Container for univariate data.
More...
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def | __init__ (self, fData=None, dWeights=None, dName=None, bPlanes=None, uvModelName="gauss", args, kwargs) |
| Init univariate model distirbution. More...
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def | setUVM (self, uvModelName) |
| Select target univariate model. More...
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def | setName (self, dataName) |
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def | setWeights (self, dataWeights) |
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def | setAxialBounds (self, boundingPlanes) |
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def | setData (self, fieldData, dataWeights, boundingPlanes=None) |
| Set the univariate field data and weights. More...
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def | fitMLE (self, params0=None) |
| fit model to data via maximum likelyhood. More...
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def | fitGMM (self) |
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def | fitMCMC (self) |
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| fieldData |
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| dataWeights |
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| dataName |
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| boundingPlanes |
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| uvmodel |
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Container for univariate data.
§ __init__()
def starvine.uvar.uvd.Uvd.__init__ |
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self, |
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fData = None , |
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dWeights = None , |
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dName = None , |
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bPlanes = None , |
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uvModelName = "gauss" , |
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args, |
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kwargs |
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Init univariate model distirbution.
- Parameters
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fData | |
dWeights | |
dName | |
bPlanes | |
uvModelName | |
§ fitMLE()
def starvine.uvar.uvd.Uvd.fitMLE |
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self, |
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params0 = None |
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fit model to data via maximum likelyhood.
- Parameters
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params0 | Initial guess for model parameters. If None: use default initial guess |
§ setData()
def starvine.uvar.uvd.Uvd.setData |
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self, |
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fieldData, |
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dataWeights, |
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boundingPlanes = None |
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Set the univariate field data and weights.
- Parameters
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fieldData | Scalar surface or volumetric field data |
dataWeights | weights of the data - typically areas or volumes |
boundingPlanes | (optional) <tuple> of upper and lower axial bounds |
§ setUVM()
def starvine.uvar.uvd.Uvd.setUVM |
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self, |
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uvModelName |
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Select target univariate model.
- Parameters
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uvModelName | <string> currently avalible models: "gauss", "gamma", "beta" |
The documentation for this class was generated from the following file: