spm2analyze

Read / write access to SPM2 version of analyze image format

Spm2AnalyzeHeader([binaryblock, endianness, …])

Class for SPM2 variant of basic Analyze header

Spm2AnalyzeImage(dataobj, affine[, header, …])

Class for SPM2 variant of basic Analyze image

Spm2AnalyzeHeader

class nibabel.spm2analyze.Spm2AnalyzeHeader(binaryblock=None, endianness=None, check=True)

Bases: nibabel.spm99analyze.Spm99AnalyzeHeader

Class for SPM2 variant of basic Analyze header

SPM2 variant adds the following to basic Analyze format:

  • voxel origin;

  • slope scaling of data;

  • reading - but not writing - intercept of data.

Initialize header from binary data block

Parameters
binaryblock{None, string} optional

binary block to set into header. By default, None, in which case we insert the default empty header block

endianness{None, ‘<’,’>’, other endian code} string, optional

endianness of the binaryblock. If None, guess endianness from the data.

checkbool, optional

Whether to check content of header in initialization. Default is True.

Examples

>>> hdr1 = AnalyzeHeader() # an empty header
>>> hdr1.endianness == native_code
True
>>> hdr1.get_data_shape()
(0,)
>>> hdr1.set_data_shape((1,2,3)) # now with some content
>>> hdr1.get_data_shape()
(1, 2, 3)

We can set the binary block directly via this initialization. Here we get it from the header we have just made

>>> binblock2 = hdr1.binaryblock
>>> hdr2 = AnalyzeHeader(binblock2)
>>> hdr2.get_data_shape()
(1, 2, 3)

Empty headers are native endian by default

>>> hdr2.endianness == native_code
True

You can pass valid opposite endian headers with the endianness parameter. Even empty headers can have endianness

>>> hdr3 = AnalyzeHeader(endianness=swapped_code)
>>> hdr3.endianness == swapped_code
True

If you do not pass an endianness, and you pass some data, we will try to guess from the passed data.

>>> binblock3 = hdr3.binaryblock
>>> hdr4 = AnalyzeHeader(binblock3)
>>> hdr4.endianness == swapped_code
True
__init__(binaryblock=None, endianness=None, check=True)

Initialize header from binary data block

Parameters
binaryblock{None, string} optional

binary block to set into header. By default, None, in which case we insert the default empty header block

endianness{None, ‘<’,’>’, other endian code} string, optional

endianness of the binaryblock. If None, guess endianness from the data.

checkbool, optional

Whether to check content of header in initialization. Default is True.

Examples

>>> hdr1 = AnalyzeHeader() # an empty header
>>> hdr1.endianness == native_code
True
>>> hdr1.get_data_shape()
(0,)
>>> hdr1.set_data_shape((1,2,3)) # now with some content
>>> hdr1.get_data_shape()
(1, 2, 3)

We can set the binary block directly via this initialization. Here we get it from the header we have just made

>>> binblock2 = hdr1.binaryblock
>>> hdr2 = AnalyzeHeader(binblock2)
>>> hdr2.get_data_shape()
(1, 2, 3)

Empty headers are native endian by default

>>> hdr2.endianness == native_code
True

You can pass valid opposite endian headers with the endianness parameter. Even empty headers can have endianness

>>> hdr3 = AnalyzeHeader(endianness=swapped_code)
>>> hdr3.endianness == swapped_code
True

If you do not pass an endianness, and you pass some data, we will try to guess from the passed data.

>>> binblock3 = hdr3.binaryblock
>>> hdr4 = AnalyzeHeader(binblock3)
>>> hdr4.endianness == swapped_code
True
get_slope_inter()

Get data scaling (slope) and intercept from header data

Uses the algorithm from SPM2 spm_vol_ana.m by John Ashburner

Parameters
selfheader

Mapping with fields: * scl_slope - slope * scl_inter - possible intercept (SPM2 use - shared by nifti) * glmax - the (recorded) maximum value in the data (unscaled) * glmin - recorded minimum unscaled value * cal_max - the calibrated (scaled) maximum value in the dataset * cal_min - ditto minimum value

Returns
scl_slopeNone or float

slope. None if there is no valid scaling from these fields

scl_interNone or float

intercept. Also None if there is no valid slope, intercept

Examples

>>> fields = {'scl_slope': 1, 'scl_inter': 0, 'glmax': 0, 'glmin': 0,
...           'cal_max': 0, 'cal_min': 0}
>>> hdr = Spm2AnalyzeHeader()
>>> for key, value in fields.items():
...     hdr[key] = value
>>> hdr.get_slope_inter()
(1.0, 0.0)
>>> hdr['scl_inter'] = 0.5
>>> hdr.get_slope_inter()
(1.0, 0.5)
>>> hdr['scl_inter'] = np.nan
>>> hdr.get_slope_inter()
(1.0, 0.0)

If ‘scl_slope’ is 0, nan or inf, cannot use ‘scl_slope’. Without valid information in the gl / cal fields, we cannot get scaling, and return None

>>> hdr['scl_slope'] = 0
>>> hdr.get_slope_inter()
(None, None)
>>> hdr['scl_slope'] = np.nan
>>> hdr.get_slope_inter()
(None, None)

Valid information in the gl AND cal fields are needed

>>> hdr['cal_max'] = 0.8
>>> hdr['cal_min'] = 0.2
>>> hdr.get_slope_inter()
(None, None)
>>> hdr['glmax'] = 110
>>> hdr['glmin'] = 10
>>> np.allclose(hdr.get_slope_inter(), [0.6/100, 0.2-0.6/100*10])
True
classmethod may_contain_header(binaryblock)
template_dtype = dtype([('sizeof_hdr', '<i4'), ('data_type', 'S10'), ('db_name', 'S18'), ('extents', '<i4'), ('session_error', '<i2'), ('regular', 'S1'), ('hkey_un0', 'S1'), ('dim', '<i2', (8,)), ('vox_units', 'S4'), ('cal_units', 'S8'), ('unused1', '<i2'), ('datatype', '<i2'), ('bitpix', '<i2'), ('dim_un0', '<i2'), ('pixdim', '<f4', (8,)), ('vox_offset', '<f4'), ('scl_slope', '<f4'), ('scl_inter', '<f4'), ('funused3', '<f4'), ('cal_max', '<f4'), ('cal_min', '<f4'), ('compressed', '<i4'), ('verified', '<i4'), ('glmax', '<i4'), ('glmin', '<i4'), ('descrip', 'S80'), ('aux_file', 'S24'), ('orient', 'S1'), ('origin', '<i2', (5,)), ('generated', 'S10'), ('scannum', 'S10'), ('patient_id', 'S10'), ('exp_date', 'S10'), ('exp_time', 'S10'), ('hist_un0', 'S3'), ('views', '<i4'), ('vols_added', '<i4'), ('start_field', '<i4'), ('field_skip', '<i4'), ('omax', '<i4'), ('omin', '<i4'), ('smax', '<i4'), ('smin', '<i4')])

Spm2AnalyzeImage

class nibabel.spm2analyze.Spm2AnalyzeImage(dataobj, affine, header=None, extra=None, file_map=None)

Bases: nibabel.spm99analyze.Spm99AnalyzeImage

Class for SPM2 variant of basic Analyze image

Initialize image

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

Parameters
dataobjobject

Object containg image data. It should be some object that retuns an array from np.asanyarray. It should have a shape attribute or property

affineNone or (4,4) array-like

homogenous affine giving relationship between voxel coordinates and world coordinates. Affine can also be None. In this case, obj.affine also returns None, and the affine as written to disk will depend on the file format.

headerNone or mapping or header instance, optional

metadata for this image format

extraNone or mapping, optional

metadata to associate with image that cannot be stored in the metadata of this image type

file_mapmapping, optional

mapping giving file information for this image format

__init__(dataobj, affine, header=None, extra=None, file_map=None)

Initialize image

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

Parameters
dataobjobject

Object containg image data. It should be some object that retuns an array from np.asanyarray. It should have a shape attribute or property

affineNone or (4,4) array-like

homogenous affine giving relationship between voxel coordinates and world coordinates. Affine can also be None. In this case, obj.affine also returns None, and the affine as written to disk will depend on the file format.

headerNone or mapping or header instance, optional

metadata for this image format

extraNone or mapping, optional

metadata to associate with image that cannot be stored in the metadata of this image type

file_mapmapping, optional

mapping giving file information for this image format

header_class

alias of Spm2AnalyzeHeader