From 3bddfa5830cb935fd774c6156e9031f683de6e01 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Al=C3=A1n=20Mu=C3=B1oz?= <amuoz@ed.ac.uk>
Date: Mon, 7 Mar 2022 12:11:09 +0000
Subject: [PATCH] add background_max5
---
extraction/core/functions/defaults.py | 1 +
extraction/core/functions/trap.py | 19 ++++++++++++++++---
2 files changed, 17 insertions(+), 3 deletions(-)
diff --git a/extraction/core/functions/defaults.py b/extraction/core/functions/defaults.py
index 7847fb5a..b7e67bcc 100644
--- a/extraction/core/functions/defaults.py
+++ b/extraction/core/functions/defaults.py
@@ -30,6 +30,7 @@ def exparams_from_meta(meta: Union[dict, PosixPath, str], extras=["ph"]):
"mean",
"median",
"imBackground",
+ "background_max5",
"max2p5pc",
"max2p5pc_med",
"max5px",
diff --git a/extraction/core/functions/trap.py b/extraction/core/functions/trap.py
index 483f97d8..fde16410 100644
--- a/extraction/core/functions/trap.py
+++ b/extraction/core/functions/trap.py
@@ -4,13 +4,26 @@ import numpy as np
def imBackground(cell_masks, trap_image):
- '''
+ """
:param cell_masks: (numpy 3d array) cells' segmentation mask
:param trap_image: the image for the trap in which the cell is (all
channels)
- '''
+ """
if not len(cell_masks):
cell_masks = np.zeros_like(trap_image)
background = ~cell_masks.sum(axis=2).astype(bool)
- return (np.median(trap_image[np.where(background)]))
+ return np.median(trap_image[np.where(background)])
+
+
+def background_max5(cell_masks, trap_image):
+ """
+ :param cell_masks: (numpy 3d array) cells' segmentation mask
+ :param trap_image: the image for the trap in which the cell is (all
+ channels)
+ """
+ if not len(cell_masks):
+ cell_masks = np.zeros_like(trap_image)
+
+ background = ~cell_masks.sum(axis=2).astype(bool)
+ return np.mean(np.sort(trap_image[np.where(background)])[-5:])
--
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