feat(signal): split peak detection into XY-markers + sticks rebuild

Author: PierreRaybaut

datalab/gui/actionhandler.py

@@ -1443,10 +1443,14 @@ def cra_fit(title, fitdlgfunc, tip: str | None = None):
             self.action_for("extract_pulse_features")
             self.action_for("extract_peak_positions")
             self.new_action(
-                _("Peak detection"),
-                separator=True,
+                _("Peak detection..."),
                 triggered=self.panel.processor.compute_peak_detection,
                 icon_name="peak_detect.svg",
+                tip=_(
+                    "Interactive peak detection: adjust threshold and minimum "
+                    "distance visually, then store detected peaks as an "
+                    "XY-markers table result"
+                ),
             )
             self.action_for("sampling_rate_period", separator=True)
             self.action_for("dynamic_parameters", context_menu_pos=-1)
@@ -1457,6 +1461,16 @@ def create_last_actions(self):
         """Create actions that are added to the menus in the end"""
         super().create_last_actions()
         with self.new_category(ActionCategory.OPERATION):
+            self.new_action(
+                _("Create signal from markers table..."),
+                separator=True,
+                triggered=self.panel.processor.compute_markers_to_signal,
+                icon_name="peak_detect.svg",
+                tip=_(
+                    "Build a sticks signal from an XY-markers table result "
+                    "(e.g. from 'Extract peak positions')"
+                ),
+            )
             self.action_for("signals_to_image", separator=True)
 
         with self.new_category(ActionCategory.VIEW):

datalab/gui/processor/signal.py

@@ -11,11 +11,13 @@
 import re
 from collections.abc import Callable
 
+import guidata.dataset as gds
 import numpy as np
 import sigima.params
 import sigima.proc.base as sigima_base
 import sigima.proc.signal as sips
 from guidata.qthelpers import exec_dialog
+from qtpy import QtWidgets as QW
 from sigima.objects import (
     NormalDistributionParam,
     PoissonDistributionParam,
@@ -27,6 +29,7 @@
 )
 from sigima.objects.scalar import GeometryResult, TableResult
 
+from datalab.adapters_metadata.table_adapter import TableAdapter
 from datalab.config import _
 from datalab.gui.processor.base import BaseProcessor
 from datalab.utils.qthelpers import qt_try_except
@@ -329,12 +332,6 @@ def register_processing(self) -> None:
             paramclass=sigima.params.PowerParam,
             icon_name="power.svg",
         )
-        self.register_1_to_1(
-            sips.peak_detection,
-            _("Peak detection"),
-            paramclass=sigima.params.PeakDetectionParam,
-            icon_name="peak_detect.svg",
-        )
         # Frequency filters
         self.register_1_to_1(
             sips.lowpass,
@@ -610,8 +607,18 @@ def compute_all_stability(
     def compute_peak_detection(
         self, param: sigima.params.PeakDetectionParam | None = None
     ) -> None:
-        """Detect peaks from data
-        with :py:func:`sigima.proc.signal.peak_detection`"""
+        """Interactive peak detection.
+
+        Opens :class:`~datalab.widgets.signalpeak.SignalPeakDetectionDialog`
+        to set the detection threshold and minimum distance visually, then
+        stores the detected peak positions as an XY-markers
+        :class:`~sigima.objects.scalar.TableResult` attached to the signal
+        (via :py:func:`sigima.proc.signal.extract_peak_positions`).
+
+        To rebuild the historical *sticks* signal from the detected peaks,
+        use :py:meth:`compute_markers_to_signal` afterwards (menu
+        *Operations ▸ Create signal from markers table…*).
+        """
         obj = self.panel.objview.get_sel_objects(include_groups=True)[0]
         edit, param = self.init_param(
             param, sips.PeakDetectionParam, _("Peak detection")
@@ -623,7 +630,57 @@ def compute_peak_detection(
                 param.min_dist = dlg.get_min_dist()
             else:
                 return
-        self.run_feature("peak_detection", param)
+        self.run_feature("extract_peak_positions", param)
+
+    @qt_try_except()
+    def compute_markers_to_signal(self) -> None:
+        """Build a sticks signal from an XY-markers table result
+        with :py:func:`sigima.proc.signal.markers_table_to_signal`.
+        """
+        selected = self.panel.objview.get_sel_objects(include_groups=True)
+        if not selected:
+            return
+        title = _("Create signal from markers table")
+        last_choice: str | None = None
+        for obj in selected:
+            adapters = [
+                a
+                for a in TableAdapter.iterate_from_obj(obj)
+                if a.result.is_xy_markers()
+            ]
+            if not adapters:
+                QW.QMessageBox.information(
+                    self.mainwindow,
+                    title,
+                    _(
+                        "Signal '%s' has no XY-markers table result. "
+                        "Run 'Extract peak positions' (or another XY-markers "
+                        "analysis) first."
+                    )
+                    % obj.title,
+                )
+                continue
+            if len(adapters) == 1:
+                adapter = adapters[0]
+            else:
+                titles = [a.result.title for a in adapters]
+                default_idx = titles.index(last_choice) if last_choice in titles else 0
+                choices = list(enumerate(titles))
+
+                class _MarkersChoice(gds.DataSet):
+                    """Markers table selection."""
+
+                    index = gds.ChoiceItem(
+                        _("Markers table"), choices, default=default_idx
+                    )
+
+                choice = _MarkersChoice(title)
+                if not choice.edit(self.mainwindow):
+                    continue
+                adapter = adapters[choice.index]
+                last_choice = titles[choice.index]
+            signal = sips.markers_table_to_signal(adapter.result, ref=obj)
+            self.panel.add_object(signal)
 
     @qt_try_except()
     def compute_polyfit(

datalab/locale/fr/LC_MESSAGES/datalab.po

@@ -694,8 +694,17 @@ msgstr "Ordonnée à x=..."
 msgid "Compute the ordinate at a given x value (linear interpolation)"
 msgstr "Calcule l'ordonnée à une valeur x donnée (interpolation linéaire)"
 
-msgid "Peak detection"
-msgstr "Détection de pics"
+msgid "Peak detection..."
+msgstr "Détection de pics..."
+
+msgid "Interactive peak detection: adjust threshold and minimum distance visually, then store detected peaks as an XY-markers table result"
+msgstr "Détection de pics interactive : ajustez visuellement le seuil et la distance minimale, puis stockez les pics détectés sous la forme d'une table de marqueurs XY"
+
+msgid "Create signal from markers table..."
+msgstr "Créer un signal à partir d'une table de marqueurs..."
+
+msgid "Build a sticks signal from an XY-markers table result (e.g. from 'Extract peak positions')"
+msgstr "Crée un signal de type bâtons à partir d'une table de marqueurs XY (p.ex. issue de la commande 'Extraire les positions des pics')"
 
 msgid "Curve anti-aliasing"
 msgstr "Anticrénelage des courbes"
@@ -2066,6 +2075,9 @@ msgstr "Détection de contours"
 msgid "Compute contour shape fit"
 msgstr "Ajustement d'une forme géométrique à un contour"
 
+msgid "Peak detection"
+msgstr "Détection de pics"
+
 msgid "Detect peaks in the image"
 msgstr "Détection de pics dans l'image"
 
@@ -2320,6 +2332,16 @@ msgstr "Contraste"
 msgid "Compute contrast of a signal, i.e. (max-min)/(max+min), e.g. for an image profile"
 msgstr "Calcule le contraste d'un signal, c'est-à-dire (max-min)/(max+min), p.ex. pour un profil d'image"
 
+msgid "Create signal from markers table"
+msgstr "Créer un signal à partir d'une table de marqueurs"
+
+#, python-format
+msgid "Signal '%s' has no XY-markers table result. Run 'Extract peak positions' (or another XY-markers analysis) first."
+msgstr "Le signal '%s' ne possède aucun résultat de type table de marqueurs XY. Exécutez d'abord 'Extraire les positions des pics' (ou une autre analyse produisant une table de marqueurs XY)."
+
+msgid "Markers table"
+msgstr "Table de marqueurs"
+
 msgid "Full width at y"
 msgstr "Largeur à y=..."
 
@@ -3655,3 +3677,51 @@ msgstr "Merci de sélectionner le fichier à importer."
 
 msgid "Example Wizard"
 msgstr "Assistant exemple"
+
+msgid "Minimum value"
+msgstr "Valeur minimum"
+
+msgid "Maximum value"
+msgstr "Valeur maximum"
+
+msgid "Step between levels"
+msgstr "Pas entre les niveaux"
+
+msgid "Overlay image"
+msgstr "Image de fond"
+
+msgid "Show level labels"
+msgstr "Afficher les étiquettes de niveaux"
+
+msgid "Contour isoline plot"
+msgstr "Tracé de lignes de contour"
+
+msgid "Display isolines (contour lines) overlaid on the selected image, with configurable level range, step, and optional value labels"
+msgstr "Afficher les isolignes (lignes de contour) superposées à l'image sélectionnée, avec une plage de niveaux configurable, un pas entre les niveaux, et des étiquettes de valeurs optionnelles"
+
+msgid "Annotation"
+msgstr "Annotation"
+
+msgid "Contour"
+msgstr "Contour"
+
+msgid "Select a single image first."
+msgstr "Sélectionnez d'abord une seule image."
+
+msgid "Selected image does not contain finite data."
+msgstr "L'image sélectionnée ne contient pas de données finies."
+
+msgid "Selected image is constant: no contour can be drawn."
+msgstr "L'image sélectionnée est constante : aucun contour ne peut être tracé."
+
+msgid "Contour plot parameters"
+msgstr "Paramètres du tracé de contours"
+
+msgid "Maximum value must be strictly greater than minimum."
+msgstr "La valeur maximale doit être strictement supérieure à la valeur minimale."
+
+msgid "No contour was found for the selected level range."
+msgstr "Aucun contour n'a été trouvé pour la plage de niveaux sélectionnée."
+
+msgid "Show contour plot..."
+msgstr "Afficher le tracé de contours..."

datalab/tests/scenarios/common.py

@@ -187,6 +187,7 @@ def run_signal_computations(
 
     param = sigima.params.PeakDetectionParam()
     panel.processor.compute_peak_detection(param)
+    panel.processor.compute_markers_to_signal()
 
     panel.processor.compute_multigaussianfit()
 

datalab/tests/scenarios/demo.py

@@ -72,7 +72,8 @@ def test_signal_features(win: DLMainWindow, data_size: int = 500) -> None:
     sig3 = panel.objview.get_current_object()
 
     param = sigima.params.PeakDetectionParam()
-    panel.processor.run_feature("peak_detection", param)
+    panel.processor.compute_peak_detection(param)
+    panel.processor.compute_markers_to_signal()
     sig4 = panel.objview.get_current_object()
     panel.objview.select_objects([sig3, sig4])
 

doc/features/advanced/migration_v020_to_v100.rst

@@ -709,7 +709,15 @@ Some complex features still have dedicated methods:
    # These still use dedicated methods in v1.0
    proc.compute_roi_extraction(roi)
    proc.compute_multigaussianfit()
-   proc.compute_peak_detection(param)
+
+   # Peak detection (signal): ``compute_peak_detection`` still exists and
+   # opens the interactive threshold dialog as before, but it now stores
+   # the result as an XY-markers table (no sticks signal is created
+   # automatically). To rebuild the legacy sticks signal, chain with
+   # ``compute_markers_to_signal`` (or call ``run_feature("extract_peak_positions",
+   # param)`` directly when no interactive dialog is needed):
+   proc.compute_peak_detection(param)        # interactive, XY-markers result
+   proc.compute_markers_to_signal()          # optional: rebuild sticks signal
 
 Testing your plugin
 -------------------

doc/features/signal/menu_analysis.rst

@@ -113,13 +113,36 @@ If there are multiple solutions, the displayed result is the smallest value.
 Peak detection
 ^^^^^^^^^^^^^^
 
-Create a new signal from semi-automatic peak detection of each selected signal.
+DataLab offers two complementary ways to detect peaks. Both produce the
+same result: an *XY-markers* :class:`~sigima.objects.scalar.TableResult`
+attached to the signal (visible from *View ▸ Show results* and overlayed
+on the curve).
+
+.. list-table::
+    :header-rows: 1
+    :widths: 30, 70
+
+    * - Entry point
+      - Description
+    * - **Extract peak positions**
+      - Parametric entry: fill the standard parameter dialog
+        (threshold, minimum distance) and run.
+    * - **Peak detection...**
+      - Interactive entry: opens a dedicated dialog where the threshold
+        is adjusted by moving a horizontal marker and the minimum
+        distance by a slider. Detected peaks update live as vertical
+        markers.
 
 .. figure:: /images/shots/s_peak_detection.png
 
-    Peak detection dialog: threshold is adjustable by moving the
+    *Peak detection* dialog: threshold is adjustable by moving the
     horizontal marker, peaks are detected automatically (see vertical
-    markers with labels indicating peak position)
+    markers with labels indicating peak position).
+
+.. tip::
+
+    To rebuild the historical *sticks* signal from the detected peaks, use
+    *Operations ▸ Create signal from markers table…* on the selected signal.
 
 Sampling rate and period
 ^^^^^^^^^^^^^^^^^^^^^^^^

doc/features/signal/menu_operations.rst

@@ -273,6 +273,11 @@ Other mathematical functions
     * - |signal_to_image| Assemble signals into image
       - Create a 2D image by assembling selected 1D signals as rows or columns,
         with optional normalization.
+    * - |peak_detect| Create signal from markers table...
+      - Build a sticks signal from an XY-markers table result attached to the
+        selected signal — typically produced by *Analysis ▸ Extract peak
+        positions*. When several XY-markers tables are stored on the signal,
+        a dialog lets you pick the source table.
 
 
 .. |power| image:: ../../../datalab/data/icons/operations/power.svg
@@ -289,3 +294,8 @@ Other mathematical functions
     :width: 24px
     :height: 24px
     :class: dark-light no-scaled-link
+
+.. |peak_detect| image:: ../../../datalab/data/icons/processing/peak_detect.svg
+    :width: 24px
+    :height: 24px
+    :class: dark-light no-scaled-link

doc/intro/tutorials/spectrum.rst

@@ -197,10 +197,10 @@ and fit multiple peaks in the spectrum by selecting
     spectrum and the fit in the "Signals" panel on the right, so both are displayed
     in the visualization panel on the left.
 
-Alternatively, we could use the "Peak detection" feature from the "Analysis" menu to
-detect peaks in the spectrum. This is the first step of the "Multi-Gaussian fit"
-function and can be used independently to detect peaks without performing a fit,
-creating a signal with a delta function at each detected peak position.
+Alternatively, we could use the "Peak detection" feature from the "Analysis" menu
+to detect peaks in the spectrum. This is the first step of the "Multi-Gaussian fit"
+function and can be used independently to extract peak positions as a result table
+attached to the signal.
 
 .. figure:: ../../images/tutorials/spectrum/19.png
 
@@ -209,9 +209,13 @@ creating a signal with a delta function at each detected peak position.
 .. figure:: ../../images/tutorials/spectrum/21.png
 
     After adjusting the peak detection parameters (using the same dialog as
-    for the multi-Gaussian fit), click "OK". Then select both the
-    "peak_detection" result and the original spectrum in the "Signals" panel
-    to display them together in the visualization panel on the left.
+    for the multi-Gaussian fit), click "OK". The detected peak positions are
+    stored as an XY-markers result and overlayed on the spectrum.
+
+To rebuild the historical *sticks* signal — a delta function at each detected
+peak position — apply *Operations ▸ Create signal from markers table…* to the
+spectrum: this creates a child signal whose samples are the ``(x, y)`` couples
+of the markers table, rendered as sticks.
 
 Saving the workspace
 --------------------