SpectrumConfig

class pyopenms_viz._config.SpectrumConfig(*, kind: ~typing.Literal['line', 'vline', 'scatter', 'chromatogram', 'mobilogram', 'spectrum', 'peakmap', 'complex'] | None = None, x: str | None = None, y: str | None = None, z: str | None = None, by: str | None = None, canvas: ~typing.Any = None, height: int = 500, width: int = 500, grid: bool = True, toolbar_location: str = 'above', title: str = 'Mass Spectrum', xlabel: str = 'mass-to-charge', ylabel: str = 'Intensity', zlabel: str = '', title_font_size: int = 18, xaxis_label_font_size: int = 16, yaxis_label_font_size: int = 16, zaxis_label_font_size: int = 16, xaxis_labelpad: int = 16, yaxis_labelpad: int = 16, zaxis_labelpad: int = 9, xaxis_tick_font_size: int = 14, yaxis_tick_font_size: int = 14, zaxis_tick_font_size: int = 14, y_axis_location: ~typing.Literal['left', 'right'] = 'left', x_axis_location: ~typing.Literal['above', 'below'] = 'below', annotation_font_size: int = 12, color: str | ~typing.Iterator[str] = <factory>, plot_3d: bool = False, min_border: int = 0, show_plot: bool = True, relative_intensity: bool = False, aggregate_duplicates: bool = False, legend_config: ~pyopenms_viz._config.LegendConfig | dict = <factory>, opacity: float = 1.0, line_width: float = 1, line_type: str = 'solid', direction: ~typing.Literal['horizontal', 'vertical'] = 'vertical', reference_spectrum: ~pandas.core.frame.DataFrame | None = None, mirror_spectrum: bool = False, peak_color: str | None = None, bin_peaks: ~typing.Literal['auto'] | bool = False, bin_method: ~typing.Literal['none', 'sturges', 'freedman-diaconis', 'mz-tol-bin'] = 'mz-tol-bin', num_x_bins: int = 50, mz_tol: float | ~typing.Literal['freedman-diaconis', '1pct-diff'] = '1pct-diff', annotate_top_n_peaks: int | None | ~typing.Literal['all'] = 5, annotate_mz: bool = True, ion_annotation: str | None = None, sequence_annotation: str | None = None, custom_annotation: str | None = None, annotation_color: str | None = None, aggregation_method: ~typing.Literal['mean', 'sum', 'max'] = 'max')

Bases: VLineConfig

Configuration for a spectrum plot.

reference_spectrum

Reference spectrum data. Default is None.

Type:

pd.DataFrame | None

mirror_spectrum

Whether to mirror the spectrum. Default is False.

Type:

bool

peak_color

Color of the peaks. Default is None.

Type:

str | None

bin_peaks

Whether to bin peaks. Default is False.

Type:

Union[Literal[“auto”], bool]

bin_method

Method for binning peaks. Default is “mz-tol-bin”.

Type:

Literal[“none”, “sturges”, “freedman-diaconis”, “mz-tol-bin”]

num_x_bins

Number of bins along the X-axis. Default is 50. Ignored if bin_peaks is False or “auto”.

Type:

int

mz_tol

Tolerance for m/z binning. Default is “1pct-diff”.

Type:

Union[float, Literal[“freedman-diaconis”, “1pct-diff”]]

annotate_top_n_peaks

Number of top peaks to annotate. Default is 5.

Type:

int | None | Literal[“all”]

annotate_mz

Whether to annotate m/z values. Default is True.

Type:

bool

ion_annotation

Column for ion annotations. Default is None.

Type:

str | None

sequence_annotation

Column for sequence annotations. Default is None.

Type:

str | None

custom_annotation

Column for custom annotations. Default is None.

Type:

str | None

annotation_color

Color for annotations. Default is None.

Type:

str | None

aggregation_method

Method for aggregating data. Default is “max”.

Type:

Literal[“mean”, “sum”, “max”]

xlabel

Label for the X-axis. Default is “mass-to-charge”.

Type:

str

ylabel

Label for the Y-axis. Default is “Intensity”.

Type:

str

title

Title of the plot. Default is “Mass Spectrum”.

Type:

str

__eq__(other)

Return self==value.

__hash__ = None

__init__(*, kind: ~typing.Literal['line', 'vline', 'scatter', 'chromatogram', 'mobilogram', 'spectrum', 'peakmap', 'complex'] | None = None, x: str | None = None, y: str | None = None, z: str | None = None, by: str | None = None, canvas: ~typing.Any = None, height: int = 500, width: int = 500, grid: bool = True, toolbar_location: str = 'above', title: str = 'Mass Spectrum', xlabel: str = 'mass-to-charge', ylabel: str = 'Intensity', zlabel: str = '', title_font_size: int = 18, xaxis_label_font_size: int = 16, yaxis_label_font_size: int = 16, zaxis_label_font_size: int = 16, xaxis_labelpad: int = 16, yaxis_labelpad: int = 16, zaxis_labelpad: int = 9, xaxis_tick_font_size: int = 14, yaxis_tick_font_size: int = 14, zaxis_tick_font_size: int = 14, y_axis_location: ~typing.Literal['left', 'right'] = 'left', x_axis_location: ~typing.Literal['above', 'below'] = 'below', annotation_font_size: int = 12, color: str | ~typing.Iterator[str] = <factory>, plot_3d: bool = False, min_border: int = 0, show_plot: bool = True, relative_intensity: bool = False, aggregate_duplicates: bool = False, legend_config: ~pyopenms_viz._config.LegendConfig | dict = <factory>, opacity: float = 1.0, line_width: float = 1, line_type: str = 'solid', direction: ~typing.Literal['horizontal', 'vertical'] = 'vertical', reference_spectrum: ~pandas.core.frame.DataFrame | None = None, mirror_spectrum: bool = False, peak_color: str | None = None, bin_peaks: ~typing.Literal['auto'] | bool = False, bin_method: ~typing.Literal['none', 'sturges', 'freedman-diaconis', 'mz-tol-bin'] = 'mz-tol-bin', num_x_bins: int = 50, mz_tol: float | ~typing.Literal['freedman-diaconis', '1pct-diff'] = '1pct-diff', annotate_top_n_peaks: int | None | ~typing.Literal['all'] = 5, annotate_mz: bool = True, ion_annotation: str | None = None, sequence_annotation: str | None = None, custom_annotation: str | None = None, annotation_color: str | None = None, aggregation_method: ~typing.Literal['mean', 'sum', 'max'] = 'max') → None

__repr__()

Return repr(self).