def do_background_test(background_int, median_lo, median_hi, sigma, mask_zero,\
start_index=None, end_index=None):
"""
Run the background tests
Required inputs:
background_int - An integrated workspace
median_lo - Fraction of median to consider counting low
median_hi - Fraction of median to consider counting high
sigma - Error criterion as a multiple of error bar
mask_zero - If True, zero background counts will be considered a fail
"""
logger.notice('Running background count test')
# What shall we call the output
lhs_names = lhs_info('names')
if len(lhs_names) > 0:
ws_name = lhs_names[0]
else:
ws_name = '__do_background_test'
mask_bkgd, num_failures = MedianDetectorTest(InputWorkspace=background_int,
StartWorkspaceIndex=start_index, EndWorkspaceIndex=end_index,
SignificanceTest=sigma,
LowThreshold=median_lo, HighThreshold=median_hi,
LowOutlier=0.0, HighOutlier=1e100, ExcludeZeroesFromMedian=True)
#TODO: Looks like hack! why it returns negative value
return mask_bkgd, abs(num_failures)
def do_bleed_test(sample_run, max_framerate, ignored_pixels):
"""Runs the CreatePSDBleedMask algorithm
Input:
sample_run - The run number of the sample
max_framerate - The maximum allowed framerate in a tube. If None, the instrument defaults are used.
ignored_pixels - The number of central pixels to ignore. If None, the instrument defaults are used.
"""
# NOTE: Should be deployed on non-normalized workspace only!
logger.notice("Running PSD bleed test")
# Load the sample run
if __Reducer__: # Try to use generic loader which would work with files or workspaces alike
sample_run = __Reducer__.get_run_descriptor(sample_run)
data_ws = sample_run.get_workspace() # this will load data if necessary
ws_name = data_ws.name() + "_bleed"
else:
# may be sample run is already a run descriptor despite __Reducer__ have not been exposed
data_ws = sample_run.get_workspace() # this will load data if necessary
ws_name = data_ws.name() + "_bleed"
if max_framerate is None: # get defaults
max_framerate = float(data_ws.getInstrument().getNumberParameter("max-tube-framerate")[0])
if ignored_pixels is None: # get defaults
ignored_pixels = int(data_ws.getInstrument().getNumberParameter("num-ignored-pixels")[0])
else:
# Make sure it is an int
ignored_pixels = int(ignored_pixels)
# What shall we call the output
lhs_names = lhs_info("names")
if len(lhs_names) > 0:
ws_name = lhs_names[0]
else:
ws_name = "__do_bleed__test"
# Check if all necessary logs present in the workspace,as nxs workspace log names are different
# from a raw file workspace logs.
try:
nFrames = data_ws.getRun().getLogData("goodfrm").value
except RuntimeError:
try:
nFrames = data_ws.getRun().getLogData("good_frames").lastValue()
AddSampleLog(Workspace=data_ws, LogName="goodfrm", LogText=str(int(nFrames)), LogType="Number")
except RuntimeError:
raise RuntimeError(
"Bleed test fails as no appropriate 'good_frames' or 'goodfrm' log is loaded with ws: {0}\n"
"Disable bleed test by setting diag_bleed_test=False or add 'goodfrm' log to the workspace\n".format(
data_ws.name()
)
)
bleed_test, num_failed = CreatePSDBleedMask(
InputWorkspace=data_ws,
OutputWorkspace=ws_name,
MaxTubeFramerate=max_framerate,
NIgnoredCentralPixels=ignored_pixels,
)
return bleed_test, num_failed
def do_second_white_test(white_counts, comp_white_counts, tiny, large, out_lo, out_hi,
median_lo, median_hi, sigma, variation,
start_index=None, end_index=None):
"""
Run additional tests comparing given another white beam count workspace, comparing
to the first
Required inputs:
white_counts - A workspace containing the integrated counts from a
white beam vanadium run
comp_white_counts - A workspace containing the integrated counts from a
white beam vanadium run
tiny - Minimum threshold for acceptance
large - Maximum threshold for acceptance
median_lo - Fraction of median to consider counting low
median_hi - Fraction of median to consider counting high
signif - Counts within this number of multiples of the
standard dev will be kept
variation - Defines a range within which the ratio of the two counts is
allowed to fall in terms of the number of medians
"""
logger.notice('Running second white beam test')
# What shall we call the output
lhs_names = lhs_info('names')
if len(lhs_names) > 0:
ws_name = lhs_names[0]
else:
ws_name = '__do_second_white_test'
# Make sure we are a MatrixWorkspace
white_counts = ConvertToMatrixWorkspace(InputWorkspace=white_counts,OutputWorkspace=white_counts)
comp_white_counts = ConvertToMatrixWorkspace(InputWorkspace=comp_white_counts,OutputWorkspace=comp_white_counts)
# Do the white beam test
__second_white_tests, failed = do_white_test(comp_white_counts, tiny, large, median_lo, median_hi,
sigma, start_index, end_index)
# and now compare it with the first
effic_var, num_failed = DetectorEfficiencyVariation(WhiteBeamBase=white_counts, WhiteBeamCompare=comp_white_counts,
OutputWorkspace=ws_name,
Variation=variation, StartWorkspaceIndex=start_index,
EndWorkspaceIndex=end_index)
DeleteWorkspace(Workspace=str(__second_white_tests))
# Mask those that failed
maskWS = effic_var
MaskDetectors(Workspace=white_counts, MaskedWorkspace=maskWS)
MaskDetectors(Workspace=comp_white_counts, MaskedWorkspace=maskWS)
return maskWS, num_failed
def do_second_white_test(white_counts, comp_white_counts, tiny, large, out_lo, out_hi,
median_lo, median_hi, sigma, variation,
start_index=None, end_index=None):
"""
Run additional tests comparing given another white beam count workspace, comparing
to the first
Required inputs:
white_counts - A workspace containing the integrated counts from a
white beam vanadium run
comp_white_counts - A workspace containing the integrated counts from a
white beam vanadium run
tiny - Minimum threshold for acceptance
large - Maximum threshold for acceptance
median_lo - Fraction of median to consider counting low
median_hi - Fraction of median to consider counting high
signif - Counts within this number of multiples of the
standard dev will be kept
variation - Defines a range within which the ratio of the two counts is
allowed to fall in terms of the number of medians
"""
logger.notice('Running second white beam test')
# What shall we call the output
lhs_names = lhs_info('names')
if len(lhs_names) > 0:
ws_name = lhs_names[0]
else:
ws_name = '__do_second_white_test'
# Make sure we are a MatrixWorkspace
white_counts = ConvertToMatrixWorkspace(InputWorkspace=white_counts,OutputWorkspace=white_counts)
comp_white_counts = ConvertToMatrixWorkspace(InputWorkspace=comp_white_counts,OutputWorkspace=comp_white_counts)
# Do the white beam test
__second_white_tests, failed = do_white_test(comp_white_counts, tiny, large, median_lo, median_hi,
sigma, start_index, end_index)
# and now compare it with the first
effic_var, num_failed = DetectorEfficiencyVariation(WhiteBeamBase=white_counts, WhiteBeamCompare=comp_white_counts,
OutputWorkspace=ws_name,
Variation=variation, StartWorkspaceIndex=start_index,
EndWorkspaceIndex=end_index)
DeleteWorkspace(Workspace=str(__second_white_tests))
# Mask those that failed
maskWS = effic_var
MaskDetectors(Workspace=white_counts, MaskedWorkspace=maskWS)
MaskDetectors(Workspace=comp_white_counts, MaskedWorkspace=maskWS)
return maskWS, num_failed
def do_bleed_test(sample_run, max_framerate, ignored_pixels):
"""Runs the CreatePSDBleedMask algorithm
Input:
sample_run - The run number of the sample
max_framerate - The maximum allowed framerate in a tube. If None, the instrument defaults are used.
ignored_pixels - The number of central pixels to ignore. If None, the instrument defaults are used.
"""
#NOTE: Should be deployed on non-normalized workspace only!
logger.notice('Running PSD bleed test')
# Load the sample run
if __Reducer__: # Try to use generic loader which would work with files or workspaces alike
sample_run = __Reducer__.get_run_descriptor(sample_run)
data_ws = sample_run.get_workspace() # this will load data if necessary
ws_name = data_ws.name()+'_bleed'
else:
# may be sample run is already a run descriptor despite __Reducer__ have not been exposed
data_ws = sample_run.get_workspace() # this will load data if necessary
ws_name = data_ws.name()+'_bleed'
if max_framerate is None: #get defaults
max_framerate = float(data_ws.getInstrument().getNumberParameter('max-tube-framerate')[0])
if ignored_pixels is None: #get defaults
ignored_pixels = int(data_ws.getInstrument().getNumberParameter('num-ignored-pixels')[0])
else:
# Make sure it is an int
ignored_pixels = int(ignored_pixels)
# What shall we call the output
lhs_names = lhs_info('names')
if len(lhs_names) > 0:
ws_name = lhs_names[0]
else:
ws_name = '__do_bleed__test'
# Check if all necessary logs present in the workspace,as nxs workspace log names are different
# from a raw file workspace logs.
try:
nFrames= data_ws.getRun().getLogData('goodfrm').value
except RuntimeError:
try:
nFrames = data_ws.getRun().getLogData('good_frames').lastValue()
AddSampleLog(Workspace=data_ws, LogName='goodfrm', LogText=str(int(nFrames)), LogType='Number')
except RuntimeError:
raise RuntimeError("Bleed test fails as no appropriate 'good_frames' or 'goodfrm' log is loaded with ws: {0}\n"
"Disable bleed test by setting diag_bleed_test=False or add 'goodfrm' log to the workspace\n"
.format(data_ws.name()))
bleed_test, num_failed = CreatePSDBleedMask(InputWorkspace=data_ws, OutputWorkspace=ws_name,
MaxTubeFramerate=max_framerate,
NIgnoredCentralPixels=ignored_pixels)
return bleed_test, num_failed
def correct_absorption(self,ws,*args,**kwargs):
""" The generic method, which switches between fast and Monte-Carlo absorption corrections
depending on the type and properties variable provided as second input
kwargs is a dictionary, with at least one key, describing type of
corrections (fast or Monte-Carlo) and other keys (if any)
containing additional properties of the correspondent correction
algorithm.
Returns:
1) absorption-corrected workspace
2) if two output arguments are provided, second would be workspace with absorption corrections coefficients
"""
n_outputs,var_names = funcinspect.lhs_info('both')
if args is None or len(args) == 0:
if kwargs is None:
corr_properties = {}
else:
corr_properties = kwargs
else:
corr_properties = args[0]
if corr_properties is None:
corr_properties = {}
else:
if not isinstance(corr_properties,dict):
raise TypeError(
'*** Second non-keyword argument of the correct_absorption routine'
' (if present) should be a dictionary containing '
' additional parameters for selected AbsorptionCorrections algorithm')
correction_base_ws = ConvertUnits(ws,'Wavelength',EMode='Direct')
Mater_properties = self._Material
SetSampleMaterial(correction_base_ws,**Mater_properties)
if self._shape_has_axis:
self._check_MARI_axis_(ws)
if self._CanSetSample:
shape_description = self._ShapeDescription
SetSample(correction_base_ws,Geometry=shape_description)
mc_corrections = corr_properties.pop('is_mc', False)
fast_corrections = corr_properties.pop('is_fast',False)
if not(mc_corrections or fast_corrections) or (mc_corrections and fast_corrections):
fast_corrections = False # Case when both keys are true or false reverts to default
if fast_corrections:
#raise RuntimeError('Analytical absorption corrections are not currently implemented in Direct mode')
abs_corrections = self._fast_abs_corrections(correction_base_ws,corr_properties)
else:
abs_corrections = self._mc_abs_corrections(correction_base_ws,corr_properties)
abs_corrections = ConvertUnits(abs_corrections,'DeltaE',EMode='Direct')
ws = ws / abs_corrections
DeleteWorkspace(correction_base_ws)
if ws.name() != var_names[0]:
RenameWorkspace(ws,var_names[0])
if n_outputs == 1:
#DeleteWorkspace(abs_corrections)
return ws
elif n_outputs == 2:
if abs_corrections.name() != var_names[1]:
RenameWorkspace(abs_corrections,var_names[1])
return (ws,abs_corrections)
def iliad_wrapper(*args):
#seq = inspect.stack()
# output workspace name.
try:
name = funcinspect.lhs_info('names')
out_ws_name = name[0]
# no-exception-type(s) specified. Who knows what exception this internal procedure rises...
#pylint: disable=W0702
except:
out_ws_name = None
host = args[0]
if len(args) > 1:
input_file = args[1]
if len(args) > 2:
output_directory = args[2]
else:
output_directory = None
else:
input_file = None
output_directory = None
# add input file folder to data search directory if file has it
if input_file and isinstance(input_file, string_types):
data_path = os.path.dirname(input_file)
if len(data_path) > 0:
try:
config.appendDataSearchDir(str(data_path))
args[1] = os.path.basename(input_file)
#pylint: disable=bare-except
except: # if mantid is not available, this should ignore config
pass
if output_directory:
config['defaultsave.directory'] = str(output_directory)
#pylint: disable=protected-access
if host._run_from_web:
#pylint: disable=protected-access
web_vars = host._wvs.get_all_vars()
host.reducer.prop_man.set_input_parameters(**web_vars)
else:
pass # we should set already set up variables using
custom_print_function = host.set_custom_output_filename()
if custom_print_function is not None:
PropertyManager.save_file_name.set_custom_print(
custom_print_function)
#
rez = reduce(*args)
# prohibit returning workspace to web services.
#pylint: disable=protected-access
if host._run_from_web and not isinstance(rez, string_types):
rez = ""
else:
if isinstance(rez, list):
# multirep run, just return as it is
return rez
if rez is not None and out_ws_name and rez.name() != out_ws_name:
# the function does not return None, pylint is wrong
#pylint: disable=W1111
rez = PropertyManager.sample_run.synchronize_ws(
rez, out_ws_name)
return rez
def run_reduction(self):
"""" Reduces runs one by one or sum all them together and reduce after this
if wait_for_file time is > 0, it will until missing files appear on the
data search path
"""
try:
_, r = funcinspect.lhs_info('both')
out_ws_name = r[0]
# no-exception-type(s) specified. Who knows what exception this internal procedure rises...
#pylint: disable=W0702
except:
out_ws_name = None
# if this is not None, we want to run validation not reduction
if self.validate_run_number:
self.reducer.prop_man.log\
("**************************************************************************************",'warning')
self.reducer.prop_man.log\
("**************************************************************************************",'warning')
rez, mess = self.build_or_validate_result()
if rez:
self.reducer.prop_man.log("*** SUCCESS! {0}".format(mess))
self.reducer.prop_man.log\
("**************************************************************************************",'warning')
else:
self.reducer.prop_man.log(
"*** VALIDATION FAILED! {0}".format(mess))
self.reducer.prop_man.log\
("**************************************************************************************",'warning')
raise RuntimeError("Validation against old data file failed")
self.validate_run_number = None
return rez, mess
if self.reducer.sum_runs:
# --------### sum runs provided ------------------------------------###
if out_ws_name is None:
self.sum_and_reduce()
return None
else:
red_ws = self.sum_and_reduce()
RenameWorkspace(InputWorkspace=red_ws,
OutputWorkspace=out_ws_name)
return mtd[out_ws_name]
else:
# --------### reduce list of runs one by one ----------------------------###
runfiles = PropertyManager.sample_run.get_run_file_list()
if out_ws_name is None:
for file_name in runfiles:
self.reduce(file_name)
return None
else:
results = []
nruns = len(runfiles)
for num, file_name in enumerate(runfiles):
red_ws = self.reduce(file_name)
if isinstance(red_ws, list):
for ws in red_ws:
results.append(ws)
else:
if nruns == 1:
if red_ws.name() != out_ws_name:
RenameWorkspace(InputWorkspace=red_ws,
OutputWorkspace=out_ws_name)
results.append(mtd[out_ws_name])
else:
OutWSName = '{0}#{1}of{2}'.format(
out_ws_name, num + 1, nruns)
if red_ws.name() != out_ws_name:
RenameWorkspace(InputWorkspace=red_ws,
OutputWorkspace=OutWSName)
results.append(mtd[OutWSName])
#end
if len(results) == 1:
return results[0]
else:
return results
def update_defaults_from_instrument(self,pInstrument,ignore_changes=False):
""" Method used to update default parameters from the same instrument (with different parameters).
Used if initial parameters correspond to instrument with one validity dates and
current instrument has different validity dates and different default values for
these dates.
List of synonims is not modified and new properties are not added assuming that
recent dictionary and properties are most comprehensive one
ignore_changes==True when changes, caused by setting properties from instrument are not recorded
ignore_changes==False -- getChangedProperties properties after applied this method would return set
of all properties changed when applying this method
"""
self.reduction_instrument_warning(pInstrument)
# Retrieve the properties, changed from interface earlier
old_changes_list = self.getChangedProperties()
old_changes = self.create_old_changes_dict(old_changes_list)
param_list = prop_helpers.get_default_idf_param_list(pInstrument,self.__subst_dict)
# remove old changes which are not related to IDF (not to reapply it again)
old_changes = self.remove_non_IDF_changes(old_changes, param_list)
param_list,descr_dict = self._convert_params_to_properties(param_list,False,self.__descriptors)
# clear record about previous changes
self.setChangedProperties(set())
#sort parameters to have complex properties (with underscore _) first
sorted_param = OrderedDict(sorted(list(param_list.items()),key=lambda x : ord((x[0][0]).lower())))
# Walk through descriptors list and set their values
# Assignment to descriptors should accept the form, descriptor is written in IDF
changed_descriptors = set()
for key,val in iteritems(descr_dict):
if key not in old_changes_list:
try: # this is reliability check, and except ideally should never be hit. May occur if old IDF contains
# properties, not present in recent IDF.
cur_val = getattr(self,key)
setattr(self,key,val)
new_val = getattr(self,key)
#pylint: disable=bare-except
except:
try:
cur_val = getattr(self,key)
#pylint: disable=bare-except
except:
cur_val = "Undefined"
self.log("Retrieving or reapplying script property {0} failed. Property value remains: {1}"
.format(key,cur_val),'warning')
continue
new_val, cur_val = self.perform_simplfied_ws_comparison(new_val, cur_val)
if new_val != cur_val:
changed_descriptors.add(key)
changed_throug_main = True
else: # property may be changed through descriptors
changed_throug_main = False
# dependencies removed either properties are equal or not
try:
dependencies = getattr(PropertyManager,key).dependencies()
#pylint: disable=bare-except
except:
dependencies = []
for dep_name in dependencies:
if dep_name in sorted_param:
if changed_throug_main or (sorted_param[dep_name] == getattr(self,dep_name)):
del sorted_param[dep_name]
else: # remove property from old changes list not to reapply it again?
pass
#end loop
# clear record about all changes and store only changed descriptors list
self.setChangedProperties(changed_descriptors)
# Walk through the complex properties first and then through simple properties
for key,val in iteritems(sorted_param.copy()):
# complex properties may change through their dependencies so we are setting them first
public_name = self.is_complex_property(key, val)
if public_name not in old_changes_list:
exception_raised = self.update_property_value(val, public_name, param_list)
if exception_raised:
continue
else:
pass
# Dependencies removed either properties are equal or not.
# or if public_name for property in old change list. Remove dependencies
# too, as property has been set up as whole.
try:
dependencies = val.dependencies()
#pylint: disable=bare-except
except:
dependencies =[]
for dep_name in dependencies:
# delete dependent properties not to deal with them again
del sorted_param[dep_name]
#end
all_changes = self.retrieve_all_changes(old_changes, ignore_changes, old_changes_list)
num_changes = funcinspect.lhs_info('nreturns')
if num_changes > 0:
return all_changes
else:
return None
def run_reduction(self):
"""" Reduces runs one by one or sum all them together and reduce after this
if wait_for_file time is > 0, it will until missing files appear on the
data search path
"""
class time_logger:
"""" helper class to run using Python 'with' statement
and log reduction execution time and optionally
time spent on reducing every input file.
"""
def __init__(self,filename):
"filename -- short name of the log file"
self._start_time = time.time()
self._tick_time = self._start_time
filepath = os.path.dirname(os.path.realpath(__file__))
self._log_file = os.path.join(filepath,filename)
self.fh = -1;
def __enter__(self):
self.fh = open(self._log_file,"w")
lt= time.localtime(self._start_time )
res_memory = resource.getrusage(resource.RUSAGE_SELF).ru_maxrss/(1024);
ch_memory = resource.getrusage(resource.RUSAGE_CHILDREN).ru_maxrss/(1024)
self.fh.write("*** Test started: {0}/{1}/{2} at {3}:{4}\n".format(lt.tm_mday,lt.tm_mon,lt.tm_year,lt.tm_hour,lt.tm_min))
self.fh.write("*** Self Memory: {0}Kb; Kids memory {1}Kb\n".format(res_memory,ch_memory))
pv = subprocess.check_output(['free','-m'])
pvs = pv.split('\n')
self.fh.write("*** {0}\n".format(pvs[0]))
self.fh.write("*** {0}\n".format(pvs[1]))
self.fh.write("*** {0}\n".format(pvs[2]))
self.fh.flush()
return self
def __exit__(self, type, value, traceback):
fin_time = time.time()
lt = time.localtime(fin_time)
self.fh.write("*** Test finished: {0}/{1}/{2} at {3}:{4}\n".format(lt.tm_mday,lt.tm_mon,lt.tm_year,lt.tm_hour,lt.tm_min))
self.fh.write("*** Total execution time: {0:.2f}(sec)\n".format(fin_time -self._start_time))
self.fh.close()
def tick(self,fileID):
start_time = self._tick_time;
end_time = time.time()
res_memory = resource.getrusage(resource.RUSAGE_SELF).ru_maxrss/(1024)
ch_memory = resource.getrusage(resource.RUSAGE_CHILDREN).ru_maxrss/(1024)
self.fh.write("*** ---> File {0} processed in {1:.2f}sec\n".format(fileID,end_time-start_time))
self.fh.write("*** Self Memory: {0}Kb; Kids memory {1}Kb\n".format(math.ceil(res_memory),math.ceil(ch_memory)))
try:
pv = subprocess.check_output(['free','-m'])
pvs = pv.split('\n')
self.fh.write("*** {0}\n".format(pvs[1]))
self.fh.write("*** {0}\n".format(pvs[2]))
except:
#ClearCache(True,True,True,True,True,True,True)
#self.fh.write("*** Can not launch subprocess to evaluate free memory. Clearing all Mantid Caches\n")
self.fh.write("*** Can not launch subprocess to evaluate free memory.\n")
self.fh.flush()
self._tick_time = end_time
try:
_,r = funcinspect.lhs_info('both')
out_ws_name = r[0]
# no-exception-type(s) specified. Who knows what exception this internal procedure rises...
#pylint: disable=W0702
except:
out_ws_name = None
host = platform.node()
host = host.replace('.','_')
host = host.replace('-','_')
inst = config.getInstrument()
count = 1
inst_name = inst.name()
log_file_name = "{0}_performance_{1}_test{2}.txt".format(inst_name,host,count)
filepath = os.path.dirname(os.path.realpath(__file__))
ff = os.path.join(filepath,log_file_name)
while os.path.isfile(ff):
count = count+1;
log_file_name = "{0}_performance_{1}_test{2}.txt".format(inst_name,host,count)
ff = os.path.join(filepath,log_file_name)
print (' ******************* storing performance data to file: ',log_file_name)
if self.reducer.sum_runs:
# --------### sum runs provided ------------------------------------###
with time_logger(log_file_name) as log:
if out_ws_name is None:
self.sum_and_reduce()
return None
else:
red_ws = self.sum_and_reduce()
RenameWorkspace(InputWorkspace=red_ws,OutputWorkspace=out_ws_name)
return mtd[out_ws_name]
else:
# --------### reduce list of runs one by one ----------------------------###
runfiles = PropertyManager.sample_run.get_run_file_list()
with time_logger(log_file_name) as log:
if out_ws_name is None:
for file_name in runfiles:
self.reduce(file_name)
log.tick(file_name)
return None
else:
results = []
nruns = len(runfiles)
for num,file_name in enumerate(runfiles):
red_ws = self.reduce(file_name)
log.tick(file_name)
if isinstance(red_ws,list):
for ws in red_ws:
results.append(ws)
else:
if nruns == 1:
if red_ws.name() != out_ws_name:
RenameWorkspace(InputWorkspace=red_ws,OutputWorkspace=out_ws_name)
results.append(mtd[out_ws_name])
else:
OutWSName = '{0}#{1}of{2}'.format(out_ws_name,num+1,nruns)
if red_ws.name() != out_ws_name:
RenameWorkspace(InputWorkspace=red_ws,OutputWorkspace=OutWSName)
results.append(mtd[OutWSName])
#end
if len(results) == 1:
return results[0]
else:
return results
def iliad_wrapper(*args):
#seq = inspect.stack()
# output workspace name.
try:
_,r = funcinspect.lhs_info('both')
out_ws_name = r[0]
# no-exception-type(s) specified. Who knows what exception this internal procedure rises...
#pylint: disable=W0702
except:
out_ws_name = None
host = args[0]
if len(args) > 1:
input_file = args[1]
if len(args) > 2:
output_directory = args[2]
else:
output_directory = None
else:
input_file = None
output_directory = None
# add input file folder to data search directory if file has it
if input_file and isinstance(input_file,str):
data_path = os.path.dirname(input_file)
if len(data_path) > 0:
try:
config.appendDataSearchDir(str(data_path))
args[1] = os.path.basename(input_file)
#pylint: disable=bare-except
except: # if mantid is not available, this should ignore config
pass
if output_directory:
config['defaultsave.directory'] = str(output_directory)
#pylint: disable=protected-access
if host._run_from_web:
#pylint: disable=protected-access
web_vars = host._wvs.get_all_vars()
host.reducer.prop_man.set_input_parameters(**web_vars)
else:
pass # we should set already set up variables using
custom_print_function = host.set_custom_output_filename()
if custom_print_function is not None:
PropertyManager.save_file_name.set_custom_print(custom_print_function)
#
rez = reduce(*args)
# prohibit returning workspace to web services.
#pylint: disable=protected-access
if host._run_from_web and not isinstance(rez,str):
rez = ""
else:
if isinstance(rez, list):
# multirep run, just return as it is
return rez
if not(rez is None) and out_ws_name and rez.name() != out_ws_name:
# the function does not return None, pylint is wrong
#pylint: disable=W1111
rez = RenameWorkspace(InputWorkspace=rez, OutputWorkspace=out_ws_name)
return rez
def run_reduction(self):
"""" Reduces runs one by one or sum all them together and reduce after this
if wait_for_file time is > 0, it will until missing files appear on the
data search path
"""
try:
_,r = funcinspect.lhs_info('both')
out_ws_name = r[0]
# no-exception-type(s) specified. Who knows what exception this internal procedure rises...
#pylint: disable=W0702
except:
out_ws_name = None
# if this is not None, we want to run validation not reduction
if self.validate_run_number:
self.reducer.prop_man.log\
("**************************************************************************************",'warning')
self.reducer.prop_man.log\
("**************************************************************************************",'warning')
rez,mess=self.build_or_validate_result()
if rez:
self.reducer.prop_man.log("*** SUCCESS! {0}".format(mess))
self.reducer.prop_man.log\
("**************************************************************************************",'warning')
else:
self.reducer.prop_man.log("*** VALIDATION FAILED! {0}".format(mess))
self.reducer.prop_man.log\
("**************************************************************************************",'warning')
raise RuntimeError("Validation against old data file failed")
self.validate_run_number=None
return rez,mess
if self.reducer.sum_runs:
# --------### sum runs provided ------------------------------------###
if out_ws_name is None:
self.sum_and_reduce()
return None
else:
red_ws = self.sum_and_reduce()
RenameWorkspace(InputWorkspace=red_ws,OutputWorkspace=out_ws_name)
return mtd[out_ws_name]
else:
# --------### reduce list of runs one by one ----------------------------###
runfiles = PropertyManager.sample_run.get_run_file_list()
if out_ws_name is None:
for file_name in runfiles:
self.reduce(file_name)
return None
else:
results = []
nruns = len(runfiles)
for num,file_name in enumerate(runfiles):
red_ws = self.reduce(file_name)
if isinstance(red_ws,list):
for ws in red_ws:
results.append(ws)
else:
if nruns == 1:
if red_ws.name() != out_ws_name:
RenameWorkspace(InputWorkspace=red_ws,OutputWorkspace=out_ws_name)
results.append(mtd[out_ws_name])
else:
OutWSName = '{0}#{1}of{2}'.format(out_ws_name,num+1,nruns)
if red_ws.name() != out_ws_name:
RenameWorkspace(InputWorkspace=red_ws,OutputWorkspace=OutWSName)
results.append(mtd[OutWSName])
#end
if len(results) == 1:
return results[0]
else:
return results
def op_wrapper(self, other):
# Get the result variable to know what to call the output
result_info = lhs_info()
# Pass off to helper
return _do_binary_operation(algorithm, self, other, result_info,
inplace, reverse)
def arb_units(wb_run,sample_run,ei_guess,rebin,map_file='default',monovan_run=None,second_wb=None,**kwargs):
""" One step conversion of run into workspace containing information about energy transfer
Usage:
>>arb_units(wb_run,sample_run,ei_guess,rebin)
>>arb_units(wb_run,sample_run,ei_guess,rebin,**arguments)
>>arb_units(wb_run,sample_run,ei_guess,rebin,mapfile,**arguments)
>>arb_units(wb_run Whitebeam run number or file name or workspace
sample_run sample run number or file name or workspace
ei_guess Ei guess
rebin Rebin parameters
mapfile Mapfile -- if absent/'default' the defaults from IDF are used
monovan_run If present will do the absolute units normalization. Number of additional parameters
specified in **kwargs is usually requested for this. If they are absent, program uses defaults,
but the defaults (e.g. sample_mass or sample_rmm ) are usually incorrect for a particular run.
arguments The dictionary containing additional keyword arguments.
The list of allowed additional arguments is defined in InstrName_Parameters.xml file, located in
MantidPlot->View->Preferences->Mantid->Directories->Parameter Definitions
with run numbers as input:
>>dgreduce.arb_units(1000,10001,80,[-10,.1,70]) # will run on default instrument
>>dgreduce.arb_units(1000,10001,80,[-10,.1,70],'mari_res', additional keywords as required)
>>dgreduce.arb_units(1000,10001,80,'-10,.1,70','mari_res',fixei=True)
A detector calibration file must be specified if running the reduction with workspaces as input
namely:
>>w2=iliad("wb_wksp","run_wksp",ei,rebin_params,mapfile,det_cal_file=cal_file
,diag_remove_zero=False,norm_method='current')
type help() for the list of all available keywords. All availible keywords are provided in InstName_Parameters.xml file
Some samples are:
norm_method =[monitor-1],[monitor-2][Current]
background =False , True
fixei =False , True
save_format =['.spe'],['.nxspe'],'none'
detector_van_range =[20,40] in mev
bkgd_range =[15000,19000] :integration range for background tests
second_white - If provided an additional set of tests is performed on this. (default = None)
hardmaskPlus - A file specifying those spectra that should be masked without testing (default=None)
tiny - Minimum threshold for acceptance (default = 1e-10)
large - Maximum threshold for acceptance (default = 1e10)
bkgd_range - A list of two numbers indicating the background range (default=instrument defaults)
diag_van_median_rate_limit_lo - Lower bound defining outliers as fraction of median value (default = 0.01)
diag_van_median_rate_limit_hi - Upper bound defining outliers as fraction of median value (default = 100.)
diag_van_median_sigma_lo - Fraction of median to consider counting low for the white beam diag (default = 0.1)
diag_van_median_sigma_hi - Fraction of median to consider counting high for the white beam diag (default = 1.5)
diag_van_sig - Error criterion as a multiple of error bar i.e. to fail the test, the magnitude of the
difference with respect to the median value must also exceed this number of error bars (default=0.0)
diag_remove_zero - If true then zeroes in the vanadium data will count as failed (default = True)
diag_samp_samp_median_sigma_lo - Fraction of median to consider counting low for the white beam diag (default = 0)
diag_samp_samp_median_sigma_hi - Fraction of median to consider counting high for the white beam diag (default = 2.0)
diag_samp_sig - Error criterion as a multiple of error bar i.e. to fail the test, the magnitude of the"
difference with respect to the median value must also exceed this number of error bars (default=3.3)
variation -The number of medians the ratio of the first/second white beam can deviate from
the average by (default=1.1)
bleed_test - If true then the CreatePSDBleedMask algorithm is run
bleed_maxrate - If the bleed test is on then this is the maximum framerate allowed in a tube
bleed_pixels - If the bleed test is on then this is the number of pixels ignored within the
bleed test diagnostic
print_results - If True then the results are printed to the screen
diag_remove_zero =True, False (default):Diag zero counts in background range
bleed=True , turn bleed correction on and off on by default for Merlin and LET
sum =True,False(default) , sum multiple files
det_cal_file= a valid detector block file and path or a raw file. Setting this
will use the detector calibraion from the specified file NOT the
input raw file
mask_run = RunNumber to use for diag instead of the input run number
one2one =True, False :Reduction will not use a mapping file
hardmaskPlus=Filename :load a hardmarkfile and apply together with diag mask
hardmaskOnly=Filename :load a hardmask and use as only mask
"""
global Reducer
if Reducer is None or Reducer.instrument is None:
raise ValueError("instrument has not been defined, call setup(instrument_name) first.")
# --------------------------------------------------------------------------------------------------------
# Deal with mandatory parameters for this and may be some top level procedures
# --------------------------------------------------------------------------------------------------------
if sample_run:
Reducer.sample_run = sample_run
sample_run = None
try:
n,r=funcinspect.lhs_info('both')
wksp_out=r[0]
except:
wksp_out = "reduced_ws"
#
res = Reducer.convert_to_energy(wb_run,sample_run,ei_guess,rebin,map_file,monovan_run,second_wb,**kwargs)
#
results_name = res.name()
if results_name != wksp_out:
RenameWorkspace(InputWorkspace=results_name,OutputWorkspace=wksp_out)
return res
def abs_units(wb_for_run,sample_run,monovan_run,wb_for_monovanadium,samp_rmm,samp_mass,
ei_guess,rebin,map_file='default',monovan_mapfile='default',**kwargs):
"""
dgreduce.abs_units(wb_run Whitebeam run number or file name or workspace
sample_run Sample run run number or file name or workspace
monovan_run Monochromatic run run number or file name or workspace
wb_mono White beam for Monochromatic run run number or file name or workspace
samp_rmm Mass of formula unit of sample
samp_mass Actual sample mass
ei_guess Ei guess of run
rebin Rebin parameters for output data
map_file Mapfile for sample run
monovan_mapfile Mapfile for mono van run
keyword arguments Any specified additional keyword arguments
Example with run numbers
abs_units(11001,11002,11003,10098,250.1,5.2,80,'-10,.1,75','mari_res','mari_res')
A detector calibration file must be specified if running the reduction with workspace inputs
Example with workspace inputs
abs_units('wb_run','sam_run','mono_run','wb_for_mono',250.1,5.2,80,'-10,.1,75','mari_res','mari_res',
det_cal_file=10001,diag_remove_zero=False,norm_method='current')
A detector calibration file must be specified if running the reduction with workspace inputs
Available keywords
norm_method =[monitor-1],[monitor-2][Current]
background =False , True
fixei =False , True
save_format =['.spe'],['.nxspe'],'none'
detector_van_range =[20,40] in mev
bkgd_range =[15000,19000] :integration range for background tests
second_white - If provided an additional set of tests is performed on this. (default = None)
hard_mask_file - A file specifying those spectra that should be masked without testing (default=None)
tiny - Minimum threshold for acceptance (default = 1e-10)
large - Maximum threshold for acceptance (default = 1e10)
bkgd_range - A list of two numbers indicating the background range (default=instrument defaults)
diag_van_median_rate_limit_lo - Lower bound defining outliers as fraction of median value (default = 0.01)
diag_van_median_rate_limit_hi - Upper bound defining outliers as fraction of median value (default = 100.)
diag_van_median_sigma_lo - Fraction of median to consider counting low for the white beam diag (default = 0.1)
diag_van_median_sigma_hi - Fraction of median to consider counting high for the white beam diag (default = 1.5)
diag_van_sig - Error criterion as a multiple of error bar i.e. to fail the test, the magnitude of the
difference with respect to the median value must also exceed this number of error bars (default=0.0)
diag_remove_zero - If true then zeros in the vanadium data will count as failed (default = True)
diag_samp_samp_median_sigma_lo - Fraction of median to consider counting low for the white beam diag (default = 0)
diag_samp_samp_median_sigma_hi - Fraction of median to consider counting high for the white beam diag (default = 2.0)
diag_samp_sig - Error criterion as a multiple of error bar i.e. to fail the test, the magnitude of the"
difference with respect to the median value must also exceed this number of error bars (default=3.3)
variation -The number of medians the ratio of the first/second white beam can deviate from
the average by (default=1.1)
bleed_test - If true then the CreatePSDBleedMask algorithm is run
bleed_maxrate - If the bleed test is on then this is the maximum frame rate allowed in a tube
bleed_pixels - If the bleed test is on then this is the number of pixels ignored within the
bleed test diagnostic
print_results - If True then the results are printed to the screen
diag_remove_zero =True, False (default):Diag zero counts in background range
bleed=True , turn bleed correction on and off on by default for Merlin and LET
sum =True,False(default) , sum multiple files
det_cal_file= a valid detector block file and path or a raw file. Setting this
will use the detector calibration from the specified file NOT the
input raw file
mask_run = RunNumber to use for diag instead of the input run number
one2one =True, False :Reduction will not use a mapping file
hardmaskPlus=Filename :load a hardmarkfile and apply together with diag mask
hardmaskOnly=Filename :load a hardmask and use as only mask
use_sam_msk_on_monovan=False This will set the total mask to be that of the sample run
abs_units_van_range=[-40,40] integral range for absolute vanadium data
mono_correction_factor=float User specified correction factor for absolute units normalization
"""
kwargs['monovan_mapfile'] = monovan_mapfile
kwargs['sample_mass'] = samp_mass
kwargs['sample_rmm'] = samp_rmm
if sample_run:
Reducer.sample_run = sample_run
sample_run = None
try:
n,r=funcinspect.lhs_info('both')
results_name=r[0]
except:
results_name = Reducer.prop_man.get_sample_ws_name()
if runs_are_equal(wb_for_run,wb_for_monovanadium):# wb_for_monovanadium property does not accept duplicated workspace
wb_for_monovanadium = None # if this value is none, it is constructed to be equal to wb_for_run
wksp_out = arb_units(wb_for_run,sample_run,ei_guess,rebin,map_file,monovan_run,wb_for_monovanadium,**kwargs)
if results_name != wksp_out.getName():
RenameWorkspace(InputWorkspace=wksp_out,OutputWorkspace=results_name)
return wksp_out
def abs_units(wb_for_run,sample_run,monovan_run,wb_for_monovanadium,samp_rmm,samp_mass,
ei_guess,rebin,map_file='default',monovan_mapfile='default',**kwargs):
"""
dgreduce.abs_units(wb_run Whitebeam run number or file name or workspace
sample_run Sample run run number or file name or workspace
monovan_run Monochromatic run run number or file name or workspace
wb_mono White beam for Monochromatic run run number or file name or workspace
samp_rmm Mass of formula unit of sample
samp_mass Actual sample mass
ei_guess Ei guess of run
rebin Rebin parameters for output data
map_file Mapfile for sample run
monovan_mapfile Mapfile for mono van run
keyword arguments Any specified additional keyword arguments
Example with run numbers
abs_units(11001,11002,11003,10098,250.1,5.2,80,'-10,.1,75','mari_res','mari_res')
A detector calibration file must be specified if running the reduction with workspace inputs
Example with workspace inputs
abs_units('wb_run','sam_run','mono_run','wb_for_mono',250.1,5.2,80,'-10,.1,75','mari_res','mari_res',
det_cal_file=10001,diag_remove_zero=False,norm_method='current')
A detector calibration file must be specified if running the reduction with workspace inputs
Available keywords
norm_method =[monitor-1],[monitor-2][Current]
background =False , True
fixei =False , True
save_format =['.spe'],['.nxspe'],'none'
detector_van_range =[20,40] in mev
bkgd_range =[15000,19000] :integration range for background tests
second_white - If provided an additional set of tests is performed on this. (default = None)
hard_mask_file - A file specifying those spectra that should be masked without testing (default=None)
tiny - Minimum threshold for acceptance (default = 1e-10)
large - Maximum threshold for acceptance (default = 1e10)
bkgd_range - A list of two numbers indicating the background range (default=instrument defaults)
diag_van_median_rate_limit_lo - Lower bound defining outliers as fraction of median value (default = 0.01)
diag_van_median_rate_limit_hi - Upper bound defining outliers as fraction of median value (default = 100.)
diag_van_median_sigma_lo - Fraction of median to consider counting low for the white beam diag (default = 0.1)
diag_van_median_sigma_hi - Fraction of median to consider counting high for the white beam diag (default = 1.5)
diag_van_sig - Error criterion as a multiple of error bar i.e. to fail the test, the magnitude of the
difference with respect to the median value must also exceed this number of error bars (default=0.0)
diag_remove_zero - If true then zeros in the vanadium data will count as failed (default = True)
diag_samp_samp_median_sigma_lo - Fraction of median to consider counting low for the white beam diag (default = 0)
diag_samp_samp_median_sigma_hi - Fraction of median to consider counting high for the white beam diag (default = 2.0)
diag_samp_sig - Error criterion as a multiple of error bar i.e. to fail the test, the magnitude of the"
difference with respect to the median value must also exceed this number of error bars (default=3.3)
variation -The number of medians the ratio of the first/second white beam can deviate from
the average by (default=1.1)
bleed_test - If true then the CreatePSDBleedMask algorithm is run
bleed_maxrate - If the bleed test is on then this is the maximum frame rate allowed in a tube
bleed_pixels - If the bleed test is on then this is the number of pixels ignored within the
bleed test diagnostic
print_results - If True then the results are printed to the screen
diag_remove_zero =True, False (default):Diag zero counts in background range
bleed=True , turn bleed correction on and off on by default for Merlin and LET
sum =True,False(default) , sum multiple files
det_cal_file= a valid detector block file and path or a raw file. Setting this
will use the detector calibration from the specified file NOT the
input raw file
mask_run = RunNumber to use for diag instead of the input run number
one2one =True, False :Reduction will not use a mapping file
hardmaskPlus=Filename :load a hardmarkfile and apply together with diag mask
hardmaskOnly=Filename :load a hardmask and use as only mask
use_sam_msk_on_monovan=False This will set the total mask to be that of the sample run
abs_units_van_range=[-40,40] integral range for absolute vanadium data
mono_correction_factor=float User specified correction factor for absolute units normalization
"""
kwargs['monovan_mapfile'] = monovan_mapfile
kwargs['sample_mass'] = samp_mass
kwargs['sample_rmm'] = samp_rmm
if sample_run:
Reducer.sample_run = sample_run
sample_run = None
try:
n,r=funcinspect.lhs_info('both')
results_name=r[0]
except:
results_name = Reducer.prop_man.get_sample_ws_name()
if runs_are_equal(wb_for_run,wb_for_monovanadium):# wb_for_monovanadium property does not accept duplicated workspace
wb_for_monovanadium = None # if this value is none, it is constructed to be equal to wb_for_run
wksp_out = arb_units(wb_for_run,sample_run,ei_guess,rebin,map_file,monovan_run,wb_for_monovanadium,**kwargs)
if results_name != wksp_out.name():
RenameWorkspace(InputWorkspace=wksp_out,OutputWorkspace=results_name)
return wksp_out
def update_defaults_from_instrument(self,pInstrument,ignore_changes=False):
""" Method used to update default parameters from the same instrument (with different parameters).
Used if initial parameters correspond to instrument with one validity dates and
current instrument has different validity dates and different default values for
these dates.
List of synonims is not modified and new properties are not added assuming that
recent dictionary and properties are most comprehensive one
ignore_changes==True when changes, caused by setting properties from instrument are not recorded
ignore_changes==False -- getChangedProperties properties after applied this method would return set
of all properties changed when applying this method
"""
self.reduction_instrument_warning(pInstrument)
# Retrieve the properties, changed from interface earlier
old_changes_list = self.getChangedProperties()
old_changes = self.create_old_changes_dict(old_changes_list)
param_list = prop_helpers.get_default_idf_param_list(pInstrument,self.__subst_dict)
# remove old changes which are not related to IDF (not to reapply it again)
old_changes = self.remove_non_IDF_changes(old_changes, param_list)
param_list,descr_dict = self._convert_params_to_properties(param_list,False,self.__descriptors)
# clear record about previous changes
self.setChangedProperties(set())
#sort parameters to have complex properties (with underscore _) first
sorted_param = OrderedDict(sorted(list(param_list.items()),key=lambda x : ord((x[0][0]).lower())))
# Walk through descriptors list and set their values
# Assignment to descriptors should accept the form, descriptor is written in IDF
changed_descriptors = set()
for key,val in iteritems(descr_dict):
if key not in old_changes_list:
try: # this is reliability check, and except ideally should never be hit. May occur if old IDF contains
# properties, not present in recent IDF.
cur_val = getattr(self,key)
setattr(self,key,val)
new_val = getattr(self,key)
#pylint: disable=bare-except
except:
try:
cur_val = getattr(self,key)
#pylint: disable=bare-except
except:
cur_val = "Undefined"
self.log("Retrieving or reapplying script property {0} failed. Property value remains: {1}"
.format(key,cur_val),'warning')
continue
new_val, cur_val = self.perform_simplfied_ws_comparison(new_val, cur_val)
if new_val != cur_val:
changed_descriptors.add(key)
changed_throug_main = True
else: # property may be changed through descriptors
changed_throug_main = False
# dependencies removed either properties are equal or not
try:
dependencies = getattr(PropertyManager,key).dependencies()
#pylint: disable=bare-except
except:
dependencies = []
for dep_name in dependencies:
if dep_name in sorted_param:
if changed_throug_main or (sorted_param[dep_name] == getattr(self,dep_name)):
del sorted_param[dep_name]
else: # remove property from old changes list not to reapply it again?
pass
#end loop
# clear record about all changes and store only changed descriptors list
self.setChangedProperties(changed_descriptors)
# Walk through the complex properties first and then through simple properties
for key,val in iteritems(sorted_param.copy()):
# complex properties may change through their dependencies so we are setting them first
public_name = self.is_complex_property(key, val)
if public_name not in old_changes_list:
exception_raised = self.update_property_value(val, public_name, param_list)
if exception_raised:
continue
else:
pass
# Dependencies removed either properties are equal or not.
# or if public_name for property in old change list. Remove dependencies
# too, as property has been set up as whole.
try:
dependencies = val.dependencies()
#pylint: disable=bare-except
except:
dependencies =[]
for dep_name in dependencies:
# delete dependent properties not to deal with them again
del sorted_param[dep_name]
#end
all_changes = self.retrieve_all_changes(old_changes, ignore_changes, old_changes_list)
num_changes = funcinspect.lhs_info('nreturns')
if num_changes > 0:
return all_changes
else:
return None
def op_wrapper(self, other):
# Get the result variable to know what to call the output
result_info = lhs_info()
# Pass off to helper
return _do_binary_operation(algorithm, self, other, result_info,
inplace, reverse)
def op_wrapper(self):
# Get the result variable to know what to call the output
result_info = lhs_info()
# Pass off to helper
return _do_unary_operation(algorithm, self, result_info)
def update_defaults_from_instrument(self,
pInstrument,
ignore_changes=False):
""" Method used to update default parameters from the same instrument (with different parameters).
Used if initial parameters correspond to instrument with one validity dates and
current instrument has different validity dates and different default values for
these dates.
List of synonims is not modified and new properties are not added assuming that
recent dictionary and properties are most comprehensive one
ignore_changes==True when changes, caused by setting properties from instrument are not recorded
ignore_changes==False -- getChangedProperties properties after applied this method would return set
of all properties changed when applying this method
"""
if self.instr_name != pInstrument.getName():
self.log(
"*** WARNING: Setting reduction properties of the instrument {0} from the instrument {1}.\n"
"*** This only works if both instruments have the same reduction properties!"
.format(self.instr_name, pInstrument.getName()), 'warning')
# Retrieve the properties, changed from interface earlier
old_changes_list = self.getChangedProperties()
# record all changes, present in the old changes list
old_changes = OrderedDict()
for prop_name in old_changes_list:
old_changes[prop_name] = getattr(self, prop_name)
param_list = prop_helpers.get_default_idf_param_list(
pInstrument, self.__subst_dict)
# remove old changes which are not related to IDF (not to reapply it again)
for prop_name in old_changes.copy():
if prop_name not in param_list:
try:
dependencies = getattr(PropertyManager,
prop_name).dependencies()
#pylint: disable=bare-except
except:
dependencies = []
modified = False
for name in dependencies:
if name in param_list:
modified = True
# old parameter have been modified through compound parameter.
#its old value is irrelevant
param_list[name] = getattr(self, name)
if not modified:
del old_changes[prop_name]
#end
param_list, descr_dict = self._convert_params_to_properties(
param_list, False, self.__descriptors)
# clear record about previous changes
self.setChangedProperties(set())
#sort parameters to have complex properties (with underscore _) first
sorted_param = OrderedDict(
sorted(list(param_list.items()),
key=lambda x: ord((x[0][0]).lower())))
# Walk through descriptors list and set their values
# Assignment to descriptors should accept the form, descriptor is written in IDF
changed_descriptors = set()
for key, val in iteritems(descr_dict):
if key not in old_changes_list:
try: # this is reliability check, and except ideally should never be hit. May occur if old IDF contains
# properties, not present in recent IDF.
cur_val = getattr(self, key)
setattr(self, key, val)
new_val = getattr(self, key)
#pylint: disable=bare-except
except:
try:
cur_val = getattr(self, key)
#pylint: disable=bare-except
except:
cur_val = "Undefined"
self.log(
"Retrieving or reapplying script property {0} failed. Property value remains: {1}"
.format(key, cur_val), 'warning')
continue
if isinstance(new_val, api.Workspace) and isinstance(
cur_val, api.Workspace):
# do simplified workspace comparison which is appropriate here
if new_val.name() == cur_val.name() and \
new_val.getNumberHistograms() == cur_val.getNumberHistograms() and \
new_val.getNEvents() == cur_val.getNEvents() and \
new_val.getAxis(0).getUnit().unitID() == cur_val.getAxis(0).getUnit().unitID():
new_val = 1
cur_val = 1
#
#end
if new_val != cur_val:
changed_descriptors.add(key)
changed_throug_main = True
else: # property may be changed through descriptors
changed_throug_main = False
# dependencies removed either properties are equal or not
try:
dependencies = getattr(PropertyManager, key).dependencies()
#pylint: disable=bare-except
except:
dependencies = []
for dep_name in dependencies:
if dep_name in sorted_param:
if changed_throug_main or (sorted_param[dep_name]
== getattr(self, dep_name)):
del sorted_param[dep_name]
else: # remove property from old changes list not to reapply it again?
pass
#end loop
# clear record about all changes and store only changed descriptors list
self.setChangedProperties(changed_descriptors)
# Walk through the complex properties first and then through simple properties
for key, val in iteritems(sorted_param.copy()):
# complex properties may change through their dependencies so we are setting them first
if isinstance(val, prop_helpers.ComplexProperty):
public_name = key[1:]
else:
# no complex properties left so we have simple key-value pairs
public_name = key
if public_name not in old_changes_list:
if isinstance(val, prop_helpers.ComplexProperty):
prop_idf_val = val.__get__(param_list)
else:
prop_idf_val = val
try: # this is reliability check, and except ideally should never be hit. May occur if old IDF contains
# properties, not present in recent IDF.
cur_val = getattr(self, public_name)
#pylint: disable=bare-except
except:
self.log(
"Can not retrieve property {0} value from existing reduction parameters. Ignoring this property"
.format(public_name), 'warning')
continue
if prop_idf_val != cur_val:
setattr(self, public_name, prop_idf_val)
else:
pass
# Dependencies removed either properties are equal or not.
# or if public_name for property in old change list. Remove dependencies
# too, as property has been set up as whole.
try:
dependencies = val.dependencies()
#pylint: disable=bare-except
except:
dependencies = []
for dep_name in dependencies:
# delete dependent properties not to deal with them again
del sorted_param[dep_name]
#end
new_changes_list = self.getChangedProperties()
self.setChangedProperties(set())
# set back all changes stored earlier and may be overwritten by new IDF
# (this is just to be sure -- should not change anything as we do not set properties changed)
for key, val in iteritems(old_changes):
setattr(self, key, val)
# Clear changed properties list (is this wise?, may be we want to know that some defaults changed?)
if ignore_changes:
self.setChangedProperties(old_changes_list)
all_changes = old_changes
else:
new_changes_list = new_changes_list.union(old_changes_list)
all_changes = old_changes_list.union(new_changes_list)
self.setChangedProperties(all_changes)
n = funcinspect.lhs_info('nreturns')
if n > 0:
return all_changes
else:
return None
def arb_units(wb_run,sample_run,ei_guess,rebin,map_file='default',monovan_run=None,second_wb=None,**kwargs):
""" One step conversion of run into workspace containing information about energy transfer
Usage:
>>arb_units(wb_run,sample_run,ei_guess,rebin)
>>arb_units(wb_run,sample_run,ei_guess,rebin,**arguments)
>>arb_units(wb_run,sample_run,ei_guess,rebin,mapfile,**arguments)
>>arb_units(wb_run Whitebeam run number or file name or workspace
sample_run sample run number or file name or workspace
ei_guess Ei guess
rebin Rebin parameters
mapfile Mapfile -- if absent/'default' the defaults from IDF are used
monovan_run If present will do the absolute units normalization. Number of additional parameters
specified in **kwargs is usually requested for this. If they are absent, program uses defaults,
but the defaults (e.g. sample_mass or sample_rmm ) are usually incorrect for a particular run.
arguments The dictionary containing additional keyword arguments.
The list of allowed additional arguments is defined in InstrName_Parameters.xml file, located in
MantidPlot->View->Preferences->Mantid->Directories->Parameter Definitions
with run numbers as input:
>>dgreduce.arb_units(1000,10001,80,[-10,.1,70]) # will run on default instrument
>>dgreduce.arb_units(1000,10001,80,[-10,.1,70],'mari_res', additional keywords as required)
>>dgreduce.arb_units(1000,10001,80,'-10,.1,70','mari_res',fixei=True)
A detector calibration file must be specified if running the reduction with workspaces as input
namely:
>>w2=iliad("wb_wksp","run_wksp",ei,rebin_params,mapfile,det_cal_file=cal_file
,diag_remove_zero=False,norm_method='current')
type help() for the list of all available keywords. All availible keywords are provided in InstName_Parameters.xml file
Some samples are:
norm_method =[monitor-1],[monitor-2][Current]
background =False , True
fixei =False , True
save_format =['.spe'],['.nxspe'],'none'
detector_van_range =[20,40] in mev
bkgd_range =[15000,19000] :integration range for background tests
second_white - If provided an additional set of tests is performed on this. (default = None)
hardmaskPlus - A file specifying those spectra that should be masked without testing (default=None)
tiny - Minimum threshold for acceptance (default = 1e-10)
large - Maximum threshold for acceptance (default = 1e10)
bkgd_range - A list of two numbers indicating the background range (default=instrument defaults)
diag_van_median_rate_limit_lo - Lower bound defining outliers as fraction of median value (default = 0.01)
diag_van_median_rate_limit_hi - Upper bound defining outliers as fraction of median value (default = 100.)
diag_van_median_sigma_lo - Fraction of median to consider counting low for the white beam diag (default = 0.1)
diag_van_median_sigma_hi - Fraction of median to consider counting high for the white beam diag (default = 1.5)
diag_van_sig - Error criterion as a multiple of error bar i.e. to fail the test, the magnitude of the
difference with respect to the median value must also exceed this number of error bars (default=0.0)
diag_remove_zero - If true then zeroes in the vanadium data will count as failed (default = True)
diag_samp_samp_median_sigma_lo - Fraction of median to consider counting low for the white beam diag (default = 0)
diag_samp_samp_median_sigma_hi - Fraction of median to consider counting high for the white beam diag (default = 2.0)
diag_samp_sig - Error criterion as a multiple of error bar i.e. to fail the test, the magnitude of the"
difference with respect to the median value must also exceed this number of error bars (default=3.3)
variation -The number of medians the ratio of the first/second white beam can deviate from
the average by (default=1.1)
bleed_test - If true then the CreatePSDBleedMask algorithm is run
bleed_maxrate - If the bleed test is on then this is the maximum framerate allowed in a tube
bleed_pixels - If the bleed test is on then this is the number of pixels ignored within the
bleed test diagnostic
print_results - If True then the results are printed to the screen
diag_remove_zero =True, False (default):Diag zero counts in background range
bleed=True , turn bleed correction on and off on by default for Merlin and LET
sum =True,False(default) , sum multiple files
det_cal_file= a valid detector block file and path or a raw file. Setting this
will use the detector calibraion from the specified file NOT the
input raw file
mask_run = RunNumber to use for diag instead of the input run number
one2one =True, False :Reduction will not use a mapping file
hardmaskPlus=Filename :load a hardmarkfile and apply together with diag mask
hardmaskOnly=Filename :load a hardmask and use as only mask
"""
global Reducer
if Reducer is None or Reducer.instrument is None:
raise ValueError("instrument has not been defined, call setup(instrument_name) first.")
# --------------------------------------------------------------------------------------------------------
# Deal with mandatory parameters for this and may be some top level procedures
# --------------------------------------------------------------------------------------------------------
if sample_run:
Reducer.sample_run = sample_run
sample_run = None
try:
n,r=funcinspect.lhs_info('both')
wksp_out=r[0]
except:
wksp_out = "reduced_ws"
#
res = Reducer.convert_to_energy(wb_run,sample_run,ei_guess,rebin,map_file,monovan_run,second_wb,**kwargs)
#
results_name = res.name()
if results_name != wksp_out:
RenameWorkspace(InputWorkspace=results_name,OutputWorkspace=wksp_out)
return res
def op_wrapper(self):
# Get the result variable to know what to call the output
result_info = lhs_info()
# Pass off to helper
return _do_unary_operation(algorithm, self, result_info)
