# Copyright (c) 2020, Ecole Polytechnique Federale de Lausanne, Blue Brain Project
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#
# This file is part of NeuroM <https://github.com/BlueBrain/NeuroM>
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"""NeuroM, lightweight and fast.
Examples:
Obtain some morphometrics
>>> ap_seg_len = features.get('segment_lengths', nrn, neurite_type=neurom.APICAL_DENDRITE)
>>> ax_sec_len = features.get('section_lengths', nrn, neurite_type=neurom.AXON)
"""
import numpy as np
from neurom.core import NeuriteType as _ntype
from neurom.core import iter_neurites as _ineurites
from neurom.core.types import tree_type_checker as _is_type
from neurom.exceptions import NeuroMError
from neurom.utils import deprecated
NEURITEFEATURES = dict()
NEURONFEATURES = dict()
[docs]@deprecated(
'`register_neurite_feature`',
'Please use the decorator `neurom.features.register.feature` to register custom features')
def register_neurite_feature(name, func):
"""Register a feature to be applied to neurites.
.. warning:: This feature has been deprecated in 1.6.0
Arguments:
name: name of the feature, used for access via get() function.
func: single parameter function of a neurite.
"""
def _fun(neurites, neurite_type=_ntype.all):
"""Wrap neurite function from outer scope and map into list."""
return list(func(n) for n in _ineurites(neurites, filt=_is_type(neurite_type)))
_register_feature('NEURITEFEATURES', name, _fun, shape=(...,))
def _find_feature_func(feature_name):
"""Returns the python function used when getting a feature with `neurom.get(feature_name)`."""
for feature_dict in (NEURITEFEATURES, NEURONFEATURES):
if feature_name in feature_dict:
return feature_dict[feature_name]
raise NeuroMError(f'Unable to find feature: {feature_name}')
def _get_feature_value_and_func(feature_name, obj, **kwargs):
"""Obtain a feature from a set of morphology objects.
Arguments:
feature(string): feature to extract
obj: a neuron, population or neurite tree
kwargs: parameters to forward to underlying worker functions
Returns:
A tuple (feature, func) of the feature value and its function
"""
feat = _find_feature_func(feature_name)
res = feat(obj, **kwargs)
if len(feat.shape) != 0:
res = np.array(list(res))
return res, feat
[docs]def get(feature_name, obj, **kwargs):
"""Obtain a feature from a set of morphology objects.
Arguments:
feature(string): feature to extract
obj: a neuron, population or neurite tree
kwargs: parameters to forward to underlying worker functions
Returns:
features as a 1D, 2D or 3D numpy array.
"""
return _get_feature_value_and_func(feature_name, obj, **kwargs)[0]
_INDENT = ' ' * 4
def _indent(string, count):
"""Indent `string` by `count` * INDENT."""
indent = _INDENT * count
ret = indent + string.replace('\n', '\n' + indent)
return ret.rstrip()
def _get_doc():
"""Get a description of all the known available features."""
def get_docstring(func):
"""Extract doctstring, if possible."""
docstring = ':\n'
if func.__doc__:
docstring += _indent(func.__doc__, 2)
return docstring
ret = ['\nNeurite features (neurite, neuron, neuron population):']
ret.extend(_INDENT + '- ' + feature + get_docstring(func)
for feature, func in sorted(NEURITEFEATURES.items()))
ret.append('\nNeuron features (neuron, neuron population):')
ret.extend(_INDENT + '- ' + feature + get_docstring(func)
for feature, func in sorted(NEURONFEATURES.items()))
return '\n'.join(ret)
def _register_feature(namespace, name, func, shape):
"""Register a feature to be applied.
Upon registration, an attribute 'shape' containing the expected
shape of the function return is added to 'func'.
Arguments:
namespace(string): a namespace (must be 'NEURITEFEATURES' or 'NEURONFEATURES')
name(string): name of the feature, used to access the feature via `neurom.features.get()`.
func(callable): single parameter function of a neurite.
shape(tuple): the expected shape of the feature values
"""
setattr(func, 'shape', shape)
assert namespace in {'NEURITEFEATURES', 'NEURONFEATURES'}
feature_dict = globals()[namespace]
if name in feature_dict:
raise NeuroMError('Attempt to hide registered feature %s' % name)
feature_dict[name] = func
[docs]def feature(shape, namespace=None, name=None):
"""Feature decorator to automatically register the feature in the appropriate namespace.
Arguments:
shape(tuple): the expected shape of the feature values
namespace(string): a namespace (must be 'NEURITEFEATURES' or 'NEURONFEATURES')
name(string): name of the feature, used to access the feature via `neurom.features.get()`.
"""
def inner(func):
_register_feature(namespace, name or func.__name__, func, shape)
return func
return inner
# These imports are necessary in order to register the features
from neurom.features import neuritefunc, neuronfunc # noqa, pylint: disable=wrong-import-position
# This must be done after all features have been registered
get.__doc__ += _indent('\nFeatures:\n', 1) + _indent(_get_doc(), 2) # pylint: disable=no-member