feat(curve, waveform): add dap_parameters for lmfit customization in DAP requests

bec_widgets/cli/client.py

@@ -5418,6 +5418,7 @@ class Waveform(RPCBase):
         color: "str | None" = None,
         label: "str | None" = None,
         dap: "str | None" = None,
+        dap_parameters: "dict | lmfit.Parameters | None | object" = None,
         scan_id: "str | None" = None,
         scan_number: "int | None" = None,
         **kwargs,
@@ -5442,6 +5443,8 @@ class Waveform(RPCBase):
             dap(str): The dap model to use for the curve. When provided, a DAP curve is
                 attached automatically for device, history, or custom data sources. Use
                 the same string as the LMFit model name.
+            dap_parameters(dict | lmfit.Parameters | None): Optional lmfit parameter overrides sent to the DAP server.
+                Values can be numeric (interpreted as fixed parameters) or dicts like`{"value": 1.0, "vary": False}`.
             scan_id(str):  Optional scan ID. When provided, the curve is treated as a **history** curve and
                 the y‑data (and optional x‑data) are fetched from that historical scan. Such curves are
                 never cleared by live‑scan resets.
@@ -5458,6 +5461,7 @@ class Waveform(RPCBase):
         dap_name: "str",
         color: "str | None" = None,
         dap_oversample: "int" = 1,
+        dap_parameters: "dict | lmfit.Parameters | None" = None,
         **kwargs,
     ) -> "Curve":
         """
@@ -5470,6 +5474,7 @@ class Waveform(RPCBase):
             dap_name(str): The name of the DAP model to use.
             color(str): The color of the curve.
             dap_oversample(int): The oversampling factor for the DAP curve.
+            dap_parameters(dict | lmfit.Parameters | None): Optional lmfit parameter overrides sent to the DAP server.
             **kwargs
 
         Returns:

bec_widgets/utils/colors.py

@@ -1,11 +1,13 @@
 from __future__ import annotations
 
+from functools import lru_cache
 import re
 from typing import TYPE_CHECKING, Literal
 
 import bec_qthemes
 import numpy as np
 import pyqtgraph as pg
+from bec_lib import bec_logger
 from bec_qthemes._os_appearance.listener import OSThemeSwitchListener
 from pydantic_core import PydanticCustomError
 from qtpy.QtGui import QColor
@@ -15,6 +17,9 @@ if TYPE_CHECKING:  # pragma: no cover
     from bec_qthemes._main import AccentColors
 
 
+logger = bec_logger.logger
+
+
 def get_theme_name():
     if QApplication.instance() is None or not hasattr(QApplication.instance(), "theme"):
         return "dark"
@@ -138,6 +143,83 @@ def apply_theme(theme: Literal["dark", "light"]):
 
 
 class Colors:
+    @staticmethod
+    def list_available_colormaps() -> list[str]:
+        """
+        List colormap names available via the pyqtgraph colormap registry.
+
+        Note: This does not include `GradientEditorItem` presets (used by HistogramLUT menus).
+        """
+
+        def _list(source: str | None = None) -> list[str]:
+            try:
+                return pg.colormap.listMaps() if source is None else pg.colormap.listMaps(source)
+            except Exception:  # pragma: no cover - backend may be missing
+                return []
+
+        return [*_list(None), *_list("matplotlib"), *_list("colorcet")]
+
+    @staticmethod
+    def list_available_gradient_presets() -> list[str]:
+        """
+        List `GradientEditorItem` preset names (HistogramLUT right-click menu entries).
+        """
+        from pyqtgraph.graphicsItems.GradientEditorItem import Gradients
+
+        return list(Gradients.keys())
+
+    @staticmethod
+    def canonical_colormap_name(color_map: str) -> str:
+        """
+        Return an available colormap/preset name if a case-insensitive match exists.
+        """
+        requested = (color_map or "").strip()
+        if not requested:
+            return requested
+
+        registry = Colors.list_available_colormaps()
+        presets = Colors.list_available_gradient_presets()
+        available = set(registry) | set(presets)
+
+        if requested in available:
+            return requested
+
+        # Case-insensitive match.
+        lower_to_canonical = {name.lower(): name for name in available}
+        return lower_to_canonical.get(requested.lower(), requested)
+
+    @staticmethod
+    def get_colormap(color_map: str) -> pg.ColorMap:
+        """
+        Resolve a string into a `pg.ColorMap` using either:
+        - the `pg.colormap` registry (optionally including matplotlib/colorcet backends), or
+        - `GradientEditorItem` presets (HistogramLUT right-click menu).
+        """
+        name = Colors.canonical_colormap_name(color_map)
+        if not name:
+            raise ValueError("Empty colormap name")
+
+        return Colors._get_colormap_cached(name)
+
+    @staticmethod
+    @lru_cache(maxsize=256)
+    def _get_colormap_cached(name: str) -> pg.ColorMap:
+        # 1) Registry/backends
+        try:
+            return pg.colormap.get(name)
+        except Exception:
+            pass
+        for source in ("matplotlib", "colorcet"):
+            try:
+                return pg.colormap.get(name, source=source)
+            except Exception:
+                continue
+
+        # 2) Presets -> ColorMap
+        ge = pg.GradientEditorItem()
+        ge.loadPreset(name)
+
+        return ge.colorMap()
 
     @staticmethod
     def golden_ratio(num: int) -> list:
@@ -219,7 +301,7 @@ class Colors:
         if theme_offset < 0 or theme_offset > 1:
             raise ValueError("theme_offset must be between 0 and 1")
 
-        cmap = pg.colormap.get(colormap)
+        cmap = Colors.get_colormap(colormap)
         min_pos, max_pos = Colors.set_theme_offset(theme, theme_offset)
 
         # Generate positions that are evenly spaced within the acceptable range
@@ -267,7 +349,7 @@ class Colors:
             ValueError: If theme_offset is not between 0 and 1.
         """
 
-        cmap = pg.colormap.get(colormap)
+        cmap = Colors.get_colormap(colormap)
         phi = (1 + np.sqrt(5)) / 2  # Golden ratio
         golden_angle_conjugate = 1 - (1 / phi)  # Approximately 0.38196601125
 
@@ -533,18 +615,21 @@ class Colors:
         Raises:
             PydanticCustomError: If colormap is invalid.
         """
-        available_pg_maps = pg.colormap.listMaps()
-        available_mpl_maps = pg.colormap.listMaps("matplotlib")
-        available_mpl_colorcet = pg.colormap.listMaps("colorcet")
-
-        available_colormaps = available_pg_maps + available_mpl_maps + available_mpl_colorcet
-        if color_map not in available_colormaps:
+        normalized = Colors.canonical_colormap_name(color_map)
+        try:
+            Colors.get_colormap(normalized)
+        except Exception as ext:
+            logger.warning(f"Colormap validation error: {ext}")
             if return_error:
+                available_colormaps = sorted(
+                    set(Colors.list_available_colormaps())
+                    | set(Colors.list_available_gradient_presets())
+                )
                 raise PydanticCustomError(
                     "unsupported colormap",
-                    f"Colormap '{color_map}' not found in the current installation of pyqtgraph. Choose on the following: {available_colormaps}.",
+                    f"Colormap '{color_map}' not found in the current installation of pyqtgraph. Choose from the following: {available_colormaps}.",
                     {"wrong_value": color_map},
                 )
             else:
                 return False
-        return color_map
+        return normalized

bec_widgets/widgets/plots/image/image_base.py

@@ -9,6 +9,7 @@ from pydantic import BaseModel, ConfigDict, Field, ValidationError
 from qtpy.QtCore import QPointF, Signal, SignalInstance
 from qtpy.QtWidgets import QDialog, QVBoxLayout
 
+from bec_widgets.utils import Colors
 from bec_widgets.utils.container_utils import WidgetContainerUtils
 from bec_widgets.utils.error_popups import SafeProperty, SafeSlot
 from bec_widgets.utils.side_panel import SidePanel
@@ -131,8 +132,7 @@ class ImageLayerManager:
         image.setZValue(z_position)
         image.removed.connect(self._remove_destroyed_layer)
 
-        # FIXME: For now, we hard-code the default color map here. In the future, this should be configurable.
-        image.color_map = "plasma"
+        image.color_map = self.parent.config.color_map
 
         self.layers[name] = ImageLayer(name=name, image=image, sync=sync)
         self.plot_item.addItem(image)
@@ -249,6 +249,8 @@ class ImageBase(PlotBase):
     Base class for the Image widget.
     """
 
+    MAX_TICKS_COLORBAR = 10
+
     sync_colorbar_with_autorange = Signal()
     image_updated = Signal()
     layer_added = Signal(str)
@@ -460,18 +462,20 @@ class ImageBase(PlotBase):
                 self.setProperty("autorange", False)
 
             if style == "simple":
-                self._color_bar = pg.ColorBarItem(colorMap=self.config.color_map)
+                cmap = Colors.get_colormap(self.config.color_map)
+                self._color_bar = pg.ColorBarItem(colorMap=cmap)
                 self._color_bar.setImageItem(self.layer_manager["main"].image)
                 self._color_bar.sigLevelsChangeFinished.connect(disable_autorange)
+                self.config.color_bar = "simple"
 
             elif style == "full":
                 self._color_bar = pg.HistogramLUTItem()
                 self._color_bar.setImageItem(self.layer_manager["main"].image)
-                self._color_bar.gradient.loadPreset(self.config.color_map)
+                self.config.color_bar = "full"
+                self._apply_colormap_to_colorbar(self.config.color_map)
                 self._color_bar.sigLevelsChanged.connect(disable_autorange)
 
             self.plot_widget.addItem(self._color_bar, row=0, col=1)
-            self.config.color_bar = style
         else:
             if self._color_bar:
                 self.plot_widget.removeItem(self._color_bar)
@@ -484,6 +488,37 @@ class ImageBase(PlotBase):
         if vrange:  # should be at the end to disable the autorange if defined
             self.v_range = vrange
 
+    def _apply_colormap_to_colorbar(self, color_map: str) -> None:
+        if not self._color_bar:
+            return
+
+        cmap = Colors.get_colormap(color_map)
+
+        if self.config.color_bar == "simple":
+            self._color_bar.setColorMap(cmap)
+            return
+
+        if self.config.color_bar != "full":
+            return
+
+        gradient = getattr(self._color_bar, "gradient", None)
+        if gradient is None:
+            return
+
+        positions = np.linspace(0.0, 1.0, self.MAX_TICKS_COLORBAR)
+        colors = cmap.map(positions, mode="byte")
+
+        colors = np.asarray(colors)
+        if colors.ndim != 2:
+            return
+        if colors.shape[1] == 3:  # add alpha
+            alpha = np.full((colors.shape[0], 1), 255, dtype=colors.dtype)
+            colors = np.concatenate([colors, alpha], axis=1)
+
+        ticks = [(float(p), tuple(int(x) for x in c)) for p, c in zip(positions, colors)]
+        state = {"mode": "rgb", "ticks": ticks}
+        gradient.restoreState(state)
+
     ################################################################################
     # Static rois with roi manager
 
@@ -754,10 +789,7 @@ class ImageBase(PlotBase):
                 layer.image.color_map = value
 
             if self._color_bar:
-                if self.config.color_bar == "simple":
-                    self._color_bar.setColorMap(value)
-                elif self.config.color_bar == "full":
-                    self._color_bar.gradient.loadPreset(value)
+                self._apply_colormap_to_colorbar(self.config.color_map)
         except ValidationError:
             return
 

bec_widgets/widgets/plots/image/image_item.py

@@ -119,7 +119,8 @@ class ImageItem(BECConnector, pg.ImageItem):
         """Set a new color map."""
         try:
             self.config.color_map = value
-            self.setColorMap(value)
+            cmap = Colors.get_colormap(self.config.color_map)
+            self.setColorMap(cmap)
         except ValidationError:
             logger.error(f"Invalid colormap '{value}' provided.")
 

bec_widgets/widgets/plots/waveform/curve.py

@@ -24,6 +24,7 @@ class DeviceSignal(BaseModel):
     entry: str
     dap: str | None = None
     dap_oversample: int = 1
+    dap_parameters: dict | None = None
 
     model_config: dict = {"validate_assignment": True}
 

bec_widgets/widgets/plots/waveform/waveform.py

@@ -1,13 +1,13 @@
 from __future__ import annotations
 
 import json
-from typing import Literal
+from typing import TYPE_CHECKING, Literal
 
-import lmfit
 import numpy as np
 import pyqtgraph as pg
 from bec_lib import bec_logger, messages
 from bec_lib.endpoints import MessageEndpoints
+from bec_lib.lmfit_serializer import serialize_lmfit_params, serialize_param_object
 from bec_lib.scan_data_container import ScanDataContainer
 from pydantic import Field, ValidationError, field_validator
 from qtpy.QtCore import Qt, QTimer, Signal
@@ -41,6 +41,15 @@ from bec_widgets.widgets.services.scan_history_browser.scan_history_browser impo
 )
 
 logger = bec_logger.logger
+_DAP_PARAM = object()
+
+if TYPE_CHECKING:  # pragma: no cover
+    import lmfit  # type: ignore
+else:
+    try:
+        import lmfit  # type: ignore
+    except Exception:  # pragma: no cover
+        lmfit = None
 
 
 # noinspection PyDataclass
@@ -697,6 +706,7 @@ class Waveform(PlotBase):
         color: str | None = None,
         label: str | None = None,
         dap: str | None = None,
+        dap_parameters: dict | lmfit.Parameters | None | object = None,
         scan_id: str | None = None,
         scan_number: int | None = None,
         **kwargs,
@@ -721,6 +731,8 @@ class Waveform(PlotBase):
             dap(str): The dap model to use for the curve. When provided, a DAP curve is
                 attached automatically for device, history, or custom data sources. Use
                 the same string as the LMFit model name.
+            dap_parameters(dict | lmfit.Parameters | None): Optional lmfit parameter overrides sent to the DAP server.
+                Values can be numeric (interpreted as fixed parameters) or dicts like`{"value": 1.0, "vary": False}`.
             scan_id(str):  Optional scan ID. When provided, the curve is treated as a **history** curve and
                 the y‑data (and optional x‑data) are fetched from that historical scan. Such curves are
                 never cleared by live‑scan resets.
@@ -733,6 +745,8 @@ class Waveform(PlotBase):
         source = "custom"
         x_data = None
         y_data = None
+        if dap_parameters is _DAP_PARAM:
+            dap_parameters = kwargs.pop("dap_parameters", None) or kwargs.pop("parameters", None)
 
         # 1. Custom curve logic
         if x is not None and y is not None:
@@ -810,7 +824,9 @@ class Waveform(PlotBase):
         curve = self._add_curve(config=config, x_data=x_data, y_data=y_data)
 
         if dap is not None and curve.config.source in ("device", "history", "custom"):
-            self.add_dap_curve(device_label=curve.name(), dap_name=dap, **kwargs)
+            self.add_dap_curve(
+                device_label=curve.name(), dap_name=dap, dap_parameters=dap_parameters, **kwargs
+            )
 
         return curve
 
@@ -823,6 +839,7 @@ class Waveform(PlotBase):
         dap_name: str,
         color: str | None = None,
         dap_oversample: int = 1,
+        dap_parameters: dict | lmfit.Parameters | None = None,
         **kwargs,
     ) -> Curve:
         """
@@ -835,6 +852,7 @@ class Waveform(PlotBase):
             dap_name(str): The name of the DAP model to use.
             color(str): The color of the curve.
             dap_oversample(int): The oversampling factor for the DAP curve.
+            dap_parameters(dict | lmfit.Parameters | None): Optional lmfit parameter overrides sent to the DAP server.
             **kwargs
 
         Returns:
@@ -882,7 +900,11 @@ class Waveform(PlotBase):
 
         # Attach device signal with DAP
         config.signal = DeviceSignal(
-            name=dev_name, entry=dev_entry, dap=dap_name, dap_oversample=dap_oversample
+            name=dev_name,
+            entry=dev_entry,
+            dap=dap_name,
+            dap_oversample=dap_oversample,
+            dap_parameters=self._normalize_dap_parameters(dap_parameters),
         )
 
         # 4) Create the DAP curve config using `_add_curve(...)`
@@ -1762,12 +1784,21 @@ class Waveform(PlotBase):
                 x_min = None
                 x_max = None
 
+            dap_parameters = getattr(dap_curve.config.signal, "dap_parameters", None)
+            dap_kwargs = {
+                "data_x": x_data,
+                "data_y": y_data,
+                "oversample": dap_curve.dap_oversample,
+            }
+            if dap_parameters:
+                dap_kwargs["parameters"] = dap_parameters
+
             msg = messages.DAPRequestMessage(
                 dap_cls="LmfitService1D",
                 dap_type="on_demand",
                 config={
                     "args": [],
-                    "kwargs": {"data_x": x_data, "data_y": y_data},
+                    "kwargs": dap_kwargs,
                     "class_args": model._plugin_info["class_args"],
                     "class_kwargs": model._plugin_info["class_kwargs"],
                     "curve_label": dap_curve.name(),
@@ -1776,6 +1807,49 @@ class Waveform(PlotBase):
             )
             self.client.connector.set_and_publish(MessageEndpoints.dap_request(), msg)
 
+    @staticmethod
+    def _normalize_dap_parameters(parameters: dict | lmfit.Parameters | None) -> dict | None:
+        """
+        Normalize user-provided lmfit parameters into a JSON-serializable dict suitable for the DAP server.
+
+        Supports:
+        - `lmfit.Parameters`
+        - `dict[name -> number]` (treated as fixed parameter with `vary=False`)
+        - `dict[name -> dict]` (lmfit.Parameter fields; defaults to `vary=False` if unspecified)
+        - `dict[name -> lmfit.Parameter]`
+        """
+        if parameters is None:
+            return None
+        if lmfit is not None and isinstance(parameters, lmfit.Parameters):
+            return serialize_lmfit_params(parameters)
+        if not isinstance(parameters, dict):
+            if lmfit is None:
+                raise TypeError(
+                    "dap_parameters must be a dict when lmfit is not installed on the client."
+                )
+            raise TypeError("dap_parameters must be a dict or lmfit.Parameters (or omitted).")
+
+        normalized: dict[str, dict] = {}
+        for name, spec in parameters.items():
+            if spec is None:
+                continue
+            if isinstance(spec, (int, float, np.number)):
+                normalized[name] = {"name": name, "value": float(spec), "vary": False}
+                continue
+            if lmfit is not None and isinstance(spec, lmfit.Parameter):
+                normalized[name] = serialize_param_object(spec)
+                continue
+            if isinstance(spec, dict):
+                normalized[name] = {"name": name, **spec}
+                if "vary" not in normalized[name]:
+                    normalized[name]["vary"] = False
+                continue
+            raise TypeError(
+                f"Invalid dap_parameters entry for '{name}': expected number, dict, or lmfit.Parameter."
+            )
+
+        return normalized or None
+
     @SafeSlot(dict, dict)
     def update_dap_curves(self, msg, metadata):
         """
@@ -1793,14 +1867,6 @@ class Waveform(PlotBase):
         if not curve:
             return
 
-        # Get data from the parent (device) curve
-        parent_curve = self._find_curve_by_label(curve.config.parent_label)
-        if parent_curve is None:
-            return
-        x_parent, _ = parent_curve.get_data()
-        if x_parent is None or len(x_parent) == 0:
-            return
-
         # Retrieve and store the fit parameters and summary from the DAP server response
         try:
             curve.dap_params = msg["data"][1]["fit_parameters"]
@@ -1809,19 +1875,13 @@ class Waveform(PlotBase):
             logger.warning(f"Failed to retrieve DAP data for curve '{curve.name()}'")
             return
 
-        # Render model according to the DAP model name and parameters
-        model_name = curve.config.signal.dap
-        model_function = getattr(lmfit.models, model_name)()
-
-        x_min, x_max = x_parent.min(), x_parent.max()
-        oversample = curve.dap_oversample
-        new_x = np.linspace(x_min, x_max, int(len(x_parent) * oversample))
-
-        # Evaluate the model with the provided parameters to generate the y values
-        new_y = model_function.eval(**curve.dap_params, x=new_x)
-
-        # Update the curve with the new data
-        curve.setData(new_x, new_y)
+        # Plot the fitted curve using the server-provided output to avoid requiring lmfit on the client.
+        try:
+            fit_data = msg["data"][0]
+            curve.setData(np.asarray(fit_data["x"]), np.asarray(fit_data["y"]))
+        except Exception:
+            logger.exception(f"Failed to plot DAP result for curve '{curve.name()}'")
+            return
 
         metadata.update({"curve_id": curve_id})
         self.dap_params_update.emit(curve.dap_params, metadata)
@@ -2377,8 +2437,48 @@ class DemoApp(QMainWindow):  # pragma: no cover
         sigma = 0.8
         y = amplitude * np.exp(-((x - center) ** 2) / (2 * sigma**2)) + noise
 
+        # 1) No explicit parameters: server will use lmfit defaults/guesses.
         self.custom_waveform.plot(x=x, y=y, label="custom-gaussian", dap="GaussianModel")
 
+        # 2) Easy dict: numbers mean "fix this parameter to value" (vary=False).
+        self.custom_waveform.plot(
+            x=x,
+            y=y,
+            label="custom-gaussian-fixed-easy",
+            dap="GaussianModel",
+            dap_parameters={"amplitude": 1.0},
+            dap_oversample=5,
+        )
+
+        # 3) lmfit-style dict: any subset of lmfit.Parameter fields.
+        #    Here `center` is not fixed (vary=True) but its initial value is set.
+        self.custom_waveform.plot(
+            x=x,
+            y=y,
+            label="custom-gaussian-override-dict",
+            dap="GaussianModel",
+            dap_parameters={
+                "center": {"value": 1.2, "vary": True},
+                "sigma": {"value": sigma, "vary": False, "min": 0.0},
+            },
+        )
+
+        # 4) Passing a real `lmfit.Parameters` object (optional: requires lmfit on the client).
+        if lmfit is not None:
+            params_gauss = lmfit.models.GaussianModel().make_params()
+            params_gauss["amplitude"].set(value=amplitude, vary=False)
+            params_gauss["center"].set(value=center, vary=False)
+            params_gauss["sigma"].set(value=sigma, vary=False, min=0.0)
+            self.custom_waveform.plot(
+                x=x,
+                y=y,
+                label="custom-gaussian-fixed-params",
+                dap="GaussianModel",
+                dap_parameters=params_gauss,
+            )
+        else:
+            logger.info("Skipping lmfit.Parameters demo (lmfit not installed on client).")
+
 
 if __name__ == "__main__":  # pragma: no cover
     import sys

tests/end-2-end/test_plotting_framework_e2e.py

@@ -75,6 +75,7 @@ def test_rpc_plotting_shortcuts_init_configs(qtbot, connected_client_gui_obj):
     assert c1._config_dict["signal"] == {
         "dap": None,
         "name": "bpm4i",
+        "dap_parameters": None,
         "entry": "bpm4i",
         "dap_oversample": 1,
     }

tests/unit_tests/test_color_utils.py

@@ -82,6 +82,18 @@ def test_rgba_to_hex():
     assert Colors.rgba_to_hex(255, 87, 51) == "#FF5733FF"
 
 
+def test_validate_color_map_accepts_gradient_presets_and_greys_alias():
+    presets = {p.lower() for p in Colors.list_available_gradient_presets()}
+    candidate = next(
+        (p for p in ("grey", "gray", "bipolar", "spectrum", "flame") if p in presets), None
+    )
+    if candidate is None:
+        pytest.skip("No known GradientEditorItem presets available in this environment.")
+
+    assert Colors.validate_color_map(candidate) != ""
+    assert Colors.get_colormap(candidate) is not None
+
+
 @pytest.mark.parametrize("num", [10, 100, 400])
 def test_evenly_spaced_colors(num):
     colors_qcolor = Colors.evenly_spaced_colors(colormap="magma", num=num, format="QColor")

tests/unit_tests/test_waveform.py

@@ -516,6 +516,57 @@ def test_plot_custom_curve_with_inline_dap(qtbot, mocked_client_with_dap):
     assert dap_curve.config.signal.dap == "GaussianModel"
 
 
+def test_normalize_dap_parameters_number_dict():
+    normalized = Waveform._normalize_dap_parameters({"amplitude": 1.0, "center": 2})
+    assert normalized == {
+        "amplitude": {"name": "amplitude", "value": 1.0, "vary": False},
+        "center": {"name": "center", "value": 2.0, "vary": False},
+    }
+
+
+def test_normalize_dap_parameters_dict_spec_defaults_vary_false():
+    normalized = Waveform._normalize_dap_parameters({"sigma": {"value": 0.8, "min": 0.0}})
+    assert normalized["sigma"]["name"] == "sigma"
+    assert normalized["sigma"]["value"] == 0.8
+    assert normalized["sigma"]["min"] == 0.0
+    assert normalized["sigma"]["vary"] is False
+
+
+def test_normalize_dap_parameters_invalid_type_raises():
+    with pytest.raises(TypeError):
+        Waveform._normalize_dap_parameters(["amplitude", 1.0])  # type: ignore[arg-type]
+
+
+def test_request_dap_includes_normalized_parameters(qtbot, mocked_client_with_dap, monkeypatch):
+    wf = create_widget(qtbot, Waveform, client=mocked_client_with_dap)
+    curve = wf.plot(
+        x=[0, 1, 2],
+        y=[1, 2, 3],
+        label="custom-inline-params",
+        dap="GaussianModel",
+        dap_parameters={"amplitude": 1.0},
+    )
+    dap_curve = wf.get_curve(f"{curve.name()}-GaussianModel")
+    assert dap_curve is not None
+    dap_curve.dap_oversample = 3
+
+    captured = {}
+
+    def capture(topic, msg, *args, **kwargs):  # noqa: ARG001
+        captured["topic"] = topic
+        captured["msg"] = msg
+
+    monkeypatch.setattr(wf.client.connector, "set_and_publish", capture)
+    wf.request_dap()
+
+    msg = captured["msg"]
+    dap_kwargs = msg.content["config"]["kwargs"]
+    assert dap_kwargs["oversample"] == 3
+    assert dap_kwargs["parameters"] == {
+        "amplitude": {"name": "amplitude", "value": 1.0, "vary": False}
+    }
+
+
 def test_fetch_scan_data_and_access(qtbot, mocked_client, monkeypatch):
     """
     Test the _fetch_scan_data_and_access method returns live_data/val if in a live scan,