ReactionMonitoringTransition#
- class pyopenms.ReactionMonitoringTransition#
Bases:
objectCython implementation of _ReactionMonitoringTransition
- Original C++ documentation is available here
– Inherits from [‘CVTermList’]
- __init__()#
Overload:
- __init__(self) None
Overload:
- __init__(self, in_0: ReactionMonitoringTransition) None
Methods
Overload:
addCVTerm(self, term)Adds a CV term
addIntermediateProduct(self, product)addPrecursorCVTerm(self, cv_term)Adds precursor CV Term
addPredictionTerm(self, prediction)Adds prediction term
addProductCVTerm(self, cv_term)clearMetaInfo(self)Removes all meta values
consumeCVTerms(self, cv_term_map)Merges the given map into the member map, no duplicate checking
empty(self)getCVTerms(self)Returns the accession string of the term
getCompoundRef(self)getDecoyTransitionType(self)Returns the type of transition (target or decoy)
getIntermediateProducts(self)getKeys(self, keys)Fills the given vector with a list of all keys for which a value is set
getLibraryIntensity(self)Returns the library intensity (ion count or normalized ion count from a spectral library)
getMetaValue(self, in_0)Returns the value corresponding to a string, or
getName(self)getNativeID(self)getPeptideRef(self)getPrecursorCVTermList(self)Obtains the list of CV Terms for the precursor
getPrecursorMZ(self)Returns the precursor mz (Q1 value)
getPrediction(self)Obtains the Prediction object
getProduct(self)getProductChargeState(self)Returns the charge state of the product
getProductMZ(self)getRetentionTime(self)hasCVTerm(self, accession)hasPrecursorCVTerms(self)Returns true if precursor CV Terms exist (means it is safe to call getPrecursorCVTermList)
hasPrediction(self)Returns true if a Prediction object exists (means it is safe to call getPrediction)
isDetectingTransition(self)isIdentifyingTransition(self)isMetaEmpty(self)Returns if the MetaInfo is empty
isProductChargeStateSet(self)Returns true if charge state of product is already set
isQuantifyingTransition(self)metaRegistry(self)Returns a reference to the MetaInfoRegistry
metaValueExists(self, in_0)Returns whether an entry with the given name exists
removeMetaValue(self, in_0)Removes the DataValue corresponding to name if it exists
replaceCVTerm(self, term)Replaces the specified CV term
replaceCVTerms(self, cv_terms, accession)setCVTerms(self, terms)Sets the CV terms
setCompoundRef(self, compound_ref)setDecoyTransitionType(self, d)Sets the type of transition (target or decoy)
setDetectingTransition(self, val)setIdentifyingTransition(self, val)setIntermediateProducts(self, products)setLibraryIntensity(self, intensity)Sets the library intensity (ion count or normalized ion count from a spectral library)
setMetaValue(self, in_0, in_1)Sets the DataValue corresponding to a name
setName(self, name)setNativeID(self, name)setPeptideRef(self, peptide_ref)setPrecursorCVTermList(self, list_)Sets a list of precursor CV Terms
setPrecursorMZ(self, in_0)Sets the precursor mz (Q1 value)
setPrediction(self, prediction)Sets prediction
setProduct(self, product)setProductMZ(self, in_0)setQuantifyingTransition(self, val)setRetentionTime(self, rt)- addIntermediateProduct(self, product: TraMLProduct) None#
- clearMetaInfo(self) None#
Removes all meta values
- consumeCVTerms(self, cv_term_map: Dict[bytes, List[CVTerm]]) None#
Merges the given map into the member map, no duplicate checking
- empty(self) bool#
- getDecoyTransitionType(self) int#
Returns the type of transition (target or decoy)
- getIntermediateProducts(self) List[TraMLProduct]#
- getKeys(self, keys: List[bytes]) None#
Fills the given vector with a list of all keys for which a value is set
- getLibraryIntensity(self) float#
Returns the library intensity (ion count or normalized ion count from a spectral library)
- getMetaValue(self, in_0: bytes | str | String) int | float | bytes | str | List[int] | List[float] | List[bytes]#
Returns the value corresponding to a string, or
- getPrecursorCVTermList(self) CVTermList#
Obtains the list of CV Terms for the precursor
- getPrecursorMZ(self) float#
Returns the precursor mz (Q1 value)
- getPrediction(self) Prediction#
Obtains the Prediction object
- getProduct(self) TraMLProduct#
- getProductChargeState(self) int#
Returns the charge state of the product
- getProductMZ(self) float#
- getRetentionTime(self) RetentionTime#
- hasPrecursorCVTerms(self) bool#
Returns true if precursor CV Terms exist (means it is safe to call getPrecursorCVTermList)
- hasPrediction(self) bool#
Returns true if a Prediction object exists (means it is safe to call getPrediction)
- isDetectingTransition(self) bool#
- isIdentifyingTransition(self) bool#
- isMetaEmpty(self) bool#
Returns if the MetaInfo is empty
- isProductChargeStateSet(self) bool#
Returns true if charge state of product is already set
- isQuantifyingTransition(self) bool#
- metaRegistry(self) MetaInfoRegistry#
Returns a reference to the MetaInfoRegistry
- metaValueExists(self, in_0: bytes | str | String) bool#
Returns whether an entry with the given name exists
- removeMetaValue(self, in_0: bytes | str | String) None#
Removes the DataValue corresponding to name if it exists
- setDecoyTransitionType(self, d: int) None#
Sets the type of transition (target or decoy)
- setDetectingTransition(self, val: bool) None#
- setIdentifyingTransition(self, val: bool) None#
- setIntermediateProducts(self, products: List[TraMLProduct]) None#
- setLibraryIntensity(self, intensity: float) None#
Sets the library intensity (ion count or normalized ion count from a spectral library)
- setMetaValue(self, in_0: bytes | str | String, in_1: int | float | bytes | str | List[int] | List[float] | List[bytes]) None#
Sets the DataValue corresponding to a name
- setPrecursorCVTermList(self, list_: CVTermList) None#
Sets a list of precursor CV Terms
- setPrecursorMZ(self, in_0: float) None#
Sets the precursor mz (Q1 value)
- setPrediction(self, prediction: Prediction) None#
Sets prediction
- setProduct(self, product: TraMLProduct) None#
- setProductMZ(self, in_0: float) None#
- setQuantifyingTransition(self, val: bool) None#
- setRetentionTime(self, rt: RetentionTime) None#