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importing repro runs works

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Jan Grewe 2019-03-11 15:03:01 +01:00
parent 4bb0cb5f9d
commit c6fc8a857a
1 changed files with 49 additions and 28 deletions
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77
database.py
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@ -3,8 +3,8 @@ import datajoint as dj
import nixio as nix
import os
import glob
from util import read_info_file, find_key_recursive, deep_get, read_dataset_info, \
nix_metadata_to_yaml
import util as ut
from IPython import embed
schema = dj.schema("fish_book", locals())
@ -56,6 +56,7 @@ class Dataset(dj.Manual):
sane = False
f.close()
except ():
f = None
print("file: %s is NOT SANE!")
sane = False
return sane
@ -176,7 +177,7 @@ class RePro(dj.Manual):
@staticmethod
def get_template_tuple(repro_id=None):
tup = dict(repro_id=None, dataset_id=None, run=0, repro_name="", settings="")
tup = dict(repro_id=None, dataset_id=None, run=0, repro_name="", settings=None)
if repro_id is not None:
d = dict((RePro() & {"repro_id": repro_id}).fetch1())
return d
@ -188,9 +189,9 @@ def populate_datasets(data_path):
if not os.path.exists(data_path):
return
dset_name = os.path.split(data_path)[-1]
experimenter, rec_date, quality, comment, has_nix = read_dataset_info(os.path.join(data_path, 'info.dat'))
experimenter, rec_date, quality, comment, has_nix = ut.read_dataset_info(os.path.join(data_path, 'info.dat'))
if not experimenter:
return
return False
inserts = Dataset.get_template_tuple()
inserts["dataset_id"] = dset_name
@ -201,19 +202,20 @@ def populate_datasets(data_path):
inserts["comment"] = comment
inserts["has_nix"] = has_nix
Dataset().insert1(inserts, skip_duplicates=True)
return True
def populate_subjects(data_path):
print("Importing subject(s) of %s" % data_path)
print("\tImporting subject(s) of %s" % data_path)
dset_name = os.path.split(data_path)[-1]
info_file = os.path.join(data_path, 'info.dat')
if not os.path.exists(info_file):
return None, None, False
info = read_info_file(info_file)
info = ut.read_info_file(info_file)
p = []
find_key_recursive(info, "Subject", p)
ut.find_key_recursive(info, "Subject", p)
if len(p) > 0:
subj = deep_get(info, p)
subj = ut.deep_get(info, p)
inserts = Subject.get_template_tuple()
inserts["subject_id"] = subj["Identifier"]
inserts["species"] = subj["Species"]
@ -241,23 +243,23 @@ def populate_subjects(data_path):
def populate_cells(data_path):
print("Importing cell(s) of %s" % data_path)
print("\tImporting cell(s) of %s" % data_path)
dset_name = os.path.split(data_path)[-1]
info_file = os.path.join(data_path, 'info.dat')
if not os.path.exists(info_file):
return None, None, False
info = read_info_file(info_file)
info = ut.read_info_file(info_file)
p = []
find_key_recursive(info, "Subject", p)
subject_info = deep_get(info, p)
ut.find_key_recursive(info, "Subject", p)
subject_info = ut.deep_get(info, p)
p = []
find_key_recursive(info, "Cell", p)
cell_info = deep_get(info, p)
ut.find_key_recursive(info, "Cell", p)
cell_info = ut.deep_get(info, p)
p = []
find_key_recursive(info, "Firing Rate1", p)
firing_rate = deep_get(info, p, default=0.0)
ut.find_key_recursive(info, "Firing Rate1", p)
firing_rate = ut.deep_get(info, p, default=0.0)
if isinstance(firing_rate, str):
firing_rate = float(firing_rate[:-2])
@ -292,29 +294,43 @@ def populate_cells(data_path):
def populate_repros(data_path):
print("Importing RePro(s) of %s" % data_path)
print("\tImporting RePro(s) of %s" % data_path)
dset_name = os.path.split(data_path)[-1]
if len(Dataset & {"dataset_id": dset_name}) != 1:
return False
dataset = dict((Dataset & {"dataset_id": dset_name}).fetch1())
if dataset["has_nix"]:
print("scanning nix file")
print("\t\tscanning nix file")
nix_files = glob.glob(os.path.join(dataset["data_source"], "*.nix"))
for nf in nix_files:
if not Dataset.check_file_integrity(nf):
print("file is not sane!!!")
continue
f = nix.File.open(nf, nix.FileMode.ReadOnly)
b = f.blocks[0]
for t in b.tags:
if "relacs.repro_run" in t.type and "RePro-Info" in t.metadata.sections:
if "relacs.repro_run" in t.type:
rs = t.metadata.find_sections(lambda x: "Run" in x.props)
if len(rs) == 0:
continue
rs = rs[0]
rp = RePro.get_template_tuple()
rp["run"] = t.metadata["RePro-Info"]["Run"]
rp["run"] = rs["Run"]
rp["repro_name"] = rs["RePro"]
rp["dataset_id"] = dataset["dataset_id"]
rp["repro_id"] = t.name
rp["repro_name"] = t.metadata["RePro-Info"]["RePro"]
rp["settings"] = nix_metadata_to_yaml(t.metadata.sections[0])
settings = t.metadata.find_sections(lambda x: "settings" in x.type)
if len(settings) > 0:
rp["settings"] = ut.nix_metadata_to_yaml(settings[0])
else:
rp["settings"] = ut.nix_metadata_to_yaml(t.metadata)
RePro.insert1(rp, skip_duplicates=True)
f.close()
f = None
else:
pass
return True
def drop_tables():
@ -324,14 +340,19 @@ def drop_tables():
def populate(datasets):
for d in datasets:
#populate_datasets(d)
#populate_subjects(d)
#populate_cells(d)
populate_repros(d)
if not populate_datasets(d):
continue
populate_subjects(d)
populate_cells(d)
try:
populate_repros(d)
except ():
print("something went wrong! %s" % d)
if __name__ == "__main__":
data_dir = "../../science/high_frequency_chirps/data"
# data_dir = "../../science/high_frequency_chirps/data"
data_dir = "../high_freq_chirps/data"
datasets = glob.glob(os.path.join(data_dir, '2018*'))
# drop_tables()
populate(datasets)