From 7c573b699cb2a28467b3eccadbcf5d7bd0f25926 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Al=C3=A1n=20Mu=C3=B1oz?= <amuoz@ed.ac.uk>
Date: Tue, 17 May 2022 17:49:41 +0100
Subject: [PATCH] update image calls
---
aliby/pipeline.py | 5 ++--
aliby/tile/tiler.py | 60 ++++++++++++++++++++++++++++++++++++++++++---
2 files changed, 60 insertions(+), 5 deletions(-)
diff --git a/aliby/pipeline.py b/aliby/pipeline.py
index a3bdec83..65d36944 100644
--- a/aliby/pipeline.py
+++ b/aliby/pipeline.py
@@ -30,7 +30,8 @@ from aliby.experiment import MetaData
from aliby.haystack import initialise_tf
from aliby.baby_client import BabyRunner, BabyParameters
from aliby.tile.tiler import Tiler, TilerParameters
-from aliby.io.omero import Dataset, Image
+from aliby.io.omero import Dataset
+from aliby.io.image import Image
from agora.abc import ParametersABC, ProcessABC
from agora.io.writer import TilerWriter, BabyWriter, StateWriter, LinearBabyWriter
from agora.io.reader import StateReader
@@ -587,7 +588,7 @@ class Pipeline(ProcessABC):
> es_parameters["thresh_trap_ncells"]
)
traps_above_athresh = (
- cells_used.groupby("trap").sum().apply(np.mean, axis=1) / tile_size ** 2
+ cells_used.groupby("trap").sum().apply(np.mean, axis=1) / tile_size**2
> es_parameters["thresh_trap_area"]
)
diff --git a/aliby/tile/tiler.py b/aliby/tile/tiler.py
index c77d79e8..87ccf247 100644
--- a/aliby/tile/tiler.py
+++ b/aliby/tile/tiler.py
@@ -139,10 +139,54 @@ class TilerParameters(ParametersABC):
_defaults = {"tile_size": 117, "ref_channel": "Brightfield", "ref_z": 0}
+class TilerABC(ProcessABC):
+ """
+ Base class for different types of Tilers.
+ """
+
+ def __init__(parameters):
+ super().__init__(parameters)
+
+ @staticmethod
+ def ifoob_pad(full, slices): # TODO Remove when inheriting TilerABC
+ """
+ Returns the slices padded if it is out of bounds
+
+ Parameters:
+ ----------
+ full: (zstacks, max_size, max_size) ndarray
+ Entire position with zstacks as first axis
+ slices: tuple of two slices
+ Each slice indicates an axis to index
+
+
+ Returns
+ Trap for given slices, padded with median if needed, or np.nan if the padding is too much
+ """
+ max_size = full.shape[-1]
+
+ y, x = [slice(max(0, s.start), min(max_size, s.stop)) for s in slices]
+ trap = full[:, y, x]
+
+ padding = np.array(
+ [(-min(0, s.start), -min(0, max_size - s.stop)) for s in slices]
+ )
+ if padding.any():
+ tile_size = slices[0].stop - slices[0].start
+ if (padding > tile_size / 4).any():
+ trap = np.full((full.shape[0], tile_size, tile_size), np.nan)
+ else:
+
+ trap = np.pad(trap, [[0, 0]] + padding.tolist(), "median")
+
+ return trap
+
+
class Tiler(ProcessABC):
- """A dummy TimelapseTiler object fora Dask Demo.
+ """Remote Timelapse Tiler.
- Does trap finding and image registration."""
+ Does trap finding and image registration. Fetches images from as erver
+ """
def __init__(
self,
@@ -157,6 +201,14 @@ class Tiler(ProcessABC):
self.ref_channel = self.get_channel_index(parameters.ref_channel)
self.trap_locs = trap_locs
+ try:
+ self.z_perchannel = {
+ ch: metadata["zsectioning/nsections"] if zsect else 1
+ for zsect, ch in zip(metadata["channels"], metadata["channels/zsect"])
+ }
+ except Exception as e:
+ print(f"Warning:Tiler: No z_perchannel data: {e}")
+
@classmethod
def from_image(cls, image, parameters: TilerParameters):
return cls(image.data, image.metadata, parameters)
@@ -166,6 +218,8 @@ class Tiler(ProcessABC):
trap_locs = TrapLocations.read_hdf5(filepath)
metadata = load_attributes(filepath)
metadata["channels"] = image.metadata["channels"]
+ # metadata["zsectioning/nsections"] = image.metadata["zsectioning/nsections"]
+ # metadata["channels/zsect"] = image.metadata["channels/zsect"]
if parameters is None:
parameters = TilerParameters.default()
@@ -259,7 +313,7 @@ class Tiler(ProcessABC):
return ndtrap
@staticmethod
- def ifoob_pad(full, slices):
+ def ifoob_pad(full, slices): # TODO Remove when inheriting TilerABC
"""
Returns the slices padded if it is out of bounds
--
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