From 01a43eb8ddc11467bf830b4822c7e1125ba90811 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Lo=C3=AFc=20Le=20Guyader?= <loic.le.guyader@xfel.eu>
Date: Tue, 3 Aug 2021 13:47:14 +0200
Subject: [PATCH] Fix flat field correction display in BOZ analysis
---
src/toolbox_scs/routines/boz.py | 25 ++++++++++++++++++++-----
1 file changed, 20 insertions(+), 5 deletions(-)
diff --git a/src/toolbox_scs/routines/boz.py b/src/toolbox_scs/routines/boz.py
index 5e47f03..2b53ae1 100644
--- a/src/toolbox_scs/routines/boz.py
+++ b/src/toolbox_scs/routines/boz.py
@@ -112,7 +112,10 @@ class parameters():
def get_flat_field(self):
"""Get the flat field plane definition."""
- return np.array(self.flat_field)
+ if self.flat_field is None:
+ return None
+ else:
+ return np.array(self.flat_field)
def set_Fnl(self, Fnl):
"""Set the non-linear correction function."""
@@ -123,7 +126,10 @@ class parameters():
def get_Fnl(self):
"""Get the non-linear correction function."""
- return np.array(self.Fnl)
+ if self.Fnl is None:
+ return None
+ else:
+ return np.array(self.Fnl)
def save(self, path='./'):
"""Save the parameters as a JSON file.
@@ -822,7 +828,7 @@ def inspect_plane_fitting(avg, rois, vmin=None, vmax=None):
d = '0'
roi = rois[d]
for k, r in enumerate(['n', '0', 'p']):
- img_rois[r] = np.roll(avg, tuple(centers[r] - centers[d]))[
+ img_rois[r] = np.roll(avg, tuple(centers[d] - centers[r]))[
roi['yl']:roi['yh'], roi['xl']:roi['xh']]
im = axs[0, k].imshow(img_rois[r],
vmin=vmin,
@@ -1279,13 +1285,22 @@ def inspect_correction(params, gain=None):
fitrois[k] = params.rois[k]
# flat flat_field
- ff = compute_flat_field_correction(params.rois, params.get_flat_field())
+ plane_ff = params.get_flat_field()
+ if plane_ff is None:
+ plane_ff = [0.0, 0.0, 1.0, -1.0]
+ ff = compute_flat_field_correction(params.rois, plane_ff)
+
+ # non linearities
+ Fnl = params.get_Fnl()
+ if Fnl is None:
+ Fnl = np.arange(2**9)
+ # compute all levels of correction
data = process(np.arange(2**9), params.arr_dark, params.arr, params.tid,
fitrois, params.get_mask(), np.ones_like(ff), params.sat_level)
data_ff = process(np.arange(2**9), params.arr_dark, params.arr, params.tid,
fitrois, params.get_mask(), ff, params.sat_level)
- data_ff_nl = process(params.get_Fnl(), params.arr_dark, params.arr,
+ data_ff_nl = process(Fnl, params.arr_dark, params.arr,
params.tid, fitrois, params.get_mask(), ff, params.sat_level)
# for conversion to nb of photons
--
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