from neuron import h, crxd as rxd
from matplotlib import pyplot
import numpy
import __main__
name = __main__.__file__
if name[-3 :] == '.py':
name = name[: -3]
h.load_file('stdrun.hoc')
dend = h.Section()
dend.diam = 2
dend.nseg = 101
dend.L = 100
rxd.set_solve_type(dimension=3)
diff_constant = 1
r = rxd.Region(h.allsec(),dx=0.5)
ca = rxd.Species(r, d=diff_constant, initial=lambda node:
1 if 0.4 < node.x < 0.6 else 0)
h.finitialize()
initial_amount = (numpy.array(ca.nodes.concentration) * numpy.array(ca.nodes.volume)).sum()
for t in [25, 50, 75, 100, 125]:
h.continuerun(t)
pyplot.plot([nd.x for nd in ca.nodes], ca.nodes.concentration)
final_amount = (numpy.array(ca.nodes.concentration) * numpy.array(ca.nodes.volume)).sum()
def clearAll():
"""
Function to clear all sim objects in memory
"""
from .. import sim
import numpy as np
# clean up
sim.pc.barrier()
sim.pc.gid_clear() # clear previous gid settings
# clean cells and simData in all nodes
if hasattr(sim, 'net'):
sim.clearObj([cell.__dict__ if hasattr(cell, '__dict__') else cell for cell in sim.net.cells])
if hasattr(sim, 'simData'):
if 'stims' in list(sim.simData.keys()):
sim.clearObj([stim for stim in sim.simData['stims']])
for key in list(sim.simData.keys()): del sim.simData[key]
if hasattr(sim, 'net'):
for c in sim.net.cells: del c
for p in sim.net.pops: del p
del sim.net.params
# clean cells and simData gathered in master node
if hasattr(sim, 'rank'):
if sim.rank == 0:
if hasattr(sim, 'net'):
if hasattr(sim.net, 'allCells'):
sim.clearObj([cell.__dict__ if hasattr(cell, '__dict__') else cell for cell in sim.net.allCells])
if hasattr(sim, 'allSimData'):
for key in list(sim.allSimData.keys()): del sim.allSimData[key]
if 'stims' in list(sim.allSimData.keys()):
sim.clearObj([stim for stim in sim.allSimData['stims']])
if hasattr(sim.net, 'allCells'):
for c in sim.net.allCells: del c
del sim.net.allCells
if hasattr(sim.net, 'allPops'):
for p in sim.net.allPops: del p
del sim.net.allPops
if hasattr(sim, 'allSimData'):
del sim.allSimData
import matplotlib
matplotlib.pyplot.clf()
matplotlib.pyplot.close('all')
# clean rxd components
if hasattr(sim.net, 'rxd'):
sim.clearObj(sim.net.rxd)
if 'rxd' not in globals():
try:
from neuron import crxd as rxd
except:
pass
#try:
for r in rxd.rxd._all_reactions[:]:
if r():
rxd.rxd._unregister_reaction(r)
for s in rxd.species._all_species:
if s():
s().__del__()
rxd.region._all_regions = []
rxd.region._region_count = 0
rxd.region._c_region_lookup = None
rxd.species._species_counts = 0
rxd.section1d._purge_cptrs()
rxd.initializer.has_initialized = False
rxd.rxd.free_conc_ptrs()
rxd.rxd.free_curr_ptrs()
rxd.rxd.rxd_include_node_flux1D(0, None, None, None)
rxd.species._has_1d = False
rxd.species._has_3d = False
rxd.rxd._zero_volume_indices = np.ndarray(0, dtype=np.int_)
rxd.set_solve_type(dimension=1)
# clear reactions in case next sim does not use rxd
rxd.rxd.clear_rates()
for obj in rxd.__dict__:
sim.clearObj(obj)
#except:
# pass
if hasattr(sim, 'net'):
del sim.net
import gc; gc.collect()
dend1 = h.Section()
dend1.diam = 2
dend1.nseg = 101
dend1.L = 50
dend2 = h.Section()
dend2.diam = 2
dend2.nseg = 101
dend2.L = 50
dend2.connect(dend1)
diff_constant = 1
h.cvode_active(True)
r = rxd.Region(h.allsec(), dx=0.25)
rxd.set_solve_type([dend1], dimension=3)
ca = rxd.Species(
r,
d=diff_constant,
atolscale=0.1,
initial=lambda node: 1 if (0.8 < node.x and node.segment in dend1) or
(node.x < 0.2 and node.segment in dend2) else 0,
)
bistable_reaction = rxd.Rate(ca, -ca * (1 - ca) * (0.01 - ca))
h.finitialize()
for i in range(2):
h.fadvance()
rxd.nthread(2)
for i in range(2, 4):
