| 1 | import math |
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| 2 | import numpy |
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| 3 | from mantid.api import * # PythonAlgorithm, registerAlgorithm, WorkspaceProperty |
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| 4 | from mantid.kernel import * |
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| 5 | from mantid.simpleapi import * |
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| 6 | |
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| 7 | class LeakyFunction(IFunction1D): |
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| 8 | # equivalent to ExpDecayOsc |
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| 9 | def init(self): |
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| 10 | self.declareParameter("A",1.0) |
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| 11 | self.declareParameter("Lambda",1.0) |
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| 12 | self.declareParameter("Frequency",1.0) |
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| 13 | self.declareParameter("Phi",1.0) |
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| 14 | |
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| 15 | def function1D(self,xvals): |
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| 16 | a=self.getParameterValue("A") |
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| 17 | lam=self.getParameterValue("Lambda") |
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| 18 | frq=self.getParameterValue("Frequency") |
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| 19 | phi=self.getParameterValue("Phi") |
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| 20 | return a*numpy.cos(xvals*frq*2.0*math.pi+phi)*numpy.exp(-xvals*lam) |
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| 21 | |
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| 22 | FunctionFactory.subscribe(LeakyFunction) |
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| 23 | |
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| 24 | class LeakyFit(PythonAlgorithm): |
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| 25 | def PyInit(self): |
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| 26 | #self.declareProperty(WorkspaceProperty("InputWS","",Direction.Input),"Source run") |
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| 27 | #self.declareProperty(WorkspaceProperty("InputWS","",Direction.Input),"Data to fit, from CreateALCMap") |
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| 28 | self.declareProperty(WorkspaceProperty("OutputWSChi","",Direction.Output),"Chisq as a function of fixed F") |
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| 29 | self.declareProperty(WorkspaceProperty("OutputWSA","",Direction.Output),"Signal ampl as a function of fixed F") |
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| 30 | #self.declareProperty("StartF",0.0,doc="Lowest val of F") |
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| 31 | #self.declareProperty("EndF",0.5,doc="Highest val of F") |
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| 32 | #self.declareProperty("FPoints",20,doc="Number of F values to try") |
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| 33 | self.declareProperty("UsePythonFunc",True,doc="Use Python function instead of built in C++ one") |
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| 34 | |
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| 35 | def category(self): |
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| 36 | return "Muon" |
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| 37 | |
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| 38 | def PyExec(self): |
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| 39 | #sourcedat=self.getProperty("InputWS").value |
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| 40 | #(flatsource,Nspec,Y0,dY,dX)=QuantumFlattenWorkspace(InputWorkspace=sourcedat) |
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| 41 | sourcedat=WorkspaceFactory.create("Workspace2D",NVectors=1,XLength=5000,YLength=5000) |
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| 42 | sourcedat.dataX(0)[:]=numpy.linspace(0.0,32.0,5000) |
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| 43 | sourcedat.dataY(0)[:]=10.0*numpy.cos(sourcedat.dataX(0))+0.1*numpy.random.randn(5000) |
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| 44 | sourcedat.dataE(0)[:]=numpy.ones(5000)*0.1 |
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| 45 | # Y0=field val of 1st spectrum, dY=field increment, dX=X value offset between spectra |
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| 46 | |
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| 47 | #StartF=self.getProperty("StartF").value |
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| 48 | #EndF=self.getProperty("EndF").value |
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| 49 | #FPoints=self.getProperty("FPoints").value |
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| 50 | StartF=0.1 |
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| 51 | EndF=0.5 |
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| 52 | FPoints=20 |
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| 53 | usePythonFunc=self.getProperty("UsePythonFunc").value |
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| 54 | resultws=WorkspaceFactory.create("Workspace2D",NVectors=1,XLength=FPoints,YLength=FPoints) |
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| 55 | amplws=WorkspaceFactory.create("Workspace2D",NVectors=1,XLength=FPoints,YLength=FPoints) |
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| 56 | # progress |
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| 57 | prog_reporter=Progress(self,start=0.0, end=1.0, nreports=FPoints) |
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| 58 | FVals=numpy.linspace(StartF,EndF,FPoints) |
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| 59 | resultws.dataX(0)[:]=FVals |
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| 60 | amplws.dataX(0)[:]=FVals |
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| 61 | |
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| 62 | for j in range(FPoints): |
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| 63 | F=FVals[j] |
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| 64 | if(usePythonFunc): |
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| 65 | (stat,chisq,Covar,params,curves)=Fit(Function="name=LeakyFunction,A=0.2,Lambda=0.05,Frequency="+str(F)+",Phi=0.0", |
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| 66 | ties="Frequency="+str(F),InputWorkspace=sourcedat,Output="sourcedat") |
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| 67 | else: |
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| 68 | (stat,chisq,Covar,params,curves)=Fit(Function="name=ExpDecayOsc,A=0.2,Lambda=0.05,Frequency="+str(F)+",Phi=0.0", |
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| 69 | ties="Frequency="+str(F),InputWorkspace=sourcedat,Output="sourcedat") |
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| 70 | resultws.dataY(0)[j]=chisq |
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| 71 | amplws.dataY(0)[j]=params.column(1)[0] |
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| 72 | DeleteWorkspace(Covar) |
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| 73 | DeleteWorkspace(params) |
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| 74 | DeleteWorkspace(curves) |
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| 75 | |
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| 76 | prog_reporter.report("Processing") |
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| 77 | self.setProperty("OutputWSChi",resultws) |
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| 78 | self.setProperty("OutputWSA",amplws) |
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| 79 | |
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| 80 | AlgorithmFactory.subscribe(LeakyFit) |
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