"""Step eCode class"""
"""
Copyright (c) 2022, EPFL/Blue Brain Project
This file is part of BluePyEfe <https://github.com/BlueBrain/BluePyEfe>
This library is free software; you can redistribute it and/or modify it under
the terms of the GNU Lesser General Public License version 3.0 as published
by the Free Software Foundation.
This library 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 Lesser General Public License for more
details.
You should have received a copy of the GNU Lesser General Public License
along with this library; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
"""
import logging
import numpy
from ..recording import Recording
from .tools import base_current
from .tools import scipy_signal2d
logger = logging.getLogger(__name__)
[docs]
class Ramp(Recording):
"""Ramp current stimulus
.. code-block:: none
hypamp hypamp+amp hypamp
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|___________ / |__________________________
^ ^ ^ ^
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t=0 ton toff tend
"""
def __init__(
self,
config_data,
reader_data,
protocol_name="ramp",
efel_settings=None
):
super(Ramp, self).__init__(config_data, reader_data, protocol_name)
self.ton = None
self.toff = None
self.tend = None
self.amp = None
self.hypamp = None
self.dt = None
self.amp_rel = None
self.hypamp_rel = None
if self.t is not None and self.current is not None:
self.interpret(
self.t, self.current, self.config_data, self.reader_data
)
if self.voltage is not None:
self.set_autothreshold()
self.compute_spikecount(efel_settings)
self.export_attr = ["ton", "toff", "tend", "amp", "hypamp", "dt",
"amp_rel", "hypamp_rel"]
[docs]
def get_stimulus_parameters(self):
"""Returns the eCode parameters"""
ecode_params = {
"delay": self.ton,
"amp": self.amp,
"thresh_perc": self.amp_rel,
"duration": self.toff - self.ton,
"totduration": self.tend,
}
return ecode_params
[docs]
def interpret(self, t, current, config_data, reader_data):
"""Analyse a current with a step and extract from it the parameters
needed to reconstruct the array"""
self.dt = t[1]
# Smooth the current
smooth_current = scipy_signal2d(current, 85)
self.set_timing_ecode(["ton"], config_data)
if "toff" in config_data and config_data["toff"] is not None:
self.toff = int(round(config_data["toff"] / self.dt))
else:
self.toff = numpy.argmax(smooth_current[self.ton:]) + self.ton
hypamp_value = base_current(current)
self.set_amplitudes_ecode("hypamp", config_data, reader_data, hypamp_value)
amp_value = numpy.median(current[self.toff - 10 : self.toff]) - self.hypamp
self.set_amplitudes_ecode("amp", config_data, reader_data, amp_value)
# Converting back to ms
for name_timing in ["ton", "toff"]:
self.index_to_ms(name_timing, t)
self.tend = len(t) * self.dt
[docs]
def generate(self):
"""Generate the step current array from the parameters of the ecode"""
ton_idx = int(self.ton / self.dt)
toff_idx = int(self.toff / self.dt)
t = numpy.arange(0.0, self.tend, self.dt)
current = numpy.full(t.shape, numpy.float64(self.hypamp))
current[ton_idx:toff_idx] += numpy.linspace(
0.0, self.amp, toff_idx - ton_idx
)
return t, current