Bases: pkpd.protocols.protocol_pkpd.ProtPKPD
, pkpd.objects.PKPDModelBase2
Simultaneous fit of data obtained by different vias, e.g. IV and PO, but it can be any two vias and any two
dosing regimes, dissolution profiles, etc. It is supposed that the PK model in both cases is the same
(e.g. two monocompartments, two two-compartments, …
-
addSample(sample1, sample2)[source]
- Parameters
upperBound (lowerBound and) – a numpy array of parameters
- Returns
a list of string with “True”, “False”, “NA”, “Suspicious”
-
calculateParameterUnits(sample1, sample2)[source]
-
createFitting(prot, experiment, suffix)[source]
-
createOutputStep()[source]
-
forwardModel(parameters, x=None)[source]
-
getBounds()[source]
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getEquation()[source]
-
getModelEquation()[source]
-
getParameterNames()[source]
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keepSampleFit(fitting, prot, sampleName, x, y, yp, yplower, ypupper, prmLowerBound, prmUpperBound, optimizer2)[source]
-
mergeModelParameters()[source]
-
prepareDoseForSample(prot, sample)[source]
-
prepareForSampleAnalysis(sampleName)[source]
-
runFit(fn1, fn2)[source]
-
separateBounds(lowerBound, upperBound, parameterNames1, parameterNames2, parameterNames)[source]
-
setBounds(sample1, sample2)[source]
-
setConfidenceInterval(lowerBound, upperBound)[source]
-
setConfidenceIntervalNA()[source]
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setInitialSolution(sampleName)[source]
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setParameters(parameters)[source]
-
setXYValues(x1, y1, x2, y2)[source]
-
setupSample(prot, sample, prefix)[source]
-
setupUnderlyingProtocol(prot)[source]
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splitParameterUnits()[source]
-
updateUnderlyingExperiments(sampleName)[source]