From 102d69966fcef7f3fdb18437f1a8831734733fa3 Mon Sep 17 00:00:00 2001
From: Karim Ahmed <karim.ahmed@xfel.eu>
Date: Mon, 30 Nov 2020 09:45:43 +0100
Subject: [PATCH] [AGIPD][CORRECT] New PC data sanitization
---
cal_tools/cal_tools/agipdlib.py | 74 +++++++++++++++++++++------------
1 file changed, 48 insertions(+), 26 deletions(-)
diff --git a/cal_tools/cal_tools/agipdlib.py b/cal_tools/cal_tools/agipdlib.py
index 18328ff08..573588c58 100644
--- a/cal_tools/cal_tools/agipdlib.py
+++ b/cal_tools/cal_tools/agipdlib.py
@@ -556,18 +556,20 @@ class AgipdCorrections:
data *= rel_cor
del rel_cor
- # Set negative values for medium gain to 0
- if self.corr_bools.get('blc_set_min'):
- data[(data < 0) & (gain == 1)] = 0
-
# Adjust medium gain baseline to match highest high gain value
if self.corr_bools.get("adjust_mg_baseline"):
mgbc = self.md_additional_offset[module_idx][cellid, ...]
data[gain == 1] += mgbc[gain == 1]
del mgbc
- # Do xray correction if requested
- # The slopes we have in our constants are already relative
+ # Set negative values for medium gain to 0
+ # TODO: Probably it would be better to add it to badpixel maps,
+ # not just set to 0
+ if self.corr_bools.get('blc_set_min'):
+ data[(data < 0) & (gain == 1)] = 0
+
+ # Do xray correction if requested
+ # The slopes we have in our constants are already relative
# slopeFF = slopeFFpix/avarege(slopeFFpix)
# To apply them we have to / not *
if self.corr_bools.get("xray_corr"):
@@ -857,11 +859,10 @@ class AgipdCorrections:
Please note: Current slopesFF avaialble in calibibration
constants are created per pixel only, not per memory cell:
+
rel_high_gain = 1 if only PC data is available
rel_high_gain = rel_slopesFF if FF data is also available
-
-
* Relative gain for Medium gain stage: we derive the factor
between high and medium gain using slope information from
fits to the linear part of high and medium gain:
@@ -948,38 +949,59 @@ class AgipdCorrections:
pc_med_m = slopesPC[..., :self.max_cells, 3]
pc_med_l = slopesPC[..., :self.max_cells, 4]
- # calculate ratio high to medium gain
- pc_high_ave = np.nanmean(pc_high_m, axis=(0,1))
- pc_med_ave = np.nanmean(pc_med_m, axis=(0,1))
- # ration between HG and MG per pixel per mem cell
- # used for rel gain calculation
+ # calculate median for slopes
+ pc_high_med = np.nanmedian(pc_high_m, axis=(0,1))
+ pc_med_med = np.nanmedian(pc_med_m, axis=(0,1))
+ # calculate median for intercepts:
+ 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])] = pc_high_med[i]
+ pc_med_m[np.isnan(pc_med_m[..., i])] = pc_med_med[i]
+
+ pc_high_l[np.isnan(pc_high_l[..., i])] = pc_high_l_med[i]
+ pc_med_l[np.isnan(pc_med_l[..., 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])] = 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])] = 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])] = 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])] = pc_med_l_med[i] # noqa
+
+ # ration between HG and MG per pixel per mem cell used
+ # for rel gain calculation
frac_high_med_pix = pc_high_m / pc_med_m
# avarage ration between HG and MG as a function of
# mem cell (needed for bls_stripes)
# TODO: Per pixel would be more optimal correction
- frac_high_med = pc_high_ave / pc_med_ave
+ frac_high_med = pc_high_med / pc_med_med
# calculate additional medium-gain offset
md_additional_offset = pc_high_l - pc_med_l * pc_high_m / pc_med_m
- # Calculate relative gain. If FF constants are available,
- # use them for high gain
- # if not rel_gain is calculated using PC data only
- # if self.corr_bools.get("xray_corr"):
- # rel_gain[..., :self.max_cells, 0] /= xray_corr
-
- # PC data should be 'calibrated with X-ray data,
- # if it is not done, it is better to use 1 instead of bias
- # the results with PC arteffacts.
+ # PC data should be 'calibrated with X-ray data,
+ # if it is not done, it is better to use 1 instead of bias
+ # the results with PC arteffacts.
# rel_gain[..., 0] = 1./(pc_high_m / pc_high_ave)
-
- # High-gain (rel_gain[..., 0]) stays the same
rel_gain[..., 1] = rel_gain[..., 0] * frac_high_med_pix
rel_gain[..., 2] = rel_gain[..., 1] * 4.48
self.md_additional_offset[module_idx][...] = md_additional_offset.transpose()[...] # noqa
self.rel_gain[module_idx][...] = rel_gain[...].transpose()
self.frac_high_med[module_idx][...] = frac_high_med
-
+
self.mask[module_idx][...] = bpixels.transpose()[...]
return
--
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