MRMScoring#

class pyopenms.MRMScoring#

Bases: object

Cython implementation of _MRMScoring

Original C++ documentation is available here

__init__()#

Overload:

__init__(self) → None

Overload:

__init__(self, in_0: MRMScoring) → None

Methods

`__init__`	Overload:
`calcMIPrecursorCombinedScore`(self)
`calcMIPrecursorContrastScore`(self)
`calcMIPrecursorScore`(self)
`calcMIScore`(self)
`calcMIWeightedScore`(self, ...)
`calcRTScore`(self, peptide, ...)
`calcSeparateMIContrastScore`(self)
`calcSeparateXcorrContrastCoelutionScore`(self)	Calculate the separate cross-correlation contrast score
`calcSeparateXcorrContrastShapeScore`(self)	Calculate the separate cross-correlation contrast shape score
`calcXcorrCoelutionScore`(self)	Calculate the cross-correlation coelution score.
`calcXcorrCoelutionWeightedScore`(self, ...)	Calculate the weighted cross-correlation coelution score
`calcXcorrPrecursorContrastCoelutionScore`(self)	Calculate the precursor cross-correlation contrast score against the transitions
`calcXcorrPrecursorContrastShapeScore`(self)	Calculate the precursor cross-correlation shape score against the transitions
`calcXcorrShapeScore`(self)	Calculate the cross-correlation shape score
`calcXcorrShapeWeightedScore`(self, ...)	Calculate the weighted cross-correlation shape score
`getMIMatrix`(self)

calcMIPrecursorCombinedScore(self) → float#

calcMIPrecursorContrastScore(self) → float#

calcMIPrecursorScore(self) → float#

calcMIScore(self) → float#

calcMIWeightedScore(self, normalized_library_intensity: List[float]) → float#

calcRTScore(self, peptide: LightCompound, normalized_experimental_rt: float) → float#

calcSeparateMIContrastScore(self) → List[float]#

calcSeparateXcorrContrastCoelutionScore(self) → List[float]#: Calculate the separate cross-correlation contrast score

calcSeparateXcorrContrastShapeScore(self) → List[float]#: Calculate the separate cross-correlation contrast shape score

calcXcorrCoelutionScore(self) → float#: Calculate the cross-correlation coelution score. The score is a distance where zero indicates perfect coelution

calcXcorrCoelutionWeightedScore(self, normalized_library_intensity: List[float]) → float#

Calculate the weighted cross-correlation coelution score

The score is a distance where zero indicates perfect coelution. The score is weighted by the transition intensities, non-perfect coelution in low-intensity transitions should thus become less important

calcXcorrPrecursorContrastCoelutionScore(self) → float#

Calculate the precursor cross-correlation contrast score against the transitions

The score is a distance where zero indicates perfect coelution

calcXcorrPrecursorContrastShapeScore(self) → float#: Calculate the precursor cross-correlation shape score against the transitions

calcXcorrShapeScore(self) → float#

Calculate the cross-correlation shape score

The score is a correlation measure where 1 indicates perfect correlation and 0 means no correlation.

calcXcorrShapeWeightedScore(self, normalized_library_intensity: List[float]) → float#

Calculate the weighted cross-correlation shape score

The score is a correlation measure where 1 indicates perfect correlation and 0 means no correlation. The score is weighted by the transition intensities, non-perfect coelution in low-intensity transitions should thus become less important

getMIMatrix(self) → MatrixDouble#