| ▼Concept | OpenMS concepts (types, macros, ...) |
| Class test macros | These macros are used by the test programs in the subdirectory OpenMS/source/TEST |
| Exceptions | Exceptions |
| Condition macros | Macros used for to enforce preconditions and postconditions |
| System | Very basic functionality like file system or stopwatch |
| Datastructures | Auxiliary datastructures |
| ▼Math | Math functions and classes |
| Statistics functions | Various statistical functions |
| Misc functions | Math functions |
| ▼Kernel | Kernel datastructures |
| RangeUtils | Predicates for range operations |
| ▼Format | IO classes |
| File IO | File IO classes |
| Metadata | Classes that capture meta data about a MS or HPLC-MS experiment |
| Chemistry | |
| Spectrum Comparison | The classes within this group are used to compare single spectra, by reporting a similarity value |
| ▼Spectrum filters | This group contains filtering classes for spectra |
| Spectra Preprocessors | The spectra preprocessors filter the spectra with different criteria |
| Spectra Filters | Spectra filters report single values of spectra e.g. the TIC |
| ▼Analysis | High-level analysis like PeakPicking, Quantitation, Identification, MapAlignment |
| Topdown | Topdown-related classes |
| Quantitation | Quantitation-related classes |
| SignalProcessing | Signal processing classes (noise estimation, noise filters, baseline filters) |
| PeakPicking | Classes for the transformation of raw ms data into peak data |
| FeatureFinder | The feature detection algorithms |
| MapAlignment | The map alignment algorithms |
| FeatureGrouping | The feature grouping |
| Identification | Protein and peptide identification classes |
| DeNovo | DeNovo identification classes |
| Clustering | This class contains SpectraClustering classes These classes are components for clustering all kinds of data for which a distance relation, normalizable in the range of [0,1], is available. Mainly this will be data for which there is a corresponding CompareFunctor given (e.g. PeakSpectrum) that is yielding the similarity normalized in the range of [0,1] of such two elements, so it can easily converted to the needed distances |
| ▼Visual | Visualization classes |
| Spectrum visualization widgets | Spectrum visualization widgets |
| TOPPView | GUI elements for TOPPView |
| TOPPAS | GUI elements for TOPPAS |
| Dialogs | Dialogs for user interaction |
| Get scores from ID structures for FDR | Fills the scores_labels vector from an ID data structure |
| Sets scores to FDRs/qVals in ID data structures to the closest in a given mapping | Sets FDRs/qVals from a scores_to_FDR map in the ID data structures |
| Functions for getting values from sql-select statements | |
1.9.1 
