def main():
import csv
from neurondm.core import auth
with open(auth.get_path('resources') / '26451489 table 1.csv', 'rt') as f:
rows = [list(r) for r in zip(*csv.reader(f))]
config = Config('markram-2015',
source_file=relative_path(__file__, no_wd_value=__file__))
table1(rows)
return config,
def _ontology_data_files():
resources = 'resources'
relpaths = [
'ttl/phenotype-core.ttl',
'ttl/phenotype-indicators.ttl',
'ttl/phenotypes.ttl',
'ttl/generated/part-of-self.ttl',
]
if RELEASE:
from augpathlib import RepoPath as Path
### KILL IT WITH FIRE
try:
from neurondm.core import auth ### this is NOT ok
except Exception:
# can't catch an error that you can never import because
# it will be raised before you can import it ... SIGH
import orthauth as oa
from pyontutils.config import auth as pauth
auth = oa.configure(Path('neurondm/auth-config.py').resolve(),
include=pauth)
###
olr = Path(auth.get_path('ontology-local-repo'))
### KILL IT WITH FIRE
if not olr.exists():
original = auth.get('ontology-local-repo')
raise FileNotFoundError(
f'ontology local repo does not exist: {olr}'
f'path expanded from {original}')
elif olr.repo.active_branch.name != auth.get('neurons-branch'):
# FIXME yes indeed having to call Config in a way that is
# invoked at import time is REALLY REALLY BAD :/
raise ValueError('git is on the wrong branch! '
f'{olr.repo.active_branch}')
###
resources = Path(resources)
resources.mkdir(
) # if we add resources to git, this will error before we delete by accident
paths = [olr / rp for rp in relpaths]
for p in paths:
p.copy_to(resources / p.name)
else:
from pathlib import Path
resources = Path(resources)
paths = [Path(rp) for rp in relpaths]
return resources.absolute(), [(resources / p.name).as_posix()
for p in paths]
def main():
branch=auth.get('neurons-branch')
remote = OntId('NIFTTL:') if branch == 'master' else OntId(f'NIFRAW:{branch}/')
ont_config = ontneurons(remote)
ont_neurons = ont_config.neurons()
bn_config = Config('basic-neurons',
# FIXME this should probably be pulled in automatically
# from the import statements, and it doesn't work even as is
# also a chicken and an egg problem here
imports=[remote.iri + 'ttl/generated/swanson.ttl'])
#RDFL = oq.plugin.get('rdflib') # FIXME ick
#rdfl = RDFL(bn_config.core_graph, OntId)
#OntTerm.query.ladd(rdfl) # FIXME ick
bn_config.load_existing()
bn_neurons = bn_config.neurons()
#OntTerm.query._services = OntTerm.query._services[:-1] # FIXME ick
ndl_config = Config('neuron_data_lifted')
ndl_config.load_existing() # FIXME this is extremely slow
ndl_neurons = sorted(ndl_config.neurons())
resources = auth.get_path('resources')
cutcsv = resources / 'cut-development.csv'
with open(cutcsv.as_posix(), 'rt') as f:
rows = [l for l in csv.reader(f)]
bc = byCol(rows)
(_, *labels), *_ = zip(*bc)
labels_set0 = set(labels)
ns = []
skipped = []
bamscok = (NIFSTD.BAMSC1125,)
for n in (ont_neurons + ndl_neurons):
if n.id_ and 'BAMSC' in n.id_:
if n.id_ not in bamscok:
skipped.append(n)
continue
l = str(n.origLabel)
if l is not None:
for replace, match in rename_rules.items(): # HEH
l = l.replace(match, replace)
if l in labels:
n._origLabel = l
ns.append(n)
ns = sorted(ns)
sns = set(n.origLabel for n in ns)
labels_set1 = labels_set0 - sns
agen = [c.label for c in bc if c.autogenerated]
sagen = set(agen)
added = [c.label for c in bc if c.added]
sadded = set(added)
ans = []
sans = set()
missed = set()
_bl = [] # XXX NOTE THE CONTINUE BELOW
for n in bn_neurons:
continue # we actually get all of these with uberon, will map between them later
# can't use capitalize here because there are proper names that stay uppercase
l = n.label.replace('(swannt) ',
'').replace('Intrinsic',
'intrinsic').replace('Projection',
'projection')
for replace, match in rename_rules.items(): # HEH
l = l.replace(match, replace)
if l in agen:
n._origLabel = l
ans.append(n)
sans.add(l)
else:
missed.add(l)
_bl.append(l)
agen_missing = sagen - sans
labels_set2 = labels_set1 - sans
nlx_labels = [c.label for c in bc if c.neurolex]
snlx_labels = set(nlx_labels)
class SourceCUT(resSource):
sourceFile = 'nifstd/resources/cut-development.csv' # FIXME relative to git workingdir...
source_original = True
sources = SourceCUT(),
swanr = rdflib.Namespace(interlex_namespace('swanson/uris/readable/'))
SWAN = interlex_namespace('swanson/uris/neuroanatomical-terminology/terms/')
SWAA = interlex_namespace('swanson/uris/neuroanatomical-terminology/appendix/')
config = Config('cut-development-raw', sources=sources, source_file=relative_path(__file__),
prefixes={'swanr': swanr,
'SWAN': SWAN,
'SWAA': SWAA,})
ins = [None if OntId(n.id_).prefix == 'TEMP' else n.id_ for n in ns]
ians = [None] * len(ans)
with NeuronCUT(CUT.Mammalia):
mamns = [NeuronCUT(*zap(n.pes), id_=i, label=n._origLabel, override=bool(i)).adopt_meta(n)
for i, n in zip(ins + ians, ns + ans)]
smatch, rem = get_smatch(labels_set2)
labels_set3 = labels_set2 - smatch
added_unmapped = sadded & labels_set3
# TODO preserve the names from neuronlex on import ...
Neuron.write()
Neuron.write_python()
raw_neurons = config.neurons()
# do this before creating the new config
# even though we are in theory tripling number of neurons in the current config graph
# it won't show up in the next config (and this is why we need to reengineer)
raw_neurons_ind_undep = [n.asUndeprecated().asIndicator() for n in raw_neurons]
config = Config('cut-development', sources=sources, source_file=relative_path(__file__),
prefixes={'swanr': swanr,
'SWAN': SWAN,
'SWAA': SWAA,})
# FIXME the call to asUndprecated currenlty triggers addition
# to the current config and output graph as a side effect (ick!)
ids_updated_neurons = [n.asUndeprecated() for n in raw_neurons]
assert len(ids_updated_neurons) == len(raw_neurons)
Neuron.write()
Neuron.write_python()
progress = (len(labels_set0), len(sns), len(sans), len(smatch),
len(labels_set1), len(labels_set2), len(labels_set3))
prog_report = ('\nProgress:\n'
f'total: {progress[0]}\n'
f'from nlx: {progress[1]}\n'
f'from basic: {progress[2]}\n'
f'from match: {progress[3]}\n'
f'TODO after nlx: {progress[4]}\n'
f'TODO after basic: {progress[5]}\n'
f'TODO after match: {progress[6]}\n')
print(prog_report)
assert progress[0] == progress[1] + progress[4], 'neurolex does not add up'
assert progress[4] == progress[2] + progress[5], 'basic does not add up'
lnlx = set(n.lower() for n in snlx_labels)
sos = set(n.origLabel.lower() if n.origLabel else None for n in ndl_neurons) # FIXME load origLabel
nlx_review = lnlx - sos
nlx_missing = sorted(nlx_review)
print(f'\nNeuroLex listed as source but no mapping (n = {len(nlx_review)}):')
_ = [print(l) for l in nlx_missing]
partial = {k:v for k, v in rem.items() if v and v not in terminals}
print(f'\nPartially mapped (n = {len(partial)}):')
if partial:
mk = max((len(k) for k in partial.keys())) + 2
for k, v in sorted(partial.items()):
print(f'{k:<{mk}} {v!r}')
#print(f'{k!r:<{mk}}{v!r}')
#pprint(partial, width=200)
unmapped = sorted(labels_set3)
print(f'\nUnmapped (n = {len(labels_set3)}):')
_ = [print(l) for l in unmapped]
no_location = [n for n in Neuron.neurons()
if noneMembers((ilxtr.hasSomaLocatedIn, ilxtr.hasSomaLocatedInLayer), *n.unique_predicates)]
if __name__ == '__main__':
review_rows = export_for_review(config, unmapped, partial, nlx_missing)
breakpoint()
return config, unmapped, partial, nlx_missing
def export_for_review(config, unmapped, partial, nlx_missing,
filename='cuts-review.csv',
with_curies=False):
neurons = sorted(config.neurons())
predicates = sorted(set(e for n in neurons
for me in n.edges
for e in (me if isinstance(me, tuple) else (me,)))) # columns
q = graphBase.core_graph.transitive_subjects(rdfs.subPropertyOf, ilxtr.hasPhenotype)
all_predicates = set(s for s in q)
extra_predicates = sorted(p for p in all_predicates if p not in predicates)
col_labels = {p.e:p.eLabel for n in neurons
for mp in n.pes
for p in (mp.pes if isinstance(mp, LogicalPhenotype) else (mp,))}
header = (['curie', 'label'] +
[col_labels[p] for p in predicates] +
['Status', 'PMID', 'synonyms', 'definition'] +
[OntId(p).suffix for p in extra_predicates if not skip_pred(p)])
def neuron_to_review_row(neuron, cols=predicates): # TODO column names
_curie = neuron.ng.qname(neuron.id_)
curie = None if 'TEMP:' in _curie else _curie
row = [curie, neuron.origLabel]
for pdim in cols: # pdim -> phenotypic dimension
if pdim in neuron:
#print('>>>>>>>>>>>>>', pdim, neuron)
#if any(isinstance(p, LogicalPhenotype) for p in neuron):
#breakpoint()
row.append(','.join(sorted([f'{_._pClass.qname}|{_.pLabel}'
if with_curies else
_.pLabel
for _ in neuron[pdim]] if
isinstance(neuron[pdim], list) else
[neuron[pdim].pLabel])))
#if col == ilxtr.hasLayerLocationPhenotype:
#derp = neuron[col]
#log = [p for p in derp if isinstance(p, LogicalPhenotype)]
#if log:
#print(log, row)
#breakpoint()
else:
row.append(None)
return row
#[n for n in neurons]
resources = auth.get_path('resources')
reviewcsv = resources / filename
rows = [neuron_to_review_row(neuron) for neuron in neurons]
for i, row in enumerate(rows):
label = row[1]
if label in unmapped:
row.append('Unmapped')
elif label in partial:
rem = partial[label]
row.append(f'Partial: {rem!r}')
if label in nlx_missing:
row.append('Could not find NeuroLex mapping')
else:
row.append(None)
row.append(None) # pmid
if i < len(neurons):
n = neurons[i]
# FIXME
row.append(','.join(n.config.out_graph[n.id_:NIFRID.synonym:])) # syn
row.append(','.join(n.config.out_graph[n.id_:definition:])) # def
rows = sorted(rows, key=lambda r:(1 if r[1] is None else 0, str(r[1])))
incomplete = [[None, u] + [None] * (len(rows[0]) - 2) + ['Unmapped', None, None] for u in unmapped]
incomplete = sorted(incomplete, key=lambda r:r[1])
rows += incomplete
with open(reviewcsv.as_posix(), 'wt') as f:
writer = csv.writer(f, lineterminator='\n')
writer.writerow(header)
writer.writerows(rows)
return [header] + rows
def main():
# load in our existing graph
# note: while it would be nice to allow specification of phenotypes to be decoupled
# from insertion into the graph... maybe we could enable this, but it definitely seems
# to break a number of nice features... and we would need the phenotype graph anyway
Config('temporary-graph')
EXISTING_GRAPH = graphBase.in_graph
#EXISTING_GRAPH = rdflib.Graph()
#graphBase.in_graph = EXISTING_GRAPH
#graphBase.core_graph = EXISTING_GRAPH
local_prefix = auth.get_path('ontology-local-repo') / 'ttl'
sources = (f'{local_prefix}/NIF-Neuron-Defined.ttl',
f'{local_prefix}/NIF-Neuron.ttl',
f'{local_prefix}/NIF-Neuron-Phenotype.ttl',
f'{local_prefix}/phenotype-core.ttl',
f'{local_prefix}/phenotypes.ttl',
f'{local_prefix}/hbp-special.ttl')
for file in sources:
EXISTING_GRAPH.parse(file, format='turtle')
#EXISTING_GRAPH.namespace_manager.bind('PR', makePrefixes('PR')['PR'])
#graphBase.core_graph = EXISTING_GRAPH
#graphBase.out_graph = rdflib.Graph()
graphBase.__import_name__ = 'neurondm.lang'
proot = graphBase.core_graph.qname(PHENO_ROOT)
mroot = graphBase.core_graph.qname(MOD_ROOT)
graphBase._predicates, _psupers = getPhenotypePredicates(
EXISTING_GRAPH, proot, mroot)
g = makeGraph('merged',
prefixes={k: str(v)
for k, v in EXISTING_GRAPH.namespaces()},
graph=EXISTING_GRAPH)
reg_neurons = list(g.g.subjects(rdfs.subClassOf, _NEURON_CLASS))
tc_neurons = [
_ for (_, ) in
g.g.query('SELECT DISTINCT ?match WHERE {?match rdfs:subClassOf+ %s}' %
g.g.qname(_NEURON_CLASS))
]
def_neurons = g.get_equiv_inter(_NEURON_CLASS)
nodef = sorted(set(tc_neurons) - set(def_neurons))
og1 = MeasuredNeuron.out_graph = rdflib.Graph(
) # there is only 1 out_graph at a time, load and switch
mns = [MeasuredNeuron(id_=n) for n in nodef]
mnsp = [n for n in mns if n.pes]
graphBase.out_graph = rdflib.Graph(
) # XXX NEVER DO THIS IT IS EVIL ZALGO WILL EAT YOUR FACE
graphBase.ng.g = graphBase.out_graph
# and he did, had to swtich to graphBase for exactly this reason >_<
dns = [Neuron(id_=n) for n in sorted(def_neurons)]
#dns += [Neuron(*m.pes) if m.pes else m.id_ for m in mns]
dns += [Neuron(*m.pes) for m in mns if m.pes]
# reset everything for export
config = Config('phenotype-direct', source_file=relative_path(__file__))
#Neuron.out_graph = graphBase.out_graph # each subclass of graphBase has a distinct out graph IF it was set manually
#Neuron.out_graph = rdflib.Graph()
#ng = makeGraph('', prefixes={}, graph=Neuron.out_graph)
#ng.filename = Neuron.ng.filename
Neuron.mro()[1].existing_pes = {
} # wow, new adventures in evil python patterns mro()[1]
dns = [Neuron(*d.pes) for d in set(dns)
] # TODO remove the set and use this to test existing bags?
#from neurons.lang import WRITEPYTHON
#WRITEPYTHON(sorted(dns))
#ng.add_ont(TEMP['defined-neurons'], 'Defined Neurons', 'NIFDEFNEU',
#'VERY EXPERIMENTAL', '0.0.0.1a')
#ng.add_trip(TEMP['defined-neurons'], owl.imports, rdflib.URIRef('file:///home/tom/git/NIF-Ontology/ttl/phenotype-core.ttl'))
#ng.add_trip(TEMP['defined-neurons'], owl.imports, rdflib.URIRef('file:///home/tom/git/NIF-Ontology/ttl/phenotypes.ttl'))
#ng.write()
ontinfo = (
(Neuron.ng.ontid, rdf.type, owl.Ontology),
(Neuron.ng.ontid, rdfs.label,
rdflib.Literal('phenotype direct neurons')),
(Neuron.ng.ontid, rdfs.comment,
rdflib.Literal('Neurons derived directly from phenotype definitions')
),
)
[Neuron.out_graph.add(t) for t in ontinfo]
Neuron.write()
Neuron.write_python()
bads = [
n for n in Neuron.ng.g.subjects(rdf.type, owl.Class)
if len(list(Neuron.ng.g.predicate_objects(n))) == 1
]
if __name__ == '__main__':
breakpoint()
return config
