Source code for bmtk.utils.reports.compartment.compartment_writer

import os
import h5py
import numpy as np

from bmtk.utils.sonata.utils import add_hdf5_magic, add_hdf5_version
from .compartment_reader import CompartmentReaderVer01 as CompartmentReader
from .core import CompartmentWriterABC

    from mpi4py import MPI
    comm = MPI.COMM_WORLD
    rank = comm.Get_rank()
    nhosts = comm.Get_size()
    barrier = comm.Barrier

except Exception as exc:
    rank = 0
    nhosts = 1
    barrier = lambda: None

[docs]class PopulationWriterv01(CompartmentWriterABC, CompartmentReader): """Used to save cell membrane variables (V, Ca2+, etc) to the described hdf5 format. For parallel simulations this class will write to a seperate tmp file on each rank, then use the merge method to combine the results. This is less efficent, but doesn't require the user to install mpi4py and build h5py in parallel mode. For better performance use the CellVarRecorderParrallel class instead. """
[docs] class DataTable(object): """A small struct to keep track of different data (and buffer) tables """ def __init__(self, var_name): self.var_name = var_name # If buffering data, buffer_block will be an in-memory array and will write to data_block during when # filled. If not buffering buffer_block is an hdf5 dataset and data_block is ignored self.data_block = None self.buffer_block = None self.block_window = (0.0, 10e20)
def __init__(self, parent, population, variable=None, units=None, tstart=0.0, tstop=1.0, dt=0.01, n_steps=None, buffer_size=0, **kwargs): self._h5_base = None self._parent = parent self._population = population self._variable = variable self._units = units self._tstart = tstart self._tstop = tstop self._dt = dt self._n_steps = n_steps #if self._n_steps is None: # self._n_steps = int((self._tstop - self._tstart)/self._dt) self._tmp_files = [] self._mapping_gids = [] # list of gids in the order they appear in the data self._gid_map = {} # table for looking up the gid offsets self._element_data = {} # Used for additonal attributes in /mapping self._mapping_element_ids = [] # sections self._mapping_element_pos = [] # segments self._mapping_index = [0] # index_pointer self._buffer_size = buffer_size self._buffer_data = buffer_size > 0 self._data_block = self.DataTable(self._variable) # self._last_save_indx = 0 # for buffering, used to keep track of last timestep data was saved to disk self._buffer_block_size = 0 self._total_steps = 0 # Keep track of gids across the different ranks self._n_gids_all = 0 self._n_gids_local = 0 self._gids_beg = 0 self._gids_end = 0 # Keep track of segment counts across the different ranks self._n_segments_all = 0 self._n_segments_local = 0 self._seg_offset_beg = 0 self._seg_offset_end = 0 self._is_initialized = False @property def h5_base(self): if self._h5_base is None: self._h5_base = self._parent.report_group.create_group(self._population) return self._h5_base def _calc_offset(self): self._n_segments_all = self._n_segments_local self._seg_offset_beg = 0 self._seg_offset_end = self._n_segments_local self._n_gids_all = self._n_gids_local self._gids_beg = 0 self._gids_end = self._n_gids_local
[docs] def set_units(self, val, population=None): self._units = val
[docs] def units(self, population=None): return self._units
[docs] def set_variable(self, val, population=None): self._variable = val
[docs] def variable(self, population=None): return self._variable
[docs] def set_tstart(self, val, population=None): self._tstart = val
[docs] def tstart(self, population=None): return self._tstart
[docs] def set_tstop(self, val, population=None): self._tstop = val
[docs] def tstop(self, population=None): return self._tstop
[docs] def set_dt(self, val, population=None): self._dt = val
[docs] def dt(self, population=None): return self._dt
[docs] def n_steps(self, population=None): if self._n_steps is None: self._n_steps = int((self._tstop - self._tstart) / self._dt) return self._n_steps
[docs] def set_time_trace(self, val, population=None): raise NotImplementedError()
[docs] def time_trace(self, population=None): raise NotImplementedError()
[docs] def add_cell(self, node_id, element_ids, element_pos, **map_attrs): assert(len(element_ids) == len(element_pos)) # TODO: Check the same gid isn't added twice n_segs = len(element_pos) self._gid_map[node_id] = (self._n_segments_local, self._n_segments_local + n_segs) self._mapping_gids.append(node_id) self._mapping_element_ids.extend(element_ids) self._mapping_element_pos.extend(element_pos) self._mapping_index.append(self._mapping_index[-1] + n_segs) self._n_segments_local += n_segs self._n_gids_local += 1 for k, v in map_attrs.items(): if k not in self._element_data: self._element_data[k] = v else: self._element_data[k].extend(v)
[docs] def initialize(self, **kwargs): if self._is_initialized: return n_steps = self.n_steps() if n_steps <= 0: raise Exception('A non-zero positive integer num-of-steps is required to initialize the compartment report.' 'Please specify report length using the n_steps parameters (or using appropiate tstop,' 'tstart, and dt).') self._calc_offset() base_grp = self.h5_base var_grp = base_grp.create_group('mapping') var_grp.create_dataset('node_ids', shape=(self._n_gids_all,), dtype=np.uint) var_grp.create_dataset('element_ids', shape=(self._n_segments_all,), dtype=np.uint) var_grp.create_dataset('element_pos', shape=(self._n_segments_all,), dtype=float) var_grp.create_dataset('index_pointer', shape=(self._n_gids_all+1,), dtype=np.uint64) var_grp.create_dataset('time', data=[self.tstart(), self.tstop(), self.dt()]) for k, v in self._element_data.items(): var_grp.create_dataset(k, shape=(self._n_segments_all,), dtype=type(v[0])) var_grp['node_ids'][self._gids_beg:self._gids_end] = self._mapping_gids var_grp['element_ids'][self._seg_offset_beg:self._seg_offset_end] = self._mapping_element_ids var_grp['element_pos'][self._seg_offset_beg:self._seg_offset_end] = self._mapping_element_pos var_grp['index_pointer'][self._gids_beg:(self._gids_end+1)] = self._mapping_index for k, v in self._element_data.items(): var_grp[k][self._seg_offset_beg:self._seg_offset_end] = v self._total_steps = n_steps self._buffer_size = np.min((self._total_steps, self._buffer_size)) self._buffer_block_size = self._buffer_size if not self._buffer_data: # If data is not being buffered and instead written to the main block, we have to add a rank offset # to the gid offset for gid, gid_offset in self._gid_map.items(): self._gid_map[gid] = (gid_offset[0] + self._seg_offset_beg, gid_offset[1] + self._seg_offset_beg) if self._buffer_data: # Set up in-memory block to buffer recorded variables before writing to the dataset self._data_block.buffer_block = np.zeros((self._buffer_size, self._n_segments_local), dtype=float) self._data_block.data_block = base_grp.create_dataset('data', shape=(self.n_steps(), self._n_segments_all), dtype=float, chunks=True) if self._variable is not None: self._data_block.data_block.attrs['variable'] = self._variable if self._units is not None: self._data_block.data_block.attrs['units'] = self._units self._data_block.block_window = (0, self._buffer_block_size) else: # Since we are not buffering data, we just write directly to the on-disk dataset self._data_block.buffer_block = base_grp.create_dataset( 'data', shape=(self.n_steps(), self._n_segments_all), dtype=float, chunks=True ) if self._variable is not None: self._data_block.buffer_block.attrs['variable'] = self._variable if self._units is not None: self._data_block.buffer_block.attrs['units'] = self._units self._is_initialized = True
def _reset_buffer_window(self, tstep): blk_beg = int(tstep/self._buffer_size)*self._buffer_size blk_end = blk_beg + self._buffer_size self._data_block.block_window = (blk_beg, blk_end)
[docs] def record_cell(self, node_id, vals, tstep, population=None): """Record cell parameters. :param gid: gid of cell. :param var_name: name of variable being recorded. :param seg_vals: list of all segment values :param tstep: time step """ self.initialize() gid_beg, gid_end = self._gid_map[node_id] buffer_block = self._data_block.buffer_block if not self._buffer_data: buffer_block[tstep, gid_beg:gid_end] = vals elif self._data_block.block_window[0] <= tstep < self._data_block.block_window[1]: update_index = tstep - self._data_block.block_window[0] buffer_block[update_index, gid_beg:gid_end] = vals else: self.flush() self._reset_buffer_window(tstep) update_index = tstep - self._data_block.block_window[0] buffer_block[update_index, gid_beg:gid_end] = vals
[docs] def record_cell_block(self, node_id, vals, beg_step, end_step, population=None): """Save cell parameters one block at a time :param gid: gid of cell. :param var_name: name of variable being recorded. :param seg_vals: A vector/matrix of values being recorded """ self.initialize() gid_beg, gid_end = self._gid_map[node_id] buffer_block = self._data_block.buffer_block if isinstance(vals, list) or vals.ndim == 1: buffer_block[:, gid_beg] = vals # buffer_block[beg_step:end_step, gid_beg:gid_end] = vals else: buffer_block[:, gid_beg:gid_end] = vals
[docs] def flush(self): """Move data from memory to dataset""" if self._buffer_data: # blk_beg = self._last_save_indx # blk_end = blk_beg + self._buffer_block_size blk_beg = self._data_block.block_window[0] blk_end = self._data_block.block_window[1] if blk_end > self._total_steps: # Need to handle the case that simulation doesn't end on a block step blk_end = blk_beg + self._total_steps - blk_beg block_size = blk_end - blk_beg self._data_block.data_block[blk_beg:blk_end, :] = self._data_block.buffer_block[:block_size, :] self._reset_buffer_window(blk_end+1)
[docs] def close(self): # Let the parent take care of this pass
[docs] def merge(self): # Let the parent take care of this pass
[docs]class CompartmentWriterv01(CompartmentWriterABC): def __init__(self, file_path, mode='w', default_population=None, cache_dir=None, variable=None, units=None, buffer_size=0, tstart=0.0, tstop=0.0, dt=0.0, n_steps=None, **kwargs): self._mode = mode self._variable = variable self._units = units self._pop_tables = {} self._default_pop = default_population self._buffer_size = buffer_size self._tstart = tstart self._tstop = tstop self._dt = dt self._n_steps = n_steps self._kwargs = kwargs self._h5_handle = None self._h5report_grp = None self._mpi_rank = kwargs.get('mpi_rank', rank) self._mpi_size = kwargs.get('mpi_size', nhosts) self._final_fpath = file_path # name of file being writen too. self._cache_dir = cache_dir or os.path.dirname(os.path.abspath(file_path)) # used for mulitple ranks self._base_name = os.path.basename(file_path) # make sure file names don't clash if there are multiple reports self._interm_fpath = self._get_iterm_fpath() # In certain cases (parallelized simulation) split the final file by rank. def _get_iterm_fpath(self): if self._mpi_size > 1: return self.temp_files[self._mpi_rank] else: return self._final_fpath def _create_h5file(self): fdir = os.path.dirname(os.path.abspath(self._interm_fpath)) if not os.path.exists(fdir): os.mkdir(fdir) self._h5_handle = h5py.File(self._interm_fpath, self._mode) add_hdf5_version(self._h5_handle) add_hdf5_magic(self._h5_handle) @property def report_group(self): if self._h5report_grp is None: self._create_h5file() if 'report' in self._h5_handle.keys(): self._h5report_grp = self._h5_handle['report'] else: self._h5report_grp = self._h5_handle.create_group('report') return self._h5report_grp @property def temp_files(self): return [os.path.join(self._cache_dir, '.bmtk_tmp_cellvars_{}_{}'.format(r, self._base_name)) for r in range(self._mpi_size)]
[docs] def set_units(self, val, population=None): self[population].set_units(val)
[docs] def set_variable(self, val, population=None): self[population].set_variable(val)
[docs] def set_tstart(self, val, population=None): self[population].set_tstart(val)
[docs] def set_tstop(self, val, population=None): self[population].set_tstop(val)
[docs] def set_dt(self, val, population=None): self[population].set_dt(val)
[docs] def n_steps(self, population=None): self[population].n_steps()
[docs] def set_time_trace(self, val, population=None): self[population].set_time_trace(val)
[docs] def add_cell(self, node_id, element_ids, element_pos, population=None, **element_data): pop_str = population or self._default_pop pop_grp = self._build_or_fetch_pop(pop_str) pop_grp.add_cell(node_id=node_id, element_ids=element_ids, element_pos=element_pos, **element_data)
[docs] def initialize(self): for pop_grp in self._pop_tables.values(): pop_grp.initialize()
[docs] def record_cell(self, node_id, vals, tstep, population=None): pop_str = population or self._default_pop pop_grp = self._build_or_fetch_pop(pop_str) pop_grp.record_cell(node_id=node_id, vals=vals, tstep=tstep)
[docs] def record_cell_block(self, node_id, vals, beg_step, end_step, population=None): self[population].record_cell_block(node_id=node_id, vals=vals, beg_step=beg_step, end_step=end_step)
[docs] def flush(self): for pop_grp in self._pop_tables.values(): pop_grp.flush()
[docs] def close(self): for pop_grp in self._pop_tables.values(): pop_grp.close() if self._h5_handle is not None: self._h5_handle.close() if self._mpi_size > 1: self.merge()
[docs] def merge(self): barrier() if self._mpi_size > 1 and self._mpi_rank == 0: h5final = h5py.File(self._final_fpath, 'w') tmp_reports = [CompartmentReader(name) for name in self.temp_files if os.path.exists(name)] populations = set() for r in tmp_reports: populations.update(r.populations) for pop in populations: # Find the gid and segment offsets for each temp h5 file gid_ranges = [] # list of (gid-beg, gid-end) gid_offset = 0 total_gid_count = 0 # total number of gids across all ranks seg_ranges = [] seg_offset = 0 total_seg_count = 0 # total number of segments across all ranks times = None n_steps = 0 variable = None units = None for rpt in tmp_reports: if pop not in rpt.populations: continue report = rpt[pop] seg_count = len(report.element_pos()) # ['/mapping/element_pos']) seg_ranges.append((seg_offset, seg_offset + seg_count)) seg_offset += seg_count total_seg_count += seg_count gid_count = len(report.node_ids()) # h5_tmp['mapping/node_ids']) gid_ranges.append((gid_offset, gid_offset + gid_count)) gid_offset += gid_count total_gid_count += gid_count times = report.time() # h5_tmp['mapping/time'] n_steps = report.n_steps() variable = report.variable() units = report.units() mapping_grp = h5final.create_group('/report/{}/mapping'.format(pop)) if times is not None and len(times) > 0: mapping_grp.create_dataset('time', data=times) element_id_ds = mapping_grp.create_dataset('element_ids', shape=(total_seg_count,), dtype=np.uint) el_pos_ds = mapping_grp.create_dataset('element_pos', shape=(total_seg_count,), dtype=float) gids_ds = mapping_grp.create_dataset('node_ids', shape=(total_gid_count,), dtype=np.uint) index_pointer_ds = mapping_grp.create_dataset('index_pointer', shape=(total_gid_count + 1,), dtype=np.uint) for rpt in tmp_reports: if pop not in rpt.populations: continue report = rpt[pop] for k, v in report.custom_columns().items(): if k not in mapping_grp.keys(): mapping_grp.create_dataset(k, shape=(total_seg_count,), dtype=type(v[0])) # combine the /mapping datasets i = 0 for rpt in tmp_reports: if pop not in rpt.populations: continue report = rpt[pop] # tmp_mapping_grp = h5_tmp['mapping'] beg, end = seg_ranges[i] element_id_ds[beg:end] = report.element_ids() # tmp_mapping_grp['element_id'] el_pos_ds[beg:end] = report.element_pos() # tmp_mapping_grp['element_pos'] for k, v in report.custom_columns().items(): mapping_grp[k][beg:end] = v # shift the index pointer values index_pointer = np.array(report.index_pointer()) # tmp_mapping_grp['index_pointer']) update_index = beg + index_pointer beg, end = gid_ranges[i] gids_ds[beg:end] = report.node_ids() # tmp_mapping_grp['node_ids'] index_pointer_ds[beg:(end + 1)] = update_index i += 1 # combine the /var/data datasets data_name = '/report/{}/data'.format(pop) # data_name = '/{}/data'.format(var_name) var_data = h5final.create_dataset(data_name, shape=(n_steps, total_seg_count), dtype=float) # var_data.attrs['variable_name'] = var_name i = 0 for rpt in tmp_reports: if pop not in rpt.populations: continue report = rpt[pop] beg, end = seg_ranges[i] var_data[:, beg:end] = i += 1 if variable is not None: var_data.attrs['variable'] = variable if units is not None: var_data.attrs['units'] = units for tmp_file in self.temp_files: if os.path.exists(tmp_file): os.remove(tmp_file) barrier()
def _build_or_fetch_pop(self, population): if population is None: raise Exception('Please specify a valid node population (or use default_population parameter in constructor).') if population in self._pop_tables: pop_grp = self._pop_tables[population] else: pop_grp = PopulationWriterv01(self, population, variable=self._variable, units=self._units, tstart=self._tstart, tstop=self._tstop, dt=self._dt, buffer_size=self._buffer_size, n_steps=self._n_steps) self._pop_tables[population] = pop_grp return pop_grp def __getitem__(self, population): pop_str = population or self._default_pop return self._build_or_fetch_pop(pop_str)