KDTreeFeatureMaps#
- class pyopenms.KDTreeFeatureMaps#
Bases:
objectCython implementation of _KDTreeFeatureMaps
- Original C++ documentation is available here
– Inherits from [‘DefaultParamHandler’]
- __init__()#
Overload:
- __init__(self) None
Stores a set of features, together with a 2D tree for fast search
Overload:
- __init__(self, maps: List[FeatureMap], param: Param) None
Overload:
- __init__(self, maps: List[ConsensusMap], param: Param) None
Methods
Overload:
Overload:
charge(self, i)clear(self)getDefaults(self)Returns the default parameters
getName(self)Returns the name
getNeighborhood(self, index, result_indices, ...)Fill result with indices of all features compatible (wrt.
getParameters(self)Returns the parameters
getSubsections(self)intensity(self, i)mapIndex(self, i)mz(self, i)numMaps(self)optimizeTree(self)queryRegion(self, rt_low, rt_high, mz_low, ...)rt(self, i)setName(self, in_0)Sets the name
setParameters(self, param)Sets the parameters
size(self)treeSize(self)- addMaps()#
Overload:
- addMaps(self, maps: List[FeatureMap]) None
Add maps and balance kd-tree
Overload:
- addMaps(self, maps: List[ConsensusMap]) None
- charge(self, i: int) int#
- clear(self) None#
- getNeighborhood(self, index: int, result_indices: List[int], rt_tol: float, mz_tol: float, mz_ppm: bool, include_features_from_same_map: bool, max_pairwise_log_fc: float) None#
Fill result with indices of all features compatible (wrt. RT, m/z, map index) to the feature with index
- getSubsections(self) List[bytes]#
- intensity(self, i: int) float#
- mapIndex(self, i: int) int#
- mz(self, i: int) float#
- numMaps(self) int#
- optimizeTree(self) None#
- queryRegion(self, rt_low: float, rt_high: float, mz_low: float, mz_high: float, result_indices: List[int], ignored_map_index: int) None#
- rt(self, i: int) float#
- size(self) int#
- treeSize(self) int#