/
save_data.py
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/
save_data.py
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import argparse
import types
from owmeta_core.command import OWM
from owmeta.data_trans.wormatlas import (WormAtlasCellListDataTranslator,
WormAtlasCellListDataSource)
from owmeta.data_trans.wormbase import (WormBaseCSVDataSource,
WormbaseIonChannelCSVDataSource,
WormbaseIonChannelCSVTranslator,
CellWormBaseCSVTranslator,
WormbaseTextMatchCSVTranslator,
WormbaseTextMatchCSVDataSource)
from owmeta.data_trans.neuron_data import NeuronCSVDataSource, NeuronCSVDataTranslator
from owmeta.data_trans.connections import (NeuronConnectomeCSVTranslator,
ConnectomeCSVDataSource,
NeuronConnectomeSynapseClassTranslator)
from owmeta.data_trans.context_merge import ContextMergeDataTranslator
from owmeta.data_trans.data_with_evidence_ds import DataWithEvidenceDataSource as DWEDS
# metaclass stuff to keep track of the order of data sources in DSMethods.
# Copied from PEP 3115
class member_table(dict):
def __init__(self):
self.member_names = []
def __setitem__(self, key, value):
if key not in self:
self.member_names.append(key)
dict.__setitem__(self, key, value)
class OrderedClass(type):
@classmethod
def __prepare__(metacls, name, bases): # No keywords in this case
return member_table()
def __new__(cls, name, bases, classdict):
result = type.__new__(cls, name, bases, dict(classdict))
result.member_names = classdict.member_names
return result
class DSMethods(metaclass=OrderedClass):
# Note: Keep the ordering of
def __init__(self):
self.owm = OWM()
self.ctx = self.owm.default_context.stored
def neurons(self):
neurons = self.owm.translate(NeuronCSVDataTranslator(),
data_sources=[NeuronCSVDataSource(key='neurons')],
output_key='neurons')
self.ctx(neurons).description(
"Contains descriptions of C. elegans neurons and is the"
" principle such list for OpenWorm")
def wormatlas_cells(self):
cells = self.owm.translate(
WormAtlasCellListDataTranslator(),
data_sources=[
WormAtlasCellListDataSource(key='cells'),
DWEDS(key='neurons')],
output_key='cells')
self.ctx(cells).description(
"Lineage names and descriptions of C. elegans cells from Worm Atlas")
def ion_channels(self):
ion_channels = self.owm.translate(
WormbaseIonChannelCSVTranslator(),
data_sources=[WormbaseIonChannelCSVDataSource(key='ion_channels')],
output_key='ion_channels')
self.ctx(ion_channels).description(
"Contains Channels and ExpressionPatterns")
def wormbase_cells(self):
wb_cells = self.owm.translate(
CellWormBaseCSVTranslator(),
data_sources=[WormBaseCSVDataSource(key='wormbase_celegans_cells')],
output_key='wormbase_cells')
self.ctx(wb_cells).description(
'Contains muscles, neurons, and other cells. Neuron data is partially'
' redundant to the Worm Atlas data source')
def bently_expression(self):
bently_expression = self.owm.translate(
NeuronCSVDataTranslator(),
data_sources=[NeuronCSVDataSource(key='bently_expression')],
output_key='bently_expression')
self.ctx(bently_expression).description(
'Adds receptor, neurotransmitter, and neuropeptide relationships for Neurons')
def muscle_ion_channels(self):
muscle_ion_channels = self.owm.translate(
WormbaseTextMatchCSVTranslator(),
data_sources=[WormbaseTextMatchCSVDataSource(key='muscle_ion_channels')],
output_key='muscle_ion_channels')
self.ctx(muscle_ion_channels).description(
'Adds relationships between muscles and ion channels')
def neuron_ion_channels(self):
neuron_ion_channels = self.owm.translate(
WormbaseTextMatchCSVTranslator(),
data_sources=[WormbaseTextMatchCSVDataSource(key='neuron_ion_channels')],
output_key='neuron_ion_channels')
self.ctx(neuron_ion_channels).description(
'Adds relationships between neurons and ion channels')
def connectome(self):
emmons_connectome = self.owm.translate(
NeuronConnectomeCSVTranslator(),
data_sources=[ConnectomeCSVDataSource(key='emmons')],
named_data_sources=dict(
muscles_source=DWEDS(key='wormbase_cells'),
neurons_source=DWEDS(key='neurons')),
output_key='connectome')
self.ctx(emmons_connectome).description(
'C. elegans connectome')
def synclass(self):
connectome_synclass = self.owm.translate(
NeuronConnectomeSynapseClassTranslator(),
data_sources=[DWEDS(key='connectome')],
named_data_sources=dict(
neurotransmitter_source=ConnectomeCSVDataSource(key='connectome')),
output_key='synclass')
self.ctx(connectome_synclass).description(
'Adds inferred relationships between connections and neurotransmitters that'
' mediates communication')
def openworm_data(self):
combined_data_source = self.owm.translate(
ContextMergeDataTranslator(),
data_sources=[
DWEDS(key='neurons'),
DWEDS(key='wormbase_cells'),
DWEDS(key='ion_channels'),
DWEDS(key='bently_expression'),
DWEDS(key='muscle_ion_channels'),
DWEDS(key='neuron_ion_channels'),
DWEDS(key='connectome'),
DWEDS(key='synclass'),
DWEDS(key='cells'),
],
output_identifier='http://openworm.org/data')
def methods(self):
return list(x for x in self.member_names
if x not in ('save', 'methods') and
not x.startswith('_') and
isinstance(getattr(self, x), types.MethodType))
def save(self):
self.ctx.save()
def main():
parser = argparse.ArgumentParser()
m = DSMethods()
parser.add_argument('source', nargs='*', choices=m.methods() + ['all'])
ns = parser.parse_args()
for src in m.methods():
if 'all' in ns.source or src in ns.source:
print(f"Building {src}...")
getattr(m, src)()
if __name__ == '__main__':
main()