fixes and move all convenience methods to forntend classes
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@ -3,18 +3,18 @@ import nixio as nix
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import os
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import numpy as np
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from IPython import embed
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from database import Datasets, Repros
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from database import *
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schema = dj.schema("fish_book", locals())
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class BaselineData(object):
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def __init__(self, dataset:Datasets):
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def __init__(self, dataset:Dataset):
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self.__data = []
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self.__dataset = dataset
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self.__cell = dataset.cells[0]
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self._get_data()
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def _get_data(self):
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if not self.__dataset:
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self.__data = []
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@ -89,6 +89,9 @@ class BaselineData(object):
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if __name__ == "__main__":
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print("Test")
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dataset = Datasets & "dataset_id like '2018-11-09-aa-%' "
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baseline = BaselineData(dataset.fetch1())
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embed()
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exit()
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dataset = Dataset(tuple=(Datasets & "dataset_id like '2018-11-09-aa-%'").fetch(limit=1, as_dict=True))
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baseline = BaselineData(dataset)
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embed()
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128
database.py
128
database.py
@ -6,7 +6,6 @@ import glob
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import util as ut
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import uuid
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import yaml
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from IPython import embed
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schema = dj.schema("fish_book_new", locals())
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@ -65,25 +64,13 @@ class Datasets(dj.Manual):
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sane = False
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return sane
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@staticmethod
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def datasets(min_duration=None, experimenter=None, quality=None):
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dsets = Datasets
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if min_duration:
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dsets = dsets & "duration > %.2f" % min_duration
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if experimenter:
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dsets = dsets & dict(experimenter=experimenter)
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if quality:
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dsets = dsets & "quality like '{0:s}'".format(quality)
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return [Dataset(tuple=d) for d in dsets]
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class Dataset:
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def __init__(self, dataset_id=None, exact=False, tuple=None):
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def __init__(self, dataset_id=None, tuple=None):
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if tuple:
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self.__tuple = tuple
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elif dataset_id:
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wildcard = "%" if not exact else ""
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pattern = "dataset_id like '{0:s}{0:s}{0:s}'".format(wildcard, dataset_id, wildcard)
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pattern = "dataset_id like '{0:s}'".format(dataset_id)
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dsets = (Datasets & pattern)
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assert(len(dsets) == 1), "Dataset name is not unique!"
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self.__tuple = dsets.fetch(limit=1)[0]
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@ -136,6 +123,17 @@ class Dataset:
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subjs = (Subjects * (SubjectDatasetMap & self.__tuple))
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return [Subject(tuple=s) for s in subjs]
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@staticmethod
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def find_datasets(min_duration=None, experimenter=None, quality=None):
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dsets = Datasets
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if min_duration:
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dsets = dsets & "duration > %.2f" % min_duration
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if experimenter:
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dsets = dsets & "experimenter like '%{0:s}%'".format(experimenter)
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if quality:
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dsets = dsets & "quality like '{0:s}'".format(quality)
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return [Dataset(tuple=d) for d in dsets]
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@schema
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class Subjects(dj.Manual):
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@ -171,25 +169,7 @@ class Subjects(dj.Manual):
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self.insert1(inserts, skip_duplicates=True)
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nix_file.close()
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@staticmethod
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def subjects(species=None):
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subjs = []
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if species:
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subjs = (Subjects & "species like '%{0:s}%'".format(species))
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else:
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subjs = (Subjects & True)
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return [Subject(tuple=s for s in subjs]
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@staticmethod
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def unique_species():
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all_species = (Subjects & True).fetch("species")
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return np.unique(all_species)
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@property
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def properties(self):
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return (SubjectProperties & self).fetch1()
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#@property
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#@property
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#def datasets(self):
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# retrun
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@ -218,6 +198,22 @@ class Subject:
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cs = Cells & self.__tuple
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return [Cell(tuple=c) for c in cs]
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@property
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def properties(self):
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return (SubjectProperties & self.__tuple).fetch(as_dict=True)
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@staticmethod
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def find_subjects(species=None):
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subjs = Subjects & True
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if species:
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subjs = (Subjects & "species like '%{0:s}%'".format(species))
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return [Subject(tuple=s) for s in subjs]
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@staticmethod
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def unique_species():
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all_species = (Subjects & True).fetch("species")
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return np.unique(all_species)
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@schema
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class SubjectDatasetMap(dj.Manual):
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@ -276,24 +272,6 @@ class Cells(dj.Manual):
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return d
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return tup
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@property
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def subject(self):
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return Subjects & self
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@staticmethod
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def celltypes():
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return np.unique(Cells.fetch("cell_type"))
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@staticmethod
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def cells(celltype=None, species=None, quality="good"):
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cs = Cells * CellDatasetMap * Datasets * Subjects
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if celltype:
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cs = cs & "cell_type like '{0:s}'".format(celltype)
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if species:
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cs = cs & "species like '%{0:s}%'".format(species)
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if quality:
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cs = cs & "quality like '{0:s}'".format(quality)
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return cs
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class Cell:
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def __init__(self, cell_id=None, tuple=None):
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@ -305,12 +283,54 @@ class Cell:
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assert (len(cells) == 1), "Cell id is not unique!"
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self.__tuple = cells.fetch(as_dict=True)[0]
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else:
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print("Empty Cell, not linke to any database entry!")
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print("Empty Cell, not linked to any database entry!")
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@property
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def cell_id(self):
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return self.__tuple["cell_id"] if "cell_id" in self.__tuple.keys() else ""
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@property
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def cell_type(self):
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return self.__tuple["cell_type"] if "cell_type" in self.__tuple.keys() else ""
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@property
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def firing_rate(self):
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return self.__tuple["firing_rate"] if "firing_rate" in self.__tuple.keys() else 0.0
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@property
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def location(self):
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keys = ["structure", "region", "subregion", "depth", "lateral_pos", "transversal_section"]
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loc = {}
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for k in keys:
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if k in self.__tuple.keys():
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loc[k] = self.__tuple[k]
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else:
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loc[k] = ""
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return loc
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@property
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def subject(self):
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return Subject(tuple=(Subjects & {"subject_id": self.__tuple["subject_id"]}).fetch(limit=1, as_dict=True)[0])
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@staticmethod
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def celltypes():
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return np.unique(Cells.fetch("cell_type"))
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@staticmethod
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def find_cells(cell_type=None, species=None, quality="good"):
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cs = Cells * CellDatasetMap * Datasets * Subjects
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if cell_type:
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cs = cs & "cell_type like '{0:s}'".format(cell_type)
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if species:
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cs = cs & "species like '%{0:s}%'".format(species)
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if quality:
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cs = cs & "quality like '{0:s}'".format(quality)
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return [Cell(tuple=c) for c in cs]
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def __str__(self):
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str = ""
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str += "Cell: %s \t type: %s\n"%(self.cell_id, self.cell_type)
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return str
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@schema
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class CellDatasetMap(dj.Manual):
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@ -677,6 +697,6 @@ if __name__ == "__main__":
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# data_dir = "../high_freq_chirps/data"
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# drop_tables()
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# datasets = glob.glob("/Users/jan/zwischenlager/2012-*")2010-06-21-ac/info.dat
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datasets = glob.glob(os.path.join(data_dir, '/data/apteronotus/2018-*'))
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datasets = glob.glob(os.path.join(data_dir, '/data/apteronotus/2010-*'))
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populate(datasets, update=False)
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