pygecko.gc_tools.analysis package
Submodules
pygecko.gc_tools.analysis.analysis_settings module
- class pygecko.gc_tools.analysis.analysis_settings.Analysis_Settings(chromatogram: ndarray)
Bases:
objectAnalysis_Settings class for storing information about parameters for raw data processing.
- sn
Signal to noise ratio for peak detection.
- Type:
int
- time_range
Time range for peak detection.
- Type:
tuple
- indices_range
Indices range for peak detection.
- Type:
list
- width
Width for peak detection.
- Type:
int, float
- prominence_ms
Prominence for peak detection via MS.
- Type:
int
- prominence_fid
Prominence for peak detection via FID.
- Type:
int
- trace_prominence
Prominence for peak detection on individual mass traces.
- Type:
int
- height
Height for peak detection.
- Type:
int
- savgol_window
Window size for Savitzky-Golay filter.
- Type:
int
- max_half_window
Maximum half window size for Snip algorithm.
- Type:
int
- boarder_threshold
Threshold for boarder detection.
- Type:
int
- boarder_window
Window size for boarder detection.
- Type:
int
- max_isotopic_diff
Max deviation of isotopic peak intensity for analyte assignment.
- Type:
float
- min_rel_intensity
Minimum relative intensity for m/z trace to be considered for analyte assignment.
- Type:
float
- scan_rate
Scan rate of chromatogram.
- Type:
float
- boarder_threshold: int | None
- boarder_window: int | None
- height: int | None
- indices_range: list[int | None]
- max_half_window: int | None
- max_isotopic_diff: float | None
- min_rel_intensity: float | None
- pop(key: str, default)
- prominence_fid: int | None
- prominence_ms: int | None
- savgol_window: int | None
- scan_rate: float
- sn: int
- time_range: tuple | None
- trace_prominence: int | None
- update(**kwargs)
Updates settings by setting the keyword arguments after checking.
- Parameters:
**kwargs – Keyword arguments for settings.
- width: int | float | None
pygecko.gc_tools.analysis.quantification module
- class pygecko.gc_tools.analysis.quantification.Quantification
Bases:
objectA class wrapping functions for calculating yields based on peak areas.
- static quantify_calibration(peak: FID_Peak, standard: FID_Peak, slope: float, intercept: float) int
Returns the relative quantity of an analyte based on a calibration curve.
- Parameters:
- Returns:
Relative quantity of analyte.
- Return type:
yield_ (int)
- static quantify_polyarc(peak: FID_Peak, std_peak: FID_Peak) int
Returns the relative quantity of an analyte based on the ratio of the analytes carbon-normalized peak area to the carbon-normalized peak area of a standard.
- Parameters:
peak – Peak to calculate the relative quantity for.
std_peak – Standard peak to use for quantification.
- Returns:
Relative quantity of analyte.
- Return type:
yield_ (int)
pygecko.gc_tools.analysis.retention_indices module
- class pygecko.gc_tools.analysis.retention_indices.RI_Calibration(injection: FID_Injection | MS_Injection, c_count: int, rt: float)
Bases:
objectA class for storing information about a retention index calibration and calculating retention indices.
- calibration
Calibration injection.
- Type:
- alkanes
Array of alkanes with columns for smiles, carbon count and retention time.
- Type:
np.ndarray
- gradient
Gradient of the linear fit of the calibration.
- Type:
float
- intercept
Intercept of the linear fit of the calibration.
- Type:
float
- alkanes: ndarray
- assign_ris(gc_data: Injection | GC_Sequence, alignment=False) None
Assigns retention indices to peaks in a GC_Sequence or Injection.
- Parameters:
gc_data (Injection|GC_Sequence) – GC_Sequence or Injection to assign retention indices to.
alignment (bool) – If True, retention times are aligned to the internal standard. Default is False.
- calculate_ri(peak: Peak, align_factor=0) float | None
Returns the retention index for a given peak.
- Parameters:
peak (Peak) – Peak to calculate the retention index for.
align_factor (float) – Alignment factor for the retention time. Default is 0.
- Returns:
Retention index.
- Return type:
ri (float)
- calculate_ri_fit(rt)
Returns the retention index for a given retention time calculated using the linear fit of the calibration.
- Parameters:
rt (float) – Retention time.
- Returns:
Retention index.
- Return type:
ri (float)
- calibration: FID_Injection | MS_Injection
- gradient: float
- intercept: float
pygecko.gc_tools.analysis.spectral_matching module
- class pygecko.gc_tools.analysis.spectral_matching.Spectral_Match(peaks: tuple[MS_Peak, MS_Peak], ms_score, rt_score)
Bases:
objectA class to represent a match between two mass spectra.
- ms_score
Score of the match based on the cosine similarity of the mass spectra.
- Type:
float
- rt_score
Score of the match based on the difference in retention time.
- Type:
float
- classmethod find_peak(peak: MS_Peak, injection: MS_Injection, rt_threshold=0.1, ms_threshold=0.9) T | None
Returns a Spectral_Match object if the peak is found in the injection and None otherwise.
- Parameters:
peak (MS_Peak) – Peak to find.
injection (MS_Injection) – Injection to search for the peak.
rt_threshold (float, optional) – Retention time threshold for the match. Defaults to 0.1.
ms_threshold (float, optional) – Mass spectrum similarity threshold for the match. Defaults to 0.9.
- Returns:
Spectral_Match object if the peak is found and None otherwise.
- Return type:
Spectral_Match|None
- classmethod match_peaks(peak1: MS_Peak, peak2: MS_Peak, rt_threshold=0.1, ms_threshold=0.9) T | None
Returns a Spectral_Match object if the peaks match and None otherwise.
- Parameters:
- Returns:
Spectral_Match object if the peaks match and None otherwise.
- Return type:
Spectral_Match|None
- ms_score: float
- rt_score: float