From 423754ece3f29119d324c147baa0b0a210e0d983 Mon Sep 17 00:00:00 2001 From: wendtalexander Date: Mon, 6 Oct 2025 15:57:36 +0200 Subject: [PATCH] [inital] --- .gitignore | 11 + README.md | 0 oephys2nix/logging.py | 18 ++ oephys2nix/main.py | 76 +++++ oephys2nix/metadata.py | 28 ++ oephys2nix/tonix.py | 711 +++++++++++++++++++++++++++++++++++++++++ pyproject.toml | 16 + uv.lock | 576 +++++++++++++++++++++++++++++++++ 8 files changed, 1436 insertions(+) create mode 100644 .gitignore create mode 100644 README.md create mode 100644 oephys2nix/logging.py create mode 100644 oephys2nix/main.py create mode 100644 oephys2nix/metadata.py create mode 100644 oephys2nix/tonix.py create mode 100644 pyproject.toml create mode 100644 uv.lock diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..2462cfe --- /dev/null +++ b/.gitignore @@ -0,0 +1,11 @@ +# Python-generated files +__pycache__/ +*.py[oc] +build/ +test/ +dist/ +wheels/ +*.egg-info + +# Virtual environments +.venv diff --git a/README.md b/README.md new file mode 100644 index 0000000..e69de29 diff --git a/oephys2nix/logging.py b/oephys2nix/logging.py new file mode 100644 index 0000000..d45004c --- /dev/null +++ b/oephys2nix/logging.py @@ -0,0 +1,18 @@ +import logging + +from rich.logging import RichHandler + +DEFAULT_LOG_LEVEL = "DEBUG" + + +def setup_logging(logger: logging.Logger, level=DEFAULT_LOG_LEVEL): + if logger.hasHandlers(): + logger.handlers.clear() + stream_handler = RichHandler(rich_tracebacks=True, show_path=False) + stream_handler.setLevel(level) + fmt_shell = "%(filename)s:%(lineno)d - %(message)s" + shell_formatter = logging.Formatter(fmt_shell) + stream_handler.setFormatter(shell_formatter) + logger.addHandler(stream_handler) + logger.setLevel(level) + logging.getLogger(__name__).info(f"Logging configured with level {level}.") diff --git a/oephys2nix/main.py b/oephys2nix/main.py new file mode 100644 index 0000000..59d93a6 --- /dev/null +++ b/oephys2nix/main.py @@ -0,0 +1,76 @@ +import logging +from pathlib import Path + +import nixio +import typer +from IPython import embed +from rich.console import Console + +from oephys2nix.logging import setup_logging + +app = typer.Typer() +log = logging.getLogger(__name__) +setup_logging(log, level="DEBUG") +console = Console() + + +@app.command() +def main( + data_path: Path = typer.Argument( + ..., + help="The source directory containing the Open Ephys data.", + exists=True, + file_okay=False, + dir_okay=True, + readable=True, + resolve_path=True, + ), + ttl: bool = typer.Option( + default=True, help="For recordings that did not have a ttl pulse" + ), + overwrite: bool = typer.Option(default=True, help="Overwrites nix file"), +): + """ + Combines open ephys data with relacs data from data_path to a new nix file + """ + + log.info(f"Selected data_path is {data_path}") + open_ephys_data_paths = list(Path(data_path).rglob("*open-ephys")) + relacs_data_paths = list(Path(data_path).rglob("*relacs")) + + if not len(open_ephys_data_paths) == len(relacs_data_paths): + log.error( + f"Missmatch in data directory found open-ephys data {len(open_ephys_data_paths)} and relacs data {len(relacs_data_paths)}" + ) + log.error("Please check if both are present") + raise typer.Exit() + + for open_ephys, relacs in zip( + open_ephys_data_paths, relacs_data_paths, strict=True + ): + nix_file_name = relacs.name.split("_")[0] + "-recording.nix" + + console.print( + f"Converting [bold cyan]{open_ephys.name}[/bold cyan] and " + f"[bold magenta]{relacs.name}[/bold magenta] -> " + f"[green]{nix_file_name}[/green]" + ) + + nix_path = relacs.parent / nix_file_name + + if nix_path.exists and nix_path.is_file(): + if overwrite: + log.warning("Overwriting nix file") + nix_files = nixio.File(str(nix_file_name), nixio.FileMode.Overwrite) + else: + log.error( + "Converted nix file already exits, and Overwrite is not enabled" + ) + raise typer.Exit() + else: + log.debug("Creating nix file") + nix_files = nixio.File(str(nix_file_name), nixio.FileMode.Overwrite) + + +if __name__ == "__main__": + app() diff --git a/oephys2nix/metadata.py b/oephys2nix/metadata.py new file mode 100644 index 0000000..28b8cf6 --- /dev/null +++ b/oephys2nix/metadata.py @@ -0,0 +1,28 @@ +import nixio + + +def create_metadata_from_dict(d: dict, section: nixio.Section) -> None: + for key, value in d.items(): + if isinstance(value, dict): + new_sec = section.create_section(key, f"{type(key)}") + create_metadata_from_dict(value, new_sec) + else: + try: + section.create_property(key, values_or_dtype=value) + except TypeError: + if isinstance(value, list): + value = [str(i) for i in value] + else: + value = str(value) + section.create_property(key, values_or_dtype=value) + + +def create_dict_from_section(section: nixio.Section) -> dict: + d = {} + for key, value in section.items(): + if isinstance(value, nixio.Section): + subdict = create_dict_from_section(value) + d[key] = subdict + else: + d[key] = value.values + return d diff --git a/oephys2nix/tonix.py b/oephys2nix/tonix.py new file mode 100644 index 0000000..fff401b --- /dev/null +++ b/oephys2nix/tonix.py @@ -0,0 +1,711 @@ +import logging +import pathlib +import tomllib + +import matplotlib.pyplot as plt +import nixio +import numpy as np +import rlxnix as rlx +from IPython import embed +from neo.io import OpenEphysBinaryIO +from nixio.exceptions import DuplicateName +from scipy import signal + +log = logging.getLogger(__name__) +setup_logging(log, level="DEBUG") + + +class CreateNix: + def __init__(self, open_ephys_path, relacs_nix_path, nix_file): + self.relacs_nix_file = nixio.File.open(relacs_nix_path, nixio.FileMode.ReadOnly) + self.dataset = rlx.Dataset(relacs_nix_path) + self.relacs_block = self.relacs_nix_file.blocks[0] + self.relacs_sections = self.relacs_nix_file.sections + + self.spike_sorter_path = str(self.recording_path.resolve() / "spikesorter.nix") + + self.neo_data = OpenEphysBinaryIO(open_ephys_path).read(lazy=True) + + self.nix_file = nix_file + self.block = self.nix_file.blocks[0] + + def _load_config(self): + config_path = self.recording_path / "stimulus_config.toml" + if not config_path.is_file(): + log.debug("Stimulus config was not found") + with open(config_path, "rb") as config_file: + try: + config = tomllib.load(config_file) + config_file.close() + return config + except tomllib.TOMLDecodeError as e: + config_file.close() + raise tomllib.TOMLDecodeError(f"Error parsing TOML file: {e}") + + def _append_relacs_tag_mtags(self): + for t in self.relacs_block.tags: + log.debug(f"Appending relacs tags {t.name}") + tag = self.block.create_tag(f"relacs_{t.name}", t.type, position=t.position) + tag.extent = t.extent + tag.references.extend(self.block.groups["relacs"].data_arrays) + + sec = self.relacs_sections[f"{t.name}"] + d = create_dict_from_section(sec) + + try: + new_sec = self.nix_file.create_section(sec.name, sec.type) + create_metadata_from_dict(d, new_sec) + except DuplicateName: + pass + + tag.metadata = self.nix_file.sections[sec.name] + + for t in self.relacs_block.multi_tags: + log.debug(f"Appending relacs multi-tags {t.name}") + mtag = self.block.create_multi_tag( + f"relacs_{t.name}", + t.type, + positions=t.positions[:], + extents=t.extents[:], + ) + mtag.references.extend(self.block.groups["relacs"].data_arrays) + + sec = self.relacs_sections[f"{t.name}"] + d = create_dict_from_section(sec) + try: + new_sec = self.nix_file.create_section(sec.name, sec.type) + create_metadata_from_dict(d, new_sec) + except DuplicateName: + pass + mtag.metadata = self.nix_file.sections[sec.name] + + def _find_peak_ttl(self, time_ttl, peaks_ttl, lower, upper): + peak = time_ttl[ + peaks_ttl[(time_ttl[peaks_ttl] > lower) & (time_ttl[peaks_ttl] < upper)] + ] + + if not peak.size > 0: + log.error("No peaks found") + elif peak.size > 1: + if np.all(np.diff(peak) > 0.5): + log.error("Peaks are further aways than 0.5 seconds") + log.error(f"Peaks {peak}, Furthest aways: {np.max(peak)}") + peak = np.mean(peak) + return peak + + def _find_peak_ttl_index(self, time_ttl, peaks_ttl, current_position): + new_repro_start_index = peaks_ttl[ + (time_ttl[peaks_ttl] > current_position - 0.1) + & (time_ttl[peaks_ttl] < current_position + 0.1) + ] + + # if multiple take the last one + if new_repro_start_index.size > 1: + log.warning("Multiple current positions taking the last index") + new_repro_start_index = new_repro_start_index[-1] + + # log.debug(f"Time current repro/trial {time_ttl[new_repro_start_index]}") + if np.where(new_repro_start_index == peaks_ttl)[0] + 1 == len(peaks_ttl): + return np.array([]) + else: + next_repro_start = peaks_ttl[ + np.where(new_repro_start_index == peaks_ttl)[0] + 1 + ] + start_next_repro = time_ttl[next_repro_start] + log.debug(f"Start of new repro/trial {start_next_repro}") + return start_next_repro + + def _reference_groups(self) -> list[nixio.Group]: + return [ + self.block.groups["neuronal-data"], + # self.block.groups["spike-data"], + self.block.groups["efish"], + self.block.groups["relacs"], + ] + + def _append_mtag(self, repro, positions, extents): + try: + nix_mtag = self.block.create_multi_tag( + f"{repro.name}", + "relacs.stimulus", + positions=positions, + extents=extents, + ) + except DuplicateName: + del self.block.multi_tags[repro.name] + nix_mtag = self.block.create_multi_tag( + f"{repro.name}", + "relacs.stimulus", + positions=positions, + extents=extents, + ) + sec = self.relacs_sections[f"{repro.name}"] + d = create_dict_from_section(sec) + + try: + new_sec = self.nix_file.create_section(sec.name, sec.type) + create_metadata_from_dict(d, new_sec) + except DuplicateName: + del self.nix_file.sections[sec.name] + new_sec = self.nix_file.create_section(sec.name, sec.type) + create_metadata_from_dict(d, new_sec) + + nix_mtag.metadata = self.nix_file.sections[repro.name] + + [ + nix_mtag.references.extend(ref_groups.data_arrays) + for ref_groups in self._reference_groups + if ref_groups.data_arrays + ] + + try: + nix_group = self.block.create_group(repro.name, repro.type) + except DuplicateName: + nix_group = self.nix_file.blocks[0].groups[repro.name] + nix_group.multi_tags.append(nix_mtag) + + def _append_tag(self, repro, position, extent): + try: + nix_tag = self.block.create_tag( + f"{repro.name}", + "relacs.repro_run", + position=np.array(position).flatten(), + ) + nix_tag.extent = extent.flatten() + except DuplicateName: + del self.block.tags[repro.name] + nix_tag = self.block.create_tag( + f"{repro.name}", + "relacs.repro_run", + position=np.array(position).flatten(), + ) + nix_tag.extent = extent.flatten() + + sec = self.relacs_sections[f"{repro.name}"] + d = create_dict_from_section(sec) + + try: + new_sec = self.nix_file.create_section(sec.name, sec.type) + create_metadata_from_dict(d, new_sec) + except DuplicateName: + del self.nix_file.sections[sec.name] + new_sec = self.nix_file.create_section(sec.name, sec.type) + create_metadata_from_dict(d, new_sec) + + nix_tag.metadata = self.nix_file.sections[repro.name] + + # NOTE: adding refs to tag + [ + nix_tag.references.extend(ref_groups.data_arrays) + for ref_groups in self._reference_groups + if ref_groups.data_arrays + ] + try: + nix_group = self.block.create_group(repro.name, repro.type) + except DuplicateName: + nix_group = self.nix_file.blocks[0].groups[repro.name] + nix_group.tags.append(nix_tag) + + def create_repros_automatically(self): + ttl_oeph = self.block.data_arrays["ttl-line"][:] + time_ttl = np.arange(len(ttl_oeph)) / self.cfg.open_ephys.samplerate + time_index = np.arange(len(ttl_oeph)) + # Threshold for TTL peak + threshold = 2 + + peaks_ttl = time_index[ + (np.roll(ttl_oeph, 1) < threshold) & (ttl_oeph > threshold) + ] + # WARNING:Check if peaks are duplicates or near each other + close_peaks = np.where(np.diff(peaks_ttl) == 1)[0] + if close_peaks.size > 0: + peaks_ttl = np.delete(peaks_ttl, close_peaks) + + # NOTE: Get the first peak from the toml file + first_peak = self._find_peak_ttl( + time_ttl, + peaks_ttl, + self.stimulus_config["stimulus"]["start_repro_low"], + self.stimulus_config["stimulus"]["start_repro_high"], + ) + + current_position = np.asarray(first_peak.reshape(1)) + # NOTE: Start defined by config + for i, repro in enumerate( + self.dataset.repro_runs()[ + self.stimulus_config["stimulus"]["repro_number_start"] : + ], + start=self.stimulus_config["stimulus"]["repro_number_start"], + ): + log.debug(repro.name) + log.debug(f"Current Position {current_position.item()}") + if repro.duration < 1.0: + log.warning(f"Skipping repro {repro.name} because it is two short") + continue + + if repro.stimuli: + log.debug("Processing MultiTag") + repetition = len(repro.stimuli) + extents_mtag = np.zeros((repetition, 1)) + position_mtags = np.zeros((repetition, 1)) + + for trial, stimulus in enumerate(repro.stimuli): + duration_trial = stimulus.duration + extents_mtag[trial] = duration_trial + position_mtags[trial] = current_position + + current_position = self._find_peak_ttl_index( + time_ttl, peaks_ttl, current_position + ) + + # current_position = position_mtags[-1] + self._append_mtag(repro, position_mtags, extents_mtag) + extent = position_mtags[-1] + extents_mtag[-1] - position_mtags[0] + self._append_tag(repro, position_mtags[0], extent) + + if not current_position.size > 0: + log.info("Finishing writing") + log.info("Closing nix files") + self.close() + exit() + else: + if i == 0 and "BaselineActivity" in repro.name: + self._append_tag(repro, 0.0, current_position) + continue + + last_repro_name = self.dataset.repro_runs()[i - 1].name + last_repro_position = ( + self.block.groups[last_repro_name].tags[0].position[0] + + self.block.groups[last_repro_name].tags[0].extent[0] + ) + self._append_tag( + repro, + last_repro_position.reshape(-1, 1), + (current_position - last_repro_position).reshape(-1, 1), + ) + self.close() + # + # + # # NOTE: Create a repro tag + # t = self.block.create_tag( + # f"{repro.name}", + # f"{repro.type}", + # position=current_position, + # ) + # t.metadata = repro.metadata + # + # for i, group in enumerate( + # list(self.relacs_block.groups)[ + # self.stimulus_config["stimulus"]["repro_number_start"] : + # ], + # start=self.stimulus_config["stimulus"]["repro_number_start"], + # ): + # log.debug(group.name) + # log.debug(current_position) + # + # nix_group = self.block.groups[group.name] + # if group.name == "BaselineActivity_1": + # first_peak = 0.0 + # current_position = np.array(first_peak).reshape(1) + # + # # if no multi_tag exists just a tag + # if not group.multi_tags: + # log.debug(f"Creating Tag {group.name}") + # t = self.block.create_tag( + # f"{nix_group.name}", + # f"{nix_group.type}", + # position=current_position, + # ) + # t.metadata = self.nix_file.sections[group.name] + # + # # searching for the end of the repro in the ttl channel + # start_next_repro = time_ttl[ + # peaks_ttl[ + # ( + # time_ttl[peaks_ttl] + # > group.tags[0].extent + current_position - 1 + # ) + # & ( + # time_ttl[peaks_ttl] + # < group.tags[0].extent + current_position + 1 + # ) + # ] + # ] + # log.debug(start_next_repro) + # if start_next_repro.size > 1: + # if np.all(np.diff(start_next_repro) > 0.5): + # log.error("Wrong end point in end of repro") + # log.error(f"{start_next_repro}, {np.max(start_next_repro)}") + # start_next_repro = np.mean(start_next_repro) + # + # if not start_next_repro: + # log.error(f"No Endpoint found for repro {group.name}") + # embed() + # exit() + # t.extent = (start_next_repro - t.position[0]).reshape(1) + # # add references to the tag + # [ + # t.references.extend(ref_group.data_arrays) + # for ref_group in referencs_groups + # if ref_group.data_arrays + # ] + # nix_group.tags.append(t) + # current_position = start_next_repro.reshape(1) + # + # else: + # # NOTE: If repro has multitags + # log.debug(f"Creating Multi Tag {group.name}") + # test_mul_tags = group.multi_tags[0].positions[:] + # test_position_tag, test_extent_tag = ( + # group.tags[0].position[0], + # group.tags[0].extent[0], + # ) + # len_mtag = len( + # test_mul_tags[ + # (test_mul_tags >= test_position_tag) + # & (test_mul_tags <= (test_position_tag + test_extent_tag)) + # ] + # ) + # extents_mtag = group.multi_tags[0].extents[:][ + # (test_mul_tags >= test_position_tag) + # & (test_mul_tags <= (test_position_tag + test_extent_tag)) + # ] + # position_mtags = np.zeros((len_mtag, 1)) + # position_mtags[0] = current_position + # + # for j, extents in enumerate(extents_mtag[1:], start=1): + # next_repro_position = time_ttl[ + # peaks_ttl[ + # ( + # time_ttl[peaks_ttl] + # > extents + current_position - extents / 2 + # ) + # & (time_ttl[peaks_ttl] < extents + current_position + 2) + # ] + # ] + # if next_repro_position.size == 0: + # log.error(f"next start of MultiTag not found") + # embed() + # exit() + # + # if next_repro_position.size > 1: + # if np.all(np.diff(next_repro_position) > 0.005): + # log.error("Wrong end point in end of repro") + # log.error( + # f"{next_repro_position}, {np.max(next_repro_position)}" + # ) + # embed() + # exit() + # exit(1) + # next_repro_position = np.mean(next_repro_position) + # log.debug(f"{j}, {next_repro_position}") + # + # position_mtags[j] = next_repro_position + # current_position = next_repro_position + # + # start_next_repro = time_ttl[ + # peaks_ttl[ + # (time_ttl[peaks_ttl] > current_position + nix_mtag.extents[-1]) + # & ( + # time_ttl[peaks_ttl] + # < current_position + nix_mtag.extents[-1] + 2 + # ) + # ] + # ] + # if not start_next_repro.size == 0: + # if start_next_repro.size > 1: + # if np.all(np.diff(start_next_repro) > 0.005): + # log.error("Wrong end point in end of repro") + # log.error(f"{start_next_repro}, {np.max(start_next_repro)}") + # embed() + # exit(1) + # + # start_next_repro = np.mean(start_next_repro) + # + # else: + # log.debug( + # "No ttl pluse foud for the end of the repro create time point" + # ) + # log.debug("Taking the next ttl pulse") + # new_repro_start_index = peaks_ttl[ + # (time_ttl[peaks_ttl] > current_position - 1) + # & (time_ttl[peaks_ttl] < current_position + 2) + # ] + # + # # if multiple take the last one + # if new_repro_start_index.size > 1: + # new_repro_start_index = new_repro_start_index[-1] + # + # log.debug(time_ttl[new_repro_start_index]) + # try: + # next_repro_start = peaks_ttl[ + # np.where(new_repro_start_index == peaks_ttl)[0] + 1 + # ] + # except IndexError: + # if np.where(new_repro_start_index == peaks_ttl)[0] + 1 == len( + # peaks_ttl + # ): + # log.debug("Finishing writing") + # self.nix_file.close() + # self.relacs_nix_file.close() + # exit(1) + # if next_repro_start.size > 1: + # log.debug("Start of next Repro has multiple ttl pulse") + # embed() + # exit() + # + # # check if the time difference is greater and 5 seconds + # if ( + # not time_ttl[next_repro_start] - time_ttl[new_repro_start_index] + # > 5 + # ): + # log.error("Wrong endpoint for repro") + # exit(1) + # start_next_repro = time_ttl[next_repro_start] + # log.info(f"Start of new Repro {start_next_repro}") + # + # current_position = start_next_repro + # + # # NOTE: If SAM or Baseline we dont have to find the next current position + # if ( + # group.name.split("_")[0] == "SAM" + # or group.name.split("_")[0] == "BaselineActivity" + # # or group.name.split("_")[0] == "FileStimulus" + # ): + # current_position = current_position.reshape(1) + # log.info(f"Start of new Repro {current_position}") + # continue + # + # # peaks_repro_index = peaks_ttl[ + # # (time_ttl[peaks_ttl] > current_position - 1) + # # & (time_ttl[peaks_ttl] < current_position + 2) + # # ] + # # + # # # if multiple take the last one + # # if peaks_repro_index.size > 1: + # # peaks_repro_index = peaks_repro_index[-1] + # # + # # log.debug(time_ttl[peaks_repro_index]) + # # next_repro_start = peaks_ttl[ + # # np.where(peaks_repro_index == peaks_ttl)[0] + 1 + # # ] + # # if next_repro_start.size > 1: + # # embed() + # # + # # # check if the time difference is greater and 5 seconds + # # if not time_ttl[next_repro_start] - time_ttl[peaks_repro_index] > 5: + # # log.error("Wrong endpoint for repro") + # # embed() + # # exit() + # # current_position = time_ttl[next_repro_start] + # # log.info(f"Start of new Repro {current_position}") + # # + # # current_position = current_position.reshape(1) + # + # self.nix_file.close() + # self.relacs_nix_file.close() + + def create_repros_from_config_file( + self, + ): + ttl_oeph = self.block.data_arrays["ttl-line"][:] + peaks_ttl = signal.find_peaks( + ttl_oeph.flatten(), + **self.stimulus_config["stimulus"]["peak_detection"], + )[0] + time_ttl = np.arange(len(ttl_oeph)) / self.cfg.open_ephys.samplerate + + number_of_repros = len(self.stimulus_config["repros"]["name"]) + + referencs_groups = [ + self.block.groups["neuronal-data"], + self.block.groups["spike-data"], + self.block.groups["efish"], + ] + + for repro_index in range(number_of_repros): + name = self.stimulus_config["repros"]["name"][repro_index] + log.debug(name) + start = np.array(self.stimulus_config["repros"]["start"][repro_index]) + end = np.array(self.stimulus_config["repros"]["end"][repro_index]) + nix_group = self.block.groups[name] + if start.size > 1: + start_repro = time_ttl[ + peaks_ttl[ + (time_ttl[peaks_ttl] > start[0]) + & (time_ttl[peaks_ttl] < start[1]) + ] + ] + if start_repro.size > 1: + if np.all(np.diff(start_repro) > 0.005): + log.error("Wrong end point in end of repro") + log.error(f"{name[repro_index]}, {np.max(start_repro)}") + exit(1) + start_repro = np.mean(start_repro) + else: + start_repro = start_repro[0] + else: + start_repro = start[0] + + if end.size > 1: + end_repro = time_ttl[ + peaks_ttl[ + (time_ttl[peaks_ttl] > end[0]) & (time_ttl[peaks_ttl] < end[1]) + ] + ] + if end_repro.size > 1: + if np.all(np.diff(end_repro) > 0.005): + log.error("Wrong end point in end of repro") + log.error(f"{name[repro_index]}, {np.max(end_repro)}") + exit(1) + end_repro = np.mean(end_repro) + else: + end_repro = end[0] + + nix_tag = self.block.create_tag( + f"{nix_group.name}", + f"{nix_group.type}", + position=[start_repro], + ) + nix_tag.extent = [end_repro - start_repro] + nix_tag.metadata = self.nix_file.sections[name] + + # NOTE: adding refs to tag + [ + nix_tag.references.extend(ref_groups.data_arrays) + for ref_groups in referencs_groups + if ref_groups.data_arrays + ] + nix_group.tags.append(nix_tag) + + if not self.relacs_block.groups[name].multi_tags: + log.debug(f"no multitags in repro {name}, skipping") + continue + + start_repro_multi_tag = start_repro.copy() + positions = [] + positions.append(np.array(start_repro)) + extents = [] + extents_relacsed_nix = ( + self.relacs_block.groups[name].multi_tags[0].extents[:] + ) + extents.append(np.array(extents_relacsed_nix[0])) + index_multi_tag = 0 + while start_repro_multi_tag < end_repro: + log.debug(f"{start_repro_multi_tag}") + + start_repro_multi_tag = time_ttl[ + peaks_ttl[ + ( + time_ttl[peaks_ttl] + > start_repro_multi_tag + + extents_relacsed_nix[index_multi_tag] + ) + & ( + time_ttl[peaks_ttl] + < start_repro_multi_tag + + extents_relacsed_nix[index_multi_tag] + + 2 + ) + ] + ] + + if start_repro_multi_tag.size == 0: + log.debug("Did not find any peaks for new start multi tag") + log.debug( + f"Differenz to end of repro {end_repro - (positions[-1] + extents_relacsed_nix[index_multi_tag])}" + ) + break + + if start_repro_multi_tag.size > 1: + if np.all(np.diff(start_repro_multi_tag) > 0.005): + log.error("Wrong end point in end of repro") + log.error(f"Repro_name: {name[repro_index]}") + log.error(f"multitag_index: {index_multi_tag}") + log.error(f"max_value {np.max(start_repro_multi_tag)}") + exit(1) + start_repro_multi_tag = np.mean(start_repro_multi_tag) + else: + start_repro_multi_tag = start_repro_multi_tag[0] + if end_repro - start_repro_multi_tag < 1: + log.debug("Posssible endpoint detected") + log.debug( + f"Differenz to repro end: {end_repro - start_repro_multi_tag}" + ) + break + + positions.append(np.array(start_repro_multi_tag)) + extents.append(extents_relacsed_nix[index_multi_tag]) + + positions = np.array(positions).reshape(len(positions), 1) + extents = np.array(extents) + if positions.size != extents.size: + log.error("Calcualted positions and extents do not match ") + log.error( + f"Shape positions {positions.shape}, shape extents {extents.shape}" + ) + if positions.shape != extents.shape: + log.error("Shape of Calculated positions and extents do not match") + log.error( + f"Shape positions {positions.shape}, shape extents {extents.shape}" + ) + embed() + exit() + + nix_mtag = self.block.create_multi_tag( + f"{nix_group.name}", + f"{nix_group.type}", + positions=positions, + extents=extents, + ) + nix_mtag.metadata = self.nix_file.sections[name] + + # NOTE: adding refs to mtag + [ + nix_mtag.references.extend(ref_groups.data_arrays) + for ref_groups in referencs_groups + if ref_groups.data_arrays + ] + nix_group.multi_tags.append(nix_mtag) + + def plot_stimulus(self): + ttl_oeph = self.block.data_arrays["ttl-line"][:] + + time_index = np.arange(len(ttl_oeph)) + peaks_ttl = time_index[(np.roll(ttl_oeph, 1) < 2) & (ttl_oeph > 2)] + + stimulus_oeph = self.block.data_arrays["stimulus"] + stimulus = self.relacs_block.data_arrays["GlobalEFieldStimulus"] + + plt.plot(np.arange(stimulus.size) / 20_000.0, stimulus, label="relacs-stimulus") + plt.plot( + np.arange(len(stimulus_oeph)) / 30_000.0, + stimulus_oeph[:], + label="open-ephys", + ) + plt.plot( + np.arange(len(ttl_oeph)) / 30_000.0, + ttl_oeph[:], + label="ttl-line", + ) + plt.scatter( + np.arange(len(ttl_oeph))[peaks_ttl] / 30_000.0, + ttl_oeph[peaks_ttl], + label="detected peaks", + color="red", + zorder=100, + ) + plt.legend(loc="upper right") + plt.show() + + def close(self): + self.dataset.close() + self.nix_file.close() + self.relacs_nix_file.close() + + +# if __name__ == "__main__": +# create_nix = CreateNix() +# 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