Source code for emodelrunner.features

"""Feature-related classes."""

# Copyright 2020-2022 Blue Brain Project / EPFL

# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at


# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# See the License for the specific language governing permissions and
# limitations under the License.

import json
import logging

from bluepyopt.ephys.efeatures import eFELFeature

logger = logging.getLogger(__name__)

[docs] def get_feature( feature_config, main_protocol, protocol_name, recording_name, prefix, ): """Return feature name and eFelFeature. Args: feature_config (dict): contains the feature-related config data main_protocol (ephys.protocols.Protocol): Main Protocol containing all the protocols protocol_name (str): name of the protocol used recording_name (str): name of the recording. used to get the trace prefix (str): prefix used in naming responses, features, recordings, etc. Returns: (str, bluepyopt.ephys.efeatures.eFELFeature): feature name, feature """ # pylint: disable=too-many-locals efel_feature_name = feature_config["feature"] meanstd = feature_config["val"] if hasattr(main_protocol, "subprotocols"): protocol = main_protocol.subprotocols()[protocol_name] else: protocol = main_protocol[protocol_name] feature_name = f"{prefix}.{protocol_name}.{recording_name}.{efel_feature_name}" recording_names = {"": f"{prefix}.{protocol_name}.{recording_name}"} if "strict_stim" in feature_config: strict_stim = feature_config["strict_stim"] else: strict_stim = True if hasattr(protocol, "stim_start"): stim_start = protocol.stim_start if "threshold" in feature_config: threshold = feature_config["threshold"] else: threshold = -30 if "bAP" in protocol_name: # bAP response can be after stimulus stim_end = protocol.total_duration elif "H40S8" in protocol_name: stim_end = protocol.stim_last_start else: stim_end = protocol.stim_end stimulus_current = protocol.step_amplitude else: stim_start = None stim_end = None stimulus_current = None threshold = None feature = eFELFeature( feature_name, efel_feature_name=efel_feature_name, recording_names=recording_names, stim_start=stim_start, stim_end=stim_end, exp_mean=meanstd[0], exp_std=meanstd[1], stimulus_current=stimulus_current, threshold=threshold, int_settings={"strict_stiminterval": strict_stim}, ) return feature_name, feature
[docs] def define_efeatures(main_protocol, features_path, prefix=""): """Define the efeatures. Args: main_protocol (ephys.protocols.Protocol): Main Protocol containing all the protocols features_path (str): path to features file prefix (str): prefix used in naming responses, features, recordings, etc. Returns: dict: efeatures """ with open(features_path, "r", encoding="utf-8") as features_file: feature_definitions = json.load(features_file) if "__comment" in feature_definitions: del feature_definitions["__comment"] efeatures = {} for protocol_name, locations in feature_definitions.items(): for recording_name, feature_configs in locations.items(): for feature_config in feature_configs: feature_name, feature = get_feature( feature_config, main_protocol, protocol_name, recording_name, prefix, ) efeatures[feature_name] = feature return efeatures