Source code for spynnaker.pyNN.models.neural_projections.connectors.from_file_connector

# Copyright (c) 2017-2019 The University of Manchester
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with this program.  If not, see <>.

import os
import numpy
from pyNN.recording.files import StandardTextFile
from .from_list_connector import FromListConnector

[docs]class FromFileConnector(FromListConnector): """ Make connections according to a list read from a file. """ # pylint: disable=redefined-builtin __slots__ = ["_file"] def __init__( self, file, # @ReservedAssignment distributed=False, safe=True, callback=None, verbose=False): """ :param str file: Either an open file object or the filename of a file containing a list of connections, in the format required by :py:class:`FromListConnector`. Column headers, if included in the file, must be specified using a list or tuple, e.g.:: # columns = ["i", "j", "weight", "delay", "U", "tau_rec"] Note that the header requires `#` at the beginning of the line. :type file: str or ~io.FileIO :param bool distributed: Basic pyNN says: if this is ``True``, then each node will read connections from a file called ``filename.x``, where ``x`` is the MPI rank. This speeds up loading connections for distributed simulations. .. note:: Always leave this as ``False`` with sPyNNaker, which is not MPI-based. :param bool safe: Whether to check that weights and delays have valid values. If ``False``, this check is skipped. :param callable callback: if given, a callable that display a progress bar on the terminal. .. note:: Not supported by sPyNNaker. :param bool verbose: Whether to output extra information about the connectivity to a CSV file """ self._file = file if isinstance(file, str): real_file = self.get_reader(file) try: conn_list = self._read_conn_list(real_file, distributed) finally: real_file.close() else: conn_list = self._read_conn_list(file, distributed) column_names = self.get_reader(self._file).get_metadata().get( 'columns') if column_names is not None: column_names = [column for column in column_names if column not in ("i", "j")] # pylint: disable=too-many-arguments super().__init__( conn_list, safe=safe, verbose=verbose, column_names=column_names, callback=callback) def _read_conn_list(self, the_file, distributed): if not distributed: return filename = "{}.".format(os.path.basename(the_file.file)) # This assumes it finds the files in the right order! conns = list() for found_file in os.listdir(os.path.dirname(the_file.file)): if found_file.startswith(filename): file_reader = self.get_reader(found_file) try: conns.append( finally: file_reader.close() return numpy.concatenate(conns) def __repr__(self): return "FromFileConnector({})".format(self._file)
[docs] def get_reader(self, file): # @ReservedAssignment """ Get a file reader object using the PyNN methods. :return: A pynn StandardTextFile or similar :rtype: ~pynn.recording.files.StandardTextFile """ return StandardTextFile(file, mode="r")