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import os
import h5py
from neuron import h
from bmtk.simulator.bionet.modules.sim_module import SimulatorMod
from bmtk.simulator.bionet.io_tools import io
from bmtk.utils.reports import CompartmentReport
try:
# Check to see if h5py is built to run in parallel
if h5py.get_config().mpi:
MembraneRecorder = CompartmentReport
else:
MembraneRecorder = CompartmentReport
except Exception as e:
MembraneRecorder = CompartmentReport
MembraneRecorder._io = io
pc = h.ParallelContext()
MPI_RANK = int(pc.id())
N_HOSTS = int(pc.nhost())
[docs]def first_element(lst):
return lst[0]
transforms_table = {
'first_element': first_element,
}
[docs]class MembraneReport(SimulatorMod):
def __init__(self, tmp_dir, file_name, variable_name, cells=None, gids=None, sections='all', buffer_data=True, transform={}, **kwargs):
"""Module used for saving NEURON cell properities at each given step of the simulation.
:param tmp_dir:
:param file_name: name of h5 file to save variable.
:param variables: list of cell variables to record
:param gids: list of gids to to record
:param sections:
:param buffer_data: Set to true then data will be saved to memory until written to disk during each block, reqs.
more memory but faster. Set to false and data will be written to disk on each step (default: True)
"""
self._all_variables = list(variable_name)
self._variables = list(variable_name)
self._report_name = self._variables[0]
self._transforms = {}
# self._special_variables = []
for var_name, fnc_name in transform.items():
if fnc_name is None or len(fnc_name) == 0:
del self._transforms[var_name]
continue
fnc = transforms_table[fnc_name]
self._transforms[var_name] = fnc
self._variables.remove(var_name)
self._tmp_dir = tmp_dir
# TODO: Full path should be determined by config/simulation_reports module
self._file_name = file_name if os.path.isabs(file_name) else os.path.join(tmp_dir, file_name)
self._all_gids = cells
self._local_gids = []
self._sections = sections
self._var_recorder = None
self._gid_list = gids # list of all gids that will have their variables saved
self._data_block = {} # table of variable data indexed by [gid][variable]
self._block_step = 0 # time step within a given block
self._gid_map = None
def _get_gids(self, sim):
# get list of gids to save. Will only work for biophysical cells saved on the current MPI rank
if self._gid_list is not None:
selected_gids = set(self._gid_list)
else:
selected_gids = set(sim.net.get_node_set(self._all_gids).gids())
self._local_gids = list(set(sim.biophysical_gids) & selected_gids)
def _save_sim_data(self, sim):
pass
[docs] def initialize(self, sim):
self._var_recorder = MembraneRecorder(self._file_name, mode='w', variable=self._report_name,
buffer_size=sim.nsteps_block, tstart=0.0, tstop=sim.tstop, dt=sim.dt)
self._gid_map = sim.net.gid_pool
self._get_gids(sim)
#self._save_sim_data(sim)
# TODO: get section by name and/or list of section ids
# Build segment/section list
for gid in self._local_gids:
pop_id = self._gid_map.get_pool_id(gid)
sec_list = []
seg_list = []
cell = sim.net.get_cell_gid(gid)
cell.store_segments()
for sec_id, sec in enumerate(cell.get_sections()):
for seg in sec:
# TODO: Make sure the seg has the recorded variable(s)
sec_list.append(sec_id)
seg_list.append(seg.x)
self._var_recorder.add_cell(node_id=pop_id.node_id, population=pop_id.population, element_ids=sec_list,
element_pos=seg_list)
self._var_recorder.initialize()
[docs] def step(self, sim, tstep):
# save all necessary cells/variables at the current time-step into memory
for gid in self._local_gids:
pop_id = self._gid_map.get_pool_id(gid)
cell = sim.net.get_cell_gid(gid)
for var_name in self._variables:
seg_vals = [getattr(seg, var_name) for seg in cell.get_segments()]
self._var_recorder.record_cell(pop_id.node_id, population=pop_id.population, vals=seg_vals, tstep=tstep)
for var_name, fnc in self._transforms.items():
seg_vals = [fnc(getattr(seg, var_name)) for seg in cell.get_segments()]
# self._var_recorder.record_cell(gid, var_name, seg_vals, tstep)
self._var_recorder.record_cell(pop_id.node_id, population=pop_id.population, val=seg_vals, tstep=tstep)
self._block_step += 1
[docs] def block(self, sim, block_interval):
# write variables in memory to file
self._var_recorder.flush()
[docs] def finalize(self, sim):
# TODO: Build in mpi signaling into var_recorder
pc.barrier()
self._var_recorder.close()
#pc.barrier()
#self._var_recorder.merge()
[docs]class SomaReport(MembraneReport):
"""Special case for when only needing to save the soma variable"""
def __init__(self, tmp_dir, file_name, variable_name, cells, sections='soma', buffer_data=True, transform={}, **kwargs):
super(SomaReport, self).__init__(tmp_dir=tmp_dir, file_name=file_name, variable_name=variable_name, cells=cells,
sections=sections, buffer_data=buffer_data, transform=transform, **kwargs)
[docs] def initialize(self, sim):
self._var_recorder = MembraneRecorder(self._file_name, mode='w', variable=self._report_name,
buffer_size=sim.nsteps_block, tstart=0.0, tstop=sim.tstop, dt=sim.dt)
self._gid_map = sim.net.gid_pool
self._get_gids(sim)
for gid in self._local_gids:
pop_id = self._gid_map.get_pool_id(gid)
self._var_recorder.add_cell(pop_id.node_id, population=pop_id.population, element_ids=[0],
element_pos=[0.5])
# self._var_recorder.initialize(sim.n_steps, sim.nsteps_block)
self._var_recorder.initialize()
[docs] def step(self, sim, tstep, rel_time=0.0):
# save all necessary cells/variables at the current time-step into memory
for gid in self._local_gids:
pop_id = self._gid_map.get_pool_id(gid)
cell = sim.net.get_cell_gid(gid)
for var_name in self._variables:
var_val = getattr(cell.hobj.soma[0](0.5), var_name)
self._var_recorder.record_cell(pop_id.node_id, population=pop_id.population, vals=[var_val],
tstep=tstep)
for var_name, fnc in self._transforms.items():
var_val = getattr(cell.hobj.soma[0](0.5), var_name)
new_val = fnc(var_val)
self._var_recorder.record_cell(pop_id.node_id, population=pop_id.population, vals=[new_val],
tstep=tstep)
self._block_step += 1