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@@ -1,129 +0,0 @@
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-import nixio as nix
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-import matplotlib.pyplot as plt
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-import numpy as np
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-import os
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-from IPython import embed
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-
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-
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-def metadata_overview(nf):
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- assert(nf and isinstance(nf, nix.pycore.file.File) and nf.is_open)
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-
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- print("Print some of the stored metadata")
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- print_metadata(nix_file, sec_type="recording", sec_name="recording", max_depth=0)
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- print("\n")
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- print_metadata(nix_file, sec_name="subject")
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- print("\n")
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- print_metadata(nix_file, sec_name="cell")
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- print("\n")
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-
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-
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-def print_metadata(nf, sec_type=None, sec_name=None, max_depth=-1):
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- """Display stored metadata using the section's pprint function.
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-
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- If the desired section name or type are provided, the find_sections
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- method is used to filter the metadata, if neither is provided all sections
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- will be printed.
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-
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- Arguments:
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- nf -- opened nix file
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-
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- Keyword arguments:
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- sec_type --- string: the section type (default None)
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- sec_name --- string, the section name (default None)
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- max_depth --- int, the maximum depth of the metadata tree (default -1, i.e. unlimited)
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- """
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- assert(not sec_name or isinstance(sec_name, str))
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- assert(not sec_type or isinstance(sec_type, str))
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-
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- sec_type = sec_type.lower() if sec_type else None
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- sec_name = sec_name.lower() if sec_name else None
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- sections = nf.find_sections(lambda s:
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- (sec_type and sec_type in s.type.lower() or not sec_type)
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- and (sec_name and sec_name in s.name.lower() or not sec_name)
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- or (not sec_name and not sec_type))
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- for s in sections:
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- s.pprint(max_depth=max_depth)
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-
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-
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-def find_mtags_for_tag(block, tag):
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- """Finds the MultiTags (prepresentatives of the actual stimulus
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- outputs) that ran during a RePro run. Relacs makes sure that stimulations
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- with the same settings end up in the same MultiTag.
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-
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- Arguments:
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- block --- nix.Block, the block in which to look for MultiTags
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- tag --- nix.Tag, the Tag (aka, the RepPro run) defining the search interval
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-
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- Returns:
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- a list of MultiTags
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- a list of lists containing the position indices for the respective MultiTags
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- """
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- assert(isinstance(block, nix.pycore.block.Block))
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- assert(isinstance(tag, nix.pycore.tag.Tag))
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- mtags = []
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- positions = []
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- tag_start = np.atleast_1d(tag.position)
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- tag_end = tag_start + np.atleast_1d(tag.extent)
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- for mt in block.multi_tags:
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- mt_starts = np.atleast_1d(mt.positions[:])
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- mt_ends = mt_starts + np.atleast_1d(mt.extents[:])
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- pos = np.argwhere(mt_starts[(mt_starts > tag_start) &
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- (mt_starts < tag_end) &
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- (mt_ends <= tag_end)])[:, 0]
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- if len(pos) > 0:
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- mtags.append(mt)
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- positions.append(pos)
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- return mtags, positions
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-
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-
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-def data_overview(nf):
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- assert(nf and isinstance(nf, nix.pycore.file.File) and nf.is_open)
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- b = nf.blocks[0]
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-
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- print("Regularly sampled data:")
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- regular_sampled_data = [da for da in b.data_arrays if da.dimensions[0].dimension_type == nix.DimensionType.Sample]
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- for rsd in regular_sampled_data:
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- print("\t%s, size: %s" % (rsd.name, str(rsd.shape)))
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-
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- print("Event data:")
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- event_data = [da for da in b.data_arrays if da.dimensions[0].dimension_type == nix.DimensionType.Range]
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- for ed in event_data:
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- print("\t%s, size: %s" % (ed.name, str(ed.shape)))
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-
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- print("Sets:")
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- set_data = [da for da in b.data_arrays if da.dimensions[0].dimension_type == nix.DimensionType.Set]
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- for sd in set_data:
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- print("\t%s, size: %s" % (sd.name, str(sd.shape)))
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- print("\n")
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-
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-
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-def stimulus_overview(nf):
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- assert(nf and isinstance(nf, nix.pycore.file.File) and nf.is_open)
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- b = nf.blocks[0]
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-
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- print("Stimulations, aka RePro runs:")
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- repro_runs = [t for t in b.tags if "repro_run" in t.type]
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- for rr in repro_runs:
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- start = rr.position[0]
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- end = start + rr.extent[0]
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- print("\t RePro %s, time: %.4f --> %.4f%s" % (rr.name, start, end, rr.units[0]))
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- mts, positions = find_mtags_for_tag(b, rr)
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- for mt, pos in zip(mts, positions):
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- print("\t\t with %i stimulus repetitions" % (len(pos)))
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- print("\n")
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-
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-
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-if __name__ == "__main__":
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- example_file = "2018-11-05-ab-invivo-1.nix"
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- if not os.path.exists(example_file):
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- print("Example file was not found")
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- exit()
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- nix_file = nix.File.open(example_file, nix.FileMode.ReadOnly)
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-
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- metadata_overview(nix_file)
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-
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- data_overview(nix_file)
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-
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- stimulus_overview(nix_file)
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-
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- nix_file.close()
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