From 43b390905538c514f425d9b6be4758d55158c954 Mon Sep 17 00:00:00 2001
From: Swainlab <peter.swain@ed.ac.uk>
Date: Mon, 14 Aug 2023 16:26:46 +0100
Subject: [PATCH] partway through add multichannel op to extractor
---
src/extraction/core/extractor.py | 44 +++++++++++----------
src/extraction/core/functions/cell.py | 11 ++++++
tests/aliby/network/extraction/test_base.py | 6 +--
3 files changed, 37 insertions(+), 24 deletions(-)
diff --git a/src/extraction/core/extractor.py b/src/extraction/core/extractor.py
index 24cf7171..6d025188 100644
--- a/src/extraction/core/extractor.py
+++ b/src/extraction/core/extractor.py
@@ -140,7 +140,7 @@ class Extractor(StepABC):
[c + "_bgsub" for c in self.params.sub_bg]
)
# remove any multichannel operations requiring a missing channel
- for op, (input_ch, _, _) in dict(self.params.multichannel_ops):
+ for op, (input_ch, _, _) in self.params.multichannel_ops.items():
if not set(input_ch).issubset(available_channels_bgsub):
self.params.multichannel_ops.pop(op)
self.load_funs()
@@ -306,8 +306,6 @@ class Extractor(StepABC):
cell_labels: dict
A dict of cell labels with trap_ids as keys and a list
of cell labels as values.
- pos_info: bool
- Whether to add the position as an index or not.
Returns
-------
@@ -557,19 +555,18 @@ class Extractor(StepABC):
"""
Extract using all metrics requiring multiple channels.
"""
+ available_chs = set(self.img_bgsub.keys()).union(
+ tree_bits["tree_channels"]
+ )
d = {}
for name, (
chs,
- merge_fun,
- red_metrics,
+ reduction_fun,
+ op,
) in self.params.multichannel_ops.items():
- if len(
- set(chs).intersection(
- set(self.img_bgsub.keys()).union(
- tree_bits["tree_channels"]
- )
- )
- ) == len(chs):
+ common_chs = set(chs).intersection(available_chs)
+ # all required channels should be available
+ if len(common_chs) == len(chs):
channels_stack = np.stack(
[
self.get_imgs(ch, tiles, tree_bits["tree_channels"])
@@ -577,13 +574,18 @@ class Extractor(StepABC):
],
axis=-1,
)
- merged = RED_FUNS[merge_fun](channels_stack, axis=-1)
- d[name] = self.reduce_extract(
- red_metrics=red_metrics,
- traps=merged,
- masks=masks,
- cell_labels=cell_labels,
- **kwargs,
+ # reduce in Z
+ traps = RED_FUNS[reduction_fun](channels_stack, axis=1)
+ # evaluate multichannel op
+ if name not in d:
+ d[name] = {}
+ if reduction_fun not in d[name]:
+ d[name][reduction_fun] = {}
+ d[name][reduction_fun][op] = self.extract_traps(
+ traps,
+ masks,
+ op,
+ cell_labels,
)
return d
@@ -652,10 +654,10 @@ class Extractor(StepABC):
res_one, self.img_bgsub = self.extract_one_channel(
tree_bits, cell_labels, tiles, masks, bgs, **kwargs
)
- res_two = self.extract_multiple_channels(
+ res_multiple = self.extract_multiple_channels(
tree_bits, cell_labels, tiles, masks, **kwargs
)
- res = {**res_one, **res_two}
+ res = {**res_one, **res_multiple}
return res
def get_imgs(self, channel: t.Optional[str], tiles, channels=None):
diff --git a/src/extraction/core/functions/cell.py b/src/extraction/core/functions/cell.py
index 4d97f23a..f668c567 100644
--- a/src/extraction/core/functions/cell.py
+++ b/src/extraction/core/functions/cell.py
@@ -229,3 +229,14 @@ def moment_of_inertia(cell_mask, trap_image):
return moi
else:
return np.nan
+
+
+def ratio(cell_mask, trap_image):
+ """Find the median ratio between two fluorescence channels."""
+ if trap_image.ndim == 3 and trap_image.shape[-1] == 2:
+ fl_1 = trap_image[..., 0][cell_mask]
+ fl_2 = trap_image[..., 1][cell_mask]
+ div = np.median(fl_1 / fl_2)
+ else:
+ div = np.nan
+ return div
diff --git a/tests/aliby/network/extraction/test_base.py b/tests/aliby/network/extraction/test_base.py
index 14209dbd..1ba8b452 100644
--- a/tests/aliby/network/extraction/test_base.py
+++ b/tests/aliby/network/extraction/test_base.py
@@ -56,9 +56,9 @@ def test_extractor(imgs, masks, tree):
for ch_branches in extractor.params.tree.values():
print(
extractor.reduce_extract(
- red_metrics=ch_branches,
- traps=[traps],
- masks=[masks],
+ [traps],
+ [masks],
+ ch_branches,
labels={0: labels},
)
)
--
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