From de4c25e7b98e1d5e5ee617646941370dd1e41f1b Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Al=C3=A1n=20Mu=C3=B1oz?= <alan.munoz@ed.ac.uk>
Date: Tue, 10 Jan 2023 23:46:54 +0000
Subject: [PATCH] feat(aliby): integrate logging into existing steps
---
src/aliby/baby_client.py | 9 +++------
src/aliby/tile/tiler.py | 6 +++---
src/extraction/core/extractor.py | 24 ++++++++++--------------
3 files changed, 16 insertions(+), 23 deletions(-)
diff --git a/src/aliby/baby_client.py b/src/aliby/baby_client.py
index f13c5b02..8fcd0f06 100644
--- a/src/aliby/baby_client.py
+++ b/src/aliby/baby_client.py
@@ -13,7 +13,7 @@ import baby.errors
import h5py
import numpy as np
import requests
-from agora.abc import ParametersABC
+from agora.abc import ParametersABC, StepABC
from baby import modelsets
from baby.brain import BabyBrain
from baby.crawler import BabyCrawler
@@ -128,7 +128,7 @@ class BabyParameters(ParametersABC):
self.update("model_config", weights_flattener)
-class BabyRunner:
+class BabyRunner(StepABC):
"""A BabyRunner object for cell segmentation.
Does segmentation one time point at a time."""
@@ -157,20 +157,17 @@ class BabyRunner:
.swapaxes(1, 2)
)
- def run_tp(self, tp, with_edgemasks=True, assign_mothers=True, **kwargs):
+ def _run_tp(self, tp, with_edgemasks=True, assign_mothers=True, **kwargs):
"""Simulating processing time with sleep"""
# Access the image
t = perf_counter()
img = self.get_data(tp)
- logging.debug(f"Timing:BF_fetch:{perf_counter()-t}s")
- t = perf_counter()
segmentation = self.crawler.step(
img,
with_edgemasks=with_edgemasks,
assign_mothers=assign_mothers,
**kwargs,
)
- logging.debug(f"Timing:crawler_step:{perf_counter()-t}s")
return format_segmentation(segmentation, tp)
diff --git a/src/aliby/tile/tiler.py b/src/aliby/tile/tiler.py
index 16f9b2f8..f0a75472 100644
--- a/src/aliby/tile/tiler.py
+++ b/src/aliby/tile/tiler.py
@@ -28,7 +28,7 @@ import h5py
import numpy as np
from skimage.registration import phase_cross_correlation
-from agora.abc import ParametersABC, ProcessABC
+from agora.abc import ParametersABC, StepABC
from agora.io.writer import BridgeH5
from aliby.io.image import ImageLocalOME, ImageDir
from aliby.tile.traps import segment_traps
@@ -200,7 +200,7 @@ class TilerParameters(ParametersABC):
_defaults = {"tile_size": 117, "ref_channel": "Brightfield", "ref_z": 0}
-class Tiler(ProcessABC):
+class Tiler(StepABC):
"""
Remote Timelapse Tiler.
@@ -455,7 +455,7 @@ class Tiler(ProcessABC):
ndtrap = self.ifoob_pad(full, trap.as_range(tp))
return ndtrap
- def run_tp(self, tp):
+ def _run_tp(self, tp):
"""
Find traps if they have not yet been found.
Determine any translational drift of the current image from the
diff --git a/src/extraction/core/extractor.py b/src/extraction/core/extractor.py
index 6a5af6bc..443bbc59 100644
--- a/src/extraction/core/extractor.py
+++ b/src/extraction/core/extractor.py
@@ -1,4 +1,3 @@
-import logging
import typing as t
from time import perf_counter
from typing import List
@@ -6,7 +5,7 @@ from typing import List
import h5py
import numpy as np
import pandas as pd
-from agora.abc import ParametersABC, ProcessABC
+from agora.abc import ParametersABC, StepABC
from agora.io.cells import Cells
from agora.io.writer import Writer, load_attributes
@@ -89,7 +88,7 @@ class ExtractorParameters(ParametersABC):
return cls(**exparams_from_meta(meta))
-class Extractor(ProcessABC):
+class Extractor(StepABC):
"""
The Extractor applies a metric, such as area or median, to cells identified in the image tiles using the cell masks.
@@ -584,28 +583,22 @@ class Extractor(ProcessABC):
elif channel in self.img_bgsub:
return self.img_bgsub[channel]
- def run_tp(self, tp, **kwargs):
- """
- Wrapper to add compatiblibility with other steps of the pipeline.
- """
- return self.run(tps=[tp], **kwargs)
-
- def run(
+ def _run_tp(
self,
- tree=None,
tps: List[int] = None,
+ tree=None,
save=True,
**kwargs,
) -> dict:
"""
Parameters
----------
- tree: dict
+ tps: list of int (optional)
+ Time points to include.
+ tree: dict (optional)
Nested dictionary indicating channels, reduction functions and
metrics to be used.
For example: {'general': {'None': ['area', 'volume', 'eccentricity']}}
- tps: list of int (optional)
- Time points to include.
save: boolean (optional)
If True, save results to h5 file.
kwargs: keyword arguments (optional)
@@ -620,6 +613,9 @@ class Extractor(ProcessABC):
tree = self.params.tree
if tps is None:
tps = list(range(self.meta["time_settings/ntimepoints"][0]))
+ elif isinstance(tps, int):
+ tps = [tps]
+
# store results in dict
d = {}
for tp in tps:
--
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