PeakMapPlot

class pyopenms_viz._core.PeakMapPlot(data, x, y, z, zlabel=None, add_marginals=False, y_kind='spectrum', x_kind='chromatogram', annotation_data: DataFrame | None = None, annotation_x_lb: str = 'leftWidth', annotation_x_ub: str = 'rightWidth', annotation_y_lb: str = 'IM_leftWidth', annotation_y_ub: str = 'IM_rightWidth', annotation_colors: str = 'color', annotation_names: str = 'name', bin_peaks: Literal['auto'] | bool = 'auto', aggregation_method: Literal['mean', 'sum', 'max'] = 'mean', num_x_bins: int = 50, num_y_bins: int = 50, z_log_scale: bool = False, fill_by_z: bool = True, **kwargs)

Bases: BaseMSPlot, ABC

__init__(data, x, y, z, zlabel=None, add_marginals=False, y_kind='spectrum', x_kind='chromatogram', annotation_data: DataFrame | None = None, annotation_x_lb: str = 'leftWidth', annotation_x_ub: str = 'rightWidth', annotation_y_lb: str = 'IM_leftWidth', annotation_y_ub: str = 'IM_rightWidth', annotation_colors: str = 'color', annotation_names: str = 'name', bin_peaks: Literal['auto'] | bool = 'auto', aggregation_method: Literal['mean', 'sum', 'max'] = 'mean', num_x_bins: int = 50, num_y_bins: int = 50, z_log_scale: bool = False, fill_by_z: bool = True, **kwargs) → None

abstract _add_box_boundaries(annotation_data)

Prepare data for adding box boundaries to the plot.

Parameters:

annotation_data (DataFrame) – The feature data containing the box boundaries.

Returns:

None

property _kind

The kind of plot to assemble. Must be overridden by subclasses.

property known_columns: List[str]

List of known columns in the data, if there are duplicates outside of these columns they will be grouped in aggregation if specified

plot(x, y, z, **kwargs)

Create the plot