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from __future__ import division, print_function, absolute_import
import re
import operator as op
from six import iteritems, string_types
import functools
import numpy as np
from .simple_tree import SimpleTree
[docs]class StructureTree( SimpleTree ):
def __init__(self, nodes):
'''A tree whose nodes are brain structures and whose edges indicate
physical containment.
Parameters
----------
nodes : list of dict
Each specifies a structure. Fields are:
'acronym' : str
Abbreviated name for the structure.
'rgb_triplet' : str
Canonical RGB uint8 color assigned to this structure
'graph_id' : int
Specifies the structure graph containing this structure.
'graph_order' : int
Canonical position in the flattened structure graph.
'id': int
Unique structure specifier.
'name' : str
Full name of structure.
'structure_id_path' : list of int
This structure's ancestors (inclusive) from the root of the
tree.
'structure_set_ids' : list of int
Unique identifiers of structure sets to which this structure
belongs.
'''
super(StructureTree, self).__init__(nodes,
lambda s: int(s['id']),
lambda s: s['structure_id_path'][-2] \
if len(s['structure_id_path']) > 1 \
and s['structure_id_path'] is not None \
and np.isfinite(s['structure_id_path'][-2]) \
else None)
[docs] def get_structures_by_id(self, structure_ids):
'''Obtain a list of brain structures from their structure ids
Parameters
----------
structure_ids : list of int
Get structures corresponding to these ids.
Returns
-------
list of dict :
Each item describes a structure.
'''
return self.nodes(structure_ids)
[docs] def get_structures_by_name(self, names):
'''Obtain a list of brain structures from their names,
Parameters
----------
names : list of str
Get structures corresponding to these names.
Returns
-------
list of dict :
Each item describes a structure.
'''
return self.nodes_by_property('name', names)
[docs] def get_structures_by_acronym(self, acronyms):
'''Obtain a list of brain structures from their acronyms
Parameters
----------
names : list of str
Get structures corresponding to these acronyms.
Returns
-------
list of dict :
Each item describes a structure.
'''
return self.nodes_by_property('acronym', acronyms)
[docs] def get_structures_by_set_id(self, structure_set_ids):
'''Obtain a list of brain structures from by the sets that contain
them.
Parameters
----------
structure_set_ids : list of int
Get structures belonging to these structure sets.
Returns
-------
list of dict :
Each item describes a structure.
'''
overlap = lambda x: (set(structure_set_ids) & set(x['structure_set_ids']))
return self.filter_nodes(overlap)
[docs] def get_colormap(self):
'''Get a dictionary mapping structure ids to colors across all nodes.
Returns
-------
dict :
Keys are structure ids. Values are RGB lists of integers.
'''
return self.value_map(lambda x: x['id'],
lambda y: y['rgb_triplet'])
[docs] def get_name_map(self):
'''Get a dictionary mapping structure ids to names across all nodes.
Returns
-------
dict :
Keys are structure ids. Values are structure name strings.
'''
return self.value_map(lambda x: x['id'],
lambda y: y['name'])
[docs] def get_id_acronym_map(self):
'''Get a dictionary mapping structure acronyms to ids across all nodes.
Returns
-------
dict :
Keys are structure acronyms. Values are structure ids.
'''
return self.value_map(lambda x: x['acronym'],
lambda y: y['id'])
[docs] def get_ancestor_id_map(self):
'''Get a dictionary mapping structure ids to ancestor ids across all
nodes.
Returns
-------
dict :
Keys are structure ids. Values are lists of ancestor ids.
'''
return self.value_map(lambda x: x['id'],
lambda y: self.ancestor_ids([y['id']])[0])
[docs] def structure_descends_from(self, child_id, parent_id):
'''Tests whether one structure descends from another.
Parameters
----------
child_id : int
Id of the putative child structure.
parent_id : int
Id of the putative parent structure.
Returns
-------
bool :
True if the structure specified by child_id is a descendant of
the one specified by parent_id. Otherwise False.
'''
return parent_id in self.ancestor_ids([child_id])[0]
[docs] def get_structure_sets(self):
'''Lists all unique structure sets that are assigned to at least one
structure in the tree.
Returns
-------
list of int :
Elements are ids of structure sets.
'''
return set(functools.reduce(op.add, map(lambda x: x['structure_set_ids'],
self.nodes())))
[docs] def has_overlaps(self, structure_ids):
'''Determine if a list of structures contains structures along with
their ancestors
Parameters
----------
structure_ids : list of int
Check this set of structures for overlaps
Returns
-------
set :
Ids of structures that are the ancestors of other structures in
the supplied set.
'''
ancestor_ids = functools.reduce(op.add,
map(lambda x: x[1:],
self.ancestor_ids(structure_ids)))
return (set(ancestor_ids) & set(structure_ids))
[docs] @staticmethod
def clean_structures(structures, whitelist=None, data_transforms=None, renames=None):
'''Convert structures_with_sets query results into a form that can be
used to construct a StructureTree
Parameters
----------
structures : list of dict
Each element describes a structure. Should have a structure id path
field (str values) and a structure_sets field (list of dict).
whitelist : list of str, optional
Only these fields will be included in the final structure record. Default is
the output of StructureTree.whitelist.
data_transforms : dict, optional
Keys are str field names. Values are functions which will be applied to the
data associated with those fields. Default is to map colors from hex to rgb and
convert the structure id path to a list of int.
renames : dict, optional
Controls the field names that appear in the output structure records. Default is
to map 'color_hex_triplet' to 'rgb_triplet'.
Returns
-------
list of dict :
structures, after conversion of structure_id_path and structure_sets
'''
if whitelist is None:
whitelist = StructureTree.whitelist()
if data_transforms is None:
data_transforms = StructureTree.data_transforms()
if renames is None:
renames = StructureTree.renames()
whitelist.extend(renames.values())
for ii, st in enumerate(structures):
StructureTree.collect_sets(st)
record = {}
for name in whitelist:
if name not in st:
continue
data = st[name]
if name in data_transforms:
data = data_transforms[name](data)
if name in renames:
name = renames[name]
record[name] = data
structures[ii] = record
return structures
[docs] @staticmethod
def renames():
return {'color_hex_triplet': 'rgb_triplet'}
[docs] @staticmethod
def whitelist():
return ['acronym', 'color_hex_triplet', 'graph_id', 'graph_order', 'id',
'name', 'structure_id_path', 'structure_set_ids']
[docs] @staticmethod
def hex_to_rgb(hex_color):
'''Convert a hexadecimal color string to a uint8 triplet
Parameters
----------
hex_color : string
Must be 6 characters long, unless it is 7 long and the first
character is #. If hex_color is a triplet of int, it will be
returned unchanged.
Returns
-------
list of int :
3 characters long - 1 per two characters in the input string.
'''
if not isinstance(hex_color, string_types):
return list(hex_color)
if hex_color[0] == '#':
hex_color = hex_color[1:]
return [int(hex_color[a * 2: a*2 + 2], 16) for a in range(3)]
[docs] @staticmethod
def path_to_list(path):
'''Structure id paths are sometimes formatted as "/"-seperated strings.
This method converts them to a list of integers, if needed.
'''
if not isinstance(path, string_types):
return list(path)
return [int(stid) for stid in path.split('/') if stid != '']
[docs] @staticmethod
def collect_sets(structure):
'''Structure sets may be specified by full records or id. This method
collects all of the structure set records/ids in a structure record and
replaces them with a single list of id records.
'''
if not 'structure_sets' in structure:
structure['structure_sets'] = []
if not 'structure_set_ids' in structure:
structure['structure_set_ids'] = []
structure['structure_set_ids'].extend([sts['id'] for sts
in structure['structure_sets']])
structure['structure_set_ids'] = list(set(structure['structure_set_ids']))
del structure['structure_sets']