numGenerated = project.generatedCellPositions.getNumberInAllCellGroups()
print "Number of cells generated: " + str(numGenerated)
assert numGenerated == expectedNumberCells
print "Correct number of cells generated!"
nmlFileName = "GeneratedNeuroML.xml"
NeuroMLFileManager.saveNetworkStructureXML(project,
File(nmlFileName),
False,
False,
simConfig.getName(),
"Physiological Units",
NeuroMLConstants.NeuroMLVersion.NEUROML_VERSION_1,
None);
nmlFileName = "GeneratedNeuroML2.xml"
NeuroMLFileManager.saveNetworkStructureXML(project,
File(nmlFileName),
False,
False,
simConfig.getName(),
"Physiological Units",
NeuroMLConstants.NeuroMLVersion.NEUROML_VERSION_2_BETA,
None);
def SingleCellNML2generator(projString=" ",
ConfigDict={},
ElecLenList=[],
somaNseg=None,
savingDir=None):
projFile = File(os.getcwd(), projString)
pm = ProjectManager()
compSummary = {}
for config in ConfigDict.keys():
project = pm.loadProject(projFile)
nmlfm = NeuroMLFileManager(project)
compSummary[config] = {}
if " " in config:
configPath = config.replace(" ", "_")
else:
configPath = config
for maxElecLen in ElecLenList:
compSummary[config][str(maxElecLen)] = {}
cell = project.cellManager.getCell(ConfigDict[config])
if maxElecLen > 0:
info = CellTopologyHelper.recompartmentaliseCell(
cell, maxElecLen, project)
print "Recompartmentalising cell %s" % ConfigDict[config]
if somaNseg != None:
cell.getSegmentWithId(
0).getSection().setNumberInternalDivisions(somaNseg)
if savingDir != None:
cellpath = r'../../NeuroML2/%s/%s/%s_%f' % (
savingDir, configPath, configPath, maxElecLen)
else:
cellpath = r'../../NeuroML2/%s/%s_%f' % (
configPath, configPath, maxElecLen)
else:
if savingDir != None:
cellpath = r'../../NeuroML2/%s/%s/%s_default' % (
savingDir, configPath, configPath)
else:
cellpath = r'../../NeuroML2/%s/%s_default' % (configPath,
configPath)
summary = str(cell.getMorphSummary())
summary_string = summary.split("_")
for feature in summary_string:
feature_split = feature.split(":")
compSummary[config][str(maxElecLen)][
feature_split[0]] = feature_split[1]
# the format of summary : Segs:122_Secs:61_IntDivs:1458
print("Will be printing a cell morphology summary")
print compSummary[config][str(maxElecLen)]
######### it turns out that this does not save recompartmentalized cells - all saved cells have identical spatial discretization;
##### generateNeuroML2 receives the parent projFile but not the loaded project which is modified by the CellTopologyHelper.recompartmentaliseCell()
##################### neuroConstruct block #############################################################################
neuroConstructSeed = 1234
verbose = True
pm.doGenerate(config, neuroConstructSeed)
while pm.isGenerating():
if verbose:
print(
"Waiting for the project to be generated with Simulation Configuration: "
+ config)
time.sleep(5)
simConfig = project.simConfigInfo.getSimConfig(config)
seed = 1234
genDir = File(projFile.getParentFile(), "generatedNeuroML2")
nmlfm.generateNeuroMLFiles(
simConfig, NeuroMLConstants.NeuroMLVersion.getLatestVersion(),
LemsConstants.LemsOption.LEMS_WITHOUT_EXECUTE_MODEL,
OriginalCompartmentalisation(), seed, False, True, genDir,
"GENESIS Physiological Units", False)
########################################################################################################################
if not os.path.exists(cellpath):
print("Creating a new directory %s" % cellpath)
os.makedirs(cellpath)
else:
print("A directory %s already exists" % cellpath)
src_files = os.listdir("../generatedNeuroML2/")
for file_name in src_files:
full_file_name = os.path.join("../generatedNeuroML2/",
file_name)
if (os.path.isfile(full_file_name)):
print("Moving generated NeuroML2 to files to %s" %
cellpath)
shutil.copy(full_file_name, cellpath)
#with open("compSummary.json",'w') as fout:
#json.dump(compSummary, fout)
subprocess.call(["~/neuroConstruct/nC.sh -python RegenerateNml2.py -f"],
shell=True)
#subprocess.call(["cp compSummary.json ~/Thalamocortical/NeuroML2/"],shell=True)
quit()
def SingleCellNML2generator(projString=" ",ConfigDict={},ElecLenList=[],somaNseg=None,savingDir=None,shell=None):
projFile=File(os.getcwd(),projString)
pm=ProjectManager()
for config in ConfigDict.keys():
project=pm.loadProject(projFile)
nmlfm = NeuroMLFileManager(project)
compSummary={}
compSummary[config]={}
if " " in config:
configPath=config.replace(" ","_")
else:
configPath=config
if savingDir !=None:
full_path_to_config=r'../%s/%s'%(savingDir,configPath)
else:
full_path_to_config=r'../%s'%(configPath)
for maxElecLen in ElecLenList:
compSummary[config][str(maxElecLen)]={}
cell=project.cellManager.getCell(ConfigDict[config])
if maxElecLen > 0:
info = CellTopologyHelper.recompartmentaliseCell(cell, maxElecLen, project)
print "Recompartmentalising cell %s"%ConfigDict[config]
if somaNseg != None:
cell.getSegmentWithId(0).getSection().setNumberInternalDivisions(somaNseg)
if savingDir !=None:
cellpath = r'../%s/%s/%s_%f'%(savingDir,configPath,configPath,maxElecLen)
else:
cellpath = r'../%s/%s_%f'%(configPath,configPath,maxElecLen)
else:
if savingDir !=None:
cellpath = r'../%s/%s/%s_default'%(savingDir,configPath,configPath)
else:
cellpath = r'../%s/%s_default'%(configPath,configPath)
summary=str(cell.getMorphSummary())
summary_string=summary.split("_")
for feature in summary_string:
feature_split=feature.split(":")
compSummary[config][str(maxElecLen)][feature_split[0]]=feature_split[1]
# the format of summary : Segs:122_Secs:61_IntDivs:1458
print("Will be printing a cell morphology summary")
print compSummary[config][str(maxElecLen)]
######### it turns out that this does not save recompartmentalized cells - all saved cells have identical spatial discretization;
##### generateNeuroML2 receives the parent projFile but not the loaded project which is modified by the CellTopologyHelper.recompartmentaliseCell()
##################### neuroConstruct block #############################################################################
neuroConstructSeed=1234
verbose=True
pm.doGenerate(config, neuroConstructSeed)
while pm.isGenerating():
if verbose:
print("Waiting for the project to be generated with Simulation Configuration: "+config)
time.sleep(5)
simConfig = project.simConfigInfo.getSimConfig(config)
seed=1234
genDir = File(projFile.getParentFile(), "generatedNeuroML2")
nmlfm.generateNeuroMLFiles(simConfig,
NeuroMLConstants.NeuroMLVersion.getLatestVersion(),
LemsConstants.LemsOption.LEMS_WITHOUT_EXECUTE_MODEL,
OriginalCompartmentalisation(),
seed,
False,
True,
genDir,
"GENESIS Physiological Units",
False)
########################################################################################################################
if not os.path.exists(cellpath):
print("Creating a new directory %s"%cellpath)
os.makedirs(cellpath)
else:
print("A directory %s already exists"%cellpath)
src_files = os.listdir("../../neuroConstruct/generatedNeuroML2/")
for file_name in src_files:
full_file_name = os.path.join("../../neuroConstruct/generatedNeuroML2/", file_name)
if (os.path.isfile(full_file_name)):
print("Moving generated NeuroML2 to files to %s"%cellpath)
shutil.copy(full_file_name, cellpath)
with open(os.path.join(full_path_to_config,"compSummary.json"),'w') as fout:
json.dump(compSummary, fout)
if shell ==None:
extension='sh'
else:
extension=shell
os.chdir("../../neuroConstruct/pythonScripts")
subprocess.call("%s/nC.%s -python ../../neuroConstruct/pythonScripts/RegenerateNml2.py -f"%(os.environ["NC_HOME"],extension),shell=True)
os.chdir("../../NeuroML2/pythonScripts")
