`libgunshotmatch.method`¶

Methods for GunShotMatch analysis.

Classes:

`MethodBase`()	Base class for methods.
`Method`([intensity_matrix, peak_detection, …])	Overall GunShotMatch method.
`IntensityMatrixMethod`([crop_mass_range, …])	Method used for constructing an intensity matrix from a datafile.
`PeakDetectionMethod`([points, scans])	Method used for Biller-Biemann peak detection.
`PeakFilterMethod`([noise_filter, …])	Method used for peak filtering.
`AlignmentMethod`([rt_modulation, …])	Method used for peak alignment.
`ConsolidateMethod`([name_filter, …])	Method used for consolidation (finding most likely identity for aligned peaks).
`SavitzkyGolayMethod`([enable, window, degree])	Method parameters for the Savitzky-Golay filter.

class MethodBase[source]¶

Base class for methods.

Methods:

`from_dict`(method)	Construct a `MethodBase` from a dictionary.
`to_dict`()	Convert a `MethodBase` to a dictionary.

classmethod from_dict(method)[source]¶

Construct a MethodBase from a dictionary.

Parameters: method (Mapping[str, Any])
Return type: MethodBase

to_dict()[source]¶

Convert a MethodBase to a dictionary.

Return type: Dict[str, Any]

class Method(intensity_matrix=IntensityMatrixMethod(), peak_detection=PeakDetectionMethod(), peak_filter=PeakFilterMethod(), alignment=AlignmentMethod(), consolidate=ConsolidateMethod())[source]¶

Bases: libgunshotmatch.method.MethodBase

Overall GunShotMatch method.

Parameters

intensity_matrix (IntensityMatrixMethod) – Method used for constructing an intensity matrix from a datafile. Default IntensityMatrixMethod(crop_mass_range=(50, 500), savitzky_golay=SavitzkyGolayMethod(enable=True, window=7, degree=2), tophat=True, tophat_structure_size='1.5m').
peak_detection (PeakDetectionMethod) – Method used for Biller-Biemann peak detection. Default PeakDetectionMethod(points=10, scans=1).
peak_filter (PeakFilterMethod) – Method used for peak filtering. Default PeakFilterMethod(noise_filter=True, noise_threshold=2, base_peak_filter={73, 147}, rt_range=None).
alignment (AlignmentMethod) – Method used for peak alignment. Default AlignmentMethod(rt_modulation=2.5, gap_penalty=0.3, min_peaks=1, top_n_peaks=80, min_peak_area=0.0).
consolidate (ConsolidateMethod) – Method used for consolidation (finding most likely identity for aligned peaks). Default ConsolidateMethod(name_filter=[], min_match_factor=600, min_appearances=-1).

Attributes:

`alignment`	Method used for peak alignment.
`consolidate`	Method used for consolidation (finding most likely identity for aligned peaks).
`intensity_matrix`	Method used for constructing an intensity matrix from a datafile.
`peak_detection`	Method used for Biller-Biemann peak detection.
`peak_filter`	Method used for peak filtering.

Methods:

`from_json`(json_string)	Parse a `Method` from a JSON string.
`from_toml`(toml_string)	Parse a `Method` from a TOML string.
`to_toml`()	Convert a `Method` to a TOML string.

alignment¶

Type: AlignmentMethod

Method used for peak alignment.

consolidate¶

Type: ConsolidateMethod

Method used for consolidation (finding most likely identity for aligned peaks).

classmethod from_json(json_string)[source]¶

Parse a Method from a JSON string.

Parameters: json_string (str)
Return type: Method

classmethod from_toml(toml_string)[source]¶

Parse a Method from a TOML string.

Parameters: toml_string (str)
Return type: Method

intensity_matrix¶

Type: IntensityMatrixMethod

Method used for constructing an intensity matrix from a datafile.

peak_detection¶

Type: PeakDetectionMethod

Method used for Biller-Biemann peak detection.

peak_filter¶

Type: PeakFilterMethod

Method used for peak filtering.

to_toml()[source]¶

Convert a Method to a TOML string.

Return type: str

class IntensityMatrixMethod(crop_mass_range=(50, 500), savitzky_golay=SavitzkyGolayMethod(enable=True, window=7, degree=2), tophat=True, tophat_structure_size='1.5m')[source]¶

Bases: libgunshotmatch.method.MethodBase

Method used for constructing an intensity matrix from a datafile.

Parameters

crop_mass_range (Optional[Iterable]) – The range of masses to which the GC-MS data should be limited to. Default (50, 500).
savitzky_golay (Union[bool, SavitzkyGolayMethod, Dict[str, Any]]) – Settings for Savitzky-Golay smoothing. Default SavitzkyGolayMethod(enable=True, window=7, degree=2).
tophat (bool) – Whether to perform Tophat baseline correction. Default True.
tophat_structure_size (str) – The structure size for Tophat baseline correction. Default '1.5m'.

Attributes:

`crop_mass_range`	The range of masses to which the GC-MS data should be limited to.
`savitzky_golay`	Settings for Savitzky-Golay smoothing.
`tophat`	Whether to perform Tophat baseline correction.
`tophat_structure_size`	The structure size for Tophat baseline correction.

crop_mass_range¶

Type: Optional[Tuple[int, int]]

The range of masses to which the GC-MS data should be limited to.

savitzky_golay¶

Type: SavitzkyGolayMethod

Settings for Savitzky-Golay smoothing.

tophat¶

Type: bool

Whether to perform Tophat baseline correction.

tophat_structure_size¶

Type: str

The structure size for Tophat baseline correction.

class PeakDetectionMethod(points=10, scans=1)[source]¶

Bases: libgunshotmatch.method.MethodBase

Method used for Biller-Biemann peak detection.

Parameters

points (int) – Number of scans over which to consider a maxima to be a peak. Default 10.
scans (int) – Number of scans to combine in a single peak from to compensate for spectra skewing. Default 1.

Attributes:

`points`	Number of scans over which to consider a maxima to be a peak.
`scans`	Number of scans to combine in a single peak from to compensate for spectra skewing.

points¶

Type: int

Number of scans over which to consider a maxima to be a peak.

scans¶

Type: int

Number of scans to combine in a single peak from to compensate for spectra skewing.

class PeakFilterMethod(noise_filter=True, noise_threshold=2, base_peak_filter={73, 147}, rt_range=None)[source]¶

Bases: libgunshotmatch.method.MethodBase

Method used for peak filtering.

Parameters

noise_filter (bool) – Whether to perform automatic noise filtering of the peak list. Default True.
noise_threshold (int) – The minimum number of ions that must have intensities above the noise floor, otherwise the peak is excluded. Default 2.
base_peak_filter (Set[int]) – Peaks whose base peak is at one of the listed masses (m/z) are excluded. Default {73, 147}.
rt_range (Optional[Iterable]) – Optional retention time range (in minutes) to filter the peak list to. Default None.

Attributes:

`base_peak_filter`	Peaks whose base peak is at one of the listed masses (m/z) are excluded.
`noise_filter`	Whether to perform automatic noise filtering of the peak list.
`noise_threshold`	The minimum number of ions that must have intensities above the noise floor, otherwise the peak is excluded.
`rt_range`	Optional retention time range (in minutes) to filter the peak list to.

base_peak_filter¶

Type: Set[int]

Peaks whose base peak is at one of the listed masses (m/z) are excluded.

noise_filter¶

Type: bool

Whether to perform automatic noise filtering of the peak list.

noise_threshold¶

Type: int

The minimum number of ions that must have intensities above the noise floor, otherwise the peak is excluded.

rt_range¶

Type: Optional[Tuple[float, float]]

Optional retention time range (in minutes) to filter the peak list to.

class AlignmentMethod(rt_modulation=2.5, gap_penalty=0.3, min_peaks=1, top_n_peaks=80, min_peak_area=0.0)[source]¶

Bases: libgunshotmatch.method.MethodBase

Method used for peak alignment.

Parameters

rt_modulation (float) – Retention time tolerance parameter for pairwise alignments. Default 2.5.
gap_penalty (float) – Gap parameter for pairwise alignments. Default 0.3.
min_peaks (int) – Minimum number of peaks required for the alignment position to survive filtering. If set to -1 the number of repeats in the project are used. Default 1.
top_n_peaks (int) – Number of peaks (starting with the largest) to include in the output. Default 80.
min_peak_area (float) – Minimum area of peaks to include in the output. Default 0.0.

Attributes:

`gap_penalty`	Gap parameter for pairwise alignments.
`min_peak_area`	Minimum area of peaks to include in the output.
`min_peaks`	Minimum number of peaks required for the alignment position to survive filtering.
`rt_modulation`	Retention time tolerance parameter for pairwise alignments.
`top_n_peaks`	Number of peaks (starting with the largest) to include in the output.

gap_penalty¶

Type: float

Gap parameter for pairwise alignments.

min_peak_area¶

Type: float

Minimum area of peaks to include in the output.

min_peaks¶

Type: int

Minimum number of peaks required for the alignment position to survive filtering.

If set to -1 the number of repeats in the project are used.

rt_modulation¶

Type: float

Retention time tolerance parameter for pairwise alignments.

top_n_peaks¶

Type: int

Number of peaks (starting with the largest) to include in the output.

class ConsolidateMethod(name_filter=[], min_match_factor=600, min_appearances=- 1)[source]¶

Bases: libgunshotmatch.method.MethodBase

Method used for consolidation (finding most likely identity for aligned peaks).

Parameters

name_filter (Iterable[str]) – List of glob-style matches for compound names. Consolidated peaks matching any of these will be excluded. Default [].
min_match_factor (int) – Minimum average match factor. Consolidated peaks with an average match factor below this will be excluded. Default 600.
min_appearances (int) – Number of times the hit must appear across the individual aligned peaks. Consolidated peaks where the most common hit appears fewer times than this will be excluded. If set to -1 the number of instances of the peak in the project are used. Default -1.

Changed in version 0.2.0: Added the min_appearances argument.

Attributes:

`min_appearances`	Number of times the hit must appear across the individual aligned peaks.
`min_match_factor`	Minimum average match factor.
`name_filter`	List of glob-style matches for compound names.

min_appearances¶

Type: int

Number of times the hit must appear across the individual aligned peaks.

Consolidated peaks where the most common hit appears fewer times than this will be excluded.

If set to -1 the number of instances of the peak in the project are used.

New in version 0.2.0.

min_match_factor¶

Type: int

Minimum average match factor.

Consolidated peaks with an average match factor below this will be excluded.

name_filter¶

Type: List[str]

List of glob-style matches for compound names.

Consolidated peaks matching any of these will be excluded.

class SavitzkyGolayMethod(enable=True, window=7, degree=2)[source]¶

Bases: libgunshotmatch.method.MethodBase

Method parameters for the Savitzky-Golay filter.

New in version 0.3.0.

Parameters

enable (bool) – Whether to perform Savitzky-Golay smoothing. Default True.
window (Union[str, int]) – The window size for the Savitzky-Golay filter. Either a number of scans or a must be the form '<NUMBER>s' or '<NUMBER>m', specifying a time in seconds or minutes, respectively. Default 7.
degree (int) – The degree of the fitting polynomial for the Savitzky-Golay filter. Default 2.

Attributes:

`degree`	The degree of the fitting polynomial for the Savitzky-Golay filter.
`enable`	Whether to perform Savitzky-Golay smoothing.
`window`	The window size for the Savitzky-Golay filter.

degree¶

Type: int

The degree of the fitting polynomial for the Savitzky-Golay filter.

enable¶

Type: bool

Whether to perform Savitzky-Golay smoothing.

window¶

Type: Union[str, int]

The window size for the Savitzky-Golay filter.

Either a number of scans or a must be the form '<NUMBER>s' or '<NUMBER>m', specifying a time in seconds or minutes, respectively.

libgunshotmatch.method¶

`libgunshotmatch.method`¶