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

Automatically generated by python-semantic-release

CHANGELOG.md

@@ -1,6 +1,28 @@
 # CHANGELOG
 
 
+## v2.45.12 (2025-12-16)
+
+### Bug Fixes
+
+- **heatmap**: Flush image if config changes during scan
+  ([`e0fd976`](https://github.com/bec-project/bec_widgets/commit/e0fd97616d370722e2ebf12d0f93862ac35cb20d))
+
+- **heatmap**: Grid scan image correctly map to scan positions
+  ([`6af8a5c`](https://github.com/bec-project/bec_widgets/commit/6af8a5cbfe0f97327b31039033d3e6946388347c))
+
+- **heatmap**: More robust logic for fast and slow axis in grid scan
+  ([`d876ca7`](https://github.com/bec-project/bec_widgets/commit/d876ca72bc50f967f0872eb777f2378a3db68ddf))
+
+
+## v2.45.11 (2025-12-15)
+
+### Bug Fixes
+
+- **waveform**: Support for AsyncMultiSignal
+  ([`cd11a6c`](https://github.com/bec-project/bec_widgets/commit/cd11a6cce33f3c0642984ae6b2d159c7441e22c6))
+
+
 ## v2.45.10 (2025-12-10)
 
 ### Bug Fixes

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/heatmap/heatmap.py

@@ -268,6 +268,20 @@ class Heatmap(ImageBase):
         if show_config_label is None:
             show_config_label = self._image_config.show_config_label
 
+        def _device_key(device: HeatmapDeviceSignal | None) -> tuple[str | None, str | None]:
+            return (device.name if device else None, device.entry if device else None)
+
+        prev_cfg = getattr(self, "_image_config", None)
+        config_changed = False
+        if prev_cfg and prev_cfg.x_device and prev_cfg.y_device and prev_cfg.z_device:
+            config_changed = any(
+                (
+                    _device_key(prev_cfg.x_device) != (x_name, x_entry),
+                    _device_key(prev_cfg.y_device) != (y_name, y_entry),
+                    _device_key(prev_cfg.z_device) != (z_name, z_entry),
+                )
+            )
+
         self._image_config = HeatmapConfig(
             parent_id=self.gui_id,
             x_device=HeatmapDeviceSignal(name=x_name, entry=x_entry),
@@ -282,7 +296,10 @@ class Heatmap(ImageBase):
             show_config_label=show_config_label,
         )
         self.color_map = color_map
-        self.reload = reload
+        self.reload = reload or config_changed
+        if config_changed:
+            self._grid_index = None
+            self.main_image.clear()
         self.update_labels()
 
         self._fetch_running_scan()
@@ -603,55 +620,51 @@ class Heatmap(ImageBase):
 
         args = self.arg_bundle_to_dict(4, msg.request_inputs["arg_bundle"])
 
-        shape = (
-            args[self._image_config.x_device.entry][-1],
-            args[self._image_config.y_device.entry][-1],
-        )
+        x_entry = self._image_config.x_device.entry
+        y_entry = self._image_config.y_device.entry
+        shape = (args[x_entry][-1], args[y_entry][-1])
 
         data = self.main_image.raw_data
 
         if data is None or data.shape != shape:
             data = np.empty(shape)
             data.fill(np.nan)
-
-        def _get_grid_data(axis, snaked=True):
-            x_grid, y_grid = np.meshgrid(axis[0], axis[1])
-            if snaked:
-                y_grid.T[::2] = np.fliplr(y_grid.T[::2])
-            x_flat = x_grid.T.ravel()
-            y_flat = y_grid.T.ravel()
-            positions = np.vstack((x_flat, y_flat)).T
-            return positions
+        elif self.reload:
+            data.fill(np.nan)
 
         snaked = msg.request_inputs["kwargs"].get("snaked", True)
 
-        # If the scan's fast axis is x, we need to swap the x and y axes
-        swap = bool(msg.request_inputs["arg_bundle"][4] == self._image_config.x_device.entry)
+        slow_entry, fast_entry = (
+            msg.request_inputs["arg_bundle"][0],
+            msg.request_inputs["arg_bundle"][4],
+        )
 
-        # calculate the QTransform to put (0,0) at the axis origin
-        scan_pos = np.asarray(msg.info["positions"])
-        x_min = min(scan_pos[:, 0])
-        x_max = max(scan_pos[:, 0])
-        y_min = min(scan_pos[:, 1])
-        y_max = max(scan_pos[:, 1])
+        scan_pos = np.asarray(msg.info["positions"], dtype=float)
+        relative = bool(msg.request_inputs["kwargs"].get("relative", False))
 
-        x_range = x_max - x_min
-        y_range = y_max - y_min
+        def _axis_column(entry: str) -> int:
+            return 0 if entry == slow_entry else 1
 
-        pixel_size_x = x_range / (shape[0] - 1)
-        pixel_size_y = y_range / (shape[1] - 1)
+        def _axis_levels(entry: str, npts: int) -> np.ndarray:
+            start, stop = args[entry][:2]
+            if relative:
+                origin = float(scan_pos[0, _axis_column(entry)] - start)
+                return origin + np.linspace(start, stop, npts)
+            return np.linspace(start, stop, npts)
+
+        x_levels = _axis_levels(x_entry, shape[0])
+        y_levels = _axis_levels(y_entry, shape[1])
+
+        pixel_size_x = (
+            float(x_levels[-1] - x_levels[0]) / max(shape[0] - 1, 1) if shape[0] > 1 else 1.0
+        )
+        pixel_size_y = (
+            float(y_levels[-1] - y_levels[0]) / max(shape[1] - 1, 1) if shape[1] > 1 else 1.0
+        )
 
         transform = QTransform()
-        if swap:
-            transform.scale(pixel_size_y, pixel_size_x)
-            transform.translate(y_min / pixel_size_y - 0.5, x_min / pixel_size_x - 0.5)
-        else:
-            transform.scale(pixel_size_x, pixel_size_y)
-            transform.translate(x_min / pixel_size_x - 0.5, y_min / pixel_size_y - 0.5)
-
-        target_positions = _get_grid_data(
-            (np.arange(shape[int(swap)]), np.arange(shape[int(not swap)])), snaked=snaked
-        )
+        transform.scale(pixel_size_x, pixel_size_y)
+        transform.translate(x_levels[0] / pixel_size_x - 0.5, y_levels[0] / pixel_size_y - 0.5)
 
         # Fill the data array with the z values
         if self._grid_index is None or self.reload:
@@ -659,7 +672,16 @@ class Heatmap(ImageBase):
             self.reload = False
 
         for i in range(self._grid_index, len(z_data)):
-            data[target_positions[i, int(swap)], target_positions[i, int(not swap)]] = z_data[i]
+            slow_i, fast_i = divmod(i, args[fast_entry][-1])
+            if snaked and (slow_i % 2 == 1):
+                fast_i = args[fast_entry][-1] - 1 - fast_i
+
+            if x_entry == fast_entry:
+                x_i, y_i = fast_i, slow_i
+            else:
+                x_i, y_i = slow_i, fast_i
+
+            data[x_i, y_i] = z_data[i]
         self._grid_index = len(z_data)
         return data, transform
 

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(...)`
@@ -1520,7 +1542,7 @@ class Waveform(PlotBase):
 
         self.request_dap_update.emit()
 
-    def _check_async_signal_found(self, name: str, signal: str) -> bool:
+    def _check_async_signal_found(self, name: str, signal: str) -> tuple[bool, str]:
         """
         Check if the async signal is found in the BEC device manager.
 
@@ -1529,13 +1551,16 @@ class Waveform(PlotBase):
             signal(str): The entry of the async signal.
 
         Returns:
-            bool: True if the async signal is found, False otherwise.
+            tuple[bool, str]: A tuple where the first element is True if the async signal is found (False otherwise),
+                and the second element is the signal name (either the original signal or the storage_name for AsyncMultiSignal).
         """
-        bec_async_signals = self.client.device_manager.get_bec_signals("AsyncSignal")
+        bec_async_signals = self.client.device_manager.get_bec_signals(
+            ["AsyncSignal", "AsyncMultiSignal"]
+        )
         for entry_name, _, entry_data in bec_async_signals:
             if entry_name == name and entry_data.get("obj_name") == signal:
-                return True
-        return False
+                return True, entry_data.get("storage_name")
+        return False, signal
 
     def _setup_async_curve(self, curve: Curve):
         """
@@ -1546,7 +1571,7 @@ class Waveform(PlotBase):
         """
         name = curve.config.signal.name
         signal = curve.config.signal.entry
-        async_signal_found = self._check_async_signal_found(name, signal)
+        async_signal_found, signal = self._check_async_signal_found(name, signal)
 
         try:
             curve.clear_data()
@@ -1759,12 +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(),
@@ -1773,6 +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):
         """
@@ -1790,14 +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"]
@@ -1806,19 +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)
@@ -2374,8 +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

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "bec_widgets"
-version = "2.45.10"
+version = "2.45.12"
 description = "BEC Widgets"
 requires-python = ">=3.11"
 classifiers = [

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_heatmap_widget.py

@@ -4,6 +4,7 @@ import numpy as np
 import pytest
 from bec_lib import messages
 from bec_lib.scan_history import ScanHistory
+from qtpy.QtCore import QPointF
 
 from bec_widgets.widgets.plots.heatmap.heatmap import Heatmap, HeatmapConfig, HeatmapDeviceSignal
 
@@ -125,12 +126,16 @@ def test_heatmap_get_image_data_unsupported_scan(heatmap_widget):
 
 
 def test_heatmap_get_grid_scan_image(heatmap_widget):
+    x_levels = np.linspace(-5, 5, 10).tolist()
+    y_levels = np.linspace(-5, 5, 10).tolist()
     scan_msg = messages.ScanStatusMessage(
         scan_id="123",
         status="open",
         scan_name="grid_scan",
         metadata={},
-        info={"positions": np.random.rand(100, 2).tolist()},
+        info={
+            "positions": _grid_positions(slow_levels=x_levels, fast_levels=y_levels, snaked=True)
+        },
         request_inputs={"arg_bundle": ["samx", -5, 5, 10, "samy", -5, 5, 10], "kwargs": {}},
     )
     heatmap_widget._image_config = HeatmapConfig(
@@ -145,6 +150,111 @@ def test_heatmap_get_grid_scan_image(heatmap_widget):
     assert sorted(np.asarray(img, dtype=int).flatten().tolist()) == list(range(100))
 
 
+def _grid_positions(
+    *, slow_levels: list[float], fast_levels: list[float], snaked: bool, slow_is_col0: bool = True
+) -> list[list[float]]:
+    positions: list[list[float]] = []
+    for slow_i, slow_val in enumerate(slow_levels):
+        row_fast = fast_levels if (not snaked or slow_i % 2 == 0) else list(reversed(fast_levels))
+        for fast_val in row_fast:
+            if slow_is_col0:
+                positions.append([slow_val, fast_val])
+            else:
+                positions.append([fast_val, slow_val])
+    return positions
+
+
+def test_heatmap_grid_scan_direction_and_snaking_x_fast(heatmap_widget):
+    heatmap_widget._image_config = HeatmapConfig(
+        parent_id="parent_id",
+        x_device=HeatmapDeviceSignal(name="samx", entry="samx"),
+        y_device=HeatmapDeviceSignal(name="samy", entry="samy"),
+        z_device=HeatmapDeviceSignal(name="bpm4i", entry="bpm4i"),
+        color_map="viridis",
+    )
+
+    # x decreases (relative), y increases (relative), x is fast axis
+    x0 = 10.0
+    y0 = -3.0
+    x_levels = (x0 + np.linspace(1.0, -1.0, 3)).tolist()
+    y_levels = (y0 + np.linspace(-2.0, 2.0, 2)).tolist()
+    snaked = True
+
+    scan_msg = messages.ScanStatusMessage(
+        scan_id="123",
+        status="open",
+        scan_name="grid_scan",
+        metadata={},
+        info={
+            "positions": _grid_positions(slow_levels=y_levels, fast_levels=x_levels, snaked=snaked)
+        },
+        request_inputs={
+            "arg_bundle": ["samy", -2.0, 2.0, 2, "samx", 1.0, -1.0, 3],
+            "kwargs": {"snaked": snaked, "relative": True},
+        },
+    )
+
+    img, transform = heatmap_widget.get_grid_scan_image(list(range(6)), msg=scan_msg)
+
+    assert img.shape == (3, 2)
+    assert img[0, 0] == 0  # first point: (x0,y0) in scan order
+    assert img[2, 1] == 3  # second row first point due to snaking
+    assert img[0, 1] == 5  # last point in second row
+
+    p0 = transform.map(QPointF(0.5, 0.5))
+    p1 = transform.map(QPointF(2.5, 1.5))
+    assert p0.x() == pytest.approx(x_levels[0])
+    assert p0.y() == pytest.approx(y_levels[0])
+    assert p1.x() == pytest.approx(x_levels[-1])
+    assert p1.y() == pytest.approx(y_levels[-1])
+
+
+def test_heatmap_grid_scan_direction_and_snaking_y_fast(heatmap_widget):
+    heatmap_widget._image_config = HeatmapConfig(
+        parent_id="parent_id",
+        x_device=HeatmapDeviceSignal(name="samx", entry="samx"),
+        y_device=HeatmapDeviceSignal(name="samy", entry="samy"),
+        z_device=HeatmapDeviceSignal(name="bpm4i", entry="bpm4i"),
+        color_map="viridis",
+    )
+
+    # x decreases (relative), y increases (relative), y is fast axis
+    x0 = 1.5
+    y0 = 22.0
+    x_levels = (x0 + np.linspace(1.0, -1.0, 3)).tolist()
+    y_levels = (y0 + np.linspace(-2.0, 2.0, 2)).tolist()
+    snaked = True
+
+    scan_msg = messages.ScanStatusMessage(
+        scan_id="123",
+        status="open",
+        scan_name="grid_scan",
+        metadata={},
+        info={
+            "positions": _grid_positions(slow_levels=x_levels, fast_levels=y_levels, snaked=snaked)
+        },
+        request_inputs={
+            "arg_bundle": ["samx", 1.0, -1.0, 3, "samy", -2.0, 2.0, 2],
+            "kwargs": {"snaked": snaked, "relative": True},
+        },
+    )
+
+    img, transform = heatmap_widget.get_grid_scan_image(list(range(6)), msg=scan_msg)
+
+    assert img.shape == (3, 2)
+    assert img[0, 0] == 0
+    # For y-fast scans, snaking reverses the y index on every odd x row.
+    assert img[1, 1] == 2
+    assert img[1, 0] == 3
+
+    p0 = transform.map(QPointF(0.5, 0.5))
+    p1 = transform.map(QPointF(2.5, 1.5))
+    assert p0.x() == pytest.approx(x_levels[0])
+    assert p0.y() == pytest.approx(y_levels[0])
+    assert p1.x() == pytest.approx(x_levels[-1])
+    assert p1.y() == pytest.approx(y_levels[-1])
+
+
 def test_heatmap_get_step_scan_image(heatmap_widget):
 
     scan_msg = messages.ScanStatusMessage(
@@ -193,12 +303,16 @@ def test_heatmap_update_plot(heatmap_widget):
         color_map="viridis",
     )
     heatmap_widget.scan_item = create_dummy_scan_item()
+    x_levels = np.linspace(-5, 5, 10).tolist()
+    y_levels = np.linspace(-5, 5, 10).tolist()
     heatmap_widget.scan_item.status_message = messages.ScanStatusMessage(
         scan_id="123",
         status="open",
         scan_name="grid_scan",
         metadata={},
-        info={"positions": np.random.rand(100, 2).tolist()},
+        info={
+            "positions": _grid_positions(slow_levels=x_levels, fast_levels=y_levels, snaked=True)
+        },
         request_inputs={"arg_bundle": ["samx", -5, 5, 10, "samy", -5, 5, 10], "kwargs": {}},
     )
     with mock.patch.object(heatmap_widget.main_image, "setImage") as mock_set_image:

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,