tidyms.raw_data_utils¶

Functions used to extract information from raw data.

accumulate_spectra(ms_data: MSData, *, start_time: float, end_time: float, subtract_left_time: float | None = None, subtract_right_time: float | None = None, ms_level: int = 1) → MSSpectrum¶

accumulates a series of consecutive spectra into a single spectrum.

Parameters:

ms_dataMSData
start_time: float: Start accumulating scans at this scan time.
end_time: float: Ends accumulation after this scan time.
subtract_left_timefloat or None, default=None: Scans with acquisition times lower than this value are subtracted from the accumulated spectrum. If None, no subtraction is done.
subtract_right_timefloat or None, default=None: Scans with acquisition times greater than this value are subtracted from the accumulated spectrum. If None, no subtraction is done.
ms_levelint, default=1: ms level used to build the accumulated spectrum.

Returns:

MSSpectrum

make_chromatograms(ms_data: MSData, mz: ndarray, *, window: float | None = None, accumulator: str = 'sum', fill_missing: bool = True, ms_level: int = 1, start_time: float = 0.0, end_time: float | None = None) → List[Chromatogram]¶

Computes extracted ion chromatograms using a list of m/z values.

Parameters:

ms_dataMSData
mzarray: m/z values used to build the EICs.
windowpositive number or None, default=None: m/z tolerance used to build the EICs. If ms_data.instrument is "qtof", the default value is 0.05. If ms_data.instrument is "orbitrap" the default value is 0.005.
accumulator{“sum”, “mean”}, default=”sum”: Mode used to accumulate the values inside the m/z window. "sum" computes the total intensity inside the window. "mean" divides the total intensity using the number of points inside the window.
fill_missingbool, default=True: If True, sets the intensity to zero if no signal was found in a given scan. If False, missing values are set to NaN.
ms_levelint, default=1: ms level used to build the chromatograms.
start_timefloat, default=0.0: include scans starting at this acquisition time.
end_timefloat or None, default=None: Stops when the acquisition time is higher than this value.

Returns:

chromatogramsList of Chromatograms

make_roi(ms_data: MSData, *, tolerance: float | None = None, max_missing: int | None = None, min_length: int | None = None, min_intensity: float = 0.0, multiple_match: str = 'reduce', mz_reduce: str | Callable = 'mean', sp_reduce: str | Callable = 'sum', targeted_mz: ndarray | None = None, pad: int | None = None, ms_level: int = 1, start_time: float = 0.0, end_time: float | None = None, min_snr: float = 10, min_distance: float | None = None) → List[Roi]¶

Builds regions of interest (ROI) from raw data.

ROI are created by connecting values across scans based on the closeness in m/z. See the user guide for a description of the algorithm used.

Parameters:

ms_dataMSData

tolerancepositive number or None, default=None

m/z tolerance to connect values across scans. If None, the value is set based on the value of ms_data.instrument. If "qtof" is used, the tolerance is 0.01. If "orbitrap" is used, the tolerance is 0.005.

max_missingnon-negative integer or None, default=None

maximum number of consecutive missing values in a valid ROI. If None, the value is set to 1.

min_lengthpositive integer or None, default=None

The minimum length of a valid ROI, defined as the number of non-NaN values in the ROI. If, None, the value is set based on ms_data.separation. If "uplc", the value is set to 10. If "hplc", the value is set to 20.

min_intensitynon-negative number , default=0.0

Minimum intensity in a valid ROI.

pad: int or None, default=None

Pad dummy values to the left and right of the ROI. This produces better peak picking results when searching low intensity peaks in a ROI. Using None set the value to 2.

multiple_match{“closest”, “reduce”}, default=”reduce”

How peaks are matched when there is more than one valid match. If "closest" is used, the closest peak is assigned as a match and the others are used to create new ROIs. If "reduce" is used, unique m/z and intensity values are generated using the reduce function in mz_reduce and sp_reduce respectively.

mz_reduce“mean” or Callable, default=”mean”

Function used to reduce m/z values. If "mean" is used, the mean value of all valid m/z is used. Any function that accepts numpy arrays and return numbers can be used. Used only when multiple_match is set to "reduce". See the following prototype:

def mz_reduce(mz_match: np.ndarray) -> float:
    pass

sp_reduce{“mean”, “sum”} or Callable, default=”sum”

Function used to reduce intensity values. "mean" computes the mean intensity and "sum" computes the total intensity. Any function that accepts numpy arrays and return numbers can be used. Only used when multiple_match is set to "reduce". See the prototype shown on mz_reduce.

targeted_mznumpy.ndarray or None, default=None

A list of m/z values to perform a targeted ROI creation. If this value is provided, only ROI with these m/z values will be created.

ms_levelint, default=1

ms level used to build the ROI.

start_timefloat, default=0.0

Use scans starting at this acquisition time.

end_timefloat or None, default=None

Stops when the acquisition time is higher than this value.

min_snrpositive number, default=10.0

Minimum signal-to-noise ratio of the peaks. Used only to convert profile data to centroid mode

min_distancepositive number or None, default=None

Minimum distance between consecutive peaks. If None, the value is set to 0.01 if ms_data.instrument is "qtof" or to 0.005 if ms_data.instrument is "orbitrap". Used only to convert profile data to centroid mode.

Returns:

roilist[Roi]: A list with the detected regions of interest.