[AGIPD][DARK] Sort dark runs

Description

This is the second and last piece for sorting AGIPD dark runs

• Remove validate_gain_runs() function and moving needed error to new function.
• Create new function to sort dark runs.
• Add tests for the new function and remove tests for removed function
• Sort dark runs in Dark notebook before reading conditions.

Sorting dark runs

Expected patterns to use for sorting dark runs are:

• XRay: 0, DarkHG: 1, DarkMG: 2, DarkLG: 3, PC: 4, and CS: 5.

For Adaptive gain mode: All 3 runs have XRay patterns. On the other hand for fixed gain mode we expected DarkHG, DarkMG, and DarkLG patterns

Adaptive mode

For AGIPD1M patterns can be checked from ctrl_src/patternTypeIndex for the integer value or ctrl_src/patternType for the string value. However, AGIPD500K patterns can be checked from ctrl_src/expTypeIndex with integer value or expType for the string value.

Fixed Mode

Run order for fixed gain can only be decided using the gain modes.

How Has This Been Tested?

• TBD

Relevant Documents (optional)

Types of changes

• New feature (non-breaking change which adds functionality)
• Test (additional or refactored tests)

Checklist:

• A calibration_configuration updated for the know old proposals for AGIPD500K with sort_runs = False : An MR has the changes. To be merged with the next release

Reviewers

@kluyvert @schmidtp

src/cal_tools/agipdlib.py

@@ -343,19 +343,18 @@ class AgipdCtrlRuns:
         assert len(self.runs) == 3, f"AGIPD dark runs are expected to be 3. {len(self.runs)} runs are given."  # noqa
         # Expected patterns:
         # XRay: 0, DarkHG: 1, DarkMG: 2, DarkLG: 3, PC: 4 and CS: 5.
-        sort_by = {}
-
-        if self.gain_modes == self.adaptive_gain_modes:  # Adaptive gain
+        sort_by = None
+        sort_values = []
+        if self.gain_modes == self.adaptive_gain_modes:  # Adaptive gain # sort by patterns
             # Patterns -> DarkHG: 1, DarkMG: 2, DarkLG: 3
             if "AGIPD1M" in self.ctrl_src:
-                pattern_dataset = "patternTypeIndex"
+                sort_by = "patternTypeIndex"
             elif "AGIPD500K" in self.ctrl_src:
-                pattern_dataset = "expTypeIndex"
+                sort_by = "expTypeIndex"
 
-            sort_by[pattern_dataset] = []  # sort by patterns
             for c in self.run_ctrls:
-                sort_by[pattern_dataset].append(c.run_dc[
-                    self.ctrl_src, pattern_dataset].as_single_value())
+                sort_values.append(
+                    c.run_dc[self.ctrl_src, sort_by].as_single_value())
 
         # Check if a mix of adaptive and fixed gain runs.
         elif any(gm == AgipdGainMode.ADAPTIVE_GAIN for gm in self.gain_modes):
@@ -363,18 +362,18 @@ class AgipdCtrlRuns:
                 f"Given runs {self.runs} have a mix of ADAPTIVE and "
                 f"FIXED gain modes: {self.gain_modes}.")
         else:  # Fixed gain: Patterns is X-Ray: 0 for all runs.
-            sort_by["gainModeIndex"] = [int(gm) for gm in self.gain_modes]
+            sort_by = "gainModeIndex"
+            sort_values = [int(gm) for gm in self.gain_modes]
 
-        zipped_lists = zip(
-            list(sort_by.values())[0], self.runs, self.run_ctrls)
+        zipped_lists = zip(sort_values, self.runs, self.run_ctrls)
 
         # Sort the lists based on the patterns
         sorted_zipped_lists = sorted(zipped_lists, key=lambda item: item[0])
         _, sorted_runs, sorted_run_ctrls = zip(*sorted_zipped_lists)
         if sorted_runs != self.runs:
             Warning("Given dark runs are unsorted. Runs will be sorted from"
-                    f" {self.runs} with {list(sort_by.keys())[0]}"
-                    f" {list(sort_by.values())} to {sorted_runs}.")
+                    f" {self.runs} with {sort_by}:"
+                    f" {sort_values} to {sorted_runs}.")
             # Update run_ctrls and runs order
             self.runs = list(sorted_runs)
             self.run_ctrls = list(sorted_run_ctrls)