def include_file(self, path, include_dirs = []):
"""
Includes a file into the current model.
@param path: Path to the file to be included.
@type path: str
@param include_dirs: Optional alternate include search path.
@type include_dirs: list(str)
"""
if self.include_includes:
if self.debug: print("------------------ Including a file: %s"%path)
inc_dirs = include_dirs if include_dirs else self.include_dirs
parser = LEMSFileParser(self, inc_dirs, self.include_includes)
if os.access(path, os.F_OK):
if not path in self.included_files:
parser.parse(open(path).read())
self.included_files.append(path)
return
else:
if self.debug: print("Already included: %s"%path)
return
else:
for inc_dir in inc_dirs:
new_path = (inc_dir + '/' + path)
if os.access(new_path, os.F_OK):
if not new_path in self.included_files:
parser.parse(open(new_path).read())
self.included_files.append(new_path)
return
else:
if self.debug: print("Already included: %s"%path)
return
raise Exception('Unable to open ' + path)
def import_from_file(self, filepath):
"""
Import a model from a file.
@param filepath: File to be imported.
@type filepath: str
"""
inc_dirs = self.include_directories[:]
inc_dirs.append(dirname(filepath))
parser = LEMSFileParser(self, inc_dirs, self.include_includes)
with open(filepath) as f:
parser.parse(f.read())
def get_lems_model_with_units():
global lems_model_with_units
if lems_model_with_units == None:
jar_path = get_path_to_jnml_jar()
#print_comment_v("Loading standard NeuroML2 dimension/unit definitions from %s"%jar_path)
jar = zipfile.ZipFile(jar_path, 'r')
dims_units = jar.read('NeuroML2CoreTypes/NeuroMLCoreDimensions.xml')
lems_model_with_units = lems_model.Model(include_includes=False)
parser = LEMSFileParser(lems_model_with_units)
parser.parse(dims_units)
return lems_model_with_units
def import_from_file(self, filepath):
"""
Import a model from a file.
@param filepath: File to be imported.
@type filepath: str
"""
inc_dirs = self.include_directories[:]
inc_dirs.append(dirname(filepath))
parser = LEMSFileParser(self, inc_dirs, self.include_includes)
with open(filepath) as f:
parser.parse(f.read())
def get_lems_model_with_units():
global lems_model_with_units
if lems_model_with_units == None:
jar_path = get_path_to_jnml_jar()
print_comment_v("Loading standard NeuroML2 dimension/unit definitions from %s"%jar_path)
jar = zipfile.ZipFile(jar_path, 'r')
dims_units = jar.read('NeuroML2CoreTypes/NeuroMLCoreDimensions.xml')
lems_model_with_units = lems_model.Model(include_includes=False)
parser = LEMSFileParser(lems_model_with_units)
parser.parse(dims_units)
return lems_model_with_units
def include_file(self, path, include_dirs = []):
"""
Includes a file into the current model.
@param path: Path to the file to be included.
@type path: str
@param include_dirs: Optional alternate include search path.
@type include_dirs: list(str)
"""
if self.include_includes:
if self.debug: print("------------------ Including a file: %s"%path)
inc_dirs = include_dirs if include_dirs else self.include_dirs
parser = LEMSFileParser(self, inc_dirs, self.include_includes)
if os.access(path, os.F_OK):
if not path in self.included_files:
parser.parse(open(path).read())
self.included_files.append(path)
return
else:
if self.debug: print("Already included: %s"%path)
return
else:
for inc_dir in inc_dirs:
new_path = (inc_dir + '/' + path)
if os.access(new_path, os.F_OK):
if not new_path in self.included_files:
parser.parse(open(new_path).read())
self.included_files.append(new_path)
return
else:
if self.debug: print("Already included: %s"%path)
return
raise Exception('Unable to open ' + path)
def _get_lems_model_with_neuroml2_types(cls):
from pyneuroml.pynml import get_path_to_jnml_jar
from pyneuroml.pynml import read_lems_file
from lems.parser.LEMS import LEMSFileParser
import zipfile
lems_model = lems.Model(include_includes=False)
parser = LEMSFileParser(lems_model)
jar_path = get_path_to_jnml_jar()
# print_comment_v("Loading standard NeuroML2 dimension/unit definitions from %s"%jar_path)
jar = zipfile.ZipFile(jar_path, "r")
new_lems = jar.read("NeuroML2CoreTypes/NeuroMLCoreDimensions.xml")
parser.parse(new_lems)
new_lems = jar.read("NeuroML2CoreTypes/NeuroMLCoreCompTypes.xml")
parser.parse(new_lems)
new_lems = jar.read("NeuroML2CoreTypes/Cells.xml")
parser.parse(new_lems)
new_lems = jar.read("NeuroML2CoreTypes/Networks.xml")
parser.parse(new_lems)
new_lems = jar.read("NeuroML2CoreTypes/Simulation.xml")
parser.parse(new_lems)
new_lems = jar.read("NeuroML2CoreTypes/Synapses.xml")
parser.parse(new_lems)
new_lems = jar.read("NeuroML2CoreTypes/PyNN.xml")
parser.parse(new_lems)
return lems_model
def _load_lems_file_with_neuroml2_types(cls, lems_filename):
from pyneuroml.pynml import get_path_to_jnml_jar
from pyneuroml.pynml import read_lems_file
from lems.parser.LEMS import LEMSFileParser
import zipfile
lems_model = lems.Model(include_includes=False)
parser = LEMSFileParser(lems_model)
jar_path = get_path_to_jnml_jar()
# print_comment_v("Loading standard NeuroML2 dimension/unit definitions from %s"%jar_path)
jar = zipfile.ZipFile(jar_path, 'r')
new_lems = jar.read('NeuroML2CoreTypes/NeuroMLCoreDimensions.xml')
parser.parse(new_lems)
new_lems = jar.read('NeuroML2CoreTypes/NeuroMLCoreCompTypes.xml')
parser.parse(new_lems)
new_lems = jar.read('NeuroML2CoreTypes/Cells.xml')
parser.parse(new_lems)
new_lems = jar.read('NeuroML2CoreTypes/Networks.xml')
parser.parse(new_lems)
new_lems = jar.read('NeuroML2CoreTypes/Simulation.xml')
parser.parse(new_lems)
new_lems = jar.read('NeuroML2CoreTypes/Synapses.xml')
parser.parse(new_lems)
new_lems = jar.read('NeuroML2CoreTypes/PyNN.xml')
parser.parse(new_lems)
model = read_lems_file(lems_filename,
include_includes=False,
fail_on_missing_includes=True,
debug=True)
for cid, c in model.components.items():
lems_model.components[cid] = c
for ctid, ct in model.component_types.items():
lems_model.component_types[ctid] = ct
return lems_model
