rustdf/data/
meta.rs

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extern crate rusqlite;

use rusqlite::{Connection, Result};
use std::path::Path;

#[derive(Debug, Clone)]
pub struct DiaMsMisInfo {
    pub frame_id: u32,
    pub window_group: u32,
}

#[derive(Debug, Clone)]
pub struct DiaMsMsWindow {
    pub window_group: u32,
    pub scan_num_begin: u32,
    pub scan_num_end: u32,
    pub isolation_mz: f64,
    pub isolation_width: f64,
    pub collision_energy: f64,
}

#[derive(Debug, Clone)]
pub struct PasefMsMsMeta {
    pub frame_id: i64,
    pub scan_num_begin: i64,
    pub scan_num_end: i64,
    pub isolation_mz: f64,
    pub isolation_width: f64,
    pub collision_energy: f64,
    pub precursor_id: i64,
}

#[derive(Debug, Clone)]
pub struct DDAPrecursorMeta {
    pub precursor_id: i64,
    pub precursor_mz_highest_intensity: f64,
    pub precursor_mz_average: f64,
    pub precursor_mz_monoisotopic: Option<f64>,
    pub precursor_charge: Option<i64>,
    pub precursor_average_scan_number: f64,
    pub precursor_total_intensity: f64,
    pub precursor_frame_id: i64,
}

#[derive(Debug, Clone)]
pub struct DDAPrecursor {
    pub frame_id: i64,
    pub precursor_id: i64,
    pub mono_mz: Option<f64>,
    pub highest_intensity_mz: f64,
    pub average_mz: f64,
    pub charge: Option<i64>,
    pub inverse_ion_mobility: f64,
    pub collision_energy: f64,
    pub precuror_total_intensity: f64,
    pub isolation_mz: f64,
    pub isolation_width: f64,
}

#[derive(Debug, Clone)]
pub struct DDAFragmentInfo {
    pub frame_id: i64,
    pub scan_begin: i64,
    pub scan_end: i64,
    pub isolation_mz: f64,
    pub isolation_width: f64,
    pub collision_energy: f64,
    pub precursor_id: i64,
}

pub struct DIAFragmentFrameInfo {}

pub struct DIAWindowGroupInfo {}

#[derive(Debug)]
pub struct GlobalMetaData {
    pub schema_type: String,
    pub schema_version_major: i64,
    pub schema_version_minor: i64,
    pub acquisition_software_vendor: String,
    pub instrument_vendor: String,
    pub closed_property: i64,
    pub tims_compression_type: i64,
    pub max_num_peaks_per_scan: i64,
    pub mz_acquisition_range_lower: f64,
    pub mz_acquisition_range_upper: f64,
    pub one_over_k0_range_lower: f64,
    pub one_over_k0_range_upper: f64,
    pub tof_max_index: u32,
}

#[derive(Debug)]
pub struct FrameMeta {
    pub id: i64,
    pub time: f64,
    pub polarity: String,
    pub scan_mode: i64,
    pub ms_ms_type: i64,
    pub tims_id: i64,
    pub max_intensity: f64,
    pub sum_intensity: f64,
    pub num_scans: i64,
    pub num_peaks: i64,
    pub mz_calibration: i64,
    pub t_1: f64,
    pub t_2: f64,
    pub tims_calibration: i64,
    pub property_group: i64,
    pub accumulation_time: f64,
    pub ramp_time: f64,
}

struct GlobalMetaInternal {
    key: String,
    value: String,
}

pub fn read_dda_precursor_meta(
    bruker_d_folder_name: &str,
) -> Result<Vec<DDAPrecursorMeta>, Box<dyn std::error::Error>> {
    // Connect to the database
    let db_path = Path::new(bruker_d_folder_name).join("analysis.tdf");
    let conn = Connection::open(db_path)?;

    // prepare the query
    let rows: Vec<&str> = vec![
        "Id",
        "LargestPeakMz",
        "AverageMz",
        "MonoisotopicMz",
        "Charge",
        "ScanNumber",
        "Intensity",
        "Parent",
    ];
    let query = format!("SELECT {} FROM Precursors", rows.join(", "));

    // execute the query
    let frames_rows: Result<Vec<DDAPrecursorMeta>, _> = conn
        .prepare(&query)?
        .query_map([], |row| {
            Ok(DDAPrecursorMeta {
                precursor_id: row.get(0)?,
                precursor_mz_highest_intensity: row.get(1)?,
                precursor_mz_average: row.get(2)?,
                precursor_mz_monoisotopic: row.get(3)?, // Now using Option<f64>
                precursor_charge: row.get(4)?,          // Now using Option<i64>
                precursor_average_scan_number: row.get(5)?,
                precursor_total_intensity: row.get(6)?,
                precursor_frame_id: row.get(7)?,
            })
        })?
        .collect();

    // return the frames
    Ok(frames_rows?)
}

pub fn read_pasef_frame_ms_ms_info(
    bruker_d_folder_name: &str,
) -> Result<Vec<PasefMsMsMeta>, Box<dyn std::error::Error>> {
    // Connect to the database
    let db_path = Path::new(bruker_d_folder_name).join("analysis.tdf");
    let conn = Connection::open(db_path)?;

    // prepare the query
    let rows: Vec<&str> = vec![
        "Frame",
        "ScanNumBegin",
        "ScanNumEnd",
        "IsolationMz",
        "IsolationWidth",
        "CollisionEnergy",
        "Precursor",
    ];
    let query = format!("SELECT {} FROM PasefFrameMsMsInfo", rows.join(", "));

    // execute the query
    let frames_rows: Result<Vec<PasefMsMsMeta>, _> = conn
        .prepare(&query)?
        .query_map([], |row| {
            Ok(PasefMsMsMeta {
                frame_id: row.get(0)?,
                scan_num_begin: row.get(1)?,
                scan_num_end: row.get(2)?,
                isolation_mz: row.get(3)?,
                isolation_width: row.get(4)?,
                collision_energy: row.get(5)?,
                precursor_id: row.get(6)?,
            })
        })?
        .collect();

    // return the frames
    Ok(frames_rows?)
}

// Read the global meta data from the analysis.tdf file
pub fn read_global_meta_sql(
    bruker_d_folder_name: &str,
) -> Result<GlobalMetaData, Box<dyn std::error::Error>> {
    // Connect to the database
    let db_path = Path::new(bruker_d_folder_name).join("analysis.tdf");
    let conn = Connection::open(db_path)?;

    // execute the query
    let frames_rows: Result<Vec<GlobalMetaInternal>, _> = conn
        .prepare("SELECT * FROM GlobalMetadata")?
        .query_map([], |row| {
            Ok(GlobalMetaInternal {
                key: row.get(0)?,
                value: row.get(1)?,
            })
        })?
        .collect();

    let mut global_meta = GlobalMetaData {
        schema_type: String::new(),
        schema_version_major: -1,
        schema_version_minor: -1,
        acquisition_software_vendor: String::new(),
        instrument_vendor: String::new(),
        closed_property: -1,
        tims_compression_type: -1,
        max_num_peaks_per_scan: -1,
        mz_acquisition_range_lower: -1.0,
        mz_acquisition_range_upper: -1.0,
        one_over_k0_range_lower: -1.0,
        one_over_k0_range_upper: -1.0,
        tof_max_index: 0,
    };

    // go over the keys and parse values for the global meta data
    for row in frames_rows? {
        match row.key.as_str() {
            "SchemaType" => global_meta.schema_type = row.value,
            "SchemaVersionMajor" => {
                global_meta.schema_version_major = row.value.parse::<i64>().unwrap()
            }
            "SchemaVersionMinor" => {
                global_meta.schema_version_minor = row.value.parse::<i64>().unwrap()
            }
            "AcquisitionSoftwareVendor" => global_meta.acquisition_software_vendor = row.value,
            "InstrumentVendor" => global_meta.instrument_vendor = row.value,
            "ClosedProperly" => global_meta.closed_property = row.value.parse::<i64>().unwrap(),
            "TimsCompressionType" => {
                global_meta.tims_compression_type = row.value.parse::<i64>().unwrap()
            }
            "MaxNumPeaksPerScan" => {
                global_meta.max_num_peaks_per_scan = row.value.parse::<i64>().unwrap()
            }
            "MzAcqRangeLower" => {
                global_meta.mz_acquisition_range_lower = row.value.parse::<f64>().unwrap()
            }
            "MzAcqRangeUpper" => {
                global_meta.mz_acquisition_range_upper = row.value.parse::<f64>().unwrap()
            }
            "OneOverK0AcqRangeLower" => {
                global_meta.one_over_k0_range_lower = row.value.parse::<f64>().unwrap()
            }
            "OneOverK0AcqRangeUpper" => {
                global_meta.one_over_k0_range_upper = row.value.parse::<f64>().unwrap()
            }
            "DigitizerNumSamples" => {
                global_meta.tof_max_index = (row.value.parse::<i64>().unwrap() + 1) as u32
            }
            _ => (),
        }
    }
    // return global_meta
    Ok(global_meta)
}

// Read the frame meta data from the analysis.tdf file
pub fn read_meta_data_sql(
    bruker_d_folder_name: &str,
) -> Result<Vec<FrameMeta>, Box<dyn std::error::Error>> {
    // Connect to the database
    let db_path = Path::new(bruker_d_folder_name).join("analysis.tdf");
    let conn = Connection::open(db_path)?;

    // prepare the query
    let rows: Vec<&str> = vec![
        "Id",
        "Time",
        "ScanMode",
        "Polarity",
        "MsMsType",
        "TimsId",
        "MaxIntensity",
        "SummedIntensities",
        "NumScans",
        "NumPeaks",
        "MzCalibration",
        "T1",
        "T2",
        "TimsCalibration",
        "PropertyGroup",
        "AccumulationTime",
        "RampTime",
    ];
    let query = format!("SELECT {} FROM Frames", rows.join(", "));

    // execute the query
    let frames_rows: Result<Vec<FrameMeta>, _> = conn
        .prepare(&query)?
        .query_map([], |row| {
            Ok(FrameMeta {
                id: row.get(0)?,
                time: row.get(1)?,
                scan_mode: row.get(2)?,
                polarity: row.get(3)?,
                ms_ms_type: row.get(4)?,
                tims_id: row.get(5)?,
                max_intensity: row.get(6)?,
                sum_intensity: row.get(7)?,
                num_scans: row.get(8)?,
                num_peaks: row.get(9)?,
                mz_calibration: row.get(10)?,
                t_1: row.get(11)?,
                t_2: row.get(12)?,
                tims_calibration: row.get(13)?,
                property_group: row.get(14)?,
                accumulation_time: row.get(15)?,
                ramp_time: row.get(16)?,
            })
        })?
        .collect();

    // return the frames
    Ok(frames_rows?)
}

pub fn read_dia_ms_ms_info(
    bruker_d_folder_name: &str,
) -> Result<Vec<DiaMsMisInfo>, Box<dyn std::error::Error>> {
    // Connect to the database
    let db_path = Path::new(bruker_d_folder_name).join("analysis.tdf");
    let conn = Connection::open(db_path)?;

    // prepare the query
    let rows: Vec<&str> = vec!["Frame", "WindowGroup"];
    let query = format!("SELECT {} FROM DiaFrameMsMsInfo", rows.join(", "));

    // execute the query
    let frames_rows: Result<Vec<DiaMsMisInfo>, _> = conn
        .prepare(&query)?
        .query_map([], |row| {
            Ok(DiaMsMisInfo {
                frame_id: row.get(0)?,
                window_group: row.get(1)?,
            })
        })?
        .collect();

    // return the frames
    Ok(frames_rows?)
}

pub fn read_dia_ms_ms_windows(
    bruker_d_folder_name: &str,
) -> Result<Vec<DiaMsMsWindow>, Box<dyn std::error::Error>> {
    // Connect to the database
    let db_path = Path::new(bruker_d_folder_name).join("analysis.tdf");
    let conn = Connection::open(db_path)?;

    // prepare the query
    let rows: Vec<&str> = vec![
        "WindowGroup",
        "ScanNumBegin",
        "ScanNumEnd",
        "IsolationMz",
        "IsolationWidth",
        "CollisionEnergy",
    ];
    let query = format!("SELECT {} FROM DiaFrameMsMsWindows", rows.join(", "));

    // execute the query
    let frames_rows: Result<Vec<DiaMsMsWindow>, _> = conn
        .prepare(&query)?
        .query_map([], |row| {
            Ok(DiaMsMsWindow {
                window_group: row.get(0)?,
                scan_num_begin: row.get(1)?,
                scan_num_end: row.get(2)?,
                isolation_mz: row.get(3)?,
                isolation_width: row.get(4)?,
                collision_energy: row.get(5)?,
            })
        })?
        .collect();

    // return the frames
    Ok(frames_rows?)
}
rustdf/data/meta.rs

rustdf/data/
meta.rs
