nix-examples/single_cell_intracellular_spikes/explore.py

import nixio as nix
import matplotlib.pyplot as plt
import numpy as np
import os
from IPython import embed


def metadata_overview(nf):
    assert(nf and isinstance(nf, nix.pycore.file.File) and nf.is_open)

    print("Print some of the stored metadata")
    print_metadata(nix_file, sec_type="recording", sec_name="recording", max_depth=0)
    print("\n")
    print_metadata(nix_file, sec_name="subject")
    print("\n")
    print_metadata(nix_file, sec_name="cell")
    print("\n")


def print_metadata(nf, sec_type=None, sec_name=None, max_depth=-1):
    """Display stored metadata using the section's pprint function.

    If the desired section name or type are provided, the find_sections
    method is used to filter the metadata, if neither is provided all sections
    will be printed.

    Arguments:
    nf -- opened nix file

    Keyword arguments:
    sec_type --- string: the section type (default None)
    sec_name --- string, the section name (default None)
    max_depth --- int, the maximum depth of the metadata tree (default -1, i.e. unlimited)
    """
    assert(not sec_name or isinstance(sec_name, str))
    assert(not sec_type or isinstance(sec_type, str))

    sec_type = sec_type.lower() if sec_type else None
    sec_name = sec_name.lower() if sec_name else None
    sections = nf.find_sections(lambda s:
                                (sec_type and sec_type in s.type.lower() or not sec_type)
                                and (sec_name and sec_name in s.name.lower() or not sec_name)
                                or (not sec_name and not sec_type))
    for s in sections:
        s.pprint(max_depth=max_depth)


def find_mtags_for_tag(block, tag):
    """Finds the MultiTags (prepresentatives of the actual stimulus
    outputs) that ran during a RePro run. Relacs makes sure that stimulations
    with the same settings end up in the same MultiTag.

    Arguments:
    block --- nix.Block, the block in which to look for MultiTags
    tag --- nix.Tag, the Tag (aka, the RepPro run) defining the search interval

    Returns:
    a list of MultiTags
    a list of lists containing the position indices for the respective MultiTags
    """
    assert(isinstance(block, nix.pycore.block.Block))
    assert(isinstance(tag, nix.pycore.tag.Tag))
    mtags = []
    positions = []
    tag_start = np.atleast_1d(tag.position)
    tag_end = tag_start + np.atleast_1d(tag.extent)
    for mt in block.multi_tags:
        mt_starts = np.atleast_1d(mt.positions[:])
        mt_ends = mt_starts + np.atleast_1d(mt.extents[:])
        pos = np.argwhere(mt_starts[(mt_starts > tag_start) &
                                    (mt_starts < tag_end) &
                                    (mt_ends <= tag_end)])[:, 0]
        if len(pos) > 0:
            mtags.append(mt)
            positions.append(pos)
    return mtags, positions


def data_overview(nf):
    assert(nf and isinstance(nf, nix.pycore.file.File) and nf.is_open)
    b = nf.blocks[0]

    print("Regularly sampled data:")
    regular_sampled_data = [da for da in b.data_arrays if da.dimensions[0].dimension_type == nix.DimensionType.Sample]
    for rsd in regular_sampled_data:
        print("\t%s, size: %s" % (rsd.name, str(rsd.shape)))

    print("Event data:")
    event_data = [da for da in b.data_arrays if da.dimensions[0].dimension_type == nix.DimensionType.Range]
    for ed in event_data:
        print("\t%s, size: %s" % (ed.name, str(ed.shape)))

    print("Sets:")
    set_data = [da for da in b.data_arrays if da.dimensions[0].dimension_type == nix.DimensionType.Set]
    for sd in set_data:
        print("\t%s, size: %s" % (sd.name, str(sd.shape)))
    print("\n")


def stimulus_overview(nf):
    assert(nf and isinstance(nf, nix.pycore.file.File) and nf.is_open)
    b = nf.blocks[0]

    print("Stimulations, aka RePro runs:")
    repro_runs = [t for t in b.tags if "repro_run" in t.type]
    for rr in repro_runs:
        start = rr.position[0]
        end = start + rr.extent[0]
        print("\t RePro %s,  time: %.4f --> %.4f%s" % (rr.name, start, end, rr.units[0]))
        mts, positions = find_mtags_for_tag(b, rr)
        for mt, pos in zip(mts, positions):
            print("\t\t with %i stimulus repetitions" % (len(pos)))
    print("\n")


if __name__ == "__main__":
    example_file = "2018-11-05-ab-invivo-1.nix"
    if not os.path.exists(example_file):
        print("Example file was not found")
        exit()
    nix_file = nix.File.open(example_file, nix.FileMode.ReadOnly)

    metadata_overview(nix_file)

    data_overview(nix_file)

    stimulus_overview(nix_file)
    
    nix_file.close()