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import os
import h5py
import math
import pandas as pd
from neuron import h
import numpy as np
from bmtk.simulator.bionet.modules.sim_module import SimulatorMod
from bmtk.utils.sonata.utils import add_hdf5_magic, add_hdf5_version
pc = h.ParallelContext()
MPI_RANK = int(pc.id())
N_HOSTS = int(pc.nhost())
[docs]class EcpMod(SimulatorMod):
def __init__(self, tmp_dir, file_name, electrode_positions, contributions_dir=None, cells=None, variable_name='v',
electrode_channels=None, cell_bounds=None, minimum_distance=None):
self._ecp_output = file_name if os.path.isabs(file_name) else os.path.join(tmp_dir, file_name)
self._positions_file = electrode_positions
self._tmp_outputdir = tmp_dir
if contributions_dir is not None:
self._save_individ_cells = True
self._contributions_dir = contributions_dir if os.path.isabs(contributions_dir) else os.path.join(tmp_dir, contributions_dir)
else:
self._save_individ_cells = False
self._contributions_dir = None
if cell_bounds is None:
self._cells = cells
else:
self._cells = list(np.arange(cell_bounds[0],cell_bounds[1]+1))
if minimum_distance and minimum_distance != 'auto':
try:
minimum_distance = max(float(minimum_distance), 0)
except Exception as e:
minimum_distance = 0
self.minimum_distance = minimum_distance
self._rel = None
self._fih1 = None
self._rel_nsites = 0
self._block_size = 0
self._saved_gids = {}
self._nsteps = 0
self._tstep = 0 # accumlative time step
# self._rel_time = 0 #
self._block_step = 0 # time step within the given block of time
self._tstep_start_block = 0
self._data_block = None
self._cell_var_files = {}
self._tmp_ecp_file = self._get_tmp_fname(MPI_RANK)
self._tmp_ecp_handle = None
# self._tmp_ecp_dataset = None
self._local_gids = []
def _get_tmp_fname(self, rank):
return os.path.join(self._tmp_outputdir, 'tmp_{}_{}'.format(MPI_RANK, os.path.basename(self._ecp_output)))
def _create_ecp_file(self, sim):
dt = sim.dt
tstop = sim.tstop
self._nsteps = int(round(tstop/dt))
# create file to temporary store ecp data on each rank
self._tmp_ecp_handle = h5py.File(self._tmp_ecp_file, 'a')
self._tmp_ecp_handle.create_dataset('/ecp/data', (self._nsteps, self._rel_nsites), maxshape=(None, self._rel_nsites),
dtype=np.float64,
chunks=True)
# only the primary node will need to save the final ecp
if MPI_RANK == 0:
with h5py.File(self._ecp_output, 'w') as f5:
add_hdf5_magic(f5)
add_hdf5_version(f5)
f5.create_dataset('/ecp/data', (self._nsteps, self._rel_nsites), maxshape=(None, self._rel_nsites),
dtype=np.float64,
chunks=True)
f5['/ecp/data'].attrs['units'] = 'mV'
#f5.attrs['dt'] = dt
#f5.attrs['tstart'] = 0.0
#f5.attrs['tstop'] = tstop
f5.create_dataset('/ecp/time', (3,), data=(0.0, sim.tstop, sim.dt))
f5['/ecp/time'].attrs['units'] = 'ms'
# Save channels. Current we record from all channels, may want to be more selective in the future.
f5.create_dataset('/ecp/channel_id', data=np.arange(self._rel.nsites))
pc.barrier()
def _create_cell_file(self, gid):
if not self._save_individ_cells:
return
file_name = os.path.join(self._contributions_dir, '{}.h5'.format(int(gid)))
file_h5 = h5py.File(file_name, 'a')
self._cell_var_files[gid] = file_h5
file_h5.create_dataset('/ecp/data', (self._nsteps, self._rel_nsites), maxshape=(None, self._rel_nsites), chunks=True)
# self._cell_var_files[gid] = file_h5['ecp']
def _calculate_ecp(self, sim):
self._rel = RecXElectrode(self._positions_file, self.minimum_distance)
for gid in self._local_gids:
cell = sim.net.get_cell_gid(gid)
#cell = sim.net.get_local_cell(gid)
# cell = sim.net.cells[gid]
self._rel.calc_transfer_resistance(gid, cell.seg_coords)
self._rel_nsites = self._rel.nsites
sim.h.cvode.use_fast_imem(1) # make i_membrane_ a range variable
def set_pointers():
for gid, cell in sim.net.get_local_cells().items():
#for gid, cell in sim.net.local_cells.items():
# for gid, cell in sim.net.cells.items():
cell.set_im_ptr()
self._fih1 = sim.h.FInitializeHandler(0, set_pointers)
def _save_block(self, interval):
"""Add """
itstart, itend = interval
self._tmp_ecp_handle['/ecp/data'][itstart:itend, :] += self._data_block[0:(itend - itstart), :]
self._tmp_ecp_handle.flush()
self._data_block[:] = 0.0
def _save_ecp(self, sim):
"""Save ECP from each rank to disk into a single file"""
block_size = sim.nsteps_block
nblocks, remain = divmod(self._nsteps, block_size)
ivals = [i*block_size for i in range(nblocks+1)]
if remain != 0:
ivals.append(self._nsteps)
for rank in range(N_HOSTS): # iterate over the ranks
if rank == MPI_RANK: # wait until finished with a particular rank
with h5py.File(self._ecp_output, 'a') as ecp_f5:
for i in range(len(ivals)-1):
ecp_f5['/ecp/data'][ivals[i]:ivals[i+1], :] += self._tmp_ecp_handle['/ecp/data'][ivals[i]:ivals[i+1], :]
pc.barrier()
def _save_cell_vars(self, interval):
itstart, itend = interval
for gid, data in self._saved_gids.items():
h5_file = self._cell_var_files[gid]
h5_file['/ecp/data'][itstart:itend, :] = data[0:(itend-itstart), :]
h5_file.flush()
data[:] = 0.0
def _delete_tmp_files(self):
if os.path.exists(self._tmp_ecp_file):
self._tmp_ecp_handle.close()
os.remove(self._tmp_ecp_file)
[docs] def initialize(self, sim):
if self._contributions_dir and (not os.path.exists(self._contributions_dir)) and MPI_RANK == 0:
os.makedirs(self._contributions_dir)
pc.barrier()
self._block_size = sim.nsteps_block
# Get list of gids being recorded
selected_gids = set(sim.net.get_node_set(self._cells).gids())
self._local_gids = list(set(sim.biophysical_gids) & selected_gids)
self._calculate_ecp(sim)
self._create_ecp_file(sim)
# ecp data
self._data_block = np.zeros((self._block_size, self._rel_nsites))
# create list of all cells whose ecp values will be saved separetly
self._saved_gids = {gid: np.empty((self._block_size, self._rel_nsites))
for gid in self._local_gids}
for gid in self._saved_gids.keys():
self._create_cell_file(gid)
pc.barrier()
[docs] def step(self, sim, tstep):
for gid in self._local_gids: # compute ecp only from the biophysical cells
cell = sim.net.get_cell_gid(gid)
im = cell.get_im()
tr = self._rel.get_transfer_resistance(gid)
ecp = np.dot(tr, im)
if gid in self._saved_gids.keys():
# save individual contribution
self._saved_gids[gid][self._block_step, :] = ecp
# add to total ecp contribution
self._data_block[self._block_step, :] += ecp
self._block_step += 1
[docs] def block(self, sim, block_interval):
self._save_block(block_interval)
if self._save_individ_cells:
self._save_cell_vars(block_interval)
self._block_step = 0
self._tstep_start_block = self._tstep
[docs] def finalize(self, sim):
if self._block_step > 0:
# just in case the simulation doesn't end on a block step
self.block(sim, (sim.n_steps - self._block_step, sim.n_steps))
self._save_ecp(sim)
self._delete_tmp_files()
pc.barrier()
[docs]class RecXElectrode(object):
"""Extracellular electrode
"""
def __init__(self, positions, minimum_distance):
"""Create an array"""
# self.conf = conf
electrode_file = positions # self.conf["recXelectrode"]["positions"]
# convert coordinates to ndarray, The first index is xyz and the second is the channel number
el_df = pd.read_csv(electrode_file, sep=' ')
self.pos = el_df[['x_pos', 'y_pos', 'z_pos']].T.values
#self.pos = el_df.as_matrix(columns=['x_pos', 'y_pos', 'z_pos']).T
self.nsites = self.pos.shape[1]
# self.conf['run']['nsites'] = self.nsites # add to the config
self.transfer_resistances = {} # V_e = transfer_resistance*Im
self.minimum_distance = minimum_distance
[docs] def drift(self):
# will include function to model electrode drift
pass
[docs] def get_transfer_resistance(self, gid):
return self.transfer_resistances[gid]
[docs] def calc_transfer_resistance(self, gid, seg_coords):
"""Precompute mapping from segment to electrode locations"""
sigma = 0.3 # mS/mm
r05 = (seg_coords.p0 + seg_coords.p1) / 2
dl = seg_coords.p1 - seg_coords.p0
if self.minimum_distance == 'auto':
rm = seg_coords.d / 2 # set minimum distance to the radius of each segment
else:
rm = self.minimum_distance # set a common minimum distance
nseg = r05.shape[1]
tr = np.zeros((self.nsites, nseg))
for j in range(self.nsites): # calculate mapping for each site on the electrode
rel = np.expand_dims(self.pos[:, j], axis=1) # coordinates of a j-th site on the electrode
rel_05 = rel - r05 # distance between electrode and segment centers
# compute dot product column-wise, the resulting array has as many columns as original
r2 = np.einsum('ij,ij->j', rel_05, rel_05)
# compute dot product column-wise, the resulting array has as many columns as original
rlldl = np.einsum('ij,ij->j', rel_05, dl)
dlmag = np.linalg.norm(dl, axis=0) # length of each segment
rll = abs(rlldl / dlmag) # component of r parallel to the segment axis it must be always positive
rT2 = r2 - rll ** 2 # square of perpendicular component
up = rll + dlmag / 2
low = rll - dlmag / 2
if self.minimum_distance:
# if electrode projection on segment axis is within distance rm to the segment
# check perpendicular distance to the segment axis and set lower limit to rm
np.fmax(rT2, rm * rm, out=rT2, where=low < rm)
num = up + np.sqrt(up ** 2 + rT2)
den = low + np.sqrt(low ** 2 + rT2)
tr[j, :] = np.log(num / den) / dlmag # units of (um) use with im_ (total seg current)
tr *= 1 / (4 * math.pi * sigma)
self.transfer_resistances[gid] = tr
