Add customizable result shape and marker styles

Add four new settings to configure visual appearance of result shapes
and markers through the Settings dialog (Visualization tab):

- Shape style for signals/images: line, fill, symbol properties
- Marker style for signals/images: cursor appearance and labels

Author: PierreRaybaut

CHANGELOG.md

@@ -198,6 +198,24 @@ See DataLab [roadmap page](https://datalab-platform.com/en/contributing/roadmap.
   * Ideal for analyzing sensor data, temperature logs, and time-series measurements
   * This closes [Issue #258](https://github.com/DataLab-Platform/DataLab/issues/258) - Add support for CSV files with date/time X-axis
 
+* **Customizable result shape and marker styles**: New settings to configure visual appearance of result shapes and markers
+  * Added four new button controls in the Settings dialog (Visualization tab) to customize styles:
+    * **Shape style for signals**: Configure line style, color, width, fill pattern, symbol appearance, and selection styles for annotation shapes on signal plots
+    * **Marker style for signals**: Configure cursor marker appearance including line style, symbol, text labels, and background transparency for signal analysis results
+    * **Shape style for images**: Configure annotation shape appearance for image plots optimized for image visualization
+    * **Marker style for images**: Configure cursor marker styles for image analysis results
+  * **Editable through PlotPy's shape parameter dialog**: Clicking each button opens an interactive editor with comprehensive style options including:
+    * Line properties: style (solid, dashed, dotted), color, width
+    * Fill properties: pattern, color, transparency
+    * Symbol properties: marker type, size, edge and face colors
+    * Selection appearance: different styles when shapes are selected
+    * Text formatting for marker labels
+  * **Persistent configuration**: All style settings are saved in the user configuration file and preserved across sessions
+  * **Applied to all result shapes and markers**: Styles are applied to all result shapes and markers from analysis operations (peak detection, FWHM, centroid, statistics, etc.)
+  * **Shape refresh on settings change**: When shape/marker parameters are modified in Settings, users are prompted to refresh existing result shapes on visible plots to apply the new styles
+  * Improves workflow flexibility by allowing users to establish consistent visual styling for their analysis results
+  * Particularly useful for creating presentation-ready plots with custom color schemes or for adapting to different display environments
+
 * **Enhance metadata handling by adding function name context to results**:
   * When computation functions (e.g., `full_width_at_y`, `x_at_y`) create results with parameters, the function name is now stored
   * Analysis parameters tab displays function name as a comment above parameter information for better context

datalab/adapters_metadata/common.py

@@ -95,6 +95,33 @@ def append(self, adapter: BaseResultAdapter, obj: SignalObj | ImageObj) -> None:
             self.short_ids.append(sid)
 
 
+def have_results(objs: list[SignalObj | ImageObj]) -> bool:
+    """Return True if any object has results
+
+    Args:
+        objs: List of objects
+
+    Returns:
+        True if any object has results, False otherwise
+    """
+    return bool(
+        any(GeometryAdapter.iterate_from_obj(obj) for obj in objs)
+        or any(TableAdapter.iterate_from_obj(obj) for obj in objs)
+    )
+
+
+def have_geometry_results(objs: list[SignalObj | ImageObj]) -> bool:
+    """Return True if any object has geometry results
+
+    Args:
+        objs: List of objects
+
+    Returns:
+        True if any object has geometry results, False otherwise
+    """
+    return bool(any(GeometryAdapter.iterate_from_obj(obj) for obj in objs))
+
+
 def create_resultdata_dict(
     objs: list[SignalObj | ImageObj],
 ) -> dict[str, ResultData]:

datalab/adapters_plotpy/base.py

@@ -10,23 +10,23 @@
 from __future__ import annotations
 
 import json
-from typing import (
-    TYPE_CHECKING,
-)
+from typing import TYPE_CHECKING
 
+import guidata.dataset as gds
 from guidata.io import JSONReader, JSONWriter
 from plotpy.io import load_items, save_items
 from plotpy.items import (
     AbstractLabelItem,
+    AnnotatedPoint,
     AnnotatedSegment,
     AnnotatedShape,
 )
 
+from datalab.config import Conf
+
 if TYPE_CHECKING:
-    from plotpy.items import (
-        AbstractShape,
-    )
-    from plotpy.styles import AnnotationParam
+    from plotpy.items import AbstractShape
+    from plotpy.styles import AnnotationParam, ShapeParam
 
 
 def config_annotated_shape(

datalab/adapters_plotpy/objects/scalar.py

@@ -15,6 +15,7 @@
 from collections.abc import Iterable
 from typing import TYPE_CHECKING, Literal
 
+import guidata.dataset as gds
 import numpy as np
 from guidata.configtools import get_font
 from plotpy.builder import make
@@ -91,14 +92,14 @@ def __init__(self, result_adapter: GeometryAdapter) -> None:
         super().__init__(result_adapter)
 
     def iterate_shape_items(
-        self, fmt: str, lbl: bool, option: Literal["s", "i"]
+        self, fmt: str, lbl: bool, prefix: Literal["s", "i"]
     ) -> Iterable:
         """Iterate over metadata shape plot items.
 
         Args:
             fmt: numeric format (e.g. "%.3f")
             lbl: if True, show shape labels
-            option: shape style option ("s" for signal, "i" for image)
+            prefix: "s" for signal, "i" for image
 
         Yields:
             Plot item
@@ -110,7 +111,7 @@ def iterate_shape_items(
         for idx, coords in enumerate(self.result_adapter.result.coords):
             if idx >= max_shapes:
                 break
-            yield self.create_shape_item(coords, fmt, lbl, option)
+            yield self.create_shape_item(coords, fmt, lbl, prefix)
 
         # If shapes were truncated, create a warning label
         if total_coords > max_shapes:
@@ -129,7 +130,7 @@ def iterate_shape_items(
             yield warning_label
 
     def create_shape_item(
-        self, coords: np.ndarray, fmt: str, lbl: bool, option: Literal["s", "i"]
+        self, coords: np.ndarray, fmt: str, lbl: bool, prefix: Literal["s", "i"]
     ) -> (
         AnnotatedPoint
         | Marker
@@ -146,7 +147,7 @@ def create_shape_item(
             coords: coordinate array
             fmt: numeric format (e.g. "%.3f")
             lbl: if True, show shape labels
-            option: shape style option ("s" for signal, "i" for image)
+            prefix: "s" for signal, "i" for image
 
         Returns:
             Plot item
@@ -209,8 +210,30 @@ def create_shape_item(
             raise NotImplementedError(
                 f"Unsupported shape kind: {self.result_adapter.result.kind}"
             )
+
         if isinstance(item, AnnotatedShape):
-            config_annotated_shape(item, fmt, lbl, "results", option)
+            config_annotated_shape(item, fmt, lbl, "results", f"{prefix}/annotation")
+            # Apply settings for annotated shapes (except AnnotatedPoint)
+            if not isinstance(item, AnnotatedPoint):
+                if prefix == "s":
+                    config_param = Conf.view.sig_shape_param.get()
+                else:
+                    config_param = Conf.view.ima_shape_param.get()
+                shape_param: ShapeParam = item.shape.shapeparam
+                gds.update_dataset(shape_param, config_param)
+                shape_param.update_item(item.shape)
+
+        if isinstance(item, Marker):
+            item.set_style("results", f"{prefix}/marker")
+            # Apply cursor/marker settings from config
+            if prefix == "s":
+                config_param = Conf.view.sig_marker_param.get()
+            else:
+                config_param = Conf.view.ima_marker_param.get()
+            param = item.markerparam
+            gds.update_dataset(param, config_param)
+            param.update_item(item)
+
         set_plot_item_editable(item, False)
         return item
 
@@ -241,20 +264,7 @@ def label(x, y):  # pylint: disable=unused-argument
             def label(x, y):
                 return txt % (x, y)
 
-        marker = make.marker(
-            position=(x0, y0),
-            markerstyle=mstyle,
-            label_cb=label,
-            linestyle="DashLine",
-            color="#ffff00",
-        )
-        param = marker.markerparam
-        param.symbol.marker = "Diamond"
-        param.symbol.size = 9
-        param.symbol.edgecolor = "#ffff00"
-        param.symbol.facecolor = "#ffff00"
-        param.symbol.alpha = 0.7
-        param.update_item(marker)
+        marker = make.marker(position=(x0, y0), markerstyle=mstyle, label_cb=label)
         return marker