From 8dd90e05bdc0c160c58c1a6d47bb2bc9136e887a Mon Sep 17 00:00:00 2001
From: ahmedk <karim.ahmed@xfel.eu>
Date: Fri, 29 Sep 2023 16:07:08 +0200
Subject: [PATCH] new function validate_dark_runs_order
---
src/cal_tools/jungfraulib.py | 89 ++++++++++++++++++++++++++++++++++++
1 file changed, 89 insertions(+)
diff --git a/src/cal_tools/jungfraulib.py b/src/cal_tools/jungfraulib.py
index a7041c5f7..8ca256dd6 100644
--- a/src/cal_tools/jungfraulib.py
+++ b/src/cal_tools/jungfraulib.py
@@ -119,3 +119,92 @@ class JungfrauCtrl():
return 1
else: # DYNAMIC, FORCE_SWITCH_G1, FORCE_SWITCH_G2 or None
return 0
+
+
+MODES_ORDER = {
+ JGM.DYNAMIC.value: 0,
+ JGM.FORCE_SWITCH_HG1.value: 1,
+ JGM.FORCE_SWITCH_HG2.value: 2,
+ JGM.FIX_GAIN_1.value: 3,
+ JGM.FIX_GAIN_2.value: 4,
+}
+EXPECTED_RUN_ORDER = [
+ [
+ JGM.DYNAMIC.value,
+ JGM.FORCE_SWITCH_HG1.value,
+ JGM.FORCE_SWITCH_HG2.value
+ ],
+ [
+ JGM.DYNAMIC.value,
+ JGM.FIX_GAIN_1.value,
+ JGM.FIX_GAIN_2.value
+ ],
+]
+
+
+def validate_dark_runs_order(
+ raw_folder,
+ runs,
+ ctrl_src,
+ modes_order=MODES_ORDER,
+ expected_run_order=EXPECTED_RUN_ORDER
+):
+ """Validate the 3 dark runs given for Jungfrau.
+
+ Args:
+ raw_folder (str): RAW folder for the validated dark runs.
+ runs (list, optional): [High run, Medium run, Low run]. Defaults to [].
+ ctrl_src (str): Control source path for slow data.
+ modes_order (dict): Gain modes order to sort the runs by.
+ expected_run_order (list):Expected dark runs order to process.
+ Raises:
+ ValueError: Wrong given dark runs
+ """
+ assert len(runs) == 3, "Wrong number of runs. expected a list of 3 runs."
+
+ run_gm_mapping = dict()
+ for run in runs:
+ ctrl_data = JungfrauCtrl(
+ extra_data.RunDirectory(f"{raw_folder}/r{run:04d}/"),
+ ctrl_src)
+ gm = ctrl_data.get_gain_mode_str()
+ run_gm_mapping[run] = gm
+
+ # 1st legacy case before having run.settings in data.
+ if all(value is None for value in run_gm_mapping.values()):
+ warning("run.settings is not stored in the data "
+ f"to read. Hence assuming gain_mode = {gm}"
+ " for adaptive old data.")
+ return runs
+
+ run_gm_mapping = dict(sorted(
+ run_gm_mapping.items(),
+ key=lambda item: modes_order[item[1]]
+ ))
+ if list(run_gm_mapping.keys()) != runs:
+ warning("Given dark runs are unsorted. "
+ f"Runs will be sorted from {runs} of gain modes "
+ f"{list(run_gm_mapping.values())} to "
+ f"{list(run_gm_mapping.keys())}")
+
+ runs = list(run_gm_mapping.keys())
+ modes = list(run_gm_mapping.values())
+
+ legacy_adaptive = [
+ JGM.DYNAMIC.value,
+ JGM.DYNAMIC.value,
+ JGM.FORCE_SWITCH_HG1.value
+ ]
+
+ # 2nd legacy case with CTRL/MDL bug resulting in wrong run settings.
+ if modes == legacy_adaptive:
+ warning(f"run.settings for medium and low gain runs"
+ f" are wrong {modes[1:]}. This is an expected "
+ f"bug for old raw data. Setting gain_mode to {gm}.")
+ elif not modes in expected_run_order:
+ raise ValueError("Wrong dark runs are given. "
+ f"The given three runs are {runs} with "
+ f"wrong gain modes {modes}."
+ "Please verify the selected 3 dark runs to process.")
+
+ return runs
--
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