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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.
#
### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
"""Read / write access to NIfTI1 image format
NIfTI1 format defined at http://nifti.nimh.nih.gov/nifti-1/
"""
from __future__ import annotations
import warnings
from io import BytesIO
import numpy as np
import numpy.linalg as npl
from . import analyze # module import
from .arrayproxy import get_obj_dtype
from .batteryrunners import Report
from .casting import have_binary128
from .deprecated import alert_future_error
from .filebasedimages import ImageFileError, SerializableImage
from .optpkg import optional_package
from .quaternions import fillpositive, mat2quat, quat2mat
from .spatialimages import HeaderDataError
from .spm99analyze import SpmAnalyzeHeader
from .volumeutils import Recoder, endian_codes, make_dt_codes
pdcm, have_dicom, _ = optional_package('pydicom')
# nifti1 flat header definition for Analyze-like first 348 bytes
# first number in comments indicates offset in file header in bytes
# fmt: off
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; units 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'
]
# fmt: on
# Full header numpy dtype
header_dtype = np.dtype(header_dtd)
# datatypes not in analyze format, with codes
if have_binary128():
# Only enable 128 bit floats if we really have IEEE binary 128 longdoubles
_float128t: type[np.generic] = np.longdouble
_complex256t: type[np.generic] = np.longcomplex
else:
_float128t = np.void
_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'),
(5, 'template', 'NIFTI_XFORM_TEMPLATE_OTHER'),
),
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'),
# FSL-specific intent codes - codes used by FNIRT
# ($FSLDIR/warpfns/fnirt_file_reader.h:104)
(2006, 'fnirt disp field', (), 'FSL_FNIRT_DISPLACEMENT_FIELD'),
(2007, 'fnirt cubic spline coef', (), 'FSL_CUBIC_SPLINE_COEFFICIENTS'),
(2008, 'fnirt dct coef', (), 'FSL_DCT_COEFFICIENTS'),
(2009, 'fnirt quad spline coef', (), 'FSL_QUADRATIC_SPLINE_COEFFICIENTS'),
# FSL-specific intent codes - codes used by TOPUP
# ($FSLDIR/topup/topup_file_io.h:104)
(2016, 'topup cubic spline coef ', (), 'FSL_TOPUP_CUBIC_SPLINE_COEFFICIENTS'),
(2017, 'topup quad spline coef', (), 'FSL_TOPUP_QUADRATIC_SPLINE_COEFFICIENTS'),
(2018, 'topup field', (), 'FSL_TOPUP_FIELD'),
),
fields=('code', 'label', 'parameters', 'niistring'),
)
class Nifti1Extension:
"""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 or 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
if size % 16 != 0:
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 = f"Nifti1Extension('{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.tobytes())
# 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(b'\x00' * (extstart + rawsize - fileobj.tell()))
class Nifti1DicomExtension(Nifti1Extension):
"""NIfTI1 DICOM header extension
This class is a thin wrapper around pydicom to read a binary DICOM
byte string. If pydicom is available, content is exposed as a Dicom Dataset.
Otherwise, this silently falls back to the standard NiftiExtension class
and content is the raw bytestring loaded directly from the nifti file
header.
"""
def __init__(self, code, content, parent_hdr=None):
"""
Parameters
----------
code : int or str
Canonical extension code as defined in the NIfTI standard, given
either as integer or corresponding label
(see :data:`~nibabel.nifti1.extension_codes`)
content : bytes or pydicom Dataset or None
Extension content - either a bytestring as read from the NIfTI file
header or an existing pydicom Dataset. If a bystestring, the content
is converted into a Dataset on initialization. If None, a new empty
Dataset is created.
parent_hdr : :class:`~nibabel.nifti1.Nifti1Header`, optional
If a dicom extension belongs to an existing
:class:`~nibabel.nifti1.Nifti1Header`, it may be provided here to
ensure that the DICOM dataset is written with correctly corresponding
endianness; otherwise it is assumed the dataset is little endian.
Notes
-----
code should always be 2 for DICOM.
"""
self._code = code
if parent_hdr:
self._is_little_endian = parent_hdr.endianness == '<'
else:
self._is_little_endian = True
if isinstance(content, pdcm.dataset.Dataset):
self._is_implicit_VR = False
self._raw_content = self._mangle(content)
self._content = content
elif isinstance(content, bytes): # Got a byte string - unmangle it
self._raw_content = content
self._is_implicit_VR = self._guess_implicit_VR()
ds = self._unmangle(content, self._is_implicit_VR, self._is_little_endian)
self._content = ds
elif content is None: # initialize a new dicom dataset
self._is_implicit_VR = False
self._content = pdcm.dataset.Dataset()
else:
raise TypeError(
f'content must be either a bytestring or a pydicom Dataset. '
f'Got {content.__class__}'
)
def _guess_implicit_VR(self):
"""Try to guess DICOM syntax by checking for valid VRs.
Without a DICOM Transfer Syntax, it's difficult to tell if Value
Representations (VRs) are included in the DICOM encoding or not.
This reads where the first VR would be and checks it against a list of
valid VRs
"""
potential_vr = self._raw_content[4:6].decode()
if potential_vr in pdcm.values.converters.keys():
implicit_VR = False
else:
implicit_VR = True
return implicit_VR
def _unmangle(self, value, is_implicit_VR=False, is_little_endian=True):
bio = BytesIO(value)
ds = pdcm.filereader.read_dataset(bio, is_implicit_VR, is_little_endian)
return ds
def _mangle(self, dataset):
bio = BytesIO()
dio = pdcm.filebase.DicomFileLike(bio)
dio.is_implicit_VR = self._is_implicit_VR
dio.is_little_endian = self._is_little_endian
ds_len = pdcm.filewriter.write_dataset(dio, dataset)
dio.seek(0)
return dio.read(ds_len)
# 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', Nifti1DicomExtension if have_dicom else 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):
return 'Nifti1Extensions(%s)' % ', '.join(str(e) for e in self)
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.frombuffer(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:
warnings.warn(
'Extension size is not a multiple of 16 bytes; '
'Assuming size is correct and hoping for the best',
UserWarning,
)
# 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(b'\x00')
# '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
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 construction, and
# ``from_fileobj`` for reading from file
exts_klass = Nifti1Extensions
# Signal whether this is single (header + data) file
is_single = True
# Default voxel data offsets for single and pair
pair_vox_offset = 0
single_vox_offset = 352
# Magics for single and pair
pair_magic = b'ni1'
single_magic = b'n+1'
# Quaternion threshold near 0, based on float32 precision
quaternion_threshold = np.finfo(np.float32).eps * 3
def __init__(self, binaryblock=None, endianness=None, check=True, extensions=()):
"""Initialize header from binary data block and extensions"""
super().__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)
# Need to test *slice* of extension_status to preserve byte string type
# on Python 3
if len(extension_status) < 4 or extension_status[0:1] == b'\x00':
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; set if necessary
if self.is_single:
vox_offset = self._structarr['vox_offset']
min_vox_offset = self.single_vox_offset + self.extensions.get_sizeondisk()
if vox_offset == 0: # vox offset unset; set as necessary
self._structarr['vox_offset'] = min_vox_offset
elif vox_offset < min_vox_offset:
raise HeaderDataError(
f'vox offset set to {vox_offset}, but need at least {min_vox_offset}'
)
super().write_to(fileobj)
# Write extensions
if len(self.extensions) == 0:
# If single file, write required 0 stream to signal no extensions
if self.is_single:
fileobj.write(b'\x00' * 4)
return
# Signal there are extensions that follow
fileobj.write(b'\x01\x00\x00\x00')
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().default_structarr(endianness)
if klass.is_single:
hdr_data['magic'] = klass.single_magic
else:
hdr_data['magic'] = klass.pair_magic
return hdr_data
@classmethod
def from_header(klass, header=None, check=True):
"""Class method to create header from another header
Extend Analyze header copy by copying extensions from other Nifti
types.
Parameters
----------
header : ``Header`` instance or mapping
a header of this class, or another class of header for
conversion to this type
check : {True, False}
whether to check header for integrity
Returns
-------
hdr : header instance
fresh header instance of our own class
"""
new_hdr = super().from_header(header, check)
if isinstance(header, Nifti1Header):
new_hdr.extensions[:] = header.extensions[:]
return new_hdr
def get_data_shape(self):
"""Get shape of data
Examples
--------
>>> hdr = Nifti1Header()
>>> hdr.get_data_shape()
(0,)
>>> hdr.set_data_shape((1,2,3))
>>> hdr.get_data_shape()
(1, 2, 3)
Expanding number of dimensions gets default zooms
>>> hdr.get_zooms()
(1.0, 1.0, 1.0)
Notes
-----
Applies freesurfer hack for large vectors described in `issue 100`_ and
`save_nifti.m <save77_>`_.
Allows for freesurfer hack for 7th order icosahedron surface described
in `issue 309`_, load_nifti.m_, and `save_nifti.m <save50_>`_.
"""
shape = super().get_data_shape()
# Apply freesurfer hack for large vectors
if shape[:3] == (-1, 1, 1):
vec_len = int(self._structarr['glmin'])
if vec_len == 0:
raise HeaderDataError(
'-1 in dim[1] but 0 in glmin; inconsistent freesurfer type header?'
)
return (vec_len, 1, 1) + shape[3:]
# Apply freesurfer hack for ico7 surface
elif shape[:3] == (27307, 1, 6):
return (163842, 1, 1) + shape[3:]
else: # Normal case
return shape
def set_data_shape(self, shape):
"""Set shape of data # noqa
If ``ndims == len(shape)`` then we set zooms for dimensions higher than
``ndims`` to 1.0
Nifti1 images can have up to seven dimensions. For FreeSurfer-variant
Nifti surface files, the first dimension is assumed to correspond to
vertices/nodes on a surface, and dimensions two and three are
constrained to have depth of 1. Dimensions 4-7 are constrained only by
type bounds.
Parameters
----------
shape : sequence
sequence of integers specifying data array shape
Notes
-----
Applies freesurfer hack for large vectors described in `issue 100`_ and
`save_nifti.m <save77_>`_.
Allows for freesurfer hack for 7th order icosahedron surface described
in `issue 309`_, load_nifti.m_, and `save_nifti.m <save50_>`_.
The Nifti1 `standard header`_ allows for the following "point set"
definition of a surface, not currently implemented in nibabel.
::
To signify that the vector value at each voxel is really a
spatial coordinate (e.g., the vertices or nodes of a surface mesh):
- dataset must have a 5th dimension
- intent_code must be NIFTI_INTENT_POINTSET
- dim[0] = 5
- dim[1] = number of points
- dim[2] = dim[3] = dim[4] = 1
- dim[5] must be the dimensionality of space (e.g., 3 => 3D space).
- intent_name may describe the object these points come from
(e.g., "pial", "gray/white" , "EEG", "MEG").
.. _issue 100: https://github.com/nipy/nibabel/issues/100
.. _issue 309: https://github.com/nipy/nibabel/issues/309
.. _save77:
https://github.com/fieldtrip/fieldtrip/blob/428798b/external/freesurfer/save_nifti.m#L77-L82
.. _save50:
https://github.com/fieldtrip/fieldtrip/blob/428798b/external/freesurfer/save_nifti.m#L50-L56
.. _load_nifti.m:
https://github.com/fieldtrip/fieldtrip/blob/428798b/external/freesurfer/load_nifti.m#L86-L89
.. _standard header: http://nifti.nimh.nih.gov/pub/dist/src/niftilib/nifti1.h
"""
hdr = self._structarr
shape = tuple(shape)
# Apply freesurfer hack for ico7 surface
if shape[:3] == (163842, 1, 1):
shape = (27307, 1, 6) + shape[3:]
# Apply freesurfer hack for large vectors
elif (
len(shape) >= 3
and shape[1:3] == (1, 1)
and shape[0] > np.iinfo(hdr['dim'].dtype.base).max
):
try:
hdr['glmin'] = shape[0]
except OverflowError:
overflow = True
else:
overflow = hdr['glmin'] != shape[0]
if overflow:
raise HeaderDataError(f'shape[0] {shape[0]} does not fit in glmax datatype')
warnings.warn(
'Using large vector Freesurfer hack; header will '
'not be compatible with SPM or FSL',
stacklevel=2,
)
shape = (-1, 1, 1) + shape[3:]
super().set_data_shape(shape)
def set_data_dtype(self, datatype):
"""Set numpy dtype for data from code or dtype or type
Using :py:class:`int` or ``"int"`` is disallowed, as these types
will be interpreted as ``np.int64``, which is almost never desired.
``np.int64`` is permitted for those intent on making poor choices.
Examples
--------
>>> hdr = Nifti1Header()
>>> hdr.set_data_dtype(np.uint8)
>>> hdr.get_data_dtype()
dtype('uint8')
>>> hdr.set_data_dtype(np.dtype(np.uint8))
>>> hdr.get_data_dtype()
dtype('uint8')
>>> hdr.set_data_dtype('implausible')
Traceback (most recent call last):
...
nibabel.spatialimages.HeaderDataError: data dtype "implausible" not recognized
>>> hdr.set_data_dtype('none')
Traceback (most recent call last):
...
nibabel.spatialimages.HeaderDataError: data dtype "none" known but not supported
>>> hdr.set_data_dtype(np.void)
Traceback (most recent call last):
...
nibabel.spatialimages.HeaderDataError: data dtype "<class 'numpy.void'>" known
but not supported
>>> hdr.set_data_dtype('int')
Traceback (most recent call last):
...
ValueError: Invalid data type 'int'. Specify a sized integer, e.g., 'uint8' or numpy.int16.
>>> hdr.set_data_dtype(int)
Traceback (most recent call last):
...
ValueError: Invalid data type <class 'int'>. Specify a sized integer, e.g., 'uint8' or
numpy.int16.
>>> hdr.set_data_dtype('int64')
>>> hdr.get_data_dtype() == np.dtype('int64')
True
"""
if not isinstance(datatype, np.dtype) and datatype in (int, 'int'):
raise ValueError(
f'Invalid data type {datatype!r}. Specify a sized integer, '
"e.g., 'uint8' or numpy.int16."
)
super().set_data_dtype(datatype)
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 precision of stored values in header
return fillpositive(bcd, self.quaternion_threshold)
def get_qform(self, coded=False):
"""Return 4x4 affine matrix from qform parameters in header
Parameters
----------
coded : bool, optional
If True, return {affine or None}, and qform code. If False, just
return affine. {affine or None} means, return None if qform code
== 0, and affine otherwise.
Returns
-------
affine : None or (4,4) ndarray
If `coded` is False, always return affine reconstructed from qform
quaternion. If `coded` is True, return None if qform code is 0,
else return the affine.
code : int
Qform code. Only returned if `coded` is True.
"""
hdr = self._structarr
code = int(hdr['qform_code'])
if code == 0 and coded:
return None, 0
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