From 62b184049ee19aa13f3f41241cf824e85344824f Mon Sep 17 00:00:00 2001
From: Wenduo Zhou <zhouw@ornl.gov>
Date: Mon, 28 Dec 2015 07:19:42 -0500
Subject: [PATCH] Refs #14796. Fixed some issues.
---
.../plugins/algorithms/SNSPowderReduction.py | 135 +++++++++++-------
1 file changed, 82 insertions(+), 53 deletions(-)
diff --git a/Framework/PythonInterface/plugins/algorithms/SNSPowderReduction.py b/Framework/PythonInterface/plugins/algorithms/SNSPowderReduction.py
index 5a0e0a08380..9e0dfb5b109 100644
--- a/Framework/PythonInterface/plugins/algorithms/SNSPowderReduction.py
+++ b/Framework/PythonInterface/plugins/algorithms/SNSPowderReduction.py
@@ -266,7 +266,8 @@ class SNSPowderReduction(DataProcessorAlgorithm):
self.COMPRESS_TOL_TOF = 0.01
# Process data
- workspacelist = [] # all data workspaces that will be converted to d-spacing in the end
+ # List stores the workspacename of all data workspaces that will be converted to d-spacing in the end.
+ workspacelist = []
samwksplist = []
self._lowResTOFoffset = self.getProperty("LowResolutionSpectraOffset").value
@@ -297,13 +298,14 @@ class SNSPowderReduction(DataProcessorAlgorithm):
if self._splitws is not None:
raise NotImplementedError("Summing spectra and filtering events are not supported simultaneously.")
- sam_ws_ = self._focusAndSum(samRuns, SUFFIX, timeFilterWall, calib,\
- preserveEvents=preserveEvents)
- assert isinstance(sam_ws_, str)
+ sam_ws_name = self._focusAndSum(samRuns, SUFFIX, timeFilterWall, calib,
+ preserveEvents=preserveEvents)
+ assert isinstance(sam_ws_name, str), 'Returned from _focusAndSum() must be a string but not' \
+ '%s. ' % str(type(sam_ws_name))
- samRuns = [sam_ws_]
- workspacelist.append(str(sam_ws_))
- samwksplist.append(str(sam_ws_))
+ samRuns = [sam_ws_name]
+ workspacelist.append(sam_ws_name)
+ samwksplist.append(sam_ws_name)
# ENDIF (SUM)
# Process each sample run
@@ -320,23 +322,18 @@ class SNSPowderReduction(DataProcessorAlgorithm):
if isinstance(returned, list):
# Returned with a list of workspaces
focusedwksplist = returned
- run_index = 0
- for run in focusedwksplist:
- assert isinstance(run, str)
- if run is not None:
- samwksplist.append(run)
- workspacelist.append(str(run))
- else:
- self.log().warning("Found a None entry in returned focused workspaces. "
- "Index = %d." % run_index)
- # ENDIF
- run_index += 1
+ for sam_ws_name in focusedwksplist:
+ assert isinstance(sam_ws_name, str), 'Impossible to have a non-string value in ' \
+ 'returned focused workspaces\' names.'
+ samwksplist.append(sam_ws_name)
+ workspacelist.append(sam_ws_name)
# END-FOR
else:
- run = returned
- assert isinstance(run, str)
- samwksplist.append(run)
- workspacelist.append(str(run))
+ # returned as a single workspace
+ sam_ws_name = returned
+ assert isinstance(sam_ws_name, str)
+ samwksplist.append(sam_ws_name)
+ workspacelist.append(sam_ws_name)
# ENDIF
# ENDIF
# ENDFOR
@@ -684,54 +681,85 @@ class SNSPowderReduction(DataProcessorAlgorithm):
return outName
#pylint: disable=too-many-arguments
- def _focusAndSum(self, runnumbers, extension, filterWall, calib, preserveEvents=True):
- """Load, sum, and focus data in chunks"""
+ def _focusAndSum(self, run_number_list, extension, filterWall, calib, preserveEvents=True):
+ """Load, sum, and focus data in chunks
+ Purpose:
+ Load, sum and focus data in chunks;
+ Requirements:
+ 1. input run numbers are in numpy array or list
+ Guarantees:
+ The experimental runs are focused and summed together
+ @param run_number_list:
+ @param extension:
+ @param filterWall:
+ @param calib:
+ @param preserveEvents:
+ @return: string as the summed workspace's name
+ """
+ # Check requirements
+ assert isinstance(run_number_list, numpy.array) or isinstance(run_number_list, list)
+
sumRun = None
info = None
- for temp in runnumbers:
- runnumber = temp
- self.log().information("[Sum] Process run number %s. " %(str(runnumber)))
+ for run_number in run_number_list:
+ # check
+ error_message = 'Run number %s should be integer or numpy.int32. But it is %s.' % (str(run_number),
+ str(type(run_number)))
+ assert isinstance(run_number, int) or isinstance(run_number, numpy.int32), error_message
+ self.log().information("[Sum] Process run number %d. " % run_number)
+
+ # focus one run
+ out_ws_name = self._focusChunks(run_number, extension, filterWall, calib,
+ normalisebycurrent=False,
+ preserveEvents=preserveEvents)
+ assert isinstance(out_ws_name, str), 'Output from _focusChunks() should be a string but' \
+ ' not %s.' % str(type(out_ws_name))
+ assert self.does_workspace_exist(out_ws_name)
- temp = self._focusChunks(temp, extension, filterWall, calib,\
- normalisebycurrent=False,
- preserveEvents=preserveEvents)
tempinfo = self._getinfo(temp)
+ # sum reduced runs
if sumRun is None:
- sumRun = temp
+ # First run. No need to sumRun
+ sumRun = out_ws_name
info = tempinfo
else:
+ # Non-first run. Add this run to current summed run
self.checkInfoMatch(info, tempinfo)
-
- sumRun = api.Plus(LHSWorkspace=sumRun, RHSWorkspace=temp, OutputWorkspace=sumRun,
- ClearRHSWorkspace=allEventWorkspaces(sumRun, temp))
- if sumRun.id() == EVENT_WORKSPACE_ID:
- sumRun = api.CompressEvents(InputWorkspace=sumRun, OutputWorkspace=sumRun,\
- Tolerance=self.COMPRESS_TOL_TOF) # 10ns
- api.DeleteWorkspace(str(temp))
+ # add current workspace to sub sum
+ temp_ws = api.Plus(LHSWorkspace=sumRun, RHSWorkspace=out_ws_name, OutputWorkspace=sumRun,
+ ClearRHSWorkspace=allEventWorkspaces(sumRun, out_ws_name))
+ if temp_ws.id() == EVENT_WORKSPACE_ID:
+ temp_ws = api.CompressEvents(InputWorkspace=sumRun, OutputWorkspace=sumRun,
+ Tolerance=self.COMPRESS_TOL_TOF) # 10ns
+ assert temp_ws is not None
+ # after adding all events, delete the current workspace.
+ api.DeleteWorkspace(out_ws_name)
# ENDIF
# ENDFOR (processing each)
+
if self._normalisebycurrent is True:
- sumRun = api.NormaliseByCurrent(InputWorkspace=sumRun,
- OutputWorkspace=sumRun)
- sumRun.getRun()['gsas_monitor'] = 1
+ temp_ws = api.NormaliseByCurrent(InputWorkspace=sumRun,
+ OutputWorkspace=sumRun)
+ temp_ws.getRun()['gsas_monitor'] = 1
return sumRun
-
#pylint: disable=too-many-arguments,too-many-locals,too-many-branches
def _focusChunks(self, runnumber, extension, filterWall, calib,
normalisebycurrent, splitwksp=None, preserveEvents=True):
- """ Load, (optional) split and focus data in chunks
-
- Arguments:
- - runnumber : integer for run number
- - normalisebycurrent: Set to False if summing runs for correct math
- - splitwksp: SplittersWorkspace (if None then no split)
- - filterWall: Enabled if splitwksp is defined
-
- Return:
+ """
+ Load, (optional) split and focus data in chunks
+ @param runnumber: integer for run number
+ @param extension:
+ @param filterWall: Enabled if splitwksp is defined
+ @param calib:
+ @param normalisebycurrent: Set to False if summing runs for correct math
+ @param splitwksp: SplittersWorkspace (if None then no split)
+ @param preserveEvents:
+ @return: a string as the returned workspace's name or a list of strings as the returned workspaces' names
+ in the case that split workspace is used.
"""
# generate the workspace name
self.log().information("_focusChunks(): runnumber = %d, extension = %s" % (runnumber, extension))
@@ -771,7 +799,7 @@ class SNSPowderReduction(DataProcessorAlgorithm):
# Split the workspace if it is required
if do_split_raw_wksp is True:
- output_ws_name_list = self._split_workspace(raw_ws_name_chunk, splitwksp)
+ output_ws_name_list = self._split_workspace(raw_ws_name_chunk, splitwksp.name())
else:
# Histogram data
output_ws_name_list = [raw_ws_name_chunk]
@@ -1346,7 +1374,8 @@ class SNSPowderReduction(DataProcessorAlgorithm):
"""
# Check requirements
assert isinstance(raw_ws_name, str), 'Raw workspace name must be a string.'
- assert isinstance(split_ws_name, str)
+ assert isinstance(split_ws_name, str), 'Input split workspace name must be string,' \
+ 'but not of type %s' % str(type(split_ws_name))
assert self.does_workspace_exist(split_ws_name)
raw_ws = self.get_workspace(workspace_name=raw_ws_name)
--
GitLab