Refs #11607. Additional parameter for setting threshold.

Also added paragraph to documentation.

Code/Mantid/Framework/PythonInterface/plugins/algorithms/PoldiLoadRuns.py

@@ -10,6 +10,7 @@ class PoldiLoadRuns(PythonAlgorithm):
     _nameTemplate = ""
     _mergeCheckEnabled = True
     _autoMaskBadDetectors = True
+    _autoMaskThreshold = 3.0
 
     def category(self):
         return "SINQ\\Poldi"
@@ -50,6 +51,11 @@ def PyInit(self):
                              doc=('Automatically disable detectors with unusually small or large values, in addition'
                                   ' to those masked in the instrument definition.'))
 
+        self.declareProperty('BadDetectorThreshold', 3.0, direction=Direction.Input,
+                             doc=('Detectors are masked based on how much their intensity (integrated over time) '
+                                  'deviates from the median calculated from all detectors. This parameter indicates '
+                                  'how many times bigger the intensity needs to be for a detector to be masked.'))
+
         self.declareProperty(WorkspaceProperty(name='OutputWorkspace',
                                                defaultValue='',
                                                direction=Direction.Output),
@@ -100,6 +106,7 @@ def PyExec(self):
 
         # The same for removing additional dead or misbehaving wires
         self._autoMaskBadDetectors = self.getProperty('MaskBadDetectors').value
+        self._autoMaskThreshold = self.getProperty('BadDetectorThreshold').value
 
         # Get a list of output workspace names.
         outputWorkspaces = self.getLoadedWorkspaceNames(year, mergeRange, mergeWidth)
@@ -201,8 +208,8 @@ def loadAndTruncateData(self, workspaceName, year, j):
     def autoMaskBadDetectors(self, currentTotalWsName):
         Integration(currentTotalWsName, OutputWorkspace='integrated')
 
-        MedianDetectorTest('integrated', SignificanceTest=4.0, HighOutlier=400, CorrectForSolidAngle=False,
-                           OutputWorkspace='maskWorkspace')
+        MedianDetectorTest('integrated', SignificanceTest=3.0, HighThreshold=self._autoMaskThreshold, HighOutlier=200, \
+                           CorrectForSolidAngle=False, OutputWorkspace='maskWorkspace')
 
         MaskDetectors(Workspace=AnalysisDataService.retrieve(currentTotalWsName), MaskedWorkspace='maskWorkspace')
 

Code/Mantid/Testing/SystemTests/tests/analysis/POLDILoadRunsTest.py

@@ -4,6 +4,7 @@
 from mantid.api import *
 import numpy as np
 
+
 class POLDILoadRunsTest(stresstesting.MantidStressTest):
     """This assembly of test cases checks that the behavior of PoldiLoadRuns is correct."""
 
@@ -132,11 +133,22 @@ def loadWorkspacesDontOverwriteOther(self):
 
     def checkRemoveBadDetectors(self):
         # Determine bad detectors automatically
-        twoWorkspacesMerged = PoldiLoadRuns(2013, 6903, 6904, 2, MaskBadDetectors=True)
+        twoWorkspacesMerged = PoldiLoadRuns(2013, 6903, 6904, 2, MaskBadDetectors=True,
+                                            BadDetectorThreshold=2.5)
+
+        wsMerged = AnalysisDataService.retrieve("twoWorkspacesMerged_data_6904")
+        self.assertEquals(len([True for x in range(wsMerged.getNumberHistograms()) if wsMerged.getDetector(
+            x).isMasked()]), 36)
+
+        self.clearAnalysisDataService()
+
+        # Lower threshold, more excluded detectors
+        twoWorkspacesMerged = PoldiLoadRuns(2013, 6903, 6904, 2, MaskBadDetectors=True,
+                                            BadDetectorThreshold=2.0)
 
         wsMerged = AnalysisDataService.retrieve("twoWorkspacesMerged_data_6904")
         self.assertEquals(len([True for x in range(wsMerged.getNumberHistograms()) if wsMerged.getDetector(
-            x).isMasked()]), 76)
+            x).isMasked()]), 49)
 
         self.clearAnalysisDataService()
 

Code/Mantid/docs/source/algorithms/PoldiLoadRuns-v1.rst

@@ -9,7 +9,11 @@
 Description
 -----------
 
-This algorithm makes it easier to load POLDI data. Besides importing the raw data (:ref:`algm-LoadSINQ`), it performs the otherwise manually performed steps of instrument loading (:ref:`algm-LoadInstrument`), truncation (:ref:`algm-PoldiTruncateData`). To make the algorithm more useful, it is possible to load data from multiple runs by specifying a range. In many cases, data files need to be merged in a systematic manner, which is also covered by this algorithm. For this purpose there is a parameter that specifies how the files of the specified range should be merged. The data files are named following the scheme `group_data_run`, where `group` is the name specified in `OutputWorkspace` and `run` is the run number and placed into a WorkspaceGroup with the name given in `OutputWorkspace`.
+This algorithm makes it easier to load POLDI data. Besides importing the raw data (:ref:`algm-LoadSINQ`), it performsthe otherwise manually performed steps of instrument loading (:ref:`algm-LoadInstrument`), truncation (:ref:`algm-PoldiTruncateData`). To make the algorithm more useful, it is possible to load data from multiple runs by specifying a range. In many cases, data files need to be merged in a systematic manner, which is also covered by this algorithm. For this purpose there is a parameter that specifies how the files of the specified range should be merged. The data files are named following the scheme `group_data_run`, where `group` is the name specified in `OutputWorkspace` and `run` is the run number and placed into a WorkspaceGroup with the name given in `OutputWorkspace`.
+
+By default, detectors that show unusually large integrated intensities are excluded if the pass a certain threshold
+with respect to the median of integrated intensities in all detectors. The threshold can be adjusted using an
+additional parameter. Detectors that are masked in the instrument definition are always masked.
 
 The data loaded in this way can be used directly for further processing with :ref:`algm-PoldiAutoCorrelation`.