def __init__(self,
tmp_dir,
spikes_file_csv=None,
spikes_file=None,
spikes_file_nwb=None,
spikes_sort_order=None):
def _get_path(file_name):
# Unless file-name is an absolute path then it should be placed in the $OUTPUT_DIR
if file_name is None:
return None
return file_name if os.path.isabs(file_name) else os.path.join(
tmp_dir, file_name)
self._csv_fname = _get_path(spikes_file_csv)
self._h5_fname = _get_path(spikes_file)
self._nwb_fname = _get_path(spikes_file_nwb)
self._tmp_dir = tmp_dir
self._tmp_file_base = 'tmp_spike_times'
self._spike_labels = os.path.join(self._tmp_dir, self._tmp_file_base)
self._spike_writer = SpikeTrainWriter(tmp_dir=tmp_dir,
mpi_rank=MPI_RANK,
mpi_size=N_HOSTS)
self._spike_writer.delimiter = '\t'
self._spike_writer.gid_col = 0
self._spike_writer.time_col = 1
self._sort_order = spikes_sort_order
self._spike_detector = None
def __init__(self,
tmp_dir,
spikes_file_csv=None,
spikes_file=None,
spikes_file_nwb=None,
spikes_sort_order=None):
# TODO: Have option to turn off caching spikes to csv.
def _file_path(file_name):
if file_name is None:
return None
return file_name if os.path.isabs(file_name) else os.path.join(
tmp_dir, file_name)
self._csv_fname = _file_path(spikes_file_csv)
self._save_csv = spikes_file_csv is not None
self._h5_fname = _file_path(spikes_file)
self._save_h5 = spikes_file is not None
self._nwb_fname = _file_path(spikes_file_nwb)
self._save_nwb = spikes_file_nwb is not None
self._tmpdir = tmp_dir
self._sort_order = spikes_sort_order
self._spike_writer = SpikeTrainWriter(tmp_dir=tmp_dir,
mpi_rank=MPI_RANK,
mpi_size=N_HOSTS)
def __spike_writer_orig(self):
from bmtk.utils.io.spike_trains import SpikeTrainWriter
tmpdir = tempfile.mkdtemp()
spike_trains = SpikeTrainWriter(tmpdir)
for node_id in range(1000):
spike_trains.add_spike(1.0, node_id)
for node_id in range(1000, 3000):
spike_trains.add_spikes(np.linspace(0, 2000.0, 1000), node_id)
spike_trains.flush()
spike_trains.close()
def __init__(self,
tmp_dir,
spikes_file_csv=None,
spikes_file=None,
spikes_file_nwb=None,
spikes_sort_order=None):
# TODO: Have option to turn off caching spikes to csv.
self._csv_fname = spikes_file_csv
self._save_csv = spikes_file_csv is not None
self._h5_fname = spikes_file
self._save_h5 = spikes_file is not None
self._nwb_fname = spikes_file_nwb
self._save_nwb = spikes_file_nwb is not None
self._tmpdir = tmp_dir
self._sort_order = spikes_sort_order
self._spike_writer = SpikeTrainWriter(tmp_dir=tmp_dir,
mpi_rank=MPI_RANK,
mpi_size=N_HOSTS)
def __init__(self,
tmp_dir,
spikes_file_csv=None,
spikes_file=None,
spikes_file_nwb=None,
spikes_sort_order=None):
self._csv_fname = spikes_file_csv
self._h5_fname = spikes_file
self._nwb_fname = spikes_file_nwb
self._tmp_dir = tmp_dir
self._tmp_file_base = 'tmp_spike_times'
self._spike_labels = os.path.join(self._tmp_dir, self._tmp_file_base)
self._spike_writer = SpikeTrainWriter(tmp_dir=tmp_dir,
mpi_rank=MPI_RANK,
mpi_size=N_HOSTS)
self._spike_writer.delimiter = '\t'
self._spike_writer.gid_col = 0
self._spike_writer.time_col = 1
self._sort_order = spikes_sort_order
self._spike_detector = None
def __init__(self,
spikes_file_csv=None,
spikes_file=None,
spikes_file_nwb=None,
tmp_dir='output'):
def _get_file_path(file_name):
if file_name is None or os.path.isabs(file_name):
return file_name
return os.path.join(tmp_dir, file_name)
self._csv_fname = _get_file_path(spikes_file_csv)
self._save_csv = spikes_file_csv is not None
self._h5_fname = _get_file_path(spikes_file)
self._save_h5 = spikes_file is not None
self._nwb_fname = _get_file_path(spikes_file_nwb)
self._save_nwb = spikes_file_nwb is not None
self._tmpdir = tmp_dir
self._spike_writer = SpikeTrainWriter(tmp_dir=tmp_dir)
class SpikesMod(SimulatorMod):
"""Module use for saving spikes
"""
def __init__(self,
tmp_dir,
spikes_file_csv=None,
spikes_file=None,
spikes_file_nwb=None,
spikes_sort_order=None):
# TODO: Have option to turn off caching spikes to csv.
self._csv_fname = spikes_file_csv
self._save_csv = spikes_file_csv is not None
self._h5_fname = spikes_file
self._save_h5 = spikes_file is not None
self._nwb_fname = spikes_file_nwb
self._save_nwb = spikes_file_nwb is not None
self._tmpdir = tmp_dir
self._sort_order = spikes_sort_order
self._spike_writer = SpikeTrainWriter(tmp_dir=tmp_dir,
mpi_rank=MPI_RANK,
mpi_size=N_HOSTS)
def initialize(self, sim):
# TODO: since it's possible that other modules may need to access spikes, set_spikes_recordings() should
# probably be called in the simulator itself.
sim.set_spikes_recording()
def block(self, sim, block_interval):
# take spikes from Simulator spikes vector and save to the tmp file
for gid, tVec in sim.spikes_table.items():
for t in tVec:
self._spike_writer.add_spike(time=t, gid=gid)
pc.barrier() # wait until all ranks have been saved
sim.set_spikes_recording() # reset recording vector
def finalize(self, sim):
self._spike_writer.flush()
pc.barrier()
if self._save_csv:
self._spike_writer.to_csv(self._csv_fname,
sort_order=self._sort_order)
pc.barrier()
if self._save_h5:
self._spike_writer.to_hdf5(self._h5_fname,
sort_order=self._sort_order)
pc.barrier()
if self._save_nwb:
self._spike_writer.to_nwb(self._nwb_fname,
sort_order=self._sort_order)
pc.barrier()
self._spike_writer.close()
class SpikesMod(object):
"""Module use for saving spikes
"""
def __init__(self,
tmp_dir,
spikes_file_csv=None,
spikes_file=None,
spikes_file_nwb=None,
spikes_sort_order=None):
def _get_path(file_name):
# Unless file-name is an absolute path then it should be placed in the $OUTPUT_DIR
if file_name is None:
return None
return file_name if os.path.isabs(file_name) else os.path.join(
tmp_dir, file_name)
self._csv_fname = _get_path(spikes_file_csv)
self._h5_fname = _get_path(spikes_file)
self._nwb_fname = _get_path(spikes_file_nwb)
self._tmp_dir = tmp_dir
self._tmp_file_base = 'tmp_spike_times'
self._spike_labels = os.path.join(self._tmp_dir, self._tmp_file_base)
self._spike_writer = SpikeTrainWriter(tmp_dir=tmp_dir,
mpi_rank=MPI_RANK,
mpi_size=N_HOSTS)
self._spike_writer.delimiter = '\t'
self._spike_writer.gid_col = 0
self._spike_writer.time_col = 1
self._sort_order = spikes_sort_order
self._spike_detector = None
def initialize(self, sim):
self._spike_detector = nest.Create(
"spike_detector", 1, {
'label': self._spike_labels,
'withtime': True,
'withgid': True,
'to_file': True
})
for pop_name, pop in sim._graph._nestid2nodeid_map.items():
nest.Connect(list(pop.keys()), self._spike_detector)
def finalize(self, sim):
if MPI_RANK == 0:
for gdf_file in glob.glob(self._spike_labels + '*.gdf'):
self._spike_writer.add_spikes_file(gdf_file)
io.barrier()
gid_map = sim._graph._nestid2gid
if self._csv_fname is not None:
self._spike_writer.to_csv(self._csv_fname,
sort_order=self._sort_order,
gid_map=gid_map)
io.barrier()
if self._h5_fname is not None:
self._spike_writer.to_hdf5(self._h5_fname,
sort_order=self._sort_order,
gid_map=gid_map)
io.barrier()
if self._nwb_fname is not None:
self._spike_writer.to_nwb(self._nwb_fname,
sort_order=self._sort_order,
gid_map=gid_map)
io.barrier()
self._spike_writer.close()
class SpikesGenerator(SimModule):
def __init__(self,
spikes_file_csv=None,
spikes_file=None,
spikes_file_nwb=None,
tmp_dir='output'):
def _get_file_path(file_name):
if file_name is None or os.path.isabs(file_name):
return file_name
return os.path.join(tmp_dir, file_name)
self._csv_fname = _get_file_path(spikes_file_csv)
self._save_csv = spikes_file_csv is not None
self._h5_fname = _get_file_path(spikes_file)
self._save_h5 = spikes_file is not None
self._nwb_fname = _get_file_path(spikes_file_nwb)
self._save_nwb = spikes_file_nwb is not None
self._tmpdir = tmp_dir
self._spike_writer = SpikeTrainWriter(tmp_dir=tmp_dir)
def save(self, sim, gid, times, rates):
try:
spike_trains = np.array(
f_rate_to_spike_train(times * 1000.0, rates,
np.random.randint(10000),
1000. * min(times), 1000. * max(times),
0.1))
except:
# convert to milliseconds and hence the multiplication by 1000
spike_trains = 1000.0 * np.array(
pg.generate_inhomogenous_poisson(
times, rates, seed=np.random.randint(10000)))
self._spike_writer.add_spikes(times=spike_trains, gid=gid)
def finalize(self, sim):
self._spike_writer.flush()
if self._save_csv:
self._spike_writer.to_csv(self._csv_fname)
if self._save_h5:
self._spike_writer.to_hdf5(self._h5_fname)
if self._save_nwb:
self._spike_writer.to_nwb(self._nwb_fname)
self._spike_writer.close()