def make_neurolex_graph():
# neurolex test stuff
nlxpref = {'ilx':'http://uri.interlex.org/base/'}
nlxpref.update(NIFPREFIXES)
neurolex = makeGraph('neurolex-temp', nlxpref)
neurolex.g.parse('/tmp/neurolex_basic.ttl', format='turtle')
ILXPO = 'ilx:partOf'
nj = neurolex.make_scigraph_json(ILXPO)
g_, h = creatTree(*Query('NIFGA:birnlex_796', ILXPO, 'INCOMING', 10), json=nj)
i_, j_ = creatTree(*Query('NIFGA:nlx_412', ILXPO, 'INCOMING', 10), json=nj)
brht = sorted(set(flatten(h[0],[])))
wmht = sorted(set(flatten(j_[0],[])))
ufixedrb = {'NIFGA:' + k.split(':')[1]:v for k, v in u_replaced_by.items()}
b_nlx_replaced_by = new_replaced_by(brht, ufixedrb)
w_nlx_replaced_by = new_replaced_by(wmht, ufixedrb)
additional_edges = defaultdict(list) # TODO this could be fun for the future but is a nightmare atm
for edge in h[-1]['edges'] + j_[-1]['edges']:
additional_edges[edge['sub']] = edge
additional_edges[edge['obj']] = edge
#filter out bad edges becase we are lazy
additional_edges = {k:v for k, v in additional_edges.items()
if k in b_nlx_replaced_by or k in w_nlx_replaced_by}
print('neurolex tree') # computed above
print(g_)
print(i_)
return additional_edges
def print_trees(graph, bridge):
PPO = 'ro:proper_part_of'
HPP = 'ro:has_proper_part'
hpp = HPP.replace('ro:', graph.namespaces['ro'])
ppo = PPO.replace('ro:', graph.namespaces['ro'])
a, b = creatTree(*Query(tc.red('birnlex_796'), HPP, 'OUTGOING', 10), # FIXME seems to be a last one wins bug here with birnlex_796 vs NIFGA:birnlex_796 depending on the has seed...
json=graph.make_scigraph_json(HPP))
c, d = creatTree(*Query('NIFGA:birnlex_796', hpp, 'OUTGOING', 10), graph=sgg)
j = bridge.make_scigraph_json(HPP) # issue https://github.com/RDFLib/rdflib/pull/661
e, f = creatTree(*Query('UBERON:0000955', HPP, 'OUTGOING', 10), json=j)
k_, l_ = creatTree(*Query('NIFGA:nlx_anat_101177', ppo, 'INCOMING', 10), graph=sgg)
merge = dict(d[-1]) # full tree with ppo converted to hpp
merge['nodes'].extend(l_[-1]['nodes'])
merge['edges'].extend([{'sub':e['obj'], 'pred':hpp, 'obj':e['sub']} for e in l_[-1]['edges']])
m_, n_ = creatTree(*Query('NIFGA:birnlex_796', hpp, 'OUTGOING', 10), json=merge)
print('nifga dep')
print(a)
print('nifga live')
print(c)
print('new bridge')
print(e)
print('nifga total (both directions)')
print(m_)
print('nifga white matter')
print(k_)
return a, b, c, d, e, f, k_, l_, m_, n_
def print_trees(graph, bridge):
PPO = 'ro:proper_part_of'
HPP = 'ro:has_proper_part'
hpp = HPP.replace('ro:', graph.namespaces['ro'])
ppo = PPO.replace('ro:', graph.namespaces['ro'])
a, b = creatTree(
*Query(
tc.red('birnlex_796'), HPP, 'OUTGOING', 10
), # FIXME seems to be a last one wins bug here with birnlex_796 vs NIFGA:birnlex_796 depending on the has seed...
json=graph.make_scigraph_json(HPP))
c, d = creatTree(*Query('NIFGA:birnlex_796', hpp, 'OUTGOING', 10),
graph=sgg)
j = bridge.make_scigraph_json(
HPP) # issue https://github.com/RDFLib/rdflib/pull/661
e, f = creatTree(*Query('UBERON:0000955', HPP, 'OUTGOING', 10), json=j)
k_, l_ = creatTree(*Query('NIFGA:nlx_anat_101177', ppo, 'INCOMING', 10),
graph=sgg)
merge = dict(d[-1]) # full tree with ppo converted to hpp
merge['nodes'].extend(l_[-1]['nodes'])
merge['edges'].extend([{
'sub': e['obj'],
'pred': hpp,
'obj': e['sub']
} for e in l_[-1]['edges']])
m_, n_ = creatTree(*Query('NIFGA:birnlex_796', hpp, 'OUTGOING', 10),
json=merge)
print('nifga dep')
print(a)
print('nifga live')
print(c)
print('new bridge')
print(e)
print('nifga total (both directions)')
print(m_)
print('nifga white matter')
print(k_)
return a, b, c, d, e, f, k_, l_, m_, n_
def make_neurolex_graph():
# neurolex test stuff
nlxpref = {'ilx': 'http://uri.interlex.org/base/'}
nlxpref.update(NIFPREFIXES)
neurolex = makeGraph('neurolex-temp', nlxpref)
neurolex.g.parse('/tmp/neurolex_basic.ttl', format='turtle')
ILXPO = 'ilx:partOf'
nj = neurolex.make_scigraph_json(ILXPO)
g_, h = creatTree(*Query('NIFGA:birnlex_796', ILXPO, 'INCOMING', 10),
json=nj)
i_, j_ = creatTree(*Query('NIFGA:nlx_412', ILXPO, 'INCOMING', 10), json=nj)
brht = sorted(set(flatten(h[0], [])))
wmht = sorted(set(flatten(j_[0], [])))
ufixedrb = {
'NIFGA:' + k.split(':')[1]: v
for k, v in u_replaced_by.items()
}
b_nlx_replaced_by = new_replaced_by(brht, ufixedrb)
w_nlx_replaced_by = new_replaced_by(wmht, ufixedrb)
additional_edges = defaultdict(
list) # TODO this could be fun for the future but is a nightmare atm
for edge in h[-1]['edges'] + j_[-1]['edges']:
additional_edges[edge['sub']] = edge
additional_edges[edge['obj']] = edge
#filter out bad edges becase we are lazy
additional_edges = {
k: v
for k, v in additional_edges.items()
if k in b_nlx_replaced_by or k in w_nlx_replaced_by
}
print('neurolex tree') # computed above
print(g_)
print(i_)
return additional_edges
def check_hierarchy(graph, root, edge, label_edge=None):
a, b = creatTree(*Query(root, edge, 'INCOMING', 10),
json=graph.make_scigraph_json(edge, label_edge))
print(a)
def swanson():
""" not really a parcellation scheme """
source = 'resources/swanson_aligned.txt'
ONT_PATH = GENERATED
filename = 'swanson_hierarchies'
ontid = ONT_PATH + filename + '.ttl'
PREFIXES = makePrefixes('', 'ilx', 'owl', 'skos', 'NIFRID', 'ILXREPLACE')
PREFIXES.update({
#'':ontid + '/', # looking for better options
'SWAN': interlex_namespace('swanson/nt/term'),
'SWAA': interlex_namespace('swanson/nt/appendix'),
})
new_graph = makeGraph(filename, PREFIXES, writeloc=WRITELOC)
new_graph.add_ont(
ontid, 'Swanson brain partomies', 'Swanson 2014 Partonomies',
'This file is automatically generated from ' + source + '.' + NOTICE,
TODAY)
# FIXME citations should really go on the ... anatomy? scheme artifact
definingCitation = 'Swanson, Larry W. Neuroanatomical Terminology: a lexicon of classical origins and historical foundations. Oxford University Press, USA, 2014.'
definingCitationID = 'ISBN:9780195340624'
new_graph.add_trip(ontid, 'NIFRID:definingCitation', definingCitation)
new_graph.add_trip(ontid, 'NIFRID:definingCitationID', definingCitationID)
with open(source, 'rt') as f:
lines = [l.strip() for l in f.readlines()]
# join header on page 794
lines[635] += ' ' + lines.pop(636)
#fix for capitalization since this header is reused
fixed = ' or '.join([
' ('.join([n.capitalize() for n in _.split(' (')])
for _ in lines[635].lower().split(' or ')
]).replace('human', 'HUMAN')
lines[635] = fixed
data = []
for l in lines:
if not l.startswith('#'):
level = l.count('.' * 5)
l = l.strip('.')
if ' (' in l:
if ') or' in l:
n1, l = l.split(') or')
area_name, citationP = n1.strip().split(' (')
citation = citationP.rstrip(')')
d = (level, area_name, citation, 'NEXT SYN')
data.append(d)
#print(tc.red(tc.bold(repr(d))))
area_name, citationP = l.strip().split(' (')
citation = citationP.rstrip(')')
else:
area_name = l
citation = None
d = (level, area_name, citation, None)
#print(d)
data.append(d)
results = async_getter(sgv.findByTerm, [(d[1], ) for d in data])
#results = [None] * len(data)
curies = [[r['curie'] for r in _ if 'UBERON' in r['curie']] if _ else []
for _ in results]
output = [_[0] if _ else None for _ in curies]
header = ['Depth', 'Name', 'Citation', 'NextSyn', 'Uberon']
zoop = [header] + [r for r in zip(*zip(*data), output)] + \
[(0, 'Appendix END None', None, None, None)] # needed to add last appendix
class SP(rowParse):
def __init__(self):
self.nodes = defaultdict(dict)
self._appendix = 0
self.appendicies = {}
self._last_at_level = {}
self.names = defaultdict(set)
self.children = defaultdict(set)
self.parents = defaultdict(set)
self.next_syn = False
super().__init__(zoop)
def Depth(self, value):
if self.next_syn:
self.synonym = self.next_syn
else:
self.synonym = False
self.depth = value
def Name(self, value):
self.name = value
def Citation(self, value):
self.citation = value
def NextSyn(self, value):
if value:
self.next_syn = self._rowind
else:
self.next_syn = False
def Uberon(self, value):
self.uberon = value
def _row_post(self):
# check if we are in the next appendix
# may want to xref ids between appendicies as well...
if self.depth == 0:
if self.name.startswith('Appendix'):
if self._appendix:
self.appendicies[self._appendix]['children'] = dict(
self.children)
self.appendicies[self._appendix]['parents'] = dict(
self.parents)
self._last_at_level = {}
self.children = defaultdict(set)
self.parents = defaultdict(set)
_, num, apname = self.name.split(' ', 2)
if num == 'END':
return
self._appendix = int(num)
self.appendicies[self._appendix] = {
'name':
apname.capitalize(),
'type':
self.citation.capitalize() if self.citation else None
}
return
else:
if ' [' in self.name:
name, taxonB = self.name.split(' [')
self.name = name
self.appendicies[self._appendix][
'taxon'] = taxonB.rstrip(']').capitalize()
else: # top level is animalia
self.appendicies[
self._appendix]['taxon'] = 'ANIMALIA'.capitalize()
self.name = self.name.capitalize()
self.citation = self.citation.capitalize()
# nodes
if self.synonym:
self.nodes[self.synonym]['synonym'] = self.name
self.nodes[self.synonym]['syn-cite'] = self.citation
self.nodes[self.synonym]['syn-uberon'] = self.uberon
return
else:
if self.citation: # Transverse Longitudinal etc all @ lvl4
self.names[self.name + ' ' + self.citation].add(
self._rowind)
else:
self.name += str(self._appendix) + self.nodes[
self._last_at_level[self.depth - 1]]['label']
#print(level, self.name)
# can't return here because they are their own level
# replace with actually doing something...
self.nodes[self._rowind]['label'] = self.name
self.nodes[self._rowind]['citation'] = self.citation
self.nodes[self._rowind]['uberon'] = self.uberon
# edges
self._last_at_level[self.depth] = self._rowind
# TODO will need something to deal with the Lateral/
if self.depth > 0:
try:
parent = self._last_at_level[self.depth - 1]
except:
embed()
self.children[parent].add(self._rowind)
self.parents[self._rowind].add(parent)
def _end(self):
replace = {}
for asdf in [
sorted(n) for k, n in self.names.items() if len(n) > 1
]:
replace_with, to_replace = asdf[0], asdf[1:]
for r in to_replace:
replace[r] = replace_with
for r, rw in replace.items():
#print(self.nodes[rw])
o = self.nodes.pop(r)
#print(o)
for vals in self.appendicies.values():
children = vals['children']
parents = vals['parents']
# need reversed so children are corrected before swap
for r, rw in reversed(sorted(replace.items())):
if r in parents:
child = r
new_child = rw
parent = parents.pop(child)
parents[new_child] = parent
parent = list(parent)[0]
children[parent].remove(child)
children[parent].add(new_child)
if r in children:
parent = r
new_parent = rw
childs = children.pop(parent)
children[new_parent] = childs
for child in childs:
parents[child] = {new_parent}
self.nodes = dict(self.nodes)
sp = SP()
tp = [
_ for _ in sorted([
'{: <50}'.format(n['label']) +
n['uberon'] if n['uberon'] else n['label']
for n in sp.nodes.values()
])
]
#print('\n'.join(tp))
#print(sp.appendicies[1].keys())
#print(sp.nodes[1].keys())
nbase = PREFIXES['SWAN'] + '%s'
json_ = {'nodes': [], 'edges': []}
parent = ILXREPLACE('swansonBrainRegionConcept')
for node, anns in sp.nodes.items():
nid = nbase % node
new_graph.add_class(nid, parent, label=anns['label'])
new_graph.add_trip(nid, 'NIFRID:definingCitation', anns['citation'])
json_['nodes'].append({'lbl': anns['label'], 'id': 'SWA:' + str(node)})
#if anns['uberon']:
#new_graph.add_trip(nid, owl.equivalentClass, anns['uberon']) # issues arrise here...
for appendix, data in sp.appendicies.items():
aid = PREFIXES['SWAA'] + str(appendix)
new_graph.add_class(aid, label=data['name'].capitalize())
new_graph.add_trip(
aid, 'ilx:hasTaxonRank',
data['taxon']) # FIXME appendix is the data artifact...
children = data['children']
ahp = HASPART + str(appendix)
apo = PARTOF + str(appendix)
new_graph.add_op(ahp, transitive=True)
new_graph.add_op(apo, inverse=ahp, transitive=True)
for parent, childs in children.items(
): # FIXME does this give complete coverage?
pid = nbase % parent
for child in childs:
cid = nbase % child
new_graph.add_hierarchy(
cid, ahp, pid) # note hierarhcy inverts direction
new_graph.add_hierarchy(pid, apo, cid)
json_['edges'].append({
'sub': 'SWA:' + str(child),
'pred': apo,
'obj': 'SWA:' + str(parent)
})
new_graph.write()
if False:
Query = namedtuple('Query',
['root', 'relationshipType', 'direction', 'depth'])
mapping = (1, 1, 1, 1, 30, 83, 69, 70, 74, 1) # should generate?
for i, n in enumerate(mapping):
a, b = creatTree(*Query('SWA:' + str(n), 'ilx:partOf' + str(i + 1),
'INCOMING', 10),
json=json_)
print(a)
return ontid, None
def check_hierarchy(graph, root, edge, label_edge=None):
a, b = creatTree(*Query(root, edge, 'INCOMING', 10), json=graph.make_scigraph_json(edge, label_edge))
print(a)
def swanson():
""" not really a parcellation scheme """
ONT_PATH = 'http://ontology.neuinfo.org/NIF/ttl/generated/'
filename = 'swanson_hierarchies'
ontid = ONT_PATH + filename + '.ttl'
PREFIXES = makePrefixes('ilx', 'owl', 'OBOANN', 'UBERON')
PREFIXES.update({
'':ontid + '/', # looking for better options
'SWAN':'http://swanson.org/node/',
'SWAA':'http://swanson.org/appendix/',
})
new_graph = makeGraph(filename, PREFIXES, writeloc='/tmp/parc/')
new_graph.add_ont(ontid,
'Swanson brain partomies',
'Swanson 2014 Partonomies',
'This file is automatically generated from....',
TODAY)
with open('resources/swanson_aligned.txt', 'rt') as f:
lines = [l.strip() for l in f.readlines()]
# join header on page 794
lines[635] += ' ' + lines.pop(636)
#fix for capitalization since this header is reused
fixed = ' or '.join([' ('.join([n.capitalize() for n in _.split(' (')]) for _ in lines[635].lower().split(' or ')]).replace('human','HUMAN')
lines[635] = fixed
data = []
for l in lines:
if not l.startswith('#'):
level = l.count('.'*5)
l = l.strip('.')
if ' (' in l:
if ') or' in l:
n1, l = l.split(') or')
area_name, citationP = n1.strip().split(' (')
citation = citationP.rstrip(')')
d = (level, area_name, citation, 'NEXT SYN')
data.append(d)
#print(tc.red(tc.bold(repr(d))))
area_name, citationP = l.strip().split(' (')
citation = citationP.rstrip(')')
else:
area_name = l
citation = None
d = (level, area_name, citation, None)
#print(d)
data.append(d)
results = async_getter(sgv.findByTerm, [(d[1],) for d in data])
#results = [None] * len(data)
curies = [[r['curie'] for r in _ if 'UBERON' in r['curie']] if _ else [] for _ in results]
output = [_[0] if _ else None for _ in curies]
header = ['Depth', 'Name', 'Citation', 'NextSyn', 'Uberon']
zoop = [header] + [r for r in zip(*zip(*data), output)] + \
[(0, 'Appendix END None', None, None, None)] # needed to add last appendix
class SP(rowParse):
def __init__(self):
self.nodes = defaultdict(dict)
self._appendix = 0
self.appendicies = {}
self._last_at_level = {}
self.names = defaultdict(set)
self.children = defaultdict(set)
self.parents = defaultdict(set)
self.next_syn = False
super().__init__(zoop)
def Depth(self, value):
if self.next_syn:
self.synonym = self.next_syn
else:
self.synonym = False
self.depth = value
def Name(self, value):
self.name = value
def Citation(self, value):
self.citation = value
def NextSyn(self, value):
if value:
self.next_syn = self._rowind
else:
self.next_syn = False
def Uberon(self, value):
self.uberon = value
def _row_post(self):
# check if we are in the next appendix
# may want to xref ids between appendicies as well...
if self.depth == 0:
if self.name.startswith('Appendix'):
if self._appendix:
self.appendicies[self._appendix]['children'] = dict(self.children)
self.appendicies[self._appendix]['parents'] = dict(self.parents)
self._last_at_level = {}
self.children = defaultdict(set)
self.parents = defaultdict(set)
_, num, apname = self.name.split(' ', 2)
if num == 'END':
return
self._appendix = int(num)
self.appendicies[self._appendix] = {
'name':apname.capitalize(),
'type':self.citation.capitalize() if self.citation else None}
return
else:
if ' [' in self.name:
name, taxonB = self.name.split(' [')
self.name = name
self.appendicies[self._appendix]['taxon'] = taxonB.rstrip(']').capitalize()
else: # top level is animalia
self.appendicies[self._appendix]['taxon'] = 'ANIMALIA'.capitalize()
self.name = self.name.capitalize()
self.citation = self.citation.capitalize()
# nodes
if self.synonym:
self.nodes[self.synonym]['synonym'] = self.name
self.nodes[self.synonym]['syn-cite'] = self.citation
self.nodes[self.synonym]['syn-uberon'] = self.uberon
return
else:
if self.citation: # Transverse Longitudinal etc all @ lvl4
self.names[self.name + ' ' + self.citation].add(self._rowind)
else:
self.name += str(self._appendix) + self.nodes[self._last_at_level[self.depth - 1]]['label']
#print(level, self.name)
# can't return here because they are their own level
# replace with actually doing something...
self.nodes[self._rowind]['label'] = self.name
self.nodes[self._rowind]['citation'] = self.citation
self.nodes[self._rowind]['uberon'] = self.uberon
# edges
self._last_at_level[self.depth] = self._rowind
# TODO will need something to deal with the Lateral/
if self.depth > 0:
try:
parent = self._last_at_level[self.depth - 1]
except:
embed()
self.children[parent].add(self._rowind)
self.parents[self._rowind].add(parent)
def _end(self):
replace = {}
for asdf in [sorted(n) for k,n in self.names.items() if len(n) > 1]:
replace_with, to_replace = asdf[0], asdf[1:]
for r in to_replace:
replace[r] = replace_with
for r, rw in replace.items():
#print(self.nodes[rw])
o = self.nodes.pop(r)
#print(o)
for vals in self.appendicies.values():
children = vals['children']
parents = vals['parents']
# need reversed so children are corrected before swap
for r, rw in reversed(sorted(replace.items())):
if r in parents:
child = r
new_child = rw
parent = parents.pop(child)
parents[new_child] = parent
parent = list(parent)[0]
children[parent].remove(child)
children[parent].add(new_child)
if r in children:
parent = r
new_parent = rw
childs = children.pop(parent)
children[new_parent] = childs
for child in childs:
parents[child] = {new_parent}
self.nodes = dict(self.nodes)
sp = SP()
tp = [_ for _ in sorted(['{: <50}'.format(n['label']) + n['uberon'] if n['uberon'] else n['label'] for n in sp.nodes.values()])]
#print('\n'.join(tp))
#print(sp.appendicies[1].keys())
#print(sp.nodes[1].keys())
nbase = 'http://swanson.org/node/%s'
json_ = {'nodes':[],'edges':[]}
for node, anns in sp.nodes.items():
nid = nbase % node
new_graph.add_class(nid, 'ilx:swansonBrainRegionConcept', label=anns['label'])
new_graph.add_node(nid, 'OBOANN:definingCitation', anns['citation'])
json_['nodes'].append({'lbl':anns['label'],'id':'SWA:' + str(node)})
#if anns['uberon']:
#new_graph.add_node(nid, rdflib.OWL.equivalentClass, anns['uberon']) # issues arrise here...
for appendix, data in sp.appendicies.items():
aid = 'http://swanson.org/appendix/%s' % appendix
new_graph.add_class(aid, label=data['name'].capitalize())
new_graph.add_node(aid, 'ilx:hasTaxonRank', data['taxon']) # FIXME appendix is the data artifact...
children = data['children']
ahp = HASPART + str(appendix)
apo = PARTOF + str(appendix)
new_graph.add_op(ahp, transitive=True)
new_graph.add_op(apo, inverse=ahp, transitive=True)
for parent, childs in children.items(): # FIXME does this give complete coverage?
pid = nbase % parent
for child in childs:
cid = nbase % child
new_graph.add_hierarchy(cid, ahp, pid) # note hierarhcy inverts direction
new_graph.add_hierarchy(pid, apo, cid)
json_['edges'].append({'sub':'SWA:' + str(child),'pred':apo,'obj':'SWA:' + str(parent)})
new_graph.write(convert=False)
if False:
Query = namedtuple('Query', ['root','relationshipType','direction','depth'])
mapping = (1, 1, 1, 1, 30, 83, 69, 70, 74, 1) # should generate?
for i, n in enumerate(mapping):
a, b = creatTree(*Query('SWA:' + str(n), 'ilx:partOf' + str(i + 1), 'INCOMING', 10), json=json_)
print(a)
return ontid, None
