Merge pull request #98 from singjc/main

fix/refactor: minor code clean up and fix for annotations in peakmaps

Author: singjc

pyopenms_viz/_bokeh/core.py

@@ -1,42 +1,39 @@
 from __future__ import annotations
 
 from abc import ABC
+from typing import Tuple
 
-from typing import Tuple, Iterator
-from dataclasses import dataclass
-
-from bokeh.plotting import figure
-from bokeh.palettes import Plasma256
-from bokeh.transform import linear_cmap
 from bokeh.models import (
+    BoxEditTool,
     ColumnDataSource,
+    GlyphRenderer,
+    Label,
     Legend,
     Range1d,
-    BoxEditTool,
     Span,
     VStrip,
-    GlyphRenderer,
-    Label,
 )
-
-from pandas.core.frame import DataFrame
+from bokeh.palettes import Plasma256
+from bokeh.plotting import figure
+from bokeh.transform import linear_cmap
 from numpy import nan
+from pandas.core.frame import DataFrame
 
 # pyopenms_viz imports
 from .._core import (
-    BasePlot,
-    LinePlot,
-    VLinePlot,
-    ScatterPlot,
+    APPEND_PLOT_DOC,
     BaseMSPlot,
+    BasePlot,
     ChromatogramPlot,
+    LinePlot,
     MobilogramPlot,
     PeakMapPlot,
+    ScatterPlot,
     SpectrumPlot,
-    APPEND_PLOT_DOC,
+    VLinePlot,
 )
 from .._misc import ColorGenerator, MarkerShapeGenerator, is_latex_formatted
-from ..constants import PEAK_BOUNDARY_ICON, FEATURE_BOUNDARY_ICON
+from ..constants import FEATURE_BOUNDARY_ICON, PEAK_BOUNDARY_ICON
 
 
 class BOKEHPlot(BasePlot, ABC):
@@ -60,11 +57,11 @@ def fig(self, value):
 
     def _load_extension(self) -> None:
         try:
-            from bokeh.plotting import figure, show
             from bokeh.models import ColumnDataSource, Legend
+            from bokeh.plotting import figure, show
         except ImportError:
             raise ImportError(
-                f"bokeh is not installed. Please install using `pip install bokeh` to use this plotting library in pyopenms-viz"
+                "bokeh is not installed. Please install using `pip install bokeh` to use this plotting library in pyopenms-viz"
             )
 
     def _create_figure(self):
@@ -303,7 +300,6 @@ def plot(self):
                 line_width=self.line_width,
             )
         else:
-
             legend_items = []
             for group, df in self.data.groupby(self.by, sort=False):
                 source = ColumnDataSource(df)
@@ -439,7 +435,6 @@ def plot(self):
 
 
 class BOKEH_MSPlot(BaseMSPlot, BOKEHPlot, ABC):
-
     def get_line_renderer(self, **kwargs) -> None:
         return BOKEHLinePlot(**kwargs)
 
@@ -555,9 +550,7 @@ class BOKEHPeakMapPlot(BOKEH_MSPlot, PeakMapPlot):
 
     # NOTE: canvas is only used in matplotlib backend
     def create_main_plot(self, canvas=None):
-
         if not self.plot_3d:
-
             scatterPlot = self.get_scatter_renderer(data=self.data, config=self._config)
 
             tooltips, custom_hover_data = self._create_tooltips(

pyopenms_viz/_config.py

@@ -1,14 +1,15 @@
-from abc import ABC, ABCMeta
-from dataclasses import dataclass, field, asdict, fields
-from typing import Tuple, Literal, Dict, Any, Union, Iterator
+from abc import ABC
 from copy import deepcopy
-from ._misc import ColorGenerator, MarkerShapeGenerator
+from dataclasses import asdict, dataclass, field, fields
+from typing import Any, Dict, Iterator, Literal, Tuple, Union
+
 import pandas as pd
 
+from ._misc import ColorGenerator, MarkerShapeGenerator
+
 
 @dataclass(kw_only=True)
 class BaseConfig(ABC):
-
     @classmethod
     def from_dict(cls, config_dict: Dict[str, Any]) -> "BaseConfig":
         """
@@ -87,6 +88,7 @@ class LegendConfig(BaseConfig):
         1.2,
         0.5,
     )  # for fine control legend positioning in matplotlib
+    ncol: int = 1  # number of columns in legend
 
     @staticmethod
     def _matplotlibLegendLocationMapper(loc):
@@ -288,7 +290,6 @@ class ScatterConfig(BasePlotConfig):
     )
 
     def __post_init__(self):
-
         super().__post_init__()
         if not isinstance(self.marker, MarkerShapeGenerator):
             self.marker = MarkerShapeGenerator(shapes=self.marker)
@@ -424,6 +425,10 @@ class PeakMapConfig(ScatterConfig):
         x_kind (str): Type of plot for the X-axis marginal. Defaults to "chromatogram".
         aggregation_method (Literal["mean", "sum", "max"]): Method for aggregating data. Defaults to "mean".
         annotation_data (pd.DataFrame | None): Data for annotations. Defaults to None.
+        annotation_colormap (str): Colormap for annotations. Defaults to "Dark2".
+        annotation_line_width (float): Width of the annotation lines. Defaults to 3.
+        annotation_line_type (str): Type of the annotation lines (e.g., "solid", "dashed"). Defaults to "solid".
+        annotation_legend_config (Dict | LegendConfig): Configuration for the annotation legend. Defaults to a LegendConfig instance with title "Features".
         xlabel (str): Label for the X-axis. Defaults to "Retention Time".
         ylabel (str): Label for the Y-axis. Defaults to "mass-to-charge".
         zlabel (str): Label for the Z-axis. Defaults to "Intensity".
@@ -448,6 +453,18 @@ def marginal_config_factory(kind):
 
     aggregation_method: Literal["mean", "sum", "max"] = "mean"
     annotation_data: pd.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"
+    annotation_colormap: str = "Dark2"
+    annotation_line_width: float = 3
+    annotation_line_type: str = "solid"
+    annotation_legend_config: Dict | LegendConfig = field(
+        default_factory=ScatterConfig.default_legend_factory
+    )
 
     ### override axes and title labels
     xlabel: str = "Retention Time"
@@ -498,6 +515,10 @@ def __post_init__(self):
         self.annotation_data = (
             None if self.annotation_data is None else self.annotation_data.copy()
         )
+        if not isinstance(self.annotation_legend_config, LegendConfig):
+            self.annotation_legend_config = LegendConfig.from_dict(
+                self.annotation_legend_config
+            )
 
 
 def bokeh_line_dash_mapper(bokeh_dash, target_library="plotly"):