Struct TimsDatasetDIA 

pub struct TimsDatasetDIA {
    pub loader: TimsDataLoader,
    pub global_meta_data: GlobalMetaData,
    pub meta_data: Vec<FrameMeta>,
    pub dia_ms_ms_info: Vec<DiaMsMisInfo>,
    pub dia_ms_ms_windows: Vec<DiaMsMsWindow>,
    pub dia_index: DiaIndex,
}

Fields

loader: TimsDataLoader

global_meta_data: GlobalMetaData

meta_data: Vec<FrameMeta>

dia_ms_ms_info: Vec<DiaMsMisInfo>

dia_ms_ms_windows: Vec<DiaMsMsWindow>

dia_index: DiaIndex

Implementations

impl TimsDatasetDIA

pub fn new( bruker_lib_path: &str, data_path: &str, in_memory: bool, use_bruker_sdk: bool, ) -> Self

pub fn new_with_mz_calibration( data_path: &str, in_memory: bool, tof_intercept: f64, tof_slope: f64, ) -> Self

Create a DIA dataset with regression-derived m/z calibration.

This method uses externally-provided m/z calibration coefficients (e.g., from linear regression on SDK data) instead of the simple boundary model.

pub fn program_for_group(&self, g: u32) -> Ms2GroupProgram

pub fn program_slices_for_group(&self, group: u32) -> Vec<ProgramSlice>

Collect all program slices for a window group from DiaFrameMsMsWindows. Isolation window: [isolation_mz - width/2, isolation_mz + width/2]

pub fn sample_precursor_signal( &self, num_frames: usize, max_intensity: f64, take_probability: f64, ) -> TimsFrame

pub fn sample_fragment_signal( &self, num_frames: usize, window_group: u32, max_intensity: f64, take_probability: f64, ) -> TimsFrame

pub fn dia_window_groups(&self) -> Vec<u32>

All DIA window_group IDs present in the file (sorted unique).

pub fn window_groups_for_precursor( &self, prec_mz: f32, im_apex: f32, ) -> Vec<u32>

pub fn fragment_frame_ids_and_times_for_group_core( &self, window_group: u32, ) -> (Vec<u32>, Vec<f32>)

RT-sorted fragment frames for a given DIA group.

pub fn scan_unions_for_window_group_core( &self, window_group: u32, ) -> Option<Vec<(usize, usize)>>

Merged, sorted global scan unions for this DIA group, from DiaFrameMsMsWindows. Returns None if there are no window rows for this group.

pub fn mz_bounds_for_window_group_core( &self, window_group: u32, ) -> Option<(f32, f32)>

m/z unions (min..max) for the group from DiaFrameMsMsWindows (wide clamp).

pub fn make_rt_frames_for_group( &self, window_group: u32, tof_step: i32, ) -> RtFrames

RT-sorted FRAGMENT frames + times for a DIA group, converted into FrameBinView rows. tof_step controls TOF granularity of CSR binning.

pub fn make_rt_frames_for_precursor(&self, tof_step: i32) -> RtFrames

RT-sorted PRECURSOR frames (ms_ms_type == 0) into FrameBinView rows. tof_step controls TOF granularity of CSR binning.

pub fn tof_scale_for_group(&self, window_group: u32, tof_step: i32) -> TofScale

Build a TOF-based scale for a DIA group. tof_step = 1 → max TOF resolution; larger steps downsample.

pub fn tof_scale_from_frames_scan( &self, frame_ids: &[u32], tof_step: i32, ) -> Option<TofScale>

Conservative: derive a TOF scale by scanning actual frame data.

pub fn evaluate_specs_1d_threads( &self, rt_frames: &RtFrames, specs: &[ClusterSpec1D], opts: &Eval1DOpts, num_threads: usize, ) -> Vec<ClusterResult1D>

Evaluate a batch of 1D cluster specs on the given RtFrames.

• Runs spec evaluation (marginals + moment fits) in parallel.
• Optionally attaches raw points using the finalized TOF-bin window and the spec’s IM/RT windows.
• num_threads == 0 => use rayon’s global pool.

pub fn clusters_for_group( &self, window_group: u32, tof_step: i32, im_peaks: &[ImPeak1D], rt_params: RtExpandParams, build_opts: &BuildSpecOpts, eval_opts: &Eval1DOpts, require_rt_overlap: bool, num_threads: usize, ) -> Vec<ClusterResult1D>

pub fn clusters_for_precursor( &self, tof_step: i32, im_peaks: &[ImPeak1D], rt_params: RtExpandParams, build_opts: &BuildSpecOpts, eval_opts: &Eval1DOpts, require_rt_overlap: bool, num_threads: usize, ) -> Vec<ClusterResult1D>

pub fn build_pseudo_spectra_from_clusters_geom( &self, ms1: &[ClusterResult1D], ms2: &[ClusterResult1D], features: Option<&[SimpleFeature]>, cand_opts: &CandidateOpts, score_opts: &ScoreOpts, pseudo_opts: &PseudoSpecOpts, ) -> PseudoBuildResult

End-to-end DIA → pseudo-DDA builder (geometric scoring).

Thin wrapper around build_pseudo_spectra_end_to_end.

pub fn build_pseudo_spectra_from_clusters_xic( &self, ms1: &[ClusterResult1D], ms2: &[ClusterResult1D], features: Option<&[SimpleFeature]>, cand_opts: &CandidateOpts, xic_opts: &XicScoreOpts, pseudo_opts: &PseudoSpecOpts, ) -> PseudoBuildResult

End-to-end DIA → pseudo-DDA builder (XIC-based scoring).

Thin wrapper around build_pseudo_spectra_end_to_end_xic.

pub fn build_pseudo_spectra_all_pairs_from_clusters( &self, ms1: &[ClusterResult1D], ms2: &[ClusterResult1D], features: Option<&[SimpleFeature]>, pseudo_opts: &PseudoSpecOpts, ) -> PseudoBuildResult

Naive “all pairs” builder stays as-is, still returning Vec.

pub fn clusters_for_group_opts( &self, window_group: u32, im_peaks: &[ImPeak1D], opts: &ClusterExtractionOpts, ) -> Vec<ClusterResult1D>

Extract clusters for a DIA window group using options struct.

pub fn clusters_for_precursor_opts( &self, im_peaks: &[ImPeak1D], opts: &ClusterExtractionOpts, ) -> Vec<ClusterResult1D>

Extract clusters for precursor (MS1) frames using options struct.

pub fn tof_rt_grid_precursor(&self, tof_step: i32) -> TofRtGrid

Dense TOF×RT grid for all PRECURSOR (MS1) frames. tof_step controls TOF bin granularity (1 = full resolution).

pub fn tof_rt_grid_for_group( &self, window_group: u32, tof_step: i32, ) -> TofRtGrid

Dense TOF×RT grid for FRAGMENT frames in a DIA window group. tof_step controls TOF bin granularity (1 = full resolution).

pub fn debug_extract_raw_for_clusters( &self, clusters: &[ClusterResult1D], window_group: Option<u32>, tof_step: i32, max_points: Option<usize>, num_threads: usize, ) -> Vec<RawPoints>

Debug helper: for a bunch of clusters that all live on the same DIA grid (either MS1 or one MS2 window_group), extract RawPoints per cluster.

• clusters: precursor or fragment clusters. All must have the same ms_level.
• window_group: if you pass Some(g), we treat them as MS2 clusters on that DIA group. If None and ms_level == 2, we try to infer g from the first cluster’s window_group.
• tof_step: must be the same as used during clustering.
• max_points: optional thinning cap per cluster.
• num_threads: used for get_slice in the raw extractor.

Trait Implementations

impl IndexConverter for TimsDatasetDIA

fn tof_to_mz(&self, frame_id: u32, tof_values: &Vec<u32>) -> Vec<f64>

fn mz_to_tof(&self, frame_id: u32, mz_values: &Vec<f64>) -> Vec<u32>

fn scan_to_inverse_mobility( &self, frame_id: u32, scan_values: &Vec<u32>, ) -> Vec<f64>

fn inverse_mobility_to_scan( &self, frame_id: u32, inverse_mobility_values: &Vec<f64>, ) -> Vec<u32>

impl TimsData for TimsDatasetDIA

fn get_frame(&self, frame_id: u32) -> TimsFrame

fn get_raw_frame(&self, frame_id: u32) -> RawTimsFrame

fn get_slice(&self, frame_ids: Vec<u32>, num_threads: usize) -> TimsSlice

fn get_acquisition_mode(&self) -> AcquisitionMode

fn get_frame_count(&self) -> i32

fn get_data_path(&self) -> &str