From cfb4708a91ab73cf480ddd5b166b7f7ead34d7d0 Mon Sep 17 00:00:00 2001
From: ahmedk <karim.ahmed@xfel.eu>
Date: Fri, 1 Apr 2022 06:57:04 +0200
Subject: [PATCH] skip PC sanitization with constants of v1
---
src/cal_tools/agipdlib.py | 58 +++++++++++++++++++++++----------------
1 file changed, 34 insertions(+), 24 deletions(-)
diff --git a/src/cal_tools/agipdlib.py b/src/cal_tools/agipdlib.py
index 820d83a4f..f68e3b5d7 100644
--- a/src/cal_tools/agipdlib.py
+++ b/src/cal_tools/agipdlib.py
@@ -1225,30 +1225,40 @@ class AgipdCorrections:
pc_high_l_med = np.nanmedian(pc_high_l, axis=(0, 1))
pc_med_l_med = np.nanmedian(pc_med_l, axis=(0, 1))
- # sanitize PC data
- # (it should be done already on the level of constants)
- # In the following loop,
- # replace `nan`s across memory cells with
- # the median value calculated previously.
- # Then, values outside of the valid range (0.8 and 1.2)
- # are fixed to the median value.
- # This is applied for high and medium gain stages
- for i in range(self.max_cells):
- pc_high_m[np.isnan(pc_high_m[..., i]), i] = pc_high_med[i]
- pc_med_m[np.isnan(pc_med_m[..., i]), i] = pc_med_med[i]
-
- pc_high_l[np.isnan(pc_high_l[..., i]), i] = pc_high_l_med[i]
- pc_med_l[np.isnan(pc_med_l[..., i]), i] = pc_med_l_med[i]
-
- pc_high_m[(pc_high_m[..., i] < 0.8 * pc_high_med[i]) |
- (pc_high_m[..., i] > 1.2 * pc_high_med[i]), i] = pc_high_med[i] # noqa
- pc_med_m[(pc_med_m[..., i] < 0.8 * pc_med_med[i]) |
- (pc_med_m[..., i] > 1.2 * pc_med_med[i]), i] = pc_med_med[i] # noqa
-
- pc_high_l[(pc_high_l[..., i] < 0.8 * pc_high_l_med[i]) |
- (pc_high_l[..., i] > 1.2 * pc_high_l_med[i]), i] = pc_high_l_med[i] # noqa
- pc_med_l[(pc_med_l[..., i] < 0.8 * pc_med_l_med[i]) |
- (pc_med_l[..., i] > 1.2 * pc_med_l_med[i]), i] = pc_med_l_med[i] # noqa
+ if variant == 0:
+ # sanitize PC data with CCV variant = 0.
+ # Sanitization is already done for constants
+ # with CCV variant = 1
+ # In the following loop,
+ # replace `nan`s across memory cells with
+ # the median value calculated previously.
+ # Then, values outside of the valid range (0.8 and 1.2)
+ # are fixed to the median value.
+ # This is applied for high and medium gain stages
+ for i in range(self.max_cells):
+ pc_high_m[
+ np.isnan(pc_high_m[..., i]), i] = pc_high_med[i]
+ pc_med_m[
+ np.isnan(pc_med_m[..., i]), i] = pc_med_med[i]
+
+ pc_high_l[
+ np.isnan(pc_high_l[..., i]), i] = pc_high_l_med[i]
+ pc_med_l[
+ np.isnan(pc_med_l[..., i]), i] = pc_med_l_med[i]
+
+ pc_high_m[
+ (pc_high_m[..., i] < 0.8 * pc_high_med[i]) |
+ (pc_high_m[..., i] > 1.2 * pc_high_med[i]), i] = pc_high_med[i] # noqa
+ pc_med_m[
+ (pc_med_m[..., i] < 0.8 * pc_med_med[i]) |
+ (pc_med_m[..., i] > 1.2 * pc_med_med[i]), i] = pc_med_med[i] # noqa
+
+ pc_high_l[
+ (pc_high_l[..., i] < 0.8 * pc_high_l_med[i]) |
+ (pc_high_l[..., i] > 1.2 * pc_high_l_med[i]), i] = pc_high_l_med[i] # noqa
+ pc_med_l[
+ (pc_med_l[..., i] < 0.8 * pc_med_l_med[i]) |
+ (pc_med_l[..., i] > 1.2 * pc_med_l_med[i]), i] = pc_med_l_med[i] # noqa
# ration between HG and MG per pixel per mem cell used
# for rel gain calculation
--
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