#################################################################################
## ##
## Copyright C 2018 Juan P. Dominguez-Morales ##
## ##
## This file is part of pyNAVIS. ##
## ##
## pyNAVIS 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. ##
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## pyNAVIS is distributed in the hope that it will be useful, ##
## but WITHOUT ANY WARRANTY; without even the implied warranty of ##
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.See the ##
## GNU General Public License for more details. ##
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## You should have received a copy of the GNU General Public License ##
## along with pyNAVIS. If not, see <http://www.gnu.org/licenses/>. ##
## ##
#################################################################################
[docs]class MainSettings:
"""
Class that collects the main configuration settings of pyNAVIS
Attributes:
mono_stereo (int): Set to 0 for mono files and 1 for stereo files.
bin_size (int): Bin width (or window size) to use when processing the information.
ts_tick (float): Timestamp tick. Correspondence factor between timestamp value in file and actual time.
num_channels (int): Number of cochlea channels.
address_size (int): Number of bytes that each address is using. Only needed when loading .aedat files
timestamp_size (int): Number of bytes that each timestamp is using. Only needed when loading .aedat files
on_off_both (int): Select wether the addresses contained in the file are ON, OFF or if it is using both.
reset_timestamp (boolean): Select wether to have timedtamps starting at 0 (True) or leave it as they are (False).
Notes:
Set ts_tick to 1 for .aedat files recorded with jAER, to 0.2 for files recorded with USBAERmini2, and to 80e-3 for files recorded with zynqGrabber.
Set address_size to 2 for .eadat files recorded with USBAERmini2, or to 4 for files recorded with jAER.
This parameter is only relevant for loading AEDAT (.aedat) files.
Set on_off_both to 0 if addresses are only ON or OFF, or to 1 if using both ON and OFF.
reset_timestamp subtracts the smallest timestamp in the file to each of the timestamps.
"""
def __init__(self, num_channels, mono_stereo = 0, address_size = 2, timestamp_size=4, ts_tick = 1, bin_size = 20000, on_off_both = 1, reset_timestamp = True):
self.num_channels = num_channels
self.mono_stereo = mono_stereo
self.address_size = address_size
self.timestamp_size = timestamp_size
self.ts_tick = ts_tick
self.bin_size = bin_size
self.on_off_both = on_off_both
self.reset_timestamp = reset_timestamp
class LocalizationSettings:
"""
Class that collects the configuration settings of pyNAVS when working with a NAS model that integrates the sound source localization model.
Attributes:
mso_start_channel (int): First NAS frequency channel that is connected to the MSO module.
mso_end_channel (int): Last NAS frequency channel that is connected to the MSO module.
mso_num_neurons_channel (int): Number of coincidence detector neurons used for each frequency channel in the MSO module.
lso_start_channel (int): First NAS frequency channel that is connected to the LSO module.
lso_end_channel (int): Last NAS frequency channel that is connected to the LSO module.
lso_num_neurons_channel (int): Number of neurons used for each frequency channel in the LSO module.
Notes:
The first frequency channel is channel number 0.
The frequency channel range should match the parameter num_channels set in MainSettings.
The values set here should be the same that the one used for generating the FPGA configuration file.
"""
def __init__(self, mso_start_channel, mso_end_channel, mso_num_neurons_channel, lso_start_channel = 0, lso_end_channel = 1, lso_num_neurons_channel = 1):
self.mso_start_channel = mso_start_channel
self.mso_end_channel = mso_end_channel
self.mso_num_neurons_channel = mso_num_neurons_channel
self.lso_start_channel = lso_start_channel
self.lso_end_channel = lso_end_channel
self.lso_num_neurons_channel = lso_num_neurons_channel