diff --git a/Framework/PythonInterface/plugins/algorithms/LoadDNSLegacy.py b/Framework/PythonInterface/plugins/algorithms/LoadDNSLegacy.py
index 3e0d662c0bab2582ab528674e39ad3dcd7c9713c..9aa40f7e2982ea51066690b06bb991bf0b66b99d 100644
--- a/Framework/PythonInterface/plugins/algorithms/LoadDNSLegacy.py
+++ b/Framework/PythonInterface/plugins/algorithms/LoadDNSLegacy.py
@@ -1,6 +1,7 @@
from __future__ import (absolute_import, division, print_function)
import mantid.simpleapi as api
import numpy as np
+from scipy.constants import m_n, h
import os
import sys
from mantid.api import PythonAlgorithm, AlgorithmFactory, WorkspaceProperty, \
@@ -22,6 +23,7 @@ class LoadDNSLegacy(PythonAlgorithm):
"""
PythonAlgorithm.__init__(self)
self.tolerance = 1e-2
+ self.instrument = None
def category(self):
"""
@@ -44,7 +46,7 @@ class LoadDNSLegacy(PythonAlgorithm):
"Name of DNS experimental data file.")
self.declareProperty(FileProperty("CoilCurrentsTable", "",
- FileAction.Load, ['.txt']),
+ FileAction.OptionalLoad, ['.txt']),
"Name of file containing table of coil currents and polarisations.")
self.declareProperty(WorkspaceProperty("OutputWorkspace",
@@ -57,12 +59,23 @@ class LoadDNSLegacy(PythonAlgorithm):
def get_polarisation_table(self):
# load polarisation table
+ poltable = []
poltable_name = self.getPropertyValue("CoilCurrentsTable")
+ if not poltable_name:
+ # read the table from IDF
+ for p in ['x', 'y', 'z']:
+ currents = self.instrument.getStringParameter("{}_currents".format(p))[0].split(';')
+ for cur in currents:
+ row = {'polarisation': p, 'comment': '7'}
+ row['C_a'], row['C_b'], row['C_c'], row['C_z'] = [float(c) for c in cur.split(',')]
+ poltable.append(row)
+ self.log().debug("Loaded polarisation table:\n" + str(poltable))
+ return poltable
try:
- currents = np.genfromtxt(poltable_name, names=True, dtype=None)
+ currents = np.genfromtxt(poltable_name, names=True, dtype='U2,U2,f8,f8,f8,f8')
+ self.log().debug("Coil currents are: " + str(currents))
except ValueError as err:
raise RuntimeError("Invalid coil currents table: " + str(err))
- poltable = []
colnames = currents.dtype.names
poltable = [dict(list(zip(colnames, cur))) for cur in currents]
self.log().debug("Loaded polarisation table:\n" + str(poltable))
@@ -98,6 +111,8 @@ class LoadDNSLegacy(PythonAlgorithm):
message = "File " + filename + " does not contain any data!"
self.log().error(message)
raise RuntimeError(message)
+ # sample logs
+ logs = {"names": [], "values": [], "units": []}
# load run information
metadata = DNSdata()
@@ -108,6 +123,10 @@ class LoadDNSLegacy(PythonAlgorithm):
self.log().error(message)
raise RuntimeError(message)
+ tmp = api.LoadEmptyInstrument(InstrumentName='DNS')
+ self.instrument = tmp.getInstrument()
+ api.DeleteWorkspace(tmp)
+
# load polarisation table and determine polarisation
poltable = self.get_polarisation_table()
pol = self.get_polarisation(metadata, poltable)
@@ -116,10 +135,48 @@ class LoadDNSLegacy(PythonAlgorithm):
self.log().warning("Failed to determine polarisation for " + filename +
". Values have been set to undefined.")
ndet = 24
- # this needed to be able to use ConvertToMD
- dataX = np.zeros(2*ndet)
- dataX.fill(metadata.wavelength + 0.00001)
- dataX[::2] -= 0.000002
+ unitX="Wavelength"
+ if metadata.tof_channel_number < 2:
+ dataX = np.zeros(2*ndet)
+ dataX.fill(metadata.wavelength + 0.00001)
+ dataX[::2] -= 0.000002
+ else:
+ unitX="TOF"
+
+ # get instrument parameters
+ l1 = np.linalg.norm(self.instrument.getSample().getPos() - self.instrument.getSource().getPos())
+ self.log().notice("L1 = {} m".format(l1))
+ dt_factor = float(self.instrument.getStringParameter("channel_width_factor")[0])
+
+ # channel width
+ dt = metadata.tof_channel_width*dt_factor
+ # calculate tof1
+ velocity = h/(m_n*metadata.wavelength*1e-10) # m/s
+ tof1 = 1e+06*l1/velocity # microseconds
+ self.log().debug("TOF1 = {} microseconds".format(tof1))
+ self.log().debug("Delay time = {} microsecond".format(metadata.tof_delay_time))
+ # create dataX array
+ x0 = tof1 + metadata.tof_delay_time
+ self.log().debug("TOF1 = {} microseconds".format(tof1))
+ dataX = np.linspace(x0, x0+metadata.tof_channel_number*dt, metadata.tof_channel_number+1)
+
+ # sample logs
+ logs["names"].extend(["channel_width", "TOF1", "delay_time", "tof_channels"])
+ logs["values"].extend([dt, tof1, metadata.tof_delay_time, metadata.tof_channel_number])
+ logs["units"].extend(["microseconds", "microseconds", "microseconds", ""])
+ if metadata.tof_elastic_channel:
+ logs["names"].append("EPP")
+ logs["values"].append(metadata.tof_elastic_channel)
+ logs["units"].append("")
+ if metadata.chopper_rotation_speed:
+ logs["names"].append("chopper_speed")
+ logs["values"].append(metadata.chopper_rotation_speed)
+ logs["units"].append("Hz")
+ if metadata.chopper_slits:
+ logs["names"].append("chopper_slits")
+ logs["values"].append(metadata.chopper_slits)
+ logs["units"].append("")
+
# data normalization
factor = 1.0
yunit = "Counts"
@@ -141,7 +198,7 @@ class LoadDNSLegacy(PythonAlgorithm):
dataE = np.sqrt(data_array[0:ndet, 1:])/factor
# create workspace
api.CreateWorkspace(OutputWorkspace=outws_name, DataX=dataX, DataY=dataY,
- DataE=dataE, NSpec=ndet, UnitX="Wavelength")
+ DataE=dataE, NSpec=ndet, UnitX=unitX)
outws = api.AnalysisDataService.retrieve(outws_name)
api.LoadInstrument(outws, InstrumentName='DNS', RewriteSpectraMap=True)
@@ -156,68 +213,40 @@ class LoadDNSLegacy(PythonAlgorithm):
# rotate the detector bank to the proper position
api.RotateInstrumentComponent(outws, "bank0", X=0, Y=1, Z=0, Angle=metadata.deterota)
# add sample log Ei and wavelength
- api.AddSampleLog(outws, LogName='Ei', LogText=str(metadata.incident_energy),
- LogType='Number', LogUnit='meV')
- api.AddSampleLog(outws, LogName='wavelength', LogText=str(metadata.wavelength),
- LogType='Number', LogUnit='Angstrom')
+ logs["names"].extend(["Ei", "wavelength"])
+ logs["values"].extend([metadata.incident_energy, metadata.wavelength])
+ logs["units"].extend(["meV", "Angstrom"])
+
# add other sample logs
- api.AddSampleLog(outws, LogName='deterota', LogText=str(metadata.deterota),
- LogType='Number', LogUnit='Degrees')
- api.AddSampleLog(outws, 'mon_sum',
- LogText=str(float(metadata.monitor_counts)), LogType='Number')
- api.AddSampleLog(outws, LogName='duration', LogText=str(metadata.duration),
- LogType='Number', LogUnit='Seconds')
- api.AddSampleLog(outws, LogName='huber', LogText=str(metadata.huber),
- LogType='Number', LogUnit='Degrees')
- api.AddSampleLog(outws, LogName='omega', LogText=str(metadata.huber - metadata.deterota),
- LogType='Number', LogUnit='Degrees')
- api.AddSampleLog(outws, LogName='T1', LogText=str(metadata.temp1),
- LogType='Number', LogUnit='K')
- api.AddSampleLog(outws, LogName='T2', LogText=str(metadata.temp2),
- LogType='Number', LogUnit='K')
- api.AddSampleLog(outws, LogName='Tsp', LogText=str(metadata.tsp),
- LogType='Number', LogUnit='K')
- # flipper
- api.AddSampleLog(outws, LogName='flipper_precession',
- LogText=str(metadata.flipper_precession_current),
- LogType='Number', LogUnit='A')
- api.AddSampleLog(outws, LogName='flipper_z_compensation',
- LogText=str(metadata.flipper_z_compensation_current),
- LogType='Number', LogUnit='A')
+ logs["names"].extend(["deterota", "mon_sum", "duration", "huber", "omega", "T1", "T2", "Tsp"])
+ logs["values"].extend([metadata.deterota, metadata.monitor_counts, metadata.duration,
+ metadata.huber, metadata.huber - metadata.deterota,
+ metadata.temp1, metadata.temp2, metadata.tsp])
+ logs["units"].extend(["Degrees", "Counts", "Seconds", "Degrees", "Degrees", "K", "K", "K"])
+
+ # flipper, coil currents and polarisation
flipper_status = 'OFF' # flipper OFF
if abs(metadata.flipper_precession_current) > sys.float_info.epsilon:
flipper_status = 'ON' # flipper ON
- api.AddSampleLog(outws, LogName='flipper',
- LogText=flipper_status, LogType='String')
- # coil currents
- api.AddSampleLog(outws, LogName='C_a', LogText=str(metadata.a_coil_current),
- LogType='Number', LogUnit='A')
- api.AddSampleLog(outws, LogName='C_b', LogText=str(metadata.b_coil_current),
- LogType='Number', LogUnit='A')
- api.AddSampleLog(outws, LogName='C_c', LogText=str(metadata.c_coil_current),
- LogType='Number', LogUnit='A')
- api.AddSampleLog(outws, LogName='C_z', LogText=str(metadata.z_coil_current),
- LogType='Number', LogUnit='A')
- # type of polarisation
- api.AddSampleLog(outws, 'polarisation', LogText=pol[0], LogType='String')
- api.AddSampleLog(outws, 'polarisation_comment', LogText=str(pol[1]), LogType='String')
+ logs["names"].extend(["flipper_precession", "flipper_z_compensation", "flipper",
+ "C_a", "C_b", "C_c", "C_z", "polarisation", "polarisation_comment"])
+ logs["values"].extend([metadata.flipper_precession_current,
+ metadata.flipper_z_compensation_current, flipper_status,
+ metadata.a_coil_current, metadata.b_coil_current,
+ metadata.c_coil_current, metadata.z_coil_current,
+ str(pol[0]), str(pol[1])])
+ logs["units"].extend(["A", "A", "", "A", "A", "A", "A", "", ""])
+
# slits
- api.AddSampleLog(outws, LogName='slit_i_upper_blade_position',
- LogText=str(metadata.slit_i_upper_blade_position),
- LogType='Number', LogUnit='mm')
- api.AddSampleLog(outws, LogName='slit_i_lower_blade_position',
- LogText=str(metadata.slit_i_lower_blade_position),
- LogType='Number', LogUnit='mm')
- api.AddSampleLog(outws, LogName='slit_i_left_blade_position',
- LogText=str(metadata.slit_i_left_blade_position),
- LogType='Number', LogUnit='mm')
- api.AddSampleLog(outws, 'slit_i_right_blade_position',
- LogText=str(metadata.slit_i_right_blade_position),
- LogType='Number', LogUnit='mm')
- # data normalization
+ logs["names"].extend(["slit_i_upper_blade_position", "slit_i_lower_blade_position",
+ "slit_i_left_blade_position", "slit_i_right_blade_position"])
+ logs["values"].extend([metadata.slit_i_upper_blade_position, metadata.slit_i_lower_blade_position,
+ metadata.slit_i_left_blade_position, metadata.slit_i_right_blade_position])
+ logs["units"].extend(["mm", "mm", "mm", "mm"])
# add information whether the data are normalized (duration/monitor/no):
api.AddSampleLog(outws, LogName='normalized', LogText=norm, LogType='String')
+ api.AddSampleLogMultiple(outws, LogNames=logs["names"], LogValues=logs["values"], LogUnits=logs["units"])
outws.setYUnit(yunit)
outws.setYUnitLabel(ylabel)
diff --git a/Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/BayesQuasi.py b/Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/BayesQuasi.py
index ce10d94d7bf42eb6b46abc3712bd0631a6561538..cd3908232e0272f728eac9a6c53407b3edce6e3f 100644
--- a/Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/BayesQuasi.py
+++ b/Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/BayesQuasi.py
@@ -1,4 +1,4 @@
-#pylint: disable=invalid-name,too-many-instance-attributes,too-many-branches,no-init,redefined-builtin
+# pylint: disable=invalid-name,too-many-instance-attributes,too-many-branches,no-init,redefined-builtin
from __future__ import (absolute_import, division, print_function)
from six.moves import range
from six import next
@@ -13,16 +13,16 @@ from mantid.kernel import StringListValidator, Direction
import mantid.simpleapi as s_api
from mantid import config, logger
from IndirectCommon import *
+
MTD_PLOT = import_mantidplot()
if is_supported_f2py_platform():
- QLr = import_f2py("QLres")
- QLd = import_f2py("QLdata")
- Qse = import_f2py("QLse")
+ QLr = import_f2py("QLres")
+ QLd = import_f2py("QLdata")
+ Qse = import_f2py("QLse")
class BayesQuasi(PythonAlgorithm):
-
_program = None
_samWS = None
_resWS = None
@@ -42,16 +42,16 @@ class BayesQuasi(PythonAlgorithm):
return "Workflow\\MIDAS"
def summary(self):
- return "This algorithm runs the Fortran QLines programs which fits a Delta function of"+\
- " amplitude 0 and Lorentzians of amplitude A(j) and HWHM W(j) where j=1,2,3. The"+\
- " whole function is then convoled with the resolution function."
+ return "This algorithm runs the Fortran QLines programs which fits a Delta function of" + \
+ " amplitude 0 and Lorentzians of amplitude A(j) and HWHM W(j) where j=1,2,3. The" + \
+ " whole function is then convolved with the resolution function."
def version(self):
return 1
def PyInit(self):
self.declareProperty(name='Program', defaultValue='QL',
- validator=StringListValidator(['QL','QSe']),
+ validator=StringListValidator(['QL', 'QSe']),
doc='The type of program to run (either QL or QSe)')
self.declareProperty(MatrixWorkspaceProperty('SampleWorkspace', '', direction=Direction.Input),
@@ -81,7 +81,7 @@ class BayesQuasi(PythonAlgorithm):
doc='Fit option for using the elastic peak')
self.declareProperty(name='Background', defaultValue='Flat',
- validator=StringListValidator(['Sloping','Flat','Zero']),
+ validator=StringListValidator(['Sloping', 'Flat', 'Zero']),
doc='Fit option for the type of background')
self.declareProperty(name='FixedWidth', defaultValue=True,
@@ -131,7 +131,7 @@ class BayesQuasi(PythonAlgorithm):
self._wfile = self.getPropertyValue('WidthFile')
self._loop = self.getProperty('Loop').value
- #pylint: disable=too-many-locals,too-many-statements
+ # pylint: disable=too-many-locals,too-many-statements
def PyExec(self):
# Check for platform support
@@ -142,18 +142,18 @@ class BayesQuasi(PythonAlgorithm):
raise RuntimeError(unsupported_msg)
from IndirectBayes import (CalcErange, GetXYE)
- setup_prog = Progress(self, start=0.0, end=0.3, nreports = 5)
+ setup_prog = Progress(self, start=0.0, end=0.3, nreports=5)
self.log().information('BayesQuasi input')
erange = [self._e_min, self._e_max]
nbins = [self._sam_bins, self._res_bins]
setup_prog.report('Converting to binary for Fortran')
- #convert true/false to 1/0 for fortran
+ # convert true/false to 1/0 for fortran
o_el = 1 if self._elastic else 0
o_w1 = 1 if self._width else 0
o_res = 1 if self._res_norm else 0
- #fortran code uses background choices defined using the following numbers
+ # fortran code uses background choices defined using the following numbers
setup_prog.report('Encoding input options')
if self._background == 'Sloping':
o_bgd = 2
@@ -170,11 +170,11 @@ class BayesQuasi(PythonAlgorithm):
workdir = os.getcwd()
logger.information('Default Save directory is not set. Defaulting to current working Directory: ' + workdir)
- array_len = 4096 # length of array in Fortran
+ array_len = 4096 # length of array in Fortran
setup_prog.report('Checking X Range')
- CheckXrange(erange,'Energy')
+ CheckXrange(erange, 'Energy')
- nbin,nrbin = nbins[0], nbins[1]
+ nbin, nrbin = nbins[0], nbins[1]
logger.information('Sample is ' + self._samWS)
logger.information('Resolution is ' + self._resWS)
@@ -195,16 +195,16 @@ class BayesQuasi(PythonAlgorithm):
erange = [self._e_min, self._e_max]
setup_prog.report('Checking Analysers')
- CheckAnalysers(self._samWS,self._resWS)
+ CheckAnalysers(self._samWS, self._resWS)
setup_prog.report('Obtaining EFixed, theta and Q')
efix = getEfixed(self._samWS)
theta, Q = GetThetaQ(self._samWS)
- nsam,ntc = CheckHistZero(self._samWS)
+ nsam, ntc = CheckHistZero(self._samWS)
totalNoSam = nsam
- #check if we're performing a sequential fit
+ # check if we're performing a sequential fit
if not self._loop:
nsam = 1
@@ -213,54 +213,54 @@ class BayesQuasi(PythonAlgorithm):
setup_prog.report('Checking Histograms')
if self._program == 'QL':
if nres == 1:
- prog = 'QLr' # res file
+ prog = 'QLr' # res file
else:
- prog = 'QLd' # data file
- CheckHistSame(self._samWS,'Sample',self._resWS,'Resolution')
+ prog = 'QLd' # data file
+ CheckHistSame(self._samWS, 'Sample', self._resWS, 'Resolution')
elif self._program == 'QSe':
if nres == 1:
- prog = 'QSe' # res file
+ prog = 'QSe' # res file
else:
raise ValueError('Stretched Exp ONLY works with RES file')
- logger.information('Version is ' +prog)
- logger.information(' Number of spectra = '+str(nsam))
- logger.information(' Erange : '+str(erange[0])+' to '+str(erange[1]))
+ logger.information('Version is ' + prog)
+ logger.information(' Number of spectra = ' + str(nsam))
+ logger.information(' Erange : ' + str(erange[0]) + ' to ' + str(erange[1]))
setup_prog.report('Reading files')
- Wy,We = self._read_width_file(self._width,self._wfile,totalNoSam)
- dtn,xsc = self._read_norm_file(self._res_norm,self._resnormWS,totalNoSam)
+ Wy, We = self._read_width_file(self._width, self._wfile, totalNoSam)
+ dtn, xsc = self._read_norm_file(self._res_norm, self._resnormWS, totalNoSam)
setup_prog.report('Establishing output workspace name')
- fname = self._samWS[:-4] + '_'+ prog
+ fname = self._samWS[:-4] + '_' + prog
probWS = fname + '_Prob'
fitWS = fname + '_Fit'
- wrks=os.path.join(workdir, self._samWS[:-4])
- logger.information(' lptfile : '+wrks+'_'+prog+'.lpt')
- lwrk=len(wrks)
- wrks.ljust(140,' ')
- wrkr=self._resWS
- wrkr.ljust(140,' ')
+ wrks = os.path.join(workdir, self._samWS[:-4])
+ logger.information(' lptfile : ' + wrks + '_' + prog + '.lpt')
+ lwrk = len(wrks)
+ wrks.ljust(140, ' ')
+ wrkr = self._resWS
+ wrkr.ljust(140, ' ')
setup_prog.report('Initialising probability list')
# initialise probability list
if self._program == 'QL':
prob0, prob1, prob2 = [], [], []
xQ = np.array([Q[0]])
- for m in range(1,nsam):
- xQ = np.append(xQ,Q[m])
+ for m in range(1, nsam):
+ xQ = np.append(xQ, Q[m])
xProb = xQ
- xProb = np.append(xProb,xQ)
- xProb = np.append(xProb,xQ)
- eProb = np.zeros(3*nsam)
+ xProb = np.append(xProb, xQ)
+ xProb = np.append(xProb, xQ)
+ eProb = np.zeros(3 * nsam)
group = ''
- workflow_prog = Progress(self, start=0.3, end=0.7, nreports=nsam*3)
- for spectrum in range(0,nsam):
- logger.information('Group ' +str(spectrum)+ ' at angle '+ str(theta[spectrum]))
- nsp = spectrum+1
+ workflow_prog = Progress(self, start=0.3, end=0.7, nreports=nsam * 3)
+ for spectrum in range(0, nsam):
+ logger.information('Group ' + str(spectrum) + ' at angle ' + str(theta[spectrum]))
+ nsp = spectrum + 1
- nout,bnorm,Xdat,Xv,Yv,Ev = CalcErange(self._samWS,spectrum,erange,nbin)
+ nout, bnorm, Xdat, Xv, Yv, Ev = CalcErange(self._samWS, spectrum, erange, nbin)
Ndat = nout[0]
Imin = nout[1]
Imax = nout[2]
@@ -268,33 +268,33 @@ class BayesQuasi(PythonAlgorithm):
mm = spectrum
else:
mm = 0
- Nb,Xb,Yb,Eb = GetXYE(self._resWS,mm,array_len) # get resolution data
+ Nb, Xb, Yb, Eb = GetXYE(self._resWS, mm, array_len) # get resolution data
numb = [nsam, nsp, ntc, Ndat, nbin, Imin, Imax, Nb, nrbin]
rscl = 1.0
reals = [efix, theta[spectrum], rscl, bnorm]
if prog == 'QLr':
workflow_prog.report('Processing Sample number %i as Lorentzian' % spectrum)
- nd,xout,yout,eout,yfit,yprob=QLr.qlres(numb,Xv,Yv,Ev,reals,fitOp,
- Xdat,Xb,Yb,Wy,We,dtn,xsc,
- wrks,wrkr,lwrk)
- message = ' Log(prob) : '+str(yprob[0])+' '+str(yprob[1])+' '+str(yprob[2])+' '+str(yprob[3])
+ nd, xout, yout, eout, yfit, yprob = QLr.qlres(numb, Xv, Yv, Ev, reals, fitOp,
+ Xdat, Xb, Yb, Wy, We, dtn, xsc,
+ wrks, wrkr, lwrk)
+ message = ' Log(prob) : ' + str(yprob[0]) + ' ' + str(yprob[1]) + ' ' + str(yprob[2]) + ' ' + str(yprob[3])
logger.information(message)
if prog == 'QLd':
workflow_prog.report('Processing Sample number %i' % spectrum)
- nd,xout,yout,eout,yfit,yprob=QLd.qldata(numb,Xv,Yv,Ev,reals,fitOp,
- Xdat,Xb,Yb,Eb,Wy,We,
- wrks,wrkr,lwrk)
- message = ' Log(prob) : '+str(yprob[0])+' '+str(yprob[1])+' '+str(yprob[2])+' '+str(yprob[3])
+ nd, xout, yout, eout, yfit, yprob = QLd.qldata(numb, Xv, Yv, Ev, reals, fitOp,
+ Xdat, Xb, Yb, Eb, Wy, We,
+ wrks, wrkr, lwrk)
+ message = ' Log(prob) : ' + str(yprob[0]) + ' ' + str(yprob[1]) + ' ' + str(yprob[2]) + ' ' + str(yprob[3])
logger.information(message)
if prog == 'QSe':
workflow_prog.report('Processing Sample number %i as Stretched Exp' % spectrum)
- nd,xout,yout,eout,yfit,yprob=Qse.qlstexp(numb,Xv,Yv,Ev,reals,fitOp,
- Xdat,Xb,Yb,Wy,We,dtn,xsc,
- wrks,wrkr,lwrk)
+ nd, xout, yout, eout, yfit, yprob = Qse.qlstexp(numb, Xv, Yv, Ev, reals, fitOp,
+ Xdat, Xb, Yb, Wy, We, dtn, xsc,
+ wrks, wrkr, lwrk)
dataX = xout[:nd]
- dataX = np.append(dataX,2*xout[nd-1]-xout[nd-2])
- yfit_list = np.split(yfit[:4*nd],4)
+ dataX = np.append(dataX, 2 * xout[nd - 1] - xout[nd - 2])
+ yfit_list = np.split(yfit[:4 * nd], 4)
dataF1 = yfit_list[1]
if self._program == 'QL':
dataF2 = yfit_list[2]
@@ -303,25 +303,25 @@ class BayesQuasi(PythonAlgorithm):
datX = dataX
datY = yout[:nd]
datE = eout[:nd]
- datX = np.append(datX,dataX)
- datY = np.append(datY,dataF1[:nd])
- datE = np.append(datE,dataG)
+ datX = np.append(datX, dataX)
+ datY = np.append(datY, dataF1[:nd])
+ datE = np.append(datE, dataG)
res1 = dataF1[:nd] - yout[:nd]
- datX = np.append(datX,dataX)
- datY = np.append(datY,res1)
- datE = np.append(datE,dataG)
+ datX = np.append(datX, dataX)
+ datY = np.append(datY, res1)
+ datE = np.append(datE, dataG)
nsp = 3
names = 'data,fit.1,diff.1'
res_plot = [0, 1, 2]
if self._program == 'QL':
workflow_prog.report('Processing Lorentzian result data')
- datX = np.append(datX,dataX)
- datY = np.append(datY,dataF2[:nd])
- datE = np.append(datE,dataG)
+ datX = np.append(datX, dataX)
+ datY = np.append(datY, dataF2[:nd])
+ datE = np.append(datE, dataG)
res2 = dataF2[:nd] - yout[:nd]
- datX = np.append(datX,dataX)
- datY = np.append(datY,res2)
- datE = np.append(datE,dataG)
+ datX = np.append(datX, dataX)
+ datY = np.append(datY, res2)
+ datE = np.append(datE, dataG)
nsp += 2
names += ',fit.2,diff.2'
res_plot.append(4)
@@ -330,8 +330,8 @@ class BayesQuasi(PythonAlgorithm):
prob2.append(yprob[2])
# create result workspace
- fitWS = fname+'_Workspaces'
- fout = fname+'_Workspace_'+ str(spectrum)
+ fitWS = fname + '_Workspaces'
+ fout = fname + '_Workspace_' + str(spectrum)
workflow_prog.report('Creating OutputWorkspace')
s_api.CreateWorkspace(OutputWorkspace=fout, DataX=datX, DataY=datY, DataE=datE,
@@ -342,29 +342,32 @@ class BayesQuasi(PythonAlgorithm):
comp_prog = Progress(self, start=0.7, end=0.8, nreports=2)
comp_prog.report('Creating Group Workspace')
- s_api.GroupWorkspaces(InputWorkspaces=group,OutputWorkspace=fitWS)
+ s_api.GroupWorkspaces(InputWorkspaces=group, OutputWorkspace=fitWS)
if self._program == 'QL':
comp_prog.report('Processing Lorentzian probability data')
yPr0 = np.array([prob0[0]])
yPr1 = np.array([prob1[0]])
yPr2 = np.array([prob2[0]])
- for m in range(1,nsam):
- yPr0 = np.append(yPr0,prob0[m])
- yPr1 = np.append(yPr1,prob1[m])
- yPr2 = np.append(yPr2,prob2[m])
+ for m in range(1, nsam):
+ yPr0 = np.append(yPr0, prob0[m])
+ yPr1 = np.append(yPr1, prob1[m])
+ yPr2 = np.append(yPr2, prob2[m])
yProb = yPr0
- yProb = np.append(yProb,yPr1)
- yProb = np.append(yProb,yPr2)
+ yProb = np.append(yProb, yPr1)
+ yProb = np.append(yProb, yPr2)
s_api.CreateWorkspace(OutputWorkspace=probWS, DataX=xProb, DataY=yProb, DataE=eProb,
Nspec=3, UnitX='MomentumTransfer')
outWS = self.C2Fw(fname)
if self._program == 'QSe':
- comp_prog.report('Runnning C2Se')
+ comp_prog.report('Running C2Se')
outWS = self.C2Se(fname)
- log_prog = Progress(self, start=0.8, end =1.0, nreports=8)
- #Add some sample logs to the output workspaces
+ # Sort x axis
+ s_api.SortXAxis(InputWorkspace=outWS, OutputWorkspace=outWS, EnableLogging=False)
+
+ log_prog = Progress(self, start=0.8, end=1.0, nreports=8)
+ # Add some sample logs to the output workspaces
log_prog.report('Copying Logs to outputWorkspace')
s_api.CopyLogs(InputWorkspace=self._samWS, OutputWorkspace=outWS)
log_prog.report('Adding Sample logs to Output workspace')
@@ -373,13 +376,14 @@ class BayesQuasi(PythonAlgorithm):
s_api.CopyLogs(InputWorkspace=self._samWS, OutputWorkspace=fitWS)
log_prog.report('Adding sample logs to Fit workspace')
self._add_sample_logs(fitWS, prog, erange, nbins)
- log_prog.report('Finialising log copying')
+ log_prog.report('Finalising log copying')
self.setProperty('OutputWorkspaceFit', fitWS)
self.setProperty('OutputWorkspaceResult', outWS)
log_prog.report('Setting workspace properties')
if self._program == 'QL':
+ s_api.SortXAxis(InputWorkspace=probWS, OutputWorkspace=probWS, EnableLogging=False)
self.setProperty('OutputWorkspaceProb', probWS)
def _add_sample_logs(self, workspace, fit_program, e_range, binning):
@@ -413,9 +417,9 @@ class BayesQuasi(PythonAlgorithm):
log_alg.execute()
def C2Se(self, sname):
- outWS = sname+'_Result'
- asc = self._read_ascii_file(sname+'.qse')
- var = asc[3].split() #split line on spaces
+ outWS = sname + '_Result'
+ asc = self._read_ascii_file(sname + '.qse')
+ var = asc[3].split() # split line on spaces
nspec = var[0]
var = ExtractInt(asc[6])
first = 7
@@ -429,8 +433,8 @@ class BayesQuasi(PythonAlgorithm):
dataE = np.array([])
data = np.array([dataX, dataY, dataE])
- for _ in range(0,ns):
- first,Q,_,fw,it,be = self.SeBlock(asc,first)
+ for _ in range(0, ns):
+ first, Q, _, fw, it, be = self.SeBlock(asc, first)
Xout.append(Q)
Yf.append(fw[0])
Ef.append(fw[1])
@@ -461,9 +465,9 @@ class BayesQuasi(PythonAlgorithm):
def _add_xye_data(self, data, xout, Y, E):
dX, dY, dE = data[0], data[1], data[2]
- dX = np.append(dX,np.array(xout))
- dY = np.append(dY,np.array(Y))
- dE = np.append(dE,np.array(E))
+ dX = np.append(dX, np.array(xout))
+ dY = np.append(dY, np.array(Y))
+ dE = np.append(dE, np.array(E))
data = (dX, dY, dE)
return dX, dY, dE, data
@@ -478,51 +482,51 @@ class BayesQuasi(PythonAlgorithm):
asc.append(line)
return asc
- def SeBlock(self, a, index): #read Ascii block of Integers
+ def SeBlock(self, a, index): # read Ascii block of Integers
index += 1
- val = ExtractFloat(a[index]) #Q,AMAX,HWHM
+ val = ExtractFloat(a[index]) # Q,AMAX,HWHM
Q = val[0]
AMAX = val[1]
HWHM = val[2]
index += 1
- val = ExtractFloat(a[index]) #A0
- int0 = [AMAX*val[0]]
+ val = ExtractFloat(a[index]) # A0
+ int0 = [AMAX * val[0]]
index += 1
- val = ExtractFloat(a[index]) #AI,FWHM index peak
- fw = [2.*HWHM*val[1]]
- integer = [AMAX*val[0]]
+ val = ExtractFloat(a[index]) # AI,FWHM index peak
+ fw = [2. * HWHM * val[1]]
+ integer = [AMAX * val[0]]
index += 1
- val = ExtractFloat(a[index]) #SIG0
+ val = ExtractFloat(a[index]) # SIG0
int0.append(val[0])
index += 1
- val = ExtractFloat(a[index]) #SIG3K
- integer.append(AMAX*math.sqrt(math.fabs(val[0])+1.0e-20))
+ val = ExtractFloat(a[index]) # SIG3K
+ integer.append(AMAX * math.sqrt(math.fabs(val[0]) + 1.0e-20))
index += 1
- val = ExtractFloat(a[index]) #SIG1K
- fw.append(2.0*HWHM*math.sqrt(math.fabs(val[0])+1.0e-20))
+ val = ExtractFloat(a[index]) # SIG1K
+ fw.append(2.0 * HWHM * math.sqrt(math.fabs(val[0]) + 1.0e-20))
index += 1
- be = ExtractFloat(a[index]) #EXPBET
+ be = ExtractFloat(a[index]) # EXPBET
index += 1
- val = ExtractFloat(a[index]) #SIG2K
- be.append(math.sqrt(math.fabs(val[0])+1.0e-20))
+ val = ExtractFloat(a[index]) # SIG2K
+ be.append(math.sqrt(math.fabs(val[0]) + 1.0e-20))
index += 1
- return index, Q, int0 ,fw , integer, be #values as list
+ return index, Q, int0, fw, integer, be # values as list
- def _get_res_norm(self, resnormWS,ngrp):
- if ngrp == 0: # read values from WS
- dtnorm = s_api.mtd[resnormWS+'_Intensity'].readY(0)
- xscale = s_api.mtd[resnormWS+'_Stretch'].readY(0)
- else: # constant values
+ def _get_res_norm(self, resnormWS, ngrp):
+ if ngrp == 0: # read values from WS
+ dtnorm = s_api.mtd[resnormWS + '_Intensity'].readY(0)
+ xscale = s_api.mtd[resnormWS + '_Stretch'].readY(0)
+ else: # constant values
dtnorm = []
xscale = []
- for _ in range(0,ngrp):
+ for _ in range(0, ngrp):
dtnorm.append(1.0)
xscale.append(1.0)
- dtn=PadArray(dtnorm,51) # pad for Fortran call
- xsc=PadArray(xscale,51)
- return dtn,xsc
+ dtn = PadArray(dtnorm, 51) # pad for Fortran call
+ xsc = PadArray(xscale, 51)
+ return dtn, xsc
- def _read_norm_file(self, readRes,resnormWS,nsam): # get norm & scale values
+ def _read_norm_file(self, readRes, resnormWS, nsam): # get norm & scale values
resnorm_root = resnormWS
# Obtain root of resnorm group name
if '_Intensity' in resnormWS:
@@ -530,25 +534,25 @@ class BayesQuasi(PythonAlgorithm):
if '_Stretch' in resnormWS:
resnorm_root = resnormWS[:-8]
- if readRes: # use ResNorm file option=o_res
- Xin = s_api.mtd[resnorm_root+'_Intensity'].readX(0)
- nrm = len(Xin) # no. points from length of x array
+ if readRes: # use ResNorm file option=o_res
+ Xin = s_api.mtd[resnorm_root + '_Intensity'].readX(0)
+ nrm = len(Xin) # no. points from length of x array
if nrm == 0:
raise ValueError('ResNorm file has no Intensity points')
- Xin = s_api.mtd[resnorm_root+'_Stretch'].readX(0) # no. points from length of x array
+ Xin = s_api.mtd[resnorm_root + '_Stretch'].readX(0) # no. points from length of x array
if len(Xin) == 0:
raise ValueError('ResNorm file has no xscale points')
- if nrm != nsam: # check that no. groups are the same
- raise ValueError('ResNorm groups (' +str(nrm) + ') not = Sample (' +str(nsam) +')')
+ if nrm != nsam: # check that no. groups are the same
+ raise ValueError('ResNorm groups (' + str(nrm) + ') not = Sample (' + str(nsam) + ')')
else:
- dtn,xsc = self._get_res_norm(resnorm_root,0)
+ dtn, xsc = self._get_res_norm(resnorm_root, 0)
else:
# do not use ResNorm file
- dtn,xsc = self._get_res_norm(resnorm_root,nsam)
- return dtn,xsc
+ dtn, xsc = self._get_res_norm(resnorm_root, nsam)
+ return dtn, xsc
- #Reads in a width ASCII file
- def _read_width_file(self, readWidth,widthFile,numSampleGroups):
+ # Reads in a width ASCII file
+ def _read_width_file(self, readWidth, widthFile, numSampleGroups):
widthY, widthE = [], []
if readWidth:
logger.information('Width file is ' + widthFile)
@@ -566,72 +570,72 @@ class BayesQuasi(PythonAlgorithm):
numLines = len(asc)
if numLines == 0:
raise ValueError('No groups in width file')
- if numLines != numSampleGroups: # check that no. groups are the same
- raise ValueError('Width groups (' +str(numLines) + ') not = Sample (' +str(numSampleGroups) +')')
+ if numLines != numSampleGroups: # check that no. groups are the same
+ raise ValueError('Width groups (' + str(numLines) + ') not = Sample (' + str(numSampleGroups) + ')')
else:
# no file: just use constant values
widthY = np.zeros(numSampleGroups)
widthE = np.zeros(numSampleGroups)
# pad for Fortran call
- widthY = PadArray(widthY,51)
- widthE = PadArray(widthE,51)
+ widthY = PadArray(widthY, 51)
+ widthE = PadArray(widthE, 51)
return widthY, widthE
def C2Fw(self, sname):
- output_workspace = sname+'_Result'
+ output_workspace = sname + '_Result'
num_spectra = 0
axis_names = []
x, y, e = [], [], []
- for nl in range(1,4):
- num_params = nl*3+1
+ for nl in range(1, 4):
+ num_params = nl * 3 + 1
num_spectra += num_params
amplitude_data, width_data = [], []
- amplitude_error, width_error = [], []
+ amplitude_error, width_error = [], []
- #read data from file output by fortran code
- file_name = sname + '.ql' +str(nl)
+ # read data from file output by fortran code
+ file_name = sname + '.ql' + str(nl)
x_data, peak_data, peak_error = self._read_ql_file(file_name, nl)
x_data = np.asarray(x_data)
amplitude_data, width_data, height_data = peak_data
amplitude_error, width_error, height_error = peak_error
- #transpose y and e data into workspace rows
+ # transpose y and e data into workspace rows
amplitude_data, width_data = np.asarray(amplitude_data).T, np.asarray(width_data).T
amplitude_error, width_error = np.asarray(amplitude_error).T, np.asarray(width_error).T
height_data, height_error = np.asarray(height_data), np.asarray(height_error)
- #calculate EISF and EISF error
- total = height_data+amplitude_data
+ # calculate EISF and EISF error
+ total = height_data + amplitude_data
EISF_data = height_data / total
- total_error = height_error**2 + amplitude_error**2
- EISF_error = EISF_data * np.sqrt((height_error**2/height_data**2) + (total_error/total**2))
+ total_error = height_error ** 2 + amplitude_error ** 2
+ EISF_error = EISF_data * np.sqrt((height_error ** 2 / height_data ** 2) + (total_error / total ** 2))
- #interlace amplitudes and widths of the peaks
+ # interlace amplitudes and widths of the peaks
y.append(np.asarray(height_data))
for amp, width, EISF in zip(amplitude_data, width_data, EISF_data):
y.append(amp)
y.append(width)
y.append(EISF)
- #iterlace amplitude and width errors of the peaks
+ # interlace amplitude and width errors of the peaks
e.append(np.asarray(height_error))
for amp, width, EISF in zip(amplitude_error, width_error, EISF_error):
e.append(amp)
e.append(width)
e.append(EISF)
- #create x data and axis names for each function
- axis_names.append('f'+str(nl)+'.f0.'+'Height')
+ # create x data and axis names for each function
+ axis_names.append('f' + str(nl) + '.f0.' + 'Height')
x.append(x_data)
- for j in range(1,nl+1):
- axis_names.append('f'+str(nl)+'.f'+str(j)+'.Amplitude')
+ for j in range(1, nl + 1):
+ axis_names.append('f' + str(nl) + '.f' + str(j) + '.Amplitude')
x.append(x_data)
- axis_names.append('f'+str(nl)+'.f'+str(j)+'.FWHM')
+ axis_names.append('f' + str(nl) + '.f' + str(j) + '.FWHM')
x.append(x_data)
- axis_names.append('f'+str(nl)+'.f'+str(j)+'.EISF')
+ axis_names.append('f' + str(nl) + '.f' + str(j) + '.EISF')
x.append(x_data)
x = np.asarray(x).flatten()
@@ -644,83 +648,84 @@ class BayesQuasi(PythonAlgorithm):
return output_workspace
def _yield_floats(self, block):
- #yield a list of floats from a list of lines of text
- #encapsulates the iteration over a block of lines
+ # yield a list of floats from a list of lines of text
+ # encapsulates the iteration over a block of lines
for line in block:
yield ExtractFloat(line)
def _read_ql_file(self, file_name, nl):
- #offet to ignore header
+ # offset to ignore header
header_offset = 8
- block_size = 4+nl*3
+ block_size = 4 + nl * 3
asc = self._read_ascii_file(file_name)
- #extract number of blocks from the file header
+ # extract number of blocks from the file header
num_blocks = int(ExtractFloat(asc[3])[0])
q_data = []
amp_data, FWHM_data, height_data = [], [], []
amp_error, FWHM_error, height_error = [], [], []
- #iterate over each block of fit parameters in the file
- #each block corresponds to a single column in the final workspace
+ # iterate over each block of fit parameters in the file
+ # each block corresponds to a single column in the final workspace
for block_num in range(num_blocks):
- lower_index = header_offset+(block_size*block_num)
- upper_index = lower_index+block_size
+ lower_index = header_offset + (block_size * block_num)
+ upper_index = lower_index + block_size
- #create iterator for each line in the block
+ # create iterator for each line in the block
line_pointer = self._yield_floats(asc[lower_index:upper_index])
- #Q,AMAX,HWHM,BSCL,GSCL
+ # Q,AMAX,HWHM,BSCL,GSCL
line = next(line_pointer)
Q, AMAX, HWHM, _, _ = line
q_data.append(Q)
- #A0,A1,A2,A4
+ # A0,A1,A2,A4
line = next(line_pointer)
- block_height = AMAX*line[0]
+ block_height = AMAX * line[0]
- #parse peak data from block
+ # parse peak data from block
block_FWHM = []
block_amplitude = []
for _ in range(nl):
- #Amplitude,FWHM for each peak
+ # Amplitude,FWHM for each peak
line = next(line_pointer)
- amp = AMAX*line[0]
- FWHM = 2.*HWHM*line[1]
+ amp = AMAX * line[0]
+ FWHM = 2. * HWHM * line[1]
block_amplitude.append(amp)
block_FWHM.append(FWHM)
- #next parse error data from block
- #SIG0
+ # next parse error data from block
+ # SIG0
line = next(line_pointer)
block_height_e = line[0]
block_FWHM_e = []
block_amplitude_e = []
for _ in range(nl):
- #Amplitude error,FWHM error for each peak
- #SIGIK
+ # Amplitude error,FWHM error for each peak
+ # SIGIK
line = next(line_pointer)
- amp = AMAX*math.sqrt(math.fabs(line[0])+1.0e-20)
+ amp = AMAX * math.sqrt(math.fabs(line[0]) + 1.0e-20)
block_amplitude_e.append(amp)
- #SIGFK
+ # SIGFK
line = next(line_pointer)
- FWHM = 2.0*HWHM*math.sqrt(math.fabs(line[0])+1.0e-20)
+ FWHM = 2.0 * HWHM * math.sqrt(math.fabs(line[0]) + 1.0e-20)
block_FWHM_e.append(FWHM)
- #append data from block
+ # append data from block
amp_data.append(block_amplitude)
FWHM_data.append(block_FWHM)
height_data.append(block_height)
- #append error values from block
+ # append error values from block
amp_error.append(block_amplitude_e)
FWHM_error.append(block_FWHM_e)
height_error.append(block_height_e)
return q_data, (amp_data, FWHM_data, height_data), (amp_error, FWHM_error, height_error)
+
# Register algorithm with Mantid
AlgorithmFactory.subscribe(BayesQuasi)
diff --git a/Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/BayesStretch.py b/Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/BayesStretch.py
index f173b1db8998799ad83fc6d0fce6eae18be5a831..b13b0565765d903b0ca85052cbdee06c229d5145 100644
--- a/Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/BayesStretch.py
+++ b/Framework/PythonInterface/plugins/algorithms/WorkflowAlgorithms/BayesStretch.py
@@ -1,4 +1,4 @@
-#pylint: disable=invalid-name,too-many-instance-attributes,too-many-branches,no-init
+# pylint: disable=invalid-name,too-many-instance-attributes,too-many-branches,no-init
from __future__ import (absolute_import, division, print_function)
from IndirectImport import *
@@ -11,11 +11,10 @@ import os
import numpy as np
if is_supported_f2py_platform():
- Que = import_f2py("Quest")
+ Que = import_f2py("Quest")
class BayesStretch(PythonAlgorithm):
-
_sam_name = None
_sam_ws = None
_res_name = None
@@ -59,7 +58,7 @@ class BayesStretch(PythonAlgorithm):
doc='Fit option for using the elastic peak')
self.declareProperty(name='Background', defaultValue='Flat',
- validator=StringListValidator(['Sloping','Flat','Zero']),
+ validator=StringListValidator(['Sloping', 'Flat', 'Zero']),
doc='Fit option for the type of background')
self.declareProperty(name='NumberSigma', defaultValue=50,
@@ -96,13 +95,13 @@ class BayesStretch(PythonAlgorithm):
return issues
- #pylint: disable=too-many-locals
+ # pylint: disable=too-many-locals
def PyExec(self):
run_f2py_compatibility_test()
from IndirectBayes import (CalcErange, GetXYE)
from IndirectCommon import (CheckXrange, CheckAnalysers, getEfixed, GetThetaQ, CheckHistZero)
- setup_prog = Progress(self, start=0.0, end=0.3, nreports = 5)
+ setup_prog = Progress(self, start=0.0, end=0.3, nreports=5)
logger.information('BayesStretch input')
logger.information('Sample is %s' % self._sam_name)
logger.information('Resolution is %s' % self._res_name)
@@ -123,9 +122,9 @@ class BayesStretch(PythonAlgorithm):
theta, Q = GetThetaQ(self._sam_name)
setup_prog.report('Checking Histograms')
- nsam,ntc = CheckHistZero(self._sam_name)
+ nsam, ntc = CheckHistZero(self._sam_name)
- #check if we're performing a sequential fit
+ # check if we're performing a sequential fit
if not self._loop:
nsam = 1
@@ -135,22 +134,22 @@ class BayesStretch(PythonAlgorithm):
setup_prog.report('Creating FORTRAN Input')
fname = self._sam_name[:-4] + '_Stretch'
- wrks=os.path.join(workdir, self._sam_name[:-4])
+ wrks = os.path.join(workdir, self._sam_name[:-4])
logger.information('lptfile : %s_Qst.lpt' % wrks)
- lwrk=len(wrks)
+ lwrk = len(wrks)
wrks.ljust(140, ' ')
- wrkr=self._res_name
+ wrkr = self._res_name
wrkr.ljust(140, ' ')
- eBet0 = np.zeros(self._nbet) # set errors to zero
- eSig0 = np.zeros(self._nsig) # set errors to zero
+ eBet0 = np.zeros(self._nbet) # set errors to zero
+ eSig0 = np.zeros(self._nsig) # set errors to zero
rscl = 1.0
Qaxis = ''
- workflow_prog = Progress(self, start=0.3, end=0.7, nreports=nsam*3)
+ workflow_prog = Progress(self, start=0.3, end=0.7, nreports=nsam * 3)
# Empty arrays to hold Sigma and Bet x,y,e values
- xSig, ySig, eSig = [],[],[]
- xBet, yBet, eBet = [],[],[]
+ xSig, ySig, eSig = [], [], []
+ xBet, yBet, eBet = [], [], []
for m in range(nsam):
logger.information('Group %i at angle %f' % (m, theta[m]))
@@ -168,13 +167,13 @@ class BayesStretch(PythonAlgorithm):
reals = [efix, theta[m], rscl, bnorm]
workflow_prog.report('Processing spectrum number %i' % m)
- xsout, ysout, xbout, ybout, zpout=Que.quest(numb, Xv, Yv, Ev, reals, fitOp,
- Xdat, Xb, Yb, wrks, wrkr, lwrk)
- dataXs = xsout[:self._nsig] # reduce from fixed FORTRAN array
+ xsout, ysout, xbout, ybout, zpout = Que.quest(numb, Xv, Yv, Ev, reals, fitOp,
+ Xdat, Xb, Yb, wrks, wrkr, lwrk)
+ dataXs = xsout[:self._nsig] # reduce from fixed FORTRAN array
dataYs = ysout[:self._nsig]
dataXb = xbout[:self._nbet]
dataYb = ybout[:self._nbet]
- zpWS = fname + '_Zp' +str(m)
+ zpWS = fname + '_Zp' + str(m)
if m > 0:
Qaxis += ','
Qaxis += str(Q[m])
@@ -184,7 +183,7 @@ class BayesStretch(PythonAlgorithm):
dataEz = []
for n in range(self._nsig):
- yfit_list = np.split(zpout[:self._nsig*self._nbet], self._nsig)
+ yfit_list = np.split(zpout[:self._nsig * self._nbet], self._nsig)
dataYzp = yfit_list[n]
dataXz = np.append(dataXz, xbout[:self._nbet])
@@ -194,19 +193,19 @@ class BayesStretch(PythonAlgorithm):
zpWS = fname + '_Zp' + str(m)
self._create_workspace(zpWS, [dataXz, dataYz, dataEz], self._nsig, dataXs, True)
- xSig = np.append(xSig,dataXs)
- ySig = np.append(ySig,dataYs)
- eSig = np.append(eSig,eSig0)
- xBet = np.append(xBet,dataXb)
- yBet = np.append(yBet,dataYb)
- eBet = np.append(eBet,eBet0)
+ xSig = np.append(xSig, dataXs)
+ ySig = np.append(ySig, dataYs)
+ eSig = np.append(eSig, eSig0)
+ xBet = np.append(xBet, dataXb)
+ yBet = np.append(yBet, dataYb)
+ eBet = np.append(eBet, eBet0)
if m == 0:
groupZ = zpWS
else:
- groupZ = groupZ +','+ zpWS
+ groupZ = groupZ + ',' + zpWS
- #create workspaces for sigma and beta
+ # create workspaces for sigma and beta
workflow_prog.report('Creating OutputWorkspace')
self._create_workspace(fname + '_Sigma', [xSig, ySig, eSig], nsam, Qaxis)
self._create_workspace(fname + '_Beta', [xBet, yBet, eBet], nsam, Qaxis)
@@ -219,31 +218,35 @@ class BayesStretch(PythonAlgorithm):
s_api.GroupWorkspaces(InputWorkspaces=groupZ,
OutputWorkspace=contour_ws)
- #Add some sample logs to the output workspaces
- log_prog = Progress(self, start=0.8, end =1.0, nreports=6)
+ # Add some sample logs to the output workspaces
+ log_prog = Progress(self, start=0.8, end=1.0, nreports=6)
log_prog.report('Copying Logs to Fit workspace')
copy_log_alg = self.createChildAlgorithm('CopyLogs', enableLogging=False)
copy_log_alg.setProperty('InputWorkspace', self._sam_name)
- copy_log_alg.setProperty('OutputWorkspace',fit_ws)
+ copy_log_alg.setProperty('OutputWorkspace', fit_ws)
copy_log_alg.execute()
log_prog.report('Adding Sample logs to Fit workspace')
self._add_sample_logs(fit_ws, self._erange, self._nbins[0])
log_prog.report('Copying logs to Contour workspace')
- copy_log_alg.setProperty('InputWorkspace',self._sam_name)
- copy_log_alg.setProperty('OutputWorkspace',contour_ws)
+ copy_log_alg.setProperty('InputWorkspace', self._sam_name)
+ copy_log_alg.setProperty('OutputWorkspace', contour_ws)
copy_log_alg.execute()
log_prog.report('Adding sample logs to Contour workspace')
self._add_sample_logs(contour_ws, self._erange, self._nbins[0])
log_prog.report('Finialising log copying')
+ # sort x axis
+ s_api.SortXAxis(InputWorkspace=fit_ws, OutputWorkspace=fit_ws, EnableLogging=False)
+ s_api.SortXAxis(InputWorkspace=contour_ws, OutputWorkspace=contour_ws, EnableLogging=False)
+
self.setProperty('OutputWorkspaceFit', fit_ws)
self.setProperty('OutputWorkspaceContour', contour_ws)
log_prog.report('Setting workspace properties')
-#----------------------------- Helper functions -----------------------------
+ # ----------------------------- Helper functions -----------------------------
def _encode_fit_ops(self, elastic, background):
"""
@@ -274,8 +277,8 @@ class BayesStretch(PythonAlgorithm):
logger.information('Defaulting to current working Directory: ' + workdir)
return workdir
- #pylint: disable=too-many-arguments
- def _create_workspace(self, name, xye, num_spec, vert_axis, is_zp_ws = False):
+ # pylint: disable=too-many-arguments
+ def _create_workspace(self, name, xye, num_spec, vert_axis, is_zp_ws=False):
"""
Creates a workspace from FORTRAN data
@@ -299,11 +302,11 @@ class BayesStretch(PythonAlgorithm):
unitx = ws.getAxis(0).setUnit("Label")
if is_zp_ws:
unity = ws.getAxis(1).setUnit("Label")
- unitx.setLabel('beta' , '')
- unity.setLabel('sigma' , '')
+ unitx.setLabel('beta', '')
+ unity.setLabel('sigma', '')
else:
if name[:4] == 'Beta':
- unitx.setLabel('beta' , '')
+ unitx.setLabel('beta', '')
else:
unitx.setLabel('sigma', '')
@@ -314,7 +317,7 @@ class BayesStretch(PythonAlgorithm):
energy_min, energy_max = erange
log_names = ['res_file', 'background', 'elastic_peak',
- 'energy_min', 'energy_max','sample_binning']
+ 'energy_min', 'energy_max', 'sample_binning']
log_values = [self._res_name, str(self._background), str(self._elastic),
energy_min, energy_max, sample_binning]
@@ -322,7 +325,7 @@ class BayesStretch(PythonAlgorithm):
add_log.setProperty('Workspace', workspace)
add_log.setProperty('LogNames', log_names)
add_log.setProperty('LogValues', log_values)
- add_log.setProperty('ParseType', True) # Should determine String/Number type
+ add_log.setProperty('ParseType', True) # Should determine String/Number type
add_log.execute()
def _get_properties(self):
@@ -343,4 +346,4 @@ class BayesStretch(PythonAlgorithm):
self._nbins = [self._sam_bins, 1]
-AlgorithmFactory.subscribe(BayesStretch) # Register algorithm with Mantid
+AlgorithmFactory.subscribe(BayesStretch) # Register algorithm with Mantid
diff --git a/Framework/PythonInterface/plugins/algorithms/dnsdata.py b/Framework/PythonInterface/plugins/algorithms/dnsdata.py
index 667e20f8dad35ad44a79cf461bb5d73d0712cf68..c94073886c40873816d95c1fb47c9985f266993c 100644
--- a/Framework/PythonInterface/plugins/algorithms/dnsdata.py
+++ b/Framework/PythonInterface/plugins/algorithms/dnsdata.py
@@ -1,7 +1,7 @@
# pylint: disable=too-many-instance-attributes,too-few-public-methods
from __future__ import (absolute_import, division, print_function)
import re
-import datetime
+from dateutil.parser import parse
class DNSdata(object):
@@ -182,11 +182,14 @@ class DNSdata(object):
if self.tof_channel_number > 1:
self.tof_channel_width = float(b6splitted[3].split()[3])
self.tof_delay_time = float(b6splitted[4].split()[2])
- self.tof_elastic_channel = int(b6splitted[6].split()[3])
+ if len(b6splitted[6].split()) > 3:
+ self.tof_elastic_channel = int(b6splitted[6].split()[3])
# chopper rotation speed
- self.chopper_rotation_speed = float(b6splitted[7].split()[2])
+ if len(b6splitted[7].split()) > 2:
+ self.chopper_rotation_speed = float(b6splitted[7].split()[2])
# chopper number of slits
- self.chopper_slits = int(b6splitted[5].split()[2])
+ if len(b6splitted[5].split()) > 2:
+ self.chopper_slits = int(b6splitted[5].split()[2])
# parse block 7 (Time and monitor)
# assume everything to be at the fixed positions
@@ -203,11 +206,9 @@ class DNSdata(object):
self.monitor_counts = int(line[1])
# start_time and end_time (if specified)
outfmt = "%Y-%m-%dT%H:%M:%S"
- sinfmt = "start at %a %b %d %H:%M:%S %Y"
- einfmt = "stopped at %a %b %d %H:%M:%S %Y"
try:
- self.start_time = datetime.datetime.strptime(b7splitted[5], sinfmt).strftime(outfmt)
- self.end_time = datetime.datetime.strptime(b7splitted[6], einfmt).strftime(outfmt)
+ self.start_time = parse(b7splitted[5][10:].strip()).strftime(outfmt)
+ self.end_time = parse(b7splitted[6][10:].strip()).strftime(outfmt)
except ValueError:
# if start and end time are not given, let them empty
pass
diff --git a/Framework/PythonInterface/test/python/plugins/algorithms/LoadDNSLegacyTest.py b/Framework/PythonInterface/test/python/plugins/algorithms/LoadDNSLegacyTest.py
index 059b81760cd61e57d5fae6d26fccccb8525afdf5..e82f2ead43cc8554d74cb51eed0edc608d5f1a66 100644
--- a/Framework/PythonInterface/test/python/plugins/algorithms/LoadDNSLegacyTest.py
+++ b/Framework/PythonInterface/test/python/plugins/algorithms/LoadDNSLegacyTest.py
@@ -36,7 +36,7 @@ class LoadDNSLegacyTest(unittest.TestCase):
self.assertEqual(-8.54, run.getProperty('deterota').value)
self.assertEqual(8332872, run.getProperty('mon_sum').value)
self.assertEqual('z', run.getProperty('polarisation').value)
- self.assertEqual('7', run.getProperty('polarisation_comment').value)
+ self.assertEqual('7', str(run.getProperty('polarisation_comment').value))
self.assertEqual('no', run.getProperty('normalized').value)
# check whether detector bank is rotated
det = ws.getDetector(0)
@@ -128,5 +128,64 @@ class LoadDNSLegacyTest(unittest.TestCase):
run_algorithm("DeleteWorkspace", Workspace=outputWorkspaceName)
return
+ def test_LoadNoCurtable(self):
+ outputWorkspaceName = "LoadDNSLegacyTest_Test6"
+ filename = "dn134011vana.d_dat"
+ alg_test = run_algorithm("LoadDNSLegacy", Filename=filename, Normalization='no',
+ OutputWorkspace=outputWorkspaceName)
+ self.assertTrue(alg_test.isExecuted())
+
+ # Verify some values
+ ws = AnalysisDataService.retrieve(outputWorkspaceName)
+ # dimensions
+ self.assertEqual(24, ws.getNumberHistograms())
+ self.assertEqual(2, ws.getNumDims())
+ # data array
+ self.assertEqual(31461, ws.readY(1))
+ self.assertEqual(13340, ws.readY(23))
+ # sample logs
+ run = ws.getRun()
+ self.assertEqual(-8.54, run.getProperty('deterota').value)
+ self.assertEqual(8332872, run.getProperty('mon_sum').value)
+ self.assertEqual('z', run.getProperty('polarisation').value)
+ self.assertEqual('7', str(run.getProperty('polarisation_comment').value))
+ self.assertEqual('no', run.getProperty('normalized').value)
+ # check whether detector bank is rotated
+ det = ws.getDetector(0)
+ self.assertAlmostEqual(8.54, ws.detectorSignedTwoTheta(det)*180/pi)
+ run_algorithm("DeleteWorkspace", Workspace=outputWorkspaceName)
+ return
+
+ def test_LoadTOF(self):
+ outputWorkspaceName = "LoadDNSLegacyTest_Test7"
+ filename = "dnstof.d_dat"
+ tof1 = 385.651 # must be changed if L1 will change
+ alg_test = run_algorithm("LoadDNSLegacy", Filename=filename, Normalization='no',
+ OutputWorkspace=outputWorkspaceName)
+ self.assertTrue(alg_test.isExecuted())
+
+ # Verify some values
+ ws = AnalysisDataService.retrieve(outputWorkspaceName)
+ # dimensions
+ self.assertEqual(24, ws.getNumberHistograms())
+ self.assertEqual(100, ws.getNumberBins())
+ # data array
+ self.assertEqual(1, ws.readY(19)[5])
+ self.assertAlmostEqual(tof1, ws.readX(0)[0], 3)
+ self.assertAlmostEqual(tof1+802.0*100, ws.readX(0)[100], 3)
+ # sample logs
+ run = ws.getRun()
+ self.assertEqual(-7.5, run.getProperty('deterota').value)
+ self.assertEqual(100, run.getProperty('tof_channels').value)
+ self.assertEqual(51428, run.getProperty('mon_sum').value)
+ self.assertEqual('z', run.getProperty('polarisation').value)
+ self.assertEqual('7', str(run.getProperty('polarisation_comment').value))
+ self.assertEqual('no', run.getProperty('normalized').value)
+ # check whether detector bank is rotated
+ det = ws.getDetector(0)
+ self.assertAlmostEqual(7.5, ws.detectorSignedTwoTheta(det)*180/pi)
+ run_algorithm("DeleteWorkspace", Workspace=outputWorkspaceName)
+ return
+
if __name__ == '__main__':
unittest.main()
diff --git a/MantidPlot/src/ApplicationWindow.cpp b/MantidPlot/src/ApplicationWindow.cpp
index e04dcb5b389be8c1935bebf389a044fb94893fd6..7e25c17a310391517283cabd4359233bd320e6c4 100644
--- a/MantidPlot/src/ApplicationWindow.cpp
+++ b/MantidPlot/src/ApplicationWindow.cpp
@@ -6051,7 +6051,7 @@ bool ApplicationWindow::saveProject(bool compress) {
return true;
}
-void ApplicationWindow::prepareSaveProject() {
+int ApplicationWindow::execSaveProjectDialog() {
std::vector<IProjectSerialisable *> windows;
for (auto window : getSerialisableWindows()) {
@@ -6071,9 +6071,11 @@ void ApplicationWindow::prepareSaveProject() {
projectname, *serialiser, windows, this);
connect(m_projectSaveView, SIGNAL(projectSaved()), this,
SLOT(postSaveProject()));
- m_projectSaveView->show();
+ return m_projectSaveView->exec();
}
+void ApplicationWindow::prepareSaveProject() { execSaveProjectDialog(); }
+
/**
* The project was just saved. Update the main window.
*/
@@ -9175,32 +9177,6 @@ void ApplicationWindow::closeWindow(MdiSubWindow *window) {
emit modified();
}
-/**
- * Called when the user choses to close the program
- */
-void ApplicationWindow::prepareToCloseMantid() {
- if (!saved) {
- QString savemsg =
- tr("Save changes to project: <p><b> %1 </b> ?").arg(projectname);
- int result =
- QMessageBox::information(this, tr("MantidPlot"), savemsg, tr("Yes"),
- tr("No"), tr("Cancel"), 0, 2);
- if (result == 0) {
- prepareSaveProject();
- // When we're finished saving trigger the close event
- connect(m_projectSaveView, SIGNAL(finished(int)), qApp,
- SLOT(closeAllWindows()));
- return;
- } else if (result == 2) {
- // User wanted to cancel, do nothing
- return;
- }
- }
-
- // Call to close all the windows and shutdown Mantid
- QApplication::closeAllWindows();
-}
-
/** Add a serialisable window to the application
* @param window :: the window to add
*/
@@ -9809,6 +9785,25 @@ void ApplicationWindow::closeEvent(QCloseEvent *ce) {
// script is running.
}
+ if (!saved) {
+ QString savemsg =
+ tr("Save changes to project: <p><b> %1 </b> ?").arg(projectname);
+ int result =
+ QMessageBox::information(this, tr("MantidPlot"), savemsg, tr("Yes"),
+ tr("No"), tr("Cancel"), 0, 2);
+ if (result == 0) {
+ auto response = execSaveProjectDialog();
+ if (response != QDialog::Accepted) {
+ ce->ignore();
+ return;
+ }
+ } else if (result == 2) {
+ // User wanted to cancel, do nothing
+ ce->ignore();
+ return;
+ }
+ }
+
// Close the remaining MDI windows. The Python API is required to be active
// when the MDI window destructor is called so that those references can be
// cleaned up meaning we cannot rely on the deleteLater functionality to
@@ -9851,6 +9846,7 @@ void ApplicationWindow::closeEvent(QCloseEvent *ce) {
scriptingEnv()->finalize();
ce->accept();
+ qApp->closeAllWindows();
}
void ApplicationWindow::customEvent(QEvent *e) {
@@ -11821,8 +11817,7 @@ void ApplicationWindow::createActions() {
actionCloseAllWindows = new MantidQt::MantidWidgets::TrackedAction(
QIcon(getQPixmap("quit_xpm")), tr("&Quit"), this);
actionCloseAllWindows->setShortcut(tr("Ctrl+Q"));
- connect(actionCloseAllWindows, SIGNAL(triggered()), this,
- SLOT(prepareToCloseMantid()));
+ connect(actionCloseAllWindows, SIGNAL(triggered()), this, SLOT(close()));
actionDeleteFitTables = new MantidQt::MantidWidgets::TrackedAction(
QIcon(getQPixmap("close_xpm")), tr("Delete &Fit Tables"), this);
diff --git a/MantidPlot/src/ApplicationWindow.h b/MantidPlot/src/ApplicationWindow.h
index b1a274f27167744bc8b52030723fbb7775f4f6a6..6cacd88828e1dc32670559761869eaad20147d62 100644
--- a/MantidPlot/src/ApplicationWindow.h
+++ b/MantidPlot/src/ApplicationWindow.h
@@ -270,6 +270,8 @@ public slots:
void saveProjectAs(const QString &fileName = QString(),
bool compress = false);
bool saveProject(bool compress = false);
+ /// Run the project saver dialog
+ int execSaveProjectDialog();
/// Show the project saver dialog
void prepareSaveProject();
/// Update application window post save
@@ -603,7 +605,6 @@ public slots:
void closeActiveWindow();
void closeSimilarWindows();
void closeWindow(MdiSubWindow *window);
- void prepareToCloseMantid();
//! Does all the cleaning work before actually deleting a window!
void removeWindowFromLists(MdiSubWindow *w);
diff --git a/MantidPlot/src/ProjectSaveView.cpp b/MantidPlot/src/ProjectSaveView.cpp
index 5fe91179c2f067538859bb00e7416fea694ad113..74b030c511d3179978d067016775d01cf90256b1 100644
--- a/MantidPlot/src/ProjectSaveView.cpp
+++ b/MantidPlot/src/ProjectSaveView.cpp
@@ -205,6 +205,9 @@ void ProjectSaveView::save(bool checked) {
emit projectSaved();
close();
+ // Set the result code after calling close() because
+ // close() sets it to QDialog::Rejected
+ setResult(QDialog::Accepted);
}
/**
diff --git a/MantidPlot/test/squish_test_suites/refl_gui_tests/objects.map b/MantidPlot/test/squish_test_suites/refl_gui_tests/objects.map
index 768666ead13d4203ac6daba99d8f84c7bfbdc29e..00d8574e329ff5e80a884411875b6a779db9b9a7 100644
--- a/MantidPlot/test/squish_test_suites/refl_gui_tests/objects.map
+++ b/MantidPlot/test/squish_test_suites/refl_gui_tests/objects.map
@@ -2,6 +2,8 @@
:2_HeaderViewItem {container=':tableMain_QHeaderView' text='2' type='HeaderViewItem'}
:Discard_QPushButton {text='Discard' type='QPushButton' unnamed='1' visible='1' window=':_QMessageBox_2'}
:Don't Save_QPushButton {text='Don\\'t Save' type='QPushButton' unnamed='1' visible='1' window=':_QMessageBox_2'}
+:ISIS Reflectometry (Old).splitterList_QSplitter {name='splitterList' type='QSplitter' visible='1' window=':ISIS Reflectometry (Old)_ReflGui'}
+:ISIS Reflectometry (Old)_ReflGui {name='windowRefl' type='ReflGui' visible='1' windowTitle='ISIS Reflectometry (Old)'}
:ISIS Reflectometry.File_QMenu {name='menuFile' title='File' type='QMenu' visible='1' window=':ISIS Reflectometry_ReflGui'}
:ISIS Reflectometry.Instrument:_QLabel {name='labelInstrument' text='Instrument:' type='QLabel' visible='1' window=':ISIS Reflectometry_ReflGui'}
:ISIS Reflectometry.menuBar_QMenuBar {name='menuBar' type='QMenuBar' visible='1' window=':ISIS Reflectometry_ReflGui'}
@@ -24,11 +26,13 @@
:_QMessageBox_2 {type='QMessageBox' unnamed='1' visible='1'}
:comboInstrument_QComboBox {buddy=':ISIS Reflectometry.Instrument:_QLabel' name='comboInstrument' type='QComboBox' visible='1'}
:splitterList.Process_QPushButton {container=':ISIS Reflectometry.splitterList_QSplitter' name='buttonProcess' text='Process' type='QPushButton' visible='1'}
+:splitterList.buttonProcess_QPushButton {container=':ISIS Reflectometry (Old).splitterList_QSplitter' name='buttonProcess' text='Process' type='QPushButton' visible='1'}
:splitterList.tableMain_QTableWidget {container=':ISIS Reflectometry.splitterList_QSplitter' name='tableMain' type='QTableWidget' visible='1'}
+:splitterList.tableMain_QTableWidget_2 {container=':ISIS Reflectometry (Old).splitterList_QSplitter' name='tableMain' type='QTableWidget' visible='1'}
:splitterList.widgetBottomRight_QWidget {container=':ISIS Reflectometry.splitterList_QSplitter' name='widgetBottomRight' type='QWidget' visible='1'}
-:tableMain.Plot_QPushButton {container=':splitterList.tableMain_QTableWidget' text='Plot' type='QPushButton' unnamed='1' visible='1'}
-:tableMain.Yes_QPushButton {container=':splitterList.tableMain_QTableWidget' text='Yes' type='QPushButton' unnamed='1' visible='1'}
-:tableMain_QCheckBox {container=':splitterList.tableMain_QTableWidget' type='QCheckBox' unnamed='1' visible='1'}
+:tableMain.Plot_QPushButton {container=':splitterList.tableMain_QTableWidget_2' text='Plot' type='QPushButton' unnamed='1' visible='1'}
+:tableMain.Yes_QPushButton {container=':splitterList.tableMain_QTableWidget_2' text='Yes' type='QPushButton' unnamed='1' visible='1'}
+:tableMain_QCheckBox {container=':splitterList.tableMain_QTableWidget_2' type='QCheckBox' unnamed='1' visible='1'}
:tableMain_QExpandingLineEdit {columnIndex='0' container=':splitterList.tableMain_QTableWidget' rowIndex='0' type='QExpandingLineEdit' unnamed='1' visible='1'}
:tableMain_QExpandingLineEdit_2 {columnIndex='1' container=':splitterList.tableMain_QTableWidget' rowIndex='0' type='QExpandingLineEdit' unnamed='1' visible='1'}
:tableMain_QExpandingLineEdit_3 {columnIndex='2' container=':splitterList.tableMain_QTableWidget' rowIndex='0' type='QExpandingLineEdit' unnamed='1' visible='1'}
diff --git a/MantidQt/API/inc/MantidQtAPI/MantidQwtWorkspaceData.h b/MantidQt/API/inc/MantidQtAPI/MantidQwtWorkspaceData.h
index e6bf6801417f5c9f6c15a986d3d620ea57fd6feb..19aa809d348090bce5cab7de862e357b3613aa2c 100644
--- a/MantidQt/API/inc/MantidQtAPI/MantidQwtWorkspaceData.h
+++ b/MantidQt/API/inc/MantidQtAPI/MantidQwtWorkspaceData.h
@@ -53,19 +53,19 @@ public:
virtual size_t esize() const;
virtual double e(size_t i) const;
virtual double ex(size_t i) const;
+ bool isPlottable() const;
virtual void setLogScaleY(bool on);
virtual bool logScaleY() const;
- virtual void saveLowestPositiveValue(const double v);
+ void setMinimumPositiveValue(const double v);
virtual double getYMin() const;
virtual double getYMax() const;
-
virtual void setXOffset(const double x);
virtual void setYOffset(const double y);
virtual void setWaterfallPlot(bool on);
virtual bool isWaterfallPlot() const;
double offsetY() const { return m_offsetY; }
- void calculateYMinAndMax(/*const std::vector<double> &yvalues*/) const;
+ void calculateYMinAndMax() const;
protected:
virtual double getX(size_t i) const = 0;
@@ -74,6 +74,8 @@ protected:
virtual double getEX(size_t i) const = 0;
private:
+ enum class DataStatus : uint8_t { Undefined, NotPlottable, Plottable };
+
/// Indicates that the data is plotted on a log y scale
bool m_logScaleY;
@@ -86,6 +88,9 @@ private:
/// highest y value
mutable double m_maxY;
+ /// True if data is 'sensible' to plot
+ mutable DataStatus m_plottable;
+
/// Indicates whether or not waterfall plots are enabled
bool m_isWaterfall;
diff --git a/MantidQt/API/inc/MantidQtAPI/QwtWorkspaceSpectrumData.h b/MantidQt/API/inc/MantidQtAPI/QwtWorkspaceSpectrumData.h
index 9bd9e55162297634c93ba61e80c935cfc13b7ca3..271e2ab4fc530ff9837e451e0d531003e4db5f42 100644
--- a/MantidQt/API/inc/MantidQtAPI/QwtWorkspaceSpectrumData.h
+++ b/MantidQt/API/inc/MantidQtAPI/QwtWorkspaceSpectrumData.h
@@ -51,8 +51,6 @@ public:
/// Number of error bars to plot
size_t esize() const override;
- // double getYMin() const override;
- // double getYMax() const override;
/// Return the label to use for the X axis
QString getXAxisLabel() const override;
/// Return the label to use for the Y axis
@@ -61,17 +59,8 @@ public:
bool isHistogram() const { return m_isHistogram; }
bool dataIsNormalized() const { return m_dataIsNormalized; }
- ///// Inform the data that it is to be plotted on a log y scale
- // void setLogScale(bool on) override;
- // bool logScaleY() const override { return m_logScaleY; }
- // void saveLowestPositiveValue(const double v) override;
bool setAsDistribution(bool on = true);
- //// Sets offsets for and enables waterfall plots
- // void setXOffset(const double x) override;
- // void setYOffset(const double y) override;
- // void setWaterfallPlot(bool on) override;
-
protected:
// Assignment operator (virtualized). MSVC not happy with compiler generated
// one
diff --git a/MantidQt/API/src/MantidQwtIMDWorkspaceData.cpp b/MantidQt/API/src/MantidQwtIMDWorkspaceData.cpp
index 076e3c3a3ace055eddecc9f4587f117d5206d99c..04eabd9041b3abfb26d2410cd82d44eafac7b12d 100644
--- a/MantidQt/API/src/MantidQwtIMDWorkspaceData.cpp
+++ b/MantidQt/API/src/MantidQwtIMDWorkspaceData.cpp
@@ -159,7 +159,12 @@ void MantidQwtIMDWorkspaceData::calculateMinMax() { calculateYMinAndMax(); }
//-----------------------------------------------------------------------------
/** Size of the data set
*/
-size_t MantidQwtIMDWorkspaceData::size() const { return m_Y.size(); }
+size_t MantidQwtIMDWorkspaceData::size() const {
+ if (!isPlottable()) {
+ return 0;
+ }
+ return m_Y.size();
+}
/** Return the x value of data point i
@param i :: Index
@@ -199,7 +204,12 @@ double MantidQwtIMDWorkspaceData::getEX(size_t i) const {
double MantidQwtIMDWorkspaceData::getE(size_t i) const { return m_E[i]; }
/// Number of error bars to plot
-size_t MantidQwtIMDWorkspaceData::esize() const { return m_E.size(); }
+size_t MantidQwtIMDWorkspaceData::esize() const {
+ if (!isPlottable()) {
+ return 0;
+ }
+ return m_E.size();
+}
bool MantidQwtIMDWorkspaceData::setAsDistribution(bool on) {
m_isDistribution = on;
diff --git a/MantidQt/API/src/MantidQwtWorkspaceData.cpp b/MantidQt/API/src/MantidQwtWorkspaceData.cpp
index 7e450ded1b99a6fb408bb78a1a5b13fd22d9efe4..0913a30986af6adf4e9d347b5ab9449bd919d693 100644
--- a/MantidQt/API/src/MantidQwtWorkspaceData.cpp
+++ b/MantidQt/API/src/MantidQwtWorkspaceData.cpp
@@ -2,9 +2,19 @@
#include <cmath>
+namespace {
+/// Minimum value considered positive
+constexpr double MIN_POSITIVE = 1e-3;
+/// Maximum value considered positive
+constexpr double MAX_POSITIVE = 1e30;
+/// Arbitrary multiplier between min/max if they are equal
+constexpr double MIN_MAX_DELTA = 1.001;
+}
+
MantidQwtWorkspaceData::MantidQwtWorkspaceData(bool logScaleY)
: m_logScaleY(logScaleY), m_minY(0), m_minPositive(0), m_maxY(0),
- m_isWaterfall(false), m_offsetX(0), m_offsetY(0) {}
+ m_plottable(DataStatus::Undefined), m_isWaterfall(false), m_offsetX(0),
+ m_offsetY(0) {}
MantidQwtWorkspaceData::MantidQwtWorkspaceData(
const MantidQwtWorkspaceData &data) {
@@ -18,6 +28,7 @@ operator=(const MantidQwtWorkspaceData &data) {
m_minY = data.m_minY;
m_minPositive = data.m_minPositive;
m_maxY = data.m_maxY;
+ m_plottable = data.m_plottable;
m_isWaterfall = data.m_isWaterfall;
m_offsetX = data.m_offsetX;
m_offsetY = data.m_offsetY;
@@ -27,11 +38,16 @@ operator=(const MantidQwtWorkspaceData &data) {
/// Calculate absolute minimum and maximum values in a vector. Also find the
/// smallest positive value.
void MantidQwtWorkspaceData::calculateYMinAndMax() const {
-
- const double maxDouble = std::numeric_limits<double>::max();
- double curMin = maxDouble;
- double curMinPos = maxDouble;
- double curMax = -maxDouble;
+ // Set this to true to get the "real" data size
+ // It's correct value is then recalculated below. This is not
+ // too nice but a big refactor is not worth it given the new
+ // workbench/plotting developments.
+ m_plottable = DataStatus::Plottable;
+ m_minY = m_maxY = m_minPositive = 0.0;
+
+ double ymin(std::numeric_limits<double>::max()),
+ ymax(-std::numeric_limits<double>::max()),
+ yminPos(std::numeric_limits<double>::max());
for (size_t i = 0; i < size(); ++i) {
auto val = y(i);
// skip NaNs
@@ -39,41 +55,47 @@ void MantidQwtWorkspaceData::calculateYMinAndMax() const {
continue;
// Update our values as appropriate
- if (val < curMin)
- curMin = val;
- if (val < curMinPos && val > 0)
- curMinPos = val;
- if (val > curMax)
- curMax = val;
- }
-
- // Save the results
- if (curMin == maxDouble) {
- m_minY = 0.0;
- m_minPositive = 0.1;
- m_maxY = 1.0;
- return;
- } else {
- m_minY = curMin;
- }
-
- if (curMax == curMin) {
- curMax *= 1.1;
+ if (val < ymin)
+ ymin = val;
+ if (val > 0.0 && val < yminPos)
+ yminPos = val;
+ if (val > ymax)
+ ymax = val;
}
- m_maxY = curMax;
- if (curMinPos == maxDouble) {
- m_minPositive = 0.1;
+ if (ymin < std::numeric_limits<double>::max()) {
+ // Values are sensible range
+ m_minY = ymin;
+ // Ensure there is a difference beteween max and min
+ m_maxY = (ymax != ymin) ? ymax : ymin * MIN_MAX_DELTA;
+
+ // Minimum positive value is kept for log scales
+ if (yminPos < std::numeric_limits<double>::max()) {
+ m_minPositive = yminPos;
+ m_plottable = DataStatus::Plottable;
+ } else {
+ // All values are <= 0
+ m_minPositive = MIN_POSITIVE;
+ m_plottable =
+ logScaleY() ? DataStatus::NotPlottable : DataStatus::Plottable;
+ }
} else {
- m_minPositive = curMinPos;
+ // Set to arbitrary values (this is unlikely to happen)
+ m_minY = 0.0;
+ m_maxY = MAX_POSITIVE;
+ m_minPositive = MIN_POSITIVE;
+ m_plottable = DataStatus::NotPlottable;
}
}
-void MantidQwtWorkspaceData::setLogScaleY(bool on) { m_logScaleY = on; }
+void MantidQwtWorkspaceData::setLogScaleY(bool on) {
+ m_logScaleY = on;
+ calculateYMinAndMax();
+}
bool MantidQwtWorkspaceData::logScaleY() const { return m_logScaleY; }
-void MantidQwtWorkspaceData::saveLowestPositiveValue(const double v) {
+void MantidQwtWorkspaceData::setMinimumPositiveValue(const double v) {
if (v > 0)
m_minPositive = v;
}
@@ -91,7 +113,7 @@ bool MantidQwtWorkspaceData::isWaterfallPlot() const { return m_isWaterfall; }
* @return the lowest y value.
*/
double MantidQwtWorkspaceData::getYMin() const {
- if (m_minPositive == 0.0) {
+ if (m_plottable == DataStatus::Undefined) {
calculateYMinAndMax();
}
return m_logScaleY ? m_minPositive : m_minY;
@@ -102,7 +124,7 @@ double MantidQwtWorkspaceData::getYMin() const {
* @return the highest y value.
*/
double MantidQwtWorkspaceData::getYMax() const {
- if (m_minPositive == 0.0) {
+ if (m_plottable == DataStatus::Undefined) {
calculateYMinAndMax();
}
if (m_logScaleY && m_maxY <= 0)
@@ -121,7 +143,12 @@ double MantidQwtWorkspaceData::y(size_t i) const {
return tmp;
}
-size_t MantidQwtWorkspaceData::esize() const { return this->size(); }
+size_t MantidQwtWorkspaceData::esize() const {
+ if (!isPlottable()) {
+ return 0;
+ }
+ return this->size();
+}
double MantidQwtWorkspaceData::e(size_t i) const {
double ei = getE(i);
@@ -137,5 +164,19 @@ double MantidQwtWorkspaceData::e(size_t i) const {
double MantidQwtWorkspaceData::ex(size_t i) const { return getEX(i); }
+/**
+ * @brief MantidQwtWorkspaceData::isPlottable
+ * Data is considered plottable if either:
+ * - scale != log or
+ * - scale == log & all(y) > 0.0
+ * @return True if the data is considered plottable, false otherwise
+ */
+bool MantidQwtWorkspaceData::isPlottable() const {
+ return (m_plottable == DataStatus::Plottable);
+}
+
+//------------------------------------------------------------------------------
+// MantidQwtMatrixWorkspaceData class
+//------------------------------------------------------------------------------
MantidQwtMatrixWorkspaceData::MantidQwtMatrixWorkspaceData(bool logScaleY)
: MantidQwtWorkspaceData(logScaleY) {}
diff --git a/MantidQt/API/src/QwtWorkspaceBinData.cpp b/MantidQt/API/src/QwtWorkspaceBinData.cpp
index 1408a915bf058796e1eab73bbab25a4042fc90eb..fff267417f87ed37bc4f7df67df7fe0566875c70 100644
--- a/MantidQt/API/src/QwtWorkspaceBinData.cpp
+++ b/MantidQt/API/src/QwtWorkspaceBinData.cpp
@@ -32,7 +32,12 @@ QwtWorkspaceBinData *QwtWorkspaceBinData::copyWithNewSource(
/** Size of the data set
*/
-size_t QwtWorkspaceBinData::size() const { return m_Y.size(); }
+size_t QwtWorkspaceBinData::size() const {
+ if (!isPlottable()) {
+ return 0;
+ }
+ return m_Y.size();
+}
/**
Return the x value of data point i
@@ -71,7 +76,6 @@ QString QwtWorkspaceBinData::getYAxisLabel() const { return m_yTitle; }
QwtWorkspaceBinData &QwtWorkspaceBinData::
operator=(const QwtWorkspaceBinData &rhs) {
if (this != &rhs) {
- static_cast<MantidQwtMatrixWorkspaceData &>(*this) = rhs;
m_binIndex = rhs.m_binIndex;
m_X = rhs.m_X;
m_Y = rhs.m_Y;
diff --git a/MantidQt/API/src/QwtWorkspaceSpectrumData.cpp b/MantidQt/API/src/QwtWorkspaceSpectrumData.cpp
index 1c1af2e4584898088869fbac26698cdae9117657..b0f92cfd1bd488120eabcd74f9b71a9d3a473179 100644
--- a/MantidQt/API/src/QwtWorkspaceSpectrumData.cpp
+++ b/MantidQt/API/src/QwtWorkspaceSpectrumData.cpp
@@ -53,6 +53,9 @@ QwtWorkspaceSpectrumData *QwtWorkspaceSpectrumData::copyWithNewSource(
/** Size of the data set
*/
size_t QwtWorkspaceSpectrumData::size() const {
+ if (!isPlottable()) {
+ return 0;
+ }
if (m_binCentres || m_isHistogram) {
return m_Y.size();
}
@@ -94,7 +97,12 @@ double QwtWorkspaceSpectrumData::getE(size_t i) const {
return ei;
}
-size_t QwtWorkspaceSpectrumData::esize() const { return m_E.size(); }
+size_t QwtWorkspaceSpectrumData::esize() const {
+ if (!isPlottable()) {
+ return 0;
+ }
+ return m_E.size();
+}
/**
* @return A string containin the text to use as an X axis label
@@ -121,7 +129,6 @@ bool QwtWorkspaceSpectrumData::setAsDistribution(bool on) {
QwtWorkspaceSpectrumData &QwtWorkspaceSpectrumData::
operator=(const QwtWorkspaceSpectrumData &rhs) {
if (this != &rhs) {
- static_cast<MantidQwtMatrixWorkspaceData &>(*this) = rhs;
m_wsIndex = rhs.m_wsIndex;
m_X = rhs.m_X;
m_Y = rhs.m_Y;
diff --git a/MantidQt/CustomInterfaces/src/Indirect/IndirectDiffractionReduction.cpp b/MantidQt/CustomInterfaces/src/Indirect/IndirectDiffractionReduction.cpp
index 08dc707c1441ec441e735c6b4180fe5396e7851d..07c65385b2aea9e7a8a8283d555b97eb132a730f 100644
--- a/MantidQt/CustomInterfaces/src/Indirect/IndirectDiffractionReduction.cpp
+++ b/MantidQt/CustomInterfaces/src/Indirect/IndirectDiffractionReduction.cpp
@@ -191,8 +191,7 @@ void IndirectDiffractionReduction::plotResults() {
const auto workspaceExists =
AnalysisDataService::Instance().doesExist(it);
if (workspaceExists)
- pyInput += "plotSpectrum('" + QString::fromStdString(it) +
- "', 0, error_bars = True)\n";
+ pyInput += "plotSpectrum('" + QString::fromStdString(it) + "', 0)\n";
else
showInformationBox(QString::fromStdString(
"Workspace '" + it + "' not found\nUnable to plot workspace"));
diff --git a/MantidQt/CustomInterfaces/src/Indirect/IndirectTab.cpp b/MantidQt/CustomInterfaces/src/Indirect/IndirectTab.cpp
index 6137629fa50bfd24b3072c238fbf5493789322e0..011e992ca85117dca7e1a6f447fdcccaa065b9eb 100644
--- a/MantidQt/CustomInterfaces/src/Indirect/IndirectTab.cpp
+++ b/MantidQt/CustomInterfaces/src/Indirect/IndirectTab.cpp
@@ -259,7 +259,7 @@ void IndirectTab::plotSpectrum(const QStringList &workspaceNames, int wsIndex) {
pyInput += workspaceNames.join("','");
pyInput += "'], ";
pyInput += QString::number(wsIndex);
- pyInput += ", error_bars = True)\n";
+ pyInput += ")\n";
m_pythonRunner.runPythonCode(pyInput);
}
@@ -303,7 +303,7 @@ void IndirectTab::plotSpectrum(const QStringList &workspaceNames, int specStart,
pyInput += QString::number(specStart);
pyInput += ",";
pyInput += QString::number(specEnd + 1);
- pyInput += ")), error_bars = True)\n";
+ pyInput += ")))\n";
m_pythonRunner.runPythonCode(pyInput);
}
@@ -355,7 +355,7 @@ void IndirectTab::plotSpectra(const QStringList &workspaceNames,
pyInput += " ,";
pyInput += QString::number(wsIndices[i]);
}
- pyInput += "], error_bars = True)\n";
+ pyInput += "])\n";
m_pythonRunner.runPythonCode(pyInput);
}
@@ -418,7 +418,7 @@ void IndirectTab::plotTimeBin(const QStringList &workspaceNames, int binIndex) {
pyInput += workspaceNames.join("','");
pyInput += "'], ";
pyInput += QString::number(binIndex);
- pyInput += ", error_bars=True)\n";
+ pyInput += ")\n";
m_pythonRunner.runPythonCode(pyInput);
}
diff --git a/MantidQt/SliceViewer/src/LineViewer.cpp b/MantidQt/SliceViewer/src/LineViewer.cpp
index 3b7d28000928484e72d73d69fffbbe82844d12f2..096773b0bc82799134d17fab47578233b0a8e04f 100644
--- a/MantidQt/SliceViewer/src/LineViewer.cpp
+++ b/MantidQt/SliceViewer/src/LineViewer.cpp
@@ -1027,7 +1027,7 @@ void LineViewer::setupScaleEngine(MantidQwtWorkspaceData &curveData) {
if (m_lineOptions->isLogScaledY()) {
engine = new QwtLog10ScaleEngine();
- curveData.saveLowestPositiveValue(from);
+ curveData.setMinimumPositiveValue(from);
} else {
engine = new QwtLinearScaleEngine();
}
diff --git a/Testing/Data/UnitTest/dnstof.d_dat.md5 b/Testing/Data/UnitTest/dnstof.d_dat.md5
new file mode 100644
index 0000000000000000000000000000000000000000..9d42867130c1dfa824b80f78cd7bd2f0534e4912
--- /dev/null
+++ b/Testing/Data/UnitTest/dnstof.d_dat.md5
@@ -0,0 +1 @@
+22cfa93c259ea5cc843dd01dec305cd6
diff --git a/docs/source/algorithms/LoadDNSLegacy-v1.rst b/docs/source/algorithms/LoadDNSLegacy-v1.rst
index 96b17ef1347e24281e2c9e7153be137f458cdab7..ebe85d2b41d2bab38e634cc1d4694c7fd83347c1 100644
--- a/docs/source/algorithms/LoadDNSLegacy-v1.rst
+++ b/docs/source/algorithms/LoadDNSLegacy-v1.rst
@@ -14,7 +14,13 @@ Description
This algorithm is being developed for a specific instrument. It might get changed or even
removed without a notification, should instrument scientists decide to do so.
-This algorithm loads a DNS legacy data file into a :ref:`Workspace2D <Workspace2D>`. The loader rotates the detector bank in the position given in the data file.
+This algorithm loads a DNS legacy data file into a :ref:`Workspace2D <Workspace2D>`. The loader rotates the detector bank in the position given in the data file.
+
+**Output**
+
+- For diffraction mode data (only one time channel) output is the :ref:`Workspace2D <Workspace2D>` with the X-axis in the wavelength units.
+
+- For TOF data (more than one time channel) output is the :ref:`Workspace2D <Workspace2D>` with the X-axis in TOF units. The lower bin boundary for the channel :math:`i`, :math:`t_i` is calculated as :math:`t_i = t_1 + t_{delay} + i*\Delta t`, where :math:`\Delta t` is the channel width and :math:`t_1` is the time-of-flight from the source (chopper) to sample. Given in the data file channel width is scaled by the *channel_width_factor* which can be set in the :ref:`parameter file <InstrumentParameterFile>`.
**Normalization**
@@ -28,7 +34,9 @@ The **Normalization** option offers the following choices:
**Polarisation**
-Since polarisation is not specified in the DNS legacy files, coil currents table is required to lookup for the polarisation and set the *polarisation* sample log. The coil currents table is a text file containing the following table.
+Since polarisation is not specified in the DNS legacy files, coil currents table is required to lookup for the polarisation and set the *polarisation* sample log. The default coil currents are given as *x_currents*, *y_currents* and *z_currents* parameters in the :ref:`parameter file <InstrumentParameterFile>` for x, y, and z polarisations, respectively.
+
+Alternatively, the text file with the coil currents table may be provided (optionally). The coil currents table is a text file containing the following table.
+--------------+----------+-------+-------+-------+-------+
| polarisation | comment | C_a | C_b | C_c | C_z |
@@ -42,9 +50,9 @@ Since polarisation is not specified in the DNS legacy files, coil currents table
| x | 7 | 0 | -2.1 | -0.97 | 2.21 |
+--------------+----------+-------+-------+-------+-------+
-First row must contain the listed column headers, other rows contain coil currents for each polarisation. Rows with different currents for one polarisation are alowed. Columns are separated by tab symbols. This table must be provided to the user by instrument scientist.
+First row must contain the listed column headers, other rows contain coil currents for each polarisation. Rows with different currents for one polarisation are alowed. Columns are separated by tab symbols.
-This algorithm only supports DNS instrument in its configuration before major upgrade.
+This algorithm only supports DNS instrument in its configuration with one detector bank (polarisation analysis).
Usage
-----
@@ -55,10 +63,9 @@ Usage
# data file.
datafile = 'dn134011vana.d_dat'
- coilcurrents = 'currents.txt'
# Load dataset
- ws = LoadDNSLegacy(datafile, Normalization='monitor', CoilCurrentsTable=coilcurrents)
+ ws = LoadDNSLegacy(datafile, Normalization='monitor')
print "This workspace has", ws.getNumDims(), "dimensions and has", ws.getNumberHistograms(), "histograms."
diff --git a/docs/source/release/v3.10.0/framework.rst b/docs/source/release/v3.10.0/framework.rst
index e254dafc12828b2087e98cd6e075daed1769e0da..f8a4a13954918cb3a8bd2524906c724c2ff1084b 100644
--- a/docs/source/release/v3.10.0/framework.rst
+++ b/docs/source/release/v3.10.0/framework.rst
@@ -50,6 +50,7 @@ Improved
- Improved parallel scaling of :ref:`MDNormSCD <algm-MDNormSCD>` with > 4 cores.
- Improved parallel scaling of :ref:`MDNormDirectSCD <algm-MDNormDirectSC>` with > 4 cores.
- Reduced execution time of ``EventList::sortTof`` by over 2x, improving performance in algorithms such as :ref:`algm-CompressEvents` and :ref:`algm-SortEvents` which call it.
+- :ref:`LoadDNSLegacy <algm-LoadDNSLegacy-v1>` can now read the TOF data. CoilCurrentsTable is now optional. The default coil currents are now in the instrument parameters file.
- :ref:`LoadNexusProcessed <algm-LoadNexusProcessed>` is now approximately 33x faster when loading a ``PeaksWorkspace`` with a large instrument attached.
Bug Fixes
diff --git a/docs/source/release/v3.10.0/indirect_inelastic.rst b/docs/source/release/v3.10.0/indirect_inelastic.rst
index 3b7dc52115c4719f0cbd57608c9fd9b65bd6d08e..9f30ce2567f652125455324116a25c4a39ac999d 100644
--- a/docs/source/release/v3.10.0/indirect_inelastic.rst
+++ b/docs/source/release/v3.10.0/indirect_inelastic.rst
@@ -55,6 +55,8 @@ Improvements
- OSIRIS diffraction now rebins container workspaces to match the sample workspace
- :ref:`ISISIndirectDiffractionReduction <algm-ISISIndirectDiffractionReduction>` now fully supports VESUVIO data
- Inelastic pixel ID's in BASIS instrument definition file grouped into continuous physical pixels.
+- Added SortXAxis to Bayes Quasi and Stretch
+- Removed error bars as default
Bugfixes
@@ -64,5 +66,6 @@ Bugfixes
- *Abins*: fix setting very small off-diagonal elements of b tensors
- Fix errors from calling Rebin from VisionReduction.
- Fixed validation of inputs in *CalculatePaalmanPings*
+- IN16_Definition.xml has been updated with a Monitor ID change from 19 to 29 to fix a duplicate identity issue
`Full list of changes on GitHub <http://github.com/mantidproject/mantid/pulls?q=is%3Apr+milestone%3A%22Release+3.10%22+is%3Amerged+label%3A%22Component%3A+Indirect+Inelastic%22>`_
diff --git a/docs/source/release/v3.10.0/ui.rst b/docs/source/release/v3.10.0/ui.rst
index f700a2410ee822b2e500cc961b725b836db558f1..3d6aef4d273fd0c23ec9870a42f5d9140ded54b4 100644
--- a/docs/source/release/v3.10.0/ui.rst
+++ b/docs/source/release/v3.10.0/ui.rst
@@ -26,15 +26,19 @@ User Interface
Instrument View
###############
- - Added the ability to visualise peaks generated by :ref:`algm-PredictPeaks` which fall off detectors.
- - Added the ability to zoom out on an unwrapped view.
- - Fixed a bug preventing the some of the banks from being visible when using a U correction.
- - Fixed a bug where pressing delete would delete a workspace even when the dock was not focused.
- - Fixed a bug where the user would not be prompted before deleting workspaces even if confirmations were turned on.
+
+- Added the ability to visualise peaks generated by :ref:`algm-PredictPeaks` which fall off detectors.
+- Added the ability to zoom out on an unwrapped view.
+- Fixed a bug preventing the some of the banks from being visible when using a U correction.
+- Fixed a bug where pressing delete would delete a workspace even when the dock was not focused.
+- Fixed a bug where the user would not be prompted before deleting workspaces even if confirmations were turned on.
Plotting Improvements
#####################
+- Curves where all(Y) <= 0 are now not plotted when the Y-scale is set to logarithmic.
+ The previous behaviour assigned an arbitrary value of 0.1 which was confusing.
+
Algorithm Toolbox
#################
diff --git a/instrument/DNS_Definition_PAonly.xml b/instrument/DNS_Definition_PAonly.xml
index 15fab5107e83e6003b9de06370116d574f8369eb..3cfa615ef75bf0c443ef327bb522c2c331344978 100644
--- a/instrument/DNS_Definition_PAonly.xml
+++ b/instrument/DNS_Definition_PAonly.xml
@@ -16,9 +16,9 @@
<handedness val="right" />
</reference-frame>
</defaults>
- <!-- moderator -->
+ <!-- chopper -->
<component type="moderator">
- <location z="-2.27" />
+ <location z="-0.36325" />
</component>
<type name="moderator" is="Source"></type>
<!-- monitor -->
diff --git a/instrument/DNS_Parameters.xml b/instrument/DNS_Parameters.xml
new file mode 100644
index 0000000000000000000000000000000000000000..f5db344a2b75f0999fd5b13ae306c86f69058a23
--- /dev/null
+++ b/instrument/DNS_Parameters.xml
@@ -0,0 +1,63 @@
+<?xml version="1.0" encoding="UTF-8" ?>
+<parameter-file instrument="DNS" valid-from="2013-10-01T00:00:00">
+
+ <component-link name="DNS">
+
+ <parameter name="deltaE-mode" type="string">
+ <value val="direct" />
+ </parameter>
+
+ <!-- Coil currents Ca, Cb, Cc, Cz to determine the neutron polarisation -->
+ <parameter name="x_currents" type="string">
+ <value val="0,-2,-0.77,-2.21; -0.5,-1.5,-1.2,-2.15" />
+ </parameter>
+ <parameter name="y_currents" type="string">
+ <value val="0,1.60,-2.77,-2.21; 0,-1.4,1.65,-2.15" />
+ </parameter>
+ <parameter name="z_currents" type="string">
+ <value val="0,0.11,-0.5,0; 0,0.15,-0.5,0" />
+ </parameter>
+
+ <!-- Scaling factor to calculate the channel width in microseconds -->
+ <parameter name="channel_width_factor" type="string">
+ <value val="20.0" />
+ </parameter>
+
+ <!-- 2theta tolerance, degrees -->
+ <parameter name="two_theta_tolerance" type="string">
+ <value val="0.1" />
+ </parameter>
+
+ <!-- file suffixes to lookup for the standard data -->
+ <!-- Vanadium -->
+ <parameter name="vana" type="string">
+ <value val="vana"/>
+ </parameter>
+ <!-- NiCr -->
+ <parameter name="nicr" type="string">
+ <value val="nicr"/>
+ </parameter>
+ <!-- Instrument background -->
+ <parameter name="bkg" type="string">
+ <value val="leer"/>
+ </parameter>
+
+ <!-- Normalization workspace name suffix -->
+ <parameter name="normws_suffix" type="string">
+ <value val="_n"/>
+ </parameter>
+
+ <!-- formula for Monitor efficiency calculation. Algorithm: MonitorEfficiencyCorUser -->
+ <parameter name="formula_mon_eff" type="string">
+ <value val="sqrt(e/25.3)" />
+ </parameter>
+
+ <!-- Distance [m] between sample and equatorial line of the detector. Mandatory
+ if you want to correct the flight paths. -->
+ <parameter name="l2" type="string">
+ <value val="0.80" />
+ </parameter>
+
+ </component-link>
+
+</parameter-file>
diff --git a/instrument/IN16_Definition.xml b/instrument/IN16_Definition.xml
index 683e89cfa5591f687757d038d5e82a50a670a6c6..f01387c9644b6fb6605e46a18694bf64ba7a90b8 100644
--- a/instrument/IN16_Definition.xml
+++ b/instrument/IN16_Definition.xml
@@ -66,7 +66,7 @@
</type>
<idlist idname="monitor1">
- <id val="19" />
+ <id val="29" />
</idlist>
<!-- detector components -->
diff --git a/scripts/Diffraction/isis_powder/abstract_inst.py b/scripts/Diffraction/isis_powder/abstract_inst.py
index 57f6b5445641cd514cd3cb2bf6f1e63d619c617d..b79f1764e795c5e3eb0403684a34825f7b6c2801 100644
--- a/scripts/Diffraction/isis_powder/abstract_inst.py
+++ b/scripts/Diffraction/isis_powder/abstract_inst.py
@@ -159,6 +159,15 @@ class AbstractInst(object):
"""
return None
+ def _get_instrument_bin_widths(self):
+ """
+ Returns the bin widths to rebin the focused workspace to. If
+ the instrument does not want this step a value of None should
+ not rebin the workspace
+ :return: List of bin widths or None if no rebinning should take place
+ """
+ return None
+
def _generate_auto_vanadium_calibration(self, run_details):
"""
Used by focus if a vanadium spline was not found to automatically generate said spline if the instrument
diff --git a/scripts/Diffraction/isis_powder/polaris.py b/scripts/Diffraction/isis_powder/polaris.py
index 1f841dd02984d7daf47b279d213ab5c9e5ce0ffb..b365c8ac351448c22ee39980bdfcaa2085c905d7 100644
--- a/scripts/Diffraction/isis_powder/polaris.py
+++ b/scripts/Diffraction/isis_powder/polaris.py
@@ -85,6 +85,9 @@ class Polaris(AbstractInst):
def _get_input_batching_mode(self):
return self._inst_settings.input_mode
+ def _get_instrument_bin_widths(self):
+ return self._inst_settings.focused_bin_widths
+
def _get_run_details(self, run_number_string):
run_number_string_key = run_number_string + str(self._inst_settings.file_extension)
if run_number_string_key in self._run_details_cached_obj:
diff --git a/scripts/Diffraction/isis_powder/polaris_routines/polaris_advanced_config.py b/scripts/Diffraction/isis_powder/polaris_routines/polaris_advanced_config.py
index a083c3580632377bbfd64b1a677c11af91031183..3d30c280b7e84d0dc43ae78b109ebfa2d90e702a 100644
--- a/scripts/Diffraction/isis_powder/polaris_routines/polaris_advanced_config.py
+++ b/scripts/Diffraction/isis_powder/polaris_routines/polaris_advanced_config.py
@@ -30,6 +30,16 @@ focused_cropping_values = [
(1500, 19900), # Bank 5
]
+focused_bin_widths = [
+ # Note you want these to be negative for logarithmic (dt / t) binning
+ # else the output file will be larger than 1GB
+ -0.0050, # Bank 1
+ -0.0010, # Bank 2
+ -0.0010, # Bank 3
+ -0.0010, # Bank 4
+ -0.0005, # Bank 5
+]
+
vanadium_cropping_values = [
(800, 19995), # Bank 1
(800, 19995), # Bank 2
@@ -67,5 +77,6 @@ variables = {
"file_names_dict": file_names,
"script_params": script_params,
"focused_cropping_values": focused_cropping_values,
- "vanadium_cropping_values": vanadium_cropping_values
+ "vanadium_cropping_values": vanadium_cropping_values,
+ "focused_bin_widths": focused_bin_widths,
}
diff --git a/scripts/Diffraction/isis_powder/polaris_routines/polaris_param_mapping.py b/scripts/Diffraction/isis_powder/polaris_routines/polaris_param_mapping.py
index 7a74533c7223f2d088b7fd4ef38b91f0384a2fa0..829a95b2885a72a895bc51994040e6f712a6b188 100644
--- a/scripts/Diffraction/isis_powder/polaris_routines/polaris_param_mapping.py
+++ b/scripts/Diffraction/isis_powder/polaris_routines/polaris_param_mapping.py
@@ -15,6 +15,7 @@ attr_mapping = \
ParamMapEntry(ext_name="file_ext", int_name="file_extension", optional=True),
ParamMapEntry(ext_name="first_cycle_run_no", int_name="run_in_range"),
ParamMapEntry(ext_name="focused_cropping_values", int_name="focused_cropping_values"),
+ ParamMapEntry(ext_name="focused_bin_widths", int_name="focused_bin_widths"),
ParamMapEntry(ext_name="grouping_file_name", int_name="grouping_file_name"),
ParamMapEntry(ext_name="input_mode", int_name="input_mode", enum_class=INPUT_BATCHING),
ParamMapEntry(ext_name="masking_file_name", int_name="masking_file_name"),
diff --git a/scripts/Diffraction/isis_powder/routines/common.py b/scripts/Diffraction/isis_powder/routines/common.py
index 8f819e0bd395f4e9e12a6e556433328a9c1cab38..b5743646a58d32f065c5811a2c4513d58707baab 100644
--- a/scripts/Diffraction/isis_powder/routines/common.py
+++ b/scripts/Diffraction/isis_powder/routines/common.py
@@ -258,6 +258,64 @@ def load_current_normalised_ws_list(run_number_string, instrument, input_batchin
return normalised_ws_list
+def rebin_workspace(workspace, new_bin_width, start_x=None, end_x=None):
+ """
+ Rebins the specified workspace with the specified new bin width. Allows the user
+ to also set optionally the first and final bin boundaries of the histogram too.
+ If the bin boundaries are not set they are preserved from the original workspace
+ :param workspace: The workspace to rebin
+ :param new_bin_width: The new bin width to use across the workspace
+ :param start_x: (Optional) The first x bin to crop to
+ :param end_x: (Optional) The final x bin to crop to
+ :return: The rebinned workspace
+ """
+
+ # Find the starting and ending bin boundaries if they were not set
+ if start_x is None:
+ start_x = workspace.readX(0)[0]
+ if end_x is None:
+ end_x = workspace.readX(0)[-1]
+
+ rebin_string = str(start_x) + ',' + str(new_bin_width) + ',' + str(end_x)
+ workspace = mantid.Rebin(InputWorkspace=workspace, OutputWorkspace=workspace, Params=rebin_string)
+ return workspace
+
+
+def rebin_workspace_list(workspace_list, bin_width_list, start_x_list=None, end_x_list=None):
+ """
+ Rebins a list of workspaces with the specified bin widths in the list provided.
+ The number of bin widths and workspaces in the list must match. Additionally if
+ the optional parameters for start_x_list or end_x_list are provided these must
+ have the same length too.
+ :param workspace_list: The list of workspaces to rebin in place
+ :param bin_width_list: The list of new bin widths to apply to each workspace
+ :param start_x_list: The list of starting x boundaries to rebin to
+ :param end_x_list: The list of ending x boundaries to rebin to
+ :return: List of rebinned workspace
+ """
+ if not isinstance(workspace_list, list) or not isinstance(bin_width_list, list):
+ raise RuntimeError("One of the types passed to rebin_workspace_list was not a list")
+
+ ws_list_len = len(workspace_list)
+ if ws_list_len != len(bin_width_list):
+ raise ValueError("The number of bin widths found to rebin to does not match the number of banks")
+ if start_x_list and len(start_x_list) != ws_list_len:
+ raise ValueError("The number of starting bin values does not match the number of banks")
+ if end_x_list and len(end_x_list) != ws_list_len:
+ raise ValueError("The number of ending bin values does not match the number of banks")
+
+ # Create a list of None types of equal length to make using zip iterator easy
+ start_x_list = [None] * ws_list_len if start_x_list is None else start_x_list
+ end_x_list = [None] * ws_list_len if end_x_list is None else end_x_list
+
+ output_list = []
+ for ws, bin_width, start_x, end_x in zip(workspace_list, bin_width_list, start_x_list, end_x_list):
+ output_list.append(rebin_workspace(workspace=ws, new_bin_width=bin_width,
+ start_x=start_x, end_x=end_x))
+
+ return output_list
+
+
def remove_intermediate_workspace(workspaces):
"""
Removes the specified workspace(s) from the ADS. Can accept lists of workspaces. It
diff --git a/scripts/Diffraction/isis_powder/routines/focus.py b/scripts/Diffraction/isis_powder/routines/focus.py
index a6b2034e09e2defcae765ea028cb83b705ad9559..380acf77c31cd012cba07f38afe0f249e83418ef 100644
--- a/scripts/Diffraction/isis_powder/routines/focus.py
+++ b/scripts/Diffraction/isis_powder/routines/focus.py
@@ -23,7 +23,7 @@ def _focus_one_ws(ws, run_number, instrument, perform_vanadium_norm):
if perform_vanadium_norm:
_test_splined_vanadium_exists(instrument, run_details)
- # Subtract empty beam runs
+ # Subtract empty instrument runs
input_workspace = common.subtract_summed_runs(ws_to_correct=ws, instrument=instrument,
empty_sample_ws_string=run_details.empty_runs)
# Subtract a sample empty if specified
@@ -46,10 +46,16 @@ def _focus_one_ws(ws, run_number, instrument, perform_vanadium_norm):
input_workspace=focused_ws,
perform_vanadium_norm=perform_vanadium_norm)
- cropped_spectra = instrument._crop_banks_to_user_tof(calibrated_spectra)
+ output_spectra = instrument._crop_banks_to_user_tof(calibrated_spectra)
+
+ bin_widths = instrument._get_instrument_bin_widths()
+ if bin_widths:
+ # Reduce the bin width if required on this instrument
+ output_spectra = common.rebin_workspace_list(workspace_list=output_spectra,
+ bin_width_list=bin_widths)
# Output
- d_spacing_group, tof_group = instrument._output_focused_ws(cropped_spectra, run_details=run_details)
+ d_spacing_group, tof_group = instrument._output_focused_ws(output_spectra, run_details=run_details)
common.keep_single_ws_unit(d_spacing_group=d_spacing_group, tof_group=tof_group,
unit_to_keep=instrument._get_unit_to_keep())
@@ -58,7 +64,7 @@ def _focus_one_ws(ws, run_number, instrument, perform_vanadium_norm):
common.remove_intermediate_workspace(input_workspace)
common.remove_intermediate_workspace(aligned_ws)
common.remove_intermediate_workspace(focused_ws)
- common.remove_intermediate_workspace(cropped_spectra)
+ common.remove_intermediate_workspace(output_spectra)
return d_spacing_group
diff --git a/scripts/Inelastic/IndirectReductionCommon.py b/scripts/Inelastic/IndirectReductionCommon.py
index 84ce8f7e568571ddb5120dfeb084b96c5a5defac..81266cf0a52563a025034d9a76474ea56aed8e26 100644
--- a/scripts/Inelastic/IndirectReductionCommon.py
+++ b/scripts/Inelastic/IndirectReductionCommon.py
@@ -629,7 +629,7 @@ def plot_reduction(workspace_name, plot_type):
from mantidplot import plotSpectrum
num_spectra = mtd[workspace_name].getNumberHistograms()
try:
- plotSpectrum(workspace_name, range(0, num_spectra), error_bars=True)
+ plotSpectrum(workspace_name, range(0, num_spectra))
except RuntimeError:
logger.notice('Spectrum plotting canceled by user')
diff --git a/scripts/test/ISISPowderCommonTest.py b/scripts/test/ISISPowderCommonTest.py
index cdce94a461ec977c9b7f34960ce69e86070c12d4..68ece3c1035ddcaabb8eea6f9035d2add656fe99 100644
--- a/scripts/test/ISISPowderCommonTest.py
+++ b/scripts/test/ISISPowderCommonTest.py
@@ -162,7 +162,7 @@ class ISISPowderCommonTest(unittest.TestCase):
def test_extract_ws_spectra(self):
number_of_expected_banks = 5
- ws_to_split = mantid.CreateSampleWorkspace(XMin=0, XMax=1, BankPixelWidth=1,
+ ws_to_split = mantid.CreateSampleWorkspace(XMin=0, XMax=2, BankPixelWidth=1,
NumBanks=number_of_expected_banks)
input_name = ws_to_split.getName()
@@ -314,19 +314,125 @@ class ISISPowderCommonTest(unittest.TestCase):
self.assertAlmostEqual(result_ws_two, result_ext_two)
self.assertNotAlmostEqual(result_ext_one, result_ext_two)
+ def test_rebin_bin_boundary_defaults(self):
+ ws = mantid.CreateSampleWorkspace(OutputWorkspace='test_rebin_bin_boundary_default',
+ Function='Flat background', NumBanks=1, BankPixelWidth=1, XMax=10, BinWidth=1)
+ new_bin_width = 0.5
+ # Originally had bins at 1 unit each. So binning of 0.5 should give us 2n bins back
+ original_number_bins = ws.getNumberBins()
+ original_first_x_val = ws.readX(0)[0]
+ original_last_x_val = ws.readX(0)[-1]
+
+ expected_bins = original_number_bins * 2
+
+ ws = common.rebin_workspace(workspace=ws, new_bin_width=new_bin_width)
+ self.assertEqual(ws.getNumberBins(), expected_bins)
+
+ # Check bin boundaries were preserved
+ self.assertEqual(ws.readX(0)[0], original_first_x_val)
+ self.assertEqual(ws.readX(0)[-1], original_last_x_val)
+
+ mantid.DeleteWorkspace(ws)
+
+ def test_rebin_bin_boundary_specified(self):
+ ws = mantid.CreateSampleWorkspace(OutputWorkspace='test_rebin_bin_boundary_specified',
+ Function='Flat background', NumBanks=1, BankPixelWidth=1, XMax=10, BinWidth=1)
+ # Originally we had 10 bins from 0, 10. Resize from 0, 0.5, 5 so we should have the same number of output
+ # bins with different boundaries
+ new_bin_width = 0.5
+ original_number_bins = ws.getNumberBins()
+
+ expected_start_x = 1
+ expected_end_x = 6
+
+ ws = common.rebin_workspace(workspace=ws, new_bin_width=new_bin_width,
+ start_x=expected_start_x, end_x=expected_end_x)
+
+ # Check number of bins is the same as we halved the bin width and interval so we should have n bins
+ self.assertEqual(ws.getNumberBins(), original_number_bins)
+
+ # Check bin boundaries were changed
+ self.assertEqual(ws.readX(0)[0], expected_start_x)
+ self.assertEqual(ws.readX(0)[-1], expected_end_x)
+
+ mantid.DeleteWorkspace(ws)
+
+ def test_rebin_workspace_list_defaults(self):
+ new_bin_width = 0.5
+ number_of_ws = 10
+
+ ws_bin_widths = [new_bin_width] * number_of_ws
+ ws_list = []
+ for i in range(number_of_ws):
+ out_name = "test_rebin_workspace_list_defaults_" + str(i)
+ ws_list.append(mantid.CreateSampleWorkspace(OutputWorkspace=out_name, Function='Flat background',
+ NumBanks=1, BankPixelWidth=1, XMax=10, BinWidth=1))
+ # What if the item passed in is not a list
+ err_msg_not_list = "was not a list"
+ with assertRaisesRegex(self, RuntimeError, err_msg_not_list):
+ common.rebin_workspace_list(workspace_list=ws_list, bin_width_list=None)
+
+ with assertRaisesRegex(self, RuntimeError, err_msg_not_list):
+ common.rebin_workspace_list(workspace_list=None, bin_width_list=[])
+
+ # What about if the lists aren't the same length
+ with assertRaisesRegex(self, ValueError, "does not match the number of banks"):
+ incorrect_number_bin_widths = [1] * (number_of_ws - 1)
+ common.rebin_workspace_list(workspace_list=ws_list, bin_width_list=incorrect_number_bin_widths)
+
+ # Does it return all the workspaces as a list - another unit test checks the implementation
+ output = common.rebin_workspace_list(workspace_list=ws_list, bin_width_list=ws_bin_widths)
+ self.assertEqual(len(output), number_of_ws)
+
+ for ws in output:
+ mantid.DeleteWorkspace(ws)
+
+ def test_rebin_workspace_list_x_start_end(self):
+ new_start_x = 1
+ new_end_x = 5
+ new_bin_width = 0.5
+ number_of_ws = 10
+
+ ws_bin_widths = [new_bin_width] * number_of_ws
+ start_x_list = [new_start_x] * number_of_ws
+ end_x_list = [new_end_x] * number_of_ws
+
+ ws_list = []
+ for i in range(number_of_ws):
+ out_name = "test_rebin_workspace_list_defaults_" + str(i)
+ ws_list.append(mantid.CreateSampleWorkspace(OutputWorkspace=out_name, Function='Flat background',
+ NumBanks=1, BankPixelWidth=1, XMax=10, BinWidth=1))
+
+ # Are the lengths checked
+ incorrect_length = [1] * (number_of_ws - 1)
+ with assertRaisesRegex(self, ValueError, "The number of starting bin values"):
+ common.rebin_workspace_list(workspace_list=ws_list, bin_width_list=ws_bin_widths,
+ start_x_list=incorrect_length, end_x_list=end_x_list)
+ with assertRaisesRegex(self, ValueError, "The number of ending bin values"):
+ common.rebin_workspace_list(workspace_list=ws_list, bin_width_list=ws_bin_widths,
+ start_x_list=start_x_list, end_x_list=incorrect_length)
+
+ output_list = common.rebin_workspace_list(workspace_list=ws_list, bin_width_list=ws_bin_widths,
+ start_x_list=start_x_list, end_x_list=end_x_list)
+ self.assertEqual(len(output_list), number_of_ws)
+ for ws in output_list:
+ self.assertEqual(ws.readX(0)[0], new_start_x)
+ self.assertEqual(ws.readX(0)[-1], new_end_x)
+ mantid.DeleteWorkspace(ws)
+
def test_remove_intermediate_workspace(self):
ws_list = []
ws_names_list = []
ws_single_name = "remove_intermediate_ws-single"
ws_single = mantid.CreateSampleWorkspace(OutputWorkspace=ws_single_name, NumBanks=1, BankPixelWidth=1,
- XMax=2, BinWidth=1)
+ XMax=10, BinWidth=1)
for i in range(0, 3):
out_name = "remove_intermediate_ws_" + str(i)
ws_names_list.append(out_name)
ws_list.append(mantid.CreateSampleWorkspace(OutputWorkspace=out_name, NumBanks=1, BankPixelWidth=1,
- XMax=2, BinWidth=1))
+ XMax=10, BinWidth=1))
# Check single workspaces are removed
self.assertEqual(True, mantid.mtd.doesExist(ws_single_name))