From 838e7402d1f165bec8373f885b8873a9c1124bf4 Mon Sep 17 00:00:00 2001
From: Laurent Mercadier <laurent.mercadier@xfel.eu>
Date: Tue, 27 Aug 2024 07:27:36 +0200
Subject: [PATCH] Update get_bam() to process average data
---
src/toolbox_scs/detectors/bam_detectors.py | 58 ++++++++++++----------
1 file changed, 33 insertions(+), 25 deletions(-)
diff --git a/src/toolbox_scs/detectors/bam_detectors.py b/src/toolbox_scs/detectors/bam_detectors.py
index 39f2984..70226f4 100644
--- a/src/toolbox_scs/detectors/bam_detectors.py
+++ b/src/toolbox_scs/detectors/bam_detectors.py
@@ -39,12 +39,12 @@ def get_bam(run, mnemonics=None, merge_with=None, bunchPattern='sase3',
DataCollection containing the bam data.
mnemonics: str or list of str
mnemonics for BAM, e.g. "BAM1932M" or ["BAM414", "BAM1932M"].
- If None, defaults to "BAM1932M" in case no merge_with dataset
- is provided.
+ the arrays are either taken from merge_with or loaded from
+ the DataCollection run.
merge_with: xarray Dataset
If provided, the resulting Dataset will be merged with this
- one. The BAM variables of merge_with (if any) will also be
- selected, aligned and merged.
+ one. If merge_with contains variables in mnemonics, they will
+ be selected, aligned and merged.
bunchPattern: str
'sase1' or 'sase3' or 'scs_ppl', bunch pattern
used to extract peaks. The pulse ID dimension will be named
@@ -68,20 +68,20 @@ def get_bam(run, mnemonics=None, merge_with=None, bunchPattern='sase3',
mnemonics = [mnemonics] if isinstance(mnemonics, str) else mnemonics
for m in mnemonics:
if any([(k in m) for k in bam_mnemos]):
- if merge_with is not None and m in merge_with:
- continue
+ #if merge_with is not None and m in merge_with:
+ # continue
m2.append(m)
- if merge_with is not None:
- in_mw = []
- for m, da in merge_with.items():
- if any([(k in m) for k in bam_mnemos]) and 'BAMbunchId' in da.dims:
- in_mw.append(m)
- m2 += in_mw
-
- if len(m2) == 0:
+ #if merge_with is not None:
+ # in_mw = []
+ # for m, da in merge_with.items():
+ # if any([(k in m) for k in bam_mnemos]) and 'BAMbunchId' in da.dims:
+ # in_mw.append(m)
+ # m2 += in_mw
+
+ mnemonics = list(set(m2))
+ if len(mnemonics) == 0:
log.info('no BAM mnemonics to process. Skipping.')
return merge_with
- mnemonics = list(set(m2))
# Prepare the dataset of non-BAM data to merge with
if bool(merge_with):
ds_mw = merge_with.drop(mnemonics, errors='ignore')
@@ -101,16 +101,24 @@ def get_bam(run, mnemonics=None, merge_with=None, bunchPattern='sase3',
da_bam = merge_with[m]
else:
da_bam = get_array(run, m)
- da_bam = da_bam.sel(BAMbunchId=slice(0, None, 2))
- # align the pulse Id
- if bpt is not None:
- n = mask.sizes[dim_names[bunchPattern]]
- da_bam = da_bam.isel(BAMbunchId=slice(0, n))
- da_bam = da_bam.assign_coords(BAMbunchId=np.arange(0, n))
- da_bam = da_bam.rename(BAMbunchId=dim_names[bunchPattern])
- da_bam = da_bam.where(mask, drop=True)
- if run_mnemonics[m]['key'] != 'data.lowChargeArrivalTime':
- da_bam *= 1e-3
+ if len(da_bam.dims) == 2:
+ da_bam = da_bam.sel(BAMbunchId=slice(0, None, 2))
+ # align the pulse Id
+ if bpt is not None:
+ n = mask.sizes[dim_names[bunchPattern]]
+ da_bam = da_bam.isel(BAMbunchId=slice(0, n))
+ da_bam = da_bam.assign_coords(BAMbunchId=np.arange(0, n))
+ da_bam = da_bam.rename(BAMbunchId=dim_names[bunchPattern])
+ da_bam = da_bam.where(mask, drop=True)
+ # make sure unit is picosecond
+ if run_mnemonics[m]['key'] != 'data.lowChargeArrivalTime':
+ da_bam *= 1e-3
+ else:
+ # The 1D values (mean, std dev...) are in fs, need to convert to ps
+ mnemo = run_mnemonics[m]
+ first_val = run[mnemo['source']][mnemo['key']].train_from_index(0)[1]
+ if first_val == da_bam[0]:
+ da_bam *= 1e-3
ds = ds.merge(da_bam, join='inner')
# merge with non-BAM dataset
ds = ds_mw.merge(ds, join='inner')
--
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