def create_finfos():
fields = defaultdict(list)
for el in moose.wildcardFind('/test/#'):
print el
mobj = moose.element(el)
for f in moose.getFieldNames(mobj.className, 'lookup'):
fields[mobj].append(getattr(mobj, f))
for f in moose.getFieldNames(mobj.className, 'element'):
fields[mobj].append(getattr(mobj, f))
return fields
def create_finfos():
fields = defaultdict(list)
for el in moose.wildcardFind('/test/#'):
print el
mobj = moose.element(el)
for f in moose.getFieldNames(mobj.className, 'lookup'):
fields[mobj].append(getattr(mobj, f))
for f in moose.getFieldNames(mobj.className, 'element'):
fields[mobj].append(getattr(mobj, f))
return fields
def loadtree(hdfnode, moosenode):
"""Load the element tree saved under the group `hdfnode` into `moosenode`"""
pathclass = {}
basepath = hdfnode.attr['path']
if basepath != '/':
basepath = basepath + '/'
emdata = hdfnode['ematrix'][:]
sorted_paths = sorted(emdata['path'], key=lambda x: x.count('/'))
dims = dict(emdata['path', 'dims'])
classes = dict(emdata['path', 'class'])
current = moose.getCwe()
moose.setCwe(moosenode)
# First create all the ematrices
for path in sorted_paths:
rpath = path[len(basepath):]
classname = classes[path]
shape = dims[path]
em = moose.ematrix(rpath, shape, classname)
wfields = {}
for cinfo in moose__.element('/classes').children:
cname = cinfo[0].name
wfields[cname] = [f[len('set_'):] for f in moose__.getFieldNames(cname, 'destFinfo')
if f.startswith('set_') and f not in ['set_this', 'set_name', 'set_lastDimension', 'set_runTime'] and not f.startswith('set_num_')]
for key in hdfnode['/elements']:
dset = hdfnode['/elements/'][key][:]
fieldnames = dset.dtype.names
for ii in range(len(dset)):
obj = moose__.element(dset['path'][ii][len(basepath):])
for f in wfields[obj.class_]:
obj.setField(f, dset[f][ii])
def restorestate(filename):
wfields = {}
for cinfo in moose.element('/classes').children:
cname = cinfo[0].name
wfields[cname] = [
f[len('set_'):] for f in moose.getFieldNames(cname, 'destFinfo')
if f.startswith('set_') and f not in
['set_this', 'set_name', 'set_lastDimension', 'set_runTime']
and not f.startswith('set_num_')
]
with h5.File(filename, 'r') as fd:
typeinfo = fd['/metadata/typeinfo'][:]
classdict = {}
dimsdict = dict(zip(typeinfo['path'], typeinfo['dims']))
classdict = dict(zip(typeinfo['path'], typeinfo['class']))
parentdict = dict(zip(typeinfo['path'], typeinfo['parent']))
sorted_paths = sorted(typeinfo['path'], key=lambda x: x.count('/'))
for path in sorted_paths:
name = path.rpartition('/')[-1].partition('[')[0]
moose.vec(parentdict[path] + '/' + name, eval(dimsdict[path]),
classdict[path])
for key in fd['/elements']:
dset = fd['/elements/'][key][:]
fieldnames = dset.dtype.names
for ii in range(len(dset)):
obj = moose.element(dset['path'][ii])
for f in wfields[obj.className]:
obj.setField(f, dset[f][ii])
def loadtree(hdfnode, moosenode):
"""Load the element tree saved under the group `hdfnode` into `moosenode`"""
pathclass = {}
basepath = hdfnode.attr['path']
if basepath != '/':
basepath = basepath + '/'
emdata = hdfnode['vec'][:]
sorted_paths = sorted(emdata['path'], key=lambda x: x.count('/'))
dims = dict(emdata['path', 'dims'])
classes = dict(emdata['path', 'class'])
current = moose.getCwe()
moose.setCwe(moosenode)
# First create all the ematrices
for path in sorted_paths:
rpath = path[len(basepath):]
classname = classes[path]
shape = dims[path]
em = moose.vec(rpath, shape, classname)
wfields = {}
for cinfo in moose.element('/classes').children:
cname = cinfo[0].name
wfields[cname] = [
f[len('set_'):] for f in moose.getFieldNames(cname, 'destFinfo')
if f.startswith('set_') and f not in
['set_this', 'set_name', 'set_lastDimension', 'set_runTime']
and not f.startswith('set_num_')
]
for key in hdfnode['/elements']:
dset = hdfnode['/elements/'][key][:]
fieldnames = dset.dtype.names
for ii in range(len(dset)):
obj = moose.element(dset['path'][ii][len(basepath):])
for f in wfields[obj.className]:
obj.setField(f, dset[f][ii])
def test_other():
a1 = moose.Pool('/ada')
assert a1.className == 'Pool', a1.className
finfo = moose.getFieldDict(a1.className)
s = moose.Streamer('/asdada')
p = moose.PulseGen('pg1')
assert p.delay[0] == 0.0
p.delay[1] = 0.99
assert p.delay[1] == 0.99, p.delay[1]
c = moose.Stoich('/dadaa')
v1 = moose.getFieldNames(c)
v2 = c.getFieldNames()
assert v1 == v2
assert len(v1) > 10, v1
def restorestate(filename):
wfields = {}
for cinfo in moose__.element('/classes').children:
cname = cinfo[0].name
wfields[cname] = [f[len('set_'):] for f in moose__.getFieldNames(cname, 'destFinfo')
if f.startswith('set_') and f not in ['set_this', 'set_name', 'set_lastDimension', 'set_runTime'] and not f.startswith('set_num_')]
with h5.File(filename, 'r') as fd:
typeinfo = fd['/metadata/typeinfo'][:]
classdict = {}
dimsdict = dict(zip(typeinfo['path'], typeinfo['dims']))
classdict = dict(zip(typeinfo['path'], typeinfo['class']))
parentdict = dict(zip(typeinfo['path'], typeinfo['parent']))
sorted_paths = sorted(typeinfo['path'], key=lambda x: x.count('/'))
for path in sorted_paths:
name = path.rpartition('/')[-1].partition('[')[0]
moose__.ematrix(parentdict[path] + '/' + name, eval(dimsdict[path]), classdict[path])
for key in fd['/elements']:
dset = fd['/elements/'][key][:]
fieldnames = dset.dtype.names
for ii in range(len(dset)):
obj = moose__.element(dset['path'][ii])
for f in wfields[obj.class_]:
obj.setField(f, dset[f][ii])
moose.reinit()
# start simulation at 0 nA injection current.
moose.start(0.3)
moose.showfields(soma) # check Vm
soma.inject = -1E-12
# reset simulation
moose.reint()
# start simulation at -1pA injection current.
moose.start(0.3)
moose.showfields(soma)
# Creation of pulse generator.
pulse = moose.PulseGen('pulse')
moose.showfield('pulse')
pulse.delay[0] = 50E-3 # First delay.
pulse.width[0] = 100E03 # Pulse width.
pulse.level[0] = 1E-9 # Pulse amplitude.
pulse.delat[1] = 1E9
moose.getFieldNames(
'PulseGen',
'srcFinfo') # returns list of message outlets for a moose element class.
moose.getFieldNames(
'Compartment',
'destFinfo') # returns list of message inlets for a moose element class.
soma.getFieldNames('destFinfo')
moose.showmsg(
'soma') # shows message connetions statistics of the moose element.
