TransformationModelLowess
- class pyopenms.TransformationModelLowess
Bases:
objectCython implementation of _TransformationModelLowess
- Original C++ documentation is available here
– Inherits from [‘TransformationModel’]
- __init__(self, data: List[TM_DataPoint], params: Param) None
Methods
__init__(self, data, params)checkDatumRange(self, datum, datum_min, ...)Check that the datum is within the valid min and max bounds
checkValidWeight(self, weight, valid_weights)Check for a valid weighting function string
evaluate(self, value)getDefaultParameters(self, in_0)getParameters(self)getValidXWeights(self)Returns a list of valid x weight function stringss
getValidYWeights(self)Returns a list of valid y weight function strings
unWeightData(self, data)Unweight the data by the given weight function
unWeightDatum(self, datum, weight)Apply the reverse of the weighting function to the data
weightData(self, data)Weight the data by the given weight function
weightDatum(self, datum, weight)Weight the data according to the weighting function
- checkDatumRange(self, datum: float, datum_min: float, datum_max: float) float
Check that the datum is within the valid min and max bounds
- checkValidWeight(self, weight: Union[bytes, str, String], valid_weights: List[bytes]) bool
Check for a valid weighting function string
- evaluate(self, value: float) float
- getValidXWeights(self) List[bytes]
Returns a list of valid x weight function stringss
- getValidYWeights(self) List[bytes]
Returns a list of valid y weight function strings
- unWeightData(self, data: List[TM_DataPoint]) None
Unweight the data by the given weight function
- unWeightDatum(self, datum: float, weight: Union[bytes, str, String]) float
Apply the reverse of the weighting function to the data
- weightData(self, data: List[TM_DataPoint]) None
Weight the data by the given weight function