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#!/usr/bin/env python
#
# atlases.py - API which provides access to the atlas image files contained
# in $FSLDIR/data/atlases/
#
# Author: Paul McCarthy <pauldmccarthy@gmail.com>
#
"""This module provides access to FSL atlas images, typically contained in
``$FSLDIR/data/atlases/``. The :class:`AtlasRegistry` class provides access
to these atlases, and allows the user to load atlases stored in other
locations. A single :class:`.AtlasRegistry` instance is created when this
module is first imported - it is available as a module level attribute called
:attr:`registry`, and some of its methods are available as module-level
functions:
.. autosummary::
:nosignatures:
getAtlasDescription
loadAtlas
addAtlas
You must call the :meth:`.AtlasRegistry.rescanAtlases` function before any of
the other functions will work. The :func:`loadAtlas` function allows you to
load an atlas image, which will be one of the following atlas-specific
:class:`.Image` sub-classes:
.. autosummary::
:nosignatures:
LabelAtlas
StatisticAtlas
ProbabilisticAtlas
"""
from __future__ import division
import xml.etree.ElementTree as et
import os.path as op
import glob
import bisect
import logging
import numpy as np
import fsl.data.image as fslimage
import fsl.data.constants as constants
from fsl.utils.platform import platform
import fsl.utils.image.resample as resample
import fsl.transform.affine as affine
import fsl.utils.notifier as notifier
import fsl.utils.settings as fslsettings
import fsl.utils.deprecated as deprecated
log = logging.getLogger(__name__)
class AtlasRegistry(notifier.Notifier):
"""The ``AtlasRegistry`` maintains a list of all known atlases.
When the :meth:`rescanAtlases` method is called, the ``AtlasRegistry``
loads all of the FSL XML atlas specification files in
``$FSLDIR/data/atlases``, and builds a list of :class:`AtlasDescription`
instances, each of which contains information about one atlas.
The :meth:`addAtlas` method allows other atlases to be added to the
registry. Whenever a new atlas is added, the ``AtlasRegistry`` notifies
any registered listeners via the :class:`.Notifier` interface with the
topic ``'add'``, passing it the newly loaded class:`AtlasDecsription`.
Similarly, the :meth:`removeAtlas` method allows individual atlases to be
removed. When this occurs, registered listeners on the ``'remove'`` topic
are notified, and passed the ``AtlasDescription`` instance of the removed
atlas.
The ``AtlasRegistry`` stores a list of all known atlases via the
:mod:`.settings` module. When an ``AtlasRegistry`` is created, it loads
in any previously known atlases. Whenever a new atlas is added, this
list is updated. See the :meth:`__getKnownAtlases` and
:meth:`_saveKnownAtlases` methods.
"""
def __init__(self):
"""Create an ``AtlasRegistry``. """
# instances in existence, sorted
# by AtlasDescription.name.
def rescanAtlases(self):
"""Causes the ``AtlasRegistry`` to rescan available atlases from
``$FSLDIR``. Atlases are loaded from the ``fsl.data.atlases`` setting
(via the :mod:`.settings` module), and from ``$FSLDIR/data/atlases/``.
"""
log.debug('Initialising atlas registry')
self.__atlasDescs = []
# Get $FSLDIR atlases
if platform.fsldir is not None:
fsldir = op.join(platform.fsldir, 'data', 'atlases')
fslPaths = sorted(glob.glob(op.join(fsldir, '*.xml')))
# Any extra atlases that have
# been loaded in the past
extraIDs, extraPaths = self.__getKnownAtlases()
# FSLDIR atlases first, any
# other atlases second.
atlasPaths = list(fslPaths) + extraPaths
atlasIDs = [None] * len(fslPaths) + extraIDs
with self.skipAll():
for atlasID, atlasPath in zip(atlasIDs, atlasPaths):
# The FSLDIR atlases are probably
# listed twice - from the above glob,
# and from the saved extraPaths. So
# we remove any duplicates.
if atlasID is not None and self.hasAtlas(atlasID):
continue
try:
self.addAtlas(atlasPath, atlasID, save=False)
log.warning('Failed to load atlas '
'specification {}'.format(atlasPath),
exc_info=True)
def listAtlases(self):
"""Returns a list containing :class:`AtlasDescription` objects for
all available atlases. The atlases are ordered in terms of the
``AtlasDescription.name`` attribute (converted to lower case).
"""
return list(self.__atlasDescs)
def hasAtlas(self, atlasID):
"""Returns ``True`` if this ``AtlasRegistry`` has an atlas with the
specified ``atlasID``.
"""
return atlasID in [d.atlasID for d in self.__atlasDescs]
def getAtlasDescription(self, atlasID):
"""Returns an :class:`AtlasDescription` instance describing the
atlas with the given ``atlasID``.
"""
for desc in self.__atlasDescs:
if desc.atlasID == atlasID:
return desc
raise KeyError('Unknown atlas ID: {}'.format(atlasID))
def loadAtlas(self, atlasID, loadSummary=False, resolution=None, **kwargs):
"""Loads and returns an :class:`Atlas` instance for the atlas
with the given ``atlasID``.
:arg loadSummary: If ``True``, a 3D :class:`LabelAtlas` image is
loaded. Otherwise, if the atlas is probabilistic,
a 4D :class:`ProbabilisticAtlas` image is loaded.
:arg resolution: Optional. Desired isotropic atlas resolution in
millimetres, e.g. ``1.0`` or ``2.0``. The available
atlas with the nearest resolution to this value
will be returned. If not provided, the highest
resolution atlas will be loaded.
"""
# label atlases are only
# available in 'summary' form
if atlasDesc.atlasType == 'label':
loadSummary = True
if loadSummary: atype = LabelAtlas
else: atype = ProbabilisticAtlas
return atype(atlasDesc, resolution, **kwargs)
def addAtlas(self, filename, atlasID=None, save=True):
"""Add an atlas from the given XML specification file to the registry.
:arg filename: Path to a FSL XML atlas specification file.
:arg atlasID: ID to give this atlas. If not provided, the file
base name (converted to lower-case) is used. If an
atlas with the given ID already exists, this new atlas
is given a unique id.
:arg save: If ``True`` (the default), this atlas will be saved
so that it will be available in future instantiations.
"""
filename = op.abspath(filename)
if atlasID is None:
atlasIDBase = op.splitext(op.basename(filename))[0].lower()
atlasID = atlasIDBase
else:
atlasIDBase = atlasID
# If an atlas with the same ID/path
# already exists, raise an error
if self.hasAtlas(atlasID):
raise KeyError('An atlas with ID "{}" already '
'exists'.format(atlasID))
desc = AtlasDescription(filename, atlasID)
log.debug('Adding atlas to registry: {} / {}'.format(
desc.atlasID,
desc.specPath))
return desc
def removeAtlas(self, atlasID):
"""Removes the atlas with the specified ``atlasID`` from this
``AtlasRegistry``.
"""
for i, desc in enumerate(self.__atlasDescs):
if desc.atlasID == atlasID:
log.debug('Removing atlas from registry: {} / {}'.format(
desc.atlasID,
desc.specPath))
if remove is not None:
self.notify(topic='remove', value=remove)
def __getKnownAtlases(self):
"""Returns a list of tuples containing the IDs and paths of all known
atlases .
The atlases are retrieved via the :mod:`.settings` module - a setting
with the name ``fsl.data.atlases`` is assumed to contain a string of
``atlasID=specPath`` pairs, separated with the operating system file
path separator (``:`` on Unix/Linux).
See also :meth:`__saveKnownAtlases`.
"""
try:
if atlases is None: atlases = []
else: atlases = atlases.split(op.pathsep)
atlases = [e.split('=') for e in atlases]
atlases = [(name.strip(), path.strip())
for name, path in atlases
if op.exists(path)]
names = [e[0] for e in atlases]
paths = [e[1] for e in atlases]
return names, paths
return [], []
def __saveKnownAtlases(self):
"""Saves the IDs and paths of all atlases which are currently in
the registry. The atlases are saved via the :mod:`.settings` module.
"""
if self.__atlasDescs is None:
return
for desc in self.__atlasDescs:
atlases.append((desc.atlasID, desc.specPath))
atlases = ['{}={}'.format(name, path) for name, path in atlases]
atlases = op.pathsep.join(atlases)
class AtlasLabel(object):
"""The ``AtlasLabel`` class is used by the :class:`AtlasDescription` class
as a container object used for storing atlas label information.
An ``AtlasLabel`` instance contains the following attributes:
========= ================================================================
``name`` Region name
``index`` The index of this label into the list of all labels in the
``AtlasDescription`` that owns it. For statistic/probabilistic
atlases, this is also the index into the 4D atlas image of the
volume that corresponds to this region.
``value`` For label atlases and summary images, the value of voxels that
are in this region.
``x`` X coordinate of the region in world space
``y`` Y coordinate of the region in world space
``z`` Z coordinate of the region in world space
========= ================================================================
.. note:: The ``x``, ``y`` and ``z`` label coordinates are pre-calculated
centre-of-gravity coordinates, as listed in the atlas xml file.
They are in the coordinate system defined by the transformation
matrix for the first image in the ``images`` list of the atlas
XML file (typically MNI152 space).
"""
def __init__(self, name, index, value, x, y, z):
self.name = name
self.index = index
self.value = value
self.x = x
self.y = y
self.z = z
def __eq__(self, other):
"""Compares the ``index`` of this ``AtlasLabel`` with another.
"""
return self.index == other.index
def __neq__(self, other):
"""Compares the ``index`` of this ``AtlasLabel`` with another.
"""
return self.index != other.index
def __lt__(self, other):
"""Compares this ``AtlasLabel`` with another by their ``index``
attribute.
"""
return self.index < other.index
def __repr__(self):
"""
Represents AtlasLabel as string
"""
return '{}({}, index={}, value={})'.format(
self.__class__.__name__, self.name,
self.index, self.value,
)
class AtlasDescription(object):
"""An ``AtlasDescription`` instance parses and stores the information
stored in the FSL XML file that describes a single FSL atlas. An XML
atlas specification file is assumed to have a structure that looks like
the following:
.. code-block:: xml
<atlas>
<header>
<name></name> # Atlas name
<type></type> # 'Statistic', 'Probabilistic' or 'Label'
<statistic></statistic> # Optional. Type of statistic
<units></units> # Optional. Units of measurement
<precision></precision> # Optional. Decimal precision to report
<upper></upper> # Optional. Upper threshold
<lower></lower> # Optional. Lower threshold
<images>
<imagefile>
</imagefile> # If type is Probabilistic, path
# to 4D image file, one volume per
# label, Otherwise, if type is
# Label, path to 3D label file
# (identical to the summaryimagefile
# below). The path must be specified
# as relative to the location of this
# XML file.
<summaryimagefile> # Path to 3D label summary file,
</summaryimagefile> # Every <image> must be accompanied
# by a <summaryimage> - for label
# atlases, they will typically refer
# to the same image file.
</images>
... # More images - generally both
# 1mm and 2mm versions (in
# MNI152 space) are available
</header>
<data>
# index - For statistic/probabilistic atlases, index of corresponding
# volume in 4D image file. For label images, the value of
# voxels which are in the corresponding region. For
# statistic/probabilistic atlases, it is assumed that the
# value for each region in the summary image(s) are equal to
# ``index + 1``.
#
#
# x |
# y |- XYZ *voxel* coordinates into the first image of the <images>
# | list
# z |
<label index="0" x="0" y="0" z="0">Name</label>
...
</data>
</atlas>
Each ``AtlasDescription`` is assigned an identifier, which is simply the
XML file name describing the atlas, sans-suffix, and converted to lower
case. For exmaple, the atlas described by:
``$FSLDIR/data/atlases/HarvardOxford-Cortical.xml``
is given the identifier
``harvardoxford-cortical``
The following attributes are available on an ``AtlasDescription`` instance:
================= ======================================================
``atlasID`` The atlas ID, as described above.
``name`` Name of the atlas.
``specPath`` Path to the atlas XML specification file.
``atlasType`` Atlas type - either *statistic*, *probabilistic* or
*label*.
``statistic`` Type of statistic, for statistic atlases.
``units`` Unit of measurement, for statistic atlases.
``precision`` Reporting precision, for statistic atlases.
``upper`` Upper threshold, for statistic atlases.
``lower`` Lower threshold, for statistic atlases.
``images`` A list of images available for this atlas - usually
:math:`1mm^3` and :math:`2mm^3` images are present.
``summaryImages`` For probabilistic atlases, a list of *summary* images,
which are just 3D labelled variants of the atlas.
``pixdims`` A list of ``(x, y, z)`` pixdim tuples in mm, one for
each image in ``images``.
``xforms`` A list of affine transformation matrices (as ``4*4``
``numpy`` arrays), one for each image in ``images``,
defining the voxel to world coordinate transformations.
``labels`` A list of :class`AtlasLabel` objects, describing each
region / label in the atlas.
================= ======================================================
"""
def __init__(self, filename, atlasID=None):
"""Create an ``AtlasDescription`` instance.
:arg filename: Name of the XML file describing the atlas.
:arg atlasID: ID to use for this atlas. If not provided, the file
base name is used.
log.debug('Loading atlas description from {}'.format(filename))
root = et.parse(filename)
header = root.find('header')
data = root.find('data')
if atlasID is None:
atlasID = op.splitext(op.basename(filename))[0].lower()
self.atlasID = atlasID
self.specPath = op.abspath(filename)
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self.name = header.find('name').text.strip()
self.atlasType = header.find('type').text.strip().lower()
# Spelling error in some of the atlas.xml files.
if self.atlasType == 'probabalistic':
self.atlasType = 'probabilistic'
if self.atlasType == 'statistic':
fields = ['statistic', 'units', 'lower', 'upper', 'precision']
values = {}
for field in fields:
elem = header.find(field)
if elem is not None and elem.text is not None:
values[field] = elem.text.strip()
self.statistic = values.get('statistic', '')
self.units = values.get('units', '')
self.lower = float(values.get('lower', 0))
self.upper = float(values.get('upper', 100))
self.precision = int( values.get('precision', 2))
elif self.atlasType == 'probabilistic':
self.statistic = ''
self.units = '%'
self.lower = 5
self.upper = 100
self.precision = 0
images = header.findall('images')
self.images = []
self.summaryImages = []
self.pixdims = []
self.xforms = []
atlasDir = op.dirname(self.specPath)
for image in images:
# Every image must also have a summary image
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imagefile = image.find('imagefile') .text.strip()
summaryimagefile = image.find('summaryimagefile').text.strip()
# Assuming that the path
# names begin with a slash
imagefile = op.normpath(atlasDir + imagefile)
summaryimagefile = op.normpath(atlasDir + summaryimagefile)
i = fslimage.Image(imagefile, loadData=False, calcRange=False)
self.images .append(imagefile)
self.summaryImages.append(summaryimagefile)
self.pixdims .append(i.pixdim[:3])
self.xforms .append(i.voxToWorldMat)
labels = data.findall('label')
self.labels = []
# Refs to AtlasLabel objects
# indexed by their value.
# Used by the find method.
self.__labelsByValue = {}
# The xyz coordinates for each label are in terms
# of the voxel space of the first images element
# in the header. For convenience, we're going to
# transform all of these voxel coordinates into
# MNI152 space coordinates.
coords = np.zeros((len(labels), 3), dtype=np.float32)
for i, label in enumerate(labels):
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name = label.text.strip()
index = int( label.attrib['index'])
x = float(label.attrib['x'])
y = float(label.attrib['y'])
z = float(label.attrib['z'])
# For label images, the index field
# contains the region value
if self.atlasType == 'label':
value = index
index = i
# For probablistic images, the index
# field specifies the volume in the
# 4D atlas corresponding to the region.
# It is assumed that the summary value
# for each region is index + 1
else:
value = index + 1
al = AtlasLabel(name, index, value, x, y, z)
coords[i] = (x, y, z)
self.labels.append(al)
self.__labelsByValue[value] = al
# Load the appropriate transformation matrix
# and transform all those voxel coordinates
# into world coordinates
coords = affine.transform(coords, self.xforms[0])
# Update the coordinates
# in our label objects
for i, label in enumerate(self.labels):
label.x, label.y, label.z = coords[i]
# Make sure the labels are sorted by index
self.labels = list(sorted(self.labels))
def find(self, index=None, value=None, name=None):
"""Find an :class:`.AtlasLabel` either by ``index``, or by ``value``.
Exactly one of ``index``, ``value``, or ``name`` may be specified - a
``ValueError`` is raised otherwise. If an invalid ``index``, ``name``, or
``value`` is specified, an ``IndexError`` or ``KeyError`` will be
raised.
.. note:: A 4D ``ProbabilisticAtlas`` may have more volumes than
labels, and a 3D ``LabelAtlas`` may have more values
than labels.
"""
if ((index is not None) + (value is not None) + (name is not None)) != 1:
raise ValueError('Only one of index, value, or name may be specified')
if index is not None: return self.labels[ index]
elif value is not None: return self.__labelsByValue[int(value)]
else:
matches = [l for l in self.labels if l.name == name]
if len(matches) == 0:
# look for partial matches only if there are no full matches
matches = [l for l in self.labels if l.name[:len(name)] == name]
if len(matches) == 0:
raise IndexError('No match for {} found in labels {}'.format(
name, tuple(l.name for l in self.labels)
))
elif len(matches) > 1:
raise IndexError('Multiple matches for {} found in labels {}'.format(
name, tuple(l.name for l in self.labels)
))
return matches[0]
def __eq__(self, other):
"""Compares the ``atlasID`` of this ``AtlasDescription`` with another.
"""
return self.atlasID == other.atlasID
def __neq__(self, other):
"""Compares the ``atlasID`` of this ``AtlasDescription`` with another.
"""
return self.atlasID != other.atlasID
def __lt__(self, other):
"""Compares this ``AtlasDescription`` with another by their ``name``
attribute.
"""
return self.name.lower() < other.name.lower()
def __repr__(self, ):
"""
String representation of AtlasDescription
"""
return '{}({})'.format(self.__class__.__name__, self.atlasID)
class Atlas(fslimage.Image):
"""This is the base class for the :class:`LabelAtlas` and
:class:`ProbabilisticAtlas` classes. It contains some initialisation
logic common to both.
"""
def __init__(self,
atlasDesc,
resolution=None,
isLabel=False,
**kwargs):
"""Initialise an ``Atlas``.
:arg atlasDesc: The :class:`AtlasDescription` instance which
describes the atlas.
:arg resolution: Desired isotropic resolution in millimetres.
:arg isLabel: Pass in ``True`` for label atlases, ``False`` for
statistic/probabilistic atlases.
All other arguments are passed to :meth:`.Image.__init__`.
"""
# Get the index of the atlas with the
# nearest resolution to that provided.
# If a reslution has not been provided,
# choose the atlas image with the
# highest resolution.
#
# We divide by three to get the atlas
# image index because there are three
# pixdim values for each atlas.
res = resolution
reses = np.concatenate(atlasDesc.pixdims)
if resolution is None: imageIdx = np.argmin(reses)
else: imageIdx = np.argmin(np.abs(reses - res))
imageIdx = imageIdx // 3
if isLabel: imageFile = atlasDesc.summaryImages[imageIdx]
else: imageFile = atlasDesc.images[ imageIdx]
fslimage.Image.__init__(self, imageFile, **kwargs)
# Even though all the FSL atlases
# are in MNI152 space, not all of
# their sform_codes are correctly set
None, code=constants.NIFTI_XFORM_MNI_152)
self.desc = atlasDesc
def find(self, *args, **kwargs):
"""Find an ``AtlasLabel`` - see the :meth:`AtlasDescription.find`
method.
"""
return self.desc.find(*args, **kwargs)
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def prepareMask(self, mask):
"""Makes sure that the given mask has the same resolution as this
atlas, so it can be used for querying. Used by the
:meth:`.LabelAtlas.maskLabels` and
:meth:`.StatisticAtlas.maskValues` methods.
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:arg mask: A :class:`.Image`
:returns: A ``numpy`` array containing the resampled mask data.
:raises: A :exc:`MaskError` if the mask is not in the same space as
this atlas, or does not have three dimensions.
"""
# Make sure that the mask has the same
# number of voxels as the atlas image.
# Use nearest neighbour interpolation
# for resampling, as it is most likely
# that the mask is binary.
try:
mask, xform = resample.resample(
mask, self.shape[:3], dtype=np.float32, order=0)
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except ValueError:
raise MaskError('Mask has wrong number of dimensions')
# TODO allow non-aligned mask - as long as it overlaps
# in world coordinates, it should be allowed
if not fslimage.Image(mask, xform=xform).sameSpace(self):
raise MaskError('Mask is not in the same space as atlas')
return mask
class MaskError(Exception):
"""Exception raised by the :meth:`LabelAtlas.maskLabel` and
:meth:`StatisticAtlas.maskValues` when a mask is provided which
does not match the atlas space.
"""
class LabelAtlas(Atlas):
"""A 3D atlas which contains integer labels for each region.
The ``LabelAtlas`` class provides the :meth:`label` method, which
makes looking up the label at a location easy.
"""
def __init__(self, atlasDesc, resolution=None, **kwargs):
"""Create a ``LabelAtlas`` instance.
:arg atlasDesc: The :class:`AtlasDescription` instance describing
the atlas.
:arg resolution: Desired isotropic resolution in millimetres.
Atlas.__init__(self, atlasDesc, resolution, True, **kwargs)
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def label(self, location, *args, **kwargs):
"""Looks up and returns the label of the region at the given
location.
:arg location: Can be one of the following:
- A sequence of three values, interpreted as
atlas coordinates. In this case, :meth:`coordLabel`
is called.
- An :class:`.Image` which is interpreted as a
weighted mask. In this case, :meth:`maskLabel` is
called.
All other arguments are passed through to the :meth:`coordLabel` or
:meth:`maskLabel` methods.
:returns: The return value of either :meth:`coordLabel` or
:meth:`maskLabel`.
"""
if isinstance(location, fslimage.Image):
return self.maskLabel(location, *args, **kwargs)
else:
return self.coordLabel(location, *args, **kwargs)
def coordLabel(self, loc, voxel=False):
"""Looks up and returns the label at the given location.
:arg loc: A sequence of three values, interpreted as atlas
coordinates. In this case, :meth:`coordLabel` is called.
:arg voxel: Defaults to ``False``. If ``True``, the ``location``
is interpreted as voxel coordinates.
:returns: The label at the given coordinates, or ``None`` if the
coordinates are out of bounds.
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.. note:: Use the :meth:`find` method to retrieve the ``AtlasLabel``
associated with each returned value.
if not voxel:
loc = affine.transform([loc], self.worldToVoxMat)[0]
loc = [int(v) for v in loc.round()]
if loc[0] < 0 or \
loc[1] < 0 or \
loc[2] < 0 or \
loc[0] >= self.shape[0] or \
loc[1] >= self.shape[1] or \
loc[2] >= self.shape[2]:
return None
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return self[loc[0], loc[1], loc[2]]
def maskLabel(self, mask):
"""Looks up and returns the proportions of all regions that are present
in the given ``mask``.
:arg mask: A 3D :class:`.Image`` which is interpreted as a weighted
mask. If the ``mask`` shape does not match that of this
``LabelAtlas``, it is resampled using
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:meth:`.Image.resample`, with nearest-neighbour
interpolation.
:returns: A tuple containing:
- A sequence of all values which are present in the mask
- A sequence containing the proportion, within the mask,
of each present value. The proportions are returned as
values between 0 and 100.
.. note:: Use the :meth:`find` method to retrieve the ``AtlasLabel``
associated with each returned value.
"""
# Extract the values that are in
# the mask, and their corresponding
# mask weights
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mask = self.prepareMask(mask)
boolmask = mask > 0
vals = self[boolmask]
weights = mask[boolmask]
weightsum = weights.sum()
gotValues = np.unique(vals)
values = []
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# Only consider labels that
# this atlas is aware of
for label in self.desc.labels:
if label.value in gotValues:
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# Figure out the number of all voxels
# in the mask with this value, weighted
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# by the mask.
prop = weights[vals == label.value].sum()
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# Normalise it to be a proportion
# of all voxels in the mask. We
# multiply by 100 because the FSL
# probabilistic atlases store their
# probabilities as percentages.
values.append(label.value)
Paul McCarthy
committed
props .append(100 * prop / weightsum)
return values, props
def get(self, label=None, index=None, value=None, name=None, binary=True):
"""Returns the binary image for the given label.
Only one of the arguments should be used to define the label
:arg label: :class:`AtlasLabel` contained within this atlas
:arg index: index of the label
:arg value: value of the label
:arg name: string of the label
:arg binary: If ``True`` (the default), the image will contain 1s in
the label region. Otherwise the image will contain the
label value.
:return: :class:`.Image` with the mask
"""
if ((label is not None) + (index is not None) +
(value is not None) + (name is not None)) != 1:
raise ValueError('Only one of label, index, value, or name may be specified')
if label is None:
label = self.find(index=index, name=name, value=value)
elif label not in self.desc.labels:
raise ValueError("Unknown label provided")
arr = (self.data == label.value).astype(np.int32)
if not binary:
arr[arr > 0] = label.value
return fslimage.Image(arr, name=label.name, header=self.header)
class StatisticAtlas(Atlas):
"""A ``StatisticAtlas`` is a 4D image which contains one volume for
each region in the atlas; each volume contains some statistic value
for the corresponding region.
The :class:`ProbabilisticAtlas` is a specialisation of the
``StatisticAtlas``
def __init__(self, atlasDesc, resolution=None, **kwargs):
"""Create a ``StatisticAtlas`` instance.
:arg atlasDesc: The :class:`AtlasDescription` instance describing
the atlas.
:arg resolution: Desired isotropic resolution in millimetres.
"""
Atlas.__init__(self, atlasDesc, resolution, False, **kwargs)
def get(self, label=None, index=None, value=None, name=None):
"""Returns the statistic image at the given label.
Only one of the arguments should be used to define the label
:arg label: :class:`AtlasLabel` contained within this atlas
:arg index: index of the label
:arg value: value of the label
:arg name: string of the label
:return: :class:`.Image` with the statistic values for the
specified label.
"""
if ((label is not None) + (index is not None) +
(value is not None) + (name is not None)) != 1:
raise ValueError('Only one of label, index, value, or name may be specified')
if label is None:
label = self.find(index=index, value=value, name=name)
elif label not in self.desc.labels:
raise ValueError("Unknown label provided")
arr = self[..., label.index]
return fslimage.Image(arr, name=label.name, header=self.header)
def values(self, location, *args, **kwargs):
"""Looks up and returns the values of of all regions at the given
location.
:arg location: Can be one of the following: