# Copyright (c) 2015, Ecole Polytechnique Federale de Lausanne, Blue Brain Project
# All rights reserved.
#
# 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 = fst.get('segment_lengths', nrn, neurite_type=neurom.APICAL_DENDRITE)
>>> ax_sec_len = fst.get('section_lengths', nrn, neurite_type=neurom.AXON)
'''
import numpy as _np
from . import _neuritefunc as _nrt
from . import _neuronfunc as _nrn
from ._core import FstNeuron
from ..core import NeuriteType as _ntype
from ..core import iter_neurites as _ineurites
from ..core.types import tree_type_checker as _is_type
from ..exceptions import NeuroMError
NEURITEFEATURES = {
'total_length': _nrt.total_length,
'total_length_per_neurite': _nrt.total_length_per_neurite,
'neurite_lengths': _nrt.total_length_per_neurite,
'terminal_path_lengths_per_neurite': _nrt.terminal_path_lengths_per_neurite,
'section_lengths': _nrt.section_lengths,
'section_term_lengths': _nrt.section_term_lengths,
'section_bif_lengths': _nrt.section_bif_lengths,
'neurite_volumes': _nrt.total_volume_per_neurite,
'neurite_volume_density': _nrt.neurite_volume_density,
'section_volumes': _nrt.section_volumes,
'section_areas': _nrt.section_areas,
'section_tortuosity': _nrt.section_tortuosity,
'section_path_distances': _nrt.section_path_lengths,
'number_of_sections': _nrt.number_of_sections,
'number_of_sections_per_neurite': _nrt.number_of_sections_per_neurite,
'number_of_neurites': _nrt.number_of_neurites,
'number_of_bifurcations': _nrt.number_of_bifurcations,
'number_of_forking_points': _nrt.number_of_forking_points,
'number_of_terminations': _nrt.number_of_terminations,
'section_branch_orders': _nrt.section_branch_orders,
'section_term_branch_orders': _nrt.section_term_branch_orders,
'section_bif_branch_orders': _nrt.section_bif_branch_orders,
'section_radial_distances': _nrt.section_radial_distances,
'local_bifurcation_angles': _nrt.local_bifurcation_angles,
'remote_bifurcation_angles': _nrt.remote_bifurcation_angles,
'partition': _nrt.bifurcation_partitions,
'partition_asymmetry': _nrt.partition_asymmetries,
'number_of_segments': _nrt.number_of_segments,
'segment_lengths': _nrt.segment_lengths,
'segment_volumes': _nrt.segment_volumes,
'segment_radii': _nrt.segment_radii,
'segment_midpoints': _nrt.segment_midpoints,
'segment_taper_rates': _nrt.segment_taper_rates,
'segment_radial_distances': _nrt.segment_radial_distances,
'segment_meander_angles': _nrt.segment_meander_angles,
'principal_direction_extents': _nrt.principal_direction_extents
}
NEURONFEATURES = {
'soma_radii': _nrn.soma_radii,
'soma_surface_areas': _nrn.soma_surface_areas,
'trunk_origin_radii': _nrn.trunk_origin_radii,
'trunk_origin_azimuths': _nrn.trunk_origin_azimuths,
'trunk_origin_elevations': _nrn.trunk_origin_elevations,
'trunk_section_lengths': _nrn.trunk_section_lengths,
}
[docs]def register_neurite_feature(name, func):
'''Register a feature to be applied to neurites
Parameters:
name: name of the feature, used for access via get() function.
func: single parameter function of a neurite.
'''
if name in NEURITEFEATURES:
raise NeuroMError('Attempt to hide registered feature %s', name)
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)))
NEURONFEATURES[name] = _fun
[docs]def get(feature, obj, **kwargs):
'''Obtain a feature from a set of morphology objects
Parameters:
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 or 2D numpy array.
'''
feature = (NEURITEFEATURES[feature] if feature in NEURITEFEATURES
else NEURONFEATURES[feature])
return _np.array(list(feature(obj, **kwargs)))
_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)
get.__doc__ += _indent('\nFeatures:\n', 1) + _indent(_get_doc(), 2) # pylint: disable=no-member