTENT_SHAPE")),
fields=('code', 'label', 'parameters', 'niistring'))
class Nifti1Extension(object):
"""Baseclass for NIfTI1 header extensions.
This class is sufficient to handle very simple text-based extensions, such
as `comment`. More sophisticated extensions should/will be supported by
dedicated subclasses.
"""
def __init__(self, code, content):
"""
Parameters
----------
code : int|str
Canonical extension code as defined in the NIfTI standard, given
either as integer or corresponding label
(see :data:`~nibabel.nifti1.extension_codes`)
content : str
Extension content as read from the NIfTI file header. This content is
converted into a runtime representation.
"""
try:
self._code = extension_codes.code[code]
except KeyError:
# XXX or fail or at least complain?
self._code = code
self._content = self._unmangle(content)
def _unmangle(self, value):
"""Convert the extension content into its runtime representation.
The default implementation does nothing at all.
Parameters
----------
value : str
Extension content as read from file.
Returns
-------
The same object that was passed as `value`.
Notes
-----
Subclasses should reimplement this method to provide the desired
unmangling procedure and may return any type of object.
"""
return value
def _mangle(self, value):
"""Convert the extension content into NIfTI file header representation.
The default implementation does nothing at all.
Parameters
----------
value : str
Extension content in runtime form.
Returns
-------
str
Notes
-----
Subclasses should reimplement this method to provide the desired
mangling procedure.
"""
return value
def get_code(self):
"""Return the canonical extension type code."""
return self._code
def get_content(self):
"""Return the extension content in its runtime representation."""
return self._content
def get_sizeondisk(self):
"""Return the size of the extension in the NIfTI file.
"""
# need raw value size plus 8 bytes for esize and ecode
size = len(self._mangle(self._content))
size += 8
# extensions size has to be a multiple of 16 bytes
size += 16 - (size % 16)
return size
def __repr__(self):
try:
code = extension_codes.label[self._code]
except KeyError:
# deal with unknown codes
code = self._code
s = "Nifti1Extension('%s', '%s')" % (code, self._content)
return s
def __eq__(self, other):
return (self._code, self._content) == (other._code, other._content)
def __ne__(self, other):
return not self == other
def write_to(self, fileobj, byteswap):
''' Write header extensions to fileobj
Write starts at fileobj current file position.
Parameters
----------
fileobj : file-like object
Should implement ``write`` method
byteswap : boolean
Flag if byteswapping the data is required.
Returns
-------
None
'''
extstart = fileobj.tell()
rawsize = self.get_sizeondisk()
# write esize and ecode first
extinfo = np.array((rawsize, self._code), dtype=np.int32)
if byteswap:
extinfo = extinfo.byteswap()
fileobj.write(extinfo.tostring())
# followed by the actual extension content
# XXX if mangling upon load is implemented, it should be reverted here
fileobj.write(self._mangle(self._content))
# be nice and zero out remaining part of the extension till the
# next 16 byte border
fileobj.write(ZEROB * (extstart + rawsize - fileobj.tell()))
# NIfTI header extension type codes (ECODE)
# see nifti1_io.h for a complete list of all known extensions and
# references to their description or contacts of the respective
# initiators
extension_codes = Recoder((
(0, "ignore", Nifti1Extension),
(2, "dicom", Nifti1Extension),
(4, "afni", Nifti1Extension),
(6, "comment", Nifti1Extension),
(8, "xcede", Nifti1Extension),
(10, "jimdiminfo", Nifti1Extension),
(12, "workflow_fwds", Nifti1Extension),
(14, "freesurfer", Nifti1Extension),
(16, "pypickle", Nifti1Extension)
),
fields=('code', 'label', 'handler'))
class Nifti1Extensions(list):
"""Simple extension collection, implemented as a list-subclass.
"""
def count(self, ecode):
"""Returns the number of extensions matching a given *ecode*.
Parameters
----------
code : int | str
The ecode can be specified either literal or as numerical value.
"""
count = 0
code = extension_codes.code[ecode]
for e in self:
if e.get_code() == code:
count += 1
return count
def get_codes(self):
"""Return a list of the extension code of all available extensions"""
return [e.get_code() for e in self]
def get_sizeondisk(self):
"""Return the size of the complete header extensions in the NIfTI file.
"""
return np.sum([e.get_sizeondisk() for e in self])
def __repr__(self):
s = "Nifti1Extensions(%s)" \
% ', '.join([str(e) for e in self])
return s
def __cmp__(self, other):
return cmp(list(self), list(other))
def write_to(self, fileobj, byteswap):
''' Write header extensions to fileobj
Write starts at fileobj current file position.
Parameters
----------
fileobj : file-like object
Should implement ``write`` method
byteswap : boolean
Flag if byteswapping the data is required.
Returns
-------
None
'''
for e in self:
e.write_to(fileobj, byteswap)
@classmethod
def from_fileobj(klass, fileobj, size, byteswap):
'''Read header extensions from a fileobj
Parameters
----------
fileobj : file-like object
We begin reading the extensions at the current file position
size : int
Number of bytes to read. If negative, fileobj will be read till its
end.
byteswap : boolean
Flag if byteswapping the read data is required.
Returns
-------
An extension list. This list might be empty in case not extensions
were present in fileobj.
'''
# make empty extension list
extensions = klass()
# assume the file pointer is at the beginning of any extensions.
# read until the whole header is parsed (each extension is a multiple
# of 16 bytes) or in case of a separate header file till the end
# (break inside the body)
while size >= 16 or size < 0:
# the next 8 bytes should have esize and ecode
ext_def = fileobj.read(8)
# nothing was read and instructed to read till the end
# -> assume all extensions where parsed and break
if not len(ext_def) and size < 0:
break
# otherwise there should be a full extension header
if not len(ext_def) == 8:
raise HeaderDataError('failed to read extension header')
ext_def = np.fromstring(ext_def, dtype=np.int32)
if byteswap:
ext_def = ext_def.byteswap()
# be extra verbose
ecode = ext_def[1]
esize = ext_def[0]
if esize % 16:
raise HeaderDataError(
'extension size is not a multiple of 16 bytes')
# read extension itself; esize includes the 8 bytes already read
evalue = fileobj.read(int(esize - 8))
if not len(evalue) == esize - 8:
raise HeaderDataError('failed to read extension content')
# note that we read a full extension
size -= esize
# store raw extension content, but strip trailing NULL chars
evalue = evalue.rstrip(ZEROB)
# 'extension_codes' also knows the best implementation to handle
# a particular extension type
try:
ext = extension_codes.handler[ecode](ecode, evalue)
except KeyError:
# unknown extension type
# XXX complain or fail or go with a generic extension
ext = Nifti1Extension(ecode, evalue)
extensions.append(ext)
return extensions
def state_stamper(self, caller):
""" Return stamp for current state of `self`
Parameters
----------
caller : callable
callable with which we can process our state
Returns
-------
stamp : object
object unique to this state of `self`
"""
return self.__class__, caller(list(self))
class Nifti1Header(SpmAnalyzeHeader):
''' Class for NIFTI1 header
The NIFTI1 header has many more coded fields than the simpler Analyze
variants. Nifti1 headers also have extensions.
Nifti allows the header to be a separate file, as part of a nifti image /
header pair, or to precede the data in a single file. The object needs to
know which type it is, in order to manage the voxel offset pointing to the
data, extension reading, and writing the correct magic string.
This class handles the header-preceding-data case.
'''
# Copies of module level definitions
template_dtype = header_dtype
_data_type_codes = data_type_codes
# fields with recoders for their values
_field_recoders = {'datatype': data_type_codes,
'qform_code': xform_codes,
'sform_code': xform_codes,
'intent_code': intent_codes,
'slice_code': slice_order_codes}
# data scaling capabilities
has_data_slope = True
has_data_intercept = True
# Extension class; should implement __call__ for contruction, and
# ``from_fileobj`` for reading from file
exts_klass = Nifti1Extensions
# Signal whether this is single (header + data) file
is_single = True
def __init__(self,
binaryblock=None,
endianness=None,
check=True,
extensions=()):
''' Initialize header from binary data block and extensions
'''
super(Nifti1Header, self).__init__(binaryblock,
endianness,
check)
self.extensions = self.exts_klass(extensions)
def copy(self):
''' Return copy of header
Take reference to extensions as well as copy of header contents
'''
return self.__class__(
self.binaryblock,
self.endianness,
False,
self.extensions)
@classmethod
def from_fileobj(klass, fileobj, endianness=None, check=True):
raw_str = fileobj.read(klass.template_dtype.itemsize)
hdr = klass(raw_str, endianness, check)
# Read next 4 bytes to see if we have extensions. The nifti standard
# has this as a 4 byte string; if the first value is not zero, then we
# have extensions.
extension_status = fileobj.read(4)
if len(extension_status) < 4 or extension_status[0] == ZEROB:
return hdr
# If this is a detached header file read to end
if not klass.is_single:
extsize = -1
else: # otherwise read until the beginning of the data
extsize = hdr._structarr['vox_offset'] - fileobj.tell()
byteswap = endian_codes['native'] != hdr.endianness
hdr.extensions = klass.exts_klass.from_fileobj(fileobj, extsize, byteswap)
return hdr
def write_to(self, fileobj):
# First check that vox offset is large enough
if self.is_single:
vox_offset = self._structarr['vox_offset']
min_vox_offset = 352 + self.extensions.get_sizeondisk()
if vox_offset < min_vox_offset:
raise HeaderDataError('vox offset of %d, but need at least %d'
% (vox_offset, min_vox_offset))
super(Nifti1Header, self).write_to(fileobj)
if len(self.extensions) == 0:
# If single file, write required 0 stream to signal no extensions
if self.is_single:
fileobj.write(ZEROB * 4)
return
# Signal there are extensions that follow
fileobj.write(ints2bytes([1, 0, 0, 0]))
byteswap = endian_codes['native'] != self.endianness
self.extensions.write_to(fileobj, byteswap)
def get_best_affine(self):
''' Select best of available transforms '''
hdr = self._structarr
if hdr['sform_code'] != 0:
return self.get_sform()
if hdr['qform_code'] != 0:
return self.get_qform()
return self.get_base_affine()
@classmethod
def default_structarr(klass, endianness=None):
''' Create empty header binary block with given endianness '''
hdr_data = super(Nifti1Header, klass).default_structarr(endianness)
if klass.is_single:
hdr_data['magic'] = 'n+1'
hdr_data['vox_offset'] = 352
else:
hdr_data['magic'] = 'ni1'
hdr_data['vox_offset'] = 0
return hdr_data
def state_stamper(self, caller):
""" Return stamp for current state of `self`
Parameters
----------
caller : None or callable
May be object from which this method was called.
Returns
-------
stamp : object
object unique to this state of `self`
"""
return self.__class__, self.binaryblock, caller(self.extensions)
def get_qform_quaternion(self):
''' Compute quaternion from b, c, d of quaternion
Fills a value by assuming this is a unit quaternion
'''
hdr = self._structarr
bcd = [hdr['quatern_b'], hdr['quatern_c'], hdr['quatern_d']]
# Adjust threshold to fact that source data was float32
return fillpositive(bcd, FLOAT32_EPS_3)
def get_qform(self):
''' Return 4x4 affine matrix from qform parameters in header '''
hdr = self._structarr
quat = self.get_qform_quaternion()
R = quat2mat(quat)
vox = hdr['pixdim'][1:4].copy()
if np.any(vox) < 0:
raise HeaderDataError('pixdims[1,2,3] should be positive')
qfac = hdr['pixdim'][0]
if qfac not in (-1, 1):
raise HeaderDataError('qfac (pixdim[0]) should be 1 or -1')
vox[-1] *= qfac
S = np.diag(vox)
M = np.dot(R, S)
out = np.eye(4)
out[0:3, 0:3] = M
out[0:3, 3] = [hdr['qoffset_x'], hdr['qoffset_y'], hdr['qoffset_z']]
return out
def set_qform(self, affine, code=None):
''' Set qform header values from 4x4 affine
Parameters
----------
hdr : nifti1 header
affine : 4x4 array
affine transform to write into qform
code : None, string or integer
String or integer giving meaning of transform in *affine*.
The default is None. If code is None, then {if current
qform code is not 0, leave code as it is in the header; else
set to 2 ('aligned')}.
Notes
-----
The qform transform only encodes translations, rotations and
zooms. If there are shear components to the `affine` transform,
the written qform gives the closest approximation where the
rotation matrix is orthogonal. This is to allow quaternion
representation. The orthogonal representation enforces
orthogonal axes.
Examples
--------
>>> hdr = Nifti1Header()
>>> int(hdr['qform_code']) # gives 0 - unknown
0
>>> affine = np.diag([1,2,3,1])
>>> np.all(hdr.get_qform() == affine)
False
>>> hdr.set_qform(affine)
>>> np.all(hdr.get_qform() == affine)
True
>>> int(hdr['qform_code']) # gives 2 - aligned
2
>>> hdr.set_qform(affine, code='talairach')
>>> int(hdr['qform_code'])
3
>>> hdr.set_qform(affine, code=None)
>>> int(hdr['qform_code'])
3
>>> hdr.set_qform(affine, code='scanner')
>>> int(hdr['qform_code'])
1
'''
hdr = self._structarr
if code is None:
code = hdr['qform_code']
if code == 0: # default is 'aligned'
hdr['qform_code'] = 2
else:
code = self._field_recoders['qform_code'][code]
hdr['qform_code'] = code
if not affine.shape == (4, 4):
raise TypeError('Need 4x4 affine as input')
trans = affine[:3, 3]
RZS = affine[:3, :3]
zooms = np.sqrt(np.sum(RZS * RZS, axis=0))
R = RZS / zooms
# Set qfac to make R determinant positive
if npl.det(R) > 0:
qfac = 1
else:
qfac = -1
R[:, -1] *= -1
# Make R orthogonal (to allow quaternion representation)
# The orthogonal representation enforces orthogonal axes
# (a subtle requirement of the NIFTI format qform transform)
# Transform below is polar decomposition, returning the closest
# orthogonal matrix PR, to input R
P, S, Qs = npl.svd(R)
PR = np.dot(P, Qs)
# Convert to quaternion
quat = mat2quat(PR)
# Set into header
hdr['qoffset_x'], hdr['qoffset_y'], hdr['qoffset_z'] = trans
hdr['pixdim'][0] = qfac
hdr['pixdim'][1:4] = zooms
hdr['quatern_b'], hdr['quatern_c'], hdr['quatern_d'] = quat[1:]
def get_sform(self):
''' Return sform 4x4 affine matrix from header '''
hdr = self._structarr
out = np.eye(4)
out[0, :] = hdr['srow_x'][:]
out[1, :] = hdr['srow_y'][:]
out[2, :] = hdr['srow_z'][:]
return out
def set_sform(self, affine, code=None):
''' Set sform transform from 4x4 affine
Parameters
----------
hdr : nifti1 header
affine : 4x4 array
affine transform to write into sform
code : None, string or integer
String or integer giving meaning of transform in *affine*.
The default is None. If code is None, then {if current
sform code is not 0, leave code as it is in the header; else
set to 2 ('aligned')}.
Examples
--------
>>> hdr = Nifti1Header()
>>> int(hdr['sform_code']) # gives 0 - unknown
0
>>> affine = np.diag([1,2,3,1])
>>> np.all(hdr.get_sform() == affine)
False
>>> hdr.set_sform(affine)
>>> np.all(hdr.get_sform() == affine)
True
>>> int(hdr['sform_code']) # gives 2 - aligned
2
>>> hdr.set_sform(affine, code='talairach')
>>> int(hdr['sform_code'])
3
>>> hdr.set_sform(affine, code=None)
>>> int(hdr['sform_code'])
3
>>> hdr.set_sform(affine, code='scanner')
>>> int(hdr['sform_code'])
1
'''
hdr = self._structarr
if code is None:
code = hdr['sform_code']
if code == 0:
hdr['sform_code'] = 2 # aligned
else:
code = self._field_recoders['sform_code'][code]
hdr['sform_code'] = code
hdr['srow_x'][:] = affine[0, :]
hdr['srow_y'][:] = affine[1, :]
hdr['srow_z'][:] = affine[2, :]
def get_slope_inter(self):
''' Get data scaling (slope) and DC offset (intercept) from header data
Parameters
----------
self : header object
Should have fields (keys)
* scl_slope - slope
* scl_inter - intercept
Returns
-------
slope : None or float
scaling (slope). None if there is no valid scaling from these fields
inter : None or float
offset (intercept). None if there is no valid scaling or if offset is
not finite.
Examples
--------
>>> hdr = Nifti1Header()
>>> hdr.get_slope_inter()
(1.0, 0.0)
>>> hdr['scl_slope'] = 0
>>> hdr.get_slope_inter()
(None, None)
>>> hdr['scl_slope'] = np.nan
>>> hdr.get_slope_inter()
(None, None)
>>> hdr['scl_slope'] = 1
>>> hdr['scl_inter'] = 1
>>> hdr.get_slope_inter()
(1.0, 1.0)
>>> hdr['scl_inter'] = np.inf
>>> hdr.get_slope_inter()
(1.0, None)
'''
scale = float(self['scl_slope'])
dc_offset = float(self['scl_inter'])
if scale == 0 or not np.isfinite(scale):
return None, None
if not np.isfinite(dc_offset):
dc_offset = None
return scale, dc_offset
def set_slope_inter(self, slope, inter=0.0):
''' Set slope and / or intercept into header
Set slope and intercept for image data, such that, if the image
data is ``arr``, then the scaled image data will be ``(arr *
slope) + inter``
Parameters
----------
slope : None or float
If None, implies `slope` of 0. When the slope is set to 0 or a
not-finite value, ``get_slope_inter`` returns (None, None), i.e.
`inter` is ignored unless there is a valid value for `slope`.
inter : None or float, optional
intercept. None implies inter value of 0.
'''
if slope is None:
slope = 0.0
if inter is None:
inter = 0.0
self._structarr['scl_slope'] = slope
self._structarr['scl_inter'] = inter
def get_dim_info(self):
''' Gets nifti MRI slice etc dimension information
Returns
-------
freq : {None,0,1,2}
Which data array axis is freqency encode direction
phase : {None,0,1,2}
Which data array axis is phase encode direction
slice : {None,0,1,2}
Which data array axis is slice encode direction
where ``data array`` is the array returned by ``get_data``
Because nifti1 files are natively Fortran indexed:
0 is fastest changing in file
1 is medium changing in file
2 is slowest changing in file
``None`` means the axis appears not to be specified.
Examples
--------
See set_dim_info function
'''
hdr = self._structarr
info = int(hdr['dim_info'])
freq = info & 3
phase = (info >> 2) & 3
slice = (info >> 4) & 3
return (freq-1 if freq else None,
phase-1 if phase else None,
slice-1 if slice else None)
def set_dim_info(self, freq=None, phase=None, slice=None):
''' Sets nifti MRI slice etc dimension information
Parameters
----------
hdr : nifti1 header
freq : {None, 0, 1, 2}
axis of data array refering to freqency encoding
phase : {None, 0, 1, 2}
axis of data array refering to phase encoding
slice : {None, 0, 1, 2}
axis of data array refering to slice encoding
``None`` means the axis is not specified.
Examples
--------
>>> hdr = Nifti1Header()
>>> hdr.set_dim_info(1, 2, 0)
>>> hdr.get_dim_info()
(1, 2, 0)
>>> hdr.set_dim_info(freq=1, phase=2, slice=0)
>>> hdr.get_dim_info()
(1, 2, 0)
>>> hdr.set_dim_info()
>>> hdr.get_dim_info()
(None, None, None)
>>> hdr.set_dim_info(freq=1, phase=None, slice=0)
>>> hdr.get_dim_info()
(1, None, 0)
Notes
-----
This is stored in one byte in the header
'''
for inp in (freq, phase, slice):
if inp not in (None, 0, 1, 2):
raise HeaderDataError('Inputs must be in [None, 0, 1, 2]')
info = 0
if not freq is None:
info = info | ((freq+1) & 3)
if not phase is None:
info = info | (((phase+1) & 3) << 2)
if not slice is None:
info = info | (((slice+1) & 3) << 4)
self._structarr['dim_info'] = info
def get_intent(self, code_repr='label'):
''' Get intent code, parameters and name
Parameters
----------
code_repr : string
string giving output form of intent code representation.
Default is 'label'; use 'code' for integer representation.
Returns
-------
code : string or integer
intent code, or string describing code
parameters : tuple
parameters for the intent
name : string
intent name
Examples
--------
>>> hdr = Nifti1Header()
>>> hdr.set_intent('t test', (10,), name='some score')
>>> hdr.get_intent()
('t test', (10.0,), 'some score')
>>> hdr.get_intent('code')
(3, (10.0,), 'some score')
'''
hdr = self._structarr
recoder = self._field_recoders['intent_code']
code = int(hdr['intent_code'])