def test_ste():
m1 = model()
# one state ste with two self transitions
var = m1["s"](0.5)._ref_v
thresh1 = h.ref(-50)
thresh2 = h.ref(-10)
result = []
ste = h.StateTransitionEvent(1)
ste.transition(0, 0, var, thresh1, (act, (1, m1, thresh1, result)))
ste.transition(0, 0, var, thresh2, (act, (2, m1, thresh2, result)))
fih = h.FInitializeHandler((on_finit, (ste, result)))
run(5)
print("final v=%g" % m1["s"](0.5).v)
chk_result(2, result, m1)
h.cvode_active(1)
run(20)
chk_result(2, result, m1)
h.cvode_active(1)
h.cvode.condition_order(2)
run(5)
chk_result(2, result, m1)
h.cvode.condition_order(1)
h.cvode_active(0)
# ste associated with point process
del fih, ste
ste = h.StateTransitionEvent(2, m1["ic"])
fih = h.FInitializeHandler((on_finit, (ste, result)))
run(5)
# transition with hoc callback
h("""proc foo() { printf("foo called at t=%g\\n", t) }""")
thresh3 = h.ref(-30)
ste.transition(0, 0, var, thresh3, "foo()")
run(5)
# transition with hoc callback in hoc object
h("""
begintemplate FooSTEtest
objref this
proc foo() { printf("foo in %s called at t=%g\\n", this, t) }
endtemplate FooSTEtest
""")
thresh4 = h.ref(-20)
obj = h.FooSTEtest()
ste.transition(0, 0, var, thresh4, "foo()", obj)
run(5)
del ste, fih
assert h.List("StateTransitionEvent").count() == 0
assert h.List("FInitializeHandler").count() == 0
def __init__(self):
html = """
<table style="width:100%">
<tr><td><button data-onclick="init()">Init (mV)</button></td><td><input type="number" data-variable="v_init"></input></tr>
<tr><td><button data-onclick="run()">Init & run</button></td></tr>
<tr><td><button data-onclick="stopbutton()">Stop</button></td></tr>
<tr><td><button data-onclick="do_continue_until()">Continue until (ms)</button></td><td><input type="number" data-variable="continue_til"></input></tr>
<tr><td><button data-onclick="do_continue_for()">Continue for (ms)</button></td><td><input type="number" data-variable="continue_for"></input></tr>
<tr><td><button data-onclick="fadvance()">Single Step</button></td></tr>
<tr><td>t (ms)</td><td><input type="number" data-variable="t"></input></tr>
<tr><td>tstop (ms)</td><td><input type="number" data-variable="tstop"></input></tr>
<tr><td>dt (ms)</td><td><input type="number" data-variable="dt"></input></tr>
<tr><td>Real Time (s)</td><td><input type="number" data-variable="realtime" disabled></input></tr>
</table>
"""
self.my_continue_til = h.ref(5)
self.my_continue_for = h.ref(1)
user_mappings = {
'v_init':
h._ref_v_init,
'continue_til':
self.my_continue_til,
'continue_for':
self.my_continue_for,
't':
h._ref_t,
'tstop':
h._ref_tstop,
'dt':
h._ref_dt,
'run()':
h.run,
'init()':
h.stdinit,
'fadvance()':
h.fadvance,
'realtime':
h._ref_realtime,
'stopbutton()':
self.stop,
'do_continue_until()':
lambda: h.continuerun(self.my_continue_til[0]),
'do_continue_for()':
lambda: h.continuerun(h.t + self.my_continue_for[0])
}
self._frame = make_browser_html(html,
user_mappings=user_mappings,
title='Run Control',
size=(280, 400))
def all(substring, start=0, end=-1):
results = []
mt = h.MechanismType(1)
cnt = int(mt.count())
end = cnt if end == -1 or end > cnt else end
for i in range(start, end):
if mt.is_netcon_target(i) and not mt.is_artificial(i):
mt.select(i)
n = h.ref("")
mt.selected(n)
mechname = n[0]
if substring not in mechname:
continue
if uses_pointer(mechname):
print("\n%d> %s has a POINTER" % (i, mechname))
if 'ProbAMPANMDA_EMS' not in mechname:
continue
print("\n%d of %d" % (i, cnt))
print(mechname)
for h.secondorder in [0, 2]:
m, result = one(mechname)
if cnt > 30:
m.g = None
if result:
results.append((i, result, m.g))
del m
h.secondorder = 0
return results
def det(m):
hm = h.Matrix(m.shape[0], m.shape[1])
for i in range(int(hm.nrow())):
hm.setcol(i, h.Vector(m[:, i]))
e = h.ref(0)
d = hm.det(e)
return d * 10.0**e[0]
def __init__ (self, type, li) :
self.izhtype = type
vbox, hbox, hbox1 = h.VBox(), h.HBox(), h.HBox()
self.vbox = vbox
lil = len(li)
self.cols, self.rows = {20:(4,5), 8:(4,2), 9:(3,3)}[lil]
self.label=h.ref('================================================================================')
vbox.intercept(1)
h.xpanel("")
h.xvarlabel(self.label)
if newmodel(self.izhtype):
h.xlabel("V' = (k*(V-vr)*(V-vt) - u + Iin)/C if (V>vpeak) V=c [reset]")
h.xlabel("u' = a*(b*(V-vr) - u) if (V>vpeak) u=u+d")
else:
h.xlabel("v' = 0.04*v*v + f*v + g - u + Iin; if (v>thresh) v=c [reset]")
h.xlabel("u' = a*(b*v - u); if (v>thresh) u=u+d")
h.xpanel()
hbox1.intercept(1)
h.xpanel(""); h.xbutton("RUN",h.run); h.xpanel()
self.xvalue('I0','I0')
self.xvalue('I1','I1')
self.xvalue('T1','T1')
hbox1.intercept(0); hbox1.map("")
hbox.intercept(1)
for ii,(k,v) in enumerate(li.iteritems()):
if ii%self.rows==0: h.xpanel("")
h.xbutton(k, (lambda f, arg1, arg2: lambda: f(arg1,arg2))(p, k, v)) # alternative is to use functools.partial
if ii%self.rows==self.rows-1: h.xpanel()
hbox.intercept(0); hbox.map("")
vbox.intercept(0); vbox.map("Spike patterns")
self.label[0]=""
def mechVarList ():
msname = h.ref('')
varList = {}
for i, mechtype in enumerate(['mechs','pointps']):
mt = h.MechanismType(i) # either distributed mechs (0) or point process (1)
varList[mechtype] = {}
for j in xrange(int(mt.count())):
mt.select(j)
mt.selected(msname)
ms = h.MechanismStandard(msname[0], 1) # PARAMETER (modifiable)
varList[mechtype][msname[0]] = []
propName = h.ref('')
for var in xrange(int(ms.count())):
k = ms.name(propName, var)
varList[mechtype][msname[0]].append(propName[0])
return varList
def mechVarList ():
msname = h.ref('')
varList = {}
for i, mechtype in enumerate(['mechs','pointps']):
mt = h.MechanismType(i) # either distributed mechs (0) or point process (1)
varList[mechtype] = {}
for j in xrange(int(mt.count())):
mt.select(j)
mt.selected(msname)
ms = h.MechanismStandard(msname[0], 1) # PARAMETER (modifiable)
varList[mechtype][msname[0]] = []
propName = h.ref('')
for var in xrange(int(ms.count())):
k = ms.name(propName, var)
varList[mechtype][msname[0]].append(propName[0])
return varList
def paramPanel(self):
self.box = h.VBox()
self.box.intercept(1)
h.xpanel('')
h.xlabel('Likelihood numerical parameters')
h.xlabel(' Measurement noise')
c = self.Eve.Obs.C
for o in c:
h.xvalue('sigma: ' + o.hpt.s(), (o, 'sigma'), 1)
h.xlabel(' Process noise')
h.xvalue('Injection interval', (self, 'inj_invl'), 1,
self.inj_invl_changed)
s = h.Vector()
cvodewrap.states(s)
sref = h.ref('')
for i in range(len(s)):
cvodewrap.statename(i, sref, 1)
h.xvalue('Diffusion Coeff[%d,%d]: ' % (i, i) + sref[0],
(self.processNoise[i], 'x'), 1, (self.fillPB, i))
h.xcheckbox('Fox & Lu Diffusion (for Hodgkin-Huxley)?', (self, 'hhB'),
self.hhBButton)
h.xvalue(' Fox & Lu: Number Na Channels', (self, 'nNa'), 1,
self.hhBButton)
h.xvalue(' Fox & Lu: Number K Channels', (self, 'nK'), 1,
self.hhBButton)
h.xlabel(' Initial Uncertainty')
for i in range(len(s)):
print i
cvodewrap.statename(i, sref, 1)
h.xvalue('Initial Stand Dev[%d]: ' % i + sref[0],
(self.Sdiag[i], 'x'), 1, (self.fillS, i))
h.xbutton('Show state funnels', self.show_state_funnels)
h.xpanel()
self.box.intercept(0)
self.box.map('Likelihood parameters')
def sparse_print(m):
j = h.ref(0)
for i in range(int(m.nrow())):
print(i, end=' ')
for jx in range(int(m.sprowlen(i))):
x = m.spgetrowval(i, jx, j)
print(" %d:%g" % (j[0], x))
print()
def pname(msname):
s = h.ref('')
for i in xrange(-1, 4):
ms = h.MechanismStandard(msname, i)
print '\n', msname, ' vartype=%d' % i # vartype = 1 -> PARAMETER
for j in xrange(int(ms.count())):
k = ms.name(s, j)
print '%-5d %-20s size=%d' % (j, s[0], k)
def get_mech_globals(mechname, var=-1):
ms = h.MechanismStandard(mechname, var)
name = h.ref('')
mech_globals = {}
for j in range(ms.count()):
ms.name(name, j)
mech_globals[name[0]] = getattr(h, name[0])
return mech_globals
def pname(msname):
s = h.ref('')
for i in range(-1, 4):
ms = h.MechanismStandard(msname, i)
print('\n', msname, ' vartype=%d' % i) # vartype = 1 -> PARAMETER
for j in range(int(ms.count())):
k = ms.name(s, j)
print('%-5d %-20s size=%d' % (j, s[0], k))
def cellran(gid, nclist):
r = h.Random()
r.Random123(gid)
r.uniform(1.0, 1.1)
cell = pc.gid2cell(gid)
for sec in cell.all:
sec.L *= r.repick()
for seg in sec:
seg.diam *= r.repick()
seg.cm *= r.repick()
#print 'diam ', seg.diam, 'cm ', seg.cm
#mechanism variables
for mech in seg:
ms = h.MechanismStandard(mech.name(), 1)
for i in range(int(ms.count())):
varname = h.ref("")
sz = ms.name(varname, i)
n = varname[0]
x = seg.__getattribute__(n)
setattr(seg, n, x * r.repick())
#print n, seg.__getattribute__(n)
#point process parameters
for p in seg.point_processes():
n = p.hname()
n = n[:n.index('[')]
if n == 'HalfGap':
continue
ms = h.MechanismStandard(n, 1)
for i in range(int(ms.count())):
varname = h.ref("")
ms.name(varname, i)
x = p.__getattribute__(varname[0])
setattr(p, varname[0], x * r.repick())
#print varname[0], p.__getattribute__(varname[0])
#netcons targeting the cell
for nc in nclist:
if nc.postcell() == cell:
nc.weight[0] *= r.repick()
nc.delay *= r.repick()
pc.threshold(gid, pc.threshold(gid) + r.uniform(-9, 0))
def cellran(gid, nclist):
r = h.Random()
r.Random123(gid)
r.uniform(1.0, 1.1)
cell = pc.gid2cell(gid)
for sec in cell.all:
sec.L *= r.repick()
for seg in sec:
seg.diam *= r.repick()
seg.cm *= r.repick()
#print 'diam ', seg.diam, 'cm ', seg.cm
#mechanism variables
for mech in seg:
ms = h.MechanismStandard(mech.name(), 1)
for i in range(int(ms.count())):
varname = h.ref("")
sz = ms.name(varname, i)
n = varname[0]
x = seg.__getattribute__(n)
setattr(seg, n, x * r.repick())
#print n, seg.__getattribute__(n)
#point process parameters
for p in seg.point_processes():
n = p.hname()
n = n[:n.index('[')]
if n == 'HalfGap':
continue
ms = h.MechanismStandard(n, 1)
for i in range(int(ms.count())):
varname = h.ref("")
ms.name(varname, i)
x = p.__getattribute__(varname[0])
setattr(p, varname[0], x * r.repick())
#print varname[0], p.__getattribute__(varname[0])
#netcons targeting the cell
for nc in nclist:
if nc.postcell() == cell:
nc.weight[0] *= r.repick()
nc.delay *= r.repick()
pc.threshold(gid, pc.threshold(gid) + r.uniform(-9, 0))
def ptype():
msname = h.ref('')
propList = {}
for i, mechtype in enumerate(['mechs','pointps']):
mt = h.MechanismType(i) # either distributed mechs (0) or point process (1)
propList[mechtype] = {}
for j in xrange(int(mt.count())):
mt.select(j)
mt.selected(msname)
print '\n\n', msname[0], ' mechanismtype=%d' % j
pname(msname[0])
ms = h.MechanismStandard(msname[0], 1) # PARAMETER (modifiable)
propList[mechtype][msname[0]] = []
propName = h.ref('')
for prop in xrange(int(ms.count())):
k = ms.name(propName, prop)
propList[mechtype][msname[0]].append(propName[0])
print propList
def get_mech_names():
_mech_names = []
mt = h.MechanismType(0)
mname = h.ref("")
for i in range(int(mt.count())):
mt.select(i)
mt.selected(mname)
_mech_names.append(mname[0])
return _mech_names
def get_mech_globals(mechname):
ms = h.MechanismStandard(mechname, -1)
name = h.ref('')
mech_globals = []
integer2 = int(ms.count())
for j in range(integer2):
ms.name(name, j)
mech_globals.append(name[0])
return mech_globals
def get_mech_names():
_mech_names = []
mt = h.MechanismType(0)
mname = h.ref('')
for i in range(int(mt.count())):
mt.select(i)
mt.selected(mname)
_mech_names.append(mname[0])
return _mech_names
def uses_pointer(mechname):
# do not get involved with POINTER
ms = h.MechanismStandard(mechname, 0)
for i in range(int(ms.count())):
n = h.ref("")
ms.name(n, i)
if ms.get(n[0]) == -1e+300:
return True
return False
def ptype():
msname = h.ref('')
propList = {}
for i, mechtype in enumerate(['mechs', 'pointps']):
mt = h.MechanismType(
i) # either distributed mechs (0) or point process (1)
propList[mechtype] = {}
for j in range(int(mt.count())):
mt.select(j)
mt.selected(msname)
print('\n\n', msname[0], ' mechanismtype=%d' % j)
pname(msname[0])
ms = h.MechanismStandard(msname[0], 1) # PARAMETER (modifiable)
propList[mechtype][msname[0]] = []
propName = h.ref('')
for prop in range(int(ms.count())):
k = ms.name(propName, prop)
propList[mechtype][msname[0]].append(propName[0])
print(propList)
def barname(mech='it'):
'''return the name of a gbar (max conductance) for a given mechanism name'''
l = []
pname, ms = h.ref(''), h.MechanismStandard(mech, 1)
for i in range(int(ms.count())):
ms.name(pname, i)
l.append(pname[0])
ll = [x for x in l if 'bar' in x]
if len(ll) != 1:
raise Exception("Can't identify proper parameter for %s: %s" %
(mech, ll))
return ll[0]
def get_rangevars(mech_name):
ms = h.MechanismStandard(mech_name)
suffix = '_' + mech_name
lensuffix = len(suffix)
mname = h.ref('')
result = []
for i in range(int(ms.count())):
ms.name(mname, i)
my_mname = mname[0]
if my_mname.endswith(suffix):
my_mname = my_mname[:-lensuffix]
result.append({'type': 'NEURONMECH', 'mech': mech_name, 'var': my_mname, 'name': mech_name + '.' + my_mname})
return result
def get_rangevars(mech_name):
ms = h.MechanismStandard(mech_name)
suffix = '_' + mech_name
lensuffix = len(suffix)
mname = h.ref('')
result = []
for i in range(int(ms.count())):
ms.name(mname, i)
my_mname = mname[0]
if my_mname.endswith(suffix):
my_mname = my_mname[:-lensuffix]
result.append({'type': 'NEURONMECH', 'mech': mech_name, 'var': my_mname, 'name': mech_name + '.' + my_mname})
return result
def _is_loaded_mechanisms():
# copied from:
# https://www.neuron.yale.edu/neuron/static/py_doc/modelspec/programmatic/mechtype.html
mt = h.MechanismType(0)
mname = h.ref('')
mnames = list()
for i in range(mt.count()):
mt.select(i)
mt.selected(mname)
mnames.append(mname[0])
if 'hh2' not in mnames:
return False
else:
return True
def secinfo():
result = "\n"
for sec in h.allsec():
r = [h.ref(0) for _ in range(3)]
pseg = sec.parentseg()
px = ("parent %s(%g)"%(pseg.sec.name(),pseg.x)) if pseg is not None else ""
style = ""
if sec.pt3dstyle():
h.pt3dstyle(1, r[0], r[1], r[2], sec=sec)
style = [i[0] for i in r]
result += "%s L=%g %s %s\n" % (str(sec), sec.L, str(style), px)
for i in range(sec.n3d()):
result += " %d %g %g %g %g\n" % (i, sec.x3d(i), sec.y3d(i), sec.z3d(i), sec.diam3d(i))
return result
def mechVarList():
"""
Function for/to <short description of `netpyne.conversion.neuronPyHoc.mechVarList`>
"""
msname = h.ref('')
varList = {}
for i, mechtype in enumerate(['mechs', 'pointps']):
mt = h.MechanismType(
i) # either distributed mechs (0) or point process (1)
varList[mechtype] = {}
for j in range(int(mt.count())):
mt.select(j)
mt.selected(msname)
ms = h.MechanismStandard(msname[0], 1) # PARAMETER (modifiable)
varList[mechtype][msname[0]] = []
propName = h.ref('')
for var in range(int(ms.count())):
k = ms.name(propName, var)
varList[mechtype][msname[0]].append(propName[0])
return varList
def bld(x, y):
global g, tt, ttstr, grp, sgrp, pras
tt = 0.0
ttstr = h.ref('tt=0.000000000')
v = h.VBox()
v.intercept(1)
g = h.Graph()
g.size(0, x, 0, y)
h.xpanel("", 1)
h.xvarlabel(ttstr)
h.xvalue("group", (this_module, "grp"), 1, ttcallback)
h.xslider((this_module, "sgrp"), 0, 100, ttscallback)
h.xpanel()
v.intercept(0)
v.map("wave front", 100, 100, 700, 500)
return v
def find_template(env,
template_name,
path=['templates'],
template_file=None,
root=0):
"""
Finds and loads a template located in a directory within the given path list.
:param env: :class:'Env'
:param template_name: str; name of hoc template
:param path: list of str; directories to look for hoc template
:param template_file: str; file_name containing definition of hoc template
:param root: int; MPI.COMM_WORLD.rank
"""
pc = env.pc
rank = int(pc.id())
found = False
foundv = h.Vector(1)
template_path = ''
if template_file is None:
template_file = '%s.hoc' % template_name
if pc is not None:
pc.barrier()
if (pc is None) or (int(pc.id()) == root):
for template_dir in path:
if template_file is None:
template_path = '%s/%s.hoc' % (template_dir, template_name)
else:
template_path = '%s/%s' % (template_dir, template_file)
found = os.path.isfile(template_path)
if found and (rank == root):
logger.info('Loaded %s from %s' %
(template_name, template_path))
break
foundv.x[0] = 1 if found else 0
if pc is not None:
pc.barrier()
pc.broadcast(foundv, root)
if foundv.x[0] > 0.0:
s = h.ref(template_path)
if pc is not None:
pc.broadcast(s, root)
h.load_file(s)
else:
raise Exception(
'find_template: template %s not found: file %s; path is %s' %
(template_name, template_file, str(path)))
def get_rangevars(mech_name):
ms = h.MechanismStandard(mech_name)
suffix = "_" + mech_name
lensuffix = len(suffix)
mname = h.ref("")
result = []
for i in range(int(ms.count())):
ms.name(mname, i)
my_mname = mname[0]
if my_mname.endswith(suffix):
my_mname = my_mname[:-lensuffix]
result.append({
"type": "NEURONMECH",
"mech": mech_name,
"var": my_mname,
"name": mech_name + "." + my_mname,
})
return result
def is_loaded_mechanisms():
# copied from:
# https://www.neuron.yale.edu/neuron/static/py_doc/modelspec/programmatic/mechtype.html
mt = h.MechanismType(0)
mname = h.ref('')
mnames = list()
for i in range(mt.count()):
mt.select(i)
mt.selected(mname)
mnames.append(mname[0])
# note this check only works for the original hnn model
# need to generalize for any model
if 'hh2' not in mnames:
return False
else:
return True
def constraintsPanel(self):
self.box = h.HBox()
self.box.intercept(1)
self.box.ref(self)
s = h.Vector()
cvodewrap.states(s)
nstates = len(s)
sref = h.ref('')
h.xpanel("")
h.xlabel('0<=')
for i in range(nstates):
h.xcheckbox('', (self.geq0[i], 'x'), self.constraintsButton)
h.xpanel()
h.xpanel("")
h.xlabel('>=1')
for i in range(nstates):
cvodewrap.statename(i, sref, 1)
h.xcheckbox(sref[0], (self.leq1[i], 'x'), self.constraintsButton)
h.xpanel()
for j in range(self.nsums):
h.xpanel("")
h.xlabel("S%d" % j)
for i in range(nstates):
h.xcheckbox('', (self.sumto1[j][i], 'x'),
self.constraintsButton)
h.xpanel()
h.xpanel("")
h.xbutton("Add Sum-to-1", self.constraintsButton)
h.xbutton("Remove Empty", self.constraintsButton)
h.xbutton("Close", self.constraintsButton)
h.xlabel('QP Solver:')
h.xstatebutton('cvxopt', (self, 'cvxopt_sel'), self.constraintsButton)
h.xstatebutton('custom', (self, 'custom_sel'), self.constraintsButton)
h.xpanel()
self.box.intercept(0)
self.box.map("Constraints")
from neuron import h
h.load_file('stdrun.hoc')
soma = h.Section(name='soma')
seg = soma(0.5)
soma.insert('hh')
ic = h.IClamp(seg)
ic.amp = 40 # since by default a very large section
ic.delay = 1
ic.dur = 1
is_checked_ref = h.ref(0)
class Ref():
def __init__(self, checked):
self.checked = checked
is_checked = Ref(0)
def onpress():
print("checkbox changed! as if")
if isinstance(is_checked, Ref):
print("value: ", is_checked.checked)
else:
print("value: ", is_checked[0])
return
#now only in HocTopLevelInterpreter
names = ['ref', 'cas', 'allsec', 'Section', 'setpointer']
from neuron import h
o = h
d = dir(o)
for i in names:
assert(i in d)
print((eval("o.%s" % i).__doc__))
o = h.IClamp()
d = dir(o)
for i in names:
assert(i not in d)
assert('get_segment' in d)
print((o.get_segment.__doc__))
print("success")
s = [h.Section(name='s'+str(i)) for i in range(5)]
print(s)
for sec in h.allsec():
print((h.cas()))
r = h.ref("hello")
print((r[0] == 'hello'))
from neuron import h
# Print the names of all density mechanisms
mt = h.MechanismType(0)
mname = h.ref('')
integer = int(mt.count())
print(type(integer))
for i in range(integer):
mt.select(i)
mt.selected(mname)
print(mname[0])
def get_mech_globals(mechname):
ms = h.MechanismStandard(mechname, -1)
name = h.ref('')
mech_globals = []
integer2 = int(ms.count())
for j in range(integer2):
ms.name(name, j)
mech_globals.append(name[0])
return mech_globals
print(get_mech_globals('ca_ion'))
def psection(sec):
from neuron import h, _has_rxd
try:
if _has_rxd['crxd']:
from neuron import crxd as rxd
from neuron.crxd import region, species
from neuron.crxd import rxd as rxd_module
else:
from neuron import rxd
from neuron.rxd import region, species
from neuron.rxd import rxd as rxd_module
have_rxd = True
except:
have_rxd = False
results = {}
mname = h.ref('')
# point processes
pps = {}
mt = h.MechanismType(1)
for i in range(int(mt.count())):
mt.select(i)
mypps = set()
pp = mt.pp_begin(sec=sec)
while pp is not None:
mypps.add(pp)
pp = mt.pp_next()
if mypps:
mt.selected(mname)
pps[mname[0]] = mypps
results['point_processes'] = pps
center_seg_dir = dir(sec(0.5))
mechs_present = []
# membrane mechanisms
mt = h.MechanismType(0)
for i in range(int(mt.count())):
mt.select(i)
mt.selected(mname)
name = mname[0]
if name in center_seg_dir:
mechs_present.append(name)
results['density_mechs'] = {}
results['ions'] = {}
for mech in mechs_present:
my_results = {}
ms = h.MechanismStandard(mech, 0)
for j in range(int(ms.count())):
n = int(ms.name(mname, j))
name = mname[0]
pvals = []
# TODO: technically this is assuming everything that ends with _ion
# is an ion. Check this.
if mech.endswith('_ion'):
pvals = [getattr(seg, name) for seg in sec]
else:
mechname = name#+ '_' + mech
for seg in sec:
if n > 1:
pvals.append([getattr(seg, mechname)[i] for i in range(n)])
else:
pvals.append(getattr(seg, mechname))
my_results[name[:-(len(mech) + 1)] if name.endswith('_' + mech) else name] = pvals
# TODO: should be a better way of testing if an ion
if mech.endswith('_ion'):
results['ions'][mech[:-4]] = my_results
else:
results['density_mechs'][mech] = my_results
morphology = {'L': sec.L,
'diam': [seg.diam for seg in sec],
'pts3d': [(sec.x3d(i), sec.y3d(i), sec.z3d(i), sec.diam3d(i)) for i in range(sec.n3d())],
'parent': sec.parentseg(),
'trueparent': sec.trueparentseg()}
results['morphology'] = morphology
results['nseg'] = sec.nseg
results['Ra'] = sec.Ra
results['cm'] = [seg.cm for seg in sec]
if have_rxd:
regions = {r() for r in region._all_regions if r() is not None and sec in r().secs}
results['regions'] = regions
my_species = []
for sp in species._all_species:
sp = sp()
if sp is not None:
sp_regions = sp._regions
if not hasattr(sp_regions, '__len__'):
sp_regions = [sp_regions]
if any(r in sp_regions for r in regions):
my_species.append(sp)
results['species'] = set(my_species)
results['name'] = sec.hname()
results['hoc_internal_name'] = sec.hoc_internal_name()
results['cell'] = sec.cell()
#all_active_reactions = [r() for r in rxd_module._all_reactions if r() is not None]
return results
def psection(sec):
from neuron import h, _has_rxd
try:
if _has_rxd['crxd']:
from neuron import crxd as rxd
from neuron.crxd import region, species
from neuron.crxd import rxd as rxd_module
else:
from neuron import rxd
from neuron.rxd import region, species
from neuron.rxd import rxd as rxd_module
have_rxd = True
except:
have_rxd = False
results = {}
mname = h.ref('')
# point processes
pps = {}
mt = h.MechanismType(1)
for i in range(int(mt.count())):
mt.select(i)
mypps = set()
pp = mt.pp_begin(sec=sec)
while pp is not None:
mypps.add(pp)
pp = mt.pp_next()
if mypps:
mt.selected(mname)
pps[mname[0]] = mypps
results['point_processes'] = pps
center_seg_dir = dir(sec(0.5))
mechs_present = []
# membrane mechanisms
mt = h.MechanismType(0)
for i in range(int(mt.count())):
mt.select(i)
mt.selected(mname)
name = mname[0]
if name in center_seg_dir:
mechs_present.append(name)
results['density_mechs'] = {}
results['ions'] = {}
for mech in mechs_present:
my_results = {}
ms = h.MechanismStandard(mech, 0)
for j in range(int(ms.count())):
n = int(ms.name(mname, j))
name = mname[0]
pvals = []
# TODO: technically this is assuming everything that ends with _ion
# is an ion. Check this.
if mech.endswith('_ion'):
pvals = [getattr(seg, name) for seg in sec]
else:
mechname = name #+ '_' + mech
for seg in sec:
if n > 1:
pvals.append(
[getattr(seg, mechname)[i] for i in range(n)])
else:
pvals.append(getattr(seg, mechname))
my_results[name[:-(len(mech) +
1)] if name.endswith('_' +
mech) else name] = pvals
# TODO: should be a better way of testing if an ion
if mech.endswith('_ion'):
results['ions'][mech[:-4]] = my_results
else:
results['density_mechs'][mech] = my_results
morphology = {
'L':
sec.L,
'diam': [seg.diam for seg in sec],
'pts3d': [(sec.x3d(i), sec.y3d(i), sec.z3d(i), sec.diam3d(i))
for i in range(sec.n3d())],
'parent':
sec.parentseg(),
'trueparent':
sec.trueparentseg()
}
results['morphology'] = morphology
results['nseg'] = sec.nseg
results['Ra'] = sec.Ra
results['cm'] = [seg.cm for seg in sec]
if have_rxd:
regions = {
r()
for r in region._all_regions if r() is not None and sec in r().secs
}
results['regions'] = regions
my_species = []
for sp in species._all_species:
sp = sp()
if sp is not None:
sp_regions = sp._regions
if not hasattr(sp_regions, '__len__'):
sp_regions = [sp_regions]
if any(r in sp_regions for r in regions):
my_species.append(sp)
results['species'] = set(my_species)
results['name'] = sec.hname()
results['hoc_internal_name'] = sec.hoc_internal_name()
results['cell'] = sec.cell()
#all_active_reactions = [r() for r in rxd_module._all_reactions if r() is not None]
return results
from neuron import h
for j in range(2):
mt = h.MechanismType(j)
name = h.ref("")
for i in range(mt.count()):
mt.select(i)
mt.selected(name)
a = mt.code().split(sep='\n')
print(("%s : %s" % (name[0], a[0])))
def all_mechanism_types():
"""Return a dictionary of all available mechanism types.
Each dictionary key is the name of a mechanism and each value is
another dictionary containing information about the mechanism::
mechanism_types = {
'mech_name1': {
'point_process': bool,
'artificial_cell': bool,
'netcon_target': bool,
'has_netevent': bool,
'internal_type': int,
'globals': {name:size, ...},
'parameters': {name:size, ...},
'assigned': {name:size, ...},
'state': {name:size, ...},
},
'mech_name2': {...},
'mech_name3': {...},
...
}
* point_process: False for distributed mechanisms, True for point
processes and artificial cells.
* artificial_cell: True for artificial cells, False otherwise
* netcon_target: True if the mechanism can receive NetCon events
* has_netevent: True if the mechanism can emit NetCon events
* internal_type: Integer specifying the NEURON internal type index of
the mechanism
* globals: dict of the name and vector size of the mechanism's global
variables
* parameters: dict of the name and vector size of the mechanism's
parameter variables
* assigned: dict of the name and vector size of the mechanism's
assigned variables
* state: dict of the name and vector size of the mechanism's state
variables
For more information on global, parameter, assigned, and state
variables see:
http://www.neuron.yale.edu/neuron/static/docs/help/neuron/nmodl/nmodl.html
"""
if Mechanism._mech_types is None:
Mechanism._mech_types = collections.OrderedDict()
mname = h.ref('')
# Iterate over two mechanism types (distributed, point/artificial)
for i in [0, 1]:
mt = h.MechanismType(i)
nmech = int(mt.count())
# Iterate over all mechanisms of this type
for j in range(nmech):
mt.select(j)
mt.selected(mname)
# General mechanism properties
name = mname[0] # convert hoc string ptr to python str
desc = {
'point_process': bool(i),
'netcon_target': bool(mt.is_netcon_target(j)),
'has_netevent': bool(mt.has_net_event(j)),
'artificial_cell': bool(mt.is_artificial(j)),
'internal_type': int(mt.internal_type()),
}
# Collect information about 4 different types of variables
for k,ptype in [(-1, 'globals'), (1, 'parameters'),
(2, 'assigned'), (3, 'state')]:
desc[ptype] = {} # collections.OrderedDict()
ms = h.MechanismStandard(name, k)
for l in range(int(ms.count())):
psize = ms.name(mname, l)
pname = mname[0] # parameter name
desc[ptype][pname] = int(psize)
# Assemble everything in one place
Mechanism._mech_types[name] = desc
return Mechanism._mech_types