diff --git a/extraction/core/extractor.py b/extraction/core/extractor.py index b588678276f555df62738c65e2ce41fb35477a2c..1a41716835da1cca36ed7081df8d3dbf79f59a3b 100644 --- a/extraction/core/extractor.py +++ b/extraction/core/extractor.py @@ -1,7 +1,7 @@ import logging import typing as t from time import perf_counter -from typing import Callable, Dict, List +from typing import List import h5py import numpy as np @@ -19,7 +19,6 @@ from extraction.core.functions.loaders import ( load_mergefuns, load_redfuns, ) -from extraction.core.functions.utils import depth # Global parameters used to load functions that either analyse cells or their background. These global parameters both allow the functions to be stored in a dictionary for access only on demand and to be defined simply in extraction/core/functions. CELL_FUNS, TRAPFUNS, FUNS = load_funs() @@ -38,9 +37,9 @@ class ExtractorParameters(ParametersABC): def __init__( self, - tree: Dict[str, Dict[Callable, List[str]]] = None, + tree: t.Dict[str, t.Dict[t.Callable, t.List[str]]], sub_bg: set = set(), - multichannel_ops: Dict = {}, + multichannel_ops: t.Dict = {}, ): """ Parameters @@ -53,7 +52,7 @@ class ExtractorParameters(ParametersABC): sub_bg: set multichannel_ops: dict """ - self.tree = fill_tree(tree) + self.tree = tree self.sub_bg = sub_bg self.multichannel_ops = multichannel_ops @@ -220,7 +219,7 @@ class Extractor(ProcessABC): # load metadata from h5 file whose name is given by self.local self.meta = load_attributes(self.local) - def get_traps( + def get_tiles( self, tp: int, channels: list = None, @@ -231,7 +230,7 @@ class Extractor(ProcessABC): Finds traps for a given time point and given channels and z-stacks. Returns None if no traps are found. - Any additional keyword arguments are passed to tiler.get_traps_timepoint + Any additional keyword arguments are passed to tiler.get_tiles_timepoint Parameters ---------- @@ -270,7 +269,7 @@ class Extractor(ProcessABC): traps: List[np.array], masks: List[np.array], metric: str, - labels: Dict = None, + labels: t.Dict = None, ) -> dict: """ Apply a function to a whole position.