From 66b9f977a44392a618fc91d49f79b5a60351d5db Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Lo=C3=AFc=20Le=20Guyader?= <loic.le.guyader@xfel.eu>
Date: Tue, 11 Apr 2023 14:21:47 +0200
Subject: [PATCH] Improve automatic BOZ ROIs determination
---
src/toolbox_scs/routines/boz.py | 23 +++++++++++++++--------
1 file changed, 15 insertions(+), 8 deletions(-)
diff --git a/src/toolbox_scs/routines/boz.py b/src/toolbox_scs/routines/boz.py
index c15821c..9ba0d96 100644
--- a/src/toolbox_scs/routines/boz.py
+++ b/src/toolbox_scs/routines/boz.py
@@ -647,25 +647,32 @@ def find_rois(data_mean, threshold, extended=False):
pX = data_mean.mean(axis=0)
pX = pX[:256] # half the ladder since there is a gap in the middle
pY = data_mean.mean(axis=1)
+ pX = pX/np.max(pX)
+ pY = pY/np.max(pY)
# along X
- lowX = int(np.argmax(pX[:64] > threshold)) # 1st occurrence returned
- highX = int(np.argmax(pX[192:] <= threshold) + 192) # 1st occ. returned
+ lowX = int(np.argmax(pX > threshold)) # 1st occurrence returned
+ highX = int(pX.shape[0] - np.argmax(pX[::-1] > threshold) - 1) # last occ. returned
- leftX = int(np.argmin(pX[64:128]) + 64)
- rightX = int(np.argmin(pX[128:192]) + 128)
+ midX = int(0.5*(lowX+highX))
+
+ leftX2 = int(np.argmax(pX[lowX+5:midX-5] < threshold)) + lowX + 5
+ midX2 = int(np.argmax(pX[midX+5:highX-5] < threshold)) + midX + 5
+
+ midX1 = int(midX - 5 - np.argmax(pX[midX-5:lowX+5:-1] < threshold))
+ rightX1 = int(highX - 5 - np.argmax(pX[highX-5:midX+5:-1] < threshold))
# along Y
lowY = int(np.argmax(pY > threshold)) # 1st occurrence returned
- highY = int(pY.shape[0] - np.argmax(pY[::-1] > threshold) - 1) # 1st occ. returned
+ highY = int(pY.shape[0] - np.argmax(pY[::-1] > threshold) - 1) # last occ. returned
# define rois
rois = {}
# beam roi
- rois['n'] = {'xl': lowX, 'xh': leftX, 'yl': lowY, 'yh': highY}
- rois['0'] = {'xl': leftX, 'xh': rightX, 'yl': lowY, 'yh': highY}
- rois['p'] = {'xl': rightX, 'xh': highX, 'yl': lowY, 'yh': highY}
+ rois['n'] = {'xl': lowX, 'xh': leftX2, 'yl': lowY, 'yh': highY}
+ rois['0'] = {'xl': midX1, 'xh': midX2, 'yl': lowY, 'yh': highY}
+ rois['p'] = {'xl': rightX1, 'xh': highX, 'yl': lowY, 'yh': highY}
# saturation roi
rois['sat'] = {'xl': lowX, 'xh': highX, 'yl': lowY, 'yh': highY}
--
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