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Shorten workspace names #149

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merged 2 commits into from
Dec 6, 2024
Merged

Shorten workspace names #149

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9400cc2
Shorten ws names
GuiMacielPereira Dec 6, 2024
224b12d
Shorten another name
GuiMacielPereira Dec 6, 2024
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52 changes: 30 additions & 22 deletions src/mvesuvio/analysis_fitting.py
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Original file line number Diff line number Diff line change
Expand Up @@ -147,7 +147,7 @@ def subtractAllMassesExceptFirst(ic, ws, ncpForEachMass):
mask = np.all(ws.extractY() == 0, axis=0)
dataY[:, mask] = 0

wsSubMass = CloneWorkspace(InputWorkspace=ws, OutputWorkspace=ws.name() + "_Mass0")
wsSubMass = CloneWorkspace(InputWorkspace=ws, OutputWorkspace=ws.name() + "_m0")
passDataIntoWS(dataX, dataY, dataE, wsSubMass)
wsMask, maskList = ExtractMask(ws)
MaskDetectors(Workspace=wsSubMass, MaskedWorkspace=wsMask)
Expand Down Expand Up @@ -185,7 +185,7 @@ def ySpaceReduction(wsTOF, mass0, yFitIC, ncp):

# Normalize spectra of specieal workspace
wsJoYN = Divide(
wsJoYB, wsJoYInt, OutputWorkspace=wsJoYB.name() + "_Normalised"
wsJoYB, wsJoYInt, OutputWorkspace=wsJoYB.name() + "_norm"
)
wsJoYAvg = weightedAvgXBins(wsJoYN, xp)
return wsJoYN, wsJoYAvg
Expand All @@ -208,7 +208,7 @@ def ySpaceReduction(wsTOF, mass0, yFitIC, ncp):


def convertToYSpace(wsTOF, mass0):
wsJoY = ConvertToYSpace(wsTOF, Mass=mass0, OutputWorkspace=wsTOF.name() + "_JoY")
wsJoY = ConvertToYSpace(wsTOF, Mass=mass0, OutputWorkspace=wsTOF.name() + "_joy")
return wsJoY


Expand All @@ -217,10 +217,10 @@ def rebinAndNorm(wsJoY, rebinPars):
InputWorkspace=wsJoY,
Params=rebinPars,
FullBinsOnly=True,
OutputWorkspace=wsJoY.name() + "_Rebinned",
OutputWorkspace=wsJoY.name() + "_rebin",
)
wsJoYInt = Integration(wsJoYR, OutputWorkspace=wsJoYR.name() + "_Integrated")
wsJoYNorm = Divide(wsJoYR, wsJoYInt, OutputWorkspace=wsJoYR.name() + "_Normalised")
wsJoYInt = Integration(wsJoYR, OutputWorkspace=wsJoYR.name() + "_integrated")
wsJoYNorm = Divide(wsJoYR, wsJoYInt, OutputWorkspace=wsJoYR.name() + "_norm")
return wsJoYNorm, wsJoYInt


Expand Down Expand Up @@ -301,7 +301,7 @@ def weightedAvgXBins(wsXBins, xp):
DataY=meansY,
DataE=meansE,
NSpec=1,
OutputWorkspace=wsXBins.name() + "_WeightedAvg",
OutputWorkspace=wsXBins.name() + "_wavg",
)
return wsYSpaceAvg

Expand Down Expand Up @@ -365,7 +365,7 @@ def weightedAvgCols(wsYSpace):
DataY=meanY,
DataE=meanE,
NSpec=1,
OutputWorkspace=wsYSpace.name() + "_WeightedAvg",
OutputWorkspace=wsYSpace.name() + "_wavg",
)
return wsYSpaceAvg

Expand Down Expand Up @@ -474,7 +474,7 @@ def symmetrizeWs(avgYSpace):
else:
dataYS, dataES = weightedSymArr(dataY, dataE)

wsSym = CloneWorkspace(avgYSpace, OutputWorkspace=avgYSpace.name() + "_Symmetrised")
wsSym = CloneWorkspace(avgYSpace, OutputWorkspace=avgYSpace.name() + "_sym")
wsSym = passDataIntoWS(dataX, dataYS, dataES, wsSym)
return wsSym

Expand Down Expand Up @@ -893,14 +893,21 @@ def createFitResultsWorkspace(
):
"""Creates workspace similar to the ones created by Mantid Fit."""

wsMinFit = CreateWorkspace(
ws_fit_profile = CreateWorkspace(
DataX=dataX,
DataY=dataY,
DataE=dataE,
NSpec=1,
OutputWorkspace=wsYSpaceSym.name() + "_minuit",
)
ws_fit_complete = CreateWorkspace(
DataX=np.concatenate((dataX, dataX, dataX)),
DataY=np.concatenate((dataY, dataYFit, Residuals)),
DataE=np.concatenate((dataE, dataYSigma, np.zeros(len(dataE)))),
NSpec=3,
OutputWorkspace=wsYSpaceSym.name() + "_Fitted_Minuit",
OutputWorkspace=wsYSpaceSym.name() + "_minuit_Workspace",
)
return wsMinFit
return ws_fit_complete


def saveMinuitPlot(yFitIC, wsMinuitFit, mObj):
Expand All @@ -927,7 +934,7 @@ def saveMinuitPlot(yFitIC, wsMinuitFit, mObj):

def createCorrelationTableWorkspace(wsYSpaceSym, parameters, corrMatrix):
tableWS = CreateEmptyTableWorkspace(
OutputWorkspace=wsYSpaceSym.name() + "_Fitted_Minuit_NormalizedCovarianceMatrix"
OutputWorkspace=wsYSpaceSym.name() + "_minuit_NormalizedCovarianceMatrix"
)
tableWS.setTitle("Minuit Fit")
tableWS.addColumn(type="str", name="Name")
Expand Down Expand Up @@ -1211,7 +1218,7 @@ def createFitParametersTableWorkspace(
):
# Create Parameters workspace
tableWS = CreateEmptyTableWorkspace(
OutputWorkspace=wsYSpaceSym.name() + "_Fitted_Minuit_Parameters"
OutputWorkspace=wsYSpaceSym.name() + "_minuit_Parameters"
)
tableWS.setTitle("Minuit Fit")
tableWS.addColumn(type="str", name="Name")
Expand Down Expand Up @@ -1297,7 +1304,8 @@ def fitProfileMantidFit(yFitIC, wsYSpaceSym, wsRes):
else:
raise ValueError("fitmodel not recognized.")

outputName = wsYSpaceSym.name() + "_Fitted_" + minimizer
suffix = 'lm' if minimizer=="Levenberg-Marquardt" else minimizer.lower()
outputName = wsYSpaceSym.name() + "_" + suffix
CloneWorkspace(InputWorkspace=wsYSpaceSym, OutputWorkspace=outputName)

Fit(
Expand All @@ -1314,17 +1322,17 @@ def printYSpaceFitResults(wsJoYName):
print("\nFit in Y Space results:")
foundWS = []
try:
wsFitLM = mtd[wsJoYName + "_Fitted_Levenberg-Marquardt_Parameters"]
wsFitLM = mtd[wsJoYName + "_lm_Parameters"]
foundWS.append(wsFitLM)
except KeyError:
pass
try:
wsFitSimplex = mtd[wsJoYName + "_Fitted_Simplex_Parameters"]
wsFitSimplex = mtd[wsJoYName + "_simplex_Parameters"]
foundWS.append(wsFitSimplex)
except KeyError:
pass
try:
wsFitMinuit = mtd[wsJoYName + "_Fitted_Minuit_Parameters"]
wsFitMinuit = mtd[wsJoYName + "_minuit_Parameters"]
foundWS.append(wsFitMinuit)
except KeyError:
pass
Expand Down Expand Up @@ -1353,7 +1361,7 @@ def __init__(self, ic, yFitIC, wsFinalName, wsYSpaceAvgName):
wsResSum = mtd[wsFinalName + "_Resolution_Sum"]

wsJoYAvg = mtd[wsYSpaceAvgName]
wsSubMassName = wsYSpaceAvgName.split("_JoY_")[0]
wsSubMassName = wsYSpaceAvgName.split("_joy_")[0]
wsMass0 = mtd[wsSubMassName]

self.finalRawDataY = wsFinal.extractY()
Expand All @@ -1367,19 +1375,19 @@ def __init__(self, ic, yFitIC, wsFinalName, wsYSpaceAvgName):
poptList = []
perrList = []
try:
wsFitMinuit = mtd[wsJoYAvg.name() + "_Fitted_Minuit_Parameters"]
wsFitMinuit = mtd[wsJoYAvg.name() + "_minuit_Parameters"]
poptList.append(wsFitMinuit.column("Value"))
perrList.append(wsFitMinuit.column("Error"))
except:
pass
try:
wsFitLM = mtd[wsJoYAvg.name() + "_Fitted_Levenberg-Marquardt_Parameters"]
wsFitLM = mtd[wsJoYAvg.name() + "_lm_Parameters"]
poptList.append(wsFitLM.column("Value"))
perrList.append(wsFitLM.column("Error"))
except:
pass
try:
wsFitSimplex = mtd[wsJoYAvg.name() + "_Fitted_Simplex_Parameters"]
wsFitSimplex = mtd[wsJoYAvg.name() + "_simplex_Parameters"]
poptList.append(wsFitSimplex.column("Value"))
perrList.append(wsFitSimplex.column("Error"))
except:
Expand Down
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