def show3Dimage(self):
"""Generate 3D view button has been pressed"""
print_v("image3D button was clicked.")
self.update_net_sim()
self.tabs.setCurrentWidget(self.all_tabs[self.IMAGE_3D_TAB])
from neuromllite.NetworkGenerator import generate_neuroml2_from_network
nml_file_name, nml_doc = generate_neuroml2_from_network(self.network,
print_summary=True,
format='xml',
base_dir=None,
copy_included_elements=False,
target_dir=None,
validate=False,
simulation=self.simulation)
post_args = "-png"
from pyneuroml.pynml import run_jneuroml
run_jneuroml("",
nml_file_name,
post_args,
verbose = True)
nml_view_file = nml_file_name.replace('.nml','.png')
self.add_image(nml_view_file, self.IMAGE_3D_TAB)
def showLemsView(self):
"""Generate lemsView button has been pressed"""
print_v("lemsView button was clicked.")
self.update_net_sim()
self.tabs.setCurrentWidget(self.all_tabs[self.LEMS_VIEW_TAB])
self.update_net_sim()
from neuromllite.NetworkGenerator import generate_neuroml2_from_network
from neuromllite.NetworkGenerator import generate_and_run
lems_file_name = generate_and_run(self.simulation,
simulator='jNeuroML_norun',
network=self.network,
return_results=True,
base_dir=self.sim_base_dir)
post_args = "-graph"
from pyneuroml.pynml import run_jneuroml
run_jneuroml("",
lems_file_name,
post_args,
verbose = True)
lems_view_file = lems_file_name.replace('.xml','.png')
self.add_image(lems_view_file, self.LEMS_VIEW_TAB)
def validate_neuroml2_lems_file(
nml2_lems_file_name, max_memory=DEFAULTS["default_java_max_memory"], exit_on_fail=True, return_string=False,
):
# type: (str, str) -> bool
"""Validate a NeuroML 2 LEMS file using jNeuroML.
Note that this uses jNeuroML and so is aware of the standard NeuroML LEMS
definitions.
TODO: allow inclusion of other paths for user-defined LEMS definitions
(does the -norun option allow the use of -I?)
:param nml2_lems_file_name: name of file to validate
:type nml2_lems_file_name: str
:param max_memory: memory to use for the Java virtual machine
:type max_memory: str
:param exit_on_fail: toggle whether command should exit if jnml fails
:type exit_on_fail: bool
:param return_string: toggle whether the output string should be returned
:type return_string: bool
:returns: Either a bool, or a tuple (bool, str): True if jnml ran without errors, false if jnml fails; along with the message returned by jnml
"""
post_args = ""
post_args += "-norun"
return run_jneuroml(
"",
nml2_lems_file_name,
post_args,
max_memory=max_memory,
verbose=False,
report_jnml_output=True,
exit_on_fail=exit_on_fail,
return_string=return_string,
)
def convert_channels_to_mod(lems_file):
from pyneuroml import pynml
pynml.run_jneuroml("", lems_file, "-neuron")
def convert_channels_to_mod(lems_file):
from pyneuroml import pynml
pynml.run_jneuroml("", lems_file, "-neuron")