# 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)

'''

from functools import partial
import numpy as _np

from . import _neuritefunc as _nrt
from . import _neuronfunc as _nrn
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
from ._core import FstNeuron

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,
    'section_bif_radial_distances': _nrt.section_bif_radial_distances,
    'section_term_radial_distances': _nrt.section_term_radial_distances,
    'section_end_distances': _nrt.section_end_distances,
    'section_strahler_orders': _nrt.section_strahler_orders,
    'local_bifurcation_angles': _nrt.local_bifurcation_angles,
    'remote_bifurcation_angles': _nrt.remote_bifurcation_angles,
    'partition': _nrt.bifurcation_partitions,
    'partition_asymmetry': _nrt.partition_asymmetries,
    'partition_pairs': _nrt.partition_pairs,
    'partition_asymmetry_length': partial(_nrt.partition_asymmetries, variant='length'),
    'sibling_ratio': _nrt.sibling_ratios,
    'diameter_power_relation': _nrt.diameter_power_relations,
    'number_of_segments': _nrt.number_of_segments,
    'segment_lengths': _nrt.segment_lengths,
    'segment_areas': _nrt.segment_areas,
    'segment_volumes': _nrt.segment_volumes,
    'segment_radii': _nrt.segment_radii,
    'segment_midpoints': _nrt.segment_midpoints,
    'segment_taper_rates': _nrt.segment_taper_rates,
    'segment_path_lengths': _nrt.segment_path_lengths,
    'section_taper_rates': _nrt.section_taper_rates,
    'segment_radial_distances': _nrt.segment_radial_distances,
    'segment_meander_angles': _nrt.segment_meander_angles,
    'principal_direction_extents': _nrt.principal_direction_extents,
    'total_area_per_neurite': _nrt.total_area_per_neurite,
}

NEURONFEATURES = {
    'soma_radii': _nrn.soma_radii,
    'soma_surface_areas': _nrn.soma_surface_areas,
    'soma_volumes': _nrn.soma_volumes,
    '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,
    'trunk_angles': _nrn.trunk_angles,
    'trunk_vectors': _nrn.trunk_vectors,
    'sholl_frequency': _nrn.sholl_frequency,
}


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


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
